WorldWideScience

Sample records for modelling spatially distributed

  1. Spatial distribution of emissions to air – the SPREAD model

    DEFF Research Database (Denmark)

    Plejdrup, Marlene Schmidt; Gyldenkærne, Steen

    to the requirements for reporting of gridded emissions to CLRTAP. Spatial emission data is e.g. used as input for air quality modelling, which again serves as input for assessment and evaluation of health effects. For these purposes distributions with higher spatial resolution have been requested. Previously......The National Environmental Research Institute (NERI), Aarhus University, completes the annual national emission inventories for greenhouse gases and air pollutants according to Denmark’s obligations under international conventions, e.g. the climate convention, UNFCCC and the convention on long......-range transboundary air pollution, CLRTAP. NERI has developed a model to distribute emissions from the national emission inventories on a 1x1 km grid covering the Danish land and sea territory. The new spatial high resolution distribution model for emissions to air (SPREAD) has been developed according...

  2. Spatial distribution of emissions to air - the SPREAD model

    Energy Technology Data Exchange (ETDEWEB)

    Plejdrup, M.S.; Gyldenkaerne, S.

    2011-04-15

    The National Environmental Research Institute (NERI), Aarhus University, completes the annual national emission inventories for greenhouse gases and air pollutants according to Denmark's obligations under international conventions, e.g. the climate convention, UNFCCC and the convention on long-range transboundary air pollution, CLRTAP. NERI has developed a model to distribute emissions from the national emission inventories on a 1x1 km grid covering the Danish land and sea territory. The new spatial high resolution distribution model for emissions to air (SPREAD) has been developed according to the requirements for reporting of gridded emissions to CLRTAP. Spatial emission data is e.g. used as input for air quality modelling, which again serves as input for assessment and evaluation of health effects. For these purposes distributions with higher spatial resolution have been requested. Previously, a distribution on the 17x17 km EMEP grid has been set up and used in research projects combined with detailed distributions for a few sectors or sub-sectors e.g. a distribution for emissions from road traffic on 1x1 km resolution. SPREAD is developed to generate improved spatial emission data for e.g. air quality modelling in exposure studies. SPREAD includes emission distributions for each sector in the Danish inventory system; stationary combustion, mobile sources, fugitive emissions from fuels, industrial processes, solvents and other product use, agriculture and waste. This model enables generation of distributions for single sectors and for a number of sub-sectors and single sources as well. This report documents the methodologies in this first version of SPREAD and presents selected results. Further, a number of potential improvements for later versions of SPREAD are addressed and discussed. (Author)

  3. Modelling the Spatial Distribution of Wind Energy Resources in Latvia

    Science.gov (United States)

    Aniskevich, S.; Bezrukovs, V.; Zandovskis, U.; Bezrukovs, D.

    2017-12-01

    The paper studies spatial wind energy flow distribution in Latvia based on wind speed measurements carried out at an altitude of 10 m over a period of two years, from 2015 to 2016. The measurements, with 1 min increments, were carried out using certified measuring instruments installed at 22 observation stations of the Latvian National Hydrometeorological and Climatological Service of the Latvian Environment, Geology and Meteorology Centre (LEGMC). The models of the spatial distribution of averaged wind speed and wind energy density were developed using the method of spatial interpolation based on the historical measurement results and presented in the form of colour contour maps with a 1×1 km resolution. The paper also provides the results of wind speed spatial distribution modelling using a climatological reanalysis ERA5 at the altitudes of 10, 54, 100 and 136 m with a 31×31 km resolution. The analysis includes the comparison of actual wind speed measurement results with the outcomes of ERA5 modelling for meteorological observation stations in Ainazi, Daugavpils, Priekuli, Saldus and Ventspils.

  4. A modal approach to modeling spatially distributed vibration energy dissipation.

    Energy Technology Data Exchange (ETDEWEB)

    Segalman, Daniel Joseph

    2010-08-01

    The nonlinear behavior of mechanical joints is a confounding element in modeling the dynamic response of structures. Though there has been some progress in recent years in modeling individual joints, modeling the full structure with myriad frictional interfaces has remained an obstinate challenge. A strategy is suggested for structural dynamics modeling that can account for the combined effect of interface friction distributed spatially about the structure. This approach accommodates the following observations: (1) At small to modest amplitudes, the nonlinearity of jointed structures is manifest primarily in the energy dissipation - visible as vibration damping; (2) Correspondingly, measured vibration modes do not change significantly with amplitude; and (3) Significant coupling among the modes does not appear to result at modest amplitudes. The mathematical approach presented here postulates the preservation of linear modes and invests all the nonlinearity in the evolution of the modal coordinates. The constitutive form selected is one that works well in modeling spatially discrete joints. When compared against a mathematical truth model, the distributed dissipation approximation performs well.

  5. Scaling precipitation input to spatially distributed hydrological models by measured snow distribution

    Directory of Open Access Journals (Sweden)

    Christian Vögeli

    2016-12-01

    Full Text Available Accurate knowledge on snow distribution in alpine terrain is crucial for various applicationssuch as flood risk assessment, avalanche warning or managing water supply and hydro-power.To simulate the seasonal snow cover development in alpine terrain, the spatially distributed,physics-based model Alpine3D is suitable. The model is typically driven by spatial interpolationsof observations from automatic weather stations (AWS, leading to errors in the spatial distributionof atmospheric forcing. With recent advances in remote sensing techniques, maps of snowdepth can be acquired with high spatial resolution and accuracy. In this work, maps of the snowdepth distribution, calculated from summer and winter digital surface models based on AirborneDigital Sensors (ADS, are used to scale precipitation input data, with the aim to improve theaccuracy of simulation of the spatial distribution of snow with Alpine3D. A simple method toscale and redistribute precipitation is presented and the performance is analysed. The scalingmethod is only applied if it is snowing. For rainfall the precipitation is distributed by interpolation,with a simple air temperature threshold used for the determination of the precipitation phase.It was found that the accuracy of spatial snow distribution could be improved significantly forthe simulated domain. The standard deviation of absolute snow depth error is reduced up toa factor 3.4 to less than 20 cm. The mean absolute error in snow distribution was reducedwhen using representative input sources for the simulation domain. For inter-annual scaling, themodel performance could also be improved, even when using a remote sensing dataset from adifferent winter. In conclusion, using remote sensing data to process precipitation input, complexprocesses such as preferential snow deposition and snow relocation due to wind or avalanches,can be substituted and modelling performance of spatial snow distribution is improved.

  6. FUEL3-D: A Spatially Explicit Fractal Fuel Distribution Model

    Science.gov (United States)

    Russell A. Parsons

    2006-01-01

    Efforts to quantitatively evaluate the effectiveness of fuels treatments are hampered by inconsistencies between the spatial scale at which fuel treatments are implemented and the spatial scale, and detail, with which we model fire and fuel interactions. Central to this scale inconsistency is the resolution at which variability within the fuel bed is considered. Crown...

  7. Modelling the spatial distribution of linear landscape elements in Europe

    NARCIS (Netherlands)

    Zanden, van der E.H.; Verburg, P.H.; Mücher, C.A.

    2013-01-01

    Linear landscape elements, such as ditches, hedgerows, lines of trees and field margins, provide important habitats and ecosystem services and function as ecological infrastructure for species within agricultural landscapes. Spatial maps of the distribution of these elements are needed to better

  8. Working models for spatial distribution and level of Mars' seismicity

    Science.gov (United States)

    Knapmeyer, M.; Oberst, J.; Hauber, E.; Wählisch, M.; Deuchler, C.; Wagner, R.

    2006-11-01

    We present synthetic catalogs of Mars quakes, intended to be used for performance assessments of future seismic networks on the planet. We have compiled a new inventory of compressional and extensional tectonic faults for the planet Mars, comprising 8500 faults with a total length of 680,000 km. The faults were mapped on the basis of Mars Orbiting Laser Altimeter (MOLA) shaded relief. Hence we expect to have assembled a homogeneous data set, not biased by illumination and viewing conditions of image data. Updated models of Martian crater statistics and geological maps were used to assign new maximum ages to all faults. On the basis of the fault catalog, spatial distributions of seismicity were simulated, using assumptions on the available annual seismic moment budget, the moment-frequency relationship, and a relation between rupture length and released moment. We have constructed five different models of Martian seismicity, predicting an annual moment release between 3.42 × 1016 Nm and 4.78 × 1018 Nm and up to 572 events with magnitudes greater than 4 per year as upper limit end-member case. Most events are expected on the Tharsis shield, but minor seismic centers are expected south of Hellas and north of Utopia Planitia.

  9. Distributed multi-criteria model evaluation and spatial association analysis

    Science.gov (United States)

    Scherer, Laura; Pfister, Stephan

    2015-04-01

    Model performance, if evaluated, is often communicated by a single indicator and at an aggregated level; however, it does not embrace the trade-offs between different indicators and the inherent spatial heterogeneity of model efficiency. In this study, we simulated the water balance of the Mississippi watershed using the Soil and Water Assessment Tool (SWAT). The model was calibrated against monthly river discharge at 131 measurement stations. Its time series were bisected to allow for subsequent validation at the same gauges. Furthermore, the model was validated against evapotranspiration which was available as a continuous raster based on remote sensing. The model performance was evaluated for each of the 451 sub-watersheds using four different criteria: 1) Nash-Sutcliffe efficiency (NSE), 2) percent bias (PBIAS), 3) root mean square error (RMSE) normalized to standard deviation (RSR), as well as 4) a combined indicator of the squared correlation coefficient and the linear regression slope (bR2). Conditions that might lead to a poor model performance include aridity, a very flat and steep relief, snowfall and dams, as indicated by previous research. In an attempt to explain spatial differences in model efficiency, the goodness of the model was spatially compared to these four phenomena by means of a bivariate spatial association measure which combines Pearson's correlation coefficient and Moran's index for spatial autocorrelation. In order to assess the model performance of the Mississippi watershed as a whole, three different averages of the sub-watershed results were computed by 1) applying equal weights, 2) weighting by the mean observed river discharge, 3) weighting by the upstream catchment area and the square root of the time series length. Ratings of model performance differed significantly in space and according to efficiency criterion. The model performed much better in the humid Eastern region than in the arid Western region which was confirmed by the

  10. Spatial distribution

    DEFF Research Database (Denmark)

    Borregaard, Michael Krabbe; Hendrichsen, Ditte Katrine; Nachman, Gøsta Støger

    2008-01-01

    populations reflects the location and fragmentation pattern of the habitat types preferred by the species, and the complex dynamics of migration, colonization, and population growth taking place over the landscape. Within these, individuals are distributed among each other in regular or clumped patterns...

  11. From spatial ecology to spatial epidemiology: modeling spatial distributions of different cancer types with principal coordinates of neighbor matrices.

    Science.gov (United States)

    Voutilainen, Ari; Tolppanen, Anna-Maija; Vehviläinen-Julkunen, Katri; Sherwood, Paula R

    2014-01-01

    Epidemiology and ecology share many fundamental research questions. Here we describe how principal coordinates of neighbor matrices (PCNM), a method from spatial ecology, can be applied to spatial epidemiology. PCNM is based on geographical distances among sites and can be applied to any set of sites providing a good coverage of a study area. In the present study, PCNM eigenvectors corresponding to positive autocorrelation were used as explanatory variables in linear regressions to model incidences of eight most common cancer types in Finnish municipalities (n = 320). The dataset was provided by the Finnish Cancer Registry and it included altogether 615,839 cases between 1953 and 2010. PCNM resulted in 165 vectors with a positive eigenvalue. The first PCNM vector corresponded to the wavelength of hundreds of kilometers as it contrasted two main subareas so that municipalities located in southwestern Finland had the highest positive site scores and those located in midwestern Finland had the highest negative scores in that vector. Correspondingly, the 165(th) PCNM vector indicated variation mainly between the two small municipalities located in South Finland. The vectors explained 13 - 58% of the spatial variation in cancer incidences. The number of outliers having standardized residual > |3| was very low, one to six per model, and even lower, zero to two per model, according to Chauvenet's criterion. The spatial variation of prostate cancer was best captured (adjusted r (2) = 0.579). PCNM can act as a complementary method to causal modeling to achieve a better understanding of the spatial structure of both the response and explanatory variables, and to assess the spatial importance of unmeasured explanatory factors. PCNM vectors can be used as proxies for demographics and causative agents to deal with autocorrelation, multicollinearity, and confounding variables. PCNM may help to extend spatial epidemiology to areas with limited availability of

  12. Temporal and spatial distribution characteristics of water resources in Guangdong Province based on a cloud model

    Directory of Open Access Journals (Sweden)

    Qi Zhou

    2015-10-01

    Full Text Available With a focus on the difficulty of quantitatively describing the degree of nonuniformity of temporal and spatial distributions of water resources, quantitative research was carried out on the temporal and spatial distribution characteristics of water resources in Guangdong Province from 1956 to 2000 based on a cloud model. The spatial variation of the temporal distribution characteristics and the temporal variation of the spatial distribution characteristics were both analyzed. In addition, the relationships between the numerical characteristics of the cloud model of temporal and spatial distributions of water resources and precipitation were also studied. The results show that, using a cloud model, it is possible to intuitively describe the temporal and spatial distribution characteristics of water resources in cloud images. Water resources in Guangdong Province and their temporal and spatial distribution characteristics are differentiated by their geographic locations. Downstream and coastal areas have a larger amount of water resources with greater uniformity and stronger stability in terms of temporal distribution. Regions with more precipitation possess larger amounts of water resources, and years with more precipitation show greater nonuniformity in the spatial distribution of water resources. The correlation between the nonuniformity of the temporal distribution and local precipitation is small, and no correlation is found between the stability of the nonuniformity of the temporal and spatial distributions of water resources and precipitation. The amount of water resources in Guangdong Province shows an increasing trend from 1956 to 2000, the nonuniformity of the spatial distribution of water resources declines, and the stability of the nonuniformity of the spatial distribution of water resources is enhanced.

  13. A novel spatial performance metric for robust pattern optimization of distributed hydrological models

    Science.gov (United States)

    Stisen, S.; Demirel, C.; Koch, J.

    2017-12-01

    Evaluation of performance is an integral part of model development and calibration as well as it is of paramount importance when communicating modelling results to stakeholders and the scientific community. There exists a comprehensive and well tested toolbox of metrics to assess temporal model performance in the hydrological modelling community. On the contrary, the experience to evaluate spatial performance is not corresponding to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study aims at making a contribution towards advancing spatial pattern oriented model evaluation for distributed hydrological models. This is achieved by introducing a novel spatial performance metric which provides robust pattern performance during model calibration. The promoted SPAtial EFficiency (spaef) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multi-component approach is necessary in order to adequately compare spatial patterns. spaef, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are tested in a spatial pattern oriented model calibration of a catchment model in Denmark. The calibration is constrained by a remote sensing based spatial pattern of evapotranspiration and discharge timeseries at two stations. Our results stress that stand-alone metrics tend to fail to provide holistic pattern information to the optimizer which underlines the importance of multi-component metrics. The three spaef components are independent which allows them to complement each other in a meaningful way. This study promotes the use of bias insensitive metrics which allow comparing variables which are related but may differ in unit in order to optimally exploit spatial observations made available by remote sensing

  14. Hierarchical spatial models for predicting pygmy rabbit distribution and relative abundance

    Science.gov (United States)

    Wilson, T.L.; Odei, J.B.; Hooten, M.B.; Edwards, T.C.

    2010-01-01

    Conservationists routinely use species distribution models to plan conservation, restoration and development actions, while ecologists use them to infer process from pattern. These models tend to work well for common or easily observable species, but are of limited utility for rare and cryptic species. This may be because honest accounting of known observation bias and spatial autocorrelation are rarely included, thereby limiting statistical inference of resulting distribution maps. We specified and implemented a spatially explicit Bayesian hierarchical model for a cryptic mammal species (pygmy rabbit Brachylagus idahoensis). Our approach used two levels of indirect sign that are naturally hierarchical (burrows and faecal pellets) to build a model that allows for inference on regression coefficients as well as spatially explicit model parameters. We also produced maps of rabbit distribution (occupied burrows) and relative abundance (number of burrows expected to be occupied by pygmy rabbits). The model demonstrated statistically rigorous spatial prediction by including spatial autocorrelation and measurement uncertainty. We demonstrated flexibility of our modelling framework by depicting probabilistic distribution predictions using different assumptions of pygmy rabbit habitat requirements. Spatial representations of the variance of posterior predictive distributions were obtained to evaluate heterogeneity in model fit across the spatial domain. Leave-one-out cross-validation was conducted to evaluate the overall model fit. Synthesis and applications. Our method draws on the strengths of previous work, thereby bridging and extending two active areas of ecological research: species distribution models and multi-state occupancy modelling. Our framework can be extended to encompass both larger extents and other species for which direct estimation of abundance is difficult. ?? 2010 The Authors. Journal compilation ?? 2010 British Ecological Society.

  15. Continuous time modelling of dynamical spatial lattice data observed at sparsely distributed times

    DEFF Research Database (Denmark)

    Rasmussen, Jakob Gulddahl; Møller, Jesper

    2007-01-01

    , and they exhibit spatial interaction. For specificity we consider a particular dynamical spatial lattice data set which has previously been analysed by a discrete time model involving unknown normalizing constants. We discuss the advantages and disadvantages of using continuous time processes compared......Summary. We consider statistical and computational aspects of simulation-based Bayesian inference for a spatial-temporal model based on a multivariate point process which is only observed at sparsely distributed times. The point processes are indexed by the sites of a spatial lattice...

  16. Modelling the distribution of fish accounting for spatial correlation and overdispersion

    DEFF Research Database (Denmark)

    Lewy, Peter; Kristensen, Kasper

    2009-01-01

    The spatial distribution of cod (Gadus morhua) in the North Sea and the Skagerrak was analysed over a 24-year period using the Log Gaussian Cox Process (LGCP). In contrast to other spatial models of the distribution of fish, LGCP avoids problems with zero observations and includes the spatial...... correlation between observations. It is therefore possible to predict and interpolate unobserved densities at any location in the area. This is important for obtaining unbiased estimates of stock concentration and other measures depending on the distribution in the entire area. Results show that the spatial...... correlation and dispersion of cod catches remained unchanged during winter throughout the period, in spite of a drastic decline in stock abundance and a movement of the centre of gravity of the distribution towards the northeast in the same period. For the age groups considered, the concentration of the stock...

  17. Impact of precipitation spatial resolution on the hydrological response of an integrated distributed water resources model

    DEFF Research Database (Denmark)

    Fu, Suhua; Sonnenborg, Torben; Jensen, Karsten Høgh

    2011-01-01

    Precipitation is a key input variable to hydrological models, and the spatial variability of the input is expected to impact the hydrological response predicted by a distributed model. In this study, the effect of spatial resolution of precipitation on runoff , recharge and groundwater head...... was analyzed in the Alergaarde catchment in Denmark. Six different precipitation spatial resolutions were used as inputs to a physically based, distributed hydrological model, the MIKE SHE model. The results showed that the resolution of precipitation input had no apparent effect on annual water balance...... of the total catchment and runoff discharge hydrograph at watershed outlet. On the other hand, groundwater recharge and groundwater head were both aff ected. The impact of the spatial resolution of precipitation input is reduced with increasing catchment size. The effect on stream discharge is relatively low...

  18. A model for the spatial distribution of snow water equivalent parameterized from the spatial variability of precipitation

    Directory of Open Access Journals (Sweden)

    T. Skaugen

    2016-09-01

    Full Text Available Snow is an important and complicated element in hydrological modelling. The traditional catchment hydrological model with its many free calibration parameters, also in snow sub-models, is not a well-suited tool for predicting conditions for which it has not been calibrated. Such conditions include prediction in ungauged basins and assessing hydrological effects of climate change. In this study, a new model for the spatial distribution of snow water equivalent (SWE, parameterized solely from observed spatial variability of precipitation, is compared with the current snow distribution model used in the operational flood forecasting models in Norway. The former model uses a dynamic gamma distribution and is called Snow Distribution_Gamma, (SD_G, whereas the latter model has a fixed, calibrated coefficient of variation, which parameterizes a log-normal model for snow distribution and is called Snow Distribution_Log-Normal (SD_LN. The two models are implemented in the parameter parsimonious rainfall–runoff model Distance Distribution Dynamics (DDD, and their capability for predicting runoff, SWE and snow-covered area (SCA is tested and compared for 71 Norwegian catchments. The calibration period is 1985–2000 and validation period is 2000–2014. Results show that SD_G better simulates SCA when compared with MODIS satellite-derived snow cover. In addition, SWE is simulated more realistically in that seasonal snow is melted out and the building up of "snow towers" and giving spurious positive trends in SWE, typical for SD_LN, is prevented. The precision of runoff simulations using SD_G is slightly inferior, with a reduction in Nash–Sutcliffe and Kling–Gupta efficiency criterion of 0.01, but it is shown that the high precision in runoff prediction using SD_LN is accompanied with erroneous simulations of SWE.

  19. [On selection criteria in spatially distributed models of competition].

    Science.gov (United States)

    Il'ichev, V G; Il'icheva, O A

    2014-01-01

    Discrete models of competitors (initial population and mutants) are considered in which reproduction is set by increasing and concave function, and migration in the space consisting of a set of areas, is described by a Markov matrix. This allows the use of the theory of monotonous operators to study problems of selection, coexistence and stability. It is shown that the higher is the number of areas, more and more severe constraints of selective advantage to initial population are required.

  20. Modelling malaria incidence by an autoregressive distributed lag model with spatial component.

    Science.gov (United States)

    Laguna, Francisco; Grillet, María Eugenia; León, José R; Ludeña, Carenne

    2017-08-01

    The influence of climatic variables on the dynamics of human malaria has been widely highlighted. Also, it is known that this mosquito-borne infection varies in space and time. However, when the data is spatially incomplete most popular spatio-temporal methods of analysis cannot be applied directly. In this paper, we develop a two step methodology to model the spatio-temporal dependence of malaria incidence on local rainfall, temperature, and humidity as well as the regional sea surface temperatures (SST) in the northern coast of Venezuela. First, we fit an autoregressive distributed lag model (ARDL) to the weekly data, and then, we adjust a linear separable spacial vectorial autoregressive model (VAR) to the residuals of the ARDL. Finally, the model parameters are tuned using a Markov Chain Monte Carlo (MCMC) procedure derived from the Metropolis-Hastings algorithm. Our results show that the best model to account for the variations of malaria incidence from 2001 to 2008 in 10 endemic Municipalities in North-Eastern Venezuela is a logit model that included the accumulated local precipitation in combination with the local maximum temperature of the preceding month as positive regressors. Additionally, we show that although malaria dynamics is highly heterogeneous in space, a detailed analysis of the estimated spatial parameters in our model yield important insights regarding the joint behavior of the disease incidence across the different counties in our study. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions

    Science.gov (United States)

    Fenicia, Fabrizio; Kavetski, Dmitri; Savenije, Hubert H. G.; Pfister, Laurent

    2016-02-01

    This paper explores the development and application of distributed hydrological models, focusing on the key decisions of how to discretize the landscape, which model structures to use in each landscape element, and how to link model parameters across multiple landscape elements. The case study considers the Attert catchment in Luxembourg—a 300 km2 mesoscale catchment with 10 nested subcatchments that exhibit clearly different streamflow dynamics. The research questions are investigated using conceptual models applied at hydrologic response unit (HRU) scales (1-4 HRUs) on 6 hourly time steps. Multiple model structures are hypothesized and implemented using the SUPERFLEX framework. Following calibration, space/time model transferability is tested using a split-sample approach, with evaluation criteria including streamflow prediction error metrics and hydrological signatures. Our results suggest that: (1) models using geology-based HRUs are more robust and capture the spatial variability of streamflow time series and signatures better than models using topography-based HRUs; this finding supports the hypothesis that, in the Attert, geology exerts a stronger control than topography on streamflow generation, (2) streamflow dynamics of different HRUs can be represented using distinct and remarkably simple model structures, which can be interpreted in terms of the perceived dominant hydrologic processes in each geology type, and (3) the same maximum root zone storage can be used across the three dominant geological units with no loss in model transferability; this finding suggests that the partitioning of water between streamflow and evaporation in the study area is largely independent of geology and can be used to improve model parsimony. The modeling methodology introduced in this study is general and can be used to advance our broader understanding and prediction of hydrological behavior, including the landscape characteristics that control hydrologic response, the

  2. Evaluating Bayesian spatial methods for modelling species distributions with clumped and restricted occurrence data.

    Directory of Open Access Journals (Sweden)

    David W Redding

    Full Text Available Statistical approaches for inferring the spatial distribution of taxa (Species Distribution Models, SDMs commonly rely on available occurrence data, which is often clumped and geographically restricted. Although available SDM methods address some of these factors, they could be more directly and accurately modelled using a spatially-explicit approach. Software to fit models with spatial autocorrelation parameters in SDMs are now widely available, but whether such approaches for inferring SDMs aid predictions compared to other methodologies is unknown. Here, within a simulated environment using 1000 generated species' ranges, we compared the performance of two commonly used non-spatial SDM methods (Maximum Entropy Modelling, MAXENT and boosted regression trees, BRT, to a spatial Bayesian SDM method (fitted using R-INLA, when the underlying data exhibit varying combinations of clumping and geographic restriction. Finally, we tested how any recommended methodological settings designed to account for spatially non-random patterns in the data impact inference. Spatial Bayesian SDM method was the most consistently accurate method, being in the top 2 most accurate methods in 7 out of 8 data sampling scenarios. Within high-coverage sample datasets, all methods performed fairly similarly. When sampling points were randomly spread, BRT had a 1-3% greater accuracy over the other methods and when samples were clumped, the spatial Bayesian SDM method had a 4%-8% better AUC score. Alternatively, when sampling points were restricted to a small section of the true range all methods were on average 10-12% less accurate, with greater variation among the methods. Model inference under the recommended settings to account for autocorrelation was not impacted by clumping or restriction of data, except for the complexity of the spatial regression term in the spatial Bayesian model. Methods, such as those made available by R-INLA, can be successfully used to account

  3. Assessment of Homodyned K Distribution Modeling Ultrasonic Speckles from Scatterers with Varying Spatial Organizations

    Directory of Open Access Journals (Sweden)

    Xiao Hu

    2017-01-01

    Full Text Available Objective. This paper presents an assessment of physical meanings of parameter and goodness of fit for homodyned K (HK distribution modeling ultrasonic speckles from scatterer distributions with wide-varying spatial organizations. Methods. A set of 3D scatterer phantoms based on gamma distributions is built to be implemented from the clustered to random to uniform scatterer distributions continuously. The model parameters are obtained by maximum likelihood estimation (MLE from statistical histograms of the ultrasonic envelope data and then compared with those by the optimally fitting models chosen from three single distributions. Results show that the parameters of the HK distribution still present their respective physical meanings of independent contributions in the scatterer distributions. Moreover, the HK distribution presents better goodness of fit with a maximum relative MLE difference of 6.23% for random or clustered scatterers with a well-organized periodic structure. Experiments based on ultrasonic envelope data from common carotid arterial B-mode images of human subjects validate the modeling performance of HK distribution. Conclusion. We conclude that the HK model for ultrasonic speckles is a better choice for characterizing tissue with a wide variety of spatial organizations, especially the emphasis on the goodness of fit for the tissue in practical applications.

  4. Modelling the spatial distribution of SO2 and NO(x) emissions in Ireland

    NARCIS (Netherlands)

    Kluizenaar, Y.de; Aherne, J.; Farrell, E.P.

    2001-01-01

    The spatial distributions of sulphur dioxide (SO2) and nitrogen oxides (NO(x)) emissions are essential inputs to models of atmospheric transport and deposition. Information of this type is required for international negotiations on emission reduction through the critical load approach.

  5. Application of the Multitype Strauss Point Model for Characterizing the Spatial Distribution of Landslides

    Directory of Open Access Journals (Sweden)

    Iswar Das

    2016-01-01

    Full Text Available Landslides are common but complex natural hazards. They occur on the Earth’s surface following a mass movement process. This study applies the multitype Strauss point process model to analyze the spatial distributions of small and large landslides along with geoenvironmental covariates. It addresses landslides as a set of irregularly distributed point-type locations within a spatial region. Their intensity and spatial interactions are analyzed by means of the distance correlation functions, model fitting, and simulation. We use as a dataset the landslide occurrences for 28 years from a landslide prone road corridor in the Indian Himalayas. The landslides are investigated for their spatial character, that is, whether they show inhibition or occur as a regular or a clustered point pattern, and for their interaction with landslides in the neighbourhood. Results show that the covariates lithology, land cover, road buffer, drainage density, and terrain units significantly improved model fitting. A comparison of the output made with logistic regression model output showed a superior prediction performance for the multitype Strauss model. We compared results of this model with the multitype/hard core Strauss point process model that further improved the modeling. Results from the study can be used to generate landslide susceptibility scenarios. The paper concludes that a multitype Strauss point process model enriches the set of statistical tools that can comprehensively analyze landslide data.

  6. A Multi-Resolution Spatial Model for Large Datasets Based on the Skew-t Distribution

    KAUST Repository

    Tagle, Felipe

    2017-12-06

    Large, non-Gaussian spatial datasets pose a considerable modeling challenge as the dependence structure implied by the model needs to be captured at different scales, while retaining feasible inference. Skew-normal and skew-t distributions have only recently begun to appear in the spatial statistics literature, without much consideration, however, for the ability to capture dependence at multiple resolutions, and simultaneously achieve feasible inference for increasingly large data sets. This article presents the first multi-resolution spatial model inspired by the skew-t distribution, where a large-scale effect follows a multivariate normal distribution and the fine-scale effects follow a multivariate skew-normal distributions. The resulting marginal distribution for each region is skew-t, thereby allowing for greater flexibility in capturing skewness and heavy tails characterizing many environmental datasets. Likelihood-based inference is performed using a Monte Carlo EM algorithm. The model is applied as a stochastic generator of daily wind speeds over Saudi Arabia.

  7. Applying Spatially Distributed Rainfall to a Hydrological Model in a Tropical Watershed, Manoa Watershed, in Hawaii

    Science.gov (United States)

    Huang, Y. F.; Tsang, Y. P.

    2017-12-01

    Rainfall in Hawaii is characterized with high spatial and temporal variability. In the south side of Oahu, the Manoa watershed, with an area of 11 km2, has the annual maximum rainfall of 3900mm and the minimum rainfall of 1000 mm. Despite this high spatial heterogeneity, the rain gage network seems insufficiently capture this pattern. When simulating stream flow and predicting floods with hydrological models in Hawaii, the model performance is often unsatisfactory because of inadequate representation of rainfall data. Longman et al. (in prep.) have developed the spatially distributed daily rainfall across the Hawaiian Islands by applying ordinary kriging, yet these data have not been applied to hydrological models. In this study, we used the Soil and Water Assessment Tool (SWAT) model to assess the streamflow simulation by applying spatially-distributed rainfall in the Manoa watershed. We first used point daily-rainfall at Lyon Arboretum from National Center of Environmental Information (NCEI) as the uniform rainfall input. Secondly, we summarized sub-watershed mean rainfall from the daily spatial-statistical rainfall. Both rainfall data are available from 1999 to 2014. The SWAT was set up for five-year warm-up, nine-year calibration, and two-year validation. The model parameters were calibrated and validated with four U.S. Geological Survey stream gages. We compared the calibrated watershed parameters, characteristics, and assess the streamflow hydrographs from these two rainfall inputs. The differences and improvement of using spatially distributed rainfall input in SWAT were discussed. In addition to improving the model by the representation of rainfall, this study helped us having a better understanding of the watershed hydrological response in Hawaii.

  8. Calibration of a distributed hydrologic model using observed spatial patterns from MODIS data

    Science.gov (United States)

    Demirel, Mehmet C.; González, Gorka M.; Mai, Juliane; Stisen, Simon

    2016-04-01

    Distributed hydrologic models are typically calibrated against streamflow observations at the outlet of the basin. Along with these observations from gauging stations, satellite based estimates offer independent evaluation data such as remotely sensed actual evapotranspiration (aET) and land surface temperature. The primary objective of the study is to compare model calibrations against traditional downstream discharge measurements with calibrations against simulated spatial patterns and combinations of both types of observations. While the discharge based model calibration typically improves the temporal dynamics of the model, it seems to give rise to minimum improvement of the simulated spatial patterns. In contrast, objective functions specifically targeting the spatial pattern performance could potentially increase the spatial model performance. However, most modeling studies, including the model formulations and parameterization, are not designed to actually change the simulated spatial pattern during calibration. This study investigates the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale hydrologic model (mHM). This model is selected as it allows for a change in the spatial distribution of key soil parameters through the optimization of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) values directly as input. In addition the simulated aET can be estimated at a spatial resolution suitable for comparison to the spatial patterns observed with MODIS data. To increase our control on spatial calibration we introduced three additional parameters to the model. These new parameters are part of an empirical equation to the calculate crop coefficient (Kc) from daily LAI maps and used to update potential evapotranspiration (PET) as model inputs. This is done instead of correcting/updating PET with just a uniform (or aspect driven) factor used in the mHM model

  9. Spatial distribution modelling of the endangered bivalve Pinna nobilis in a Marine Protected Area

    Directory of Open Access Journals (Sweden)

    M. VÁZQUEZ-LUIS

    2014-09-01

    Full Text Available The spatial distribution of Pinna nobilis densities have been analysed through a geostatistical approach in the MPA of Cabrera National Park, Balearic Islands (Spain, Western Mediterranean Sea. Regression kriging was used to model the effect of environmental variables on the density of living individuals of P. nobilis and generate a predictive map of its distribution within the MPA. The environmental variables considered for the model were: depth; slope; habitat type and heterogeneity; wave exposure; and MPA zoning. A total of 378 transects were randomly distributed with a total of 149,000 m2 surveyed at a depth range from 4.2 to 46 m. The recorded P. nobilis densities are among the highest in the Mediterranean Sea. With respect to the prediction model, results indicate that benthic habitats play a key role in the spatial distribution of P. nobilis, with higher densities in seagrass meadows of Posidonia oceanica. The fan mussel population density peaked at 9 m depth, decreasing with depth. Also, decreasing densities are expected with increasing exposure to waves. The predicted map shows some hotspots of density different in size and distributed along the MPA, and provides valuable information for the spatial conservation management of this species.

  10. Modeling of the spatial distribution of ten endangered bird species in jurisdiction of Corantioquia

    International Nuclear Information System (INIS)

    Gomez M, Ana Maria; Alvarez, Esteban

    2006-01-01

    Recently, thanks to advances made in Geographic Information Systems (GIS), techniques have been developed for the construction of models that predict the spatial distribution of species and other attributes of biodiversity. These methods have allowed for the development of objective criteria that are fundamental for making decisions regarding the creation of protected areas systems throughout the world. In this research, the spatial distribution of ten endangered species of birds found within the jurisdiction of CORANTIOQUIA (JDC from here on) was modelled, using GIS techniques. The JDC was divided into 177 squares of 15 x 10 Km and the following variables were quantified within each one: presence or absence of endangered species of birds, rainfall, temperature, sun brightness, relative humidity, day duration, altitude, vegetal cover, slope and primary net productivity. With the help of logistic regression were made predictive models. Based on logistic regressions techniques predictive models were made. These models allow to explain a percentage between 24% and 80% of spatial distribution variability of these species. Those results can help in the identification of valuable zones for the biodiversity conservation. In places where there are neither the time or the economic resources to carry out exhaustive analyses of biodiversity, the models can predict the probable presence of this endangered species

  11. Spatially Explicit Modeling Reveals Cephalopod Distributions Match Contrasting Trophic Pathways in the Western Mediterranean Sea.

    Directory of Open Access Journals (Sweden)

    Patricia Puerta

    Full Text Available Populations of the same species can experience different responses to the environment throughout their distributional range as a result of spatial and temporal heterogeneity in habitat conditions. This highlights the importance of understanding the processes governing species distribution at local scales. However, research on species distribution often averages environmental covariates across large geographic areas, missing variability in population-environment interactions within geographically distinct regions. We used spatially explicit models to identify interactions between species and environmental, including chlorophyll a (Chla and sea surface temperature (SST, and trophic (prey density conditions, along with processes governing the distribution of two cephalopods with contrasting life-histories (octopus and squid across the western Mediterranean Sea. This approach is relevant for cephalopods, since their population dynamics are especially sensitive to variations in habitat conditions and rarely stable in abundance and location. The regional distributions of the two cephalopod species matched two different trophic pathways present in the western Mediterranean Sea, associated with the Gulf of Lion upwelling and the Ebro river discharges respectively. The effects of the studied environmental and trophic conditions were spatially variant in both species, with usually stronger effects along their distributional boundaries. We identify areas where prey availability limited the abundance of cephalopod populations as well as contrasting effects of temperature in the warmest regions. Despite distributional patterns matching productive areas, a general negative effect of Chla on cephalopod densities suggests that competition pressure is common in the study area. Additionally, results highlight the importance of trophic interactions, beyond other common environmental factors, in shaping the distribution of cephalopod populations. Our study presents

  12. Modelling and predicting the spatial distribution of tree root density in heterogeneous forest ecosystems.

    Science.gov (United States)

    Mao, Zhun; Saint-André, Laurent; Bourrier, Franck; Stokes, Alexia; Cordonnier, Thomas

    2015-08-01

    In mountain ecosystems, predicting root density in three dimensions (3-D) is highly challenging due to the spatial heterogeneity of forest communities. This study presents a simple and semi-mechanistic model, named ChaMRoots, that predicts root interception density (RID, number of roots m(-2)). ChaMRoots hypothesizes that RID at a given point is affected by the presence of roots from surrounding trees forming a polygon shape. The model comprises three sub-models for predicting: (1) the spatial heterogeneity - RID of the finest roots in the top soil layer as a function of tree basal area at breast height, and the distance between the tree and a given point; (2) the diameter spectrum - the distribution of RID as a function of root diameter up to 50 mm thick; and (3) the vertical profile - the distribution of RID as a function of soil depth. The RID data used for fitting in the model were measured in two uneven-aged mountain forest ecosystems in the French Alps. These sites differ in tree density and species composition. In general, the validation of each sub-model indicated that all sub-models of ChaMRoots had good fits. The model achieved a highly satisfactory compromise between the number of aerial input parameters and the fit to the observed data. The semi-mechanistic ChaMRoots model focuses on the spatial distribution of root density at the tree cluster scale, in contrast to the majority of published root models, which function at the level of the individual. Based on easy-to-measure characteristics, simple forest inventory protocols and three sub-models, it achieves a good compromise between the complexity of the case study area and that of the global model structure. ChaMRoots can be easily coupled with spatially explicit individual-based forest dynamics models and thus provides a highly transferable approach for modelling 3-D root spatial distribution in complex forest ecosystems. © The Author 2015. Published by Oxford University Press on behalf of the

  13. Analysis of spatial distribution of Tehran Metropolis urban services using models of urban planning

    Directory of Open Access Journals (Sweden)

    A. Lorestani

    2016-04-01

    Full Text Available The process of spatial distribution of urban services in order to provide equitable access to opportunities and reduced regional disparities, and earning the highest citizen satisfaction are among the main challenges facing urban management. This requires knowledge of the current status of spatial distribution of public services in the city, followed by optimal resource allocation under varying circumstances. This analytical-comparative study aimed to investigate the spatial distribution of urban public services, and rank different districts of Tehran in terms of benefiting from public services. To achieve this goal, quantitative models of planning, including factor analysis, composite Human Development Index, taxonomical model and standardization method were used. For the final ranking of districts of Tehran, the sum of numerical value of each district was calculated in four ways. Based on this method, districts 1, 3, 22, 12 and 6 were ranked first to fifth, and districts 13, 10, 8, 17 and 14 were ranked last, respectively. Using cluster analysis model, different districts of Tehran metropolis were clustered on the basis of numerical value of districts in the models used. Based on above-mentioned results, districts 1, 3, 12, 22, 6 and 21, with a final score of 66 and above, included in the first cluster and identified as over-developed districts; and districts 14, 10, 8 and 17, with a final score of 13 or less, included in the fifth cluster and identified as disadvantaged districts.

  14. A watershed scale spatially-distributed model for streambank erosion rate driven by channel curvature

    Science.gov (United States)

    McMillan, Mitchell; Hu, Zhiyong

    2017-10-01

    Streambank erosion is a major source of fluvial sediment, but few large-scale, spatially distributed models exist to quantify streambank erosion rates. We introduce a spatially distributed model for streambank erosion applicable to sinuous, single-thread channels. We argue that such a model can adequately characterize streambank erosion rates, measured at the outsides of bends over a 2-year time period, throughout a large region. The model is based on the widely-used excess-velocity equation and comprised three components: a physics-based hydrodynamic model, a large-scale 1-dimensional model of average monthly discharge, and an empirical bank erodibility parameterization. The hydrodynamic submodel requires inputs of channel centerline, slope, width, depth, friction factor, and a scour factor A; the large-scale watershed submodel utilizes watershed-averaged monthly outputs of the Noah-2.8 land surface model; bank erodibility is based on tree cover and bank height as proxies for root density. The model was calibrated with erosion rates measured in sand-bed streams throughout the northern Gulf of Mexico coastal plain. The calibrated model outperforms a purely empirical model, as well as a model based only on excess velocity, illustrating the utility of combining a physics-based hydrodynamic model with an empirical bank erodibility relationship. The model could be improved by incorporating spatial variability in channel roughness and the hydrodynamic scour factor, which are here assumed constant. A reach-scale application of the model is illustrated on ∼1 km of a medium-sized, mixed forest-pasture stream, where the model identifies streambank erosion hotspots on forested and non-forested bends.

  15. The fractal spatial distribution of pancreatic islets in three dimensions: a self-avoiding growth model

    International Nuclear Information System (INIS)

    Jo, Junghyo; Periwal, Vipul; Hörnblad, Andreas; Ahlgren, Ulf; Kilimnik, German; Hara, Manami

    2013-01-01

    The islets of Langerhans, responsible for controlling blood glucose levels, are dispersed within the pancreas. A universal power law governing the fractal spatial distribution of islets in two-dimensional pancreatic sections has been reported. However, the fractal geometry in the actual three-dimensional pancreas volume, and the developmental process that gives rise to such a self-similar structure, has not been investigated. Here, we examined the three-dimensional spatial distribution of islets in intact mouse pancreata using optical projection tomography and found a power law with a fractal dimension of 2.1. Furthermore, based on two-dimensional pancreatic sections of human autopsies, we found that the distribution of human islets also follows a universal power law with a fractal dimension of 1.5 in adult pancreata, which agrees with the value previously reported in smaller mammalian pancreas sections. Finally, we developed a self-avoiding growth model for the development of the islet distribution and found that the fractal nature of the spatial islet distribution may be associated with the self-avoidance in the branching process of vascularization in the pancreas. (paper)

  16. Fractal spatial distribution of pancreatic islets in three dimensions: a self-avoiding growth model

    Science.gov (United States)

    Jo, Junghyo; Hörnblad, Andreas; Kilimnik, German; Hara, Manami; Ahlgren, Ulf; Periwal, Vipul

    2013-01-01

    The islets of Langerhans, responsible for controlling blood glucose levels, are dispersed within the pancreas. A universal power law governing the fractal spatial distribution of islets in two-dimensional pancreatic sections has been reported. However, the fractal geometry in the actual three-dimensional pancreas volume, and the developmental process that gives rise to such a self-similar structure, have not been investigated. Here, we examined the three-dimensional spatial distribution of islets in intact mouse pancreata using optical projection tomography and found a power law with a fractal dimension, 2.1. Furthermore, based on two-dimensional pancreatic sections of human autopsies, we found that the distribution of human islets also follows a universal power law with fractal dimension 1.5 in adult pancreata, which agrees with the value previously reported in smaller mammalian pancreas sections. Finally, we developed a self-avoiding growth model for the development of the islet distribution and found that the fractal nature of the spatial islet distribution may be associated with the self-avoidance in the branching process of vascularization in the pancreas. PMID:23629025

  17. Habitat modeling for cetacean management: Spatial distribution in the southern Pelagos Sanctuary (Mediterranean Sea)

    Science.gov (United States)

    Pennino, Maria Grazia; Mérigot, Bastien; Fonseca, Vinícius Prado; Monni, Virginia; Rotta, Andrea

    2017-07-01

    Effective management and conservation of wild populations requires knowledge of their habitats, especially by mean of quantitative analyses of their spatial distributions. The Pelagos Sanctuary is a dedicated marine protected area for Mediterranean marine mammals covering an area of 90,000 km2 in the north-western Mediterranean Sea between Italy, France and the Principate of Monaco. In the south of the Sanctuary, i.e. along the Sardinian coast, a range of diverse human activities (cities, industry, fishery, tourism) exerts several current ad potential threats to cetacean populations. In addition, marine mammals are recognized by the EU Marine Strategy Framework Directive as essential components of sustainable ecosystems. Yet, knowledge on the spatial distribution and ecology of cetaceans in this area is quite scarce. Here we modeled occurrence of the three most abundant species known in the Sanctuary, i.e. the striped dolphin (Stenella coeruleoalba), the bottlenose dolphin (Tursiops truncatus) and the fin whales (Balaenoptera physalus), using sighting data from scientific surveys collected from 2012 to 2014 during summer time. Bayesian site-occupancy models were used to model their spatial distribution in relation to habitat taking into account oceanographic (sea surface temperature, primary production, photosynthetically active radiation, chlorophyll-a concentration) and topographic (depth, slope, distance of the land) variables. Cetaceans responded differently to the habitat features, with higher occurrence predicted in the more productive areas on submarine canyons. These results provide ecological information useful to enhance management plans and establish baseline for future population trend studies.

  18. Review and possible development direction of the methods for modeling of soil pollutants spatial distribution

    Science.gov (United States)

    Tarasov, D. A.; Medvedev, A. N.; Sergeev, A. P.; Buevich, A. G.

    2017-07-01

    Forecasting of environmental pollutants spatial distribution is a significant field of research in view of the current concerns regarding environment all over the world. Due to the danger to health and environment associated with an increase in pollution of air, soil, water and biosphere, it is very important to have the models that are capable to describe the modern distribution of contaminants and to forecast the dynamic of their spreading in future at different territories. This article addresses the methods, which applied the most often in this field, with an accent on soil pollution. The possible direction of such methods further development is suggested.

  19. Modeling the isotopic evolution of snowpack and snowmelt: Testing a spatially distributed parsimonious approach.

    Science.gov (United States)

    Ala-Aho, Pertti; Tetzlaff, Doerthe; McNamara, James P; Laudon, Hjalmar; Kormos, Patrick; Soulsby, Chris

    2017-07-01

    Use of stable water isotopes has become increasingly popular in quantifying water flow paths and travel times in hydrological systems using tracer-aided modeling. In snow-influenced catchments, snowmelt produces a traceable isotopic signal, which differs from original snowfall isotopic composition because of isotopic fractionation in the snowpack. These fractionation processes in snow are relatively well understood, but representing their spatiotemporal variability in tracer-aided studies remains a challenge. We present a novel, parsimonious modeling method to account for the snowpack isotope fractionation and estimate isotope ratios in snowmelt water in a fully spatially distributed manner. Our model introduces two calibration parameters that alone account for the isotopic fractionation caused by sublimation from interception and ground snow storage, and snowmelt fractionation progressively enriching the snowmelt runoff. The isotope routines are linked to a generic process-based snow interception-accumulation-melt model facilitating simulation of spatially distributed snowmelt runoff. We use a synthetic modeling experiment to demonstrate the functionality of the model algorithms in different landscape locations and under different canopy characteristics. We also provide a proof-of-concept model test and successfully reproduce isotopic ratios in snowmelt runoff sampled with snowmelt lysimeters in two long-term experimental catchment with contrasting winter conditions. To our knowledge, the method is the first such tool to allow estimation of the spatially distributed nature of isotopic fractionation in snowpacks and the resulting isotope ratios in snowmelt runoff. The method can thus provide a useful tool for tracer-aided modeling to better understand the integrated nature of flow, mixing, and transport processes in snow-influenced catchments.

  20. TREX: Spatially distributed model to assess watershed contaminant transport and fate

    International Nuclear Information System (INIS)

    Velleux, Mark L.; England, John F.; Julien, Pierre Y.

    2008-01-01

    Contaminant releases from upland areas can have adverse water quality and stream ecology impacts. TREX (Two-dimensional, Runoff, Erosion, and Export) is a spatially distributed, physically-based model to simulate chemical transport and fate at the watershed scale. TREX combines surface hydrology and sediment transport features from the CASC2D watershed model with chemical transport features from the WASP/IPX series of water quality models. In addition to surface runoff and sediment transport, TREX simulates: (1) chemical erosion, advection, and deposition; (2) chemical partitioning and phase distribution; and (3) chemical infiltration and redistribution. Floodplain interactions for water, sediment, and chemicals are also simulated. To demonstrate the potential for using TREX to simulate chemical transport at the watershed scale, a screening-level application was developed for the California Gulch watershed mine-waste site in Colorado. Runoff, sediment transport, and metals (Cu, Cd, Zn) transport were simulated for a calibration event and a validation event. The model reproduced measured peak flows, and times to peak at the watershed outlet and three internal locations. Simulated flow volumes were within approximately 10% of measured conditions. Model results were also generally within measured ranges of total suspended solid and metal concentrations. TREX is an appropriate tool for investigating multimedia environmental problems that involve water, soils, and chemical interactions in a spatially distributed manner within a watershed

  1. A spatially distributed model for assessment of the effects of changing land use and climate on urban stream quality: Development of a Spatially Distributed Urban Water Quality Model

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Ning [Department of Civil and Environmental Engineering, University of Washington, Seattle WA USA; Pacific Northwest National Laboratory, Richland WA USA; Yearsley, John [Department of Civil and Environmental Engineering, University of Washington, Seattle WA USA; Baptiste, Marisa [Department of Civil and Environmental Engineering, University of Washington, Seattle WA USA; Cao, Qian [Department of Geography, University of California Los Angeles, Los Angeles CA USA; Lettenmaier, Dennis P. [Department of Geography, University of California Los Angeles, Los Angeles CA USA; Nijssen, Bart [Department of Civil and Environmental Engineering, University of Washington, Seattle WA USA

    2016-08-22

    While the effects of land use change in urban areas have been widely examined, the combined effects of climate and land use change on the quality of urban and urbanizing streams have received much less attention. We describe a modeling framework that is applicable to the evaluation of potential changes in urban water quality and associated hydrologic changes in response to ongoing climate and landscape alteration. The grid-based spatially distributed model, DHSVM-WQ, is an outgrowth of the Distributed Hydrology-Soil-Vegetation Model (DHSVM) that incorporates modules for assessing hydrology and water quality in urbanized watersheds at a high spatial and temporal resolution. DHSVM-WQ simulates surface runoff quality and in-stream processes that control the transport of nonpoint-source (NPS) pollutants into urban streams. We configure DHSVM-WQ for three partially urbanized catchments in the Puget Sound region to evaluate the water quality responses to current conditions and projected changes in climate and/or land use over the next century. Here we focus on total suspended solids (TSS) and total phosphorus (TP) from nonpoint sources (runoff), as well as stream temperature. The projection of future land use is characterized by a combination of densification in existing urban or partially urban areas, and expansion of the urban footprint. The climate change scenarios consist of individual and concurrent changes in temperature and precipitation. Future precipitation is projected to increase in winter and decrease in summer, while future temperature is projected to increase throughout the year. Our results show that urbanization has a much greater effect than climate change on both the magnitude and seasonal variability of streamflow, TSS and TP loads largely due to substantially increased streamflow, and particularly winter flow peaks. Water temperature is more sensitive to climate warming scenarios than to urbanization and precipitation changes. Future urbanization and

  2. Modeling the spatial distribution of African buffalo (Syncerus caffer in the Kruger National Park, South Africa.

    Directory of Open Access Journals (Sweden)

    Kristen Hughes

    Full Text Available The population density of wildlife reservoirs contributes to disease transmission risk for domestic animals. The objective of this study was to model the African buffalo distribution of the Kruger National Park. A secondary objective was to collect field data to evaluate models and determine environmental predictors of buffalo detection. Spatial distribution models were created using buffalo census information and archived data from previous research. Field data were collected during the dry (August 2012 and wet (January 2013 seasons using a random walk design. The fit of the prediction models were assessed descriptively and formally by calculating the root mean square error (rMSE of deviations from field observations. Logistic regression was used to estimate the effects of environmental variables on the detection of buffalo herds and linear regression was used to identify predictors of larger herd sizes. A zero-inflated Poisson model produced distributions that were most consistent with expected buffalo behavior. Field data confirmed that environmental factors including season (P = 0.008, vegetation type (P = 0.002, and vegetation density (P = 0.010 were significant predictors of buffalo detection. Bachelor herds were more likely to be detected in dense vegetation (P = 0.005 and during the wet season (P = 0.022 compared to the larger mixed-sex herds. Static distribution models for African buffalo can produce biologically reasonable results but environmental factors have significant effects and therefore could be used to improve model performance. Accurate distribution models are critical for the evaluation of disease risk and to model disease transmission.

  3. Modeling the spatial distribution of African buffalo (Syncerus caffer) in the Kruger National Park, South Africa

    Science.gov (United States)

    Hughes, Kristen; Budke, Christine M.; Ward, Michael P.; Kerry, Ruth; Ingram, Ben

    2017-01-01

    The population density of wildlife reservoirs contributes to disease transmission risk for domestic animals. The objective of this study was to model the African buffalo distribution of the Kruger National Park. A secondary objective was to collect field data to evaluate models and determine environmental predictors of buffalo detection. Spatial distribution models were created using buffalo census information and archived data from previous research. Field data were collected during the dry (August 2012) and wet (January 2013) seasons using a random walk design. The fit of the prediction models were assessed descriptively and formally by calculating the root mean square error (rMSE) of deviations from field observations. Logistic regression was used to estimate the effects of environmental variables on the detection of buffalo herds and linear regression was used to identify predictors of larger herd sizes. A zero-inflated Poisson model produced distributions that were most consistent with expected buffalo behavior. Field data confirmed that environmental factors including season (P = 0.008), vegetation type (P = 0.002), and vegetation density (P = 0.010) were significant predictors of buffalo detection. Bachelor herds were more likely to be detected in dense vegetation (P = 0.005) and during the wet season (P = 0.022) compared to the larger mixed-sex herds. Static distribution models for African buffalo can produce biologically reasonable results but environmental factors have significant effects and therefore could be used to improve model performance. Accurate distribution models are critical for the evaluation of disease risk and to model disease transmission. PMID:28902858

  4. Preliminary model constraints on the spatial and luminosity distributions of GRBs observed by BATSE. [Gamma Ray Bursts

    Science.gov (United States)

    Hakkila, Jon; Meegan, Charles A.

    1992-01-01

    The GRB angular/intensity distributions observed by BATSE greatly constrain models of the spatial and luminosity source distributions. Single populations of Galactic Disk and Galactic Halo sources appear to be untenable, and only a limited subset of models made up of sources in a symmetric Galactic Corona satisfy the observations. Comments are made on other classes of models.

  5. Spatial autocorrelation in predictors reduces the impact of positional uncertainty in occurrence data on species distribution modelling

    NARCIS (Netherlands)

    Naimi, B.; Skidmore, A.K.; Groen, T.A.; Hamm, N.A.S.

    2011-01-01

    Aim To investigate the impact of positional uncertainty in species occurrences on the predictions of seven commonly used species distribution models (SDMs), and explore its interaction with spatial autocorrelation in predictors. Methods A series of artificial datasets covering 155 scenarios

  6. Spatial distribution of mineral dust single scattering albedo based on DREAM model

    Science.gov (United States)

    Kuzmanoski, Maja; Ničković, Slobodan; Ilić, Luka

    2016-04-01

    Mineral dust comprises a significant part of global aerosol burden. There is a large uncertainty in estimating role of dust in Earth's climate system, partly due to poor characterization of its optical properties. Single scattering albedo is one of key optical properties determining radiative effects of dust particles. While it depends on dust particle sizes, it is also strongly influenced by dust mineral composition, particularly the content of light-absorbing iron oxides and the mixing state (external or internal). However, an assumption of uniform dust composition is typically used in models. To better represent single scattering albedo in dust atmospheric models, required to increase accuracy of dust radiative effect estimates, it is necessary to include information on particle mineral content. In this study, we present the spatial distribution of dust single scattering albedo based on the Dust Regional Atmospheric Model (DREAM) with incorporated particle mineral composition. The domain of the model covers Northern Africa, Middle East and the European continent, with horizontal resolution set to 1/5°. It uses eight particle size bins within the 0.1-10 μm radius range. Focusing on dust episode of June 2010, we analyze dust single scattering albedo spatial distribution over the model domain, based on particle sizes and mineral composition from model output; we discuss changes in this optical property after long-range transport. Furthermore, we examine how the AERONET-derived aerosol properties respond to dust mineralogy. Finally we use AERONET data to evaluate model-based single scattering albedo. Acknowledgement We would like to thank the AERONET network and the principal investigators, as well as their staff, for establishing and maintaining the AERONET sites used in this work.

  7. Spatially distributed environmental fate modelling of terbuthylazine in a mesoscale agricultural catchment using passive sampler data

    Science.gov (United States)

    Gassmann, Matthias; Farlin, Julien; Gallé, Tom

    2017-04-01

    Agricultural application of herbicides often leads to significant herbicide losses to receiving rivers. The impact of agricultural practices on water pollution can be assessed by process-based reactive transport modelling using catchment scale models. Prior to investigations of management practices, these models have to be calibrated using sampling data. However, most previous studies only used concentrations at the catchment outlet for model calibration and validation. Thus, even if the applied model is spatially distributed, predicted spatial differences of pesticide loss cannot be directly compared to observations. In this study, we applied the spatially distributed reactive transport model Zin-AgriTra in the mesoscale (78 km2) catchment of the Wark River in Luxembourg in order to simulate concentrations of terbuthylazine in river water. In contrast to former studies, we used six sampling points, equipped with passive samplers, for pesticide model validation. Three samplers were located in the main channel of the river and three in smaller tributaries. At each sampling point, event mean concentration of six events from May to July 2011 were calculated by subtraction of baseflow-mass from total collected mass assuming time-proportional uptake by passive samplers. Continuous discharge measurements and high-resolution autosampling during events allowed for accurate load calculations at the outlet. Detailed information about maize cultivation in the catchment and nation-wide terbuthylazine application statistics (341 g/ha in the 3rd week of May) were used for a definition of the pesticide input function of the model. The hydrological model was manually calibrated to fit baseflow and spring/summer events. Substance fluxes were calibrated using a Latin Hypercube of physico-chemical substance characteristics as provided by the literature: surface soil half-lives of 10-35 d, Freundlich KOC of 150-330 ml/g, Freundlich n of 0.9 - 1 and adsorption/desorption kinetics of 20

  8. Modeling the spatial distribution of the parameters of the coolant in the reactor volume

    International Nuclear Information System (INIS)

    Nikonov, S.P.

    2011-01-01

    In this paper the approach to the question about the spatial distribution of the parameters of the coolant in-reactor volume. To describe the in-core space is used specially developed preprocessor. When the work of the preprocessor in the first place, is recreated on the basis of available information (mostly-the original drawings) with high accuracy three-dimensional description of the structures of the reactor volume and, secondly, are prepared on this basis blocks input to the nodal system code improved estimate ATHLET, allows to take into account the hydrodynamic interaction between the spatial control volumes. As an example the special case of solutions of international standard problem on the reconstruction of the transition process in the third unit of the Kalinin nuclear power plant, due to the shutdown of one of the four Main Coolant Pumps in operation at the rated capacity (first download). Model-core area consists of approximately 58 000 control volumes and spatial relationships. It shows the influence of certain structural units of the core to the distribution of the mass floe rate of its height. It is detected a strong cross-flow coolant in the area over the baffle. Moreover, we study the distribution of the coolant temperature at the assembly head of WWER-1000 reactor. It is shown that in the region of the top of the assembly head, where we have installation of thermocouples, the flow coolant for internal assemblies core is formed by only from guide channel Reactor control and protected system Control rod flow, or a mixture of the guide channel flow and flow from the area in front of top grid head assembly (the peripheral assemblies). It is shown that the magnitude of the flow guide channels affects not only the position of control rods, but also the presence of a particular type of measuring channels (Self powered neutron detector sensors or Temperature control sensors) in the cassette. (Author)

  9. Comparison of spatially and temporally distributed recharge simulated using coupled and decoupled watershed hydrology models

    Science.gov (United States)

    Hevesi, J. A.; Woolfenden, L. R.; Niswonger, R. G.; Nishikawa, T.

    2011-12-01

    Estimation of the temporal and spatial distribution of watershed-scale recharge is often required for the development of transient groundwater-flow models and for quantifying water budgets. The temporal distribution of recharge has often been empirically estimated by scaling precipitation distributions. For larger watersheds, however, temporal change in the spatial distribution of recharge is affected by spatial and temporal variability in precipitation and air temperature, combined with the effects of heterogeneity in the physical characteristics of the watershed; these factors make it difficult to represent transient recharge using empirical scaling methods. Precipitation-runoff models, calibrated to available streamflow records, have been used to simulate the changing distribution and magnitude of recharge, but the uncertainty in simulated recharge estimates usually is high due to the uncertainty in input data and other components of the water balance. In this study, GSFLOW, an integrated hydrologic model, was used to evaluate differences in simulated water balances and the magnitude and distribution of transient recharge using decoupled and coupled simulations of surface-water and groundwater flow in the Santa Rosa Plain watershed (SRPW), California, USA. GSFLOW is an integration of the precipitation-runoff model PRMS and the groundwater flow model MODFLOW. GSFLOW was run as a decoupled (PRMS-only) precipitation-runoff model, independent of the MODFLOW, to develop a preliminary ensemble of estimated water balances and recharge simulations. The ensemble consisted of a set of 60-year (water years 1950 through 2010) daily simulation results, all of which provided satisfactory calibration results to available daily streamflow records at 12 gaging sites within the SRPW. The PRMs parameter files developed for the calibrated PRMS-only simulations were used as input for the coupled GSFLOW simulations that were calibrated to available well hydrographs for water years

  10. Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

    Directory of Open Access Journals (Sweden)

    M. C. Demirel

    2018-02-01

    Full Text Available Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the

  11. Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

    Science.gov (United States)

    Demirel, Mehmet C.; Mai, Juliane; Mendiguren, Gorka; Koch, Julian; Samaniego, Luis; Stisen, Simon

    2018-02-01

    Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM) is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the shuffled complex

  12. A Spatially Distributed Conceptual Model for Estimating Suspended Sediment Yield in Alpine catchments

    Science.gov (United States)

    Costa, Anna; Molnar, Peter; Anghileri, Daniela

    2017-04-01

    Suspended sediment is associated with nutrient and contaminant transport in water courses. Estimating suspended sediment load is relevant for water-quality assessment, recreational activities, reservoir sedimentation issues, and ecological habitat assessment. Suspended sediment concentration (SSC) along channels is usually reproduced by suspended sediment rating curves, which relate SSC to discharge with a power law equation. Large uncertainty characterizes rating curves based only on discharge, because sediment supply is not explicitly accounted for. The aim of this work is to develop a source-oriented formulation of suspended sediment dynamics and to estimate suspended sediment yield at the outlet of a large Alpine catchment (upper Rhône basin, Switzerland). We propose a novel modelling approach for suspended sediment which accounts for sediment supply by taking into account the variety of sediment sources in an Alpine environment, i.e. the spatial location of sediment sources (e.g. distance from the outlet and lithology) and the different processes of sediment production and transport (e.g. by rainfall, overland flow, snowmelt). Four main sediment sources, typical of Alpine environments, are included in our model: glacial erosion, hillslope erosion, channel erosion and erosion by mass wasting processes. The predictive model is based on gridded datasets of precipitation and air temperature which drive spatially distributed degree-day models to simulate snowmelt and ice-melt, and determine erosive rainfall. A mass balance at the grid scale determines daily runoff. Each cell belongs to a different sediment source (e.g. hillslope, channel, glacier cell). The amount of sediment entrained and transported in suspension is simulated through non-linear functions of runoff, specific for sediment production and transport processes occurring at the grid scale (e.g. rainfall erosion, snowmelt-driven overland flow). Erodibility factors identify different lithological units

  13. Resolving structural errors in a spatially distributed hydrologic model using ensemble Kalman filter state updates

    Directory of Open Access Journals (Sweden)

    J. H. Spaaks

    2013-09-01

    Full Text Available In hydrological modeling, model structures are developed in an iterative cycle as more and different types of measurements become available and our understanding of the hillslope or watershed improves. However, with increasing complexity of the model, it becomes more and more difficult to detect which parts of the model are deficient, or which processes should also be incorporated into the model during the next development step. In this study, we first compare two methods (the Shuffled Complex Evolution Metropolis algorithm (SCEM-UA and the Simultaneous parameter Optimization and Data Assimilation algorithm (SODA to calibrate a purposely deficient 3-D hillslope-scale model to error-free, artificially generated measurements. We use a multi-objective approach based on distributed pressure head at the soil–bedrock interface and hillslope-scale discharge and water balance. For these idealized circumstances, SODA's usefulness as a diagnostic methodology is demonstrated by its ability to identify the timing and location of processes that are missing in the model. We show that SODA's state updates provide information that could readily be incorporated into an improved model structure, and that this type of information cannot be gained from parameter estimation methods such as SCEM-UA. We then expand on the SODA result by performing yet another calibration, in which we investigate whether SODA's state updating patterns are still capable of providing insight into model structure deficiencies when there are fewer measurements, which are moreover subject to measurement noise. We conclude that SODA can help guide the discussion between experimentalists and modelers by providing accurate and detailed information on how to improve spatially distributed hydrologic models.

  14. Use of spatially distributed time-integrated sediment sampling networks and distributed fine sediment modelling to inform catchment management.

    Science.gov (United States)

    Perks, M T; Warburton, J; Bracken, L J; Reaney, S M; Emery, S B; Hirst, S

    2017-11-01

    Under the EU Water Framework Directive, suspended sediment is omitted from environmental quality standards and compliance targets. This omission is partly explained by difficulties in assessing the complex dose-response of ecological communities. But equally, it is hindered by a lack of spatially distributed estimates of suspended sediment variability across catchments. In this paper, we demonstrate the inability of traditional, discrete sampling campaigns for assessing exposure to fine sediment. Sampling frequencies based on Environmental Quality Standard protocols, whilst reflecting typical manual sampling constraints, are unable to determine the magnitude of sediment exposure with an acceptable level of precision. Deviations from actual concentrations range between -35 and +20% based on the interquartile range of simulations. As an alternative, we assess the value of low-cost, suspended sediment sampling networks for quantifying suspended sediment transfer (SST). In this study of the 362 km 2 upland Esk catchment we observe that spatial patterns of sediment flux are consistent over the two year monitoring period across a network of 17 monitoring sites. This enables the key contributing sub-catchments of Butter Beck (SST: 1141 t km 2 yr -1 ) and Glaisdale Beck (SST: 841 t km 2 yr -1 ) to be identified. The time-integrated samplers offer a feasible alternative to traditional infrequent and discrete sampling approaches for assessing spatio-temporal changes in contamination. In conjunction with a spatially distributed diffuse pollution model (SCIMAP), time-integrated sediment sampling is an effective means of identifying critical sediment source areas in the catchment, which can better inform sediment management strategies for pollution prevention and control. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Spatial Distribution of Fate and Transport Parameters Using Cxtfit in a Karstified Limestone Model

    Science.gov (United States)

    Toro, J.; Padilla, I. Y.

    2017-12-01

    Karst environments have a high capacity to transport and store large amounts of water. This makes karst aquifers a productive resource for human consumption and ecological integrity, but also makes them vulnerable to potential contamination of hazardous chemical substances. High heterogeneity and anisotropy of karst aquifer properties make them very difficult to characterize for accurate prediction of contaminant mobility and persistence in groundwater. Current technologies to characterize and quantify flow and transport processes at field-scale is limited by low resolution of spatiotemporal data. To enhance this resolution and provide the essential knowledge of karst groundwater systems, studies at laboratory scale can be conducted. This work uses an intermediate karstified lab-scale physical model (IKLPM) to study fate and transport processes and assess viable tools to characterize heterogeneities in karst systems. Transport experiments are conducted in the IKLPM using step injections of calcium chloride, uranine, and rhodamine wt tracers. Temporal concentration distributions (TCDs) obtained from the experiments are analyzed using the method of moments and CXTFIT to quantify fate and transport parameters in the system at various flow rates. The spatial distribution of the estimated fate and transport parameters for the tracers revealed high variability related to preferential flow heterogeneities and scale dependence. Results are integrated to define spatially-variable transport regions within the system and assess their fate and transport characteristics.

  16. Predicting Spatial Distribution of Key Honeybee Pests in Kenya Using Remotely Sensed and Bioclimatic Variables: Key Honeybee Pests Distribution Models

    Directory of Open Access Journals (Sweden)

    David M. Makori

    2017-02-01

    Full Text Available Bee keeping is indispensable to global food production. It is an alternate income source, especially in rural underdeveloped African settlements, and an important forest conservation incentive. However, dwindling honeybee colonies around the world are attributed to pests and diseases whose spatial distribution and influences are not well established. In this study, we used remotely sensed data to improve the reliability of pest ecological niche (EN models to attain reliable pest distribution maps. Occurrence data on four pests (Aethina tumida, Galleria mellonella, Oplostomus haroldi and Varroa destructor were collected from apiaries within four main agro-ecological regions responsible for over 80% of Kenya’s bee keeping. Africlim bioclimatic and derived normalized difference vegetation index (NDVI variables were used to model their ecological niches using Maximum Entropy (MaxEnt. Combined precipitation variables had a high positive logit influence on all remotely sensed and biotic models’ performance. Remotely sensed vegetation variables had a substantial effect on the model, contributing up to 40.8% for G. mellonella and regions with high rainfall seasonality were predicted to be high-risk areas. Projections (to 2055 indicated that, with the current climate change trend, these regions will experience increased honeybee pest risk. We conclude that honeybee pests could be modelled using bioclimatic data and remotely sensed variables in MaxEnt. Although the bioclimatic data were most relevant in all model results, incorporating vegetation seasonality variables to improve mapping the ‘actual’ habitat of key honeybee pests and to identify risk and containment zones needs to be further investigated.

  17. Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

    DEFF Research Database (Denmark)

    Demirel, Mehmet C.; Mai, Juliane; Mendiguren Gonzalez, Gorka

    2018-01-01

    selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient...

  18. Modeling the effect of urban infrastructure on hydrologic processes within i-Tree Hydro, a statistically and spatially distributed model

    Science.gov (United States)

    Taggart, T. P.; Endreny, T. A.; Nowak, D.

    2014-12-01

    Gray and green infrastructure in urban environments alters many natural hydrologic processes, creating an urban water balance unique to the developed environment. A common way to assess the consequences of impervious cover and grey infrastructure is by measuring runoff hydrographs. This focus on the watershed outlet masks the spatial variation of hydrologic process alterations across the urban environment in response to localized landscape characteristics. We attempt to represent this spatial variation in the urban environment using the statistically and spatially distributed i-Tree Hydro model, a scoping level urban forest effects water balance model. i-Tree Hydro has undergone expansion and modification to include the effect of green infrastructure processes, road network attributes, and urban pipe system leakages. These additions to the model are intended to increase the understanding of the altered urban hydrologic cycle by examining the effects of the location of these structures on the water balance. Specifically, the effect of these additional structures and functions on the spatially varying properties of interception, soil moisture and runoff generation. Differences in predicted properties and optimized parameter sets between the two models are examined and related to the recent landscape modifications. Datasets used in this study consist of watersheds and sewersheds within the Syracuse, NY metropolitan area, an urban area that has integrated green and gray infrastructure practices to alleviate stormwater problems.

  19. Using a spatially-distributed hydrologic biogeochemistry model with nitrogen transport to study the spatial variation of carbon stocks and fluxes in a Critical Zone Observatory

    Science.gov (United States)

    Shi, Y.; Eissenstat, D. M.; He, Y.; Davis, K. J.

    2017-12-01

    Most current biogeochemical models are 1-D and represent one point in space. Therefore, they cannot resolve topographically driven land surface heterogeneity (e.g., lateral water flow, soil moisture, soil temperature, solar radiation) or the spatial pattern of nutrient availability. A spatially distributed forest biogeochemical model with nitrogen transport, Flux-PIHM-BGC, has been developed by coupling a 1-D mechanistic biogeochemical model Biome-BGC (BBGC) with a spatially distributed land surface hydrologic model, Flux-PIHM, and adding an advection dominated nitrogen transport module. Flux-PIHM is a coupled physically based model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model, and is augmented by adding a topographic solar radiation module. Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as land surface heterogeneities caused by topography. In the coupled Flux-PIHM-BGC model, each Flux-PIHM model grid couples a 1-D BBGC model, while nitrogen is transported among model grids via surface and subsurface water flow. In each grid, Flux-PIHM provides BBGC with soil moisture, soil temperature, and solar radiation, while BBGC provides Flux-PIHM with spatially-distributed leaf area index. The coupled Flux-PIHM-BGC model has been implemented at the Susquehanna/Shale Hills Critical Zone Observatory. The model-predicted aboveground vegetation carbon and soil carbon distributions generally agree with the macro patterns observed within the watershed. The importance of abiotic variables (including soil moisture, soil temperature, solar radiation, and soil mineral nitrogen) in predicting aboveground carbon distribution is calculated using a random forest. The result suggests that the spatial pattern of aboveground carbon is controlled by the distribution of soil mineral nitrogen. A Flux-PIHM-BGC simulation

  20. Predicting habitat suitability for rare plants at local spatial scales using a species distribution model.

    Science.gov (United States)

    Gogol-Prokurat, Melanie

    2011-01-01

    If species distribution models (SDMs) can rank habitat suitability at a local scale, they may be a valuable conservation planning tool for rare, patchily distributed species. This study assessed the ability of Maxent, an SDM reported to be appropriate for modeling rare species, to rank habitat suitability at a local scale for four edaphic endemic rare plants of gabbroic soils in El Dorado County, California, and examined the effects of grain size, spatial extent, and fine-grain environmental predictors on local-scale model accuracy. Models were developed using species occurrence data mapped on public lands and were evaluated using an independent data set of presence and absence locations on surrounding lands, mimicking a typical conservation-planning scenario that prioritizes potential habitat on unsurveyed lands surrounding known occurrences. Maxent produced models that were successful at discriminating between suitable and unsuitable habitat at the local scale for all four species, and predicted habitat suitability values were proportional to likelihood of occurrence or population abundance for three of four species. Unfortunately, models with the best discrimination (i.e., AUC) were not always the most useful for ranking habitat suitability. The use of independent test data showed metrics that were valuable for evaluating which variables and model choices (e.g., grain, extent) to use in guiding habitat prioritization for conservation of these species. A goodness-of-fit test was used to determine whether habitat suitability values ranked habitat suitability on a continuous scale. If they did not, a minimum acceptable error predicted area criterion was used to determine the threshold for classifying habitat as suitable or unsuitable. I found a trade-off between model extent and the use of fine-grain environmental variables: goodness of fit was improved at larger extents, and fine-grain environmental variables improved local-scale accuracy, but fine-grain variables

  1. Effect of head model on Monte Carlo modeling of spatial sensitivity distribution for functional near-infrared spectroscopy

    Directory of Open Access Journals (Sweden)

    Ting Li

    2015-09-01

    Full Text Available Modeling Light propagation within human head to deduce spatial sensitivity distribution (SSD is important for Near-infrared spectroscopy (NIRS/imaging (NIRI and diffuse correlation tomography. Lots of head models have been used on this issue, including layered head model, artificial simplified head model, MRI slices described head model, and visible human head model. Hereinto, visible Chinese human (VCH head model is considered to be a most faithful presentation of anatomical structure, and has been highlighted to be employed in modeling light propagation. However, it is not practical for all researchers to use VCH head models and actually increasing number of people are using magnet resonance imaging (MRI head models. Here, all the above head models were simulated and compared, and we focused on the effect of using different head models on predictions of SSD. Our results were in line with the previous reports on the effect of cerebral cortex folding geometry. Moreover, the influence on SSD increases with the fidelity of head models. And surprisingly, the SSD percentages in scalp and gray matter (region of interest in MRI head model were found to be 80% and 125% higher than in VCH head model. MRI head models induced nonignorable discrepancy in SSD estimation when compared with VCH head model. This study, as we believe, is the first to focus on comparison among full serials of head model on estimating SSD, and provided quantitative evidence for MRI head model users to calibrate their SSD estimation.

  2. A Modelling Approach on Fine Particle Spatial Distribution for Street Canyons in Asian Residential Community

    Science.gov (United States)

    Ling, Hong; Lung, Shih-Chun Candice; Uhrner, Ulrich

    2016-04-01

    Rapidly increasing urban pollution poses severe health risks.Especially fine particles pollution is considered to be closely related to respiratory and cardiovascular disease. In this work, ambient fine particles are studied in street canyons of a typical Asian residential community using a computational fluid dynamics (CFD) dispersion modelling approach. The community is characterised by an artery road with a busy traffic flow of about 4000 light vehicles (mainly cars and motorcycles) per hour at rush hours, three streets with hundreds light vehicles per hour at rush hours and several small lanes with less traffic. The objective is to study the spatial distribution of the ambient fine particle concentrations within micro-environments, in order to assess fine particle exposure of the people living in the community. The GRAL modelling system is used to simulate and assess the emission and dispersion of the traffic-related fine particles within the community. Traffic emission factors and traffic situation is assigned using both field observation and local emissions inventory data. High resolution digital elevation data (DEM) and building height data are used to resolve the topographical features. Air quality monitoring and mobile monitoring within the community is used to validate the simulation results. By using this modelling approach, the dispersion of fine particles in street canyons is simulated; the impact of wind condition and street orientation are investigated; the contributions of car and motorcycle emissions are quantified respectively; the residents' exposure level of fine particles is assessed. The study is funded by "Taiwan Megacity Environmental Research (II)-chemistry and environmental impacts of boundary layer aerosols (Year 2-3) (103-2111-M-001-001-); Spatial variability and organic markers of aerosols (Year 3)(104-2111-M-001 -005 -)"

  3. A spatially distributed and physically based tool to modelling rainfall-triggered landslides

    Science.gov (United States)

    Arnone, E.; Noto, L. V.; Lepore, C.; Bras, R. L.

    2009-09-01

    Landslides are a serious threat to lives and property throughout the world. Over the last few years the need to provide consistent tools and support to decision-makers and land managers have led to significant progress in the analysis and understanding of the occurrence of landslides. The causes of landslides are varied. Multiple dynamic processes are involved in driving slope failures. One of these causes is prolonged rainfall, which affect slope stability in different ways. Water entering the ground beneath a slope always causes a rise of the piezometric surface, which in turn involves an increase of the pore-water pressure and a decrease of the soil shear resistance. For this reason, knowledge of spatio-temporal dynamics of soil water content, groundwater and infiltration processes is of considerable importance in the understanding and prediction of landslides dynamics. Many methods and techniques have been proposed to estimate when and where rainfall could trigger slope failure. In this paper a spatially distributed and physically based approach is presented, which integrates of a failure model with an hydrological one. The hydrological model used in the study is the tRIBS model (Triangulated Irregular Network (TIN-based) Real-Time Integrated Basin Simulator) that allows simulation of spatial and temporal hydrological dynamics influencing the landsliding, in particular infiltration, evapotranspiration, groundwater dynamics and soil moisture conditions. In order to evaluate the slope stability, the infinite slope model has been implemented in tRIBS, making up a new component of the model. For each computational element, the model is able to verify the stability condition as a function of the safety factor, splitting between the unconditionally stable and the conditionally stable computational cells. The amount of detached soil and its possible path are also estimated. The variations in elevation due to the landslides modify the basin morphology. The

  4. Modeling the Hydrological Regime of Turkana Lake (Kenya, Ethiopia) by Combining Spatially Distributed Hydrological Modeling and Remote Sensing Datasets

    Science.gov (United States)

    Anghileri, D.; Kaelin, A.; Peleg, N.; Fatichi, S.; Molnar, P.; Roques, C.; Longuevergne, L.; Burlando, P.

    2017-12-01

    Hydrological modeling in poorly gauged basins can benefit from the use of remote sensing datasets although there are challenges associated with the mismatch in spatial and temporal scales between catchment scale hydrological models and remote sensing products. We model the hydrological processes and long-term water budget of the Lake Turkana catchment, a transboundary basin between Kenya and Ethiopia, by integrating several remote sensing products into a spatially distributed and physically explicit model, Topkapi-ETH. Lake Turkana is the world largest desert lake draining a catchment of 145'500 km2. It has three main contributing rivers: the Omo river, which contributes most of the annual lake inflow, the Turkwel river, and the Kerio rivers, which contribute the remaining part. The lake levels have shown great variations in the last decades due to long-term climate fluctuations and the regulation of three reservoirs, Gibe I, II, and III, which significantly alter the hydrological seasonality. Another large reservoir is planned and may be built in the next decade, generating concerns about the fate of Lake Turkana in the long run because of this additional anthropogenic pressure and increasing evaporation driven by climate change. We consider different remote sensing datasets, i.e., TRMM-V7 for precipitation, MERRA-2 for temperature, as inputs to the spatially distributed hydrological model. We validate the simulation results with other remote sensing datasets, i.e., GRACE for total water storage anomalies, GLDAS-NOAH for soil moisture, ERA-Interim/Land for surface runoff, and TOPEX/Poseidon for satellite altimetry data. Results highlight how different remote sensing products can be integrated into a hydrological modeling framework accounting for their relative uncertainties. We also carried out simulations with the artificial reservoirs planned in the north part of the catchment and without any reservoirs, to assess their impacts on the catchment hydrological

  5. A hierarchical model for estimating the spatial distribution and abundance of animals detected by continuous-time recorders.

    Directory of Open Access Journals (Sweden)

    Robert M Dorazio

    Full Text Available Several spatial capture-recapture (SCR models have been developed to estimate animal abundance by analyzing the detections of individuals in a spatial array of traps. Most of these models do not use the actual dates and times of detection, even though this information is readily available when using continuous-time recorders, such as microphones or motion-activated cameras. Instead most SCR models either partition the period of trap operation into a set of subjectively chosen discrete intervals and ignore multiple detections of the same individual within each interval, or they simply use the frequency of detections during the period of trap operation and ignore the observed times of detection. Both practices make inefficient use of potentially important information in the data.We developed a hierarchical SCR model to estimate the spatial distribution and abundance of animals detected with continuous-time recorders. Our model includes two kinds of point processes: a spatial process to specify the distribution of latent activity centers of individuals within the region of sampling and a temporal process to specify temporal patterns in the detections of individuals. We illustrated this SCR model by analyzing spatial and temporal patterns evident in the camera-trap detections of tigers living in and around the Nagarahole Tiger Reserve in India. We also conducted a simulation study to examine the performance of our model when analyzing data sets of greater complexity than the tiger data.Our approach provides three important benefits: First, it exploits all of the information in SCR data obtained using continuous-time recorders. Second, it is sufficiently versatile to allow the effects of both space use and behavior of animals to be specified as functions of covariates that vary over space and time. Third, it allows both the spatial distribution and abundance of individuals to be estimated, effectively providing a species distribution model, even in

  6. Modelling the effect of intersections in linear habitat on spatial distribution and local population density

    NARCIS (Netherlands)

    Langevelde, van F.; Grashof-Bokdam, C.J.

    2011-01-01

    Many species in human-dominated landscapes find their habitat in linear elements, such as road verges, hedgerows and ditches. Local concentrations of species have been observed in the intersections of linear elements, but their spatial distribution and local population density in this linear habitat

  7. MODELING SPATIAL DISTRIBUTION OF A RARE AND ENDANGERED PLANT SPECIES (Brainea insignis IN CENTRAL TAIWAN

    Directory of Open Access Journals (Sweden)

    W.-C. Wang

    2012-07-01

    Full Text Available With an increase in the rate of species extinction, we should choose right methods that are sustainable on the basis of appropriate science and human needs to conserve ecosystems and rare species. Species distribution modeling (SDM uses 3S technology and statistics and becomes increasingly important in ecology. Brainea insignis (cycad-fern, CF has been categorized a rare, endangered plant species, and thus was chosen as a target for the study. Five sampling schemes were created with different combinations of CF samples collected from three sites in Huisun forest station and one site, 10 km farther north from Huisun. Four models, MAXENT, GARP, generalized linear models (GLM, and discriminant analysis (DA, were developed based on topographic variables, and were evaluated by five sampling schemes. The accuracy of MAXENT was the highest, followed by GLM and GARP, and DA was the lowest. More importantly, they can identify the potential habitat less than 10% of the study area in the first round of SDM, thereby prioritizing either the field-survey area where microclimatic, edaphic or biotic data can be collected for refining predictions of potential habitat in the later rounds of SDM or search areas for new population discovery. However, it was shown unlikely to extend spatial patterns of CFs from one area to another with a big separation or to a larger area by predictive models merely based on topographic variables. Follow-up studies will attempt to incorporate proxy indicators that can be extracted from hyperspectral images or LIDAR DEM and substitute for direct parameters to make predictive models applicable on a broader scale.

  8. Using a spatially-distributed hydrologic biogeochemistry model to study the spatial variation of carbon processes in a Critical Zone Observatory

    Science.gov (United States)

    Shi, Y.; Eissenstat, D. M.; Davis, K. J.; He, Y.

    2016-12-01

    Forest carbon processes are affected by, among other factors, soil moisture, soil temperature, soil nutrients and solar radiation. Most of the current biogeochemical models are 1-D and represent one point in space. Therefore, they cannot resolve the topographically driven hill-slope land surface heterogeneity or the spatial pattern of nutrient availability. A spatially distributed forest ecosystem model, Flux-PIHM-BGC, has been developed by coupling a 1-D mechanistic biogeochemical model Biome-BGC (BBGC) with a spatially distributed land surface hydrologic model, Flux-PIHM. Flux-PIHM is a coupled physically based model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. In the coupled Flux-PIHM-BGC model, each Flux-PIHM model grid couples a 1-D BBGC model, while soil nitrogen is transported among model grids via subsurface water flow. In each grid, Flux-PIHM provides BBGC with soil moisture, soil temperature, and solar radiation information, while BBGC provides Flux-PIHM with leaf area index. The coupled Flux-PIHM-BGC model has been implemented at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). Model results suggest that the vegetation and soil carbon distribution is primarily constrained by nitorgen availability (affected by nitorgen transport via topographically driven subsurface flow), and also constrained by solar radiation and root zone soil moisture. The predicted vegetation and soil carbon distribution generally agrees with the macro pattern observed within the watershed. The coupled ecosystem-hydrologic model provides an important tool to study the impact of topography on watershed carbon processes, as well as the impact of climate change on water resources.

  9. Modelling the temporal and spatial distribution of ecological variables in Beibu Gulf

    Science.gov (United States)

    Pan, H.; Huang, L.; Yang, S.; Shi, D.; Pan, W.

    2017-12-01

    Beibu Gulf is an important semi-enclosed gulf located in northern South China Sea. It is rich in natural resources and its coastal rim is undergoing a rapid economic growth in recent years. Study on the spatial and temporal distribution of ecological variables by the influence of physical and biological processes in Beibu Gulf can provide the theoretical basis for the utilization of resources and environmental protection. Based on the MEC three-dimensional hydrodynamic model, a nutrient-phytoplankton-zooplankton-detritus (NPZD) model was applied to simulate the distribution of ecological variables in Beibu Gulf. The result shows that the ecosystem in Beibu Gulf is significantly influenced by dynamic conditions. In autumn and winter, great amount of nutrient-rich water from western Guangdong coastal area passes through Qiongzhou Strait and flows into Beibu Gulf, with about 108.3×103 t of inorganic nitrogen and 3.7×103 t of phosphate annually, leading to phytoplankton bloom. In summer, most of the nutrients come from rivers so high concentrations of nutrients and chlorophyll-a appear on estuaries. The annual net nutrient inputs from South China Sea into Beibu Gulf are 66.6×103 t for inorganic nitrogen and 4.6×103 t for phosphate. Phytoplankton plays an important role in nutrients' refreshment: a) Absorption by the process of photosynthesis is the biggest nutrient sink. b) Cellular release from dead phytoplankton is the biggest source in inorganic budget, making up for 33.4% of nitrogen consumed by photosynthesis while the process of respiration is the biggest source in phosphate budget, making up for 32.4% of phosphorus consumed by photosynthesis. c) Mineralization from detritus is also a considerable supplement of inorganic nutrients. Overall, biological process has more influence than physical process on the nutrient cycle budget in Beibu Gulf. The comparison of the result with remote sensing and in-situ data indicates that the model is able to simulate the

  10. Modeling spatial distribution of oxygen in 3d culture of islet beta-cells.

    Science.gov (United States)

    McReynolds, John; Wen, Yu; Li, Xiaofei; Guan, Jianjun; Jin, Sha

    2017-01-01

    Three-dimensional (3D) scaffold culture of pancreatic β-cell has been proven to be able to better mimic physiological conditions in the body. However, one critical issue with culturing pancreatic β-cells is that β-cells consume large amounts of oxygen, and hence insufficient oxygen supply in the culture leads to loss of β-cell mass and functions. This becomes more significant when cells are cultured in a 3D scaffold. In this study, in order to understand the effect of oxygen tension inside a cell-laden collagen culture on β-cell proliferation, a culture model with encapsulation of an oxygen-generator was established. The oxygen-generator was made by embedding hydrogen peroxide into nontoxic polydimethylsiloxane to avoid the toxicity of a chemical reaction in the β-cell culture. To examine the effectiveness of the oxygenation enabled 3D culture, the spatial-temporal distribution of oxygen tension inside a scaffold was evaluated by a mathematical modeling approach. Our simulation results indicated that an oxygenation-aided 3D culture would augment the oxygen supply required for the β-cells. Furthermore, we identified that cell seeding density and the capacity of the oxygenator are two critical parameters in the optimization of the culture. Notably, cell-laden scaffold cultures with an in situ oxygen supply significantly improved the β-cells' biological function. These β-cells possess high insulin secretion capacity. The results obtained in this work would provide valuable information for optimizing and encouraging functional β-cell cultures. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 33:221-228, 2017. © 2016 American Institute of Chemical Engineers.

  11. Species distribution models predict temporal but not spatial variation in forest growth

    NARCIS (Netherlands)

    Maaten, van der Ernest; Hamann, A.; Maaten-Theunissen, van der M.; Bergsma, A.R.; Hengeveld, G.M.; Lammeren, van R.J.A.; Mohren, G.M.J.; Nabuurs, G.J.; Terhürne, R.L.; Sterck, F.J.

    2017-01-01

    Bioclimate envelope models have been widely used to illustrate the discrepancy between current species distributions and their potential habitat under climate change. However, the realism and correct interpretation of such projections has been the subject of considerable discussion. Here, we

  12. Effects of spatially distributed sectoral water management on the redistribution of water resources in an integrated water model

    Science.gov (United States)

    Voisin, Nathalie; Hejazi, Mohamad I.; Leung, L. Ruby; Liu, Lu; Huang, Maoyi; Li, Hong-Yi; Tesfa, Teklu

    2017-05-01

    Realistic representations of sectoral water withdrawals and consumptive demands and their allocation to surface and groundwater sources are important for improving modeling of the integrated water cycle. To inform future model development, we enhance the representation of water management in a regional Earth system (ES) model with a spatially distributed allocation of sectoral water demands simulated by a regional integrated assessment (IA) model to surface and groundwater systems. The integrated modeling framework (IA-ES) is evaluated by analyzing the simulated regulated flow and sectoral supply deficit in major hydrologic regions of the conterminous U.S, which differ from ES studies looking at water storage variations. Decreases in historical supply deficit are used as metrics to evaluate IA-ES model improvement in representating the complex sectoral human activities for assessing future adaptation and mitigation strategies. We also assess the spatial changes in both regulated flow and unmet demands, for irrigation and nonirrigation sectors, resulting from the individual and combined additions of groundwater and return flow modules. Results show that groundwater use has a pronounced regional and sectoral effect by reducing water supply deficit. The effects of sectoral return flow exhibit a clear east-west contrast in the hydrologic patterns, so the return flow component combined with the IA sectoral demands is a major driver for spatial redistribution of water resources and water deficits in the US. Our analysis highlights the need for spatially distributed sectoral representation of water management to capture the regional differences in interbasin redistribution of water resources and deficits.

  13. The research on spatial load forecasting model and method of electricity energy alternative based on cloud theory in distribution network

    Science.gov (United States)

    Zhou, Honglian; Li, Juan; Hu, Zhiyun; Li, Qingbo; Liu, Zifa; Wang, Wei

    2017-11-01

    The research on electrical energy alternative mainly focus on alternative energy potential, expanding strategy and benefit analysis due to lack of historical data. This paper presents the total spatial load forecasting model in distribution network based on the proposed electrical energy alternative development coefficient which is generated by electricity energy objective issued by governments. To deal with fuzzy and uncertain in load forecasting for electric boiler and heater, the cloud theory and the regularity in the process of electrical energy alternative popularization are used. The component of electrical alternative spatial load forecasting is presented in sequence. The proposed method is verified in a typical case.

  14. Integration of Spatially Hydrological Modelling on Bentong Catchment, Pahang, Peninsular Malaysia Using Distributed GIS-based Rainfall Runoff Model

    Directory of Open Access Journals (Sweden)

    Rosli, M.H.

    2017-07-01

    Full Text Available With the advance of GIS technology, hydrology model can simulated at catchment wide scale. The objective is to integrate National Resource Conservation Service (NRCS Curve Number (CN with kinematic wave and manning’s equation using GIS to develop a simple GIS-based distributed model to simulate rainfall runoff in Bentong catchment. Model was built using Spatial Distributed Direct Hydrograph (SDDH concept and applying the time area (TA approach in presenting the predicted discharge hydrograph. The effective precipitation estimation was first calculated using the NRCS CN method. Then, the core maps that consists of digital elevation model (DEM, soil and land use map in grid. DEM was used to derive slope, flow direction and flow accumulation while soil and land use map used to derive roughness coefficient and CN. The overland velocity and channel velocity estimation derived from combination of kinematic wave theory with Manning’s equation. To capture the time frame, the travel time map was divided into isochrones in order to generate the TA histogram and finally. The creation of SDDH using the TA histogram which will lead to the estimation of travel time for the catchment. Simulated hydrograph was plotted together with the observed discharge for comparison. Six storm events used for model performance evaluation using statistical measure such as Nash-Sutcliffe efficiency (NSE, percent bias (PBIAS and coefficient of determination (R2;. SDDH model performed quite well as NSE gave result ranging from 0.55 to 0.68 with mean of 0.6. PBIAS indicate that the model slightly over predicted compared to observed hydrograph with result ranges from -46.71 (the most over predicted to +4.83 (the most under predicted with average of -20.73%. R2; ranges between 0.55 to 0.82 with mean of 0.67. When comparing the time to peak, (tp, min, and peak discharge, (pd, m3/s, results gave NSEtp 0.82, PBIAStp 0.65, R2tp 0.32, NSEpd 0.95, PBIASpd 14.49 and R2pd 0

  15. Improving simulated spatial distribution of productivity and biomass in Amazon forests using the ACME land model

    Science.gov (United States)

    Yang, X.; Thornton, P. E.; Ricciuto, D. M.; Shi, X.; Xu, M.; Hoffman, F. M.; Norby, R. J.

    2017-12-01

    Tropical forests play a crucial role in the global carbon cycle, accounting for one third of the global NPP and containing about 25% of global vegetation biomass and soil carbon. This is particularly true for tropical forests in the Amazon region, as it comprises approximately 50% of the world's tropical forests. It is therefore important for us to understand and represent the processes that determine the fluxes and storage of carbon in these forests. In this study, we show that the implementation of phosphorus (P) cycle and P limitation in the ACME Land Model (ALM) improves simulated spatial pattern of NPP. The P-enabled ALM is able to capture the west-to-east gradient of productivity, consistent with field observations. We also show that by improving the representation of mortality processes, ALM is able to reproduce the observed spatial pattern of above ground biomass across the Amazon region.

  16. Climate change and the potential global distribution of Aedes aegypti: spatial modelling using GIS and CLIMEX.

    Science.gov (United States)

    Khormi, Hassan M; Kumar, Lalit

    2014-05-01

    We examined the potential added risk posed by global climate change on the dengue vector Aedes aegypti abundance using CLIMEX, a powerful tool for exploring the relationship between the fundamental and realised niche of any species. After calibrating the model using data from several knowledge domains, including geographical distribution records, we estimated potential distributions of the mosquito under current and future potential scenarios. The impact of climate change on its potential distribution was assessed with two global climate models, the CSIRO-Mk3.0 and the MIROC-H, run with two potential, future emission scenarios (A1B and A2) published by the Intergovernmental Panel on Climate Change. We compared today's climate situation with two arbitrarily chosen future time points (2030 and 2070) to see the impact on the worldwide distribution of A. aegypti . The model for the current global climate indicated favourable areas for the mosquito within its known distribution in tropical and subtropical areas. However, even if much of the tropics and subtropics will continue to be suitable, the climatically favourable areas for A. aegypti globally are projected to contract under the future scenarios produced by these models, while currently unfavourable areas, such as inland Australia, the Arabian Peninsula, southern Iran and some parts of North America may become climatically favourable for this mosquito species. The climate models for the Aedes dengue vector presented here should be useful for management purposes as they can be adapted for decision/making regarding allocation of resources for dengue risk toward areas where risk infection remains and away from areas where climatic suitability is likely to decrease in the future.

  17. Automated modelling of spatially-distributed glacier ice thickness and volume

    Science.gov (United States)

    James, William H. M.; Carrivick, Jonathan L.

    2016-07-01

    Ice thickness distribution and volume are both key parameters for glaciological and hydrological applications. This study presents VOLTA (Volume and Topography Automation), which is a Python script tool for ArcGISTM that requires just a digital elevation model (DEM) and glacier outline(s) to model distributed ice thickness, volume and bed topography. Ice thickness is initially estimated at points along an automatically generated centreline network based on the perfect-plasticity rheology assumption, taking into account a valley side drag component of the force balance equation. Distributed ice thickness is subsequently interpolated using a glaciologically correct algorithm. For five glaciers with independent field-measured bed topography, VOLTA modelled volumes were between 26.5% (underestimate) and 16.6% (overestimate) of that derived from field observations. Greatest differences were where an asymmetric valley cross section shape was present or where significant valley infill had occurred. Compared with other methods of modelling ice thickness and volume, key advantages of VOLTA are: a fully automated approach and a user friendly graphical user interface (GUI), GIS consistent geometry, fully automated centreline generation, inclusion of a side drag component in the force balance equation, estimation of glacier basal shear stress for each individual glacier, fully distributed ice thickness output and the ability to process multiple glaciers rapidly. VOLTA is capable of regional scale ice volume assessment, which is a key parameter for exploring glacier response to climate change. VOLTA also permits subtraction of modelled ice thickness from the input surface elevation to produce an ice-free DEM, which is a key input for reconstruction of former glaciers. VOLTA could assist with prediction of future glacier geometry changes and hence in projection of future meltwater fluxes.

  18. A method to employ the spatial organization of catchments into semi-distributed rainfall-runoff models

    Science.gov (United States)

    Oppel, Henning; Schumann, Andreas

    2017-08-01

    A distributed or semi-distributed deterministic hydrological model should consider the hydrologically most relevant catchment characteristics. These are heterogeneously distributed within a watershed but often interrelated and subject to a certain spatial organization which results in archetypes of combined characteristics. In order to reproduce the natural rainfall-runoff response the reduction of variance of catchment properties as well as the incorporation of the spatial organization of the catchment are desirable. In this study the width-function approach is utilized as a basic characteristic to analyse the succession of catchment characteristics. By applying this technique we were able to assess the context of catchment properties like soil or topology along the streamflow length and the network geomorphology, giving indications of the spatial organization of a catchment. Moreover, this information and this technique have been implemented in an algorithm for automated sub-basin ascertainment, which included the definition of zones within the newly defined sub-basins. The objective was to provide sub-basins that were less heterogeneous than common separation schemes. The algorithm was applied to two parameters characterizing the topology and soil of four mid-European watersheds. Resulting partitions indicated a wide range of applicability for the method and the algorithm. Additionally, the intersection of derived zones for different catchment characteristics could give insights into sub-basin similarities. Finally, a HBV96 case study demonstrated the potential benefits of modelling with the new subdivision technique.

  19. A method to employ the spatial organization of catchments into semi-distributed rainfall–runoff models

    Directory of Open Access Journals (Sweden)

    H. Oppel

    2017-08-01

    Full Text Available A distributed or semi-distributed deterministic hydrological model should consider the hydrologically most relevant catchment characteristics. These are heterogeneously distributed within a watershed but often interrelated and subject to a certain spatial organization which results in archetypes of combined characteristics. In order to reproduce the natural rainfall–runoff response the reduction of variance of catchment properties as well as the incorporation of the spatial organization of the catchment are desirable. In this study the width-function approach is utilized as a basic characteristic to analyse the succession of catchment characteristics. By applying this technique we were able to assess the context of catchment properties like soil or topology along the streamflow length and the network geomorphology, giving indications of the spatial organization of a catchment. Moreover, this information and this technique have been implemented in an algorithm for automated sub-basin ascertainment, which included the definition of zones within the newly defined sub-basins. The objective was to provide sub-basins that were less heterogeneous than common separation schemes. The algorithm was applied to two parameters characterizing the topology and soil of four mid-European watersheds. Resulting partitions indicated a wide range of applicability for the method and the algorithm. Additionally, the intersection of derived zones for different catchment characteristics could give insights into sub-basin similarities. Finally, a HBV96 case study demonstrated the potential benefits of modelling with the new subdivision technique.

  20. Geostatistical modeling of the spatial distribution of sediment oxygen demand within a Coastal Plain blackwater watershed.

    Science.gov (United States)

    Todd, M Jason; Lowrance, R Richard; Goovaerts, Pierre; Vellidis, George; Pringle, Catherine M

    2010-10-15

    Blackwater streams are found throughout the Coastal Plain of the southeastern United States and are characterized by a series of instream floodplain swamps that play a critical role in determining the water quality of these systems. Within the state of Georgia, many of these streams are listed in violation of the state's dissolved oxygen (DO) standard. Previous work has shown that sediment oxygen demand (SOD) is elevated in instream floodplain swamps and due to these areas of intense oxygen demand, these locations play a major role in determining the oxygen balance of the watershed as a whole. This work also showed SOD rates to be positively correlated with the concentration of total organic carbon. This study builds on previous work by using geostatistics and Sequential Gaussian Simulation to investigate the patchiness and distribution of total organic carbon (TOC) at the reach scale. This was achieved by interpolating TOC observations and simulated SOD rates based on a linear regression. Additionally, this study identifies areas within the stream system prone to high SOD at representative 3rd and 5th order locations. Results show that SOD was spatially correlated with the differences in distribution of TOC at both locations and that these differences in distribution are likely a result of the differing hydrologic regime and watershed position. Mapping of floodplain soils at the watershed scale shows that areas of organic sediment are widespread and become more prevalent in higher order streams. DO dynamics within blackwater systems are a complicated mix of natural and anthropogenic influences, but this paper illustrates the importance of instream swamps in enhancing SOD at the watershed scale. Moreover, our study illustrates the influence of instream swamps on oxygen demand while providing support that many of these systems are naturally low in DO.

  1. Spatial distribution of aquatic insects

    DEFF Research Database (Denmark)

    Iversen, Lars Lønsmann

    and shape the habitat requirements and distribution of one of the most affected groups of freshwater species: aquatic insects. It comprises four chapters each addressing different spatial factors in relation to the occurrence of aquatic insects in Europe. Chapter I examine two spatial ecological processes...... niche is derived from local distribution patterns, without incorporating landscape history it can lead to an erroneous niche definition. Chapter III provides some of the first evidence for differences in dispersal phenology related to flight potential in aquatic insects. The chapter highlights...

  2. Modelling shallow landslide susceptibility by means of a subsurface flow path connectivity index and estimates of soil depth spatial distribution

    Directory of Open Access Journals (Sweden)

    C. Lanni

    2012-11-01

    Full Text Available Topographic index-based hydrological models have gained wide use to describe the hydrological control on the triggering of rainfall-induced shallow landslides at the catchment scale. A common assumption in these models is that a spatially continuous water table occurs simultaneously across the catchment. However, during a rainfall event isolated patches of subsurface saturation form above an impeding layer and their hydrological connectivity is a necessary condition for lateral flow initiation at a point on the hillslope.

    Here, a new hydrological model is presented, which allows us to account for the concept of hydrological connectivity while keeping the simplicity of the topographic index approach. A dynamic topographic index is used to describe the transient lateral flow that is established at a hillslope element when the rainfall amount exceeds a threshold value allowing for (a development of a perched water table above an impeding layer, and (b hydrological connectivity between the hillslope element and its own upslope contributing area. A spatially variable soil depth is the main control of hydrological connectivity in the model. The hydrological model is coupled with the infinite slope stability model and with a scaling model for the rainfall frequency–duration relationship to determine the return period of the critical rainfall needed to cause instability on three catchments located in the Italian Alps, where a survey of soil depth spatial distribution is available. The model is compared with a quasi-dynamic model in which the dynamic nature of the hydrological connectivity is neglected. The results show a better performance of the new model in predicting observed shallow landslides, implying that soil depth spatial variability and connectivity bear a significant control on shallow landsliding.

  3. Spatial Distributions of Metal Atoms During Carbon SWNTs Formation: Measurements and Modelling

    Science.gov (United States)

    Cau, M.; Dorval, N.; Attal-Tretout, B.; Cochon, J. L.; Loiseau, A.; Farhat, S.; Hinkov, I.; Scott, C. D.

    2004-01-01

    Experiments and modelling have been undertaken to clarify the role of metal catalysts during single-wall carbon nanotube formation. For instance, we wonder whether the metal catalyst is active as an atom, a cluster, a liquid or solid nanoparticle [1]. A reactor has been developed for synthesis by continuous CO2-laser vaporisation of a carbon-nickel-cobalt target in laminar helium flow. The laser induced fluorescence technique [2] is applied for local probing of gaseous Ni, Co and CZ species throughout the hot carbon flow of the target heated up to 3500 K. A rapid depletion of C2 in contrast to the spatial extent of metal atoms is observed in the plume (Fig. 1). This asserts that C2 condenses earlier than Ni and Co atoms.[3, 4]. The depletion is even faster when catalysts are present. It may indicate that an interaction between metal atoms and carbon dimers takes place in the gas as soon as they are expelled from the target surface. Two methods of modelling are used: a spatially I-D calculation developed originally for the arc process [5], and a zero-D time dependent calculation, solving the chemical kinetics along the streamlines [6]. The latter includes Ni cluster formation. The peak of C2 density is calculated close to the target surface where the temperature is the highest. In the hot region, C; is dominant. As the carbon products move away from the target and mix with the ambient helium, they recombine into larger clusters, as demonstrated by the peak of C5 density around 1 mm. The profile of Ni-atom density compares fairly well with the measured one (Fig. 2). The early increase is due to the drop of temperature, and the final decrease beyond 6 mm results from Ni cluster formation at the eutectic temperature (approx.1600 K).

  4. Dengue Vectors and their Spatial Distribution.

    Science.gov (United States)

    Higa, Yukiko

    2011-12-01

    The distribution of dengue vectors, Ae. aegypti and Ae. albopictus, is affected by climatic factors. In addition, since their life cycles are well adapted to the human environment, environmental changes resulting from human activity such as urbanization exert a great impact on vector distribution. The different responses of Ae. aegypti and Ae albopictus to various environments result in a difference in spatial distribution along north-south and urban-rural gradients, and between the indoors and outdoors. In the north-south gradient, climate associated with survival is an important factor in spatial distribution. In the urban-rural gradient, different distribution reflects a difference in adult niches and is modified by geographic and human factors. The direct response of the two species to the environment around houses is related to different spatial distribution indoors and outdoors. Dengue viruses circulate mainly between human and vector mosquitoes, and the vector presence is a limiting factor of transmission. Therefore, spatial distribution of dengue vectors is a significant concern in the epidemiology of the disease.Current technologies such as GIS, satellite imagery and statistical models allow researchers to predict the spatial distribution of vectors in the changing environment. Although it is difficult to confirm the actual effect of environmental and climate changes on vector abundance and vector-borne diseases, environmental changes caused by humans and human behavioral changes due to climate change can be expected to exert an impact on dengue vectors. Longitudinal monitoring of dengue vectors and viruses is therefore necessary.

  5. Modeling for spatial multilevel structural data

    Science.gov (United States)

    Min, Suqin; He, Xiaoqun

    2013-03-01

    The traditional multilevel model assumed independence between groups. However, the datasets grouped by geographical units often has spatial dependence. The individual is influenced not only by its region but also by the adjacent regions, and level-2 residual distribution assumption of traditional multilevel model is violated. In order to deal with such spatial multilevel data, we introduce spatial statistics and spatial econometric models into multilevel model, and apply spatial parameters and adjacency matrix in traditional level-2 model to reflect the spatial autocorrelation. Spatial lag model express spatial effects. We build spatial multilevel model which consider both multilevel thinking and spatial correlation.

  6. Modeling the spatial distribution of wolf (Canis lupus pallipes attacks on human using genetic algorithm (GARP in Hamedan province

    Directory of Open Access Journals (Sweden)

    N Behdarvand

    2012-06-01

    Full Text Available In recent decades due to steady human population growth coupled with increased use of resources and habitat degradation, conflicts between humans and carnivores have greatly been expanded. In order to mitigate these conflicts based on a clear understanding of conflict patterns, applying the species distribution models as helpful methods has been suggested. Occurring the recent conflict between wolves and local communities in Hamedan province is a clear case of this problem. In this study, capabilities of the genetic algorithm (GARP were assessed in the modeling spatial distribution of wolf attacks in Hamedan province during 2006-2012. The area under the receiver operating characteristic curve (ROC was used to evaluate performance of the model. Findings indicated that the applied modelingapproach has a very good performance (area under curve=0.856 inpredicting the spatial distribution of wolf attacks on humans. In addition, based on the results of sensitivity analysis, land-cover t ype, human population density and distance from main road were the most effective parameters. Findings of the present study can be applied in formulation of an adaptive management plan for wolf conservation and mitigation of the conflicts with local communities.

  7. Integrating a reservoir regulation scheme into a spatially distributed hydrological model

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Gang; Gao, Huilin; Naz, Bibi S.; Kao, Shih-Chieh; Voisin, Nathalie

    2016-12-01

    During the past several decades, numerous reservoirs have been built across the world for a variety of purposes such as flood control, irrigation, municipal/industrial water supplies, and hydropower generation. Consequently, natural streamflow timing and magnitude have been altered significantly by reservoir operations. In addition, the hydrological cycle can be modified by land use/land cover and climate changes. To understand the fine scale feedback between hydrological processes and water management decisions, a distributed hydrological model embedded with a reservoir component is of desire. In this study, a multi-purpose reservoir module with predefined complex operational rules was integrated into the Distributed Hydrology Soil Vegetation Model (DHSVM). Conditional operating rules, which are designed to reduce flood risk and enhance water supply reliability, were adopted in this module. The performance of the integrated model was tested over the upper Brazos River Basin in Texas, where two U.S. Army Corps of Engineers reservoirs, Lake Whitney and Aquilla Lake, are located. The integrated DHSVM model was calibrated and validated using observed reservoir inflow, outflow, and storage data. The error statistics were summarized for both reservoirs on a daily, weekly, and monthly basis. Using the weekly reservoir storage for Lake Whitney as an example, the coefficients of determination (R2) and the Nash-Sutcliff Efficiency (NSE) are 0.85 and 0.75, respectively. These results suggest that this reservoir module has promise for use in sub-monthly hydrological simulations. Enabled with the new reservoir component, the DHSVM model provides a platform to support adaptive water resources management under the impacts of evolving anthropogenic activities and substantial environmental changes.

  8. Predicting spatial and temporal distribution of Indo-Pacific lionfish (Pterois volitans) in Biscayne Bay through habitat suitability modeling

    Science.gov (United States)

    Bernal, Nicholas A.; DeAngelis, Donald L.; Schofield, Pamela J.; Sullivan Sealey, Kathleen

    2014-01-01

    Invasive species may exhibit higher levels of growth and reproduction when environmental conditions are most suitable, and thus their effects on native fauna may be intensified. Understanding potential impacts of these species, especially in the nascent stages of a biological invasion, requires critical information concerning spatial and temporal distributions of habitat suitability. Using empirically supported environmental variables (e.g., temperature, salinity, dissolved oxygen, rugosity, and benthic substrate), our models predicted habitat suitability for the invasive lionfish (Pterois volitans) in Biscayne Bay, Florida. The use of Geographic Information Systems (GIS) as a platform for the modeling process allowed us to quantify correlations between temporal (seasonal) fluctuations in the above variables and the spatial distribution of five discrete habitat quality classes, whose ranges are supported by statistical deviations from the apparent best conditions described in prior studies. Analysis of the resulting models revealed little fluctuation in spatial extent of the five habitat classes on a monthly basis. Class 5, which represented the area with environmental variables closest to the best conditions for lionfish, occupied approximately one-third of Biscayne Bay, with subsequent habitats declining in area. A key finding from this study was that habitat suitability increased eastward from the coastline, where higher quality habitats were adjacent to the Atlantic Ocean and displayed marine levels of ambient water quality. Corroboration of the models with sightings from the USGS-NAS database appeared to support our findings by nesting 79 % of values within habitat class 5; however, field testing (i.e., lionfish surveys) is necessary to confirm the relationship between habitat classes and lionfish distribution.

  9. Development of a spatially distributed model of fish population density for habitat assessment of rivers

    Science.gov (United States)

    Sui, Pengzhe; Iwasaki, Akito; Ryo, Masahiro; Saavedra, Oliver; Yoshimura, Chihiro

    2013-04-01

    Flow conditions play an important role in sustaining biodiversity of river ecosystem. However, their relations to freshwater fishes, especially to fish population density, have not been clearly described. This study, therefore, aimed to propose a new methodology to quantitatively link habitat conditions, including flow conditions and other physical conditions, to population density of fish species. We developed a basin-scale fish distribution model by integrating the concept of habitat suitability assessment with a distributed hydrological model (DHM) in order to estimate fish population density with particular attention to flow conditions. Generalized linear model (GLM) was employed to evaluate the relationship between population density of fish species and major environmental factors. The target basin was Sagami River in central Japan, where the river reach was divided into 10 sections by estuary, confluences of tributaries, and river-crossing structures (dams, weirs). The DHM was employed to simulate river discharge from 1998 to 2005, which was used to calculate 10 flow indices including mean discharge, 25th and 75th percentile discharge, duration of low and high flows, number of floods. In addition, 5 water quality parameters and 13 other physical conditions (such as basin area, river width, mean diameter of riverbed material, and number of river-crossing structures upstream and downstream) of each river section were considered as environmental variables. In case of Sagami River, 10 habitat variables among them were then selected based on their correlations to avoid multicollinearity. Finally, the best GLM was developed for each species based on Akaike's information criterion. As results, population densities of 16 fish species in Sagami River were modelled, and correlation coefficients between observed and calculated population densities for 10 species were more than 0.70. The key habitat factors for population density varied among fish species. Minimum

  10. Multivariate geostatistical modeling of the spatial sediment distribution in a large scale drainage basin, Upper Rhone, Switzerland

    Science.gov (United States)

    Schoch, Anna; Blöthe, Jan Henrik; Hoffmann, Thomas; Schrott, Lothar

    2018-02-01

    There is a notable discrepancy between detailed sediment budget studies in small headwater catchments ( 103 km2) in higher order catchments applying modeling and/or remote sensing based approaches for major sediment storage delineation. To bridge the gap between these scales, we compiled an inventory of sediment and bedrock coverage from field mapping, remote sensing analysis and published data for five key sites in the Upper Rhone Basin (Val d'Illiez, Val de la Liène, Turtmanntal, Lötschental, Goms; 360.3 km2, equivalent to 6.7% of the Upper Rhone Basin). This inventory was used as training and testing data for the classification of sediment and bedrock cover. From a digital elevation model (2 × 2 m ground resolution) and Landsat imagery we derived 22 parameters characterizing local morphometry, topography and position, contributing area, and climatic and biotic factors on different spatial scales, which were used as inputs for different statistical models (logistic regression, principal component logistic regression, generalized additive model). Best prediction results with an excellent performance (mean AUROC: 0.8721 ± 0.0012) and both a high spatial and non-spatial transferability were achieved applying a generalized additive model. Since the model has a high thematic consistency, the independent input variables chosen based on their geomorphic relevance are suitable to model the spatial distribution of sediment. Our high-resolution classification shows that 53.5 ± 21.7% of the Upper Rhone Basin are covered with sediment. These are by no means evenly distributed: small headwaters (< 5 km2) feature a very strong variability in sediment coverage, with watersheds drowning in sediments juxtaposed to watersheds devoid of sediment cover. In contrast, larger watersheds predominantly show a bimodal distribution, with highest densities for bedrock (30-40%) being consistently lower than for sediment cover (60-65%). Earlier studies quantifying sedimentary cover and

  11. An experimental and theoretical model of children’s search behavior in relation to target conspicuity and spatial distribution

    Science.gov (United States)

    Rosetti, Marcos Francisco; Pacheco-Cobos, Luis; Larralde, Hernán; Hudson, Robyn

    2010-11-01

    This work explores search trajectories of children attempting to find targets distributed on a playing field. This task, of ludic nature, was developed to test the effect of conspicuity and spatial distribution of targets on the searcher’s performance. The searcher’s path was recorded by a Global Positioning System (GPS) device attached to the child’s waist. Participants were not rewarded nor their performance rated. Variation in the conspicuity of the targets influenced search performance as expected; cryptic targets resulted in slower searches and longer, more tortuous paths. Extracting the main features of the paths showed that the children: (1) paid little attention to the spatial distribution and at least in the conspicuous condition approximately followed a nearest neighbor pattern of target collection, (2) were strongly influenced by the conspicuity of the targets. We implemented a simple statistical model for the search rules mimicking the children’s behavior at the level of individual (coarsened) steps. The model reproduced the main features of the children’s paths without the participation of memory or planning.

  12. A spatially distributed hydroeconomic model to assess the effects of drought on land use, farm profits, and agricultural employment

    Science.gov (United States)

    Maneta, M. P.; Torres, M. O.; Wallender, W. W.; Vosti, S.; Howitt, R.; Rodrigues, L.; Bassoi, L. H.; Panday, S.

    2009-11-01

    In this paper a high-resolution linked hydroeconomic model is demonstrated for drought conditions in a Brazilian river basin. The economic model of agriculture includes 13 decision variables that can be optimized to maximize farmers' yearly net revenues. The economic model uses a multi-input multioutput nonlinear constant elasticity of substitution (CES) production function simulating agricultural production. The hydrologic component is a detailed physics-based three-dimensional hydrodynamic model that simulates changes in the hydrologic system derived from agricultural activity while in turn providing biophysical constraints to the economic system. The linked models capture the effects of the interactions between the hydrologic and the economic systems at high spatial and temporal resolutions, ensuring that the model converges to an optimal economic scenario that takes into account the spatial and temporal distribution of the water resources. The operation and usefulness of the models are demonstrated in a rural catchment area of about 10 km2 within the São Francisco River Basin in Brazil. Two droughts of increasing intensity are simulated to investigate how farmers behave under rain shortfalls of different severity. The results show that farmers react to rainfall shortages to minimize their effects on farm profits, and that the impact on farmers depends, among other things, on their location in the watershed and on their access to groundwater.

  13. Spatial distributions of niche-constructing populations

    Directory of Open Access Journals (Sweden)

    Xiaozhuo Han

    2015-12-01

    Full Text Available Niche construction theory regards organisms not only as the object of natural selection but also an active subject that can change their own selective pressure through eco-evolutionary feedbacks. Through reviewing the existing works on the theoretical models of niche construction, here we present the progress made on how niche construction influences genetic structure of spatially structured populations and the spatial-temporal dynamics of metapopulations, with special focuses on mathematical models and simulation methods. The majority of results confirmed that niche construction can significantly alter the evolutionary trajectories of structured populations. Organism-environmental interactions induced by niche construction can have profound influence on the dynamics, competition and diversity of metapopulations. It can affect fine-scale spatially distribution of species and spatial heterogeneity of the environment. We further propose a few research directions with potentials, such as applying adaptive dynamics or spatial game theory to explore the effect of niche construction on phenotypic evolution and diversification.

  14. A biomimetic physiological model for human adipose tissue by adipocytes and endothelial cell cocultures with spatially controlled distribution

    International Nuclear Information System (INIS)

    Yao, Rui; Zhang, Renji; Lin, Feng; Du, Yanan; Luan, Jie

    2013-01-01

    An in vitro model that recapitulates the characteristics of native human adipose tissue would largely benefit pathology studies and therapy development. In this paper, we fabricated a physiological model composed of both human adipocytes and endothelial cells with spatially controlled distribution that biomimics the structure and composition of human adipose tissue. Detailed studies into the cell–cell interactions between the adipocytes and endothelial cells revealed a mutual-enhanced effect which resembles the in vivo routine. Furthermore, comparisons between planar coculture and model coculture demonstrated improved adipocyte function as well as endothelial cell proliferation under the same conditions. This research provided a reliable model for human adipose tissue development studies and potential obesity-related therapy development. (paper)

  15. The random field model of the spatial distribution of heavy vehicle loads on long-span bridges

    Science.gov (United States)

    Chen, Zhicheng; Bao, Yuequan; Li, Hui

    2016-04-01

    A stochastic model based on Markov random field is proposed to model the spatial distribution of vehicle loads on longspan bridges. The bridge deck is divided into a finite set of discrete grid cells, each cell has two states according to whether the cell is occupied by the heavy vehicle load or not, then a four-neighbor lattice-structured undirected graphical model with each node corresponding to a cell state variable is proposed to model the location distribution of heavy vehicle loads on the bridge deck. The node potential is defined to quantitatively describe the randomness of node state, and the edge potential is defined to quantitatively describe the correlation of the connected node pair. The junction tree algorithm is employed to obtain the systematic solutions of inference problems of the graphical model. A marked random variable is assigned to each node to represent the amplitude of the total weight of vehicle applied on the corresponding cell of the bridge deck. The rationality of the model is validated by a Monte Carlo simulation of a learned model based on monitored data of a cable-stayed bridge.

  16. Evaluation of Spatial Pattern of Altered Flow Regimes on a River Network Using a Distributed Hydrological Model.

    Science.gov (United States)

    Ryo, Masahiro; Iwasaki, Yuichi; Yoshimura, Chihiro; Saavedra V, Oliver C

    2015-01-01

    Alteration of the spatial variability of natural flow regimes has been less studied than that of the temporal variability, despite its ecological importance for river ecosystems. Here, we aimed to quantify the spatial patterns of flow regime alterations along a river network in the Sagami River, Japan, by estimating river discharge under natural and altered flow conditions. We used a distributed hydrological model, which simulates hydrological processes spatiotemporally, to estimate 20-year daily river discharge along the river network. Then, 33 hydrologic indices (i.e., Indicators of Hydrologic Alteration) were calculated from the simulated discharge to estimate the spatial patterns of their alterations. Some hydrologic indices were relatively well estimated such as the magnitude and timing of maximum flows, monthly median flows, and the frequency of low and high flow pulses. The accuracy was evaluated with correlation analysis (r > 0.4) and the Kolmogorov-Smirnov test (α = 0.05) by comparing these indices calculated from both observed and simulated discharge. The spatial patterns of the flow regime alterations varied depending on the hydrologic indices. For example, both the median flow in August and the frequency of high flow pulses were reduced by the maximum of approximately 70%, but these strongest alterations were detected at different locations (i.e., on the mainstream and the tributary, respectively). These results are likely caused by different operational purposes of multiple water control facilities. The results imply that the evaluation only at discharge gauges is insufficient to capture the alteration of the flow regime. Our findings clearly emphasize the importance of evaluating the spatial pattern of flow regime alteration on a river network where its discharge is affected by multiple water control facilities.

  17. Evaluation of Spatial Pattern of Altered Flow Regimes on a River Network Using a Distributed Hydrological Model

    Science.gov (United States)

    Ryo, Masahiro; Iwasaki, Yuichi; Yoshimura, Chihiro; Saavedra V., Oliver C.

    2015-01-01

    Alteration of the spatial variability of natural flow regimes has been less studied than that of the temporal variability, despite its ecological importance for river ecosystems. Here, we aimed to quantify the spatial patterns of flow regime alterations along a river network in the Sagami River, Japan, by estimating river discharge under natural and altered flow conditions. We used a distributed hydrological model, which simulates hydrological processes spatiotemporally, to estimate 20-year daily river discharge along the river network. Then, 33 hydrologic indices (i.e., Indicators of Hydrologic Alteration) were calculated from the simulated discharge to estimate the spatial patterns of their alterations. Some hydrologic indices were relatively well estimated such as the magnitude and timing of maximum flows, monthly median flows, and the frequency of low and high flow pulses. The accuracy was evaluated with correlation analysis (r > 0.4) and the Kolmogorov–Smirnov test (α = 0.05) by comparing these indices calculated from both observed and simulated discharge. The spatial patterns of the flow regime alterations varied depending on the hydrologic indices. For example, both the median flow in August and the frequency of high flow pulses were reduced by the maximum of approximately 70%, but these strongest alterations were detected at different locations (i.e., on the mainstream and the tributary, respectively). These results are likely caused by different operational purposes of multiple water control facilities. The results imply that the evaluation only at discharge gauges is insufficient to capture the alteration of the flow regime. Our findings clearly emphasize the importance of evaluating the spatial pattern of flow regime alteration on a river network where its discharge is affected by multiple water control facilities. PMID:26207997

  18. Increasing parameter certainty and data utility through multi-objective calibration of a spatially distributed temperature and solute model

    Directory of Open Access Journals (Sweden)

    C. Bandaragoda

    2011-05-01

    Full Text Available To support the goal of distributed hydrologic and instream model predictions based on physical processes, we explore multi-dimensional parameterization determined by a broad set of observations. We present a systematic approach to using various data types at spatially distributed locations to decrease parameter bounds sampled within calibration algorithms that ultimately provide information regarding the extent of individual processes represented within the model structure. Through the use of a simulation matrix, parameter sets are first locally optimized by fitting the respective data at one or two locations and then the best results are selected to resolve which parameter sets perform best at all locations, or globally. This approach is illustrated using the Two-Zone Temperature and Solute (TZTS model for a case study in the Virgin River, Utah, USA, where temperature and solute tracer data were collected at multiple locations and zones within the river that represent the fate and transport of both heat and solute through the study reach. The result was a narrowed parameter space and increased parameter certainty which, based on our results, would not have been as successful if only single objective algorithms were used. We also found that the global optimum is best defined by multiple spatially distributed local optima, which supports the hypothesis that there is a discrete and narrowly bounded parameter range that represents the processes controlling the dominant hydrologic responses. Further, we illustrate that the optimization process itself can be used to determine which observed responses and locations are most useful for estimating the parameters that result in a global fit to guide future data collection efforts.

  19. Developing spatial models of sugar kelp ( Saccharina latissima) potential distribution under natural conditions and areas of its disappearance in Skagerrak

    Science.gov (United States)

    Bekkby, Trine; Moy, Frithjof E.

    2011-12-01

    Sugar kelp ( Saccharina latissima) forests have an important ecological function in the coastal zone, as they inhabit a high number and a specific composition of fauna. In 2002, a large-scale disappearance of sugar kelp was observed in Skagerrak and parts of the south-western coast of Norway, and the perennial sugar kelp forests were replaced by opportunistic and ephemeral filamentous algae. For management purposes, including identifying areas for restoration initiatives, maps of where sugar kelp forests are supposed to be found and where and under what conditions they have disappeared are needed. Based on modelled and field-measured geophysical variables and presence/absence/loss data of sugar kelp, we therefore developed spatial predictive probability models (i.e. maps) for sugar kelp potential distribution under natural conditions and areas of kelp loss. The influence of geophysical factors was analysed using generalized additive models (GAMs). Using the Akaike Information Criterion (AIC) for model selection, we found that wave exposure, depth, light exposure and slope best explained the potential distribution of sugar kelp. Areas of sugar kelp disappearance were identified by the combined effect of wave and light exposure. These models were developed into maps presented to the managers.

  20. Modelling habitat preference and estimating the spatial distribution of Australian Sea Lions (Neophoca cinerea); "A first exploration "

    NARCIS (Netherlands)

    Aarts, G.M.; Brasseur, S.M.J.M.

    2008-01-01

    Managing the Australian sea lion (Neophoca cinerea) population and mitigating its interactions with commercial fisheries, requires an understanding of their spatial distribution and habitat preference at sea. Numerous wildlife telemetry devices have been attached to individual seals from different

  1. Predicting wildfire occurrence distribution with spatial point process models and its uncertainty assessment: a case study in the Lake Tahoe Basin, USA

    Science.gov (United States)

    Jian Yang; Peter J. Weisberg; Thomas E. Dilts; E. Louise Loudermilk; Robert M. Scheller; Alison Stanton; Carl Skinner

    2015-01-01

    Strategic fire and fuel management planning benefits from detailed understanding of how wildfire occurrences are distributed spatially under current climate, and from predictive models of future wildfire occurrence given climate change scenarios. In this study, we fitted historical wildfire occurrence data from 1986 to 2009 to a suite of spatial point process (SPP)...

  2. Fluvial Transport Model from Spatial Distribution Analysis of Libyan Desert Glass Mass on the Great Sand Sea (Southwest Egypt: Clues to Primary Glass Distribution

    Directory of Open Access Journals (Sweden)

    Nancy Jimenez-Martinez

    2015-04-01

    Full Text Available Libyan Desert Glass (LDG is a natural silica-rich melted rock found as pieces scattered over the sand and bedrock of the Western Desert of Egypt, northeast of the Gilf Kebir. In this work, a population mixture analysis serves to relate the present spatial distribution of LDG mass density with the Late Oligocene–Early Miocene fluvial dynamics in the Western Desert of Egypt. This was verified from a spatial distribution model that was predicted from the log-normal kriging method using the LDG–mass-dependent transformed variable, Y(x. Both low- and high-density normal populations (–9.2 < Y(x < –3.5 and –3.8 < Y(x < 2.1, respectively were identified. The low-density population was the result of an ordinary fluvial LDG transport/deposition sequence that was active from the time of the melting process, and which lasted until the end of activity of the Gilf River. The surface distribution of the high-density population allowed us to restrict the source area of the melting process. We demonstrate the importance of this geostatistical study in unveiling the probable location of the point where the melting of surficial material occurred and the role of the Gilf River in the configuration of the observed strewn field.

  3. Spatial Streamflow Forecasting in a Large River Basin in Northwestern Mexico using a Fully-distributed Hydrologic Model

    Science.gov (United States)

    Robles-Morua, A.; Vivoni, E. R.; Mayer, A. S.

    2010-12-01

    Spatial forecasting of streamflows in large watersheds in northwest Mexico is a challenge due to limited stream gauge stations and the high spatiotemporal variability of precipitation and landscape characteristics. To adequately manage water resources in this region, it is important to understand the spatiotemporal variability of streamflows. In this study, a distributed hydrologic model, the TIN-Based Real Time Basin Simulator (tRIBS), was parameterized to generate estimates of streamflow as they relate to rainfall variability and landscape characteristics in the Rio Sonora (~ 9,500 km2) in northwest Mexico. Our distributed approach divided the watershed into 291 un-gauged subbasins (92% of total basin area). For each subbasin, tRIBS was forced using sparse ground observations from June 1, 2007 to May 31, 2008. To improve the model forcing, we explored the use of the North American Land Data Assimilation System (NLDAS) as an alternative method. Our simulations included spatiotemporal forcing from: (1) a sparse network of ground-based stations (hourly resolution), (2) raw model products (12 km pixel, hourly resolution) from NLDAS, and (3) the NLDAS product adjusted using available ground data. Simulations for the ungauged sub-basins were coupled to a Muskingum-Cunge model that routed the resulting streamflows to the watershed outlet for comparison with the only available stream gauge. Our continuous simulations provide spatially distributed estimates of streamflow, which allowed distinguishing regions with different contributions to the main stem of the river. Comparisons between the simulations illustrate the impact of different rainfall forcings on the overall magnitude of streamflow estimates. Ground-based forcings typically overestimate streamflow predictions in the northern regions of the basin relative to the adjusted NLDAS dataset. Furthermore, we explore the relationship between the spatiotemporal variability of runoff generation mechanisms and landscape

  4. Application of the MacCormack scheme to overland flow routing for high-spatial resolution distributed hydrological model

    Science.gov (United States)

    Zhang, Ling; Nan, Zhuotong; Liang, Xu; Xu, Yi; Hernández, Felipe; Li, Lianxia

    2018-03-01

    Although process-based distributed hydrological models (PDHMs) are evolving rapidly over the last few decades, their extensive applications are still challenged by the computational expenses. This study attempted, for the first time, to apply the numerically efficient MacCormack algorithm to overland flow routing in a representative high-spatial resolution PDHM, i.e., the distributed hydrology-soil-vegetation model (DHSVM), in order to improve its computational efficiency. The analytical verification indicates that both the semi and full versions of the MacCormack schemes exhibit robust numerical stability and are more computationally efficient than the conventional explicit linear scheme. The full-version outperforms the semi-version in terms of simulation accuracy when a same time step is adopted. The semi-MacCormack scheme was implemented into DHSVM (version 3.1.2) to solve the kinematic wave equations for overland flow routing. The performance and practicality of the enhanced DHSVM-MacCormack model was assessed by performing two groups of modeling experiments in the Mercer Creek watershed, a small urban catchment near Bellevue, Washington. The experiments show that DHSVM-MacCormack can considerably improve the computational efficiency without compromising the simulation accuracy of the original DHSVM model. More specifically, with the same computational environment and model settings, the computational time required by DHSVM-MacCormack can be reduced to several dozen minutes for a simulation period of three months (in contrast with one day and a half by the original DHSVM model) without noticeable sacrifice of the accuracy. The MacCormack scheme proves to be applicable to overland flow routing in DHSVM, which implies that it can be coupled into other PHDMs for watershed routing to either significantly improve their computational efficiency or to make the kinematic wave routing for high resolution modeling computational feasible.

  5. Spatial modeling to project Southern Appalachian Trout distribution in warmer climate

    Science.gov (United States)

    Patrica A. Flebbe; Laura D. Roghair; Jennifer L. Bruggink

    2006-01-01

    In the southern Appalachian Mountains, the distributions of native brook trout Salvelinus fontinalis and introduced rainbow trout Oncorhynchus mykiss and brown trout Salmo trutta are presently limited by temperature and are expected to be limited further by a warmer climate. To estimate trout habitat in a future...

  6. Analysing the distribution of synaptic vesicles using a spatial point process model

    DEFF Research Database (Denmark)

    Khanmohammadi, Mahdieh; Waagepetersen, Rasmus; Nava, Nicoletta

    2014-01-01

    Stress can affect the brain functionality in many ways. As the synaptic vesicles have a major role in nervous signal transportation in synapses, their distribution in relationship to the active zone is very important in studying the neuron responses. We study the effect of stress on brain functio...

  7. Resolving structural errors in a spatially distributed hydrologic model using ensemble Kalman filter state updates

    NARCIS (Netherlands)

    Spaaks, J.H.; Bouten, W.

    2013-01-01

    In hydrological modeling, model structures are developed in an iterative cycle as more and different types of measurements become available and our understanding of the hillslope or watershed improves. However, with increasing complexity of the model, it becomes more and more difficult to detect

  8. Advances in the spatially distributed ages-w model: parallel computation, java connection framework (JCF) integration, and streamflow/nitrogen dynamics assessment

    Science.gov (United States)

    AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic and water quality (H/WQ) simulation components under the Java Connection Framework (JCF) and the Object Modeling System (OMS) environmental modeling framework. AgES-W is implicitly scala...

  9. Characterizing the spatial distribution of ambient ultrafine particles in Toronto, Canada: A land use regression model.

    Science.gov (United States)

    Weichenthal, Scott; Van Ryswyk, Keith; Goldstein, Alon; Shekarrizfard, Maryam; Hatzopoulou, Marianne

    2016-01-01

    Exposure models are needed to evaluate the chronic health effects of ambient ultrafine particles (bus routes as well as variables for the number of on-street trees, parks, open space, and the length of bus routes within a 100 m buffer. There was no systematic difference between measured and predicted values when the model was evaluated in an external dataset, although the R(2) value decreased (R(2) = 50%). This model will be used to evaluate the chronic health effects of UFPs using population-based cohorts in the Toronto area. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

  10. Spatial Distribution of Volcanic Hotspots and Paterae on Io: Implications for Tidal Heating Models and Magmatic Pathways

    Science.gov (United States)

    Hamilton, C. W.; Beggan, C. D.; Lopes, R.; Williams, D. A.; Radenbaugh, J.

    2011-01-01

    Io, the innermost of Jupiter's Galilean satellites, is the most volcanically active body in the Solar. System. Io's global mean heat flow is approximately 2 W/square m, which is approximately 20 times larger than on Earth. High surface temperatures concentrate within "hotspots" and, to date, 172 Ionian hotspots have been identified by spacecraft and Earth-based telescopes. The Laplace resonance between Io, Europa, and Ganymede maintains these satellites in noncircular orbits and causes displacement of their tidal bulges as the overhead position of Jupiter changes for each moon. Gravitational interactions between Jupiter and Io dominate the orbital evolution of the Laplacian system and generate enormous heat within to as tidal energy is dissipated. If this energy were transferred out of Io at the same rate as it is generated, then the associated surface heat flux would be 2.24 +/- 0.45 W/square m. This estimate is in good agreement with observed global heat flow, but to better constrain tidal dissipation mechanisms and infer how thermal energy is transferred to Io's surface, it is critical to closely examine the spatial distribution of volcanic features. End-member tidal dissipation models either consider that heating occurs completely in the mantle, or completely in the asthenosphere. Mixed models typically favor one-third mantle and two-thirds asthenosphere heating. Recent models also consider the effects of mantle-asthenosphere boundary permeability and asthenospheric instabilities. Deep-mantle heating models predict maximum surface heat flux near the poles, whereas asthenosphere heating models predict maxima near the equator-particularly in the Sub-Jovian and Anti-Jovian hemispheres, with smaller maxima occurring at orbit tangent longitudes. Previous studies have examined the global distribution of Ionian hotspots and patera (i.e., irregular or complex craters with scalloped edges that are generally interpreted to be volcanic calderas), but in this study, we

  11. Modeling the Spatial Distribution of Eshnan (seidlitzia Rosmarinus) Shrubs to Exploring Their Ecological Interactions in Drylands of Central Iran

    Science.gov (United States)

    Erfanifard, Y.; Khosravi, E.

    2015-12-01

    Evaluating the interactions of woody plants has been a major research topic of ecological investigations in arid ecosystems. Plant-plant interactions can shift from positive (facilitation) to negative (competition) depending on levels of environmental stress and determine the spatial pattern of plants. The spatial distribution analysis of plants via different summary statistics can reveal the interactions of plants and how they influence one another. An aggregated distribution indicates facilitative interactions among plants, while dispersion of species reflects their competition for scarce resources. This study was aimed to explore the intraspecific interactions of eshnan (Seidlitzia rosmarinus) shrubs in arid lands, central Iran, using different summary statistics (i.e., pair correlation function g(r), O-ring function O(r), nearest neighbour distribution function D(r), spherical contact distribution function Hs(r)). The observed pattern of shrubs showed significant spatial heterogeneity as compared to inhomogeneous Poisson process (α=0.05). The results of g(r) and O(r) revealed the significant aggregation of eshnan shrubs up to scale of 3 m (α=0.05). The results of D(r) and Hs(r) also showed that maximum distance to nearest shrub was 6 m and the distribution of the sizes of gaps was significantly different from random distribution up to this spatial scale. In general, it was concluded that there were positive interactions between eshnan shrubs at small scales and they were aggregated due to their intraspecific facilitation effects in the study area.

  12. MODELING THE SPATIAL DISTRIBUTION OF ESHNAN (SEIDLITZIA ROSMARINUS SHRUBS TO EXPLORING THEIR ECOLOGICAL INTERACTIONS IN DRYLANDS OF CENTRAL IRAN

    Directory of Open Access Journals (Sweden)

    Y. Erfanifard

    2015-12-01

    Full Text Available Evaluating the interactions of woody plants has been a major research topic of ecological investigations in arid ecosystems. Plant-plant interactions can shift from positive (facilitation to negative (competition depending on levels of environmental stress and determine the spatial pattern of plants. The spatial distribution analysis of plants via different summary statistics can reveal the interactions of plants and how they influence one another. An aggregated distribution indicates facilitative interactions among plants, while dispersion of species reflects their competition for scarce resources. This study was aimed to explore the intraspecific interactions of eshnan (Seidlitzia rosmarinus shrubs in arid lands, central Iran, using different summary statistics (i.e., pair correlation function g(r, O-ring function O(r, nearest neighbour distribution function D(r, spherical contact distribution function Hs(r. The observed pattern of shrubs showed significant spatial heterogeneity as compared to inhomogeneous Poisson process (α=0.05. The results of g(r and O(r revealed the significant aggregation of eshnan shrubs up to scale of 3 m (α=0.05. The results of D(r and Hs(r also showed that maximum distance to nearest shrub was 6 m and the distribution of the sizes of gaps was significantly different from random distribution up to this spatial scale. In general, it was concluded that there were positive interactions between eshnan shrubs at small scales and they were aggregated due to their intraspecific facilitation effects in the study area.

  13. SPATIAL-TEMPORAL DISTRIBUTION OF WATERBORNE INFECTIOUS DISEASE RISK USING THE HYDRAULIC MODEL AND OUTPATIENT DATA

    Science.gov (United States)

    Amano, Ayako; Sakuma, Taisuke; Kazama, So

    This study evaluated waterborne infectious diseases risk and incidence rate around Phonm Penh in Cambodia. We use the hydraulic flood simulation, coliform bacterium diffusion model, dose-response model and outpatient data for quantitative analysis. The results obtained are as follows; 1. The incidence (incidence rate) of diarrhea as water borne diseases risk is 0.14 million people (9%) in the inundation area. 2. The residents in the inundation area are exposed up to 4 times as high risk as daily mean calculated by the integrated model combined in the regional scale. 3.The infectious disease risk due to floods and inundation indicated is effective as an element to explain the risk. The scenario explains 34% number of patient estimated by the outpatient data.

  14. Modelling distribution of archaeological settlement evidence based on heterogeneous spatial and temporal data

    Czech Academy of Sciences Publication Activity Database

    Demján, P.; Dreslerová, Dagmar

    2016-01-01

    Roč. 69, May (2016), s. 100-109 ISSN 0305-4403 Institutional support: RVO:67985912 Keywords : settlement density * evidence density estimation * predictive modelling * prehistory * large datasets Subject RIV: AC - Archeology, Anthropology, Ethnology Impact factor: 2.602, year: 2016

  15. Spatial Distribution of Market Centers

    Directory of Open Access Journals (Sweden)

    Md. Morshedul Islam

    2018-03-01

    Full Text Available The present study is an attempt to find the location pattern, distribution and their sphere of influences of market centers in Rangpur City Corporation, Bangladesh. Rangpur is facing some problems like a traffic jam, noisy environment, population pressure etc due to the over population in full day long in the center of this city, all of the whole sale and retail sale markets are located in the middle. Location of Market is always influencing the daily life of the city population who are directly or indirectly connected with the market. If the market strategically distributed in an area they don’t face such kind of problems. Analysis or investigation shows that at about all of the market centers are located in the center of Rangpur and in the residential area of Rangpur. The maximum 67% market centers are found in the high-income residential area. Rangpur City Corporation, Bangladesh Bureau of Statistics and survey of Bangladesh provided the maps, reports and relevant documents of the study. The spatial dispersion pattern of market centers is clustered together at one place 0.33(Nearest Neighbor Index value, R found in the study area. Geographical Information System (GIS and other software also used to analyze the maps and diagrams. Investigation refers that, the market of Rangpur city have a clustered pattern and different levels of market centers found on the bases of centrality scores. By this centrality scores or levels, found the variation of influencing spheres of market centers in Rangpur City.

  16. Combined statistical and spatially distributed hydrological model for evaluating future drought indices in Virginia

    Directory of Open Access Journals (Sweden)

    Hyunwoo Kang

    2017-08-01

    New hydrological insights for the region: The results of the ensemble mean of SSI indicated that there was an overall increase in agricultural drought occurrences projected in the New (>1.3 times and Rappahannock (>1.13 times river basins due to increases in evapotranspiration and surface and groundwater flow. However, MSDI and MPDSI exhibited a decrease in projected future drought, despite increases in precipitation, which suggests that it is essential to use hybrid-modeling approaches and to interpret application-specific drought indices that consider both precipitation and temperature changes.

  17. Calculation of spatial distribution of optical escape factor and its application to He I collisional-radiative model

    International Nuclear Information System (INIS)

    Iida, Yohei; Kado, Shinichiro; Tanaka, Satoru

    2010-01-01

    An integral analytical formula for a spatial distribution of the optical escape factor (OEF) in an infinite cylindrical plasma is derived as a function of an arbitrary upper state spatial density profile, the temperature ratio of the upper state to the lower state, and the optical depth of the corresponding transition. Test calculations are carried out for three different upper state profiles, i.e., uniform (rectangular), parabolic, and Gaussian upper state profiles. The OEF takes on negative values at the periphery of the parabolic and Gaussian upper state profiles. These characteristics cannot be expressed by the conventional OEF formulas derived for the center of the plasma, even though the optical depth is increased. In addition to the analytical derivation of the formula, two practical formulas are proposed: an empirical formula of the spatial distribution of the OEF for the Gaussian upper state density profile and a linear formula of the OEF distribution for upper state profiles that are expressed as linear combinations. These formulas enable us to calculate the spatial distribution of the OEF for the multiple-Gaussian upper state profile without the need for time-consuming integral calculations.

  18. Ecological and spatial modeling : mapping ecosystems, landscape changes, and plant species distribution in Llanos del Orinoco, Venezuela

    NARCIS (Netherlands)

    Moreno, E.J.C.

    2007-01-01

    The transformation of Llanos del Orinoco, focused on the flooding savanna, is evaluated in terms of the change and replacement of the savanna ecosystem and the plant species distribution under a Landscape Ecological approach. This research is carried out at three spatial scales: sub-continental,

  19. Contribution of topographically based landslide hazard modelling to the analysis of the spatial distribution and ecology of kauri

    NARCIS (Netherlands)

    Claessens, L.F.G.; Verburg, P.H.; Schoorl, J.M.; Veldkamp, A.

    2006-01-01

    In this paper the use of topographical attributes for the analysis of the spatial distribution and ecological cycle of kauri (Agathis australis), a canopy emergent conifer tree from northern New Zealand, is studied. Several primary and secondary topographical attributes are derived from a Digital

  20. Hierarchical species distribution models

    Science.gov (United States)

    Hefley, Trevor J.; Hooten, Mevin B.

    2016-01-01

    Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.

  1. Impact of rainfall spatial distribution on rainfall-runoff modelling efficiency and initial soil moisture conditions estimation

    Directory of Open Access Journals (Sweden)

    Y. Tramblay

    2011-01-01

    Full Text Available A good knowledge of rainfall is essential for hydrological operational purposes such as flood forecasting. The objective of this paper was to analyze, on a relatively large sample of flood events, how rainfall-runoff modeling using an event-based model can be sensitive to the use of spatial rainfall compared to mean areal rainfall over the watershed. This comparison was based not only on the model's efficiency in reproducing the flood events but also through the estimation of the initial conditions by the model, using different rainfall inputs. The initial conditions of soil moisture are indeed a key factor for flood modeling in the Mediterranean region. In order to provide a soil moisture index that could be related to the initial condition of the model, the soil moisture output of the Safran-Isba-Modcou (SIM model developed by Météo-France was used. This study was done in the Gardon catchment (545 km2 in South France, using uniform or spatial rainfall data derived from rain gauge and radar for 16 flood events. The event-based model considered combines the SCS runoff production model and the Lag and Route routing model. Results show that spatial rainfall increases the efficiency of the model. The advantage of using spatial rainfall is marked for some of the largest flood events. In addition, the relationship between the model's initial condition and the external predictor of soil moisture provided by the SIM model is better when using spatial rainfall, in particular when using spatial radar data with R2 values increasing from 0.61 to 0.72.

  2. Modelling the spatial distribution of Fasciola hepatica in bovines using decision tree, logistic regression and GIS query approaches for Brazil.

    Science.gov (United States)

    Bennema, S C; Molento, M B; Scholte, R G; Carvalho, O S; Pritsch, I

    2017-11-01

    Fascioliasis is a condition caused by the trematode Fasciola hepatica. In this paper, the spatial distribution of F. hepatica in bovines in Brazil was modelled using a decision tree approach and a logistic regression, combined with a geographic information system (GIS) query. In the decision tree and the logistic model, isothermality had the strongest influence on disease prevalence. Also, the 50-year average precipitation in the warmest quarter of the year was included as a risk factor, having a negative influence on the parasite prevalence. The risk maps developed using both techniques, showed a predicted higher prevalence mainly in the South of Brazil. The prediction performance seemed to be high, but both techniques failed to reach a high accuracy in predicting the medium and high prevalence classes to the entire country. The GIS query map, based on the range of isothermality, minimum temperature of coldest month, precipitation of warmest quarter of the year, altitude and the average dailyland surface temperature, showed a possibility of presence of F. hepatica in a very large area. The risk maps produced using these methods can be used to focus activities of animal and public health programmes, even on non-evaluated F. hepatica areas.

  3. Global distribution and sources of dissolved inorganic nitrogen export to the coastal zone: Results from a spatially explicit, global model

    NARCIS (Netherlands)

    Dumont, E.L.; Harrison, J.A.; Kroeze, C.; Bakker, E.J.; Seitzinger, S.P.

    2005-01-01

    Here we describe, test, and apply a spatially explicit, global model for predicting dissolved inorganic nitrogen (DIN) export by rivers to coastal waters (NEWS-DIN). NEWS-DIN was developed as part of an internally consistent suite of global nutrient export models. Modeled and measured DIN export

  4. Spatial distribution maps for benthic communities

    DEFF Research Database (Denmark)

    Sørensen, Per S.

    1999-01-01

    simulation, Markov random fields and Boolean models. Geostatistical simulation provides a means of assessing the variability of random field functionals such as the estimated distribution area of a benthic species. The Markov random field allows the spatial distribution of the benthic communities...... to be modelled as a less smooth or regular phenomena than assumed when using geostatistical models. The use of Markov random fields in a Markov chain Monte Carlo simulation framework enables an alternative means of assessing variability of image functionals that is based on a sound theoretical basis......-scan sonar for mapping of benthic communities remains an open task to be studied in the future. The data processing methodology developed is a contribution to the emerging field of hydroacoustic marine biology. The method of penalised maximum pseudo-likelihood for estimation of the Ising model under a huge...

  5. Spatial cluster modelling

    CERN Document Server

    Lawson, Andrew B

    2002-01-01

    Research has generated a number of advances in methods for spatial cluster modelling in recent years, particularly in the area of Bayesian cluster modelling. Along with these advances has come an explosion of interest in the potential applications of this work, especially in epidemiology and genome research. In one integrated volume, this book reviews the state-of-the-art in spatial clustering and spatial cluster modelling, bringing together research and applications previously scattered throughout the literature. It begins with an overview of the field, then presents a series of chapters that illuminate the nature and purpose of cluster modelling within different application areas, including astrophysics, epidemiology, ecology, and imaging. The focus then shifts to methods, with discussions on point and object process modelling, perfect sampling of cluster processes, partitioning in space and space-time, spatial and spatio-temporal process modelling, nonparametric methods for clustering, and spatio-temporal ...

  6. A tutorial on Palm distributions for spatial point processes

    DEFF Research Database (Denmark)

    Coeurjolly, Jean-Francois; Møller, Jesper; Waagepetersen, Rasmus Plenge

    2017-01-01

    This tutorial provides an introduction to Palm distributions for spatial point processes. Initially, in the context of finite point processes, we give an explicit definition of Palm distributions in terms of their density functions. Then we review Palm distributions in the general case. Finally, we...... discuss some examples of Palm distributions for specific models and some applications....

  7. Spatial prediction of Lactarius deliciosus and Lactarius salmonicolor mushroom distribution with logistic regression models in the Kızılcasu Planning Unit, Turkey.

    Science.gov (United States)

    Mumcu Kucuker, Derya; Baskent, Emin Zeki

    2015-01-01

    Integration of non-wood forest products (NWFPs) into forest management planning has become an increasingly important issue in forestry over the last decade. Among NWFPs, mushrooms are valued due to their medicinal, commercial, high nutritional and recreational importance. Commercial mushroom harvesting also provides important income to local dwellers and contributes to the economic value of regional forests. Sustainable management of these products at the regional scale requires information on their locations in diverse forest settings and the ability to predict and map their spatial distributions over the landscape. This study focuses on modeling the spatial distribution of commercially harvested Lactarius deliciosus and L. salmonicolor mushrooms in the Kızılcasu Forest Planning Unit, Turkey. The best models were developed based on topographic, climatic and stand characteristics, separately through logistic regression analysis using SPSS™. The best topographic model provided better classification success (69.3 %) than the best climatic (65.4 %) and stand (65 %) models. However, the overall best model, with 73 % overall classification success, used a mix of several variables. The best models were integrated into an Arc/Info GIS program to create spatial distribution maps of L. deliciosus and L. salmonicolor in the planning area. Our approach may be useful to predict the occurrence and distribution of other NWFPs and provide a valuable tool for designing silvicultural prescriptions and preparing multiple-use forest management plans.

  8. Revised spatially distributed global livestock emissions

    Science.gov (United States)

    Asrar, G.; Wolf, J.; West, T. O.

    2015-12-01

    Livestock play an important role in agricultural carbon cycling through consumption of biomass and emissions of methane. Quantification and spatial distribution of methane and carbon dioxide produced by livestock is needed to develop bottom-up estimates for carbon monitoring. These estimates serve as stand-alone international emissions estimates, as input to global emissions modeling, and as comparisons or constraints to flux estimates from atmospheric inversion models. Recent results for the US suggest that the 2006 IPCC default coefficients may underestimate livestock methane emissions. In this project, revised coefficients were calculated for cattle and swine in all global regions, based on reported changes in body mass, quality and quantity of feed, milk production, and management of living animals and manure for these regions. New estimates of livestock methane and carbon dioxide emissions were calculated using the revised coefficients and global livestock population data. Spatial distribution of population data and associated fluxes was conducted using the MODIS Land Cover Type 5, version 5.1 (i.e. MCD12Q1 data product), and a previously published downscaling algorithm for reconciling inventory and satellite-based land cover data at 0.05 degree resolution. Preliminary results for 2013 indicate greater emissions than those calculated using the IPCC 2006 coefficients. Global total enteric fermentation methane increased by 6%, while manure management methane increased by 38%, with variation among species and regions resulting in improved spatial distributions of livestock emissions. These new estimates of total livestock methane are comparable to other recently reported studies for the entire US and the State of California. These new regional/global estimates will improve the ability to reconcile top-down and bottom-up estimates of methane production as well as provide updated global estimates for use in development and evaluation of Earth system models.

  9. Application of land use regression modelling to assess the spatial distribution of road traffic noise in three European cities.

    Science.gov (United States)

    Aguilera, Inmaculada; Foraster, Maria; Basagaña, Xavier; Corradi, Elisabetta; Deltell, Alexandre; Morelli, Xavier; Phuleria, Harish C; Ragettli, Martina S; Rivera, Marcela; Thomasson, Alexandre; Slama, Rémy; Künzli, Nino

    2015-01-01

    Noise prediction models and noise maps are used to estimate the exposure to road traffic noise, but their availability and the quality of the noise estimates is sometimes limited. This paper explores the application of land use regression (LUR) modelling to assess the long-term intraurban spatial variability of road traffic noise in three European cities. Short-term measurements of road traffic noise taken in Basel, Switzerland (n=60), Girona, Spain (n=40), and Grenoble, France (n=41), were used to develop two LUR models: (a) a "GIS-only" model, which considered only predictor variables derived with Geographic Information Systems; and (b) a "Best" model, which in addition considered the variables collected while visiting the measurement sites. Both noise measurements and noise estimates from LUR models were compared with noise estimates from standard noise models developed for each city by the local authorities. Model performance (adjusted R(2)) was 0.66-0.87 for "GIS-only" models, and 0.70-0.89 for "Best" models. Short-term noise measurements showed a high correlation (r=0.62-0.78) with noise estimates from the standard noise models. LUR noise estimates did not show any systematic differences in the spatial patterns when compared with those from standard noise models. LUR modelling with accurate GIS source data can be a promising tool for noise exposure assessment with applications in epidemiological studies.

  10. Spatial patterns of distribution, abundance, and species diversity of small odontocetes estimated using density surface modeling with line transect sampling

    Science.gov (United States)

    Kanaji, Yu; Okazaki, Makoto; Miyashita, Tomio

    2017-06-01

    Spatial patterns of distribution, abundance, and species diversity of small odontocetes including species in the Delphinidae and Phocoenidae families were investigated using long-term dedicated sighting survey data collected between 1983 and 2006 in the North Pacific. Species diversity indices were calculated from abundance estimated using density surface modeling of line-transect data. The estimated abundance ranged from 19,521 individuals in killer whale to 1,886,022 in pantropical spotted dolphin. The predicted density maps showed that the habitats of small odontocetes corresponded well with distinct oceanic domains. Species richness was estimated to be highest between 30 and 40°N where warm- and cold-water currents converge. Simpson's Diversity Index showed latitudinal diversity gradients of decreasing species numbers toward the poles. Higher diversity was also estimated in the coastal areas and the zonal areas around 35-42°N. Coastal-offshore gradients and latitudinal gradients are known for many taxa. The zonal areas around 35°N and 40°N coincide with the Kuroshio Current and its extension and the subarctic boundary, respectively. These results suggest that the species diversity of small odontocetes primarily follows general patterns of latitudinal and longitudinal gradients, while the confluence of faunas originating in distinct water masses increases species diversify in frontal waters around 30-40°N. Population densities tended to be higher for the species inhabiting higher latitudes, but were highest for intermediate latitudes at approximately 35-40°N. According to latitudinal gradients in water temperature and biological productivity, the costs for thermoregulation will decrease in warmer low latitudes, while feeding efficiency will increase in colder high latitudes. These trade-offs could optimize population density in intermediate latitudes.

  11. Species Distribution Modelling

    DEFF Research Database (Denmark)

    Gomes, Vitor H. F.; Ijff, Stephanie D.; Raes, Niels

    2018-01-01

    Species distribution models (SDMs) are widely used in ecology and conservation. Presence-only SDMs such as MaxEnt frequently use natural history collections (NHCs) as occurrence data, given their huge numbers and accessibility. NHCs are often spatially biased which may generate inaccuracies in SD...

  12. 4D-SAS: A Distributed Dynamic-Data Driven Simulation and Analysis System for Massive Spatial Agent-Based Modeling

    Directory of Open Access Journals (Sweden)

    Zhenqiang Li

    2016-03-01

    Full Text Available Significant computation challenges are emerging as agent-based modeling becomes more complicated and dynamically data-driven. In this context, parallel simulation is an attractive solution when dealing with massive data and computation requirements. Nearly all the available distributed simulation systems, however, do not support geospatial phenomena modeling, dynamic data injection, and real-time visualization. To tackle these problems, we propose a distributed dynamic-data driven simulation and analysis system (4D-SAS specifically for massive spatial agent-based modeling to support real-time representation and analysis of geospatial phenomena. To accomplish large-scale geospatial problem-solving, the 4D-SAS system was spatially enabled to support geospatial model development and employs high-performance computing to improve simulation performance. It can automatically decompose simulation tasks and distribute them among computing nodes following two common schemes: order division or spatial decomposition. Moreover, it provides streaming channels and a storage database to incorporate dynamic data into simulation models; updating agent context in real-time. A new online visualization module was developed based on a GIS mapping library, SharpMap, for an animated display of model execution to help clients understand the model outputs efficiently. To evaluate the system’s efficiency and scalability, two different spatially explicitly agent-based models, an en-route choice model, and a forest fire propagation model, were created on 4D-SAS. Simulation results illustrate that 4D-SAS provides an efficient platform for dynamic data-driven geospatial modeling, e.g., both discrete multi-agent simulation and grid-based cellular automata, demonstrating efficient support for massive parallel simulation. The parallel efficiency of the two models is above 0.7 and remains nearly stable in our experiments.

  13. Producing Distribution Maps for a Spatially-Explicit Ecosystem Model Using Large Monitoring and Environmental Databases and a Combination of Interpolation and Extrapolation

    Directory of Open Access Journals (Sweden)

    Arnaud Grüss

    2018-01-01

    Full Text Available To be able to simulate spatial patterns of predator-prey interactions, many spatially-explicit ecosystem modeling platforms, including Atlantis, need to be provided with distribution maps defining the annual or seasonal spatial distributions of functional groups and life stages. We developed a methodology combining extrapolation and interpolation of the predictions made by statistical habitat models to produce distribution maps for the fish and invertebrates represented in the Atlantis model of the Gulf of Mexico (GOM Large Marine Ecosystem (LME (“Atlantis-GOM”. This methodology consists of: (1 compiling a large monitoring database, gathering all the fisheries-independent and fisheries-dependent data collected in the northern (U.S. GOM since 2000; (2 compiling a large environmental database, storing all the environmental parameters known to influence the spatial distribution patterns of fish and invertebrates of the GOM; (3 fitting binomial generalized additive models (GAMs to the large monitoring and environmental databases, and geostatistical binomial generalized linear mixed models (GLMMs to the large monitoring database; and (4 employing GAM predictions to infer spatial distributions in the southern GOM, and GLMM predictions to infer spatial distributions in the U.S. GOM. Thus, our methodology allows for reasonable extrapolation in the southern GOM based on a large amount of monitoring and environmental data, and for interpolation in the U.S. GOM accurately reflecting the probability of encountering fish and invertebrates in that region. We used an iterative cross-validation procedure to validate GAMs. When a GAM did not pass the validation test, we employed a GAM for a related functional group/life stage to generate distribution maps for the southern GOM. In addition, no geostatistical GLMMs were fit for the functional groups and life stages whose depth, longitudinal and latitudinal ranges within the U.S. GOM are not entirely covered by

  14. Selecting Optimal Random Forest Predictive Models: A Case Study on Predicting the Spatial Distribution of Seabed Hardness.

    Science.gov (United States)

    Li, Jin; Tran, Maggie; Siwabessy, Justy

    2016-01-01

    Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia's marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70). We developed optimal predictive models to predict seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), knowledge informed AVI (KIAVI), Boruta and regularized RF (RRF) were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness of four classes can be predicted with a high degree of accuracy; 3) the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5) FS methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to 'small p and large n' problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and

  15. Selecting Optimal Random Forest Predictive Models: A Case Study on Predicting the Spatial Distribution of Seabed Hardness

    Science.gov (United States)

    Li, Jin; Tran, Maggie; Siwabessy, Justy

    2016-01-01

    Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia’s marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70). We developed optimal predictive models to predict seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), knowledge informed AVI (KIAVI), Boruta and regularized RF (RRF) were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness of four classes can be predicted with a high degree of accuracy; 3) the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5) FS methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to ‘small p and large n’ problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and

  16. Modelling spatial distribution of soil steady state infiltration rate in an urban park (Vingis Parkas, Vilnius, Lithuania)

    Science.gov (United States)

    Pereira, Paulo; Cerda, Artemi; Depellegrin, Daniel; Misiune, Ieva; Bogunovic, Igor; Menchov, Oleksandr

    2016-04-01

    larger urban park in Vilnius, Vinguis Parkas. The studied area is located near the Neris River and occupies an area of approximately 162 hectares. Inside the park a total of 95 randomly points were selected to measure soil steady infiltration, between April and September of 2016. At each sampling point, 4 infiltration measurements were carried out using a cylinder infiltrometer with 15 cm higher and a diameter of 7 cm (Cerda, 1996). Each experiment has the duration of 1 hour and the measurements of the infiltrated water were carried out 1, 2, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55 and 60 minutes (Cerda, 1996). The steady state infiltration value of each sampling point corresponds to the average value of the 4 measurements. In each point, the 4 measurements were separated by 5 meters to take in account the spatial variability (Neris et al., 2013). In total 380 infiltration tests were carried out (95x4). Previous to data modelling, data normality was assessed using the shapiro wilk-test and homogeneity of the variances, using Levene test, respectively. The original data was not normally distributed and, only respected the Gaussian distribution and heteroscedasticity after a logarithmic transformation. Data modelling was carried out using transformed data. The accuracy of steady-state soil infiltration spatial distribution was carried out testing several interpolation methods, as Inverse Distance to a Weight (IDW) with the power of 1,2,3,4 and 5, Local Polynomial methods, with the power of 1 and 2 Radial Basis Functions - Spline With Tension (SPT), Completely Regularized Spline (CRS), Multiquadratic (MTQ), Inverse Multiquadratic (IMTQ) and Thin Plate Spline (TPS) - and Geostatistical methods as, Ordinary Kriging (OK), Simple Kriging (SK) and Universal Kriging (UK) (Pereira et al., 2015). Methods performance was assessed calculating the Root Square Mean Error (RMSE) from the errors obtained from cross-validation. The results showed that on average steady state

  17. Examining spatiotemporal distribution and CPUE-environment relationships for the jumbo flying squid Dosidicus gigas offshore Peru based on spatial autoregressive model

    Science.gov (United States)

    Feng, Yongjiu; Chen, Xinjun; Liu, Yang

    2017-09-01

    The spatiotemporal distribution and relationship between nominal catch-per-unit-effort (CPUE) and environment for the jumbo flying squid (Dosidicus gigas) were examined in offshore Peruvian waters during 2009-2013. Three typical oceanographic factors affecting the squid habitat were investigated in this research, including sea surface temperature (SST), sea surface salinity (SSS) and sea surface height (SSH). We studied the CPUE-environment relationships for D. gigas using a spatially-lagged version of spatial autoregressive (SAR) model and a generalized additive model (GAM), with the latter for auxiliary and comparative purposes. The annual fishery centroids were distributed broadly in an area bounded by 79.5°-82.7°W and 11.9°-17.1°S, while the monthly fishery centroids were spatially close and lay in a smaller area bounded by 81.0°-81.2°W and 14.3°-15.4°S. Our results show that the preferred environmental ranges for D. gigas offshore Peru were 20.9°-21.9°C for SST, 35.16-35.32 for SSS and 27.2-31.5 cm for SSH in the areas bounded by 78°-80°W/82-84°W and 15°-18°S. Monthly spatial distributions during October to December were predicted using the calibrated GAM and SAR models and general similarities were found between the observed and predicted patterns for the nominal CPUE of D. gigas. The overall accuracies for the hotspots generated by the SAR model were much higher than those produced by the GAM model for all three months. Our results contribute to a better understanding of the spatiotemporal distributions of D. gigas offshore Peru, and offer a new SAR modeling method for advancing fishery science.

  18. Spatial analysis of distribution of dengue cases in Espírito Santo, Brazil, in 2010: use of Bayesian model

    Directory of Open Access Journals (Sweden)

    Taizi Honorato

    2014-01-01

    Full Text Available OBJECTIVE: To study the relationship between the risk of dengue and sociodemographic variables through the use of spatial regression models fully Bayesian in the municipalities of Espírito Santo in 2010. METHOD: This is an ecological study and exploration that used spatial analysis tools in preparing thematic maps with data obtained from SinanNet. An analysis by area, taking as unit the municipalities of the state, was performed. Thematic maps were constructed by the computer program R 2.15.00 and Deviance Information Criterion (DIC, calculated in WinBugs, Absolut and Normalized Mean Error (NMAE were the criteria used to compare the models. RESULTS: We were able to geocode 21,933 dengue cases (rate of 623.99 cases per 100 thousand habitants with a higher incidence in the municipalities of Vitória, Serra and Colatina; model with spatial effect with the covariates trash and income showed the best performance at DIC and Nmae criteria. CONCLUSION: It was possible to identify the relationship of dengue with factors outside the health sector and to identify areas with higher risk of disease.

  19. Prediction of spatial distribution for some land use allometric ...

    African Journals Online (AJOL)

    Prediction of spatial distribution for some land use allometric characteristics in land use planning models with geostatistic and Geographical Information System (GIS) (Case study: Boein and Miandasht, Isfahan Province, Iran)

  20. Spatial distribution of thermal energy in equilibrium.

    Science.gov (United States)

    Bar-Sinai, Yohai; Bouchbinder, Eran

    2015-06-01

    The equipartition theorem states that in equilibrium, thermal energy is equally distributed among uncoupled degrees of freedom that appear quadratically in the system's Hamiltonian. However, for spatially coupled degrees of freedom, such as interacting particles, one may speculate that the spatial distribution of thermal energy may differ from the value predicted by equipartition, possibly quite substantially in strongly inhomogeneous or disordered systems. Here we show that for systems undergoing simple Gaussian fluctuations around an equilibrium state, the spatial distribution is universally bounded from above by 1/2k(B)T. We further show that in one-dimensional systems with short-range interactions, the thermal energy is equally partitioned even for coupled degrees of freedom in the thermodynamic limit and that in higher dimensions nontrivial spatial distributions emerge. Some implications are discussed.

  1. A simple daily soil-water balance model for estimating the spatial and temporal distribution of groundwater recharge in temperate humid areas

    Science.gov (United States)

    Dripps, W.R.; Bradbury, K.R.

    2007-01-01

    Quantifying the spatial and temporal distribution of natural groundwater recharge is usually a prerequisite for effective groundwater modeling and management. As flow models become increasingly utilized for management decisions, there is an increased need for simple, practical methods to delineate recharge zones and quantify recharge rates. Existing models for estimating recharge distributions are data intensive, require extensive parameterization, and take a significant investment of time in order to establish. The Wisconsin Geological and Natural History Survey (WGNHS) has developed a simple daily soil-water balance (SWB) model that uses readily available soil, land cover, topographic, and climatic data in conjunction with a geographic information system (GIS) to estimate the temporal and spatial distribution of groundwater recharge at the watershed scale for temperate humid areas. To demonstrate the methodology and the applicability and performance of the model, two case studies are presented: one for the forested Trout Lake watershed of north central Wisconsin, USA and the other for the urban-agricultural Pheasant Branch Creek watershed of south central Wisconsin, USA. Overall, the SWB model performs well and presents modelers and planners with a practical tool for providing recharge estimates for modeling and water resource planning purposes in humid areas. ?? Springer-Verlag 2007.

  2. Spatial and Temporal Distribution of Plasmodium vivax Malaria in Korea Estimated with a Hierarchical Generalized Linear Model.

    Science.gov (United States)

    Noh, Maengseok; Lee, Youngjo; Oh, Seungyoung; Chu, Chaeshin; Gwack, Jin; Youn, Seung-Ki; Cho, Shin Hyeong; Lee, Won Ja; Huh, Sun

    2012-12-01

    The spatial and temporal correlations were estimated to determine Plasmodium vivax malarial transmission pattern in Korea from 2001-2011 with the hierarchical generalized linear model. Malaria cases reported to the Korea Centers for Disease Control and Prevention from 2001 to 2011 were analyzed with descriptive statistics and the incidence was estimated according to age, sex, and year by the hierarchical generalized linear model. Spatial and temporal correlation was estimated and the best model was selected from nine models. Results were presented as diseases map according to age and sex. The incidence according to age was highest in the 20-25-year-old group (244.52 infections/100,000). Mean ages of infected males and females were 31.0 years and 45.3 years with incidences 7.8 infections/100,000 and 7.1 infections/100,000 after estimation. The mean month for infection was mid-July with incidence 10.4 infections/100,000. The best-fit model showed that there was a spatial and temporal correlation in the malarial transmission. Incidence was very low or negligible in areas distant from the demilitarized zone between Republic of Korea and Democratic People's Republic of Korea (North Korea) if the 20-29-year-old male group was omitted in the diseases map. Malarial transmission in a region in Korea was influenced by the incidence in adjacent regions in recent years. Since malaria in Korea mainly originates from mosquitoes from North Korea, there will be continuous decrease if there is no further outbreak in North Korea.

  3. Parameter estimation for a cohesive sediment transport model by assimilating satellite observations in the Hangzhou Bay: Temporal variations and spatial distributions

    Science.gov (United States)

    Wang, Daosheng; Zhang, Jicai; He, Xianqiang; Chu, Dongdong; Lv, Xianqing; Wang, Ya Ping; Yang, Yang; Fan, Daidu; Gao, Shu

    2018-01-01

    Model parameters in the suspended cohesive sediment transport models are critical for the accurate simulation of suspended sediment concentrations (SSCs). Difficulties in estimating the model parameters still prevent numerical modeling of the sediment transport from achieving a high level of predictability. Based on a three-dimensional cohesive sediment transport model and its adjoint model, the satellite remote sensing data of SSCs during both spring tide and neap tide, retrieved from Geostationary Ocean Color Imager (GOCI), are assimilated to synchronously estimate four spatially and temporally varying parameters in the Hangzhou Bay in China, including settling velocity, resuspension rate, inflow open boundary conditions and initial conditions. After data assimilation, the model performance is significantly improved. Through several sensitivity experiments, the spatial and temporal variation tendencies of the estimated model parameters are verified to be robust and not affected by model settings. The pattern for the variations of the estimated parameters is analyzed and summarized. The temporal variations and spatial distributions of the estimated settling velocity are negatively correlated with current speed, which can be explained using the combination of flocculation process and Stokes' law. The temporal variations and spatial distributions of the estimated resuspension rate are also negatively correlated with current speed, which are related to the grain size of the seabed sediments under different current velocities. Besides, the estimated inflow open boundary conditions reach the local maximum values near the low water slack conditions and the estimated initial conditions are negatively correlated with water depth, which is consistent with the general understanding. The relationships between the estimated parameters and the hydrodynamic fields can be suggestive for improving the parameterization in cohesive sediment transport models.

  4. A comparison between modelling for spatial distribution of thaw depths using MODIS datasets and observational data of permafrost in Mongolia

    Science.gov (United States)

    Zorigt, Munkhtsetseg; Alexander, Orkhonselenge; Kwadijk, Jaap; van Beek, Eelco

    2016-04-01

    Thaw and freezing depth and the related variation in the top of the active layer of the permafrost are important variables for studying runoff production in permafrost regions. In this study we provide data on spatially distributed thawing depths in Mongolia based on Kudryavtsev approach. This approach requires land surface temperature (LSTs) and soil physical characteristics for estimating thaw depths. Measured data of ground land surface temperatures is lacking in Mongolia. Therefore, we estimated the LST based on satellite images of surface temperatures. Monthly values of the LSTs were obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) data. Soil physical characteristics are defined by reference values from previous studies (Tumurbaatar, 2004; Anarmaa, 2006). We validated the results by comparing them with the observational data of permafrost boreholes in Mongolia in 2002-2009 CALM, 2009. The results indicate that thaw depths range between 0-14.5 m from southern to northern parts of Mongolia. This study shows that distribution of thaw depths using the MODIS LSTs can indicate a general overview of thaw depths distribution throughout the country.

  5. Modelling the spatial distribution of plaice ( Pleuronectes platessa), sole ( Solea solea) and thornback ray ( Raja clavata) in UK waters for marine management and planning

    Science.gov (United States)

    Maxwell, D. L.; Stelzenmüller, V.; Eastwood, P. D.; Rogers, S. I.

    2009-04-01

    Species distribution maps are needed for ecosystem-based marine management including the development of marine spatial plans. If such maps are based on predictive models then modelling procedures should aim to maximise validation success, and any uncertainty in the predictions needs to be made explicit. We developed a predictive modelling approach to produce robust maps of the distributions of selected marine species at a regional scale. We used 14 years of survey data to map the distributions of plaice, sole and thornback ray in three hydrographic regions comprising parts of the Irish Sea, Celtic Sea and the English Channel with the help of the hybrid technique regression kriging, which combines regression models with geostatistical tools. For each species-region combination we constructed logistic Generalized Linear Models (GLMs) based on presence-absence data using the environmental variables: depth, bottom temperature, bed shear stress and sediment type, as predictors. We selected GLMs using the mean squared error of prediction (MSEP) estimated by cross-validation then conducted a geostatistical analysis of the residuals to incorporate spatial structure in the predictions. In general, we found that species occurrence was positively related to shallow areas, a bed shear stress of between 0 and 1.5 N/m 2, and the presence of sandy sediment. Predicted species occurrence probabilities were in good agreement with survey observations. This modelling framework selects environmental models based on predictive ability and considers the effect of spatial autocorrelation on predictions, together with the simultaneous presentation of observations, associated uncertainties, and predictions. The potential benefit of these distribution maps to marine management and planning is discussed.

  6. Spatial statistics for modeling of abundance and distribution of wildlife species in the Masai Mara ecosystem, Kenya

    NARCIS (Netherlands)

    Khaemba, W.M.; Stein, A.

    2001-01-01

    This study illustrates the use of modern statistical procedures for better wildlife management by addressing three key issues: determination of abundance, modeling of animal distributions and variability of diversity in space and time. Prior information in Markov Chain Monte Carlo (MCMC) methods is

  7. Vineyard weeds control practices impact on surface water transfers: using numerical tracer experiment coupled to a distributed hydrological model to manage agricultural practices spatial arrangements.

    Science.gov (United States)

    Colin, F.; Moussa, R.

    2009-04-01

    In rural basins, agricultural landscape management highly influences water and pollutants transfers. Landuse, agricultural practices and their spatial arrangements are at issue. Hydrological model are widely used to explore impacts of anthropogenic influences on experimental catchments. But planning all spatial arrangements leads to a possible cases count which cannot be considered. On the basis of the recent « numerical experiment » approach, we propose a « numerical tracer function » which had to be coupled to a distributed rainfall-runoff model. This function simulate the transfer of a virtual tracer successively spread on each distributed unit inside the catchment. It allows to rank hydrological spatial units according to their hydrological contribution to the surface flows, particularly at the catchment outlet. It was used with the distributed model MHYDAS in an agricultural context. The case study concerns the experimental Roujan vine-growing catchment (1km², south of France) studied since 1992. In this Mediterranean context, we focus on the soil hydraulic conductivity distributed parameter because it highly depends on weed control practices (chemical weeding induces a lot more runoff than mechanical weeding). We checked model sensitivity analysis to soil hydraulic conductivity spatial arrangement on runoff coefficient, peak discharge and catchment lag-time. Results show (i) the use of the tracer function is more efficient than a random approach to improve sensitivity to spatial arrangements from point of view of simulated discharge range, (ii) the first factor explaining hydrological simulations variability was practices area ratio, (iii) variability induced by practices spatial arrangements was significant on runoff coefficient and peak discharge for balanced practices area ratio and on lag-time for low area ratio of chemical weeding practices. From the actual situation on the experimental Roujan catchment (40% of tilled and 60% of non tilled vineyard

  8. [Distribution of spatial attention in position recognition].

    Science.gov (United States)

    Kumada, T; Kikuchi, T

    1988-06-01

    Spatial limitation in visual information processing was examined with dot-in-matrix patterns by using a probe recognition procedure. The independent variables were the number (1-16 dots) and the position of target dots. Subjects were four undergraduate students. The data were analyzed and discussed from three points of view; span of attention, spatial limitation of recognition and visual attention. The following became clear: First, the span of position recognition was 4.8. Second, "spatial span of attention" was defined as the range of dot positions at which subjects can perceive target dots with 75% or more accuracy. It extended around the fixation point and shrinked with the increase of the number of target dots. Finally, the distribution of spatial attention was estimated for each target dot condition under the assumption that the hit RT at each probe position reflects the amount of attention allocated there. Distributions estimated were cone-shaped, and the height and extent changed with the number of target dots. It was suggested that spatial limitation (i.e. spatial span of attention) in the processing of spatial positions can be explained by the notion of distribution of spatial attention.

  9. Historical reconstruction of spatial distribution of land use/land cover in the early reclaimed time of Northeast China——Based on the HLURM model

    Science.gov (United States)

    Yang, Yuanyuan; Zhang, Shuwen; Liu, Yansui

    2017-04-01

    Understanding long-term human-environment interactions is essential to understanding changes in terrestrial ecosystems and this requires historical reconstruction of past land cover changes. Historical reconstruction of land use/land cover (LULC) aims to reproduce information concerning past land use, not only the quantity of land use/cover in a historical period, but also the spatial distribution. Recently, improved remote sensing technology has made feasible the continuous observation of land cover. However, remotely-sensed data have only existed for the last four decades at most, following the advent of the first land satellite, LandSat-1, launched in 1972. Prior to that, other data sources must be relied on, which may cover the global scale but often inconsistently. In this context, increasing numbers of researchers have made efforts to reconstruct historical LULC based on prime data sources and research approaches. And significant progress in gathering historical land change data has been made both at global and regional scales. However, most of the existing historical LULC reconstructions do not sufficiently meet the requirements of climate assessments due to insufficient spatial and thematic detail and the lack of consideration of various land change types. Most current studies do not thematically represent 100% of the land area, and ignore the consideration of completing land categories and land conversion types. Current research mainly focuses on arable land, wetland and forestland and it does not provide information on land categories such as settlement, water, and other land types. It is a research direction to build historical spatial land use and land cover datasets with high resolution. This paper provides a retrospective overview of historical reconstruction methods of past land-cover based on the prime data sources and research approaches. This research also explored the possibility of building a spatial-explicit modeling framework named HLURM

  10. Hazard tolerance of spatially distributed complex networks

    International Nuclear Information System (INIS)

    Dunn, Sarah; Wilkinson, Sean

    2017-01-01

    In this paper, we present a new methodology for quantifying the reliability of complex systems, using techniques from network graph theory. In recent years, network theory has been applied to many areas of research and has allowed us to gain insight into the behaviour of real systems that would otherwise be difficult or impossible to analyse, for example increasingly complex infrastructure systems. Although this work has made great advances in understanding complex systems, the vast majority of these studies only consider a systems topological reliability and largely ignore their spatial component. It has been shown that the omission of this spatial component can have potentially devastating consequences. In this paper, we propose a number of algorithms for generating a range of synthetic spatial networks with different topological and spatial characteristics and identify real-world networks that share the same characteristics. We assess the influence of nodal location and the spatial distribution of highly connected nodes on hazard tolerance by comparing our generic networks to benchmark networks. We discuss the relevance of these findings for real world networks and show that the combination of topological and spatial configurations renders many real world networks vulnerable to certain spatial hazards. - Highlights: • We develop a method for quantifying the reliability of real-world systems. • We assess the spatial resilience of synthetic spatially distributed networks. • We form algorithms to generate spatial scale-free and exponential networks. • We show how these “synthetic” networks are proxies for real world systems. • Conclude that many real world systems are vulnerable to spatially coherent hazard.

  11. Methods and theory in bone modeling drift: comparing spatial analyses of primary bone distributions in the human humerus.

    Science.gov (United States)

    Maggiano, Corey M; Maggiano, Isabel S; Tiesler, Vera G; Chi-Keb, Julio R; Stout, Sam D

    2016-01-01

    This study compares two novel methods quantifying bone shaft tissue distributions, and relates observations on human humeral growth patterns for applications in anthropological and anatomical research. Microstructural variation in compact bone occurs due to developmental and mechanically adaptive circumstances that are 'recorded' by forming bone and are important for interpretations of growth, health, physical activity, adaptation, and identity in the past and present. Those interpretations hinge on a detailed understanding of the modeling process by which bones achieve their diametric shape, diaphyseal curvature, and general position relative to other elements. Bone modeling is a complex aspect of growth, potentially causing the shaft to drift transversely through formation and resorption on opposing cortices. Unfortunately, the specifics of modeling drift are largely unknown for most skeletal elements. Moreover, bone modeling has seen little quantitative methodological development compared with secondary bone processes, such as intracortical remodeling. The techniques proposed here, starburst point-count and 45° cross-polarization hand-drawn histomorphometry, permit the statistical and populational analysis of human primary tissue distributions and provide similar results despite being suitable for different applications. This analysis of a pooled archaeological and modern skeletal sample confirms the importance of extreme asymmetry in bone modeling as a major determinant of microstructural variation in diaphyses. Specifically, humeral drift is posteromedial in the human humerus, accompanied by a significant rotational trend. In general, results encourage the usage of endocortical primary bone distributions as an indicator and summary of bone modeling drift, enabling quantitative analysis by direction and proportion in other elements and populations. © 2015 Anatomical Society.

  12. Can a one-layer optical skin model including melanin and inhomogeneously distributed blood explain spatially resolved diffuse reflectance spectra?

    Science.gov (United States)

    Karlsson, Hanna; Pettersson, Anders; Larsson, Marcus; Strömberg, Tomas

    2011-02-01

    Model based analysis of calibrated diffuse reflectance spectroscopy can be used for determining oxygenation and concentration of skin chromophores. This study aimed at assessing the effect of including melanin in addition to hemoglobin (Hb) as chromophores and compensating for inhomogeneously distributed blood (vessel packaging), in a single-layer skin model. Spectra from four humans were collected during different provocations using a twochannel fiber optic probe with source-detector separations 0.4 and 1.2 mm. Absolute calibrated spectra using data from either a single distance or both distances were analyzed using inverse Monte Carlo for light transport and Levenberg-Marquardt for non-linear fitting. The model fitting was excellent using a single distance. However, the estimated model failed to explain spectra from the other distance. The two-distance model did not fit the data well at either distance. Model fitting was significantly improved including melanin and vessel packaging. The most prominent effect when fitting data from the larger separation compared to the smaller separation was a different light scattering decay with wavelength, while the tissue fraction of Hb and saturation were similar. For modeling spectra at both distances, we propose using either a multi-layer skin model or a more advanced model for the scattering phase function.

  13. SPATIAL DISTRIBUTION OF POVERTY AT DIFFERENT SCALES

    Directory of Open Access Journals (Sweden)

    Gandhi PAWITAN

    2010-01-01

    Full Text Available Poverty mapping is usually developed from some sources of data, such as from census and survey data. In some practical application, the poverty was measured usually by household income or expenditure of daily basic consumption. Using different scales and zoning on a particular set of spatial data may leads to problems in interpreting the results. In practice, organizations publish statistics and maps at a particular area level. Minot and Baulch (2005a discussed some consequences of using aggregated level data in poverty mapping, which may affect the validity of the output. The key point of this paper is to compare spatial distribution of the poverty at two different scale, which is the province and district level. How the spatial distribution of the poverty at province level can be use to infer the distribution at the district level. The geographical weighted regression will be applied, and the poverty data of Vietnam will be used as an illustration.

  14. Ensemble filter based estimation of spatially distributed parameters in a mesoscale dust model: experiments with simulated and real data

    Directory of Open Access Journals (Sweden)

    V. M. Khade

    2013-03-01

    Full Text Available The ensemble adjustment Kalman filter (EAKF is used to estimate the erodibility fraction parameter field in a coupled meteorology and dust aerosol model (Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS over the Sahara desert. Erodibility is often employed as the key parameter to map dust source. It is used along with surface winds (or surface wind stress to calculate dust emissions. Using the Saharan desert as a test bed, a perfect model Observation System Simulation Experiments (OSSEs with 40 ensemble members, and observations of aerosol optical depth (AOD, the EAKF is shown to recover correct values of erodibility at about 80% of the points in the domain. It is found that dust advected from upstream grid points acts as noise and complicates erodibility estimation. It is also found that the rate of convergence is significantly impacted by the structure of the initial distribution of erodibility estimates; isotropic initial distributions exhibit slow convergence, while initial distributions with geographically localized structure converge more quickly. Experiments using observations of Deep Blue AOD retrievals from the MODIS satellite sensor result in erodibility estimates that are considerably lower than the values used operationally. Verification shows that the use of the tuned erodibility field results in better predictions of AOD over the west Sahara and the Arabian Peninsula.

  15. The use of bivariate spatial modeling of questionnaire and parasitology data to predict the distribution of Schistosoma haematobium in Coastal Kenya.

    Directory of Open Access Journals (Sweden)

    Hugh J W Sturrock

    Full Text Available Questionnaires of reported blood in urine (BIU distributed through the existing school system provide a rapid and reliable method to classify schools according to the prevalence of Schistosoma haematobium, thereby helping in the targeting of schistosomiasis control. However, not all schools return questionnaires and it is unclear whether treatment is warranted in such schools. This study investigates the use of bivariate spatial modelling of available and multiple data sources to predict the prevalence of S. haematobium at every school along the Kenyan coast.Data from a questionnaire survey conducted by the Kenya Ministry of Education in Coast Province in 2009 were combined with available parasitological and environmental data in a Bayesian bivariate spatial model. This modeled the relationship between BIU data and environmental covariates, as well as the relationship between BIU and S. haematobium infection prevalence, to predict S. haematobium infection prevalence at all schools in the study region. Validation procedures were implemented to assess the predictive accuracy of endemicity classification.The prevalence of BIU was negatively correlated with distance to nearest river and there was considerable residual spatial correlation at small (~15 km spatial scales. There was a predictable relationship between the prevalence of reported BIU and S. haematobium infection. The final model exhibited excellent sensitivity (0.94 but moderate specificity (0.69 in identifying low (<10% prevalence schools, and had poor performance in differentiating between moderate and high prevalence schools (sensitivity 0.5, specificity 1.Schistosomiasis is highly focal and there is a need to target treatment on a school-by-school basis. The use of bivariate spatial modelling can supplement questionnaire data to identify schools requiring mass treatment, but is unable to distinguish between moderate and high prevalence schools.

  16. Modelling spatial distribution of Patagonian toothfish through life-stages and sex and its implications for the fishery on the Kerguelen Plateau

    Science.gov (United States)

    Péron, Clara; Welsford, Dirk C.; Ziegler, Philippe; Lamb, Timothy D.; Gasco, Nicolas; Chazeau, Charlotte; Sinègre, Romain; Duhamel, Guy

    2016-02-01

    Size and sex specific habitat preferences are common in animal populations and can have important implications for sound spatial management of harvested species. Patagonian toothfish (Dissostichus eleginoides) is a commercially exploited fish species characterised by its longevity (>50 yo) and its extremely broad distribution in depths ranging from 10 m to 2500 m on most of the Plateaux, banks and seamounts of the Southern Ocean. As many bentho-pelagic fish species, Patagonian toothfish exhibits sexual dimorphism and ontogenetic habitat shift towards deeper waters as they grow. In this study, we modelled the spatial structure of Patagonian toothfish population (median total length and sex composition) in a data-rich area, the Kerguelen Plateau (Southern Indian Ocean), to better understand the ecological drivers of their distributional patterns and inform current and future fishery management strategies. We applied spatially-explicit statistical models to quantify and predict the effects of the complex topography of the Kerguelen Plateau in structuring the spatial distribution of Patagonian toothfish total length and sex ratio, while controlling for gear selectivity and season. Model predictions showed that juvenile toothfish live in shallow regions (shelf and banks) and move downward progressively up to 600 m while they grow. Between 600 m and 1200 m, the downward movement stops and fish settle at their preferred depths. While in this depth range, fish are ∼75 cm long and most vulnerable to fisheries. As they approach maturity large fish move downward to deep-sea habitats (from 1200 m to >2300 m) and head towards the spawning grounds on the western side of the plateau and around Skiff Bank. Importantly, the sex ratio was not evenly distributed across the Plateau; prediction maps revealed a higher proportion of females in the South whereas a strong male-bias sex ratio (70%) occurred in the North-West. Large-scale prediction maps derived from our models assisted in

  17. Spatial distribution and leaching behavior of pollutants from phosphogypsum stocked in a gypstack: Geochemical characterization and modeling.

    Science.gov (United States)

    Bisone, Sara; Gautier, Mathieu; Chatain, Vincent; Blanc, Denise

    2017-05-15

    Phosphogypsum (PPG) is the byproduct of the production of phosphoric acid and phosphate fertilizers from phosphate rocks (PR) by acid digestion. Despite the technical feasibility, the impurities present in this waste make its reuse critical and large amounts of PPG are stockpiled, resulting in the production of polluted acid leachates. The aim of the present study was to characterize the spatial variability and evolution in time of a 20-year-old gypstack and to study the geochemical behavior of the waste in order to assess the best management options. Chemical and mineralogical analyses were performed on core samples taken from 4 different depths of the stack down to 13.5 m. Despite the high homogeneity shown by chemical and mineral characterization, leaching tests revealed a different chemical behavior with depth. pH-dependent leaching tests were also performed to measure the acid neutralization capacity of the studied matrices and to determine the leachability of the elements or pollutants of concern as a function of pH. The study was focused on Ca, Fe Na, Si, Cd and Sr and on F - , PO 4 3- and SO 4 2- anions. The geochemical modeling of these tests with PHREEQC enabled the identification of the minor phases controlling the solubilization of the elements analyzed. Validation of the model by the simulation of a column leaching test suggested that the model could be used as a predictive tool to assess different management scenarios. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Multicriteria optimization of the spatial dose distribution

    Energy Technology Data Exchange (ETDEWEB)

    Schlaefer, Alexander [Medical Robotics Group, Universität zu Lübeck, Lübeck 23562, Germany and Institute of Medical Technology, Hamburg University of Technology, Hamburg 21073 (Germany); Viulet, Tiberiu [Medical Robotics Group, Universität zu Lübeck, Lübeck 23562 (Germany); Muacevic, Alexander; Fürweger, Christoph [European CyberKnife Center Munich, Munich 81377 (Germany)

    2013-12-15

    Purpose: Treatment planning for radiation therapy involves trade-offs with respect to different clinical goals. Typically, the dose distribution is evaluated based on few statistics and dose–volume histograms. Particularly for stereotactic treatments, the spatial dose distribution represents further criteria, e.g., when considering the gradient between subregions of volumes of interest. The authors have studied how to consider the spatial dose distribution using a multicriteria optimization approach.Methods: The authors have extended a stepwise multicriteria optimization approach to include criteria with respect to the local dose distribution. Based on a three-dimensional visualization of the dose the authors use a software tool allowing interaction with the dose distribution to map objectives with respect to its shape to a constrained optimization problem. Similarly, conflicting criteria are highlighted and the planner decides if and where to relax the shape of the dose distribution.Results: To demonstrate the potential of spatial multicriteria optimization, the tool was applied to a prostate and meningioma case. For the prostate case, local sparing of the rectal wall and shaping of a boost volume are achieved through local relaxations and while maintaining the remaining dose distribution. For the meningioma, target coverage is improved by compromising low dose conformality toward noncritical structures. A comparison of dose–volume histograms illustrates the importance of spatial information for achieving the trade-offs.Conclusions: The results show that it is possible to consider the location of conflicting criteria during treatment planning. Particularly, it is possible to conserve already achieved goals with respect to the dose distribution, to visualize potential trade-offs, and to relax constraints locally. Hence, the proposed approach facilitates a systematic exploration of the optimal shape of the dose distribution.

  19. Multicriteria optimization of the spatial dose distribution

    International Nuclear Information System (INIS)

    Schlaefer, Alexander; Viulet, Tiberiu; Muacevic, Alexander; Fürweger, Christoph

    2013-01-01

    Purpose: Treatment planning for radiation therapy involves trade-offs with respect to different clinical goals. Typically, the dose distribution is evaluated based on few statistics and dose–volume histograms. Particularly for stereotactic treatments, the spatial dose distribution represents further criteria, e.g., when considering the gradient between subregions of volumes of interest. The authors have studied how to consider the spatial dose distribution using a multicriteria optimization approach.Methods: The authors have extended a stepwise multicriteria optimization approach to include criteria with respect to the local dose distribution. Based on a three-dimensional visualization of the dose the authors use a software tool allowing interaction with the dose distribution to map objectives with respect to its shape to a constrained optimization problem. Similarly, conflicting criteria are highlighted and the planner decides if and where to relax the shape of the dose distribution.Results: To demonstrate the potential of spatial multicriteria optimization, the tool was applied to a prostate and meningioma case. For the prostate case, local sparing of the rectal wall and shaping of a boost volume are achieved through local relaxations and while maintaining the remaining dose distribution. For the meningioma, target coverage is improved by compromising low dose conformality toward noncritical structures. A comparison of dose–volume histograms illustrates the importance of spatial information for achieving the trade-offs.Conclusions: The results show that it is possible to consider the location of conflicting criteria during treatment planning. Particularly, it is possible to conserve already achieved goals with respect to the dose distribution, to visualize potential trade-offs, and to relax constraints locally. Hence, the proposed approach facilitates a systematic exploration of the optimal shape of the dose distribution

  20. Computational model of vascular endothelial growth factor spatial distribution in muscle and pro-angiogenic cell therapy.

    Directory of Open Access Journals (Sweden)

    Feilim Mac Gabhann

    2006-09-01

    Full Text Available Members of the vascular endothelial growth factor (VEGF family of proteins are critical regulators of angiogenesis. VEGF concentration gradients are important for activation and chemotactic guidance of capillary sprouting, but measurement of these gradients in vivo is not currently possible. We have constructed a biophysically and molecularly detailed computational model to study microenvironmental transport of two isoforms of VEGF in rat extensor digitorum longus skeletal muscle under in vivo conditions. Using parameters based on experimental measurements, the model includes: VEGF secretion from muscle fibers; binding to the extracellular matrix; binding to and activation of endothelial cell surface VEGF receptors; and internalization. For 2-D cross sections of tissue, we analyzed predicted VEGF distributions, gradients, and receptor binding. Significant VEGF gradients (up to 12% change in VEGF concentration over 10 mum were predicted in resting skeletal muscle with uniform VEGF secretion, due to non-uniform capillary distribution. These relative VEGF gradients were not sensitive to extracellular matrix composition, or to the overall VEGF expression level, but were dependent on VEGF receptor density and affinity, and internalization rate parameters. VEGF upregulation in a subset of fibers increased VEGF gradients, simulating transplantation of pro-angiogenic myoblasts, a possible therapy for ischemic diseases. The number and relative position of overexpressing fibers determined the VEGF gradients and distribution of VEGF receptor activation. With total VEGF expression level in the tissue unchanged, concentrating overexpression into a small number of adjacent fibers can increase the number of capillaries activated. The VEGF concentration gradients predicted for resting muscle (average 3% VEGF/10 mum is sufficient for cellular sensing; the tip cell of a vessel sprout is approximately 50 mum long. The VEGF gradients also result in heterogeneity in

  1. Predicting temporal development of discharge and nitrate in relation to dynamic changes of spatial crop distribution in three land use scenario runs with a catchment model

    Science.gov (United States)

    Guse, Björn; Pfannerstill, Matthias; Geertz, Jörn; Fohrer, Nicola

    2014-05-01

    In the past years, relevant changes in the use of agricultural areas were observed in German catchments. To achieve good ecological conditions in river basins as demanded by the European Water Framework Directive, the implications of land use change on water quantity and especially water quality needs to be quantified. Therefore, recent data of agricultural crops are prepared for the catchment scale. Based on this, simulations of future land use scenarios are carried out with a hydrological catchment model to analyse the linkage between dynamic changes of land use and modeled discharge and nutrients. Spatial and temporal variations of changes within agricultural areas lead to a dynamic change of pressures on the ecological status of rivers. While static land use distributions assume constant conditions for agricultural areas for the whole simulation period, dynamic changes of agricultural areas and their spatial patterns consider the varying land use conditions within the scenario simulation. In our study, a dynamic modeling of spatial distributions for agricultural crops and its impacts on discharge and nitrate is presented at the catchment scale. The area proportions of the crops are estimated in a data-based statistical approach and are implemented into the eco-hydrological model SWAT for recent and future conditions To obtain an accurate reproduction of the water cycle, the SWAT model is calibrated for discharge and nitrate time series for recent conditions. Three land use change scenarios are developed for the study catchment focusing on a dominance of food production, energy crops and on a best ecological practise. According to the scenarios, the spatial crop distribution is updated dynamically for each year, while non-agricultural land use types remain constant. The SWAT model provides satisfying results for discharge and nitrate. The evaluation of the three land use change scenarios for the period from 2021 to 2030 shows low differences in discharge, while

  2. Application of GIS and logistic regression to fossil pollen data in modelling present and past spatial distribution of the Colombian savanna

    Energy Technology Data Exchange (ETDEWEB)

    Flantua, Suzette G.A.; Boxel, John H. van; Hooghiemstra, Henry; Smaalen, John van [University of Amsterdam, Faculty of Science, Institute for Biodiversity and Ecosystem Dynamics, Amsterdam (Netherlands)

    2007-12-15

    Climate changes affect the abundance, geographic extent, and floral composition of vegetation, which are reflected in the pollen rain. Sediment cores taken from lakes and peat bogs can be analysed for their pollen content. The fossil pollen records provide information on the temporal changes in climate and palaeo-environments. Although the complexity of the variables influencing vegetation distribution requires a multi-dimensional approach, only a few research projects have used GIS to analyse pollen data. This paper presents a new approach to palynological data analysis by combining GIS and spatial modelling. Eastern Colombia was chosen as a study area owing to the migration of the forest-savanna boundary since the last glacial maximum, and the availability of pollen records. Logistic regression has been used to identify the climatic variables that determine the distribution of savanna and forest in eastern Colombia. These variables were used to create a predictive land-cover model, which was subsequently implemented into a GIS to perform spatial analysis on the results. The palynological data from the study area were incorporated into the GIS. Reconstructed maps of past vegetation distribution by interpolation showed a new approach of regional multi-site data synthesis related to climatic parameters. The logistic regression model resulted in a map with 85.7% predictive accuracy, which is considered useful for the reconstruction of future and past land-cover distributions. The suitability of palynological GIS application depends on the number of pollen sites, the distribution of the pollen sites over the area of interest, and the degree of overlap of the age ranges of the pollen records. (orig.)

  3. Spatial clustering and halo occupation distribution modelling of local AGN via cross-correlation measurements with 2MASS galaxies

    Science.gov (United States)

    Krumpe, Mirko; Miyaji, Takamitsu; Coil, Alison L.; Aceves, Hector

    2018-02-01

    We present the clustering properties and halo occupation distribution (HOD) modelling of very low redshift, hard X-ray-detected active galactic nuclei (AGN) using cross-correlation function measurements with Two-Micron All Sky Survey galaxies. Spanning a redshift range of 0.007 type I and type II AGN. We find a large-scale bias for the full AGN sample of b=1.04^{+0.10}_{-0.11}, which corresponds to a typical host dark matter halo mass of M_h^typ=12.84^{+0.22}_{-0.30} h^{-1} M_{⊙}. When split into low and high X-ray luminosity and type I and type II AGN subsamples, we detect no statistically significant differences in the large-scale bias parameters. However, there are differences in the small-scale clustering, which are reflected in the full HOD model results. We find that low and high X-ray luminosity AGN, as well as type I and type II AGN, occupy dark matter haloes differently, with 3.4σ and 4.0σ differences in their mean halo masses, respectively, when split by luminosity and type. The latter finding contradicts a simple orientation-based AGN unification model. As a by-product of our cross-correlation approach, we also present the first HOD model of 2MASS galaxies.

  4. The Model of Voronoi's Polygons and Density: Diagnosis of Spatial Distribution of Education Services of EJA in Divinópolis, Minas Gerais, Brazil.

    Directory of Open Access Journals (Sweden)

    Diogo De Castro Guadalupe

    2014-05-01

    Full Text Available This paper represents the application of a methodology that supports urban environmental studies to the identification and mapping of areas of influential points or spatial phenomenal occurrences, using the techniques of Multicriterial Analysis and of Voronoi Polygon. It focuses on the use of institutional alphanumeric database transformed into spatial analysis by the use of GIS and models of distribution, to support decision-making regarding allocation strategies and expansion of centers of experimental education called “EJA” (Youth and Adults Education in Divinópolis, a city in the state of Minas Gerais, Brazil. It describes the process of data that composes information which makes possible to perform urban analyzes and to simulate the scenarios considering the expansion of the system and the review of the allocation of some points.

  5. Traveling waves in a spatially-distributed Wilson-Cowan model of cortex: From fronts to pulses

    Science.gov (United States)

    Harris, Jeremy D.; Ermentrout, Bard

    2018-04-01

    Wave propagation in excitable media has been studied in various biological, chemical, and physical systems. Waves are among the most common evoked and spontaneous organized activity seen in cortical networks. In this paper, we study traveling fronts and pulses in a spatially-extended version of the Wilson-Cowan equations, a neural firing rate model of sensory cortex having two population types: Excitatory and inhibitory. We are primarily interested in the case when the local or space-clamped dynamics has three fixed points: (1) a stable down state; (2) a saddle point with stable manifold that acts as a threshold for firing; (3) an up state having stability that depends on the time scale of the inhibition. In the case when the up state is stable, we look for wave fronts, which transition the media from a down to up state, and when the up state is unstable, we are interested in pulses, a transient increase in firing that returns to the down state. We explore the behavior of these waves as the time and space scales of the inhibitory population vary. Some interesting findings include bistability between a traveling front and pulse, fronts that join the down state to an oscillation or spatiotemporal pattern, and pulses which go through an oscillatory instability.

  6. [Study on the spatial distribution and related risks of Rhombomys opimus, based on the ecological niche modeling in Junggar Basin, Xinjiang].

    Science.gov (United States)

    Wang, Mei; Luo, Tao; Zhao, Jian; Wang, Qiguo; Li, Bo; Azha, Ti; Zhang, Yujiang; Li, Qun

    2014-09-01

    In order to understand the distribution of the host animals in Junggar Basin, this study intended to map the spatial distribution and identifying the risk of Rhombomys opimus in the framework of ecological niche theory based on the "3S" technology. Data on Rhombomys opimus was obtained through a series of field surveys. Environmental variables were achieved through data from Remote Sensing. Maxent modeling was built to map the potential distribution of Rhombomys opimus, with its risks identified. The prediction model showed ideal accuracy, with the AUC value as 0.968. Probability of Maximum Youden Index was defined as the threshold being used. The sensitivity and specificity showed as 91.4% and 63.3%, respectively. The accuracy was 73.8%, and the Kappa coefficient was 0.495. The positive predictive value was 59.7%. The negative predictive value was 92.6%. The predicted high risk area was 37 304 km2, with 6.2% in the whole area, distributed in 18 counties, including Changji Hui Autonomous Prefecture, Urumqi, Karamay and so on. The number of people under high risk would come about 120 000, scattering in the areas of 261 square kilometers. It was feasible to predict the potential distribution of Rhombomys opimus based on the ecological niche theory as well as environmental variables derived from data through remote sensing. More specific high-risk areas could be identified under this technique so as to guide the monitoring programs.

  7. Applying the Triangle Method for the parameterization of irrigated areas as input for spatially distributed hydrological modeling - Assessing future drought risk in the Gaza Strip (Palestine).

    Science.gov (United States)

    Gampe, David; Ludwig, Ralf; Qahman, Khalid; Afifi, Samir

    2016-02-01

    In the Mediterranean region, particularly in the Gaza strip, an increased risk of drought is among the major concerns related to climate change. The impacts of climate change on water availability, drought risk and food security can be assessed by means of hydro-climatological modeling. However, the region is prone to severe observation data scarcity, which limits the potential for robust model parameterization, calibration and validation. In this study, the physically based, spatially distributed hydrological model WaSiM is parameterized and evaluated using satellite imagery to assess hydrological quantities. The Triangle Method estimates actual evapotranspiration (ETR) through the Normalized Difference Vegetation Index (NDVI) and land surface temperature (LST) provided by Landsat TM imagery. So-derived spatially distributed evapotranspiration is then used in two ways: first a subset of the imagery is used to parameterize the irrigation module of WaSiM and second, withheld scenes are applied to evaluate the performance of the hydrological model in the data scarce study area. The results show acceptable overall correlation with the validation scenes (r=0.53) and an improvement over the usual irrigation parameterization scheme using land use information exclusively. This model setup is then applied for future drought risk assessment in the Gaza Strip using a small ensemble of four regional climate projections for the period 2041-2070. Hydrological modeling reveals an increased risk of drought, assessed with an evapotranspiration index, compared to the reference period 1971-2000. Current irrigation procedures cannot maintain the agricultural productivity under future conditions without adaptation. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Spatially distributed groundwater recharge estimated using a water-budget model for the Island of Maui, Hawai`i, 1978–2007

    Science.gov (United States)

    Johnson, Adam G.; Engott, John A.; Bassiouni, Maoya; Rotzoll, Kolja

    2014-12-14

    Demand for freshwater on the Island of Maui is expected to grow. To evaluate the availability of fresh groundwater, estimates of groundwater recharge are needed. A water-budget model with a daily computation interval was developed and used to estimate the spatial distribution of recharge on Maui for average climate conditions (1978–2007 rainfall and 2010 land cover) and for drought conditions (1998–2002 rainfall and 2010 land cover). For average climate conditions, mean annual recharge for Maui is about 1,309 million gallons per day, or about 44 percent of precipitation (rainfall and fog interception). Recharge for average climate conditions is about 39 percent of total water inflow consisting of precipitation, irrigation, septic leachate, and seepage from reservoirs and cesspools. Most recharge occurs on the wet, windward slopes of Haleakalā and on the wet, uplands of West Maui Mountain. Dry, coastal areas generally have low recharge. In the dry isthmus, however, irrigated fields have greater recharge than nearby unirrigated areas. For drought conditions, mean annual recharge for Maui is about 1,010 million gallons per day, which is 23 percent less than recharge for average climate conditions. For individual aquifer-system areas used for groundwater management, recharge for drought conditions is about 8 to 51 percent less than recharge for average climate conditions. The spatial distribution of rainfall is the primary factor determining spatially distributed recharge estimates for most areas on Maui. In wet areas, recharge estimates are also sensitive to water-budget parameters that are related to runoff, fog interception, and forest-canopy evaporation. In dry areas, recharge estimates are most sensitive to irrigated crop areas and parameters related to evapotranspiration.

  9. Modelling the spatial and seasonal distribution of suitable habitats of schistosomiasis intermediate host snails using Maxent in Ndumo area, KwaZulu-Natal Province, South Africa

    Directory of Open Access Journals (Sweden)

    Tawanda Manyangadze

    2016-11-01

    Full Text Available Abstract Background Schistosomiasis is a snail-borne disease endemic in sub-Saharan Africa transmitted by freshwater snails. The distribution of schistosomiasis coincides with that of the intermediate hosts as determined by climatic and environmental factors. The aim of this paper was to model the spatial and seasonal distribution of suitable habitats for Bulinus globosus and Biomphalaria pfeifferi snail species (intermediate hosts for Schistosoma haematobium and Schistosoma mansoni, respectively in the Ndumo area of uMkhanyakude district, South Africa. Methods Maximum Entropy (Maxent modelling technique was used to predict the distribution of suitable habitats for B. globosus and B. pfeifferi using presence-only datasets with ≥ 5 and ≤ 12 sampling points in different seasons. Precipitation, maximum and minimum temperatures, Normalised Difference Vegetation Index (NDVI, Normalised Difference Water Index (NDWI, pH, slope and Enhanced Vegetation Index (EVI were the background variables in the Maxent models. The models were validated using the area under the curve (AUC and omission rate. Results The predicted suitable habitats for intermediate snail hosts varied with seasons. The AUC for models in all seasons ranged from 0.71 to 1 and the prediction rates were between 0.8 and 0.9. Although B. globosus was found at more localities in the Ndumo area, there was also evidence of cohabiting with B. pfiefferi at some of the locations. NDWI had significant contribution to the models in all seasons. Conclusion The Maxent model is robust in snail habitat suitability modelling even with small dataset of presence-only sampling sites. Application of the methods and design used in this study may be useful in developing a control and management programme for schistosomiasis in the Ndumo area.

  10. Spatio-temporal Analysis of Hydrological Drought at Catchment Scale Using a Spatially-distributed Hydrological Model

    NARCIS (Netherlands)

    Mercado, Vitali Diaz; Perez, Gerald Corzo; Solomatine, Dimitri; Lanen, Van Henny A.J.

    2016-01-01

    Lately, drought is more intense and much more severe around the globe, causing more deaths than other hazards in the past century. Drought can be characterized quantitatively for its spatial extent, intensity and duration by using drought indicators. Several indicators have been developed in

  11. ArcNEMO, a spatially distributed nutrient emission model developed in Python to quantify losses of nitrogen and phosphorous from agriculture to surface waters

    Science.gov (United States)

    Van Opstal, Mattias; Tits, Mia; Beckers, Veronique; Batelaan, Okke; Van Orshoven, Jos; Elsen, Annemie; Diels, Jan; D'heygere, Tom; Van Hoof, Kor

    2014-05-01

    Pollution of surface water bodies with nitrogen (N) and phosphorous (P) from agricultural sources is a major problem in areas with intensive agriculture in Europe. The Flemish Environment Agency requires information on how spatially explicit policy measures on manure and fertilizer use, and changes in land use and soil management affect the N and P concentration in the surface waters in the region of Flanders, Belgium. To assist in this, a new spatially distributed, mechanistic nutrient emission model was developed in the open-source language Python. The model is called ArcNEMO (Nutrient Emission MOdel). The model is fully integrated in ArcGIS, but could be easily adapted to work with open-source GIS software. In Flanders, detailed information is available each year on the delineation of each agricultural parcel and the crops grown on them. Parcels are linked to farms, and for each farm yearly manure and fertilizer use is available. To take full advantage of this information and to be able to simulate nutrient losses to the high-density surface water network, the model makes use of grid cells of 50 by 50m. A fertilizer allocation model was developed to calculate from the yearly parcel and farm data the fertilizer and manure input per grid cell for further use in the ArcNEMO-model. The model architecture was chosen such that the model can be used to simulate spatially explicit monthly discharge and losses of N and P to the surface water for the whole of Flanders (13,500 km²) over periods of 10-20 years. The extended time period is necessary because residence times in groundwater and the rates of organic matter turnover imply that water quality reacts slowly to changes of land use and fertilization practices. Vertical water flow and nutrient transport in the unsaturated zone are described per grid cell using a cascading bucket-type model with daily time steps. Groundwater flow is described by solving the 2D-groundwater flow equation using an explicit numerical

  12. Using isotopes to constrain water flux and age estimates in snow-influenced catchments using the STARR (Spatially distributed Tracer-Aided Rainfall-Runoff) model

    Science.gov (United States)

    Ala-aho, Pertti; Tetzlaff, Doerthe; McNamara, James P.; Laudon, Hjalmar; Soulsby, Chris

    2017-10-01

    Tracer-aided hydrological models are increasingly used to reveal fundamentals of runoff generation processes and water travel times in catchments. Modelling studies integrating stable water isotopes as tracers are mostly based in temperate and warm climates, leaving catchments with strong snow influences underrepresented in the literature. Such catchments are challenging, as the isotopic tracer signals in water entering the catchments as snowmelt are typically distorted from incoming precipitation due to fractionation processes in seasonal snowpack. We used the Spatially distributed Tracer-Aided Rainfall-Runoff (STARR) model to simulate fluxes, storage, and mixing of water and tracers, as well as estimating water ages in three long-term experimental catchments with varying degrees of snow influence and contrasting landscape characteristics. In the context of northern catchments the sites have exceptionally long and rich data sets of hydrometric data and - most importantly - stable water isotopes for both rain and snow conditions. To adapt the STARR model for sites with strong snow influence, we used a novel parsimonious calculation scheme that takes into account the isotopic fractionation through snow sublimation and snowmelt. The modified STARR setup simulated the streamflows, isotope ratios, and snow pack dynamics quite well in all three catchments. From this, our simulations indicated contrasting median water ages and water age distributions between catchments brought about mainly by differences in topography and soil characteristics. However, the variable degree of snow influence in catchments also had a major influence on the stream hydrograph, storage dynamics, and water age distributions, which was captured by the model. Our study suggested that snow sublimation fractionation processes can be important to include in tracer-aided modelling for catchments with seasonal snowpack, while the influence of fractionation during snowmelt could not be unequivocally

  13. Novel Image Processing Interface to Relate DSB Spatial Distribution from Immunofluorescence Foci Experiments to the State-of-the-Art Models of DNA Breakage

    Science.gov (United States)

    Ponomarev, A. L.; Cucinotta, F. A.

    2004-01-01

    A recently developed software (NASARadiationTrackImage) allows a quick and automatic segmentation of foci that indicate spatial localization of specific proteins that are visualized by immunofluorescence. Of interest are the spatial and temporal distribution of foci such as gammaH2AX, a signal of the phosphorylation of a variant of the histone H2A that has been shown to correspond to DSBs, or proteins involved in DSB processing, such as ATM, Rad51, and p53, following exposures of human cells to high charge and energy (HZE) ion irradiation. Experimental data are recorded as sets of two-dimensional images in color with cells and foci of gammaH2AX, ATM, Rad51 or others shown. Different cells, levels of radiation and timing after radiation were recorded. The software allows us to calculate the number of foci per cell, overall intensity of light in foci and their spatial organization. A simple statistical model allows for testing of foci overlap (eclipse). A more complex statistical model previously known as DNAbreak simulates track structure and random chromosome geometry. It has one adjustable parameter corresponding to an average intensity of DSB creation in cubic micrometers of DNA volume per particle track or unit dose. Its limitation is the low-resolution limit both in physical space and DSB's along DNA. It works adequately on the scale of a cell and provides further insights on how the geometry of tracks and DNA affects genomic damage of the cell and subsequent repair. Future developments of the model for the description of the time evolution of DNA damage response proteins, and more robust track structure models will be discussed.

  14. Spatial distribution and assessment of nutrient pollution in Lake Toba using 2D-multi layers hydrodynamic model and DPSIR framework

    Science.gov (United States)

    Sunaryani, A.; Harsono, E.; Rustini, H. A.; Nomosatryo, S.

    2018-02-01

    Lake Toba is the largest lake in Indonesia utilized as a source of life-support for drinking and clean water, energy sources, aquaculture and tourism. Nowadays the water quality in Lake Toba has decreased due to the presence of excessive nutrient (nitrogen: N and phosphorus: P). This study aims to describe the spatial distribution of nutrient pollution and to develop a decision support tool for the identification and evaluation of nutrient pollution control in Lake Toba. Spatial distribution method was conducted by 2D-multi layers hydrodynamic model, while DPSIR Framework is used as a tool for the assessment. The results showed that the concentration of nutrient was low and tended to increase along the water depth, but nutrient concentration in aquaculture zones was very high and the trophic state index has reached eutrophic state. The principal anthropogenic driving forces were population growth and the development of aquaculture, livestock, agriculture, and tourism. The main environmental pressures showed that aquaculture and livestock waste are the most important nutrient sources (93% of N and 87% of P loads). State analysis showed that high nutrient concentration and increased algal growth lead to oxygen depletion. The impacts of these conditions were massive fish kills, loss of amenities and tourism value, also decreased usability of clean water supply. This study can be a useful information for decision-makers to evaluate nutrient pollution control. Nutrient pollution issue in Lake Toba requires the attention of local government and public society to maintain its sustainability.

  15. Location Aggregation of Spatial Population CTMC Models

    Directory of Open Access Journals (Sweden)

    Luca Bortolussi

    2016-10-01

    Full Text Available In this paper we focus on spatial Markov population models, describing the stochastic evolution of populations of agents, explicitly modelling their spatial distribution, representing space as a discrete, finite graph. More specifically, we present a heuristic approach to aggregating spatial locations, which is designed to preserve the dynamical behaviour of the model whilst reducing the computational cost of analysis. Our approach combines stochastic approximation ideas (moment closure, linear noise, with computational statistics (spectral clustering to obtain an efficient aggregation, which is experimentally shown to be reasonably accurate on two case studies: an instance of epidemic spreading and a London bike sharing scenario.

  16. Spatial indoor radon distribution in Mexico City

    International Nuclear Information System (INIS)

    Franco-Marina, Francisco; Villalba-Caloca, Jaime; Segovia, Nuria; Tavera, Leticia

    2003-01-01

    We present a spatial analysis of residential radon concentrations in the Mexico City Metropolitan Area, which we intend to use to assign radon exposure in an ongoing case-control study. As part of a probabilistic household survey, carried out between May and June 1999, 501 dwellings were selected for indoor placement of solid state nuclear track detectors (LR 115) in a cup array over a period of approximately 90 days. As part of the sampling design, the city was grid partitioned into nine zones and a sample of dwellings was selected in each zone. All zones were simultaneously surveyed. The stratified sampling design allowed us to obtain radon geometric means, adjusted for household characteristics, week of detector placement and number of days of measurement for these zones. Additionally, adjusted geometric means were estimated for the 100 census tracts surveyed and this information was used to obtain a more detailed spatial distribution of residential radon levels through kriging interpolation and surface contouring. Radon levels depended on the room of placement, the floor level and the ventilation habits but not on building materials. Regarding the city zone, the highest adjusted geometric mean was found in the southwest (136 Bqm -3 ), where 46% of the households had an estimated radon level in excess of 200 Bqm -3 . In the rest of the city, the geometric mean concentration ranged between 41 and 98 Bqm -3 . A more detailed spatial distribution showed that, in general, most of the eastern and middle zones of the city had estimated radon geometric means below 74 Bqm -3 , while the western ones had geometric means above this concentration. Very high geometric means, exceeding 111 Bqm -3 and even reaching 288 Bqm -3 , are estimated for some areas located in the southern and western zones of Mexico City. The obtained spatial distribution shows that the areas with very high estimated residential radon concentrations are close to inactive volcanic mountains. We believe

  17. The mARM spatially distributed soil evolution model: A computationally efficient modeling framework and analysis of hillslope soil surface organization

    Science.gov (United States)

    Cohen, Sagy; Willgoose, Garry; Hancock, Greg

    2009-09-01

    Hillslope surface armouring and weathering processes have received little attention in geomorphologic and hydrologic models due to their complexity and the uncertainty associated with them. Their importance, however, in a wide range of spatial processes is well recognized. A physically based armouring and weathering computer model (ARMOUR) has previously been used to successfully simulate the effect of these processes on erosion and soil grading at a hillslope scale. This model is, however, computationally complex and cannot realistically be applied over large areas or over long periods of time. A simplified process conceptualization approach is presented (named mARM) which uses a novel approach of modeling physical processes using transition matrices, which is orders of magnitude faster. We describe in detail the modeling framework. We calibrate and evaluate the model against ARMOUR simulations and show it matches ARMOUR for a range of conditions. The computational efficiency of mARM allowed us to easily examine time- and space-varying relationships between erosion and physical weathering rates at the hillslope scale. For erosion-dominated slopes the surface coarsens over time, while for weathering domination the surface fines over time. When erosion and weathering are comparable in scale a slope can be weathering-dominated upslope (where runoff and therefore erosion is low) and armouring-dominated downslope. In all cases, for a constant gradient slope the surface armour coarsens downslope as a result of a balance between erosion and weathering. Thus even for weathering-dominated slopes the surface grading catena is dependent on armouring through the balance between weathering and armouring. We also observed that for many slopes the surface initially armours but, after some period of time (space- and rate-dependent), weathering begins to dominate and the surface subsequently fines. Depending on the relative magnitude of armouring and weathering the final

  18. Ocean Color Products Supporting the Assessment of Good Environmental Status: Development of a Spatial Distribution Model for the Seagrass Posidonia Oceanica (L.) Delille, 1813

    Science.gov (United States)

    Zucchetta, M.; Taji, M. A.; Mangin, A.; Pastres, R.

    2015-12-01

    binomial generalized linear model as a function of the bathymetry and some water characteristics mainly obtained from satellite data. Full resolution (c.a. 300m) Medium Resolution Imaging Spectrometer (MERIS) sensor imagery have been processed in order to extract a set of environmental variables to be coupled to seagrass distribution in the areas used to calibrate the model and for the whole North Africa coast (i.e. model application area). For the period 2003-2011 we processed data of: 1) the diffuse attenuation coefficient 2) coloured dissolved organic matter 3) Particle backscatter at 443nm; 4) Euphotic depth, estimated considering the coefficient of extinction of light; 5) Euphotic depth/ depth ratio, combining the estimation of euphotic depth with the bathymetry. Other variables have been resampled at MERIS full resolution, like data obtained from Moderate Resolution Imaging Spectroradiometer (MODIS; Sea Surface Temperature and Photosynthetically Available Radiation) or by model simulation (e.g. water salinity). The fitted model suggests that water transparency plays a major role, but also other variables, such as salinity and photosynthetically available radiation at surface, are important at larger spatial scales in explaining meadows distribution. The availability of high resolution time-series of input data allowed us to apply the validated model to the whole NA coast. Using model predictions to identify areas with suitable conditions for P. oceanica, it was possible to develop an indicator of potential habitat use and to define baseline reference conditions, necessary for the assessment of Good Environmental Status in Mediterranean coastal waters. This work shows how the Ocean and Land Colour Instrument (OLCI) within the Sentinel-3 mission can be exploited - thanks to the way opened by MERIS - to carry out the operational monitoring needed for the implementation of the UNEP MAP and EU MSFD Ecosystem Approach to the integrated management of land, water and living

  19. Soil erosion and sediment delivery in a mountain catchment under land use change: using point fallout 137Cs for calibrating a spatially distributed numerical model

    Science.gov (United States)

    Alatorre, L. C.; Beguería, S.; Lana-Renault, N.; Navas, A.; García-Ruiz, J. M.

    2011-12-01

    Soil erosion and sediment yield are strongly affected by land use/land cover (LULC). Spatially distributed erosion models are useful tools for comparing erosion resulting from current LULC with a number of alternative scenarios, being of great interest to assess the expected effect of LULC changes. In this study the soil erosion and sediment delivery model WATEM/SEDEM was applied to a small experimental catchment in the Central Spanish Pyrenees. Model calibration was carried out based on a dataset of soil redistribution rates derived from 137Cs inventories along three representative transects, allowing capture differences per land use in the main model parameters. Model calibration showed a good convergence to a global optimum in the parameter space. Validation of the model results against seven years of recorded sediment yield at the catchment outlet was satisfactory. Two LULC scenarios where then modeled to reproduce the land use at the beginning of the twentieth Century and a hypothetic future scenario, and to compare the simulation results to the current LULC situation. The results show a reduction of about one order of magnitude in gross erosion (3180 to 350 Mg yr-1) and sediment delivery (11.2 to 1.2 Mg yr-1 ha-1) during the last decades as a result of the abandonment of traditional land uses (mostly agriculture) and subsequent vegetation re-colonization. The simulation also allowed assessing differences in the sediment sources and sinks within the catchment.

  20. The spatial distribution of flocking foragers : disentangling the effects of food availability, interference and conspecific attraction by means of spatial autoregressive modeling

    NARCIS (Netherlands)

    Folmer, Eelke O.; Olff, Han; Piersma, Theunis; Robinson, Rob

    Patch choice of foraging animals is typically assumed to depend positively on food availability and negatively on interference while benefits of the co-occurrence of conspecifics tend to be ignored. In this paper we integrate a classical functional response model based on resource availability and

  1. DISENTANGLING INTERPOLATION AND EXTRAPOLATION UNCERTAINTIES IN SPECIES DISTRIBUTION MODELS: A NOVEL VISUALIZATION TECHNIQUE FOR THE SPATIAL VARIATION OF PREDICTOR VARIABLE COLINEARITY

    Directory of Open Access Journals (Sweden)

    Dennis Rödder

    2012-08-01

    Full Text Available Abstract. - Species distribution models (SDMs are increasingly used in many scientific fields, with most studies requiring the application of the SDM to predict the likelihood of occurrence and/or environmental suitability in locations and time periods outside the range of the data set used to fit the model. Uncertainty in the quality of SDM predictions caused by errors of interpolation and extrapolation has been acknowledged for a long time, but the explicit consideration of the magnitude of such errors is, as yet, uncommon. Among other issues, the spatial variation in the colinearity of the environmental predictor variables used in the development of SDMs may cause misleading predictions when applying SDMs to novel locations and time periods. In this paper, we provide a framework for the spatially explicit identification of areas prone to errors caused by changes in the inter-correlation structure (i.e. their colinearity of environmental predictors used for SDM development. The proposed method is compatible with all SDM algorithms currently employed, and expands the available toolbox for assessing the uncertainties raising from SDM predictions. We provide an implementation of the analysis as a script for the R statistical platform in an online appendix.

  2. The mARM3D spatially distributed soil evolution model: Three-dimensional model framework and analysis of hillslope and landform responses

    Science.gov (United States)

    Cohen, Sagy; Willgoose, Garry; Hancock, Greg

    2010-10-01

    We present a three-dimensional landscape-pedogenesis model, mARM3D (matrices ARMOUR 3D), which simulates soil evolution as a function of erosion and pedogenic processes. The model simulates the discretized soil profile for points on a spatial grid. The approach, using transition matrices, is computationally efficient and allows the simulation of large-scale spatial coupling and long-term soil evolution. We study the effect of the depth-dependent soil-weathering rate (i.e., the rate of soil particle breakdown) and bedrock-lowering rate (i.e., the rate of conversion of bedrock to soil). The difference in depth-dependent weathering functions has a significant effect on the in-profile soil properties through depth, specifically particle size grading. However, the depth dependency has a relatively minor effect on the surface properties of the soil profile, with all weathering functions generating very similar surface properties. The surface properties were a function of the cumulative amount of weathering (i.e., the integral of the weathering function over exhumation) with finer surface grading for higher weathering rates. Soil thickness could be estimated without explicitly modeling soil thickness. Thickness was negatively correlated with surface median grain size. As thickness decreases, the surface grading coarsens. This was driven by surface erosion, where as surface grading coarsens, erosion decreases and the soil deepens. Weathering and erosion interact to spatially organize the surface soil grading with a log-log relationship between surface grading, contributing area, and local slope. This relationship was independent of the weathering function. This relationship might be useful for the spatial description of soil properties in digital soil mapping.

  3. Inputs and spatial distribution patterns of Cr in Jiaozhou Bay

    Science.gov (United States)

    Yang, Dongfang; Miao, Zhenqing; Huang, Xinmin; Wei, Linzhen; Feng, Ming

    2018-03-01

    Cr pollution in marine bays has been one of the critical environmental issues, and understanding the input and spatial distribution patterns is essential to pollution control. In according to the source strengths of the major pollution sources, the input patterns of pollutants to marine bay include slight, moderate and heavy, and the spatial distribution are corresponding to three block models respectively. This paper analyzed input patterns and distributions of Cr in Jiaozhou Bay, eastern China based on investigation on Cr in surface waters during 1979-1983. Results showed that the input strengths of Cr in Jiaozhou Bay could be classified as moderate input and slight input, and the input strengths were 32.32-112.30 μg L-1 and 4.17-19.76 μg L-1, respectively. The input patterns of Cr included two patterns of moderate input and slight input, and the horizontal distributions could be defined by means of Block Model 2 and Block Model 3, respectively. In case of moderate input pattern via overland runoff, Cr contents were decreasing from the estuaries to the bay mouth, and the distribution pattern was parallel. In case of moderate input pattern via marine current, Cr contents were decreasing from the bay mouth to the bay, and the distribution pattern was parallel to circular. The Block Models were able to reveal the transferring process of various pollutants, and were helpful to understand the distributions of pollutants in marine bay.

  4. Continuous Spatial Process Models for Spatial Extreme Values

    KAUST Repository

    Sang, Huiyan

    2010-01-28

    We propose a hierarchical modeling approach for explaining a collection of point-referenced extreme values. In particular, annual maxima over space and time are assumed to follow generalized extreme value (GEV) distributions, with parameters μ, σ, and ξ specified in the latent stage to reflect underlying spatio-temporal structure. The novelty here is that we relax the conditionally independence assumption in the first stage of the hierarchial model, an assumption which has been adopted in previous work. This assumption implies that realizations of the the surface of spatial maxima will be everywhere discontinuous. For many phenomena including, e. g., temperature and precipitation, this behavior is inappropriate. Instead, we offer a spatial process model for extreme values that provides mean square continuous realizations, where the behavior of the surface is driven by the spatial dependence which is unexplained under the latent spatio-temporal specification for the GEV parameters. In this sense, the first stage smoothing is viewed as fine scale or short range smoothing while the larger scale smoothing will be captured in the second stage of the modeling. In addition, as would be desired, we are able to implement spatial interpolation for extreme values based on this model. A simulation study and a study on actual annual maximum rainfall for a region in South Africa are used to illustrate the performance of the model. © 2009 International Biometric Society.

  5. Exploring the spatial distribution of light interception and photosynthesis of canopies by means of a functional-structural plant model

    NARCIS (Netherlands)

    Sarlikioti, V.; Visser, de P.H.B.; Marcelis, L.F.M.

    2011-01-01

    Background and Aims - At present most process-based models and the majority of three-dimensional models include simplifications of plant architecture that can compromise the accuracy of light interception simulations and, accordingly, canopy photosynthesis. The aim of this paper is to analyse canopy

  6. Modeling the spatial distribution of forest crown biomass and effects on fire behavior with FUEL3D and WFDS

    Science.gov (United States)

    Russell A. Parsons; William Mell; Peter McCauley

    2010-01-01

    Crown fire poses challenges to fire managers and can endanger fire fighters. Understanding of how fire interacts with tree crowns is essential to informed decisions about crown fire. Current operational crown fire predictions in the United States assume homogeneous crown fuels. While a new class of research fire models, which model fire behavior with computational...

  7. Verifying the Dependence of Fractal Coefficients on Different Spatial Distributions

    International Nuclear Information System (INIS)

    Gospodinov, Dragomir; Marekova, Elisaveta; Marinov, Alexander

    2010-01-01

    A fractal distribution requires that the number of objects larger than a specific size r has a power-law dependence on the size N(r) = C/r D ∝r -D where D is the fractal dimension. Usually the correlation integral is calculated to estimate the correlation fractal dimension of epicentres. A 'box-counting' procedure could also be applied giving the 'capacity' fractal dimension. The fractal dimension can be an integer and then it is equivalent to a Euclidean dimension (it is zero of a point, one of a segment, of a square is two and of a cube is three). In general the fractal dimension is not an integer but a fractional dimension and there comes the origin of the term 'fractal'. The use of a power-law to statistically describe a set of events or phenomena reveals the lack of a characteristic length scale, that is fractal objects are scale invariant. Scaling invariance and chaotic behavior constitute the base of a lot of natural hazards phenomena. Many studies of earthquakes reveal that their occurrence exhibits scale-invariant properties, so the fractal dimension can characterize them. It has first been confirmed that both aftershock rate decay in time and earthquake size distribution follow a power law. Recently many other earthquake distributions have been found to be scale-invariant. The spatial distribution of both regional seismicity and aftershocks show some fractal features. Earthquake spatial distributions are considered fractal, but indirectly. There are two possible models, which result in fractal earthquake distributions. The first model considers that a fractal distribution of faults leads to a fractal distribution of earthquakes, because each earthquake is characteristic of the fault on which it occurs. The second assumes that each fault has a fractal distribution of earthquakes. Observations strongly favour the first hypothesis.The fractal coefficients analysis provides some important advantages in examining earthquake spatial distribution, which are

  8. Analysis of the spatial and temporal variation of seasonal snow accumulation in alpine catchments using airborne laser scanning : basic research for the adaptation of spatially distributed hydrological models to mountain regions

    International Nuclear Information System (INIS)

    Helfricht, K.

    2014-01-01

    Information about the spatial distribution of snow accumulation is a prerequisitefor adaptating hydro-meteorological models to achieve realistic simulations of therunoff from mountain catchments. Therefore, the spatial snow depthdistribution in complex topography of ice-free terrain and glaciers was investigatedusing airborne laser scanning (ALS) data. This thesis presents for the first time an analysis of the persistence and the variability of the snow patterns at the end of five accumulation seasons in a comparatively large catchment. ALS derived seasonal surface elevation changes on glaciers were compared to the actual snow depths calculated from ground penetrating radar (GPR) measurements. Areas of increased deviations. In the investigated region, the ALS-derived snow depths on most of the glacier surface do not deviate markedly from actual snow depths. 75% of a the total area showed low inter-annual variability of standardized snow depths at the end of the five accumulation seasons. The high inter-annual variability of snow depths could be attributed to changes in the ice cover within the investigated 10-yearperiod for much of the remaining area. Avalanches and snow sloughs continuously contribute to the accumulation on glaciers, but their share of the total snow covervolume is small. The assimilation of SWE maps calculated from ALS data in the adaptation of snow-hydrological models to mountain catchments improved the results not only for the but also for the simulated snow cover distribution and for the mass balance of the glaciers. The results demonstrate that ALS data are a beneficial source for extensive analysis of snow patterns and for modeling the runoff from high Alpine catchments.(author) [de

  9. Spatial and temporal distribution of geophysical disasters

    Directory of Open Access Journals (Sweden)

    Cvetković Vladimir

    2013-01-01

    Full Text Available Natural disasters of all kinds (meteorological, hydrological, geophysical, climatological and biological are increasingly becoming part of everyday life of modern human. The consequences are often devastating, to the life, health and property of people, as well to the security of states and the entire international regions. In this regard, we noted the need for a comprehensive investigation of the phenomenology of natural disasters. In addition, it is particularly important to pay attention to the different factors that might correlate with each other to indicate more dubious and more original facts about their characteristics. However, as the issue of natural disasters is very wide, the subject of this paper will be forms, consequences, temporal and spatial distribution of geophysical natural disasters, while analysis of other disasters will be the subject of our future research. Using an international database on natural disasters of the centre for research on the epidemiology of disasters (CRED based in Brussels, with the support of the statistical analysis (SPSS, we tried to point out the number, trends, consequences, the spatial and temporal distribution of earthquakes, volcanic eruptions and dry mass movements in the world, from 1900 to 2013.

  10. Spatially Distributed Assimilation of Remotely Sensed Leaf Area Index and Potential Evapotranspiration for Hydrologic Modeling in Wetland Landscapes

    Science.gov (United States)

    Rajib, A.; Evenson, G. R.; Golden, H. E.; Lane, C.

    2017-12-01

    Evapotranspiration (ET), a highly dynamic flux in wetland landscapes, regulates the accuracy of surface/sub-surface runoff simulation in a hydrologic model. Accordingly, considerable uncertainty in simulating ET-related processes remains, including our limited ability to incorporate realistic ground conditions, particularly those involved with complex land-atmosphere feedbacks, vegetation growth, and energy balances. Uncertainty persists despite using high resolution topography and/or detailed land use data. Thus, a good hydrologic model can produce right answers for wrong reasons. In this study, we develop an efficient approach for multi-variable assimilation of remotely sensed earth observations (EOs) into a hydrologic model and apply it in the 1700 km2 Pipestem Creek watershed in the Prairie Pothole Region of North Dakota, USA. Our goal is to employ EOs, specifically Leaf Area Index (LAI) and Potential Evapotranspiration (PET), as surrogates for the aforementioned processes without overruling the model's built-in physical/semi-empirical process conceptualizations. To do this, we modified the source code of an already-improved version of the Soil and Water Assessment Tool (SWAT) for wetland hydrology (Evenson et al. 2016 HP 30(22):4168) to directly assimilate remotely-sensed LAI and PET (obtained from the 500 m and 1 km Moderate Resolution Imaging Spectroradiometer (MODIS) gridded products, respectively) into each model Hydrologic Response Unit (HRU). Two configurations of the model, one with and one without EO assimilation, are calibrated against streamflow observations at the watershed outlet. Spatio-temporal changes in the HRU-level water balance, based on calibrated outputs, are evaluated using MODIS Actual Evapotranspiration (AET) as a reference. It is expected that the model configuration having remotely sensed LAI and PET, will simulate more realistic land-atmosphere feedbacks, vegetation growth and energy balance. As a result, this will decrease simulated

  11. Analysis of spatial distribution characteristics of dissolved organic matter in typical greenhouse soil of northern China using three dimensional fluorescence spectra technique and parallel factor analysis model.

    Science.gov (United States)

    Pan, Hong-wei; Lei, Hong-jun; Han, Yu-ping; Xi, Bei-dou; He, Xiao-song; Xu, Qi-gong; Li, Dan

    2014-06-01

    The aim of the present work is to study the soil DOM characteristics in the vegetable greenhouse with a long-term of cultivation. Results showed that the soil DOM mainly consisted of three components, fulvic acid-like (C1), humic acid-like (C2) and protein-like (C3), with C1 as the majority one. The distribution of DOM in space was also studied. In vertical direction, C1 and C2 decreased significantly with the increase in soil depth, while C3 component decreased after increased. The humification coefficient decreased fast from 0-20 to 30-40 cm, and then increased from 30-40 to 40-50 cm. In the horizontal direction, the level of C2 component varied greatly in space, while that of C1 component changed little, and that of C3 component fell in between the above two. The change in the humification degree of each soil layer significantly varied spatially. Humification process of soil organic matter mainly occurred in the surface soil layer. In addition, the humification degree in space also changed significantly. The new ideas of this study are: (1) Analyze the composition and spatial heterogeneity of soil DOM in the vegetable greenhouse; (2) Use three dimensional fluorescence spectra technology and parallel factor analysis model successfully to quantify the components of soil DOM, which provides a new method for the soil DOM analysis.

  12. Spatial Damage Distribution over Cube Armoured Roundheads

    DEFF Research Database (Denmark)

    Alonso, Enrique Maciñeira; Burcharth, Hans F.

    2009-01-01

    Different authors have studied and defined the most critical sector of the roundheads with respect to armour stability in order to calculate the mass needed in the units of the armour. This sector has been located between 90° and 135° relative to the orthogonal of the waves. Moreover, from...... provides data on damage distribution over the head obtained in 3D physical model tests with short crested waves at Aalborg University. Furthermore, the factors influencing the distributions are explained....

  13. Compressive Feedback Control Design for Spatially Distributed Systems

    Science.gov (United States)

    2017-01-03

    AFRL-AFOSR-VA-TR-2017-0004 Compressive Feedback Control Design for Spatially Distributed Systems Nader Motee LEHIGH UNIVERSITY 526 BRODHEAD AVE...0158 Compressive Feedback Control Design for Spatially Distributed Systems Program Manager: Dr. Frederick A. Leve Principle Investigator: Nader Motee...Feedback Control Design for Spatially Distributed Systems Summary of Accomplishments and Research Results 1 Systemic Performance and Robustness

  14. Spatial soil zinc content distribution from terrain parameters: a GIS-based decision-tree model in Lebanon.

    Science.gov (United States)

    Bou Kheir, Rania; Greve, Mogens H; Abdallah, Chadi; Dalgaard, Tommy

    2010-02-01

    Heavy metal contamination has been and continues to be a worldwide phenomenon that has attracted a great deal of attention from governments and regulatory bodies. In this context, our study proposes a regression-tree model to predict the concentration level of zinc in the soils of northern Lebanon (as a case study of Mediterranean landscapes) under a GIS environment. The developed tree-model explained 88% of variance in zinc concentration using pH (100% in relative importance), surroundings of waste areas (90%), proximity to roads (80%), nearness to cities (50%), distance to drainage line (25%), lithology (24%), land cover/use (14%), slope gradient (10%), conductivity (7%), soil type (7%), organic matter (5%), and soil depth (5%). The overall accuracy of the quantitative zinc map produced (at 1:50.000 scale) was estimated to be 78%. The proposed tree model is relatively simple and may also be applied to other areas. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

  15. Exact and Numerical Solutions of a Spatially-Distributed Mathematical Model for Fluid and Solute Transport in Peritoneal Dialysis

    Directory of Open Access Journals (Sweden)

    Roman Cherniha

    2016-06-01

    Full Text Available The nonlinear mathematical model for solute and fluid transport induced by the osmotic pressure of glucose and albumin with the dependence of several parameters on the hydrostatic pressure is described. In particular, the fractional space available for macromolecules (albumin was used as a typical example and fractional fluid void volume were assumed to be different functions of hydrostatic pressure. In order to find non-uniform steady-state solutions analytically, some mathematical restrictions on the model parameters were applied. Exact formulae (involving hypergeometric functions for the density of fluid flux from blood to tissue and the fluid flux across tissues were constructed. In order to justify the applicability of the analytical results obtained, a wide range of numerical simulations were performed. It was found that the analytical formulae can describe with good approximation the fluid and solute transport (especially the rate of ultrafiltration for a wide range of values of the model parameters.

  16. Mechanical Motion Induced by Spatially Distributed Limit-Cycle Oscillators

    Science.gov (United States)

    Sakaguchi, Hidetsugu; Mukae, Yuuki

    2017-03-01

    Spatially distributed limited-cycle oscillators are seen in various physical and biological systems. In internal organs, mechanical motions are induced by the stimuli of spatially distributed limit-cycle oscillators. We study several mechanical motions by limit-cycle oscillators using simple model equations. One problem is deformation waves of radius oscillation induced by desynchronized limit-cycle oscillators, which is motivated by peristaltic motion of the small intestine. A resonance-like phenomenon is found in the deformation waves, and particles can be transported by the deformation waves. Another is the beating motion of the heart. The expansion and contraction motion is realized by a spatially synchronized limit-cycle oscillation; however, the strong beating disappears by spiral chaos, which is closely related to serious arrhythmia in the heart.

  17. Calibration by Hydrological Response Unit of a National Hydrologic Model to Improve Spatial Representation and Distribution of Parameters

    Science.gov (United States)

    Norton, P. A., II

    2015-12-01

    The U. S. Geological Survey is developing a National Hydrologic Model (NHM) to support consistent hydrologic modeling across the conterminous United States (CONUS). The Precipitation-Runoff Modeling System (PRMS) simulates daily hydrologic and energy processes in watersheds, and is used for the NHM application. For PRMS each watershed is divided into hydrologic response units (HRUs); by default each HRU is assumed to have a uniform hydrologic response. The Geospatial Fabric (GF) is a database containing initial parameter values for input to PRMS and was created for the NHM. The parameter values in the GF were derived from datasets that characterize the physical features of the entire CONUS. The NHM application is composed of more than 100,000 HRUs from the GF. Selected parameter values commonly are adjusted by basin in PRMS using an automated calibration process based on calibration targets, such as streamflow. Providing each HRU with distinct values that captures variability within the CONUS may improve simulation performance of the NHM. During calibration of the NHM by HRU, selected parameter values are adjusted for PRMS based on calibration targets, such as streamflow, snow water equivalent (SWE) and actual evapotranspiration (AET). Simulated SWE, AET, and runoff were compared to value ranges derived from multiple sources (e.g. the Snow Data Assimilation System, the Moderate Resolution Imaging Spectroradiometer (i.e. MODIS) Global Evapotranspiration Project, the Simplified Surface Energy Balance model, and the Monthly Water Balance Model). This provides each HRU with a distinct set of parameter values that captures the variability within the CONUS, leading to improved model performance. We present simulation results from the NHM after preliminary calibration, including the results of basin-level calibration for the NHM using: 1) default initial GF parameter values, and 2) parameter values calibrated by HRU.

  18. Spatial distribution of angular momentum inside the nucleon

    Science.gov (United States)

    Lorcé, Cédric; Mantovani, Luca; Pasquini, Barbara

    2018-01-01

    We discuss in detail the spatial distribution of angular momentum inside the nucleon. We show that the discrepancies between different definitions originate from terms that integrate to zero. Even though these terms can safely be dropped at the integrated level, they have to be taken into account when discussing distributions. Using the scalar diquark model, we illustrate our results and, for the first time, check explicitly that the equivalence between kinetic and canonical orbital angular momentum persists at the level of distributions, as expected in a system without gauge degrees of freedom.

  19. Modeling the effects of forest harvesting on landscape structure and the spatial distribution of cowbird brood parasitism

    Science.gov (United States)

    Eric J. Gustafson; Thomas R. Crow

    1994-01-01

    Timber harvesting affects both composition and structure of the landscape and has important consequences for organisms using forest habitats. A timber harvest allocation model was constructed that allows the input of specific rules to allocate forest stands for clearcutting to generate landscape patterns reflecting the "look and feel" of managed landscapes....

  20. Modelled spatial and seasonal distribution of Blue Whiting (Micromesistius poutassou) larvae in the North-East Atlantic (1951 to 2005)

    DEFF Research Database (Denmark)

    2014-01-01

    Blue whiting (Micromesistius poutassou, http://www.marinespecies.org/aphia.php?p=taxdetails&id=126439) is a small mesopelagic planktivorous gadoid found throughout the North-East Atlantic. This data contains the results of a model-based analysis of larvae captured by the Continuous Plankton...

  1. European Corn Borer life stage model: Regional estimates of pest development and spatial distribution under present and future climate

    Czech Academy of Sciences Publication Activity Database

    Trnka, M.; Muška, F.; Semerádová, Daniela; Dubrovský, Martin; Kocmánková, E.; Žalud, Z.

    2007-01-01

    Roč. 207, 2-4 (2007), s. 61-84 ISSN 0304-3800 R&D Projects: GA MZe QG60051; GA ČR(CZ) GA522/05/0125 Grant - others:6th FP EU(XE) GOCE 037005 Institutional research plan: CEZ:AV0Z30420517 Keywords : Corn borer * ECAMON * GCMs * Degree day model * Climate change impacts Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 2.077, year: 2007

  2. Spatial soil zinc content distribution from terrain parameters: A GIS-based decision-tree model in Lebanon

    Energy Technology Data Exchange (ETDEWEB)

    Bou Kheir, Rania, E-mail: rania.boukheir@agrsci.d [Lebanese University, Faculty of Letters and Human Sciences, Department of Geography, GIS Research Laboratory, P.O. Box 90-1065, Fanar (Lebanon); Department of Agroecology and Environment, Faculty of Agricultural Sciences (DJF), Aarhus University, Blichers Alle 20, P.O. Box 50, DK-8830 Tjele (Denmark); Greve, Mogens H. [Department of Agroecology and Environment, Faculty of Agricultural Sciences (DJF), Aarhus University, Blichers Alle 20, P.O. Box 50, DK-8830 Tjele (Denmark); Abdallah, Chadi [National Council for Scientific Research, Remote Sensing Center, P.O. Box 11-8281, Beirut (Lebanon); Dalgaard, Tommy [Department of Agroecology and Environment, Faculty of Agricultural Sciences (DJF), Aarhus University, Blichers Alle 20, P.O. Box 50, DK-8830 Tjele (Denmark)

    2010-02-15

    Heavy metal contamination has been and continues to be a worldwide phenomenon that has attracted a great deal of attention from governments and regulatory bodies. In this context, our study proposes a regression-tree model to predict the concentration level of zinc in the soils of northern Lebanon (as a case study of Mediterranean landscapes) under a GIS environment. The developed tree-model explained 88% of variance in zinc concentration using pH (100% in relative importance), surroundings of waste areas (90%), proximity to roads (80%), nearness to cities (50%), distance to drainage line (25%), lithology (24%), land cover/use (14%), slope gradient (10%), conductivity (7%), soil type (7%), organic matter (5%), and soil depth (5%). The overall accuracy of the quantitative zinc map produced (at 1:50.000 scale) was estimated to be 78%. The proposed tree model is relatively simple and may also be applied to other areas. - GIS regression-tree analysis explained 88% of the variability in field/laboratory Zinc concentrations.

  3. Modelling spatial distribution of snails transmitting parasitic worms with importance to human and animal health and analysis of distributional changes in relation to climate

    DEFF Research Database (Denmark)

    Pedersen, Ulrik Bo; Midzi, Nicholas; Mduluza, Takafira

    2014-01-01

    The environment, the on-going global climate change and the ecology of animal species determine the localisation of habitats and the geographical distribution of the various species in nature. The aim of this study was to explore the effects of such changes on snail species not only of interest t...

  4. Precipitation-Runoff Modeling System (PRMS) and Streamflow Response to Spatially Distributed Precipitation in Two Large Watersheds in Northern California

    Science.gov (United States)

    Dhakal, A. S.; Adera, S.; Niswonger, R. G.; Gardner, M.

    2016-12-01

    The ability of the Precipitation-Runoff Modeling System (PRMS) to predict peak intensity, peak timing, base flow, and volume of streamflow was examined in Arroyo Hondo (180 km2) and Upper Alameda Creek (85 km2), two sub-watersheds of the Alameda Creek watershed in Northern California. Rainfall-runoff volume ratios vary widely, and can exceed 0.85 during mid-winter flashy rainstorm events. Due to dry antecedent soil moisture conditions, the first storms of the hydrologic year often produce smaller rainfall-runoff volume ratios. Runoff response in this watershed is highly hysteretic; large precipitation events are required to generate runoff following a 4-week period without precipitation. After about 150 mm of cumulative rainfall, streamflow responds quickly to subsequent storms, with variations depending on rainstorm intensity. Inputs to PRMS included precipitation, temperature, topography, vegetation, soils, and land cover data. The data was prepared for input into PRMS using a suite of data processing Python scripts written by the Desert Research Institute and U.S. Geological Survey. PRMS was calibrated by comparing simulated streamflow to measured streamflow at a daily time step during the period 1995 - 2014. The PRMS model is being used to better understand the different patterns of streamflow observed in the Alameda Creek watershed. Although Arroyo Hondo receives more rainfall than Upper Alameda Creek, it is not clear whether the differences in streamflow patterns are a result of differences in rainfall or other variables, such as geology, slope and aspect. We investigate the ability of PRMS to simulate daily streamflow in the two sub-watersheds for a variety of antecedent soil moisture conditions and rainfall intensities. After successful simulation of watershed runoff processes, the model will be expanded using GSFLOW to simulate integrated surface water and groundwater to support water resources planning and management in the Alameda Creek watershed.

  5. Anticipating potential biodiversity conflicts for future biofuel crops in South Africa: incorporating spatial filters with species distribution models

    CSIR Research Space (South Africa)

    Blanchard, R

    2014-04-01

    Full Text Available for biodiversity (Evans et al., 2010, Wilcove et al., 2000), as a wider 17 range of land types can be brought into production when compared to conventional 18 agricultural areas (Beringer et al., 2011, Field et al., 2007, Righelato & Spracklen, 2007). 19 One... modelling (SDM) techniques that rely on 3 presence-only records have been shown to provide a useful screening tool to determine 4 suitable climatic environments for potential dedicated energy crops (Evans et al., 2010). The 5 recent use of SDMs...

  6. Application of inverse modeling technique to describe hydrogeochemical processes responsible to spatial distribution of groundwater quality along flowpath

    Directory of Open Access Journals (Sweden)

    Tjahyo NugrohoAdji

    2013-07-01

    The result shows that firstly, the aquifer within the research area can be grouped into several aquifer systems (i.e. denudational hill, colluvial plain, alluvial plain, and beach ridges from recharge to discharge which generally have potential groundwater resources in terms of the depth and fluctuation of groundwater table. Secondly, flownets analysis gives three flowpaths that are plausible to be modeled in order to describe their hydrogeochemical reactions. Thirdly, the Saturation Indices (SI analysis shows that there are a positive correlation between the mineral occurrence and composition and the value of SI from recharge to discharge. In addition, The Mass Balance Model indicates that dissolution and precipitation of aquifer minerals is dominantly change the chemical composition along flowpath and the rate of the mass transfer between two wells shows a discrepancy and be certain of the percentage of the nature of aquifer mineral. Lastly, there is an interesting characteristic of mass balance chemical reaction occurs which is the entire chemical reaction shows that the sum of smallest mineral fmmol/litre will firstly always totally be reacted.

  7. Study on Finite Element Model Updating in Highway Bridge Static Loading Test Using Spatially-Distributed Optical Fiber Sensors.

    Science.gov (United States)

    Wu, Bitao; Lu, Huaxi; Chen, Bo; Gao, Zhicheng

    2017-07-19

    A finite model updating method that combines dynamic-static long-gauge strain responses is proposed for highway bridge static loading tests. For this method, the objective function consisting of static long-gauge stains and the first order modal macro-strain parameter (frequency) is established, wherein the local bending stiffness, density and boundary conditions of the structures are selected as the design variables. The relationship between the macro-strain and local element stiffness was studied first. It is revealed that the macro-strain is inversely proportional to the local stiffness covered by the long-gauge strain sensor. This corresponding relation is important for the modification of the local stiffness based on the macro-strain. The local and global parameters can be simultaneously updated. Then, a series of numerical simulation and experiments were conducted to verify the effectiveness of the proposed method. The results show that the static deformation, macro-strain and macro-strain modal can be predicted well by using the proposed updating model.

  8. Environmental Distributions of Benzo[a]pyrene in China: Current and Future Emission Reduction Scenarios Explored Using a Spatially Explicit Multimedia Fate Model.

    Science.gov (United States)

    Zhu, Ying; Tao, Shu; Price, Oliver R; Shen, Huizhong; Jones, Kevin C; Sweetman, Andrew J

    2015-12-01

    SESAMe v3.0, a spatially explicit multimedia fate model with 50 × 50 km(2) resolution, has been developed for China to predict environmental concentrations of benzo[a]pyrene (BaP) using an atmospheric emission inventory for 2007. Model predictions are compared with environmental monitoring data obtained from an extensive review of the literature. The model performs well in predicting multimedia concentrations and distributions. Predicted concentrations are compared with guideline values; highest values with some exceedances occur mainly in the North China Plain, Mid Inner Mongolia, and parts of three northeast provinces, Xi'an, Shanghai, and south of Jiangsu province, East Sichuan Basin, middle of Guizhou and Guangzhou. Two potential future scenarios have been assessed using SESAMe v3.0 for 2030 as BaP emission is reduced by (1) technological improvement for coal consumption in energy production and industry sectors in Scenario 1 (Sc1) and (2) technological improvement and control of indoor biomass burning for cooking and indoor space heating and prohibition of open burning of biomass in 2030 in Scenario 2 (Sc2). Sc2 is more efficient in reducing the areas with exceedance of guideline values. Use of SESAMe v3.0 provides insights on future research needs and can inform decision making on options for source reduction.

  9. Mathematical models application for mapping soils spatial distribution on the example of the farm from the North of Udmurt Republic of Russia

    Science.gov (United States)

    Dokuchaev, P. M.; Meshalkina, J. L.; Yaroslavtsev, A. M.

    2018-01-01

    Comparative analysis of soils geospatial modeling using multinomial logistic regression, decision trees, random forest, regression trees and support vector machines algorithms was conducted. The visual interpretation of the digital maps obtained and their comparison with the existing map, as well as the quantitative assessment of the individual soil groups detection overall accuracy and of the models kappa showed that multiple logistic regression, support vector method, and random forest models application with spatial prediction of the conditional soil groups distribution can be reliably used for mapping of the study area. It has shown the most accurate detection for sod-podzolics soils (Phaeozems Albic) lightly eroded and moderately eroded soils. In second place, according to the mean overall accuracy of the prediction, there are sod-podzolics soils – non-eroded and warp one, as well as sod-gley soils (Umbrisols Gleyic) and alluvial soils (Fluvisols Dystric, Umbric). Heavy eroded sod-podzolics and gray forest soils (Phaeozems Albic) were detected by methods of automatic classification worst of all.

  10. Quantitative evaluation of legacy phosphorus and its spatial distribution.

    Science.gov (United States)

    Lou, Hezhen; Zhao, Changsen; Yang, Shengtian; Shi, Liuhua; Wang, Yue; Ren, Xiaoyu; Bai, Juan

    2018-04-01

    A phosphorus resource crisis threatens the security of global crop production, especially in developing countries like China and Brazil. Legacy phosphorus (legacy-P), which is left behind in agricultural soil by over-fertilization, can help address this issue as a new resource in the soil phosphorus pool. However, issues involved with calculating and defining the spatial distribution of legacy-P hinder its future utilization. To resolve these issues, this study applied remote sensing and ecohydrological modeling to precisely quantify legacy-P and define its spatial distribution in China's Sanjiang Plain from 2000 to 2014. The total legacy-P in the study area was calculated as 579,090 t with an annual average of 38,600 t; this comprises 51.83% of the phosphorus fertilizer applied annually. From 2000 to 2014, the annual amount of legacy-P increased by more than 3.42-fold, equivalent to a 2460-ton increase each year. The spatial distribution of legacy-P showed heterogeneity and agglomeration in this area, with peaks in cultivated land experiencing long-term agricultural development. This study supplies a new approach to finding legacy-P in soil as a precondition for future utilization. Once its spatial distribution is known, legacy-P can be better utilized in agriculture to help alleviate the phosphorus resource crisis. Copyright © 2018 Elsevier Ltd. All rights reserved.

  11. Gulf of California species and catch spatial distributions and historical time series - Developing end-to-end models of the Gulf of California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The purpose of this project is to develop spatially discrete end-to-end models of the northern Gulf of California, linking oceanography, biogeochemistry, food web...

  12. Assessing conditions influencing the longitudinal distribution of exotic brown trout (Salmo trutta) in a mountain stream: a spatially-explicit modeling approach

    Science.gov (United States)

    Meredith, Christy S.; Budy, Phaedra; Hooten, Mevin B.; Oliveira Prates, Marcos

    2017-01-01

    Trout species often segregate along elevational gradients, yet the mechanisms driving this pattern are not fully understood. On the Logan River, Utah, USA, exotic brown trout (Salmo trutta) dominate at low elevations but are near-absent from high elevations with native Bonneville cutthroat trout (Onchorhynchus clarkii utah). We used a spatially-explicit Bayesian modeling approach to evaluate how abiotic conditions (describing mechanisms related to temperature and physical habitat) as well as propagule pressure explained the distribution of brown trout in this system. Many covariates strongly explained redd abundance based on model performance and coefficient strength, including average annual temperature, average summer temperature, gravel availability, distance from a concentrated stocking area, and anchor ice-impeded distance from a concentrated stocking area. In contrast, covariates that exhibited low performance in models and/or a weak relationship to redd abundance included reach-average water depth, stocking intensity to the reach, average winter temperature, and number of days with anchor ice. Even if climate change creates more suitable summer temperature conditions for brown trout at high elevations, our findings suggest their success may be limited by other conditions. The potential role of anchor ice in limiting movement upstream is compelling considering evidence suggesting anchor ice prevalence on the Logan River has decreased significantly over the last several decades, likely in response to climatic changes. Further experimental and field research is needed to explore the role of anchor ice, spawning gravel availability, and locations of historical stocking in structuring brown trout distributions on the Logan River and elsewhere.

  13. Spatial Modeling for Resources Framework (SMRF)

    Science.gov (United States)

    Spatial Modeling for Resources Framework (SMRF) was developed by Dr. Scott Havens at the USDA Agricultural Research Service (ARS) in Boise, ID. SMRF was designed to increase the flexibility of taking measured weather data and distributing the point measurements across a watershed. SMRF was developed...

  14. Environmental DNA reflects spatial and temporal jellyfish distribution

    OpenAIRE

    Minamoto, Toshifumi; Fukuda, Miho; Katsuhara, Koki R.; Fujiwara, Ayaka; Hidaka, Shunsuke; Yamamoto, Satoshi; Takahashi, Kohji; Masuda, Reiji

    2017-01-01

    Recent development of environmental DNA (eDNA) analysis allows us to survey underwater macro-organisms easily and cost effectively; however, there have been no reports on eDNA detection or quantification for jellyfish. Here we present the first report on an eDNA analysis of marine jellyfish using Japanese sea nettle (Chrysaora pacifica) as a model species by combining a tank experiment with spatial and temporal distribution surveys. We performed a tank experiment monitoring eDNA concentration...

  15. Spatial and temporal distribution of natural disasters

    Directory of Open Access Journals (Sweden)

    Cvetković Vladimir M.

    2014-01-01

    Full Text Available The subject of quantitative research is determining the spatial and temporal distribution of natural disasters worldwide for the period 1900-2013. Considering that it is a mass phenomenon, which consists of multiple units, most preferred scientific method for making conclusions on natural disasters is the statistical method. Thereby, a statistical survey has been conducted in the way that raw data about all natural disasters in the first step were downloaded (25.552 in the form of Excel file from the international database on disasters (CRED in Brussels, and then analyzed in program for statistical analysis of data SPSS. Within the geospatial distribution the total number and consequences of natural disasters were analyzed by continents. According to the same principle, within temporal analysis we examined distribution of the total number and effects of natural disasters on annual, monthly and daily levels. Statistical results of analysis clearly indicate that the number of natural disasters has increased, with their recorded maximum in the period from 2000 to 2013. Certainly, one can not absolutely say this is true in view of starting to pay serious attention to quantitative indicators. Also, it can not be said that the international database (CRED included absolutely all natural disasters in the world, considering that it was created thanks to the submission of national reports on natural disasters. Such way of data collection can have serious shortcomings, given the diverse subjectivities. In addition, the question that arises is whether most underdeveloped countries submitted their reports. Bearing in mind the increasing trend in the number and severity of natural disasters in the global geographic space, the survey results represent a good argument for initiation of serious reforms of the system of protection and rescue against natural disasters in countries around the world. Results of research impact on raising awareness among citizens

  16. Spatial Distribution of Infection Risk of SARS Transmission in a Hospital Ward

    DEFF Research Database (Denmark)

    Qian, Hua; Li, Yuguo; Nielsen, Peter V.

    2009-01-01

    The classical Wells-Riley model for predicting risk of airborne transmission of diseases assumes a uniform spatial distribution of the infected cases in an enclosed space. A new mathematical model is developed here for predicting the spatial distribution of infection risk of airborne transmitted ......, such as inpatients in a hospital ward, passengers in an airplane etc....

  17. Species Composition of Sand Flies (Diptera: Psychodidae) and Modeling the Spatial Distribution of Main Vectors of Cutaneous Leishmaniasis in Hormozgan Province, Southern Iran.

    Science.gov (United States)

    Hanafi-Bojd, Ahmad Ali; Khoobdel, Mehdi; Soleimani-Ahmadi, Moussa; Azizi, Kourosh; Aghaei Afshar, Abbas; Jaberhashemi, Seyed Aghil; Fekri, Sajjad; Safari, Reza

    2018-02-28

    Cutaneous Leishmaniasis (CL) is one of the main neglected vector-borne diseases in the Middle East, including Iran. This study aimed to map the spatial distribution and species composition of sand flies in Hormozgan Province and to predict the best ecological niches for main CL vectors in this area. A database that included all earlier studies on sand flies in Hormozgan Province was established. Sand flies were also collected from some localities across the province. Prediction maps for main vectors were developed using MaxEnt model. A total of 27 sand fly species were reported from the study area. Phlebotomus papatasi Scopoli, Phlebotomus sergenti s.l. Parrot, Phlebotomus alexandri Sinton, Sergentomyia sintoni Pringle, Sergentomyia clydei Sinton, Sergentomyia tiberiadis Adler, and Sergentomyia baghdadis Adler (Diptera: Psychodidae) had the widest distribution range. The probability of their presence as the main vectors of CL was calculated to be 0.0003-0.9410 and 0.0031-0.8880 for P. papatasi and P. sergenti s.l., respectively. The best ecological niches for P. papatasi were found in the central south, southeast, and a narrow area in southwest, whereas central south to northern area had better niches for P. sergenti s.l. The endemic areas are in Bandar-e Jask, where transmission occurs, whereas in Bastak, the cases were imported from endemic foci of Fars province. In conclusion, proven and suspected vectors of CL and VL were recorded in this study. Due to the existence of endemic foci of CL, and favorite ecological niches for its vectors, there is potential risk of emerging CL in new areas.

  18. Integrating SMOS brightness temperatures with a new conceptual spatially distributed hydrological model for improving flood and drought predictions at large scale.

    Science.gov (United States)

    Hostache, Renaud; Rains, Dominik; Chini, Marco; Lievens, Hans; Verhoest, Niko E. C.; Matgen, Patrick

    2017-04-01

    Motivated by climate change and its impact on the scarcity or excess of water in many parts of the world, several agencies and research institutions have taken initiatives in monitoring and predicting the hydrologic cycle at a global scale. Such a monitoring/prediction effort is important for understanding the vulnerability to extreme hydrological events and for providing early warnings. This can be based on an optimal combination of hydro-meteorological models and remote sensing, in which satellite measurements can be used as forcing or calibration data or for regularly updating the model states or parameters. Many advances have been made in these domains and the near future will bring new opportunities with respect to remote sensing as a result of the increasing number of spaceborn sensors enabling the large scale monitoring of water resources. Besides of these advances, there is currently a tendency to refine and further complicate physically-based hydrologic models to better capture the hydrologic processes at hand. However, this may not necessarily be beneficial for large-scale hydrology, as computational efforts are therefore increasing significantly. As a matter of fact, a novel thematic science question that is to be investigated is whether a flexible conceptual model can match the performance of a complex physically-based model for hydrologic simulations at large scale. In this context, the main objective of this study is to investigate how innovative techniques that allow for the estimation of soil moisture from satellite data can help in reducing errors and uncertainties in large scale conceptual hydro-meteorological modelling. A spatially distributed conceptual hydrologic model has been set up based on recent developments of the SUPERFLEX modelling framework. As it requires limited computational efforts, this model enables early warnings for large areas. Using as forcings the ERA-Interim public dataset and coupled with the CMEM radiative transfer model

  19. Spatial and temporal patterns of global onshore wind speed distribution

    International Nuclear Information System (INIS)

    Zhou, Yuyu; Smith, Steven J

    2013-01-01

    Wind power, a renewable energy source, can play an important role in electrical energy generation. Information regarding wind energy potential is important both for energy related modeling and for decision-making in the policy community. While wind speed datasets with high spatial and temporal resolution are often ultimately used for detailed planning, simpler assumptions are often used in analysis work. An accurate representation of the wind speed frequency distribution is needed in order to properly characterize wind energy potential. Using a power density method, this study estimated global variation in wind parameters as fitted to a Weibull density function using NCEP/climate forecast system reanalysis (CFSR) data over land areas. The Weibull distribution performs well in fitting the time series wind speed data at most locations according to R 2 , root mean square error, and power density error. The wind speed frequency distribution, as represented by the Weibull k parameter, exhibits a large amount of spatial variation, a regionally varying amount of seasonal variation, and relatively low decadal variation. We also analyzed the potential error in wind power estimation when a commonly assumed Rayleigh distribution (Weibull k = 2) is used. We find that the assumption of the same Weibull parameter across large regions can result in non-negligible errors. While large-scale wind speed data are often presented in the form of mean wind speeds, these results highlight the need to also provide information on the wind speed frequency distribution. (letter)

  20. Impact of the aging process of black carbon aerosols on their spatial distribution, hygroscopicity, and radiative forcing in a global climate model

    Science.gov (United States)

    Goto, D.; Oshima, N.; Nakajima, T.; Takemura, T.; Ohara, T.

    2012-11-01

    Black carbon (BC) absorbs shortwave radiation more strongly than any other type of aerosol, and an accurate simulation of the aging processes of BC-containing particle is required to properly predict aerosol radiative forcing (ARF) and climate change. However, BC aging processes have been simplified in general circulation models (GCMs) due to limited computational resources. In particular, differences in the representation of the mixing states of BC-containing particles between GCMs constitute one of main reasons for the uncertainty in ARF estimates. To understand an impact of the BC aging processes and the mixing state of BC on the spatial distribution of BC and ARF caused by BC (BC-ARF), we implemented three different methods of incorporating BC aging processes into a global aerosol transport model, SPRINTARS: (1) the "AGV" method, using variable conversion rates of BC aging based on a new type of parameterization depending on both BC amount and sulfuric acid; (2) the "AGF" method, using a constant conversion rate used worldwide in GCMs; and (3) the "ORIG" method, which is used in the original SPRINTARS. First, we found that these different methods produced different BC burden within 10% over industrial areas and 50% over remote oceans. Second, a ratio of water-insoluble BC to total BC (WIBC ratio) was very different among the three methods. Near the BC source region, for example, the WIBC ratios were estimated to be 80-90% (AGV and AGF) and 50-60% (ORIG). Third, although the BC aging process in GCMs had small impacts on the BC burden, they had a large impact on BC-ARF through a change in both the WIBC ratio and non-BC compounds coating on BC cores. As a result, possible differences in the treatment of the BC aging process between aerosol modeling studies can produce a difference of approximately 0.3 Wm-2 in the magnitude of BC-ARF, which is comparable to the uncertainty suggested by results from a global aerosol modeling intercomparison project, AeroCom. The

  1. Hierarchical Bayesian spatial models for multispecies conservation planning and monitoring.

    Science.gov (United States)

    Carroll, Carlos; Johnson, Devin S; Dunk, Jeffrey R; Zielinski, William J

    2010-12-01

    Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence-absence data derived from regional monitoring programs to develop models with both landscape and site-level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence-absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad-scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km(2) hexagons), can increase the relevance of habitat models to multispecies

  2. Modeling the irradiation facility in the Deir Al-Hajar area to calculate the spatial gamma dose distribution using the MCNP code

    International Nuclear Information System (INIS)

    Khattab, K.; Bush, M; Kassery, H.

    2009-03-01

    A 3-D model for the irradiation plant which belongs to the Atomic Energy Commission, Department of Radiation Technology in the Deir Al-Hajar area near Damascus, is presented in this work using the MCNP-4C code. This model is used to calculate the spatial gamma ray dose in the (x, y, z) coordinate. Good agreements are noticed between the measured and the calculated results. (author)

  3. On the spatial distributions of dense cores in Orion B

    Science.gov (United States)

    Parker, Richard J.

    2018-05-01

    We quantify the spatial distributions of dense cores in three spatially distinct areas of the Orion B star-forming region. For L1622, NGC 2068/NGC 2071, and NGC 2023/NGC 2024, we measure the amount of spatial substructure using the Q-parameter and find all three regions to be spatially substructured (Q Orion B, the mass segregation cannot be dynamical. Our results are also inconsistent with simulations in which the most massive stars form via competitive accretion, and instead hint that magnetic fields may be important in influencing the primordial spatial distributions of gas and stars in star-forming regions.

  4. RSS as a distribution medium for geo-spatial hypermedia

    DEFF Research Database (Denmark)

    Hansen, Frank Allan; Christensen, Bent Guldbjerg; Bouvin, Niels Olof

    2005-01-01

    This paper describes how the XML based RSS syndication formats used in weblogs can be utilized as the distribution medium for geo-spatial hypermedia, and how this approach can be used to create a highly distributed multi-user annotation system for geo-spatial hypermedia. It is demonstrated, how...

  5. [Thoughts on the spatial distribution of population].

    Science.gov (United States)

    Borisovna, L; Velez, F

    1991-12-01

    city in all age groups, especially in the 15-19 cohort. A large proportion of the migrants were more highly educated than the average city dweller. The average rate of growth of the working age population in the city was 6% from 1970-80, implying a need for 35,000 new jobs annually. But in 1980-90, only 10,000 new jobs were added each year. The relative importance of tertiary sector employment has increased significantly. A review of the population characteristics and spatial distribution of the city and state of Puebla strongly suggests that decentralization should be vigorously pursued as a means of improving the wellbeing of the population.

  6. Comparison of modeling methods to predict the spatial distribution of deep-sea coral and sponge in the Gulf of Alaska

    Science.gov (United States)

    Rooper, Christopher N.; Zimmermann, Mark; Prescott, Megan M.

    2017-08-01

    Deep-sea coral and sponge ecosystems are widespread throughout most of Alaska's marine waters, and are associated with many different species of fishes and invertebrates. These ecosystems are vulnerable to the effects of commercial fishing activities and climate change. We compared four commonly used species distribution models (general linear models, generalized additive models, boosted regression trees and random forest models) and an ensemble model to predict the presence or absence and abundance of six groups of benthic invertebrate taxa in the Gulf of Alaska. All four model types performed adequately on training data for predicting presence and absence, with regression forest models having the best overall performance measured by the area under the receiver-operating-curve (AUC). The models also performed well on the test data for presence and absence with average AUCs ranging from 0.66 to 0.82. For the test data, ensemble models performed the best. For abundance data, there was an obvious demarcation in performance between the two regression-based methods (general linear models and generalized additive models), and the tree-based models. The boosted regression tree and random forest models out-performed the other models by a wide margin on both the training and testing data. However, there was a significant drop-off in performance for all models of invertebrate abundance ( 50%) when moving from the training data to the testing data. Ensemble model performance was between the tree-based and regression-based methods. The maps of predictions from the models for both presence and abundance agreed very well across model types, with an increase in variability in predictions for the abundance data. We conclude that where data conforms well to the modeled distribution (such as the presence-absence data and binomial distribution in this study), the four types of models will provide similar results, although the regression-type models may be more consistent with

  7. Spatial Distribution of Soil Fauna In Long Term No Tillage

    Science.gov (United States)

    Corbo, J. Z. F.; Vieira, S. R.; Siqueira, G. M.

    2012-04-01

    The soil is a complex system constituted by living beings, organic and mineral particles, whose components define their physical, chemical and biological properties. Soil fauna plays an important role in soil and may reflect and interfere in its functionality. These organisms' populations may be influenced by management practices, fertilization, liming and porosity, among others. Such changes may reduce the composition and distribution of soil fauna community. Thus, this study aimed to determine the spatial variability of soil fauna in consolidated no-tillage system. The experimental area is located at Instituto Agronômico in Campinas (São Paulo, Brazil). The sampling was conducted in a Rhodic Eutrudox, under no tillage system and 302 points distributed in a 3.2 hectare area in a regular grid of 10.00 m x 10.00 m were sampled. The soil fauna was sampled with "Pitfall Traps" method and traps remained in the area for seven days. Data were analyzed using descriptive statistics to determine the main statistical moments (mean variance, coefficient of variation, standard deviation, skewness and kurtosis). Geostatistical tools were used to determine the spatial variability of the attributes using the experimental semivariogram. For the biodiversity analysis, Shannon and Pielou indexes and richness were calculated for each sample. Geostatistics has proven to be a great tool for mapping the spatial variability of groups from the soil epigeal fauna. The family Formicidae proved to be the most abundant and dominant in the study area. The parameters of descriptive statistics showed that all attributes studied showed lognormal frequency distribution for groups from the epigeal soil fauna. The exponential model was the most suited for the obtained data, for both groups of epigeal soil fauna (Acari, Araneae, Coleoptera, Formicidae and Coleoptera larva), and the other biodiversity indexes. The sampling scheme (10.00 m x 10.00 m) was not sufficient to detect the spatial

  8. Origin of Pareto-like spatial distributions in ecosystems.

    Science.gov (United States)

    Manor, Alon; Shnerb, Nadav M

    2008-12-31

    Recent studies of cluster distribution in various ecosystems revealed Pareto statistics for the size of spatial colonies. These results were supported by cellular automata simulations that yield robust criticality for endogenous pattern formation based on positive feedback. We show that this patch statistics is a manifestation of the law of proportionate effect. Mapping the stochastic model to a Markov birth-death process, the transition rates are shown to scale linearly with cluster size. This mapping provides a connection between patch statistics and the dynamics of the ecosystem; the "first passage time" for different colonies emerges as a powerful tool that discriminates between endogenous and exogenous clustering mechanisms. Imminent catastrophic shifts (such as desertification) manifest themselves in a drastic change of the stability properties of spatial colonies.

  9. Flow distributions and spatial correlations in human brain capillary networks

    Science.gov (United States)

    Lorthois, Sylvie; Peyrounette, Myriam; Larue, Anne; Le Borgne, Tanguy

    2015-11-01

    The vascular system of the human brain cortex is composed of a space filling mesh-like capillary network connected upstream and downstream to branched quasi-fractal arterioles and venules. The distribution of blood flow rates in these networks may affect the efficiency of oxygen transfer processes. Here, we investigate the distribution and correlation properties of blood flow velocities from numerical simulations in large 3D human intra-cortical vascular network (10000 segments) obtained from an anatomical database. In each segment, flow is solved from a 1D non-linear model taking account of the complex rheological properties of blood flow in microcirculation to deduce blood pressure, blood flow and red blood cell volume fraction distributions throughout the network. The network structural complexity is found to impart broad and spatially correlated Lagrangian velocity distributions, leading to power law transit time distributions. The origins of this behavior (existence of velocity correlations in capillary networks, influence of the coupling with the feeding arterioles and draining veins, topological disorder, complex blood rheology) are studied by comparison with results obtained in various model capillary networks of controlled disorder. ERC BrainMicroFlow GA615102, ERC ReactiveFronts GA648377.

  10. Temporal acceleration of spatially distributed kinetic Monte Carlo simulations

    International Nuclear Information System (INIS)

    Chatterjee, Abhijit; Vlachos, Dionisios G.

    2006-01-01

    The computational intensity of kinetic Monte Carlo (KMC) simulation is a major impediment in simulating large length and time scales. In recent work, an approximate method for KMC simulation of spatially uniform systems, termed the binomial τ-leap method, was introduced [A. Chatterjee, D.G. Vlachos, M.A. Katsoulakis, Binomial distribution based τ-leap accelerated stochastic simulation, J. Chem. Phys. 122 (2005) 024112], where molecular bundles instead of individual processes are executed over coarse-grained time increments. This temporal coarse-graining can lead to significant computational savings but its generalization to spatially lattice KMC simulation has not been realized yet. Here we extend the binomial τ-leap method to lattice KMC simulations by combining it with spatially adaptive coarse-graining. Absolute stability and computational speed-up analyses for spatial systems along with simulations provide insights into the conditions where accuracy and substantial acceleration of the new spatio-temporal coarse-graining method are ensured. Model systems demonstrate that the r-time increment criterion of Chatterjee et al. obeys the absolute stability limit for values of r up to near 1

  11. Modelling Deep Water Habitats to Develop a Spatially Explicit, Fine Scale Understanding of the Distribution of the Western Rock Lobster, Panulirus cygnus

    Science.gov (United States)

    Hovey, Renae K.; Van Niel, Kimberly P.; Bellchambers, Lynda M.; Pember, Matthew B.

    2012-01-01

    Background The western rock lobster, Panulirus cygnus, is endemic to Western Australia and supports substantial commercial and recreational fisheries. Due to and its wide distribution and the commercial and recreational importance of the species a key component of managing western rock lobster is understanding the ecological processes and interactions that may influence lobster abundance and distribution. Using terrain analyses and distribution models of substrate and benthic biota, we assess the physical drivers that influence the distribution of lobsters at a key fishery site. Methods and Findings Using data collected from hydroacoustic and towed video surveys, 20 variables (including geophysical, substrate and biota variables) were developed to predict the distributions of substrate type (three classes of reef, rhodoliths and sand) and dominant biota (kelp, sessile invertebrates and macroalgae) within a 40 km2 area about 30 km off the west Australian coast. Lobster presence/absence data were collected within this area using georeferenced pots. These datasets were used to develop a classification tree model for predicting the distribution of the western rock lobster. Interestingly, kelp and reef were not selected as predictors. Instead, the model selected geophysical and geomorphic scalar variables, which emphasise a mix of terrain within limited distances. The model of lobster presence had an adjusted D2 of 64 and an 80% correct classification. Conclusions Species distribution models indicate that juxtaposition in fine scale terrain is most important to the western rock lobster. While key features like kelp and reef may be important to lobster distribution at a broad scale, it is the fine scale features in terrain that are likely to define its ecological niche. Determining the most appropriate landscape configuration and scale will be essential to refining niche habitats and will aid in selecting appropriate sites for protecting critical lobster habitats. PMID

  12. Spatial Distribution of Black Bear Incident Reports in Michigan.

    Directory of Open Access Journals (Sweden)

    Jamie E McFadden-Hiller

    Full Text Available Interactions between humans and carnivores have existed for centuries due to competition for food and space. American black bears are increasing in abundance and populations are expanding geographically in many portions of its range, including areas that are also increasing in human density, often resulting in associated increases in human-bear conflict (hereafter, bear incidents. We used public reports of bear incidents in Michigan, USA, from 2003-2011 to assess the relative contributions of ecological and anthropogenic variables in explaining the spatial distribution of bear incidents and estimated the potential risk of bear incidents. We used weighted Normalized Difference Vegetation Index mean as an index of primary productivity, region (i.e., Upper Peninsula or Lower Peninsula, primary and secondary road densities, and percentage land cover type within 6.5-km2 circular buffers around bear incidents and random points. We developed 22 a priori models and used generalized linear models and Akaike's Information Criterion (AIC to rank models. The global model was the best compromise between model complexity and model fit (w = 0.99, with a ΔAIC 8.99 units from the second best performing model. We found that as deciduous forest cover increased, the probability of bear incident occurrence increased. Among the measured anthropogenic variables, cultivated crops and primary roads were the most important in our AIC-best model and were both positively related to the probability of bear incident occurrence. The spatial distribution of relative bear incident risk varied markedly throughout Michigan. Forest cover fragmented with agriculture and other anthropogenic activities presents an environment that likely facilitates bear incidents. Our map can help wildlife managers identify areas of bear incident occurrence, which in turn can be used to help develop strategies aimed at reducing incidents. Researchers and wildlife managers can use similar mapping

  13. Spatial Distribution of Black Bear Incident Reports in Michigan.

    Science.gov (United States)

    McFadden-Hiller, Jamie E; Beyer, Dean E; Belant, Jerrold L

    2016-01-01

    Interactions between humans and carnivores have existed for centuries due to competition for food and space. American black bears are increasing in abundance and populations are expanding geographically in many portions of its range, including areas that are also increasing in human density, often resulting in associated increases in human-bear conflict (hereafter, bear incidents). We used public reports of bear incidents in Michigan, USA, from 2003-2011 to assess the relative contributions of ecological and anthropogenic variables in explaining the spatial distribution of bear incidents and estimated the potential risk of bear incidents. We used weighted Normalized Difference Vegetation Index mean as an index of primary productivity, region (i.e., Upper Peninsula or Lower Peninsula), primary and secondary road densities, and percentage land cover type within 6.5-km2 circular buffers around bear incidents and random points. We developed 22 a priori models and used generalized linear models and Akaike's Information Criterion (AIC) to rank models. The global model was the best compromise between model complexity and model fit (w = 0.99), with a ΔAIC 8.99 units from the second best performing model. We found that as deciduous forest cover increased, the probability of bear incident occurrence increased. Among the measured anthropogenic variables, cultivated crops and primary roads were the most important in our AIC-best model and were both positively related to the probability of bear incident occurrence. The spatial distribution of relative bear incident risk varied markedly throughout Michigan. Forest cover fragmented with agriculture and other anthropogenic activities presents an environment that likely facilitates bear incidents. Our map can help wildlife managers identify areas of bear incident occurrence, which in turn can be used to help develop strategies aimed at reducing incidents. Researchers and wildlife managers can use similar mapping techniques to

  14. Bounding species distribution models

    Directory of Open Access Journals (Sweden)

    Thomas J. STOHLGREN, Catherine S. JARNEVICH, Wayne E. ESAIAS,Jeffrey T. MORISETTE

    2011-10-01

    Full Text Available Species distribution models are increasing in popularity for mapping suitable habitat for species of management concern. Many investigators now recognize that extrapolations of these models with geographic information systems (GIS might be sensitive to the environmental bounds of the data used in their development, yet there is no recommended best practice for “clamping” model extrapolations. We relied on two commonly used modeling approaches: classification and regression tree (CART and maximum entropy (Maxent models, and we tested a simple alteration of the model extrapolations, bounding extrapolations to the maximum and minimum values of primary environmental predictors, to provide a more realistic map of suitable habitat of hybridized Africanized honey bees in the southwestern United States. Findings suggest that multiple models of bounding, and the most conservative bounding of species distribution models, like those presented here, should probably replace the unbounded or loosely bounded techniques currently used [Current Zoology 57 (5: 642–647, 2011].

  15. Bounding Species Distribution Models

    Science.gov (United States)

    Stohlgren, Thomas J.; Jarnevich, Cahterine S.; Morisette, Jeffrey T.; Esaias, Wayne E.

    2011-01-01

    Species distribution models are increasing in popularity for mapping suitable habitat for species of management concern. Many investigators now recognize that extrapolations of these models with geographic information systems (GIS) might be sensitive to the environmental bounds of the data used in their development, yet there is no recommended best practice for "clamping" model extrapolations. We relied on two commonly used modeling approaches: classification and regression tree (CART) and maximum entropy (Maxent) models, and we tested a simple alteration of the model extrapolations, bounding extrapolations to the maximum and minimum values of primary environmental predictors, to provide a more realistic map of suitable habitat of hybridized Africanized honey bees in the southwestern United States. Findings suggest that multiple models of bounding, and the most conservative bounding of species distribution models, like those presented here, should probably replace the unbounded or loosely bounded techniques currently used [Current Zoology 57 (5): 642-647, 2011].

  16. Spatial and mass distributions of molecular clouds and spiral structure

    International Nuclear Information System (INIS)

    Kwan, J.; Valdes, F.; National Optical Astronomy Observatories, Tucson, AZ)

    1987-01-01

    The growth of molecular clouds resulting from cloud-cloud collisions and coalescence in the Galactic ring between 4 and 8 kpc are modeled, taking into account the presence of a spiral potential and the mutual cloud-cloud gravitational attraction. The mean lifetime of molecular clouds is determined to be about 200 million years. The clouds are present in both spiral arm and interarm regions, but a spiral pattern in their spatial distribution is clearly discernible, with the more massive clouds showing a stronger correlation with the spiral arms. As viewed from within the Galactic disk, however, it is very difficult to ascertain that the molecular cloud distribution in longitude-velocity space has a spiral pattern. 19 references

  17. Gaussian theory for spatially distributed self-propelled particles

    Science.gov (United States)

    Seyed-Allaei, Hamid; Schimansky-Geier, Lutz; Ejtehadi, Mohammad Reza

    2016-12-01

    Obtaining a reduced description with particle and momentum flux densities outgoing from the microscopic equations of motion of the particles requires approximations. The usual method, we refer to as truncation method, is to zero Fourier modes of the orientation distribution starting from a given number. Here we propose another method to derive continuum equations for interacting self-propelled particles. The derivation is based on a Gaussian approximation (GA) of the distribution of the direction of particles. First, by means of simulation of the microscopic model, we justify that the distribution of individual directions fits well to a wrapped Gaussian distribution. Second, we numerically integrate the continuum equations derived in the GA in order to compare with results of simulations. We obtain that the global polarization in the GA exhibits a hysteresis in dependence on the noise intensity. It shows qualitatively the same behavior as we find in particles simulations. Moreover, both global polarizations agree perfectly for low noise intensities. The spatiotemporal structures of the GA are also in agreement with simulations. We conclude that the GA shows qualitative agreement for a wide range of noise intensities. In particular, for low noise intensities the agreement with simulations is better as other approximations, making the GA to an acceptable candidates of describing spatially distributed self-propelled particles.

  18. Spatial and temporal distribution of onroad CO2 emissions at the Urban spatial scale

    Science.gov (United States)

    Song, Y.; Gurney, K. R.; Zhou, Y.; Mendoza, D. L.

    2011-12-01

    The Hestia Project is a multi-disciplinary effort to help better understand the spatial and temporal distribution of fossil fuel carbon dioxide (CO2) emission at urban scale. Onroad transportation is an essential source of CO2 emissions. This study examines two urban domains: Marion County (Indianapolis) and Los Angeles County and explores the methods and results associated with the spatial and temporal distribution of local urban onroad CO2 emissions. We utilize a bottom-up approach and spatially distribute county emissions based on the Annual Average Daily Traffic (AADT) counts provided by local Department of Transportation. The total amount of CO2 emissions is calculated by the National Mobile Inventory Model (NMIM) for Marion County and the EMission FACtors (EMFAC) model for Los Angeles County. The NMIM model provides CO2 emissions based on vehicle miles traveled (VMT) data at the county-level from the national county database (NCD). The EMFAC model provides CO2 emissions for California State based on vehicle activities, including VMT, vehicle population and fuel types. A GIS road atlas is retrieved from the US Census Bureau. Further spatial analysis and integration are performed by GIS software to distribute onroad CO2 emission according to the traffic volume. The temporal allocation of onroad CO2 emission is based on the hourly traffic data obtained from the Metropolitan Planning Orgnizations (MPO) for Marion County and Department of Transportation for Los Angeles County. The annual CO2 emissions are distributed according to each hourly fraction of traffic counts. Due to the fact that ATR stations are unevenly distributed in space, we create Thiessen polygons such that each road segment is linked to the nearest neighboring ATR station. The hourly profile for each individual station is then combined to create a "climatology" of CO2 emissions in time on each road segment. We find that for Marion County in the year 2002, urban interstate and arterial roads have

  19. Property Improvement in CZT via Modeling and Processing Innovations . Te-particles in vertical gradient freeze CZT: Size and Spatial Distributions and Constitutional Supercooling

    Energy Technology Data Exchange (ETDEWEB)

    Henager, Charles H. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Alvine, Kyle J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Bliss, Mary [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Riley, Brian J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Stave, Jean A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2014-10-01

    A section of a vertical gradient freeze CZT boule approximately 2100-mm3 with a planar area of 300-mm2 was prepared and examined using transmitted IR microscopy at various magnifications to determine the three-dimensional spatial and size distributions of Te-particles over large longitudinal and radial length scales. The boule section was approximately 50-mm wide by 60-mm in length by 7-mm thick and was doubly polished for TIR work. Te-particles were imaged through the thickness using extended focal imaging to locate the particles in thickness planes spaced 15-µm apart and then in plane of the image using xy-coordinates of the particle center of mass so that a true three dimensional particle map was assembled for a 1-mm by 45-mm longitudinal strip and for a 1-mm by 50-mm radial strip. Te-particle density distributions were determined as a function of longitudinal and radial positions in these strips, and treating the particles as vertices of a network created a 3D image of the particle spatial distribution. Te-particles exhibited a multi-modal log-normal size density distribution that indicated a slight preference for increasing size with longitudinal growth time, while showing a pronounced cellular network structure throughout the boule that can be correlated to dislocation network sizes in CZT. Higher magnification images revealed a typical Rayleigh-instability pearl string morphology with large and small satellite droplets. This study includes solidification experiments in small crucibles of 30:70 mixtures of Cd:Te to reduce the melting point below 1273 K (1000°C). These solidification experiments were performed over a wide range of cooling rates and clearly demonstrated a growth instability with Te-particle capture that is suggested to be responsible for one of the peaks in the size distribution using size discrimination visualization. The results are discussed with regard to a manifold Te-particle genesis history as 1) Te

  20. A SVR Learning Based Sensor Placement Approach for Nonlinear Spatially Distributed Systems

    Directory of Open Access Journals (Sweden)

    Xian-xia Zhang

    2016-01-01

    Full Text Available Many industrial processes are inherently distributed in space and time and are called spatially distributed dynamical systems (SDDSs. Sensor placement affects capturing the spatial distribution and then becomes crucial issue to model or control an SDDS. In this study, a new data-driven based sensor placement method is developed. SVR algorithm is innovatively used to extract the characteristics of spatial distribution from a spatiotemporal data set. The support vectors learned by SVR represent the crucial spatial data structure in the spatiotemporal data set, which can be employed to determine optimal sensor location and sensor number. A systematic sensor placement design scheme in three steps (data collection, SVR learning, and sensor locating is developed for an easy implementation. Finally, effectiveness of the proposed sensor placement scheme is validated on two spatiotemporal 3D fuzzy controlled spatially distributed systems.

  1. Effect of the spatial distribution of physical aquifer properties on modelled water table depth and stream discharge in a headwater catchment

    Directory of Open Access Journals (Sweden)

    C. Gascuel-Odoux

    2010-07-01

    Full Text Available Water table depth and its dynamics on hillslopes are often poorly predicted despite they control both water transit time within the catchment and solute fluxes at the catchment outlet. This paper analyses how relaxing the assumption of lateral homogeneity of physical properties can improve simulations of water table depth and dynamics. Four different spatial models relating hydraulic conductivity to topography have been tested: a simple linear relationship, a linear relationship with two different topographic indexes, two Ks domains with a transitional area. The Hill-Vi model has been modified to test these hypotheses. The studied catchment (Kervidy-Naizin, Western France is underlain by schist crystalline bedrock. A shallow and perennial groundwater highly reactive to rainfall events mainly develops in the weathered saprolite layer. The results indicate that (1 discharge and the water table in the riparian zone are similarly predicted by the four models, (2 distinguishing two Ks domains constitutes the best model and slightly improves prediction of the water table upslope, and (3 including spatial variations in the other parameters such as porosity or rate of hydraulic conductivity decrease with depth does not improve the results. These results underline the necessity of better investigations of upslope areas in hillslope hydrology.

  2. Climate change and spatial distribution of vegetation in Colombia

    Directory of Open Access Journals (Sweden)

    Juan Carlos Alarcon Hincapie

    2013-12-01

    Full Text Available Vegetation change under two climate change scenarios in different periods of the 21st Century are modeled for Colombia. Vegetation for the years 1970 to 2000 was reproduced using the Holdridge model with climate data with a spatial resolution of 900 meters. The vegetation types that occupied the most territory were sub-humid tropical forest, tropical dry forest and Andean wet forest. These results were validated by comparing with the Colombian ecosystem map (SINA, 2007, which confirmed a high degree of similarity between the modeled spatial vegetation patterns and modern ecosystem distributions. Future vegetation maps were simulated using data generated by a regional climate model under two scenarios (A2 and B2; IPCC, 2007 for the periods 2011-2040 and 2070-2100. Based on our predictions high altitude vegetation will convert to that of lower altitudes and drier provinces with the most dramatic change occurring in the A2 scenario from 2070-2100. The most affected areas are the páramo and other high Andean vegetation types, which in the timeframe of the explored scenarios will disappear by the middle of the 21st Century.

  3. Impacts of Spatial Distribution of Impervious Areas on Runoff Response of Hillslope Catchments: Simulation Study

    Science.gov (United States)

    This study analyzes variations in the model-projected changes in catchment runoff response after urbanization that stem from variations in the spatial distribution of impervious areas, interevent differences in temporal rainfall structure, and antecedent soil moisture (ASM). In t...

  4. Inner membrane fusion mediates spatial distribution of axonal mitochondria

    Science.gov (United States)

    Yu, Yiyi; Lee, Hao-Chih; Chen, Kuan-Chieh; Suhan, Joseph; Qiu, Minhua; Ba, Qinle; Yang, Ge

    2016-01-01

    In eukaryotic cells, mitochondria form a dynamic interconnected network to respond to changing needs at different subcellular locations. A fundamental yet unanswered question regarding this network is whether, and if so how, local fusion and fission of individual mitochondria affect their global distribution. To address this question, we developed high-resolution computational image analysis techniques to examine the relations between mitochondrial fusion/fission and spatial distribution within the axon of Drosophila larval neurons. We found that stationary and moving mitochondria underwent fusion and fission regularly but followed different spatial distribution patterns and exhibited different morphology. Disruption of inner membrane fusion by knockdown of dOpa1, Drosophila Optic Atrophy 1, not only increased the spatial density of stationary and moving mitochondria but also changed their spatial distributions and morphology differentially. Knockdown of dOpa1 also impaired axonal transport of mitochondria. But the changed spatial distributions of mitochondria resulted primarily from disruption of inner membrane fusion because knockdown of Milton, a mitochondrial kinesin-1 adapter, caused similar transport velocity impairment but different spatial distributions. Together, our data reveals that stationary mitochondria within the axon interconnect with moving mitochondria through fusion and fission and that local inner membrane fusion between individual mitochondria mediates their global distribution. PMID:26742817

  5. Spatial data modelling and maximum entropy theory

    Czech Academy of Sciences Publication Activity Database

    Klimešová, Dana; Ocelíková, E.

    2005-01-01

    Roč. 51, č. 2 (2005), s. 80-83 ISSN 0139-570X Institutional research plan: CEZ:AV0Z10750506 Keywords : spatial data classification * distribution function * error distribution Subject RIV: BD - Theory of Information

  6. Staling of white wheat bread crumb and effect of maltogenic α-amylases. Part 1: Spatial distribution and kinetic modeling of hardness and resilience.

    Science.gov (United States)

    Amigo, José Manuel; Del Olmo Alvarez, Arantxa; Engelsen, Merete Møller; Lundkvist, Henrik; Engelsen, Søren Balling

    2016-10-01

    Bread staling is one of the most costly food deterioration processes. This study presents an in-depth, multivariate, statistical assessment of the differences in the staling process of white wheat bread as a function of storage time, usage of maltogenic α-amylases and spatial position in the loaf by texture measurements and non-linear fitting (Avrami). This study demonstrates the effects of anti-staling enzymes upon bread staling, where significant changes in the spatial staling kinetics occur. While the spatial development of staling is reduced in the outer crumb by anti-staling enzymes, the staling is retarded in the middle. The Avrami model suggests that this happens by two different competing mechanisms: one which increases the initial staling rate, and one which slows the convergence towards the limiting hardness. The two enzyme treated breads differed widely in early and ultimate resilience, despite the fact that they were adjusted to provide the same ultimate hardness. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Biodiversity and spatial distribution of Rotifera in a shallow ...

    African Journals Online (AJOL)

    Biodiversity and spatial distribution of Rotifera in a shallow hyperuetrophic tropical Lake (Cameroon). TSH Zebaze, T Njine, N Kemka, D Niyitegeka, M Nola, MS Foto, E Djiukom, G Ajeagah, HJ Dumont ...

  8. Spatial Distribution and Accessibility of Health Facilities in Akwa ...

    African Journals Online (AJOL)

    The attainment of this goal is a function of the spatial pattern of distribution of healthcare facilities and a measure of the degree of accessibility to healthcare services. This paper therefore analyzed the spatial patterns of healthcare facilities in Akwa Ibom State against the philosophy of achieving the MDGs in the health sector ...

  9. Combination of genetics and spatial modelling highlights the sensitivity of cod (Gadus morhua) population diversity in the North Sea to distributions of fishing

    DEFF Research Database (Denmark)

    Heath, Michael R.; Culling, Mark A.; Crozier, Walter W.

    2014-01-01

    Conserving genetic diversity in animal populations is important for sustaining their ability to respond to environmental change. However, the “between-population” component of genetic diversity (biocomplexity) is threatened in many exploited populations, particularly marine fish, where harvest...... North Sea (Viking) unit by the more widespread (Dogger) unit, and its premature extinction under some spatial patterns of fishing. Fishery catch limits for cod are set at the scale of the whole North Sea without regard to such subpopulation dynamics. Our model offers a method to quantify adjustments...

  10. StreamFlow 1.0: an extension to the spatially distributed snow model Alpine3D for hydrological modelling and deterministic stream temperature prediction

    Science.gov (United States)

    Gallice, Aurélien; Bavay, Mathias; Brauchli, Tristan; Comola, Francesco; Lehning, Michael; Huwald, Hendrik

    2016-12-01

    Climate change is expected to strongly impact the hydrological and thermal regimes of Alpine rivers within the coming decades. In this context, the development of hydrological models accounting for the specific dynamics of Alpine catchments appears as one of the promising approaches to reduce our uncertainty of future mountain hydrology. This paper describes the improvements brought to StreamFlow, an existing model for hydrological and stream temperature prediction built as an external extension to the physically based snow model Alpine3D. StreamFlow's source code has been entirely written anew, taking advantage of object-oriented programming to significantly improve its structure and ease the implementation of future developments. The source code is now publicly available online, along with a complete documentation. A special emphasis has been put on modularity during the re-implementation of StreamFlow, so that many model aspects can be represented using different alternatives. For example, several options are now available to model the advection of water within the stream. This allows for an easy and fast comparison between different approaches and helps in defining more reliable uncertainty estimates of the model forecasts. In particular, a case study in a Swiss Alpine catchment reveals that the stream temperature predictions are particularly sensitive to the approach used to model the temperature of subsurface flow, a fact which has been poorly reported in the literature to date. Based on the case study, StreamFlow is shown to reproduce hourly mean discharge with a Nash-Sutcliffe efficiency (NSE) of 0.82 and hourly mean temperature with a NSE of 0.78.

  11. Spatial distribution of soil organic carbon stocks in France

    Directory of Open Access Journals (Sweden)

    M. P. Martin

    2011-05-01

    Full Text Available Soil organic carbon plays a major role in the global carbon budget, and can act as a source or a sink of atmospheric carbon, thereby possibly influencing the course of climate change. Changes in soil organic carbon (SOC stocks are now taken into account in international negotiations regarding climate change. Consequently, developing sampling schemes and models for estimating the spatial distribution of SOC stocks is a priority. The French soil monitoring network has been established on a 16 km × 16 km grid and the first sampling campaign has recently been completed, providing around 2200 measurements of stocks of soil organic carbon, obtained through an in situ composite sampling, uniformly distributed over the French territory.

    We calibrated a boosted regression tree model on the observed stocks, modelling SOC stocks as a function of other variables such as climatic parameters, vegetation net primary productivity, soil properties and land use. The calibrated model was evaluated through cross-validation and eventually used for estimating SOC stocks for mainland France. Two other models were calibrated on forest and agricultural soils separately, in order to assess more precisely the influence of pedo-climatic variables on SOC for such soils.

    The boosted regression tree model showed good predictive ability, and enabled quantification of relationships between SOC stocks and pedo-climatic variables (plus their interactions over the French territory. These relationships strongly depended on the land use, and more specifically, differed between forest soils and cultivated soil. The total estimate of SOC stocks in France was 3.260 ± 0.872 PgC for the first 30 cm. It was compared to another estimate, based on the previously published European soil organic carbon and bulk density maps, of 5.303 PgC. We demonstrate that the present estimate might better represent the actual SOC stock distributions of France, and consequently that the

  12. Spatial distribution of gender inequality in Brazil

    OpenAIRE

    Patrícia Verônica Pinheiro Sales Lima; Marina Rocha de Sousa; Ahmad Saeed Khan; Leonardo Andrade Rocha

    2015-01-01

    The purpose of this article was to analyze how gender inequality is distributed all over the Brazil. To that end, it has been built the Multidimensional Gender Inequality Index (MGII), a synthetic index. The main findings underlined that inequality between men and women manifests itself at different degrees in the federal units, but it is determined by a variety of common factors. The asymmetries are observed, mainly, in the political, labor and income dimensions.  El artículo pretende ana...

  13. Spatial distribution of gender inequality in Brazil

    Directory of Open Access Journals (Sweden)

    Patrícia Verônica Pinheiro Sales Lima

    2015-07-01

    Full Text Available The purpose of this article was to analyze how gender inequality is distributed all over the Brazil. To that end, it has been built the Multidimensional Gender Inequality Index (MGII, a synthetic index. The main findings underlined that inequality between men and women manifests itself at different degrees in the federal units, but it is determined by a variety of common factors. The asymmetries are observed, mainly, in the political, labor and income dimensions.

  14. Spatial distribution of erosion and deposition on an agricultural watershed

    Science.gov (United States)

    Pineux, Nathalie; Gilles, Colinet; Degré, Aurore

    2013-04-01

    To better understand the agricultural landscapes evolution becomes an essential preoccupation and, for this, it is needed to take into account the sediments deposition, in a distributed way. As it is not possible in practice to study all terrestrial surfaces in detail by instrumenting sectors to obtain data, models of prediction are valuable tools to control the current problems, to predict the future tendencies and to provide a scientific base to the political decisions. In our case, a landscape evolution model is needed, which aims at representing both erosion and sedimentation and dynamically adjusts the landscape to erosion and deposition by modifying the initial digital elevation model. The Landsoil model (Landscape design for Soil conservation under soil use and climate change), among others, could fulfil this objective. It has the advantage to take the soil variability into account. This model, designed for the analysis of agricultural landscape, is suitable for simulations from parcel to catchment scale, is spatially distributed and event-based. Observed quantitative data are essential (notably to calibrate the model) but still limited. Particularly, we lack observations spatially distributed on the watershed. For this purpose, we choose a watershed in Belgium (Wallonia) which is a 124 ha agricultural zone in the loamy region. Its slopes range from 0% to 9%. To test the predictions of the model, comparisons will be done with: - sediment measurements which are done with water samplings in four points on the site to compare the net erosion results; - sediment selective measurements (depth variation observed along graduated bares placed on site) to compare the erosion and deposition results; - very accurate DSM's (6,76 cm pixel resolution X-Y) obtained by the drone (Gatewing X100) each winter. Besides planning what the landscape evolution should be, a revision of the soil map (drew in 1958) is organized to compare with the past situation and establish how the

  15. Forecasting species distributions with geo-spatial data: R objects that predict from averages of competing statistical models or data mining methods

    Science.gov (United States)

    Salas, L. A.; Veloz, S.; Ballard, G.

    2011-12-01

    Most forecasting approaches based on statistical models and data mining methods share a set of characteristics: all are constructed from train sets and validated against test sets using methods to avoid over-fitting on the training data; standard validation methods are used (e.g., AUC values for binary response data); some form of model averaging is applied when predicting new values from a set of competing models; measurements of error of predictions and goodness-of-fit of each competing model are reported and made spatially explicit. Many packages exist in R to fit statistical models and for data mining, but few include algorithms for forecasting and there are no model-averaging methods. However, results from these packages are commonly reported in R objects (S4 classes) that usually extend from other objects, and so they share methods in common (e.g., "predict", "aic"). Here we illustrate an approach that takes advantages of the abovementioned commonalities to develop a "framework" using objects that fit competing models with algorithms for forecasting and include model averaging methods. These objects can be easily extended to incorporate new kinds of statistical and data mining methods. We illustrate this approach with three types of objects and show how to interact with them to produce weighted averages from competing models, and some tabular and graphic outputs. These objects have been compiled into an R package ("RavianForecasting" - http://data.prbo.org/apps/ravian). We encourage others to use and contribute toward the development of these types of forecasting objects, or to develop alternatives with similar flexibility. We show how these can be easily extended to incorporate new statistical methods, new outputs, new methods to weigh averages, and new methods to validate the models.

  16. Combining a finite mixture distribution model with indicator kriging to delineate and map the spatial patterns of soil heavy metal pollution in Chunghua County, central Taiwan

    International Nuclear Information System (INIS)

    Lin Yupin; Cheng Baiyou; Shyu, G.-S.; Chang, T.-K.

    2010-01-01

    This study identifies the natural background, anthropogenic background and distribution of contamination caused by heavy metal pollutants in soil in Chunghua County of central Taiwan by using a finite mixture distribution model (FMDM). The probabilities of contaminated area distribution are mapped using single-variable indicator kriging and multiple-variable indicator kriging (MVIK) with the FMDM cut-off values and regulation thresholds for heavy metals. FMDM results indicate that Cr, Cu, Ni and Zn can be individually fitted by a mixture model representing the background and contamination distributions of the four metals in soil. The FMDM cut-off values for contamination caused by the metals are close to the regulation thresholds, except for the cut-off value of Zn. The receiver operating characteristic (ROC) curve validates that indicator kriging and MVIK with FMDM cut-off values can reliably delineate heavy metals contamination, particularly for areas lacking background information and high heavy metal concentrations in soil. - Effectively determine pollution threshold and map contaminated areas.

  17. Predicting the spatial distribution of leaf litterfall in a mixed deciduous forest

    NARCIS (Netherlands)

    Staelens, Jeroen; Nachtergale, Lieven; Luyssaert, Sebastiaan

    2004-01-01

    An accurate prediction of the spatial distribution of litterfall can improve insight in the interaction between the canopy layer and forest floor characteristics, which is a key feature in forest nutrient cycling. Attempts to model the spatial variability of litterfall have been made across forest

  18. A Spatially Extended Model for Residential Segregation

    Directory of Open Access Journals (Sweden)

    Antonio Aguilera

    2007-01-01

    Full Text Available We analyze urban spatial segregation phenomenon in terms of the income distribution over a population, and an inflationary parameter weighting the evolution of housing prices. For this, we develop a discrete spatially extended model based on a multiagent approach. In our model, the mobility of socioeconomic agents is driven only by the housing prices. Agents exchange location in order to fit their status to the cost of their housing. On the other hand, the price of a particular house depends on the status of its tenant, and on the neighborhood mean lodging cost weighted by a control parameter. The agent's dynamics converges to a spatially organized configuration, whose regularity is measured by using an entropy-like indicator. This simple model provides a dynamical process organizing the virtual city, in a way that the population inequality and the inflationary parameter determine the degree of residential segregation in the final stage of the process, in agreement with the segregation-inequality thesis put forward by Douglas Massey.

  19. Holographic monitoring of spatial distributions of singlet oxygen in water

    Science.gov (United States)

    Belashov, A. V.; Bel'tyukova, D. M.; Vasyutinskii, O. S.; Petrov, N. V.; Semenova, I. V.; Chupov, A. S.

    2014-12-01

    A method for monitoring spatial distributions of singlet oxygen in biological media has been developed. Singlet oxygen was generated using Radachlorin® photosensitizer, while thermal disturbances caused by nonradiative deactivation of singlet oxygen were detected by the holographic interferometry technique. Processing of interferograms yields temperature maps that characterize the deactivation process and show the distribution of singlet oxygen species.

  20. Factors driving firm's spatial decisions on distribution channel layout

    NARCIS (Netherlands)

    Onstein, A.T.C.; Ektesaby, M.; Rezaei, J.; Tavasszy, L.A.; van Damme, D.A.

    2017-01-01

    Spatial decisions on distribution channel layout involve the layout of the transport and storage system between production and consumption as well as the selection of distribution centre locations. Both are strategic company decisions to meet logistics challenges, i.e. delivering the right product

  1. First contact distributions for spatial patterns: regularity and estimation

    NARCIS (Netherlands)

    Hansen, M.B.; Baddeley, A.J.; Gill, R.D.

    1999-01-01

    For applications in spatial statistics an important property of a random set X in Rk is its rst contact distribution This is the distribution of the distance from a xed point to the nearest point of X where distance is measured using scalar dilations of a xed test set B We show that if B is convex

  2. Juvenile Penaeid Shrimp Density, Spatial Distribution and Size ...

    African Journals Online (AJOL)

    The effects of habitat characteristics (mangrove creek, sandflat, mudflat and seagrass meadow) water salinity, temperature, and depth on the density, spatial distribution and size distribution of juveniles of five commercially important penaied shrimp species (Metapenaus monoceros, M. stebbingi, Fenneropenaeus indicus, ...

  3. Spatial distribution of dust in the shell elliptical NGC 5982

    NARCIS (Netherlands)

    del Burgo, C.; Carter, D.; Sikkema, G.

    Aims. Shells in Ellipticals are peculiar faint sharp edged features that are thought to be formed by galaxy mergers. We determine the shell and dust distributions, and colours of a well-resolved shell and the underlying galaxy in NGC 5982, and compare the spatial distributions of the dust and gas

  4. Non-homogeneous Behaviour of the Spatial Distribution of ...

    Indian Academy of Sciences (India)

    Abstract. In this paper the longitudinal and latitudinal spatial distribu- tion of macrospicules is examined. We found a statistical relationship between the active longitude (determined by sunspot groups) and the lon- gitudinal distribution of macrospicules. This distribution of macrospicules shows an inhomogeneity and ...

  5. An Assessment of the Spatial Distribution of Government Secondary ...

    African Journals Online (AJOL)

    It reveals that the spatial distribution of Government Owned Secondary Schools in Zaria area is very uneven. The paper argues that uneven distribution of Government Owned Secondary education facilities as well as their inadequacy and inefficiency encourage the proliferation of Private Owned Secondary Schools (POSS) ...

  6. Patterns in the spatial distribution of Peruvian anchovy ( Engraulis ringens) revealed by spatially explicit fishing data

    Science.gov (United States)

    Bertrand, Sophie; Díaz, Erich; Lengaigne, Matthieu

    2008-10-01

    Peruvian anchovy ( Engraulis ringens) stock abundance is tightly driven by the high and unpredictable variability of the Humboldt Current Ecosystem. Management of the fishery therefore cannot rely on mid- or long-term management policy alone but needs to be adaptive at relatively short time scales. Regular acoustic surveys are performed on the stock at intervals of 2 to 4 times a year, but there is a need for more time continuous monitoring indicators to ensure that management can respond at suitable time scales. Existing literature suggests that spatially explicit data on the location of fishing activities could be used as a proxy for target stock distribution. Spatially explicit commercial fishing data could therefore guide adaptive management decisions at shorter time scales than is possible through scientific stock surveys. In this study we therefore aim to (1) estimate the position of fishing operations for the entire fleet of Peruvian anchovy purse-seiners using the Peruvian satellite vessel monitoring system (VMS), and (2) quantify the extent to which the distribution of purse-seine sets describes anchovy distribution. To estimate fishing set positions from vessel tracks derived from VMS data we developed a methodology based on artificial neural networks (ANN) trained on a sample of fishing trips with known fishing set positions (exact fishing positions are known for approximately 1.5% of the fleet from an at-sea observer program). The ANN correctly identified 83% of the real fishing sets and largely outperformed comparative linear models. This network is then used to forecast fishing operations for those trips where no observers were onboard. To quantify the extent to which fishing set distribution was correlated to stock distribution we compared three metrics describing features of the distributions (the mean distance to the coast, the total area of distribution, and a clustering index) for concomitant acoustic survey observations and fishing set positions

  7. Environmental DNA reflects spatial and temporal jellyfish distribution.

    Science.gov (United States)

    Minamoto, Toshifumi; Fukuda, Miho; Katsuhara, Koki R; Fujiwara, Ayaka; Hidaka, Shunsuke; Yamamoto, Satoshi; Takahashi, Kohji; Masuda, Reiji

    2017-01-01

    Recent development of environmental DNA (eDNA) analysis allows us to survey underwater macro-organisms easily and cost effectively; however, there have been no reports on eDNA detection or quantification for jellyfish. Here we present the first report on an eDNA analysis of marine jellyfish using Japanese sea nettle (Chrysaora pacifica) as a model species by combining a tank experiment with spatial and temporal distribution surveys. We performed a tank experiment monitoring eDNA concentrations over a range of time intervals after the introduction of jellyfish, and quantified the eDNA concentrations by quantitative real-time PCR. The eDNA concentrations peaked twice, at 1 and 8 h after the beginning of the experiment, and became stable within 48 h. The estimated release rates of the eDNA in jellyfish were higher than the rates previously reported in fishes. A spatial survey was conducted in June 2014 in Maizuru Bay, Kyoto, in which eDNA was collected from surface water and sea floor water samples at 47 sites while jellyfish near surface water were counted on board by eye. The distribution of eDNA in the bay corresponded with the distribution of jellyfish inferred by visual observation, and the eDNA concentration in the bay was ~13 times higher on the sea floor than on the surface. The temporal survey was conducted from March to November 2014, in which jellyfish were counted by eye every morning while eDNA was collected from surface and sea floor water at three sampling points along a pier once a month. The temporal fluctuation pattern of the eDNA concentrations and the numbers of observed individuals were well correlated. We conclude that an eDNA approach is applicable for jellyfish species in the ocean.

  8. Environmental DNA reflects spatial and temporal jellyfish distribution.

    Directory of Open Access Journals (Sweden)

    Toshifumi Minamoto

    Full Text Available Recent development of environmental DNA (eDNA analysis allows us to survey underwater macro-organisms easily and cost effectively; however, there have been no reports on eDNA detection or quantification for jellyfish. Here we present the first report on an eDNA analysis of marine jellyfish using Japanese sea nettle (Chrysaora pacifica as a model species by combining a tank experiment with spatial and temporal distribution surveys. We performed a tank experiment monitoring eDNA concentrations over a range of time intervals after the introduction of jellyfish, and quantified the eDNA concentrations by quantitative real-time PCR. The eDNA concentrations peaked twice, at 1 and 8 h after the beginning of the experiment, and became stable within 48 h. The estimated release rates of the eDNA in jellyfish were higher than the rates previously reported in fishes. A spatial survey was conducted in June 2014 in Maizuru Bay, Kyoto, in which eDNA was collected from surface water and sea floor water samples at 47 sites while jellyfish near surface water were counted on board by eye. The distribution of eDNA in the bay corresponded with the distribution of jellyfish inferred by visual observation, and the eDNA concentration in the bay was ~13 times higher on the sea floor than on the surface. The temporal survey was conducted from March to November 2014, in which jellyfish were counted by eye every morning while eDNA was collected from surface and sea floor water at three sampling points along a pier once a month. The temporal fluctuation pattern of the eDNA concentrations and the numbers of observed individuals were well correlated. We conclude that an eDNA approach is applicable for jellyfish species in the ocean.

  9. Determination and optimization of spatial samples for distributed measurements.

    Energy Technology Data Exchange (ETDEWEB)

    Huo, Xiaoming (Georgia Institute of Technology, Atlanta, GA); Tran, Hy D.; Shilling, Katherine Meghan; Kim, Heeyong (Georgia Institute of Technology, Atlanta, GA)

    2010-10-01

    There are no accepted standards for determining how many measurements to take during part inspection or where to take them, or for assessing confidence in the evaluation of acceptance based on these measurements. The goal of this work was to develop a standard method for determining the number of measurements, together with the spatial distribution of measurements and the associated risks for false acceptance and false rejection. Two paths have been taken to create a standard method for selecting sampling points. A wavelet-based model has been developed to select measurement points and to determine confidence in the measurement after the points are taken. An adaptive sampling strategy has been studied to determine implementation feasibility on commercial measurement equipment. Results using both real and simulated data are presented for each of the paths.

  10. Survey gear calibration independent of spatial fish distribution

    DEFF Research Database (Denmark)

    Lewy, Peter; Nielsen, J. Rasmus; Hovgård, Holger

    2004-01-01

    Trawl surveys provide important information for evaluation of relative stock abundance fluctuations over time. Therefore, when survey gears or vessels are changed, it is important to compare the efficiency and selectivity of old and new gears and vessels. A method for estimation of conversion...... factors is developed based on a survey design where paired hauls are taken in the same trawl track line. The method explicitly accounts for changes in fish density caused by trawling disturbance. A generalized linear model for paired hauls catches is analytically derived and the gear conversion...... and disturbance parameters with their precision are obtained using standard software. Simulation studies carried out additionally showed that the estimated conversion factors were practically unbiased. Because of the independence of the spatial fish distribution, the new method is preferable to the traditional...

  11. Wind Farms’ Spatial Distribution Effect on Power System Reserves Requirements

    DEFF Research Database (Denmark)

    Sørensen, Poul Ejnar; Cutululis, Nicolaos Antonio

    2010-01-01

    The wind power development during last millennium was typically based on small wind turbines dispersed over large areas, leading to a significant smoothing of the wind power fluctuations in a power system balancing area. The present development goes towards much larger wind farms, concentrated...... in smaller areas, which causes the total wind power fluctuations in power system areas to increase significantly. The impact of future large wind farms spatial distribution with respect to the power system reserve requirements is analyzed in this paper. For this purpose, Correlated Wind (CorWind) power time...... series simulation model developed to simulate wind power variability over a large area is used. As a study case, two scenarios for short term offshore wind power development in the West Danish power system region are used. The first scenario assumes that all the wind farms are built in the region...

  12. Integrating water by plant roots over spatially distributed soil salinity

    Science.gov (United States)

    Homaee, Mehdi; Schmidhalter, Urs

    2010-05-01

    In numerical simulation models dealing with water movement and solute transport in vadose zone, the water budget largely depends on uptake patterns by plant roots. In real field conditions, the uptake pattern largely changes in time and space. When dealing with soil and water salinity, most saline soils demonstrate spatially distributed osmotic head over the root zone. In order to quantify such processes, the major difficulty stems from lacking a sink term function that adequately accounts for the extraction term especially under variable soil water osmotic heads. The question of how plants integrate such space variable over its rooting depth remains as interesting issue for investigators. To move one step forward towards countering this concern, a well equipped experiment was conducted under heterogeneously distributed salinity over the root zone with alfalfa. The extraction rates of soil increments were calculated with the one dimensional form of Richards equation. The results indicated that the plant uptake rate under different mean soil salinities preliminary reacts to soil salinity, whereas at given water content and salinity the "evaporative demand" and "root activity" become more important to control the uptake patterns. Further analysis revealed that root activity is inconstant when imposed to variable soil salinity. It can be concluded that under heterogeneously distributed salinity, most water is taken from the less saline increment while the extraction from other root zone increments with higher salinities never stops.

  13. Positional information generated by spatially distributed signaling cascades.

    Directory of Open Access Journals (Sweden)

    Javier Muñoz-García

    2009-03-01

    Full Text Available The temporal and stationary behavior of protein modification cascades has been extensively studied, yet little is known about the spatial aspects of signal propagation. We have previously shown that the spatial separation of opposing enzymes, such as a kinase and a phosphatase, creates signaling activity gradients. Here we show under what conditions signals stall in the space or robustly propagate through spatially distributed signaling cascades. Robust signal propagation results in activity gradients with long plateaus, which abruptly decay at successive spatial locations. We derive an approximate analytical solution that relates the maximal amplitude and propagation length of each activation profile with the cascade level, protein diffusivity, and the ratio of the opposing enzyme activities. The control of the spatial signal propagation appears to be very different from the control of transient temporal responses for spatially homogenous cascades. For spatially distributed cascades where activating and deactivating enzymes operate far from saturation, the ratio of the opposing enzyme activities is shown to be a key parameter controlling signal propagation. The signaling gradients characteristic for robust signal propagation exemplify a pattern formation mechanism that generates precise spatial guidance for multiple cellular processes and conveys information about the cell size to the nucleus.

  14. Spatial distribution of leprosy in Brazil: a literature review

    Directory of Open Access Journals (Sweden)

    Cláuffer Luiz Machado Silva

    Full Text Available Abstract Leprosy remains a public health problem in developing countries. Among communicable diseases, it is one of the leading causes of permanent disability. Brazil had not reached the goal of reducing cases to less than 1 per 10,000 population. This study aimed to analyze the spatial distribution of leprosy cases in Brazil, using a literature review. The search strategy included the LILACS and MEDLINE databases with no language or period restriction. Ecological studies with spatial data analysis were considered as a criterion for the inclusion. We found 38 studies for review after the selection criteria. Among the epidemiological indicators of the disease, the most common was the new case detection rate. Several articles have explored the association between spatial distribution of leprosy and socioeconomic, demographic, and environmental factors. The most common unit of analysis was the municipality. The spatial distribution methods mostly used were: empirical Bayesian method, autocorrelation (Moran’s I index and Kernel estimates. The distribution of leprosy was very heterogeneous, independent of the unit of analysis. There was a decrease in the rate of detection and among under-15-year-olds, but some regions maintained high endemicity during the study period. The distribution and risk of illness were directly related to living conditions of the population. Improved access to health services was associated with increased detection rate in some regions. Spatial analysis seems to be a very useful tool to study leprosy and to guide interventions and surveillance.

  15. Spatial distribution of leprosy in Brazil: a literature review.

    Science.gov (United States)

    Silva, Cláuffer Luiz Machado; Fonseca, Sandra Costa; Kawa, Helia; Palmer, Dayanna de Oliveira Quintanilha

    2017-01-01

    Leprosy remains a public health problem in developing countries. Among communicable diseases, it is one of the leading causes of permanent disability. Brazil had not reached the goal of reducing cases to less than 1 per 10,000 population. This study aimed to analyze the spatial distribution of leprosy cases in Brazil, using a literature review. The search strategy included the LILACS and MEDLINE databases with no language or period restriction. Ecological studies with spatial data analysis were considered as a criterion for the inclusion. We found 38 studies for review after the selection criteria. Among the epidemiological indicators of the disease, the most common was the new case detection rate. Several articles have explored the association between spatial distribution of leprosy and socioeconomic, demographic, and environmental factors. The most common unit of analysis was the municipality. The spatial distribution methods mostly used were: empirical Bayesian method, autocorrelation (Moran's I index) and Kernel estimates. The distribution of leprosy was very heterogeneous, independent of the unit of analysis. There was a decrease in the rate of detection and among under-15-year-olds, but some regions maintained high endemicity during the study period. The distribution and risk of illness were directly related to living conditions of the population. Improved access to health services was associated with increased detection rate in some regions. Spatial analysis seems to be a very useful tool to study leprosy and to guide interventions and surveillance.

  16. Spatial bedrock erosion distribution in a natural gorge

    Science.gov (United States)

    Beer, A. R.; Turowski, J. M.; Kirchner, J. W.

    2015-12-01

    Quantitative analysis of morphological evolution both in terrestrial and planetary landscapes is of increasing interest in the geosciences. In mountainous regions, bedrock channel formation as a consequence of the interaction of uplift and erosion processes is fundamental for the entire surface evolution. Hence, the accurate description of bedrock channel development is important for landscape modelling. To verify existing concepts developed in the lab and to analyse how in situ channel erosion rates depend on the interrelations of discharge, sediment transport and topography, there is a need of highly resolved topographic field data. We analyse bedrock erosion over two years in a bedrock gorge downstream of the Gorner glacier above the town of Zermatt, Switzerland. At the study site, the Gornera stream cuts through a roche moutonnée in serpentine rock of 25m length, 5m width and 8m depth. We surveyed bedrock erosion rates using repeat terrestrial laser scanning (TLS) with an average point spacing of 5mm. Bedrock erosion rates in direction of the individual surface normals were studied directly on the scanned point clouds applying the M3C2 algorithm (Lague et al., 2013, ISPRS). The surveyed erosion patterns were compared to a simple stream erosivity visualisation obtained from painted bedrock sections at the study location. Spatially distributed erosion rates on bedrock surfaces based on millions of scan points allow deduction of millimeter-scale mean annual values of lateral erosion, incision and downstream erosion on protruding streambed surfaces. The erosion rate on a specific surface point is shown to depend on the position of this surface point in the channel's cross section, its height above the streambed and its spatial orientation to the streamflow. Abrasion by impacting bedload was likely the spatially dominant erosion process, as confirmed by the observed patterns along the painted bedrock sections. However, a single plucking event accounted for the half

  17. Spatial Stochastic Point Models for Reservoir Characterization

    Energy Technology Data Exchange (ETDEWEB)

    Syversveen, Anne Randi

    1997-12-31

    The main part of this thesis discusses stochastic modelling of geology in petroleum reservoirs. A marked point model is defined for objects against a background in a two-dimensional vertical cross section of the reservoir. The model handles conditioning on observations from more than one well for each object and contains interaction between objects, and the objects have the correct length distribution when penetrated by wells. The model is developed in a Bayesian setting. The model and the simulation algorithm are demonstrated by means of an example with simulated data. The thesis also deals with object recognition in image analysis, in a Bayesian framework, and with a special type of spatial Cox processes called log-Gaussian Cox processes. In these processes, the logarithm of the intensity function is a Gaussian process. The class of log-Gaussian Cox processes provides flexible models for clustering. The distribution of such a process is completely characterized by the intensity and the pair correlation function of the Cox process. 170 refs., 37 figs., 5 tabs.

  18. The application of GIS based decision-tree models for generating the spatial distribution of hydromorphic organic landscapes in relation to digital terrain data

    DEFF Research Database (Denmark)

    Kheir, Rania Bou; Bøcher, Peder Klith; Greve, Mette Balslev

    2010-01-01

    measurements in hydromorphic landscapes of the Danish area chosen. A large number of tree-based classification models (186) were developed using (1) all of the parameters, (2) the primary DEM-derived topographic (morphological/hydrological) parameters only, (3) selected pairs of parameters and (4) excluding......Accurate information about organic/mineral soil occurrence is a prerequisite for many land resources management applications (including climate change mitigation). This paper aims at investigating the potential of using geomorphometrical analysis and decision tree modeling to predict the geographic...... distribution of hydromorphic organic landscapes in unsampled area in Denmark. Nine primary (elevation, slope angle, slope aspect, plan curvature, profile curvature, tangent curvature, flow direction, flow accumulation, and specific catchment area) and one secondary (steady-state topographic wetness index...

  19. Analyzing the hydrological impact of afforestation and tree species in two catchments with contrasting soil properties using the spatially distributed model MIKE SHE SWET

    DEFF Research Database (Denmark)

    Sonnenborg, Torben Obel; Christiansen, Jesper Riis; Pang, Bo

    2017-01-01

    Groundwater depletion occurs at a global scale but requires regional strategies for sustainable management of freshwater resources. In Denmark the groundwater quantity and quality is under pressure, and forested areas are considered to protect groundwater reservoirs. However, little is known on how...... afforestation or forest conversion impacts the water resource at the catchment scale. We hypothesize that the groundwater formation and streamflow is increased when water consuming conifers are replaced with the less consumptive broadleaf tree species. To test this a distributed hydrological model...... with an energy-based description of evaporation and transpiration processes (MIKE SHE SWET) was used. Large scale hydrological models were established for two geologically (sandy/clayey) contrasting catchments in Denmark; Skjern and Lejre catchments. Land use scenarios were defined with forest vegetation...

  20. Spatial distribution measured by the modulation transfer function

    International Nuclear Information System (INIS)

    Rossi, P.; Brice, D.K.; Doyle, B.L.

    2003-01-01

    Spatial distributions in ion micro-beam and IBA experimental practice are regularly characterized through the parameters of FWHM and tail area percentage (TF, tail fraction). Linear and stationary transducer theory allows these distributions to be described in the Fourier-dual frequency space, and provides an indirect method to evaluate them through measurement of the modulation transfer function (MTF). We suggest direct measurement of MTF by employing bar pattern grids, similar to those used for calibration of radiological equipment. Assuming spatial distributions of the form exp(-(|αx|) η ), we are able to relate the MTF measurements to the more popular FWHM and TF. This new approach to determine spatial resolution can become a standard for use by the micro-beam community

  1. Spatial distributions and interstellar reaction processes.

    Science.gov (United States)

    Neill, Justin L; Steber, Amanda L; Muckle, Matt T; Zaleski, Daniel P; Lattanzi, Valerio; Spezzano, Silvia; McCarthy, Michael C; Remijan, Anthony J; Friedel, Douglas N; Widicus Weaver, Susanna L; Pate, Brooks H

    2011-06-23

    Methyl formate presents a challenge for the conventional chemical mechanisms assumed to guide interstellar organic chemistry. Previous studies of potential formation pathways for methyl formate in interstellar clouds ruled out gas-phase chemistry as a major production route, and more recent chemical kinetics models indicate that it may form efficiently from radical-radical chemistry on ice surfaces. Yet, recent chemical imaging studies of methyl formate and molecules potentially related to its formation suggest that it may form through previously unexplored gas-phase chemistry. Motivated by these findings, two new gas-phase ion-molecule formation routes are proposed and characterized using electronic structure theory with conformational specificity. The proposed reactions, acid-catalyzed Fisher esterification and methyl cation transfer, both produce the less stable trans-conformational isomer of protonated methyl formate in relatively high abundance under the kinetically controlled conditions relevant to interstellar chemistry. Gas-phase neutral methyl formate can be produced from its protonated counterpart through either a dissociative electron recombination reaction or a proton transfer reaction to a molecule with larger proton affinity. Retention (or partial retention) of the conformation in these neutralization reactions would yield trans-methyl formate in an abundance that exceeds predictions under thermodynamic equilibrium at typical interstellar temperatures of ≤100 K. For this reason, this conformer may prove to be an excellent probe of gas-phase chemistry in interstellar clouds. Motivated by new theoretical predictions, the rotational spectrum of trans-methyl formate has been measured for the first time in the laboratory, and seven lines have now been detected in the interstellar medium using the publicly available PRIMOS survey from the NRAO Green Bank Telescope.

  2. Analysis of the spatial distribution between successive earthquakes

    International Nuclear Information System (INIS)

    Davidsen, Joern; Paczuski, Maya

    2005-01-01

    Spatial distances between subsequent earthquakes in southern California exhibit scale-free statistics, with a critical exponent δ≅0.6, as well as finite size scaling. The statistics are independent of the threshold magnitude as long as the catalog is complete, but depend strongly on the temporal ordering of events, rather than the geometry of the spatial epicenter distribution. Nevertheless, the spatial distance and waiting time between subsequent earthquakes are uncorrelated with each other. These observations contradict the theory of aftershock zone scaling with main shock magnitude

  3. Spatial emission modelling for residential wood combustion in Denmark

    DEFF Research Database (Denmark)

    Plejdrup, Marlene Schmidt; Nielsen, Ole-Kenneth; Brandt, Jørgen

    2016-01-01

    model with the developed weighting factors (76 ton PM2.5) is in good agreement with the case study (95 ton PM2.5), and that the new model has improved the spatial emission distribution significantly compared to the previous model (284 ton PM2.5). Additionally, a sensitivity analysis was done...

  4. Characterizing the spatial distribution of giant pandas (Ailuropoda melanoleuca) in fragmented forest landscapes

    NARCIS (Netherlands)

    Wang, T.; Ye, X.P.; Skidmore, A.K.; Toxopeus, A.G.

    2010-01-01

    Aim. To examine the effects of forest fragmentation on the distribution of the entire wild giant panda (Ailuropoda melanoleuca) population, and to propose a modelling approach for monitoring the spatial distribution and habitat of pandas at the landscape scale using Moderate Resolution Imaging

  5. Time-dependent density functional theory (TD-DFT) coupled with reference interaction site model self-consistent field explicitly including spatial electron density distribution (RISM-SCF-SEDD)

    Science.gov (United States)

    Yokogawa, D.

    2016-09-01

    Theoretical approach to design bright bio-imaging molecules is one of the most progressing ones. However, because of the system size and computational accuracy, the number of theoretical studies is limited to our knowledge. To overcome the difficulties, we developed a new method based on reference interaction site model self-consistent field explicitly including spatial electron density distribution and time-dependent density functional theory. We applied it to the calculation of indole and 5-cyanoindole at ground and excited states in gas and solution phases. The changes in the optimized geometries were clearly explained with resonance structures and the Stokes shift was correctly reproduced.

  6. Spatial and temporal distribution of ionospheric currents-4: altitude ...

    African Journals Online (AJOL)

    (a) The continuous distribution of current density model reproduces the altitude distribution parameters of EEJ current density very well, (b) the altitude distribution parameters of EEJ current density in India and Peru are not significantly different and (c) The altitude distribution parameters of EEJ current density from rockets ...

  7. Evaluating water erosion prediction project model using Cesium-137-derived spatial soil redistribution data

    Science.gov (United States)

    The lack of spatial soil erosion data has been a major constraint on the refinement and application of physically based erosion models. Spatially distributed models can only be thoroughly validated with distributed erosion data. The fallout cesium-137 has been widely used to generate spatial soil re...

  8. Controls on the spatial distribution of oceanic δ13CDIC

    Directory of Open Access Journals (Sweden)

    P. B. Holden

    2013-03-01

    Full Text Available We describe the design and evaluation of a large ensemble of coupled climate–carbon cycle simulations with the Earth system model of intermediate complexity GENIE. This ensemble has been designed for application to a range of carbon cycle questions, including the causes of late-Quaternary fluctuations in atmospheric CO2. Here we evaluate the ensemble by applying it to a transient experiment over the recent industrial era (1858 to 2008 AD. We employ singular vector decomposition and principal component emulation to investigate the spatial modes of ensemble variability of oceanic dissolved inorganic carbon (DIC δ13C, considering both the spun-up pre-industrial state and the transient change. These analyses allow us to separate the natural (pre-industrial and anthropogenic controls on the δ13CDIC distribution. We apply the same dimensionally-reduced emulation techniques to consider the drivers of the spatial uncertainty in anthropogenic DIC. We show that the sources of uncertainty related to the uptake of anthropogenic δ13CDIC and DIC are quite distinct. Uncertainty in anthropogenic δ13C uptake is controlled by air–sea gas exchange, which explains 63% of modelled variance. This mode of variability is largely absent from the ensemble variability in CO2 uptake, which is rather driven by uncertainties in thermocline ventilation rates. Although the need to account for air–sea gas exchange is well known, these results suggest that, to leading order, uncertainties in the ocean uptake of anthropogenic 13C and CO2 are governed by very different processes. This illustrates the difficulties in reconstructing one from the other, and furthermore highlights the need for careful targeting of both δ13CDIC and DIC observations to better constrain the ocean sink of anthropogenic CO2.

  9. Spatial distribution of Nemesis lamna Risso 1826 (Copepoda ...

    African Journals Online (AJOL)

    The selection of a specific site of attachment by a copepod parasite is determined by a set of mostly unknown factors. The spatial distribution of Nemesis lamna on the gill filaments of white sharks Carcharodon carcharias was investigated. The complete set of left gills of 11 hosts was examined and the location, orientation ...

  10. Composition and spatial distribution of cephalopods in two North ...

    African Journals Online (AJOL)

    The faunistic composition and the spatial distribution of the cephalopod fauna were studied and compared in two areas of the north-western Mediterranean: the Catalan Sea (Spanish coast) and the northern Tyrrhenian Sea (Italian coast). In all, 46 species were collected in the Catalan Sea and 36 in the northern Tyrrhenian ...

  11. Spatial distribution of glycerophospholipids in the ocular lens.

    Directory of Open Access Journals (Sweden)

    Jaroslav Pól

    Full Text Available Knowledge of the spatial distribution of lipids in the intraocular lens is important for understanding the physiology and biochemistry of this unique tissue and for gaining a better insight into the mechanisms underlying diseases of the lens. Following our previous study showing the spatial distribution of sphingolipids in the porcine lens, the current study used ultra performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOFMS to provide the whole lipidome of porcine lens and these studies were supplemented by matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI MSI of the lens using ultra-high resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS to determine the spatial distribution of glycerophospholipids. Altogether 172 lipid species were identified with high confidence and their concentration was determined. Sphingomyelins, phosphatidylcholines, and phosphatidylethanolamines were the most abundant lipid classes. We then determined the spatial and concentration-dependent distributions of 20 phosphatidylcholines, 6 phosphatidylethanolamines, and 4 phosphatidic acids. Based on the planar molecular images of the lipids, we report the organization of fiber cell membranes within the ocular lens and suggest roles for these lipids in normal and diseased lenses.

  12. A preliminary survey and analysis of the spatial distribution of ...

    African Journals Online (AJOL)

    The spatial distribution of aquatic macroinvertebrates in the Okavango River Delta, Botswana, was investigated during the lowwater period in February 2003. This complements an earlier study undertaken during high-water in June 2000. Seventy-five samples were taken in a range of aquatic habitats at 29 georeference ...

  13. Spatial distribution and habitat characterisation of mosquito species ...

    African Journals Online (AJOL)

    Background: Infections with mosquito-borne parasites are common in human populations inhabiting tropical regions of the world. Malaria is endemic along Kenyan Lake Victoria basin and its vectors are fresh water breeders. However, much less is known about the current spatial distribution and habitat characterisation of ...

  14. Spatial Distribution of Micro Finance Institutions and Agricultural ...

    African Journals Online (AJOL)

    This study examines the impact of spatial distribution of Micro-finance institutions on Agricultural development in Ekiti State, Nigeria. Agriculture is an engine for economic growth in developing countries and rural microfinance is also critical to that growth. Data for this study were collected through primary sources.

  15. Spatial distribution of saline water and possible sources of intrusion ...

    African Journals Online (AJOL)

    user

    The spatial distribution of saline water and possible sources of intrusion into Lekki lagoon and transitional effects on the lacustrine ichthyofaunal characteristics were studied during March, 2006 and. February, 2008. The water quality analysis indicated that, salinity has drastically increased recently in the lagoon (0.007 to ...

  16. Spatial distribution of potential and positive Aedes aegypti breeding sites

    Directory of Open Access Journals (Sweden)

    Daniel Elías Cuartas

    2017-03-01

    Conclusions: The spatial relationship between positive and potential A. aegypti breeding sites both indoors and outdoors is dynamic and highly sensitive to the characteristics of each territory. Knowing how positive and potential breeding sites are distributed contributes to the prioritization of resources and actions in vector control programs.

  17. Spatial distribution of saline water and possible sources of intrusion ...

    African Journals Online (AJOL)

    The spatial distribution of saline water and possible sources of intrusion into Lekki lagoon and transitional effects on the lacustrine ichthyofaunal characteristics were studied during March, 2006 and February, 2008. The water quality analysis indicated that, salinity has drastically increased recently in the lagoon (0.007 to ...

  18. Influence of shade systems on spatial distribution and infestation of ...

    African Journals Online (AJOL)

    ACSS

    3. Spatial distribution and infestation of the Black Coffee Twig Borer on coffee proximal to the stem), middle and tip. (upper 3rd portion distal to the stem) sections. Number of X. compactus entry holes in each section was then determined after which, they were dissected near the entry holes and the direction of X. compactus ...

  19. The effect of spatial planning patterns on distribution of pedestrians ...

    African Journals Online (AJOL)

    Abstract. This study focuses on public spaces of residential neighbourhoods in the City of Nairobi. It establishes various spatial characteristics, hence patterns, that have a bearing on the distribution of pedestrians therein. A higher encounter rate of pedestrians is a desirable public space quality given that the higher degree ...

  20. Spatial and Temporal Distribution of Reef Fish Spawning ...

    African Journals Online (AJOL)

    The spatial patterns among fish families were attributed to a combination of differences in species abundance and distribution as well as variation in fishing effort. Spawning periodicity reported by fishers indicated that for snappers and rabbitfishes, the most activity occurred across a protracted period of October to April/May, ...

  1. Examining the Spatial Distribution of Marijuana Establishments in Colorado

    Science.gov (United States)

    Kerski, Joseph

    2018-01-01

    In this 22-question activity, high school students investigate the spatial distribution of marijuana stores in Colorado using an interactive web map containing stores, centers, highways, population, and other data at several scales. After completing this lesson, students will know and be able to: (1) Use interactive maps, layers, and tools in…

  2. Development of Spatial Distribution Patterns by Biofilm Cells

    DEFF Research Database (Denmark)

    Haagensen, Janus Anders Juul; Hansen, Susse Kirkelund; Bak Christensen, Bjarke

    2015-01-01

    Confined spatial patterns of microbial distribution are prevalent in nature, such as in microbial mats, soil communities, and water stream biofilms. The symbiotic two-species consortium of Pseudomonas putida and Acinetobacter sp. C6, originally isolated from a creosote-polluted aquifer, has evolved...

  3. Investigation of Spatial Distribution Properties of Mid-Infrared ...

    African Journals Online (AJOL)

    The spatial distribution properties of quantum cascade lasers with emission wavelengths around 7 µm were measured. In addition, the emission profile on a plane orthogonal to the propagation axis of the beam were measured and the full width at half maximum (FWHM) on the orthogonal and lateral directions calculated.

  4. Spatial distribution of atmospheric carbon monoxide over Bay of ...

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Earth System Science; Volume 117; Issue 4. Spatial distribution of atmospheric carbon monoxide over Bay of Bengal and Arabian Sea: Measurements during pre-monsoon period of 2006. V R Aneesh G Mohankumar S Sampath. Volume 117 Issue 4 August 2008 pp 449-455 ...

  5. Spatial factor analysis: a new tool for estimating joint species distributions and correlations in species range

    DEFF Research Database (Denmark)

    Thorson, James T.; Scheuerell, Mark D.; Shelton, Andrew O.

    2015-01-01

    1. Predicting and explaining the distribution and density of species is one of the oldest concerns in ecology. Species distributions can be estimated using geostatistical methods, which estimate a latent spatial variable explaining observed variation in densities, but geostatistical methods may...... be imprecise for species with low densities or few observations. Additionally, simple geostatistical methods fail to account for correlations in distribution among species and generally estimate such cross-correlations as a post hoc exercise. 2. We therefore present spatial factor analysis (SFA), a spatial...... model for estimating a low-rank approximation to multivariate data, and use it to jointly estimate the distribution of multiple species simultaneously. We also derive an analytic estimate of cross-correlations among species from SFA parameters. 3. As a first example, we show that distributions for 10...

  6. Fractal nature of hydrocarbon deposits. 2. Spatial distribution

    International Nuclear Information System (INIS)

    Barton, C.C.; Schutter, T.A; Herring, P.R.; Thomas, W.J.; Scholz, C.H.

    1991-01-01

    Hydrocarbons are unevenly distributed within reservoirs and are found in patches whose size distribution is a fractal over a wide range of scales. The spatial distribution of the patches is also fractal and this can be used to constrain the design of drilling strategies also defined by a fractal dimension. Fractal distributions are scale independent and are characterized by a power-law scaling exponent termed the fractal dimension. The authors have performed fractal analyses on the spatial distribution of producing and showing wells combined and of dry wells in 1,600-mi 2 portions of the Denver and Powder River basins that were nearly completely drilled on quarter-mile square-grid spacings. They have limited their analyses to wells drilled to single stratigraphic intervals so that the map pattern revealed by drilling is representative of the spatial patchiness of hydrocarbons at depth. The fractal dimensions for the spatial patchiness of hydrocarbons in the two basins are 1.5 and 1.4, respectively. The fractal dimension for the pattern of all wells drilled is 1.8 for both basins, which suggests a drilling strategy with a fractal dimension significantly higher than the dimensions 1.5 and 1.4 sufficient to efficiently and economically explore these reservoirs. In fact, the fractal analysis reveals that the drilling strategy used in these basins approaches a fractal dimension of 2.0, which is equivalent to random drilling with no geologic input. Knowledge of the fractal dimension of a reservoir prior to drilling would provide a basis for selecting and a criterion for halting a drilling strategy for exploration whose fractal dimension closely matches that of the spatial fractal dimension of the reservoir, such a strategy should prove more efficient and economical than current practice

  7. 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.

  8. Spatial Uncertainty Analysis of Ecological Models

    Energy Technology Data Exchange (ETDEWEB)

    Jager, H.I.; Ashwood, T.L.; Jackson, B.L.; King, A.W.

    2000-09-02

    The authors evaluated the sensitivity of a habitat model and a source-sink population model to spatial uncertainty in landscapes with different statistical properties and for hypothetical species with different habitat requirements. Sequential indicator simulation generated alternative landscapes from a source map. Their results showed that spatial uncertainty was highest for landscapes in which suitable habitat was rare and spatially uncorrelated. Although, they were able to exert some control over the degree of spatial uncertainty by varying the sampling density drawn from the source map, intrinsic spatial properties (i.e., average frequency and degree of spatial autocorrelation) played a dominant role in determining variation among realized maps. To evaluate the ecological significance of landscape variation, they compared the variation in predictions from a simple habitat model to variation among landscapes for three species types. Spatial uncertainty in predictions of the amount of source habitat depended on both the spatial life history characteristics of the species and the statistical attributes of the synthetic landscapes. Species differences were greatest when the landscape contained a high proportion of suitable habitat. The predicted amount of source habitat was greater for edge-dependent (interior) species in landscapes with spatially uncorrelated(correlated) suitable habitat. A source-sink model demonstrated that, although variation among landscapes resulted in relatively little variation in overall population growth rate, this spatial uncertainty was sufficient in some situations, to produce qualitatively different predictions about population viability (i.e., population decline vs. increase).

  9. Finessing atlas data for species distribution models

    NARCIS (Netherlands)

    Niamir, A.; Skidmore, A.K.; Toxopeus, A.G.; Munoz, A.R.; Real, R.

    2011-01-01

    Aim The spatial resolution of species atlases and therefore resulting model predictions are often too coarse for local applications. Collecting distribution data at a finer resolution for large numbers of species requires a comprehensive sampling effort, making it impractical and expensive. This

  10. Spatial distribution sampling and Monte Carlo simulation of radioactive isotopes

    CERN Document Server

    Krainer, Alexander Michael

    2015-01-01

    This work focuses on the implementation of a program for random sampling of uniformly spatially distributed isotopes for Monte Carlo particle simulations and in specific FLUKA. With FLUKA it is possible to calculate the radio nuclide production in high energy fields. The decay of these nuclide, and therefore the resulting radiation field, however can only be simulated in the same geometry. This works gives the tool to simulate the decay of the produced nuclide in other geometries. With that the radiation field from an irradiated object can be simulated in arbitrary environments. The sampling of isotope mixtures was tested by simulating a 50/50 mixture of $Cs^{137}$ and $Co^{60}$. These isotopes are both well known and provide therefore a first reliable benchmark in that respect. The sampling of uniformly distributed coordinates was tested using the histogram test for various spatial distributions. The advantages and disadvantages of the program compared to standard methods are demonstrated in the real life ca...

  11. Dynamic spatial panels : models, methods, and inferences

    NARCIS (Netherlands)

    Elhorst, J. Paul

    This paper provides a survey of the existing literature on the specification and estimation of dynamic spatial panel data models, a collection of models for spatial panels extended to include one or more of the following variables and/or error terms: a dependent variable lagged in time, a dependent

  12. Moving beyond abundance distributions: neutral theory and spatial patterns in a tropical forest.

    Science.gov (United States)

    May, Felix; Huth, Andreas; Wiegand, Thorsten

    2015-03-07

    Assessing the relative importance of different processes that determine the spatial distribution of species and the dynamics in highly diverse plant communities remains a challenging question in ecology. Previous modelling approaches often focused on single aggregated forest diversity patterns that convey limited information on the underlying dynamic processes. Here, we use recent advances in inference for stochastic simulation models to evaluate the ability of a spatially explicit and spatially continuous neutral model to quantitatively predict six spatial and non-spatial patterns observed at the 50 ha tropical forest plot on Barro Colorado Island, Panama. The patterns capture different aspects of forest dynamics and biodiversity structure, such as annual mortality rate, species richness, species abundance distribution, beta-diversity and the species-area relationship (SAR). The model correctly predicted each pattern independently and up to five patterns simultaneously. However, the model was unable to match the SAR and beta-diversity simultaneously. Our study moves previous theory towards a dynamic spatial theory of biodiversity and demonstrates the value of spatial data to identify ecological processes. This opens up new avenues to evaluate the consequences of additional process for community assembly and dynamics.

  13. Assessing ecohydrological controls on catchment water storage, flux and age dynamics using tracers in a physically-based, spatially distributed model

    Science.gov (United States)

    Kuppel, S.; Tetzlaff, D.; Maneta, M. P.; Soulsby, C.

    2017-12-01

    Stable water isotope tracing has been extensively used in a wide range of geographical environments as a means to understand the sources, flow paths and ages of water stored and exiting a landscape via evapotranspiration, surface runoff and/or stream flow. Comparisons of isotopic signatures of precipitation and water in streams, soils, groundwater and plant xylem facilitates the assessment of how plant water use may affect preferential hydrologic pathways, storage dynamics and transit times in the critical zone. While tracers are also invaluable for testing model structure and accuracy, in most cases the measured isotopic signatures have been used to guide the calibration of conceptual runoff models with simplified vegetation and energy balance representation, which lacks sufficient detail to constrain key ecohydrological controls on flow paths and water ages. Here, we use a physically-based, distributed ecohydrological model (EcH2O) which we have extended to track 2H and 18O (including fractionation processes), and water age. This work is part of the "VeWa" project which aims at understanding ecohydrological couplings across climatic gradients in the wider North, where the hydrological implications of projected environmental change are essentially unknown though expected to be high. EcH2O combines a hydrologic scheme with an explicit representation of plant growth and phenology while resolving the energy balance across the soil-vegetation-atmosphere continuum. We focus on a montane catchment in Scotland, where unique long-term, high resolution hydrometric, ecohydrological and isotopic data allows for extensive model testing and projections. Results show the importance of incorporating soil fractionation processes to explain stream isotope dynamics, particularly seasonal enrichment in this humid, energy-limited catchment. This generic process-based approach facilitates analysis of dynamics in isotopes, storage and ages for the different hydrological compartments

  14. Spatial-Temporal Correlation Properties of the 3GPP Spatial Channel Model and the Kronecker MIMO Channel Model

    Directory of Open Access Journals (Sweden)

    Cheng-Xiang Wang

    2007-02-01

    Full Text Available The performance of multiple-input multiple-output (MIMO systems is greatly influenced by the spatial-temporal correlation properties of the underlying MIMO channels. This paper investigates the spatial-temporal correlation characteristics of the spatial channel model (SCM in the Third Generation Partnership Project (3GPP and the Kronecker-based stochastic model (KBSM at three levels, namely, the cluster level, link level, and system level. The KBSM has both the spatial separability and spatial-temporal separability at all the three levels. The spatial-temporal separability is observed for the SCM only at the system level, but not at the cluster and link levels. The SCM shows the spatial separability at the link and system levels, but not at the cluster level since its spatial correlation is related to the joint distribution of the angle of arrival (AoA and angle of departure (AoD. The KBSM with the Gaussian-shaped power azimuth spectrum (PAS is found to fit best the 3GPP SCM in terms of the spatial correlations. Despite its simplicity and analytical tractability, the KBSM is restricted to model only the average spatial-temporal behavior of MIMO channels. The SCM provides more insights of the variations of different MIMO channel realizations, but the implementation complexity is relatively high.

  15. Distribución potencial del Pinus martinezii: un modelo espacial basado en conocimiento ecológico y análisis multicriterio Potential distribution of Pinus martinezii: an spatial model based in ecological knowledge and muticriteria analysis

    Directory of Open Access Journals (Sweden)

    Óscar Leal-Nares

    2012-12-01

    Full Text Available El modelado de la distribución potencial y actual de las especies se ha convertido en un área de investigación muy activa; generalmente se basa en el concepto de nicho ecológico y se apoya en el uso de programas de cómputo. El objetivo principal de esta investigación fue elaborar un modelo de distribución potencial de Pinus martinezii en la cuenca del lago de Cuitzeo, utilizando información ambiental y datos de presencia de la especie, lo que requirió identificar los factores ambientales que determinan la distribución de P. martinezii, y elaborar un perfil bioclimático de la especie. El modelo se apoyó en un análisis multicriterio dentro de un sistema de información geográfica. Los atributos se agruparon en 3 criterios: geopedológicos, morfométricos y climáticos. De acuerdo con el mapa que se obtuvo, en la cuenca hay 2 zonas principales de distribución potencial de P. martinezii y algunas regiones aisladas donde no se encontraron poblaciones. El modelo espacial constituye una herramienta importante para planificar labores de conservación y reforestación; asimismo, puede utilizarse para planificar exploraciones en busca de nuevas poblaciones de P. martinezii que no han sido registradas, o identificar sitios donde esta especie pueda reintroducirse.The modeling of potential and current distribution of species has become a very active research area. Generally, modeling is based on the concept of ecological niche, and is supported by the use of computer programs. The main objective of this project was to develop a potential distribution model of Pinus martinezii in the Cuitzeo Lake basin using data of environmental variables, and presence of the target species. To this purpose, the environmental factors that determine the distribution of P. martinezii were identified, and a bioclimatic profile of the species was made. The modeling was based on a spatial multicriteria analyisis. The attributes were grouped into 3 criteria

  16. A distributed snow-evolution modeling system (SnowModel)

    Science.gov (United States)

    Glen E. Liston; Kelly. Elder

    2006-01-01

    SnowModel is a spatially distributed snow-evolution modeling system designed for application in landscapes, climates, and conditions where snow occurs. It is an aggregation of four submodels: MicroMet defines meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowPack simulates snow depth and water-equivalent evolution, and SnowTran-3D...

  17. A spatial pattern analysis of the halophytic species distribution in an arid coastal environment.

    Science.gov (United States)

    Badreldin, Nasem; Uria-Diez, J; Mateu, J; Youssef, Ali; Stal, Cornelis; El-Bana, Magdy; Magdy, Ahmed; Goossens, Rudi

    2015-05-01

    Obtaining information about the spatial distribution of desert plants is considered as a serious challenge for ecologists and environmental modeling due to the required intensive field work and infrastructures in harsh and remote arid environments. A new method was applied for assessing the spatial distribution of the halophytic species (HS) in an arid coastal environment. This method was based on the object-based image analysis for a high-resolution Google Earth satellite image. The integration of the image processing techniques and field work provided accurate information about the spatial distribution of HS. The extracted objects were based on assumptions that explained the plant-pixel relationship. Three different types of digital image processing techniques were implemented and validated to obtain an accurate HS spatial distribution. A total of 2703 individuals of the HS community were found in the case study, and approximately 82% were located above an elevation of 2 m. The micro-topography exhibited a significant negative relationship with pH and EC (r = -0.79 and -0.81, respectively, p < 0.001). The spatial structure was modeled using stochastic point processes, in particular a hybrid family of Gibbs processes. A new model is proposed that uses a hard-core structure at very short distances, together with a cluster structure in short-to-medium distances and a Poisson structure for larger distances. This model was found to fit the data perfectly well.

  18. The formulation and estimation of a spatial skew-normal generalized ordered-response model.

    Science.gov (United States)

    2016-06-01

    This paper proposes a new spatial generalized ordered response model with skew-normal kernel error terms and an : associated estimation method. It contributes to the spatial analysis field by allowing a flexible and parametric skew-normal : distribut...

  19. Estimating the Spatial Distribution of Groundwater Age Using Synoptic Surveys of Environmental Tracers in Streams

    Science.gov (United States)

    Gardner, W. P.

    2017-12-01

    A model which simulates tracer concentration in surface water as a function the age distribution of groundwater discharge is used to characterize groundwater flow systems at a variety of spatial scales. We develop the theory behind the model and demonstrate its application in several groundwater systems of local to regional scale. A 1-D stream transport model, which includes: advection, dispersion, gas exchange, first-order decay and groundwater inflow is coupled a lumped parameter model that calculates the concentration of environmental tracers in discharging groundwater as a function of the groundwater residence time distribution. The lumped parameters, which describe the residence time distribution, are allowed to vary spatially, and multiple environmental tracers can be simulated. This model allows us to calculate the longitudinal profile of tracer concentration in streams as a function of the spatially variable groundwater age distribution. By fitting model results to observations of stream chemistry and discharge, we can then estimate the spatial distribution of groundwater age. The volume of groundwater discharge to streams can be estimated using a subset of environmental tracers, applied tracers, synoptic stream gauging or other methods, and the age of groundwater then estimated using the previously calculated groundwater discharge and observed environmental tracer concentrations. Synoptic surveys of SF6, CFC's, 3H and 222Rn, along with measured stream discharge are used to estimate the groundwater inflow distribution and mean age for regional scale surveys of the Berland River in west-central Alberta. We find that groundwater entering the Berland has observable age, and that the age estimated using our stream survey is of similar order to limited samples from groundwater wells in the region. Our results show that the stream can be used as an easily accessible location to constrain the regional scale spatial distribution of groundwater age.

  20. Modeling spatial patterns of plant distribution as a consequence of hydrological dynamic processes in a Venezuelan flooding savanna = Modelo espacial de distribución de plantas como consecuencia de la dinámica hidrológica en una sabana inundable Venezolana

    NARCIS (Netherlands)

    Chacón-Moreno, E.J.; Smith, J.K.; Skidmore, A.K.; Prins, H.H.T.; Toxopeus, A.G.

    2007-01-01

    This study presents the main results of the analysis and integration of ecological ordination and spatially explicit relationships into an ecological-spatial model. This allows understanding, evaluating and predicting the distribution of dominant plant species in a changing flooding savanna

  1. Spatial Uncertainty Model for Visual Features Using a Kinect™ Sensor

    Directory of Open Access Journals (Sweden)

    Jae-Han Park

    2012-06-01

    Full Text Available This study proposes a mathematical uncertainty model for the spatial measurement of visual features using Kinect™ sensors. This model can provide qualitative and quantitative analysis for the utilization of Kinect™ sensors as 3D perception sensors. In order to achieve this objective, we derived the propagation relationship of the uncertainties between the disparity image space and the real Cartesian space with the mapping function between the two spaces. Using this propagation relationship, we obtained the mathematical model for the covariance matrix of the measurement error, which represents the uncertainty for spatial position of visual features from Kinect™ sensors. In order to derive the quantitative model of spatial uncertainty for visual features, we estimated the covariance matrix in the disparity image space using collected visual feature data. Further, we computed the spatial uncertainty information by applying the covariance matrix in the disparity image space and the calibrated sensor parameters to the proposed mathematical model. This spatial uncertainty model was verified by comparing the uncertainty ellipsoids for spatial covariance matrices and the distribution of scattered matching visual features. We expect that this spatial uncertainty model and its analyses will be useful in various Kinect™ sensor applications.

  2. Spatial uncertainty model for visual features using a Kinect™ sensor.

    Science.gov (United States)

    Park, Jae-Han; Shin, Yong-Deuk; Bae, Ji-Hun; Baeg, Moon-Hong

    2012-01-01

    This study proposes a mathematical uncertainty model for the spatial measurement of visual features using Kinect™ sensors. This model can provide qualitative and quantitative analysis for the utilization of Kinect™ sensors as 3D perception sensors. In order to achieve this objective, we derived the propagation relationship of the uncertainties between the disparity image space and the real Cartesian space with the mapping function between the two spaces. Using this propagation relationship, we obtained the mathematical model for the covariance matrix of the measurement error, which represents the uncertainty for spatial position of visual features from Kinect™ sensors. In order to derive the quantitative model of spatial uncertainty for visual features, we estimated the covariance matrix in the disparity image space using collected visual feature data. Further, we computed the spatial uncertainty information by applying the covariance matrix in the disparity image space and the calibrated sensor parameters to the proposed mathematical model. This spatial uncertainty model was verified by comparing the uncertainty ellipsoids for spatial covariance matrices and the distribution of scattered matching visual features. We expect that this spatial uncertainty model and its analyses will be useful in various Kinect™ sensor applications.

  3. Prediction of the Spatial Distribution of Bovine Endemic Fluorosis Using Ordinary Kriging

    Directory of Open Access Journals (Sweden)

    Li Lin

    2015-04-01

    Full Text Available The aim of the studies was to develop an alternative method which could overcome the lack of sampling to improve the efficiency of control efforts for bovine endemic fluorosis. The spatial distribution characteristics of the disease were analysed and a prediction model for the estimation of fluorosis distribution in some districts in northwest Liaoning province in China was established. The model used ordinary kriging, and was evaluated using cross-validation. Analysis showed that the distribution of the disease was spatial autocorrelation. The prediction error of the cross-validation (ME = -0.0092, PMSE = 0.627, AKSE = 0.597, and RMSP = 1.007 and comparison with the actual disease distribution indicated that the prediction map accurately distributed bovine endemic fluorosis. It is feasible to predict bovine endemic fluorosis in the area by using ordinary kriging and limited data.

  4. Managing distributed dynamic systems with spatial grasp technology

    CERN Document Server

    Sapaty, Peter Simon

    2017-01-01

    The book describes a novel ideology and supporting information technology for integral management of both civil and defence-orientated large, distributed dynamic systems. The approach is based on a high-level Spatial Grasp Language, SGL, expressing solutions in physical, virtual, executive and combined environments in the form of active self-evolving and self-propagating patterns spatially matching the systems to be created, modified and controlled. The communicating interpreters of SGL can be installed in key system points, which may be in large numbers (up to millions and billions) and represent equipped humans, robots, laptops, smartphones, smart sensors, etc. Operating under gestalt-inspired scenarios in SGL initially injected from any points, these systems can be effectively converted into goal-driven spatial machines (rather than computers as dealing with physical matter too) capable of responding to numerous challenges caused by growing world dynamics in the 21st century. Including numerous practical e...

  5. The Impact of Spatial and Temporal Resolutions in Tropical Summer Rainfall Distribution: Preliminary Results

    Science.gov (United States)

    Liu, Q.; Chiu, L. S.; Hao, X.

    2017-10-01

    The abundance or lack of rainfall affects peoples' life and activities. As a major component of the global hydrological cycle (Chokngamwong & Chiu, 2007), accurate representations at various spatial and temporal scales are crucial for a lot of decision making processes. Climate models show a warmer and wetter climate due to increases of Greenhouse Gases (GHG). However, the models' resolutions are often too coarse to be directly applicable to local scales that are useful for mitigation purposes. Hence disaggregation (downscaling) procedures are needed to transfer the coarse scale products to higher spatial and temporal resolutions. The aim of this paper is to examine the changes in the statistical parameters of rainfall at various spatial and temporal resolutions. The TRMM Multi-satellite Precipitation Analysis (TMPA) at 0.25 degree, 3 hourly grid rainfall data for a summer is aggregated to 0.5,1.0, 2.0 and 2.5 degree and at 6, 12, 24 hourly, pentad (five days) and monthly resolutions. The probability distributions (PDF) and cumulative distribution functions(CDF) of rain amount at these resolutions are computed and modeled as a mixed distribution. Parameters of the PDFs are compared using the Kolmogrov-Smironov (KS) test, both for the mixed and the marginal distribution. These distributions are shown to be distinct. The marginal distributions are fitted with Lognormal and Gamma distributions and it is found that the Gamma distributions fit much better than the Lognormal.

  6. Spatial distribution of enzyme activities in the rhizosphere

    Science.gov (United States)

    Razavi, Bahar S.; Zarebanadkouki, Mohsen; Blagodatskaya, Evgenia; Kuzyakov, Yakov

    2015-04-01

    The rhizosphere, the tiny zone of soil surrounding roots, certainly represents one of the most dynamic habitat and interfaces on Earth. Activities of enzymes produced by both plant roots and microbes are the primary biological drivers of organic matter decomposition and nutrient cycling. That is why there is an urgent need in spatially explicit methods for the determination of the rhizosphere extension and enzyme distribution. Recently, zymography as a new technique based on diffusion of enzymes through the 1 mm gel plate for analysis has been introduced (Spohn & Kuzyakov, 2013). We developed the zymography technique to visualize the enzyme activities with a higher spatial resolution. For the first time, we aimed at quantitative imaging of enzyme activities as a function of distance from the root tip and the root surface in the soil. We visualized the two dimensional distribution of the activity of three enzymes: β-glucosidase, phosphatase and leucine amino peptidase in the rhizosphere of maize using fluorogenically labelled substrates. Spatial-resolution of fluorescent images was improved by direct application of a substrate saturated membrane to the soil-root system. The newly-developed direct zymography visualized heterogeneity of enzyme activities along the roots. The activity of all enzymes was the highest at the apical parts of individual roots. Across the roots, the enzyme activities were higher at immediate vicinity of the roots (1.5 mm) and gradually decreased towards the bulk soil. Spatial patterns of enzyme activities as a function of distance from the root surface were enzyme specific, with highest extension for phosphatase. We conclude that improved zymography is promising in situ technique to analyze, visualize and quantify spatial distribution of enzyme activities in the rhizosphere hotspots. References Spohn, M., Kuzyakov, Y., 2013. Phosphorus mineralization can be driven by microbial need for carbon. Soil Biology & Biochemistry 61: 69-75

  7. Panchromatic SED modelling of spatially resolved galaxies

    Science.gov (United States)

    Smith, Daniel J. B.; Hayward, Christopher C.

    2018-05-01

    We test the efficacy of the energy-balance spectral energy distribution (SED) fitting code MAGPHYS for recovering the spatially resolved properties of a simulated isolated disc galaxy, for which it was not designed. We perform 226 950 MAGPHYS SED fits to regions between 0.2 and 25 kpc in size across the galaxy's disc, viewed from three different sight-lines, to probe how well MAGPHYS can recover key galaxy properties based on 21 bands of UV-far-infrared model photometry. MAGPHYS yields statistically acceptable fits to >99 per cent of the pixels within the r-band effective radius and between 59 and 77 percent of pixels within 20 kpc of the nucleus. MAGPHYS is able to recover the distribution of stellar mass, star formation rate (SFR), specific SFR, dust luminosity, dust mass, and V-band attenuation reasonably well, especially when the pixel size is ≳ 1 kpc, whereas non-standard outputs (stellar metallicity and mass-weighted age) are recovered less well. Accurate recovery is more challenging in the smallest sub-regions of the disc (pixel scale ≲ 1 kpc), where the energy balance criterion becomes increasingly incorrect. Estimating integrated galaxy properties by summing the recovered pixel values, the true integrated values of all parameters considered except metallicity and age are well recovered at all spatial resolutions, ranging from 0.2 kpc to integrating across the disc, albeit with some evidence for resolution-dependent biases. These results must be considered when attempting to analyse the structure of real galaxies with actual observational data, for which the `ground truth' is unknown.

  8. LEACHED SOILS IN SLOVENIA: PEDOLOGICAL PROPERTIES, SPATIAL DISTRIBUTION AND CLASSIFICATION

    OpenAIRE

    Rok TURNIŠKI; Helena GRČMAN

    2018-01-01

    Eluvial-illuvial processes plays key role in pedogenesis, especially in the development of leached soils. As reported in Slovenian soil map 1 : 25.000 leached soils cover 2,3 % of Slovenian territory. They occur on different parent materials, mostly on flat relief preserved from erosion and colluvial processes. The aim of our study is the evaluation of their morpohological, physical and chemical properties, spatial distribution and dependency on soil forming factors, especially on parent mate...

  9. LUMINOUS SATELLITES OF EARLY-TYPE GALAXIES. I. SPATIAL DISTRIBUTION

    International Nuclear Information System (INIS)

    Nierenberg, A. M.; Auger, M. W.; Treu, T.; Marshall, P. J.; Fassnacht, C. D.

    2011-01-01

    We study the spatial distribution of faint satellites of intermediate redshift (0.1 s = 1.7 +0.9 -0.8 ) that is comparable to the number of Milky Way satellites with similar host-satellite contrast. The average projected radial profile of the satellite distribution is isothermal (γ p = -1.0 +0.3 -0.4 ), which is consistent with the observed central mass density profile of massive early-type galaxies. Furthermore, the satellite distribution is highly anisotropic (isotropy is ruled out at a >99.99% confidence level). Defining φ to be the offset between the major axis of the satellite spatial distribution and the major axis of the host light profile, we find a maximum posterior probability of φ = 0 and |φ| less than 42 0 at the 68% confidence level. The alignment of the satellite distribution with the light of the host is consistent with simulations, assuming that light traces mass for the host galaxy as observed for lens galaxies. The anisotropy of the satellite population enhances its ability to produce the flux ratio anomalies observed in gravitationally lensed quasars.

  10. Hierarchical modeling and analysis for spatial data

    CERN Document Server

    Banerjee, Sudipto; Gelfand, Alan E

    2003-01-01

    Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis, or written at a level often inaccessible to those lacking a strong background in mathematical statistics.Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and dat

  11. Spatial distribution of enzyme driven reactions at micro-scales

    Science.gov (United States)

    Kandeler, Ellen; Boeddinghaus, Runa; Nassal, Dinah; Preusser, Sebastian; Marhan, Sven; Poll, Christian

    2017-04-01

    Studies of microbial biogeography can often provide key insights into the physiologies, environmental tolerances, and ecological strategies of soil microorganisms that dominate in natural environments. In comparison with aquatic systems, soils are particularly heterogeneous. Soil heterogeneity results from the interaction of a hierarchical series of interrelated variables that fluctuate at many different spatial and temporal scales. Whereas spatial dependence of chemical and physical soil properties is well known at scales ranging from decimetres to several hundred metres, the spatial structure of soil enzymes is less clear. Previous work has primarily focused on spatial heterogeneity at a single analytical scale using the distribution of individual cells, specific types of organisms or collective parameters such as bacterial abundance or total microbial biomass. There are fewer studies that have considered variations in community function and soil enzyme activities. This presentation will give an overview about recent studies focusing on spatial pattern of different soil enzymes in the terrestrial environment. Whereas zymography allows the visualization of enzyme pattern in the close vicinity of roots, micro-sampling strategies followed by MUF analyses clarify micro-scale pattern of enzymes associated to specific microhabitats (micro-aggregates, organo-mineral complexes, subsoil compartments).

  12. Models and Inference for Multivariate Spatial Extremes

    KAUST Repository

    Vettori, Sabrina

    2017-12-07

    The development of flexible and interpretable statistical methods is necessary in order to provide appropriate risk assessment measures for extreme events and natural disasters. In this thesis, we address this challenge by contributing to the developing research field of Extreme-Value Theory. We initially study the performance of existing parametric and non-parametric estimators of extremal dependence for multivariate maxima. As the dimensionality increases, non-parametric estimators are more flexible than parametric methods but present some loss in efficiency that we quantify under various scenarios. We introduce a statistical tool which imposes the required shape constraints on non-parametric estimators in high dimensions, significantly improving their performance. Furthermore, by embedding the tree-based max-stable nested logistic distribution in the Bayesian framework, we develop a statistical algorithm that identifies the most likely tree structures representing the data\\'s extremal dependence using the reversible jump Monte Carlo Markov Chain method. A mixture of these trees is then used for uncertainty assessment in prediction through Bayesian model averaging. The computational complexity of full likelihood inference is significantly decreased by deriving a recursive formula for the nested logistic model likelihood. The algorithm performance is verified through simulation experiments which also compare different likelihood procedures. Finally, we extend the nested logistic representation to the spatial framework in order to jointly model multivariate variables collected across a spatial region. This situation emerges often in environmental applications but is not often considered in the current literature. Simulation experiments show that the new class of multivariate max-stable processes is able to detect both the cross and inner spatial dependence of a number of extreme variables at a relatively low computational cost, thanks to its Bayesian hierarchical

  13. Modelling the spatial distribution of endemic Caesalpinioideae in Central Africa, a contribution to the evaluation of actual protected areas in the region

    DEFF Research Database (Denmark)

    Ndayishimiye, Joël; Greve, Michelle; Stoffelen, P.

    2012-01-01

    variables (soil, elevation, and slope). Environmental variables and species occurrence data were obtained respectively from the WorldClim database and from herbarium specimens kept at the National Botanic Garden of Belgium and the Université Libre de Bruxelles. Our results suggest that the distribution...... of endemic species is influenced by a combination of climatic and non-climatic variables. Soil type, temperature annual range and precipitation of the driest month were the most important predictor variables. Overlaying the potential distributions of the seven selected species indicated three areas...

  14. Applications of spatial statistical network models to stream data

    Science.gov (United States)

    Isaak, Daniel J.; Peterson, Erin E.; Ver Hoef, Jay M.; Wenger, Seth J.; Falke, Jeffrey A.; Torgersen, Christian E.; Sowder, Colin; Steel, E. Ashley; Fortin, Marie-Josée; Jordan, Chris E.; Ruesch, Aaron S.; Som, Nicholas; Monestiez, Pascal

    2014-01-01

    Streams and rivers host a significant portion of Earth's biodiversity and provide important ecosystem services for human populations. Accurate information regarding the status and trends of stream resources is vital for their effective conservation and management. Most statistical techniques applied to data measured on stream networks were developed for terrestrial applications and are not optimized for streams. A new class of spatial statistical model, based on valid covariance structures for stream networks, can be used with many common types of stream data (e.g., water quality attributes, habitat conditions, biological surveys) through application of appropriate distributions (e.g., Gaussian, binomial, Poisson). The spatial statistical network models account for spatial autocorrelation (i.e., nonindependence) among measurements, which allows their application to databases with clustered measurement locations. Large amounts of stream data exist in many areas where spatial statistical analyses could be used to develop novel insights, improve predictions at unsampled sites, and aid in the design of efficient monitoring strategies at relatively low cost. We review the topic of spatial autocorrelation and its effects on statistical inference, demonstrate the use of spatial statistics with stream datasets relevant to common research and management questions, and discuss additional applications and development potential for spatial statistics on stream networks. Free software for implementing the spatial statistical network models has been developed that enables custom applications with many stream databases.

  15. Analysis of shifts in the spatial distribution of vegetation due to climate change

    Science.gov (United States)

    del Jesus, Manuel; Díez-Sierra, Javier; Rinaldo, Andrea; Rodríguez-Iturbe, Ignacio

    2017-04-01

    Climate change will modify the statistical regime of most climatological variables, inducing changes on average values and in the natural variability of environmental variables. These environmental variables may be used to explain the spatial distribution of functional types of vegetation in arid and semiarid watersheds through the use of plant optimization theories. Therefore, plant optimization theories may be used to approximate the response of the spatial distribution of vegetation to a changing climate. Predicting changes in these spatial distributions is important to understand how climate change may affect vegetated ecosystems, but it is also important for hydrological engineering applications where climate change effects on water availability are assessed. In this work, Maximum Entropy Production (MEP) is used as the plant optimization theory that describes the spatial distribution of functional types of vegetation. Current climatological conditions are obtained from direct observations from meteorological stations. Climate change effects are evaluated for different temporal horizons and different climate change scenarios using numerical model outputs from the CMIP5. Rainfall estimates are downscaled by means of a stochastic point process used to model rainfall. The study is carried out for the Rio Salado watershed, located within the Sevilleta LTER site, in New Mexico (USA). Results show the expected changes in the spatial distribution of vegetation and allow to evaluate the expected variability of the changes. The updated spatial distributions allow to evaluate the vegetated ecosystem health and its updated resilience. These results can then be used to inform the hydrological modeling part of climate change assessments analyzing water availability in arid and semiarid watersheds.

  16. Spatial Allocator for air quality modeling

    Science.gov (United States)

    The Spatial Allocator is a set of tools that helps users manipulate and generate data files related to emissions and air quality modeling without requiring the use of a commercial Geographic Information System.

  17. Spatial distribution of cancer in Kohgilooyeh and Boyerahmad province

    Directory of Open Access Journals (Sweden)

    M Fararouei

    2016-02-01

    Full Text Available Spatial distribution of cancer is one of the powerful tools in epidemiology of cancer. The present study is designed to understand the geographical distribution of most frequent types of cancer in K&B province. Methods: All registered cases of cancer are reviewed and duplicate cases were removed. The data was analyzed using Arcgis software. Results: Of all registered cases, 1273  remained for analysis of which 57% were residences of urban areas. Cities including  Sisakht, Yasuj and Dehdsasht were shown to have highest incidence rates among the Urban areas. Dena, Sepidar and Kohmare Khaleghi had the highest rates among the rural areas in the province. Skin cancer was the most common type of cancer which had the highest rates of incidence in Sisakht and Dehdasht and Dena and Sepidar among urban and rural areas respectively. Conclusion: The distribution of cancer was not even in the province. Attitude and consumption of wild and regional plants are introduced as the potential risk factors for such a spatial distribution of the common cancers I the province. The results of this study could be used for further analytical studies to understand the regional etiology of cancer in the province.

  18. Mathematical Modeling of spatial disease variables by Spatial Fuzzy Logic for Spatial Decision Support Systems

    Science.gov (United States)

    Platz, M.; Rapp, J.; Groessler, M.; Niehaus, E.; Babu, A.; Soman, B.

    2014-11-01

    A Spatial Decision Support System (SDSS) provides support for decision makers and should not be viewed as replacing human intelligence with machines. Therefore it is reasonable that decision makers are able to use a feature to analyze the provided spatial decision support in detail to crosscheck the digital support of the SDSS with their own expertise. Spatial decision support is based on risk and resource maps in a Geographic Information System (GIS) with relevant layers e.g. environmental, health and socio-economic data. Spatial fuzzy logic allows the representation of spatial properties with a value of truth in the range between 0 and 1. Decision makers can refer to the visualization of the spatial truth of single risk variables of a disease. Spatial fuzzy logic rules that support the allocation of limited resources according to risk can be evaluated with measure theory on topological spaces, which allows to visualize the applicability of this rules as well in a map. Our paper is based on the concept of a spatial fuzzy logic on topological spaces that contributes to the development of an adaptive Early Warning And Response System (EWARS) providing decision support for the current or future spatial distribution of a disease. It supports the decision maker in testing interventions based on available resources and apply risk mitigation strategies and provide guidance tailored to the geo-location of the user via mobile devices. The software component of the system would be based on open source software and the software developed during this project will also be in the open source domain, so that an open community can build on the results and tailor further work to regional or international requirements and constraints. A freely available EWARS Spatial Fuzzy Logic Demo was developed wich enables a user to visualize risk and resource maps based on individual data in several data formats.

  19. Spatial distribution of soil erosion and suspended sediment ...

    Indian Academy of Sciences (India)

    extension modules (spatial analysis, hydrologic model, 3D Analyst, Network Analyst), and the Object-Oriented Programming Language. (Avenue). This data consists of slope, area, aver- age elevation, roughness, CN value, etc. In addi- tion, GIS can also determine the flow direction, the accumulated discharge, the main ...

  20. Monofractal and multifractal analysis of the spatial distribution of earthquakes in the central zone of Chile.

    Science.gov (United States)

    Pastén, Denisse; Muñoz, Víctor; Cisternas, Armando; Rogan, José; Valdivia, Juan Alejandro

    2011-12-01

    Statistical and fractal properties of the spatial distribution of earthquakes in the central zone of Chile are studied. In particular, data are shown to behave according to the well-known Gutenberg-Richter law. The fractal structure is evident for epicenters, not for hypocenters. The multifractal spectrum is also determined, both for the spatial distribution of epicenters and hypocenters. For negative values of the index of multifractal measure q, the multifractal spectrum, which usually cannot be reliably found from data, is calculated from a generalized Cantor-set model, which fits the multifractal spectrum for q > 0, a technique which has been previously applied for analysis of solar wind data.

  1. Evaluating spatial patterns in hydrological modelling

    DEFF Research Database (Denmark)

    Koch, Julian

    is not fully exploited by current modelling frameworks due to the lack of suitable spatial performance metrics. Furthermore, the traditional model evaluation using discharge is found unsuitable to lay confidence on the predicted catchment inherent spatial variability of hydrological processes in a fully...... the contiguous United Sates (10^6 km2). To this end, the thesis at hand applies a set of spatial performance metrics on various hydrological variables, namely land-surface-temperature (LST), evapotranspiration (ET) and soil moisture. The inspiration for the applied metrics is found in related fields...

  2. Temporal and spatial distribution of high energy electrons at Jupiter

    Science.gov (United States)

    Jun, I.; Garrett, H. B.; Ratliff, J. M.

    2003-04-01

    Measurements of the high energy, omni-directional electron environment by the Galileo spacecraft Energetic Particle Detector (EPD) were used to study the high energy electron environment in the Jovian magnetosphere, especially in the region between 8 to 18 Rj (1 Rj = 1 Jovian radius = 71,400 km). 10-minute averages of the EPD data collected between Jupiter orbit insertion (JOI) in 1995 and the orbit number 33 (I33) in 2002 form an extensive dataset, which has been extremely useful to observe temporal and spatial variability of the Jovian high energy electron environment. The count rates of the EPD electron channels (0.174, 0.304, 0.527, 1.5, 2.0, and 11 MeV) were grouped into 0.5 Rj or 0.5 L bins and analyzed statistically. The results indicate that: (1) a log-normal Gaussian distribution well describes the statistics of the high energy electron environment (for example, electron differential fluxes) in the Jovian magnetosphere, in the region studied here; (2) the high energy electron environments inferred by the Galileo EPD measurements are in a close agreement with the data obtained using the Divine model, which was developed more than 30 years ago from Pioneer 10, 11 and Voyager 1, 2 data; (3) the data are better organized when plotted against magnetic radial parameter L than Rj; (4) the standard deviations of the 0.174, 0.304, 0.527 MeV channel count rates are larger than those of the 1.5, 2.0, 11 MeV count rates in 12 Rj. These observations are very helpful to understand short- and long-term, and local variability of the Jovian high energy electron environment, and are discussed in detail.

  3. Spatial pattern of diarrhea based on regional economic and environment by spatial autoregressive model

    Science.gov (United States)

    Bekti, Rokhana Dwi; Nurhadiyanti, Gita; Irwansyah, Edy

    2014-10-01

    The diarrhea case pattern information, especially for toddler, is very important. It is used to show the distribution of diarrhea in every region, relationship among that locations, and regional economic characteristic or environmental behavior. So, this research uses spatial pattern to perform them. This method includes: Moran's I, Spatial Autoregressive Models (SAR), and Local Indicator of Spatial Autocorrelation (LISA). It uses sample from 23 sub districts of Bekasi Regency, West Java, Indonesia. Diarrhea case, regional economic, and environmental behavior of households have a spatial relationship among sub district. SAR shows that the percentage of Regional Gross Domestic Product is significantly effect on diarrhea at α = 10%. Therefore illiteracy and health center facilities are significant at α = 5%. With LISA test, sub districts in southern Bekasi have high dependencies with Cikarang Selatan, Serang Baru, and Setu. This research also builds development application that is based on java and R to support data analysis.

  4. Spatial distribution of luminous X-ray binaries in spiral galaxies

    OpenAIRE

    Zuo, Zhao-yu; Li, Xiang-dong; Liu, Xi-wei

    2008-01-01

    We have modelled the spatial distribution of luminous X-ray binaries (XRBs) in spiral galaxies that are like the Milky Way using an evolutionary population synthesis code. In agreement with previous theoretical expectations and observations, we find that both high- and low-mass XRBs show clear concentrations towards the galactic plane and bulge.We also compare XRB distributions under the galactic potential with a dark matter halo and the modified Newtonian dynamics potential, and we suggest t...

  5. Reducing Spatial Data Complexity for Classification Models

    International Nuclear Information System (INIS)

    Ruta, Dymitr; Gabrys, Bogdan

    2007-01-01

    Intelligent data analytics gradually becomes a day-to-day reality of today's businesses. However, despite rapidly increasing storage and computational power current state-of-the-art predictive models still can not handle massive and noisy corporate data warehouses. What is more adaptive and real-time operational environment requires multiple models to be frequently retrained which further hinders their use. Various data reduction techniques ranging from data sampling up to density retention models attempt to address this challenge by capturing a summarised data structure, yet they either do not account for labelled data or degrade the classification performance of the model trained on the condensed dataset. Our response is a proposition of a new general framework for reducing the complexity of labelled data by means of controlled spatial redistribution of class densities in the input space. On the example of Parzen Labelled Data Compressor (PLDC) we demonstrate a simulatory data condensation process directly inspired by the electrostatic field interaction where the data are moved and merged following the attracting and repelling interactions with the other labelled data. The process is controlled by the class density function built on the original data that acts as a class-sensitive potential field ensuring preservation of the original class density distributions, yet allowing data to rearrange and merge joining together their soft class partitions. As a result we achieved a model that reduces the labelled datasets much further than any competitive approaches yet with the maximum retention of the original class densities and hence the classification performance. PLDC leaves the reduced dataset with the soft accumulative class weights allowing for efficient online updates and as shown in a series of experiments if coupled with Parzen Density Classifier (PDC) significantly outperforms competitive data condensation methods in terms of classification performance at the

  6. Crime Modeling using Spatial Regression Approach

    Science.gov (United States)

    Saleh Ahmar, Ansari; Adiatma; Kasim Aidid, M.

    2018-01-01

    Act of criminality in Indonesia increased both variety and quantity every year. As murder, rape, assault, vandalism, theft, fraud, fencing, and other cases that make people feel unsafe. Risk of society exposed to crime is the number of reported cases in the police institution. The higher of the number of reporter to the police institution then the number of crime in the region is increasing. In this research, modeling criminality in South Sulawesi, Indonesia with the dependent variable used is the society exposed to the risk of crime. Modelling done by area approach is the using Spatial Autoregressive (SAR) and Spatial Error Model (SEM) methods. The independent variable used is the population density, the number of poor population, GDP per capita, unemployment and the human development index (HDI). Based on the analysis using spatial regression can be shown that there are no dependencies spatial both lag or errors in South Sulawesi.

  7. A spatial model of mosquito host-seeking behavior.

    Directory of Open Access Journals (Sweden)

    Bree Cummins

    Full Text Available Mosquito host-seeking behavior and heterogeneity in host distribution are important factors in predicting the transmission dynamics of mosquito-borne infections such as dengue fever, malaria, chikungunya, and West Nile virus. We develop and analyze a new mathematical model to describe the effect of spatial heterogeneity on the contact rate between mosquito vectors and hosts. The model includes odor plumes generated by spatially distributed hosts, wind velocity, and mosquito behavior based on both the prevailing wind and the odor plume. On a spatial scale of meters and a time scale of minutes, we compare the effectiveness of different plume-finding and plume-tracking strategies that mosquitoes could use to locate a host. The results show that two different models of chemotaxis are capable of producing comparable results given appropriate parameter choices and that host finding is optimized by a strategy of flying across the wind until the odor plume is intercepted. We also assess the impact of changing the level of host aggregation on mosquito host-finding success near the end of the host-seeking flight. When clusters of hosts are more tightly associated on smaller patches, the odor plume is narrower and the biting rate per host is decreased. For two host groups of unequal number but equal spatial density, the biting rate per host is lower in the group with more individuals, indicative of an attack abatement effect of host aggregation. We discuss how this approach could assist parameter choices in compartmental models that do not explicitly model the spatial arrangement of individuals and how the model could address larger spatial scales and other probability models for mosquito behavior, such as Lévy distributions.

  8. Predicting a roadkill hotspots based on spatial distribution of Korean water deer (Hydropotes inermis argyropus) using Maxent model in South Korea Expressway : In Case of Cheongju-Sangju Expressway

    Science.gov (United States)

    Park, Hyomin; Lee, Sangdon

    2016-04-01

    Road construction has direct and indirect effects on ecosystems. Especially wildlife-vehicle conflicts (roadkills) caused by roads are a considerable threat for population of many species. This study aims to identify the effects of topographic characteristics and spatial distribution of Korean water deer (Hydropotes inermis). Korean water deer is indigenous and native species in Korea that listed LC (least concern) by IUCN redlist categories. Korean water deer population is growing every year occupying for most of roadkills (>70%) in Korean express highway. In order to predict a distribution of the Korean water deer, we selected factors that most affected water deer's habitat. Major habitats of waterdeer are known as agricultural area, forest area and water. Based on this result, eight factors were selected (land cover map, vegetation map, age class of forest, diameter class of tree, population, slope of study site, elevation of study site, distance of river), and made a thematic map by using GIS program (ESRI, Arc GIS 10.3.1 ver.). To analyze the affected factors of waterdeer distribution, GPS data and thematic map of study area were entered into Maxent model (Maxent 3.3.3.k.). Results of analysis were verified by the AUC (Area Unit Curve) of ROC (Receiver Operating Characteristic). The ROC curve used the sensitivity and specificity as a reference for determining the prediction efficiency of the model and AUC area of ROC curve was higher prediction efficiency closer to '1.' Selecting factors that affected the distribution of waterdeer were land cover map, diameter class of tree and elevation of study site. The value of AUC was 0.623. To predict the water deer's roadkills hot spot on Cheongju-Sangju Expressway, the thematic map was prepared based on GPS data of roadkill spots. As a result, the topographic factors that affected waterdeer roadkill were land cover map, actual vegetation map and age class of forest and the value of AUC was 0.854. Through this study, we

  9. Spatial distributions at equilibrium under heterogeneous transient subdiffusion.

    Science.gov (United States)

    Berry, Hugues; Soula, Hédi A

    2014-01-01

    Experimental measurements of the mobility of macromolecules, especially proteins, in cells and their membranes consistently report transient subdiffusion with possibly position-dependent-non-homogeneous-properties. However, the spatiotemporal dynamics of protein mobility when transient subdiffusion is restricted to a subregion of space is still unclear. Here, we investigated the spatial distribution at equilibrium of proteins undergoing transient subdiffusion due to continuous-time random walks (CTRW) in a restricted subregion of a two-dimensional space. Our Monte-Carlo simulations suggest that this process leads to a non-homogeneous spatial distribution of the proteins at equilibrium, where proteins increasingly accumulate in the CTRW subregion as its anomalous properties are increasingly marked. In the case of transient CTRW, we show that this accumulation is dictated by the asymptotic Brownian regime and not by the initial anomalous transient dynamics. Moreover, our results also show that this dominance of the asymptotic Brownian regime cannot be simply generalized to other scenarios of transient subdiffusion. In particular, non-homogeneous transient subdiffusion due to hindrance by randomly-located immobile obstacles does not lead to such a strong local accumulation. These results suggest that, even though they exhibit the same time-dependence of the mean-squared displacement, the different scenarios proposed to account for subdiffusion in the cell lead to different protein distribution in space, even at equilibrium and without coupling with reaction.

  10. Spatial distributions at equilibrium under heterogeneous transient subdiffusion

    Directory of Open Access Journals (Sweden)

    Hugues eBerry

    2014-11-01

    Full Text Available Experimental measurements of the mobility of macromolecules, especially proteins, in cells and their membranes consistently report transient subdiffusion with possibly position-dependent -- nonhomogeneous -- properties. However, the spatiotemporal dynamics of protein mobility when transient subdiffusion is restricted to a subregion of space is still unclear. Here, we investigated the spatial distribution at equilibrium of proteins undergoing transient subdiffusion due to continuous-time random walks (CTRW in a restricted subregion of a two-dimensional space. Our Monte-Carlo simulations suggest that this process leads to a nonhomogeneous spatial distribution of the proteins at equilibrium, where proteins increasingly accumulate in the CTRW subregion as its anomalous properties are increasingly marked. In the case of transient CTRW, we show that this accumulation is dictated by the asymptotic Brownian regime and not by the initial anomalous transient dynamics. Moreover, our results also show that this dominance of the asymptotic Brownian regime cannot be simply generalized to other scenarios of transient subdiffusion. In particular, nonhomogeneous transient subdiffusion due to hindrance by randomly-located immobile obstacles does not lead to such a strong local accumulation. These results suggest that, even though they exhibit the same time-dependence of the mean-squared displacement, the different scenarios proposed to account for subdiffusion in the cell lead to different protein distribution in space, even at equilibrium and without coupling with reaction.

  11. [Spatial distribution of nests of Acromyrmex crassispinus (Forel) (Hymenoptera: Formicidae) in Pinus taeda plantations].

    Science.gov (United States)

    Nickele, Mariane A; Oliveira, Edilson B de; Reis Filho, Wilson; Iede, Edson T; Ribeiro, Rodrigo D

    2010-01-01

    The spatial distribution of insects is essential to perform control strategies, to improve sample techniques and to estimate economic losses. We aimed to determine the spatial distribution of nests of Acromyrmex crassispinus (Forel) in Pinus taeda plantations. The experiments were carried out in P. taeda plantations with different ages (treatments: recently-planted, three and six-year old plants). The study took place in Rio Negrinho and in Três Barras, SC. Three plots of one hectare were delimited in each treatment, and plots were divided in 64 sample units. The analysis of the dispersion index [variance/mean relationship (I), index of Morisita (Iδ) and k exponent of negative binomial distribution] showed that the majority of the samplings presented random distribution. Among the three distributions of probabilities studied: Poisson, positive binomial and negative binomial, the Poisson distribution was the best model to fit the spatial distribution of A. crassispinus nests in all samplings. The result was a random distribution in the plantings of different ages.

  12. MODELING SPATIAL TREE PATTERNS IN THE TAPAJÓS FOREST USING INTERFEROMETRIC HEIGHT

    Directory of Open Access Journals (Sweden)

    João R. dos Santos

    2005-04-01

    Full Text Available The spatial distribution of very large trees in primary Amazon forest is extracted from a digital model of interferometric forest height by an approach of local maximum filtering. The spatial point patterns of very large trees are modeled by a series of Markov point process models. Spatial distribution is regular, and interaction decreases with distance; very large trees are shown to exert repulsive interaction with their neighboring very large trees.

  13. Spatial relationship between tumor perfusion and endogeneous glucose distribution

    International Nuclear Information System (INIS)

    Schroeder, T.; Larrier, N.; Viglianti, B.; Rabbani, Z.N.; Peltz, C.; Vujascovic, Z.; Dewhirst, M.W.

    2003-01-01

    Earlier studies detecting glucose in tissue and solid tumors by bioluminescence imaging suggested, that glucose distribution patterns may be spatially related to functional vascularity. The purpose of this study was to evaluate this relationship by comparing glucose distribution patterns as determined by bioluminescence imaging to perfusion patterns of endogeneous Hoechst 33342 in rats bearing mammary carcinomas. R 3230 mammary carcinoma cells have been implanted subcutaneously into 7 female Fischer 344 rats. Two months post implantation, after injection of Hoechst 33342 the tumors were removed and snap frozen to conserve metabolite levels. Concomitantly, blood was sampled from the animals for analysis of glucose concentrations using a micodialysis analyzer. Cryosections of the tumors have been prepared, and every slice has been analyzed for both, Hoechst binding by fluorescence microscopy, and for glucose distribution patterns using bioluminescence imaging. In many cases vascular structures could be retrieved by the spatial pattern of glucose distribution. In some cases however, higher glucose concentrations could be found independent from Hoechst signal. On the other hand, regions of high Hoechst signal are not necessarily correlated with high glucose concentrations. When comparing blood and tissue glucose levels, tissue glucose content as measured with bioluminescence imaging (1.9-3.5 mM) is considerably lower than blood glucose (5.6-8.0 mM), demonstrating the expected gradient from blood to tissue. This study demonstrates the feasibility of monitoring glucose gradients in relation to functional vasculature throughout the body, from blood down to tissue or tumor and further, throughout the microenvironment of the solid tumor. Glucose distribution patterns may be an important tool in perfusion studies, e. g. in detecting the direction of blood flow in ex-vivo samples or in estimating glucose consumption rates of tumor cells adjacent to or in between perfused

  14. Digital autoradiography technique for studying of spatial Impurity distributions Delara

    International Nuclear Information System (INIS)

    Khamrayeva, S.

    2001-01-01

    In this report, the possibilities of the digital image processing for autoradiographic investigations of impurity distributions in the different objects (crystals, biology, geology et al) are shown. Activation autoradiography based on the secondary beta-irradiation is the method spread widely for investigations of the spatial distribution of chemical elements in the different objects. The analysis of autoradiography features is connected with the elucidation of optical density distribution of photoemulsion by means of photometry. The photoemulsion is used as detector of secondary beta irradiation. For different technological and nature materials to have elemental shifts the fine structure of chemical element distribution is often interested. But photometry makes it difficult to study the inhomogeneous chemical elements with the little gradient of concentration (near 20%). Therefore, the suppression of the background and betterment of linear solvability are the main problems of autoradiographic analysis. Application of the fast-acting digital computers and the technical means of signals treatment are allowed to spread the possibilities and the resolution of activation autoradiography. Mechanism of creation of autoradiographic features is described. The treatment of autoradiograms was conducted with the help of the dialogue system having matrix in 512 x 512 elements. For the interpretation of the experimental data clustering analysis methodology was used. Classification of the zones on the minimum of the square mistake was conducted according to the data of histograms of the optical densities of the studying autoradiograms. It was proposed algorithm for digital treatment for reconstruction of autoradiographic features. At a minimal contrast the resolution of the method has been enhanced on the degree by adaptation of methods of digital image processing (DIP) to suppress background activity. Results of the digital autoradiographic investigations of spatial impurity

  15. Spatial patterns of seaweed distribution in Malaysia using GIS

    Science.gov (United States)

    Lian, Du Hai; Sim, Jillian Ooi Lean; Fauzi, Rosmadi; Moi, Phang Siew

    2008-10-01

    The objective of this article is to represent spatial patterns of seaweed distribution in Malaysia. Seaweeds have been collected since 1984 along coastlines of 4675 km of peninsular Malaysia, Sabah, and Sarawak. However, there is no seaweed database and they cannot be displayed in a geographic view. Therefore, a database with 805 georeferenced observations was setup and GIS is used to analyze seaweed diversity based on this database. The highest number of observations is 94 which occur along east coastline of peninsular Malaysia. The highest number of species richness is 82 which are also along east coastline of peninsular Malaysia. Rhodophyta has the highest species richness while Chlorophyta has the least species richness.

  16. Agent-based Algorithm for Spatial Distribution of Objects

    KAUST Repository

    Collier, Nathan

    2012-06-02

    In this paper we present an agent-based algorithm for the spatial distribution of objects. The algorithm is a generalization of the bubble mesh algorithm, initially created for the point insertion stage of the meshing process of the finite element method. The bubble mesh algorithm treats objects in space as bubbles, which repel and attract each other. The dynamics of each bubble are approximated by solving a series of ordinary differential equations. We present numerical results for a meshing application as well as a graph visualization application.

  17. Fine-Scale Spatial Heterogeneity in the Distribution of Waterborne Protozoa in a Drinking Water Reservoir.

    Science.gov (United States)

    Burnet, Jean-Baptiste; Ogorzaly, Leslie; Penny, Christian; Cauchie, Henry-Michel

    2015-09-23

    The occurrence of faecal pathogens in drinking water resources constitutes a threat to the supply of safe drinking water, even in industrialized nations. To efficiently assess and monitor the risk posed by these pathogens, sampling deserves careful design, based on preliminary knowledge on their distribution dynamics in water. For the protozoan pathogens Cryptosporidium and Giardia, only little is known about their spatial distribution within drinking water supplies, especially at fine scale. Two-dimensional distribution maps were generated by sampling cross-sections at meter resolution in two different zones of a drinking water reservoir. Samples were analysed for protozoan pathogens as well as for E. coli, turbidity and physico-chemical parameters. Parasites displayed heterogeneous distribution patterns, as reflected by significant (oo)cyst density gradients along reservoir depth. Spatial correlations between parasites and E. coli were observed near the reservoir inlet but were absent in the downstream lacustrine zone. Measurements of surface and subsurface flow velocities suggest a role of local hydrodynamics on these spatial patterns. This fine-scale spatial study emphasizes the importance of sampling design (site, depth and position on the reservoir) for the acquisition of representative parasite data and for optimization of microbial risk assessment and monitoring. Such spatial information should prove useful to the modelling of pathogen transport dynamics in drinking water supplies.

  18. Optimization of spatial light distribution through genetic algorithms for vision systems applied to quality control

    International Nuclear Information System (INIS)

    Castellini, P; Cecchini, S; Stroppa, L; Paone, N

    2015-01-01

    The paper presents an adaptive illumination system for image quality enhancement in vision-based quality control systems. In particular, a spatial modulation of illumination intensity is proposed in order to improve image quality, thus compensating for different target scattering properties, local reflections and fluctuations of ambient light. The desired spatial modulation of illumination is obtained by a digital light projector, used to illuminate the scene with an arbitrary spatial distribution of light intensity, designed to improve feature extraction in the region of interest. The spatial distribution of illumination is optimized by running a genetic algorithm. An image quality estimator is used to close the feedback loop and to stop iterations once the desired image quality is reached. The technique proves particularly valuable for optimizing the spatial illumination distribution in the region of interest, with the remarkable capability of the genetic algorithm to adapt the light distribution to very different target reflectivity and ambient conditions. The final objective of the proposed technique is the improvement of the matching score in the recognition of parts through matching algorithms, hence of the diagnosis of machine vision-based quality inspections. The procedure has been validated both by a numerical model and by an experimental test, referring to a significant problem of quality control for the washing machine manufacturing industry: the recognition of a metallic clamp. Its applicability to other domains is also presented, specifically for the visual inspection of shoes with retro-reflective tape and T-shirts with paillettes. (paper)

  19. Effects of spatially distributed sectoral water management on the redistribution of water resources in an integrated water model: SECTORAL WATER MANAGEMENT IN IA-ESM

    Energy Technology Data Exchange (ETDEWEB)

    Voisin, Nathalie [Pacific Northwest National Laboratory, Richland Washington USA; Hejazi, Mohamad I. [Joint Global Change Research Institute, College Park Maryland USA; Leung, L. Ruby [Pacific Northwest National Laboratory, Richland Washington USA; Liu, Lu [Department of Civil and Environmental Engineering, University of Maryland, College Park Maryland USA; Huang, Maoyi [Pacific Northwest National Laboratory, Richland Washington USA; Li, Hong-Yi [Montana State University, College of Agriculture, Bozeman Montana USA; Tesfa, Teklu [Pacific Northwest National Laboratory, Richland Washington USA

    2017-05-01

    To advance understanding of the interactions between human activities and the water cycle, an integrated terrestrial water cycle component has been developed for Earth system models. This includes a land surface model fully coupled to a river routing model and a generic water management model to simulate natural and regulated flows. A global integrated assessment model and its regionalized version for the U.S. are used to simulate water demand consistent with the energy technology and socio-economics scenarios. Human influence on the hydrologic cycle includes regulation and storage from reservoirs, consumptive use and withdrawal from multiple sectors ( irrigation and non-irrigation) and overall redistribution of water resources in space and time. As groundwater provides an important source of water supply for irrigation and other uses, the integrated modeling framework has been extended with a simplified representation of groundwater as an additional supply source, and return flow generated from differences between withdrawals and consumptive uses from both groundwater and surface water systems. The groundwater supply and return flow modules are evaluated by analyzing the simulated regulated flow, reservoir storage and supply deficit for irrigation and non-irrigation sectors over major hydrologic regions of the conterminous U.S. The modeling framework is then used to provide insights on the reliability of water resources by isolating the reliability due to return flow and/or groundwater sources of water. Our results show that high sectoral ratio of withdrawals over consumptive demand adds significant stress on the water resources management that can be alleviated by reservoir storage capacity. The return flow representation therefore exhibits a clear east-west contrast in its hydrologic signature, as well as in its ability to help meet water demand. Groundwater use has a limited hydrologic signature but the most pronounced signature is in terms of decreasing water

  20. Thrust Slip Rates as a Control on the Presence and Spatial Distribution of High Metamorphic Heating Rates in Collisional Systems: The "Hot Iron" Model Revisited

    Science.gov (United States)

    Thigpen, R.; Ashley, K. T.; Law, R. D.; Mako, C. A.

    2017-12-01

    In natural systems, two key observations indicate that major strain discontinuities such as faults and shear zones should play a fundamental role in orogenic thermal evolution: (1) Large faults and shear zones often separate components of the composite orogen that have experienced broadly different thermal and deformational histories, and (2) quantitative metamorphic and diffusional studies indicate that heating rates are much faster and the duration of peak conditions much shorter in natural collisional systems than those predicted by numerical continuum deformation models. Because heat transfer processes such as conduction usually operate at much slower time scales than rates of other tectonic processes, thermal evolution is often transient and thus can be strongly influenced by tectonic disturbances that occur at rates much faster than thermal relaxation. Here, we use coupled thermal-mechanical finite element models of thrust faults to explore how fault slip rate may fundamentally influence the thermal evolution of individual footwall and hanging wall thrust slices. The model geometry involves a single crustal-scale thrust with a dip of 25° that is translated up the ramp at average velocities of 20, 35, and 50 km Myr-1, interpreted to represent average to relatively high slip rates observed in many collisional systems. Boundary conditions include crustal radioactive heat production, basal mantle heat flow, and surface erosion rates that are a function of thrust rate and subsequent topography generation. In the models, translation of the hanging wall along the crustal-scale detachment results in erosion, exhumation, and retrograde metamorphism of the emerging hanging wall topography and coeval burial, `hot iron' heating, and prograde metamorphism of the thrust footwall. Thrust slip rates of 20, 35, and 50 km Myr-1 yield maximum footwall heating rates ranging from 55-90° C Myr-1 and maximum hanging wall cooling rates of 138-303° C Myr-1. These relatively rapid

  1. Analysing earthquake slip models with the spatial prediction comparison test

    KAUST Repository

    Zhang, L.

    2014-11-10

    Earthquake rupture models inferred from inversions of geophysical and/or geodetic data exhibit remarkable variability due to uncertainties in modelling assumptions, the use of different inversion algorithms, or variations in data selection and data processing. A robust statistical comparison of different rupture models obtained for a single earthquake is needed to quantify the intra-event variability, both for benchmark exercises and for real earthquakes. The same approach may be useful to characterize (dis-)similarities in events that are typically grouped into a common class of events (e.g. moderate-size crustal strike-slip earthquakes or tsunamigenic large subduction earthquakes). For this purpose, we examine the performance of the spatial prediction comparison test (SPCT), a statistical test developed to compare spatial (random) fields by means of a chosen loss function that describes an error relation between a 2-D field (‘model’) and a reference model. We implement and calibrate the SPCT approach for a suite of synthetic 2-D slip distributions, generated as spatial random fields with various characteristics, and then apply the method to results of a benchmark inversion exercise with known solution. We find the SPCT to be sensitive to different spatial correlations lengths, and different heterogeneity levels of the slip distributions. The SPCT approach proves to be a simple and effective tool for ranking the slip models with respect to a reference model.

  2. Sensor placement for calibration of spatially varying model parameters

    Science.gov (United States)

    Nath, Paromita; Hu, Zhen; Mahadevan, Sankaran

    2017-08-01

    This paper presents a sensor placement optimization framework for the calibration of spatially varying model parameters. To account for the randomness of the calibration parameters over space and across specimens, the spatially varying parameter is represented as a random field. Based on this representation, Bayesian calibration of spatially varying parameter is investigated. To reduce the required computational effort during Bayesian calibration, the original computer simulation model is substituted with Kriging surrogate models based on the singular value decomposition (SVD) of the model response and the Karhunen-Loeve expansion (KLE) of the spatially varying parameters. A sensor placement optimization problem is then formulated based on the Bayesian calibration to maximize the expected information gain measured by the expected Kullback-Leibler (K-L) divergence. The optimization problem needs to evaluate the expected K-L divergence repeatedly which requires repeated calibration of the spatially varying parameter, and this significantly increases the computational effort of solving the optimization problem. To overcome this challenge, an approximation for the posterior distribution is employed within the optimization problem to facilitate the identification of the optimal sensor locations using the simulated annealing algorithm. A heat transfer problem with spatially varying thermal conductivity is used to demonstrate the effectiveness of the proposed method.

  3. Origin and spatial distribution of metals in agricultural soils

    International Nuclear Information System (INIS)

    Mohammadpour, Gh.A.; Karbassi, A.R.; Baghvand, A.

    2016-01-01

    Presence of toxic metals in agricultural soils can impose adverse health impact on consumers. The main purpose of this study was to determine spatial distribution of elements Fe, Sb, Mn in agriculture soils and crops of Hamedan Province in Iran. Soil samples (0-20 cm depth) were collected from an area of 2831 km 2 . Iron, Antimony and Manganese in samples of soil and agricultural crops were extracted and their amount was determined using atomic absorption spectrometer. The spatial distribution map of the studied elements was developed using Kriging method. The main concentration of Fe, Sb and Mn in the soil of the study area is about 3.8%, 2.5 and 403 mg/kg, respectively. According to chemical partitioning studies, the anthropogenic share of Fe, Sb and Mn is about 28.51%, 34.83% and 30.35%, respectively. Results of comparison of heavy metals pollution intensity in the agricultural soil with geoaccumulation index and also pollution index, illustrated that iron and manganese are classified in the Non-polluted class and antimony is in the moderately polluted class. Analysis of zoning map of pollution index showed that Fe, Sb and Mn are of geological sources. In fact, these metals are naturally found in soil. However, anthropogenic activities have led to more accumulation of these metals in the soil. The obtained health risk for metals in agricultural crops is indicative of safe value for consumers.

  4. Distribution system modeling and analysis

    CERN Document Server

    Kersting, William H

    2001-01-01

    For decades, distribution engineers did not have the sophisticated tools developed for analyzing transmission systems-often they had only their instincts. Things have changed, and we now have computer programs that allow engineers to simulate, analyze, and optimize distribution systems. Powerful as these programs are, however, without a real understanding of the operating characteristics of a distribution system, engineers using the programs can easily make serious errors in their designs and operating procedures. Distribution System Modeling and Analysis helps prevent those errors. It gives readers a basic understanding of the modeling and operating characteristics of the major components of a distribution system. One by one, the author develops and analyzes each component as a stand-alone element, then puts them all together to analyze a distribution system comprising the various shunt and series devices for power-flow and short-circuit studies. He includes the derivation of all models and includes many num...

  5. Occurrence and spatial distribution of microplastics in sediments from Norderney

    International Nuclear Information System (INIS)

    Dekiff, Jens H.; Remy, Dominique; Klasmeier, Jörg; Fries, Elke

    2014-01-01

    The spatial distribution of small potential microplastics (SPM) ( 1 mm) was also examined. Small microparticles were extracted from 36 one kg sediment samples and analysed by visual microscopic inspection and partly by thermal desorption pyrolysis gas chromatography/mass spectrometry. The smallest particle size that could be analysed with this method was estimated to be 100 μm. The mean number of SPM at the three sampling sites (n = 12) was 1.7, 1.3 and 2.3 particles per kg dry sediment, respectively. SPM were identified as polypropylene, polyethylene, polyethylene terephthalate, polyvinylchloride, polystyrene and polyamide. The organic plastic additives found were benzophenone, 1,2-benzenedicarboxylic acid, dimethyl phthalate, diethylhexyl phthalate, dibutyl phthalate, diethyl phthalate, phenol and 2,4-di-tert-butylphenol. Particles were distributed rather homogenously and the occurrence of SPM did not correlate with that of VPD. -- Highlights: • The small-scale variability of small potential microplastics (<1 mm) occurrence in beach sediments was studied. • Within 500 m, small potential microplastics (<1 mm) were distributed rather homogeneously in investigated beach sediments. • The occurrence of small potential microplastics (<1 mm) did not correlate with that of visible plastic debris. • Procedural contamination of sediments by fibres (blank) constitutes an analytical problem. • These findings must be considered when setting up standardized monitoring protocols. -- On a small scale within 500 m, small microplastics are distributed rather homogeneously in sediments from the North Sea island of Norderney

  6. Spatial patterns of distribution and abundance of Harrisia portoricensis, an endangered Caribbean cactus

    Science.gov (United States)

    J. Rojas-Sandoval; E. J. Melendez-Ackerman; NO-VALUE

    2013-01-01

    Aims The spatial distribution of biotic and abiotic factors may play a dominant role in determining the distribution and abundance of plants in arid and semiarid environments. In this study, we evaluated how spatial patterns of microhabitat variables and the degree of spatial dependence of these variables influence the distribution and abundance of the endangered...

  7. Fine-scale spatial distribution of plants and resources on a sandy soil in the Sahel

    NARCIS (Netherlands)

    Rietkerk, M.G.; Ouedraogo, T.; Kumar, L.; Sanou, S.; Langevelde, F. van; Kiema, A.; Koppel, J. van de; Andel, J. van; Hearne, J.; Skidmore, A.K.; Ridder, N. de; Stroosnijder, L.; Prins, H.H.T.

    2002-01-01

    We studied fine-scale spatial plant distribution in relation to the spatial distribution of erodible soil particles, organic matter, nutrients and soil water on a sandy to sandy loam soil in the Sahel. We hypothesized that the distribution of annual plants would be highly spatially autocorrelated

  8. Spatial Distribution of Adults of Triozoida limbata (Enderlein) (Hemiptera: Triozidae) in Guava Plants.

    Science.gov (United States)

    Marcelino, M C S; Barbosa, J C

    2016-04-01

    The psyllid Triozoida limbata (Enderlein) (Hemiptera: Triozidae) is a major pest in guava, feeding primarily on new shoots. Despite its importance, there are no studies on the spatial distribution of T. limbata on guava. Such studies are needed to establish sequential sampling plans for decision making in pest control. Thus, an experiment was carried out in a 9-year-old commercial guava orchard divided into 100 sampling units or plots. Double-sided yellow sticky traps were placed on one plant per plot (sample unit) to capture and monitor T. limbata adults from April 2011 to May 2012. To determine the insect distribution in the area, we calculated the variance-to-mean ratio index (I), the Morisita index (I δ ), Green's coefficient (Cx), and the k exponent of the negative binomial distribution. Most of the samples showed that the adults had a moderate to highly aggregated distribution. Statistical models were also used to study the pest spatial distribution by fitting the number of adults captured to the Poisson and negative binomial distributions. The negative binomial distribution model best fitted the data of the number of adult psyllids captured by the traps, which is consistent with an aggregated distribution.

  9. Spatial distribution of the source-receptor relationship of sulfur in Northeast Asia

    Directory of Open Access Journals (Sweden)

    M. Kajino

    2011-07-01

    Full Text Available The spatial distribution of the source-receptor relationship (SRR of sulfur over Northeast Asia was examined using a chemical transport model (RAQM off-line coupled with a meteorological model (MM5. The simulation was conducted for the entire year of 2002. The results were evaluated using monitoring data for six remote stations of the Acid Deposition Monitoring Network in East Asia (EANET. The modeled SO2 and O3 concentrations agreed well with the observations quantitatively. The modeled aerosol and wet deposition fluxes of SO42− were underestimated by 30 % and 50 %, respectively. The domain was divided into 5 source-receptor regions: (I North China; (II Central China; (III South China; (IV South Korea; and (V Japan. The sulfur deposition in each receptor region amounted to about 50–75 % of the emissions from the same region. The largest contribution to the deposition in each region was originated from the same region, accounting for 53–84 %. The second largest contribution was due to Region II, supplying 14–43 %. The spatial distributions of the SRRs revealed that subregional values varied by about two times more than regional averages due to nonuniformity across the deposition fields. Examining the spatial distributions of the deposition fields was important for identifying subregional areas where the deposition was highest within a receptor region. The horizontal distribution changed substantially according to season.

  10. Image categorization based on spatial visual vocabulary model

    Science.gov (United States)

    Wang, Yuxin; He, Changqin; Guo, He; Feng, Zhen; Jia, Qi

    2010-08-01

    In this paper, we propose an approach to recognize scene categories by means of a novel method named spatial visual vocabulary. Firstly, we hierarchically divide images into sub regions and construct the spatial visual vocabulary by grouping the low-level features collected from every corresponding spatial sub region into a specified number of clusters using k-means algorithm. To recognize the category of a scene, the visual vocabulary distributions of all spatial sub regions are concatenated to form a global feature vector. The classification is obtained using LIBSVM, a support vector machine classifier. Our goal is to find a universal framework which is applicable to various types of features, so two kinds of features are used in the experiments: "V1-like" filters and PACT features. In almost all experimental cases, the proposed model achieves superior results. Source codes are available by email.

  11. A method for statistically comparing spatial distribution maps

    Directory of Open Access Journals (Sweden)

    Reynolds Mary G

    2009-01-01

    Full Text Available Abstract Background Ecological niche modeling is a method for estimation of species distributions based on certain ecological parameters. Thus far, empirical determination of significant differences between independently generated distribution maps for a single species (maps which are created through equivalent processes, but with different ecological input parameters, has been challenging. Results We describe a method for comparing model outcomes, which allows a statistical evaluation of whether the strength of prediction and breadth of predicted areas is measurably different between projected distributions. To create ecological niche models for statistical comparison, we utilized GARP (Genetic Algorithm for Rule-Set Production software to generate ecological niche models of human monkeypox in Africa. We created several models, keeping constant the case location input records for each model but varying the ecological input data. In order to assess the relative importance of each ecological parameter included in the development of the individual predicted distributions, we performed pixel-to-pixel comparisons between model outcomes and calculated the mean difference in pixel scores. We used a two sample Student's t-test, (assuming as null hypothesis that both maps were identical to each other regardless of which input parameters were used to examine whether the mean difference in corresponding pixel scores from one map to another was greater than would be expected by chance alone. We also utilized weighted kappa statistics, frequency distributions, and percent difference to look at the disparities in pixel scores. Multiple independent statistical tests indicated precipitation as the single most important independent ecological parameter in the niche model for human monkeypox disease. Conclusion In addition to improving our understanding of the natural factors influencing the distribution of human monkeypox disease, such pixel-to-pixel comparison

  12. Hydronic distribution system computer model

    Energy Technology Data Exchange (ETDEWEB)

    Andrews, J.W.; Strasser, J.J.

    1994-10-01

    A computer model of a hot-water boiler and its associated hydronic thermal distribution loop has been developed at Brookhaven National Laboratory (BNL). It is intended to be incorporated as a submodel in a comprehensive model of residential-scale thermal distribution systems developed at Lawrence Berkeley. This will give the combined model the capability of modeling forced-air and hydronic distribution systems in the same house using the same supporting software. This report describes the development of the BNL hydronics model, initial results and internal consistency checks, and its intended relationship to the LBL model. A method of interacting with the LBL model that does not require physical integration of the two codes is described. This will provide capability now, with reduced up-front cost, as long as the number of runs required is not large.

  13. Identifying biotic interactions which drive the spatial distribution of a mosquito community.

    Science.gov (United States)

    Golding, Nick; Nunn, Miles A; Purse, Bethan V

    2015-07-14

    Spatial variation in the risk of many mosquito-borne pathogens is strongly influenced by the distribution of communities of suitable vector mosquitoes. The spatial distributions of such communities have been linked to the abiotic habitat requirements of each constituent mosquito species, but the biotic interactions between mosquitoes and other species are less well understood. Determining which fauna restrict the presence and abundance of key mosquito species in vector communities may identify species which could be employed as natural biological control agents. Whilst biotic interactions have been studied in the laboratory, a lack of appropriate statistical methods has prohibited the identification of key interactions which influence mosquito distributions in the field. Joint species distribution models (JSDMs) have recently been developed to identify biotic interactions influencing the distributions of species from empirical data. We apply a JSDM to field data on the spatial distribution of mosquitoes in a UK wetland to identify both abiotic factors and biotic interactions driving the composition of the community. As expected, mosquito larval distributions in this wetland habitat are strongly driven by environmental covariates including water depth, temperature and oxidation-reduction potential. By factoring out these environmental variables, we are able to identify species (ditch shrimp of the genus Palaemonetes and fish) as predators which appear to restrict mosquito distributions. JSDMs offer vector ecologists a way to identify potentially important biotic interactions influencing the distributions of disease vectors from widely available field data. This information is crucial to understand the likely effects of habitat management for vector control and to identify species with the potential for use in biological control programmes. We provide an R package BayesComm to enable the wider application of these models.

  14. Distribuição espacial do risco: modelagem da mortalidade infantil em Porto Alegre, Rio Grande do Sul, Brasil Spatial risk distribution: modeling infant mortality in Porto Alegre, Rio Grande do Sul State, Brazil

    Directory of Open Access Journals (Sweden)

    Silvia E. Shimakura

    2001-10-01

    Full Text Available Estimação e mapeamento de perfis de risco são interesses da Epidemiologia. Neste trabalho, é analisada a distribuição espacial de casos de mortalidade infantil, comparados a controles de nascidos vivos amostrados do Sistema de Informações sobre Nascidos Vivos da cidade de Porto Alegre, Rio Grande do Sul, Brasil. A modelagem adotada neste trabalho baseia-se em um processo pontual espacial, na qual se define uma medida de risco que varia continuamente sobre a região de estudo e estimada por meio de métodos de modelos aditivos generalizados. Essa abordagem possui a vantagem de permitir a incorporação, no modelo, de efeitos de determinantes individuais e ecológicos de risco sob forma simples e de fácil interpretação. Também permite a construção de contornos de tolerância que auxiliam na identificação de áreas de alto/baixo risco e de um teste global da hipótese nula de risco constante relativa à região. A aplicação do método aos dados de mortalidade infantil mostrou variação espacial no risco altamente significativa para mortalidade neonatal e não significativa para mortalidade pós-neonatal.Estimation and mapping of risk profiles are the main concerns of epidemiology. This paper analyzes spatial distribution of infant mortality cases as compared to live-born controls from Porto Alegre, Rio Grande do Sul. The modeling framework adopted in this research work is a spatial point process. Under this structure, a risk measure which continuously varies over the study region is defined and estimated using generalized additive model methods. This approach has the advantage of allowing for risk factors that are simple and easy to interpret. The procedure also allows the construction of tolerance contours which help identify areas of significantly high/low risk and an overall test for the null hypothesis of constant risk over the region. Application of this method to infant mortality data showed a highly significant spatial

  15. Spatial distribution of venous gas emboli in the lungs

    Science.gov (United States)

    Souders, J. E.; Doshier, J. B.; Polissar, N. L.; Hlastala, M. P.

    1999-01-01

    The distribution of gaseous pulmonary emboli is presumed to be determined by their buoyancy. We hypothesized that regional pulmonary blood flow may also influence their distribution. Therefore, pulmonary blood flow was measured in supine, anesthetized dogs with use of 15-microm fluorescent microspheres at baseline and during N(2) embolism. The animals were killed, and the lungs were excised, air-dried, and diced into approximately 2-cm(3) pieces with weights and spatial coordinates recorded. Embolism was defined as a >10% flow decrease relative to baseline. Vertically, the incidence of embolism increased substantially by 6 +/- 1% per additional centimeter in height compared with baseline (P = 0.0003). Embolism also increased radially by 3 +/- 1%/cm from the hilum (P = 0.002). There was a weaker but statistically significant increase in embolism to pieces with greater baseline flow, 9 +/- 2% for every 1. 0 increase in relative baseline flow (P = 0.008). We conclude that the distribution of gaseous emboli is influenced by buoyancy and flow dynamics within the pulmonary vasculature.

  16. Using Spatial Gradients to Model Localization Phenomena

    Energy Technology Data Exchange (ETDEWEB)

    D.J.Bammann; D.Mosher; D.A.Hughes; N.R.Moody; P.R.Dawson

    1999-07-01

    We present the final report on a Laboratory-Directed Research and Development project, Using Spatial Gradients to Model Localization Phenomena, performed during the fiscal years 1996 through 1998. The project focused on including spatial gradients in the temporal evolution equations of the state variables that describe hardening in metal plasticity models. The motivation was to investigate the numerical aspects associated with post-bifurcation mesh dependent finite element solutions in problems involving damage or crack propagation as well as problems in which strain Localizations occur. The addition of the spatial gradients introduces a mathematical length scale that eliminates the mesh dependency of the solution. In addition, new experimental techniques were developed to identify the physical mechanism associated with the numerical length scale.

  17. Landscape Modelling and Simulation Using Spatial Data

    Directory of Open Access Journals (Sweden)

    Amjed Naser Mohsin AL-Hameedawi

    2017-08-01

    Full Text Available In this paper a procedure was performed for engendering spatial model of landscape acclimated to reality simulation. This procedure based on combining spatial data and field measurements with computer graphics reproduced using Blender software. Thereafter that we are possible to form a 3D simulation based on VIS ALL packages. The objective was to make a model utilising GIS, including inputs to the feature attribute data. The objective of these efforts concentrated on coordinating a tolerable spatial prototype, circumscribing facilitation scheme and outlining the intended framework. Thus; the eventual result was utilized in simulation form. The performed procedure contains not only data gathering, fieldwork and paradigm providing, but extended to supply a new method necessary to provide the respective 3D simulation mapping production, which authorises the decision makers as well as investors to achieve permanent acceptance an independent navigation system for Geoscience applications.

  18. Spatial Determinants of Import Traffic Distribution At Port Harcourt (Nigeria

    Directory of Open Access Journals (Sweden)

    Soddy I. Inyang

    2013-07-01

    Full Text Available This paper highlights the result of a study carried out to examine the Geographic determinants of import traffic distribution at the Port Harcourt Port. A substantial aspect of the study involved building a regression model to estimate import distribution from the Port. The import function was specified in log-linear form. The adequacy of the model was then tested; this, involved statistical experiments to obtain the R-squared, as well as t and f values. Further test on the adequacy of the nwdel was conducted through diagnostic exercises designed to check for inulticollinedrity and heteroscedasticity, in the data used. Results obtained show that road distance and manufacturing industries are significant Geographic determinants of import Cargo distribution at the study Port. It is therefore important to lake the two variables into account in any policy or planning exercise at Port Harcourt Port.

  19. Cartograms tool to represent spatial uncertainty in species distribution

    Directory of Open Access Journals (Sweden)

    Duccio Rocchini

    2017-02-01

    Full Text Available Species distribution models have become an important tool for biodiversity monitoring. Like all statistical modelling techniques developed based on field data, they are prone to uncertainty due to bias in the sampling (e.g. identification, effort, detectability. In this study, we explicitly quantify and map the uncertainty derived from sampling effort bias. With that aim, we extracted data from the widely used GBIF dataset to map this semantic bias using cartograms.

  20. Macular pigment spatial distribution effects on glare disability.

    Science.gov (United States)

    Putnam, Christopher M; Bassi, Carl J

    2015-01-01

    This project explored the relationship of the macular pigment optical density (MPOD) spatial profile with measures of glare disability (GD) across the macula. A novel device was used to measure MPOD across the central 16° of retina along four radii using customized heterochromatic flicker photometry (cHFP)at eccentricities of 0°, 2°, 4°, 6° and 8°. MPOD was measured as discrete and integrated values at all measured retinal loci. GD was calculated as a difference in contrast sensitivity (CS) between no glare and glare conditions using identical stimuli presented at the same eccentricities. GD was defined as [(CSNo Glare-CSGlare)/CSNo Glare] in order to isolate the glare attenuation effects of MPOD by controlling for CS variability among the subject sample. Correlations of the discrete and integrated MPOD with GD were compared. The cHFP identified reliable MPOD spatial distribution maps demonstrating a 1st-order exponential decay as a function of increasing eccentricity. There was a significant negative correlation between both measures of foveal MPOD and GD using 6 cycles per degree (cpd) and 9 cpd stimuli. Significant correlations were found between corresponding parafoveal MPOD measures and GD at 2 and 4° of eccentricity using 9 cpd stimuli with greater MPOD associated with less glare disability. These results are consistent with the glare attenuation effects of MP at higher spatial frequencies and support the hypothesis that discrete and integrated measures of MPOD have similar correlations with glare attenuation effects across the macula. Additionally, peak foveal MPOD appears to influence GD across the macula. Copyright © 2014 Spanish General Council of Optometry. Published by Elsevier Espana. All rights reserved.

  1. Testing spatial heterogeneity with stock assessment models

    DEFF Research Database (Denmark)

    Jardim, Ernesto; Eero, Margit; Silva, Alexandra

    2018-01-01

    This paper describes a methodology that combines meta-population theory and stock assessment models to gain insights about spatial heterogeneity of the meta-population in an operational time frame. The methodology was tested with stochastic simulations for different degrees of connectivity betwee...

  2. A Non-Gaussian Spatial Generalized Linear Latent Variable Model

    KAUST Repository

    Irincheeva, Irina

    2012-08-03

    We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.

  3. Impacts of C-uptake by plants on the spatial distribution of14C accumulated in vegetation around a nuclear facility-Application of a sophisticated land surface14C model to the Rokkasho reprocessing plant, Japan.

    Science.gov (United States)

    Ota, Masakazu; Katata, Genki; Nagai, Haruyasu; Terada, Hiroaki

    2016-10-01

    The impacts of carbon uptake by plants on the spatial distribution of radiocarbon ( 14 C) accumulated in vegetation around a nuclear facility were investigated by numerical simulations using a sophisticated land surface 14 C model (SOLVEG-II). In the simulation, SOLVEG-II was combined with a mesoscale meteorological model and an atmospheric dispersion model. The model combination was applied to simulate the transfer of 14 CO 2 and to assess the radiological impact of 14 C accumulation in rice grains during test operations of the Rokkasho reprocessing plant (RRP), Japan, in 2007. The calculated 14 C-specific activities in rice grains agreed with the observed activities in paddy fields around the RRP within a factor of four. The annual effective dose delivered from 14 C in the rice grain was estimated to be less than 0.7 μSv, only 0.07% of the annual effective dose limit of 1 mSv for the public. Numerical experiments of hypothetical continuous atmospheric 14 CO 2 release from the RRP showed that the 14 C-specific activities of rice plants at harvest differed from the annual mean activities in the air. The difference was attributed to seasonal variations in the atmospheric 14 CO 2 concentration and the growth of the rice plant. Accumulation of 14 C in the rice plant significantly increased when 14 CO 2 releases were limited during daytime hours, compared with the results observed during the nighttime. These results indicated that plant growth stages and diurnal photosynthesis should be considered in predictions of the ingestion dose of 14 C for long-term chronic releases and short-term diurnal releases of 14 CO 2 , respectively. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. The 3-D global spatial data model foundation of the spatial data infrastructure

    CERN Document Server

    Burkholder, Earl F

    2008-01-01

    Traditional methods for handling spatial data are encumbered by the assumption of separate origins for horizontal and vertical measurements. Modern measurement systems operate in a 3-D spatial environment. The 3-D Global Spatial Data Model: Foundation of the Spatial Data Infrastructure offers a new model for handling digital spatial data, the global spatial data model or GSDM. The GSDM preserves the integrity of three-dimensional spatial data while also providing additional benefits such as simpler equations, worldwide standardization, and the ability to track spatial data accuracy with greater specificity and convenience. This groundbreaking spatial model incorporates both a functional model and a stochastic model to connect the physical world to the ECEF rectangular system. Combining horizontal and vertical data into a single, three-dimensional database, this authoritative monograph provides a logical development of theoretical concepts and practical tools that can be used to handle spatial data mo...

  5. Abiotic and biotic controls on local spatial distribution and performance of Boechera stricta

    Directory of Open Access Journals (Sweden)

    KUSUM J NAITHANI

    2014-07-01

    Full Text Available This study investigates the relative influence of biotic and abiotic factors on community dynamics using an integrated approach and highlights the influence of space on genotypic and phenotypic traits in plant community structure. We examined the relative influence of topography, environment, spatial distance, and intra- and interspecific interactions on spatial distribution and performance of Boechera stricta (rockcress, a close perennial relative of model plant Arabidopsis. First, using Bayesian kriging, we mapped the topography and environmental gradients and explored the spatial distribution of naturally occurring rockcress plants and two neighbors, Taraxacum officinale (dandelion and Solidago missouriensis (goldenrod found in close proximity within a typical diverse meadow community across topographic and environmental gradients. We then evaluated direct and indirect relationships among variables using Mantel path analysis and developed a network displaying abiotic and biotic interactions in this community. We found significant spatial autocorrelation among rockcress individuals, either because of common microhabitats as displayed by high density of individuals at lower elevation and high soil moisture area, or limited dispersal as shown by significant spatial autocorrelation of naturally occurring inbred lines, or a combination of both. Goldenrod and dandelion density around rockcress does not show any direct relationship with rockcress fecundity, possibly due to spatial segregation of resources. However, dandelion density around rockcress shows an indirect negative influence on rockcress fecundity via herbivory, indicating interspecific competition. Overall, we suggest that common microhabitat preference and limited dispersal are the main drivers for spatial distribution. However, intra-specific interactions and insect herbivory are the main drivers of rockcress performance in the meadow community.

  6. Spatial Double Generalized Beta Regression Models: Extensions and Application to Study Quality of Education in Colombia

    Science.gov (United States)

    Cepeda-Cuervo, Edilberto; Núñez-Antón, Vicente

    2013-01-01

    In this article, a proposed Bayesian extension of the generalized beta spatial regression models is applied to the analysis of the quality of education in Colombia. We briefly revise the beta distribution and describe the joint modeling approach for the mean and dispersion parameters in the spatial regression models' setting. Finally, we motivate…

  7. Spatial Models and Networks of Living Systems

    DEFF Research Database (Denmark)

    Juul, Jeppe Søgaard

    . Such systems are known to be stabilized by spatial structure. Finally, I analyse data from a large mobile phone network and show that people who are topologically close in the network have similar communication patterns. This main part of the thesis is based on six different articles, which I have co...... with interactions defined by network topology. In this thesis I first describe three different biological models of ageing and cancer, in which spatial structure is important for the system dynamics. I then turn to describe characteristics of ecosystems consisting of three cyclically interacting species...

  8. Approximate Bayesian computation for spatial SEIR(S) epidemic models.

    Science.gov (United States)

    Brown, Grant D; Porter, Aaron T; Oleson, Jacob J; Hinman, Jessica A

    2018-02-01

    Approximate Bayesia n Computation (ABC) provides an attractive approach to estimation in complex Bayesian inferential problems for which evaluation of the kernel of the posterior distribution is impossible or computationally expensive. These highly parallelizable techniques have been successfully applied to many fields, particularly in cases where more traditional approaches such as Markov chain Monte Carlo (MCMC) are impractical. In this work, we demonstrate the application of approximate Bayesian inference to spatially heterogeneous Susceptible-Exposed-Infectious-Removed (SEIR) stochastic epidemic models. These models have a tractable posterior distribution, however MCMC techniques nevertheless become computationally infeasible for moderately sized problems. We discuss the practical implementation of these techniques via the open source ABSEIR package for R. The performance of ABC relative to traditional MCMC methods in a small problem is explored under simulation, as well as in the spatially heterogeneous context of the 2014 epidemic of Chikungunya in the Americas. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Tomographic radiotracer studies of the spatial distribution of heterogeneous geochemical transport processes

    International Nuclear Information System (INIS)

    Gruendig, Marion; Richter, Michael; Seese, Anita; Sabri, Osama

    2007-01-01

    Within the scope of the further development of geochemical transport models the consideration of the influence of the heterogeneous structures of the geological layers plays an important role. For the verification and parameter estimation of such models it is necessary to measure the heterogeneous transport and sorption processes inside the samples. Tomographic radiotracer methods (positron emission tomography (PET)) enable nondestructive spatially resolved observations of the transport processes in these layers. A special quantitative evaluation system for geoscientific PET studies was developed. Investigations of the water flow distribution in a drill core of a lignite mining dump and of the migration of Cu ions in a horizontal soil column illustrate the potential of this method. Spatial distribution functions of the flow velocity, the specific mass flow and the longitudinal dispersivity were determined on the basis of PET investigations

  10. Using geomorphological variables to predict the spatial distribution of plant species in agricultural drainage networks.

    Science.gov (United States)

    Rudi, Gabrielle; Bailly, Jean-Stéphane; Vinatier, Fabrice

    2018-01-01

    To optimize ecosystem services provided by agricultural drainage networks (ditches) in headwater catchments, we need to manage the spatial distribution of plant species living in these networks. Geomorphological variables have been shown to be important predictors of plant distribution in other ecosystems because they control the water regime, the sediment deposition rates and the sun exposure in the ditches. Whether such variables may be used to predict plant distribution in agricultural drainage networks is unknown. We collected presence and absence data for 10 herbaceous plant species in a subset of a network of drainage ditches (35 km long) within a Mediterranean agricultural catchment. We simulated their spatial distribution with GLM and Maxent model using geomorphological variables and distance to natural lands and roads. Models were validated using k-fold cross-validation. We then compared the mean Area Under the Curve (AUC) values obtained for each model and other metrics issued from the confusion matrices between observed and predicted variables. Based on the results of all metrics, the models were efficient at predicting the distribution of seven species out of ten, confirming the relevance of geomorphological variables and distance to natural lands and roads to explain the occurrence of plant species in this Mediterranean catchment. In particular, the importance of the landscape geomorphological variables, ie the importance of the geomorphological features encompassing a broad environment around the ditch, has been highlighted. This suggests that agro-ecological measures for managing ecosystem services provided by ditch plants should focus on the control of the hydrological and sedimentological connectivity at the catchment scale. For example, the density of the ditch network could be modified or the spatial distribution of vegetative filter strips used for sediment trapping could be optimized. In addition, the vegetative filter strips could constitute

  11. SAMICS marketing and distribution model

    Science.gov (United States)

    1978-01-01

    A SAMICS (Solar Array Manufacturing Industry Costing Standards) was formulated as a computer simulation model. Given a proper description of the manufacturing technology as input, this model computes the manufacturing price of solar arrays for a broad range of production levels. This report presents a model for computing these marketing and distribution costs, the end point of the model being the loading dock of the final manufacturer.

  12. Spatial modelling and ecology of Echinococcus multilocularis transmission in China.

    Science.gov (United States)

    Danson, F Mark; Giraudoux, Patrick; Craig, Philip S

    2006-01-01

    Recent research in central China has suggested that the most likely transmission mechanism for Echinococcus multilocularis to humans is via domestic dogs which are allowed to roam freely and hunt (infected) small mammals within areas close to villages or in areas of tented pasture. This assertion has led to the hypothesis that there is a landscape control on transmission risk since the proximity of suitable habitat for susceptible small mammals appears to be the key. We have tested this hypothesis in a number of endemic areas in China, notably south Gansu Province and the Tibetan region of western Sichuan Province. The fundamental landscape control is its effect at a regional scale on small mammal species assemblages (susceptible species are not ubiquitous) and, at a local scale, the spatial distributions of small mammal populations. To date the research has examined relationships between landscape composition and patterns of human infection, landscape and small mammal distributions and recently the relationships between landscape and dog infection rates. The key tool to characterize landscape is satellite remote sensing and these data are used as inputs to drive spatial models of transmission risk. This paper reviews the progress that has been made so far in spatial modeling of the ecology of E. multilocularis with particular reference to China, outlines current research issues, and describes a framework for building a spatial-temporal model of transmission ecology.

  13. Population dynamics and spatial distribution of Abaris basistriata Chaudoir, 1873 (Coleoptera: Carabidae

    Directory of Open Access Journals (Sweden)

    Ivan Carlos Fernandes Martins

    2016-02-01

    Full Text Available ABSTRACT Abaris basistriata, a beetle species dominant in agroecosystems and natural habitats, may benefit from the establishment of nearby refuge areas or crop field centers. To confirm this hypothesis, we analyzed the spatial distribution of the species and verified the population dynamics of this predator in a soybean/corn rotation crop and a central refuge area. The 1-ha experimental area was divided in half by a range of herbaceous plants (2 m in width and 80 m in length. Beetle samples were collected using pitfall traps every fortnight during the in-season and every month during the off-season (a total of 27 sampling occurrences. Population fluctuation was analyzed by correlating the total number of specimens with plant phenology. We used multiple regression analysis with variable (stepwise selection to examine the influence of meteorological factors on species occurrence. To determine the spatial distribution, data were analyzed using dispersion indices and probabilistic models based on the Coleoptera frequency distribution. Distribution visualization was assessed using a linear interpolation map. A total of 143 A. basistriata specimens were collected, with 83 from the soybean/corn area and 60 from the refuge area. Periods of large population size occurred during a season with high rainfall and high maximum and minimum temperatures. On the basis of the spatial distribution analysis of A. basistriata, it is likely that the beetles occur in an aggregate form, preferably in the refuge area.

  14. Spatial models of Northern Bobwhite populations for conservation planning

    Science.gov (United States)

    Twedt, Daniel J.; Wilson, R. Randy; Keister, Amy S.

    2007-01-01

    Since 1980, northern bobwhite (Colinus virginianus) range-wide populations declined 3.9% annually. Within the West Gulf Coastal Plain Bird Conservation Region in the south-central United States, populations of this quail species have declined 6.8% annually. These declines sparked calls for land use change and prompted implementation of various conservation practices. However, to effectively reverse these declines and restore northern bobwhite to their former population levels, habitat conservation and management efforts must target establishment and maintenance of sustainable populations. To provide guidance for conservation and restoration of habitat capable of supporting sustainable northern bobwhite populations in the West Gulf Coastal Plain, we modeled their spatial distribution using landscape characteristics derived from 1992 National Land Cover Data and bird detections, from 1990 to 1994, along 10-stop Breeding Bird Survey route segments. Four landscape metrics influenced detections of northern bobwhite: detections were greater in areas with more grassland and increased aggregation of agricultural lands, but detections were reduced in areas with increased density of land cover edge and grassland edge. Using these landscape metrics, we projected the abundance and spatial distribution of northern bobwhite populations across the entire West Gulf Coastal Plain. Predicted populations closely approximated abundance estimates from a different cadre of concurrently collected data but model predictions did not accurately reflect bobwhite detections along species-specific call-count routes in Arkansas and Louisiana. Using similar methods, we also projected northern bobwhite population distribution circa 1980 based on Land Use Land Cover data and bird survey data from 1976 to 1984. We compared our 1980 spatial projections with our spatial estimate of 1992 populations to identify areas of population change. Additionally, we used our projection of the spatial

  15. Sodium Atoms in the Lunar Exotail: Observed Velocity and Spatial Distributions

    Science.gov (United States)

    Line, Michael R.; Mierkiewicz, E. J.; Oliversen, R. J.; Wilson, J. K.; Haffner, L. M.; Roesler, F. L.

    2011-01-01

    The lunar sodium tail extends long distances due to radiation pressure on sodium atoms in the lunar exosphere. Our earlier observations determined the average radial velocity of sodium atoms moving down the lunar tail beyond Earth along the Sun-Moon-Earth line (i.e., the anti-lunar point) to be 12.4 km/s. Here we use the Wisconsin H-alpha Mapper to obtain the first kinematically resolved maps of the intensity and velocity distribution of this emission over a 15 x times 15 deg region on the sky near the anti-lunar point. We present both spatially and spectrally resolved observations obtained over four nights around new moon in October 2007. The spatial distribution of the sodium atoms is elongated along the ecliptic with the location of the peak intensity drifting 3 degrees east along the ecliptic per night. Preliminary modeling results suggest that the spatial and velocity distributions in the sodium exotail are sensitive to the near surface lunar sodium velocity distribution and that observations of this sort along with detailed modeling offer new opportunities to describe the time history of lunar surface sputtering over several days.

  16. Influence of the spatial discretization degree on the hydrological response of a flatland watershed through distributed mathematical modeling; Influencia del grado de discretizacion espacial en la respuesta hidrologica de una cuenca de llanura mediante modelacion matematica distribuida

    Energy Technology Data Exchange (ETDEWEB)

    Stenta, Herman Roberto; Riccardi, Gerardo A; Basile, Pedro A [Universidad Nacional de Rosario (Mexico)

    2008-07-15

    Distributed hydrological models are suitable for the determination of time and space variability of hydrological responses within a given watershed. In a watershed, the model can be implemented with different levels of space resolution, mainly as a function of data availability, objectives of the numerical study, and requirements of the system to be modeled. In this paper, the effects on landscape representation due to different cell sizes are analyzed and scaling of parameters in a lower spatial resolution level is proposed in order to obtain similarity in hydrological responses between different degrees of discretization. The comparison was made in terms of maximum discharge, maximum flow velocity, and maximum water depth by simulating a number of observed and hypothetical hydrological events. The concept of total equilibrium state of the watershed was used. Under these circumstances, the roughness coefficients associated to overland and stream flow and the storage function of each discretization element were adjusted separately for the lower spatial resolution level. The results show that the similarity in hydrological responses, in terms of maximum water depth, obtained by adjusting the storage function of the cells, is better than that corresponding to the adjustment of roughness coefficients. [Spanish] Los modelos matematicos de parametros distribuidos resultan particularmente apropiados para determinar la variabilidad espacial y temporal de las respuestas hidrologicas dentro de un determinado sistema hidrico. En una cuenca es posible realizar la constitucion de un modelo con diferentes niveles de detalle en funcion principalmente de la disponibilidad de informacion de entrada necesaria, de los objetivos de estudio y de los requerimientos de modelado del sistema. En el presente trabajo se analizan los efectos producidos en la representacion del relieve debido a los diferentes tamanos de celda en que se ha discretizado una cuenca de llanura y se propone el

  17. Spatial distribution of reflected gamma rays by Monte Carlo simulation

    International Nuclear Information System (INIS)

    Jehouani, A.; Merzouki, A.; Boutadghart, F.; Ghassoun, J.

    2007-01-01

    In nuclear facilities, the reflection of gamma rays of the walls and metals constitutes an unknown origin of radiation. These reflected gamma rays must be estimated and determined. This study concerns reflected gamma rays on metal slabs. We evaluated the spatial distribution of the reflected gamma rays spectra by using the Monte Carlo method. An appropriate estimator for the double differential albedo is used to determine the energy spectra and the angular distribution of reflected gamma rays by slabs of iron and aluminium. We took into the account the principal interactions of gamma rays with matter: photoelectric, coherent scattering (Rayleigh), incoherent scattering (Compton) and pair creation. The Klein-Nishina differential cross section was used to select direction and energy of scattered photons after each Compton scattering. The obtained spectra show peaks at 0.511 * MeV for higher source energy. The Results are in good agreement with those obtained by the TRIPOLI code [J.C. Nimal et al., TRIPOLI02: Programme de Monte Carlo Polycinsetique a Trois dimensions, CEA Rapport, Commissariat a l'Energie Atomique.

  18. Spatially explicit modeling in ecology: A review

    Science.gov (United States)

    DeAngelis, Donald L.; Yurek, Simeon

    2017-01-01

    The use of spatially explicit models (SEMs) in ecology has grown enormously in the past two decades. One major advancement has been that fine-scale details of landscapes, and of spatially dependent biological processes, such as dispersal and invasion, can now be simulated with great precision, due to improvements in computer technology. Many areas of modeling have shifted toward a focus on capturing these fine-scale details, to improve mechanistic understanding of ecosystems. However, spatially implicit models (SIMs) have played a dominant role in ecology, and arguments have been made that SIMs, which account for the effects of space without specifying spatial positions, have an advantage of being simpler and more broadly applicable, perhaps contributing more to understanding. We address this debate by comparing SEMs and SIMs in examples from the past few decades of modeling research. We argue that, although SIMs have been the dominant approach in the incorporation of space in theoretical ecology, SEMs have unique advantages for addressing pragmatic questions concerning species populations or communities in specific places, because local conditions, such as spatial heterogeneities, organism behaviors, and other contingencies, produce dynamics and patterns that usually cannot be incorporated into simpler SIMs. SEMs are also able to describe mechanisms at the local scale that can create amplifying positive feedbacks at that scale, creating emergent patterns at larger scales, and therefore are important to basic ecological theory. We review the use of SEMs at the level of populations, interacting populations, food webs, and ecosystems and argue that SEMs are not only essential in pragmatic issues, but must play a role in the understanding of causal relationships on landscapes.

  19. Is a matrix exponential specification suitable for the modeling of spatial correlation structures?

    Science.gov (United States)

    Strauß, Magdalena E; Mezzetti, Maura; Leorato, Samantha

    2017-05-01

    This paper investigates the adequacy of the matrix exponential spatial specifications (MESS) as an alternative to the widely used spatial autoregressive models (SAR). To provide as complete a picture as possible, we extend the analysis to all the main spatial models governed by matrix exponentials comparing them with their spatial autoregressive counterparts. We propose a new implementation of Bayesian parameter estimation for the MESS model with vague prior distributions, which is shown to be precise and computationally efficient. Our implementations also account for spatially lagged regressors. We further allow for location-specific heterogeneity, which we model by including spatial splines. We conclude by comparing the performances of the different model specifications in applications to a real data set and by running simulations. Both the applications and the simulations suggest that the spatial splines are a flexible and efficient way to account for spatial heterogeneities governed by unknown mechanisms.

  20. Assessment of Rainfall-induced Landslide Potential and Spatial Distribution

    Science.gov (United States)

    Chen, Yie-Ruey; Tsai, Kuang-Jung; Chen, Jing-Wen; Chiang, Jie-Lun; Hsieh, Shun-Chieh; Chue, Yung-Sheng

    2016-04-01

    Recently, due to the global climate change, most of the time the rainfall in Taiwan is of short duration but with high intensity. Due to Taiwan's steep terrain, rainfall-induced landslides often occur and lead to human causalities and properties loss. Taiwan's government has invested huge reconstruction funds to the affected areas. However, after rehabilitation they still face the risk of secondary sediment disasters. Therefore, this study assesses rainfall-induced (secondary) landslide potential and spatial distribution in watershed of Southern Taiwan under extreme climate change. The study areas in this research are Baolai and Jianshan villages in the watershed of the Laonongxi River Basin in the Southern Taiwan. This study focused on the 3 years after Typhoon Morakot (2009 to 2011). During this period, the study area experienced six heavy rainfall events including five typhoons and one heavy rainfall. The genetic adaptive neural network, texture analysis and GIS were implemented in the analysis techniques for the interpretation of satellite images and to obtain surface information and hazard log data and to analyze land use change. A multivariate hazards evaluation method was applied to quantitatively analyze the weights of various natural environmental and slope development hazard factors. Furthermore, this study established a slope landslide potential assessment model and depicted a slope landslide potential diagram by using the GIS platform. The interaction between (secondary) landslide mechanism, scale, and location was analyzed using association analysis of landslide historical data and regional environmental characteristics. The results of image classification before and after six heavy rainfall events show that the values of coefficient of agreement are at medium-high level. By multivariate hazards evaluation method, geology and the effective accumulative rainfall (EAR) are the most important factors. Slope, distance from fault, aspect, land disturbance

  1. Spatial Preference Modelling for equitable infrastructure provision: an application of Sen's Capability Approach

    Science.gov (United States)

    Wismadi, Arif; Zuidgeest, Mark; Brussel, Mark; van Maarseveen, Martin

    2014-01-01

    To determine whether the inclusion of spatial neighbourhood comparison factors in Preference Modelling allows spatial decision support systems (SDSSs) to better address spatial equity, we introduce Spatial Preference Modelling (SPM). To evaluate the effectiveness of this model in addressing equity, various standardisation functions in both Non-Spatial Preference Modelling and SPM are compared. The evaluation involves applying the model to a resource location-allocation problem for transport infrastructure in the Special Province of Yogyakarta in Indonesia. We apply Amartya Sen's Capability Approach to define opportunity to mobility as a non-income indicator. Using the extended Moran's I interpretation for spatial equity, we evaluate the distribution output regarding, first, `the spatial distribution patterns of priority targeting for allocation' (SPT) and, second, `the effect of new distribution patterns after location-allocation' (ELA). The Moran's I index of the initial map and its comparison with six patterns for SPT as well as ELA consistently indicates that the SPM is more effective for addressing spatial equity. We conclude that the inclusion of spatial neighbourhood comparison factors in Preference Modelling improves the capability of SDSS to address spatial equity. This study thus proposes a new formal method for SDSS with specific attention on resource location-allocation to address spatial equity.

  2. Spatial distribution of the chemical properties of the soil and of soybean yield in the field

    Directory of Open Access Journals (Sweden)

    Alexandre Gazolla-Neto

    2016-06-01

    Full Text Available ABSTRACT The aim of this study was to evaluate the spatial dependence between chemical properties of the soil and yield components in the soybean using precision farming techniques. Samples of the soil and plants were taken from georeferenced points to determine the chemical properties of the soil and the yield components. The results were submitted to Pearson correlation analysis, descriptive statistics and geostatistics. The coefficient of variation showed a wide range of distribution for the chemical attributes of the soil, with the highest indices being found for the levels of available phosphorus (102% and potassium (72.65%. Soil pH and organic matter showed a coefficient of variation of 5.96 and 15.93% respectively. Semivariogram analysis of the yield components (productivity, 1,000-seed weight and number of seeds and the chemical properties of the soil (organic matter, pH, phosphorus, potassium, calcium, magnesium, boron, manganese and zinc fitted the spherical model with moderate spatial dependence, with values ranging from 200 to 700 m. Spatial distribution by means of map interpolation was efficient in evaluating spatial variability, allowing the identification and quantification of regions of low and high productivity in the production area, together with the distribution of soil attributes and their respective levels of availability to the soybean plants.

  3. The model of drugs distribution dynamics in biological tissue

    Science.gov (United States)

    Ginevskij, D. A.; Izhevskij, P. V.; Sheino, I. N.

    2017-09-01

    The dose distribution by Neutron Capture Therapy follows the distribution of 10B in the tissue. The modern models of pharmacokinetics of drugs describe the processes occurring in conditioned "chambers" (blood-organ-tumor), but fail to describe the spatial distribution of the drug in the tumor and in normal tissue. The mathematical model of the spatial distribution dynamics of drugs in the tissue, depending on the concentration of the drug in the blood, was developed. The modeling method is the representation of the biological structure in the form of a randomly inhomogeneous medium in which the 10B distribution occurs. The parameters of the model, which cannot be determined rigorously in the experiment, are taken as the quantities subject to the laws of the unconnected random processes. The estimates of 10B distribution preparations in the tumor and healthy tissue, inside/outside the cells, are obtained.

  4. Linking spatial and dynamic models for traffic maneuvers

    DEFF Research Database (Denmark)

    Olderog, Ernst-Rüdiger; Ravn, Anders Peter; Wisniewski, Rafal

    2015-01-01

    For traffic maneuvers of multiple vehicles on highways we build an abstract spatial and a concrete dynamic model. In the spatial model we show the safety (collision freedom) of lane-change maneuvers. By linking the spatial and dynamic model via suitable refinements of the spatial atoms to distance...

  5. The spatial distribution of underage tobacco sales in Los Angeles.

    Science.gov (United States)

    Lipton, Robert; Banerjee, Aniruddha; Levy, David; Manzanilla, Nora; Cochrane, Michelle

    2008-01-01

    Underage tobacco sales is considered a serious public health problem in Los Angeles. Anecdotally, rates have been thought to be quite high. In this paper, using spatial statistical techniques, we describe underage tobacco sales, identifying areas with high levels of sales and hot spots controlling for sociodemographic measures. Six hundred eighty-nine tobacco outlets were investigated throughout the city of Los Angeles in 2001. We consider the factors that explain vendor location of illegal sales of tobacco to underage youth and focus on those areas with especially high rates of illegal sales when controlling for other independent measures. Using data from the census, the LA City Attorney's Office, and public records on school locations in Los Angeles, we employ general least-squares (GLS) estimators in order to avoid biased estimates. vendor location of underage tobacco compliance checks, violators, and nonviolators. Underage tobacco sales in Los Angeles were very high (33.5%) for the entire city in 2001. In many zip codes this rate is considerably higher (60%-100%). When conducting spatial modeling, lower income and ethnicity were strongly associated with increases in underage tobacco sales. Hotspot areas of underage tobacco sales also had much lower mean family income and a much higher percentage of foreign born and greater population density. Spatial techniques were used to better identify areas where vendors sell tobacco to underage youth. Lower income areas were much more likely to both have higher rates of underage tobacco sales and to be a hot spot for such sales. Population density is also significantly associated with underage tobacco sales. The study's limitations are noted.

  6. Sparse modeling of spatial environmental variables associated with asthma.

    Science.gov (United States)

    Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W

    2015-02-01

    Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.

  7. Airborne measurements of spatial NO2 distributions during AROMAT

    Science.gov (United States)

    Meier, Andreas Carlos; Seyler, André; Schönhardt, Anja; Richter, Andreas; Ruhtz, Thomas; Lindemann, Carsten; Burrows, John P.

    2015-04-01

    Nitrogen oxides, NOx (NOx = NO + NO2) play a key role in tropospheric chemistry. In addition to their directly harmful effects on the respiratory system of living organisms, they influence the levels of tropospheric ozone and contribute to acid rain and eutrophication of ecosystems. As they are produced in combustion processes, they can serve as an indicator for anthropogenic air pollution. In September 2014 several European research groups conducted the ESA funded Airborne ROmanian Measurements of Aerosols and Trace gases (AROMAT) campaign to test and intercompare newly developed airborne observation sytsems dedicated to air quality satellite validation studies. The IUP Bremen contributed to this campaign with its Airborne imaging DOAS instrument for Measurements of Atmospheric Pollution (AirMAP) on board a Cessna 207 turbo, operated by the FU Berlin. AirMAP allows the retrieval of integrated NO2 column densities in a stripe below the aircraft at a fine spatial resolution of up to 30 x 80 m2, at a typical flight altitude. Measurements have been performed over the city of Bucharest, creating for the first time high spatial resolution maps of Bucharest's NO2 distribution in a time window of approx. 2 hours. The observations were synchronised with ground-based car MAX-DOAS measurements for comparison. In addition, measurements were taken over the city of Berlin, Germany and at the Rovinari power plant, Romania. In this work the results of the research flights will be presented and conclusions will be drawn on the quality of the measurements, their applicability for satellite data validation and possible improvements for future measurements.

  8. Spatial Distribution of Star Formation in High Redshift Galaxies

    Science.gov (United States)

    Cunnyngham, Ian; Takamiya, M.; Willmer, C.; Chun, M.; Young, M.

    2011-01-01

    Integral field unit spectroscopy taken of galaxies with redshifts between 0.6 and 0.8 utilizing Gemini Observatory’s GMOS instrument were used to investigate the spatial distribution of star-forming regions by measuring the Hβ and [OII]λ3727 emission line fluxes. These galaxies were selected based on the strength of Hβ and [OII]λ3727 as measured from slit LRIS/Keck spectra. The process of calibrating and reducing data into cubes -- possessing two spatial dimensions, and one for wavelength -- was automated via a custom batch script using the Gemini IRAF routines. Among these galaxies only the bluest sources clearly show [OII] in the IFU regardless of total galaxy luminosity. The brightest galaxies lack [OII] emission and it is posited that two different modes of star formation exist among this seemingly homogeneous group of z=0.7 star-forming galaxies. In order to increase the galaxy sample to include redshifts from 0.3 to 0.9, public Gemini IFU data are being sought. Python scripts were written to mine the Gemini Science Archive for candidate observations, cross-reference the target of these observations with information from the NASA Extragalactic Database, and then present the resultant database in sortable, searchable, cross-linked web-interface using Django to facilitate navigation. By increasing the sample, we expect to characterize these two different modes of star formation which could be high-redshift counterparts of the U/LIRGs and dwarf starburst galaxies like NGC 1569/NGC 4449. The authors acknowledge funds provided by the National Science Foundation (AST 0909240).

  9. Factor Copula Models for Replicated Spatial Data

    KAUST Repository

    Krupskii, Pavel

    2016-12-19

    We propose a new copula model that can be used with replicated spatial data. Unlike the multivariate normal copula, the proposed copula is based on the assumption that a common factor exists and affects the joint dependence of all measurements of the process. Moreover, the proposed copula can model tail dependence and tail asymmetry. The model is parameterized in terms of a covariance function that may be chosen from the many models proposed in the literature, such as the Matérn model. For some choice of common factors, the joint copula density is given in closed form and therefore likelihood estimation is very fast. In the general case, one-dimensional numerical integration is needed to calculate the likelihood, but estimation is still reasonably fast even with large data sets. We use simulation studies to show the wide range of dependence structures that can be generated by the proposed model with different choices of common factors. We apply the proposed model to spatial temperature data and compare its performance with some popular geostatistics models.

  10. Stochastic analysis to assess the spatial distribution of groundwater nitrate concentrations in the Po catchment (Italy)

    International Nuclear Information System (INIS)

    Cinnirella, Sergio; Buttafuoco, Gabriele; Pirrone, Nicola

    2005-01-01

    A large database including temporal trends of physical, ecological and socio-economic data was developed within the EUROCAT project. The aim was to estimate the nutrient fluxes for different socio-economic scenarios at catchment and coastal zone level of the Po catchment (Northern Italy) with reference to the Water Quality Objectives reported in the Water Framework Directive (WFD 2000/60/CE) and also in Italian legislation. Emission data derived from different sources at national, regional and local levels are referred to point and non-point sources. While non-point (diffuse) sources are simply integrated into the nutrient flux model, point sources are irregularly distributed. Intensive farming activity in the Po valley is one of the main Pressure factors Driving groundwater pollution in the catchment, therefore understanding the spatial variability of groundwater nitrate concentrations is a critical issue to be considered in developing a Water Quality Management Plan. In order to use the scattered point source data as input in our biogeochemical and transport models, it was necessary to predict their values and associated uncertainty at unsampled locations. This study reports the spatial distribution and uncertainty of groundwater nitrate concentration at a test site of the Po watershed using a probabilistic approach. Our approach was based on geostatistical sequential Gaussian simulation used to yield a series of stochastic images characterized by equally probable spatial distributions of the nitrate concentration across the area. Post-processing of many simulations allowed the mapping of contaminated and uncontaminated areas and provided a model for the uncertainty in the spatial distribution of nitrate concentrations. - The stochastic simulation should be preferred to kriging in environmental studies, whenever it is critical to preserve the variation of a variable

  11. Spatial distribution of cavitation-shock-pressure around a jet-flow gate-valve

    International Nuclear Information System (INIS)

    Oba, Risaburo; Takayama, Kazuyoshi; Ito, Yukio; Miyakura, Hideto; Nozaki, Satoru; Ishige, Tadashi; Sonoda, Shuji; Sakamoto, Kenji.

    1987-01-01

    To make clear the mechanism of cavitation erosion, the spatial distribution of cavitation shock pressures were quantitatively measured by a pressure sensitive sheet in the 1/10 scale model of a jet-flow gate-valve, for various valve-openings and cavitation numbers. The dynamic pressure response of the sheet was corrected by the shock wave generated from detonation explosives. It is made clear that the erosive shock pressures are distributed in a limited part of the whole cavitation region, and the safety region without the fatal cavitation erosion is defined. (author)

  12. Development, Testing, and Sensitivity and Uncertainty Analyses of a Transport and Reaction Simulation Engine (TaRSE) for Spatially Distributed Modeling of Phosphorus in South Florida Peat Marsh Wetlands

    Science.gov (United States)

    Jawitz, James W.; Munoz-Carpena, Rafael; Muller, Stuart; Grace, Kevin A.; James, Andrew I.

    2008-01-01

    Alterations to the predevelopment delivery of water and nutrients into the Everglades of southern Florida have been occurring for nearly a century. Major regional drainage projects, large-scale agricultural development, and changes to the hydrology of the Kissimmee River-Lake Okeechobee watershed have resulted in substantial phosphorus transport increases by surface waters. Excess phosphorus has accumulated in the soils of northern Everglades marshes to levels that have impaired the natural resources of the region. Regulations now limit the amount of phosphorous that enters the Everglades through an extensive network of water-control structures. This study involved the development and application of water-quality modeling components that may be applied to existing hydrologic models of southern Florida to evaluate the effects of different management scenarios. The result of this work is a spatially distributed water-quality model for phosphorus transport and cycling in wetlands. The model solves the advection-dispersion equation on an unstructured triangular mesh and incorporates a wide range of user-selectable mechanisms for phosphorus uptake and release parameters. In general, the phosphorus model contains transfers between stores; examples of stores that can be included are soil, water column (solutes), pore water, macrophytes, suspended solids (plankton), and biofilm. Examples of transfers are growth, senescence, settling, diffusion, and so forth, described with first order, second order, and Monod types of transformations. Local water depths and velocities are determined from an existing two-dimensional, overland-flow hydrologic model. The South Florida Water Management District Regional Simulation Model was used in this study. The model is applied to three case studies: intact cores of wetland soils with water, outdoor mesocosoms, and a large constructed wetland; namely, Cell 4 of Stormwater Treatment Area 1 West (STA-1W Cell 4). Different levels of complexity

  13. Spatial and Temporal Clustering in a Simple Earthquake Asperity Model

    Science.gov (United States)

    Tiampo, K. F.; Kazemian, J.; Dominguez, R.; Klein, W.

    2016-12-01

    Natural earthquake fault systems are highly heterogeneous in space, the result of inhomogeneities that are a function of the variety of materials of different strengths. However, despite their inhomogeneous nature, real faults are often modeled as spatially homogeneous systems. Here we present a simple earthquake fault model based on the Olami-Feder-Christensen (OFC) and Rundle-Jackson-Brown (RJB) cellular automata models with long-range interactions that incorporates asperities, or stronger sites, into the lattice (Rundle and Jackson, 1977; Olami et al., 1992). These asperity cells are significantly stronger than the surrounding lattice sites but eventually rupture when the applied stress reaches their higher threshold stress. The introduction of these spatial heterogeneities results in spatial and temporal clustering in the model similar to that seen in natural fault systems. We observe sequences of activity that begin with a gradually accelerating number of larger events, or foreshocks, prior to a large event, followed by a tail of decreasing activity, or aftershocks. These recurrent large events occur at regular intervals and the characteristic time between events and their magnitude are a function of the stress dissipation parameter. The relative length of the foreshock to aftershock sequence depends on the amount of stress dissipation in the system. This work provides further evidence that the spatial and temporal patterns observed in natural seismicity are strongly influenced by the underlying physical properties and are not solely the result of a simple cascade mechanism. We find that the scaling depends not only on the amount of damage, but also on the spatial distribution of that damage (Dominguez et al., 2011; Kazemian et al., 2014). Here we compare the modeled sequences to those of natural earthquake sequences from California and around the world in order to investigate the interplay between cascade dynamics and spatial structure.

  14. Effect of electrode density and measurement noise on the spatial resolution of cortical potential distribution.

    Science.gov (United States)

    Ryynänen, Outi R M; Hyttinen, Jari A K; Laarne, Päivi H; Malmivuo, Jaakko A

    2004-09-01

    The purpose of the present study was to examine the spatial resolution of electroencephalography (EEG) by means of inverse cortical EEG solution. The main interest was to study how the number of measurement electrodes and the amount of measurement noise affects the spatial resolution. A three-layer spherical head model was used to obtain the source-field relationship of cortical potentials and scalp EEG field. Singular value decomposition was used to evaluate the spatial resolution with various measurement noise estimates. The results suggest that as the measurement noise increases the advantage of dense electrode systems is decreased. With low realistic measurement noise, a more accurate inverse cortical potential distribution can be obtained with an electrode system where the distance between two electrodes is as small as 16 mm, corresponding to as many as 256 measurement electrodes. In clinical measurement environments, it is always beneficial to have at least 64 measurement electrodes.

  15. Spatially distributed effects of mental exhaustion on resting-state FMRI networks

    NARCIS (Netherlands)

    Esposito, Fabrizio; Otto, Tobias; Zijlstra, Fred R H; Goebel, R.

    2014-01-01

    Brain activity during rest is spatially coherent over functional connectivity networks called resting-state networks. In resting-state functional magnetic resonance imaging, independent component analysis yields spatially distributed network representations reflecting distinct mental processes, such

  16. Spatial distribution of calcium-gated chloride channels in olfactory cilia.

    Science.gov (United States)

    French, Donald A; Badamdorj, Dorjsuren; Kleene, Steven J

    2010-12-30

    In vertebrate olfactory receptor neurons, sensory cilia transduce odor stimuli into changes in neuronal membrane potential. The voltage changes are primarily caused by the sequential openings of two types of channel: a cyclic-nucleotide-gated (CNG) cationic channel and a calcium-gated chloride channel. In frog, the cilia are 25 to 200 µm in length, so the spatial distributions of the channels may be an important determinant of odor sensitivity. To determine the spatial distribution of the chloride channels, we recorded from single cilia as calcium was allowed to diffuse down the length of the cilium and activate the channels. A computational model of this experiment allowed an estimate of the spatial distribution of the chloride channels. On average, the channels were concentrated in a narrow band centered at a distance of 29% of the ciliary length, measured from the base of the cilium. This matches the location of the CNG channels determined previously. This non-uniform distribution of transduction proteins is consistent with similar findings in other cilia. On average, the two types of olfactory transduction channel are concentrated in the same region of the cilium. This may contribute to the efficient detection of weak stimuli.

  17. Effects of cell spatial organization and size distribution on ultrasound backscattering.

    Science.gov (United States)

    Saha, Ratan K; Kolios, Michael C

    2011-10-01

    In ultrasound tissue characterization dealing with cellular aggregates (such as tumors), it can be hypothesized that cell microstructure and spatial distribution dominate the backscatter signal. Effects of spatial organization and size distribution of nuclei in cell aggregates on ultrasound backscatter are examined in this work using 2-D computer simulations. The nuclei embedded in cytoplasm were assumed to be weak scatterers of incident ultrasound waves, and therefore multiple scattering could be neglected. The fluid sphere model was employed to obtain the scattering amplitude for each nucleus and the backscatter echo was generated by summing scattered signals originating from many nuclei. A Monte Carlo algorithm was implemented to generate realizations of cell aggregates. It was found that the integrated backscattering coefficient (IBSC) computed between 10 and 30 MHz increased by about 27 dB for a spatially random distribution of mono-disperse nuclei (radius = 4.5 μm) compared with that of a sample of periodically positioned mono-disperse nuclei. The IBSC also increased by nearly 7 dB (between 10 and 30 MHz) for a spatially random distribution of poly-disperse nuclei (mean radius ± SD = 4.5 ± 1.54 μm) compared with that of a spatially random distribution of mono-disperse nuclei. Two different Gaussian pulses with center frequencies 5 and 25 MHz were employed to study the backscatter envelope statistics. An 80% bandwidth was chosen for each case with approximately 0.32 mm as the full-width at half-maximum (FWHM) for the first pulse and 0.06 mm for the second. The incident beam was approximated as a Gaussian beam (FWHM = 2.11 and 1.05 mm for those pulses, respectively). The backscatter signal envelope histograms generally followed the Rayleigh distribution for mono-disperse and poly-disperse samples. However, for samples with partially ordered nuclei, if the irradiating pulse contained a frequency for which ultrasound wavelength and scatter periodicity became

  18. Spatial and spatio-temporal bayesian models with R - INLA

    CERN Document Server

    Blangiardo, Marta

    2015-01-01

    Dedication iiiPreface ix1 Introduction 11.1 Why spatial and spatio-temporal statistics? 11.2 Why do we use Bayesian methods for modelling spatial and spatio-temporal structures? 21.3 Why INLA? 31.4 Datasets 32 Introduction to 212.1 The language 212.2 objects 222.3 Data and session management 342.4 Packages 352.5 Programming in 362.6 Basic statistical analysis with 393 Introduction to Bayesian Methods 533.1 Bayesian Philosophy 533.2 Basic Probability Elements 573.3 Bayes Theorem 623.4 Prior and Posterior Distributions 643.5 Working with the Posterior Distribution 663.6 Choosing the Prior Distr

  19. How well do food distributions predict spatial distributions of shorebirds with different degrees of self-organization?

    Science.gov (United States)

    Folmer, Eelke O; Olff, Han; Piersma, Theunis

    2010-07-01

    1. Habitat selection models usually assume that the spatial distributions of animals depend positively on the distributions of resources and negatively on interference. However, the presence of conspecifics at a given location also signals safety and the availability of resources. This may induce followers to select contiguous patches and causes animals to cluster. Resource availability, interference and attraction therefore jointly lead to self-organized patterns in foraging animals. 2. We analyse the distribution of foraging shorebirds at landscape level on the basis of a resource-based model to establish, albeit indirectly, the importance of conspecific attraction and interference. 3. At 23 intertidal sites with a mean area of 170 ha spread out over the Dutch Wadden Sea, the spatial distribution of six abundant shorebird species was determined. The location of individuals and groups was mapped using a simple method based on projective geometry, enabling fast mapping of low-tide foraging shorebird distributions. We analysed the suitability of these 23 sites in terms of food availability and travel distances to high tide roosts. 4. We introduce an interference sensitivity scale which maps interference as a function of inter-individual distance. We thus obtain interference-insensitive species, which are only sensitive to interference at short inter-individual distances (and may thus pack densely) and interference-sensitive species which interfere over greater inter-individual distances (and thus form sparse flocks). 5. We found that interference-insensitive species like red knot (Calidris canutus) and dunlins (Calidris alpina) are more clustered than predicted by the spatial distribution of their food resources. This suggests that these species follow each other when selecting foraging patches. In contrast, curlew (Numenius arquata) and grey plover (Pluvialis squatarola), known to be sensitive to interference, form sparse flocks. Hence, resource-based models have

  20. Optimal exploitation of spatially distributed trophic resources and population stability

    Science.gov (United States)

    Basset, A.; Fedele, M.; DeAngelis, D.L.

    2002-01-01

    The relationships between optimal foraging of individuals and population stability are addressed by testing, with a spatially explicit model, the effect of patch departure behaviour on individual energetics and population stability. A factorial experimental design was used to analyse the relevance of the behavioural factor in relation to three factors that are known to affect individual energetics; i.e. resource growth rate (RGR), assimilation efficiency (AE), and body size of individuals. The factorial combination of these factors produced 432 cases, and 1000 replicate simulations were run for each case. Net energy intake rates of the modelled consumers increased with increasing RGR, consumer AE, and consumer body size, as expected. Moreover, through their patch departure behaviour, by selecting the resource level at which they departed from the patch, individuals managed to substantially increase their net energy intake rates. Population stability was also affected by the behavioural factors and by the other factors, but with highly non-linear responses. Whenever resources were limiting for the consumers because of low RGR, large individual body size or low AE, population density at the equilibrium was directly related to the patch departure behaviour; on the other hand, optimal patch departure behaviour, which maximised the net energy intake at the individual level, had a negative influence on population stability whenever resource availability was high for the consumers. The consumer growth rate (r) and numerical dynamics, as well as the spatial and temporal fluctuations of resource density, which were the proximate causes of population stability or instability, were affected by the behavioural factor as strongly or even more strongly than by the others factors considered here. Therefore, patch departure behaviour can act as a feedback control of individual energetics, allowing consumers to optimise a potential trade-off between short-term individual fitness

  1. Factors driving the spatial layout of distribution channels

    NARCIS (Netherlands)

    Onstein, A.T.C.; Ektesaby, M.; Rezaei, J.; Tavasszy, L.A.; van Damme, D.A.

    2017-01-01

    Research statement Our study analyses the factors that drive decision-making on distribution structures, including the layout of distribution channels and the locations of distribution centres. Distribution is a primary firm activity, which strongly influences logistics costs and logistics

  2. Artificial neural networks for spatial distribution of fuel assemblies in reload of PWR reactors

    International Nuclear Information System (INIS)

    Oliveira, Edyene; Castro, Victor F.; Velásquez, Carlos E.; Pereira, Claubia

    2017-01-01

    An artificial neural network methodology is being developed in order to find an optimum spatial distribution of the fuel assemblies in a nuclear reactor core during reload. The main bounding parameter of the modelling was the neutron multiplication factor, k ef f . The characteristics of the network are defined by the nuclear parameters: cycle, burnup, enrichment, fuel type, and average power peak of each element. These parameters were obtained by the ORNL nuclear code package SCALE6.0. As for the artificial neural network, the ANN Feedforward Multi L ayer P erceptron with various layers and neurons were constructed. Three algorithms were used and tested: LM (Levenberg-Marquardt), SCG (Scaled Conjugate Gradient) and BayR (Bayesian Regularization). Artificial neural network have implemented using MATLAB 2015a version. As preliminary results, the spatial distribution of the fuel assemblies in the core using a neural network was slightly better than the standard core. (author)

  3. Development of a distributed air pollutant dry deposition modeling framework

    Science.gov (United States)

    Satoshi Hirabayashi; Charles N. Kroll; David J. Nowak

    2012-01-01

    A distributed air pollutant dry deposition modeling systemwas developed with a geographic information system (GIS) to enhance the functionality of i-Tree Eco (i-Tree, 2011). With the developed system, temperature, leaf area index (LAI) and air pollutant concentration in a spatially distributed form can be estimated, and based on these and other input variables, dry...

  4. Spatial variability and parametric uncertainty in performance assessment models

    International Nuclear Information System (INIS)

    Pensado, Osvaldo; Mancillas, James; Painter, Scott; Tomishima, Yasuo

    2011-01-01

    The problem of defining an appropriate treatment of distribution functions (which could represent spatial variability or parametric uncertainty) is examined based on a generic performance assessment model for a high-level waste repository. The generic model incorporated source term models available in GoldSim ® , the TDRW code for contaminant transport in sparse fracture networks with a complex fracture-matrix interaction process, and a biosphere dose model known as BDOSE TM . Using the GoldSim framework, several Monte Carlo sampling approaches and transport conceptualizations were evaluated to explore the effect of various treatments of spatial variability and parametric uncertainty on dose estimates. Results from a model employing a representative source and ensemble-averaged pathway properties were compared to results from a model allowing for stochastic variation of transport properties along streamline segments (i.e., explicit representation of spatial variability within a Monte Carlo realization). We concluded that the sampling approach and the definition of an ensemble representative do influence consequence estimates. In the examples analyzed in this paper, approaches considering limited variability of a transport resistance parameter along a streamline increased the frequency of fast pathways resulting in relatively high dose estimates, while those allowing for broad variability along streamlines increased the frequency of 'bottlenecks' reducing dose estimates. On this basis, simplified approaches with limited consideration of variability may suffice for intended uses of the performance assessment model, such as evaluation of site safety. (author)

  5. The spatial distribution of shocked gas in the Orion nebula

    Science.gov (United States)

    Beck, S. C.; Beckwith, S.

    1983-01-01

    Observations of the spatial distribution of extinction and excitation temperature toward the molecular hydrogen emission in the Orion molecular cloud OMC-1 are presented. Most, although not all, of the observed structure in the near-infrared line intensities results from variations in the column density of vibrationally excited H2 and is not due to variable extinction or temperature. The extinction toward the center of the emission region is between 1 and 2 mag at 4712/cm, the frequency of the v = 1-0 S(1) line, but increases toward the edges. The lack of emission from the eastern part of the nebula may result from increased extinction in that direction. Variations in the extinction temperature are less than the observational uncertainties of + or - 200 K at all but one position observed. Therefore, the excitation temperature of the hydrogen molecules is probably not a strong function of either the shock velocity or the density of the gas. Observations of the v = 3-2 S(3) line in the direction of strongest emission indicate the presence of gas temperatures about 2700 K and place constraints on the column density of gas which is at higher temperature.

  6. Landslide characteristics and spatial distribution in the Rwenzori Mountains, Uganda

    Science.gov (United States)

    Jacobs, Liesbet; Dewitte, Olivier; Poesen, Jean; Maes, Jan; Mertens, Kewan; Sekajugo, John; Kervyn, Matthieu

    2017-10-01

    In many landslide-prone regions, data on landslide characteristics remain poor or inexistent. This is also the case for the Rwenzori Mountains, located on the border of Uganda and the DR Congo. There, landslides frequently occur and cause fatalities and substantial damage to private property and infrastructure. In this paper, we present the results of a field inventory performed in three representative study areas covering 114 km2. A total of 371 landslides were mapped and analyzed for their geomorphological characteristics and their spatial distribution. The average landslide areas varied from less than 0.3 ha in the gneiss-dominated highlands to >1 ha in the rift alluvium of the lowlands. Large landslides (>1.5 ha) are well represented while smaller landslides (slides in gneiss and of deep rotational soil slides in the rift alluvium is observed. Slope angle is the main controlling topographic factor for landslides with the highest landslide concentrations for slope angles above 25-30° in the highlands and 10-15° in the lowlands. The undercutting of slopes by rivers and excavations for construction are important preparatory factors. Rainfall-triggered landslides are the most common in the area, however in the zones of influence of the last two major earthquakes (1966: Mw = 6.6 and 1994: Mw = 6.2), 12 co-seismic landslides were also observed.

  7. Spatial Distribution of Fungal Communities in an Arable Soil.

    Directory of Open Access Journals (Sweden)

    Julia Moll

    Full Text Available Fungi are prominent drivers of ecological processes in soils, so that fungal communities across different soil ecosystems have been well investigated. However, for arable soils taxonomically resolved fine-scale studies including vertical itemization of fungal communities are still missing. Here, we combined a cloning/Sanger sequencing approach of the ITS/LSU region as marker for general fungi and of the partial SSU region for arbuscular mycorrhizal fungi (AMF to characterize the microbiome in different maize soil habitats. Four compartments were analyzed over two annual cycles 2009 and 2010: a ploughed soil in 0-10 cm, b rooted soil in 40-50 cm, c root-free soil in 60-70 cm soil depth and d maize roots. Ascomycota was the most dominant phylum across all compartments. Fungal communities including yeasts and AMF differed strongly between compartments. Inter alia, Tetracladium, the overall largest MOTU (molecular operational taxonomic unit, occurred in all compartments, whereas Trichosporon dominated all soil compartments. Sequences belonging to unclassified Helotiales were forming the most abundant MOTUs exclusively present in roots. This study gives new insights on spatial distribution of fungi and helps to link fungal communities to specific ecological properties such as varying resources, which characterize particular niches of the heterogeneous soil environment.

  8. Evaluate the Spatial Distribution of ICT Indicators in Fourteen Areas of Isfahan Municipality

    Directory of Open Access Journals (Sweden)

    Ahmad Shahivandi

    2012-10-01

    Full Text Available Today, one of the criteria for the assessment of development of countries, international organizations and world economy is the achievement of the level of ICT. In addition, a fair distribution of this tool for better and update services is very important. The purpose of this study was to assess the spatial distribution parameters and hardware experts in the areas of ICT and informatics users fourteen municipality of Isfahan. Descriptive research method was analytic and for ranking, grading and determination of distribution models, statistical indicators Mac Granahan, cluster analysis and factor differences were used. The results showed that the different regions of Isfahan Municipality of enjoyment of these indicators were not equal to. Generally, these areas formed four classes to enjoy, have relatively less ill, have enjoyed and have been classified. The scattering coefficient showed large differences in the type and distribution of these indices in Isfahan Municipality there..

  9. Optimal use of resources structures home ranges and spatial distribution of black bears

    Science.gov (United States)

    Mitchell, M.S.; Powell, R.A.

    2007-01-01

    Research has shown that territories of animals are economical. Home ranges should be similarly efficient with respect to spatially distributed resources and this should structure their distribution on a landscape, although neither has been demonstrated empirically. To test these hypotheses, we used home range models that optimize resource use according to resource-maximizing and area-minimizing strategies to evaluate the home ranges of female black bears, Ursus americanus, living in the southern Appalachian Mountains. We tested general predictions of our models using 104 home ranges of adult female bears studied in the Pisgah Bear Sanctuary, North Carolina, U.S.A., from 1981 to 2001. We also used our models to estimate home ranges for each real home range under a variety of strategies and constraints and compared similarity of simulated to real home ranges. We found that home ranges of female bears were efficient with respect to the spatial distribution of resources and were best explained by an area-minimizing strategy with moderate resource thresholds and low levels of resource depression. Although resource depression probably influenced the spatial distribution of home ranges on the landscape, levels of resource depression were too low to quantify accurately. Home ranges of lactating females had higher resource thresholds and were more susceptible to resource depression than those of breeding females. We conclude that home ranges of animals, like territories, are economical with respect to resources, and that resource depression may be the mechanism behind ideal free or ideal preemptive distributions on complex, heterogeneous landscapes. ?? 2007 The Association for the Study of Animal Behaviour.

  10. Indoorgml - a Standard for Indoor Spatial Modeling

    Science.gov (United States)

    Li, Ki-Joune

    2016-06-01

    With recent progress of mobile devices and indoor positioning technologies, it becomes possible to provide location-based services in indoor space as well as outdoor space. It is in a seamless way between indoor and outdoor spaces or in an independent way only for indoor space. However, we cannot simply apply spatial models developed for outdoor space to indoor space due to their differences. For example, coordinate reference systems are employed to indicate a specific position in outdoor space, while the location in indoor space is rather specified by cell number such as room number. Unlike outdoor space, the distance between two points in indoor space is not determined by the length of the straight line but the constraints given by indoor components such as walls, stairs, and doors. For this reason, we need to establish a new framework for indoor space from fundamental theoretical basis, indoor spatial data models, and information systems to store, manage, and analyse indoor spatial data. In order to provide this framework, an international standard, called IndoorGML has been developed and published by OGC (Open Geospatial Consortium). This standard is based on a cellular notion of space, which considers an indoor space as a set of non-overlapping cells. It consists of two types of modules; core module and extension module. While core module consists of four basic conceptual and implementation modeling components (geometric model for cell, topology between cells, semantic model of cell, and multi-layered space model), extension modules may be defined on the top of the core module to support an application area. As the first version of the standard, we provide an extension for indoor navigation.

  11. Spatially explicit non-Mendelian diploid model

    OpenAIRE

    Lanchier, N.; Neuhauser, C.

    2009-01-01

    We introduce a spatially explicit model for the competition between type $a$ and type $b$ alleles. Each vertex of the $d$-dimensional integer lattice is occupied by a diploid individual, which is in one of three possible states or genotypes: $aa$, $ab$ or $bb$. We are interested in the long-term behavior of the gene frequencies when Mendel's law of segregation does not hold. This results in a voter type model depending on four parameters; each of these parameters measures the strength of comp...

  12. Spatial and temporal distribution of falciparum malaria in China

    Directory of Open Access Journals (Sweden)

    Lin Hualiang

    2009-06-01

    Full Text Available Abstract Background Falciparum malaria is the most deadly among the four main types of human malaria. Although great success has been achieved since the launch of the National Malaria Control Programme in 1955, malaria remains a serious public health problem in China. This paper aimed to analyse the geographic distribution, demographic patterns and time trends of falciparum malaria in China. Methods The annual numbers of falciparum malaria cases during 1992–2003 and the individual case reports of each clinical falciparum malaria during 2004–2005 were extracted from communicable disease information systems in China Center for Diseases Control and Prevention. The annual number of cases and the annual incidence were mapped by matching them to corresponding province- and county-level administrative units in a geographic information system. The distribution of falciparum malaria by age, gender and origin of infection was analysed. Time-series analysis was conducted to investigate the relationship between the falciparum malaria in the endemic provinces and the imported falciparum malaria in non-endemic provinces. Results Falciparum malaria was endemic in two provinces of China during 2004–05. Imported malaria was reported in 26 non-endemic provinces. Annual incidence of falciparum malaria was mapped at county level in the two endemic provinces of China: Yunnan and Hainan. The sex ratio (male vs. female for the number of cases in Yunnan was 1.6 in the children of 0–15 years and it reached 5.7 in the adults over 15 years of age. The number of malaria cases in Yunnan was positively correlated with the imported malaria of concurrent months in the non-endemic provinces. Conclusion The endemic area of falciparum malaria in China has remained restricted to two provinces, Yunnan and Hainan. Stable transmission occurs in the bordering region of Yunnan and the hilly-forested south of Hainan. The age and gender distribution in the endemic area is

  13. The relative spatial distributions of high- and low-luminosity galaxies toward Coma

    International Nuclear Information System (INIS)

    Salzer, J.J.; Hanson, M.M.; Gavazzi, G.

    1990-01-01

    The relative spatial distributions of low- and high-mass galaxies which lie in a field in the direction of the Coma Supercluster are investigated. Three tests are used to compare the distributions of high-luminosity and low-luminosity galaxies in the field: correlation functions, nearest neighbor distributions, and local density environments. All three tests indicate that the low-luminosity galaxies are significantly less confined to the structure defined by the luminous galaxies than are the luminous galaxies themselves. Several galaxies in the low-luminosity subsample are within voids. These findings lend support to various models for the formation of large-scale structure that include biased galaxy formation. In particular, the ratio of the amplitudes of the correlation functions for dwarfs and giants agrees closely with the predictions of the cold dark matter models of White et al. (1987). 54 refs

  14. The spatial heterogeneity between Japanese encephalitis incidence distribution and environmental variables in Nepal.

    Directory of Open Access Journals (Sweden)

    Daniel E Impoinvil

    Full Text Available To identify potential environmental drivers of Japanese Encephalitis virus (JE transmission in Nepal, we conducted an ecological study to determine the spatial association between 2005 Nepal JE incidence, and climate, agricultural, and land-cover variables at district level.District-level data on JE cases were examined using Local Indicators of Spatial Association (LISA analysis to identify spatial clusters from 2004 to 2008 and 2005 data was used to fit a spatial lag regression model with climate, agriculture and land-cover variables.Prior to 2006, there was a single large cluster of JE cases located in the Far-West and Mid-West terai regions of Nepal. After 2005, the distribution of JE cases in Nepal shifted with clusters found in the central hill areas. JE incidence during the 2005 epidemic had a stronger association with May mean monthly temperature and April mean monthly total precipitation compared to mean annual temperature and precipitation. A parsimonious spatial lag regression model revealed, 1 a significant negative relationship between JE incidence and April precipitation, 2 a significant positive relationship between JE incidence and percentage of irrigated land 3 a non-significant negative relationship between JE incidence and percentage of grassland cover, and 4 a unimodal non-significant relationship between JE Incidence and pig-to-human ratio.JE cases clustered in the terai prior to 2006 where it seemed to shift to the Kathmandu region in subsequent years. The spatial pattern of JE cases during the 2005 epidemic in Nepal was significantly associated with low precipitation and the percentage of irrigated land. Despite the availability of an effective vaccine, it is still important to understand environmental drivers of JEV transmission since the enzootic cycle of JEV transmission is not likely to be totally interrupted. Understanding the spatial dynamics of JE risk factors may be useful in providing important information to the

  15. Analysis of the Spatial Distribution of Galaxies by Multiscale Methods

    Directory of Open Access Journals (Sweden)

    E. Saar

    2005-09-01

    Full Text Available Galaxies are arranged in interconnected walls and filaments forming a cosmic web encompassing huge, nearly empty, regions between the structures. Many statistical methods have been proposed in the past in order to describe the galaxy distribution and discriminate the different cosmological models. We present in this paper multiscale geometric transforms sensitive to clusters, sheets, and walls: the 3D isotropic undecimated wavelet transform, the 3D ridgelet transform, and the 3D beamlet transform. We show that statistical properties of transform coefficients measure in a coherent and statistically reliable way, the degree of clustering, filamentarity, sheetedness, and voidedness of a data set.

  16. Assessing fit in Bayesian models for spatial processes

    KAUST Repository

    Jun, M.

    2014-09-16

    © 2014 John Wiley & Sons, Ltd. Gaussian random fields are frequently used to model spatial and spatial-temporal data, particularly in geostatistical settings. As much of the attention of the statistics community has been focused on defining and estimating the mean and covariance functions of these processes, little effort has been devoted to developing goodness-of-fit tests to allow users to assess the models\\' adequacy. We describe a general goodness-of-fit test and related graphical diagnostics for assessing the fit of Bayesian Gaussian process models using pivotal discrepancy measures. Our method is applicable for both regularly and irregularly spaced observation locations on planar and spherical domains. The essential idea behind our method is to evaluate pivotal quantities defined for a realization of a Gaussian random field at parameter values drawn from the posterior distribution. Because the nominal distribution of the resulting pivotal discrepancy measures is known, it is possible to quantitatively assess model fit directly from the output of Markov chain Monte Carlo algorithms used to sample from the posterior distribution on the parameter space. We illustrate our method in a simulation study and in two applications.

  17. The quantitative modelling of human spatial habitability

    Science.gov (United States)

    Wise, J. A.

    1985-01-01

    A model for the quantitative assessment of human spatial habitability is presented in the space station context. The visual aspect assesses how interior spaces appear to the inhabitants. This aspect concerns criteria such as sensed spaciousness and the affective (emotional) connotations of settings' appearances. The kinesthetic aspect evaluates the available space in terms of its suitability to accommodate human movement patterns, as well as the postural and anthrometric changes due to microgravity. Finally, social logic concerns how the volume and geometry of available space either affirms or contravenes established social and organizational expectations for spatial arrangements. Here, the criteria include privacy, status, social power, and proxemics (the uses of space as a medium of social communication).

  18. Modeling mental spatial reasoning about cardinal directions.

    Science.gov (United States)

    Schultheis, Holger; Bertel, Sven; Barkowsky, Thomas

    2014-01-01

    This article presents research into human mental spatial reasoning with orientation knowledge. In particular, we look at reasoning problems about cardinal directions that possess multiple valid solutions (i.e., are spatially underdetermined), at human preferences for some of these solutions, and at representational and procedural factors that lead to such preferences. The article presents, first, a discussion of existing, related conceptual and computational approaches; second, results of empirical research into the solution preferences that human reasoners actually have; and, third, a novel computational model that relies on a parsimonious and flexible spatio-analogical knowledge representation structure to robustly reproduce the behavior observed with human reasoners. Copyright © 2014 Cognitive Science Society, Inc.

  19. A general modeling framework for describing spatially structured population dynamics

    Science.gov (United States)

    Sample, Christine; Fryxell, John; Bieri, Joanna; Federico, Paula; Earl, Julia; Wiederholt, Ruscena; Mattsson, Brady; Flockhart, Tyler; Nicol, Sam; Diffendorfer, James E.; Thogmartin, Wayne E.; Erickson, Richard A.; Norris, D. Ryan

    2017-01-01

    Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance

  20. A general modeling framework for describing spatially structured population dynamics.

    Science.gov (United States)

    Sample, Christine; Fryxell, John M; Bieri, Joanna A; Federico, Paula; Earl, Julia E; Wiederholt, Ruscena; Mattsson, Brady J; Flockhart, D T Tyler; Nicol, Sam; Diffendorfer, Jay E; Thogmartin, Wayne E; Erickson, Richard A; Norris, D Ryan

    2018-01-01

    Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance

  1. Spatial distribution of Corvidae in transformed landscapes of Zhytomyr region

    Directory of Open Access Journals (Sweden)

    A. V. Matsyura

    2016-03-01

    Full Text Available The spatial distribution and abundance of Corvidae species was studied in Zhytomyr region with a focus on rural and urban differences in the studied parameters. We selected Rook (Corvus frugilegus L., Western Jackdaw (C. monedula L., Hooded Crow (C. cornix L., Eurasian Magpie (Pica pica L., Eurasian Jay (Garrulus glandarius L., and Common Raven (Corvus corax L.. All observations were made during 2009–2012. During the study period some 38 survey paths of more than 8,000 km were surveyed in 21 settlements of Zhytomyr region, among them 13 were in Zhytomyr city. The aim of our study was to establish the number and density of Corvidae in different seasons in the settlements of Zhytomyr region along a rural-urban gradient. The average density of Rooks was 55.9 ind./km2. We also found a strong correlation between Rook density and the rural-urban gradient and observed that the number of Rooks wintering in cities significantly increased due to the influx from villages. The peak number of Rooks in villages was registered in the breeding and post-breeding season while in the cities it was high in winter and during the spring migration. The average density of Eurasian Magpie in the study area was 8.7 ind./km2 and had a weak correlation with the urban-rural gradient. The density of Eurasian Magpies in urban areas differs significantly only from the density of birds in villages with a population of ca. 1,000 people. The density of Magpies varied insignificantly within a narrow range during the three years of research, remaining relatively stable, which suggests that the species successfully adjusts to conditions in transformed landscapes. The urban-rural gradient significantly affects the density of Hooded Crows. The average density of birds in towns was 6.6 ind./km2. In breeding period the urban birds had a low density and rural crows, on the contrary, had a high density, the density of birds in the nesting period was greater than in autumn and winter

  2. Low Frequency Electrostatic Waves in Weakly Inhomogeneous Magnetoplasma Modeled by Lorentzian (kappa) Distributions

    National Research Council Canada - National Science Library

    Basu, Bamandas

    2008-01-01

    Linear dispersion relations for electrostatic waves in spatially inhomogeneous, current-carrying anisotropic plasma, where the equilibrium particle velocity distributions are modeled by various Lorentzian (kappa...

  3. Spatial Database Modeling for Indoor Navigation Systems

    Science.gov (United States)

    Gotlib, Dariusz; Gnat, Miłosz

    2013-12-01

    For many years, cartographers are involved in designing GIS and navigation systems. Most GIS applications use the outdoor data. Increasingly, similar applications are used inside buildings. Therefore it is important to find the proper model of indoor spatial database. The development of indoor navigation systems should utilize advanced teleinformation, geoinformatics, geodetic and cartographical knowledge. The authors present the fundamental requirements for the indoor data model for navigation purposes. Presenting some of the solutions adopted in the world they emphasize that navigation applications require specific data to present the navigation routes in the right way. There is presented original solution for indoor data model created by authors on the basis of BISDM model. Its purpose is to expand the opportunities for use in indoor navigation.

  4. Spatial Models and Networks of Living Systems

    DEFF Research Database (Denmark)

    Juul, Jeppe Søgaard

    with interactions defined by network topology. In this thesis I first describe three different biological models of ageing and cancer, in which spatial structure is important for the system dynamics. I then turn to describe characteristics of ecosystems consisting of three cyclically interacting species......When studying the dynamics of living systems, insight can often be gained by developing a mathematical model that can predict future behaviour of the system or help classify system characteristics. However, in living cells, organisms, and especially groups of interacting individuals, a large number...... of different factors influence the time development of the system. This often makes it challenging to construct a mathematical model from which to draw conclusions. One traditional way of capturing the dynamics in a mathematical model is to formulate a set of coupled differential equations for the essential...

  5. Dynamical quorum sensing and clustering dynamics in a population of spatially distributed active rotators

    Science.gov (United States)

    Sakaguchi, Hidetsugu; Maeyama, Satomi

    2013-02-01

    A model of clustering dynamics is proposed for a population of spatially distributed active rotators. A transition from excitable to oscillatory dynamics is induced by the increase of the local density of active rotators. It is interpreted as dynamical quorum sensing. In the oscillation regime, phase waves propagate without decay, which generates an effectively long-range interaction in the clustering dynamics. The clustering process becomes facilitated and only one dominant cluster appears rapidly as a result of the dynamical quorum sensing. An exact localized solution is found to a simplified model equation, and the competitive dynamics between two localized states is studied numerically.

  6. Evaluation of alkalinity spatial distribution in an up-flow fixed bed anaerobic digester.

    Science.gov (United States)

    Hmissi, Maha; Harmand, Jérôme; Alcaraz-Gonzalez, Victor; Shayeb, Hedi

    2018-02-01

    In this paper, an experimental study upon alkalinity and hydrodynamic behavior in an anaerobic up-flow fixed bed reactor for the treatment of tequila vinasses is presented. Measurements of volatile fatty acids, pH, alkalinity and bicarbonate were obtained at three sampling points in the reactor in the axial axis. Then, the spatial distribution of alkalinity is studied and discussed. Moreover, for further control process purposes, a hydrodynamic model based on the use of two interconnected two-steps reduced AM2 type models is proposed and its parameters are identified using experimental data.

  7. Investigating the spatial distribution and effects of nearshore topography on Acropora cervicornis abundance in Southeast Florida

    Directory of Open Access Journals (Sweden)

    Nicole L. D’Antonio

    2016-09-01

    Full Text Available Dense Acropora cervicornis aggregations, or patches, have been documented within nearshore habitats in Southeast Florida (SE FL despite close proximity to numerous anthropogenic stressors and subjection to frequent natural disturbance events. Limited information has been published concerning the distribution and abundance of A. cervicornis outside of these known dense patches. The first goal of this study was to conduct a spatially extensive and inclusive survey (9.78 km2 to determine whether A. cervicornis distribution in the nearshore habitat of SE FL was spatially uniform or clustered. The second goal was to investigate potential relationships between broad-scale seafloor topography and A. cervicornis abundance using high resolution bathymetric data. Acropora cervicornis was distributed throughout the study area, and the Getis-Ord Gi* statistic and Anselin Local Moran’s I spatial cluster analysis showed significant clustering along topographic features termed ridge crests. Significant clustering was further supported by the inverse distance weighted surface model. Ordinal logistic regression indicated 1 as distance from a ridge increases, odds of reduced A. cervicornis abundance increases; 2 as topographic elevation increases, odds of increased abundance increases; and 3 as mean depth increases, odds of increased abundance increases. This study provides detailed information on A. cervicornis distribution and abundance at a regional scale and supports modeling its distributions in similar habitats elsewhere throughout the western Atlantic and Caribbean. Acropora cervicornis is frequently observed and in areas an abundant species within the nearshore habitat along the SE FL portion of the Florida Reef Tract (FRT. This study provides a better understanding of local habitat associations thus facilitating appropriate management of the nearshore environment and species conservation. The portion of the FRT between Hillsboro and Port Everglades

  8. Spatial Economics Model Predicting Transport Volume

    Directory of Open Access Journals (Sweden)

    Lu Bo

    2016-10-01

    Full Text Available It is extremely important to predict the logistics requirements in a scientific and rational way. However, in recent years, the improvement effect on the prediction method is not very significant and the traditional statistical prediction method has the defects of low precision and poor interpretation of the prediction model, which cannot only guarantee the generalization ability of the prediction model theoretically, but also cannot explain the models effectively. Therefore, in combination with the theories of the spatial economics, industrial economics, and neo-classical economics, taking city of Zhuanghe as the research object, the study identifies the leading industry that can produce a large number of cargoes, and further predicts the static logistics generation of the Zhuanghe and hinterlands. By integrating various factors that can affect the regional logistics requirements, this study established a logistics requirements potential model from the aspect of spatial economic principles, and expanded the way of logistics requirements prediction from the single statistical principles to an new area of special and regional economics.

  9. A Computational Model of Spatial Development

    Science.gov (United States)

    Hiraki, Kazuo; Sashima, Akio; Phillips, Steven

    Psychological experiments on children's development of spatial knowledge suggest experience at self-locomotion with visual tracking as important factors. Yet, the mechanism underlying development is unknown. We propose a robot that learns to mentally track a target object (i.e., maintaining a representation of an object's position when outside the field-of-view) as a model for spatial development. Mental tracking is considered as prediction of an object's position given the previous environmental state and motor commands, and the current environment state resulting from movement. Following Jordan & Rumelhart's (1992) forward modeling architecture the system consists of two components: an inverse model of sensory input to desired motor commands; and a forward model of motor commands to desired sensory input (goals). The robot was tested on the `three cups' paradigm (where children are required to select the cup containing the hidden object under various movement conditions). Consistent with child development, without the capacity for self-locomotion the robot's errors are self-center based. When given the ability of self-locomotion the robot responds allocentrically.

  10. Spherical Process Models for Global Spatial Statistics

    KAUST Repository

    Jeong, Jaehong

    2017-11-28

    Statistical models used in geophysical, environmental, and climate science applications must reflect the curvature of the spatial domain in global data. Over the past few decades, statisticians have developed covariance models that capture the spatial and temporal behavior of these global data sets. Though the geodesic distance is the most natural metric for measuring distance on the surface of a sphere, mathematical limitations have compelled statisticians to use the chordal distance to compute the covariance matrix in many applications instead, which may cause physically unrealistic distortions. Therefore, covariance functions directly defined on a sphere using the geodesic distance are needed. We discuss the issues that arise when dealing with spherical data sets on a global scale and provide references to recent literature. We review the current approaches to building process models on spheres, including the differential operator, the stochastic partial differential equation, the kernel convolution, and the deformation approaches. We illustrate realizations obtained from Gaussian processes with different covariance structures and the use of isotropic and nonstationary covariance models through deformations and geographical indicators for global surface temperature data. To assess the suitability of each method, we compare their log-likelihood values and prediction scores, and we end with a discussion of related research problems.

  11. Latent spatial models and sampling design for landscape genetics

    Science.gov (United States)

    Hanks, Ephraim M.; Hooten, Mevin B.; Knick, Steven T.; Oyler-McCance, Sara J.; Fike, Jennifer A.; Cross, Todd B.; Schwartz, Michael K.

    2016-01-01

    We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial random effect to allow for spatial correlation between genetic observations. We illustrate how modern dimension reduction approaches to spatial statistics can allow for efficient computation in landscape genetic statistical models covering large spatial domains. We apply our approach to propose a retrospective spatial sampling design for greater sage-grouse (Centrocercus urophasianus) population genetics in the western United States.

  12. Unsupervised Posture Modeling Based on Spatial-Temporal Movement Features

    Science.gov (United States)

    Yan, Chunjuan

    Traditional posture modeling for human action recognition is based on silhouette segmentation, which is subject to the noise from illumination variation and posture occlusions and shadow interruptions. In this paper, we extract spatial temporal movement features from human actions and adopt unsupervised clustering method for salient posture learning. First, spatial-temporal interest points (STIPs) were extracted according to the properties of human movement, and then, histogram of gradient was built to describe the distribution of STIPs in each frame for a single pose. In addition, the training samples were clustered by non-supervised classification method. Moreover, the salient postures were modeled with GMM according to Expectation Maximization (EM) estimation. The experiment results proved that our method can effectively and accurately recognize human's action postures.

  13. Spatial distribution and socioeconomic context of tuberculosis in Rio de Janeiro, Brazil

    Directory of Open Access Journals (Sweden)

    Alessandra Gonçalves Lisbôa Pereira

    2015-01-01

    Full Text Available OBJECTIVE To analyze the spatial distribution of risk for tuberculosis and its socioeconomic determinants in the city of Rio de Janeiro, Brazil.METHODS An ecological study on the association between the mean incidence rate of tuberculosis from 2004 to 2006 and socioeconomic indicators of the Censo Demográfico (Demographic Census of 2000. The unit of analysis was the home district registered in the Sistema de Informação de Agravos de Notificação (Notifiable Diseases Information System of Rio de Janeiro, Southeastern Brazil. The rates were standardized by sex and age group, and smoothed by the empirical Bayes method. Spatial autocorrelation was evaluated by Moran’s I. Multiple linear regression models were studied and the appropriateness of incorporating the spatial component in modeling was evaluated.RESULTS We observed a higher risk of the disease in some neighborhoods of the port and north regions, as well as a high incidence in the slums of Rocinha and Vidigal, in the south region, and Cidade de Deus, in the west. The final model identified a positive association for the variables: percentage of permanent private households in which the head of the house earns three to five minimum wages; percentage of individual residents in the neighborhood; and percentage of people living in homes with more than two people per bedroom.CONCLUSIONS The spatial analysis identified areas of risk of tuberculosis incidence in the neighborhoods of the city of Rio de Janeiro and also found spatial dependence for the incidence of tuberculosis and some socioeconomic variables. However, the inclusion of the space component in the final model was not required during the modeling process.

  14. Spatial distribution and socioeconomic context of tuberculosis in Rio de Janeiro, Brazil.

    Science.gov (United States)

    Pereira, Alessandra Gonçalves Lisbôa; Medronho, Roberto de Andrade; Escosteguy, Claudia Caminha; Valencia, Luis Iván Ortiz; Magalhães, Mônica de Avelar Figueiredo Mafra

    2015-01-01

    OBJECTIVE To analyze the spatial distribution of risk for tuberculosis and its socioeconomic determinants in the city of Rio de Janeiro, Brazil. METHODS An ecological study on the association between the mean incidence rate of tuberculosis from 2004 to 2006 and socioeconomic indicators of the Censo Demográfico (Demographic Census) of 2000. The unit of analysis was the home district registered in the Sistema de Informação de Agravos de Notificação (Notifiable Diseases Information System) of Rio de Janeiro, Southeastern Brazil. The rates were standardized by sex and age group, and smoothed by the empirical Bayes method. Spatial autocorrelation was evaluated by Moran's I. Multiple linear regression models were studied and the appropriateness of incorporating the spatial component in modeling was evaluated. RESULTS We observed a higher risk of the disease in some neighborhoods of the port and north regions, as well as a high incidence in the slums of Rocinha and Vidigal, in the south region, and Cidade de Deus, in the west. The final model identified a positive association for the variables: percentage of permanent private households in which the head of the house earns three to five minimum wages; percentage of individual residents in the neighborhood; and percentage of people living in homes with more than two people per bedroom. CONCLUSIONS The spatial analysis identified areas of risk of tuberculosis incidence in the neighborhoods of the city of Rio de Janeiro and also found spatial dependence for the incidence of tuberculosis and some socioeconomic variables. However, the inclusion of the space component in the final model was not required during the modeling process.

  15. Spatial linear flows of finite length with nonuniform intensity distribution

    Directory of Open Access Journals (Sweden)

    Mikhaylov Ivan Evgrafovich

    2014-02-01

    Full Text Available Irrotational flows produced by spatial linear flows of finite length with different uneven lows of discharge over the flow length are represented in cylindrical coordinate system. Flows with the length 2a are placed in infinite space filled with ideal (inviscid fluid. In “А” variant discharge is fading linearly downward along the length of the flow. In “B” variant in upper half of the flow (length a discharge is fading linearly downward, in lower half of the flow discharge is fading linearly from the middle point to lower end. In “C” variant discharge of the flow is growing linearly from upper and lower ends to middle point.Equations for discharge distribution along the length of the flow are provided for each variant. Equations consist of two terms and include two dimensional parameters and current coordinate that allows integrating on flow length. Analytical expressions are derived for speed potential functions and flow speed components for flow speeds produced by analyzed flows. These analytical expressions consist of dimensional parameters of discharge distribution patterns along the length of the flow. Flow lines equation (meridional sections of flow surfaces for variants “A”, “B”, “C” is unsolvable in quadratures. Flow lines plotting is proposed to be made by finite difference method. Equations for flow line plotting are provided for each variant. Calculations of these equations show that the analyzed flows have the following flow lines: “A” has confocal hyperbolical curves, “B” and “C” have confocal hyperboles. Flow surfaces are confocal hyperboloids produced by rotation of these hyperboles about the axis passing through the flows. In “A” variant the space filled with fluid is separated by vividly horizontal flow surface in two parts. In upper part that includes the smaller part of the flow length flow lines are oriented downward, in lower part – upward. The equation defining coordinate of

  16. LEACHED SOILS IN SLOVENIA: PEDOLOGICAL PROPERTIES, SPATIAL DISTRIBUTION AND CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    Rok TURNIŠKI

    2018-04-01

    Full Text Available Eluvial-illuvial processes plays key role in pedogenesis, especially in the development of leached soils. As reported in Slovenian soil map 1 : 25.000 leached soils cover 2,3 % of Slovenian territory. They occur on different parent materials, mostly on flat relief preserved from erosion and colluvial processes. The aim of our study is the evaluation of their morpohological, physical and chemical properties, spatial distribution and dependency on soil forming factors, especially on parent material. Pedological properties are demonstrated according to analytical and descriptive data of 49 leached soils from the pedological base of Soil Information System of Slovenia. Obvious leaching processes are clearly recognized in almost all profiles of leached soils. Eluvial horizon in comparison to illuvial horizon has lower pH value, which is in average 4,4 and 4,6 for E and Bt horizon respectively, brighter color, lower base saturation (in average for 16,6 % and lower CEC (in average for 5,5 mmolc 100 g -1 soil. On average ratio of clay content between illuvial and eluvial horizon is 1,63. In the 75 % of all studied leached soils this ratio is above 1,38. After evaluation, according to WRB classification, an argic horizon is identified only in 40 soil profiles, while other 9 profiles do not match criteria of sufficient textural differentiation or there is not enough data to classify them. Detailed overview of the WRB criteria for argic horizons (cation exchange capacity of clay fraction and base saturation in argic horizons reveals that Luvisols and Alisols are the most widespread groups in Slovenia among leached soil. Against expectations based on different references, we do not determined Acrisols within Soil Map Database.

  17. The Spatial Distribution of Volcanic Events on Io in 2013-2015

    Science.gov (United States)

    de Kleer, Katherine R.; de Pater, Imke

    2015-11-01

    The spatial distribution of heat flow on Io is a key prediction of tidal heat dissipation models, and therefore provides an important constraint for understanding Io’s interior. However, the majority of our knowledge about eruption locations is derived from geological features tracing long time periods (e.g. Hamilton et al., 2013), and from activity during the Galileo era (e.g. Davies et al., 2015; Veeder et al., 2015).We report on new results from a campaign to image Io in the near-infrared with adaptive optics on the Keck and Gemini N telescopes. We observed Io on 93 nights between August 2013 and June 2015, detecting volcanic activity at dozens of hot spot locations. We present the spatial distribution of the observed eruption sites during this period, and compare this with the distributions inferred from past hot spot and patera locations by previous authors. We discuss the locations of eruptions of different magnitudes, including a preponderance of bright activity at latitudes polewards of 45 degrees in both hemispheres and an apparent spatial clustering of activity in the months following large eruptions. Finally, we address the durations of the detected eruptions, as well as connecting our findings to the EXCEED Mission’s observations of the Io plasma torus during the same time period.

  18. Modelling spatial density using continuous wavelet transforms

    Indian Academy of Sciences (India)

    Space debris; wavelets; Mexican hat; Laplace distribution; random search; parameter estimation. ... Author Affiliations. D Sudheer Reddy1 N Gopal Reddy2 A K Anilkumar3. Digital Mapping and Modelling Division, Advanced Data Processing Research Institute, Secunderabad 500 009, India; Department of Mathematics, ...

  19. The spatial distribution of pet dogs and pet cats on the island of Ireland.

    Science.gov (United States)

    Downes, Martin J; Clegg, Tracy A; Collins, Daniel M; McGrath, Guy; More, Simon J

    2011-06-10

    There is considerable international research regarding the link between human demographics and pet ownership. In several international studies, pet ownership was associated with household demographics including: the presence of children in the household, urban/rural location, level of education and age/family structure. What is lacking across all these studies, however, is an understanding of how these pets are spatially distributed throughout the regions under study. This paper describes the spatial distribution of pet dog and pet cat owning households on the island of Ireland. In 2006, there were an estimated 640,620 pet dog owning households and 215,542 pet cat owning households in Ireland. These estimates are derived from logistic regression modelling, based on household composition to determine pet dog ownership and the type of house to determine pet cat ownership. Results are presented using chloropleth maps. There is a higher density of pet dog owning households in the east of Ireland and in the cities than the west of Ireland and rural areas. However, in urban districts there are a lower proportion of households owning pet dogs than in rural districts. There are more households with cats in the urban areas, but the proportion of households with cats is greater in rural areas. The difference in spatial distribution of dog ownership is a reflection of a generally higher density of households in the east of Ireland and in major cities. The higher proportion of ownership in the west is understandable given the higher proportion of farmers and rural dwellings in this area. Spatial representation allows us to visualise the impact of human household distribution on the density of both pet dogs and pet cats on the island of Ireland. This information can be used when analysing risk of disease spread, for market research and for instigating veterinary care.

  20. The spatial distribution of pet dogs and pet cats on the island of Ireland

    Science.gov (United States)

    2011-01-01

    Background There is considerable international research regarding the link between human demographics and pet ownership. In several international studies, pet ownership was associated with household demographics including: the presence of children in the household, urban/rural location, level of education and age/family structure. What is lacking across all these studies, however, is an understanding of how these pets are spatially distributed throughout the regions under study. This paper describes the spatial distribution of pet dog and pet cat owning households on the island of Ireland. Results In 2006, there were an estimated 640,620 pet dog owning households and 215,542 pet cat owning households in Ireland. These estimates are derived from logistic regression modelling, based on household composition to determine pet dog ownership and the type of house to determine pet cat ownership. Results are presented using chloropleth maps. There is a higher density of pet dog owning households in the east of Ireland and in the cities than the west of Ireland and rural areas. However, in urban districts there are a lower proportion of households owning pet dogs than in rural districts. There are more households with cats in the urban areas, but the proportion of households with cats is greater in rural areas. Conclusions The difference in spatial distribution of dog ownership is a reflection of a generally higher density of households in the east of Ireland and in major cities. The higher proportion of ownership in the west is understandable given the higher proportion of farmers and rural dwellings in this area. Spatial representation allows us to visualise the impact of human household distribution on the density of both pet dogs and pet cats on the island of Ireland. This information can be used when analysing risk of disease spread, for market research and for instigating veterinary care. PMID:21663606

  1. The spatial distribution of pet dogs and pet cats on the island of Ireland

    Directory of Open Access Journals (Sweden)

    More Simon J

    2011-06-01

    Full Text Available Abstract Background There is considerable international research regarding the link between human demographics and pet ownership. In several international studies, pet ownership was associated with household demographics including: the presence of children in the household, urban/rural location, level of education and age/family structure. What is lacking across all these studies, however, is an understanding of how these pets are spatially distributed throughout the regions under study. This paper describes the spatial distribution of pet dog and pet cat owning households on the island of Ireland. Results In 2006, there were an estimated 640,620 pet dog owning households and 215,542 pet cat owning households in Ireland. These estimates are derived from logistic regression modelling, based on household composition to determine pet dog ownership and the type of house to determine pet cat ownership. Results are presented using chloropleth maps. There is a higher