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Sample records for geostatistical study evaluation

  1. Preliminary evaluation of uranium deposits. A geostatistical study of drilling density in Wyoming solution fronts

    International Nuclear Information System (INIS)

    Sandefur, R.L.; Grant, D.C.

    1976-01-01

    Studies of a roll-front uranium deposit in Shirley Basin Wyoming indicate that preliminary evaluation of the reserve potential of an ore body is possible with less drilling than currently practiced in industry. Estimating ore reserves from sparse drilling is difficult because most reserve calculation techniques do not give the accuracy of the estimate. A study of several deposits with a variety of drilling densities shows that geostatistics consistently provides a method of assessing the accuracy of an ore reserve estimate. Geostatistics provides the geologist with an additional descriptive technique - one which is valuable in the economic assessment of a uranium deposit. Closely spaced drilling on past properties provides both geological and geometric insight into the occurrence of uranium in roll-front type deposits. Just as the geological insight assists in locating new ore bodies and siting preferential drill locations, the geometric insight can be applied mathematically to evaluate the accuracy of a new ore reserve estimate. By expressing the geometry in numerical terms, geostatistics extracts important geological characteristics and uses this information to aid in describing the unknown characteristics of a property. (author)

  2. Quick evaluation of multiple geostatistical models using upscaling with coarse grids: A practical study

    Energy Technology Data Exchange (ETDEWEB)

    Lemouzy, P. [Institut Francais du Petrole and ELF/IFP Helios Group, Pau (France)

    1997-08-01

    In field delineation phase, uncertainty in hydrocarbon reservoir descriptions is large. To quickly examine the impact of this uncertainty on production performance, it is necessary to evaluate a large number of descriptions in relation to possible production methods (well spacing, injection rate, etc.). The method of using coarse upscaled models was first proposed by Ballin. Unlike other methods (connectivity analysis, tracer simulations), it considers parameters such as PVT, well management, etc. After a detailed review of upscaling issues, applications to water-injection cases (either with balance or imbalance of production, with or without aquifer) and to depletion of an oil reservoir with aquifer coning are presented. Much more important than the method of permeability upscaling far from wells, the need of correct upscaling of numerical well representation is pointed out Methods are proposed to accurately represent fluids volumes in coarse models. Simple methods to upscale relative permeabilities, and methods to efficiently correct numerical dispersion are proposed. Good results are obtained for water injection. The coarse upscaling method allows the performance of sensitivity analyses on model parameters at a much lower CPU cost than comprehensive simulations. Models representing extreme behaviors can be easily distinguished. For depletion of an oil reservoir showing aquifer coning, however, the method did not work property. It is our opinion that further research is required for upscaling close to wells. We therefore recombined this method for practical use in the case of water injection.

  3. Geostatistical evaluation of travel time uncertainties

    International Nuclear Information System (INIS)

    Devary, J.L.

    1983-08-01

    Data on potentiometric head and hydraulic conductivity, gathered from the Wolfcamp Formation of the Permian System, have exhibited tremendous spatial variability as a result of heterogeneities in the media and the presence of petroleum and natural gas deposits. Geostatistical data analysis and error propagation techniques (kriging and conditional simulation) were applied to determine the effect of potentiometric head uncertainties on radionuclide travel paths and travel times through the Wolfcamp Formation. Blok-average kriging was utilized to remove measurement error from potentiometric head data. The travel time calculations have been enhanced by the use of an inverse technique to determine the relative hydraulic conductivity along travel paths. In this way, the spatial variability of the hydraulic conductivity corresponding to streamline convergence and divergence may be included in the analysis. 22 references, 11 figures, 1 table

  4. Use of geostatistics on broiler production for evaluation of different minimum ventilation systems during brooding phase

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    Thayla Morandi Ridolfi de Carvalho

    2012-01-01

    Full Text Available The objective of this research was to evaluate different minimum ventilation systems, in relation to air quality and thermal comfort using geostatistics in brooding phase. The minimum ventilation systems were: Blue House I: exhaust fans + curtain management (end of the building; Blue House II: exhaust fans + side curtain management; and Dark House: exhaust fans + flag. The climate variables evaluated were: dry bulb temperature, relative humidity, air velocity, carbon dioxide and ammonia concentration, during winter time, at 9 a.m., in 80 equidistant points in brooding area. Data were evaluated by geostatistic technique. The results indicate that Wider broiler houses (above 15.0 m width present the greatest ammonia and humidity concentration. Blue House II present the best results in relation to air quality. However, none of the studied broiler houses present an ideal thermal comfort.

  5. Study on geological environment model using geostatistics method

    International Nuclear Information System (INIS)

    Honda, Makoto; Suzuki, Makoto; Sakurai, Hideyuki; Iwasa, Kengo; Matsui, Hiroya

    2005-03-01

    The purpose of this study is to develop the geostatistical procedure for modeling geological environments and to evaluate the quantitative relationship between the amount of information and the reliability of the model using the data sets obtained in the surface-based investigation phase (Phase 1) of the Horonobe Underground Research Laboratory Project. This study lasts for three years from FY2004 to FY2006 and this report includes the research in FY2005 as the second year of three-year study. In FY2005 research, the hydrogeological model was built as well as FY2004 research using the data obtained from the deep boreholes (HDB-6, 7 and 8) and the ground magnetotelluric (AMT) survey which were executed in FY2004 in addition to the data sets used in the first year of study. Above all, the relationship between the amount of information and the reliability of the model was demonstrated through a comparison of the models at each step which corresponds to the investigation stage in each FY. Furthermore, the statistical test was applied for detecting the difference of basic statistics of various data due to geological features with a view to taking the geological information into the modeling procedures. (author)

  6. Evaluation of geostatistical parameters based on well tests; Estimation de parametres geostatistiques a partir de tests de puits

    Energy Technology Data Exchange (ETDEWEB)

    Gauthier, Y.

    1997-10-20

    Geostatistical tools are increasingly used to model permeability fields in subsurface reservoirs, which are considered as a particular random variable development depending of several geostatistical parameters such as variance and correlation length. The first part of the thesis is devoted to the study of relations existing between the transient well pressure (the well test) and the stochastic permeability field, using the apparent permeability concept.The well test performs a moving permeability average over larger and larger volume with increasing time. In the second part, the geostatistical parameters are evaluated using well test data; a Bayesian framework is used and parameters are estimated using the maximum likelihood principle by maximizing the well test data probability density function with respect to these parameters. This method, involving a well test fast evaluation, provides an estimation of the correlation length and the variance over different realizations of a two-dimensional permeability field

  7. How to evaluate the risks of exceeding limits: geostatistical models and their application to air pollution

    International Nuclear Information System (INIS)

    Fouquet, Ch. de; Deraisme, J.; Bobbia, M.

    2007-01-01

    Geo-statistics is increasingly applied to the study of environmental risks in a variety of sectors, especially in the fields of soil decontamination and the evaluation of the risks due to air pollution. Geo-statistics offers a rigorous stochastic modeling approach that makes it possible to answer questions expressed in terms of uncertainty and risk. This article focusses on nonlinear geo-statistical methods, based on the Gaussian random function model, whose essential properties are summarised. We use two examples to characterize situations where direct and thus rapid methods provide appropriate solutions and cases that inevitably require more laborious simulation techniques. Exposure of the population of the Rouen metropolitan area to the risk of NO 2 pollution is assessed by simulations, but the surface area where the pollution exceeds the threshold limit can be easily estimated with nonlinear conditional expectation techniques. A second example is used to discuss the bias introduced by direct simulation, here of a percentile of daily SO 2 concentration for one year in the city of Le Havre; an operational solution is proposed. (authors)

  8. Evaluation of stationary and non-stationary geostatistical models for inferring hydraulic conductivity values at Aespoe

    International Nuclear Information System (INIS)

    La Pointe, P.R.

    1994-11-01

    This report describes the comparison of stationary and non-stationary geostatistical models for the purpose of inferring block-scale hydraulic conductivity values from packer tests at Aespoe. The comparison between models is made through the evaluation of cross-validation statistics for three experimental designs. The first experiment consisted of a 'Delete-1' test previously used at Finnsjoen. The second test consisted of 'Delete-10%' and the third test was a 'Delete-50%' test. Preliminary data analysis showed that the 3 m and 30 m packer test data can be treated as a sample from a single population for the purposes of geostatistical analyses. Analysis of the 3 m data does not indicate that there are any systematic statistical changes with depth, rock type, fracture zone vs non-fracture zone or other mappable factor. Directional variograms are ambiguous to interpret due to the clustered nature of the data, but do not show any obvious anisotropy that should be accounted for in geostatistical analysis. Stationary analysis suggested that there exists a sizeable spatially uncorrelated component ('Nugget Effect') in the 3 m data, on the order of 60% of the observed variance for the various models fitted. Four different nested models were automatically fit to the data. Results for all models in terms of cross-validation statistics were very similar for the first set of validation tests. Non-stationary analysis established that both the order of drift and the order of the intrinsic random functions is low. This study also suggests that conventional cross-validation studies and automatic variogram fitting are not necessarily evaluating how well a model will infer block scale hydraulic conductivity values. 20 refs, 20 figs, 14 tabs

  9. Characterization of groundwater quality using water evaluation indices, multivariate statistics and geostatistics in central Bangladesh

    Directory of Open Access Journals (Sweden)

    Md. Bodrud-Doza

    2016-04-01

    Full Text Available This study investigates the groundwater quality in the Faridpur district of central Bangladesh based on preselected 60 sample points. Water evaluation indices and a number of statistical approaches such as multivariate statistics and geostatistics are applied to characterize water quality, which is a major factor for controlling the groundwater quality in term of drinking purposes. The study reveal that EC, TDS, Ca2+, total As and Fe values of groundwater samples exceeded Bangladesh and international standards. Ground water quality index (GWQI exhibited that about 47% of the samples were belonging to good quality water for drinking purposes. The heavy metal pollution index (HPI, degree of contamination (Cd, heavy metal evaluation index (HEI reveal that most of the samples belong to low level of pollution. However, Cd provide better alternative than other indices. Principle component analysis (PCA suggests that groundwater quality is mainly related to geogenic (rock–water interaction and anthropogenic source (agrogenic and domestic sewage in the study area. Subsequently, the findings of cluster analysis (CA and correlation matrix (CM are also consistent with the PCA results. The spatial distributions of groundwater quality parameters are determined by geostatistical modeling. The exponential semivariagram model is validated as the best fitted models for most of the indices values. It is expected that outcomes of the study will provide insights for decision makers taking proper measures for groundwater quality management in central Bangladesh.

  10. Evaluation of permeability of compacted bentonite ground considering heterogeneity by geostatistics

    International Nuclear Information System (INIS)

    Tanaka, Yukihisa; Nakamura, Kunihiko; Kudo, Kohji; Hironaga, Michihiko; Nakagami, Motonori; Niwase, Kazuhito; Komatsu, Shin-ichi

    2007-01-01

    The permeability of the bentonite ground as an engineered barrier is possibly designed to the value which is lower than that determined in terms of required performance because of heterogeneous distribution of permeability in the ground, which might be considerable when the ground is created by the compaction method. The effect of heterogeneity in the ground on the permeability of the bentonite ground should be evaluated by overall permeability of the ground, whereas in practice, the effect is evaluated by the distribution of permeability in the ground. Thus, in this study, overall permeability of the bentonite ground is evaluated from the permeability of the bentonite ground is evaluated from the permeability distribution determined using the geostatistical method with the dry density data as well as permeability data of the undisturbed sample recovered from the bentonite ground. Consequently, it was proved through this study that possibility of overestimation of permeability of the bentonite ground can be reduced if the overall permeability is used. (author)

  11. Evaluation of statistical and geostatistical models of digital soil properties mapping in tropical mountain regions

    Directory of Open Access Journals (Sweden)

    Waldir de Carvalho Junior

    2014-06-01

    Full Text Available Soil properties have an enormous impact on economic and environmental aspects of agricultural production. Quantitative relationships between soil properties and the factors that influence their variability are the basis of digital soil mapping. The predictive models of soil properties evaluated in this work are statistical (multiple linear regression-MLR and geostatistical (ordinary kriging and co-kriging. The study was conducted in the municipality of Bom Jardim, RJ, using a soil database with 208 sampling points. Predictive models were evaluated for sand, silt and clay fractions, pH in water and organic carbon at six depths according to the specifications of the consortium of digital soil mapping at the global level (GlobalSoilMap. Continuous covariates and categorical predictors were used and their contributions to the model assessed. Only the environmental covariates elevation, aspect, stream power index (SPI, soil wetness index (SWI, normalized difference vegetation index (NDVI, and b3/b2 band ratio were significantly correlated with soil properties. The predictive models had a mean coefficient of determination of 0.21. Best results were obtained with the geostatistical predictive models, where the highest coefficient of determination 0.43 was associated with sand properties between 60 to 100 cm deep. The use of a sparse data set of soil properties for digital mapping can explain only part of the spatial variation of these properties. The results may be related to the sampling density and the quantity and quality of the environmental covariates and predictive models used.

  12. Application of geostatistics in Beach Placer

    International Nuclear Information System (INIS)

    Sundar, G.

    2016-01-01

    The goal of Geostatistics is in the prediction of possible spatial distribution of a property. Application of Geostatistics has gained significance in the field of exploration, evaluation and mining. In the case of beach and inland placer sands exploration, geostatistics can be used in optimising the drill hole spacing, estimate resources of the total heavy minerals (THM), estimation on different grid pattern and grade - tonnage curves. Steps involved in a geostatistical study are exploratory data analysis, creation of experimental variogram, variogram model fitting, kriging and cross validation. Basic tools in geostatistics are variogram and kriging. Characteristics of a variogram are sill, range and nugget. There is a necessity for variogram model fitting prior to kriging. Commonly used variogram models are spherical, exponential and gaussian

  13. Geostatistical Study of Precipitation on the Island of Crete

    Science.gov (United States)

    Agou, Vasiliki D.; Varouchakis, Emmanouil A.; Hristopulos, Dionissios T.

    2015-04-01

    Understanding and predicting the spatiotemporal patterns of precipitation in the Mediterranean islands is an important topic of research, which is emphasized by alarming long-term predictions for increased drought conditions [4]. The analysis of records from drought-prone areas around the world has demonstrated that precipitation data are non-Gaussian. Typically, such data are fitted to the gamma distribution function and then transformed into a normalized index, the so-called Standardized Precipitation Index (SPI) [5]. The SPI can be defined for different time scales and has been applied to data from various regions [2]. Precipitation maps can be constructed using the stochastic method of Ordinary Kriging [1]. Such mathematical tools help to better understand the space-time variability and to plan water resources management. We present preliminary results of an ongoing investigation of the space-time precipitation distribution on the island of Crete (Greece). The study spans the time period from 1948 to 2012 and extends over an area of 8 336 km2. The data comprise monthly precipitation measured at 56 stations. Analysis of the data showed that the most severe drought occurred in 1950 followed by 1989, whereas the wettest year was 2002 followed by 1977. A spatial trend was observed with the spatially averaged annual precipitation in the West measured at about 450mm higher than in the East. Analysis of the data also revealed strong correlations between the precipitation in the western and eastern parts of the island. In addition to longitude, elevation (masl) was determined to be an important factor that exhibits strong linear correlation with precipitation. The precipitation data exhibit wet and dry periods with strong variability even during the wet period. Thus, fitting the data to specific probability distribution models has proved challenging. Different time scales, e.g. monthly, biannual, and annual have been investigated. Herein we focus on annual

  14. Comparative study of the geostatistical ore reserve estimation method over the conventional methods

    International Nuclear Information System (INIS)

    Kim, Y.C.; Knudsen, H.P.

    1975-01-01

    Part I contains a comprehensive treatment of the comparative study of the geostatistical ore reserve estimation method over the conventional methods. The conventional methods chosen for comparison were: (a) the polygon method, (b) the inverse of the distance squared method, and (c) a method similar to (b) but allowing different weights in different directions. Briefly, the overall result from this comparative study is in favor of the use of geostatistics in most cases because the method has lived up to its theoretical claims. A good exposition on the theory of geostatistics, the adopted study procedures, conclusions and recommended future research are given in Part I. Part II of this report contains the results of the second and the third study objectives, which are to assess the potential benefits that can be derived by the introduction of the geostatistical method to the current state-of-the-art in uranium reserve estimation method and to be instrumental in generating the acceptance of the new method by practitioners through illustrative examples, assuming its superiority and practicality. These are given in the form of illustrative examples on the use of geostatistics and the accompanying computer program user's guide

  15. Geostatistical modelling of carbon monoxide levels in Khartoum State (Sudan) - GIS pilot based study

    Energy Technology Data Exchange (ETDEWEB)

    Alhuseen, A [Comenius University in Bratislava, Faculty of Natural Sciences, Dept. of Landscape Ecology, 84215 Bratislava (Slovakia); Madani, M [Ministry of Environment and Physical Development, 1111 Khartoum (Sudan)

    2012-04-25

    The objective of this study is to develop a digital GIS model; that can evaluate, predict and visualize carbon monoxide (CO) levels in Khartoum state. To achieve this aim, sample data had been collected, processed and managed to generate a dynamic GIS model of carbon monoxide levels in the study area. Parametric data collected from the field and analysis carried throughout this study show that (CO) emissions were lower than the allowable ambient air quality standards released by National Environment Protection Council (NEPC-USA) for 1998. However, this pilot study has found emissions of (CO) in Omdurman city were the highest. This pilot study shows that GIS and geostatistical modeling can be used as a powerful tool to produce maps of exposure. (authors)

  16. Geostatistical methods for radiological evaluation and risk analysis of contaminated premises

    International Nuclear Information System (INIS)

    Desnoyers, Y.; Jeannee, N.; Chiles, J.P.; Dubot, D.

    2009-01-01

    Full text: At the end of process equipment dismantling, the complete decontamination of nuclear facilities requires the radiological assessment of residual activity levels of building structures. As stated by the IAEA, 'Segregation and characterization of contaminated materials are the key elements of waste minimization'. From this point of view, the set up of an appropriate evaluation methodology is of primordial importance. The radiological characterization of contaminated premises can be divided into three steps. First, the most exhaustive facility analysis provides historical, functional and qualitative information. Then, a systematic (exhaustive or not) control of the emergent signal is performed by means of in situ measurement methods such as surface control device combined with in situ gamma spectrometry. Besides, in order to assess the contamination depth, samples can be collected from boreholes at several locations within the premises and analyzed. Combined with historical information and emergent signal maps, such data improve and reinforce the preliminary waste zoning. In order to provide reliable estimates while avoiding supplementary investigation costs, there is therefore a crucial need for sampling optimization methods together with appropriate data processing techniques. The relevance of the geostatistical methodology relies on the presence of a spatial continuity for radiological contamination. In this case, geostatistics provides reliable methods for activity estimation, uncertainty quantification and risk analysis, which are essential decision-making tools for decommissioning and dismantling projects of nuclear installations. Besides, the ability of this geostatistical framework to provide answers to several key issues that generally occur during the clean-up preparation phase is discussed: How to optimise the investigation costs? How to deal with data quality issues? How to consistently take into account auxiliary information such as historical

  17. The Use of Geostatistics in the Study of Floral Phenology of Vulpia geniculata (L. Link

    Directory of Open Access Journals (Sweden)

    Eduardo J. León Ruiz

    2012-01-01

    Full Text Available Traditionally phenology studies have been focused on changes through time, but there exist many instances in ecological research where it is necessary to interpolate among spatially stratified samples. The combined use of Geographical Information Systems (GIS and Geostatistics can be an essential tool for spatial analysis in phenological studies. Geostatistics are a family of statistics that describe correlations through space/time and they can be used for both quantifying spatial correlation and interpolating unsampled points. In the present work, estimations based upon Geostatistics and GIS mapping have enabled the construction of spatial models that reflect phenological evolution of Vulpia geniculata (L. Link throughout the study area during sampling season. Ten sampling points, scattered troughout the city and low mountains in the “Sierra de Córdoba” were chosen to carry out the weekly phenological monitoring during flowering season. The phenological data were interpolated by applying the traditional geostatitical method of Kriging, which was used to ellaborate weekly estimations of V. geniculata phenology in unsampled areas. Finally, the application of Geostatistics and GIS to create phenological maps could be an essential complement in pollen aerobiological studies, given the increased interest in obtaining automatic aerobiological forecasting maps.

  18. A comparison between geostatistical analyses and sedimentological studies at the Hartbeestfontien gold mine

    International Nuclear Information System (INIS)

    Magri, E.J.

    1978-01-01

    For life-of-mine planning, as well as for short- and medium-term planning of grades and mine layouts, it is extremely important to have a clear understanding of the patterns followed by the distribution of gold and uranium within the mining area. This study is an attempt to reconcile the geostatistical approach to the determination of ore-shoot directions, via an analysis of the spatial distribution of gold and uranium values, with the sedimentological approach, which is based on the direct measurement of geological features. For the routine geostatistical estimation of ore reserves, the Hartebeestfontein gold mine was divided into ll sections. In each of these sections, the ore-shoot directions were calculated for gold and uranium from the anisotropies disclosed by geostatistical variogram analyses. This study presents a comparison of these results with those obtained from direct geological measurements of paleo-current directions. The results suggest that geological and geostatistical studies could be of significant mutual benefit [af

  19. A conceptual sedimentological-geostatistical model of aquifer heterogeneity based on outcrop studies

    International Nuclear Information System (INIS)

    Davis, J.M.

    1994-01-01

    Three outcrop studies were conducted in deposits of different depositional environments. At each site, permeability measurements were obtained with an air-minipermeameter developed as part of this study. In addition, the geological units were mapped with either surveying, photographs, or both. Geostatistical analysis of the permeability data was performed to estimate the characteristics of the probability distribution function and the spatial correlation structure. The information obtained from the geological mapping was then compared with the results of the geostatistical analysis for any relationships that may exist. The main field site was located in the Albuquerque Basin of central New Mexico at an outcrop of the Pliocene-Pleistocene Sierra Ladrones Formation. The second study was conducted on the walls of waste pits in alluvial fan deposits at the Nevada Test Site. The third study was conducted on an outcrop of an eolian deposit (miocene) south of Socorro, New Mexico. The results of the three studies were then used to construct a conceptual model relating depositional environment to geostatistical models of heterogeneity. The model presented is largely qualitative but provides a basis for further hypothesis formulation and testing

  20. A conceptual sedimentological-geostatistical model of aquifer heterogeneity based on outcrop studies

    Energy Technology Data Exchange (ETDEWEB)

    Davis, J.M.

    1994-01-01

    Three outcrop studies were conducted in deposits of different depositional environments. At each site, permeability measurements were obtained with an air-minipermeameter developed as part of this study. In addition, the geological units were mapped with either surveying, photographs, or both. Geostatistical analysis of the permeability data was performed to estimate the characteristics of the probability distribution function and the spatial correlation structure. The information obtained from the geological mapping was then compared with the results of the geostatistical analysis for any relationships that may exist. The main field site was located in the Albuquerque Basin of central New Mexico at an outcrop of the Pliocene-Pleistocene Sierra Ladrones Formation. The second study was conducted on the walls of waste pits in alluvial fan deposits at the Nevada Test Site. The third study was conducted on an outcrop of an eolian deposit (miocene) south of Socorro, New Mexico. The results of the three studies were then used to construct a conceptual model relating depositional environment to geostatistical models of heterogeneity. The model presented is largely qualitative but provides a basis for further hypothesis formulation and testing.

  1. Geostatistical evaluation of integrated marsh management impact on mosquito vectors using before-after-control-impact (BACI design

    Directory of Open Access Journals (Sweden)

    Dempsey Mary E

    2009-06-01

    Full Text Available Abstract Background In many parts of the world, salt marshes play a key ecological role as the interface between the marine and the terrestrial environments. Salt marshes are also exceedingly important for public health as larval habitat for mosquitoes that are vectors of disease and significant biting pests. Although grid ditching and pesticides have been effective in salt marsh mosquito control, marsh degradation and other environmental considerations compel a different approach. Targeted habitat modification and biological control methods known as Open Marsh Water Management (OMWM had been proposed as a viable alternative to marsh-wide physical alterations and chemical control. However, traditional larval sampling techniques may not adequately assess the impacts of marsh management on mosquito larvae. To assess the effectiveness of integrated OMWM and marsh restoration techniques for mosquito control, we analyzed the results of a 5-year OMWM/marsh restoration project to determine changes in mosquito larval production using GIS and geostatistical methods. Methods The following parameters were evaluated using "Before-After-Control-Impact" (BACI design: frequency and geographic extent of larval production, intensity of larval production, changes in larval habitat, and number of larvicide applications. The analyses were performed using Moran's I, Getis-Ord, and Spatial Scan statistics on aggregated before and after data as well as data collected over time. This allowed comparison of control and treatment areas to identify changes attributable to the OMWM/marsh restoration modifications. Results The frequency of finding mosquito larvae in the treatment areas was reduced by 70% resulting in a loss of spatial larval clusters compared to those found in the control areas. This effect was observed directly following OMWM treatment and remained significant throughout the study period. The greatly reduced frequency of finding larvae in the treatment

  2. Geostatistical evaluation of integrated marsh management impact on mosquito vectors using before-after-control-impact (BACI) design.

    Science.gov (United States)

    Rochlin, Ilia; Iwanejko, Tom; Dempsey, Mary E; Ninivaggi, Dominick V

    2009-06-23

    In many parts of the world, salt marshes play a key ecological role as the interface between the marine and the terrestrial environments. Salt marshes are also exceedingly important for public health as larval habitat for mosquitoes that are vectors of disease and significant biting pests. Although grid ditching and pesticides have been effective in salt marsh mosquito control, marsh degradation and other environmental considerations compel a different approach. Targeted habitat modification and biological control methods known as Open Marsh Water Management (OMWM) had been proposed as a viable alternative to marsh-wide physical alterations and chemical control. However, traditional larval sampling techniques may not adequately assess the impacts of marsh management on mosquito larvae. To assess the effectiveness of integrated OMWM and marsh restoration techniques for mosquito control, we analyzed the results of a 5-year OMWM/marsh restoration project to determine changes in mosquito larval production using GIS and geostatistical methods. The following parameters were evaluated using "Before-After-Control-Impact" (BACI) design: frequency and geographic extent of larval production, intensity of larval production, changes in larval habitat, and number of larvicide applications. The analyses were performed using Moran's I, Getis-Ord, and Spatial Scan statistics on aggregated before and after data as well as data collected over time. This allowed comparison of control and treatment areas to identify changes attributable to the OMWM/marsh restoration modifications. The frequency of finding mosquito larvae in the treatment areas was reduced by 70% resulting in a loss of spatial larval clusters compared to those found in the control areas. This effect was observed directly following OMWM treatment and remained significant throughout the study period. The greatly reduced frequency of finding larvae in the treatment areas led to a significant decrease (approximately 44%) in

  3. Geostatistical models for air pollution

    International Nuclear Information System (INIS)

    Pereira, M.J.; Soares, A.; Almeida, J.; Branquinho, C.

    2000-01-01

    The objective of this paper is to present geostatistical models applied to the spatial characterisation of air pollution phenomena. A concise presentation of the geostatistical methodologies is illustrated with practical examples. The case study was conducted in an underground copper-mine located on the southern of Portugal, where a biomonitoring program using lichens has been implemented. Given the characteristics of lichens as indicators of air pollution it was possible to gather a great amount of data in space, which enabled the development and application of geostatistical methodologies. The advantages of using geostatistical models compared with deterministic models, as environmental control tools, are highlighted. (author)

  4. A geostatistical analysis of geostatistics

    NARCIS (Netherlands)

    Hengl, T.; Minasny, B.; Gould, M.

    2009-01-01

    The bibliometric indices of the scientific field of geostatistics were analyzed using statistical and spatial data analysis. The publications and their citation statistics were obtained from the Web of Science (4000 most relevant), Scopus (2000 most relevant) and Google Scholar (5389). The focus was

  5. A geostatistical method applied to the geochemical study of the Chichinautzin Volcanic Field in Mexico

    Science.gov (United States)

    Robidoux, P.; Roberge, J.; Urbina Oviedo, C. A.

    2011-12-01

    The origin of magmatism and the role of the subducted Coco's Plate in the Chichinautzin volcanic field (CVF), Mexico is still a subject of debate. It has been established that mafic magmas of alkali type (subduction) and calc-alkali type (OIB) are produced in the CVF and both groups cannot be related by simple fractional crystallization. Therefore, many geochemical studies have been done, and many models have been proposed. The main goal of the work present here is to provide a new tool for the visualization and interpretation of geochemical data using geostatistics and geospatial analysis techniques. It contains a complete geodatabase built from referred samples over the 2500 km2 area of CVF and its neighbour stratovolcanoes (Popocatepetl, Iztaccihuatl and Nevado de Toluca). From this database, map of different geochemical markers were done to visualise geochemical signature in a geographical manner, to test the statistic distribution with a cartographic technique and highlight any spatial correlations. The distribution and regionalization of the geochemical signatures can be viewed in a two-dimensional space using a specific spatial analysis tools from a Geographic Information System (GIS). The model of spatial distribution is tested with Linear Decrease (LD) and Inverse Distance Weight (IDW) interpolation technique because they best represent the geostatistical characteristics of the geodatabase. We found that ratio of Ba/Nb, Nb/Ta, Th/Nb show first order tendency, which means visible spatial variation over a large scale area. Monogenetic volcanoes in the center of the CVF have distinct values compare to those of the Popocatepetl-Iztaccihuatl polygenetic complex which are spatially well defined. Inside the Valley of Mexico, a large quantity of monogenetic cone in the eastern portion of CVF has ratios similar to the Iztaccihuatl and Popocatepetl complex. Other ratios like alkalis vs SiO2, V/Ti, La/Yb, Zr/Y show different spatial tendencies. In that case, second

  6. Application of geostatistical simulation to compile seismotectonic provinces based on earthquake databases (case study: Iran)

    Science.gov (United States)

    Jalali, Mohammad; Ramazi, Hamidreza

    2018-04-01

    This article is devoted to application of a simulation algorithm based on geostatistical methods to compile and update seismotectonic provinces in which Iran has been chosen as a case study. Traditionally, tectonic maps together with seismological data and information (e.g., earthquake catalogues, earthquake mechanism, and microseismic data) have been used to update seismotectonic provinces. In many cases, incomplete earthquake catalogues are one of the important challenges in this procedure. To overcome this problem, a geostatistical simulation algorithm, turning band simulation, TBSIM, was applied to make a synthetic data to improve incomplete earthquake catalogues. Then, the synthetic data was added to the traditional information to study the seismicity homogeneity and classify the areas according to tectonic and seismic properties to update seismotectonic provinces. In this paper, (i) different magnitude types in the studied catalogues have been homogenized to moment magnitude (Mw), and earthquake declustering was then carried out to remove aftershocks and foreshocks; (ii) time normalization method was introduced to decrease the uncertainty in a temporal domain prior to start the simulation procedure; (iii) variography has been carried out in each subregion to study spatial regressions (e.g., west-southwestern area showed a spatial regression from 0.4 to 1.4 decimal degrees; the maximum range identified in the azimuth of 135 ± 10); (iv) TBSIM algorithm was then applied to make simulated events which gave rise to make 68,800 synthetic events according to the spatial regression found in several directions; (v) simulated events (i.e., magnitudes) were classified based on their intensity in ArcGIS packages and homogenous seismic zones have been determined. Finally, according to the synthetic data, tectonic features, and actual earthquake catalogues, 17 seismotectonic provinces were introduced in four major classes introduced as very high, high, moderate, and low

  7. A geostatistical study of the uranium deposit at Kvanefjeld, the Ilimaussaq intrusion, South Greenland

    International Nuclear Information System (INIS)

    Lund Clausen, F.

    1982-05-01

    The uranium deposit at Kvanefjeld within the Ilimaussaq intrusion in South Greenland has been tested by diamond drilling, hole logging, chip sampling and field gamma-spectrometric surveys. Based on these different types of spatially distributed samples the uranium variation within the deposit was studied. The spatial variation, which comprises a large random component, was modelled, and the intrinsic function was used to establish gradetonnage curves by the best linear unbiased estimator of geostatistics (kriging). From data obtained by a ground surface gamma-spectrometric survey it is shown that the uranium variation is possibly subject to a spatial anisotropy consistent with the geology. The uranium variation has a second-order stationarity. A global estimation of the total reserves shows that single block grade values are always estimated with high errors. This is mainly caused by the poor spatial structure and the very sparse sampling pattern. The best way to solve this problem appears to be a selective type of kriging. The overall uranium reserves are estimated as 23600 tons with a mean grade of 297 ppm (cutoff grade 250 ppm U). Studies of data from a test adit show that local geostatistical estimation can be done with acceptably small errors provided that a close sampling pattern is used. A regression relationship is established to correct field gamma-spectrometric measures of bulk grades towards truer values. Multivariate cluster and discriminant analyses were used to classify lujavrite samples based on their trace element content. Misclassification is due to a possibly continuous transition between naujakasite lujavrite and arfvedsonite lujavrite. Some of the main mineralogical differences between the geological units are identified by the discriminating effect of the individual variable. (author)

  8. Geostatistical analysis of groundwater chemistry in Japan. Evaluation of the base case groundwater data set

    Energy Technology Data Exchange (ETDEWEB)

    Salter, P.F.; Apted, M.J. [Monitor Scientific LLC, Denver, CO (United States); Sasamoto, Hiroshi; Yui, Mikazu

    1999-05-01

    The groundwater chemistry is one of important geological environment for performance assessment of high level radioactive disposal system. This report describes the results of geostatistical analysis of groundwater chemistry in Japan. Over 15,000 separate groundwater analyses have been collected of deep Japanese groundwaters for the purpose of evaluating the range of geochemical conditions for geological radioactive waste repositories in Japan. The significance to issues such as radioelement solubility limits, sorption, corrosion of overpack, behavior of compacted clay buffers, and many other factors involved in safety assessment. It is important therefore, that a small, but representative set of groundwater types be identified so that defensible models and data for generic repository performance assessment can be established. Principal component analysis (PCA) is used to categorize representative deep groundwater types from this extensive data set. PCA is a multi-variate statistical analysis technique, similar to factor analysis or eigenvector analysis, designed to provide the best possible resolution of the variability within multi-variate data sets. PCA allows the graphical inspection of the most important similarities (clustering) and differences among samples, based on simultaneous consideration of all variables in the dataset, in a low dimensionality plot. It also allows the analyst to determine the reasons behind any pattern that is observed. In this study, PCA has been aided by hierarchical cluster analysis (HCA), in which statistical indices of similarity among multiple samples are used to distinguish distinct clusters of samples. HCA allows the natural, a priori, grouping of data into clusters showing similar attributes and is graphically represented in a dendrogram Pirouette is the multivariate statistical software package used to conduct the PCA and HCA for the Japanese groundwater dataset. An audit of the initial 15,000 sample dataset on the basis of

  9. Application of Bayesian geostatistics for evaluation of mass discharge uncertainty at contaminated sites

    Science.gov (United States)

    Troldborg, Mads; Nowak, Wolfgang; Lange, Ida V.; Santos, Marta C.; Binning, Philip J.; Bjerg, Poul L.

    2012-09-01

    Mass discharge estimates are increasingly being used when assessing risks of groundwater contamination and designing remedial systems at contaminated sites. Such estimates are, however, rather uncertain as they integrate uncertain spatial distributions of both concentration and groundwater flow. Here a geostatistical simulation method for quantifying the uncertainty of the mass discharge across a multilevel control plane is presented. The method accounts for (1) heterogeneity of both the flow field and the concentration distribution through Bayesian geostatistics, (2) measurement uncertainty, and (3) uncertain source zone and transport parameters. The method generates conditional realizations of the spatial flow and concentration distribution. An analytical macrodispersive transport solution is employed to simulate the mean concentration distribution, and a geostatistical model of the Box-Cox transformed concentration data is used to simulate observed deviations from this mean solution. By combining the flow and concentration realizations, a mass discharge probability distribution is obtained. The method has the advantage of avoiding the heavy computational burden of three-dimensional numerical flow and transport simulation coupled with geostatistical inversion. It may therefore be of practical relevance to practitioners compared to existing methods that are either too simple or computationally demanding. The method is demonstrated on a field site contaminated with chlorinated ethenes. For this site, we show that including a physically meaningful concentration trend and the cosimulation of hydraulic conductivity and hydraulic gradient across the transect helps constrain the mass discharge uncertainty. The number of sampling points required for accurate mass discharge estimation and the relative influence of different data types on mass discharge uncertainty is discussed.

  10. A Bayesian geostatistical approach for evaluating the uncertainty of contaminant mass discharges from point sources

    Science.gov (United States)

    Troldborg, M.; Nowak, W.; Binning, P. J.; Bjerg, P. L.

    2012-12-01

    Estimates of mass discharge (mass/time) are increasingly being used when assessing risks of groundwater contamination and designing remedial systems at contaminated sites. Mass discharge estimates are, however, prone to rather large uncertainties as they integrate uncertain spatial distributions of both concentration and groundwater flow velocities. For risk assessments or any other decisions that are being based on mass discharge estimates, it is essential to address these uncertainties. We present a novel Bayesian geostatistical approach for quantifying the uncertainty of the mass discharge across a multilevel control plane. The method decouples the flow and transport simulation and has the advantage of avoiding the heavy computational burden of three-dimensional numerical flow and transport simulation coupled with geostatistical inversion. It may therefore be of practical relevance to practitioners compared to existing methods that are either too simple or computationally demanding. The method is based on conditional geostatistical simulation and accounts for i) heterogeneity of both the flow field and the concentration distribution through Bayesian geostatistics (including the uncertainty in covariance functions), ii) measurement uncertainty, and iii) uncertain source zone geometry and transport parameters. The method generates multiple equally likely realizations of the spatial flow and concentration distribution, which all honour the measured data at the control plane. The flow realizations are generated by analytical co-simulation of the hydraulic conductivity and the hydraulic gradient across the control plane. These realizations are made consistent with measurements of both hydraulic conductivity and head at the site. An analytical macro-dispersive transport solution is employed to simulate the mean concentration distribution across the control plane, and a geostatistical model of the Box-Cox transformed concentration data is used to simulate observed

  11. Evaluation of spatial variability of metal bioavailability in soils using geostatistics

    DEFF Research Database (Denmark)

    Owsianiak, Mikolaj; Hauschild, Michael Zwicky; Rosenbaum, Ralph K.

    2012-01-01

    Soil properties show signifficant spatial variability at local, regional and continental scales. This is a challenge for life cycle impact assessment (LCIA) of metals, because fate, bioavailability and effect factors are controlled by environmental chemistry and can vary orders of magnitude...... is performed using ArcGIS Geostatistical Analyst. Results show that BFs of copper span a range of 6 orders of magnitude, and have signifficant spatial variability at local and continental scales. The model nugget variance is signifficantly higher than zero, suggesting the presence of spatial variability...

  12. Application of Bayesian geostatistics for evaluation of mass discharge uncertainty at contaminated sites

    DEFF Research Database (Denmark)

    Troldborg, Mads; Nowak, Wolfgang; Lange, Ida Vedel

    2012-01-01

    , and (3) uncertain source zone and transport parameters. The method generates conditional realizations of the spatial flow and concentration distribution. An analytical macrodispersive transport solution is employed to simulate the mean concentration distribution, and a geostatistical model of the Box-Cox...... transformed concentration data is used to simulate observed deviations from this mean solution. By combining the flow and concentration realizations, a mass discharge probability distribution is obtained. The method has the advantage of avoiding the heavy computational burden of three-dimensional numerical...

  13. A Bayesian geostatistical approach for evaluating the uncertainty of contaminant mass discharges from point sources

    DEFF Research Database (Denmark)

    Troldborg, Mads; Nowak, Wolfgang; Binning, Philip John

    and the hydraulic gradient across the control plane and are consistent with measurements of both hydraulic conductivity and head at the site. An analytical macro-dispersive transport solution is employed to simulate the mean concentration distribution across the control plane, and a geostatistical model of the Box-Cox...... transformed concentration data is used to simulate observed deviations from this mean solution. By combining the flow and concentration realizations, a mass discharge probability distribution is obtained. Tests show that the decoupled approach is both efficient and able to provide accurate uncertainty...

  14. Dose rate estimates and spatial interpolation maps of outdoor gamma dose rate with geostatistical methods; A case study from Artvin, Turkey

    International Nuclear Information System (INIS)

    Yeşilkanat, Cafer Mert; Kobya, Yaşar; Taşkin, Halim; Çevik, Uğur

    2015-01-01

    In this study, compliance of geostatistical estimation methods is compared to ensure investigation and imaging natural Fon radiation using the minimum number of data. Artvin province, which has a quite hilly terrain and wide variety of soil and located in the north–east of Turkey, is selected as the study area. Outdoor gamma dose rate (OGDR), which is an important determinant of environmental radioactivity level, is measured in 204 stations. Spatial structure of OGDR is determined by anisotropic, isotropic and residual variograms. Ordinary kriging (OK) and universal kriging (UK) interpolation estimations were calculated with the help of model parameters obtained from these variograms. In OK, although calculations are made based on positions of points where samples are taken, in the UK technique, general soil groups and altitude values directly affecting OGDR are included in the calculations. When two methods are evaluated based on their performances, it has been determined that UK model (r = 0.88, p < 0.001) gives quite better results than OK model (r = 0.64, p < 0.001). In addition, as a result of the maps created at the end of the study, it was illustrated that local changes are better reflected by UK method compared to OK method and its error variance is found to be lower. - Highlights: • The spatial dispersion of gamma dose rates in Artvin, which possesses one of the roughest lands in Turkey were studied. • The performance of different Geostatistic methods (OK and UK methods) for dispersion of gamma dose rates were compared. • Estimation values were calculated for non-sampling points by using the geostatistical model, the results were mapped. • The general radiological structure was determined in much less time with lower costs compared to experimental methods. • When theoretical methods are evaluated, it was obtained that UK gives more descriptive results compared to OK.

  15. Geostatistics as a tool to study mite dispersion in physic nut plantations.

    Science.gov (United States)

    Rosado, J F; Picanço, M C; Sarmento, R A; Pereira, R M; Pedro-Neto, M; Galdino, T V S; de Sousa Saraiva, A; Erasmo, E A L

    2015-08-01

    Spatial distribution studies in pest management identify the locations where pest attacks on crops are most severe, enabling us to understand and predict the movement of such pests. Studies on the spatial distribution of two mite species, however, are rather scarce. The mites Polyphagotarsonemus latus and Tetranychus bastosi are the major pests affecting physic nut plantations (Jatropha curcas). Therefore, the objective of this study was to measure the spatial distributions of P. latus and T. bastosi in the physic nut plantations. Mite densities were monitored over 2 years in two different plantations. Sample locations were georeferenced. The experimental data were analyzed using geostatistical analyses. The total mite density was found to be higher when only one species was present (T. bastosi). When both the mite species were found in the same plantation, their peak densities occurred at different times. These mites, however, exhibited uniform spatial distribution when found at extreme densities (low or high). However, the mites showed an aggregated distribution in intermediate densities. Mite spatial distribution models were isotropic. Mite colonization commenced at the periphery of the areas under study, whereas the high-density patches extended until they reached 30 m in diameter. This has not been reported for J. curcas plants before.

  16. Survey and Zoning of Soil Physical and Chemical Properties Using Geostatistical Methods in GIS (Case Study: Miankangi Region in Sistan

    Directory of Open Access Journals (Sweden)

    M. Hashemi

    2017-02-01

    Full Text Available Introduction: In order to provide a database, it is essential having access to accurate information on soil spatial variation for soil sustainable management such as proper application of fertilizers. Spatial variations in soil properties are common but it is important for understanding these changes, particularly in agricultural lands for careful planning and land management. Materials and Methods: To this end, in winter 1391, 189 undisturbed soil samples (0-30 cm depth in a regular lattice with a spacing of 500 m were gathered from the surface of Miankangi land, Sistan plain, and their physical and chemical properties were studied. The land area of the region is about 4,500 hectares; the average elevation of studied area is 489.2 meters above sea level with different land uses. Soil texture was measured by the hydrometer methods (11, Also EC and pH (39, calcium carbonate equivalent (37 and the saturation percentage of soils were determined. Kriging, Co-Kriging, Inverse Distance Weighting and Local Polynomial Interpolation techniques were evaluated to produce a soil characteristics map of the study area zoning and to select the best geostatistical methods. Cross-validation techniques and Root Mean Square Error (RMSE were used. Results and Discussion: Normalized test results showed that all of the soil properties except calcium carbonate and soil clay content had normal distribution. In addition, the results of correlation test showed that the soil saturation percentage was positively correlated with silt content (r=0.43 and p

  17. Epidemiological study of hazelnut bacterial blight in central Italy by using laboratory analysis and geostatistics.

    Directory of Open Access Journals (Sweden)

    Jay Ram Lamichhane

    Full Text Available Incidence of Xanthomonas arboricola pv. corylina, the causal agent of hazelnut bacterial blight, was analyzed spatially in relation to the pedoclimatic factors. Hazelnut grown in twelve municipalities situated in the province of Viterbo, central Italy was studied. A consistent number of bacterial isolates were obtained from the infected tissues of hazelnut collected in three years (2010-2012. The isolates, characterized by phenotypic tests, did not show any difference among them. Spatial patterns of pedoclimatic data, analyzed by geostatistics showed a strong positive correlation of disease incidence with higher values of rainfall, thermal shock and soil nitrogen; a weak positive correlation with soil aluminium content and a strong negative correlation with the values of Mg/K ratio. No correlation of the disease incidence was found with soil pH. Disease incidence ranged from very low (<1% to very high (almost 75% across the orchards. Young plants (4-year old were the most affected by the disease confirming a weak negative correlation of the disease incidence with plant age. Plant cultivars did not show any difference in susceptibility to the pathogen. Possible role of climate change on the epidemiology of the disease is discussed. Improved management practices are recommended for effective control of the disease.

  18. Geostatistics and GIS: tools for characterizing environmental contamination.

    Science.gov (United States)

    Henshaw, Shannon L; Curriero, Frank C; Shields, Timothy M; Glass, Gregory E; Strickland, Paul T; Breysse, Patrick N

    2004-08-01

    Geostatistics is a set of statistical techniques used in the analysis of georeferenced data that can be applied to environmental contamination and remediation studies. In this study, the 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE) contamination at a Superfund site in western Maryland is evaluated. Concern about the site and its future clean up has triggered interest within the community because residential development surrounds the area. Spatial statistical methods, of which geostatistics is a subset, are becoming increasingly popular, in part due to the availability of geographic information system (GIS) software in a variety of application packages. In this article, the joint use of ArcGIS software and the R statistical computing environment are demonstrated as an approach for comprehensive geostatistical analyses. The spatial regression method, kriging, is used to provide predictions of DDE levels at unsampled locations both within the site and the surrounding areas where residential development is ongoing.

  19. Geostatistical and Stochastic Study of Flow and Tracer Transport in the Unsaturated Zone at Yucca Mountain

    International Nuclear Information System (INIS)

    Ye, Ming; Pan, Feng; Hu, Xiaolong; Zhu, Jianting

    2007-01-01

    Yucca Mountain has been proposed by the U.S. Department of Energy as the nation's long-term, permanent geologic repository for spent nuclear fuel or high-level radioactive waste. The potential repository would be located in Yucca Mountain's unsaturated zone (UZ), which acts as a critical natural barrier delaying arrival of radionuclides to the water table. Since radionuclide transport in groundwater can pose serious threats to human health and the environment, it is important to understand how much and how fast water and radionuclides travel through the UZ to groundwater. The UZ system consists of multiple hydrogeologic units whose hydraulic and geochemical properties exhibit systematic and random spatial variation, or heterogeneity, at multiple scales. Predictions of radionuclide transport under such complicated conditions are uncertain, and the uncertainty complicates decision making and risk analysis. This project aims at using geostatistical and stochastic methods to assess uncertainty of unsaturated flow and radionuclide transport in the UZ at Yucca Mountain. Focus of this study is parameter uncertainty of hydraulic and transport properties of the UZ. The parametric uncertainty arises since limited parameter measurements are unable to deterministically describe spatial variability of the parameters. In this project, matrix porosity, permeability and sorption coefficient of the reactive tracer (neptunium) of the UZ are treated as random variables. Corresponding propagation of parametric uncertainty is quantitatively measured using mean, variance, 5th and 95th percentiles of simulated state variables (e.g., saturation, capillary pressure, percolation flux, and travel time). These statistics are evaluated using a Monte Carlo method, in which a three-dimensional flow and transport model implemented using the TOUGH2 code is executed with multiple parameter realizations of the random model parameters. The project specifically studies uncertainty of unsaturated flow

  20. Qualitative and quantitative comparison of geostatistical techniques of porosity prediction from the seismic and logging data: a case study from the Blackfoot Field, Alberta, Canada

    Science.gov (United States)

    Maurya, S. P.; Singh, K. H.; Singh, N. P.

    2018-05-01

    In present study, three recently developed geostatistical methods, single attribute analysis, multi-attribute analysis and probabilistic neural network algorithm have been used to predict porosity in inter well region for Blackfoot field, Alberta, Canada, an offshore oil field. These techniques make use of seismic attributes, generated by model based inversion and colored inversion techniques. The principle objective of the study is to find the suitable combination of seismic inversion and geostatistical techniques to predict porosity and identification of prospective zones in 3D seismic volume. The porosity estimated from these geostatistical approaches is corroborated with the well log porosity. The results suggest that all the three implemented geostatistical methods are efficient and reliable to predict the porosity but the multi-attribute and probabilistic neural network analysis provide more accurate and high resolution porosity sections. A low impedance (6000-8000 m/s g/cc) and high porosity (> 15%) zone is interpreted from inverted impedance and porosity sections respectively between 1060 and 1075 ms time interval and is characterized as reservoir. The qualitative and quantitative results demonstrate that of all the employed geostatistical methods, the probabilistic neural network along with model based inversion is the most efficient method for predicting porosity in inter well region.

  1. Introduction to Geostatistics

    Science.gov (United States)

    Kitanidis, P. K.

    1997-05-01

    Introduction to Geostatistics presents practical techniques for engineers and earth scientists who routinely encounter interpolation and estimation problems when analyzing data from field observations. Requiring no background in statistics, and with a unique approach that synthesizes classic and geostatistical methods, this book offers linear estimation methods for practitioners and advanced students. Well illustrated with exercises and worked examples, Introduction to Geostatistics is designed for graduate-level courses in earth sciences and environmental engineering.

  2. Applicability of geostatistical procedures for the evaluation of hydrogeological parameters of a fractured aquifer in the Ronneburg mine district

    International Nuclear Information System (INIS)

    Grasshoff, C.; Schetelig, K.; Tomschi, H.

    1998-01-01

    The following paper demonstrates, how a geostatistical approach can help interpolating hydrogeological parameters over a certain area. The basic elements developed by G. Matheron in the sixties are represented as the preconditions and assumptions, which provide the best results of the estimation. The variogram as the most important tool in geostatistics offers the opportunity to describe the correlating behaviour of a regionalized variable. Some kriging procedures are briefly introduced, which provide under varying circumstances estimating of non-measured values with the theoretical variogram-model. In the Ronneburg mine district 108 screened drill-holes could provide coefficients of hydraulic conductivity. These were interpolated with ordinary kriging over the whole investigation area. An error calculation was performed, which could prove the accuracy of the estimation. Short prospects point out some difficulties handling with geostatistic procedures and make suggestions for further investigations. (orig.) [de

  3. Geostatistical investigations of rock masses

    International Nuclear Information System (INIS)

    Matar, J.A.; Sarquis, M.A.; Girardi, J.P.; Tabbia, G.H.

    1987-01-01

    The geostatistical tehniques applied for the selection of a minimun fracturation volume in Sierra del Medio allow to quantify and qualify the variability of mechanic characteristics and density of fracture and also the level of reliability in estimations. The role of geostatistics is discussed in this work so as to select minimun fracturation blocks as a very important site selection step. The only variable used is the 'jointing density' so as to detect the principal fracture systems affecting the rocky massif. It was used on the semivariograms corresponding to the previously mentioned regionalized variables. The different results of fracturation are compared with the deep and shallow geological survey to obtain two and three dimensional models. The range of the geostatistical techniques to detect local geological phenomena such as faults is discussed. The variability model obtained from the borehole data computations is investigated taking as basis the vertical Columnar Model of Discontinuity (fractures) hypothesis derived from geological studies about spatial behaviour of the joint systems and from geostatistical interpretation. (Author) [es

  4. Application of Geostatistical Modelling to Study the Exploration Adequacy of Uniaxial Compressive Strength of Intact Rock alongthe Behesht-Abad Tunnel Route

    Directory of Open Access Journals (Sweden)

    Mohammad Doustmohammadi

    2014-12-01

    Full Text Available Uniaxial compressive strength (UCS is one of the most significant factors on the stability of underground excavation projects. Most of the time, this factor can be obtained by exploratory boreholes evaluation. Due to the large distance between exploratory boreholes in the majority of geotechnical projects, the application of geostatistical methods has increased as an estimator of rock mass properties. The present paper ties the estimation of UCS values of intact rock to the distance between boreholes of the Behesht-Abad tunnel in central Iran, using SGEMS geostatistical program. Variography showed that UCS estimation of intact rock using geostatistical methods is reasonable. The model establishment and validation was done after assessment that the model was trustworthy. Cross validation proved the high accuracy (98% and reliability of the model to estimate uniaxial compressive strength. The UCS values were then estimated along the tunnel axis. Moreover, using geostatistical estimation led to better identification of the pros and cons of geotechnical explorations in each location of tunnel route.

  5. Geostatistical uncertainty of assessing air quality using high-spatial-resolution lichen data: A health study in the urban area of Sines, Portugal.

    Science.gov (United States)

    Ribeiro, Manuel C; Pinho, P; Branquinho, C; Llop, Esteve; Pereira, Maria J

    2016-08-15

    In most studies correlating health outcomes with air pollution, personal exposure assignments are based on measurements collected at air-quality monitoring stations not coinciding with health data locations. In such cases, interpolators are needed to predict air quality in unsampled locations and to assign personal exposures. Moreover, a measure of the spatial uncertainty of exposures should be incorporated, especially in urban areas where concentrations vary at short distances due to changes in land use and pollution intensity. These studies are limited by the lack of literature comparing exposure uncertainty derived from distinct spatial interpolators. Here, we addressed these issues with two interpolation methods: regression Kriging (RK) and ordinary Kriging (OK). These methods were used to generate air-quality simulations with a geostatistical algorithm. For each method, the geostatistical uncertainty was drawn from generalized linear model (GLM) analysis. We analyzed the association between air quality and birth weight. Personal health data (n=227) and exposure data were collected in Sines (Portugal) during 2007-2010. Because air-quality monitoring stations in the city do not offer high-spatial-resolution measurements (n=1), we used lichen data as an ecological indicator of air quality (n=83). We found no significant difference in the fit of GLMs with any of the geostatistical methods. With RK, however, the models tended to fit better more often and worse less often. Moreover, the geostatistical uncertainty results showed a marginally higher mean and precision with RK. Combined with lichen data and land-use data of high spatial resolution, RK is a more effective geostatistical method for relating health outcomes with air quality in urban areas. This is particularly important in small cities, which generally do not have expensive air-quality monitoring stations with high spatial resolution. Further, alternative ways of linking human activities with their

  6. Geostatistics project of the National Uranium Resource Evaluation Program. Progress report, April-September 1980

    International Nuclear Information System (INIS)

    Johnson, M.E.; Howell, J.A.; Jackson, C.K.; Patterson, D.; Beckman, R.J.; Campbell, K.; Bement, T.R.

    1981-03-01

    A large computer code was written to perform a number of discriminant analysis procedures on aerial radiometric data. Work on percentile estimation, using the normal and log-normal probability distributions, was extended. Additional work was performed on methods of computing with large data sets. Attempts are being made to evaluate the behavior of principal components analysis relative to element distribution in a survey area. We also provided general statistical consulting in such areas as discriminant analysis, filtering, and kriging

  7. Geostatistical methods in evaluating spatial variability of groundwater quality in Al-Kharj Region, Saudi Arabia

    Science.gov (United States)

    Al-Omran, Abdulrasoul M.; Aly, Anwar A.; Al-Wabel, Mohammad I.; Al-Shayaa, Mohammad S.; Sallam, Abdulazeam S.; Nadeem, Mahmoud E.

    2017-11-01

    The analyses of 180 groundwater samples of Al-Kharj, Saudi Arabia, recorded that most groundwaters are unsuitable for drinking uses due to high salinity; however, they can be used for irrigation with some restriction. The electric conductivity of studied groundwater ranged between 1.05 and 10.15 dS m-1 with an average of 3.0 dS m-1. Nitrate was also found in high concentration in some groundwater. Piper diagrams revealed that the majority of water samples are magnesium-calcium/sulfate-chloride water type. The Gibbs's diagram revealed that the chemical weathering of rock-forming minerals and evaporation are influencing the groundwater chemistry. A kriging method was used for predicting spatial distribution of salinity (EC dS m-1) and NO3 - (mg L-1) in Al-Kharj's groundwater using data of 180 different locations. After normalization of data, variogram was drawn, for selecting suitable model for fitness on experimental variogram, less residual sum of squares value was used. Then cross-validation and root mean square error were used to select the best method for interpolation. The kriging method was found suitable methods for groundwater interpolation and management using either GS+ or ArcGIS.

  8. Evaluating the effect of sampling and spatial correlation on ground-water travel time uncertainty coupling geostatistical, stochastic, and first order, second moment methods

    International Nuclear Information System (INIS)

    Andrews, R.W.; LaVenue, A.M.; McNeish, J.A.

    1989-01-01

    Ground-water travel time predictions at potential high-level waste repositories are subject to a degree of uncertainty due to the scale of averaging incorporated in conceptual models of the ground-water flow regime as well as the lack of data on the spatial variability of the hydrogeologic parameters. The present study describes the effect of limited observations of a spatially correlated permeability field on the predicted ground-water travel time uncertainty. Varying permeability correlation lengths have been used to investigate the importance of this geostatistical property on the tails of the travel time distribution. This study uses both geostatistical and differential analysis techniques. Following the generation of a spatially correlated permeability field which is considered reality, semivariogram analyses are performed upon small random subsets of the generated field to determine the geostatistical properties of the field represented by the observations. Kriging is then employed to generate a kriged permeability field and the corresponding standard deviation of the estimated field conditioned by the limited observations. Using both the real and kriged fields, the ground-water flow regime is simulated and ground-water travel paths and travel times are determined for various starting points. These results are used to define the ground-water travel time uncertainty due to path variability. The variance of the ground-water travel time along particular paths due to the variance of the permeability field estimated using kriging is then calculated using the first order, second moment method. The uncertainties in predicted travel time due to path and parameter uncertainties are then combined into a single distribution

  9. Regional-scale geostatistical inverse modeling of North American CO2 fluxes: a synthetic data study

    Directory of Open Access Journals (Sweden)

    A. M. Michalak

    2010-07-01

    Full Text Available A series of synthetic data experiments is performed to investigate the ability of a regional atmospheric inversion to estimate grid-scale CO2 fluxes during the growing season over North America. The inversions are performed within a geostatistical framework without the use of any prior flux estimates or auxiliary variables, in order to focus on the atmospheric constraint provided by the nine towers collecting continuous, calibrated CO2 measurements in 2004. Using synthetic measurements and their associated concentration footprints, flux and model-data mismatch covariance parameters are first optimized, and then fluxes and their uncertainties are estimated at three different temporal resolutions. These temporal resolutions, which include a four-day average, a four-day-average diurnal cycle with 3-hourly increments, and 3-hourly fluxes, are chosen to help assess the impact of temporal aggregation errors on the estimated fluxes and covariance parameters. Estimating fluxes at a temporal resolution that can adjust the diurnal variability is found to be critical both for recovering covariance parameters directly from the atmospheric data, and for inferring accurate ecoregion-scale fluxes. Accounting for both spatial and temporal a priori covariance in the flux distribution is also found to be necessary for recovering accurate a posteriori uncertainty bounds on the estimated fluxes. Overall, the results suggest that even a fairly sparse network of 9 towers collecting continuous CO2 measurements across the continent, used with no auxiliary information or prior estimates of the flux distribution in time or space, can be used to infer relatively accurate monthly ecoregion scale CO2 surface fluxes over North America within estimated uncertainty bounds. Simulated random transport error is shown to decrease the quality of flux estimates in under-constrained areas at the ecoregion scale, although the uncertainty bounds remain realistic. While these synthetic

  10. Seismic forecast using geostatistics

    International Nuclear Information System (INIS)

    Grecu, Valeriu; Mateiciuc, Doru

    2007-01-01

    The main idea of this research direction consists in the special way of constructing a new type of mathematical function as being a correlation between a computed statistical quantity and another physical quantity. This type of function called 'position function' was taken over by the authors of this study in the field of seismology with the hope of solving - at least partially - the difficult problem of seismic forecast. The geostatistic method of analysis focuses on the process of energy accumulation in a given seismic area, completing this analysis by a so-called loading function. This function - in fact a temporal function - describes the process of energy accumulation during a seismic cycle from a given seismic area. It was possible to discover a law of evolution of the seismic cycles that was materialized in a so-called characteristic function. This special function will help us to forecast the magnitude and the occurrence moment of the largest earthquake in the analysed area. Since 2000, the authors have been evolving to a new stage of testing: real - time analysis, in order to verify the quality of the method. There were five large earthquakes forecasts. (authors)

  11. Geostatistical methodology for waste optimization of contaminated premises - 59344

    International Nuclear Information System (INIS)

    Desnoyers, Yvon; Dubot, Didier

    2012-01-01

    The presented methodological study illustrates a Geo-statistical approach suitable for radiological evaluation in nuclear premises. The waste characterization is mainly focused on floor concrete surfaces. By modeling the spatial continuity of activities, Geo-statistics provide sound methods to estimate and map radiological activities, together with their uncertainty. The multivariate approach allows the integration of numerous surface radiation measurements in order to improve the estimation of activity levels from concrete samples. This way, a sequential and iterative investigation strategy proves to be relevant to fulfill the different evaluation objectives. Waste characterization is performed on risk maps rather than on direct interpolation maps (due to bias of the selection on kriging results). The use of several estimation supports (punctual, 1 m 2 , room) allows a relevant radiological waste categorization thanks to cost-benefit analysis according to the risk of exceeding a given activity threshold. Global results, mainly total activity, are similarly quantified to precociously lead the waste management for the dismantling and decommissioning project. This paper recalled the geo-statistics principles and demonstrated how this methodology provides innovative tools for the radiological evaluation of contaminated premises. The relevance of this approach relies on the presence of a spatial continuity for radiological contamination. In this case, geo-statistics provides reliable activity estimates, uncertainty quantification and risk analysis, which are essential decision-making tools for decommissioning and dismantling projects of nuclear installations. Waste characterization is then performed taking all relevant information into account: historical knowledge, surface measurements and samples. Thanks to the multivariate processing, the different investigation stages can be rationalized as regards quantity and positioning. Waste characterization is finally

  12. 10th International Geostatistics Congress

    CERN Document Server

    Rodrigo-Ilarri, Javier; Rodrigo-Clavero, María; Cassiraga, Eduardo; Vargas-Guzmán, José

    2017-01-01

    This book contains selected contributions presented at the 10th International Geostatistics Congress held in Valencia from 5 to 9 September, 2016. This is a quadrennial congress that serves as the meeting point for any engineer, professional, practitioner or scientist working in geostatistics. The book contains carefully reviewed papers on geostatistical theory and applications in fields such as mining engineering, petroleum engineering, environmental science, hydrology, ecology, and other fields.

  13. Assessment and modeling of the groundwater hydrogeochemical quality parameters via geostatistical approaches

    Science.gov (United States)

    Karami, Shawgar; Madani, Hassan; Katibeh, Homayoon; Fatehi Marj, Ahmad

    2018-03-01

    Geostatistical methods are one of the advanced techniques used for interpolation of groundwater quality data. The results obtained from geostatistics will be useful for decision makers to adopt suitable remedial measures to protect the quality of groundwater sources. Data used in this study were collected from 78 wells in Varamin plain aquifer located in southeast of Tehran, Iran, in 2013. Ordinary kriging method was used in this study to evaluate groundwater quality parameters. According to what has been mentioned in this paper, seven main quality parameters (i.e. total dissolved solids (TDS), sodium adsorption ratio (SAR), electrical conductivity (EC), sodium (Na+), total hardness (TH), chloride (Cl-) and sulfate (SO4 2-)), have been analyzed and interpreted by statistical and geostatistical methods. After data normalization by Nscore method in WinGslib software, variography as a geostatistical tool to define spatial regression was compiled and experimental variograms were plotted by GS+ software. Then, the best theoretical model was fitted to each variogram based on the minimum RSS. Cross validation method was used to determine the accuracy of the estimated data. Eventually, estimation maps of groundwater quality were prepared in WinGslib software and estimation variance map and estimation error map were presented to evaluate the quality of estimation in each estimated point. Results showed that kriging method is more accurate than the traditional interpolation methods.

  14. "Geo-statistics methods and neural networks in geophysical applications: A case study"

    Science.gov (United States)

    Rodriguez Sandoval, R.; Urrutia Fucugauchi, J.; Ramirez Cruz, L. C.

    2008-12-01

    The study is focus in the Ebano-Panuco basin of northeastern Mexico, which is being explored for hydrocarbon reservoirs. These reservoirs are in limestones and there is interest in determining porosity and permeability in the carbonate sequences. The porosity maps presented in this study are estimated from application of multiattribute and neural networks techniques, which combine geophysics logs and 3-D seismic data by means of statistical relationships. The multiattribute analysis is a process to predict a volume of any underground petrophysical measurement from well-log and seismic data. The data consist of a series of target logs from wells which tie a 3-D seismic volume. The target logs are neutron porosity logs. From the 3-D seismic volume a series of sample attributes is calculated. The objective of this study is to derive a set of attributes and the target log values. The selected set is determined by a process of forward stepwise regression. The analysis can be linear or nonlinear. In the linear mode the method consists of a series of weights derived by least-square minimization. In the nonlinear mode, a neural network is trained using the select attributes as inputs. In this case we used a probabilistic neural network PNN. The method is applied to a real data set from PEMEX. For better reservoir characterization the porosity distribution was estimated using both techniques. The case shown a continues improvement in the prediction of the porosity from the multiattribute to the neural network analysis. The improvement is in the training and the validation, which are important indicators of the reliability of the results. The neural network showed an improvement in resolution over the multiattribute analysis. The final maps provide more realistic results of the porosity distribution.

  15. 4th International Geostatistics Congress

    CERN Document Server

    1993-01-01

    The contributions in this book were presented at the Fourth International Geostatistics Congress held in Tróia, Portugal, in September 1992. They provide a comprehensive account of the current state of the art of geostatistics, including recent theoretical developments and new applications. In particular, readers will find descriptions and applications of the more recent methods of stochastic simulation together with data integration techniques applied to the modelling of hydrocabon reservoirs. In other fields there are stationary and non-stationary geostatistical applications to geology, climatology, pollution control, soil science, hydrology and human sciences. The papers also provide an insight into new trends in geostatistics particularly the increasing interaction with many other scientific disciplines. This book is a significant reference work for practitioners of geostatistics both in academia and industry.

  16. 7th International Geostatistics Congress

    CERN Document Server

    Deutsch, Clayton

    2005-01-01

    The conference proceedings consist of approximately 120 technical papers presented at the Seventh International Geostatistics Congress held in Banff, Alberta, Canada in 2004. All the papers were reviewed by an international panel of leading geostatisticians. The five major sections are: theory, mining, petroleum, environmental and other applications. The first section showcases new and innovative ideas in the theoretical development of geostatistics as a whole; these ideas will have large impact on (1) the directions of future geostatistical research, and (2) the conventional approaches to heterogeneity modelling in a wide range of natural resource industries. The next four sections are focused on applications and innovations relating to the use of geostatistics in specific industries. Historically, mining, petroleum and environmental industries have embraced the use of geostatistics for uncertainty characterization, so these three industries are identified as major application areas. The last section is open...

  17. A Streamlined Approach by a Combination of Bioindication and Geostatistical Methods for Assessing Air Contaminants and Their Effects on Human Health in Industrialized Areas: A Case Study in Southern Brazil

    Directory of Open Access Journals (Sweden)

    Angélica B. Ferreira

    2017-09-01

    Full Text Available Industrialization in developing countries associated with urban growth results in a number of economic benefits, especially in small or medium-sized cities, but leads to a number of environmental and public health consequences. This problem is further aggravated when adequate infrastructure is lacking to monitor the environmental impacts left by industries and refineries. In this study, a new protocol was designed combining biomonitoring and geostatistics to evaluate the possible effects of shale industry emissions on human health and wellbeing. Futhermore, the traditional and expensive air quality method based on PM2.5 measuring was also used to validate the low-cost geostatistical approach. Chemical analysis was performed using Energy Dispersive X-ray Fluorescence Spectrometer (EDXRF to measure inorganic elements in tree bark and shale retorted samples in São Mateus do Sul city, Southern Brazil. Fe, S, and Si were considered potential pollutants in the study area. Distribution maps of element concentrations were generated from the dataset and used to estimate the spatial behavior of Fe, S, and Si and the range from their hot spot(s, highlighting the regions sorrounding the shale refinery. This evidence was also demonstrated in the measurements of PM2.5 concentrations, which are in agreement with the information obtained from the biomonitoring and geostatistical model. Factor and descriptive analyses performed on the concentrations of tree bark contaminants suggest that Fe, S, and Si might be used as indicators of industrial emissions. The number of cases of respiratory diseases obtained from local basic health unit were used to assess a possible correlation between shale refinery emissions and cases of repiratory disease. These data are public and may be accessed on the website of the the Brazilian Ministry of Health. Significant associations were found between the health data and refinery activities. The combination of the spatial

  18. Ore reserve evalution, through geostatistical methods, in sector C-09, Pocos de Caldas, MG-Brazil

    International Nuclear Information System (INIS)

    Guerra, P.A.G.; Censi, A.C.; Marques, J.P.M.; Huijbregts, Ch.

    1978-01-01

    In sector C-09, Pocos de Caldas in the state of Minas Gerais, geostatistical techniques have been used to evaluate the tonnage of U 3 O 8 and associated minerals and to delimit ore from sterile areas. The calculation of reserve was based on borehole information including the results of chemical and/or radiometric analysis. Two-and three dimensional evalutions were made following the existing geological models. Initially, the evaluation was based on chemical analysis using the more classical geostatistical technique of kriging. This was followed by a second evaluation using the more recent technique of co-kriging which permited the incorporation of radiometric information in the calculations. The correlation between ore grade and radiometric was studied using the method of cross-covariance. Following restrictions imposed by mining considerations, a probabilistic selection was made of blocks of appropriate dimensions so as to evaluate the grade tonnage curve for each panel. (Author) [pt

  19. Applications of stochastic models and geostatistical analyses to study sources and spatial patterns of soil heavy metals in a metalliferous industrial district of China

    International Nuclear Information System (INIS)

    Zhong, Buqing; Liang, Tao; Wang, Lingqing; Li, Kexin

    2014-01-01

    An extensive soil survey was conducted to study pollution sources and delineate contamination of heavy metals in one of the metalliferous industrial bases, in the karst areas of southwest China. A total of 597 topsoil samples were collected and the concentrations of five heavy metals, namely Cd, As (metalloid), Pb, Hg and Cr were analyzed. Stochastic models including a conditional inference tree (CIT) and a finite mixture distribution model (FMDM) were applied to identify the sources and partition the contribution from natural and anthropogenic sources for heavy metal in topsoils of the study area. Regression trees for Cd, As, Pb and Hg were proved to depend mostly on indicators of anthropogenic activities such as industrial type and distance from urban area, while the regression tree for Cr was found to be mainly influenced by the geogenic characteristics. The FMDM analysis showed that the geometric means of modeled background values for Cd, As, Pb, Hg and Cr were close to their background values previously reported in the study area, while the contamination of Cd and Hg were widespread in the study area, imposing potentially detrimental effects on organisms through the food chain. Finally, the probabilities of single and multiple heavy metals exceeding the threshold values derived from the FMDM were estimated using indicator kriging (IK) and multivariate indicator kriging (MVIK). The high probabilities exceeding the thresholds of heavy metals were associated with metalliferous production and atmospheric deposition of heavy metals transported from the urban and industrial areas. Geostatistics coupled with stochastic models provide an effective way to delineate multiple heavy metal pollution to facilitate improved environmental management. - Highlights: • Conditional inference tree can identify variables controlling metal distribution. • Finite mixture distribution model can partition natural and anthropogenic sources. • Geostatistics with stochastic models

  20. Applications of stochastic models and geostatistical analyses to study sources and spatial patterns of soil heavy metals in a metalliferous industrial district of China

    Energy Technology Data Exchange (ETDEWEB)

    Zhong, Buqing; Liang, Tao, E-mail: liangt@igsnrr.ac.cn; Wang, Lingqing; Li, Kexin

    2014-08-15

    An extensive soil survey was conducted to study pollution sources and delineate contamination of heavy metals in one of the metalliferous industrial bases, in the karst areas of southwest China. A total of 597 topsoil samples were collected and the concentrations of five heavy metals, namely Cd, As (metalloid), Pb, Hg and Cr were analyzed. Stochastic models including a conditional inference tree (CIT) and a finite mixture distribution model (FMDM) were applied to identify the sources and partition the contribution from natural and anthropogenic sources for heavy metal in topsoils of the study area. Regression trees for Cd, As, Pb and Hg were proved to depend mostly on indicators of anthropogenic activities such as industrial type and distance from urban area, while the regression tree for Cr was found to be mainly influenced by the geogenic characteristics. The FMDM analysis showed that the geometric means of modeled background values for Cd, As, Pb, Hg and Cr were close to their background values previously reported in the study area, while the contamination of Cd and Hg were widespread in the study area, imposing potentially detrimental effects on organisms through the food chain. Finally, the probabilities of single and multiple heavy metals exceeding the threshold values derived from the FMDM were estimated using indicator kriging (IK) and multivariate indicator kriging (MVIK). The high probabilities exceeding the thresholds of heavy metals were associated with metalliferous production and atmospheric deposition of heavy metals transported from the urban and industrial areas. Geostatistics coupled with stochastic models provide an effective way to delineate multiple heavy metal pollution to facilitate improved environmental management. - Highlights: • Conditional inference tree can identify variables controlling metal distribution. • Finite mixture distribution model can partition natural and anthropogenic sources. • Geostatistics with stochastic models

  1. Computational system for geostatistical analysis

    Directory of Open Access Journals (Sweden)

    Vendrusculo Laurimar Gonçalves

    2004-01-01

    Full Text Available Geostatistics identifies the spatial structure of variables representing several phenomena and its use is becoming more intense in agricultural activities. This paper describes a computer program, based on Windows Interfaces (Borland Delphi, which performs spatial analyses of datasets through geostatistic tools: Classical statistical calculations, average, cross- and directional semivariograms, simple kriging estimates and jackknifing calculations. A published dataset of soil Carbon and Nitrogen was used to validate the system. The system was useful for the geostatistical analysis process, for the manipulation of the computational routines in a MS-DOS environment. The Windows development approach allowed the user to model the semivariogram graphically with a major degree of interaction, functionality rarely available in similar programs. Given its characteristic of quick prototypation and simplicity when incorporating correlated routines, the Delphi environment presents the main advantage of permitting the evolution of this system.

  2. Technology demonstration: geostatistical and hydrologic analysis of salt areas. Assessment of effectiveness of geologic isolation systems

    International Nuclear Information System (INIS)

    Doctor, P.G.; Oberlander, P.L.; Rice, W.A.; Devary, J.L.; Nelson, R.W.; Tucker, P.E.

    1982-09-01

    The Office of Nuclear Waste Isolation (ONWI) requested Pacific Northwest Laboratory (PNL) to: (1) use geostatistical analyses to evaluate the adequacy of hydrologic data from three salt regions, each of which contains a potential nuclear waste repository site; and (2) demonstrate a methodology that allows quantification of the value of additional data collection. The three regions examined are the Paradox Basin in Utah, the Permian Basin in Texas, and the Mississippi Study Area. Additional and new data became available to ONWI during and following these analyses; therefore, this report must be considered a methodology demonstration here would apply as illustrated had the complete data sets been available. A combination of geostatistical and hydrologic analyses was used for this demonstration. Geostatistical analyses provided an optimal estimate of the potentiometric surface from the available data, a measure of the uncertainty of that estimate, and a means for selecting and evaluating the location of future data. The hydrologic analyses included the calculation of transmissivities, flow paths, travel times, and ground-water flow rates from hypothetical repository sites. Simulation techniques were used to evaluate the effect of optimally located future data on the potentiometric surface, flow lines, travel times, and flow rates. Data availability, quality, quantity, and conformance with model assumptions differed in each of the salt areas. Report highlights for the three locations are given

  3. Geostatistical ore reserve estimation for a roll-front type uranium deposit (practitioner's guide)

    International Nuclear Information System (INIS)

    Kim, Y.C.; Knudsen, H.P.

    1977-01-01

    This report comprises two parts. Part I contains illustrative examples of each phase of a geostatistical study using a roll-front type uranium deposit. Part II contains five computer programs and comprehensive users' manuals for these programs which are necessary to make a practical geostatistical study

  4. Multiobjective design of aquifer monitoring networks for optimal spatial prediction and geostatistical parameter estimation

    Science.gov (United States)

    Alzraiee, Ayman H.; Bau, Domenico A.; Garcia, Luis A.

    2013-06-01

    Effective sampling of hydrogeological systems is essential in guiding groundwater management practices. Optimal sampling of groundwater systems has previously been formulated based on the assumption that heterogeneous subsurface properties can be modeled using a geostatistical approach. Therefore, the monitoring schemes have been developed to concurrently minimize the uncertainty in the spatial distribution of systems' states and parameters, such as the hydraulic conductivity K and the hydraulic head H, and the uncertainty in the geostatistical model of system parameters using a single objective function that aggregates all objectives. However, it has been shown that the aggregation of possibly conflicting objective functions is sensitive to the adopted aggregation scheme and may lead to distorted results. In addition, the uncertainties in geostatistical parameters affect the uncertainty in the spatial prediction of K and H according to a complex nonlinear relationship, which has often been ineffectively evaluated using a first-order approximation. In this study, we propose a multiobjective optimization framework to assist the design of monitoring networks of K and H with the goal of optimizing their spatial predictions and estimating the geostatistical parameters of the K field. The framework stems from the combination of a data assimilation (DA) algorithm and a multiobjective evolutionary algorithm (MOEA). The DA algorithm is based on the ensemble Kalman filter, a Monte-Carlo-based Bayesian update scheme for nonlinear systems, which is employed to approximate the posterior uncertainty in K, H, and the geostatistical parameters of K obtained by collecting new measurements. Multiple MOEA experiments are used to investigate the trade-off among design objectives and identify the corresponding monitoring schemes. The methodology is applied to design a sampling network for a shallow unconfined groundwater system located in Rocky Ford, Colorado. Results indicate that

  5. A practical primer on geostatistics

    Science.gov (United States)

    Olea, Ricardo A.

    2009-01-01

    The Challenge—Most geological phenomena are extraordinarily complex in their interrelationships and vast in their geographical extension. Ordinarily, engineers and geoscientists are faced with corporate or scientific requirements to properly prepare geological models with measurements involving a small fraction of the entire area or volume of interest. Exact description of a system such as an oil reservoir is neither feasible nor economically possible. The results are necessarily uncertain. Note that the uncertainty is not an intrinsic property of the systems; it is the result of incomplete knowledge by the observer.The Aim of Geostatistics—The main objective of geostatistics is the characterization of spatial systems that are incompletely known, systems that are common in geology. A key difference from classical statistics is that geostatistics uses the sampling location of every measurement. Unless the measurements show spatial correlation, the application of geostatistics is pointless. Ordinarily the need for additional knowledge goes beyond a few points, which explains the display of results graphically as fishnet plots, block diagrams, and maps.Geostatistical Methods—Geostatistics is a collection of numerical techniques for the characterization of spatial attributes using primarily two tools: probabilistic models, which are used for spatial data in a manner similar to the way in which time-series analysis characterizes temporal data, or pattern recognition techniques. The probabilistic models are used as a way to handle uncertainty in results away from sampling locations, making a radical departure from alternative approaches like inverse distance estimation methods.Differences with Time Series—On dealing with time-series analysis, users frequently concentrate their attention on extrapolations for making forecasts. Although users of geostatistics may be interested in extrapolation, the methods work at their best interpolating. This simple difference

  6. MIDDLE MIOCENE DEPOSITIONAL MODEL IN THE DRAVA DEPRESSION DESCRIBED BY GEOSTATISTICAL POROSITY AND THICKNESS MAPS (CASE STUDY: STARI GRADAC-BARCS NYUGAT FIELD

    Directory of Open Access Journals (Sweden)

    Tomislav Malvić

    2006-12-01

    Full Text Available Neogene depositional environments in the Drava depression can be classified in two groups. One group is of local alluvial fans, which were active during the period of Middle Miocene (Badenian extension through the entire Pannonian Basin. The second group is represented by continuous Pannonian and Pontian sedimentation starting with lacustrine environment of partly deep water and partly prodelta (turbidity fans and terminating at the delta plain sedimentation. The coarse-grained sediments of alluvial fans have the great hydrocarbon potential, because they often comprise reservoir rocks. Reservoir deposits are mostly overlain (as result of fan migration by pelitic seal deposits and sometimes including organic rich source facies. That Badenian sequences are often characterised by complete petroleum systems, what is confirmed by large number of oil and gas discoveries in such sediments in the Drava and other Croatian depressions. Alluvial environments are characterised by frequent changes of petrophysical properties, due to local character of depositional mechanism and material sources. In the presented paper, Stari Gradac-Barcs Nyugat field is selected as a case study for demonstrating the above mentioned heterogenic features of the Badenian sequences. Structural solutions are compared by maps of parameters related to depositional environment, i.e. porosity and thickness maps. Geostatistics were used for spatial extension of input dataset. The spatial variability of porosity values, i.e. reservoir quality, is interpreted by transition among different sub-environments (facies in the alluvial fan system.

  7. Geostatistics - bloodhound of uranium exploration

    International Nuclear Information System (INIS)

    David, Michel

    1979-01-01

    Geostatistics makes possible the efficient use of the information contained in core samples obtained by diamond drilling. The probability that a core represents the true content of a deposit, and the likely content of an orebody between two core samples can both be estimated using geostatistical methods. A confidence interval can be given for the mean grade of a deposit. The use of a computer is essential in the calculation of the continuity function, the variogram, when as many as 800,000 core samples may be involved. The results may be used to determine where additional samples need to be taken, and to develop a picture of the probable grades throughout the deposit. The basic mathematical model is about 15 years old, but applications to different types of deposit require various adaptations. The Ecole Polytechnique is currently developing methods for uranium deposits. (LL)

  8. Benchmarking a geostatistical procedure for the homogenisation of annual precipitation series

    Science.gov (United States)

    Caineta, Júlio; Ribeiro, Sara; Henriques, Roberto; Soares, Amílcar; Costa, Ana Cristina

    2014-05-01

    The European project COST Action ES0601, Advances in homogenisation methods of climate series: an integrated approach (HOME), has brought to attention the importance of establishing reliable homogenisation methods for climate data. In order to achieve that, a benchmark data set, containing monthly and daily temperature and precipitation data, was created to be used as a comparison basis for the effectiveness of those methods. Several contributions were submitted and evaluated by a number of performance metrics, validating the results against realistic inhomogeneous data. HOME also led to the development of new homogenisation software packages, which included feedback and lessons learned during the project. Preliminary studies have suggested a geostatistical stochastic approach, which uses Direct Sequential Simulation (DSS), as a promising methodology for the homogenisation of precipitation data series. Based on the spatial and temporal correlation between the neighbouring stations, DSS calculates local probability density functions at a candidate station to detect inhomogeneities. The purpose of the current study is to test and compare this geostatistical approach with the methods previously presented in the HOME project, using surrogate precipitation series from the HOME benchmark data set. The benchmark data set contains monthly precipitation surrogate series, from which annual precipitation data series were derived. These annual precipitation series were subject to exploratory analysis and to a thorough variography study. The geostatistical approach was then applied to the data set, based on different scenarios for the spatial continuity. Implementing this procedure also promoted the development of a computer program that aims to assist on the homogenisation of climate data, while minimising user interaction. Finally, in order to compare the effectiveness of this methodology with the homogenisation methods submitted during the HOME project, the obtained results

  9. Applications of stochastic models and geostatistical analyses to study sources and spatial patterns of soil heavy metals in a metalliferous industrial district of China.

    Science.gov (United States)

    Zhong, Buqing; Liang, Tao; Wang, Lingqing; Li, Kexin

    2014-08-15

    An extensive soil survey was conducted to study pollution sources and delineate contamination of heavy metals in one of the metalliferous industrial bases, in the karst areas of southwest China. A total of 597 topsoil samples were collected and the concentrations of five heavy metals, namely Cd, As (metalloid), Pb, Hg and Cr were analyzed. Stochastic models including a conditional inference tree (CIT) and a finite mixture distribution model (FMDM) were applied to identify the sources and partition the contribution from natural and anthropogenic sources for heavy metal in topsoils of the study area. Regression trees for Cd, As, Pb and Hg were proved to depend mostly on indicators of anthropogenic activities such as industrial type and distance from urban area, while the regression tree for Cr was found to be mainly influenced by the geogenic characteristics. The FMDM analysis showed that the geometric means of modeled background values for Cd, As, Pb, Hg and Cr were close to their background values previously reported in the study area, while the contamination of Cd and Hg were widespread in the study area, imposing potentially detrimental effects on organisms through the food chain. Finally, the probabilities of single and multiple heavy metals exceeding the threshold values derived from the FMDM were estimated using indicator kriging (IK) and multivariate indicator kriging (MVIK). The high probabilities exceeding the thresholds of heavy metals were associated with metalliferous production and atmospheric deposition of heavy metals transported from the urban and industrial areas. Geostatistics coupled with stochastic models provide an effective way to delineate multiple heavy metal pollution to facilitate improved environmental management. Copyright © 2014 Elsevier B.V. All rights reserved.

  10. Constrained optimisation of spatial sampling : a geostatistical approach

    NARCIS (Netherlands)

    Groenigen, van J.W.

    1999-01-01

    Aims

    This thesis aims at the development of optimal sampling strategies for geostatistical studies. Special emphasis is on the optimal use of ancillary data, such as co-related imagery, preliminary observations and historic knowledge. Although the object of all studies

  11. Study of the permeability up-scaling by direct filtering of geostatistical model; Etude du changement d'echelle des permeabilites par filtrage direct du modele geostatistique

    Energy Technology Data Exchange (ETDEWEB)

    Zargar, G

    2005-10-15

    In this thesis, we present a new approach, which consists in directly up-scaling the geostatistical permeability distribution rather than the individual realizations. Practically, filtering techniques based on. the FFT (Fast Fourier Transform), allows us to generate geostatistical images, which sample the up-scaled distributions. In the log normal case, an equivalence hydraulic criterion is proposed, allowing to re-estimate the geometric mean of the permeabilities. In the anisotropic case, the effective geometric mean becomes a tensor which depends on the level of filtering used and it can be calculated by a method of renormalisation. Then, the method was generalized for the categorial model. Numerical tests of the method were set up for isotropic, anisotropic and categorial models, which shows good agreement with theory. (author)

  12. Study of the permeability up-scaling by direct filtering of geostatistical model; Etude du changement d'echelle des permeabilites par filtrage direct du modele geostatistique

    Energy Technology Data Exchange (ETDEWEB)

    Zargar, G.

    2005-10-15

    In this thesis, we present a new approach, which consists in directly up-scaling the geostatistical permeability distribution rather than the individual realizations. Practically, filtering techniques based on. the FFT (Fast Fourier Transform), allows us to generate geostatistical images, which sample the up-scaled distributions. In the log normal case, an equivalence hydraulic criterion is proposed, allowing to re-estimate the geometric mean of the permeabilities. In the anisotropic case, the effective geometric mean becomes a tensor which depends on the level of filtering used and it can be calculated by a method of renormalisation. Then, the method was generalized for the categorial model. Numerical tests of the method were set up for isotropic, anisotropic and categorial models, which shows good agreement with theory. (author)

  13. Geostatistical enhancement of european hydrological predictions

    Science.gov (United States)

    Pugliese, Alessio; Castellarin, Attilio; Parajka, Juraj; Arheimer, Berit; Bagli, Stefano; Mazzoli, Paolo; Montanari, Alberto; Blöschl, Günter

    2016-04-01

    Geostatistical Enhancement of European Hydrological Prediction (GEEHP) is a research experiment developed within the EU funded SWITCH-ON project, which proposes to conduct comparative experiments in a virtual laboratory in order to share water-related information and tackle changes in the hydrosphere for operational needs (http://www.water-switch-on.eu). The main objective of GEEHP deals with the prediction of streamflow indices and signatures in ungauged basins at different spatial scales. In particular, among several possible hydrological signatures we focus in our experiment on the prediction of flow-duration curves (FDCs) along the stream-network, which has attracted an increasing scientific attention in the last decades due to the large number of practical and technical applications of the curves (e.g. hydropower potential estimation, riverine habitat suitability and ecological assessments, etc.). We apply a geostatistical procedure based on Top-kriging, which has been recently shown to be particularly reliable and easy-to-use regionalization approach, employing two different type of streamflow data: pan-European E-HYPE simulations (http://hypeweb.smhi.se/europehype) and observed daily streamflow series collected in two pilot study regions, i.e. Tyrol (merging data from Austrian and Italian stream gauging networks) and Sweden. The merger of the two study regions results in a rather large area (~450000 km2) and might be considered as a proxy for a pan-European application of the approach. In a first phase, we implement a bidirectional validation, i.e. E-HYPE catchments are set as training sites to predict FDCs at the same sites where observed data are available, and vice-versa. Such a validation procedure reveals (1) the usability of the proposed approach for predicting the FDCs over the entire river network of interest using alternatively observed data and E-HYPE simulations and (2) the accuracy of E-HYPE-based predictions of FDCs in ungauged sites. In a

  14. Geostatistical methods for the integrated information; Metodos geoestadisticos para la integracion de informacion

    Energy Technology Data Exchange (ETDEWEB)

    Cassiraga, E F; Gomez-Hernandez, J J [Departamento de Ingenieria Hidraulica y Medio Ambiente, Universidad Politecnica de Valencia, Valencia (Spain)

    1996-10-01

    The main objective of this report is to describe the different geostatistical techniques to use the geophysical and hydrological parameters. We analyze the characteristics of estimation methods used in others studies.

  15. ASSESSMENT SPATIAL VARIABILITY OF SOIL ERODIBILITY BY USING OF GEOSTATISTIC AND GIS (Case study MEHR watershed of SABZEVAR

    Directory of Open Access Journals (Sweden)

    Ayoubi, S.A

    2005-05-01

    Full Text Available Soil erodibility is one of the key factors on some sediment and soil erosion models such as USLE, MUSLE, RUSLE, AUSLE (USLE modified in LS factor and MMF and represents like K factor and is function of particle distribution, organic mater, soil structure and ermeability. Traditional methods do not take spatial variability and estimate precision of variables in to consideration and amount of them are constant across the whole of soil series .This study was performed to assess spatial variability of soil erodibility and its relevant variables at MEHR watershed from Khorasan province, in northern Iran. Interested network was designed by 110 samples like nested- systematic with distance about 50, 100, 250 and 500 meter across the study area by preparing point map at GIS. Sampling points were identified in field by an Global Positioning system. Soil sampling was done at depth of 0-5cm of ground surface and permeability was studied at depth of 5-30 cm. Some soil properties such as particle distribution and organic mater were measured at laboratory. Particle size distribution was determined by Hydrometer method and Organic matter was measured by wet oxidation approach. Then spatial analysis was done. Variography analysis on soil attributes according to soil erodibility, showed that Gaussian, exponential and spherical models were the most models to predict spatial variability of soil parameters. The range of spatial dependencies was changed from 320 to 3200 m. Soil attribute maps prepared by kriging technique using models parameters. Then soil attributes were composed by Wischmeier (1978 formula in Illwis media to calculate K factor. Amount of soil erodibility changed from 0.13 to 0.91 that it's maximum and minimum was identified in east and southwest of studiedarea. Soil spatial variability pattern, is similar to silt pattern due to high effect of silt on soil rodibility, Also that is partially confirmed with geology map, indicated which soil

  16. Geostatistical inference using crosshole ground-penetrating radar

    DEFF Research Database (Denmark)

    Looms, Majken C; Hansen, Thomas Mejer; Cordua, Knud Skou

    2010-01-01

    of the subsurface are used to evaluate the uncertainty of the inversion estimate. We have explored the full potential of the geostatistical inference method using several synthetic models of varying correlation structures and have tested the influence of different assumptions concerning the choice of covariance...... reflection profile. Furthermore, the inferred values of the subsurface global variance and the mean velocity have been corroborated with moisturecontent measurements, obtained gravimetrically from samples collected at the field site....

  17. Use of geostatistics for remediation planning to transcend urban political boundaries

    International Nuclear Information System (INIS)

    Milillo, Tammy M.; Sinha, Gaurav; Gardella, Joseph A.

    2012-01-01

    Soil remediation plans are often dictated by areas of jurisdiction or property lines instead of scientific information. This study exemplifies how geostatistically interpolated surfaces can substantially improve remediation planning. Ordinary kriging, ordinary co-kriging, and inverse distance weighting spatial interpolation methods were compared for analyzing surface and sub-surface soil sample data originally collected by the US EPA and researchers at the University at Buffalo in Hickory Woods, an industrial–residential neighborhood in Buffalo, NY, where both lead and arsenic contamination is present. Past clean-up efforts estimated contamination levels from point samples, but parcel and agency jurisdiction boundaries were used to define remediation sites, rather than geostatistical models estimating the spatial behavior of the contaminants in the soil. Residents were understandably dissatisfied with the arbitrariness of the remediation plan. In this study we show how geostatistical mapping and participatory assessment can make soil remediation scientifically defensible, socially acceptable, and economically feasible. - Highlights: ► Point samples and property boundaries do not appropriately determine the extent of soil contamination. ► Kriging and co-kriging provide best concentration estimates for mapping soil contamination and refining clean-up sites. ► Maps provide a visual representation of geostatistical results to communities to aid in geostatistical decision making. ► Incorporating community input into the assessment of neighborhoods is good public policy practice. - Using geostatistical interpolation and mapping results to involve the affected community can substantially improve remediation planning and promote its long-term effectiveness.

  18. Geostatistical analysis of the flood risk perception queries in the village of Navaluenga (Central Spain)

    Science.gov (United States)

    Guardiola-Albert, Carolina; Díez-Herrero, Andrés; Amérigo, María; García, Juan Antonio; María Bodoque, José; Fernández-Naranjo, Nuria

    2017-04-01

    response actions, such as designing optimal evacuation routes during flood emergencies. Geostatistical tools also provide a set of interpolation techniques for the prediction of the variable value at unstudied similar locations, basing on the sample point values and other variables related with the measured variable. We attempt different geostatistical interpolation methods to obtain continuous surfaces of the risk perception and level of awareness in the study area. The use of these maps for future extensions and actualizations of the Civil Protection Plan is evaluated. References Bodoque, J. M., Amérigo, M., Díez-Herrero, A., García, J. A., Cortés, B., Ballesteros-Cánovas, J. A., & Olcina, J. (2016). Improvement of resilience of urban areas by integrating social perception in flash-flood risk management.Journal of Hydrology.

  19. The role of geostatistics in medical geology

    Science.gov (United States)

    Goovaerts, Pierre

    2014-05-01

    Since its development in the mining industry, geostatistics has emerged as the primary tool for spatial data analysis in various fields, ranging from earth and atmospheric sciences, to agriculture, soil science, remote sensing, and more recently environmental exposure assessment. In the last few years, these tools have been tailored to the field of medical geography or spatial epidemiology, which is concerned with the study of spatial patterns of disease incidence and mortality and the identification of potential 'causes' of disease, such as environmental exposure, diet and unhealthy behaviors, economic or socio-demographic factors. On the other hand, medical geology is an emerging interdisciplinary scientific field studying the relationship between natural geological factors and their effects on human and animal health. This paper provides an introduction to the field of medical geology with an overview of geostatistical methods available for the analysis of geological and health data. Key concepts are illustrated using the mapping of groundwater arsenic concentrations across eleven Michigan counties and the exploration of its relationship to the incidence of prostate cancer at the township level. Arsenic in drinking-water is a major problem and has received much attention because of the large human population exposed and the extremely high concentrations (e.g. 600 to 700 μg/L) recorded in many instances. Few studies have however assessed the risks associated with exposure to low levels of arsenic (say water in the United States. In the Michigan thumb region, arsenopyrite (up to 7% As by weight) has been identified in the bedrock of the Marshall Sandstone aquifer, one of the region's most productive aquifers. Epidemiologic studies have suggested a possible associationbetween exposure to inorganic arsenic and prostate cancer mortality, including a study of populations residing in Utah. The information available for the present ecological study (i.e. analysis of

  20. 3D vadose zone modeling using geostatistical inferences

    International Nuclear Information System (INIS)

    Knutson, C.F.; Lee, C.B.

    1991-01-01

    In developing a 3D model of the 600 ft thick interbedded basalt and sediment complex that constitutes the vadose zone at the Radioactive Waste Management Complex (RWMC) at the Idaho National Engineering Laboratory (INEL) geostatistical data were captured for 12--15 parameters (e.g. permeability, porosity, saturation, etc. and flow height, flow width, flow internal zonation, etc.). This two scale data set was generated from studies of subsurface core and geophysical log suites at RWMC and from surface outcrop exposures located at the Box Canyon of the Big Lost River and from Hell's Half Acre lava field all located in the general RWMC area. Based on these currently available data, it is possible to build a 3D stochastic model that utilizes: cumulative distribution functions obtained from the geostatistical data; backstripping and rebuilding of stratigraphic units; an ''expert'' system that incorporates rules based on expert geologic analysis and experimentally derived geostatistics for providing: (a) a structural and isopach map of each layer, (b) a realization of the flow geometry of each basalt flow unit, and (c) a realization of the internal flow parameters (eg permeability, porosity, and saturation) for each flow. 10 refs., 4 figs., 1 tab

  1. Demonstration of a geostatistical approach to physically consistent downscaling of climate modeling simulations

    KAUST Repository

    Jha, Sanjeev Kumar; Mariethoz, Gregoire; Evans, Jason P.; McCabe, Matthew

    2013-01-01

    A downscaling approach based on multiple-point geostatistics (MPS) is presented. The key concept underlying MPS is to sample spatial patterns from within training images, which can then be used in characterizing the relationship between different variables across multiple scales. The approach is used here to downscale climate variables including skin surface temperature (TSK), soil moisture (SMOIS), and latent heat flux (LH). The performance of the approach is assessed by applying it to data derived from a regional climate model of the Murray-Darling basin in southeast Australia, using model outputs at two spatial resolutions of 50 and 10 km. The data used in this study cover the period from 1985 to 2006, with 1985 to 2005 used for generating the training images that define the relationships of the variables across the different spatial scales. Subsequently, the spatial distributions for the variables in the year 2006 are determined at 10 km resolution using the 50 km resolution data as input. The MPS geostatistical downscaling approach reproduces the spatial distribution of TSK, SMOIS, and LH at 10 km resolution with the correct spatial patterns over different seasons, while providing uncertainty estimates through the use of multiple realizations. The technique has the potential to not only bridge issues of spatial resolution in regional and global climate model simulations but also in feature sharpening in remote sensing applications through image fusion, filling gaps in spatial data, evaluating downscaled variables with available remote sensing images, and aggregating/disaggregating hydrological and groundwater variables for catchment studies.

  2. Integration of dynamical data in a geostatistical model of reservoir; Integration des donnees dynamiques dans un modele geostatistique de reservoir

    Energy Technology Data Exchange (ETDEWEB)

    Costa Reis, L.

    2001-01-01

    We have developed in this thesis a methodology of integrated characterization of heterogeneous reservoirs, from geologic modeling to history matching. This methodology is applied to the reservoir PBR, situated in Campos Basin, offshore Brazil, which has been producing since June 1979. This work is an extension of two other thesis concerning geologic and geostatistical modeling of the reservoir PBR from well data and seismic information. We extended the geostatistical litho-type model to the whole reservoir by using a particular approach of the non-stationary truncated Gaussian simulation method. This approach facilitated the application of the gradual deformation method to history matching. The main stages of the methodology for dynamic data integration in a geostatistical reservoir model are presented. We constructed a reservoir model and the initial difficulties in the history matching led us to modify some choices in the geological, geostatistical and flow models. These difficulties show the importance of dynamic data integration in reservoir modeling. The petrophysical property assignment within the litho-types was done by using well test data. We used an inversion procedure to evaluate the petrophysical parameters of the litho-types. The up-scaling is a necessary stage to reduce the flow simulation time. We compared several up-scaling methods and we show that the passage from the fine geostatistical model to the coarse flow model should be done very carefully. The choice of the fitting parameter depends on the objective of the study. In the case of the reservoir PBR, where water is injected in order to improve the oil recovery, the water rate of the producing wells is directly related to the reservoir heterogeneity. Thus, the water rate was chosen as the fitting parameter. We obtained significant improvements in the history matching of the reservoir PBR. First, by using a method we have proposed, called patchwork. This method allows us to built a coherent

  3. Geostatistical methods applied to field model residuals

    DEFF Research Database (Denmark)

    Maule, Fox; Mosegaard, K.; Olsen, Nils

    consists of measurement errors and unmodelled signal), and is typically assumed to be uncorrelated and Gaussian distributed. We have applied geostatistical methods to analyse the residuals of the Oersted(09d/04) field model [http://www.dsri.dk/Oersted/Field_models/IGRF_2005_candidates/], which is based...

  4. Satellite Magnetic Residuals Investigated With Geostatistical Methods

    DEFF Research Database (Denmark)

    Fox Maule, Chaterine; Mosegaard, Klaus; Olsen, Nils

    2005-01-01

    (which consists of measurement errors and unmodeled signal), and is typically assumed to be uncorrelated and Gaussian distributed. We have applied geostatistical methods to analyze the residuals of the Oersted (09d/04) field model (www.dsri.dk/Oersted/Field models/IGRF 2005 candidates/), which is based...

  5. Industrial experience feedback of a geostatistical estimation of contaminated soil volumes - 59181

    International Nuclear Information System (INIS)

    Faucheux, Claire; Jeannee, Nicolas

    2012-01-01

    Geo-statistics meets a growing interest for the remediation forecast of potentially contaminated sites, by providing adapted methods to perform both chemical and radiological pollution mapping, to estimate contaminated volumes, potentially integrating auxiliary information, and to set up adaptive sampling strategies. As part of demonstration studies carried out for GeoSiPol (Geo-statistics for Polluted Sites), geo-statistics has been applied for the detailed diagnosis of a former oil depot in France. The ability within the geo-statistical framework to generate pessimistic / probable / optimistic scenarios for the contaminated volumes allows a quantification of the risks associated to the remediation process: e.g. the financial risk to excavate clean soils, the sanitary risk to leave contaminated soils in place. After a first mapping, an iterative approach leads to collect additional samples in areas previously identified as highly uncertain. Estimated volumes are then updated and compared to the volumes actually excavated. This benchmarking therefore provides a practical feedback on the performance of the geo-statistical methodology. (authors)

  6. Data analysis for radiological characterisation: Geostatistical and statistical complementarity

    International Nuclear Information System (INIS)

    Desnoyers, Yvon; Dubot, Didier

    2012-01-01

    Radiological characterisation may cover a large range of evaluation objectives during a decommissioning and dismantling (D and D) project: removal of doubt, delineation of contaminated materials, monitoring of the decontamination work and final survey. At each stage, collecting relevant data to be able to draw the conclusions needed is quite a big challenge. In particular two radiological characterisation stages require an advanced sampling process and data analysis, namely the initial categorization and optimisation of the materials to be removed and the final survey to demonstrate compliance with clearance levels. On the one hand the latter is widely used and well developed in national guides and norms, using random sampling designs and statistical data analysis. On the other hand a more complex evaluation methodology has to be implemented for the initial radiological characterisation, both for sampling design and for data analysis. The geostatistical framework is an efficient way to satisfy the radiological characterisation requirements providing a sound decision-making approach for the decommissioning and dismantling of nuclear premises. The relevance of the geostatistical methodology relies on the presence of a spatial continuity for radiological contamination. Thus geo-statistics provides reliable methods for activity estimation, uncertainty quantification and risk analysis, leading to a sound classification of radiological waste (surfaces and volumes). This way, the radiological characterization of contaminated premises can be divided into three steps. First, the most exhaustive facility analysis provides historical and qualitative information. Then, a systematic (exhaustive or not) surface survey of the contamination is implemented on a regular grid. Finally, in order to assess activity levels and contamination depths, destructive samples are collected at several locations within the premises (based on the surface survey results) and analysed. Combined with

  7. Risk Assessment of Sediment Pollution Using Geostatistical Simulations

    Science.gov (United States)

    Golay, J.; Kanevski, M.

    2012-04-01

    Environmental monitoring networks (EMN) discreetly measure the intensities of continuous phenomena (e.g. pollution, temperature, etc.). Spatial prediction models, like kriging, are then used for modeling. But, they give rise to smooth representations of phenomena which leads to overestimations or underestimations of extreme values. Moreover, they do not reproduce the spatial variability of the original data and the corresponding uncertainties. When dealing with risk assessment, this is unacceptable, since extreme values must be retrieved and probabilities of exceeding given thresholds must be computed [Kanevski et al., 2009]. In order to overcome these obstacles, geostatistics provides another approach: conditional stochastic simulations. Here, the basic idea is to generate multiple estimates of variable values (e.g. pollution concentration) at every location of interest which are calculated as stochastic realizations of an unknown random function (see, for example, [Kanevski, 2008], where both theoretical concepts and real data case studies are presented in detail). Many algorithms implement this approach. The most widely used in spatial modeling are sequential Gaussian simulations/cosimulations, sequential indicator simulations/cosimulations and direct simulations. In the present study, several algorithms of geostatistical conditional simulations were applied on real data collected from Lake Geneva. The main objectives were to compare their effectiveness in reproducing global statistics (histograms, variograms) and the way they characterize the variability and uncertainty of the contamination patterns. The dataset is composed of 200 measurements of the contamination of the lake sediments by heavy metals (i.e. Cadmium, Mercury, Zinc, Copper, Titanium and Chromium). The results obtained show some differences highlighting that risk assessment can be influenced by the algorithm it relies on. Moreover, hybrid models based on machine learning algorithms and

  8. Geostatistical analysis of prevailing groundwater conditions and potential solute migration at Elstow, Bedfordshire

    International Nuclear Information System (INIS)

    MacKay, R.; Cooper, T.A.; Porter, J.D.; O'Connell, P.E.; Metcalfe, A.V.

    1988-06-01

    A geostatistical approach is applied in a study of the potential migration of contaminants from a hypothetical waste disposal facility near Elstow, Bedfordshire. A deterministic numerical model of groundwater flow in the Kellaways Sands formation and adjacent layers is coupled with geostatistical simulation of the heterogeneous transmissivity field of this principal formation. A particle tracking technique is used to predict the migration pathways for alternative realisations of flow. Alternative statistical descriptions of the spatial structure of the transmissivity field are implemented and the temporal and spatial distributions of escape of contaminants to the biosphere are investigated. (author)

  9. Validating spatial structure in canopy water content using geostatistics

    Science.gov (United States)

    Sanderson, E. W.; Zhang, M. H.; Ustin, S. L.; Rejmankova, E.; Haxo, R. S.

    1995-01-01

    Heterogeneity in ecological phenomena are scale dependent and affect the hierarchical structure of image data. AVIRIS pixels average reflectance produced by complex absorption and scattering interactions between biogeochemical composition, canopy architecture, view and illumination angles, species distributions, and plant cover as well as other factors. These scales affect validation of pixel reflectance, typically performed by relating pixel spectra to ground measurements acquired at scales of 1m(exp 2) or less (e.g., field spectra, foilage and soil samples, etc.). As image analysis becomes more sophisticated, such as those for detection of canopy chemistry, better validation becomes a critical problem. This paper presents a methodology for bridging between point measurements and pixels using geostatistics. Geostatistics have been extensively used in geological or hydrogeolocial studies but have received little application in ecological studies. The key criteria for kriging estimation is that the phenomena varies in space and that an underlying controlling process produces spatial correlation between the measured data points. Ecological variation meets this requirement because communities vary along environmental gradients like soil moisture, nutrient availability, or topography.

  10. Mapping aboveground woody biomass using forest inventory, remote sensing and geostatistical techniques.

    Science.gov (United States)

    Yadav, Bechu K V; Nandy, S

    2015-05-01

    Mapping forest biomass is fundamental for estimating CO₂ emissions, and planning and monitoring of forests and ecosystem productivity. The present study attempted to map aboveground woody biomass (AGWB) integrating forest inventory, remote sensing and geostatistical techniques, viz., direct radiometric relationships (DRR), k-nearest neighbours (k-NN) and cokriging (CoK) and to evaluate their accuracy. A part of the Timli Forest Range of Kalsi Soil and Water Conservation Division, Uttarakhand, India was selected for the present study. Stratified random sampling was used to collect biophysical data from 36 sample plots of 0.1 ha (31.62 m × 31.62 m) size. Species-specific volumetric equations were used for calculating volume and multiplied by specific gravity to get biomass. Three forest-type density classes, viz. 10-40, 40-70 and >70% of Shorea robusta forest and four non-forest classes were delineated using on-screen visual interpretation of IRS P6 LISS-III data of December 2012. The volume in different strata of forest-type density ranged from 189.84 to 484.36 m(3) ha(-1). The total growing stock of the forest was found to be 2,024,652.88 m(3). The AGWB ranged from 143 to 421 Mgha(-1). Spectral bands and vegetation indices were used as independent variables and biomass as dependent variable for DRR, k-NN and CoK. After validation and comparison, k-NN method of Mahalanobis distance (root mean square error (RMSE) = 42.25 Mgha(-1)) was found to be the best method followed by fuzzy distance and Euclidean distance with RMSE of 44.23 and 45.13 Mgha(-1) respectively. DRR was found to be the least accurate method with RMSE of 67.17 Mgha(-1). The study highlighted the potential of integrating of forest inventory, remote sensing and geostatistical techniques for forest biomass mapping.

  11. Applicability of geostatistical procedures for the evaluation of hydrogeological parameters of a fractured aquifer in the Ronneburg mine district; Anwendbarkeit geostatistischer Verfahren zur Beurteilung hydrogeologischer Parameter eines heterogenen Kluftaquifers im Ronneburger Bergbaurevier

    Energy Technology Data Exchange (ETDEWEB)

    Grasshoff, C.; Schetelig, K. [RWTH Aachen, Lehrstuhl fuer Ingenieurgeologie und Hydrogeologie (Germany); Tomschi, H. [Harress Pickel Consult GmbH, Huerth (Germany)

    1998-12-31

    The following paper demonstrates, how a geostatistical approach can help interpolating hydrogeological parameters over a certain area. The basic elements developed by G. Matheron in the sixties are represented as the preconditions and assumptions, which provide the best results of the estimation. The variogram as the most important tool in geostatistics offers the opportunity to describe the correlating behaviour of a regionalized variable. Some kriging procedures are briefly introduced, which provide under varying circumstances estimating of non-measured values with the theoretical variogram-model. In the Ronneburg mine district 108 screened drill-holes could provide coefficients of hydraulic conductivity. These were interpolated with ordinary kriging over the whole investigation area. An error calculation was performed, which could prove the accuracy of the estimation. Short prospects point out some difficulties handling with geostatistic procedures and make suggestions for further investigations. (orig.) [Deutsch] Der folgende Artikel soll aufzeigen, inwiefern ein geostatistischer Ansatz hilfreich ist, um hydrogeologische Parameter flaechenhaft zu interpolieren. Dabei werden die von Matheron in den sechziger Jahren entwickelten Grundlagen vorgestellt und die Voraussetzungen definiert, unter denen die geostatistischen Schaetzmethoden die besten Ergebnisse liefern. Das Variogramm, als wichtigstes Werkzeug, bietet die Moeglichkeit, die raeumliche Korrelation der untersuchten Variable zu belegen. Mehrere Kriging-Verfahren werden skizzenhaft vorgestellt, die es unter unterschiedlichen Voraussetzungen ermoeglichen, an den Stellen des Untersuchungsgebietes, wo keine Messungen vorliegen, Schaetzungen aus dem Variogramm-Modell zu errechnen. Im Ronneburger Bergbaugebiet wurden aus 108 verfilterten Bohrungen k{sub f}-Werte gewonnen, die mittels Ordinary Kriging flaechenhaft ueber das gesamte Untersuchungsgebiet interpoliert wurden. Eine Fehlerabschaetzung gibt ueber die

  12. Geostatistics – a tool applied to the distribution of Legionella pneumophila in a hospital water system

    Directory of Open Access Journals (Sweden)

    Pasqualina Laganà

    2015-12-01

    Full Text Available [b]Introduction.[/b] Legionnaires’ disease is normally acquired by inhalation of legionellae from a contaminated environmental source. Water systems of large buildings, such as hospitals, are often contaminated with legionellae and therefore represent a potential risk for the hospital population. The aim of this study was to evaluate the potential contamination of [i]Legionella pneumophila[/i] (LP in a large hospital in Italy through georeferential statistical analysis to assess the possible sources of dispersion and, consequently, the risk of exposure for both health care staff and patients. [b]Materials and Method. [/b]LP serogroups 1 and 2–14 distribution was considered in the wards housed on two consecutive floors of the hospital building. On the basis of information provided by 53 bacteriological analysis, a ‘random’ grid of points was chosen and spatial geostatistics or [i]FAIk Kriging[/i] was applied and compared with the results of classical statistical analysis. [b]Results[/b]. Over 50% of the examined samples were positive for [i]Legionella pneumophila[/i]. LP 1 was isolated in 69% of samples from the ground floor and in 60% of sample from the first floor; LP 2–14 in 36% of sample from the ground floor and 24% from the first. The iso-estimation maps show clearly the most contaminated pipe and the difference in the diffusion of the different [i]L. pneumophila[/i] serogroups. [b]Conclusion.[/b] Experimental work has demonstrated that geostatistical methods applied to the microbiological analysis of water matrices allows a better modeling of the phenomenon under study, a greater potential for risk management and a greater choice of methods of prevention and environmental recovery to be put in place with respect to the classical statistical analysis.

  13. Soil moisture estimation by assimilating L-band microwave brightness temperature with geostatistics and observation localization.

    Directory of Open Access Journals (Sweden)

    Xujun Han

    Full Text Available The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL; the other is observation localization (OL. Compared with CL, OL is easy to parallelize and more efficient for large-scale analysis. This paper evaluated OL in soil moisture profile characterizations, in which the geostatistical semivariogram was used to fit the spatial correlated characteristics of synthetic L-Band microwave brightness temperature measurement. The fitted semivariogram model and the local ensemble transform Kalman filter algorithm are combined together to weight and assimilate the observations within a local region surrounding the grid cell of land surface model to be analyzed. Six scenarios were compared: 1_Obs with one nearest observation assimilated, 5_Obs with no more than five nearest local observations assimilated, and 9_Obs with no more than nine nearest local observations assimilated. The scenarios with no more than 16, 25, and 36 local observations were also compared. From the results we can conclude that more local observations involved in assimilation will improve estimations with an upper bound of 9 observations in this case. This study demonstrates the potentials of geostatistical correlation representation in OL to improve data assimilation of catchment scale soil moisture using synthetic L-band microwave brightness temperature, which cannot cover the study area fully in space due to vegetation effects.

  14. Soil moisture estimation by assimilating L-band microwave brightness temperature with geostatistics and observation localization.

    Science.gov (United States)

    Han, Xujun; Li, Xin; Rigon, Riccardo; Jin, Rui; Endrizzi, Stefano

    2015-01-01

    The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL); the other is observation localization (OL). Compared with CL, OL is easy to parallelize and more efficient for large-scale analysis. This paper evaluated OL in soil moisture profile characterizations, in which the geostatistical semivariogram was used to fit the spatial correlated characteristics of synthetic L-Band microwave brightness temperature measurement. The fitted semivariogram model and the local ensemble transform Kalman filter algorithm are combined together to weight and assimilate the observations within a local region surrounding the grid cell of land surface model to be analyzed. Six scenarios were compared: 1_Obs with one nearest observation assimilated, 5_Obs with no more than five nearest local observations assimilated, and 9_Obs with no more than nine nearest local observations assimilated. The scenarios with no more than 16, 25, and 36 local observations were also compared. From the results we can conclude that more local observations involved in assimilation will improve estimations with an upper bound of 9 observations in this case. This study demonstrates the potentials of geostatistical correlation representation in OL to improve data assimilation of catchment scale soil moisture using synthetic L-band microwave brightness temperature, which cannot cover the study area fully in space due to vegetation effects.

  15. Uso da geoestatística para avaliar a captação automática dos níveis de pressão sonora em instalações de creche para suínos Geostatistics to evaluate the automatic acquisiton of sound pressure levels in pig nursery facilities

    Directory of Open Access Journals (Sweden)

    Giselle Borges

    2010-06-01

    Full Text Available Este trabalho teve o objetivo de estudar a influência da distribuição de decibelímetros na captação automática dos níveis de pressão sonora, em ambiente de produção intensiva de suínos. O experimento foi conduzido em sala do setor de creche de uma granja comercial de suínos situada no município de Monte Mor, Estado de São Paulo. A sala foi dividida em dez quadrantes idênticos, e os decibelímetros foram instalados no centro geométrico de cada quadrante. Utilizou-se a geoestatística para avaliar a dependência espacial entre os decibelímetros e para predizer os níveis de pressão sonora em locais onde estes não foram instalados. Os dados foram analisados pela correlação entre os decibelímetros e por intermédio da geoestatística, que possibilitou afirmar que não houve dependência espacial entre os pontos de registro dos níveis de pressão sonora. Por intermédio da interpolação dos pontos de captura utilizando o processo de krigagem, foi possível predizer os níveis de pressão sonora nos locais onde não havia decibelímetros no interior da instalação. Verificou-se homogeneidade de propagação dos níveis de pressão sonora no interior da instalação, concluindo que, para o ambiente avaliado, o uso de somente um equipamento para o registro automático dos níveis de pressão sonora é suficiente.The objective of this work was to study the influence of decibelimeters distribution in the automatic acquisition of sound pressure levels in pig nursery facilities. The experiment was conducted in a nursering room of a commercial swine's facility situated in the city of Monte Mor, State of São Paulo, Brazil. The room was divided in ten identical quadrants and the geometrical center of each quadrant was installed the decibelimeters. Geostatistics was used to evaluate the spatial dependence among the decibelimeters and to predict sound pressure levels in the places that they were not installed. Data were analyzed by the

  16. The application of geostatistics in erosion hazard mapping

    NARCIS (Netherlands)

    Beurden, S.A.H.A. van; Riezebos, H.Th.

    1988-01-01

    Geostatistical interpolation or kriging of soil and vegetation variables has become an important alternative to other mapping techniques. Although a reconnaissance sampling is necessary and basic requirements of geostatistics have to be met, kriging has the advantage of giving estimates with a

  17. Quantifying natural delta variability using a multiple-point geostatistics prior uncertainty model

    Science.gov (United States)

    Scheidt, Céline; Fernandes, Anjali M.; Paola, Chris; Caers, Jef

    2016-10-01

    We address the question of quantifying uncertainty associated with autogenic pattern variability in a channelized transport system by means of a modern geostatistical method. This question has considerable relevance for practical subsurface applications as well, particularly those related to uncertainty quantification relying on Bayesian approaches. Specifically, we show how the autogenic variability in a laboratory experiment can be represented and reproduced by a multiple-point geostatistical prior uncertainty model. The latter geostatistical method requires selection of a limited set of training images from which a possibly infinite set of geostatistical model realizations, mimicking the training image patterns, can be generated. To that end, we investigate two methods to determine how many training images and what training images should be provided to reproduce natural autogenic variability. The first method relies on distance-based clustering of overhead snapshots of the experiment; the second method relies on a rate of change quantification by means of a computer vision algorithm termed the demon algorithm. We show quantitatively that with either training image selection method, we can statistically reproduce the natural variability of the delta formed in the experiment. In addition, we study the nature of the patterns represented in the set of training images as a representation of the "eigenpatterns" of the natural system. The eigenpattern in the training image sets display patterns consistent with previous physical interpretations of the fundamental modes of this type of delta system: a highly channelized, incisional mode; a poorly channelized, depositional mode; and an intermediate mode between the two.

  18. Forecasting Interest Rates Using Geostatistical Techniques

    Directory of Open Access Journals (Sweden)

    Giuseppe Arbia

    2015-11-01

    Full Text Available Geostatistical spatial models are widely used in many applied fields to forecast data observed on continuous three-dimensional surfaces. We propose to extend their use to finance and, in particular, to forecasting yield curves. We present the results of an empirical application where we apply the proposed method to forecast Euro Zero Rates (2003–2014 using the Ordinary Kriging method based on the anisotropic variogram. Furthermore, a comparison with other recent methods for forecasting yield curves is proposed. The results show that the model is characterized by good levels of predictions’ accuracy and it is competitive with the other forecasting models considered.

  19. Geostatistical Approach to Estimating the Gold Ore Characteristics and Gold Reserves: A Case Study Daksa Area, Quang Nam Province, Viet Nam

    Science.gov (United States)

    Luan Truong, Xuan; Luong Le, Van; Quang Truong, Xuan

    2015-04-01

    Daksa gold deposit is the biggest gold deposits in Vietnam. The Daksa geological structure complicated, distributed mainly metamorphosed sedimentary NuiVu formation (PR3-?1nv2). The sulfide gold ore bodies distributed in quartz schist, quartz - biotite related to faut and distribution wing anticline. The gold ore bodies form circuits, network circuits, circuits lenses; fill the cup surface layer of the developing northeast - southwest; is the less than or west longitude north - SE. The results show that, Au and accompanying elements (Ag, Pb and Zn) have correlated pretty closely. All of its consistent with the logarithmic distribution standard, in accordance with the law of distribution of content mineral rare. The structure functions have nugget effect and spherical models with show that Au and accompanying elements special variation are changes. Au contents shown local anisotropy, no clearly anisotropy (K=1,17) and weakly anisotropy (K=1,4). Intensity mineralization of the ore bodies are quite high with demand spherical conversion coefficient ranging from 0.49 to 0.75 and from 0.66 to 0.97 (for other body). With nugget effects, ore bodies shown that it is consistent with mineralization in the ore bodies study, ore erasable, micro vein, infilling fractures in quartz vein. All of variogram presents local anisotropy, indicated gold mineralization at study area has least two-mineralization stages, consistent with the analysis of mineralography samples. By the results of the structure function study, the authors present the system optimization for exploration deposit and used to evaluate gold reserves by Ordinary Kriging. High accuracy of Kriging estimation results are expressed in the minimum Kriging variance, by compare the results calculated by some other methods (such as distance inverse weighting method, ..) and specially compare to the results of a some blocks have been exploited. Key words: Geostat and gold deposits VN. Daksa and gold mineralization. Geostat

  20. The use of sequential indicator simulation to characterize geostatistical uncertainty

    International Nuclear Information System (INIS)

    Hansen, K.M.

    1992-10-01

    Sequential indicator simulation (SIS) is a geostatistical technique designed to aid in the characterization of uncertainty about the structure or behavior of natural systems. This report discusses a simulation experiment designed to study the quality of uncertainty bounds generated using SIS. The results indicate that, while SIS may produce reasonable uncertainty bounds in many situations, factors like the number and location of available sample data, the quality of variogram models produced by the user, and the characteristics of the geologic region to be modeled, can all have substantial effects on the accuracy and precision of estimated confidence limits. It is recommended that users of SIS conduct validation studies for the technique on their particular regions of interest before accepting the output uncertainty bounds

  1. A geostatistical methodology to assess the accuracy of unsaturated flow models

    International Nuclear Information System (INIS)

    Smoot, J.L.; Williams, R.E.

    1996-04-01

    The Pacific Northwest National Laboratory spatiotemporal movement of water injected into (PNNL) has developed a Hydrologic unsaturated sediments at the Hanford Site in Evaluation Methodology (HEM) to assist the Washington State was used to develop a new U.S. Nuclear Regulatory Commission in method for evaluating mathematical model evaluating the potential that infiltrating meteoric predictions. Measured water content data were water will produce leachate at commercial low- interpolated geostatistically to a 16 x 16 x 36 level radioactive waste disposal sites. Two key grid at several time intervals. Then a issues are raised in the HEM: (1) evaluation of mathematical model was used to predict water mathematical models that predict facility content at the same grid locations at the selected performance, and (2) estimation of the times. Node-by-node comparison of the uncertainty associated with these mathematical mathematical model predictions with the model predictions. The technical objective of geostatistically interpolated values was this research is to adapt geostatistical tools conducted. The method facilitates a complete commonly used for model parameter estimation accounting and categorization of model error at to the problem of estimating the spatial every node. The comparison suggests that distribution of the dependent variable to be model results generally are within measurement calculated by the model. To fulfill this error. The worst model error occurs in silt objective, a database describing the lenses and is in excess of measurement error

  2. A geostatistical methodology to assess the accuracy of unsaturated flow models

    Energy Technology Data Exchange (ETDEWEB)

    Smoot, J.L.; Williams, R.E.

    1996-04-01

    The Pacific Northwest National Laboratory spatiotemporal movement of water injected into (PNNL) has developed a Hydrologic unsaturated sediments at the Hanford Site in Evaluation Methodology (HEM) to assist the Washington State was used to develop a new U.S. Nuclear Regulatory Commission in method for evaluating mathematical model evaluating the potential that infiltrating meteoric predictions. Measured water content data were water will produce leachate at commercial low- interpolated geostatistically to a 16 x 16 x 36 level radioactive waste disposal sites. Two key grid at several time intervals. Then a issues are raised in the HEM: (1) evaluation of mathematical model was used to predict water mathematical models that predict facility content at the same grid locations at the selected performance, and (2) estimation of the times. Node-by-node comparison of the uncertainty associated with these mathematical mathematical model predictions with the model predictions. The technical objective of geostatistically interpolated values was this research is to adapt geostatistical tools conducted. The method facilitates a complete commonly used for model parameter estimation accounting and categorization of model error at to the problem of estimating the spatial every node. The comparison suggests that distribution of the dependent variable to be model results generally are within measurement calculated by the model. To fulfill this error. The worst model error occurs in silt objective, a database describing the lenses and is in excess of measurement error.

  3. Chapter J: Issues and challenges in the application of geostatistics and spatial-data analysis to the characterization of sand-and-gravel resources

    Science.gov (United States)

    Hack, Daniel R.

    2005-01-01

    Sand-and-gravel (aggregate) resources are a critical component of the Nation's infrastructure, yet aggregate-mining technologies lag far behind those of metalliferous mining and other sectors. Deposit-evaluation and site-characterization methodologies are antiquated, and few serious studies of the potential applications of spatial-data analysis and geostatistics have been published. However, because of commodity usage and the necessary proximity of a mine to end use, aggregate-resource exploration and evaluation differ fundamentally from comparable activities for metalliferous ores. Acceptable practices, therefore, can reflect this cruder scale. The increasing use of computer technologies is colliding with the need for sand-and-gravel mines to modernize and improve their overall efficiency of exploration, mine planning, scheduling, automation, and other operations. The emergence of megaquarries in the 21st century will also be a contributing factor. Preliminary research into the practical applications of exploratory-data analysis (EDA) have been promising. For example, EDA was used to develop a linear-regression equation to forecast freeze-thaw durability from absorption values for Lower Paleozoic carbonate rocks mined for crushed aggregate from quarries in Oklahoma. Applications of EDA within a spatial context, a method of spatial-data analysis, have also been promising, as with the investigation of undeveloped sand-and-gravel resources in the sedimentary deposits of Pleistocene Lake Bonneville, Utah. Formal geostatistical investigations of sand-and-gravel deposits are quite rare, and the primary focus of those studies that have been completed is on the spatial characterization of deposit thickness and its subsequent effect on ore reserves. A thorough investigation of a gravel deposit in an active aggregate-mining area in central Essex, U.K., emphasized the problems inherent in the geostatistical characterization of particle-size-analysis data. Beyond such factors

  4. Indoor radon variations in central Iran and its geostatistical map

    Science.gov (United States)

    Hadad, Kamal; Mokhtari, Javad

    2015-02-01

    We present the results of 2 year indoor radon survey in 10 cities of Yazd province in Central Iran (covering an area of 80,000 km2). We used passive diffusive samplers with LATEX polycarbonate films as Solid State Nuclear Track Detector (SSNTD). This study carried out in central Iran where there are major minerals and uranium mines. Our results indicate that despite few extraordinary high concentrations, average annual concentrations of indoor radon are within ICRP guidelines. When geostatistical spatial distribution of radon mapped onto geographical features of the province it was observed that risk of high radon concentration increases near the Saqand, Bafq, Harat and Abarkooh cities, this depended on the elevation and vicinity of the ores and mines.

  5. Geostatistical Analysis Methods for Estimation of Environmental Data Homogeneity

    Directory of Open Access Journals (Sweden)

    Aleksandr Danilov

    2018-01-01

    Full Text Available The methodology for assessing the spatial homogeneity of ecosystems with the possibility of subsequent zoning of territories in terms of the degree of disturbance of the environment is considered in the study. The degree of pollution of the water body was reconstructed on the basis of hydrochemical monitoring data and information on the level of the technogenic load in one year. As a result, the greatest environmental stress zones were isolated and correct zoning using geostatistical analysis techniques was proved. Mathematical algorithm computing system was implemented in an object-oriented programming C #. A software application has been obtained that allows quickly assessing the scale and spatial localization of pollution during the initial analysis of the environmental situation.

  6. Geostatistical analysis and kriging of Hexachlorocyclohexane residues in topsoil from Tianjin, China

    International Nuclear Information System (INIS)

    Li, B.G.; Cao, J.; Liu, W.X.; Shen, W.R.; Wang, X.J.; Tao, S.

    2006-01-01

    A previously published data set of HCH isomer concentrations in topsoil samples from Tianjin, China, was subjected to geospatial analysis. Semivariograms were calculated and modeled using geostatistical techniques. Parameters of semivariogram models were analyzed and compared for four HCH isomers. Two-dimensional ordinary block kriging was applied to HCH isomers data set for mapping purposes. Dot maps and gray-scaled raster maps of HCH concentrations were presented based on kriging results. The appropriateness of the kriging procedure for mapping purposes was evaluated based on the kriging errors and kriging variances. It was found that ordinary block kriging can be applied to interpolate HCH concentrations in Tianjin topsoil with acceptable accuracy for mapping purposes. - Geostatistical analysis and kriging were applied to HCH concentrations in topsoil of Tianjin, China for mapping purposes

  7. Assessment of effectiveness of geologic isolation systems: geostatistical modeling of pore velocity

    International Nuclear Information System (INIS)

    Devary, J.L.; Doctor, P.G.

    1981-06-01

    A significant part of evaluating a geologic formation as a nuclear waste repository involves the modeling of contaminant transport in the surrounding media in the event the repository is breached. The commonly used contaminant transport models are deterministic. However, the spatial variability of hydrologic field parameters introduces uncertainties into contaminant transport predictions. This paper discusses the application of geostatistical techniques to the modeling of spatially varying hydrologic field parameters required as input to contaminant transport analyses. Kriging estimation techniques were applied to Hanford Reservation field data to calculate hydraulic conductivity and the ground-water potential gradients. These quantities were statistically combined to estimate the groundwater pore velocity and to characterize the pore velocity estimation error. Combining geostatistical modeling techniques with product error propagation techniques results in an effective stochastic characterization of groundwater pore velocity, a hydrologic parameter required for contaminant transport analyses

  8. Geostatistical interpolation for modelling SPT data in northern Izmir

    Indian Academy of Sciences (India)

    data scatter' stems from the natural randomness of the system under con- ... Geostatistical methods were originally used for ore reserve calculations by the ... ing grain size distribution, plasticity, strength parameters and water content, for ...

  9. Delineating Hydrofacies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics

    Energy Technology Data Exchange (ETDEWEB)

    Song, Xuehang [Florida State Univ., Tallahassee, FL (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Chen, Xingyuan [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Ye, Ming [Florida State Univ., Tallahassee, FL (United States); Dai, Zhenxue [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hammond, Glenn Edward [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-07-01

    This study develops a new framework of facies-based data assimilation for characterizing spatial distribution of hydrofacies and estimating their associated hydraulic properties. This framework couples ensemble data assimilation with transition probability-based geostatistical model via a parameterization based on a level set function. The nature of ensemble data assimilation makes the framework efficient and flexible to be integrated with various types of observation data. The transition probability-based geostatistical model keeps the updated hydrofacies distributions under geological constrains. The framework is illustrated by using a two-dimensional synthetic study that estimates hydrofacies spatial distribution and permeability in each hydrofacies from transient head data. Our results show that the proposed framework can characterize hydrofacies distribution and associated permeability with adequate accuracy even with limited direct measurements of hydrofacies. Our study provides a promising starting point for hydrofacies delineation in complex real problems.

  10. Geostatistical Spatio-Time model of crime in el Salvador: Structural and Predictive Analysis

    Directory of Open Access Journals (Sweden)

    Welman Rosa Alvarado

    2011-07-01

    Full Text Available Today, to study a geospatial and spatio-temporal phenomena requires searching statistical tools that enable the analysis of the dependency of space, time and interactions. The science that studies this kind of subjects is the Geoestatics which the goal is to predict spatial phenomenon. This science is considered the base for modeling phenomena that involves interactions between space and time. In the past 10 years, the Geostatistic had seen a great development in areas like the geology, soils, remote sensing, epidemiology, agriculture, ecology, economy, etc. In this research, the geostatistic had been apply to build a predictive map about crime in El Salvador; for that the variability of space and time together is studied to generate crime scenarios: crime hot spots are determined, crime vulnerable groups are identified, to improve political decisions and facilitate to decision makers about the insecurity in the country.

  11. Optimizing Groundwater Monitoring Networks Using Integrated Statistical and Geostatistical Approaches

    Directory of Open Access Journals (Sweden)

    Jay Krishna Thakur

    2015-08-01

    Full Text Available The aim of this work is to investigate new approaches using methods based on statistics and geo-statistics for spatio-temporal optimization of groundwater monitoring networks. The formulated and integrated methods were tested with the groundwater quality data set of Bitterfeld/Wolfen, Germany. Spatially, the monitoring network was optimized using geo-statistical methods. Temporal optimization of the monitoring network was carried out using Sen’s method (1968. For geostatistical network optimization, a geostatistical spatio-temporal algorithm was used to identify redundant wells in 2- and 2.5-D Quaternary and Tertiary aquifers. Influences of interpolation block width, dimension, contaminant association, groundwater flow direction and aquifer homogeneity on statistical and geostatistical methods for monitoring network optimization were analysed. The integrated approach shows 37% and 28% redundancies in the monitoring network in Quaternary aquifer and Tertiary aquifer respectively. The geostatistical method also recommends 41 and 22 new monitoring wells in the Quaternary and Tertiary aquifers respectively. In temporal optimization, an overall optimized sampling interval was recommended in terms of lower quartile (238 days, median quartile (317 days and upper quartile (401 days in the research area of Bitterfeld/Wolfen. Demonstrated methods for improving groundwater monitoring network can be used in real monitoring network optimization with due consideration given to influencing factors.

  12. A geostatistical model of facies-architecture and internal heterogeneity of Rotliegend-reservoirs developed from outcrop-analogues. Outcrop-analogue study Cutler Group (Utah/USA)

    Energy Technology Data Exchange (ETDEWEB)

    Irmen, A.

    2001-10-01

    The aim of this DGMK study was the collection of data that document the distribution of facies units within mixed fluvial/aeolian deposits. The Cutler Group of southeastern Utah was chosen as an outcrop analog since it contains all major lithofacies common within such deposits (aeolian dunes and interdunes, fluvial channel-films as well as lacustrine and Sabkha deposits). Because of the outstanding outcrop quality in this region, numerous detailed datasets could be collected, which allowed the visualization of size, distribution, and sedimentological inventory of the different facies in various ''paleogeographical'' maps and diagrams. A genetic model, which explains the presence of correlative horizons and cyclic patterns of deposition, could be developed. (orig.) [German] Zielsetzung dieses DGMK-Forschungsvorhabens war es, quantitative Daten zur Verteilung fazieller Einheiten innerhalb eines gemischt fluviatil/aeolischen Ablagerungsraums zu gewinnen. Die Cutler Group im Suedosten des amerikanischen Bundesstaates Utah wurde als Aufschlussanalog gewaehlt, in welchem die typischen Ablagerungen eines solchen Deposystems vorhanden sind (aeolische Duenen und -Interduenen, fluviatile Rinnenfuellungen, sowie lakustrine und Sabkha-Ablagerungen). Aufgrund der hervorragenden Aufschlusssituation konnten detaillierte Datensaetze gewonnen werden, welche die Darstellung von Groesse, bevorzugter Ausrichtung und Sedimentologie potentieller Heterogenitaetselemente entweder direkt als ''paleogeographische'' Karten, oder in statistischer Form ermoeglichten. Ein genetisches Modell erklaert die Zyklizitaet der Ablagerungen und die Anwesenheit von weitraeumig korrelierbaren Horizonten. (orig.)

  13. Integration of GIS, Geostatistics, and 3-D Technology to Assess the Spatial Distribution of Soil Moisture

    Science.gov (United States)

    Betts, M.; Tsegaye, T.; Tadesse, W.; Coleman, T. L.; Fahsi, A.

    1998-01-01

    The spatial and temporal distribution of near surface soil moisture is of fundamental importance to many physical, biological, biogeochemical, and hydrological processes. However, knowledge of these space-time dynamics and the processes which control them remains unclear. The integration of geographic information systems (GIS) and geostatistics together promise a simple mechanism to evaluate and display the spatial and temporal distribution of this vital hydrologic and physical variable. Therefore, this research demonstrates the use of geostatistics and GIS to predict and display soil moisture distribution under vegetated and non-vegetated plots. The research was conducted at the Winfred Thomas Agricultural Experiment Station (WTAES), Hazel Green, Alabama. Soil moisture measurement were done on a 10 by 10 m grid from tall fescue grass (GR), alfalfa (AA), bare rough (BR), and bare smooth (BS) plots. Results indicated that variance associated with soil moisture was higher for vegetated plots than non-vegetated plots. The presence of vegetation in general contributed to the spatial variability of soil moisture. Integration of geostatistics and GIS can improve the productivity of farm lands and the precision of farming.

  14. Application of a computationally efficient geostatistical approach to characterizing variably spaced water-table data

    International Nuclear Information System (INIS)

    Quinn, J.J.

    1996-01-01

    Geostatistical analysis of hydraulic head data is useful in producing unbiased contour plots of head estimates and relative errors. However, at most sites being characterized, monitoring wells are generally present at different densities, with clusters of wells in some areas and few wells elsewhere. The problem that arises when kriging data at different densities is in achieving adequate resolution of the grid while maintaining computational efficiency and working within software limitations. For the site considered, 113 data points were available over a 14-mi 2 study area, including 57 monitoring wells within an area of concern of 1.5 mi 2 . Variogram analyses of the data indicate a linear model with a negligible nugget effect. The geostatistical package used in the study allows a maximum grid of 100 by 100 cells. Two-dimensional kriging was performed for the entire study area with a 500-ft grid spacing, while the smaller zone was modeled separately with a 100-ft spacing. In this manner, grid cells for the dense area and the sparse area remained small relative to the well separation distances, and the maximum dimensions of the program were not exceeded. The spatial head results for the detailed zone were then nested into the regional output by use of a graphical, object-oriented database that performed the contouring of the geostatistical output. This study benefitted from the two-scale approach and from very fine geostatistical grid spacings relative to typical data separation distances. The combining of the sparse, regional results with those from the finer-resolution area of concern yielded contours that honored the actual data at every measurement location. The method applied in this study can also be used to generate reproducible, unbiased representations of other types of spatial data

  15. Robust spatialization of soil water content at the scale of an agricultural field using geophysical and geostatistical methods

    Science.gov (United States)

    Henine, Hocine; Tournebize, Julien; Laurent, Gourdol; Christophe, Hissler; Cournede, Paul-Henry; Clement, Remi

    2017-04-01

    Research on the Critical Zone (CZ) is a prerequisite for undertaking issues related to ecosystemic services that human societies rely on (nutrient cycles, water supply and quality). However, while the upper part of CZ (vegetation, soil, surface water) is readily accessible, knowledge of the subsurface remains limited, due to the point-scale character of conventional direct observations. While the potential for geophysical methods to overcome this limitation is recognized, the translation of the geophysical information into physical properties or states of interest remains a challenge (e.g. the translation of soil electrical resistivity into soil water content). In this study, we propose a geostatistical framework using the Bayesian Maximum Entropy (BME) approach to assimilate geophysical and point-scale data. We especially focus on the prediction of the spatial distribution of soil water content using (1) TDR point-scale measurements of soil water content, which are considered as accurate data, and (2) soil water content data derived from electrical resistivity measurements, which are uncertain data but spatially dense. We used a synthetic dataset obtained with a vertical 2D domain to evaluate the performance of this geostatistical approach. Spatio-temporal simulations of soil water content were carried out using Hydrus-software for different scenarios: homogeneous or heterogeneous hydraulic conductivity distribution, and continuous or punctual infiltration pattern. From the simulations of soil water content, conceptual soil resistivity models were built using a forward modeling approach and point sampling of water content values, vertically ranged, were done. These two datasets are similar to field measurements of soil electrical resistivity (using electrical resistivity tomography, ERT) and soil water content (using TDR probes) obtained at the Boissy-le-Chatel site, in Orgeval catchment (East of Paris, France). We then integrated them into a specialization

  16. Geostatistical risk estimation at waste disposal sites in the presence of hot spots

    International Nuclear Information System (INIS)

    Komnitsas, Kostas; Modis, Kostas

    2009-01-01

    The present paper aims to estimate risk by using geostatistics at the wider coal mining/waste disposal site of Belkovskaya, Tula region, in Russia. In this area the presence of hot spots causes a spatial trend in the mean value of the random field and a non-Gaussian data distribution. Prior to application of geostatistics, subtraction of trend and appropriate smoothing and transformation of the data into a Gaussian form were carried out; risk maps were then generated for the wider study area in order to assess the probability of exceeding risk thresholds. Finally, the present paper discusses the need for homogenization of soil risk thresholds regarding hazardous elements that will enhance reliability of risk estimation and enable application of appropriate rehabilitation actions in contaminated areas.

  17. Topsoil moisture mapping using geostatistical techniques under different Mediterranean climatic conditions.

    Science.gov (United States)

    Martínez-Murillo, J F; Hueso-González, P; Ruiz-Sinoga, J D

    2017-10-01

    Soil mapping has been considered as an important factor in the widening of Soil Science and giving response to many different environmental questions. Geostatistical techniques, through kriging and co-kriging techniques, have made possible to improve the understanding of eco-geomorphologic variables, e.g., soil moisture. This study is focused on mapping of topsoil moisture using geostatistical techniques under different Mediterranean climatic conditions (humid, dry and semiarid) in three small watersheds and considering topography and soil properties as key factors. A Digital Elevation Model (DEM) with a resolution of 1×1m was derived from a topographical survey as well as soils were sampled to analyzed soil properties controlling topsoil moisture, which was measured during 4-years. Afterwards, some topography attributes were derived from the DEM, the soil properties analyzed in laboratory, and the topsoil moisture was modeled for the entire watersheds applying three geostatistical techniques: i) ordinary kriging; ii) co-kriging considering as co-variate topography attributes; and iii) co-kriging ta considering as co-variates topography attributes and gravel content. The results indicated topsoil moisture was more accurately mapped in the dry and semiarid watersheds when co-kriging procedure was performed. The study is a contribution to improve the efficiency and accuracy of studies about the Mediterranean eco-geomorphologic system and soil hydrology in field conditions. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Exploring prediction uncertainty of spatial data in geostatistical and machine learning Approaches

    Science.gov (United States)

    Klump, J. F.; Fouedjio, F.

    2017-12-01

    Geostatistical methods such as kriging with external drift as well as machine learning techniques such as quantile regression forest have been intensively used for modelling spatial data. In addition to providing predictions for target variables, both approaches are able to deliver a quantification of the uncertainty associated with the prediction at a target location. Geostatistical approaches are, by essence, adequate for providing such prediction uncertainties and their behaviour is well understood. However, they often require significant data pre-processing and rely on assumptions that are rarely met in practice. Machine learning algorithms such as random forest regression, on the other hand, require less data pre-processing and are non-parametric. This makes the application of machine learning algorithms to geostatistical problems an attractive proposition. The objective of this study is to compare kriging with external drift and quantile regression forest with respect to their ability to deliver reliable prediction uncertainties of spatial data. In our comparison we use both simulated and real world datasets. Apart from classical performance indicators, comparisons make use of accuracy plots, probability interval width plots, and the visual examinations of the uncertainty maps provided by the two approaches. By comparing random forest regression to kriging we found that both methods produced comparable maps of estimated values for our variables of interest. However, the measure of uncertainty provided by random forest seems to be quite different to the measure of uncertainty provided by kriging. In particular, the lack of spatial context can give misleading results in areas without ground truth data. These preliminary results raise questions about assessing the risks associated with decisions based on the predictions from geostatistical and machine learning algorithms in a spatial context, e.g. mineral exploration.

  19. Multivariate analysis and geostatistics of the fertility of a humic rhodic hapludox under coffee cultivation

    Directory of Open Access Journals (Sweden)

    Samuel de Assis Silva

    2012-04-01

    Full Text Available The spatial variability of soil and plant properties exerts great influence on the yeld of agricultural crops. This study analyzed the spatial variability of the fertility of a Humic Rhodic Hapludox with Arabic coffee, using principal component analysis, cluster analysis and geostatistics in combination. The experiment was carried out in an area under Coffea arabica L., variety Catucai 20/15 - 479. The soil was sampled at a depth 0.20 m, at 50 points of a sampling grid. The following chemical properties were determined: P, K+, Ca2+, Mg2+, Na+, S, Al3+, pH, H + Al, SB, t, T, V, m, OM, Na saturation index (SSI, remaining phosphorus (P-rem, and micronutrients (Zn, Fe, Mn, Cu and B. The data were analyzed with descriptive statistics, followed by principal component and cluster analyses. Geostatistics were used to check and quantify the degree of spatial dependence of properties, represented by principal components. The principal component analysis allowed a dimensional reduction of the problem, providing interpretable components, with little information loss. Despite the characteristic information loss of principal component analysis, the combination of this technique with geostatistical analysis was efficient for the quantification and determination of the structure of spatial dependence of soil fertility. In general, the availability of soil mineral nutrients was low and the levels of acidity and exchangeable Al were high.

  20. Modelling Geomechanical Heterogeneity of Rock Masses Using Direct and Indirect Geostatistical Conditional Simulation Methods

    Science.gov (United States)

    Eivazy, Hesameddin; Esmaieli, Kamran; Jean, Raynald

    2017-12-01

    An accurate characterization and modelling of rock mass geomechanical heterogeneity can lead to more efficient mine planning and design. Using deterministic approaches and random field methods for modelling rock mass heterogeneity is known to be limited in simulating the spatial variation and spatial pattern of the geomechanical properties. Although the applications of geostatistical techniques have demonstrated improvements in modelling the heterogeneity of geomechanical properties, geostatistical estimation methods such as Kriging result in estimates of geomechanical variables that are not fully representative of field observations. This paper reports on the development of 3D models for spatial variability of rock mass geomechanical properties using geostatistical conditional simulation method based on sequential Gaussian simulation. A methodology to simulate the heterogeneity of rock mass quality based on the rock mass rating is proposed and applied to a large open-pit mine in Canada. Using geomechanical core logging data collected from the mine site, a direct and an indirect approach were used to model the spatial variability of rock mass quality. The results of the two modelling approaches were validated against collected field data. The study aims to quantify the risks of pit slope failure and provides a measure of uncertainties in spatial variability of rock mass properties in different areas of the pit.

  1. A space and time scale-dependent nonlinear geostatistical approach for downscaling daily precipitation and temperature

    KAUST Repository

    Jha, Sanjeev Kumar

    2015-07-21

    A geostatistical framework is proposed to downscale daily precipitation and temperature. The methodology is based on multiple-point geostatistics (MPS), where a multivariate training image is used to represent the spatial relationship between daily precipitation and daily temperature over several years. Here, the training image consists of daily rainfall and temperature outputs from the Weather Research and Forecasting (WRF) model at 50 km and 10 km resolution for a twenty year period ranging from 1985 to 2004. The data are used to predict downscaled climate variables for the year 2005. The result, for each downscaled pixel, is daily time series of precipitation and temperature that are spatially dependent. Comparison of predicted precipitation and temperature against a reference dataset indicates that both the seasonal average climate response together with the temporal variability are well reproduced. The explicit inclusion of time dependence is explored by considering the climate properties of the previous day as an additional variable. Comparison of simulations with and without inclusion of time dependence shows that the temporal dependence only slightly improves the daily prediction because the temporal variability is already well represented in the conditioning data. Overall, the study shows that the multiple-point geostatistics approach is an efficient tool to be used for statistical downscaling to obtain local scale estimates of precipitation and temperature from General Circulation Models. This article is protected by copyright. All rights reserved.

  2. Geostatistical regularization operators for geophysical inverse problems on irregular meshes

    Science.gov (United States)

    Jordi, C.; Doetsch, J.; Günther, T.; Schmelzbach, C.; Robertsson, J. OA

    2018-05-01

    Irregular meshes allow to include complicated subsurface structures into geophysical modelling and inverse problems. The non-uniqueness of these inverse problems requires appropriate regularization that can incorporate a priori information. However, defining regularization operators for irregular discretizations is not trivial. Different schemes for calculating smoothness operators on irregular meshes have been proposed. In contrast to classical regularization constraints that are only defined using the nearest neighbours of a cell, geostatistical operators include a larger neighbourhood around a particular cell. A correlation model defines the extent of the neighbourhood and allows to incorporate information about geological structures. We propose an approach to calculate geostatistical operators for inverse problems on irregular meshes by eigendecomposition of a covariance matrix that contains the a priori geological information. Using our approach, the calculation of the operator matrix becomes tractable for 3-D inverse problems on irregular meshes. We tested the performance of the geostatistical regularization operators and compared them against the results of anisotropic smoothing in inversions of 2-D surface synthetic electrical resistivity tomography (ERT) data as well as in the inversion of a realistic 3-D cross-well synthetic ERT scenario. The inversions of 2-D ERT and seismic traveltime field data with geostatistical regularization provide results that are in good accordance with the expected geology and thus facilitate their interpretation. In particular, for layered structures the geostatistical regularization provides geologically more plausible results compared to the anisotropic smoothness constraints.

  3. Analysis and simulation of wireless signal propagation applying geostatistical interpolation techniques

    Science.gov (United States)

    Kolyaie, S.; Yaghooti, M.; Majidi, G.

    2011-12-01

    This paper is a part of an ongoing research to examine the capability of geostatistical analysis for mobile networks coverage prediction, simulation and tuning. Mobile network coverage predictions are used to find network coverage gaps and areas with poor serviceability. They are essential data for engineering and management in order to make better decision regarding rollout, planning and optimisation of mobile networks.The objective of this research is to evaluate different interpolation techniques in coverage prediction. In method presented here, raw data collected from drive testing a sample of roads in study area is analysed and various continuous surfaces are created using different interpolation methods. Two general interpolation methods are used in this paper with different variables; first, Inverse Distance Weighting (IDW) with various powers and number of neighbours and second, ordinary kriging with Gaussian, spherical, circular and exponential semivariogram models with different number of neighbours. For the result comparison, we have used check points coming from the same drive test data. Prediction values for check points are extracted from each surface and the differences with actual value are computed. The output of this research helps finding an optimised and accurate model for coverage prediction.

  4. Geostatistics for Mapping Leaf Area Index over a Cropland Landscape: Efficiency Sampling Assessment

    Directory of Open Access Journals (Sweden)

    Javier Garcia-Haro

    2010-11-01

    Full Text Available This paper evaluates the performance of spatial methods to estimate leaf area index (LAI fields from ground-based measurements at high-spatial resolution over a cropland landscape. Three geostatistical model variants of the kriging technique, the ordinary kriging (OK, the collocated cokriging (CKC and kriging with an external drift (KED are used. The study focused on the influence of the spatial sampling protocol, auxiliary information, and spatial resolution in the estimates. The main advantage of these models lies in the possibility of considering the spatial dependence of the data and, in the case of the KED and CKC, the auxiliary information for each location used for prediction purposes. A high-resolution NDVI image computed from SPOT TOA reflectance data is used as an auxiliary variable in LAI predictions. The CKC and KED predictions have proven the relevance of the auxiliary information to reproduce the spatial pattern at local scales, proving the KED model to be the best estimator when a non-stationary trend is observed. Advantages and limitations of the methods in LAI field predictions for two systematic and two stratified spatial samplings are discussed for high (20 m, medium (300 m and coarse (1 km spatial scales. The KED has exhibited the best observed local accuracy for all the spatial samplings. Meanwhile, the OK model provides comparable results when a well stratified sampling scheme is considered by land cover.

  5. Statistics and geostatistics: Kriging and use of hemivariogram functions in the structural investigation of uranium deposits

    International Nuclear Information System (INIS)

    Lucero Michaut, H.N.

    1980-01-01

    After presenting some general conceptual considerations regarding the theory of regionalized variables, the paper deals with specific applications of the intrinsic dispersion law to the determination, description and quantification of structures. It then briefly describes two uranium deposits in Cordoba province, the study of which yielded the basic data and parameters for compiling the geostatistical results presented. Before taking up the matter of structural interpretations, it refers briefly to the mathematical relationship between the number of sampling points available and the number of directions that can be investigated by the variogram method and also emphasizes the need for quantifying regionalization concepts on the basis of a table of absolute dimensionalities. In the case of the ''Rodolfo'' deposit it presents and comments on the hemivariograms for concentrations, thicknesses and accumulations, drawing attention at the same time to the existence of significant nest-like phenomena (gigogne structures). In this connection there is also a discussion of the case of iterative lenticular mineralization on a natural and a simulated model. The ''Schlagintweit'' deposit is dealt with in the same way, with descriptions and evaluations of the subjacent structures revealed by the hemivariographic analysis of grades, mineralization thicknesses and accumulations. This is followed by some considerations on the possibility of applying Krige and Matheron correctors in the moderation of anomalous mineralized thicknesses. In conclusion, the paper presents a ''range ellipse'' for grades; this is designed to supplement the grid of sampling points for the ''Rodolfo'' deposit by means of Matheronian kriging techniques. (author)

  6. Geostatistics and Geographic Information System to Analyze the Spatial Distribution of the Diversity of Anastrepha Species (Diptera: Tephritidae): the Effect of Forest Fragments in an Urban Area.

    Science.gov (United States)

    Garcia, A G; Araujo, M R; Uramoto, K; Walder, J M M; Zucchi, R A

    2017-12-08

    Fruit flies are among the most damaging insect pests of commercial fruit in Brazil. It is important to understand the landscape elements that may favor these flies. In the present study, spatial data from surveys of species of Anastrepha Schiner (Diptera: Tephritidae) in an urban area with forest fragments were analyzed, using geostatistics and Geographic Information System (GIS) to map the diversity of insects and evaluate how the forest fragments drive the spatial patterns. The results indicated a high diversity of species associated with large fragments, and a trend toward lower diversity in the more urbanized area, as the fragment sizes decreased. We concluded that the diversity of Anastrepha species is directly and positively related to large and continuous forest fragments in urbanized areas, and that combining geostatistics and GIS is a promising method for use in insect-pest management and sampling involving fruit flies. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  7. A Novel Approach of Understanding and Incorporating Error of Chemical Transport Models into a Geostatistical Framework

    Science.gov (United States)

    Reyes, J.; Vizuete, W.; Serre, M. L.; Xu, Y.

    2015-12-01

    The EPA employs a vast monitoring network to measure ambient PM2.5 concentrations across the United States with one of its goals being to quantify exposure within the population. However, there are several areas of the country with sparse monitoring spatially and temporally. One means to fill in these monitoring gaps is to use PM2.5 modeled estimates from Chemical Transport Models (CTMs) specifically the Community Multi-scale Air Quality (CMAQ) model. CMAQ is able to provide complete spatial coverage but is subject to systematic and random error due to model uncertainty. Due to the deterministic nature of CMAQ, often these uncertainties are not quantified. Much effort is employed to quantify the efficacy of these models through different metrics of model performance. Currently evaluation is specific to only locations with observed data. Multiyear studies across the United States are challenging because the error and model performance of CMAQ are not uniform over such large space/time domains. Error changes regionally and temporally. Because of the complex mix of species that constitute PM2.5, CMAQ error is also a function of increasing PM2.5 concentration. To address this issue we introduce a model performance evaluation for PM2.5 CMAQ that is regionalized and non-linear. This model performance evaluation leads to error quantification for each CMAQ grid. Areas and time periods of error being better qualified. The regionalized error correction approach is non-linear and is therefore more flexible at characterizing model performance than approaches that rely on linearity assumptions and assume homoscedasticity of CMAQ predictions errors. Corrected CMAQ data are then incorporated into the modern geostatistical framework of Bayesian Maximum Entropy (BME). Through cross validation it is shown that incorporating error-corrected CMAQ data leads to more accurate estimates than just using observed data by themselves.

  8. Reducing uncertainty in geostatistical description with well testing pressure data

    Energy Technology Data Exchange (ETDEWEB)

    Reynolds, A.C.; He, Nanqun [Univ. of Tulsa, OK (United States); Oliver, D.S. [Chevron Petroleum Technology Company, La Habra, CA (United States)

    1997-08-01

    Geostatistics has proven to be an effective tool for generating realizations of reservoir properties conditioned to static data, e.g., core and log data and geologic knowledge. Due to the lack of closely spaced data in the lateral directions, there will be significant variability in reservoir descriptions generated by geostatistical simulation, i.e., significant uncertainty in the reservoir descriptions. In past work, we have presented procedures based on inverse problem theory for generating reservoir descriptions (rock property fields) conditioned to pressure data and geostatistical information represented as prior means for log-permeability and porosity and variograms. Although we have shown that the incorporation of pressure data reduces the uncertainty below the level contained in the geostatistical model based only on static information (the prior model), our previous results assumed did not explicitly account for uncertainties in the prior means and the parameters defining the variogram model. In this work, we investigate how pressure data can help detect errors in the prior means. If errors in the prior means are large and are not taken into account, realizations conditioned to pressure data represent incorrect samples of the a posteriori probability density function for the rock property fields, whereas, if the uncertainty in the prior mean is incorporated properly into the model, one obtains realistic realizations of the rock property fields.

  9. Geostatistics for radiological characterization: overview and application cases

    International Nuclear Information System (INIS)

    Desnoyers, Yvon

    2016-01-01

    The objective of radiological characterization is to find a suitable balance between gathering data (constrained by cost, deadlines, accessibility or radiation) and managing the issues (waste volumes, levels of activity or exposure). It is necessary to have enough information to have confidence in the results without multiplying useless data. Geo-statistics processing of data considers all available pieces of information: historical data, non-destructive measurements and laboratory analyses of samples. The spatial structure modelling is then used to produce maps and to estimate the extent of radioactive contamination (surface and depth). Quantifications of local and global uncertainties are powerful decision-making tools for better management of remediation projects at contaminated sites, and for decontamination and dismantling projects at nuclear facilities. They can be used to identify hot spots, estimate contamination of surfaces and volumes, classify radioactive waste according to thresholds, estimate source terms, and so on. The spatial structure of radioactive contamination makes the optimization of sampling (number and position of data points) particularly important. Geo-statistics methodology can help determine the initial mesh size and reduce estimation uncertainties. Several show cases are presented to illustrate why and how geo-statistics can be applied to a range of radiological characterization where investigated units can represent very small areas (a few m 2 or a few m 3 ) or very large sites (at a country scale). The focus is then put on experience gained over years in the use of geo-statistics and sampling optimization. (author)

  10. A Bayesian Markov geostatistical model for estimation of hydrogeological properties

    International Nuclear Information System (INIS)

    Rosen, L.; Gustafson, G.

    1996-01-01

    A geostatistical methodology based on Markov-chain analysis and Bayesian statistics was developed for probability estimations of hydrogeological and geological properties in the siting process of a nuclear waste repository. The probability estimates have practical use in decision-making on issues such as siting, investigation programs, and construction design. The methodology is nonparametric which makes it possible to handle information that does not exhibit standard statistical distributions, as is often the case for classified information. Data do not need to meet the requirements on additivity and normality as with the geostatistical methods based on regionalized variable theory, e.g., kriging. The methodology also has a formal way for incorporating professional judgments through the use of Bayesian statistics, which allows for updating of prior estimates to posterior probabilities each time new information becomes available. A Bayesian Markov Geostatistical Model (BayMar) software was developed for implementation of the methodology in two and three dimensions. This paper gives (1) a theoretical description of the Bayesian Markov Geostatistical Model; (2) a short description of the BayMar software; and (3) an example of application of the model for estimating the suitability for repository establishment with respect to the three parameters of lithology, hydraulic conductivity, and rock quality designation index (RQD) at 400--500 meters below ground surface in an area around the Aespoe Hard Rock Laboratory in southeastern Sweden

  11. Gstat: a program for geostatistical modelling, prediction and simulation

    Science.gov (United States)

    Pebesma, Edzer J.; Wesseling, Cees G.

    1998-01-01

    Gstat is a computer program for variogram modelling, and geostatistical prediction and simulation. It provides a generic implementation of the multivariable linear model with trends modelled as a linear function of coordinate polynomials or of user-defined base functions, and independent or dependent, geostatistically modelled, residuals. Simulation in gstat comprises conditional or unconditional (multi-) Gaussian sequential simulation of point values or block averages, or (multi-) indicator sequential simulation. Besides many of the popular options found in other geostatistical software packages, gstat offers the unique combination of (i) an interactive user interface for modelling variograms and generalized covariances (residual variograms), that uses the device-independent plotting program gnuplot for graphical display, (ii) support for several ascii and binary data and map file formats for input and output, (iii) a concise, intuitive and flexible command language, (iv) user customization of program defaults, (v) no built-in limits, and (vi) free, portable ANSI-C source code. This paper describes the class of problems gstat can solve, and addresses aspects of efficiency and implementation, managing geostatistical projects, and relevant technical details.

  12. Estimating Rainfall in Rodrigues by Geostatistics: (A) Theory | Proag ...

    African Journals Online (AJOL)

    This paper introduces the geostatistical method. Originally devised to treat problems that arise when conventional statistical theory is used in estimating changes in ore grade within a mine, it is, however, an abstract theory of statistical behaviour that is applicable to many circumstances in different areas of geology and other ...

  13. Geostatistical Characteristic of Space -Time Variation in Underground Water Selected Quality Parameters in Klodzko Water Intake Area (SW Part of Poland)

    Science.gov (United States)

    Namysłowska-Wilczyńska, Barbara

    2016-04-01

    . These data were subjected to spatial analyses using statistical and geostatistical methods. The evaluation of basic statistics of the investigated quality parameters, including their histograms of distributions, scatter diagrams between these parameters and also correlation coefficients r were presented in this article. The directional semivariogram function and the ordinary (block) kriging procedure were used to build the 3D geostatistical model. The geostatistical parameters of the theoretical models of directional semivariograms of the studied water quality parameters, calculated along the time interval and along the wells depth (taking into account the terrain elevation), were used in the ordinary (block) kriging estimation. The obtained results of estimation, i.e. block diagrams allowed to determine the levels of increased values Z* of studied underground water quality parameters. Analysis of the variability in the selected quality parameters of underground water for an analyzed area in Klodzko water intake was enriched by referring to the results of geostatistical studies carried out for underground water quality parameters and also for a treated water and in Klodzko water supply system (iron Fe, manganese Mn, ammonium ion NH4+ contents), discussed in earlier works. Spatial and time variation in the latter-mentioned parameters was analysed on the basis of the data (2007÷2011, 2008÷2011). Generally, the behaviour of the underground water quality parameters has been found to vary in space and time. Thanks to the spatial analyses of the variation in the quality parameters in the Kłodzko underground water intake area some regularities (trends) in the variation in water quality have been identified.

  14. Geostatistical radar-raingauge combination with nonparametric correlograms: methodological considerations and application in Switzerland

    Science.gov (United States)

    Schiemann, R.; Erdin, R.; Willi, M.; Frei, C.; Berenguer, M.; Sempere-Torres, D.

    2011-05-01

    Modelling spatial covariance is an essential part of all geostatistical methods. Traditionally, parametric semivariogram models are fit from available data. More recently, it has been suggested to use nonparametric correlograms obtained from spatially complete data fields. Here, both estimation techniques are compared. Nonparametric correlograms are shown to have a substantial negative bias. Nonetheless, when combined with the sample variance of the spatial field under consideration, they yield an estimate of the semivariogram that is unbiased for small lag distances. This justifies the use of this estimation technique in geostatistical applications. Various formulations of geostatistical combination (Kriging) methods are used here for the construction of hourly precipitation grids for Switzerland based on data from a sparse realtime network of raingauges and from a spatially complete radar composite. Two variants of Ordinary Kriging (OK) are used to interpolate the sparse gauge observations. In both OK variants, the radar data are only used to determine the semivariogram model. One variant relies on a traditional parametric semivariogram estimate, whereas the other variant uses the nonparametric correlogram. The variants are tested for three cases and the impact of the semivariogram model on the Kriging prediction is illustrated. For the three test cases, the method using nonparametric correlograms performs equally well or better than the traditional method, and at the same time offers great practical advantages. Furthermore, two variants of Kriging with external drift (KED) are tested, both of which use the radar data to estimate nonparametric correlograms, and as the external drift variable. The first KED variant has been used previously for geostatistical radar-raingauge merging in Catalonia (Spain). The second variant is newly proposed here and is an extension of the first. Both variants are evaluated for the three test cases as well as an extended evaluation

  15. Spatial analysis of groundwater levels using Fuzzy Logic and geostatistical tools

    Science.gov (United States)

    Theodoridou, P. G.; Varouchakis, E. A.; Karatzas, G. P.

    2017-12-01

    The spatial variability evaluation of the water table of an aquifer provides useful information in water resources management plans. Geostatistical methods are often employed to map the free surface of an aquifer. In geostatistical analysis using Kriging techniques the selection of the optimal variogram is very important for the optimal method performance. This work compares three different criteria to assess the theoretical variogram that fits to the experimental one: the Least Squares Sum method, the Akaike Information Criterion and the Cressie's Indicator. Moreover, variable distance metrics such as the Euclidean, Minkowski, Manhattan, Canberra and Bray-Curtis are applied to calculate the distance between the observation and the prediction points, that affects both the variogram calculation and the Kriging estimator. A Fuzzy Logic System is then applied to define the appropriate neighbors for each estimation point used in the Kriging algorithm. The two criteria used during the Fuzzy Logic process are the distance between observation and estimation points and the groundwater level value at each observation point. The proposed techniques are applied to a data set of 250 hydraulic head measurements distributed over an alluvial aquifer. The analysis showed that the Power-law variogram model and Manhattan distance metric within ordinary kriging provide the best results when the comprehensive geostatistical analysis process is applied. On the other hand, the Fuzzy Logic approach leads to a Gaussian variogram model and significantly improves the estimation performance. The two different variogram models can be explained in terms of a fractional Brownian motion approach and of aquifer behavior at local scale. Finally, maps of hydraulic head spatial variability and of predictions uncertainty are constructed for the area with the two different approaches comparing their advantages and drawbacks.

  16. GEOSTATISTICAL BASED SUSCEPTIBILITY MAPPING OF SOIL EROSION AND OPTIMIZATION OF ITS CAUSATIVE FACTORS: A CONCEPTUAL FRAMEWORK

    Directory of Open Access Journals (Sweden)

    ABDULKADIR T. SHOLAGBERU

    2017-11-01

    Full Text Available Soil erosion hazard is the second biggest environmental challenges after population growth causing land degradation, desertification and water deterioration. Its impacts on watersheds include loss of soil nutrients, reduced reservoir capacity through siltation which may lead to flood risk, landslide, high water turbidity, etc. These problems become more pronounced in human altered mountainous areas through intensive agricultural activities, deforestation and increased urbanization among others. However, due to challenging nature of soil erosion management, there is great interest in assessing its spatial distribution and susceptibility levels. This study is thus intend to review the recent literatures and develop a novel framework for soil erosion susceptibility mapping using geostatistical based support vector machine (SVM, remote sensing and GIS techniques. The conceptual framework is to bridge the identified knowledge gaps in the area of causative factors’ (CFs selection. In this research, RUSLE model, field studies and the existing soil erosion maps for the study area will be integrated for the development of inventory map. Spatial data such as Landsat 8, digital soil and geological maps, digital elevation model and hydrological data shall be processed for the extraction of erosion CFs. GISbased SVM techniques will be adopted for the establishment of spatial relationships between soil erosion and its CFs, and subsequently for the development of erosion susceptibility maps. The results of this study include evaluation of predictive capability of GIS-based SVM in soil erosion mapping and identification of the most influential CFs for erosion susceptibility assessment. This study will serve as a guide to watershed planners and to alleviate soil erosion challenges and its related hazards.

  17. Use of stratigraphic, petrographic, hydrogeologic and geochemical information for hydrogeologic modelling based on geostatistical simulation

    International Nuclear Information System (INIS)

    Rohlig, K.J.; Fischer, H.; Poltl, B.

    2004-01-01

    This paper describes the stepwise utilization of geologic information from various sources for the construction of hydrogeological models of a sedimentary site by means of geostatistical simulation. It presents a practical application of aquifer characterisation by firstly simulating hydrogeological units and then the hydrogeological parameters. Due to the availability of a large amount of hydrogeological, geophysical and other data and information, the Gorleben site (Northern Germany) has been used for a case study in order to demonstrate the approach. The study, which has not yet been completed, tries to incorporate as much as possible of the available information and to characterise the remaining uncertainties. (author)

  18. Improved Assimilation of Streamflow and Satellite Soil Moisture with the Evolutionary Particle Filter and Geostatistical Modeling

    Science.gov (United States)

    Yan, Hongxiang; Moradkhani, Hamid; Abbaszadeh, Peyman

    2017-04-01

    Assimilation of satellite soil moisture and streamflow data into hydrologic models using has received increasing attention over the past few years. Currently, these observations are increasingly used to improve the model streamflow and soil moisture predictions. However, the performance of this land data assimilation (DA) system still suffers from two limitations: 1) satellite data scarcity and quality; and 2) particle weight degeneration. In order to overcome these two limitations, we propose two possible solutions in this study. First, the general Gaussian geostatistical approach is proposed to overcome the limitation in the space/time resolution of satellite soil moisture products thus improving their accuracy at uncovered/biased grid cells. Secondly, an evolutionary PF approach based on Genetic Algorithm (GA) and Markov Chain Monte Carlo (MCMC), the so-called EPF-MCMC, is developed to further reduce weight degeneration and improve the robustness of the land DA system. This study provides a detailed analysis of the joint and separate assimilation of streamflow and satellite soil moisture into a distributed Sacramento Soil Moisture Accounting (SAC-SMA) model, with the use of recently developed EPF-MCMC and the general Gaussian geostatistical approach. Performance is assessed over several basins in the USA selected from Model Parameter Estimation Experiment (MOPEX) and located in different climate regions. The results indicate that: 1) the general Gaussian approach can predict the soil moisture at uncovered grid cells within the expected satellite data quality threshold; 2) assimilation of satellite soil moisture inferred from the general Gaussian model can significantly improve the soil moisture predictions; and 3) in terms of both deterministic and probabilistic measures, the EPF-MCMC can achieve better streamflow predictions. These results recommend that the geostatistical model is a helpful tool to aid the remote sensing technique and the EPF-MCMC is a

  19. Can Geostatistical Models Represent Nature's Variability? An Analysis Using Flume Experiments

    Science.gov (United States)

    Scheidt, C.; Fernandes, A. M.; Paola, C.; Caers, J.

    2015-12-01

    The lack of understanding in the Earth's geological and physical processes governing sediment deposition render subsurface modeling subject to large uncertainty. Geostatistics is often used to model uncertainty because of its capability to stochastically generate spatially varying realizations of the subsurface. These methods can generate a range of realizations of a given pattern - but how representative are these of the full natural variability? And how can we identify the minimum set of images that represent this natural variability? Here we use this minimum set to define the geostatistical prior model: a set of training images that represent the range of patterns generated by autogenic variability in the sedimentary environment under study. The proper definition of the prior model is essential in capturing the variability of the depositional patterns. This work starts with a set of overhead images from an experimental basin that showed ongoing autogenic variability. We use the images to analyze the essential characteristics of this suite of patterns. In particular, our goal is to define a prior model (a minimal set of selected training images) such that geostatistical algorithms, when applied to this set, can reproduce the full measured variability. A necessary prerequisite is to define a measure of variability. In this study, we measure variability using a dissimilarity distance between the images. The distance indicates whether two snapshots contain similar depositional patterns. To reproduce the variability in the images, we apply an MPS algorithm to the set of selected snapshots of the sedimentary basin that serve as training images. The training images are chosen from among the initial set by using the distance measure to ensure that only dissimilar images are chosen. Preliminary investigations show that MPS can reproduce fairly accurately the natural variability of the experimental depositional system. Furthermore, the selected training images provide

  20. Unsupervised classification of multivariate geostatistical data: Two algorithms

    Science.gov (United States)

    Romary, Thomas; Ors, Fabien; Rivoirard, Jacques; Deraisme, Jacques

    2015-12-01

    With the increasing development of remote sensing platforms and the evolution of sampling facilities in mining and oil industry, spatial datasets are becoming increasingly large, inform a growing number of variables and cover wider and wider areas. Therefore, it is often necessary to split the domain of study to account for radically different behaviors of the natural phenomenon over the domain and to simplify the subsequent modeling step. The definition of these areas can be seen as a problem of unsupervised classification, or clustering, where we try to divide the domain into homogeneous domains with respect to the values taken by the variables in hand. The application of classical clustering methods, designed for independent observations, does not ensure the spatial coherence of the resulting classes. Image segmentation methods, based on e.g. Markov random fields, are not adapted to irregularly sampled data. Other existing approaches, based on mixtures of Gaussian random functions estimated via the expectation-maximization algorithm, are limited to reasonable sample sizes and a small number of variables. In this work, we propose two algorithms based on adaptations of classical algorithms to multivariate geostatistical data. Both algorithms are model free and can handle large volumes of multivariate, irregularly spaced data. The first one proceeds by agglomerative hierarchical clustering. The spatial coherence is ensured by a proximity condition imposed for two clusters to merge. This proximity condition relies on a graph organizing the data in the coordinates space. The hierarchical algorithm can then be seen as a graph-partitioning algorithm. Following this interpretation, a spatial version of the spectral clustering algorithm is also proposed. The performances of both algorithms are assessed on toy examples and a mining dataset.

  1. Monte Carlo Analysis of Reservoir Models Using Seismic Data and Geostatistical Models

    Science.gov (United States)

    Zunino, A.; Mosegaard, K.; Lange, K.; Melnikova, Y.; Hansen, T. M.

    2013-12-01

    We present a study on the analysis of petroleum reservoir models consistent with seismic data and geostatistical constraints performed on a synthetic reservoir model. Our aim is to invert directly for structure and rock bulk properties of the target reservoir zone. To infer the rock facies, porosity and oil saturation seismology alone is not sufficient but a rock physics model must be taken into account, which links the unknown properties to the elastic parameters. We then combine a rock physics model with a simple convolutional approach for seismic waves to invert the "measured" seismograms. To solve this inverse problem, we employ a Markov chain Monte Carlo (MCMC) method, because it offers the possibility to handle non-linearity, complex and multi-step forward models and provides realistic estimates of uncertainties. However, for large data sets the MCMC method may be impractical because of a very high computational demand. To face this challenge one strategy is to feed the algorithm with realistic models, hence relying on proper prior information. To address this problem, we utilize an algorithm drawn from geostatistics to generate geologically plausible models which represent samples of the prior distribution. The geostatistical algorithm learns the multiple-point statistics from prototype models (in the form of training images), then generates thousands of different models which are accepted or rejected by a Metropolis sampler. To further reduce the computation time we parallelize the software and run it on multi-core machines. The solution of the inverse problem is then represented by a collection of reservoir models in terms of facies, porosity and oil saturation, which constitute samples of the posterior distribution. We are finally able to produce probability maps of the properties we are interested in by performing statistical analysis on the collection of solutions.

  2. Deep fracturing of granite bodies. Literature survey, geostructural and geostatistic investigations

    International Nuclear Information System (INIS)

    Bles, J.L.; Blanchin, R.

    1986-01-01

    This report deals with investigations about deep fracturing of granite bodies, which were performed within two cost-sharing contracts between the Commission of the European Communities, the Commissariat a l'Energie Atomique and the Bureau de Recherches Geologiques et Minieres. The aim of this work was to study the evolution of fracturing in granite from the surface to larger depths, so that guidelines can be identified in order to extrapolate, at depth, the data obtained from surface investigations. These guidelines could eventually be used for feasibility studies about radioactive waste disposal. The results of structural and geostatistic investigations about the St. Sylvestre granite, as well as the literature survey about fractures encountered in two long Alpine galleries (Mont-Blanc tunnel and Arc-Isere water gallery), in the 1000 m deep borehole at Auriat, and in the Bassies granite body (Pyrenees) are presented. These results show that, for radioactive waste disposal feasibility studies: 1. The deep state of fracturing in a granite body can be estimated from results obtained at the surface; 2. Studying only the large fault network would be insufficient, both for surface investigations and for studies in deep boreholes and/or in underground galleries; 3. It is necessary to study orientations and frequencies of small fractures, so that structural mapping and statistical/geostatistical methods can be used in order to identify zones of higher and lower fracturing

  3. Development of A Bayesian Geostatistical Data Assimilation Method and Application to the Hanford 300 Area

    Science.gov (United States)

    Murakami, Haruko

    Probabilistic risk assessment of groundwater contamination requires us to incorporate large and diverse datasets at the site into the stochastic modeling of flow and transport for prediction. In quantifying the uncertainty in our predictions, we must not only combine the best estimates of the parameters based on each dataset, but also integrate the uncertainty associated with each dataset caused by measurement errors and limited number of measurements. This dissertation presents a Bayesian geostatistical data assimilation method that integrates various types of field data for characterizing heterogeneous hydrological properties. It quantifies the parameter uncertainty as a posterior distribution conditioned on all the datasets, which can be directly used in stochastic simulations to compute possible outcomes of flow and transport processes. The goal of this framework is to remove the discontinuity between data analysis and prediction. Such a direct connection between data and prediction also makes it possible to evaluate the worth of each dataset or combined worth of multiple datasets. The synthetic studies described here confirm that the data assimilation method introduced in this dissertation successfully captures the true parameter values and predicted values within the posterior distribution. The shape of the inferred posterior distributions from the method indicates the importance of estimating the entire distribution in fully accounting for parameter uncertainty. The method is then applied to integrate multiple types of datasets at the Hanford 300 Area for characterizing a three-dimensional heterogeneous hydraulic conductivity field. Comparing the results based on the different numbers or combinations of datasets shows that increasing data do not always contribute in a straightforward way to improving the posterior distribution: increasing numbers of the same data type would not necessarily be beneficial above a certain number, and also the combined effect of

  4. Training-Image Based Geostatistical Inversion Using a Spatial Generative Adversarial Neural Network

    Science.gov (United States)

    Laloy, Eric; Hérault, Romain; Jacques, Diederik; Linde, Niklas

    2018-01-01

    Probabilistic inversion within a multiple-point statistics framework is often computationally prohibitive for high-dimensional problems. To partly address this, we introduce and evaluate a new training-image based inversion approach for complex geologic media. Our approach relies on a deep neural network of the generative adversarial network (GAN) type. After training using a training image (TI), our proposed spatial GAN (SGAN) can quickly generate 2-D and 3-D unconditional realizations. A key characteristic of our SGAN is that it defines a (very) low-dimensional parameterization, thereby allowing for efficient probabilistic inversion using state-of-the-art Markov chain Monte Carlo (MCMC) methods. In addition, available direct conditioning data can be incorporated within the inversion. Several 2-D and 3-D categorical TIs are first used to analyze the performance of our SGAN for unconditional geostatistical simulation. Training our deep network can take several hours. After training, realizations containing a few millions of pixels/voxels can be produced in a matter of seconds. This makes it especially useful for simulating many thousands of realizations (e.g., for MCMC inversion) as the relative cost of the training per realization diminishes with the considered number of realizations. Synthetic inversion case studies involving 2-D steady state flow and 3-D transient hydraulic tomography with and without direct conditioning data are used to illustrate the effectiveness of our proposed SGAN-based inversion. For the 2-D case, the inversion rapidly explores the posterior model distribution. For the 3-D case, the inversion recovers model realizations that fit the data close to the target level and visually resemble the true model well.

  5. Geostatistics as a tool to improve the natural background level definition: An application in groundwater.

    Science.gov (United States)

    Dalla Libera, Nico; Fabbri, Paolo; Mason, Leonardo; Piccinini, Leonardo; Pola, Marco

    2017-11-15

    The Natural Background Level (NBL), suggested by UE BRIDGE project, is suited for spatially distributed datasets providing a regional value that could be higher than the Threshold Value (TV) set by every country. In hydro-geochemically dis-homogeneous areas, the use of a unique regional NBL, higher than TV, could arise problems to distinguish between natural occurrences and anthropogenic contaminant sources. Hence, the goal of this study is to improve the NBL definition employing a geostatistical approach, which reconstructs the contaminant spatial structure accounting geochemical and hydrogeological relationships. This integrated mapping is fundamental to evaluate the contaminant's distribution impact on the NBL, giving indications to improve it. We decided to test this method on the Drainage Basin of Venice Lagoon (DBVL, NE Italy), where the existing NBL is seven times higher than the TV. This area is notoriously affected by naturally occurring arsenic contamination. An available geochemical dataset collected by 50 piezometers was used to reconstruct the spatial distribution of arsenic in the densely populated area of the DBVL. A cokriging approach was applied exploiting the geochemical relationships among As, Fe and NH4+. The obtained spatial predictions of arsenic concentrations were divided into three different zones: i) areas with an As concentration lower than the TV, ii) areas with an As concentration between the TV and the median of the values higher than the TV, and iii) areas with an As concentration higher than the median. Following the BRIDGE suggestions, where enough samples were available, the 90th percentile for each zone was calculated to obtain a local NBL (LNBL). Differently from the original NBL, this local value gives more detailed water quality information accounting the hydrogeological and geochemical setting, and contaminant spatial variation. Hence, the LNBL could give more indications about the distinction between natural occurrence and

  6. 4th European Conference on Geostatistics for Environmental Applications

    CERN Document Server

    Carrera, Jesus; Gómez-Hernández, José

    2004-01-01

    The fourth edition of the European Conference on Geostatistics for Environmental Applications (geoENV IV) took place in Barcelona, November 27-29, 2002. As a proof that there is an increasing interest in environmental issues in the geostatistical community, the conference attracted over 100 participants, mostly Europeans (up to 10 European countries were represented), but also from other countries in the world. Only 46 contributions, selected out of around 100 submitted papers, were invited to be presented orally during the conference. Additionally 30 authors were invited to present their work in poster format during a special session. All oral and poster contributors were invited to submit their work to be considered for publication in this Kluwer series. All papers underwent a reviewing process, which consisted on two reviewers for oral presentations and one reviewer for posters. The book opens with one keynote paper by Philippe Naveau. It is followed by 40 papers that correspond to those presented orally d...

  7. Geostatistics applied to estimation of uranium bearing ore reserves

    International Nuclear Information System (INIS)

    Urbina Galan, L.I.

    1982-01-01

    A computer assisted method for assessing uranium-bearing ore deposit reserves is analyzed. Determinations of quality-thickness, namely quality by thickness calculations of mineralization, were obtained by means of a mathematical method known as the theory of rational variables for each drill-hole layer. Geostatistical results were derived based on a Fortrand computer program on a DEC 20/40 system. (author)

  8. Geostatistical mapping of Cs-137 contamination depth in building structures by integrating ISOCS measurements of different spatial supports

    Energy Technology Data Exchange (ETDEWEB)

    Boden, S.; Jacques, D. [Institute for Environment, Health and Safety, Belgian Nuclear Research Centre (SCK-CEN), Boeretang 200, BE-2400, Mol (Belgium); Rogiers, B. [Dept. of Earth and Environmental Sciences, KU Leuven - University of Leuven Celestijnenlaan 200e - bus 2410, BE-3001, Leuven (Belgium)

    2013-07-01

    Reliable methods to determine the contamination depth in nuclear building structures are very much needed for minimizing the radioactive waste volume and the decontamination workload. This paper investigates the geostatistical integration of in situ gamma-ray spectroscopy measurements of different spatial supports. A case study is presented from the BR3 decommissioning project, yielding an estimated reduction of waste volume of ∼35%, and recommendations are made for future application of the proposed methodology. (authors)

  9. 2nd European Conference on Geostatistics for Environmental Applications

    CERN Document Server

    Soares, Amílcar; Froidevaux, Roland

    1999-01-01

    The Second European Conference on Geostatistics for Environmental Ap­ plications took place in Valencia, November 18-20, 1998. Two years have past from the first meeting in Lisbon and the geostatistical community has kept active in the environmental field. In these days of congress inflation, we feel that continuity can only be achieved by ensuring quality in the papers. For this reason, all papers in the book have been reviewed by, at least, two referees, and care has been taken to ensure that the reviewer comments have been incorporated in the final version of the manuscript. We are thankful to the members of the scientific committee for their timely review of the scripts. All in all, there are three keynote papers from experts in soil science, climatology and ecology and 43 contributed papers providing a good indication of the status of geostatistics as applied in the environ­ mental field all over the world. We feel now confident that the geoENV conference series, seeded around a coffee table almost six...

  10. Evaluation of epidemiological studies

    International Nuclear Information System (INIS)

    Breckow, J.

    1995-01-01

    The publication is intended for readers with a professional background in radiation protection who are not experts in the field of epidemiology. The potentials and the limits of epidemiology are shown and concepts and terminology of radioepidemilogic studies as well as epidemiology in general are explained, in order to provide the necessary basis for understanding or performing evaluations of epidemiologic studies. (orig./VHE) [de

  11. Redesigning rain gauges network in Johor using geostatistics and simulated annealing

    Energy Technology Data Exchange (ETDEWEB)

    Aziz, Mohd Khairul Bazli Mohd, E-mail: mkbazli@yahoo.com [Centre of Preparatory and General Studies, TATI University College, 24000 Kemaman, Terengganu, Malaysia and Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor (Malaysia); Yusof, Fadhilah, E-mail: fadhilahy@utm.my [Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor (Malaysia); Daud, Zalina Mohd, E-mail: zalina@ic.utm.my [UTM Razak School of Engineering and Advanced Technology, Universiti Teknologi Malaysia, UTM KL, 54100 Kuala Lumpur (Malaysia); Yusop, Zulkifli, E-mail: zulyusop@utm.my [Institute of Environmental and Water Resource Management (IPASA), Faculty of Civil Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor (Malaysia); Kasno, Mohammad Afif, E-mail: mafifkasno@gmail.com [Malaysia - Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia, UTM KL, 54100 Kuala Lumpur (Malaysia)

    2015-02-03

    Recently, many rainfall network design techniques have been developed, discussed and compared by many researchers. Present day hydrological studies require higher levels of accuracy from collected data. In numerous basins, the rain gauge stations are located without clear scientific understanding. In this study, an attempt is made to redesign rain gauge network for Johor, Malaysia in order to meet the required level of accuracy preset by rainfall data users. The existing network of 84 rain gauges in Johor is optimized and redesigned into a new locations by using rainfall, humidity, solar radiation, temperature and wind speed data collected during the monsoon season (November - February) of 1975 until 2008. This study used the combination of geostatistics method (variance-reduction method) and simulated annealing as the algorithm of optimization during the redesigned proses. The result shows that the new rain gauge location provides minimum value of estimated variance. This shows that the combination of geostatistics method (variance-reduction method) and simulated annealing is successful in the development of the new optimum rain gauge system.

  12. Redesigning rain gauges network in Johor using geostatistics and simulated annealing

    International Nuclear Information System (INIS)

    Aziz, Mohd Khairul Bazli Mohd; Yusof, Fadhilah; Daud, Zalina Mohd; Yusop, Zulkifli; Kasno, Mohammad Afif

    2015-01-01

    Recently, many rainfall network design techniques have been developed, discussed and compared by many researchers. Present day hydrological studies require higher levels of accuracy from collected data. In numerous basins, the rain gauge stations are located without clear scientific understanding. In this study, an attempt is made to redesign rain gauge network for Johor, Malaysia in order to meet the required level of accuracy preset by rainfall data users. The existing network of 84 rain gauges in Johor is optimized and redesigned into a new locations by using rainfall, humidity, solar radiation, temperature and wind speed data collected during the monsoon season (November - February) of 1975 until 2008. This study used the combination of geostatistics method (variance-reduction method) and simulated annealing as the algorithm of optimization during the redesigned proses. The result shows that the new rain gauge location provides minimum value of estimated variance. This shows that the combination of geostatistics method (variance-reduction method) and simulated annealing is successful in the development of the new optimum rain gauge system

  13. Redesigning rain gauges network in Johor using geostatistics and simulated annealing

    Science.gov (United States)

    Aziz, Mohd Khairul Bazli Mohd; Yusof, Fadhilah; Daud, Zalina Mohd; Yusop, Zulkifli; Kasno, Mohammad Afif

    2015-02-01

    Recently, many rainfall network design techniques have been developed, discussed and compared by many researchers. Present day hydrological studies require higher levels of accuracy from collected data. In numerous basins, the rain gauge stations are located without clear scientific understanding. In this study, an attempt is made to redesign rain gauge network for Johor, Malaysia in order to meet the required level of accuracy preset by rainfall data users. The existing network of 84 rain gauges in Johor is optimized and redesigned into a new locations by using rainfall, humidity, solar radiation, temperature and wind speed data collected during the monsoon season (November - February) of 1975 until 2008. This study used the combination of geostatistics method (variance-reduction method) and simulated annealing as the algorithm of optimization during the redesigned proses. The result shows that the new rain gauge location provides minimum value of estimated variance. This shows that the combination of geostatistics method (variance-reduction method) and simulated annealing is successful in the development of the new optimum rain gauge system.

  14. Geostatistics: a common link between medical geography, mathematical geology, and medical geology.

    Science.gov (United States)

    Goovaerts, P

    2014-08-01

    Since its development in the mining industry, geostatistics has emerged as the primary tool for spatial data analysis in various fields, ranging from earth and atmospheric sciences to agriculture, soil science, remote sensing, and more recently environmental exposure assessment. In the last few years, these tools have been tailored to the field of medical geography or spatial epidemiology, which is concerned with the study of spatial patterns of disease incidence and mortality and the identification of potential 'causes' of disease, such as environmental exposure, diet and unhealthy behaviours, economic or socio-demographic factors. On the other hand, medical geology is an emerging interdisciplinary scientific field studying the relationship between natural geological factors and their effects on human and animal health. This paper provides an introduction to the field of medical geology with an overview of geostatistical methods available for the analysis of geological and health data. Key concepts are illustrated using the mapping of groundwater arsenic concentration across eleven Michigan counties and the exploration of its relationship to the incidence of prostate cancer at the township level.

  15. Bayesian geostatistical analysis and prediction of Rhodesian human African trypanosomiasis.

    Directory of Open Access Journals (Sweden)

    Nicola A Wardrop

    2010-12-01

    Full Text Available The persistent spread of Rhodesian human African trypanosomiasis (HAT in Uganda in recent years has increased concerns of a potential overlap with the Gambian form of the disease. Recent research has aimed to increase the evidence base for targeting control measures by focusing on the environmental and climatic factors that control the spatial distribution of the disease.One recent study used simple logistic regression methods to explore the relationship between prevalence of Rhodesian HAT and several social, environmental and climatic variables in two of the most recently affected districts of Uganda, and suggested the disease had spread into the study area due to the movement of infected, untreated livestock. Here we extend this study to account for spatial autocorrelation, incorporate uncertainty in input data and model parameters and undertake predictive mapping for risk of high HAT prevalence in future.Using a spatial analysis in which a generalised linear geostatistical model is used in a Bayesian framework to account explicitly for spatial autocorrelation and incorporate uncertainty in input data and model parameters we are able to demonstrate a more rigorous analytical approach, potentially resulting in more accurate parameter and significance estimates and increased predictive accuracy, thereby allowing an assessment of the validity of the livestock movement hypothesis given more robust parameter estimation and appropriate assessment of covariate effects.Analysis strongly supports the theory that Rhodesian HAT was imported to the study area via the movement of untreated, infected livestock from endemic areas. The confounding effect of health care accessibility on the spatial distribution of Rhodesian HAT and the linkages between the disease's distribution and minimum land surface temperature have also been confirmed via the application of these methods.Predictive mapping indicates an increased risk of high HAT prevalence in the future

  16. Downscaling remotely sensed imagery using area-to-point cokriging and multiple-point geostatistical simulation

    Science.gov (United States)

    Tang, Yunwei; Atkinson, Peter M.; Zhang, Jingxiong

    2015-03-01

    A cross-scale data integration method was developed and tested based on the theory of geostatistics and multiple-point geostatistics (MPG). The goal was to downscale remotely sensed images while retaining spatial structure by integrating images at different spatial resolutions. During the process of downscaling, a rich spatial correlation model in the form of a training image was incorporated to facilitate reproduction of similar local patterns in the simulated images. Area-to-point cokriging (ATPCK) was used as locally varying mean (LVM) (i.e., soft data) to deal with the change of support problem (COSP) for cross-scale integration, which MPG cannot achieve alone. Several pairs of spectral bands of remotely sensed images were tested for integration within different cross-scale case studies. The experiment shows that MPG can restore the spatial structure of the image at a fine spatial resolution given the training image and conditioning data. The super-resolution image can be predicted using the proposed method, which cannot be realised using most data integration methods. The results show that ATPCK-MPG approach can achieve greater accuracy than methods which do not account for the change of support issue.

  17. Comparing the performance of geostatistical models with additional information from covariates for sewage plume characterization.

    Science.gov (United States)

    Del Monego, Maurici; Ribeiro, Paulo Justiniano; Ramos, Patrícia

    2015-04-01

    In this work, kriging with covariates is used to model and map the spatial distribution of salinity measurements gathered by an autonomous underwater vehicle in a sea outfall monitoring campaign aiming to distinguish the effluent plume from the receiving waters and characterize its spatial variability in the vicinity of the discharge. Four different geostatistical linear models for salinity were assumed, where the distance to diffuser, the west-east positioning, and the south-north positioning were used as covariates. Sample variograms were fitted by the Matèrn models using weighted least squares and maximum likelihood estimation methods as a way to detect eventual discrepancies. Typically, the maximum likelihood method estimated very low ranges which have limited the kriging process. So, at least for these data sets, weighted least squares showed to be the most appropriate estimation method for variogram fitting. The kriged maps show clearly the spatial variation of salinity, and it is possible to identify the effluent plume in the area studied. The results obtained show some guidelines for sewage monitoring if a geostatistical analysis of the data is in mind. It is important to treat properly the existence of anomalous values and to adopt a sampling strategy that includes transects parallel and perpendicular to the effluent dispersion.

  18. Use of geostatistics in high level radioactive waste repository site characterization

    Energy Technology Data Exchange (ETDEWEB)

    Doctor, P G [Pacific Northwest Laboratory, Richland, WA (USA)

    1980-09-01

    In evaluating and characterizing sites that are candidates for use as repositories for high-level radioactive waste, there is an increasing need to estimate the uncertainty in hydrogeologic data and in the quantities calculated from them. This paper discusses the use of geostatistical techniques to estimate hydrogeologic surfaces, such as the top of a basalt formation, and to provide a measure of the uncertainty in that estimate. Maps of the uncertainty estimate, called the kriging error, can be used to evaluate where new data should be taken to affect the greatest reduction in uncertainty in the estimated surface. The methods are illustrated on a set of site-characterization data; the top-of-basalt elevations at the Hanford Site near Richland, Washington.

  19. Geostatistical modelling of the spatial life history of post-larval deepwater hake Merluccius paradoxus in the Benguela Current Large Marine Ecosystem

    DEFF Research Database (Denmark)

    Jansen, T; Kristensen, K; Fairweather, T. P.

    2017-01-01

    paradoxus are not reflected in the current assessment and management practices for the Benguela Current Large Marine Ecosystem. In this study, we compiled data from multiple demersal trawl surveys from the entire distribution area and applied state-of the-art geostatistical population modelling (Geo...

  20. Evaluating factorial kriging for seismic attributes filtering: a geostatistical filter applied to reservoir characterization; Avaliacao da krigagem fatorial na filtragem de atributos sismicos: um filtro geoestatistico aplicado a caracterizacao de reservatorios

    Energy Technology Data Exchange (ETDEWEB)

    Mundim, Evaldo Cesario

    1999-02-01

    In this dissertation the Factorial Kriging analysis for the filtering of seismic attributes applied to reservoir characterization is considered. Factorial Kriging works in the spatial, domain in a similar way to the Spectral Analysis in the frequency domain. The incorporation of filtered attributes via External Drift Kriging and Collocated Cokriging in the estimate of reservoir characterization is discussed. Its relevance for the reservoir porous volume calculation is also evaluated based on comparative analysis of the volume risk curves derived from stochastic conditional simulations with collocated variable and stochastic conditional simulations with collocated variable and stochastic conditional simulations with external drift. results prove Factorial Kriging as an efficient technique for the filtering of seismic attributes images, of which geologic features are enhanced. The attribute filtering improves the correlation between the attributes and the well data and the estimates of the reservoir properties. The differences between the estimates obtained by External Drift Kriging and Collocated Cokriging are also reduced. (author)

  1. Spatial distribution of Munida intermedia and M. sarsi (crustacea: Anomura) on the Galician continental shelf (NW Spain): Application of geostatistical analysis

    Science.gov (United States)

    Freire, J.; González-Gurriarán, E.; Olaso, I.

    1992-12-01

    Geostatistical methodology was used to analyse spatial structure and distribution of the epibenthic crustaceans Munida intermedia and M. sarsi within sets of data which had been collected during three survey cruises carried out on the Galician continental shelf (1983 and 1984). This study investigates the feasibility of using geostatistics for data collected according to traditional methods and of enhancing such methodology. The experimental variograms were calculated (pooled variance minus spatial covariance between samples taken one pair at a time vs. distance) and fitted to a 'spherical' model. The spatial structure model was used to estimate the abundance and distribution of the populations studied using the technique of kriging. The species display spatial structures, which are well marked during high density periods and in some areas (especially northern shelf). Geostatistical analysis allows identification of the density gradients in space as well as the patch grain along the continental shelf of 16-25 km diameter for M. intermedia and 12-20 km for M. sarsi. Patches of both species have a consistent location throughout the different cruises. As in other geographical areas, M. intermedia and M. sarsi usually appear at depths ranging from 200 to 500 m, with the highest densities in the continental shelf area located between Fisterra and Estaca de Bares. Althouh sampling was not originally designed specifically for geostatistics, this assay provides a measurement of spatial covariance, and shows variograms with variable structure depending on population density and geographical area. These ideas are useful in improving the design of future sampling cruises.

  2. Mercury emissions from coal combustion in Silesia, analysis using geostatistics

    Science.gov (United States)

    Zasina, Damian; Zawadzki, Jaroslaw

    2015-04-01

    Data provided by the UNEP's report on mercury [1] shows that solid fuel combustion in significant source of mercury emission to air. Silesia, located in southwestern Poland, is notably affected by mercury emission due to being one of the most industrialized Polish regions: the place of coal mining, production of metals, stone mining, mineral quarrying and chemical industry. Moreover, Silesia is the region with high population density. People are exposed to severe risk of mercury emitted from both: industrial and domestic sources (i.e. small household furnaces). Small sources have significant contribution to total emission of mercury. Official and statistical analysis, including prepared for international purposes [2] did not provide data about spatial distribution of the mercury emitted to air, however number of analysis on Polish public power and energy sector had been prepared so far [3; 4]. The distribution of locations exposed for mercury emission from small domestic sources is interesting matter merging information from various sources: statistical, economical and environmental. This paper presents geostatistical approach to distibution of mercury emission from coal combustion. Analysed data organized in 2 independent levels: individual, bottom-up approach derived from national emission reporting system [5; 6] and top down - regional data calculated basing on official statistics [7]. Analysis, that will be presented, will include comparison of spatial distributions of mercury emission using data derived from sources mentioned above. Investigation will include three voivodeships of Poland: Lower Silesian, Opole (voivodeship) and Silesian using selected geostatistical methodologies including ordinary kriging [8]. References [1] UNEP. Global Mercury Assessment 2013: Sources, Emissions, Releases and Environmental Transport. UNEP Chemicals Branch, Geneva, Switzerland, 2013. [2] NCEM. Poland's Informative Inventory Report 2014. NCEM at the IEP-NRI, 2014. http

  3. Variabilidade espacial da agregação do solo avaliada pela geometria fractal e geoestatística Spatial variability of soil aggregation evaluated by fractal geometry and geostatistics

    Directory of Open Access Journals (Sweden)

    J. R. P. Carvalho

    2004-02-01

    Full Text Available Este trabalho teve por objetivo explorar a aplicabilidade da teoria de fractais no estudo da variabilidade espacial em agregação de solo. A geometria de fractais tem sido proposta como um modelo para a distribuição de tamanho de partículas. A distribuição do tamanho de agregados do solo, expressos em termos de massa, é apresentada. Os parâmetros do modelo, tais como: a dimensão fractal D, medida representativa da fragmentação do solo (quanto maior seu valor, maior a fragmentação, e o tamanho do maior agregado R L foram definidos como ferramentas descritivas para a agregação do solo. Os agregados foram coletados em uma profundidade de 0-10 cm de um Latossolo Vermelho distrófico típico álico textura argilosa, em Angatuba, São Paulo. Uma grade regular de 100 x 100 m foi usada e a amostragem realizada em 76 pontos nos quais se determinou a distribuição de agregados por via úmida, usando água, álcool e benzeno como pré-tratamentos. Pelo exame de semivariogramas, constatou-se a ocorrência de dependência espacial. A krigagem ordinária foi usada como interpolador e mapas de contorno mostraram-se de grande utilidade na descrição da variabilidade espacial de agregação do solo.This work explored the applicability of the fractal theory for studies into space variability of soil aggregation. Fractal geometry has become a model for soil size particle distribution. The distribution of soil aggregates in terms of its mass was obtained, and model parameters such as the fractal dimension D, which is a representative measure of the soil fragmentation (the larger its value, the larger the fragmentation, and the largest aggregate size R L were defined as descriptive tools for soil aggregation. The aggregates were collected at a depth of 0-10 cm of a Clayey Ferrasol in Angatuba, São Paulo. A regular grid of 100 x 100 m was used and samples collected from 76 points, where the aggregate distribution was determined by humid way (water

  4. Multi-Criteria GIS Methodology Focused on the Location of Optimal Places for Small Hydro Power Via Hydrological and Geostatistic Aplications; Metodologia SIG Multicriterio Enfocada a la Localizacion de Enclaves Optimos para Centrales de Minihidroelectricas mediante Aplicaciones Hidrologicas y Geoestadisticas

    Energy Technology Data Exchange (ETDEWEB)

    Paz, C de la

    2013-02-01

    The main objective of this research is the development of a location methodology for sitting optimization of small hydro power (SHP) centrals. In order of achieve this goal, a Multi-Criteria Evaluation (MCE) methodology implemented through the use of tools in a GIS environment: Spatial Analysis, Geostatistic Analysis, and Hydrology have been developed. This methodology includes two different models based on the same MCE process. The substantial difference of both models is in the input data and the tools applied to estimate the energy resource and the principal factor of the methodology (caudal or accumulated flow). The first model is generated from caudal data obtained in the study area (El Bierzo), and the second one from pluviometric data and Digital Terrain Model (DTM). Both models include viability maps with greater ability areas to locate SHP facilities. As an additional objective, the study allows contrasting the results of the two developed models to evaluate their similarity. (Author)

  5. Geostatistics and cost-effective environmental remediation

    International Nuclear Information System (INIS)

    Rautman, C.A.

    1996-01-01

    Numerous sites within the U.S. Department of Energy (DOE) complex have been contaminated with various radioactive and hazardous materials by defense-related activities during the post-World War II era. The perception is that characterization and remediation of these contaminated sites will be too costly using currently available technology. Consequently, the DOE Office of Technology Development has funded development of a number of alternative processes for characterizing and remediating these sites. The former Feed-Materials Processing Center near Fernald, Ohio (USA), was selected for demonstrating several innovative technologies. Contamination at the Fernald site consists principally of particulate uranium and derivative compounds in surficial soil. A field-characterization demonstration program was conducted during the summer of 1994 specifically to demonstrate the relative economic performance of seven proposed advanced-characterization tools for measuring uranium activity of in-situ soils. These innovative measurement technologies are principally radiation detectors of varied designs. Four industry-standard measurement technologies, including conventional, regulatory-agency-accepted soil sampling followed by laboratory geochemical analysis, were also demonstrated during the program for comparative purposes. A risk-based economic-decision model has been used to evaluate the performance of these alternative characterization tools. The decision model computes the dollar value of an objective function for each of the different characterization approaches. The methodology not only can assist site operators to choose among engineering alternatives for site characterization and/or remediation, but also can provide an objective and quantitative basis for decisions with respect to the completeness of site characterization

  6. A GIS Tool for evaluating and improving NEXRAD and its application in distributed hydrologic modeling

    Science.gov (United States)

    Zhang, X.; Srinivasan, R.

    2008-12-01

    In this study, a user friendly GIS tool was developed for evaluating and improving NEXRAD using raingauge data. This GIS tool can automatically read in raingauge and NEXRAD data, evaluate the accuracy of NEXRAD for each time unit, implement several geostatistical methods to improve the accuracy of NEXRAD through raingauge data, and output spatial precipitation map for distributed hydrologic model. The geostatistical methods incorporated in this tool include Simple Kriging with varying local means, Kriging with External Drift, Regression Kriging, Co-Kriging, and a new geostatistical method that was newly developed by Li et al. (2008). This tool was applied in two test watersheds at hourly and daily temporal scale. The preliminary cross-validation results show that incorporating raingauge data to calibrate NEXRAD can pronouncedly change the spatial pattern of NEXRAD and improve its accuracy. Using different geostatistical methods, the GIS tool was applied to produce long term precipitation input for a distributed hydrologic model - Soil and Water Assessment Tool (SWAT). Animated video was generated to vividly illustrate the effect of using different precipitation input data on distributed hydrologic modeling. Currently, this GIS tool is developed as an extension of SWAT, which is used as water quantity and quality modeling tool by USDA and EPA. The flexible module based design of this tool also makes it easy to be adapted for other hydrologic models for hydrological modeling and water resources management.

  7. Cross-covariance functions for multivariate geostatistics

    KAUST Repository

    Genton, Marc G.

    2015-05-01

    Continuously indexed datasets with multiple variables have become ubiquitous in the geophysical, ecological, environmental and climate sciences, and pose substantial analysis challenges to scientists and statisticians. For many years, scientists developed models that aimed at capturing the spatial behavior for an individual process; only within the last few decades has it become commonplace to model multiple processes jointly. The key difficulty is in specifying the cross-covariance function, that is, the function responsible for the relationship between distinct variables. Indeed, these cross-covariance functions must be chosen to be consistent with marginal covariance functions in such a way that the second-order structure always yields a nonnegative definite covariance matrix. We review the main approaches to building cross-covariance models, including the linear model of coregionalization, convolution methods, the multivariate Matérn and nonstationary and space-time extensions of these among others. We additionally cover specialized constructions, including those designed for asymmetry, compact support and spherical domains, with a review of physics-constrained models. We illustrate select models on a bivariate regional climate model output example for temperature and pressure, along with a bivariate minimum and maximum temperature observational dataset; we compare models by likelihood value as well as via cross-validation co-kriging studies. The article closes with a discussion of unsolved problems. © Institute of Mathematical Statistics, 2015.

  8. Cross-covariance functions for multivariate geostatistics

    KAUST Repository

    Genton, Marc G.; Kleiber, William

    2015-01-01

    Continuously indexed datasets with multiple variables have become ubiquitous in the geophysical, ecological, environmental and climate sciences, and pose substantial analysis challenges to scientists and statisticians. For many years, scientists developed models that aimed at capturing the spatial behavior for an individual process; only within the last few decades has it become commonplace to model multiple processes jointly. The key difficulty is in specifying the cross-covariance function, that is, the function responsible for the relationship between distinct variables. Indeed, these cross-covariance functions must be chosen to be consistent with marginal covariance functions in such a way that the second-order structure always yields a nonnegative definite covariance matrix. We review the main approaches to building cross-covariance models, including the linear model of coregionalization, convolution methods, the multivariate Matérn and nonstationary and space-time extensions of these among others. We additionally cover specialized constructions, including those designed for asymmetry, compact support and spherical domains, with a review of physics-constrained models. We illustrate select models on a bivariate regional climate model output example for temperature and pressure, along with a bivariate minimum and maximum temperature observational dataset; we compare models by likelihood value as well as via cross-validation co-kriging studies. The article closes with a discussion of unsolved problems. © Institute of Mathematical Statistics, 2015.

  9. Estimating the burden of malaria in Senegal: Bayesian zero-inflated binomial geostatistical modeling of the MIS 2008 data.

    Directory of Open Access Journals (Sweden)

    Federica Giardina

    Full Text Available The Research Center for Human Development in Dakar (CRDH with the technical assistance of ICF Macro and the National Malaria Control Programme (NMCP conducted in 2008/2009 the Senegal Malaria Indicator Survey (SMIS, the first nationally representative household survey collecting parasitological data and malaria-related indicators. In this paper, we present spatially explicit parasitaemia risk estimates and number of infected children below 5 years. Geostatistical Zero-Inflated Binomial models (ZIB were developed to take into account the large number of zero-prevalence survey locations (70% in the data. Bayesian variable selection methods were incorporated within a geostatistical framework in order to choose the best set of environmental and climatic covariates associated with the parasitaemia risk. Model validation confirmed that the ZIB model had a better predictive ability than the standard Binomial analogue. Markov chain Monte Carlo (MCMC methods were used for inference. Several insecticide treated nets (ITN coverage indicators were calculated to assess the effectiveness of interventions. After adjusting for climatic and socio-economic factors, the presence of at least one ITN per every two household members and living in urban areas reduced the odds of parasitaemia by 86% and 81% respectively. Posterior estimates of the ORs related to the wealth index show a decreasing trend with the quintiles. Infection odds appear to be increasing with age. The population-adjusted prevalence ranges from 0.12% in Thillé-Boubacar to 13.1% in Dabo. Tambacounda has the highest population-adjusted predicted prevalence (8.08% whereas the region with the highest estimated number of infected children under the age of 5 years is Kolda (13940. The contemporary map and estimates of malaria burden identify the priority areas for future control interventions and provide baseline information for monitoring and evaluation. Zero-Inflated formulations are more appropriate

  10. A Geostatistical Approach to Indoor Surface Sampling Strategies

    DEFF Research Database (Denmark)

    Schneider, Thomas; Petersen, Ole Holm; Nielsen, Allan Aasbjerg

    1990-01-01

    Particulate surface contamination is of concern in production industries such as food processing, aerospace, electronics and semiconductor manufacturing. There is also an increased awareness that surface contamination should be monitored in industrial hygiene surveys. A conceptual and theoretical...... framework for designing sampling strategies is thus developed. The distribution and spatial correlation of surface contamination can be characterized using concepts from geostatistical science, where spatial applications of statistics is most developed. The theory is summarized and particulate surface...... contamination, sampled from small areas on a table, have been used to illustrate the method. First, the spatial correlation is modelled and the parameters estimated from the data. Next, it is shown how the contamination at positions not measured can be estimated with kriging, a minimum mean square error method...

  11. Geostatistical modeling of groundwater properties and assessment of their uncertainties

    International Nuclear Information System (INIS)

    Honda, Makoto; Yamamoto, Shinya; Sakurai, Hideyuki; Suzuki, Makoto; Sanada, Hiroyuki; Matsui, Hiroya; Sugita, Yutaka

    2010-01-01

    The distribution of groundwater properties is important for understanding of the deep underground hydrogeological environments. This paper proposes a geostatistical system for modeling the groundwater properties which have a correlation with the ground resistivity data obtained from widespread and exhaustive survey. That is, the methodology for the integration of resistivity data measured by various methods and the methodology for modeling the groundwater properties using the integrated resistivity data has been developed. The proposed system has also been validated using the data obtained in the Horonobe Underground Research Laboratory project. Additionally, the quantification of uncertainties in the estimated model has been tried by numerical simulations based on the data. As a result, the uncertainties of the proposal model have been estimated lower than other traditional model's. (author)

  12. Two-point versus multiple-point geostatistics: the ability of geostatistical methods to capture complex geobodies and their facies associations—an application to a channelized carbonate reservoir, southwest Iran

    International Nuclear Information System (INIS)

    Hashemi, Seyyedhossein; Javaherian, Abdolrahim; Ataee-pour, Majid; Khoshdel, Hossein

    2014-01-01

    Facies models try to explain facies architectures which have a primary control on the subsurface heterogeneities and the fluid flow characteristics of a given reservoir. In the process of facies modeling, geostatistical methods are implemented to integrate different sources of data into a consistent model. The facies models should describe facies interactions; the shape and geometry of the geobodies as they occur in reality. Two distinct categories of geostatistical techniques are two-point and multiple-point (geo) statistics (MPS). In this study, both of the aforementioned categories were applied to generate facies models. A sequential indicator simulation (SIS) and a truncated Gaussian simulation (TGS) represented two-point geostatistical methods, and a single normal equation simulation (SNESIM) selected as an MPS simulation representative. The dataset from an extremely channelized carbonate reservoir located in southwest Iran was applied to these algorithms to analyze their performance in reproducing complex curvilinear geobodies. The SNESIM algorithm needs consistent training images (TI) in which all possible facies architectures that are present in the area are included. The TI model was founded on the data acquired from modern occurrences. These analogies delivered vital information about the possible channel geometries and facies classes that are typically present in those similar environments. The MPS results were conditioned to both soft and hard data. Soft facies probabilities were acquired from a neural network workflow. In this workflow, seismic-derived attributes were implemented as the input data. Furthermore, MPS realizations were conditioned to hard data to guarantee the exact positioning and continuity of the channel bodies. A geobody extraction workflow was implemented to extract the most certain parts of the channel bodies from the seismic data. These extracted parts of the channel bodies were applied to the simulation workflow as hard data

  13. Comparing the applicability of some geostatistical methods to predict the spatial distribution of topsoil Calcium Carbonate in part of farmland of Zanjan Province

    Science.gov (United States)

    Sarmadian, Fereydoon; Keshavarzi, Ali

    2010-05-01

    Most of soils in iran, were located in the arid and semi-arid regions and have high pH (more than 7) and high amount of calcium carbonate and this problem cause to their calcification.In calcareous soils, plant growing and production is difficult. Most part of this problem, in relation to high pH and high concentration of calcium ion that cause to fixation and unavailability of elements which were dependent to pH, especially Phosphorous and some micro nutrients such as Fe, Zn, Mn and Cu. Prediction of soil calcium carbonate in non-sampled areas and mapping the calcium carbonate variability in order to sustainable management of soil fertility is very important.So, this research was done with the aim of evaluation and analyzing spatial variability of topsoil calcium carbonate as an aspect of soil fertility and plant nutrition, comparing geostatistical methods such as kriging and co-kriging and mapping topsoil calcium carbonate. For geostatistical analyzing, sampling was done with stratified random method and soil samples from 0 to 15 cm depth were collected with auger within 23 locations.In co-kriging method, salinity data was used as auxiliary variable. For comparing and evaluation of geostatistical methods, cross validation were used by statistical parameters of RMSE. The results showed that co-kriging method has the highest correlation coefficient and less RMSE and has the higher accuracy than kriging method to prediction of calcium carbonate content in non-sampled areas.

  14. Modeling spatial variability of sand-lenses in clay till settings using transition probability and multiple-point geostatistics

    DEFF Research Database (Denmark)

    Kessler, Timo Christian; Nilsson, Bertel; Klint, Knud Erik

    2010-01-01

    (TPROGS) of alternating geological facies. The second method, multiple-point statistics, uses training images to estimate the conditional probability of sand-lenses at a certain location. Both methods respect field observations such as local stratigraphy, however, only the multiple-point statistics can...... of sand-lenses in clay till. Sand-lenses mainly account for horizontal transport and are prioritised in this study. Based on field observations, the distribution has been modeled using two different geostatistical approaches. One method uses a Markov chain model calculating the transition probabilities...

  15. Assessment of nitrate pollution in the Grand Morin aquifers (France): Combined use of geostatistics and physically based modeling

    Energy Technology Data Exchange (ETDEWEB)

    Flipo, Nicolas [Centre de Geosciences, UMR Sisyphe, ENSMP, 35 rue Saint-Honore, F-77305 Fontainebleau (France)]. E-mail: nicolas.flipo@ensmp.fr; Jeannee, Nicolas [Geovariances, 49 bis, avenue Franklin Roosevelt, F-77212 Avon (France); Poulin, Michel [Centre de Geosciences, UMR Sisyphe, ENSMP, 35 rue Saint-Honore, F-77305 Fontainebleau (France); Even, Stephanie [Centre de Geosciences, UMR Sisyphe, ENSMP, 35 rue Saint-Honore, F-77305 Fontainebleau (France); Ledoux, Emmanuel [Centre de Geosciences, UMR Sisyphe, ENSMP, 35 rue Saint-Honore, F-77305 Fontainebleau (France)

    2007-03-15

    The objective of this work is to combine several approaches to better understand nitrate fate in the Grand Morin aquifers (2700 km{sup 2}), part of the Seine basin. CAWAQS results from the coupling of the hydrogeological model NEWSAM with the hydrodynamic and biogeochemical model of river PROSE. CAWAQS is coupled with the agronomic model STICS in order to simulate nitrate migration in basins. First, kriging provides a satisfactory representation of aquifer nitrate contamination from local observations, to set initial conditions for the physically based model. Then associated confidence intervals, derived from data using geostatistics, are used to validate CAWAQS results. Results and evaluation obtained from the combination of these approaches are given (period 1977-1988). Then CAWAQS is used to simulate nitrate fate for a 20-year period (1977-1996). The mean nitrate concentrations increase in aquifers is 0.09 mgN L{sup -1} yr{sup -1}, resulting from an average infiltration flux of 3500 kgN.km{sup -2} yr{sup -1}. - Combined use of geostatistics and physically based modeling allows assessment of nitrate concentrations in aquifer systems.

  16. Assessment of nitrate pollution in the Grand Morin aquifers (France): Combined use of geostatistics and physically based modeling

    International Nuclear Information System (INIS)

    Flipo, Nicolas; Jeannee, Nicolas; Poulin, Michel; Even, Stephanie; Ledoux, Emmanuel

    2007-01-01

    The objective of this work is to combine several approaches to better understand nitrate fate in the Grand Morin aquifers (2700 km 2 ), part of the Seine basin. CAWAQS results from the coupling of the hydrogeological model NEWSAM with the hydrodynamic and biogeochemical model of river PROSE. CAWAQS is coupled with the agronomic model STICS in order to simulate nitrate migration in basins. First, kriging provides a satisfactory representation of aquifer nitrate contamination from local observations, to set initial conditions for the physically based model. Then associated confidence intervals, derived from data using geostatistics, are used to validate CAWAQS results. Results and evaluation obtained from the combination of these approaches are given (period 1977-1988). Then CAWAQS is used to simulate nitrate fate for a 20-year period (1977-1996). The mean nitrate concentrations increase in aquifers is 0.09 mgN L -1 yr -1 , resulting from an average infiltration flux of 3500 kgN.km -2 yr -1 . - Combined use of geostatistics and physically based modeling allows assessment of nitrate concentrations in aquifer systems

  17. Geostatistical Analysis of Mesoscale Spatial Variability and Error in SeaWiFS and MODIS/Aqua Global Ocean Color Data

    Science.gov (United States)

    Glover, David M.; Doney, Scott C.; Oestreich, William K.; Tullo, Alisdair W.

    2018-01-01

    Mesoscale (10-300 km, weeks to months) physical variability strongly modulates the structure and dynamics of planktonic marine ecosystems via both turbulent advection and environmental impacts upon biological rates. Using structure function analysis (geostatistics), we quantify the mesoscale biological signals within global 13 year SeaWiFS (1998-2010) and 8 year MODIS/Aqua (2003-2010) chlorophyll a ocean color data (Level-3, 9 km resolution). We present geographical distributions, seasonality, and interannual variability of key geostatistical parameters: unresolved variability or noise, resolved variability, and spatial range. Resolved variability is nearly identical for both instruments, indicating that geostatistical techniques isolate a robust measure of biophysical mesoscale variability largely independent of measurement platform. In contrast, unresolved variability in MODIS/Aqua is substantially lower than in SeaWiFS, especially in oligotrophic waters where previous analysis identified a problem for the SeaWiFS instrument likely due to sensor noise characteristics. Both records exhibit a statistically significant relationship between resolved mesoscale variability and the low-pass filtered chlorophyll field horizontal gradient magnitude, consistent with physical stirring acting on large-scale gradient as an important factor supporting observed mesoscale variability. Comparable horizontal length scales for variability are found from tracer-based scaling arguments and geostatistical decorrelation. Regional variations between these length scales may reflect scale dependence of biological mechanisms that also create variability directly at the mesoscale, for example, enhanced net phytoplankton growth in coastal and frontal upwelling and convective mixing regions. Global estimates of mesoscale biophysical variability provide an improved basis for evaluating higher resolution, coupled ecosystem-ocean general circulation models, and data assimilation.

  18. Menses cup evaluation study.

    Science.gov (United States)

    Cheng, M; Kung, R; Hannah, M; Wilansky, D; Shime, J

    1995-09-01

    To determine whether the menses cup is well tolerated by menstruating women. Prospective descriptive clinical study. Normal human volunteers in an academic research environment. Fifty-one menstruating women recruited between June to December 1991. Each participant was provided with two menses cups and an instruction sheet. Baseline information, including age, occupation, martial status, parity, description of menstrual flow, and current method used to cope with menstrual flow was collected. Subjects were asked to describe their experience with the cup at 1-, 2-, 6-, and 12-month intervals. The proportion of women who found the cup acceptable. The cup was used by 51 subjects for a total of 159 cycles. Overall, 23 women (45%) found the cup an acceptable method for coping with menses. Among 29 (57%) women who used the cup for two or more cycles, 62% found it acceptable. The menses cup may be an acceptable method for some women for coping with menstrual flow.

  19. Spatial Variability and Geostatistical Prediction of Some Soil Hydraulic Coefficients of a Calcareous Soil

    Directory of Open Access Journals (Sweden)

    Ali Akbar Moosavi

    2017-02-01

    Full Text Available Introduction: Saturated hydraulic conductivity and the other hydraulic properties of soils are essential vital soil attributes that play role in the modeling of hydrological phenomena, designing irrigation-drainage systems, transportation of salts and chemical and biological pollutants within the soil. Measurement of these hydraulic properties needs some special instruments, expert technician, and are time consuming and expensive and due to their high temporal and spatial variability, a large number of measurements are needed. Nowadays, prediction of these attributes using the readily available soil data using pedotransfer functions or using the limited measurement with applying the geostatistical approaches has been receiving high attention. The study aimed to determine the spatial variability and prediction of saturated (Ks and near saturated (Kfs hydraulic conductivity, the power of Gardner equation (α, sorptivity (S, hydraulic diffusivity (D and matric flux potential (Фm of a calcareous soil. Material and Methods: The study was carried out on the soil series of Daneshkadeh located in the Bajgah Agricultural Experimental Station of Agricultural College, Shiraz University, Shiraz, Iran (1852 m above the mean sea level. This soil series with about 745 ha is a deep yellowish brow calcareous soil with textural classes of loam to clay. In the studied soil series 50 sampling locations with the sampling distances of 16, 8 , and 4 m were selected on the relatively regular sampling design. The saturated hydraulic conductivity (Ks, near saturated hydraulic conductivity (Kfs, the power of Gardner equation (α, sorptivity (S, hydraulic diffusivity (D and matric flux potential (Фm of the aforementioned sampling locations was determined using the Single Ring and Droplet methods. After, initial statistical processing, including a normality test of data, trend and stationary analysis of data, the semivariograms of each studied hydraulic attributes were

  20. DEM-based delineation for improving geostatistical interpolation of rainfall in mountainous region of Central Himalayas, India

    Science.gov (United States)

    Kumari, Madhuri; Singh, Chander Kumar; Bakimchandra, Oinam; Basistha, Ashoke

    2017-10-01

    In mountainous region with heterogeneous topography, the geostatistical modeling of the rainfall using global data set may not confirm to the intrinsic hypothesis of stationarity. This study was focused on improving the precision of the interpolated rainfall maps by spatial stratification in complex terrain. Predictions of the normal annual rainfall data were carried out by ordinary kriging, universal kriging, and co-kriging, using 80-point observations in the Indian Himalayas extending over an area of 53,484 km2. A two-step spatial clustering approach is proposed. In the first step, the study area was delineated into two regions namely lowland and upland based on the elevation derived from the digital elevation model. The delineation was based on the natural break classification method. In the next step, the rainfall data was clustered into two groups based on its spatial location in lowland or upland. The terrain ruggedness index (TRI) was incorporated as a co-variable in co-kriging interpolation algorithm. The precision of the kriged and co-kriged maps was assessed by two accuracy measures, root mean square error and Chatfield's percent better. It was observed that the stratification of rainfall data resulted in 5-20 % of increase in the performance efficiency of interpolation methods. Co-kriging outperformed the kriging models at annual and seasonal scale. The result illustrates that the stratification of the study area improves the stationarity characteristic of the point data, thus enhancing the precision of the interpolated rainfall maps derived using geostatistical methods.

  1. Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: the case of lung cancer in Long Island, New York

    Directory of Open Access Journals (Sweden)

    Goovaerts Pierre

    2004-07-01

    Full Text Available Abstract Background Complete Spatial Randomness (CSR is the null hypothesis employed by many statistical tests for spatial pattern, such as local cluster or boundary analysis. CSR is however not a relevant null hypothesis for highly complex and organized systems such as those encountered in the environmental and health sciences in which underlying spatial pattern is present. This paper presents a geostatistical approach to filter the noise caused by spatially varying population size and to generate spatially correlated neutral models that account for regional background obtained by geostatistical smoothing of observed mortality rates. These neutral models were used in conjunction with the local Moran statistics to identify spatial clusters and outliers in the geographical distribution of male and female lung cancer in Nassau, Queens, and Suffolk counties, New York, USA. Results We developed a typology of neutral models that progressively relaxes the assumptions of null hypotheses, allowing for the presence of spatial autocorrelation, non-uniform risk, and incorporation of spatially heterogeneous population sizes. Incorporation of spatial autocorrelation led to fewer significant ZIP codes than found in previous studies, confirming earlier claims that CSR can lead to over-identification of the number of significant spatial clusters or outliers. Accounting for population size through geostatistical filtering increased the size of clusters while removing most of the spatial outliers. Integration of regional background into the neutral models yielded substantially different spatial clusters and outliers, leading to the identification of ZIP codes where SMR values significantly depart from their regional background. Conclusion The approach presented in this paper enables researchers to assess geographic relationships using appropriate null hypotheses that account for the background variation extant in real-world systems. In particular, this new

  2. Time-lapse analysis of methane quantity in Mary Lee group of coal seams using filter-based multiple-point geostatistical simulation

    Science.gov (United States)

    Karacan, C. Özgen; Olea, Ricardo A.

    2013-01-01

    Coal seam degasification and its success are important for controlling methane, and thus for the health and safety of coal miners. During the course of degasification, properties of coal seams change. Thus, the changes in coal reservoir conditions and in-place gas content as well as methane emission potential into mines should be evaluated by examining time-dependent changes and the presence of major heterogeneities and geological discontinuities in the field. In this work, time-lapsed reservoir and fluid storage properties of the New Castle coal seam, Mary Lee/Blue Creek seam, and Jagger seam of Black Warrior Basin, Alabama, were determined from gas and water production history matching and production forecasting of vertical degasification wellbores. These properties were combined with isotherm and other important data to compute gas-in-place (GIP) and its change with time at borehole locations. Time-lapsed training images (TIs) of GIP and GIP difference corresponding to each coal and date were generated by using these point-wise data and Voronoi decomposition on the TI grid, which included faults as discontinuities for expansion of Voronoi regions. Filter-based multiple-point geostatistical simulations, which were preferred in this study due to anisotropies and discontinuities in the area, were used to predict time-lapsed GIP distributions within the study area. Performed simulations were used for mapping spatial time-lapsed methane quantities as well as their uncertainties within the study area.

  3. Geostatistical analysis of allele presence patterns among American black bears in eastern North Carolina

    Science.gov (United States)

    Thompson, L.M.; Van Manen, F.T.; King, T.L.

    2005-01-01

    Highways are one of the leading causes of wildlife habitat fragmentation and may particularly affect wide-ranging species, such as American black bears (Ursus americanus). We initiated a research project in 2000 to determine potential effects of a 4-lane highway on black bear ecology in Washington County, North Carolina. The research design included a treatment area (highway construction) and a control area and a pre- and post-construction phase. We used data from the pre-construction phase to determine whether we could detect scale dependency or directionality among allele occurrence patterns using geostatistics. Detection of such patterns could provide a powerful tool to measure the effects of landscape fragmentation on gene flow. We sampled DNA from roots of black bear hair at 70 hair-sampling sites on each study area for 7 weeks during fall of 2000. We used microsatellite analysis based on 10 loci to determine unique multi-locus genotypes. We examined all alleles sampled at ???25 sites on each study area and mapped their presence or absence at each hair-sample site. We calculated semivariograms, which measure the strength of statistical correlation as a function of distance, and adjusted them for anisotropy to determine the maximum direction of spatial continuity. We then calculated the mean direction of spatial continuity for all examined alleles. The mean direction of allele frequency variation was 118.3?? (SE = 8.5) on the treatment area and 172.3?? (SE = 6.0) on the control area. Rayleigh's tests showed that these directions differed from random distributions (P = 0.028 and P < 0.001, respectively), indicating consistent directional patterns for the alleles we examined in each area. Despite the small spatial scale of our study (approximately 11,000 ha for each study area), we observed distinct and consistent patterns of allele occurrence, suggesting different directions of gene flow between the study areas. These directions seemed to coincide with the

  4. Bayesian Analysis of Geostatistical Models With an Auxiliary Lattice

    KAUST Repository

    Park, Jincheol

    2012-04-01

    The Gaussian geostatistical model has been widely used for modeling spatial data. However, this model suffers from a severe difficulty in computation: it requires users to invert a large covariance matrix. This is infeasible when the number of observations is large. In this article, we propose an auxiliary lattice-based approach for tackling this difficulty. By introducing an auxiliary lattice to the space of observations and defining a Gaussian Markov random field on the auxiliary lattice, our model completely avoids the requirement of matrix inversion. It is remarkable that the computational complexity of our method is only O(n), where n is the number of observations. Hence, our method can be applied to very large datasets with reasonable computational (CPU) times. The numerical results indicate that our model can approximate Gaussian random fields very well in terms of predictions, even for those with long correlation lengths. For real data examples, our model can generally outperform conventional Gaussian random field models in both prediction errors and CPU times. Supplemental materials for the article are available online. © 2012 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.

  5. Bayesian geostatistical modeling of leishmaniasis incidence in Brazil.

    Directory of Open Access Journals (Sweden)

    Dimitrios-Alexios Karagiannis-Voules

    Full Text Available BACKGROUND: Leishmaniasis is endemic in 98 countries with an estimated 350 million people at risk and approximately 2 million cases annually. Brazil is one of the most severely affected countries. METHODOLOGY: We applied Bayesian geostatistical negative binomial models to analyze reported incidence data of cutaneous and visceral leishmaniasis in Brazil covering a 10-year period (2001-2010. Particular emphasis was placed on spatial and temporal patterns. The models were fitted using integrated nested Laplace approximations to perform fast approximate Bayesian inference. Bayesian variable selection was employed to determine the most important climatic, environmental, and socioeconomic predictors of cutaneous and visceral leishmaniasis. PRINCIPAL FINDINGS: For both types of leishmaniasis, precipitation and socioeconomic proxies were identified as important risk factors. The predicted number of cases in 2010 were 30,189 (standard deviation [SD]: 7,676 for cutaneous leishmaniasis and 4,889 (SD: 288 for visceral leishmaniasis. Our risk maps predicted the highest numbers of infected people in the states of Minas Gerais and Pará for visceral and cutaneous leishmaniasis, respectively. CONCLUSIONS/SIGNIFICANCE: Our spatially explicit, high-resolution incidence maps identified priority areas where leishmaniasis control efforts should be targeted with the ultimate goal to reduce disease incidence.

  6. Using river distance and existing hydrography data can improve the geostatistical estimation of fish tissue mercury at unsampled locations.

    Science.gov (United States)

    Money, Eric S; Sackett, Dana K; Aday, D Derek; Serre, Marc L

    2011-09-15

    Mercury in fish tissue is a major human health concern. Consumption of mercury-contaminated fish poses risks to the general population, including potentially serious developmental defects and neurological damage in young children. Therefore, it is important to accurately identify areas that have the potential for high levels of bioaccumulated mercury. However, due to time and resource constraints, it is difficult to adequately assess fish tissue mercury on a basin wide scale. We hypothesized that, given the nature of fish movement along streams, an analytical approach that takes into account distance traveled along these streams would improve the estimation accuracy for fish tissue mercury in unsampled streams. Therefore, we used a river-based Bayesian Maximum Entropy framework (river-BME) for modern space/time geostatistics to estimate fish tissue mercury at unsampled locations in the Cape Fear and Lumber Basins in eastern North Carolina. We also compared the space/time geostatistical estimation using river-BME to the more traditional Euclidean-based BME approach, with and without the inclusion of a secondary variable. Results showed that this river-based approach reduced the estimation error of fish tissue mercury by more than 13% and that the median estimate of fish tissue mercury exceeded the EPA action level of 0.3 ppm in more than 90% of river miles for the study domain.

  7. Assessing the spatial distribution of Tuta absoluta (Lepidoptera: Gelechiidae) eggs in open-field tomato cultivation through geostatistical analysis.

    Science.gov (United States)

    Martins, Júlio C; Picanço, Marcelo C; Silva, Ricardo S; Gonring, Alfredo Hr; Galdino, Tarcísio Vs; Guedes, Raul Nc

    2018-01-01

    The spatial distribution of insects is due to the interaction between individuals and the environment. Knowledge about the within-field pattern of spatial distribution of a pest is critical to planning control tactics, developing efficient sampling plans, and predicting pest damage. The leaf miner Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) is the main pest of tomato crops in several regions of the world. Despite the importance of this pest, the pattern of spatial distribution of T. absoluta on open-field tomato cultivation remains unknown. Therefore, this study aimed to characterize the spatial distribution of T. absoluta in 22 commercial open-field tomato cultivations with plants at the three phenological development stages by using geostatistical analysis. Geostatistical analysis revealed that there was strong evidence for spatially dependent (aggregated) T. absoluta eggs in 19 of the 22 sample tomato cultivations. The maps that were obtained demonstrated the aggregated structure of egg densities at the edges of the crops. Further, T. absoluta was found to accomplish egg dispersal along the rows more frequently than it does between rows. Our results indicate that the greatest egg densities of T. absoluta occur at the edges of tomato crops. These results are discussed in relation to the behavior of T. absoluta distribution within fields and in terms of their implications for improved sampling guidelines and precision targeting control methods that are essential for effective pest monitoring and management. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  8. EIA and EINP. Evaluation study

    International Nuclear Information System (INIS)

    Lande, R.W.I. van der; De Vries, E.F.

    2001-01-01

    The evaluation study on the title subjects concerns two subsidy tools in the Netherlands: the Energy Investment Rebate (EIA, abbreviated in Dutch) and the Subsidy for Energy in the non-profit sector and other special sectors (EINP, abbreviated in Dutch). The central question in the evaluation was to what extent did the EIA and EINP contribute to the original policy targets and at what costs. The evaluation has been carried out by means of a desk study, interviews, and an analysis of bottlenecks and possible solutions. [nl

  9. A Reduced-Order Successive Linear Estimator for Geostatistical Inversion and its Application in Hydraulic Tomography

    Science.gov (United States)

    Zha, Yuanyuan; Yeh, Tian-Chyi J.; Illman, Walter A.; Zeng, Wenzhi; Zhang, Yonggen; Sun, Fangqiang; Shi, Liangsheng

    2018-03-01

    Hydraulic tomography (HT) is a recently developed technology for characterizing high-resolution, site-specific heterogeneity using hydraulic data (nd) from a series of cross-hole pumping tests. To properly account for the subsurface heterogeneity and to flexibly incorporate additional information, geostatistical inverse models, which permit a large number of spatially correlated unknowns (ny), are frequently used to interpret the collected data. However, the memory storage requirements for the covariance of the unknowns (ny × ny) in these models are prodigious for large-scale 3-D problems. Moreover, the sensitivity evaluation is often computationally intensive using traditional difference method (ny forward runs). Although employment of the adjoint method can reduce the cost to nd forward runs, the adjoint model requires intrusive coding effort. In order to resolve these issues, this paper presents a Reduced-Order Successive Linear Estimator (ROSLE) for analyzing HT data. This new estimator approximates the covariance of the unknowns using Karhunen-Loeve Expansion (KLE) truncated to nkl order, and it calculates the directional sensitivities (in the directions of nkl eigenvectors) to form the covariance and cross-covariance used in the Successive Linear Estimator (SLE). In addition, the covariance of unknowns is updated every iteration by updating the eigenvalues and eigenfunctions. The computational advantages of the proposed algorithm are demonstrated through numerical experiments and a 3-D transient HT analysis of data from a highly heterogeneous field site.

  10. Delineating Facies Spatial Distribution by Integrating Ensemble Data Assimilation and Indicator Geostatistics with Level Set Transformation.

    Energy Technology Data Exchange (ETDEWEB)

    Hammond, Glenn Edward; Song, Xuehang; Ye, Ming; Dai, Zhenxue; Zachara, John; Chen, Xingyuan

    2017-03-01

    A new approach is developed to delineate the spatial distribution of discrete facies (geological units that have unique distributions of hydraulic, physical, and/or chemical properties) conditioned not only on direct data (measurements directly related to facies properties, e.g., grain size distribution obtained from borehole samples) but also on indirect data (observations indirectly related to facies distribution, e.g., hydraulic head and tracer concentration). Our method integrates for the first time ensemble data assimilation with traditional transition probability-based geostatistics. The concept of level set is introduced to build shape parameterization that allows transformation between discrete facies indicators and continuous random variables. The spatial structure of different facies is simulated by indicator models using conditioning points selected adaptively during the iterative process of data assimilation. To evaluate the new method, a two-dimensional semi-synthetic example is designed to estimate the spatial distribution and permeability of two distinct facies from transient head data induced by pumping tests. The example demonstrates that our new method adequately captures the spatial pattern of facies distribution by imposing spatial continuity through conditioning points. The new method also reproduces the overall response in hydraulic head field with better accuracy compared to data assimilation with no constraints on spatial continuity on facies.

  11. Evaluation of geophysical borehole studies

    International Nuclear Information System (INIS)

    Brotzen, O.; Duran, O.; Magnusson, K.Aa.

    Four studies concerning geophysical investigations and TV inspection in boreholes in connection with KBS studies at Finnsjoe, Karlshamn, Kraakemaala and Stripa and PRAV's studies at Studsvik have been evaluated. This has led to proposals concerning the choice of instruments and methods for future studies and a review of future work required. The evaluation has shown that the following borehole measurements are of primary interest in the continued work: Determinations of temperature and resistivity of the borehole liquid, resistance and resistivity measurements, SP, Sonic, Caliper and VLF. TV inspection, IP and gamma-gamma should also be included in the arsenal of available test methods.(author)

  12. Optimized Field Sampling and Monitoring of Airborne Hazardous Transport Plumes; A Geostatistical Simulation Approach

    International Nuclear Information System (INIS)

    Chen, DI-WEN

    2001-01-01

    Airborne hazardous plumes inadvertently released during nuclear/chemical/biological incidents are mostly of unknown composition and concentration until measurements are taken of post-accident ground concentrations from plume-ground deposition of constituents. Unfortunately, measurements often are days post-incident and rely on hazardous manned air-vehicle measurements. Before this happens, computational plume migration models are the only source of information on the plume characteristics, constituents, concentrations, directions of travel, ground deposition, etc. A mobile ''lighter than air'' (LTA) system is being developed at Oak Ridge National Laboratory that will be part of the first response in emergency conditions. These interactive and remote unmanned air vehicles will carry light-weight detectors and weather instrumentation to measure the conditions during and after plume release. This requires a cooperative computationally organized, GPS-controlled set of LTA's that self-coordinate around the objectives in an emergency situation in restricted time frames. A critical step before an optimum and cost-effective field sampling and monitoring program proceeds is the collection of data that provides statistically significant information, collected in a reliable and expeditious manner. Efficient aerial arrangements of the detectors taking the data (for active airborne release conditions) are necessary for plume identification, computational 3-dimensional reconstruction, and source distribution functions. This report describes the application of stochastic or geostatistical simulations to delineate the plume for guiding subsequent sampling and monitoring designs. A case study is presented of building digital plume images, based on existing ''hard'' experimental data and ''soft'' preliminary transport modeling results of Prairie Grass Trials Site. Markov Bayes Simulation, a coupled Bayesian/geostatistical methodology, quantitatively combines soft information

  13. The geostatistical approach for structural and stratigraphic framework analysis of offshore NW Bonaparte Basin, Australia

    International Nuclear Information System (INIS)

    Wahid, Ali; Salim, Ahmed Mohamed Ahmed; Yusoff, Wan Ismail Wan; Gaafar, Gamal Ragab

    2016-01-01

    Geostatistics or statistical approach is based on the studies of temporal and spatial trend, which depend upon spatial relationships to model known information of variable(s) at unsampled locations. The statistical technique known as kriging was used for petrophycial and facies analysis, which help to assume spatial relationship to model the geological continuity between the known data and the unknown to produce a single best guess of the unknown. Kriging is also known as optimal interpolation technique, which facilitate to generate best linear unbiased estimation of each horizon. The idea is to construct a numerical model of the lithofacies and rock properties that honor available data and further integrate with interpreting seismic sections, techtonostratigraphy chart with sea level curve (short term) and regional tectonics of the study area to find the structural and stratigraphic growth history of the NW Bonaparte Basin. By using kriging technique the models were built which help to estimate different parameters like horizons, facies, and porosities in the study area. The variograms were used to determine for identification of spatial relationship between data which help to find the depositional history of the North West (NW) Bonaparte Basin

  14. Mapping mean annual and monthly river discharges: geostatistical developments for incorporating river network dependencies

    International Nuclear Information System (INIS)

    Sauquet, Eric

    2004-01-01

    Regional hydrology is one topic that shows real improvement in partly due to new statistical development and computation facilities. Nevertheless theoretical difficulties for mapping river regime characteristics or recover these features at un gauged location remain because of the nature of the variable under study: river flows are related to a specific area that is defined by the drainage basin, are spatially organised by the river network with upstream-downstream dependencies. Estimations of hydrological descriptors are required for studying links with ecological processes at different spatial scale, from local site where biological or/and water quality data are available to large scale for sustainable development purposes. This presentation aims at describing a method for runoff pattern along the main river network. The approach dedicated to mean annual runoff is based on geostatistical interpolation procedures to which a constraint of water budget has been added. Expansion in Empirical Orthogonal Function has been considered in combination with kriging for interpolating mean monthly discharges. The methodologies are implemented within a Geographical Information System and illustrated by two study cases (two large basins in France). River flow regime descriptors are estimated for basins of more than 50km 2 . Opportunities of collaboration with a partition of France into hydro-eco regions derived from geology and climate considerations is discussed. (Author)

  15. The geostatistical approach for structural and stratigraphic framework analysis of offshore NW Bonaparte Basin, Australia

    Energy Technology Data Exchange (ETDEWEB)

    Wahid, Ali, E-mail: ali.wahid@live.com; Salim, Ahmed Mohamed Ahmed, E-mail: mohamed.salim@petronas.com.my; Yusoff, Wan Ismail Wan, E-mail: wanismail-wanyusoff@petronas.com.my [Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 32610 Tronoh, Perak (Malaysia); Gaafar, Gamal Ragab, E-mail: gaafargr@gmail.com [Petroleum Engineering Division, PETRONAS Carigali Sdn Bhd, Kuala Lumpur (Malaysia)

    2016-02-01

    Geostatistics or statistical approach is based on the studies of temporal and spatial trend, which depend upon spatial relationships to model known information of variable(s) at unsampled locations. The statistical technique known as kriging was used for petrophycial and facies analysis, which help to assume spatial relationship to model the geological continuity between the known data and the unknown to produce a single best guess of the unknown. Kriging is also known as optimal interpolation technique, which facilitate to generate best linear unbiased estimation of each horizon. The idea is to construct a numerical model of the lithofacies and rock properties that honor available data and further integrate with interpreting seismic sections, techtonostratigraphy chart with sea level curve (short term) and regional tectonics of the study area to find the structural and stratigraphic growth history of the NW Bonaparte Basin. By using kriging technique the models were built which help to estimate different parameters like horizons, facies, and porosities in the study area. The variograms were used to determine for identification of spatial relationship between data which help to find the depositional history of the North West (NW) Bonaparte Basin.

  16. Bayesian Geostatistical Modeling of Malaria Indicator Survey Data in Angola

    Science.gov (United States)

    Gosoniu, Laura; Veta, Andre Mia; Vounatsou, Penelope

    2010-01-01

    The 2006–2007 Angola Malaria Indicator Survey (AMIS) is the first nationally representative household survey in the country assessing coverage of the key malaria control interventions and measuring malaria-related burden among children under 5 years of age. In this paper, the Angolan MIS data were analyzed to produce the first smooth map of parasitaemia prevalence based on contemporary nationwide empirical data in the country. Bayesian geostatistical models were fitted to assess the effect of interventions after adjusting for environmental, climatic and socio-economic factors. Non-linear relationships between parasitaemia risk and environmental predictors were modeled by categorizing the covariates and by employing two non-parametric approaches, the B-splines and the P-splines. The results of the model validation showed that the categorical model was able to better capture the relationship between parasitaemia prevalence and the environmental factors. Model fit and prediction were handled within a Bayesian framework using Markov chain Monte Carlo (MCMC) simulations. Combining estimates of parasitaemia prevalence with the number of children under we obtained estimates of the number of infected children in the country. The population-adjusted prevalence ranges from in Namibe province to in Malanje province. The odds of parasitaemia in children living in a household with at least ITNs per person was by 41% lower (CI: 14%, 60%) than in those with fewer ITNs. The estimates of the number of parasitaemic children produced in this paper are important for planning and implementing malaria control interventions and for monitoring the impact of prevention and control activities. PMID:20351775

  17. [Distribution of soil heavy metal and pollution evaluation on the different sampling scales in farmland on Yellow River irrigation area of Ningxia: a case study in Xingqing County of Yinchuan City].

    Science.gov (United States)

    Wang, You-Qi; Bai, Yi-Ru; Wang, Jian-Yu

    2014-07-01

    Determining spatial distributions and analyses contamination condition of soil heavy metals play an important role in evaluation of the quality of agricultural ecological environment and the protection of food safety and human health. Topsoil samples (0-20 cm) from 223 sites in farmland were collected at two scales of sampling grid (1 m x 1 m, 10 m x 10 m) in the Yellow River irrigation area of Ningxia. The objectives of this study were to investigate the spatial variability of total copper (Cu), total zinc (Zn), total chrome (Cr), total cadmium (Cd) and total lead (Pb) on the two sampling scales by the classical and geostatistical analyses. The single pollution index (P(i)) and the Nemerow pollution index (P) were used to evaluate the soil heavy metal pollution. The classical statistical analyses showed that all soil heavy metals demonstrated moderate variability, the coefficient of variation (CV) changed in the following sequence: Cd > Pb > Cr > Zn > Cu. Geostatistical analyses showed that the nugget coefficient of Cd on the 10 m x 10 m scale and Pb on the 1 m x 1 m scale were 100% with pure nugget variograms, which showed weak variability affected by random factors. The nugget coefficient of the other indexes was less than 25%, which showed a strong variability affected by structural factors. The results combined with P(i) and P indicated that most soil heavy metals have slight pollution except total copper, and in general there were the trend of heavy metal accumulation in the study area.

  18. The detection of thermophilous forest hotspots in Poland using geostatistical interpolation of plant richness

    Directory of Open Access Journals (Sweden)

    Marcin Kiedrzyński

    2014-07-01

    Full Text Available Attempts to study biodiversity hotspots on a regional scale should combine compositional and functionalist criteria. The detection of hotspots in this study uses one ecologically similar group of high conservation value species as hotspot indicators, as well as focal habitat indicators, to detect the distribution of suitable environmental conditions. The method is assessed with reference to thermophilous forests in Poland – key habitats for many rare and relict species. Twenty-six high conservation priority species were used as hotspot indicators, and ten plant taxa characteristic of the Quercetalia pubescenti-petraeae phytosociological order were used as focal habitat indicators. Species distribution data was based on a 10 × 10 km grid. The number of species per grid square was interpolated by the ordinary kriging geostatistical method. Our analysis largely determined the distribution of areas with concentration of thermophilous forest flora, but also regional disjunctions and geographical barriers. Indicator species richness can be interpreted as a reflection of the actual state of habitat conditions. It can also be used to determine the location of potential species refugia and possible past and future migration routes.

  19. Geostatistical Approach to Find ‘Hotspots’ Where Biodiversity is at Risk in a Transition Country

    Directory of Open Access Journals (Sweden)

    Petrişor Alexandru-Ionuţ

    2014-10-01

    Full Text Available Global change‟ is a relatively recent concept, related to the energy - land use - climate change nexus, and designated to include all changes produced by the human species and the consequences of its activities over natural ecological complexes and biodiversity. The joint effects of these drivers of change are particularly relevant to understanding the changes of biodiversity. This study overlaps results of previous studies developed in Romania to find, explain and predict potential threats on biodiversity, including the effects of very high temperatures and low precipitations, urban sprawl and deforestation in order to identify „hotspots‟ of high risk for the loss of biodiversity using geostatistical tools. The results found two hotspots, one in the center and the other one in the south, and show that the area affected by three factors simultaneously represents 0.2% of the national territory, while paired effects cover 4% of it. The methodological advantage of this approach is its capacity to pinpoint hotspots with practical relevance. Nevertheless, its generalizing character impairs its use at the local scale..

  20. Characterizing the spatial structure of endangered species habitat using geostatistical analysis of IKONOS imagery

    Science.gov (United States)

    Wallace, C.S.A.; Marsh, S.E.

    2005-01-01

    Our study used geostatistics to extract measures that characterize the spatial structure of vegetated landscapes from satellite imagery for mapping endangered Sonoran pronghorn habitat. Fine spatial resolution IKONOS data provided information at the scale of individual trees or shrubs that permitted analysis of vegetation structure and pattern. We derived images of landscape structure by calculating local estimates of the nugget, sill, and range variogram parameters within 25 ?? 25-m image windows. These variogram parameters, which describe the spatial autocorrelation of the 1-m image pixels, are shown in previous studies to discriminate between different species-specific vegetation associations. We constructed two independent models of pronghorn landscape preference by coupling the derived measures with Sonoran pronghorn sighting data: a distribution-based model and a cluster-based model. The distribution-based model used the descriptive statistics for variogram measures at pronghorn sightings, whereas the cluster-based model used the distribution of pronghorn sightings within clusters of an unsupervised classification of derived images. Both models define similar landscapes, and validation results confirm they effectively predict the locations of an independent set of pronghorn sightings. Such information, although not a substitute for field-based knowledge of the landscape and associated ecological processes, can provide valuable reconnaissance information to guide natural resource management efforts. ?? 2005 Taylor & Francis Group Ltd.

  1. Integrating address geocoding, land use regression, and spatiotemporal geostatistical estimation for groundwater tetrachloroethylene.

    Science.gov (United States)

    Messier, Kyle P; Akita, Yasuyuki; Serre, Marc L

    2012-03-06

    Geographic information systems (GIS) based techniques are cost-effective and efficient methods used by state agencies and epidemiology researchers for estimating concentration and exposure. However, budget limitations have made statewide assessments of contamination difficult, especially in groundwater media. Many studies have implemented address geocoding, land use regression, and geostatistics independently, but this is the first to examine the benefits of integrating these GIS techniques to address the need of statewide exposure assessments. A novel framework for concentration exposure is introduced that integrates address geocoding, land use regression (LUR), below detect data modeling, and Bayesian Maximum Entropy (BME). A LUR model was developed for tetrachloroethylene that accounts for point sources and flow direction. We then integrate the LUR model into the BME method as a mean trend while also modeling below detects data as a truncated Gaussian probability distribution function. We increase available PCE data 4.7 times from previously available databases through multistage geocoding. The LUR model shows significant influence of dry cleaners at short ranges. The integration of the LUR model as mean trend in BME results in a 7.5% decrease in cross validation mean square error compared to BME with a constant mean trend.

  2. Predicting polycyclic aromatic hydrocarbons using a mass fraction approach in a geostatistical framework across North Carolina.

    Science.gov (United States)

    Reyes, Jeanette M; Hubbard, Heidi F; Stiegel, Matthew A; Pleil, Joachim D; Serre, Marc L

    2018-01-09

    Currently in the United States there are no regulatory standards for ambient concentrations of polycyclic aromatic hydrocarbons (PAHs), a class of organic compounds with known carcinogenic species. As such, monitoring data are not routinely collected resulting in limited exposure mapping and epidemiologic studies. This work develops the log-mass fraction (LMF) Bayesian maximum entropy (BME) geostatistical prediction method used to predict the concentration of nine particle-bound PAHs across the US state of North Carolina. The LMF method develops a relationship between a relatively small number of collocated PAH and fine Particulate Matter (PM2.5) samples collected in 2005 and applies that relationship to a larger number of locations where PM2.5 is routinely monitored to more broadly estimate PAH concentrations across the state. Cross validation and mapping results indicate that by incorporating both PAH and PM2.5 data, the LMF BME method reduces mean squared error by 28.4% and produces more realistic spatial gradients compared to the traditional kriging approach based solely on observed PAH data. The LMF BME method efficiently creates PAH predictions in a PAH data sparse and PM2.5 data rich setting, opening the door for more expansive epidemiologic exposure assessments of ambient PAH.

  3. A Resampling-Based Stochastic Approximation Method for Analysis of Large Geostatistical Data

    KAUST Repository

    Liang, Faming

    2013-03-01

    The Gaussian geostatistical model has been widely used in modeling of spatial data. However, it is challenging to computationally implement this method because it requires the inversion of a large covariance matrix, particularly when there is a large number of observations. This article proposes a resampling-based stochastic approximation method to address this challenge. At each iteration of the proposed method, a small subsample is drawn from the full dataset, and then the current estimate of the parameters is updated accordingly under the framework of stochastic approximation. Since the proposed method makes use of only a small proportion of the data at each iteration, it avoids inverting large covariance matrices and thus is scalable to large datasets. The proposed method also leads to a general parameter estimation approach, maximum mean log-likelihood estimation, which includes the popular maximum (log)-likelihood estimation (MLE) approach as a special case and is expected to play an important role in analyzing large datasets. Under mild conditions, it is shown that the estimator resulting from the proposed method converges in probability to a set of parameter values of equivalent Gaussian probability measures, and that the estimator is asymptotically normally distributed. To the best of the authors\\' knowledge, the present study is the first one on asymptotic normality under infill asymptotics for general covariance functions. The proposed method is illustrated with large datasets, both simulated and real. Supplementary materials for this article are available online. © 2013 American Statistical Association.

  4. Geostatistical methods in the assessment of the spatial variability of the quality of river water

    Directory of Open Access Journals (Sweden)

    Krasowska Małgorzata

    2017-01-01

    Full Text Available The research was conducted in the agricultural catchment in north–eastern Poland. The aim of this study was to check how geostatistical analysis can be useful for the detection zones and forms of supply stream by water from different sources. The work was included the implementation of hydrochemical profiles. These profiles were made by measuring the electrical conductivity (EC values and temperature along the river. On the basis of these results, the authors calculated the coefficient of Moran I and performed semivariogram and found that the EC values are correlated on a stretch of about 140 m. This means that the spatial correlation between samples of water in the stream is readable over a distance of about 140 meters. Therefore it is believed that the degree of water mineralization on this section is shaped by water entering the river channel migration in different ways: through tributaries, leachate drainage and surface runoff. In the case of the analyzed catchment, the potential sources of pollution were drainage systems. Therefore, the spatial analysis allowed the identification pollution sources in a catchment, especially in drained agricultural catchments.

  5. A Bayesian spatio-temporal geostatistical model with an auxiliary lattice for large datasets

    KAUST Repository

    Xu, Ganggang

    2015-01-01

    When spatio-temporal datasets are large, the computational burden can lead to failures in the implementation of traditional geostatistical tools. In this paper, we propose a computationally efficient Bayesian hierarchical spatio-temporal model in which the spatial dependence is approximated by a Gaussian Markov random field (GMRF) while the temporal correlation is described using a vector autoregressive model. By introducing an auxiliary lattice on the spatial region of interest, the proposed method is not only able to handle irregularly spaced observations in the spatial domain, but it is also able to bypass the missing data problem in a spatio-temporal process. Because the computational complexity of the proposed Markov chain Monte Carlo algorithm is of the order O(n) with n the total number of observations in space and time, our method can be used to handle very large spatio-temporal datasets with reasonable CPU times. The performance of the proposed model is illustrated using simulation studies and a dataset of precipitation data from the coterminous United States.

  6. Improving imperfect data from health management information systems in Africa using space-time geostatistics.

    Directory of Open Access Journals (Sweden)

    Peter W Gething

    2006-06-01

    Full Text Available Reliable and timely information on disease-specific treatment burdens within a health system is critical for the planning and monitoring of service provision. Health management information systems (HMIS exist to address this need at national scales across Africa but are failing to deliver adequate data because of widespread underreporting by health facilities. Faced with this inadequacy, vital public health decisions often rely on crudely adjusted regional and national estimates of treatment burdens.This study has taken the example of presumed malaria in outpatients within the largely incomplete Kenyan HMIS database and has defined a geostatistical modelling framework that can predict values for all data that are missing through space and time. The resulting complete set can then be used to define treatment burdens for presumed malaria at any level of spatial and temporal aggregation. Validation of the model has shown that these burdens are quantified to an acceptable level of accuracy at the district, provincial, and national scale.The modelling framework presented here provides, to our knowledge for the first time, reliable information from imperfect HMIS data to support evidence-based decision-making at national and sub-national levels.

  7. Definition of radon prone areas in Friuli Venezia Giulia region, Italy, using geostatistical tools.

    Science.gov (United States)

    Cafaro, C; Bossew, P; Giovani, C; Garavaglia, M

    2014-12-01

    Studying the geographical distribution of indoor radon concentration, using geostatistical interpolation methods, has become common for predicting and estimating the risk to the population. Here we analyse the case of Friuli Venezia Giulia (FVG), the north easternmost region of Italy. Mean value and standard deviation are, respectively, 153 Bq/m(3) and 183 Bq/m(3). The geometric mean value is 100 Bq/m(3). Spatial datasets of indoor radon concentrations are usually affected by clustering and apparent non-stationarity issues, which can eventually yield arguable results. The clustering of the present dataset seems to be non preferential. Therefore the areal estimations are not expected to be affected. Conversely, nothing can be said on the non stationarity issues and its effects. After discussing the correlation of geology with indoor radon concentration It appears they are created by the same geologic features influencing the mean and median values, and can't be eliminated via a map-based approach. To tackle these problems, in this work we deal with multiple definitions of RPA, but only in quaternary areas of FVG, using extensive simulation techniques. Copyright © 2014 Elsevier Ltd. All rights reserved.

  8. Definition of radon prone areas in Friuli Venezia Giulia region, Italy, using geostatistical tools

    International Nuclear Information System (INIS)

    Cafaro, C.; Bossew, P.; Giovani, C.; Garavaglia, M.

    2014-01-01

    Studying the geographical distribution of indoor radon concentration, using geostatistical interpolation methods, has become common for predicting and estimating the risk to the population. Here we analyse the case of Friuli Venezia Giulia (FVG), the north easternmost region of Italy. Mean value and standard deviation are, respectively, 153 Bq/m 3 and 183 Bq/m 3 . The geometric mean value is 100 Bq/m 3 . Spatial datasets of indoor radon concentrations are usually affected by clustering and apparent non-stationarity issues, which can eventually yield arguable results. The clustering of the present dataset seems to be non preferential. Therefore the areal estimations are not expected to be affected. Conversely, nothing can be said on the non stationarity issues and its effects. After discussing the correlation of geology with indoor radon concentration It appears they are created by the same geologic features influencing the mean and median values, and can't be eliminated via a map-based approach. To tackle these problems, in this work we deal with multiple definitions of RPA, but only in quaternary areas of FVG, using extensive simulation techniques. - Highlights: • The data are clustered in a preferential way, but natural clustering renders preferentiality undetectable. • Different soil classes lead to different variograms, then the database is divided to improve predictions. • The geological classes do not improve the quality of prediction more than a quadratic drift and yield arguable results. • Simulation conditioned by kriging are used to solve the change of support problem

  9. Assessment of groundwater and soil quality degradation using multivariate and geostatistical analyses, Dakhla Oasis, Egypt

    Science.gov (United States)

    Masoud, Alaa A.; El-Horiny, Mohamed M.; Atwia, Mohamed G.; Gemail, Khaled S.; Koike, Katsuaki

    2018-06-01

    Salinization of groundwater and soil resources has long been a serious environmental hazard in arid regions. This study was conducted to investigate and document the factors controlling such salinization and their inter-relationships in the Dakhla Oasis (Egypt). To accomplish this, 60 groundwater samples and 31 soil samples were collected in February 2014. Factor analysis (FA) and hierarchical cluster analysis (HCA) were integrated with geostatistical analyses to characterize the chemical properties of groundwater and soil and their spatial patterns, identify the factors controlling the pattern variability, and clarify the salinization mechanism. Groundwater quality standards revealed emergence of salinization (av. 885.8 mg/L) and extreme occurrences of Fe2+ (av. 17.22 mg/L) and Mn2+ (av. 2.38 mg/L). Soils were highly salt-affected (av. 15.2 dS m-1) and slightly alkaline (av. pH = 7.7). Evaporation and ion-exchange processes governed the evolution of two main water types: Na-Cl (52%) and Ca-Mg-Cl (47%), respectively. Salinization leads the chemical variability of both resources. Distinctive patterns of slight salinization marked the northern part and intense salinization marked the middle and southern parts. Congruence in the resources clusters confirmed common geology, soil types, and urban and agricultural practices. Minimizing the environmental and socioeconomic impacts of the resources salinization urges the need for better understanding of the hydrochemical characteristics and prediction of quality changes.

  10. Confronting uncertainty in model-based geostatistics using Markov Chain Monte Carlo simulation

    NARCIS (Netherlands)

    Minasny, B.; Vrugt, J.A.; McBratney, A.B.

    2011-01-01

    This paper demonstrates for the first time the use of Markov Chain Monte Carlo (MCMC) simulation for parameter inference in model-based soil geostatistics. We implemented the recently developed DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm to jointly summarize the posterior

  11. Geostatistics and multivariate analysis as a tool to characterize volcaniclastic deposits: Application to Nevado de Toluca volcano, Mexico

    Science.gov (United States)

    Bellotti, F.; Capra, L.; Sarocchi, D.; D'Antonio, M.

    2010-03-01

    Grain size analysis of volcaniclastic deposits is mainly used to study flow transport and depositional processes, in most cases by comparing some statistical parameters and how they change with distance from the source. In this work the geospatial and multivariate analyses are presented as a strong adaptable geostatistical tool applied to volcaniclastic deposits in order to provide an effective and relatively simple methodology for texture description, deposit discrimination and interpretation of depositional processes. We choose the case of Nevado de Toluca volcano (Mexico) due to existing knowledge of its geological evolution, stratigraphic succession and spatial distribution of volcaniclastic units. Grain size analyses and frequency distribution curves have been carried out to characterize and compare the 28-ka block-and-ash flow deposit associated to a dome destruction episode, and the El Morral debris avalanche deposit originated from the collapse of the south-eastern sector of the volcano. The geostatistical interpolation of sedimentological data allows to realize bidimensional maps draped over the volcano topography, showing the granulometric distribution, sorting and fine material concentration into the whole deposit with respect to topographic changes. In this way, it is possible to analyze a continuous surface of the grain size distribution of volcaniclastic deposits and better understand flow transport processes. The application of multivariate statistic analysis (discriminant function) indicates that this methodology could be useful in discriminating deposits with different origin or different depositional lithofacies within the same deposit. The proposed methodology could be an interesting approach to sustain more classical analysis of volcaniclastic deposits, especially where a clear field classification appears problematic because of a homogeneous texture of the deposits or their scarce and discontinuous outcrops. Our study is an example of the

  12. Geostatistical estimation of forest biomass in interior Alaska combining Landsat-derived tree cover, sampled airborne lidar and field observations

    Science.gov (United States)

    Babcock, Chad; Finley, Andrew O.; Andersen, Hans-Erik; Pattison, Robert; Cook, Bruce D.; Morton, Douglas C.; Alonzo, Michael; Nelson, Ross; Gregoire, Timothy; Ene, Liviu; Gobakken, Terje; Næsset, Erik

    2018-06-01

    The goal of this research was to develop and examine the performance of a geostatistical coregionalization modeling approach for combining field inventory measurements, strip samples of airborne lidar and Landsat-based remote sensing data products to predict aboveground biomass (AGB) in interior Alaska's Tanana Valley. The proposed modeling strategy facilitates pixel-level mapping of AGB density predictions across the entire spatial domain. Additionally, the coregionalization framework allows for statistically sound estimation of total AGB for arbitrary areal units within the study area---a key advance to support diverse management objectives in interior Alaska. This research focuses on appropriate characterization of prediction uncertainty in the form of posterior predictive coverage intervals and standard deviations. Using the framework detailed here, it is possible to quantify estimation uncertainty for any spatial extent, ranging from pixel-level predictions of AGB density to estimates of AGB stocks for the full domain. The lidar-informed coregionalization models consistently outperformed their counterpart lidar-free models in terms of point-level predictive performance and total AGB precision. Additionally, the inclusion of Landsat-derived forest cover as a covariate further improved estimation precision in regions with lower lidar sampling intensity. Our findings also demonstrate that model-based approaches that do not explicitly account for residual spatial dependence can grossly underestimate uncertainty, resulting in falsely precise estimates of AGB. On the other hand, in a geostatistical setting, residual spatial structure can be modeled within a Bayesian hierarchical framework to obtain statistically defensible assessments of uncertainty for AGB estimates.

  13. Geostatistical validation and cross-validation of magnetometric measurements of soil pollution with Potentially Toxic Elements in problematic areas

    Science.gov (United States)

    Fabijańczyk, Piotr; Zawadzki, Jarosław

    2016-04-01

    Field magnetometry is fast method that was previously effectively used to assess the potential soil pollution. One of the most popular devices that are used to measure the soil magnetic susceptibility on the soil surface is a MS2D Bartington. Single reading using MS2D device of soil magnetic susceptibility is low time-consuming but often characterized by considerable errors related to the instrument or environmental and lithogenic factors. In this connection, measured values of soil magnetic susceptibility have to be usually validated using more precise, but also much more expensive, chemical measurements. The goal of this study was to analyze validation methods of magnetometric measurements using chemical analyses of a concentration of elements in soil. Additionally, validation of surface measurements of soil magnetic susceptibility was performed using selected parameters of a distribution of magnetic susceptibility in a soil profile. Validation was performed using selected geostatistical measures of cross-correlation. The geostatistical approach was compared with validation performed using the classic statistics. Measurements were performed at selected areas located in the Upper Silesian Industrial Area in Poland, and in the selected parts of Norway. In these areas soil magnetic susceptibility was measured on the soil surface using a MS2D Bartington device and in the soil profile using MS2C Bartington device. Additionally, soil samples were taken in order to perform chemical measurements. Acknowledgment The research leading to these results has received funding from the Polish-Norwegian Research Programme operated by the National Centre for Research and Development under the Norwegian Financial Mechanism 2009-2014 in the frame of Project IMPACT - Contract No Pol-Nor/199338/45/2013.

  14. Sampling design optimisation for rainfall prediction using a non-stationary geostatistical model

    Science.gov (United States)

    Wadoux, Alexandre M. J.-C.; Brus, Dick J.; Rico-Ramirez, Miguel A.; Heuvelink, Gerard B. M.

    2017-09-01

    The accuracy of spatial predictions of rainfall by merging rain-gauge and radar data is partly determined by the sampling design of the rain-gauge network. Optimising the locations of the rain-gauges may increase the accuracy of the predictions. Existing spatial sampling design optimisation methods are based on minimisation of the spatially averaged prediction error variance under the assumption of intrinsic stationarity. Over the past years, substantial progress has been made to deal with non-stationary spatial processes in kriging. Various well-documented geostatistical models relax the assumption of stationarity in the mean, while recent studies show the importance of considering non-stationarity in the variance for environmental processes occurring in complex landscapes. We optimised the sampling locations of rain-gauges using an extension of the Kriging with External Drift (KED) model for prediction of rainfall fields. The model incorporates both non-stationarity in the mean and in the variance, which are modelled as functions of external covariates such as radar imagery, distance to radar station and radar beam blockage. Spatial predictions are made repeatedly over time, each time recalibrating the model. The space-time averaged KED variance was minimised by Spatial Simulated Annealing (SSA). The methodology was tested using a case study predicting daily rainfall in the north of England for a one-year period. Results show that (i) the proposed non-stationary variance model outperforms the stationary variance model, and (ii) a small but significant decrease of the rainfall prediction error variance is obtained with the optimised rain-gauge network. In particular, it pays off to place rain-gauges at locations where the radar imagery is inaccurate, while keeping the distribution over the study area sufficiently uniform.

  15. Geostatistical Analyses of Soil Organic Carbon Concentrations in Aligodarz Watershed, Lorestan Province

    Directory of Open Access Journals (Sweden)

    Masoud Davari

    2017-01-01

    Full Text Available Introduction: Soil organic carbon (SOC has great impacts on soil properties, soil productivity, food security, land degradation and global warming. Similar to other soil properties, SOC has a strong spatial heterogeneity as a result of dynamic interactions between parent material, climate and geological history, at both regional and continental scales. However, landscape attributes including slope, aspect, altitude, and land use types are dominant factors influencing on SOC in areas with the same parent materials and climate regime. Understanding and identifying the spatial and temporal distribution of SOC is essential to evaluate soil quality, agricultural management, watershed modeling and soil carbon sequestration budgets. Therefore, the objectives of this study was to estimate soil organic carbon content in the Aligodarz watershed, and to investigate the effects of altitude, slope, and land use type on SOC. Materials and Methods: The research was carried out in the Aligodraz watershed in Lorestan province of Iran. The study area is located between latitudes N 33° 10' 51.72"to N 33° 34' 28.22" and longitudes E 49° 27' 17.99"to E 49° 58' 40.84" 14 that covers an area of 1078.9 km2. It has an altitude between 1866.3 and 3200 m above sea-level. The primary land uses within the watershed include pasture, dryland and irrigated farming. In this study, soil samples were randomly collected from 206 sites at depth of 0– 15 cm during June and August 2003. The mean distance between samples was about 5 km. Soil samples were air-dried in the shade for about 7 days and then passed through a 0.25 mm prior to determination of SOC. Soil organic carbon content was determined in triplicate for each sample using the Walkey-Black method. Basic statistical analyses for frequency distribution, normality tests, Pearson's correlation and analysis of variance were conducted using SPSS (version 18.0. Calculation of experimental variograms and modeling of spatial

  16. Use of geostatistic techniques to describe a reservoir to be submitted into a secondary recovery process field case: {open_quotes}Eocene B-Inferior/VLG-3659, Ceuta, Venezuela{close_quotes}

    Energy Technology Data Exchange (ETDEWEB)

    Hernandez, T.; Poquioma, W. [Maraven, S.A., Caracas (Venezuela)

    1997-08-01

    This study presents the results of an integrated reservoir study of the Eocene B-Inferior/VLG-3659, Area 7, Ceuta filed. This field located in the Maracaibo Lake in the western side of Venezuela. The objective was to evaluating the feasibility to implement a secondary recovery project by means of water flooding. Core information was used for this study (194 ft), PVT analysis, RFI, build-up and statistic`s pressure analysis, modem logs and production history data. Using geostatistical techniques (Kriging) it was defined a low uncertainty geological model that was validated by means of a black oil simulator (Eclipse). The results showed a good comparison of historical pressure of the reservoir against those obtained from the model, without the need of {open_quotes}history matching{close_quotes}. It means without modifying neither the initial rock properties nor reservoir fluids. The results of this study recommended drilling in two new locations, also the reactivation of four producing wells and water flooding under peripherical array by means of four injection wells, with the recovery of an additional 30.2 MMSTB. The economical evaluation shows an internal return rate of 31.4%.

  17. A Geostatistical Toolset for Reconstructing Louisiana's Coastal Stratigraphy using Subsurface Boring and Cone Penetrometer Test Data

    Science.gov (United States)

    Li, A.; Tsai, F. T. C.; Jafari, N.; Chen, Q. J.; Bentley, S. J.

    2017-12-01

    A vast area of river deltaic wetlands stretches across southern Louisiana coast. The wetlands are suffering from a high rate of land loss, which increasingly threats coastal community and energy infrastructure. A regional stratigraphic framework of the delta plain is now imperative to answer scientific questions (such as how the delta plain grows and decays?) and to provide information to coastal protection and restoration projects (such as marsh creation and construction of levees and floodwalls). Through years, subsurface investigations in Louisiana have been conducted by state and federal agencies (Louisiana Department of Natural Resources, United States Geological Survey, United States Army Corps of Engineers, etc.), research institutes (Louisiana Geological Survey, LSU Coastal Studies Institute, etc.), engineering firms, and oil-gas companies. This has resulted in the availability of various types of data, including geological, geotechnical, and geophysical data. However, it is challenging to integrate different types of data and construct three-dimensional stratigraphy models in regional scale. In this study, a set of geostatistical methods were used to tackle this problem. An ordinary kriging method was used to regionalize continuous data, such as grain size, water content, liquid limit, plasticity index, and cone penetrometer tests (CPTs). Indicator kriging and multiple indicator kriging methods were used to regionalize categorized data, such as soil classification. A compositional kriging method was used to regionalize compositional data, such as soil composition (fractions of sand, silt and clay). Stratigraphy models were constructed for three cases in the coastal zone: (1) Inner Harbor Navigation Canal (IHNC) area: soil classification and soil behavior type (SBT) stratigraphies were constructed using ordinary kriging; (2) Middle Barataria Bay area: a soil classification stratigraphy was constructed using multiple indicator kriging; (3) Lower Barataria

  18. Geostatistical investigation into the temporal evolution of spatial structure in a shallow water table

    Directory of Open Access Journals (Sweden)

    S. W. Lyon

    2006-01-01

    Full Text Available Shallow water tables near-streams often lead to saturated, overland flow generating areas in catchments in humid climates. While these saturated areas are assumed to be principal biogeochemical hot-spots and important for issues such as non-point pollution sources, the spatial and temporal behavior of shallow water tables, and associated saturated areas, is not completely understood. This study demonstrates how geostatistical methods can be used to characterize the spatial and temporal variation of the shallow water table for the near-stream region. Event-based and seasonal changes in the spatial structure of the shallow water table, which influences the spatial pattern of surface saturation and related runoff generation, can be identified and used in conjunction to characterize the hydrology of an area. This is accomplished through semivariogram analysis and indicator kriging to produce maps combining soft data (i.e., proxy information to the variable of interest representing general shallow water table patterns with hard data (i.e., actual measurements that represent variation in the spatial structure of the shallow water table per rainfall event. The area used was a hillslope in the Catskill Mountains region of New York State. The shallow water table was monitored for a 120 m×180 m near-stream region at 44 sampling locations on 15-min intervals. Outflow of the area was measured at the same time interval. These data were analyzed at a short time interval (15 min and at a long time interval (months to characterize the changes in the hydrologic behavior of the hillslope. Indicator semivariograms based on binary-transformed ground water table data (i.e., 1 if exceeding the time-variable median depth to water table and 0 if not were created for both short and long time intervals. For the short time interval, the indicator semivariograms showed a high degree of spatial structure in the shallow water table for the spring, with increased range

  19. Geostatistical interpolation model selection based on ArcGIS and spatio-temporal variability analysis of groundwater level in piedmont plains, northwest China.

    Science.gov (United States)

    Xiao, Yong; Gu, Xiaomin; Yin, Shiyang; Shao, Jingli; Cui, Yali; Zhang, Qiulan; Niu, Yong

    2016-01-01

    Based on the geo-statistical theory and ArcGIS geo-statistical module, datas of 30 groundwater level observation wells were used to estimate the decline of groundwater level in Beijing piedmont. Seven different interpolation methods (inverse distance weighted interpolation, global polynomial interpolation, local polynomial interpolation, tension spline interpolation, ordinary Kriging interpolation, simple Kriging interpolation and universal Kriging interpolation) were used for interpolating groundwater level between 2001 and 2013. Cross-validation, absolute error and coefficient of determination (R(2)) was applied to evaluate the accuracy of different methods. The result shows that simple Kriging method gave the best fit. The analysis of spatial and temporal variability suggest that the nugget effects from 2001 to 2013 were increasing, which means the spatial correlation weakened gradually under the influence of human activities. The spatial variability in the middle areas of the alluvial-proluvial fan is relatively higher than area in top and bottom. Since the changes of the land use, groundwater level also has a temporal variation, the average decline rate of groundwater level between 2007 and 2013 increases compared with 2001-2006. Urban development and population growth cause over-exploitation of residential and industrial areas. The decline rate of the groundwater level in residential, industrial and river areas is relatively high, while the decreasing of farmland area and development of water-saving irrigation reduce the quantity of water using by agriculture and decline rate of groundwater level in agricultural area is not significant.

  20. Geostatistical analyses and hazard assessment on soil lead in Silvermines area, Ireland

    International Nuclear Information System (INIS)

    McGrath, David; Zhang Chaosheng; Carton, Owen T.

    2004-01-01

    Spatial distribution and hazard assessment of soil lead in the mining site of Silvermines, Ireland, were investigated using statistics, geostatistics and geographic information system (GIS) techniques. Positively skewed distribution and possible outlying values of Pb and other heavy metals were observed. Box-Cox transformation was applied in order to achieve normality in the data set and to reduce the effect of outliers. Geostatistical analyses were carried out, including calculation of experimental variograms and model fitting. The ordinary point kriging estimates of Pb concentration were mapped. Kriging standard deviations were regarded as the standard deviations of the interpolated pixel values, and a second map was produced, that quantified the probability of Pb concentration higher than a threshold value of 1000 mg/kg. These maps provide valuable information for hazard assessment and for decision support. - A probability map was produced that was useful for hazard assessment and decision support

  1. Geostatistical analyses and hazard assessment on soil lead in Silvermines area, Ireland

    Energy Technology Data Exchange (ETDEWEB)

    McGrath, David; Zhang Chaosheng; Carton, Owen T

    2004-01-01

    Spatial distribution and hazard assessment of soil lead in the mining site of Silvermines, Ireland, were investigated using statistics, geostatistics and geographic information system (GIS) techniques. Positively skewed distribution and possible outlying values of Pb and other heavy metals were observed. Box-Cox transformation was applied in order to achieve normality in the data set and to reduce the effect of outliers. Geostatistical analyses were carried out, including calculation of experimental variograms and model fitting. The ordinary point kriging estimates of Pb concentration were mapped. Kriging standard deviations were regarded as the standard deviations of the interpolated pixel values, and a second map was produced, that quantified the probability of Pb concentration higher than a threshold value of 1000 mg/kg. These maps provide valuable information for hazard assessment and for decision support. - A probability map was produced that was useful for hazard assessment and decision support.

  2. Geostatistical simulations for radon indoor with a nested model including the housing factor.

    Science.gov (United States)

    Cafaro, C; Giovani, C; Garavaglia, M

    2016-01-01

    The radon prone areas definition is matter of many researches in radioecology, since radon is considered a leading cause of lung tumours, therefore the authorities ask for support to develop an appropriate sanitary prevention strategy. In this paper, we use geostatistical tools to elaborate a definition accounting for some of the available information about the dwellings. Co-kriging is the proper interpolator used in geostatistics to refine the predictions by using external covariates. In advance, co-kriging is not guaranteed to improve significantly the results obtained by applying the common lognormal kriging. Here, instead, such multivariate approach leads to reduce the cross-validation residual variance to an extent which is deemed as satisfying. Furthermore, with the application of Monte Carlo simulations, the paradigm provides a more conservative radon prone areas definition than the one previously made by lognormal kriging. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. A geostatistical estimation of zinc grade in bore-core samples

    International Nuclear Information System (INIS)

    Starzec, A.

    1987-01-01

    Possibilities and preliminary results of geostatistical interpretation of the XRF determination of zinc in bore-core samples are considered. For the spherical model of the variogram the estimation variance of grade in a disk-shape sample (estimated from the grade on the circumference sample) is calculated. Variograms of zinc grade in core samples are presented and examples of the grade estimation are discussed. 4 refs., 7 figs., 1 tab. (author)

  4. Determining site-specific background level with geostatistics for remediation of heavy metals in neighborhood soils

    OpenAIRE

    Tammy M. Milillo; Gaurav Sinha; Joseph A. Gardella Jr.

    2017-01-01

    The choice of a relevant, uncontaminated site for the determination of site-specific background concentrations for pollutants is critical for planning remediation of a contaminated site. The guidelines used to arrive at concentration levels vary from state to state, complicating this process. The residential neighborhood of Hickory Woods in Buffalo, NY is an area where heavy metal concentrations and spatial distributions were measured to plan remediation. A novel geostatistics based decision ...

  5. Assessment of heterogeneous geological environment using geostatistical techniques

    International Nuclear Information System (INIS)

    Toida, Masaru; Suyama, Yasuhiro; Shiogama, Yukihiro; Atsumi, Hiroyuki; Abe, Yasunori; Furuichi, Mitsuaki

    2003-02-01

    'Geoscientific' research at Tono are developing site investigation and assessment techniques in geological environment. One of their important themes is to establish rational methodology to reduce uncertainties associated with the understanding of geological environment, which often exhibits significant heterogeneity. Purpose of this study is to identify and evaluate uncertainties associated with the understanding of geological environment. Because it is useful to guide designing effective site investigation techniques to reduce the uncertainty. For this, a methodology of the uncertainty analysis concerning the heterogeneous geological environment has been developed. In this report the methodology has also been tested through an exercise attempted in Tono area to demonstrate its applicability. This report summarizes as follows: 1) The exercise shows that the methodology considered 'variability' and 'ignorance' can demonstrate its applicability at three-dimensional case. 2) The exercise shows that the methodology can identity and evaluate uncertainties concerning ground water flow associated with performance assessment. 3) Based on sensitivity analyses, it is possible for the methodology to support designs of the following stage investigations to reduce the uncertainties efficiently. (author)

  6. Spatial Downscaling of TRMM Precipitation Using Geostatistics and Fine Scale Environmental Variables

    Directory of Open Access Journals (Sweden)

    No-Wook Park

    2013-01-01

    Full Text Available A geostatistical downscaling scheme is presented and can generate fine scale precipitation information from coarse scale Tropical Rainfall Measuring Mission (TRMM data by incorporating auxiliary fine scale environmental variables. Within the geostatistical framework, the TRMM precipitation data are first decomposed into trend and residual components. Quantitative relationships between coarse scale TRMM data and environmental variables are then estimated via regression analysis and used to derive trend components at a fine scale. Next, the residual components, which are the differences between the trend components and the original TRMM data, are then downscaled at a target fine scale via area-to-point kriging. The trend and residual components are finally added to generate fine scale precipitation estimates. Stochastic simulation is also applied to the residual components in order to generate multiple alternative realizations and to compute uncertainty measures. From an experiment using a digital elevation model (DEM and normalized difference vegetation index (NDVI, the geostatistical downscaling scheme generated the downscaling results that reflected detailed characteristics with better predictive performance, when compared with downscaling without the environmental variables. Multiple realizations and uncertainty measures from simulation also provided useful information for interpretations and further environmental modeling.

  7. Geostatistical integration and uncertainty in pollutant concentration surface under preferential sampling

    Directory of Open Access Journals (Sweden)

    Laura Grisotto

    2016-04-01

    Full Text Available In this paper the focus is on environmental statistics, with the aim of estimating the concentration surface and related uncertainty of an air pollutant. We used air quality data recorded by a network of monitoring stations within a Bayesian framework to overcome difficulties in accounting for prediction uncertainty and to integrate information provided by deterministic models based on emissions meteorology and chemico-physical characteristics of the atmosphere. Several authors have proposed such integration, but all the proposed approaches rely on representativeness and completeness of existing air pollution monitoring networks. We considered the situation in which the spatial process of interest and the sampling locations are not independent. This is known in the literature as the preferential sampling problem, which if ignored in the analysis, can bias geostatistical inferences. We developed a Bayesian geostatistical model to account for preferential sampling with the main interest in statistical integration and uncertainty. We used PM10 data arising from the air quality network of the Environmental Protection Agency of Lombardy Region (Italy and numerical outputs from the deterministic model. We specified an inhomogeneous Poisson process for the sampling locations intensities and a shared spatial random component model for the dependence between the spatial location of monitors and the pollution surface. We found greater predicted standard deviation differences in areas not properly covered by the air quality network. In conclusion, in this context inferences on prediction uncertainty may be misleading when geostatistical modelling does not take into account preferential sampling.

  8. Geostatistical modelling of soil-transmitted helminth infection in Cambodia: do socioeconomic factors improve predictions?

    Science.gov (United States)

    Karagiannis-Voules, Dimitrios-Alexios; Odermatt, Peter; Biedermann, Patricia; Khieu, Virak; Schär, Fabian; Muth, Sinuon; Utzinger, Jürg; Vounatsou, Penelope

    2015-01-01

    Soil-transmitted helminth infections are intimately connected with poverty. Yet, there is a paucity of using socioeconomic proxies in spatially explicit risk profiling. We compiled household-level socioeconomic data pertaining to sanitation, drinking-water, education and nutrition from readily available Demographic and Health Surveys, Multiple Indicator Cluster Surveys and World Health Surveys for Cambodia and aggregated the data at village level. We conducted a systematic review to identify parasitological surveys and made every effort possible to extract, georeference and upload the data in the open source Global Neglected Tropical Diseases database. Bayesian geostatistical models were employed to spatially align the village-aggregated socioeconomic predictors with the soil-transmitted helminth infection data. The risk of soil-transmitted helminth infection was predicted at a grid of 1×1km covering Cambodia. Additionally, two separate individual-level spatial analyses were carried out, for Takeo and Preah Vihear provinces, to assess and quantify the association between soil-transmitted helminth infection and socioeconomic indicators at an individual level. Overall, we obtained socioeconomic proxies from 1624 locations across the country. Surveys focussing on soil-transmitted helminth infections were extracted from 16 sources reporting data from 238 unique locations. We found that the risk of soil-transmitted helminth infection from 2000 onwards was considerably lower than in surveys conducted earlier. Population-adjusted prevalences for school-aged children from 2000 onwards were 28.7% for hookworm, 1.5% for Ascaris lumbricoides and 0.9% for Trichuris trichiura. Surprisingly, at the country-wide analyses, we did not find any significant association between soil-transmitted helminth infection and village-aggregated socioeconomic proxies. Based also on the individual-level analyses we conclude that socioeconomic proxies might not be good predictors at an

  9. Strategies for Evaluating a Freshman Studies Program.

    Science.gov (United States)

    Ketkar, Kusum; Bennett, Shelby D.

    1989-01-01

    The study developed an economic model for the evaluation of Seaton Hall University's freshman studies program. Two techniques used to evaluate the economic success of the program are break-even analysis and elasticity coefficient. (Author/MLW)

  10. Geostatistical and GIS analysis of the spatial variability of alluvial gold content in Ngoura-Colomines area, Eastern Cameroon: Implications for the exploration of primary gold deposit

    Science.gov (United States)

    Takodjou Wambo, Jonas Didero; Ganno, Sylvestre; Djonthu Lahe, Yannick Sthopira; Kouankap Nono, Gus Djibril; Fossi, Donald Hermann; Tchouatcha, Milan Stafford; Nzenti, Jean Paul

    2018-06-01

    Linear and nonlinear geostatistic is commonly used in ore grade estimation and seldom used in Geographical Information System (GIS) technology. In this study, we suggest an approach based on geostatistic linear ordinary kriging (OK) and Geographical Information System (GIS) techniques to investigate the spatial distribution of alluvial gold content, mineralized and gangue layers thicknesses from 73 pits at the Ngoura-Colomines area with the aim to determine controlling factors for the spatial distribution of mineralization and delineate the most prospective area for primary gold mineralization. Gold content varies between 0.1 and 4.6 g/m3 and has been broadly grouped into three statistical classes. These classes have been spatially subdivided into nine zones using ordinary kriging model based on physical and topographical characteristics. Both mineralized and barren layer thicknesses show randomly spatial distribution, and there is no correlation between these parameters and the gold content. This approach has shown that the Ngoura-Colomines area is located in a large shear zone compatible with the Riedel fault system composed of P and P‧ fractures oriented NE-SW and NNE-SSW respectively; E-W trending R fractures and R‧ fractures with NW-SE trends that could have contributed significantly to the establishment of this gold mineralization. The combined OK model and GIS analysis have led to the delineation of Colomines, Tissongo, Madubal and Boutou villages as the most prospective areas for the exploration of primary gold deposit in the study area.

  11. Uncertainty Estimate in Resources Assessment: A Geostatistical Contribution

    International Nuclear Information System (INIS)

    Souza, Luis Eduardo de; Costa, Joao Felipe C. L.; Koppe, Jair C.

    2004-01-01

    For many decades the mining industry regarded resources/reserves estimation and classification as a mere calculation requiring basic mathematical and geological knowledge. Most methods were based on geometrical procedures and spatial data distribution. Therefore, uncertainty associated with tonnages and grades either were ignored or mishandled, although various mining codes require a measure of confidence in the values reported. Traditional methods fail in reporting the level of confidence in the quantities and grades. Conversely, kriging is known to provide the best estimate and its associated variance. Among kriging methods, Ordinary Kriging (OK) probably is the most widely used one for mineral resource/reserve estimation, mainly because of its robustness and its facility in uncertainty assessment by using the kriging variance. It also is known that OK variance is unable to recognize local data variability, an important issue when heterogeneous mineral deposits with higher and poorer grade zones are being evaluated. Alternatively, stochastic simulation are used to build local or global uncertainty about a geological attribute respecting its statistical moments. This study investigates methods capable of incorporating uncertainty to the estimates of resources and reserves via OK and sequential gaussian and sequential indicator simulation The results showed that for the type of mineralization studied all methods classified the tonnages similarly. The methods are illustrated using an exploration drill hole data sets from a large Brazilian coal deposit

  12. Diagnostic techniques applied in geostatistics for agricultural data analysis Técnicas de diagnóstico utilizadas em geoestatística para análise de dados agrícolas

    Directory of Open Access Journals (Sweden)

    Joelmir André Borssoi

    2009-12-01

    Full Text Available The structural modeling of spatial dependence, using a geostatistical approach, is an indispensable tool to determine parameters that define this structure, applied on interpolation of values at unsampled points by kriging techniques. However, the estimation of parameters can be greatly affected by the presence of atypical observations in sampled data. The purpose of this study was to use diagnostic techniques in Gaussian spatial linear models in geostatistics to evaluate the sensitivity of maximum likelihood and restrict maximum likelihood estimators to small perturbations in these data. For this purpose, studies with simulated and experimental data were conducted. Results with simulated data showed that the diagnostic techniques were efficient to identify the perturbation in data. The results with real data indicated that atypical values among the sampled data may have a strong influence on thematic maps, thus changing the spatial dependence structure. The application of diagnostic techniques should be part of any geostatistical analysis, to ensure a better quality of the information from thematic maps.A modelagem da estrutura de dependência espacial pela abordagem da geoestatística é de fundamental importância para a definição de parâmetros que definem essa estrutura e que são utilizados na interpolação de valores em locais não amostrados, pela técnica de krigagem. Entretanto, a estimação de parâmetros pode ser muito alterada pela presença de observações atípicas nos dados amostrados. O desenvolvimento deste trabalho teve por objetivo utilizar técnicas de diagnóstico em modelos espaciais lineares gaussianos, empregados em geoestatística, para avaliar a sensibilidade dos estimadores de máxima verossimilhança e máxima verossimilhança restrita a pequenas perturbações nos dados. Foram realizados estudos de dados simulados e experimentais. O estudo com dados simulados mostrou que as técnicas de diagnóstico foram

  13. Geostatistical characterization of the Callovo-Oxfordian clay variability: from conventional and high resolution log data

    International Nuclear Information System (INIS)

    Lefranc, Marie

    2007-01-01

    Andra (National Radioactive Waste Management Agency) has conducted studies in its Meuse/Haute-Marne Underground Research Laboratory located at a depth of about 490 m in a 155-million-year-old argillaceous rock: the Callovo-Oxfordian argillite. The purpose of the present work is to obtain as much information as possible from high-resolution log data and to optimize their analysis to specify and characterize space-time variations of the argillites from the Meuse/Haute-Marne site and subsequently predict the evolution of argillite properties on a 250 km 2 zone around the underground laboratory (transposition zone). The aim is to outline a methodology to transform depth intervals into geological time intervals and thus to quantify precisely the sedimentation rate variation, estimate duration; for example the duration of bio-stratigraphical units or of hiatuses. The latter point is particularly important because a continuous time recording is often assumed in geological modelling. The spatial variations can be studied on various scales. First, well-to-well correlations are established between seven wells at different scales. Relative variations of the thickness are observed locally. Second, FMI (Full-bore Formation Micro-Imager, Schlumberger) data are studied in detail to extract as much information as possible. For example, the analysis of FMI images reveals a clear carbonate - clay inter-bedding which displays cycles. Third, geostatistical tools are used to study these cycles. The vario-graphic analysis of conventional log data shows one metre cycles. With FMI data, smaller periods can be detected. Variogram modelling and factorial kriging analysis suggest that three spatial periods exist. They vary vertically and laterally in the boreholes but cycle ratios are stable and similar to orbital-cycle ratios (Milankovitch cycles). The three periods correspond to eccentricity, obliquity and precession. Since the duration of these orbital cycles is known, depth intervals can

  14. Potential of deterministic and geostatistical rainfall interpolation under high rainfall variability and dry spells: case of Kenya's Central Highlands

    Science.gov (United States)

    Kisaka, M. Oscar; Mucheru-Muna, M.; Ngetich, F. K.; Mugwe, J.; Mugendi, D.; Mairura, F.; Shisanya, C.; Makokha, G. L.

    2016-04-01

    Drier parts of Kenya's Central Highlands endure persistent crop failure and declining agricultural productivity. These have, in part, attributed to high temperatures, prolonged dry spells and erratic rainfall. Understanding spatial-temporal variability of climatic indices such as rainfall at seasonal level is critical for optimal rain-fed agricultural productivity and natural resource management in the study area. However, the predominant setbacks in analysing hydro-meteorological events are occasioned by either lack, inadequate, or inconsistent meteorological data. Like in most other places, the sole sources of climatic data in the study region are scarce and only limited to single stations, yet with persistent missing/unrecorded data making their utilization a challenge. This study examined seasonal anomalies and variability in rainfall, drought occurrence and the efficacy of interpolation techniques in the drier regions of eastern Kenyan. Rainfall data from five stations (Machang'a, Kiritiri, Kiambere and Kindaruma and Embu) were sourced from both the Kenya Meteorology Department and on-site primary recording. Owing to some experimental work ongoing, automated recording for primary dailies in Machang'a have been ongoing since the year 2000 to date; thus, Machang'a was treated as reference (for period of record) station for selection of other stations in the region. The other stations had data sets of over 15 years with missing data of less than 10 % as required by the world meteorological organization whose quality check is subject to the Centre for Climate Systems Modeling (C2SM) through MeteoSwiss and EMPA bodies. The dailies were also subjected to homogeneity testing to evaluate whether they came from the same population. Rainfall anomaly index, coefficients of variance and probability were utilized in the analyses of rainfall variability. Spline, kriging and inverse distance weighting interpolation techniques were assessed using daily rainfall data and

  15. Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

    Science.gov (United States)

    Manzione, Rodrigo L.; Wendland, Edson; Tanikawa, Diego H.

    2012-11-01

    Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

  16. Geostatistical estimates of future recharge for the Death Valley region

    International Nuclear Information System (INIS)

    Hevesi, J.A.; Flint, A.L.

    1998-01-01

    Spatially distributed estimates of regional ground water recharge rates under both current and potential future climates are needed to evaluate a potential geologic repository for high-level nuclear waste at Yucca Mountain, Nevada, which is located within the Death Valley ground-water region (DVGWR). Determining the spatial distribution of recharge is important for regional saturated-zone ground-water flow models. In the southern Nevada region, the Maxey-Eakin method has been used for estimating recharge based on average annual precipitation. Although this method does not directly account for a variety of location-specific factors which control recharge (such as bedrock permeability, soil cover, and net radiation), precipitation is the primary factor that controls in the region. Estimates of recharge obtained by using the Maxey-Eakin method are comparable to estimates of recharge obtained by using chloride balance studies. The authors consider the Maxey-Eakin approach as a relatively simple method of obtaining preliminary estimates of recharge on a regional scale

  17. Can legal research benefit from evaluation studies?

    Directory of Open Access Journals (Sweden)

    Frans L. Leeuw

    2011-01-01

    Full Text Available The article describes what evaluation studies have to offer to legal research. Several cases and types of evaluations are presented, in relation to legal or semi-legal questions. Also, a short overview of the contemporary history of evaluation studies is presented. Finally, it will address the question of how to ensure that in legal research and in legal training attention is paid to theories, designs and methods of evaluation studies.

  18. Spatial Distribution and Mobility Assessment of Carcinogenic Heavy Metals in Soil Profiles Using Geostatistics and Random Forest, Boruta Algorithm

    Directory of Open Access Journals (Sweden)

    Asma Shaheen

    2018-03-01

    Full Text Available In third world countries, industries mainly cause environmental contamination due to lack of environmental policies or oversight during their implementation. The Sheikhupura industrial zone, which includes industries such as tanneries, leather, chemical, textiles, and colour and dyes, contributes massive amounts of untreated effluents that are released directly into drains and used for the irrigation of crops and vegetables. This practice causes not only soil contamination with an excessive amount of heavy metals, but is also considered a source of toxicity in the food chain, i.e., bioaccumulation in plants and ultimately in human body organs. The objective of this research study was to assess the spatial distribution of the heavy metals chromium (Cr, cadmium (Cd, and lead (Pb, at three depths of soil using geostatistics and the selection of significant contributing variables to soil contamination using the Random Forest (RF function of the Boruta Algorithm. A total of 60 sampling locations were selected in the study area to collect soil samples (180 samples at three depths (0–15 cm, 15–30 cm, and 60–90 cm. The soil samples were analysed for their physico-chemical properties, i.e., soil saturation, electrical conductivity (EC, organic matter (OM, pH, phosphorus (P, potassium (K, and Cr, Cd, and Pb using standard laboratory procedures. The data were analysed with comprehensive statistics and geostatistical techniques. The correlation coefficient matrix between the heavy metals and the physico-chemical properties revealed that electrical conductivity (EC had a significant (p ≤ 0.05 negative correlation with Cr, Cd, and Pb. The RF function of the Boruta Algorithm employed soil depth as a classifier and ranked the significant soil contamination parameters (Cr, Cd, Pb, EC, and P in relation to depth. The mobility factor indicated the leachate percentage of heavy metals at different vertical depths of soil. The spatial distribution pattern of

  19. Optimisation of groundwater level monitoring networks using geostatistical modelling based on the Spartan family variogram and a genetic algorithm method

    Science.gov (United States)

    Parasyris, Antonios E.; Spanoudaki, Katerina; Kampanis, Nikolaos A.

    2016-04-01

    Groundwater level monitoring networks provide essential information for water resources management, especially in areas with significant groundwater exploitation for agricultural and domestic use. Given the high maintenance costs of these networks, development of tools, which can be used by regulators for efficient network design is essential. In this work, a monitoring network optimisation tool is presented. The network optimisation tool couples geostatistical modelling based on the Spartan family variogram with a genetic algorithm method and is applied to Mires basin in Crete, Greece, an area of high socioeconomic and agricultural interest, which suffers from groundwater overexploitation leading to a dramatic decrease of groundwater levels. The purpose of the optimisation tool is to determine which wells to exclude from the monitoring network because they add little or no beneficial information to groundwater level mapping of the area. Unlike previous relevant investigations, the network optimisation tool presented here uses Ordinary Kriging with the recently-established non-differentiable Spartan variogram for groundwater level mapping, which, based on a previous geostatistical study in the area leads to optimal groundwater level mapping. Seventy boreholes operate in the area for groundwater abstraction and water level monitoring. The Spartan variogram gives overall the most accurate groundwater level estimates followed closely by the power-law model. The geostatistical model is coupled to an integer genetic algorithm method programmed in MATLAB 2015a. The algorithm is used to find the set of wells whose removal leads to the minimum error between the original water level mapping using all the available wells in the network and the groundwater level mapping using the reduced well network (error is defined as the 2-norm of the difference between the original mapping matrix with 70 wells and the mapping matrix of the reduced well network). The solution to the

  20. The Breast Health Intervention Evaluation Study

    National Research Council Canada - National Science Library

    Blumenthal, Daniel

    1997-01-01

    The Breast Health Intervention Evaluation (BRIE) Study will evaluate the relative effectiveness of three different approaches to breast health messages--a fear appeal, a positive affect appeal, and an affectively neutral, cognitive appeal...

  1. Determination of geostatistically representative sampling locations in Porsuk Dam Reservoir (Turkey)

    Science.gov (United States)

    Aksoy, A.; Yenilmez, F.; Duzgun, S.

    2013-12-01

    Several factors such as wind action, bathymetry and shape of a lake/reservoir, inflows, outflows, point and diffuse pollution sources result in spatial and temporal variations in water quality of lakes and reservoirs. The guides by the United Nations Environment Programme and the World Health Organization to design and implement water quality monitoring programs suggest that even a single monitoring station near the center or at the deepest part of a lake will be sufficient to observe long-term trends if there is good horizontal mixing. In stratified water bodies, several samples can be required. According to the guide of sampling and analysis under the Turkish Water Pollution Control Regulation, a minimum of five sampling locations should be employed to characterize the water quality in a reservoir or a lake. The European Union Water Framework Directive (2000/60/EC) states to select a sufficient number of monitoring sites to assess the magnitude and impact of point and diffuse sources and hydromorphological pressures in designing a monitoring program. Although existing regulations and guidelines include frameworks for the determination of sampling locations in surface waters, most of them do not specify a procedure in establishment of monitoring aims with representative sampling locations in lakes and reservoirs. In this study, geostatistical tools are used to determine the representative sampling locations in the Porsuk Dam Reservoir (PDR). Kernel density estimation and kriging were used in combination to select the representative sampling locations. Dissolved oxygen and specific conductivity were measured at 81 points. Sixteen of them were used for validation. In selection of the representative sampling locations, care was given to keep similar spatial structure in distributions of measured parameters. A procedure was proposed for that purpose. Results indicated that spatial structure was lost under 30 sampling points. This was as a result of varying water

  2. Geochemical mapping in polluted floodplains using handheld XRF, geophysical imaging, and geostatistics

    Science.gov (United States)

    Hošek, Michal; Matys Grygar, Tomáš; Popelka, Jan; Kiss, Timea; Elznicová, Jitka; Faměra, Martin

    2017-04-01

    In the recent years researchers have enjoyed noticeable improvements of portable analytical and geophysical methods, which allow studying floodplain architecture and deciphering pollutant distribution more easily than ever before. Our area of interest was floodplain of the Ploučnice River, particularly a pollution hotspot in Boreček, severely impacted by U mining between the 1970s and late 1980s, in particular a "radioactive flood" in 1981. In the area, we used hand drill coring and in situ (field) analysis of so acquired sediments by handheld X-ray fluorescence spectrometer (XRF), which gave us information about depth profiles of pollutants (Ba, U, Zn) and the Al/Si and Zr/Rb ratios, i.e., proxies for sediment lithology. We found that spatial distribution of pollutants (control by depth and position in the floodplain) is apparently complex and discontinuous. In some places, contamination is buried by a couple decimetres of less polluted sediments, while in other places the peak pollution is near surface, apparently without a straightforward connection with the surface topography and the distance to the river channel. We thus examined the floodplain architecture, the internal structure of the floodplain using two geophysical methods. First of them, dipole electromagnetic profiling (DEMP, also denoted EMP, MP, or Slingram) quickly acquires average electric resistivity in top strata in selected areas, which was actually top 3 m with our particular instrument. Second, electric resistivity tomography (ERT) produces much more detailed information on resistivity with depth resolution of ca 0.5 m to the depth of ca 5 m in selected lines. ERT thus allows identifying boundaries of electric resistivity domains (sediment bodies) and DEMP their spatial distribution. Based on the obtained data, we divided the floodplain to five segments with specific topography, pollution characteristics, and electric resistivity. We suppose that those segments are lithogenetic floodplain

  3. Crescent Evaluation : appendix B : state case study evaluation report

    Science.gov (United States)

    1994-02-01

    The state case study evaluation approach uniquely captured an understanding of the potential of such a system by documenting the experiences, issues, and opportunities of selected key state government personnel from a cross-section of involved agenci...

  4. Overview and technical and practical aspects for use of geostatistics in hazardous-, toxic-, and radioactive-waste-site investigations

    International Nuclear Information System (INIS)

    Bossong, C.R.; Karlinger, M.R.; Troutman, B.M.; Vecchia, A.V.

    1999-01-01

    Technical and practical aspects of applying geostatistics are developed for individuals involved in investigation at hazardous-, toxic-, and radioactive-waste sites. Important geostatistical concepts, such as variograms and ordinary, universal, and indicator kriging, are described in general terms for introductory purposes and in more detail for practical applications. Variogram modeling using measured ground-water elevation data is described in detail to illustrate principles of stationarity, anisotropy, transformations, and cross validation. Several examples of kriging applications are described using ground-water-level elevations, bedrock elevations, and ground-water-quality data. A review of contemporary literature and selected public domain software associated with geostatistics also is provided, as is a discussion of alternative methods for spatial modeling, including inverse distance weighting, triangulation, splines, trend-surface analysis, and simulation

  5. Monte Carlo full-waveform inversion of crosshole GPR data using multiple-point geostatistical a priori information

    DEFF Research Database (Denmark)

    Cordua, Knud Skou; Hansen, Thomas Mejer; Mosegaard, Klaus

    2012-01-01

    We present a general Monte Carlo full-waveform inversion strategy that integrates a priori information described by geostatistical algorithms with Bayesian inverse problem theory. The extended Metropolis algorithm can be used to sample the a posteriori probability density of highly nonlinear...... inverse problems, such as full-waveform inversion. Sequential Gibbs sampling is a method that allows efficient sampling of a priori probability densities described by geostatistical algorithms based on either two-point (e.g., Gaussian) or multiple-point statistics. We outline the theoretical framework......) Based on a posteriori realizations, complicated statistical questions can be answered, such as the probability of connectivity across a layer. (3) Complex a priori information can be included through geostatistical algorithms. These benefits, however, require more computing resources than traditional...

  6. Study design considerations in evaluating environmental impacts

    Science.gov (United States)

    Stan T. Lebow; Paul A. Cooper; Patricia Lebow

    2006-01-01

    The purpose of this chapter is to make the reader aware of how choices in study parameters may influence the outcome of treated-wood environmental impact evaluations. Evaluation of the leaching and environmental accumulation of preservatives from treated wood is a complex process. and many factors can influence the results of such studies. In laboratory studies, the...

  7. Geostatistical analysis of potentiometric data in Wolfcamp aquifer of the Palo Duro Basin, Texas

    International Nuclear Information System (INIS)

    Harper, W.V.; Furr, J.M.

    1986-04-01

    This report details a geostatistical analysis of potentiometric data from the Wolfcamp aquifer in the Palo Duro Basin, Texas. Such an analysis is a part of an overall uncertainty analysis for a high-level waste repository in salt. Both an expected potentiometric surface and the associated standard error surface are produced. The Wolfcamp data are found to be well explained by a linear trend with a superimposed spherical semivariogram. A cross-validation of the analysis confirms this. In addition, the cross-validation provides a point-by-point check to test for possible anomalous data

  8. Geostatistical description of geological heterogeneity in clayey till as input for improved characterization of contaminated sites

    DEFF Research Database (Denmark)

    Kessler, Timo Christian; Klint, K.E.S.; Renard, P.

    2010-01-01

    In low-permeability clay tills subsurface transport is governed by preferential flow in sand lenses and fractures. A proper geological model requires the integration of these features, i.e. the spatial distribution of the geological heterogeneities. Detailed mapping of sand lenses has been done...... at a clay till outcrop in Denmark to characterise the shapes and the spatial variability. Further, geostatistics were applied to simulate the distribution and to develop a heterogeneity model that can be incorporated into an existing geological model of, for example, a contaminated site....

  9. Geostatistical analysis and isoscape of ice core derived water stable isotope records in an Antarctic macro region

    Science.gov (United States)

    Hatvani, István Gábor; Leuenberger, Markus; Kohán, Balázs; Kern, Zoltán

    2017-09-01

    Water stable isotopes preserved in ice cores provide essential information about polar precipitation. In the present study, multivariate regression and variogram analyses were conducted on 22 δ2H and 53 δ18O records from 60 ice cores covering the second half of the 20th century. Taking the multicollinearity of the explanatory variables into account, as also the model's adjusted R2 and its mean absolute error, longitude, elevation and distance from the coast were found to be the main independent geographical driving factors governing the spatial δ18O variability of firn/ice in the chosen Antarctic macro region. After diminishing the effects of these factors, using variography, the weights for interpolation with kriging were obtained and the spatial autocorrelation structure of the dataset was revealed. This indicates an average area of influence with a radius of 350 km. This allows the determination of the areas which are as yet not covered by the spatial variability of the existing network of ice cores. Finally, the regional isoscape was obtained for the study area, and this may be considered the first step towards a geostatistically improved isoscape for Antarctica.

  10. Assessment of ground-water flow and chemical transport in a tidally influenced aquifer using geostatistical filtering and hydrocarbon fingerprinting

    International Nuclear Information System (INIS)

    Marquis, S.A. Jr.; Smith, E.A.

    1994-01-01

    Traditional environmental investigations at tidally influenced hazardous waste sites such as marine fuel storage terminals have generally failed to characterize ground-water flow and chemical transport because they have been based on only a cursory knowledge of plume geometry, chemicals encountered, and hydrogeologic setting and synoptic ground-water level measurement. Single-time observations cannot be used to accurately determine flow direction and gradient in tidally fluctuating aquifers since these measurements delineate hydraulic head at only one point in time during a tidal cycle, not the net effect of the fluctuations. In this study, a more rigorous approach was used to characterize flow and chemical transport in a tidally influenced aquifer at a marine fuel storage terminal using: (1) ground-water-level monitoring over three tidal cycles (72 hours), (2) geostatistical filtering of ground-water-level data using 25-hour and 71-hour filtering methods, and (3) hydrocarbon fingerprinting analysis. The results from the study indicate that naphtha released from one of the on-site naphtha tanks has been the predominant contributor to the hydrocarbon plume both on-site and downgradient off-site and that net ground-water and hydrocarbon movement has been to the southeast away from the tank since 1989

  11. Periodicity in spatial data and geostatistical models: autocorrelation between patches

    Science.gov (United States)

    Volker C. Radeloff; Todd F. Miller; Hong S. He; David J. Mladenoff

    2000-01-01

    Several recent studies in landscape ecology have found periodicity in correlograms or semi-variograms calculated, for instance, from spatial data of soils, forests, or animal populations. Some of the studies interpreted this as an indication of regular or periodic landscape patterns. This interpretation is in disagreement with other studies that doubt whether such...

  12. Evaluating Evaluation Systems: Policy Levers and Strategies for Studying Implementation of Educator Evaluation. Policy Snapshot

    Science.gov (United States)

    Matlach, Lauren

    2015-01-01

    Evaluation studies can provide feedback on implementation, support continuous improvement, and increase understanding of evaluation systems' impact on teaching and learning. Despite the importance of educator evaluation studies, states often need support to prioritize and fund them. Successful studies require expertise, time, and a shared…

  13. Spatial variability of soil pH based on GIS combined with geostatistics in Panzhihua tobacco area

    International Nuclear Information System (INIS)

    Du Wei; Wang Changquan; Li Bing; Li Qiquan; Du Qian; Hu Jianxin; Liu Chaoke

    2012-01-01

    GIS and geostatistics were utilized to study the spatial variability of soil pH in Panzhihua tobacco area. Results showed that pH values in this area ranged from 4.5 to 8.3, especially 5.5 to 6.5, and in few areas were lower than 5.0 or higher than 7.0 which can meet the need of high-quality tobacco production. The best fitting model of variogram was exponential model with the nugget/sill of soil pH in 13.61% indicating strong spatial correlation. The change process was 5.40 km and the coefficient of determination was 0.491. The spatial variability of soil pH was mainly caused by structural factors such as cane, topography and soil type. The soil pH in Panzhihua tobacco area also showed a increasing trend of northwest to southeast trend. The pH of some areas in Caochang, Gonghe and Yumen were lower, and in Dalongtan were slightly higher. (authors)

  14. Quantifying aggregated uncertainty in Plasmodium falciparum malaria prevalence and populations at risk via efficient space-time geostatistical joint simulation.

    Science.gov (United States)

    Gething, Peter W; Patil, Anand P; Hay, Simon I

    2010-04-01

    Risk maps estimating the spatial distribution of infectious diseases are required to guide public health policy from local to global scales. The advent of model-based geostatistics (MBG) has allowed these maps to be generated in a formal statistical framework, providing robust metrics of map uncertainty that enhances their utility for decision-makers. In many settings, decision-makers require spatially aggregated measures over large regions such as the mean prevalence within a country or administrative region, or national populations living under different levels of risk. Existing MBG mapping approaches provide suitable metrics of local uncertainty--the fidelity of predictions at each mapped pixel--but have not been adapted for measuring uncertainty over large areas, due largely to a series of fundamental computational constraints. Here the authors present a new efficient approximating algorithm that can generate for the first time the necessary joint simulation of prevalence values across the very large prediction spaces needed for global scale mapping. This new approach is implemented in conjunction with an established model for P. falciparum allowing robust estimates of mean prevalence at any specified level of spatial aggregation. The model is used to provide estimates of national populations at risk under three policy-relevant prevalence thresholds, along with accompanying model-based measures of uncertainty. By overcoming previously unchallenged computational barriers, this study illustrates how MBG approaches, already at the forefront of infectious disease mapping, can be extended to provide large-scale aggregate measures appropriate for decision-makers.

  15. Women's Studies Collections: A Checklist Evaluation

    Science.gov (United States)

    Bolton, Brooke A.

    2009-01-01

    A checklist evaluation on thirty-seven Women's Studies programs conducted using the individual institutions' online public access catalogs (OPACs) is presented. Although Women's Studies collections are very difficult to build, an evaluation of existing programs shows that collections, for the most part, have managed substantial coverage of the…

  16. Bridges between multiple-point geostatistics and texture synthesis: Review and guidelines for future research

    Science.gov (United States)

    Mariethoz, Gregoire; Lefebvre, Sylvain

    2014-05-01

    Multiple-Point Simulations (MPS) is a family of geostatistical tools that has received a lot of attention in recent years for the characterization of spatial phenomena in geosciences. It relies on the definition of training images to represent a given type of spatial variability, or texture. We show that the algorithmic tools used are similar in many ways to techniques developed in computer graphics, where there is a need to generate large amounts of realistic textures for applications such as video games and animated movies. Similarly to MPS, these texture synthesis methods use training images, or exemplars, to generate realistic-looking graphical textures. Both domains of multiple-point geostatistics and example-based texture synthesis present similarities in their historic development and share similar concepts. These disciplines have however remained separated, and as a result significant algorithmic innovations in each discipline have not been universally adopted. Texture synthesis algorithms present drastically increased computational efficiency, patterns reproduction and user control. At the same time, MPS developed ways to condition models to spatial data and to produce 3D stochastic realizations, which have not been thoroughly investigated in the field of texture synthesis. In this paper we review the possible links between these disciplines and show the potential and limitations of using concepts and approaches from texture synthesis in MPS. We also provide guidelines on how recent developments could benefit both fields of research, and what challenges remain open.

  17. Geostatistical Borehole Image-Based Mapping of Karst-Carbonate Aquifer Pores.

    Science.gov (United States)

    Sukop, Michael C; Cunningham, Kevin J

    2016-03-01

    Quantification of the character and spatial distribution of porosity in carbonate aquifers is important as input into computer models used in the calculation of intrinsic permeability and for next-generation, high-resolution groundwater flow simulations. Digital, optical, borehole-wall image data from three closely spaced boreholes in the karst-carbonate Biscayne aquifer in southeastern Florida are used in geostatistical experiments to assess the capabilities of various methods to create realistic two-dimensional models of vuggy megaporosity and matrix-porosity distribution in the limestone that composes the aquifer. When the borehole image data alone were used as the model training image, multiple-point geostatistics failed to detect the known spatial autocorrelation of vuggy megaporosity and matrix porosity among the three boreholes, which were only 10 m apart. Variogram analysis and subsequent Gaussian simulation produced results that showed a realistic conceptualization of horizontal continuity of strata dominated by vuggy megaporosity and matrix porosity among the three boreholes. © 2015, National Ground Water Association.

  18. Geostatistical simulations for radon indoor with a nested model including the housing factor

    International Nuclear Information System (INIS)

    Cafaro, C.; Giovani, C.; Garavaglia, M.

    2016-01-01

    The radon prone areas definition is matter of many researches in radioecology, since radon is considered a leading cause of lung tumours, therefore the authorities ask for support to develop an appropriate sanitary prevention strategy. In this paper, we use geostatistical tools to elaborate a definition accounting for some of the available information about the dwellings. Co-kriging is the proper interpolator used in geostatistics to refine the predictions by using external covariates. In advance, co-kriging is not guaranteed to improve significantly the results obtained by applying the common lognormal kriging. Here, instead, such multivariate approach leads to reduce the cross-validation residual variance to an extent which is deemed as satisfying. Furthermore, with the application of Monte Carlo simulations, the paradigm provides a more conservative radon prone areas definition than the one previously made by lognormal kriging. - Highlights: • The housing class is inserted into co-kriging via an indicator function. • Inserting the housing classes in a co-kriging improves predictions. • The housing class has a structured component in space. • A nested model is implemented into the multigaussian algorithm. • A collection of risk maps is merged into one to create RPA.

  19. Fine-grained sediment spatial distribution on the basis of a geostatistical analysis: Example of the eastern Bay of the Seine (France)

    Science.gov (United States)

    Méar, Y.; Poizot, E.; Murat, A.; Lesueur, P.; Thomas, M.

    2006-12-01

    The eastern Bay of the Seine (English Channel) was the subject in 1991 of a sampling survey of superficial sediments. Geostatistic tools were used to examine the complexity of the spatial distribution of the fine-grained fraction (discussed. Within this sedimentary unit, the distribution of the fine fraction is very heterogeneous, with mud patches of less than 4000 m diameter; the boundary between these mud patches and their substratum is very sharp. The distribution of this fine fraction appears to be controlled by an anticyclonic eddy located off the Pays de Caux. Under the influence of this, the suspended material expelled from the Seine estuary moves along the coast and swings off Antifer harbour, towards the NW. It is trapped within this eddy because of the settling of suspended particulate matter. Both at a general scale and a local scale the morphology (whether inherited or due to modern processes) has a strong influence on the spatial distribution of the fine fraction. At the general scale, the basin-like shape of the area facilitates the silting, and the presence of the submarine dunes, called "Ridins d'Antifer", clearly determines the northern limit of the muddy zone. At a local scale, the same influence is obvious: paleovalleys trap the fine sediments, whereas isolated sand dunes and ripples limit the silting. This duality of role of the morphology is therefore one of the reasons why the muddy surface is extremely heterogeneous spatially. The presence of an important population of suspension feeding echinoderm, the brittle-star Ophiothrix fragilis Abildgaard, has led to a local increase in the silting, and to the modification of the physicochemical and sedimentological parameters. A complex relationship is shown to occur between the amount of fine fraction and the number of brittle-stars (ind. m -2). Classical statistical methods are not appropriate to study the spatial distribution of the mud fraction, because the spatial component of the percentage of

  20. Handbook for evaluation studies in virtual reality

    DEFF Research Database (Denmark)

    Livatino, Salvatore; Koeffel, Christina

    2006-01-01

    of human behavior including aspects of perception, action, and task-performance. The evaluation issue calls for multi- and interdisciplinary research activities, where technical expertise is combined with humanistic knowledge and methodology. Several experts in the field of VR as well as in the field...... in evaluation studies as well as students. The aim is also to facilitate multi-disciplinary activities through the use of an evaluation handbook which would be simple and focused on VR. The applicability of this guideline has been tested in two pilot studies, which showed how this handbook could successfully...... be employed to carry out pilot (and formal) evaluations....

  1. Geostatistical Sampling Methods for Efficient Uncertainty Analysis in Flow and Transport Problems

    Science.gov (United States)

    Liodakis, Stylianos; Kyriakidis, Phaedon; Gaganis, Petros

    2015-04-01

    In hydrogeological applications involving flow and transport of in heterogeneous porous media the spatial distribution of hydraulic conductivity is often parameterized in terms of a lognormal random field based on a histogram and variogram model inferred from data and/or synthesized from relevant knowledge. Realizations of simulated conductivity fields are then generated using geostatistical simulation involving simple random (SR) sampling and are subsequently used as inputs to physically-based simulators of flow and transport in a Monte Carlo framework for evaluating the uncertainty in the spatial distribution of solute concentration due to the uncertainty in the spatial distribution of hydraulic con- ductivity [1]. Realistic uncertainty analysis, however, calls for a large number of simulated concentration fields; hence, can become expensive in terms of both time and computer re- sources. A more efficient alternative to SR sampling is Latin hypercube (LH) sampling, a special case of stratified random sampling, which yields a more representative distribution of simulated attribute values with fewer realizations [2]. Here, term representative implies realizations spanning efficiently the range of possible conductivity values corresponding to the lognormal random field. In this work we investigate the efficiency of alternative methods to classical LH sampling within the context of simulation of flow and transport in a heterogeneous porous medium. More precisely, we consider the stratified likelihood (SL) sampling method of [3], in which attribute realizations are generated using the polar simulation method by exploring the geometrical properties of the multivariate Gaussian distribution function. In addition, we propose a more efficient version of the above method, here termed minimum energy (ME) sampling, whereby a set of N representative conductivity realizations at M locations is constructed by: (i) generating a representative set of N points distributed on the

  2. IN SITU NON-INVASIVE SOIL CARBON ANALYSIS: SAMPLE SIZE AND GEOSTATISTICAL CONSIDERATIONS.

    Energy Technology Data Exchange (ETDEWEB)

    WIELOPOLSKI, L.

    2005-04-01

    I discuss a new approach for quantitative carbon analysis in soil based on INS. Although this INS method is not simple, it offers critical advantages not available with other newly emerging modalities. The key advantages of the INS system include the following: (1) It is a non-destructive method, i.e., no samples of any kind are taken. A neutron generator placed above the ground irradiates the soil, stimulating carbon characteristic gamma-ray emission that is counted by a detection system also placed above the ground. (2) The INS system can undertake multielemental analysis, so expanding its usefulness. (3) It can be used either in static or scanning modes. (4) The volume sampled by the INS method is large with a large footprint; when operating in a scanning mode, the sampled volume is continuous. (5) Except for a moderate initial cost of about $100,000 for the system, no additional expenses are required for its operation over two to three years after which a NG has to be replenished with a new tube at an approximate cost of $10,000, this regardless of the number of sites analyzed. In light of these characteristics, the INS system appears invaluable for monitoring changes in the carbon content in the field. For this purpose no calibration is required; by establishing a carbon index, changes in carbon yield can be followed with time in exactly the same location, thus giving a percent change. On the other hand, with calibration, it can be used to determine the carbon stock in the ground, thus estimating the soil's carbon inventory. However, this requires revising the standard practices for deciding upon the number of sites required to attain a given confidence level, in particular for the purposes of upward scaling. Then, geostatistical considerations should be incorporated in considering properly the averaging effects of the large volumes sampled by the INS system that would require revising standard practices in the field for determining the number of spots to

  3. Reservoir Modeling Combining Geostatistics with Markov Chain Monte Carlo Inversion

    DEFF Research Database (Denmark)

    Zunino, Andrea; Lange, Katrine; Melnikova, Yulia

    2014-01-01

    We present a study on the inversion of seismic reflection data generated from a synthetic reservoir model. Our aim is to invert directly for rock facies and porosity of the target reservoir zone. We solve this inverse problem using a Markov chain Monte Carlo (McMC) method to handle the nonlinear...

  4. Study on team evaluation. Team process model for team evaluation

    International Nuclear Information System (INIS)

    Sasou Kunihide; Ebisu, Mitsuhiro; Hirose, Ayako

    2004-01-01

    Several studies have been done to evaluate or improve team performance in nuclear and aviation industries. Crew resource management is the typical example. In addition, team evaluation recently gathers interests in other teams of lawyers, medical staff, accountants, psychiatrics, executive, etc. However, the most evaluation methods focus on the results of team behavior that can be observed through training or actual business situations. What is expected team is not only resolving problems but also training younger members being destined to lead the next generation. Therefore, the authors set the final goal of this study establishing a series of methods to evaluate and improve teams inclusively such as decision making, motivation, staffing, etc. As the first step, this study develops team process model describing viewpoints for the evaluation. The team process is defined as some kinds of power that activate or inactivate competency of individuals that is the components of team's competency. To find the team process, the authors discussed the merits of team behavior with the experienced training instructors and shift supervisors of nuclear/thermal power plants. The discussion finds four team merits and many components to realize those team merits. Classifying those components into eight groups of team processes such as 'Orientation', 'Decision Making', 'Power and Responsibility', 'Workload Management', 'Professional Trust', 'Motivation', 'Training' and 'staffing', the authors propose Team Process Model with two to four sub processes in each team process. In the future, the authors will develop methods to evaluate some of the team processes for nuclear/thermal power plant operation teams. (author)

  5. Optimizing Usability Studies by Complementary Evaluation Methods

    NARCIS (Netherlands)

    Schmettow, Martin; Bach, Cedric; Scapin, Dominique

    2014-01-01

    This paper examines combinations of complementary evaluation methods as a strategy for efficient usability problem discovery. A data set from an earlier study is re-analyzed, involving three evaluation methods applied to two virtual environment applications. Results of a mixed-effects logistic

  6. Latin hypercube sampling and geostatistical modeling of spatial uncertainty in a spatially explicit forest landscape model simulation

    Science.gov (United States)

    Chonggang Xu; Hong S. He; Yuanman Hu; Yu Chang; Xiuzhen Li; Rencang Bu

    2005-01-01

    Geostatistical stochastic simulation is always combined with Monte Carlo method to quantify the uncertainty in spatial model simulations. However, due to the relatively long running time of spatially explicit forest models as a result of their complexity, it is always infeasible to generate hundreds or thousands of Monte Carlo simulations. Thus, it is of great...

  7. Approaches in highly parameterized inversion: bgaPEST, a Bayesian geostatistical approach implementation with PEST: documentation and instructions

    Science.gov (United States)

    Fienen, Michael N.; D'Oria, Marco; Doherty, John E.; Hunt, Randall J.

    2013-01-01

    The application bgaPEST is a highly parameterized inversion software package implementing the Bayesian Geostatistical Approach in a framework compatible with the parameter estimation suite PEST. Highly parameterized inversion refers to cases in which parameters are distributed in space or time and are correlated with one another. The Bayesian aspect of bgaPEST is related to Bayesian probability theory in which prior information about parameters is formally revised on the basis of the calibration dataset used for the inversion. Conceptually, this approach formalizes the conditionality of estimated parameters on the specific data and model available. The geostatistical component of the method refers to the way in which prior information about the parameters is used. A geostatistical autocorrelation function is used to enforce structure on the parameters to avoid overfitting and unrealistic results. Bayesian Geostatistical Approach is designed to provide the smoothest solution that is consistent with the data. Optionally, users can specify a level of fit or estimate a balance between fit and model complexity informed by the data. Groundwater and surface-water applications are used as examples in this text, but the possible uses of bgaPEST extend to any distributed parameter applications.

  8. A geostatistical approach to the change-of-support problem and variable-support data fusion in spatial analysis

    Science.gov (United States)

    Wang, Jun; Wang, Yang; Zeng, Hui

    2016-01-01

    A key issue to address in synthesizing spatial data with variable-support in spatial analysis and modeling is the change-of-support problem. We present an approach for solving the change-of-support and variable-support data fusion problems. This approach is based on geostatistical inverse modeling that explicitly accounts for differences in spatial support. The inverse model is applied here to produce both the best predictions of a target support and prediction uncertainties, based on one or more measurements, while honoring measurements. Spatial data covering large geographic areas often exhibit spatial nonstationarity and can lead to computational challenge due to the large data size. We developed a local-window geostatistical inverse modeling approach to accommodate these issues of spatial nonstationarity and alleviate computational burden. We conducted experiments using synthetic and real-world raster data. Synthetic data were generated and aggregated to multiple supports and downscaled back to the original support to analyze the accuracy of spatial predictions and the correctness of prediction uncertainties. Similar experiments were conducted for real-world raster data. Real-world data with variable-support were statistically fused to produce single-support predictions and associated uncertainties. The modeling results demonstrate that geostatistical inverse modeling can produce accurate predictions and associated prediction uncertainties. It is shown that the local-window geostatistical inverse modeling approach suggested offers a practical way to solve the well-known change-of-support problem and variable-support data fusion problem in spatial analysis and modeling.

  9. Regional soil erosion assessment based on a sample survey and geostatistics

    Directory of Open Access Journals (Sweden)

    S. Yin

    2018-03-01

    Full Text Available Soil erosion is one of the most significant environmental problems in China. From 2010 to 2012, the fourth national census for soil erosion sampled 32 364 PSUs (Primary Sampling Units, small watersheds with the areas of 0.2–3 km2. Land use and soil erosion controlling factors including rainfall erosivity, soil erodibility, slope length, slope steepness, biological practice, engineering practice, and tillage practice for the PSUs were surveyed, and the soil loss rate for each land use in the PSUs was estimated using an empirical model, the Chinese Soil Loss Equation (CSLE. Though the information collected from the sample units can be aggregated to estimate soil erosion conditions on a large scale; the problem of estimating soil erosion condition on a regional scale has not been addressed well. The aim of this study is to introduce a new model-based regional soil erosion assessment method combining a sample survey and geostatistics. We compared seven spatial interpolation models based on the bivariate penalized spline over triangulation (BPST method to generate a regional soil erosion assessment from the PSUs. Shaanxi Province (3116 PSUs in China was selected for the comparison and assessment as it is one of the areas with the most serious erosion problem. Ten-fold cross-validation based on the PSU data showed the model assisted by the land use, rainfall erosivity factor (R, soil erodibility factor (K, slope steepness factor (S, and slope length factor (L derived from a 1 : 10 000 topography map is the best one, with the model efficiency coefficient (ME being 0.75 and the MSE being 55.8 % of that for the model assisted by the land use alone. Among four erosion factors as the covariates, the S factor contributed the most information, followed by K and L factors, and R factor made almost no contribution to the spatial estimation of soil loss. The LS factor derived from 30 or 90 m Shuttle Radar Topography Mission

  10. Regional soil erosion assessment based on a sample survey and geostatistics

    Science.gov (United States)

    Yin, Shuiqing; Zhu, Zhengyuan; Wang, Li; Liu, Baoyuan; Xie, Yun; Wang, Guannan; Li, Yishan

    2018-03-01

    Soil erosion is one of the most significant environmental problems in China. From 2010 to 2012, the fourth national census for soil erosion sampled 32 364 PSUs (Primary Sampling Units, small watersheds) with the areas of 0.2-3 km2. Land use and soil erosion controlling factors including rainfall erosivity, soil erodibility, slope length, slope steepness, biological practice, engineering practice, and tillage practice for the PSUs were surveyed, and the soil loss rate for each land use in the PSUs was estimated using an empirical model, the Chinese Soil Loss Equation (CSLE). Though the information collected from the sample units can be aggregated to estimate soil erosion conditions on a large scale; the problem of estimating soil erosion condition on a regional scale has not been addressed well. The aim of this study is to introduce a new model-based regional soil erosion assessment method combining a sample survey and geostatistics. We compared seven spatial interpolation models based on the bivariate penalized spline over triangulation (BPST) method to generate a regional soil erosion assessment from the PSUs. Shaanxi Province (3116 PSUs) in China was selected for the comparison and assessment as it is one of the areas with the most serious erosion problem. Ten-fold cross-validation based on the PSU data showed the model assisted by the land use, rainfall erosivity factor (R), soil erodibility factor (K), slope steepness factor (S), and slope length factor (L) derived from a 1 : 10 000 topography map is the best one, with the model efficiency coefficient (ME) being 0.75 and the MSE being 55.8 % of that for the model assisted by the land use alone. Among four erosion factors as the covariates, the S factor contributed the most information, followed by K and L factors, and R factor made almost no contribution to the spatial estimation of soil loss. The LS factor derived from 30 or 90 m Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) data

  11. The use of a genetic algorithm-based search strategy in geostatistics: application to a set of anisotropic piezometric head data

    Science.gov (United States)

    Abedini, M. J.; Nasseri, M.; Burn, D. H.

    2012-04-01

    In any geostatistical study, an important consideration is the choice of an appropriate, repeatable, and objective search strategy that controls the nearby samples to be included in the location-specific estimation procedure. Almost all geostatistical software available in the market puts the onus on the user to supply search strategy parameters in a heuristic manner. These parameters are solely controlled by geographical coordinates that are defined for the entire area under study, and the user has no guidance as to how to choose these parameters. The main thesis of the current study is that the selection of search strategy parameters has to be driven by data—both the spatial coordinates and the sample values—and cannot be chosen beforehand. For this purpose, a genetic-algorithm-based ordinary kriging with moving neighborhood technique is proposed. The search capability of a genetic algorithm is exploited to search the feature space for appropriate, either local or global, search strategy parameters. Radius of circle/sphere and/or radii of standard or rotated ellipse/ellipsoid are considered as the decision variables to be optimized by GA. The superiority of GA-based ordinary kriging is demonstrated through application to the Wolfcamp Aquifer piezometric head data. Assessment of numerical results showed that definition of search strategy parameters based on both geographical coordinates and sample values improves cross-validation statistics when compared with that based on geographical coordinates alone. In the case of a variable search neighborhood for each estimation point, optimization of local search strategy parameters for an elliptical support domain—the orientation of which is dictated by anisotropic axes—via GA was able to capture the dynamics of piezometric head in west Texas/New Mexico in an efficient way.

  12. Study on development of evaluation technique of in-situ tracer test in Horonobe Underground Research Laboratory project (Contract research)

    International Nuclear Information System (INIS)

    Yokota, Hideharu; Amano, Kenji; Maekawa, Keisuke; Kunimaru, Takanori; Naemura, Yumi; Ijiri, Yuji; Motoshima, Takayuki; Suzuki, Shunichi; Teshima, Kazufumi

    2013-06-01

    In the Horonobe Underground Research Laboratory Project, in-situ tracer tests are valuable and important as the investigations to obtain the mass transportation data of fractures in hostrock. However, it is difficult that the in-situ tests are executed under various conditions due to long test period and the tests results are evaluated about permeable heterogeneity in a fracture and/or scale effects. In this study, a number of tracer tests are simulated in a fictitious single plate fracture generated on computer. And the transport parameters are identified by fitting one- and two-dimensional models to the breakthrough curves obtained from the simulations in order to investigate the applicability of these models to the evaluation of in-situ tracer test. As a result, one-dimensional model yields larger longitudinal dispersion length than two-dimensional model in the both cases of homogeneous and heterogeneous hydraulic conductivity fields of the fictitious fracture. This is because that the effect of transverse dispersion has to be included in the longitudinal dispersion length parameter in the one-dimensional model. It is also found that the larger dipole ratio and the larger natural groundwater flow crossing the flow generated between two boreholes make the identified longitudinal dispersion length larger. And, the longitudinal dispersion length identified from a tracer test is smaller and/or larger than the macroscopic longitudinal dispersion length identified from whole fracture. It is clarified that these are occurred by shorter or longer distance between boreholes compare to the correlation length of geostatistical heterogeneity of fictitious fracture. (author)

  13. Comparison of ArcGIS and SAS Geostatistical Analyst to Estimate Population-Weighted Monthly Temperature for US Counties.

    Science.gov (United States)

    Xiaopeng, Q I; Liang, Wei; Barker, Laurie; Lekiachvili, Akaki; Xingyou, Zhang

    Temperature changes are known to have significant impacts on human health. Accurate estimates of population-weighted average monthly air temperature for US counties are needed to evaluate temperature's association with health behaviours and disease, which are sampled or reported at the county level and measured on a monthly-or 30-day-basis. Most reported temperature estimates were calculated using ArcGIS, relatively few used SAS. We compared the performance of geostatistical models to estimate population-weighted average temperature in each month for counties in 48 states using ArcGIS v9.3 and SAS v 9.2 on a CITGO platform. Monthly average temperature for Jan-Dec 2007 and elevation from 5435 weather stations were used to estimate the temperature at county population centroids. County estimates were produced with elevation as a covariate. Performance of models was assessed by comparing adjusted R 2 , mean squared error, root mean squared error, and processing time. Prediction accuracy for split validation was above 90% for 11 months in ArcGIS and all 12 months in SAS. Cokriging in SAS achieved higher prediction accuracy and lower estimation bias as compared to cokriging in ArcGIS. County-level estimates produced by both packages were positively correlated (adjusted R 2 range=0.95 to 0.99); accuracy and precision improved with elevation as a covariate. Both methods from ArcGIS and SAS are reliable for U.S. county-level temperature estimates; However, ArcGIS's merits in spatial data pre-processing and processing time may be important considerations for software selection, especially for multi-year or multi-state projects.

  14. Local Geostatistical Models and Big Data in Hydrological and Ecological Applications

    Science.gov (United States)

    Hristopulos, Dionissios

    2015-04-01

    The advent of the big data era creates new opportunities for environmental and ecological modelling but also presents significant challenges. The availability of remote sensing images and low-cost wireless sensor networks implies that spatiotemporal environmental data to cover larger spatial domains at higher spatial and temporal resolution for longer time windows. Handling such voluminous data presents several technical and scientific challenges. In particular, the geostatistical methods used to process spatiotemporal data need to overcome the dimensionality curse associated with the need to store and invert large covariance matrices. There are various mathematical approaches for addressing the dimensionality problem, including change of basis, dimensionality reduction, hierarchical schemes, and local approximations. We present a Stochastic Local Interaction (SLI) model that can be used to model local correlations in spatial data. SLI is a random field model suitable for data on discrete supports (i.e., regular lattices or irregular sampling grids). The degree of localization is determined by means of kernel functions and appropriate bandwidths. The strength of the correlations is determined by means of coefficients. In the "plain vanilla" version the parameter set involves scale and rigidity coefficients as well as a characteristic length. The latter determines in connection with the rigidity coefficient the correlation length of the random field. The SLI model is based on statistical field theory and extends previous research on Spartan spatial random fields [2,3] from continuum spaces to explicitly discrete supports. The SLI kernel functions employ adaptive bandwidths learned from the sampling spatial distribution [1]. The SLI precision matrix is expressed explicitly in terms of the model parameter and the kernel function. Hence, covariance matrix inversion is not necessary for parameter inference that is based on leave-one-out cross validation. This property

  15. Hand function evaluation: a factor analysis study.

    Science.gov (United States)

    Jarus, T; Poremba, R

    1993-05-01

    The purpose of this study was to investigate hand function evaluations. Factor analysis with varimax rotation was used to assess the fundamental characteristics of the items included in the Jebsen Hand Function Test and the Smith Hand Function Evaluation. The study sample consisted of 144 subjects without disabilities and 22 subjects with Colles fracture. Results suggest a four factor solution: Factor I--pinch movement; Factor II--grasp; Factor III--target accuracy; and Factor IV--activities of daily living. These categories differentiated the subjects without Colles fracture from the subjects with Colles fracture. A hand function evaluation consisting of these four factors would be useful. Such an evaluation that can be used for current clinical purposes is provided.

  16. Implementation of the Iterative Proportion Fitting Algorithm for Geostatistical Facies Modeling

    International Nuclear Information System (INIS)

    Li Yupeng; Deutsch, Clayton V.

    2012-01-01

    In geostatistics, most stochastic algorithm for simulation of categorical variables such as facies or rock types require a conditional probability distribution. The multivariate probability distribution of all the grouped locations including the unsampled location permits calculation of the conditional probability directly based on its definition. In this article, the iterative proportion fitting (IPF) algorithm is implemented to infer this multivariate probability. Using the IPF algorithm, the multivariate probability is obtained by iterative modification to an initial estimated multivariate probability using lower order bivariate probabilities as constraints. The imposed bivariate marginal probabilities are inferred from profiles along drill holes or wells. In the IPF process, a sparse matrix is used to calculate the marginal probabilities from the multivariate probability, which makes the iterative fitting more tractable and practical. This algorithm can be extended to higher order marginal probability constraints as used in multiple point statistics. The theoretical framework is developed and illustrated with estimation and simulation example.

  17. Geostatistical exploration of dataset assessing the heavy metal contamination in Ewekoro limestone, Southwestern Nigeria

    Directory of Open Access Journals (Sweden)

    Kehinde D. Oyeyemi

    2017-10-01

    Full Text Available The dataset for this article contains geostatistical analysis of heavy metals contamination from limestone samples collected from Ewekoro Formation in the eastern Dahomey basin, Ogun State Nigeria. The samples were manually collected and analysed using Microwave Plasma Atomic Absorption Spectrometer (MPAS. Analysis of the twenty different samples showed different levels of heavy metals concentration. The analysed nine elements are Arsenic, Mercury, Cadmium, Cobalt, Chromium, Nickel, Lead, Vanadium and Zinc. Descriptive statistics was used to explore the heavy metal concentrations individually. Pearson, Kendall tau and Spearman rho correlation coefficients was used to establish the relationships among the elements and the analysis of variance showed that there is a significant difference in the mean distribution of the heavy metals concentration within and between the groups of the 20 samples analysed. The dataset can provide insights into the health implications of the contaminants especially when the mean concentration levels of the heavy metals are compared with recommended regulatory limit concentration.

  18. Application of Geostatistics to the resolution of structural problems in homogeneous rocky massifs

    International Nuclear Information System (INIS)

    Lucero Michaut, H.N.

    1985-01-01

    The nature and possibilities of application of intrinsic functions to the structural research and the delimitation of the areas of influence in an ore deposit are briefly described. Main models to which the different distributions may be assimilated: 'logarithmic' and 'linear' among those with no sill value, and on the other hand, 'spherical', 'exponential' and 'gaussian' among those having a sill level, which allows the establishment of a range value liable to separate the field of independent samples from that of non-independent ones are shown. Thereafter as an original contribution to applied geostatistics the autor postulates 1) the application of the 'fracturing rank' as a regionalized variable after verifying its validity through strict probabilistic methodologies, and 2) a methodological extension of the conventional criterion of 'rock quality designation' to the analysis of the quality and degree of structural discontinuity in the rock surface. Finally, some examples are given of these applications. (M.E.L.) [es

  19. Characterization of a deep radiological contamination: integration of geostatistical processing and historical data - 59062

    International Nuclear Information System (INIS)

    Desnoyers, Yvon; De Moura, Patrick

    2012-01-01

    The problem of site characterization is quite complex, especially for deep radiological contamination. This article illustrates the added value of the geo-statistical processing on a real application case dealing with grounds of facilities partially dismantled at the end of the 1950's in Fontenay-aux-Roses CEA Center (France). 12 years ago, a first exploratory drill-hole confirmed the presence of a deep radiological contamination (more than 4 m deep). More recently, 8 additional drill-holes failed to delineate the contamination extension. The integration of the former topography and other geological data led to the realization of 10 additional drill holes. This final stage significantly improved the characterization of the radiological contamination, which impacted the remediation project and the initially estimated volumes. (authors)

  20. Organizational evaluation of an interprofessional study unit

    DEFF Research Database (Denmark)

    Jensen, Didde Cramer; Nørgaard, Birgitte; Draborg, Eva

    2012-01-01

    This article presents results from an organizational evaluation of an interprofessional clinical study unit (ICS) in Denmark. The aim of this study was to test whether the ICS was based on a durable organizational concept and to identify the prerequisites for the unit to be successful...

  1. PHYSIOTHERAPY FOR CLUMSY CHILDREN - AN EVALUATION STUDY

    NARCIS (Netherlands)

    SCHOEMAKER, MM; HIJLKEMA, MGJ; KALVERBOER, AF

    This study reports the findings of an effect-evaluation study of physiotherapy for clumsy children. 18 children were identified by school doctors as having poor motor co-ordination. They were followed for three months in order to exclude spontaneous improvement of motor problems; none spontaneously

  2. Model-Based Geostatistical Mapping of the Prevalence of Onchocerca volvulus in West Africa.

    Directory of Open Access Journals (Sweden)

    Simon J O'Hanlon

    2016-01-01

    Full Text Available The initial endemicity (pre-control prevalence of onchocerciasis has been shown to be an important determinant of the feasibility of elimination by mass ivermectin distribution. We present the first geostatistical map of microfilarial prevalence in the former Onchocerciasis Control Programme in West Africa (OCP before commencement of antivectorial and antiparasitic interventions.Pre-control microfilarial prevalence data from 737 villages across the 11 constituent countries in the OCP epidemiological database were used as ground-truth data. These 737 data points, plus a set of statistically selected environmental covariates, were used in a Bayesian model-based geostatistical (B-MBG approach to generate a continuous surface (at pixel resolution of 5 km x 5km of microfilarial prevalence in West Africa prior to the commencement of the OCP. Uncertainty in model predictions was measured using a suite of validation statistics, performed on bootstrap samples of held-out validation data. The mean Pearson's correlation between observed and estimated prevalence at validation locations was 0.693; the mean prediction error (average difference between observed and estimated values was 0.77%, and the mean absolute prediction error (average magnitude of difference between observed and estimated values was 12.2%. Within OCP boundaries, 17.8 million people were deemed to have been at risk, 7.55 million to have been infected, and mean microfilarial prevalence to have been 45% (range: 2-90% in 1975.This is the first map of initial onchocerciasis prevalence in West Africa using B-MBG. Important environmental predictors of infection prevalence were identified and used in a model out-performing those without spatial random effects or environmental covariates. Results may be compared with recent epidemiological mapping efforts to find areas of persisting transmission. These methods may be extended to areas where data are sparse, and may be used to help inform the

  3. MoisturEC: an R application for geostatistical estimation of moisture content from electrical conductivity data

    Science.gov (United States)

    Terry, N.; Day-Lewis, F. D.; Werkema, D. D.; Lane, J. W., Jr.

    2017-12-01

    Soil moisture is a critical parameter for agriculture, water supply, and management of landfills. Whereas direct data (as from TDR or soil moisture probes) provide localized point scale information, it is often more desirable to produce 2D and/or 3D estimates of soil moisture from noninvasive measurements. To this end, geophysical methods for indirectly assessing soil moisture have great potential, yet are limited in terms of quantitative interpretation due to uncertainty in petrophysical transformations and inherent limitations in resolution. Simple tools to produce soil moisture estimates from geophysical data are lacking. We present a new standalone program, MoisturEC, for estimating moisture content distributions from electrical conductivity data. The program uses an indicator kriging method within a geostatistical framework to incorporate hard data (as from moisture probes) and soft data (as from electrical resistivity imaging or electromagnetic induction) to produce estimates of moisture content and uncertainty. The program features data visualization and output options as well as a module for calibrating electrical conductivity with moisture content to improve estimates. The user-friendly program is written in R - a widely used, cross-platform, open source programming language that lends itself to further development and customization. We demonstrate use of the program with a numerical experiment as well as a controlled field irrigation experiment. Results produced from the combined geostatistical framework of MoisturEC show improved estimates of moisture content compared to those generated from individual datasets. This application provides a convenient and efficient means for integrating various data types and has broad utility to soil moisture monitoring in landfills, agriculture, and other problems.

  4. Integration of vertical and in-seam horizontal well production analyses with stochastic geostatistical algorithms to estimate pre-mining methane drainage efficiency from coal seams: Blue Creek seam, Alabama.

    Science.gov (United States)

    Karacan, C Özgen

    2013-07-30

    Coal seam degasification and its efficiency are directly related to the safety of coal mining. Degasification activities in the Black Warrior basin started in the early 1980s by using vertical boreholes. Although the Blue Creek seam, which is part of the Mary Lee coal group, has been the main seam of interest for coal mining, vertical wellbores have also been completed in the Pratt, Mary Lee, and Black Creek coal groups of the Upper Pottsville formation to degasify multiple seams. Currently, the Blue Creek seam is further degasified 2-3 years in advance of mining using in-seam horizontal boreholes to ensure safe mining. The studied location in this work is located between Tuscaloosa and Jefferson counties in Alabama and was degasified using 81 vertical boreholes, some of which are still active. When the current long mine expanded its operation into this area in 2009, horizontal boreholes were also drilled in advance of mining for further degasification of only the Blue Creek seam to ensure a safe and a productive operation. This paper presents an integrated study and a methodology to combine history matching results from vertical boreholes with production modeling of horizontal boreholes using geostatistical simulation to evaluate spatial effectiveness of in-seam boreholes in reducing gas-in-place (GIP). Results in this study showed that in-seam wells' boreholes had an estimated effective drainage area of 2050 acres with cumulative production of 604 MMscf methane during ~2 years of operation. With horizontal borehole production, GIP in the Blue Creek seam decreased from an average of 1.52 MMscf to 1.23 MMscf per acre. It was also shown that effective gas flow capacity, which was independently modeled using vertical borehole data, affected horizontal borehole production. GIP and effective gas flow capacity of coal seam gas were also used to predict remaining gas potential for the Blue Creek seam.

  5. Using the Direct Sampling Multiple-Point Geostatistical Method for Filling Gaps in Landsat 7 ETM+ SLC-off Imagery

    KAUST Repository

    Yin, Gaohong

    2016-05-01

    Since the failure of the Scan Line Corrector (SLC) instrument on Landsat 7, observable gaps occur in the acquired Landsat 7 imagery, impacting the spatial continuity of observed imagery. Due to the highly geometric and radiometric accuracy provided by Landsat 7, a number of approaches have been proposed to fill the gaps. However, all proposed approaches have evident constraints for universal application. The main issues in gap-filling are an inability to describe the continuity features such as meandering streams or roads, or maintaining the shape of small objects when filling gaps in heterogeneous areas. The aim of the study is to validate the feasibility of using the Direct Sampling multiple-point geostatistical method, which has been shown to reconstruct complicated geological structures satisfactorily, to fill Landsat 7 gaps. The Direct Sampling method uses a conditional stochastic resampling of known locations within a target image to fill gaps and can generate multiple reconstructions for one simulation case. The Direct Sampling method was examined across a range of land cover types including deserts, sparse rural areas, dense farmlands, urban areas, braided rivers and coastal areas to demonstrate its capacity to recover gaps accurately for various land cover types. The prediction accuracy of the Direct Sampling method was also compared with other gap-filling approaches, which have been previously demonstrated to offer satisfactory results, under both homogeneous area and heterogeneous area situations. Studies have shown that the Direct Sampling method provides sufficiently accurate prediction results for a variety of land cover types from homogeneous areas to heterogeneous land cover types. Likewise, it exhibits superior performances when used to fill gaps in heterogeneous land cover types without input image or with an input image that is temporally far from the target image in comparison with other gap-filling approaches.

  6. Quantifying the exposure of humans and the environment to oil pollution in the Niger Delta using advanced geostatistical techniques.

    Science.gov (United States)

    Obida, Christopher B; Alan Blackburn, G; Duncan Whyatt, J; Semple, Kirk T

    2018-02-01

    The Niger Delta is one of the largest oil producing regions of the world. Large numbers and volumes of oil spills have been reported in this region. What has not been quantified is the putative exposure of humans and/or the environment to this hydrocarbon pollution. In this novel study, advanced geostatistical techniques were applied to an extensive database of oil spill incidents from 2007 to 2015. The aims were to (i) identify and analyse spill hotspots along the oil pipeline network and (ii) estimate the exposure of the hydrocarbon pollution to the human population and the environment within the Niger Delta. Over the study period almost 90millionlitres of oil were released. Approximately 29% of the human population living in proximity to the pipeline network has been potentially exposed to oil contamination, of which 565,000 people live within high or very high spill intensity sectors. Over 1000km 2 of land has been contaminated by oil pollution, with broadleaved forest, mangroves and agricultural land the most heavily impacted land cover types. Proximity to the coast, roads and cities are the strongest spatial factors contributing to spill occurrence, which largely determine the accessibility of sites for pipeline sabotage and oil theft. Overall, the findings demonstrate the high levels of environmental and human exposure to hydrocarbon pollutants in the Niger Delta. These results provide evidence with which to spatially target interventions to reduce future spill incidents and mitigate the impacts of previous spills on human communities and ecosystem health. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. A geostatistical analysis of the association between armed conflicts and Plasmodium falciparum malaria in Africa, 1997-2010.

    Science.gov (United States)

    Sedda, Luigi; Qi, Qiuyin; Tatem, Andrew J

    2015-12-16

    The absence of conflict in a country has been cited as a crucial factor affecting the operational feasibility of achieving malaria control and elimination, yet mixed evidence exists on the influence that conflicts have had on malaria transmission. Over the past two decades, Africa has seen substantial numbers of armed conflicts of varying length and scale, creating conditions that can disrupt control efforts and impact malaria transmission. However, very few studies have quantitatively assessed the associations between conflicts and malaria transmission, particularly in a consistent way across multiple countries. In this analysis an explicit geostatistical, autoregressive, mixed model is employed to quantitatively assess the association between conflicts and variations in Plasmodium falciparum parasite prevalence across a 13-year period in sub-Saharan Africa. Analyses of geolocated, malaria prevalence survey variations against armed conflict data in general showed a wide, but short-lived impact of conflict events geographically. The number of countries with decreased P. falciparum parasite prevalence (17) is larger than the number of countries with increased transmission (12), and notably, some of the countries with the highest transmission pre-conflict were still found with lower transmission post-conflict. For four countries, there were no significant changes in parasite prevalence. Finally, distance from conflicts, duration of conflicts, violence of conflict, and number of conflicts were significant components in the model explaining the changes in P. falciparum parasite rate. The results suggest that the maintenance of intervention coverage and provision of healthcare in conflict situations to protect vulnerable populations can maintain gains in even the most difficult of circumstances, and that conflict does not represent a substantial barrier to elimination goals.

  8. Time-Lapse Analysis of Methane Quantity in the Mary Lee Group of Coal Seams Using Filter-Based Multiple-Point Geostatistical Simulation.

    Science.gov (United States)

    Karacan, C Özgen; Olea, Ricardo A

    2013-08-01

    Coal seam degasification and its success are important for controlling methane, and thus for the health and safety of coal miners. During the course of degasification, properties of coal seams change. Thus, the changes in coal reservoir conditions and in-place gas content as well as methane emission potential into mines should be evaluated by examining time-dependent changes and the presence of major heterogeneities and geological discontinuities in the field. In this work, time-lapsed reservoir and fluid storage properties of the New Castle coal seam, Mary Lee/Blue Creek seam, and Jagger seam of Black Warrior Basin, Alabama, were determined from gas and water production history matching and production forecasting of vertical degasification wellbores. These properties were combined with isotherm and other important data to compute gas-in-place (GIP) and its change with time at borehole locations. Time-lapsed training images (TIs) of GIP and GIP difference corresponding to each coal and date were generated by using these point-wise data and Voronoi decomposition on the TI grid, which included faults as discontinuities for expansion of Voronoi regions. Filter-based multiple-point geostatistical simulations, which were preferred in this study due to anisotropies and discontinuities in the area, were used to predict time-lapsed GIP distributions within the study area. Performed simulations were used for mapping spatial time-lapsed methane quantities as well as their uncertainties within the study area. The systematic approach presented in this paper is the first time in literature that history matching, TIs of GIPs and filter simulations are used for degasification performance evaluation and for assessing GIP for mining safety. Results from this study showed that using production history matching of coalbed methane wells to determine time-lapsed reservoir data could be used to compute spatial GIP and representative GIP TIs generated through Voronoi decomposition

  9. Evaluation of an Online Study Skills Course

    Science.gov (United States)

    Pryjmachuk, Steven; Gill, Anita; Wood, Patricia; Olleveant, Nicola; Keeley, Philip

    2012-01-01

    This article describes the evaluation of an online study skills course unit designed, using evidence-based principles, to support undergraduate students. A mixed-methods approach was employed to establish the extent to which the unit was (a) fit for purpose and (b) effective. Data were obtained from an online survey (n = 63) conducted on entry to…

  10. Evaluation of Groundwater Quality Indices of Mashhad Plain using Geostatistics and GIS Techniques

    Directory of Open Access Journals (Sweden)

    Mohammadreza Yazdani

    2017-11-01

    The outcomes illustrate that the qualitative conditions of underground water resources, particularly in TDS and TH are in the inappropriate condition in the southern parts of Mashhad. It is related to the high population density and the lack of proper drainage. It is needed to restrict over exploitation of groundwater resources in critical hot spots, along with defining alternative safe water sources for urban consumption.

  11. Geostatistics project of the National Uranium Resources Evaluation Program. Progress report, October 1978--March 1979

    International Nuclear Information System (INIS)

    Beckman, R.J.; Bement, T.R.; Campbell, K.; Howell, J.S.; Wecksung, G.W.; Whitemann, D.E.

    1979-01-01

    During the period covered by this report, research was concentrated on multivariate approaches to the analysis of aerial radiometric data. Two aspects of principal components analysis were the subjects of two publications. The procedures recommended for linear discriminant analysis were revised. Progress was made in overlaying LANDSAT data with aerial radiometric data from the Lubbock quadrangle. Some preliminary results from principal components analysis of the Wind River data were obtained

  12. Geostatistics project of the national uranium resource evaluation program. Progress report, October 1979-March 1980

    International Nuclear Information System (INIS)

    Campbell, K.; Bement, T.R.; Howell, J.A.; Beckman, R.J.; Jackson, K.; Buslee, P.

    1980-08-01

    During the period covered by this report, the authors investigated the serial properties of aerial radiometric data. Results were applied to the choice of minimum segment width in the maximum variance segments algorithm and to the use of aerial radiometric data in the design of ground sampling experiments. The report also presents the results of a comparison of normal and lognormal percentile estimation techniques. Twenty-two quadrangles are being analyzed in the search for a uranium favorability index. Computer codes developed during this investigation have been provided to the Bendix Field Engineering Corporation in Grand Junction, Colorado

  13. Optimal design of sampling and mapping schemes in the radiometric exploration of Chipilapa, El Salvador (Geo-statistics)

    International Nuclear Information System (INIS)

    Balcazar G, M.; Flores R, J.H.

    1992-01-01

    As part of the knowledge about the radiometric surface exploration, carried out in the geothermal field of Chipilapa, El Salvador, its were considered the geo-statistical parameters starting from the calculated variogram of the field data, being that the maxim distance of correlation of the samples in 'radon' in the different observation addresses (N-S, E-W, N W-S E, N E-S W), it was of 121 mts for the monitoring grill in future prospectus in the same area. Being derived of it an optimization (minimum cost) in the spacing of the field samples by means of geo-statistical techniques, without losing the detection of the anomaly. (Author)

  14. Geostatistical modeling of a fluviodeltaic reservoir in the Huyapari Field, Hamaca area, in the Faja Petrolifera del Orinoco, Venezuela

    Energy Technology Data Exchange (ETDEWEB)

    De Ascencao, Erika M.; Munckton, Toni; Digregorio, Ricardo [Petropiar (Venezuela)

    2011-07-01

    The Huyapari field, situated within the Faja Petrolifera del Orinoco (FPO) of Venezuela presents unique problems in terms of modeling. This field is spread over a wide area and is therefore subject to variable oil quality and complex fluvial facies architecture. Ameriven and PDVSA have been working on characterizing the ld's reservoirs in this field since 2000 and the aim of this paper is to present these efforts. Among others, a 3-D seismic survey completed in 1998 and a stratigraphic framework built from 149 vertical wells were used for reservoir characterization. Geostatistical techniques such as sequential Gaussian simulation with locally varying mean and cloud transform were also used. Results showed that these geostatistical methods accurately represented the architecture and properties of the reservoir and its fluid distribution. This paper showed that the application of numerous different techniques in the Hamasca area permitted reservoir complexity to be captured.

  15. Geostatistical Model-Based Estimates of Schistosomiasis Prevalence among Individuals Aged ≤20 Years in West Africa

    Science.gov (United States)

    Schur, Nadine; Hürlimann, Eveline; Garba, Amadou; Traoré, Mamadou S.; Ndir, Omar; Ratard, Raoult C.; Tchuem Tchuenté, Louis-Albert; Kristensen, Thomas K.; Utzinger, Jürg; Vounatsou, Penelope

    2011-01-01

    Background Schistosomiasis is a water-based disease that is believed to affect over 200 million people with an estimated 97% of the infections concentrated in Africa. However, these statistics are largely based on population re-adjusted data originally published by Utroska and colleagues more than 20 years ago. Hence, these estimates are outdated due to large-scale preventive chemotherapy programs, improved sanitation, water resources development and management, among other reasons. For planning, coordination, and evaluation of control activities, it is essential to possess reliable schistosomiasis prevalence maps. Methodology We analyzed survey data compiled on a newly established open-access global neglected tropical diseases database (i) to create smooth empirical prevalence maps for Schistosoma mansoni and S. haematobium for individuals aged ≤20 years in West Africa, including Cameroon, and (ii) to derive country-specific prevalence estimates. We used Bayesian geostatistical models based on environmental predictors to take into account potential clustering due to common spatially structured exposures. Prediction at unobserved locations was facilitated by joint kriging. Principal Findings Our models revealed that 50.8 million individuals aged ≤20 years in West Africa are infected with either S. mansoni, or S. haematobium, or both species concurrently. The country prevalence estimates ranged between 0.5% (The Gambia) and 37.1% (Liberia) for S. mansoni, and between 17.6% (The Gambia) and 51.6% (Sierra Leone) for S. haematobium. We observed that the combined prevalence for both schistosome species is two-fold lower in Gambia than previously reported, while we found an almost two-fold higher estimate for Liberia (58.3%) than reported before (30.0%). Our predictions are likely to overestimate overall country prevalence, since modeling was based on children and adolescents up to the age of 20 years who are at highest risk of infection. Conclusion/Significance We

  16. A Comparison of Traditional, Step-Path, and Geostatistical Techniques in the Stability Analysis of a Large Open Pit

    Science.gov (United States)

    Mayer, J. M.; Stead, D.

    2017-04-01

    With the increased drive towards deeper and more complex mine designs, geotechnical engineers are often forced to reconsider traditional deterministic design techniques in favour of probabilistic methods. These alternative techniques allow for the direct quantification of uncertainties within a risk and/or decision analysis framework. However, conventional probabilistic practices typically discretize geological materials into discrete, homogeneous domains, with attributes defined by spatially constant random variables, despite the fact that geological media display inherent heterogeneous spatial characteristics. This research directly simulates this phenomenon using a geostatistical approach, known as sequential Gaussian simulation. The method utilizes the variogram which imposes a degree of controlled spatial heterogeneity on the system. Simulations are constrained using data from the Ok Tedi mine site in Papua New Guinea and designed to randomly vary the geological strength index and uniaxial compressive strength using Monte Carlo techniques. Results suggest that conventional probabilistic techniques have a fundamental limitation compared to geostatistical approaches, as they fail to account for the spatial dependencies inherent to geotechnical datasets. This can result in erroneous model predictions, which are overly conservative when compared to the geostatistical results.

  17. Geostatistical prediction of microbial water quality throughout a stream network using meteorology, land cover, and spatiotemporal autocorrelation.

    Science.gov (United States)

    Holcomb, David Andrew; Messier, Kyle P; Serre, Marc L; Rowny, Jakob G; Stewart, Jill R

    2018-06-11

    Predictive modeling is promising as an inexpensive tool to assess water quality. We developed geostatistical predictive models of microbial water quality that empirically modelled spatiotemporal autocorrelation in measured fecal coliform (FC) bacteria concentrations to improve prediction. We compared five geostatistical models featuring different autocorrelation structures, fit to 676 observations from 19 locations in North Carolina's Jordan Lake watershed using meteorological and land cover predictor variables. Though stream distance metrics (with and without flow-weighting) failed to improve prediction over the Euclidean distance metric, incorporating temporal autocorrelation substantially improved prediction over the space-only models. We predicted FC throughout the stream network daily for one year, designating locations "impaired", "unimpaired", or "unassessed" if the probability of exceeding the state standard was >90%, 10% but <90%, respectively. We could assign impairment status to more of the stream network on days any FC were measured, suggesting frequent sample-based monitoring remains necessary, though implementing spatiotemporal predictive models may reduce the number of concurrent sampling locations required to adequately assess water quality. Together, these results suggest that prioritizing sampling at different times and conditions using geographically sparse monitoring networks is adequate to build robust and informative geostatistical models of water quality impairment.

  18. Multivariate Analysis and Modeling of Sediment Pollution Using Neural Network Models and Geostatistics

    Science.gov (United States)

    Golay, Jean; Kanevski, Mikhaïl

    2013-04-01

    The present research deals with the exploration and modeling of a complex dataset of 200 measurement points of sediment pollution by heavy metals in Lake Geneva. The fundamental idea was to use multivariate Artificial Neural Networks (ANN) along with geostatistical models and tools in order to improve the accuracy and the interpretability of data modeling. The results obtained with ANN were compared to those of traditional geostatistical algorithms like ordinary (co)kriging and (co)kriging with an external drift. Exploratory data analysis highlighted a great variety of relationships (i.e. linear, non-linear, independence) between the 11 variables of the dataset (i.e. Cadmium, Mercury, Zinc, Copper, Titanium, Chromium, Vanadium and Nickel as well as the spatial coordinates of the measurement points and their depth). Then, exploratory spatial data analysis (i.e. anisotropic variography, local spatial correlations and moving window statistics) was carried out. It was shown that the different phenomena to be modeled were characterized by high spatial anisotropies, complex spatial correlation structures and heteroscedasticity. A feature selection procedure based on General Regression Neural Networks (GRNN) was also applied to create subsets of variables enabling to improve the predictions during the modeling phase. The basic modeling was conducted using a Multilayer Perceptron (MLP) which is a workhorse of ANN. MLP models are robust and highly flexible tools which can incorporate in a nonlinear manner different kind of high-dimensional information. In the present research, the input layer was made of either two (spatial coordinates) or three neurons (when depth as auxiliary information could possibly capture an underlying trend) and the output layer was composed of one (univariate MLP) to eight neurons corresponding to the heavy metals of the dataset (multivariate MLP). MLP models with three input neurons can be referred to as Artificial Neural Networks with EXternal

  19. A comparison of geostatistically based inverse techniques for use in performance assessment analysis at the Waste Isolation Pilot Plant Site: Results from Test Case No. 1

    International Nuclear Information System (INIS)

    Zimmerman, D.A.; Gallegos, D.P.

    1993-10-01

    The groundwater flow pathway in the Culebra Dolomite aquifer at the Waste Isolation Pilot Plant (WIPP) has been identified as a potentially important pathway for radionuclide migration to the accessible environment. Consequently, uncertainties in the models used to describe flow and transport in the Culebra need to be addressed. A ''Geostatistics Test Problem'' is being developed to evaluate a number of inverse techniques that may be used for flow calculations in the WIPP performance assessment (PA). The Test Problem is actually a series of test cases, each being developed as a highly complex synthetic data set; the intent is for the ensemble of these data sets to span the range of possible conceptual models of groundwater flow at the WIPP site. The Test Problem analysis approach is to use a comparison of the probabilistic groundwater travel time (GWTT) estimates produced by each technique as the basis for the evaluation. Participants are given observations of head and transmissivity (possibly including measurement error) or other information such as drawdowns from pumping wells, and are asked to develop stochastic models of groundwater flow for the synthetic system. Cumulative distribution functions (CDFs) of groundwater flow (computed via particle tracking) are constructed using the head and transmissivity data generated through the application of each technique; one semi-analytical method generates the CDFs of groundwater flow directly. This paper describes the results from Test Case No. 1

  20. Information for decision making from imperfect national data: tracking major changes in health care use in Kenya using geostatistics

    Directory of Open Access Journals (Sweden)

    Hay Simon I

    2007-12-01

    Full Text Available Abstract Background Most Ministries of Health across Africa invest substantial resources in some form of health management information system (HMIS to coordinate the routine acquisition and compilation of monthly treatment and attendance records from health facilities nationwide. Despite the expense of these systems, poor data coverage means they are rarely, if ever, used to generate reliable evidence for decision makers. One critical weakness across Africa is the current lack of capacity to effectively monitor patterns of service use through time so that the impacts of changes in policy or service delivery can be evaluated. Here, we present a new approach that, for the first time, allows national changes in health service use during a time of major health policy change to be tracked reliably using imperfect data from a national HMIS. Methods Monthly attendance records were obtained from the Kenyan HMIS for 1 271 government-run and 402 faith-based outpatient facilities nationwide between 1996 and 2004. A space-time geostatistical model was used to compensate for the large proportion of missing records caused by non-reporting health facilities, allowing robust estimation of monthly and annual use of services by outpatients during this period. Results We were able to reconstruct robust time series of mean levels of outpatient utilisation of health facilities at the national level and for all six major provinces in Kenya. These plots revealed reliably for the first time a period of steady nationwide decline in the use of health facilities in Kenya between 1996 and 2002, followed by a dramatic increase from 2003. This pattern was consistent across different causes of attendance and was observed independently in each province. Conclusion The methodological approach presented can compensate for missing records in health information systems to provide robust estimates of national patterns of outpatient service use. This represents the first such use of

  1. Geostatistical analysis for soil moisture content under the no tillage cropping system Análise geoestatística do teor de água do solo sob sistema de cultivo em plantio direto

    Directory of Open Access Journals (Sweden)

    Célia Regina Grego

    2006-08-01

    Full Text Available Experiments in agriculture usually consider the topsoil properties to be uniform in space and, for this reason, often make inadequate use of the results. The objective of this study was to assess the variability for soil moisture content using geostatistical techniques. The experiment was carried out on a Rhodic Ferralsol (typic Haplorthox in Campinas, SP, Brazil, in an area of 3.42 ha cultivated under the no tillage system, and the sampling was made in a grid of 102 points spaced 10 m x 20 m. Access tubes were inserted down to one meter at each evaluation point in order to measure soil moisture contents (cm³ cm-3 at depths of 30, 60 and 90 cm with a neutron moisture gauge. Samplings were made between the months of August and September of 2003 and in January 2004. The soil moisture content for each sampling date was analyzed using classical statistics in order to appropriately describe the central tendency and dispersion on the data and then using geostatistics to describe the spatial variability. The comparison between the spatial variability for different samplings was made examining scaled semivariograms. Water content was mapped using interpolated values with punctual kriging. The semivariograms showed that, at the 60 cm depth, soil water content had moderate spatial dependence with ranges between 90 and 110 m. However, no spatial dependence was found for 30 and 90 cm depths in 2003. Sampling density was insufficient for an adequate characterization of the spatial variability of soil moisture contents at the 30 and 90 cm depths.Experimentos em agricultura geralmente consideram as propriedades do solo como sendo uniformes no espaço e, por esta razão, os resultados são freqüentemente mal interpretados. O objetivo deste estudo foi avaliar a variabilidade do teor de água do solo usando técnicas de geoestatística. O experimento foi desenvolvido em um Latossolo Vermelho eutroférrico, Campinas, SP, Brasil, numa área de 3,42 ha sob plantio

  2. Evaluation of roentgenologic study of the stomach

    International Nuclear Information System (INIS)

    Suh, Jung Ho; Choi, Byung So

    1972-01-01

    In order to achieve more correct diagnosis of gastric lesion, further progress in the technique of diagnosis is much desired. And so, in pursuing the more ideal study, about 7,500 cases of U. G. I. studies taken in Severance Hospital in the past 29 months from May 1969 to September 1971, have been reviewed to evaluate how the following factors will affect the demonstrability of gastric lesion in upper G. I. series. (1) Introduction of air into the stomach by nasogastric tube. (2) Kinds and concentration of barium. (3) Demonstrability according to the position of the patient. (4) Use of antispasmodics. The results may be briefly summarized as follows: 1. The intubation of nasogastric tube gives discomfort temporarily to the patient: however, it has an advantage that the amount of air required for ideal insufflation of the stomach can be controlled under the fluoroscopy. 2. About concentration and type of barium. a) Mikabarium in 90% seems to give the best result in filling study, mucosal relief study and double contrast study. b) Mikabarium in higher concentration adheres to the mucosa better, thus resulting in good double contrast: however, it tends to coagulate each other in the high concentration. c) Micropaque powder of 110% solution produces good double contrast, but it has the disadvantage of making air bubbles. d) When water is given prior to barium ingestion, the anterior wall of stomach is better demonstrated with mucosal relief study. e) To get better result in contrast study, the selection of barium is important as well as rapid and proper positioning of the patient and abdominal respiratory movement. 3. Demonstrability of the stomach lesion according to the position. a) The small lesion either in pylorus or in antrum can be best demonstrated by compression technique of double contrast method in supine position. b) The mucosal relief study in prone by adequate air insufflation was proper to demonstrate the lesion of anterior wall. c) In the lesion of the

  3. A general parallelization strategy for random path based geostatistical simulation methods

    Science.gov (United States)

    Mariethoz, Grégoire

    2010-07-01

    The size of simulation grids used for numerical models has increased by many orders of magnitude in the past years, and this trend is likely to continue. Efficient pixel-based geostatistical simulation algorithms have been developed, but for very large grids and complex spatial models, the computational burden remains heavy. As cluster computers become widely available, using parallel strategies is a natural step for increasing the usable grid size and the complexity of the models. These strategies must profit from of the possibilities offered by machines with a large number of processors. On such machines, the bottleneck is often the communication time between processors. We present a strategy distributing grid nodes among all available processors while minimizing communication and latency times. It consists in centralizing the simulation on a master processor that calls other slave processors as if they were functions simulating one node every time. The key is to decouple the sending and the receiving operations to avoid synchronization. Centralization allows having a conflict management system ensuring that nodes being simulated simultaneously do not interfere in terms of neighborhood. The strategy is computationally efficient and is versatile enough to be applicable to all random path based simulation methods.

  4. Forward modeling of gravity data using geostatistically generated subsurface density variations

    Science.gov (United States)

    Phelps, Geoffrey

    2016-01-01

    Using geostatistical models of density variations in the subsurface, constrained by geologic data, forward models of gravity anomalies can be generated by discretizing the subsurface and calculating the cumulative effect of each cell (pixel). The results of such stochastically generated forward gravity anomalies can be compared with the observed gravity anomalies to find density models that match the observed data. These models have an advantage over forward gravity anomalies generated using polygonal bodies of homogeneous density because generating numerous realizations explores a larger region of the solution space. The stochastic modeling can be thought of as dividing the forward model into two components: that due to the shape of each geologic unit and that due to the heterogeneous distribution of density within each geologic unit. The modeling demonstrates that the internally heterogeneous distribution of density within each geologic unit can contribute significantly to the resulting calculated forward gravity anomaly. Furthermore, the stochastic models match observed statistical properties of geologic units, the solution space is more broadly explored by producing a suite of successful models, and the likelihood of a particular conceptual geologic model can be compared. The Vaca Fault near Travis Air Force Base, California, can be successfully modeled as a normal or strike-slip fault, with the normal fault model being slightly more probable. It can also be modeled as a reverse fault, although this structural geologic configuration is highly unlikely given the realizations we explored.

  5. Spatiotemporal mapping of ground water pollution in a Greek lignite basin, using geostatistics

    International Nuclear Information System (INIS)

    Modis, K.

    2010-01-01

    An issue of significant interest in the mining industry in Greece is the occurrence of chemical pollutants in ground water. Ammonium, nitrites and nitrates concentrations have been monitored through an extensive sampling network in the Ptolemais lignite opencast mining area in Greece. Due to intensive mining efforts in the area, the surface topology is continuously altered, affecting the life span of the water boreholes and resulting in messy spatiotemporal distribution of data. This paper discussed the spatiotemporal mapping of ground water pollution in the Ptolemais lignite basin, using geostatistics. More specifically, the spatiotemporal distribution of ground water contamination was examined by the application of the bayesian maximum entropy theory which allows merging spatial and temporal estimations in a single model. The paper provided a description of the site and discussed the materials and methods, including samples and statistics; variography; and spatiotemporal mapping. It was concluded that in the case of the Ptolemais mining area, results revealed an underlying average yearly variation pattern of pollutant concentrations. Inspection of the produced spatiotemporal maps demonstrated a continuous increase in the risk of ammonium contamination, while risk for the other two pollutants appeared in hot spots. 18 refs., 1 tab., 7 figs.

  6. Determining site-specific background level with geostatistics for remediation of heavy metals in neighborhood soils

    Directory of Open Access Journals (Sweden)

    Tammy M. Milillo

    2017-03-01

    Full Text Available The choice of a relevant, uncontaminated site for the determination of site-specific background concentrations for pollutants is critical for planning remediation of a contaminated site. The guidelines used to arrive at concentration levels vary from state to state, complicating this process. The residential neighborhood of Hickory Woods in Buffalo, NY is an area where heavy metal concentrations and spatial distributions were measured to plan remediation. A novel geostatistics based decision making framework that relies on maps generated from indicator kriging (IK and indicator co-kriging (ICK of samples from the contaminated site itself is shown to be a viable alternative to the traditional method of choosing a reference site for remediation planning. GIS based IK and ICK, and map based analysis are performed on lead and arsenic surface and subsurface datasets to determine site-specific background concentration levels were determined to be 50 μg/g for lead and 10 μg/g for arsenic. With these results, a remediation plan was proposed which identified regions of interest and maps were created to effectively communicate the results to the environmental agencies, residents and other interested parties.

  7. A combined geostatistical-optimization model for the optimal design of a groundwater quality monitoring network

    Science.gov (United States)

    Kolosionis, Konstantinos; Papadopoulou, Maria P.

    2017-04-01

    Monitoring networks provide essential information for water resources management especially in areas with significant groundwater exploitation due to extensive agricultural activities. In this work, a simulation-optimization framework is developed based on heuristic optimization methodologies and geostatistical modeling approaches to obtain an optimal design for a groundwater quality monitoring network. Groundwater quantity and quality data obtained from 43 existing observation locations at 3 different hydrological periods in Mires basin in Crete, Greece will be used in the proposed framework in terms of Regression Kriging to develop the spatial distribution of nitrates concentration in the aquifer of interest. Based on the existing groundwater quality mapping, the proposed optimization tool will determine a cost-effective observation wells network that contributes significant information to water managers and authorities. The elimination of observation wells that add little or no beneficial information to groundwater level and quality mapping of the area can be obtain using estimations uncertainty and statistical error metrics without effecting the assessment of the groundwater quality. Given the high maintenance cost of groundwater monitoring networks, the proposed tool could used by water regulators in the decision-making process to obtain a efficient network design that is essential.

  8. A multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration.

    Science.gov (United States)

    Goovaerts, P; Albuquerque, Teresa; Antunes, Margarida

    2016-11-01

    This paper describes a multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration, with an application to an abandoned sedimentary gold mining region in Portugal. The main challenge was the existence of only a dozen gold measurements confined to the grounds of the old gold mines, which precluded the application of traditional interpolation techniques, such as cokriging. The analysis could, however, capitalize on 376 stream sediment samples that were analyzed for twenty two elements. Gold (Au) was first predicted at all 376 locations using linear regression (R 2 =0.798) and four metals (Fe, As, Sn and W), which are known to be mostly associated with the local gold's paragenesis. One hundred realizations of the spatial distribution of gold content were generated using sequential indicator simulation and a soft indicator coding of regression estimates, to supplement the hard indicator coding of gold measurements. Each simulated map then underwent a local cluster analysis to identify significant aggregates of low or high values. The one hundred classified maps were processed to derive the most likely classification of each simulated node and the associated probability of occurrence. Examining the distribution of the hot-spots and cold-spots reveals a clear enrichment in Au along the Erges River downstream from the old sedimentary mineralization.

  9. Assessing TCE source bioremediation by geostatistical analysis of a flux fence.

    Science.gov (United States)

    Cai, Zuansi; Wilson, Ryan D; Lerner, David N

    2012-01-01

    Mass discharge across transect planes is increasingly used as a metric for performance assessment of in situ groundwater remediation systems. Mass discharge estimates using concentrations measured in multilevel transects are often made by assuming a uniform flow field, and uncertainty contributions from spatial concentration and flow field variability are often overlooked. We extend our recently developed geostatistical approach to estimate mass discharge using transect data of concentration and hydraulic conductivity, so accounting for the spatial variability of both datasets. The magnitude and uncertainty of mass discharge were quantified by conditional simulation. An important benefit of the approach is that uncertainty is quantified as an integral part of the mass discharge estimate. We use this approach for performance assessment of a bioremediation experiment of a trichloroethene (TCE) source zone. Analyses of dissolved parent and daughter compounds demonstrated that the engineered bioremediation has elevated the degradation rate of TCE, resulting in a two-thirds reduction in the TCE mass discharge from the source zone. The biologically enhanced dissolution of TCE was not significant (~5%), and was less than expected. However, the discharges of the daughter products cis-1,2, dichloroethene (cDCE) and vinyl chloride (VC) increased, probably because of the rapid transformation of TCE from the source zone to the measurement transect. This suggests that enhancing the biodegradation of cDCE and VC will be crucial to successful engineered bioremediation of TCE source zones. © 2012, The Author(s). Ground Water © 2012, National Ground Water Association.

  10. Characterisation and geostatistical analysis of clay rocks in underground facilities using hyper-spectral images

    International Nuclear Information System (INIS)

    Becker, J.K.; Marschall, P.; Brunner, P.; Cholet, C.; Renard, P.; Buckley, S.; Kurz, T.

    2012-01-01

    Document available in extended abstract form only. Flow and transport processes in geological formations are controlled by the porosity and permeability which in turn are mainly controlled by the fabric and the mineralogical composition of the rock. For the assessment of transport processes in water-saturated Clay-stone formations, the relevant scales are ranging essentially from kilometers to nanometers. The spatial variability of the mineralogical composition is a key indicator for the separation of transport scales and for the derivation of the effective transport properties at a given scale. Various laboratory and in-situ techniques are available for characterizing the mineralogical composition of a rock on different scales. The imaging spectroscopy presented in this paper is a new site investigation method suitable for mapping the mineralogical composition of geological formations in 2D on a large range of scales. A combination of imaging spectrometry with other site characterization methods allows the inference of the spatial variability of the mineralogical composition in 3D over a wide range of scales with the help of advanced geostatistical methods. The method of image spectrometry utilizes the fact that the reflection of electromagnetic radiation from a surface is a function of the wavelength, the chemical-mineralogical surface properties, and physical parameters such as the grain size and surface roughness. In remote sensing applications using the sun as the light source, the reflectance is measured within the visible and infrared range, according to the atmospheric transmissibility. Many rock-forming minerals exhibit diagnostic absorption features within this range, which are caused by electronic and vibrational processes within the crystal lattice. The exact wavelength of an absorption feature is controlled by the type of ion, as well as the position of the ion within the lattice. Spectral signatures of minerals are described by a number of authors

  11. Geostatistical three-dimensional modeling of oolite shoals, St. Louis Limestone, southwest Kansas

    Science.gov (United States)

    Qi, L.; Carr, T.R.; Goldstein, R.H.

    2007-01-01

    In the Hugoton embayment of southwestern Kansas, reservoirs composed of relatively thin (Big Bow and Sand Arroyo Creek fields. Lithofacies in uncored wells were predicted from digital logs using a neural network. The tilting effect from the Laramide orogeny was removed to construct restored structural surfaces at the time of deposition. Well data and structural maps were integrated to build 3-D models of oolitic reservoirs using stochastic simulations with geometry data. Three-dimensional models provide insights into the distribution, the external and internal geometry of oolitic deposits, and the sedimentologic processes that generated reservoir intervals. The structural highs and general structural trend had a significant impact on the distribution and orientation of the oolitic complexes. The depositional pattern and connectivity analysis suggest an overall aggradation of shallow-marine deposits during pulses of relative sea level rise followed by deepening near the top of the St. Louis Limestone. Cemented oolitic deposits were modeled as barriers and baffles and tend to concentrate at the edge of oolitic complexes. Spatial distribution of porous oolitic deposits controls the internal geometry of rock properties. Integrated geostatistical modeling methods can be applicable to other complex carbonate or siliciclastic reservoirs in shallow-marine settings. Copyright ?? 2007. The American Association of Petroleum Geologists. All rights reserved.

  12. Geostatistical characterisation of geothermal parameters for a thermal aquifer storage site in Germany

    Science.gov (United States)

    Rodrigo-Ilarri, J.; Li, T.; Grathwohl, P.; Blum, P.; Bayer, P.

    2009-04-01

    The design of geothermal systems such as aquifer thermal energy storage systems (ATES) must account for a comprehensive characterisation of all relevant parameters considered for the numerical design model. Hydraulic and thermal conductivities are the most relevant parameters and its distribution determines not only the technical design but also the economic viability of such systems. Hence, the knowledge of the spatial distribution of these parameters is essential for a successful design and operation of such systems. This work shows the first results obtained when applying geostatistical techniques to the characterisation of the Esseling Site in Germany. In this site a long-term thermal tracer test (> 1 year) was performed. On this open system the spatial temperature distribution inside the aquifer was observed over time in order to obtain as much information as possible that yield to a detailed characterisation both of the hydraulic and thermal relevant parameters. This poster shows the preliminary results obtained for the Esseling Site. It has been observed that the common homogeneous approach is not sufficient to explain the observations obtained from the TRT and that parameter heterogeneity must be taken into account.

  13. Geostatistical methods for rock mass quality prediction using borehole and geophysical survey data

    Science.gov (United States)

    Chen, J.; Rubin, Y.; Sege, J. E.; Li, X.; Hehua, Z.

    2015-12-01

    For long, deep tunnels, the number of geotechnical borehole investigations during the preconstruction stage is generally limited. Yet tunnels are often constructed in geological structures with complex geometries, and in which the rock mass is fragmented from past structural deformations. Tunnel Geology Prediction (TGP) is a geophysical technique widely used during tunnel construction in China to ensure safety during construction and to prevent geological disasters. In this paper, geostatistical techniques were applied in order to integrate seismic velocity from TGP and borehole information into spatial predictions of RMR (Rock Mass Rating) in unexcavated areas. This approach is intended to apply conditional probability methods to transform seismic velocities to directly observed RMR values. The initial spatial distribution of RMR, inferred from the boreholes, was updated by including geophysical survey data in a co-kriging approach. The method applied to a real tunnel project shows significant improvements in rock mass quality predictions after including geophysical survey data, leading to better decision-making for construction safety design.

  14. Spatiotemporal mapping of ground water pollution in a Greek lignite basin, using geostatistics

    Energy Technology Data Exchange (ETDEWEB)

    Modis, K. [National Technical Univ. of Athens, Athens (Greece)

    2010-07-01

    An issue of significant interest in the mining industry in Greece is the occurrence of chemical pollutants in ground water. Ammonium, nitrites and nitrates concentrations have been monitored through an extensive sampling network in the Ptolemais lignite opencast mining area in Greece. Due to intensive mining efforts in the area, the surface topology is continuously altered, affecting the life span of the water boreholes and resulting in messy spatiotemporal distribution of data. This paper discussed the spatiotemporal mapping of ground water pollution in the Ptolemais lignite basin, using geostatistics. More specifically, the spatiotemporal distribution of ground water contamination was examined by the application of the bayesian maximum entropy theory which allows merging spatial and temporal estimations in a single model. The paper provided a description of the site and discussed the materials and methods, including samples and statistics; variography; and spatiotemporal mapping. It was concluded that in the case of the Ptolemais mining area, results revealed an underlying average yearly variation pattern of pollutant concentrations. Inspection of the produced spatiotemporal maps demonstrated a continuous increase in the risk of ammonium contamination, while risk for the other two pollutants appeared in hot spots. 18 refs., 1 tab., 7 figs.

  15. LSHSIM: A Locality Sensitive Hashing based method for multiple-point geostatistics

    Science.gov (United States)

    Moura, Pedro; Laber, Eduardo; Lopes, Hélio; Mesejo, Daniel; Pavanelli, Lucas; Jardim, João; Thiesen, Francisco; Pujol, Gabriel

    2017-10-01

    Reservoir modeling is a very important task that permits the representation of a geological region of interest, so as to generate a considerable number of possible scenarios. Since its inception, many methodologies have been proposed and, in the last two decades, multiple-point geostatistics (MPS) has been the dominant one. This methodology is strongly based on the concept of training image (TI) and the use of its characteristics, which are called patterns. In this paper, we propose a new MPS method that combines the application of a technique called Locality Sensitive Hashing (LSH), which permits to accelerate the search for patterns similar to a target one, with a Run-Length Encoding (RLE) compression technique that speeds up the calculation of the Hamming similarity. Experiments with both categorical and continuous images show that LSHSIM is computationally efficient and produce good quality realizations. In particular, for categorical data, the results suggest that LSHSIM is faster than MS-CCSIM, one of the state-of-the-art methods.

  16. Geostatistical analysis of tritium, groundwater age and other noble gas derived parameters in California.

    Science.gov (United States)

    Visser, A; Moran, J E; Hillegonds, Darren; Singleton, M J; Kulongoski, Justin T; Belitz, Kenneth; Esser, B K

    2016-03-15

    Key characteristics of California groundwater systems related to aquifer vulnerability, sustainability, recharge locations and mechanisms, and anthropogenic impact on recharge are revealed in a spatial geostatistical analysis of a unique data set of tritium, noble gases and other isotopic analyses unprecedented in size at nearly 4000 samples. The correlation length of key groundwater residence time parameters varies between tens of kilometers ((3)H; age) to the order of a hundred kilometers ((4)Heter; (14)C; (3)Hetrit). The correlation length of parameters related to climate, topography and atmospheric processes is on the order of several hundred kilometers (recharge temperature; δ(18)O). Young groundwater ages that highlight regional recharge areas are located in the eastern San Joaquin Valley, in the southern Santa Clara Valley Basin, in the upper LA basin and along unlined canals carrying Colorado River water, showing that much of the recent recharge in central and southern California is dominated by river recharge and managed aquifer recharge. Modern groundwater is found in wells with the top open intervals below 60 m depth in the southeastern San Joaquin Valley, Santa Clara Valley and Los Angeles basin, as the result of intensive pumping and/or managed aquifer recharge operations. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Mapping of Aspergillus Section Nigri in Southern Europe and Israel based on geostatistical analysis.

    Science.gov (United States)

    Battilani, P; Barbano, C; Marin, S; Sanchis, V; Kozakiewicz, Z; Magan, N

    2006-09-01

    Geostatistical analysis was applied to the incidence of Aspergillus Section Nigri and A. carbonarius in Southern Europe and Israel for the 3-year period 2001-2003 to facilitate identification of regions of high risk from contamination with these fungi and production of ochratoxin. The highest incidence of black aspergilli was normally observed at harvesting. At this grape growth stage, spatial variability of black aspergilli was significantly related to latitude and longitude, showing a positive West-East and North-South gradient. Predictive maps of infected berries incidence were drawn and showed the same trend in the 3 years, but incidence was highest in 2003, followed by 2001 and 2002. The highest incidence was always observed in Israel, Greece and Southern France, associated with the highest incidence of A. carbonarius. Southern Spain and Southern Italy also had relevant incidence of black aspergilli. The thermo-wetness maps for the 3 years showed a trend similar to the incidence of black aspergilli. The coldest and wettest year was 2002, while 2003 was the hottest and driest, particularly during August, with Israel being the hottest and driest country, followed by Greece and Southern Italy. This indicates that meteorological conditions can contribute to explain spatial distribution variation of black aspergilli within the Mediterranean basin.

  18. Geostatistical characterization of soil pollution at industrial sites Case of polycyclic aromatic hydrocarbons at former coking plants; Caracterisation geostatistique de pollutions industrielles de sols cas des hydrocarbures aromatiques polycycliques sur d'anciens sites de cokeries

    Energy Technology Data Exchange (ETDEWEB)

    Jeannee, N

    2001-05-15

    Estimating polycyclic aromatic hydrocarbons concentrations in soil at former industrial sites poses several practical problems on account of the properties of the contaminants and the history of site: 1)collection and preparation of samples from highly heterogeneous material, 2) high short scale variability, particularly in presence of backfill, 3) highly contrasted grades making the vario-gram inference complicated. The sampling strategy generally adopted for contaminated sites is based on the historical information. Systematic sampling recommended for geostatistical estimation is often considered to be excessive and unnecessary. Two former coking plants are used as test cases for comparing several geostatistical methods for estimating (i) in situ concentrations and (ii) the probability that they are above a pollution threshold. Several practical and methodological questions are considered: 1) the properties of various estimators of the experimental vario-gram and the validity of the results; 2) the use of soft data, such as historical information, organoleptic observations and semi-quantitative methods, with a view to improve the precision of the estimates; 3) the comparison of standard sampling strategies, taking into account vertical repartition of grades and the history of the site. Multiple analyses of the same sample give an approximation of the sampling error. Short scale sampling shows the difficulty of selecting soils in the absence of a spatial structure. Sensitivity studies are carried out to assess how densely sampled soft data can improve estimates. By using mainly existing models, this work aims at giving practical recommendations for the characterization of soil pollution. (author)

  19. Geostatistical characterization of soil pollution at industrial sites Case of polycyclic aromatic hydrocarbons at former coking plants; Caracterisation geostatistique de pollutions industrielles de sols cas des hydrocarbures aromatiques polycycliques sur d'anciens sites de cokeries

    Energy Technology Data Exchange (ETDEWEB)

    Jeannee, N.

    2001-05-15

    Estimating polycyclic aromatic hydrocarbons concentrations in soil at former industrial sites poses several practical problems on account of the properties of the contaminants and the history of site: 1)collection and preparation of samples from highly heterogeneous material, 2) high short scale variability, particularly in presence of backfill, 3) highly contrasted grades making the vario-gram inference complicated. The sampling strategy generally adopted for contaminated sites is based on the historical information. Systematic sampling recommended for geostatistical estimation is often considered to be excessive and unnecessary. Two former coking plants are used as test cases for comparing several geostatistical methods for estimating (i) in situ concentrations and (ii) the probability that they are above a pollution threshold. Several practical and methodological questions are considered: 1) the properties of various estimators of the experimental vario-gram and the validity of the results; 2) the use of soft data, such as historical information, organoleptic observations and semi-quantitative methods, with a view to improve the precision of the estimates; 3) the comparison of standard sampling strategies, taking into account vertical repartition of grades and the history of the site. Multiple analyses of the same sample give an approximation of the sampling error. Short scale sampling shows the difficulty of selecting soils in the absence of a spatial structure. Sensitivity studies are carried out to assess how densely sampled soft data can improve estimates. By using mainly existing models, this work aims at giving practical recommendations for the characterization of soil pollution. (author)

  20. Ground motion input in seismic evaluation studies

    International Nuclear Information System (INIS)

    Sewell, R.T.; Wu, S.C.

    1996-07-01

    This report documents research pertaining to conservatism and variability in seismic risk estimates. Specifically, it examines whether or not artificial motions produce unrealistic evaluation demands, i.e., demands significantly inconsistent with those expected from real earthquake motions. To study these issues, two types of artificial motions are considered: (a) motions with smooth response spectra, and (b) motions with realistic variations in spectral amplitude across vibration frequency. For both types of artificial motion, time histories are generated to match target spectral shapes. For comparison, empirical motions representative of those that might result from strong earthquakes in the Eastern U.S. are also considered. The study findings suggest that artificial motions resulting from typical simulation approaches (aimed at matching a given target spectrum) are generally adequate and appropriate in representing the peak-response demands that may be induced in linear structures and equipment responding to real earthquake motions. Also, given similar input Fourier energies at high-frequencies, levels of input Fourier energy at low frequencies observed for artificial motions are substantially similar to those levels noted in real earthquake motions. In addition, the study reveals specific problems resulting from the application of Western U.S. type motions for seismic evaluation of Eastern U.S. nuclear power plants

  1. Expermental Studies of quantitative evaluation using HPLC

    Directory of Open Access Journals (Sweden)

    Ki Rok Kwon

    2005-06-01

    Full Text Available Methods : This study was conducted to carry out quantitative evaluation using HPLC Content analysis was done using HPLC Results : According to HPLC analysis, each BVA-1 contained approximately 0.36㎍ melittin, and BVA-2 contained approximately 0.54㎍ melittin. But the volume of coating was so minute, slight difference exists between each needle. Conclusion : Above results indicate that the bee venom acupuncture can complement shortcomings of syringe usage as a part of Oriental medicine treatment, but extensive researches should be done for further verification.

  2. Geostatistical modeling of the gas emission zone and its in-place gas content for Pittsburgh-seam mines using sequential Gaussian simulation

    Science.gov (United States)

    Karacan, C.O.; Olea, R.A.; Goodman, G.

    2012-01-01

    Determination of the size of the gas emission zone, the locations of gas sources within, and especially the amount of gas retained in those zones is one of the most important steps for designing a successful methane control strategy and an efficient ventilation system in longwall coal mining. The formation of the gas emission zone and the potential amount of gas-in-place (GIP) that might be available for migration into a mine are factors of local geology and rock properties that usually show spatial variability in continuity and may also show geometric anisotropy. Geostatistical methods are used here for modeling and prediction of gas amounts and for assessing their associated uncertainty in gas emission zones of longwall mines for methane control.This study used core data obtained from 276 vertical exploration boreholes drilled from the surface to the bottom of the Pittsburgh coal seam in a mining district in the Northern Appalachian basin. After identifying important coal and non-coal layers for the gas emission zone, univariate statistical and semivariogram analyses were conducted for data from different formations to define the distribution and continuity of various attributes. Sequential simulations performed stochastic assessment of these attributes, such as gas content, strata thickness, and strata displacement. These analyses were followed by calculations of gas-in-place and their uncertainties in the Pittsburgh seam caved zone and fractured zone of longwall mines in this mining district. Grid blanking was used to isolate the volume over the actual panels from the entire modeled district and to calculate gas amounts that were directly related to the emissions in longwall mines.Results indicated that gas-in-place in the Pittsburgh seam, in the caved zone and in the fractured zone, as well as displacements in major rock units, showed spatial correlations that could be modeled and estimated using geostatistical methods. This study showed that GIP volumes may

  3. A new algorithm combining geostatistics with the surrogate data approach to increase the accuracy of comparisons of point radiation measurements with cloud measurements

    Science.gov (United States)

    Venema, V. K. C.; Lindau, R.; Varnai, T.; Simmer, C.

    2009-04-01

    Two main groups of statistical methods used in the Earth sciences are geostatistics and stochastic modelling. Geostatistical methods, such as various kriging algorithms, aim at estimating the mean value for every point as well as possible. In case of sparse measurements, such fields have less variability at small scales and a narrower distribution as the true field. This can lead to biases if a nonlinear process is simulated on such a kriged field. Stochastic modelling aims at reproducing the structure of the data. One of the stochastic modelling methods, the so-called surrogate data approach, replicates the value distribution and power spectrum of a certain data set. However, while stochastic methods reproduce the statistical properties of the data, the location of the measurement is not considered. Because radiative transfer through clouds is a highly nonlinear process it is essential to model the distribution (e.g. of optical depth, extinction, liquid water content or liquid water path) accurately as well as the correlations in the cloud field because of horizontal photon transport. This explains the success of surrogate cloud fields for use in 3D radiative transfer studies. However, up to now we could only achieve good results for the radiative properties averaged over the field, but not for a radiation measurement located at a certain position. Therefore we have developed a new algorithm that combines the accuracy of stochastic (surrogate) modelling with the positioning capabilities of kriging. In this way, we can automatically profit from the large geostatistical literature and software. The algorithm is tested on cloud fields from large eddy simulations (LES). On these clouds a measurement is simulated. From the pseudo-measurement we estimated the distribution and power spectrum. Furthermore, the pseudo-measurement is kriged to a field the size of the final surrogate cloud. The distribution, spectrum and the kriged field are the inputs to the algorithm. This

  4. Risk mapping of clonorchiasis in the People's Republic of China: A systematic review and Bayesian geostatistical analysis.

    Directory of Open Access Journals (Sweden)

    Ying-Si Lai

    2017-03-01

    Full Text Available Clonorchiasis, one of the most important food-borne trematodiases, affects more than 12 million people in the People's Republic of China (P.R. China. Spatially explicit risk estimates of Clonorchis sinensis infection are needed in order to target control interventions.Georeferenced survey data pertaining to infection prevalence of C. sinensis in P.R. China from 2000 onwards were obtained via a systematic review in PubMed, ISI Web of Science, Chinese National Knowledge Internet, and Wanfang Data from January 1, 2000 until January 10, 2016, with no restriction of language or study design. Additional disease data were provided by the National Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention in Shanghai. Environmental and socioeconomic proxies were extracted from remote-sensing and other data sources. Bayesian variable selection was carried out to identify the most important predictors of C. sinensis risk. Geostatistical models were applied to quantify the association between infection risk and the predictors of the disease, and to predict the risk of infection across P.R. China at high spatial resolution (over a grid with grid cell size of 5×5 km.We obtained clonorchiasis survey data at 633 unique locations in P.R. China. We observed that the risk of C. sinensis infection increased over time, particularly from 2005 onwards. We estimate that around 14.8 million (95% Bayesian credible interval 13.8-15.8 million people in P.R. China were infected with C. sinensis in 2010. Highly endemic areas (≥ 20% were concentrated in southern and northeastern parts of the country. The provinces with the highest risk of infection and the largest number of infected people were Guangdong, Guangxi, and Heilongjiang.Our results provide spatially relevant information for guiding clonorchiasis control interventions in P.R. China. The trend toward higher risk of C. sinensis infection in the recent past urges the Chinese government to

  5. Distribuição espacial de Huanglongbing (Greening em citros utilizando a geoestatística Spatial distribuition of Huanglongbing (Greening on citrus using geostatistic

    Directory of Open Access Journals (Sweden)

    Renata Moreira Leal

    2010-09-01

    Full Text Available Os objetivos do trabalho foram avaliar a distribuição espacial e a expansão da Huanglongbing (greening em talhões de citros de uma propriedade agrícola localizada no município de Araraquara-SP, utilizando a geoestatística. Para determinar o número de plantas com greening, foram realizadas inspeções periódicas em intervalos de três meses, no período de março de 2005 a julho de 2007, contando-se, em cada talhão, o número de plantas com os sintomas característicos da doença. Realizou-se a análise descritiva dos dados e, para verificar a distribuição espacial do greening, utilizou-se a geoestatística através do ajuste de semivariogramas e da interpolação dos dados por krigagem. A dependência espacial de plantas com greening apresentou raio de agregação de 300 a 560 m, indicando distribuição agregada da doença. Por meio dos mapas de krigagem, observou-se que o foco inicial de plantas doentes ocorreu nos limites da fazenda, com expansão do greening por toda a área. O intervalo de inspeção de três meses não foi adequado para a redução do greening na fazenda.The aim of this study was to use geostatistics to verify the spatial distribution of Huanglongbing (greening in oranges orchards on agricultural property located in the city of Araraquara, São Paulo. To determine the number of plants with greening, periodic inspections the three months were made from March 2005 until July 2007, counting the number of plants in each stand with the characteristic symptoms of the disease. A descriptive analysis of the data was undertaken, and geostatistics were used to verify the spatial distribution of greening through the adjustment of semivariograms and interpolation of data by kriging. The spatial dependence of plants with greening formed a beam of aggregation of 300 to 560 m, indicated an aggregated distribution of disease. Diagrams of kriging showed that initial focus of plants with greening started at the border in the

  6. Handling time in economic evaluation studies.

    Science.gov (United States)

    Permsuwan, Unchalee; Guntawongwan, Kansinee; Buddhawongsa, Piyaluk

    2014-05-01

    The discount rates and time horizons used in a health technology assessment (HTA) can have a significant impact on the results, and thus the prioritization of technologies. Therefore, it is important that clear guidance be provided on the appropriate discount rates for cost and health effect and appropriate time horizons. In this paper we conduct a review of relevant case studies and guidelines and provide guidance for all researchers conducting economic evaluations of health technologies in the Thai context. A uniform discount rate of 3% is recommended for both costs and health effects in base case analyses. A sensitivity analysis should also be conducted, with a discount range of 0-6%. For technologies where the effects are likely to sustain for at least 30y ears, a rate of 4% for costs and 2% for health effects is recommended. The time horizon should be long enough to capture the full costs and effects of the programs.

  7. Avisalmvac: evaluation studies of stability and toxicity

    Directory of Open Access Journals (Sweden)

    Daniela Botus,

    2008-12-01

    Full Text Available In Pasteur Institute laboratories there was developed AVISALMVAC, a vaccine against avian Salmonella, a biological product that contains S. enteritidis and S. typhimurium bacterin, with oil adjuvant. This paper presents the results of the studies regarding the stability and toxicity evaluation of this vaccine stored under conditions recommended by the manufacturer (2-80C at the end of the period of validity. The vaccine stability was assessed by serological and histopathological analysis of samples from SPF chickens vaccinated with the product at the end of the period of validity. The study of Avisalmvac toxicity was carried out by inoculation of the product or its components on Vero cell monolayer, and the effects were microscopically recorded or by MTT test, applied at 6 days post-inoculation. Antibody titers recorded at 2 and 3 weeks post vaccination demonstrated the vaccine ability (used after an year since manufacture to induce synthesis of specific antibodies and therefore, the product stability was proven. Histopathological examinations carried out on samples taken at 18 days post vaccinationfrom the vaccination site (skeletal muscle and skin and spleen, did not show any lesions associated to vaccination with Avisalmvac. The cytotoxicity analysis made by inoculating the vaccine or its components on Vero cell monolayer and the microscopic examination did not record visible cytopathic effects for any vaccine dilutions or vaccine components. The cell metabolism evaluation by MTT assay made at 6 days after vaccine/vaccine components inoculation on Vero monolayer, shown the ability of the vaccine and oil adjuvant to stimulate cell metabolism, and a certain degree of toxicity / inhibition of dehydrogenase metabolism associated to one of emulsifier but at dilutions higher than those used in the vaccine formula.

  8. Investigating Heuristic Evaluation: A Case Study.

    Science.gov (United States)

    Goldman, Kate Haley; Bendoly, Laura

    When museum professionals speak of evaluating a web site, they primarily mean formative evaluation, and by that they primarily mean testing the usability of the site. In the for-profit world, usability testing is a multi-million dollar industry, while non-profits often rely on far too few dollars to do too much. Hence, heuristic evaluation is one…

  9. A connectionist-geostatistical approach for classification of deformation types in ice surfaces

    Science.gov (United States)

    Goetz-Weiss, L. R.; Herzfeld, U. C.; Hale, R. G.; Hunke, E. C.; Bobeck, J.

    2014-12-01

    Deformation is a class of highly non-linear geophysical processes from which one can infer other geophysical variables in a dynamical system. For example, in an ice-dynamic model, deformation is related to velocity, basal sliding, surface elevation changes, and the stress field at the surface as well as internal to a glacier. While many of these variables cannot be observed, deformation state can be an observable variable, because deformation in glaciers (once a viscosity threshold is exceeded) manifests itself in crevasses.Given the amount of information that can be inferred from observing surface deformation, an automated method for classifying surface imagery becomes increasingly desirable. In this paper a Neural Network is used to recognize classes of crevasse types over the Bering Bagley Glacier System (BBGS) during a surge (2011-2013-?). A surge is a spatially and temporally highly variable and rapid acceleration of the glacier. Therefore, many different crevasse types occur in a short time frame and in close proximity, and these crevasse fields hold information on the geophysical processes of the surge.The connectionist-geostatistical approach uses directional experimental (discrete) variograms to parameterize images into a form that the Neural Network can recognize. Recognizing that each surge wave results in different crevasse types and that environmental conditions affect the appearance in imagery, we have developed a semi-automated pre-training software to adapt the Neural Net to chaining conditions.The method is applied to airborne and satellite imagery to classify surge crevasses from the BBGS surge. This method works well for classifying spatially repetitive images such as the crevasses over Bering Glacier. We expand the network for less repetitive images in order to analyze imagery collected over the Arctic sea ice, to assess the percentage of deformed ice for model calibration.

  10. Adjusting for sampling variability in sparse data: geostatistical approaches to disease mapping.

    Science.gov (United States)

    Hampton, Kristen H; Serre, Marc L; Gesink, Dionne C; Pilcher, Christopher D; Miller, William C

    2011-10-06

    Disease maps of crude rates from routinely collected health data indexed at a small geographical resolution pose specific statistical problems due to the sparse nature of the data. Spatial smoothers allow areas to borrow strength from neighboring regions to produce a more stable estimate of the areal value. Geostatistical smoothers are able to quantify the uncertainty in smoothed rate estimates without a high computational burden. In this paper, we introduce a uniform model extension of Bayesian Maximum Entropy (UMBME) and compare its performance to that of Poisson kriging in measures of smoothing strength and estimation accuracy as applied to simulated data and the real data example of HIV infection in North Carolina. The aim is to produce more reliable maps of disease rates in small areas to improve identification of spatial trends at the local level. In all data environments, Poisson kriging exhibited greater smoothing strength than UMBME. With the simulated data where the true latent rate of infection was known, Poisson kriging resulted in greater estimation accuracy with data that displayed low spatial autocorrelation, while UMBME provided more accurate estimators with data that displayed higher spatial autocorrelation. With the HIV data, UMBME performed slightly better than Poisson kriging in cross-validatory predictive checks, with both models performing better than the observed data model with no smoothing. Smoothing methods have different advantages depending upon both internal model assumptions that affect smoothing strength and external data environments, such as spatial correlation of the observed data. Further model comparisons in different data environments are required to provide public health practitioners with guidelines needed in choosing the most appropriate smoothing method for their particular health dataset.

  11. Adjusting for sampling variability in sparse data: geostatistical approaches to disease mapping

    Directory of Open Access Journals (Sweden)

    Pilcher Christopher D

    2011-10-01

    Full Text Available Abstract Background Disease maps of crude rates from routinely collected health data indexed at a small geographical resolution pose specific statistical problems due to the sparse nature of the data. Spatial smoothers allow areas to borrow strength from neighboring regions to produce a more stable estimate of the areal value. Geostatistical smoothers are able to quantify the uncertainty in smoothed rate estimates without a high computational burden. In this paper, we introduce a uniform model extension of Bayesian Maximum Entropy (UMBME and compare its performance to that of Poisson kriging in measures of smoothing strength and estimation accuracy as applied to simulated data and the real data example of HIV infection in North Carolina. The aim is to produce more reliable maps of disease rates in small areas to improve identification of spatial trends at the local level. Results In all data environments, Poisson kriging exhibited greater smoothing strength than UMBME. With the simulated data where the true latent rate of infection was known, Poisson kriging resulted in greater estimation accuracy with data that displayed low spatial autocorrelation, while UMBME provided more accurate estimators with data that displayed higher spatial autocorrelation. With the HIV data, UMBME performed slightly better than Poisson kriging in cross-validatory predictive checks, with both models performing better than the observed data model with no smoothing. Conclusions Smoothing methods have different advantages depending upon both internal model assumptions that affect smoothing strength and external data environments, such as spatial correlation of the observed data. Further model comparisons in different data environments are required to provide public health practitioners with guidelines needed in choosing the most appropriate smoothing method for their particular health dataset.

  12. A geostatistical approach to identify and mitigate agricultural nitrous oxide emission hotspots.

    Science.gov (United States)

    Turner, P A; Griffis, T J; Mulla, D J; Baker, J M; Venterea, R T

    2016-12-01

    Anthropogenic emissions of nitrous oxide (N 2 O), a trace gas with severe environmental costs, are greatest from agricultural soils amended with nitrogen (N) fertilizer. However, accurate N 2 O emission estimates at fine spatial scales are made difficult by their high variability, which represents a critical challenge for the management of N 2 O emissions. Here, static chamber measurements (n=60) and soil samples (n=129) were collected at approximately weekly intervals (n=6) for 42-d immediately following the application of N in a southern Minnesota cornfield (15.6-ha), typical of the systems prevalent throughout the U.S. Corn Belt. These data were integrated into a geostatistical model that resolved N 2 O emissions at a high spatial resolution (1-m). Field-scale N 2 O emissions exhibited a high degree of spatial variability, and were partitioned into three classes of emission strength: hotspots, intermediate, and coldspots. Rates of emission from hotspots were 2-fold greater than non-hotspot locations. Consequently, 36% of the field-scale emissions could be attributed to hotspots, despite representing only 21% of the total field area. Variations in elevation caused hotspots to develop in predictable locations, which were prone to nutrient and moisture accumulation caused by terrain focusing. Because these features are relatively static, our data and analyses indicate that targeted management of hotspots could efficiently reduce field-scale emissions by as much 17%, a significant benefit considering the deleterious effects of atmospheric N 2 O. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. UNCERT: geostatistics, uncertainty analysis and visualization software applied to groundwater flow and contaminant transport modeling

    International Nuclear Information System (INIS)

    Wingle, W.L.; Poeter, E.P.; McKenna, S.A.

    1999-01-01

    UNCERT is a 2D and 3D geostatistics, uncertainty analysis and visualization software package applied to ground water flow and contaminant transport modeling. It is a collection of modules that provides tools for linear regression, univariate statistics, semivariogram analysis, inverse-distance gridding, trend-surface analysis, simple and ordinary kriging and discrete conditional indicator simulation. Graphical user interfaces for MODFLOW and MT3D, ground water flow and contaminant transport models, are provided for streamlined data input and result analysis. Visualization tools are included for displaying data input and output. These include, but are not limited to, 2D and 3D scatter plots, histograms, box and whisker plots, 2D contour maps, surface renderings of 2D gridded data and 3D views of gridded data. By design, UNCERT's graphical user interface and visualization tools facilitate model design and analysis. There are few built in restrictions on data set sizes and each module (with two exceptions) can be run in either graphical or batch mode. UNCERT is in the public domain and is available from the World Wide Web with complete on-line and printable (PDF) documentation. UNCERT is written in ANSI-C with a small amount of FORTRAN77, for UNIX workstations running X-Windows and Motif (or Lesstif). This article discusses the features of each module and demonstrates how they can be used individually and in combination. The tools are applicable to a wide range of fields and are currently used by researchers in the ground water, mining, mathematics, chemistry and geophysics, to name a few disciplines. (Copyright (c) 1999 Elsevier Science B.V., Amsterdam. All rights reserved.)

  14. Massively Parallel Geostatistical Inversion of Coupled Processes in Heterogeneous Porous Media

    Science.gov (United States)

    Ngo, A.; Schwede, R. L.; Li, W.; Bastian, P.; Ippisch, O.; Cirpka, O. A.

    2012-04-01

    The quasi-linear geostatistical approach is an inversion scheme that can be used to estimate the spatial distribution of a heterogeneous hydraulic conductivity field. The estimated parameter field is considered to be a random variable that varies continuously in space, meets the measurements of dependent quantities (such as the hydraulic head, the concentration of a transported solute or its arrival time) and shows the required spatial correlation (described by certain variogram models). This is a method of conditioning a parameter field to observations. Upon discretization, this results in as many parameters as elements of the computational grid. For a full three dimensional representation of the heterogeneous subsurface it is hardly sufficient to work with resolutions (up to one million parameters) of the model domain that can be achieved on a serial computer. The forward problems to be solved within the inversion procedure consists of the elliptic steady-state groundwater flow equation and the formally elliptic but nearly hyperbolic steady-state advection-dominated solute transport equation in a heterogeneous porous medium. Both equations are discretized by Finite Element Methods (FEM) using fully scalable domain decomposition techniques. Whereas standard conforming FEM is sufficient for the flow equation, for the advection dominated transport equation, which rises well known numerical difficulties at sharp fronts or boundary layers, we use the streamline diffusion approach. The arising linear systems are solved using efficient iterative solvers with an AMG (algebraic multigrid) pre-conditioner. During each iteration step of the inversion scheme one needs to solve a multitude of forward and adjoint problems in order to calculate the sensitivities of each measurement and the related cross-covariance matrix of the unknown parameters and the observations. In order to reduce interprocess communications and to improve the scalability of the code on larger clusters

  15. Reservoir Characterization using geostatistical and numerical modeling in GIS with noble gas geochemistry

    Science.gov (United States)

    Vasquez, D. A.; Swift, J. N.; Tan, S.; Darrah, T. H.

    2013-12-01

    The integration of precise geochemical analyses with quantitative engineering modeling into an interactive GIS system allows for a sophisticated and efficient method of reservoir engineering and characterization. Geographic Information Systems (GIS) is utilized as an advanced technique for oil field reservoir analysis by combining field engineering and geological/geochemical spatial datasets with the available systematic modeling and mapping methods to integrate the information into a spatially correlated first-hand approach in defining surface and subsurface characteristics. Three key methods of analysis include: 1) Geostatistical modeling to create a static and volumetric 3-dimensional representation of the geological body, 2) Numerical modeling to develop a dynamic and interactive 2-dimensional model of fluid flow across the reservoir and 3) Noble gas geochemistry to further define the physical conditions, components and history of the geologic system. Results thus far include using engineering algorithms for interpolating electrical well log properties across the field (spontaneous potential, resistivity) yielding a highly accurate and high-resolution 3D model of rock properties. Results so far also include using numerical finite difference methods (crank-nicholson) to solve for equations describing the distribution of pressure across field yielding a 2D simulation model of fluid flow across reservoir. Ongoing noble gas geochemistry results will also include determination of the source, thermal maturity and the extent/style of fluid migration (connectivity, continuity and directionality). Future work will include developing an inverse engineering algorithm to model for permeability, porosity and water saturation.This combination of new and efficient technological and analytical capabilities is geared to provide a better understanding of the field geology and hydrocarbon dynamics system with applications to determine the presence of hydrocarbon pay zones (or

  16. Statistical Analyses of Second Indoor Bio-Release Field Evaluation Study at Idaho National Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    Amidan, Brett G.; Pulsipher, Brent A.; Matzke, Brett D.

    2009-12-17

    In September 2008 a large-scale testing operation (referred to as the INL-2 test) was performed within a two-story building (PBF-632) at the Idaho National Laboratory (INL). The report “Operational Observations on the INL-2 Experiment” defines the seven objectives for this test and discusses the results and conclusions. This is further discussed in the introduction of this report. The INL-2 test consisted of five tests (events) in which a floor (level) of the building was contaminated with the harmless biological warfare agent simulant Bg and samples were taken in most, if not all, of the rooms on the contaminated floor. After the sampling, the building was decontaminated, and the next test performed. Judgmental samples and probabilistic samples were determined and taken during each test. Vacuum, wipe, and swab samples were taken within each room. The purpose of this report is to study an additional four topics that were not within the scope of the original report. These topics are: 1) assess the quantitative assumptions about the data being normally or log-normally distributed; 2) evaluate differences and quantify the sample to sample variability within a room and across the rooms; 3) perform geostatistical types of analyses to study spatial correlations; and 4) quantify the differences observed between surface types and sampling methods for each scenario and study the consistency across the scenarios. The following four paragraphs summarize the results of each of the four additional analyses. All samples after decontamination came back negative. Because of this, it was not appropriate to determine if these clearance samples were normally distributed. As Table 1 shows, the characterization data consists of values between and inclusive of 0 and 100 CFU/cm2 (100 was the value assigned when the number is too numerous to count). The 100 values are generally much bigger than the rest of the data, causing the data to be right skewed. There are also a significant

  17. Lattice Boltzmann Simulations of Fluid Flow in Continental Carbonate Reservoir Rocks and in Upscaled Rock Models Generated with Multiple-Point Geostatistics

    Directory of Open Access Journals (Sweden)

    J. Soete

    2017-01-01

    Full Text Available Microcomputed tomography (μCT and Lattice Boltzmann Method (LBM simulations were applied to continental carbonates to quantify fluid flow. Fluid flow characteristics in these complex carbonates with multiscale pore networks are unique and the applied method allows studying their heterogeneity and anisotropy. 3D pore network models were introduced to single-phase flow simulations in Palabos, a software tool for particle-based modelling of classic computational fluid dynamics. In addition, permeability simulations were also performed on rock models generated with multiple-point geostatistics (MPS. This allowed assessing the applicability of MPS in upscaling high-resolution porosity patterns into large rock models that exceed the volume limitations of the μCT. Porosity and tortuosity control fluid flow in these porous media. Micro- and mesopores influence flow properties at larger scales in continental carbonates. Upscaling with MPS is therefore necessary to overcome volume-resolution problems of CT scanning equipment. The presented LBM-MPS workflow is applicable to other lithologies, comprising different pore types, shapes, and pore networks altogether. The lack of straightforward porosity-permeability relationships in complex carbonates highlights the necessity for a 3D approach. 3D fluid flow studies provide the best understanding of flow through porous media, which is of crucial importance in reservoir modelling.

  18. Modern space/time geostatistics using river distances: data integration of turbidity and E. coli measurements to assess fecal contamination along the Raritan River in New Jersey.

    Science.gov (United States)

    Money, Eric S; Carter, Gail P; Serre, Marc L

    2009-05-15

    Escherichia coli (E. coli) is a widely used indicator of fecal contamination in water bodies. External contact and subsequent ingestion of bacteria coming from fecal contamination can lead to harmful health effects. Since E. coli data are sometimes limited, the objective of this study is to use secondary information in the form of turbidity to improve the assessment of E. coli at unmonitored locations. We obtained all E. coli and turbidity monitoring data available from existing monitoring networks for the 2000-2006 time period for the Raritan River Basin, New Jersey. Using collocated measurements, we developed a predictive model of E. coli from turbidity data. Using this model, soft data are constructed for E. coli given turbidity measurements at 739 space/time locations where only turbidity was measured. Finally, the Bayesian Maximum Entropy (BME) method of modern space/time geostatistics was used for the data integration of monitored and predicted E. coli data to produce maps showing E. coli concentration estimated daily across the river basin. The addition of soft data in conjunction with the use of river distances reduced estimation error by about 30%. Furthermore, based on these maps, up to 35% of river miles in the Raritan Basin had a probability of E coli impairment greater than 90% on the most polluted day of the study period.

  19. Improving Classification of Airborne Laser Scanning Echoes in the Forest-Tundra Ecotone Using Geostatistical and Statistical Measures

    Directory of Open Access Journals (Sweden)

    Nadja Stumberg

    2014-05-01

    Full Text Available The vegetation in the forest-tundra ecotone zone is expected to be highly affected by climate change and requires effective monitoring techniques. Airborne laser scanning (ALS has been proposed as a tool for the detection of small pioneer trees for such vast areas using laser height and intensity data. The main objective of the present study was to assess a possible improvement in the performance of classifying tree and nontree laser echoes from high-density ALS data. The data were collected along a 1000 km long transect stretching from southern to northern Norway. Different geostatistical and statistical measures derived from laser height and intensity values were used to extent and potentially improve more simple models ignoring the spatial context. Generalised linear models (GLM and support vector machines (SVM were employed as classification methods. Total accuracies and Cohen’s kappa coefficients were calculated and compared to those of simpler models from a previous study. For both classification methods, all models revealed total accuracies similar to the results of the simpler models. Concerning classification performance, however, the comparison of the kappa coefficients indicated a significant improvement for some models both using GLM and SVM, with classification accuracies >94%.

  20. Identification of the Hydrogeochemical Processes in Groundwater Using Classic Integrated Geochemical Methods and Geostatistical Techniques, in Amol-Babol Plain, Iran

    Science.gov (United States)

    Sheikhy Narany, Tahoora; Ramli, Mohammad Firuz; Aris, Ahmad Zaharin; Sulaiman, Wan Nor Azmin; Juahir, Hafizan; Fakharian, Kazem

    2014-01-01

    Hydrogeochemical investigations had been carried out at the Amol-Babol Plain in the north of Iran. Geochemical processes and factors controlling the groundwater chemistry are identified based on the combination of classic geochemical methods with geographic information system (GIS) and geostatistical techniques. The results of the ionic ratios and Gibbs plots show that water rock interaction mechanisms, followed by cation exchange, and dissolution of carbonate and silicate minerals have influenced the groundwater chemistry in the study area. The hydrogeochemical characteristics of groundwater show a shift from low mineralized Ca-HCO3, Ca-Na-HCO3, and Ca-Cl water types to high mineralized Na-Cl water type. Three classes, namely, C1, C2, and C3, have been classified using cluster analysis. The spatial distribution maps of Na+/Cl−, Mg2+/Ca2+, and Cl−/HCO3 − ratios and electrical conductivity values indicate that the carbonate and weathering of silicate minerals played a significant role in the groundwater chemistry on the southern and western sides of the plain. However, salinization process had increased due to the influence of the evaporation-precipitation process towards the north-eastern side of the study area. PMID:24523640

  1. Application of multiple-point geostatistics to simulate the effect of small-scale aquifer heterogeneity on the efficiency of aquifer thermal energy storage

    Science.gov (United States)

    Possemiers, Mathias; Huysmans, Marijke; Batelaan, Okke

    2015-08-01

    Adequate aquifer characterization and simulation using heat transport models are indispensible for determining the optimal design for aquifer thermal energy storage (ATES) systems and wells. Recent model studies indicate that meter-scale heterogeneities in the hydraulic conductivity field introduce a considerable uncertainty in the distribution of thermal energy around an ATES system and can lead to a reduction in the thermal recoverability. In a study site in Bierbeek, Belgium, the influence of centimeter-scale clay drapes on the efficiency of a doublet ATES system and the distribution of the thermal energy around the ATES wells are quantified. Multiple-point geostatistical simulation of edge properties is used to incorporate the clay drapes in the models. The results show that clay drapes have an influence both on the distribution of thermal energy in the subsurface and on the efficiency of the ATES system. The distribution of the thermal energy is determined by the strike of the clay drapes, with the major axis of anisotropy parallel to the clay drape strike. The clay drapes have a negative impact (3.3-3.6 %) on the energy output in the models without a hydraulic gradient. In the models with a hydraulic gradient, however, the presence of clay drapes has a positive influence (1.6-10.2 %) on the energy output of the ATES system. It is concluded that it is important to incorporate small-scale heterogeneities in heat transport models to get a better estimate on ATES efficiency and distribution of thermal energy.

  2. HRCT evaluation of microtia: A retrospective study

    Directory of Open Access Journals (Sweden)

    Aruna R Patil

    2012-01-01

    Full Text Available Purpose: To determine external, middle, and inner ear abnormalities on high-resolution computed tomography (HRCT of temporal bone in patients with microtia and to predict anatomic external and middle ear anomalies as well as the degree of functional hearing impairment based on clinical grades of microtia. Materials and Methods: It was a retrospective study conducted on Indian population. Fifty-two patients with microtia were evaluated for external, middle, and inner ear anomalies on HRCT of temporal bone. Clinical grading of microtia was done based on criteria proposed by Weerda et al. in 37 patients and degree of hearing loss was assessed using pure tone audiometry or brainstem-evoked response in 32 patients. Independent statistical correlations of clinical grades of micotia with both external and middle ear anomalies detected on HRCT and the degree of hearing loss were finally obtained. Results: The external, middle, and inner ear anomalies were present in 93.1%, 74.5%, and 2.7% patients, respectively. Combined cartilaginous and bony external auditory canal atresia (EAC was the most common anatomic abnormality in our group of microtia patients. Hypoplastic mesotympanum represented the commonest middle ear anomaly. The incidence of combined ossicular dysplasia and facial canal anomalies was lower as compared to other population groups; however, we recorded a greater incidence of cholesteatoma. Both these factors can have a substantial impact on outcome of patients planned for surgery. We found no significant association between grades of microtia and external or middle ear anomalies. Similarly, no significant association was found between lower grades of microtia (grade I and II and degree of hearing loss. However, association between grade III microtia and degree of hearing loss was significant. A significant association between congenital cholesteatoma and degree of pneumatization of atretic plate and mastoid process not previously studied

  3. HRCT evaluation of microtia: A retrospective study

    International Nuclear Information System (INIS)

    Patil, Aruna R; Bhalla, Ashu; Gupta, Pankaj; Goyal, Deepali; Vishnubhatla, Sreenivas; Ramavat, Anurag; Sharma, Suresh

    2012-01-01

    To determine external, middle, and inner ear abnormalities on high-resolution computed tomography (HRCT) of temporal bone in patients with microtia and to predict anatomic external and middle ear anomalies as well as the degree of functional hearing impairment based on clinical grades of microtia. It was a retrospective study conducted on Indian population. Fifty-two patients with microtia were evaluated for external, middle, and inner ear anomalies on HRCT of temporal bone. Clinical grading of microtia was done based on criteria proposed by Weerda et al. in 37 patients and degree of hearing loss was assessed using pure tone audiometry or brainstem-evoked response in 32 patients. Independent statistical correlations of clinical grades of micotia with both external and middle ear anomalies detected on HRCT and the degree of hearing loss were finally obtained. The external, middle, and inner ear anomalies were present in 93.1%, 74.5%, and 2.7% patients, respectively. Combined cartilaginous and bony external auditory canal atresia (EAC) was the most common anatomic abnormality in our group of microtia patients. Hypoplastic mesotympanum represented the commonest middle ear anomaly. The incidence of combined ossicular dysplasia and facial canal anomalies was lower as compared to other population groups; however, we recorded a greater incidence of cholesteatoma. Both these factors can have a substantial impact on outcome of patients planned for surgery. We found no significant association between grades of microtia and external or middle ear anomalies. Similarly, no significant association was found between lower grades of microtia (grade I and II) and degree of hearing loss. However, association between grade III microtia and degree of hearing loss was significant. A significant association between congenital cholesteatoma and degree of pneumatization of atretic plate and mastoid process not previously studied was also recorded in our study

  4. Economic evaluation of CISM : a pilot study

    DEFF Research Database (Denmark)

    Vogt, Joachim

    2004-01-01

    air traffic controllers, critical incident stress management, CISM, critical incidents, critical incident stress, cost-benefit-analysis, economic evaluation, efficiency, return on investment......air traffic controllers, critical incident stress management, CISM, critical incidents, critical incident stress, cost-benefit-analysis, economic evaluation, efficiency, return on investment...

  5. Application of multiple-point geostatistics to simulate the effect of small scale aquifer heterogeneity on the efficiency of Aquifer Thermal Energy Storage (ATES)

    Science.gov (United States)

    Possemiers, Mathias; Huysmans, Marijke; Batelaan, Okke

    2015-04-01

    Adequate aquifer characterization and simulation using heat transport models are indispensible for determining the optimal design for Aquifer Thermal Energy Storage (ATES) systems and wells. Recent model studies indicate that meter scale heterogeneities in the hydraulic conductivity field introduce a considerable uncertainty in the distribution of thermal energy around an ATES system and can lead to a reduction in the thermal recoverability. In this paper, the influence of centimeter scale clay drapes on the efficiency of a doublet ATES system and the distribution of the thermal energy around the ATES wells are quantified. Multiple-point geostatistical simulation of edge properties is used to incorporate the clay drapes in the models. The results show that clay drapes have an influence both on the distribution of thermal energy in the subsurface and on the efficiency of the ATES system. The distribution of the thermal energy is determined by the strike of the clay drapes, with the major axis of anisotropy parallel to the clay drape strike. The clay drapes have a negative impact (3.3 - 3.6%) on the energy output in the models without a hydraulic gradient. In the models with a hydraulic gradient, however, the presence of clay drapes has a positive influence (1.6 - 10.2%) on the energy output of the ATES system. It is concluded that it is important to incorporate small scale heterogeneities in heat transport models to get a better estimate on ATES efficiency and distribution of thermal energy.

  6. Geostatistical Modelling of the Travertine Formation Associated with the Alicun de las Torres Thermal System by Using Electrical Tomography and Porosity Data

    International Nuclear Information System (INIS)

    Prado Perez, A. J.; Aracil, E.; Perez del Villar, L.

    2010-01-01

    In the framework of a Singular Strategic Project entitled: Advanced Technologies of Carbon, Capture and Storage (CCS)1', supported by the MICINN (Spain) and the FEDER founds (EU), specifically in the Carbon Storage Task, a comprehensive study on the CO 2 leakage as DIG (Dissolved Inorganic Carbon) in the Alicun de Las Torres (Prov. of Granada) natural analogue thermal system was envisaged. This analogous system is characterised by the presence of a very important travertine formation, which can be considered as a permanent and stable sink for CO 2 . Consequently, the estimation of the travertine mass has been a main objective of this investigation. For that, data from two complementary electrical tomography campaigns, previously treated by a powerful geostatistical tool, have been used, as well as the porosity average value of this travertine and the calcite density. Besides this, the statistical methodology applied has also allowed the establishment of a 3-D model of the travertine formation, displaying the geological contact between this formation and the underlying materials, as well as the contacts among the three units forming the travertine formation. (Author) 23 refs.

  7. Geographical distribution of the annual mean radon concentrations in primary schools of Southern Serbia – application of geostatistical methods

    International Nuclear Information System (INIS)

    Bossew, P.; Žunić, Z.S.; Stojanovska, Z.; Tollefsen, T.; Carpentieri, C.; Veselinović, N.; Komatina, S.; Vaupotič, J.; Simović, R.D.; Antignani, S.; Bochicchio, F.

    2014-01-01

    Between 2008 and 2011 a survey of radon ( 222 Rn) was performed in schools of several districts of Southern Serbia. Some results have been published previously (Žunić et al., 2010; Carpentieri et al., 2011; Žunić et al., 2013). This article concentrates on the geographical distribution of the measured Rn concentrations. Applying geostatistical methods we generate “school radon maps” of expected concentrations and of estimated probabilities that a concentration threshold is exceeded. The resulting maps show a clearly structured spatial pattern which appears related to the geological background. In particular in areas with vulcanite and granitoid rocks, elevated radon (Rn) concentrations can be expected. The “school radon map” can therefore be considered as proxy to a map of the geogenic radon potential, and allows identification of radon-prone areas, i.e. areas in which higher Rn radon concentrations can be expected for natural reasons. It must be stressed that the “radon hazard”, or potential risk, estimated this way, has to be distinguished from the actual radon risk, which is a function of exposure. This in turn may require (depending on the target variable which is supposed to measure risk) considering demographic and sociological reality, i.e. population density, distribution of building styles and living habits. -- Highlights: • A map of Rn concentrations in primary schools of Southern Serbia. • Application of geostatistical methods. • Correlation with geology found. • Can serve as proxy to identify radon prone areas

  8. Effective property determination for input to a geostatistical model of regional groundwater flow: Wellenberg T→K

    International Nuclear Information System (INIS)

    Lanyon, G.W.; Marschall, P.; Vomvoris, S.; Jaquet, O.; Mazurek, M.

    1998-01-01

    This paper describes the methodology used to estimate effective hydraulic properties for input into a regional geostatistical model of groundwater flow at the Wellenberg site in Switzerland. The methodology uses a geologically-based discrete fracture network model to calculate effective hydraulic properties for 100m blocks along each borehole. A description of the most transmissive features (Water Conducting Features or WCFs) in each borehole is used to determine local transmissivity distributions which are combined with descriptions of WCF extent, orientation and channelling to create fracture network models. WCF geometry is dependent on the class of WCF. WCF classes are defined for each type of geological structure associated with identified borehole inflows. Local to each borehole, models are conditioned on the observed transmissivity and occurrence of WCFs. Multiple realisations are calculated for each 100m block over approximately 400m of borehole. The results from the numerical upscaling are compared with conservative estimates of hydraulic conductivity. Results from unconditioned models are also compared to identify the consequences of conditioning and interval of boreholes that appear to be atypical. An inverse method is also described by which realisations of the geostatistical model can be used to condition discrete fracture network models away from the boreholes. The method can be used as a verification of the modelling approach by prediction of data at borehole locations. Applications of the models to estimation of post-closure repository performance, including cavern inflow and seal zone modelling, are illustrated

  9. Geostatistical and adjoint sensitivity techniques applied to a conceptual model of ground-water flow in the Paradox Basin, Utah

    International Nuclear Information System (INIS)

    Metcalfe, D.E.; Campbell, J.E.; RamaRao, B.S.; Harper, W.V.; Battelle Project Management Div., Columbus, OH)

    1985-01-01

    Sensitivity and uncertainty analysis are important components of performance assessment activities for potential high-level radioactive waste repositories. The application of geostatistical and adjoint sensitivity techniques to aid in the calibration of an existing conceptual model of ground-water flow is demonstrated for the Leadville Limestone in Paradox Basin, Utah. The geostatistical method called kriging is used to statistically analyze the measured potentiometric data for the Leadville. This analysis consists of identifying anomalous data and data trends and characterizing the correlation structure between data points. Adjoint sensitivity analysis is then performed to aid in the calibration of a conceptual model of ground-water flow to the Leadville measured potentiometric data. Sensitivity derivatives of the fit between the modeled Leadville potentiometric surface and the measured potentiometric data to model parameters and boundary conditions are calculated by the adjoint method. These sensitivity derivatives are used to determine which model parameter and boundary condition values should be modified to most efficiently improve the fit of modeled to measured potentiometric conditions

  10. A Computer Program for Practical Semivariogram Modeling and Ordinary Kriging: A Case Study of Porosity Distribution in an Oil Field

    Directory of Open Access Journals (Sweden)

    Mert Bayram Ali

    2017-12-01

    Full Text Available In this study, firstly, a practical and educational geostatistical program (JeoStat was developed, and then example analysis of porosity parameter distribution, using oilfield data, was presented.

  11. WMC Database Evaluation. Case Study Report

    Energy Technology Data Exchange (ETDEWEB)

    Palounek, Andrea P. T [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2015-10-29

    The WMC Database is ultimately envisioned to hold a collection of experimental data, design information, and information from computational models. This project was a first attempt at using the Database to access experimental data and extract information from it. This evaluation shows that the Database concept is sound and robust, and that the Database, once fully populated, should remain eminently usable for future researchers.

  12. Appraisal of family doctors: an evaluation study.

    NARCIS (Netherlands)

    Lewis, M.I.; Elwyn, G.; Wood, F.

    2003-01-01

    BACKGROUND: Appraisal has evolved to become a key component of workforce management. However, it is not clear from existing proposals for appraisal of doctors whether employers, health authorities or primary care organisations should take responsibility for appraisal processes. AIMS: To evaluate the

  13. An Evaluative Study of Clinical Preceptorship.

    Science.gov (United States)

    Kaviani, Nayer; Stillwell, Yvonne

    2000-01-01

    A training institute to prepare nurses to serve as preceptors of undergraduate clinical experience was evaluated by focus groups of 6 preceptors, 13 students, and 2 nurse managers. Formal preceptorship training enhanced student learning and promoted positive relationships between nurse educators and practitioners. (SK)

  14. Evaluation of multi-outcome longitudinal studies

    DEFF Research Database (Denmark)

    Jensen, Signe Marie; Pipper, Christian Bressen; Ritz, Christian

    2015-01-01

    Evaluation of intervention effects on multiple outcomes is a common scenario in clinical studies. In longitudinal studies, such evaluation is a challenge if one wishes to adequately capture simultaneous data behavior. In this situation, a common approach is to analyze each outcome separately...... conservative conclusions. We propose an alternative approach for multiplicity adjustment that incorporates dependence between outcomes, resulting in an appreciably less conservative evaluation. The ability of the proposed method to control the familywise error rate is evaluated in a simulation study...

  15. Geostatistical and stratigraphic analysis of deltaic reservoirs from the Reconcavo Basin, Brazil; Analise estratigrafica e geoestatistica de reservatorios deltaicos da Bacia do Reconcavo (BA)

    Energy Technology Data Exchange (ETDEWEB)

    Soares, Carlos Moreira

    1997-07-01

    This study presents the characterization of the external geometry of deltaic oil reservoirs, including the description of their areal distribution using geo statistic tools, such as variography and kriging. A high-resolution stratigraphic study was developed over a 25 km{sup 2} area, by using data from 276 closely-spaced wells of an oil-producer field from the Reconcavo Basin, northeastern Brazil. The studied succession records the progressive lacustrine transgression of a deltaic environment. Core data and stratigraphic cross sections suggest that the oil reservoirs are mostly amalgamated, delta-front lobes, and subordinately, crevasse deposits. Some important geometrical elements were recognized by the detailed variographic analysis developed for each stratigraphic unit (zone). The average width for the groups of deltaic lobes of one zone was measured from the variographic feature informally named as hole effect. This procedure was not possible for the other zones due to the intense lateral amalgamation of sandstones, indicated by many variographic nested structures. Net sand krigged maps for the main zones suggest a NNW-SSE orientation for the deltaic lobes, as also their common amalgamation and compensation arrangements. High-resolution stratigraphic analyses should include a more regional characterization of the depositional system that comprises the studied succession. On the other hand, geostatistical studies should be developed only after the recognition of the depositional processes acting in the study area and the geological meaning of the variable to be treated, including its spatial variability scales as a function of sand body thickness, orientation and amalgamation. (author)

  16. Evaluation of Social Studies Curriculum on Compassion ...

    African Journals Online (AJOL)

    This study examined the impact of social studies curriculum on the affective dispositions of students of Colleges of Education in North-West Zone of Nigeria. The purpose of the study was to determine the level of NCE I and NCE III students' affective dispositions in the area of compassion. One research question and one ...

  17. Geostatistical Investigations of Displacements on the Basis of Data from the Geodetic Monitoring of a Hydrotechnical Object

    Science.gov (United States)

    Namysłowska-Wilczyńska, Barbara; Wynalek, Janusz

    2017-12-01

    Geostatistical methods make the analysis of measurement data possible. This article presents the problems directed towards the use of geostatistics in spatial analysis of displacements based on geodetic monitoring. Using methods of applied (spatial) statistics, the research deals with interesting and current issues connected to space-time analysis, modeling displacements and deformations, as applied to any large-area objects on which geodetic monitoring is conducted (e.g., water dams, urban areas in the vicinity of deep excavations, areas at a macro-regional scale subject to anthropogenic influences caused by mining, etc.). These problems are very crucial, especially for safety assessment of important hydrotechnical constructions, as well as for modeling and estimating mining damage. Based on the geodetic monitoring data, a substantial basic empirical material was created, comprising many years of research results concerning displacements of controlled points situated on the crown and foreland of an exemplary earth dam, and used to assess the behaviour and safety of the object during its whole operating period. A research method at a macro-regional scale was applied to investigate some phenomena connected with the operation of the analysed big hydrotechnical construction. Applying a semivariogram function enabled the spatial variability analysis of displacements. Isotropic empirical semivariograms were calculated and then, theoretical parameters of analytical functions were determined, which approximated the courses of the mentioned empirical variability measure. Using ordinary (block) kriging at the grid nodes of an elementary spatial grid covering the analysed object, the values of the Z* estimated means of displacements were calculated together with the accompanying assessment of uncertainty estimation - a standard deviation of estimation σk. Raster maps of the distribution of estimated averages Z* and raster maps of deviations of estimation σk (in perspective

  18. Characterisation of contaminated metals using an advanced statistical toolbox - Geostatistical characterisation of contaminated metals: methodology and illustrations

    International Nuclear Information System (INIS)

    Larsson, Arne; Lidar, Per; Desnoyers, Yvon

    2014-01-01

    Radiological characterisation plays an important role in the process to recycle contaminated or potentially contaminated metals. It is a platform for planning, identification of the extent and nature of contamination, assessing potential risk impacts, cost estimation, radiation protection, management of material arising from decommissioning as well as for the release of the materials as well as the disposal of the generated secondary waste as radioactive waste. Key issues in radiological characterisation are identification of objectives, development of a measurement and sampling strategy (probabilistic, judgmental or a combination thereof), knowledge management, traceability, recording and processing of obtained information. By applying advanced combination of statistical and geostatistical in the concept better performance can be achieved at a lower cost. This paper will describe the benefits with the usage of the available methods in the different stages of the characterisation, treatment and clearance processes aiming for reliable results in line with the data quality objectives. (authors)

  19. Spatial variability of isoproturon mineralizing activity within an agricultural field: geostatistical analysis of simple physicochemical and microbiological soil parameters.

    Science.gov (United States)

    El Sebai, T; Lagacherie, B; Soulas, G; Martin-Laurent, F

    2007-02-01

    We assessed the spatial variability of isoproturon mineralization in relation to that of physicochemical and biological parameters in fifty soil samples regularly collected along a sampling grid delimited across a 0.36 ha field plot (40 x 90 m). Only faint relationships were observed between isoproturon mineralization and the soil pH, microbial C biomass, and organic nitrogen. Considerable spatial variability was observed for six of the nine parameters tested (isoproturon mineralization rates, organic nitrogen, genetic structure of the microbial communities, soil pH, microbial biomass and equivalent humidity). The map of isoproturon mineralization rates distribution was similar to that of soil pH, microbial biomass, and organic nitrogen but different from those of structure of the microbial communities and equivalent humidity. Geostatistics revealed that the spatial heterogeneity in the rate of degradation of isoproturon corresponded to that of soil pH and microbial biomass.

  20. Looking back 2005. Eleven studies evaluated

    International Nuclear Information System (INIS)

    2005-01-01

    Between December 2000 and June 2002 the Netherlands Court of Audit ('Algemene Rekenkamer') carried out a study on the title subject, focusing on the effect of energy saving measures on the energy consumption per product unit in the greenhouse sector in the Netherlands for the period 1994-2000, including the effect of the energy conservation policy for the period 1997-1999. In this retrospective the Court of Audit looks back at the results of eleven studies, among which the fore-mentioned study, in order to assess if and how the ministeries involved followed and implemented the recommendations of the Court of Audit [nl

  1. Adaptive geostatistical sampling enables efficient identification of malaria hotspots in repeated cross-sectional surveys in rural Malawi.

    Directory of Open Access Journals (Sweden)

    Alinune N Kabaghe

    Full Text Available In the context of malaria elimination, interventions will need to target high burden areas to further reduce transmission. Current tools to monitor and report disease burden lack the capacity to continuously detect fine-scale spatial and temporal variations of disease distribution exhibited by malaria. These tools use random sampling techniques that are inefficient for capturing underlying heterogeneity while health facility data in resource-limited settings are inaccurate. Continuous community surveys of malaria burden provide real-time results of local spatio-temporal variation. Adaptive geostatistical design (AGD improves prediction of outcome of interest compared to current random sampling techniques. We present findings of continuous malaria prevalence surveys using an adaptive sampling design.We conducted repeated cross sectional surveys guided by an adaptive sampling design to monitor the prevalence of malaria parasitaemia and anaemia in children below five years old in the communities living around Majete Wildlife Reserve in Chikwawa district, Southern Malawi. AGD sampling uses previously collected data to sample new locations of high prediction variance or, where prediction exceeds a set threshold. We fitted a geostatistical model to predict malaria prevalence in the area.We conducted five rounds of sampling, and tested 876 children aged 6-59 months from 1377 households over a 12-month period. Malaria prevalence prediction maps showed spatial heterogeneity and presence of hotspots-where predicted malaria prevalence was above 30%; predictors of malaria included age, socio-economic status and ownership of insecticide-treated mosquito nets.Continuous malaria prevalence surveys using adaptive sampling increased malaria prevalence prediction accuracy. Results from the surveys were readily available after data collection. The tool can assist local managers to target malaria control interventions in areas with the greatest health impact and is

  2. Geostatistical screening of flood events in the groundwater levels of the diverted inner delta of the Danube River: implications for river bed clogging

    Science.gov (United States)

    Trásy, Balázs; Garamhegyi, Tamás; Laczkó-Dobos, Péter; Kovács, József; Hatvani, István Gábor

    2018-04-01

    The efficient operation of shallow groundwater (SGW) monitoring networks is crucial to water supply, in-land water protection, agriculture and nature conservation. In the present study, the spatial representativity of such a monitoring network in an area that has been thoroughly impacted by anthropogenic activity (river diversion/damming) is assessed, namely the Szigetköz adjacent to the River Danube. The main aims were to assess the spatial representativity of the SGW monitoring network in different discharge scenarios, and investigate the directional characteristics of this representativity, i.e. establish whether geostatistical anisotropy is present, and investigate how this changes with flooding. After the subtraction of a spatial trend from the time series of 85 shallow groundwater monitoring wells tracking flood events from 2006, 2009 and 2013, variography was conducted on the residuals, and the degree of anisotropy was assessed to explore the spatial autocorrelation structure of the network. Since the raw data proved to be insufficient, an interpolated grid was derived, and the final results were scaled to be representative of the original raw data. It was found that during floods the main direction of the spatial variance of the shallow groundwater monitoring wells alters, from perpendicular to the river to parallel with it for over a period of about two week. However, witht the passing of the flood, this returns to its original orientation in 2 months. It is likely that this process is related first to the fast removal of clogged riverbed strata by the flood, then to their slower replacement. In addition, the study highlights the importance of assessing the direction of the spatial autocorrelation structure of shallow groundwater monitoring networks, especially if the aim is to derive interpolated maps for the further investigation or modeling of flow.

  3. QUALITY OF AN ACADEMIC STUDY PROGRAMME - EVALUATION MODEL

    Directory of Open Access Journals (Sweden)

    Mirna Macur

    2016-01-01

    Full Text Available Quality of an academic study programme is evaluated by many: employees (internal evaluation and by external evaluators: experts, agencies and organisations. Internal and external evaluation of an academic programme follow written structure that resembles on one of the quality models. We believe the quality models (mostly derived from EFQM excellence model don’t fit very well into non-profit activities, policies and programmes, because they are much more complex than environment, from which quality models derive from (for example assembly line. Quality of an academic study programme is very complex and understood differently by various stakeholders, so we present dimensional evaluation in the article. Dimensional evaluation, as opposed to component and holistic evaluation, is a form of analytical evaluation in which the quality of value of the evaluand is determined by looking at its performance on multiple dimensions of merit or evaluation criteria. First stakeholders of a study programme and their views, expectations and interests are presented, followed by evaluation criteria. They are both joined into the evaluation model revealing which evaluation criteria can and should be evaluated by which stakeholder. Main research questions are posed and research method for each dimension listed.

  4. Student Evaluation of Teaching: A Case Study from School of ...

    African Journals Online (AJOL)

    Purpose: This paper presents a case study of an academic department's experience with evaluation. The purpose is to review the impact of student evaluation of teaching. The paper also introduces a new evaluation scoring method: the University of Zambia Staff Appraisal System (UNZASAS) method. Method: Anonymous ...

  5. Research Governance and the Role of Evaluation: A Comparative Study

    Science.gov (United States)

    Molas-Gallart, Jordi

    2012-01-01

    Through a comparative study of the United Kingdom and Spain, this article addresses the effect of different research governance structures on the functioning and uses of research evaluation. It distinguishes three main evaluation uses: distributive, improvement, and controlling. Research evaluation in the United Kingdom plays important…

  6. Bias During the Evaluation of Animal Studies?

    Science.gov (United States)

    Knight, Andrew

    2012-02-23

    My recent book entitled The Costs and Benefits of Animal Experiments seeks to answer a key question within animal ethics, namely: is animal experimentation ethically justifiable? Or, more precisely, is it justifiable within the utilitarian cost:benefit framework that fundamentally underpins most regulations governing animal experimentation? To answer this question I reviewed more than 500 scientific publications describing animal studies, animal welfare impacts, and alternative research, toxicity testing and educational methodologies. To minimise bias I focused primarily on large-scale systematic reviews that had examined the human clinical and toxicological utility of animal studies. Despite this, Dr. Susanne Prankel recently reviewed my book in this journal, essentially accusing me of bias. However, she failed to provide any substantive evidence to refute my conclusions, let alone evidence of similar weight to that on which they are based. Those conclusions are, in fact, firmly based on utilitarian ethical reasoning, informed by scientific evidence of considerable strength, and I believe they are robust.

  7. A study protocol to evaluate the relationship between outdoor air pollution and pregnancy outcomes

    Directory of Open Access Journals (Sweden)

    Selemane Ismael

    2010-10-01

    Full Text Available Abstract Background The present study protocol is designed to assess the relationship between outdoor air pollution and low birth weight and preterm births outcomes performing a semi-ecological analysis. Semi-ecological design studies are widely used to assess effects of air pollution in humans. In this type of analysis, health outcomes and covariates are measured in individuals and exposure assignments are usually based on air quality monitor stations. Therefore, estimating individual exposures are one of the major challenges when investigating these relationships with a semi-ecologic design. Methods/Design Semi-ecologic study consisting of a retrospective cohort study with ecologic assignment of exposure is applied. Health outcomes and covariates are collected at Primary Health Care Center. Data from pregnant registry, clinical record and specific questionnaire administered orally to the mothers of children born in period 2007-2010 in Portuguese Alentejo Litoral region, are collected by the research team. Outdoor air pollution data are collected with a lichen diversity biomonitoring program, and individual pregnancy exposures are assessed with spatial geostatistical simulation, which provides the basis for uncertainty analysis of individual exposures. Awareness of outdoor air pollution uncertainty will improve validity of individual exposures assignments for further statistical analysis with multivariate regression models. Discussion Exposure misclassification is an issue of concern in semi-ecological design. In this study, personal exposures are assigned to each pregnant using geocoded addresses data. A stochastic simulation method is applied to lichen diversity values index measured at biomonitoring survey locations, in order to assess spatial uncertainty of lichen diversity value index at each geocoded address. These methods assume a model for spatial autocorrelation of exposure and provide a distribution of exposures in each study location

  8. A study protocol to evaluate the relationship between outdoor air pollution and pregnancy outcomes.

    Science.gov (United States)

    Ribeiro, Manuel C; Pereira, Maria J; Soares, Amílcar; Branquinho, Cristina; Augusto, Sofia; Llop, Esteve; Fonseca, Susana; Nave, Joaquim G; Tavares, António B; Dias, Carlos M; Silva, Ana; Selemane, Ismael; de Toro, Joaquin; Santos, Mário J; Santos, Fernanda

    2010-10-15

    The present study protocol is designed to assess the relationship between outdoor air pollution and low birth weight and preterm births outcomes performing a semi-ecological analysis. Semi-ecological design studies are widely used to assess effects of air pollution in humans. In this type of analysis, health outcomes and covariates are measured in individuals and exposure assignments are usually based on air quality monitor stations. Therefore, estimating individual exposures are one of the major challenges when investigating these relationships with a semi-ecologic design. Semi-ecologic study consisting of a retrospective cohort study with ecologic assignment of exposure is applied. Health outcomes and covariates are collected at Primary Health Care Center. Data from pregnant registry, clinical record and specific questionnaire administered orally to the mothers of children born in period 2007-2010 in Portuguese Alentejo Litoral region, are collected by the research team. Outdoor air pollution data are collected with a lichen diversity biomonitoring program, and individual pregnancy exposures are assessed with spatial geostatistical simulation, which provides the basis for uncertainty analysis of individual exposures. Awareness of outdoor air pollution uncertainty will improve validity of individual exposures assignments for further statistical analysis with multivariate regression models. Exposure misclassification is an issue of concern in semi-ecological design. In this study, personal exposures are assigned to each pregnant using geocoded addresses data. A stochastic simulation method is applied to lichen diversity values index measured at biomonitoring survey locations, in order to assess spatial uncertainty of lichen diversity value index at each geocoded address. These methods assume a model for spatial autocorrelation of exposure and provide a distribution of exposures in each study location. We believe that variability of simulated exposure values at

  9. Bias During the Evaluation of Animal Studies?

    Directory of Open Access Journals (Sweden)

    Andrew Knight

    2012-02-01

    Full Text Available My recent book entitled The Costs and Benefits of Animal Experiments seeks to answer a key question within animal ethics, namely: is animal experimentation ethically justifiable? Or, more precisely, is it justifiable within the utilitarian cost:benefit framework that fundamentally underpins most regulations governing animal experimentation? To answer this question I reviewed more than 500 scientific publications describing animal studies, animal welfare impacts, and alternative research, toxicity testing and educational methodologies. To minimise bias I focused primarily on large-scale systematic reviews that had examined the human clinical and toxicological utility of animal studies. Despite this, Dr. Susanne Prankel recently reviewed my book in this journal, essentially accusing me of bias. However, she failed to provide any substantive evidence to refute my conclusions, let alone evidence of similar weight to that on which they are based. Those conclusions are, in fact, firmly based on utilitarian ethical reasoning, informed by scientific evidence of considerable strength, and I believe they are robust.

  10. Evaluation of the Ramazzini Foundation Study of Methanol in Rats

    Science.gov (United States)

    Evaluation of the Ramazzini Foundation Study of Methanol in Rats: A Comparison of Diagnoses by the RF Study Pathologist and a Recent NTP Review Team, summarized by George Cruzan and submitted to the Methanol Institute

  11. The geostatistics of the metal concentrations in sediments from the eastern Brazilian continental shelf in areas of gas and oil production

    Science.gov (United States)

    Aguiar, Jose Edvar; de Lacerda, Luiz Drude; Miguens, Flavio Costa; Marins, Rozane Valente

    2014-04-01

    Geostatistical techniques were used to evaluate the differences in the geochemistry of metals in the marine sediments along the Eastern Brazilian continental margin along the states of Ceará and Rio Grande do Norte (Northeastern sector) and Espírito Santo (Southeastern sector). The concentrations of Al, Fe, Mn, Ba, Cd, Cu, Cr, Ni, Pb, V, Hg, and Zn were obtained from acid digestion and quantified using flame atomic absorption spectrometry (AAS), inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma atomic emission spectrometry (ICP-AES). The metals showed a similar order of concentration: Al > Fe > Ba > Mn > V > Ni > Pb > Cr > Zn > Cu, in both the Ceará; and Rio Grande do Norte shelf regions but different in the Espírito Santo shelf (Fe > Al > Mn > Ba > Zn > V > Cr > Ni > Pb > Cu. The concentrations of Hg and Cd were below the detection limit in all areas. A multivariate analysis revealed that the metals of siliciclastic origin on the continental shelf of Ceará are carried by Al. In addition, a large portion of metal deposits is connected to the iron and manganese oxides on the continental margin of Rio Grande do Norte. The metals from the continental supply on the coast of Espírito Santo (Cu, Ni, Ba, and Mn) are associated with Al; whereas Cr, Pb, V, and Zn are associated with iron in this southern area. Geochemical evaluations are needed to distinguish the origin and mineralogical differences of marine sediments within the regions. Scanning electron microscopy/energy dispersive spectrometry (SEM/EDS) applied to the sediments from the coast of Ceará showed the morphological diversity of sediment grains: biological fragments, multifaceted particles, aggregates, and crystals occurred in the three regions analyzed. Among these grains, calcite, Mg-calcite, and aragonite were predominant in the northeastern sector, whereas silicates and other minerals were predominant the southeastern sector. Mg, K, Ti, and Zr as well as the

  12. Simulation studies for the evaluation of health information technologies

    DEFF Research Database (Denmark)

    Ammenwerth, Elske; Hackl, Werner; Binzer, Kristine

    2012-01-01

    It is essential for new health information technologies (IT) to undergo rigorous evaluations to ensure they are effective and safe for use in real-world situations. However, evaluation of new health IT is challenging, as field studies are often not feasible when the technology being evaluated...... is not sufficiently mature. Laboratory-based evaluations have also been shown to have insufficient external validity. Simulation studies seem to be a way to bridge this gap. The aim of this study was to evaluate, using a simulation methodology, the impact of a new prototype of an electronic medication management...... system on the appropriateness of prescriptions and drugrelated activities, including laboratory test ordering or medication changes. This article presents the results of a controlled simulation study with 50 simulation runs, including ten doctors and five simulation patients, and discusses experiences...

  13. Análise dos atributos do solo e da produtividade da cultura de cana-de-açúcar com o uso da geoestatística e árvore de decisão Analyze the soil attributes and sugarcane yield culture with the use of geostatistics and decision trees

    Directory of Open Access Journals (Sweden)

    Zigomar Menezes de Souza

    2010-04-01

    Full Text Available Um dos desafios da agricultura de precisão é oferecer subsídios para a definição de unidades de manejo para posteriores intervenções. Portanto, o objetivo deste trabalho foi avaliar os atributos químicos do solo e a produtividade da cultura de cana-de-açúcar por meio da geoestatística e mineração de dados pela indução da árvore de decisão. A produtividade da cana-de-açúcar foi mapeada em uma área de aproximadamente 23ha, utilizando-se o critério de célula, por meio de um monitor de produtividade que permitiu a elaboração de um mapa digital que representa a superfície de produção para a área em estudo. Para determinar os atributos de um Argissolo Vermelho-Amarelo, foram coletadas as amostras no início da safra 2006/2007, utilizando-se uma grade regular de 50 x 50m, nas profundidades de 0,0-0,2m e 0,2-0,4m. Os dados dos atributos do solo e da produtividade foram analisados por meio da técnica de goestatística e classificados em três níveis de produção para indução de árvore de decisão. A árvore de decisão foi induzida no programa SAS Enterprise Miner, sendo utilizado algoritmo baseado na redução de entropia. As variáveis altitude e potássio apresentaram os maiores valores de correlação com a produtividade de cana-de-açúcar. A indução de árvores de decisão permitiu verificar que a altitude é a variável com maior potencial para interpretar os mapas de produtividade de cana-de-açúcar, auxiliando na agricultura de precisão e mostrando-se uma ferramenta adequada para o estudo de definição de zonas de manejo em área cultivada com essa cultura.One of the challenges of precision agriculture is to offer subsidies for the definition of management units for posterior interventions. Therefore, the objective of this work was to evaluate soil chemical attributes and sugarcane yield with the use of geostatistics and data mining by decision tree induction. Sugarcane yield was mapped in a 23ha field

  14. A Study on Developing Evaluation Criteria for Electronic Resources in Evaluation Indicators of Libraries

    Science.gov (United States)

    Noh, Younghee

    2010-01-01

    This study aimed to improve the current state of electronic resource evaluation in libraries. While the use of Web DB, e-book, e-journal, and other e-resources such as CD-ROM, DVD, and micro materials is increasing in libraries, their use is not comprehensively factored into the general evaluation of libraries and may diminish the reliability of…

  15. Evaluating the Evaluators: Comparative Study of High School Newspaper Critique Services.

    Science.gov (United States)

    Davis, Nancy

    High school publication staffs depend on national critique services as a major means of evaluation and recognition, but most have no measure of how one critique service compares to the others, because they can afford the entry fee for only one evaluation. Thus, a study was conducted to test the validity of three major national critique…

  16. Evaluating Students' Beliefs in Problem Solving Process: A Case Study

    Science.gov (United States)

    Ozturk, Tugba; Guven, Bulent

    2016-01-01

    Problem solving is not simply a process that ends when an answer is found; it is a scientific process that evolves from understanding the problem to evaluating the solution. This process is affected by several factors. Among these, one of the most substantial is belief. The purpose of this study was to evaluate the beliefs of high school students…

  17. A Qualitative Study on Primary School Mathematics Lesson Evaluation

    Science.gov (United States)

    Zhao, Dongchen; Ma, Yunpeng

    2009-01-01

    Through the qualitative interviews of five implementers of primary school mathematics curriculum, this study addresses the ways in which mathematics lessons are evaluated. Results show that each evaluator recognizes different aspects of a "good lesson," however, among all criteria, the design of the lesson plan, realization of the lesson…

  18. Hierarchical probabilistic regionalization of volcanism for Sengan region in Japan using multivariate statistical techniques and geostatistical interpolation techniques

    International Nuclear Information System (INIS)

    Park, Jinyong; Balasingham, P.; McKenna, Sean Andrew; Kulatilake, Pinnaduwa H. S. W.

    2004-01-01

    Sandia National Laboratories, under contract to Nuclear Waste Management Organization of Japan (NUMO), is performing research on regional classification of given sites in Japan with respect to potential volcanic disruption using multivariate statistics and geo-statistical interpolation techniques. This report provides results obtained for hierarchical probabilistic regionalization of volcanism for the Sengan region in Japan by applying multivariate statistical techniques and geostatistical interpolation techniques on the geologic data provided by NUMO. A workshop report produced in September 2003 by Sandia National Laboratories (Arnold et al., 2003) on volcanism lists a set of most important geologic variables as well as some secondary information related to volcanism. Geologic data extracted for the Sengan region in Japan from the data provided by NUMO revealed that data are not available at the same locations for all the important geologic variables. In other words, the geologic variable vectors were found to be incomplete spatially. However, it is necessary to have complete geologic variable vectors to perform multivariate statistical analyses. As a first step towards constructing complete geologic variable vectors, the Universal Transverse Mercator (UTM) zone 54 projected coordinate system and a 1 km square regular grid system were selected. The data available for each geologic variable on a geographic coordinate system were transferred to the aforementioned grid system. Also the recorded data on volcanic activity for Sengan region were produced on the same grid system. Each geologic variable map was compared with the recorded volcanic activity map to determine the geologic variables that are most important for volcanism. In the regionalized classification procedure, this step is known as the variable selection step. The following variables were determined as most important for volcanism: geothermal gradient, groundwater temperature, heat discharge, groundwater

  19. Study on the evaluation index of active power reserve

    Science.gov (United States)

    Guo, Xiaorui; Liu, Jiantao; Wang, Ke; Min, Lu

    2018-01-01

    Based on the role of active reserve at different time scales, divides the evaluation dimension of active reserve. Analysis the calculation principle of traditional reliability index such as probability of system safety, lack of power shortage and electricity shortage expectancy, and studies the applicability of these indicators to evaluate the reserve capacity on different dimensions. Resolves the evaluation index of active reserve capacity from the dimensions of time dimension, spatial dimension, system state, risk degree and economy, then construct evaluation index of active reserve capacity.

  20. A case study evaluation of the use of video technology in concrete pavement evaluation.

    Science.gov (United States)

    2000-01-01

    This report presents the results of an evaluation of video technology as a possible solution to the problem of safely collecting objective condition data for prioritizing concrete pavement rehabilitation needs in Virginia. The study involved the eval...

  1. Continuous Evaluation in Ethics Education: A Case Study.

    Science.gov (United States)

    McIntosh, Tristan; Higgs, Cory; Mumford, Michael; Connelly, Shane; DuBois, James

    2018-04-01

    A great need for systematic evaluation of ethics training programs exists. Those tasked with developing an ethics training program may be quick to dismiss the value of training evaluation in continuous process improvement. In the present effort, we use a case study approach to delineate how to leverage formative and summative evaluation measures to create a high-quality ethics education program. With regard to formative evaluation, information bearing on trainee reactions, qualitative data from the comments of trainees, in addition to empirical findings, can ensure that the training program operates smoothly. Regarding summative evaluation, measures examining trainee cognition, behavior, and organization-level results provide information about how much trainees have changed as a result of taking the ethics training. The implications of effective training program evaluation are discussed.

  2. Comparative study of heuristic evaluation and usability testing methods.

    Science.gov (United States)

    Thyvalikakath, Thankam Paul; Monaco, Valerie; Thambuganipalle, Himabindu; Schleyer, Titus

    2009-01-01

    Usability methods, such as heuristic evaluation, cognitive walk-throughs and user testing, are increasingly used to evaluate and improve the design of clinical software applications. There is still some uncertainty, however, as to how those methods can be used to support the development process and evaluation in the most meaningful manner. In this study, we compared the results of a heuristic evaluation with those of formal user tests in order to determine which usability problems were detected by both methods. We conducted heuristic evaluation and usability testing on four major commercial dental computer-based patient records (CPRs), which together cover 80% of the market for chairside computer systems among general dentists. Both methods yielded strong evidence that the dental CPRs have significant usability problems. An average of 50% of empirically-determined usability problems were identified by the preceding heuristic evaluation. Some statements of heuristic violations were specific enough to precisely identify the actual usability problem that study participants encountered. Other violations were less specific, but still manifested themselves in usability problems and poor task outcomes. In this study, heuristic evaluation identified a significant portion of problems found during usability testing. While we make no assumptions about the generalizability of the results to other domains and software systems, heuristic evaluation may, under certain circumstances, be a useful tool to determine design problems early in the development cycle.

  3. Guidance for Identifying, Selecting and Evaluating Open Literature Studies

    Science.gov (United States)

    This guidance for Office of Pesticide Program staff will assist in their evaluation of open literature studies of pesticides. It also describes how we identify, select, and ensure that data we use in risk assessments is of sufficient scientific quality.

  4. Spatio-temporal patterns of Cu contamination in mosses using geostatistical estimation

    International Nuclear Information System (INIS)

    Martins, Anabela; Figueira, Rui; Sousa, António Jorge; Sérgio, Cecília

    2012-01-01

    Several recent studies have reported temporal trends in metal contamination in mosses, but such assessments did not evaluate uncertainty in temporal changes, therefore providing weak statistical support for time comparisons. Furthermore, levels of contaminants in the environment change in both space and time, requiring space-time modelling methods for map estimation. We propose an indicator of spatial and temporal variation based on space-time estimation by indicator kriging, where uncertainty at each location is estimated from the local distribution function, thereby calculating variability intervals for comparison between several biomonitoring dates. This approach was exemplified using copper concentrations in mosses from four Portuguese surveys (1992, 1997, 2002 and 2006). Using this approach, we identified a general decrease in copper contamination, but spatial patterns were not uniform, and from the uncertainty intervals, changes could not be considered significant in the majority of the study area. - Highlights: ► We estimated copper contamination in mosses by spatio-temporal kriging between 1992 and 2006. ► We determined local distribution functions to define variation intervals at each location. ► Significance of temporal changes is assessed using an indicator based on uncertainty interval. ► There is general decrease in copper contamination, but spatial patterns are not uniform. - The contamination of copper in mosses was estimated by spatio-temporal kriging, with determination of uncertainty classes in the temporal variation.

  5. Evaluation of School Uniform Policy in Turkey: A Case Study

    Science.gov (United States)

    Cinoglu, Mustafa

    2014-01-01

    The purpose of this study is to evaluate the results of current school uniform policies according to views of stakeholders. Descriptive case study method was used for this study to understand the concerns of the stakeholders about school uniforms. Data was collected through interviews with stakeholders and also reviewing the documents in TOKI…

  6. Geostatistical evaluation of integrated marsh management impact on mosquito vectors using before-after-control-impact (BACI) design

    OpenAIRE

    Rochlin, Ilia; Iwanejko, Tom; Dempsey, Mary E; Ninivaggi, Dominick V

    2009-01-01

    Abstract Background In many parts of the world, salt marshes play a key ecological role as the interface between the marine and the terrestrial environments. Salt marshes are also exceedingly important for public health as larval habitat for mosquitoes that are vectors of disease and significant biting pests. Although grid ditching and pesticides have been effective in salt marsh mosquito control, marsh degradation and other environmental considerations compel a different approach. Targeted h...

  7. A study of combined evaluation of suppliers based on correlation

    Directory of Open Access Journals (Sweden)

    Heting Qiu

    2013-03-01

    Full Text Available Purpose: The Selection of logistics service providers is an important issue in supply chain management. But different evaluation methods may lead to different results, which could cause inconsistent conclusions. This paper makes use of a new perspective to combine with a variety of methods to eliminate the deviation of different single evaluation methods. Design/methodology/approach: This paper expounds the application of the combined evaluation method based on correlation. Entropy method, factor analysis, grey colligation evaluation and AHP have been used for research. Findings: According to the evaluate result, the ranking of suppliers obtained by each method have obvious differences. The result shows that combined evaluation method can eliminate the deviation of different single evaluation methods. Originality/value: The combined evaluation method makes up for the defects of single evaluation methods and obtains a result that is more stable and creditable with smaller deviation. This study can provide the enterprise leaders with more scientific method to select their cooperative companies. 

  8. A Combined Approach of Sensor Data Fusion and Multivariate Geostatistics for Delineation of Homogeneous Zones in an Agricultural Field

    Directory of Open Access Journals (Sweden)

    Annamaria Castrignanò

    2017-12-01

    Full Text Available To assess spatial variability at the very fine scale required by Precision Agriculture, different proximal and remote sensors have been used. They provide large amounts and different types of data which need to be combined. An integrated approach, using multivariate geostatistical data-fusion techniques and multi-source geophysical sensor data to determine simple summary scale-dependent indices, is described here. These indices can be used to delineate management zones to be submitted to differential management. Such a data fusion approach with geophysical sensors was applied in a soil of an agronomic field cropped with tomato. The synthetic regionalized factors determined, contributed to split the 3D edaphic environment into two main horizontal structures with different hydraulic properties and to disclose two main horizons in the 0–1.0-m depth with a discontinuity probably occurring between 0.40 m and 0.70 m. Comparing this partition with the soil properties measured with a shallow sampling, it was possible to verify the coherence in the topsoil between the dielectric properties and other properties more directly related to agronomic management. These results confirm the advantages of using proximal sensing as a preliminary step in the application of site-specific management. Combining disparate spatial data (data fusion is not at all a naive problem and novel and powerful methods need to be developed.

  9. Geostatistical approach for assessing soil volumes requiring remediation: validation using lead-polluted soils underlying a former smelting works.

    Science.gov (United States)

    Demougeot-Renard, Helene; De Fouquet, Chantal

    2004-10-01

    Assessing the volume of soil requiring remediation and the accuracy of this assessment constitutes an essential step in polluted site management. If this remediation volume is not properly assessed, misclassification may lead both to environmental risks (polluted soils may not be remediated) and financial risks (unexpected discovery of polluted soils may generate additional remediation costs). To minimize such risks, this paper proposes a geostatistical methodology based on stochastic simulations that allows the remediation volume and the uncertainty to be assessed using investigation data. The methodology thoroughly reproduces the conditions in which the soils are classified and extracted at the remediation stage. The validity of the approach is tested by applying it on the data collected during the investigation phase of a former lead smelting works and by comparing the results with the volume that has actually been remediated. This real remediated volume was composed of all the remediation units that were classified as polluted after systematic sampling and analysis during clean-up stage. The volume estimated from the 75 samples collected during site investigation slightly overestimates (5.3% relative error) the remediated volume deduced from 212 remediation units. Furthermore, the real volume falls within the range of uncertainty predicted using the proposed methodology.

  10. A Combined Approach of Sensor Data Fusion and Multivariate Geostatistics for Delineation of Homogeneous Zones in an Agricultural Field.

    Science.gov (United States)

    Castrignanò, Annamaria; Buttafuoco, Gabriele; Quarto, Ruggiero; Vitti, Carolina; Langella, Giuliano; Terribile, Fabio; Venezia, Accursio

    2017-12-03

    To assess spatial variability at the very fine scale required by Precision Agriculture, different proximal and remote sensors have been used. They provide large amounts and different types of data which need to be combined. An integrated approach, using multivariate geostatistical data-fusion techniques and multi-source geophysical sensor data to determine simple summary scale-dependent indices, is described here. These indices can be used to delineate management zones to be submitted to differential management. Such a data fusion approach with geophysical sensors was applied in a soil of an agronomic field cropped with tomato. The synthetic regionalized factors determined, contributed to split the 3D edaphic environment into two main horizontal structures with different hydraulic properties and to disclose two main horizons in the 0-1.0-m depth with a discontinuity probably occurring between 0.40 m and 0.70 m. Comparing this partition with the soil properties measured with a shallow sampling, it was possible to verify the coherence in the topsoil between the dielectric properties and other properties more directly related to agronomic management. These results confirm the advantages of using proximal sensing as a preliminary step in the application of site-specific management. Combining disparate spatial data (data fusion) is not at all a naive problem and novel and powerful methods need to be developed.

  11. Spatial variability of isoproturon mineralizing activity within an agricultural field: Geostatistical analysis of simple physicochemical and microbiological soil parameters

    Energy Technology Data Exchange (ETDEWEB)

    El Sebai, T. [UMR Microbiologie et Geochimie des Sols, INRA/CMSE, 17 Rue Sully, BP 86510, 21065 Dijon Cedex (France); Lagacherie, B. [UMR Microbiologie et Geochimie des Sols, INRA/CMSE, 17 Rue Sully, BP 86510, 21065 Dijon Cedex (France); Soulas, G. [UMR Microbiologie et Geochimie des Sols, INRA/CMSE, 17 Rue Sully, BP 86510, 21065 Dijon Cedex (France); Martin-Laurent, F. [UMR Microbiologie et Geochimie des Sols, INRA/CMSE, 17 Rue Sully, BP 86510, 21065 Dijon Cedex (France)]. E-mail: fmartin@dijon.inra.fr

    2007-02-15

    We assessed the spatial variability of isoproturon mineralization in relation to that of physicochemical and biological parameters in fifty soil samples regularly collected along a sampling grid delimited across a 0.36 ha field plot (40 x 90 m). Only faint relationships were observed between isoproturon mineralization and the soil pH, microbial C biomass, and organic nitrogen. Considerable spatial variability was observed for six of the nine parameters tested (isoproturon mineralization rates, organic nitrogen, genetic structure of the microbial communities, soil pH, microbial biomass and equivalent humidity). The map of isoproturon mineralization rates distribution was similar to that of soil pH, microbial biomass, and organic nitrogen but different from those of structure of the microbial communities and equivalent humidity. Geostatistics revealed that the spatial heterogeneity in the rate of degradation of isoproturon corresponded to that of soil pH and microbial biomass. - In field spatial variation of isoproturon mineralization mainly results from the spatial heterogeneity of soil pH and microbial C biomass.

  12. Spatial variability of isoproturon mineralizing activity within an agricultural field: Geostatistical analysis of simple physicochemical and microbiological soil parameters

    International Nuclear Information System (INIS)

    El Sebai, T.; Lagacherie, B.; Soulas, G.; Martin-Laurent, F.

    2007-01-01

    We assessed the spatial variability of isoproturon mineralization in relation to that of physicochemical and biological parameters in fifty soil samples regularly collected along a sampling grid delimited across a 0.36 ha field plot (40 x 90 m). Only faint relationships were observed between isoproturon mineralization and the soil pH, microbial C biomass, and organic nitrogen. Considerable spatial variability was observed for six of the nine parameters tested (isoproturon mineralization rates, organic nitrogen, genetic structure of the microbial communities, soil pH, microbial biomass and equivalent humidity). The map of isoproturon mineralization rates distribution was similar to that of soil pH, microbial biomass, and organic nitrogen but different from those of structure of the microbial communities and equivalent humidity. Geostatistics revealed that the spatial heterogeneity in the rate of degradation of isoproturon corresponded to that of soil pH and microbial biomass. - In field spatial variation of isoproturon mineralization mainly results from the spatial heterogeneity of soil pH and microbial C biomass

  13. DETERMINATION OF IMPORTANCE EVALUATION FOR THE SUBSURFACE EXPLORATORY STUDIES FACILITY

    International Nuclear Information System (INIS)

    Clark, W.J.

    1999-01-01

    This Determination of Importance Evaluation (DIE) applies to the Subsurface Exploratory Studies Facility (ESF), encompassing the Topopah Spring (TS) Loop from Station 0+00 meters (m) at the North Portal to breakthrough at the South Portal (approximately 78+77 m), the Enhanced Characterization of the Repository Block (ECRB) East-West Cross Drift Starter Tunnel (to approximate ECRB Station 0+26 m), and ancillary test and operation support areas in the TS Loop. This evaluation applies to the construction, operation, and maintenance of these excavations. A more detailed description of these items is provided in Section 6.0. Testing activities are not evaluated in this DIE. Certain construction activities with respect to testing activities are evaluated; but the testing activities themselves are not evaluated. The DIE for ESF Subsurface Testing Activities (BAJ3000000-01717-2200-000111) (CRWMS M and O 1998a) evaluates Subsurface ESF Testing activities. The construction, operation, and maintenance of the TS Loop niches and alcove slot cuts is evaluated herein and is also discussed in CRWMS M and O 1998a. The construction, operation, and maintenance of the Busted Butte subsurface test area in support of the Unsaturated Zone (UZ) Transport Test is evaluated in CRWMS M and O 1998a. Potential test-to-test interference and the waste isolation impacts of testing activities are evaluated in the ESF Subsurface Testing Activities DIE and other applicable evaluation(s) for the Job Package (JP), Test Planning Package (TPP), and/or Field Work Package (FWP). The objectives of this DIE are to determine whether the Subsurface ESF TS Loop and associated excavations, including activities associated with their construction and operation, potentially impact site characterization testing or the waste isolation capabilities of the site. Controls needed to limit any potential impacts are identified. The validity and veracity of the individual tests, including data collection, are the

  14. DETERMINATION OF IMPORTANCE EVALUATION FOR THE SUBSURFACE EXPORATORY STUDIES FACILITY

    Energy Technology Data Exchange (ETDEWEB)

    W.J. Clark

    1999-06-28

    This Determination of Importance Evaluation (DIE) applies to the Subsurface Exploratory Studies Facility (ESF), encompassing the Topopah Spring (TS) Loop from Station 0+00 meters (m) at the North Portal to breakthrough at the South Portal (approximately 78+77 m), the Enhanced Characterization of the Repository Block (ECRB) East-West Cross Drift Starter Tunnel (to approximate ECRB Station 0+26 m), and ancillary test and operation support areas in the TS Loop. This evaluation applies to the construction, operation, and maintenance of these excavations. A more detailed description of these items is provided in Section 6.0. Testing activities are not evaluated in this DIE. Certain construction activities with respect to testing activities are evaluated; but the testing activities themselves are not evaluated. The DIE for ESF Subsurface Testing Activities (BAJ3000000-01717-2200-00011 Rev 01) (CRWMS M&O 1998a) evaluates Subsurface ESF Testing activities. The construction, operation, and maintenance of the TS Loop niches and alcove slot cuts is evaluated herein and is also discussed in CRWMS M&O 1998a. The construction, operation, and maintenance of the Busted Butte subsurface test area in support of the Unsaturated Zone (UZ) Transport Test is evaluated in CRWMS M&O 1998a. Potential test-to-test interference and the waste isolation impacts of testing activities are evaluated in the ESF Subsurface Testing Activities DIE and other applicable evaluation(s) for the Job Package (JP), Test Planning Package (TPP), and/or Field Work Package (FWP). The objectives of this DIE are to determine whether the Subsurface ESF TS Loop and associated excavations, including activities associated with their construction and operation, potentially impact site characterization testing or the waste isolation capabilities of the site. Controls needed to limit any potential impacts are identified. The validity and veracity of the individual tests, including data collection, are the responsibility

  15. Characterization of Drain Surface Water: Environmental Profile, Degradation Level and Geo-statistic Monitoring

    International Nuclear Information System (INIS)

    Mumtaz, M.W.; Raza, M.A.; Ahmed, Z.; Abbas, M.N.; Hussain, M.

    2015-01-01

    The physico-chemical characterization of the surface water. Samples was carried out collected from nine sampling points of drain passing by the territory of Hafizabad city, Punjab, Pakistan. The water of drain is used by farmers for irrigation purposes in nearby agricultural fields. Twenty water quality parameters were evaluated in three turns and the results obtained were compared with the National Environmental Quality Standards (NEQS) municipal and industrial effluents prescribed limits. The highly significant difference (p<0.01) was recorded for the content of phenols, carbonyl compounds, cyanides, dissolved oxygen, biological oxygen demand, total soluble salts, total dissolved salts, nitrates and sulphates, whereas, the concentration of magnesium, potassium and oil and grease differed significantly (p<0.05) with respect to the sampling points on average basis. Non-significant difference (p>0.05) was noted for temperature, pH, electrical conductivity, hardness, calcium, sodium, chemical oxygen demand and chloride among water samples from different sampling points. Furthermore, the experimental results of different water quality parameters studied at nine sampling points of the drain were used and interpolated in ArcGIS 9.3 environment system using kriging techniques to obtain calculated values for the remaining locations of the Drain. (author)

  16. Caracterização do solo de cobertura de aterros encerrados com ferramentas (geoestatísticas Characterization of soil covers in closed landfill sites with (geostatistical tools

    Directory of Open Access Journals (Sweden)

    Alessandro Samuel-Rosa

    2011-06-01

    Full Text Available Inúmeros trabalhos abordam a elaboração de estratégias amostrais e a aplicação de ferramentas (geoestatísticas no estudo de atributos do solo. Entretanto, são escassos os trabalhos envolvendo a aplicação desta abordagem no monitoramento de solos construídos sobre aterros encerrados de resíduos sólidos urbanos. Este estudo mostra que a densidade amostral necessária para tornar possível o uso da geoestatística em tais casos, elevaria os custos operacionais. A melhor alternativa é a utilização dos métodos de estatística multivariada (análise de componentes principais e de agrupamento para definição de zonas homogêneas de manejo. Os atributos que melhor explicam a estrutura da variabilidade do solo construído são o teor de areia (ou argila, a saturação por bases e o pH, todos relacionados com a contaminação do solo com chorume e o adequado desenvolvimento da vegetação.Several studies address the development of sampling strategies and implementation of (geostatistical tools in the study of soil properties. However, there is a lack of studies in the application of such approach to monitor soil covers in closed landfill sites of urban solid waste. This study shows that the sampling density needed to make possible the use of geostatistics in such cases would raise operational costs. The best alternative is the use of multivariate statistics methods (principal components and cluster analysis to define homogeneous management zones. The soil attributes that best explain the structure of soil variability are sand (or clay content, base saturation and pH, all related with soil contamination by leachate and with the proper development of vegetation.

  17. Scaling of vegetation indices for environmental change studies

    International Nuclear Information System (INIS)

    Qi, J.; Huete, A.; Sorooshian, S.; Chehbouni, A.; Kerr, Y.

    1992-01-01

    The spatial integration of physical parameters in remote sensing studies is of critical concern when evaluating the global biophysical processes on the earth's surface. When high resolution physical parameters, such as vegetation indices, are degraded for integration into global scale studies, they differ from lower spatial resolution data due to spatial variability and the method by which these parameters are integrated. In this study, multi-spatial resolution data sets of SPOT and ground based data obtained at Walnut Gulch Experimental Watershed in southern Arizona, US during MONSOON '90 were used. These data sets were examined to study the variations of the vegetation index parameters when integrated into coarser resolutions. Different integration methods (conventional mean and Geostatistical mean) were used in simulations of high-to-low resolutions. The sensitivity of the integrated parameters were found to vary with both the spatial variability of the area and the integration methods. Modeled equations describing the scale-dependency of the vegetation index are suggested

  18. Individual performance evaluation of the Brazilian Nuclear Energy Commission (CNEN): a meta-evaluative study

    International Nuclear Information System (INIS)

    Bezerra, Leonardo Ferreira

    2017-01-01

    The present study is a summative meta-evaluation that had as objective to evaluate the quality of the process of evaluation of individual performance of the servers of the National Commission of Nuclear Energy, being guided by the scientific curiosity to know to what extent the evaluation of performance the National Commission for Nuclear Energy meets the quality standards disseminated by the Joint Committee on Standards for Educational Evaluation. The methodology chosen to be used was based on the management approach and had as a guiding principle of the study the elaboration of a framework of criteria considering the aforementioned standards. The criteria established in the criteria framework guided the preparation of the items of the questionnaire sent to the National Commission of Nuclear Energy servers. In addition to the questionnaire, the observation of this author was considered in the context where the phenomenon occurred, which allowed a better reflective analysis of the data collected by the questionnaire. Regarding the results, it can be inferred that the performance evaluation developed at the National Commission of Nuclear Energy can be considered of quality, highlighting the servers' trust for the data, the communication process of the program stages, the credibility of the evaluators, the process of negotiation of goals and adaptability of the instrument over the course of the cycle. However, there are some opportunities for improvement, considering the relevance of evaluation as a tool to improve the performance of the autarchy's servers. Among the points that need to be improved is that there is currently a lack of knowledge about the legal basis and justification of the process of evaluation process by the servers and the lack of clarity regarding the content of the final evaluation report. Among the recommendations of this study, one can consider as the most relevant the need to: disseminate the results of this meta-evaluation to the

  19. Evaluations of health promoting schools: a review of nine studies.

    Science.gov (United States)

    Mũkoma, Wanjirũ; Flisher, Alan J

    2004-09-01

    The concept of 'health promoting schools' has been embraced internationally as an effective way of promoting the health of children, adolescents, and the wider school community. It is only recently that attempts have been made to evaluate health promoting schools. This paper reviews evaluations of health promoting schools and draws useful evaluation methodology lessons. The review is confined to school-based interventions that are founded explicitly on the concept of the health promoting school and employ the concept beyond one school domain. We included nine evaluations in this review. Seven of these were published in the peer reviewed scientific literature. Two were unpublished reports. One study was a randomized controlled trial, while a quasi-experimental research design with comparison schools was used in three studies. With three exceptions, combinations of quantitative and qualitative data were collected. There was evidence that the health promoting school has some influence on various domains of health for the school community. It is also possible to integrate health promotion into the school curriculum and policies successfully. However, the evaluation of health promoting schools is complex. We discuss some of the methodological challenges of evaluating health promoting schools and make suggestions for improving future evaluations.

  20. Impact Evaluation Study for Institution Strengthening of Social Food Distribution

    Directory of Open Access Journals (Sweden)

    Budiman Notoatmojo

    2016-03-01

    Full Text Available The general objectives of this study were to evaluate whether the implementation of activities for strengthening LDPM could achieve the expected goals, to evaluate whether the LDPM strengthening activities had a positive impact. The study analysis used was descriptive, comparison, and financial analysis. The results of this study have shown that LDPM farmers’ income have increased significantly, and the Gapoktan as LPDM farmers’ institution has been significantly developing as a Bulog function in procuring grain paddy from farmers during peak harvest and distributing rice to stabilize the price of rice during the limited rice in the market.

  1. ExaGeoStat: A High Performance Unified Framework for Geostatistics on Manycore Systems

    KAUST Repository

    Abdulah, Sameh; Ltaief, Hatem; Sun, Ying; Genton, Marc G.; Keyes, David E.

    2017-01-01

    from climate and environmental science. ExaGeoStat provides a reference evaluation of statistical parameters, with which to assess the validity of the various approaches based on approximation. The framework takes a first step in the merger of large

  2. Evaluation of Emotional Literacy Activities: A Phenomenological Study

    Science.gov (United States)

    Oksuz, Yucel

    2016-01-01

    The present study aims to evaluate impact of the emotional literacy activities through participant student's experiences. Emotional literacy activities, including social-emotional skills Goleman's emotional intelligence and Fapuel's emotional literacy model designed and conducted for 2 months on primary school students, who study in 4th grade. The…

  3. Evaluation Study for Secondary Stage EFL Textbook: EFL Teachers' Perspectives

    Science.gov (United States)

    Al Harbi, Abdullah Abdul Muhsen

    2017-01-01

    This study aimed at evaluating EFL textbook for secondary stage in Saudi Public schools. Participants consisted of (100) male teachers and (73) female teachers teaching secondary stage students in two cities: Madinah and Dowadmi. The tool of the study designed to cover five dimensions: layout and design, the objectives of the textbook, teaching…

  4. Evaluating QR Code Case Studies Using a Mobile Learning Framework

    Science.gov (United States)

    Rikala, Jenni

    2014-01-01

    The aim of this study was to evaluate the feasibility of Quick Response (QR) codes and mobile devices in the context of Finnish basic education. The feasibility was analyzed through a mobile learning framework, which includes the core characteristics of mobile learning. The study is part of a larger research where the aim is to develop a…

  5. Inference of strata separation and gas emission paths in longwall overburden using continuous wavelet transform of well logs and geostatistical simulation

    Science.gov (United States)

    Karacan, C. Özgen; Olea, Ricardo A.

    2014-06-01

    Prediction of potential methane emission pathways from various sources into active mine workings or sealed gobs from longwall overburden is important for controlling methane and for improving mining safety. The aim of this paper is to infer strata separation intervals and thus gas emission pathways from standard well log data. The proposed technique was applied to well logs acquired through the Mary Lee/Blue Creek coal seam of the Upper Pottsville Formation in the Black Warrior Basin, Alabama, using well logs from a series of boreholes aligned along a nearly linear profile. For this purpose, continuous wavelet transform (CWT) of digitized gamma well logs was performed by using Mexican hat and Morlet, as the mother wavelets, to identify potential discontinuities in the signal. Pointwise Hölder exponents (PHE) of gamma logs were also computed using the generalized quadratic variations (GQV) method to identify the location and strength of singularities of well log signals as a complementary analysis. PHEs and wavelet coefficients were analyzed to find the locations of singularities along the logs. Using the well logs in this study, locations of predicted singularities were used as indicators in single normal equation simulation (SNESIM) to generate equi-probable realizations of potential strata separation intervals. Horizontal and vertical variograms of realizations were then analyzed and compared with those of indicator data and training image (TI) data using the Kruskal-Wallis test. A sum of squared differences was employed to select the most probable realization representing the locations of potential strata separations and methane flow paths. Results indicated that singularities located in well log signals reliably correlated with strata transitions or discontinuities within the strata. Geostatistical simulation of these discontinuities provided information about the location and extents of the continuous channels that may form during mining. If there is a gas

  6. Geostatistical analysis of disease data: accounting for spatial support and population density in the isopleth mapping of cancer mortality risk using area-to-point Poisson kriging

    Directory of Open Access Journals (Sweden)

    Goovaerts Pierre

    2006-11-01

    Full Text Available Abstract Background Geostatistical techniques that account for spatially varying population sizes and spatial patterns in the filtering of choropleth maps of cancer mortality were recently developed. Their implementation was facilitated by the initial assumption that all geographical units are the same size and shape, which allowed the use of geographic centroids in semivariogram estimation and kriging. Another implicit assumption was that the population at risk is uniformly distributed within each unit. This paper presents a generalization of Poisson kriging whereby the size and shape of administrative units, as well as the population density, is incorporated into the filtering of noisy mortality rates and the creation of isopleth risk maps. An innovative procedure to infer the point-support semivariogram of the risk from aggregated rates (i.e. areal data is also proposed. Results The novel methodology is applied to age-adjusted lung and cervix cancer mortality rates recorded for white females in two contrasted county geographies: 1 state of Indiana that consists of 92 counties of fairly similar size and shape, and 2 four states in the Western US (Arizona, California, Nevada and Utah forming a set of 118 counties that are vastly different geographical units. Area-to-point (ATP Poisson kriging produces risk surfaces that are less smooth than the maps created by a naïve point kriging of empirical Bayesian smoothed rates. The coherence constraint of ATP kriging also ensures that the population-weighted average of risk estimates within each geographical unit equals the areal data for this unit. Simulation studies showed that the new approach yields more accurate predictions and confidence intervals than point kriging of areal data where all counties are simply collapsed into their respective polygon centroids. Its benefit over point kriging increases as the county geography becomes more heterogeneous. Conclusion A major limitation of choropleth

  7. Geostatistical analysis of disease data: accounting for spatial support and population density in the isopleth mapping of cancer mortality risk using area-to-point Poisson kriging

    Science.gov (United States)

    Goovaerts, Pierre

    2006-01-01

    Background Geostatistical techniques that account for spatially varying population sizes and spatial patterns in the filtering of choropleth maps of cancer mortality were recently developed. Their implementation was facilitated by the initial assumption that all geographical units are the same size and shape, which allowed the use of geographic centroids in semivariogram estimation and kriging. Another implicit assumption was that the population at risk is uniformly distributed within each unit. This paper presents a generalization of Poisson kriging whereby the size and shape of administrative units, as well as the population density, is incorporated into the filtering of noisy mortality rates and the creation of isopleth risk maps. An innovative procedure to infer the point-support semivariogram of the risk from aggregated rates (i.e. areal data) is also proposed. Results The novel methodology is applied to age-adjusted lung and cervix cancer mortality rates recorded for white females in two contrasted county geographies: 1) state of Indiana that consists of 92 counties of fairly similar size and shape, and 2) four states in the Western US (Arizona, California, Nevada and Utah) forming a set of 118 counties that are vastly different geographical units. Area-to-point (ATP) Poisson kriging produces risk surfaces that are less smooth than the maps created by a naïve point kriging of empirical Bayesian smoothed rates. The coherence constraint of ATP kriging also ensures that the population-weighted average of risk estimates within each geographical unit equals the areal data for this unit. Simulation studies showed that the new approach yields more accurate predictions and confidence intervals than point kriging of areal data where all counties are simply collapsed into their respective polygon centroids. Its benefit over point kriging increases as the county geography becomes more heterogeneous. Conclusion A major limitation of choropleth maps is the common biased

  8. Radiological evaluation of tumor response in oncological studies (tumor response evaluation)

    International Nuclear Information System (INIS)

    Gebauer, B.; Riess, H.

    2011-01-01

    Purpose: Radiological-morphological response evaluation plays a major role in oncological therapy and studies for approval. Specific criteria have been developed for some tumor entities and chemotherapeutics. Application, limitations and definitions of the most frequently used criteria for tumor response evaluation will be presented. Materials and Methods: Review based on a selective literature research. Results: In clinical oncological therapy studies, WHO and RECIST are the most frequently used criteria to evaluate morphological therapy response. RECIST criteria have been modified recently, especially with respect to the evaluation of lymph nodes, and were published as RECIST 1.1 in 2009. All criteria were originally developed and defined to review clinical multicenter trials for approval. Using these criteria in a clinical situation, certain limitations have to be considered. To evaluate response, a baseline scan before therapy start is mandatory. Special tumor response criteria have been defined for some certain tumor entities. Oncologists and radiologists should define in advance which criteria are used before starting therapy. Conclusion: The use of defined criteria is very important in oncology response evaluation. In-depth knowledge of the criteria and their limits is required for correct usage. (orig.)

  9. Case study of a framing effect in course evaluations.

    Science.gov (United States)

    Lynöe, Niels; Juth, Niklas; Helgesson, Gert

    2012-01-01

    When new elements are included in the medical curriculum and the total time frame remains unchanged, established disciplines have to shorten their courses. This might bring about frustration among the teachers and students concerned, which in turn might affect how other courses are perceived. Two course evaluations, one before and one after a major change in the curriculum were compared. Comments were also analysed. We found that the students' and teachers' frustration influenced the students' evaluations of a new course in the philosophy of medicine and accordingly brought about an unintended message effect referred to as a framing effect. The results of this observational study indicate that a negative framing effect might influence course-evaluations. We suggest that this study might be used as a point of departure for further empirical studies about negative framing effects.

  10. Study on automatic ECT data evaluation by using neural network

    International Nuclear Information System (INIS)

    Komatsu, H.; Matsumoto, Y.; Badics, Z.; Aoki, K.; Nakayasu, F.; Hashimoto, M.; Miya, K.

    1994-01-01

    At the in--service inspection of the steam generator (SG) tubings in Pressurized Water Reactor (PWR) plant, eddy current testing (ECT) has been widely used at each outage. At present, ECT data evaluation is mainly performed by ECT data analyst, therefore it has the following problems. Only ECT signal configuration on the impedance trajectory is used in the evaluation. It is an enormous time consuming process. The evaluation result is influenced by the ability and experience of the analyst. Especially, it is difficult to identify the true defect signal hidden in background signals such as lift--off noise and deposit signals. In this work, the authors performed the study on the possibility of the application of neural network to ECT data evaluation. It was demonstrated that the neural network proved to be effective to identify the nature of defect, by selecting several optimum input parameters to categorize the raw ECT signals

  11. Study on dilatation of multi-criteria evaluation method (II)

    International Nuclear Information System (INIS)

    Tabaru, Yasuhiko; Tomizawa, Masao; Sasaki, Shigeo

    2003-01-01

    In the study on FBR-cycle practical application strategy conducted by JNC, as part of development of evaluation system aiming at comparative evaluation of promising concept for FBR-cycle system, they grade the value of the concepts under the criteria evaluation such as economical efficiency and environmental load. In order that this system functions effectively in selecting promising concepts, we believe that it is important to extend the range of criteria evaluation and improve objectivity and persuasiveness of it. This is why since the last fiscal year we have been studying on evaluation methodology of and investigation examples on external economical efficiency (effects on the environment and human health, safety, energy security, nuclear non-proliferation, etc.) relevant to introduction of FBR, which had not been included in the conventional evaluation of economical efficiency. In this work, we have especially focused on the external economical efficiency relevant to energy security which is peculiar to FBR-cycle and studied on its evaluation methodology and investigation examples. Firstly, we summarized up on the concept and current situation of energy security and the position of nuclear energy in energy security. Then we identified the necessity of clarifying the importance of energy security with the middle-term point of view allowing for deficiency of fossil or uranium resources, and also the importance of the role of FBR as an improvement action for it. Secondly, we studied on the current energy economic model and examined the possibility of applying energy security for quantitative evaluation. As a result, we have concluded that the general equilibrium GTAP (Global Trade Analysis Project) in which fossil resource market around the world is modeled should be effective for quantitative evaluation of long term energy security. Finally, assuming that we will conduct the quantitative evaluation of long term energy security using GTAP model in the future, we

  12. Study on uncertainty evaluation system for the safety evaluation of interim spent fuel storage facility

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Myung Hyeon; Shin, Myeong Won; Rhy, Seok Jin; Cho, Dong Keon; Park, Dong Hwan [Kyunghee Univ., Seoul (Korea, Republic of); Cheong, Beom Jin [Minstry of Science and Technology, Gwacheon (Korea, Republic of)

    1998-03-15

    The main objective os to develop a technical standards for the facility operation of the interm, spent fuel storage facility and to develop a draft for the technical criteria to be legislated. The another objective os to define a uncertainty evaluation system for burn up credit application in criticality analysis and to investigate an applicability of this topic for future regulatory activity. Investigate a status of art for the operational criteria of spent fuel interm wet storage. Collect relevant laws, decree, notices and standards related to the operation of storage facility and study on the legislation system. Develop a draft of technical standards and criteria to be legislated. Define an evaluation system for the uncertainty analysis and study on the status of art in the field of criticality safety analysis. Develop an uncertainty evaluation system in criticality analysis with burnup credit and investigate an applicability as well as its benefits of this policy.

  13. Investigation of spatial correlation in MR images of human cerebral white matter using geostatistical methods

    International Nuclear Information System (INIS)

    Keil, Fabian

    2014-01-01

    Investigating the structure of human cerebral white matter is gaining interest in the neurological as well as in the neuroscientific community. It has been demonstrated in many studies that white matter is a very dynamic structure, rather than a static construct which does not change for a lifetime. That means, structural changes within white matter can be observed even on short timescales, e.g. in the course of normal ageing, neurodegenerative diseases or even during learning processes. To investigate these changes, one method of choice is the texture analysis of images obtained from white matter. In this regard, MRI plays a distinguished role as it provides a completely non-invasive way of acquiring in vivo images of human white matter. This thesis adapted a statistical texture analysis method, known as variography, to quantify the spatial correlation of human cerebral white matter based on MR images. This method, originally introduced in geoscience, relies on the idea of spatial correlation in geological phenomena: in naturally grown structures near things are correlated stronger to each other than distant things. This work reveals that the geological principle of spatial correlation can be applied to MR images of human cerebral white matter and proves that variography is an adequate method to quantify alterations therein. Since the process of MRI data acquisition is completely different to the measuring process used to quantify geological phenomena, the variographic analysis had to be adapted carefully to MR methods in order to provide a correctly working methodology. Therefore, theoretical considerations were evaluated with numerical samples in a first, and validated with real measurements in a second step. It was shown that MR variography facilitates to reduce the information stored in the texture of a white matter image to a few highly significant parameters, thereby quantifying heterogeneity and spatial correlation distance with an accuracy better than 5

  14. Investigation of spatial correlation in MR images of human cerebral white matter using geostatistical methods

    Energy Technology Data Exchange (ETDEWEB)

    Keil, Fabian

    2014-03-20

    Investigating the structure of human cerebral white matter is gaining interest in the neurological as well as in the neuroscientific community. It has been demonstrated in many studies that white matter is a very dynamic structure, rather than a static construct which does not change for a lifetime. That means, structural changes within white matter can be observed even on short timescales, e.g. in the course of normal ageing, neurodegenerative diseases or even during learning processes. To investigate these changes, one method of choice is the texture analysis of images obtained from white matter. In this regard, MRI plays a distinguished role as it provides a completely non-invasive way of acquiring in vivo images of human white matter. This thesis adapted a statistical texture analysis method, known as variography, to quantify the spatial correlation of human cerebral white matter based on MR images. This method, originally introduced in geoscience, relies on the idea of spatial correlation in geological phenomena: in naturally grown structures near things are correlated stronger to each other than distant things. This work reveals that the geological principle of spatial correlation can be applied to MR images of human cerebral white matter and proves that variography is an adequate method to quantify alterations therein. Since the process of MRI data acquisition is completely different to the measuring process used to quantify geological phenomena, the variographic analysis had to be adapted carefully to MR methods in order to provide a correctly working methodology. Therefore, theoretical considerations were evaluated with numerical samples in a first, and validated with real measurements in a second step. It was shown that MR variography facilitates to reduce the information stored in the texture of a white matter image to a few highly significant parameters, thereby quantifying heterogeneity and spatial correlation distance with an accuracy better than 5

  15. A comparison of spatial rainfall estimation techniques: A case study ...

    African Journals Online (AJOL)

    Two geostatistical interpolation techniques (kriging and cokriging) were evaluated against inverse distance weighted (IDW) and global polynomial interpolation (GPI). Of the four spatial interpolators, kriging and cokriging produced results with the least root mean square error (RMSE). A digital elevation model (DEM) was ...

  16. Pharmacognostical study and phytochemical evaluation of brown seaweed Sargassum wightii

    Directory of Open Access Journals (Sweden)

    Jeyaraman Amutha Iswarya Devi

    2013-10-01

    Full Text Available Objective: To explore the pharmacognostical and phytochemical properties of Sargassum wightii. Methods: The qualitative microscopy, phytochemical screening, physicochemical evaluation and fluorescence analysis of the plant were carried out according to the standard procedure recommended in the WHO guidelines. Results: Macroscopic study showed that plants were dark brown, 20-30 cm in height, leaves were 5-8 cm length, shape: linear to ovate, apex: midrib in conspicuous and having the entire, serrate margin. Microscopic evaluation of the transverse section of the leaf, stem, air bladder, receptacles showed the presence of epidermis layer followed by thick cuticle, conducting strand, mesophyll and possessed antheridia or oogonia at the swollen terminal portions. The different extracts of Sargassum wightii showed the presence of steroids, alkaloids, phenolic compounds, saponins and flavonoids with varied degree. Conclusions: Various pharmacognostical parameters evaluated in this study help in the identification and standardization of the of the seaweed Sargassum wightii

  17. Verification of the geostatistical inference code INFERENS, Version 1.1, and demonstration using data from Finnsjoen

    International Nuclear Information System (INIS)

    Geier, J.

    1993-06-01

    This report describes preliminary verification and demonstration of the geostatistical inference code, INFERENS Version 1.1. This code performs regularization of packer test conductivities, and iterative generalized least-squares estimation (IGLSE) of nested covariance models and spatial trends for the regularized data. Cross-validation is used to assess the quality of the estimated models in terms of statistics for the kriging errors. The code includes a capability to generate synthetic datasets for a given configuration of packer tests; this capability can be used for verification exercises and numerical experiments to aid in the design of packer testing programs. The report presents the results of a set of verification test cases. The test cases were designed to test the ability of INFERENS 1.1 to estimate the parameters of a variety of covariance models, with or without trends. This was done using synthetic datasets. This report also describes an application of INFERENS 1.1 to the dataset from the Finnsjoen site. The results are roughly similar to those obtained previously by Norman (1992a) using INFERENS 1.0, for the comparable cases. The actual numerical results are different, which may be due to changes in the fitting algorithms, and differences in how the lag pairs are divided into lag classes. The demonstrations confirm the result previously obtained by Norman, that the fitted horizontally isotropic models are less good, in terms of their cross-validation statistics, than the corresponding isotropic models. The use of nested covariance models is demonstrated to give visually improved fits to the sample semivariograms, at both short and long lag distances. However, despite the good match to the semivariograms, the nested models obtained are not better than the simple models, in terms of cross-validation statistics

  18. Spatial analysis and risk mapping of soil-transmitted helminth infections in Brazil, using Bayesian geostatistical models.

    Science.gov (United States)

    Scholte, Ronaldo G C; Schur, Nadine; Bavia, Maria E; Carvalho, Edgar M; Chammartin, Frédérique; Utzinger, Jürg; Vounatsou, Penelope

    2013-11-01

    Soil-transmitted helminths (Ascaris lumbricoides, Trichuris trichiura and hookworm) negatively impact the health and wellbeing of hundreds of millions of people, particularly in tropical and subtropical countries, including Brazil. Reliable maps of the spatial distribution and estimates of the number of infected people are required for the control and eventual elimination of soil-transmitted helminthiasis. We used advanced Bayesian geostatistical modelling, coupled with geographical information systems and remote sensing to visualize the distribution of the three soil-transmitted helminth species in Brazil. Remotely sensed climatic and environmental data, along with socioeconomic variables from readily available databases were employed as predictors. Our models provided mean prevalence estimates for A. lumbricoides, T. trichiura and hookworm of 15.6%, 10.1% and 2.5%, respectively. By considering infection risk and population numbers at the unit of the municipality, we estimate that 29.7 million Brazilians are infected with A. lumbricoides, 19.2 million with T. trichiura and 4.7 million with hookworm. Our model-based maps identified important risk factors related to the transmission of soiltransmitted helminths and confirm that environmental variables are closely associated with indices of poverty. Our smoothed risk maps, including uncertainty, highlight areas where soil-transmitted helminthiasis control interventions are most urgently required, namely in the North and along most of the coastal areas of Brazil. We believe that our predictive risk maps are useful for disease control managers for prioritising control interventions and for providing a tool for more efficient surveillance-response mechanisms.

  19. Integration of DAS (distributed acoustic sensing) vertical seismic profile and geostatistically modeled lithology data to characterize an enhanced geothermal system.

    Science.gov (United States)

    Cronin, S. P.; Trainor Guitton, W.; Team, P.; Pare, A.; Jreij, S.; Powers, H.

    2017-12-01

    In March 2016, a 4-week field data acquisition took place at Brady's Natural Lab (BNL), an enhanced geothermal system (EGS) in Fallan, NV. During these 4 weeks, a vibe truck executed 6,633 sweeps, recorded by nodal seismometers, horizontal distributed acoustic sensing (DAS) cable, and 400 meters of vertical DAS cable. DAS provides lower signal to noise ratio than traditional geophones but better spatial resolution. The analysis of DAS VSP included Fourier transform, and filtering to remove all up-going energy. Thus, allowing for accurate first arrival picking. We present an example of the Gradual Deformation Method (GDM) using DAS VSP and lithological data to produce a distribution of valid velocity models of BNL. GDM generates continuous perturbations of prior model realizations seeking the best match to the data (i.e. minimize the misfit). Prior model realizations honoring the lithological data were created using sequential Gaussian simulation, a commonly used noniterative geostatistical method. Unlike least-squares-based methods of inversion, GDM readily incorporates a priori information, such as a variogram calculated from well-based lithology information. Additionally, by producing a distribution of models, as opposed to one optimal model, GDM allows for uncertainty quantification. This project aims at assessing the integrated technologies ability to monitor changes in the water table (possibly to one meter resolution) by exploiting the dependence of seismic wave velocities on water saturation of the subsurface. This project, which was funded in part by the National Science Foundation, is a part of the PoroTomo project, funded by a grant from the U.S. Department of Energy.

  20. The Evaluation of Study Success between Online Study and Classroom Study Environment

    Directory of Open Access Journals (Sweden)

    Singkhamfu Phudinan

    2016-01-01

    Full Text Available Online study has increasingly become more attractive to students at university level due to convenience access to their instructors and to study resources. This study has developed online social network for study. It proposes to provide lesson content availability, past lecture, by sending online study lesson media to students’ mobile phone or tablet. Approximately 85 undergraduate software engineering students participated for 1.5 semesters. In comparing the use of the study toll, and without the tool, the alterations were found between traditional classroom learning style and online study. Also, the study’s aim was to attest the online study tool’s efficiency. However, these results were not obvious when the achievement factor was controlled by the limitation of time. The primary purpose of this study is to evaluate these two groups of students with extended experiment time for a noticeable result by used questionnaires course examination, and inventory of ILP learning process. The observed, shows that students with online study tools scored higher on course examinations after measures by the mentioned methodology.

  1. Contact pressure measurement in hand tool evaluation studies

    NARCIS (Netherlands)

    Kuijt-Evers, L.F.M.; Bosch, T.

    2006-01-01

    In hand tool evaluation studies, several objective measurements are used. Grip force distribution and grip force are important as they give feedback about the force which has to be performed with the hand on the handle. A measurement technique -which is related to grip force measurement- is contact

  2. Evaluation of the finger wrinkling test: A pilot study

    NARCIS (Netherlands)

    van Barneveld, S.; van der Palen, Jacobus Adrianus Maria; van Putten, Michel Johannes Antonius Maria

    2010-01-01

    Purpose: Tilt table testing mainly evaluates the systemic cardiovascular part of the autonomic nervous system, while it is assumed that the finger wrinkling test assesses the peripheral part of the autonomic nervous system. In this study we explored whether the finger wrinkling test could be a

  3. Synthesis, biological evaluation and molecular docking studies of ...

    African Journals Online (AJOL)

    Synthesis, biological evaluation and molecular docking studies of Mannich bases derived from 1, 3, 4-oxadiazole- 2-thiones as potential urease inhibitors. ... Mannich bases (5-17) were subjected to in silico screening as urease inhibitors, using crystal structure of urease (Protein Data Bank ID: 5FSE) as a model enzyme.

  4. Peaceful Uses Bona Fides: Criteria for Evaluation and Case Studies

    Energy Technology Data Exchange (ETDEWEB)

    Ajemian, Chris K.; Hazel, Mike; Kessler, Carol E.; Mathews, Carrie E.; Morris, Fred A.; Seward, Amy M.; Peterson, Danielle J.; Smith, Brian W.

    2007-06-06

    This study applies a set of indicators to assess the peaceful nature of a state’s nuclear program. Evaluation of a country’s nuclear program relative to these indicators can help the international community to take appropriate actions to ensure that the growth of the global nuclear energy industry proceeds peacefully and to minimize nuclear proliferation risks.

  5. Evaluating the Reliability, Validity, and Usefulness of Education Cost Studies

    Science.gov (United States)

    Baker, Bruce D.

    2006-01-01

    Recent studies that purport to estimate the costs of constitutionally adequate education have been described as either a "gold standard" that should guide legislative school finance policy design and judicial evaluation, or as pure "alchemy." Methods for estimating the cost of constitutionally adequate education can be roughly…

  6. A retrospective study evaluating the efficacy of identification and ...

    African Journals Online (AJOL)

    Full Title: A retrospective study evaluating the efficacy of identification and management of sepsis at a district-level hospital internal medicine department in the Western Cape Province, South Africa, in comparison with the guidelines stipulated in the 2012 Surviving Sepsis Campaign. Background. Currently there is little ...

  7. Study Design and Data Gathering Guide for Serious Games’ Evaluation

    NARCIS (Netherlands)

    Baalsrud Hauge, Jannicke; Boyle, Elizabeth; Mayer, Igor; Nadolski, Rob; Riedel, Johann C. K. H.; Moreno-Ger, Pablo; Bellotti, Francesco; Lim, Theodore; Ritchie, James

    2013-01-01

    Baalsrud Hauge, J., Boyle, E., Mayer, I., Nadolski, R. J., Riedel, J. C. K. H., Moreno-Ger, P., Bellotti, F., Lim, T., & Ritchie, J. (2013). Study Design and Data Gathering Guide for Serious Games’ Evaluation. In T. M. Connolly, T. Hainey, E. Boyle, G. Baxter, & P. Moreno-Ger (Eds.), Psychology,

  8. Evaluating the usability of web pages: a case study

    NARCIS (Netherlands)

    Lautenbach, M.A.E.; Schegget, I.E. ter; Schoute, A.E.; Witteman, C.L.M.

    1999-01-01

    An evaluation of the Utrecht University website was carried out with 240 students. New criteria were drawn from the literature and operationalized for the study. These criteria are surveyability and findability. Web pages can be said to satisfy a usability criterion if their efficiency and

  9. Molecular evaluation of genetic diversity and association studies in ...

    Indian Academy of Sciences (India)

    Molecular evaluation of genetic diversity and association studies in rice. (Oryza sativa L.) C. Vanniarajan, K. K. Vinod and Andy Pereira. J. Genet. 91, 9–19. Table 1. Chromosome-wise distribution of SSR alleles and their number (k), polymorphic information content (PIC) and allele discrimination index (Dm). Chromosome.

  10. Building Assessment Survey and Evaluation Study Summarized Data - HVAC Characteristics

    Science.gov (United States)

    In the Building Assessment Survey and Evaluation (BASE) Study Information on the characteristics of the heating, ventilation, and air conditioning (HVAC) system(s) in the entire BASE building including types of ventilation, equipment configurations, and operation and maintenance issues was acquired by examining the building plans, conducting a building walk-through, and speaking with the building owner, manager, and/or operator.

  11. A systematic review of clinical supervision evaluation studies in nursing.

    Science.gov (United States)

    Cutcliffe, John R; Sloan, Graham; Bashaw, Marie

    2018-02-15

    According to the international, extant literature published during the last 20 years or so, clinical supervision (CS) in nursing is now a reasonably common phenomenon. Nevertheless, what appears to be noticeably 'thin on the ground' in this body of literature are empirical evaluations of CS, especially those pertaining to client outcomes. Accordingly, the authors undertook a systematic review of empirical evaluations of CS in nursing to determine the state of the science. Adopting the approach documented by Stroup et al. (JAMA, 283, 2000, 2008), the authors searched for reports of evaluation studies of CS in nursing - published during the years 1995 to 2015. Keywords for the search were 'clinical supervision', 'evaluation', 'efficacy', 'nursing', and combinations of these keywords. Electronic databases used were CINAHL, MEDLINE, PsychLIT, and the British Nursing Index. The research evidence from twenty-eight (28) studies reviewed is presented, outlining the main findings with an overview of each study presented. The following broad themes were identified and are each discussed in the study: narrative/anecdotal accounts of positive outcomes for clinical supervision, narrative/anecdotal accounts of negative outcomes for clinical supervision, empirical positive outcomes reported by supervisee, and empirical findings showing no effect by supervisee. © 2018 Australian College of Mental Health Nurses Inc.

  12. Digital Libraries and Repositories in India: An Evaluative Study

    Science.gov (United States)

    Mittal, Rekha; Mahesh, G.

    2008-01-01

    Purpose: The purpose of this research is to identify and evaluate the collections within digital libraries and repositories in India available in the public domain. Design/methodology/approach: The digital libraries and repositories were identified through a study of the literature, as well as internet searching and browsing. The resulting digital…

  13. Evaluating care from a care ethical perspective:: A pilot study.

    Science.gov (United States)

    Kuis, Esther E; Goossensen, Anne

    2017-08-01

    Care ethical theories provide an excellent opening for evaluation of healthcare practices since searching for (moments of) good care from a moral perspective is central to care ethics. However, a fruitful way to translate care ethical insights into measurable criteria and how to measure these criteria has as yet been unexplored: this study describes one of the first attempts. To investigate whether the emotional touchpoint method is suitable for evaluating care from a care ethical perspective. An adapted version of the emotional touchpoint interview method was used. Touchpoints represent the key moments to the experience of receiving care, where the patient recalls being touched emotionally or cognitively. Participants and research context: Interviews were conducted at three different care settings: a hospital, mental healthcare institution and care facility for older people. A total of 31 participants (29 patients and 2 relatives) took part in the study. Ethical considerations: The research was found not to be subject to the (Dutch) Medical Research Involving Human Subjects Act. A three-step care ethical evaluation model was developed and described using two touchpoints as examples. A focus group meeting showed that the method was considered of great value for partaking institutions in comparison with existing methods. Reflection and discussion: Considering existing methods to evaluate quality of care, the touchpoint method belongs to the category of instruments which evaluate the patient experience. The touchpoint method distinguishes itself because no pre-defined categories are used but the values of patients are followed, which is an essential issue from a care ethical perspective. The method portrays the insider perspective of patients and thereby contributes to humanizing care. The touchpoint method is a valuable instrument for evaluating care; it generates evaluation data about the core care ethical principle of responsiveness.

  14. Determination of reliability of express forecasting evaluation of radiometric enriching ability of non-ferrous ores

    International Nuclear Information System (INIS)

    Kirpishchikov, S.P.

    1991-01-01

    Use of the data of nuclear physical methods of sampling and logging enables to improve reliability of evaluation of radiometric enriching ability of ores, as well as to evaluate quantitatively this reliability. This problem may be solved by using some concepts of geostatistics. The presented results enable to conclude, that the data of nuclear-physical methods of sampling and logging can provide high reliability of evaluation of radiometric enriching ability of non-ferrous ores and their geometrization by technological types

  15. ExaGeoStat: A High Performance Unified Framework for Geostatistics on Manycore Systems

    KAUST Repository

    Abdulah, Sameh

    2017-08-09

    We present ExaGeoStat, a high performance framework for geospatial statistics in climate and environment modeling. In contrast to simulation based on partial differential equations derived from first-principles modeling, ExaGeoStat employs a statistical model based on the evaluation of the Gaussian log-likelihood function, which operates on a large dense covariance matrix. Generated by the parametrizable Matern covariance function, the resulting matrix is symmetric and positive definite. The computational tasks involved during the evaluation of the Gaussian log-likelihood function become daunting as the number n of geographical locations grows, as O(n2) storage and O(n3) operations are required. While many approximation methods have been devised from the side of statistical modeling to ameliorate these polynomial complexities, we are interested here in the complementary approach of evaluating the exact algebraic result by exploiting advances in solution algorithms and many-core computer architectures. Using state-of-the-art high performance dense linear algebra libraries associated with various leading edge parallel architectures (Intel KNLs, NVIDIA GPUs, and distributed-memory systems), ExaGeoStat raises the game for statistical applications from climate and environmental science. ExaGeoStat provides a reference evaluation of statistical parameters, with which to assess the validity of the various approaches based on approximation. The framework takes a first step in the merger of large-scale data analytics and extreme computing for geospatial statistical applications, to be followed by additional complexity reducing improvements from the solver side that can be implemented under the same interface. Thus, a single uncompromised statistical model can ultimately be executed in a wide variety of emerging exascale environments.

  16. Applicability of geostatistical methods and optimization of data for assessing hydraulic and geological conditions as a basis for remediation measures in the Ronneburg ore mining district

    International Nuclear Information System (INIS)

    Post, C.

    2001-01-01

    The remediation of the former Wismut mines in Thuringia has been planed and prepared since 1990. Objects of remediation are mines, tailing ponds and waste rock piles. Since more than 40 years of mining have had a great affect on the exploited aquifer, special emphasis is given to groundwater recharge so that minery-flooding is one of the conceivable remedial options. Controlled flooding supports minimising the expanded oxidation zone, which renders an immense pollutant potential, while at the same time the flooding reduces the quantity of acid mine water, that has to be treated. One of the main tasks of modelling the flooding progress is to determine and prognosticate the wateroutlet-places. Due to the inadequacy of the database from the production period, limited accuracy of the available data and because of the inherent uncertainty of approximations used in numerical modelling, a stochastic approach is prospected. The flooding predictions, i.e. modelling of hydrodynamical and hydrochemical conditions during and after completion of flooding predominantly depend on the spatial distribution of the hydraulic conductivity. In order to get a better understanding of the spatial heterogeneity of the Palaeozoic fractured rock aquifer, certain geostatistical interpolation methods are tested to achieve the best approach for describing the hydrogeological parameters in space. This work deals in detail with two selected geostatistical interpolation methods (ordinary and indicator kriging) and discusses their applicability and limitations including the application of the presented case. Another important target is the specification of the database and the improvement of consistency with statistical standards. The main emphasis lies on the spatial distribution of the measured hydraulic conductivity coefficient, its estimation at non-measured places and the influence of its spatial variability on modelling results. This topic is followed by the calculation of the estimation

  17. Characterization and evaluation studies on some JAERI dosimetry systems

    International Nuclear Information System (INIS)

    Kojima, T.; Sunaga, H.; Tachibana, H.; Takizawa, H.; Tanaka, R.

    2000-01-01

    Characterization and evaluation studies were carried out on some JAERI dosimetry systems, mainly alanine-ESR, in terms of the influence on the dose response of parameters such as orientation at ESR analysis, and the temperature during irradiation and analysis. Feasibility study for application of these dosimetry systems to electrons with energies lower than 4 MeV and bremsstrahlung (X rays) was also performed parallel to their reliability check through international dose intercomparison. (author)

  18. Non-destructive evaluation studies for cultural heritage

    International Nuclear Information System (INIS)

    Jayakumar, T.; Babu Rao, C.; Kumar, Anish; Rajkumar, K.V.; Sharma, G.K.; Raj, Baldev

    2009-01-01

    The results of the nondestructive evaluation studies carried out on the Delhi iron pillar and the musical pillars of the Vithala temple at Hampi, Karnataka are discussed. While studies on Delhi iron pillar were carried out with a primary aim to understand the methodology of fabrication of this pillar, the studies on the musical pillars were carried out to finger print/petroligically characterize the stones used in the construction of the musical pillars and to understand the origin of various sounds generated on tapping of the musical pillars by carrying out various acoustic studies. (author)

  19. Study on Mechanism Experiments and Evaluation Methods for Water Eutrophication

    Directory of Open Access Journals (Sweden)

    Jiabin Yu

    2017-01-01

    Full Text Available The process of water eutrophication involves the interaction of external factors, nutrients, microorganisms, and other factors. It is complex and has not yet been effectively studied. To examine the formation process of water eutrophication, a set of orthogonal experiments with three factors and four levels is designed to analyze the key factors. At the same time, with the help of a large amount of monitoring data, the principal component analysis method is used to extract the main components of water eutrophication and determine the effective evaluation indicators of eutrophication. Finally, the Bayesian theory of uncertainty is applied to the evaluation of the eutrophication process to evaluate the sample data. The simulation results demonstrate the validity of the research method.

  20. Geostatistical model-based estimates of schistosomiasis prevalence among individuals aged = 20 years in West Africa

    DEFF Research Database (Denmark)

    Schur, Nadine; Hürlimann, Eveline; Garba, Amadou

    2011-01-01

    Schistosomiasis is a water-based disease that is believed to affect over 200 million people with an estimated 97% of the infections concentrated in Africa. However, these statistics are largely based on population re-adjusted data originally published by Utroska and colleagues more than 20 years...... ago. Hence, these estimates are outdated due to large-scale preventive chemotherapy programs, improved sanitation, water resources development and management, among other reasons. For planning, coordination, and evaluation of control activities, it is essential to possess reliable schistosomiasis...

  1. A study on the quantitative evaluation of skin barrier function

    Science.gov (United States)

    Maruyama, Tomomi; Kabetani, Yasuhiro; Kido, Michiko; Yamada, Kenji; Oikaze, Hirotoshi; Takechi, Yohei; Furuta, Tomotaka; Ishii, Shoichi; Katayama, Haruna; Jeong, Hieyong; Ohno, Yuko

    2015-03-01

    We propose a quantitative evaluation method of skin barrier function using Optical Coherence Microscopy system (OCM system) with coherency of near-infrared light. There are a lot of skin problems such as itching, irritation and so on. It has been recognized skin problems are caused by impairment of skin barrier function, which prevents damage from various external stimuli and loss of water. To evaluate skin barrier function, it is a common strategy that they observe skin surface and ask patients about their skin condition. The methods are subjective judgements and they are influenced by difference of experience of persons. Furthermore, microscopy has been used to observe inner structure of the skin in detail, and in vitro measurements like microscopy requires tissue sampling. On the other hand, it is necessary to assess objectively skin barrier function by quantitative evaluation method. In addition, non-invasive and nondestructive measuring method and examination changes over time are needed. Therefore, in vivo measurements are crucial for evaluating skin barrier function. In this study, we evaluate changes of stratum corneum structure which is important for evaluating skin barrier function by comparing water-penetrated skin with normal skin using a system with coherency of near-infrared light. Proposed method can obtain in vivo 3D images of inner structure of body tissue, which is non-invasive and non-destructive measuring method. We formulate changes of skin ultrastructure after water penetration. Finally, we evaluate the limit of performance of the OCM system in this work in order to discuss how to improve the OCM system.

  2. Application of Learning Curves for Didactic Model Evaluation: Case Studies

    Directory of Open Access Journals (Sweden)

    Felix Mödritscher

    2013-01-01

    Full Text Available The success of (online courses depends, among other factors, on the underlying didactical models which have always been evaluated with qualitative and quantitative research methods. Several new evaluation techniques have been developed and established in the last years. One of them is ‘learning curves’, which aim at measuring error rates of users when they interact with adaptive educational systems, thereby enabling the underlying models to be evaluated and improved. In this paper, we report how we have applied this new method to two case studies to show that learning curves are useful to evaluate didactical models and their implementation in educational platforms. Results show that the error rates follow a power law distribution with each additional attempt if the didactical model of an instructional unit is valid. Furthermore, the initial error rate, the slope of the curve and the goodness of fit of the curve are valid indicators for the difficulty level of a course and the quality of its didactical model. As a conclusion, the idea of applying learning curves for evaluating didactical model on the basis of usage data is considered to be valuable for supporting teachers and learning content providers in improving their online courses.

  3. A framework and case studies for evaluation of enzyme ontogeny in children's health risk evaluation.

    Science.gov (United States)

    Ginsberg, Gary; Vulimiri, Suryanarayana V; Lin, Yu-Sheng; Kancherla, Jayaram; Foos, Brenda; Sonawane, Babasaheb

    2017-01-01

    Knowledge of the ontogeny of Phase I and Phase II metabolizing enzymes may be used to inform children's vulnerability based upon likely differences in internal dose from xenobiotic exposure. This might provide a qualitative assessment of toxicokinetic (TK) variability and uncertainty pertinent to early lifestages and help scope a more quantitative physiologically based toxicokinetic (PBTK) assessment. Although much is known regarding the ontogeny of metabolizing systems, this is not commonly utilized in scoping and problem formulation stage of human health risk evaluation. A framework is proposed for introducing this information into problem formulation which combines data on enzyme ontogeny and chemical-specific TK to explore potential child/adult differences in internal dose and whether such metabolic differences may be important factors in risk evaluation. The framework is illustrated with five case study chemicals, including some which are data rich and provide proof of concept, while others are data poor. Case studies for toluene and chlorpyrifos indicate potentially important child/adult TK differences while scoping for acetaminophen suggests enzyme ontogeny is unlikely to increase early-life risks. Scoping for trichloroethylene and aromatic amines indicates numerous ways that enzyme ontogeny may affect internal dose which necessitates further evaluation. PBTK modeling is a critical and feasible next step to further evaluate child-adult differences in internal dose for a number of these chemicals.

  4. Evaluation of hybrid power system alternatives: a case study

    International Nuclear Information System (INIS)

    Rosenthal, Andrew L.

    1999-01-01

    Pursuant to executive and statutory policies, the National Park Service (NPS) has been evaluating the use of photovoltaic (PV) hybrid power systems, for many of its remote, off-grid areas. This paper reports the results of a detailed technical and economic evaluation for one such area: the Needles District of Canyonlands National Park. The study evaluates the presented power systems and five alternative power generation configurations, four of which utilise PV. Projections are provided for the generator run-time and fuel use associated with each configuration as well as all initial and future costs. Included in the study are specific recommendations for energy efficiency improvements at the site. Results show that the generation systems presently in use, two full-time diesel generators, has the lowest conventional 20-year life cycle costs (LCC) of the six systems evaluated. However, when emissions costs are included (per NPS guidelines), several of the PV hybrid alternatives attain a lower LCC than the diesel-only systems. General discussion of the effects of initial versus future costs of PV hybrids as they compare with engine generator system is presented. (Author)

  5. Surgery resident selection and evaluation. A critical incident study.

    Science.gov (United States)

    Edwards, J C; Currie, M L; Wade, T P; Kaminski, D L

    1993-03-01

    This article reports a study of the process of selecting and evaluating general surgery residents. In personnel psychology terms, a job analysis of general surgery was conducted using the Critical Incident Technique (CIT). The researchers collected 235 critical incidents through structured interviews with 10 general surgery faculty members and four senior residents. The researchers then directed the surgeons in a two-step process of sorting the incidents into categories and naming the categories. The final essential categories of behavior to define surgical competence were derived through discussion among the surgeons until a consensus was formed. Those categories are knowledge/self-education, clinical performance, diagnostic skills, surgical skills, communication skills, reliability, integrity, compassion, organization skills, motivation, emotional control, and personal appearance. These categories were then used to develop an interview evaluation form for selection purposes and a performance evaluation form to be used throughout residency training. Thus a continuum of evaluation was established. The categories and critical incidents were also used to structure the interview process, which has demonstrated increased interview validity and reliability in many other studies. A handbook for structuring the interviews faculty members conduct with applicants was written, and an interview training session was held with the faculty. The process of implementation of the structured selection interviews is being documented currently through qualitative research.

  6. Economic evaluation of the Blanket Comparison and Selection Study

    International Nuclear Information System (INIS)

    Waganer, L.M.

    1985-01-01

    The economic impact of employing the highly ranked blankets in the Blanket Comparison and Selection Study (BCSS) was evaluated in the context of both a tokamak and a tandem mirror power reactor (TMR). The economic evaluation criterion was determined to be the cost of electricity. The influencing factors that were considered are the direct cost of the blankets and related systems; the annual cost of blanket replacement; and the performance of the blanket, heat transfer, and energy conversion systems. The technical and cost bases for comparison were those of the STARFIRE and Mirror Advanced Reactor Study conceptual design power plants. The economic evaluation results indicated that the nitrate-salt-cooled blanket concept is an economically attractive concept for either reactor type. The water-cooled, solid breeder blanket is attractive for the tokamak and somewhat less attractive for the TMR. The helium-cooled, liquidlithium breeder blanket is the least economically desirable of higher ranked concepts. The remaining self-cooled liquid-metal and the helium-cooled blanket concepts represent moderately attractive concepts from an economic standpoint. These results are not in concert with those found in the other BCSS evaluation areas (engineering feasibility, safety, and research and development (R and D) requirements). The blankets faring well economically had generally lower cost components, lower pumping power requirements, and good power production capability. On the other hand, helium- and lithium-cooled systems were preferred from the standpoints of safety, engineering feasibility, and R and D requirements

  7. Study of evaluation techniques of software configuration management and reliability

    Energy Technology Data Exchange (ETDEWEB)

    Youn, Cheong; Baek, Y. W.; Kim, H. C.; Han, H. C.; Choi, C. R. [Chungnam National Univ., Taejon (Korea, Republic of)

    2001-03-15

    The Study of activities to solve software safety and quality must be executed in base of establishing software development process for digitalized nuclear plant. Especially study of software testing and Verification and Validation must executed. For this purpose methodologies and tools which can improve software qualities are evaluated and software Testing, V and V and Configuration Management which can be applied to software life cycle are investigated. This study establish a guideline that can be used to assure software safety and reliability requirements in digitalized nuclear plant systems.

  8. Data envelopment analysis in service quality evaluation: an empirical study

    Science.gov (United States)

    Najafi, Seyedvahid; Saati, Saber; Tavana, Madjid

    2015-09-01

    Service quality is often conceptualized as the comparison between service expectations and the actual performance perceptions. It enhances customer satisfaction, decreases customer defection, and promotes customer loyalty. Substantial literature has examined the concept of service quality, its dimensions, and measurement methods. We introduce the perceived service quality index (PSQI) as a single measure for evaluating the multiple-item service quality construct based on the SERVQUAL model. A slack-based measure (SBM) of efficiency with constant inputs is used to calculate the PSQI. In addition, a non-linear programming model based on the SBM is proposed to delineate an improvement guideline and improve service quality. An empirical study is conducted to assess the applicability of the method proposed in this study. A large number of studies have used DEA as a benchmarking tool to measure service quality. These models do not propose a coherent performance evaluation construct and consequently fail to deliver improvement guidelines for improving service quality. The DEA models proposed in this study are designed to evaluate and improve service quality within a comprehensive framework and without any dependency on external data.

  9. Participant evaluation results for two indoor air quality studies

    International Nuclear Information System (INIS)

    Hawthorne, A.R.; Dudney, C.S.; Cohen, M.A.; Spengler, J.D.

    1987-01-01

    After two surveys for indoor air pollutants (radon and other chemicals) the homeowners were surveyed for their reactions. The results of these participant evaluation surveys, assuming that the participants that responded to the survey were representative, indicate that homeowners will accept a significant level of monitoring activity as part of an indoor air quality field study. Those participants completing surveys overwhelmingly enjoyed being in the studies and would do it again. We believe that the emphasis placed on positive homeowner interactions and efforts made to inform participants throughout our studies were positive factors in this result. There was no substantial differences noted in the responses between the 70-house study, which included a homeowner compensation payment of $100, and the 300-house study, which did not include a compensation payment. These results provide encouragement to conduct future complex, multipollutant indoor air quality studies when they are scientifically sound and cost effective

  10. Nuclear plant power up-rate study: feedwater heater evaluations

    International Nuclear Information System (INIS)

    Svensson, Eric; Catapano, Michael; Coakley, Michael; Thomas, Dan

    2014-01-01

    Given today's nuclear industry business climate, it has become common for Utility companies to consider increasing unit capacities through turbine replacement and power up-rates. An integral part of the studies conducted by many towards this end, involve the generation of a set of turbine cycle heat balances with predicted performance parameters for the up-rated condition. Once these tentative operating values are established, it becomes necessary to evaluate the suitability of the existing components within each system to ensure they are capable of continued safe and reliable operation. The ultimate cost for the up-rate, including the cost for any major required modifications or significant replacements is weighed against increased revenue generated from the up-rate over time. Exelon's Peach Bottom Atomic Power Station (PBAPS) is currently planning for an Extended Power up-rate (EPU) for both units. To ensure the existing Feedwater Heaters (FWH) could maintain the operating and transient response margins at the EPU condition, an engineering study was conducted. Powerfect Inc. in conjunction with SPX Heat Transfer LLC were contracted to provide engineering services to analyze the design, thermal performance, reliability and operating conditions at projected EPU conditions. Specifically, to address the following with regard to the station's Feedwater Heaters (FWHs): 1. Evaluate Drain Cooler (DC) Velocities - including zone inlet velocity, cross and window velocities and outlet velocities. 2. Evaluate Drain Cooler Zone Pressure Drop for effect on drain cooler margins to flashing. 3. Evaluate differential pressure allowable across the pass partition plate. 4. Evaluate Drain Cooler Tube Vibration Potential. 5. Perform detailed steam dome velocity calculations. The goal of the study was to identify the most susceptible areas within the heaters for problems and potential failures when operating at the higher duty of the EPU condition for the remaining life

  11. Status of fusion reactor blanket evaluation studies in France

    International Nuclear Information System (INIS)

    Carre, F.; Chevereau, G.; Gervaise, F.; Proust, E.

    1985-03-01

    In the frame of recent CEA studies aiming at the evaluation and at the comparison of various candidate blanket concepts in moderate power conditions (Psub(n) approximately 2 MW/m 2 ), the present work examines the neutronic and thermomechanical performances of a water cooled Li 17 Pb 83 tubular blanket and those of a helium cooled canister blanket taking advantage of the excellent breeding capability of composite Beryllium/LiAlO 2 (85/15%) breeder elements. The purpose of the following discussion is to justify the impetus for these reference concepts and to summarize the state of their evaluation studies updated by the continuous assimilation of calculations and experiments in progress

  12. Ethics reflection groups in community health services: an evaluation study.

    Science.gov (United States)

    Lillemoen, Lillian; Pedersen, Reidar

    2015-04-17

    Systematic ethics support in community health services in Norway is in the initial phase. There are few evaluation studies about the significance of ethics reflection on care. The aim of this study was to evaluate systematic ethics reflection in groups in community health (including nursing homes and residency), - from the perspectives of employees participating in the groups, the group facilitators and the service managers. The reflection groups were implemented as part of a research and development project. A mixed-methods design with qualitative focus group interviews, observations and written reports were used to evaluate. The study was conducted at two nursing homes, two home care districts and a residence for people with learning disabilities. Participants were employees, facilitators and service managers. The study was guided by ethical standard principles and was approved by the Norwegian Social Science Data Services. We found support for ethics reflection as a valuable measure to strengthen clinical practice. New and improved solutions, more cooperation between employees, and improved collaboration with patients and their families are some of the results. No negative experiences were found. Instead, the ethics reflection based on experiences and challenges in the workplace, was described as a win-win situation. The evaluation also revealed what is needed to succeed and useful tips for further development of ethics support in community health services. Ethics reflection groups focusing on ethical challenges from the participants' daily work were found to be significant for improved practice, collegial support and cooperation, personal and professional development among staff, facilitators and managers. Resources needed to succeed were managerial support, and anchoring ethics sessions in the routine of daily work.

  13. Study and Evaluation of Current and Future Aircraft Loaders

    Science.gov (United States)

    1986-08-01

    detonation intense Electromagnetic Pulse Eergy (DIP) is gene - rated which could seriously affect the electronic equipment. 2-105 The intense...speciality efforts, such as integrated logistics support (ILS), human factors engineering ( HFE ), and reliability, availability and m aintainability...task analyiis is outlined in detail in Appendix C: Human Fac- tors Enqineering Study and Evaluation of Current and Future Aircraft Loaders. The HFE

  14. High performance APCS conceptual design and evaluation scoping study

    International Nuclear Information System (INIS)

    Soelberg, N.; Liekhus, K.; Chambers, A.; Anderson, G.

    1998-02-01

    This Air Pollution Control System (APCS) Conceptual Design and Evaluation study was conducted to evaluate a high-performance (APC) system for minimizing air emissions from mixed waste thermal treatment systems. Seven variations of high-performance APCS designs were conceptualized using several design objectives. One of the system designs was selected for detailed process simulation using ASPEN PLUS to determine material and energy balances and evaluate performance. Installed system capital costs were also estimated. Sensitivity studies were conducted to evaluate the incremental cost and benefit of added carbon adsorber beds for mercury control, specific catalytic reduction for NO x control, and offgas retention tanks for holding the offgas until sample analysis is conducted to verify that the offgas meets emission limits. Results show that the high-performance dry-wet APCS can easily meet all expected emission limits except for possibly mercury. The capability to achieve high levels of mercury control (potentially necessary for thermally treating some DOE mixed streams) could not be validated using current performance data for mercury control technologies. The engineering approach and ASPEN PLUS modeling tool developed and used in this study identified APC equipment and system performance, size, cost, and other issues that are not yet resolved. These issues need to be addressed in feasibility studies and conceptual designs for new facilities or for determining how to modify existing facilities to meet expected emission limits. The ASPEN PLUS process simulation with current and refined input assumptions and calculations can be used to provide system performance information for decision-making, identifying best options, estimating costs, reducing the potential for emission violations, providing information needed for waste flow analysis, incorporating new APCS technologies in existing designs, or performing facility design and permitting activities

  15. Accuracy and uncertainty analysis of soil Bbf spatial distribution estimation at a coking plant-contaminated site based on normalization geostatistical technologies.

    Science.gov (United States)

    Liu, Geng; Niu, Junjie; Zhang, Chao; Guo, Guanlin

    2015-12-01

    Data distribution is usually skewed severely by the presence of hot spots in contaminated sites. This causes difficulties for accurate geostatistical data transformation. Three types of typical normal distribution transformation methods termed the normal score, Johnson, and Box-Cox transformations were applied to compare the effects of spatial interpolation with normal distribution transformation data of benzo(b)fluoranthene in a large-scale coking plant-contaminated site in north China. Three normal transformation methods decreased the skewness and kurtosis of the benzo(b)fluoranthene, and all the transformed data passed the Kolmogorov-Smirnov test threshold. Cross validation showed that Johnson ordinary kriging has a minimum root-mean-square error of 1.17 and a mean error of 0.19, which was more accurate than the other two models. The area with fewer sampling points and that with high levels of contamination showed the largest prediction standard errors based on the Johnson ordinary kriging prediction map. We introduce an ideal normal transformation method prior to geostatistical estimation for severely skewed data, which enhances the reliability of risk estimation and improves the accuracy for determination of remediation boundaries.

  16. Evaluate VTS benefits: A case study of Zhoushan Port

    Directory of Open Access Journals (Sweden)

    Jun-Min Mou

    2015-12-01

    Full Text Available It has been well acknowledged that Vessel Traffic Services (VTS has played a growing important role to ensure the safety of navigation in the busy ports and waterways. However, the benefits produced by VTS are usually ignored by the public and private sectors. Besides, the previous evaluations generally exist following problems: (1 It is difficult to collect the data for the parameters in the evaluation models and/or the parameters are designed illogically; (2 Those models did not take the following factors into consideration such as reducing the frequency of coastal vessel patrolling and saving human and material resources; (3 It is difficult to clearly discriminate the benefits derived from VTS and non-VTS. In this paper, a framework is presented to calculate the benefits of VTS in China. Four key indicators (safety, traffic efficiency, environmental protection and reducing supervising cost and quantitative methods have been introduced into the framework. When calculating the benefits quantitatively, the traffic condition before the construction (expansion of the VTS has acted as a benchmark. For a case study, the project of the expansion of VTS in Zhoushan Port, East China was evaluated with 10-year data. According to the results, the largest contribution is from the benefit of environmental protection. Via Cost-benefit analysis the benefit cost ratio (B/C of the VTS is up to 5.248, which shows the benefits produced by VTS are considerable. The research could provide references for VTS benefits evaluation and investment optimizing.

  17. [Comparing audiological evaluation and screening: a study on presbycusis].

    Science.gov (United States)

    Samelli, Alessandra Giannella; Negretti, Camila Aparecida; Ueda, Kerli Saori; Moreira, Renata Rodrigues; Schochat, Eliane

    2011-01-01

    Given the high prevalence of presbycusis and the damage it brings about, a screening test can be useful in the identification of hearing loss in primary care. To estimate the prevalence of hearing loss in a representative sample of elderly people living at Butantan using an audiological screening method (questionnaire) and a basic audiological evaluation; to compare the results of the two kinds of evaluations, checking the validity of this tool for hearing loss screening. Cross sectional descriptive study. 200 individuals (above 60 years old, both genders) were randomly selected to undergo audiological screening (questionnaire). Another randomly selected group encompassed 100 individuals who were submitted to a set of audiological tests. Then, we compared the results from the two methods. There were no statistically significant associations between the questionnaire and the degree of hearing loss of the patients. The prevalence of hearing loss in our sample was of 56% in the screening and of 95% when checked by the audiological evaluation. Therefore, screening was not proven valid to assess hearing when compared to audiological evaluation.

  18. Objectives and present status of the German risk evaluation study

    International Nuclear Information System (INIS)

    Birkhofer, A.; Koeberlein, K.; Heuser, F.W.

    1977-01-01

    For the German risk evaluation study, analogous to the Rasmussen report (WASH--1400), embarked upon in June 1976, the Kernkraftwerk Biblis B serves as the plant of reference. The first interim results are available for various sub-headings of the study. The main finding seems to be the decisive importance of the containment in limiting the accident consequences even in those cases where, on account of postulated failure of safety systems, the melt down of the reactor core is to be expected. (orig./HP) [de

  19. Methodology and Applications in Non-linear Model-based Geostatistics

    DEFF Research Database (Denmark)

    Christensen, Ole Fredslund

    that are approximately Gaussian. Parameter estimation and prediction for the transformed Gaussian model is studied. In some cases a transformation cannot possibly render the data Gaussian. A methodology for analysing such data was introduced by Diggle, Tawn and Moyeed (1998): The generalised linear spatial model...... priors for Bayesian inference is discussed. Procedures for parameter estimation and prediction are studied. Theoretical properties of Markov chain Monte Carlo algorithms are investigated, and different algorithms are compared. In addition, the thesis contains a manual for an R-package, geoRglmm, which...

  20. A geostatistical approach to data harmonization - Application to radioactivity exposure data

    NARCIS (Netherlands)

    Baume, O.; Skoien, J.O.; Heuvelink, G.B.M.; Pebesma, E.J.; Melles, S.J.

    2011-01-01

    Environmental issues such as air, groundwater pollution and climate change are frequently studied at spatial scales that cross boundaries between political and administrative regions. It is common for different administrations to employ different data collection methods. If these differences are not

  1. Integrating interferometric SAR data with levelling measurements of land subsidence using geostatistics

    NARCIS (Netherlands)

    Zhou, Y.; Stein, A.; Molenaar, M.

    2003-01-01

    Differential Synthetic Aperture Radar (SAR) interferometric (D-InSAR) data of ground surface deformation are affected by several error sources associated with image acquisitions and data processing. In this paper, we study the use of D-InSAR for quantifying land subsidence due to groundwater

  2. Development of Geostatistical Models to Estimate CO2 Storage Resource in Sedimentary Geologic Formations

    Science.gov (United States)

    Popova, Olga H.

    Dental hygiene students must embody effective critical thinking skills in order to provide evidence-based comprehensive patient care. The problem addressed in this study it was not known if and to what extent concept mapping and reflective journaling activities embedded in a curriculum over a 4-week period, impacted the critical thinking skills of 22 first and second-year dental hygiene students attending a community college in the Midwest. The overarching research questions were: what is the effect of concept mapping, and what is the effect of reflective journaling on the level of critical thinking skills of first and second year dental hygiene students? This quantitative study employed a quasi-experimental, pretest-posttest design. Analysis of Covariance (ANCOVA) assessed students' mean scores of critical thinking on the California Critical Thinking Skills Test (CCTST) pretest and posttest for the concept mapping and reflective journaling treatment groups. The results of the study found an increase in CCTST posttest scores with the use of both concept mapping and reflective journaling. However, the increase in scores was not found to be statistically significant. Hence, this study identified concept mapping using Ausubel's assimilation theory and reflective journaling incorporating Johns's revision of Carper's patterns of knowing as potential instructional strategies and theoretical models to enhance undergraduate students' critical thinking skills. More research is required in this area to draw further conclusions. Keywords: Critical thinking, critical thinking development, critical thinking skills, instructional strategies, concept mapping, reflective journaling, dental hygiene, college students.

  3. Photocatalytic degradation of rosuvastatin: Analytical studies and toxicity evaluations

    Energy Technology Data Exchange (ETDEWEB)

    Machado, Tiele Caprioli, E-mail: tiele@enq.ufrgs.br [Chemical Engineering Department, Federal University of Rio Grande do Sul, Rua Engenheiro Luiz Englert s/n, CEP: 90040-040 Porto Alegre, RS (Brazil); Pizzolato, Tânia Mara [Chemical Institute, Federal University of Rio Grande do Sul, Avenida Bento Gonçalves, 9500, CEP: 91501-970 Porto Alegre, RS (Brazil); Arenzon, Alexandre [Ecology Center, Federal University of Rio Grande do Sul, Avenida Bento Gonçalves, 9500, CEP: 91501-970 Porto Alegre, RS (Brazil); Segalin, Jeferson [Biotechnology Center, Federal University of Rio Grande do Sul, Avenida Bento Gonçalves, 9500, CEP: 91501-970 Porto Alegre, RS (Brazil); Lansarin, Marla Azário [Chemical Engineering Department, Federal University of Rio Grande do Sul, Rua Engenheiro Luiz Englert s/n, CEP: 90040-040 Porto Alegre, RS (Brazil)

    2015-01-01

    Photocatalytic degradation of rosuvastatin, which is a drug that has been used to reduce blood cholesterol levels, was studied in this work employing ZnO as catalyst. The experiments were carried out in a temperature-controlled batch reactor that was irradiated with UV light. Preliminary the effects of the photocatalyst loading, the initial pH and the initial rosuvastatin concentration were evaluated. The experimental results showed that rosuvastatin degradation is primarily a photocatalytic process, with pseudo-first order kinetics. The byproducts that were generated during the oxidative process were identified using nano-ultra performance liquid chromatography tandem mass spectrometry (nano-UPLC–MS/MS) and acute toxicity tests using Daphnia magna were done to evaluate the toxicity of the untreated rosuvastatin solution and the reactor effluent. - Highlights: • The photocatalytic degradation of rosuvastatin was studied under UV irradiation. • Commercial catalyst ZnO was used. • Initial rosuvastatin concentration, photocatalyst loading and pH were evaluated. • The byproducts generated during the oxidative process were detected and identified. • Acute toxicity tests using Daphnia magna were carried out.

  4. Studying the Foreign Experience of Evaluating Intellectual Potential of Organizations

    Directory of Open Access Journals (Sweden)

    Pererva Petro G.

    2016-01-01

    Full Text Available The use of intellectual capital (IC is considered in developed countries as a strategic management tool for achievement of the organizations' success in innovative activities. The article is aimed at studying the foreign experience of evaluating intellectual potential of organizations and identifying directions for its advancement and use at the domestic enterprises to improve their innovative activity. An approach to capital structure has been developed, in which the following three parts are allocated: human capital, structural capital, capital of interactions. The proposed general model for research of IC in terms of firm or region allows to evaluate not only the potential, but also several important lines of communication, namely: industrial-technological, market-customer, business environment and society, commercial operations (technology, value creation and the overall development strategy. In the proposed version of studying the IC potential, analytics are combined with management of both strategy and development tactics, based on use of resources of intellectual capital. The scheme of development management through the system of the activities of influence is recommended as well. The end result of the analytical project work provides the development package, which is issued as a supporting document of development strategy. Evaluation of the development level of intellectual capital in the context of individual enterprises and of regional complex in general has been recommended to include in the Regional innovation system (RIS as one of its functional tasks

  5. EIA and EINP. Evaluation study; EIA en EINP. Evaluatiestudie

    Energy Technology Data Exchange (ETDEWEB)

    Lande, R.W.I. van der; De Vries, E.F

    2001-11-29

    The evaluation study on the title subjects concerns two subsidy tools in the Netherlands: the Energy Investment Rebate (EIA, abbreviated in Dutch) and the Subsidy for Energy in the non-profit sector and other special sectors (EINP, abbreviated in Dutch). The central question in the evaluation was to what extent did the EIA and EINP contribute to the original policy targets and at what costs. The evaluation has been carried out by means of a desk study, interviews, and an analysis of bottlenecks and possible solutions. [Dutch] In opdracht van het ministerie van Economische Zaken is een evaluatie opgesteld van de instrumenten Energie-investeringsaftrek (EIA) en de Subsidieregeling energievoorzieningen in de non-profit sector en bijzondere sectoren (EINP). De centrale vraagstelling bij deze evaluatie was: in welke mate hebben de EIA en EINP bijgedragen aan de oorspronkelijke beleidsdoelstellingen en tegen welke kosten. Deze vraagstelling is nader uitgewerkt in de deelvragen betreffende de effectiviteit en efficiency van de regeling en de uitvoering. De evaluatie is uitgevoerd door middel van: (a) Een bureaustudie waarin de dossiers, jaarverslagen en rapportages, databestanden en overige relevante stukken zijn bestudeerd; (b) Gesprekken met degenen die bij regeling en uitvoering betrokken waren; (c) Een veldstudie waarin gesprekken zijn gevoerd met circa 40 organisaties; (d) Een analyse waarin onder andere een workshop is gehouden met betrokkenen waarin knelpunten en mogelijke oplossingen zijn besproken.

  6. Study on tube rupture strength evaluation method for rapid overheating

    International Nuclear Information System (INIS)

    Komine, Ryuji; Wada, Yusaku

    1998-08-01

    A sodium-water reaction derived from the single tube break in steam generator might overheat neighbor tubes rapidly under internal pressure loadings. If the temperature of tube wall becomes too high, it has to be evaluated that the stress of tube does not exceed the material strength limit to prevent the propagation of tube rupture. In the present study this phenomenon was recognized as the fracture of cylindrical tube with the large deformation due to overheating, and the evaluation method was investigated based on both of experimental and analytical approaches. The results obtained are as follows. (1) As for the nominal stress estimation, it was clarified through the experimental data and the detailed FEM elasto-plastic large deformation analysis that the formula used in conventional designs can be applied. (2) Within the overheating temperature limits of tubes, the creep effect is dominant, even if the loading time is too short. So the strain rate on the basis of JIS elevated temperature tensile test method for steels and heat-resisting alloys is too late and almost of total strain is composed by creep one. As a result the time dependent effect cannot be evaluated under JIS strain rate condition. (3) Creep tests in shorter time condition than a few minutes and tensile tests in higher strain rate condition than 10%/min of JIS are carried out for 2 1/4Cr-1Mo(NT) steel, and the standard values for tube rupture strength evaluation are formulated. (4) The above evaluation method based on both of the stress estimation and the strength standard values application is justified by using the tube burst test data under internal pressure. (5) The strength standard values on Type 321 ss is formulated in accordance with the procedure applied for 2 1/4Cr-1Mo(NT) steel. (author)

  7. Geostatistical analysis of the relationship between airborne electromagnetic data and borehole lithological data

    DEFF Research Database (Denmark)

    Barfod, Adrian; Møller, Ingelise; Christiansen, Anders Vest

    2015-01-01

    resistivity values, revealing different distribution functions for lithological categories. A very large and extensive dataset is available in Denmark through the national geophysical and borehole databases. These databases contain all geophysical and borehole data in Denmark and covers a large part of its......We present a large-scale study of the relationship between dense airborne SkyTEM resistivity data and sparse lithological borehole data. Airborne electromagnetic (AEM) data contains information about subsurface geology and hydrologic properties; however extracting this information is not trivial....... Today, geophysical data is used in combination with borehole data to create detailed geological models of the subsurface. The overall statistical relationship is, however, not widely known. The objective of this study is to develop a method for understanding the relationship between petrophysical...

  8. Geostatistical Simulation of Hydrofacies Heterogeneity of the West Thessaly Aquifer Systems in Greece

    International Nuclear Information System (INIS)

    Modis, K.; Sideri, D.

    2013-01-01

    Integrating geological properties, such as relative positions and proportions of different hydrofacies, is of highest importance in order to render realistic geological patterns. Sequential indicator simulation (SIS) and Plurigaussian simulation (PS) are alternative methods for conceptual and deterministic modeling for the characterization of hydrofacies distribution. In this work, we studied the spatial differentiation of hydrofacies in the alluvial aquifer system of West Thessaly basin in Greece. For this, we applied both SIS and PS techniques to an extensive set of borehole data from that basin. Histograms of model versus experimental hydrofacies proportions and indicative cross sections were plotted in order to validate the results. The PS technique was shown to be more effective in reproducing the spatial characteristics of the different hydrofacies and their distribution across the study area. In addition, the permeability differentiations reflected in the PS model are in accordance to known heterogeneities of the aquifer capacity.

  9. Geostatistical Simulation of Hydrofacies Heterogeneity of the West Thessaly Aquifer Systems in Greece

    Energy Technology Data Exchange (ETDEWEB)

    Modis, K., E-mail: kmodis@mail.ntua.gr; Sideri, D. [National Technical University of Athens, School of Mining and Metallurgical Engineering (Greece)

    2013-06-15

    Integrating geological properties, such as relative positions and proportions of different hydrofacies, is of highest importance in order to render realistic geological patterns. Sequential indicator simulation (SIS) and Plurigaussian simulation (PS) are alternative methods for conceptual and deterministic modeling for the characterization of hydrofacies distribution. In this work, we studied the spatial differentiation of hydrofacies in the alluvial aquifer system of West Thessaly basin in Greece. For this, we applied both SIS and PS techniques to an extensive set of borehole data from that basin. Histograms of model versus experimental hydrofacies proportions and indicative cross sections were plotted in order to validate the results. The PS technique was shown to be more effective in reproducing the spatial characteristics of the different hydrofacies and their distribution across the study area. In addition, the permeability differentiations reflected in the PS model are in accordance to known heterogeneities of the aquifer capacity.

  10. Spatial interpolation methods and geostatistics for mapping groundwater contamination in a coastal area.

    Science.gov (United States)

    Elumalai, Vetrimurugan; Brindha, K; Sithole, Bongani; Lakshmanan, Elango

    2017-04-01

    Mapping groundwater contaminants and identifying the sources are the initial steps in pollution control and mitigation. Due to the availability of different mapping methods and the large number of emerging pollutants, these methods need to be used together in decision making. The present study aims to map the contaminated areas in Richards Bay, South Africa and compare the results of ordinary kriging (OK) and inverse distance weighted (IDW) interpolation techniques. Statistical methods were also used for identifying contamination sources. Na-Cl groundwater type was dominant followed by Ca-Mg-Cl. Data analysis indicate that silicate weathering, ion exchange and fresh water-seawater mixing are the major geochemical processes controlling the presence of major ions in groundwater. Factor analysis also helped to confirm the results. Overlay analysis by OK and IDW gave different results. Areas where groundwater was unsuitable as a drinking source were 419 and 116 km 2 for OK and IDW, respectively. Such diverse results make decision making difficult, if only one method was to be used. Three highly contaminated zones within the study area were more accurately identified by OK. If large areas are identified as being contaminated such as by IDW in this study, the mitigation measures will be expensive. If these areas were underestimated, then even though management measures are taken, it will not be effective for a longer time. Use of multiple techniques like this study will help to avoid taking harsh decisions. Overall, the groundwater quality in this area was poor, and it is essential to identify alternate drinking water source or treat the groundwater before ingestion.

  11. The Risk-Stratified Osteoporosis Strategy Evaluation study (ROSE)

    DEFF Research Database (Denmark)

    Rubin, Katrine Hass; Holmberg, Teresa; Rothmann, Mette Juel

    2015-01-01

    The risk-stratified osteoporosis strategy evaluation study (ROSE) is a randomized prospective population-based study investigating the effectiveness of a two-step screening program for osteoporosis in women. This paper reports the study design and baseline characteristics of the study population....... 35,000 women aged 65-80 years were selected at random from the population in the Region of Southern Denmark and-before inclusion-randomized to either a screening group or a control group. As first step, a self-administered questionnaire regarding risk factors for osteoporosis based on FRAX......(®) was issued to both groups. As second step, subjects in the screening group with a 10-year probability of major osteoporotic fractures ≥15 % were offered a DXA scan. Patients diagnosed with osteoporosis from the DXA scan were advised to see their GP and discuss pharmaceutical treatment according to Danish...

  12. A Study of KHNP Nuclear Power Plant Technology Level Evaluation

    International Nuclear Information System (INIS)

    Yang, Seung Han; Lee, Sung Jin; Kim, Yo Han

    2016-01-01

    KHNP's 2030 mid and long term plan goal in technology field is securing global No. 1 NPP technology level. Quantifying technology level for this purpose, technology level at present should be surveyed. Technology level of South Korea has been surveyed by KISTEP (Korea Institute of S and T Evaluation and Planning) every two year but the technology level of KHNP has not been surveyed by any organization including KHNP itself. Also the size of technology surveyed by KISTEP was too broad to quantifying technology level of KHNP. In this paper, technology level of KHNP and South Korea are presented. In this study, NPP related technologies were divided into Level I and Level II technologies and conducted a survey for each Level II technologies using Delphi questionnaire survey that is widely used in technology level evaluation. The results of technology level and gap will be used from strategic point of view and also as a reference data for technology improvement planning

  13. Feasibility Study on Nuclear Propulsion Ship according to Economic Evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Gil, Youngmi; Yoo, Seongjin; Oh, June; Byun, Yoonchul; Woo, Ilguk [Daewoo Shipbuilding and Marine Engineering Co., Ltd, Seoul (Korea, Republic of); Kim, Jiho; Choi, Suhn [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2013-05-15

    The use of nuclear ships has been extending to the icebreaker, the deep-water exploration ship, and the floating nuclear power plant. Prior to developing the new ship, the relevant regulations need to be considered. In this study, we reviewed the nuclear ship-related regulations. In addition, economic value is one of the most important factors which should be considered in the pre-design phase. To evaluate the economics of the nuclear ship, we calculated Capital Expenditure (abbreviated as CAPEX) and Operation Expenditure (abbreviated as OPEX) for various types of ships. We reviewed the nuclear ship-related regulations and evaluated the economics of the nuclear ship compared to the diesel ship. The calculation result shows that economic feasibility of the nuclear ship depends on the oil price as well as the cost of the nuclear reactor.

  14. A Study of KHNP Nuclear Power Plant Technology Level Evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Seung Han; Lee, Sung Jin; Kim, Yo Han [KHNP, Daejeon (Korea, Republic of)

    2016-05-15

    KHNP's 2030 mid and long term plan goal in technology field is securing global No. 1 NPP technology level. Quantifying technology level for this purpose, technology level at present should be surveyed. Technology level of South Korea has been surveyed by KISTEP (Korea Institute of S and T Evaluation and Planning) every two year but the technology level of KHNP has not been surveyed by any organization including KHNP itself. Also the size of technology surveyed by KISTEP was too broad to quantifying technology level of KHNP. In this paper, technology level of KHNP and South Korea are presented. In this study, NPP related technologies were divided into Level I and Level II technologies and conducted a survey for each Level II technologies using Delphi questionnaire survey that is widely used in technology level evaluation. The results of technology level and gap will be used from strategic point of view and also as a reference data for technology improvement planning.

  15. Using Geoscience and Geostatistics to Optimize Groundwater Monitoring Networks at the Savannah River Site

    International Nuclear Information System (INIS)

    Tuckfield, R.C.

    2001-01-01

    A team of scientists, engineers, and statisticians was assembled to review the operation efficiency of groundwater monitoring networks at US Department of Energy Savannah River Site (SRS). Subsequent to a feasibility study, this team selected and conducted an analysis of the A/M area groundwater monitoring well network. The purpose was to optimize the number of groundwater wells requisite for monitoring the plumes of the principal constituent of concern, viz., trichloroethylene (TCE). The project gathered technical expertise from the Savannah River Technology Center (SRTC), the Environmental Restoration Division (ERD), and the Environmental Protection Department (EPD) of SRS

  16. The scope of costs in alcohol studies: Cost-of-illness studies differ from economic evaluations

    Directory of Open Access Journals (Sweden)

    Tariq Luqman

    2010-07-01

    Full Text Available Abstract Background Alcohol abuse results in problems on various levels in society. In terms of health, alcohol abuse is not only an important risk factor for chronic disease, but it is also related to injuries. Social harms which can be related to drinking include interpersonal problems, work problems, violent and other crimes. The scope of societal costs related to alcohol abuse in principle should be the same for both economic evaluations and cost-of-illness studies. In general, economic evaluations report a small part of all societal costs. To determine the cost- effectiveness of an intervention it is necessary that all costs and benefits are included. The purpose of this study is to describe and quantify the difference in societal costs incorporated in economic evaluations and cost-of-illness studies on alcohol abuse. Method To investigate the economic costs attributable to alcohol in cost-of-illness studies we used the results of a recent systematic review (June 2009. We performed a PubMed search to identify economic evaluations on alcohol interventions. Only economic evaluations in which two or more interventions were compared from a societal perspective were included. The proportion of health care costs and the proportion of societal costs were estimated in both type of studies. Results The proportion of healthcare costs in cost-of-illness studies was 17% and the proportion of societal costs 83%. In economic evaluations, the proportion of healthcare costs was 57%, and the proportion of societal costs was 43%. Conclusions The costs included in economic evaluations performed from a societal perspective do not correspond with those included in cost-of-illness studies. Economic evaluations on alcohol abuse underr