WorldWideScience

Sample records for modelling spatially distributed

  1. Unleashing spatially distributed ecohydrology modeling using Big Data tools

    Science.gov (United States)

    Miles, B.; Idaszak, R.

    2015-12-01

    Physically based spatially distributed ecohydrology models are useful for answering science and management questions related to the hydrology and biogeochemistry of prairie, savanna, forested, as well as urbanized ecosystems. However, these models can produce hundreds of gigabytes of spatial output for a single model run over decadal time scales when run at regional spatial scales and moderate spatial resolutions (~100-km2+ at 30-m spatial resolution) or when run for small watersheds at high spatial resolutions (~1-km2 at 3-m spatial resolution). Numerical data formats such as HDF5 can store arbitrarily large datasets. However even in HPC environments, there are practical limits on the size of single files that can be stored and reliably backed up. Even when such large datasets can be stored, querying and analyzing these data can suffer from poor performance due to memory limitations and I/O bottlenecks, for example on single workstations where memory and bandwidth are limited, or in HPC environments where data are stored separately from computational nodes. The difficulty of storing and analyzing spatial data from ecohydrology models limits our ability to harness these powerful tools. Big Data tools such as distributed databases have the potential to surmount the data storage and analysis challenges inherent to large spatial datasets. Distributed databases solve these problems by storing data close to computational nodes while enabling horizontal scalability and fault tolerance. Here we present the architecture of and preliminary results from PatchDB, a distributed datastore for managing spatial output from the Regional Hydro-Ecological Simulation System (RHESSys). The initial version of PatchDB uses message queueing to asynchronously write RHESSys model output to an Apache Cassandra cluster. Once stored in the cluster, these data can be efficiently queried to quickly produce both spatial visualizations for a particular variable (e.g. maps and animations), as well

  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. 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)

  4. Spatial distribution

    DEFF Research Database (Denmark)

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

    2008-01-01

    , depending on the nature of intraspecific interactions between them: while the individuals of some species repel each other and partition the available area, others form groups of varying size, determined by the fitness of each group member. The spatial distribution pattern of individuals again strongly......Living organisms are distributed over the entire surface of the planet. The distribution of the individuals of each species is not random; on the contrary, they are strongly dependent on the biology and ecology of the species, and vary over different spatial scale. The structure of whole...... 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...

  5. 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.

  6. 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.

  7. Spatial Distribution of Hydrologic Ecosystem Service Estimates: Comparing Two Models

    Science.gov (United States)

    Dennedy-Frank, P. J.; Ghile, Y.; Gorelick, S.; Logsdon, R. A.; Chaubey, I.; Ziv, G.

    2014-12-01

    We compare estimates of the spatial distribution of water quantity provided (annual water yield) from two ecohydrologic models: the widely-used Soil and Water Assessment Tool (SWAT) and the much simpler water models from the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) toolbox. These two models differ significantly in terms of complexity, timescale of operation, effort, and data required for calibration, and so are often used in different management contexts. We compare two study sites in the US: the Wildcat Creek Watershed (2083 km2) in Indiana, a largely agricultural watershed in a cold aseasonal climate, and the Upper Upatoi Creek Watershed (876 km2) in Georgia, a mostly forested watershed in a temperate aseasonal climate. We evaluate (1) quantitative estimates of water yield to explore how well each model represents this process, and (2) ranked estimates of water yield to indicate how useful the models are for management purposes where other social and financial factors may play significant roles. The SWAT and InVEST models provide very similar estimates of the water yield of individual subbasins in the Wildcat Creek Watershed (Pearson r = 0.92, slope = 0.89), and a similar ranking of the relative water yield of those subbasins (Spearman r = 0.86). However, the two models provide relatively different estimates of the water yield of individual subbasins in the Upper Upatoi Watershed (Pearson r = 0.25, slope = 0.14), and very different ranking of the relative water yield of those subbasins (Spearman r = -0.10). The Upper Upatoi watershed has a significant baseflow contribution due to its sandy, well-drained soils. InVEST's simple seasonality terms, which assume no change in storage over the time of the model run, may not accurately estimate water yield processes when baseflow provides such a strong contribution. Our results suggest that InVEST users take care in situations where storage changes are significant.

  8. 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

    functionality by statistically modelling the distribution of the synaptic vesicles in two groups of rats: a control group subjected to sham stress and a stressed group subjected to a single acute foot-shock (FS)-stress episode. We hypothesize that the synaptic vesicles have different spatial distributions...... in the two groups. The spatial distributions are modelled using spatial point process models with an inhomogeneous conditional intensity and repulsive pairwise interactions. Our results verify the hypothesis that the two groups have different spatial distributions....

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

    DEFF Research Database (Denmark)

    Plejdrup, Marlene Schmidt; Gyldenkærne, Steen

    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...... 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...

  10. Thematic and spatial resolutions affect model-based predictions of tree species distribution.

    Science.gov (United States)

    Liang, Yu; He, Hong S; Fraser, Jacob S; Wu, ZhiWei

    2013-01-01

    Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.

  11. 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

    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......, 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...... with discrete time processes in the setting of the present paper as well as other spatial-temporal situations....

  12. Real-time distribution of pelagic fish: combining hydroacoustics, GIS and spatial modelling at a fine spatial scale.

    Science.gov (United States)

    Muška, Milan; Tušer, Michal; Frouzová, Jaroslava; Mrkvička, Tomáš; Ricard, Daniel; Seďa, Jaromír; Morelli, Federico; Kubečka, Jan

    2018-03-29

    Understanding spatial distribution of organisms in heterogeneous environment remains one of the chief issues in ecology. Spatial organization of freshwater fish was investigated predominantly on large-scale, neglecting important local conditions and ecological processes. However, small-scale processes are of an essential importance for individual habitat preferences and hence structuring trophic cascades and species coexistence. In this work, we analysed the real-time spatial distribution of pelagic freshwater fish in the Římov Reservoir (Czechia) observed by hydroacoustics in relation to important environmental predictors during 48 hours at 3-h interval. Effect of diurnal cycle was revealed of highest significance in all spatial models with inverse trends between fish distribution and predictors in day and night in general. Our findings highlighted daytime pelagic fish distribution as highly aggregated, with general fish preferences for central, deep and highly illuminated areas, whereas nighttime distribution was more disperse and fish preferred nearshore steep sloped areas with higher depth. This turnover suggests prominent movements of significant part of fish assemblage between pelagic and nearshore areas on a diel basis. In conclusion, hydroacoustics, GIS and spatial modelling proved as valuable tool for predicting local fish distribution and elucidate its drivers, which has far reaching implications for understanding freshwater ecosystem functioning.

  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. Spatial regression methods capture prediction uncertainty in species distribution model projections through time

    Science.gov (United States)

    Alan K. Swanson; Solomon Z. Dobrowski; Andrew O. Finley; James H. Thorne; Michael K. Schwartz

    2013-01-01

    The uncertainty associated with species distribution model (SDM) projections is poorly characterized, despite its potential value to decision makers. Error estimates from most modelling techniques have been shown to be biased due to their failure to account for spatial autocorrelation (SAC) of residual error. Generalized linear mixed models (GLMM) have the ability to...

  16. 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...... 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...... 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...

  17. Benefits of incorporating spatial organisation of catchments for a semi-distributed hydrological model

    Science.gov (United States)

    Schumann, Andreas; Oppel, Henning

    2017-04-01

    To represent the hydrological behaviour of catchments a model should reproduce/reflect the hydrologically most relevant catchment characteristics. These are heterogeneously distributed within a watershed but often interrelated and subject of a certain spatial organisation. Since common models are mostly based on fundamental assumptions about hydrological processes, the reduction of variance of catchment properties as well as the incorporation of the spatial organisation of the catchment is desirable. We have developed a method that combines the idea of the width-function used for determination of the geomorphologic unit hydrograph with information about soil or topography. With this method we are able to assess the spatial organisation of selected catchment characteristics. An algorithm was developed that structures a watershed into sub-basins and other spatial units to minimise its heterogeneity. The outcomes of this algorithm are used for the spatial setup of a semi-distributed model. Since the spatial organisation of a catchment is not bound to a single characteristic, we have to embed information of multiple catchment properties. For this purpose we applied a fuzzy-based method to combine the spatial setup for multiple single characteristics into a union, optimal spatial differentiation. Utilizing this method, we are able to propose a spatial structure for a semi-distributed hydrological model, comprising the definition of sub-basins and a zonal classification within each sub-basin. Besides the improved spatial structuring, the performed analysis ameliorates modelling in another way. The spatial variability of catchment characteristics, which is considered by a minimum of heterogeneity in the zones, can be considered in a parameter constrained calibration scheme in a case study both options were used to explore the benefits of incorporating the spatial organisation and derived parameter constraints for the parametrisation of a HBV-96 model. We use two benchmark

  18. 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

  19. 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

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

    Science.gov (United States)

    Redding, David W; Lucas, Tim C D; Blackburn, Tim M; Jones, Kate E

    2017-01-01

    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 for spatial

  1. Inferring the flood frequency distribution for an ungauged basin using a spatially distributed rainfall-runoff model

    Directory of Open Access Journals (Sweden)

    G. Moretti

    2008-08-01

    Full Text Available The estimation of the peak river flow for ungauged river sections is a topical issue in applied hydrology. Spatially distributed rainfall-runoff models can be a useful tool to this end, since they are potentially able to simulate the river flow at any location of the watershed drainage network. However, it is not fully clear to what extent these models can provide reliable simulations over a wide range of spatial scales. This issue is investigated here by applying a spatially distributed, continuous simulation rainfall-runoff model to infer the flood frequency distribution of the Riarbero River. This is an ungauged mountain creek located in northern Italy, whose drainage area is 17 km2. The hydrological model is first calibrated by using a 1-year record of hourly meteorological data and river flows observed at the outlet of the 1294 km2 wide Secchia River basin, of which the Riarbero is a tributary. The model is then validated by performing a 100-year long simulation of synthetic river flow data, which allowed us to compare the simulated and observed flood frequency distributions at the Secchia River outlet and the internal cross river section of Cavola Bridge, where the basin area is 337 km2. Finally, another simulation of hourly river flows was performed by referring to the outlet of the Riarbero River, therefore allowing us to estimate the related flood frequency distribution. The results were validated by using estimates of peak river flow obtained by applying hydrological similarity principles and a regional method. The results show that the flood flow estimated through the application of the distributed model is consistent with the estimate provided by the regional procedure as well as the behaviors of the river banks. Conversely, the method based on hydrological similarity delivers an estimate that seems to be not as reliable. The analysis highlights interesting perspectives for the application of

  2. Incorporating spatial autocorrelation into species distribution models alters forecasts of climate-mediated range shifts.

    Science.gov (United States)

    Crase, Beth; Liedloff, Adam; Vesk, Peter A; Fukuda, Yusuke; Wintle, Brendan A

    2014-08-01

    Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad-scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a known autocorrelation structure, and to field observations of three mangrove communities from northern Australia displaying strong spatial autocorrelation. Three modeling approaches were implemented: environment-only models (most frequently applied in species' range forecasts), and two approaches that incorporate SA; autologistic models and residuals autocovariate (RAC) models. Differences in forecasts among modeling approaches and climate scenarios were quantified. While all model predictions at the current time closely matched that of the actual current distribution of the mangrove communities, under the climate change scenarios environment-only models forecast substantially greater range shifts than models incorporating SA. Furthermore, the magnitude of these differences intensified with increasing increments of climate change across the scenarios. When models do not account for SA, forecasts of species' range shifts indicate more extreme impacts of climate change, compared to models that explicitly account for SA. Therefore, where biological or population processes induce substantial autocorrelation in the distribution of organisms, and this is not modeled, model predictions will be inaccurate. These results have global importance for conservation efforts as inaccurate

  3. Comparison of alternative spatial resolutions in the application of a spatially distributed biogeochemical model over complex terrain

    Science.gov (United States)

    Turner, D.P.; Dodson, R.; Marks, D.

    1996-01-01

    Spatially distributed biogeochemical models may be applied over grids at a range of spatial resolutions, however, evaluation of potential errors and loss of information at relatively coarse resolutions is rare. In this study, a georeferenced database at the 1-km spatial resolution was developed to initialize and drive a process-based model (Forest-BGC) of water and carbon balance over a gridded 54976 km2 area covering two river basins in mountainous western Oregon. Corresponding data sets were also prepared at 10-km and 50-km spatial resolutions using commonly employed aggregation schemes. Estimates were made at each grid cell for climate variables including daily solar radiation, air temperature, humidity, and precipitation. The topographic structure, water holding capacity, vegetation type and leaf area index were likewise estimated for initial conditions. The daily time series for the climatic drivers was developed from interpolations of meteorological station data for the water year 1990 (1 October 1989-30 September 1990). Model outputs at the 1-km resolution showed good agreement with observed patterns in runoff and productivity. The ranges for model inputs at the 10-km and 50-km resolutions tended to contract because of the smoothed topography. Estimates for mean evapotranspiration and runoff were relatively insensitive to changing the spatial resolution of the grid whereas estimates of mean annual net primary production varied by 11%. The designation of a vegetation type and leaf area at the 50-km resolution often subsumed significant heterogeneity in vegetation, and this factor accounted for much of the difference in the mean values for the carbon flux variables. Although area wide means for model outputs were generally similar across resolutions, difference maps often revealed large areas of disagreement. Relatively high spatial resolution analyses of biogeochemical cycling are desirable from several perspectives and may be particularly important in the

  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. Modelling the potential spatial distribution of mosquito species using three different techniques

    NARCIS (Netherlands)

    Cianci, D.; Hartemink, N.; Ibáñez-Justicia, A.

    2015-01-01

    Background: Models for the spatial distribution of vector species are important tools in the assessment of the risk of establishment and subsequent spread of vector-borne diseases. The aims of this study are to define the environmental conditions suitable for several mosquito species through species

  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 the spatial distribution of Fasciola hepatica in dairy cattle in Europe

    Directory of Open Access Journals (Sweden)

    Els Ducheyne

    2015-03-01

    Full Text Available A harmonized sampling approach in combination with spatial modelling is required to update current knowledge of fasciolosis in dairy cattle in Europe. Within the scope of the EU project GLOWORM, samples from 3,359 randomly selected farms in 849 municipalities in Belgium, Germany, Ireland, Poland and Sweden were collected and their infection status assessed using an indirect bulk tank milk (BTM enzyme-linked immunosorbent assay (ELISA. Dairy farms were considered exposed when the optical density ratio (ODR exceeded the 0.3 cut-off. Two ensemble-modelling techniques, Random Forests (RF and Boosted Regression Trees (BRT, were used to obtain the spatial distribution of the probability of exposure to Fasciola hepatica using remotely sensed environmental variables (1-km spatial resolution and interpolated values from meteorological stations as predictors. The median ODRs amounted to 0.31, 0.12, 0.54, 0.25 and 0.44 for Belgium, Germany, Ireland, Poland and southern Sweden, respectively. Using the 0.3 threshold, 571 municipalities were categorized as positive and 429 as negative. RF was seen as capable of predicting the spatial distribution of exposure with an area under the receiver operation characteristic (ROC curve (AUC of 0.83 (0.96 for BRT. Both models identified rainfall and temperature as the most important factors for probability of exposure. Areas of high and low exposure were identified by both models, with BRT better at discriminating between low-probability and high-probability exposure; this model may therefore be more useful in practise. Given a harmonized sampling strategy, it should be possible to generate robust spatial models for fasciolosis in dairy cattle in Europe to be used as input for temporal models and for the detection of deviations in baseline probability. Further research is required for model output in areas outside the eco-climatic range investigated.

  13. Development of a spatially-distributed hydroecological model to simulate cottonwood seedling recruitment along rivers.

    Science.gov (United States)

    Benjankar, Rohan; Burke, Michael; Yager, Elowyn; Tonina, Daniele; Egger, Gregory; Rood, Stewart B; Merz, Norm

    2014-12-01

    Dam operations have altered flood and flow patterns and prevented successful cottonwood seedling recruitment along many rivers. To guide reservoir flow releases to meet cottonwood recruitment needs, we developed a spatially-distributed, GIS-based model that analyzes the hydrophysical requirements for cottonwood recruitment. These requirements are indicated by five physical parameters: (1) annual peak flow timing relative to the interval of seed dispersal, (2) shear stress, which characterizes disturbance, (3) local stage recession after seedling recruitment, (4) recruitment elevation above base flow stage, and (5) duration of winter flooding, which may contribute to seedling mortality. The model categorizes the potential for cottonwood recruitment in four classes and attributes a suitability value at each individual spatial location. The model accuracy was estimated with an error matrix analysis by comparing simulated and field-observed recruitment success. The overall accuracies of this Spatially-Distributed Cottonwood Recruitment model were 47% for a braided reach and 68% for a meander reach along the Kootenai River in Idaho, USA. Model accuracies increased to 64% and 72%, respectively, when fewer favorability classes were considered. The model predicted areas of similarly favorable recruitment potential for 1997 and 2006, two recent years with successful cottonwood recruitment. This model should provide a useful tool to quantify impacts of human activities and climatic variability on cottonwood recruitment, and to prescribe instream flow regimes for the conservation and restoration of riparian woodlands. Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. 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)

  15. 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.

  16. 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.

  17. Spatially Distributed, Coupled Modeling of Plant Growth, Nitrogen and Water Fluxes in an Alpine Catchment

    Science.gov (United States)

    Schneider, K.

    2001-12-01

    Carbon, water and nitrogen fluxes are closely coupled. They interact and have many feedbacks. Human interference, in particular through land use management and global change strongly modifies these fluxes. Increasing demands and conflicting interests result in an increasing need for regulation targeting different aspects of the system. Without being their main target, many of these measures directly affect water quantity, quality and availability. Improved management and planning of our water resources requires the development of integrated tools, in particular since interactions of the involved environmental and social systems often lead to unexpected or adverse results. To investigate the effect of plant growth, land use management and global change on water fluxes and quality, the PROcess oriented Modular EnvironmenT and Vegetation Model (PROMET-V) was developed. PROMET-V models the spatial patterns and temporal course of water, carbon and nitrogen fluxes using process oriented and mechanistic model components. The hydrological model is based on the Penman-Monteith approach, it uses a plant-physiological model to calculate the canopy conductance, and a multi-layer soil water model. Plant growth for different vegetation is modelled by calculating canopy photosynthesis, respiration, phenology and allocation. Plant growth and water fluxes are coupled directly through photosynthesis and transpiration. Many indirect feedbacks and interactions occur due to their mutual dependency upon leaf area, root distribution, water and nutrient availability for instance. PROMET-V calculates nitrogen fluxes and transformations. The time step used depends upon the modelled process and varies from 1 hour to 1 day. The kernel model is integrated in a raster GIS system for spatially distributed modelling. PROMET-V was tested in a pre-alpine landscape (Ammer river, 709 km**2, located in Southern Germany) which is characterized by small scale spatial heterogeneities of climate, soil and

  18. 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

  19. 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.

  20. 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

  1. Constraining Distributed Catchment Models by Incorporating Perceptual Understanding of Spatial Hydrologic Behaviour

    Science.gov (United States)

    Hutton, Christopher; Wagener, Thorsten; Freer, Jim; Han, Dawei

    2016-04-01

    Distributed models offer the potential to resolve catchment systems in more detail, and therefore simulate the hydrological impacts of spatial changes in catchment forcing (e.g. landscape change). Such models tend to contain a large number of poorly defined and spatially varying model parameters which are therefore computationally expensive to calibrate. Insufficient data can result in model parameter and structural equifinality, particularly when calibration is reliant on catchment outlet discharge behaviour alone. Evaluating spatial patterns of internal hydrological behaviour has the potential to reveal simulations that, whilst consistent with measured outlet discharge, are qualitatively dissimilar to our perceptual understanding of how the system should behave. We argue that such understanding, which may be derived from stakeholder knowledge across different catchments for certain process dynamics, is a valuable source of information to help reject non-behavioural models, and therefore identify feasible model structures and parameters. The challenge, however, is to convert different sources of often qualitative and/or semi-qualitative information into robust quantitative constraints of model states and fluxes, and combine these sources of information together to reject models within an efficient calibration framework. Here we present the development of a framework to incorporate different sources of data to efficiently calibrate distributed catchment models. For each source of information, an interval or inequality is used to define the behaviour of the catchment system. These intervals are then combined to produce a hyper-volume in state space, which is used to identify behavioural models. We apply the methodology to calibrate the Penn State Integrated Hydrological Model (PIHM) at the Wye catchment, Plynlimon, UK. Outlet discharge behaviour is successfully simulated when perceptual understanding of relative groundwater levels between lowland peat, upland peat

  2. SPATIAL AND SPECTRAL MODELING OF THE GAMMA-RAY DISTRIBUTION IN THE LARGE MAGELLANIC CLOUD

    Energy Technology Data Exchange (ETDEWEB)

    Foreman, Gary; Chu, You-Hua; Gruendl, Robert; Fields, Brian; Ricker, Paul [Department of Astronomy, University of Illinois, 1002 W. Green St., Urbana, IL 61801 (United States); Hughes, Annie, E-mail: gforema2@illinois.edu [Max-Planck-Institut für Astronomie, Königstuhl 17, D-69117 Heidelberg (Germany)

    2015-07-20

    We perform spatial and spectral analyses of the LMC gamma-ray emission collected over 66 months by the Fermi Gamma-ray Space Telescope. In our spatial analysis, we model the LMC cosmic-ray distribution and gamma-ray production using observed maps of the LMC interstellar medium, star formation history, interstellar radiation field, and synchrotron emission. We use bootstrapping of the data to quantify the robustness of spatial model performance. We model the LMC gamma-ray spectrum using fitting functions derived from the physics of π{sup 0} decay, Bremsstrahlung, and inverse Compton scattering. We find the integrated gamma-ray flux of the LMC from 200 MeV to 20 GeV to be 1.37 ± 0.02 × 10{sup −7} ph cm{sup −2} s{sup −1}, of which we attribute about 6% to inverse Compton scattering and 44% to Bremsstrahlung. From our work, we conclude that the spectral index of the LMC cosmic-ray proton population is 2.4 ± 0.2, and we find that cosmic-ray energy loss through gamma-ray production is concentrated within a few 100 pc of acceleration sites. Assuming cosmic-ray energy equipartition with magnetic fields, we estimate LMC cosmic rays encounter an average magnetic field strength ∼3 μG.

  3. Assessing modelled spatial distributions of ice water path using satellite data

    Science.gov (United States)

    Eliasson, S.; Buehler, S. A.; Milz, M.; Eriksson, P.; John, V. O.

    2010-05-01

    The climate models used in the IPCC AR4 show large differences in monthly mean cloud ice. The most valuable source of information that can be used to potentially constrain the models is global satellite data. For this, the data sets must be long enough to capture the inter-annual variability of Ice Water Path (IWP). PATMOS-x was used together with ISCCP for the annual cycle evaluation in Fig. 7 while ECHAM-5 was used for the correlation with other models in Table 3. A clear distinction between ice categories in satellite retrievals, as desired from a model point of view, is currently impossible. However, long-term satellite data sets may still be used to indicate the climatology of IWP spatial distribution. We evaluated satellite data sets from CloudSat, PATMOS-x, ISCCP, MODIS and MSPPS in terms of monthly mean IWP, to determine which data sets can be used to evaluate the climate models. IWP data from CloudSat cloud profiling radar provides the most advanced data set on clouds. As CloudSat data are too short to evaluate the model data directly, it was mainly used here to evaluate IWP from the other satellite data sets. ISCCP and MSPPS were shown to have comparatively low IWP values. ISCCP shows particularly low values in the tropics, while MSPPS has particularly low values outside the tropics. MODIS and PATMOS-x were in closest agreement with CloudSat in terms of magnitude and spatial distribution, with MODIS being the best of the two. As PATMOS-x extends over more than 25 years and is in fairly close agreement with CloudSat, it was chosen as the reference data set for the model evaluation. In general there are large discrepancies between the individual climate models, and all of the models show problems in reproducing the observed spatial distribution of cloud-ice. Comparisons consistently showed that ECHAM-5 is the GCM from IPCC AR4 closest to satellite observations.

  4. Spatial Structure of Cities and Distribution of Retail Sales - Analysis based on a Potential NEG Model (Japanese)

    OpenAIRE

    NAKAMURA Ryohei; TAKATSUKA Hajime

    2009-01-01

    This paper aims to estimate the retail sales turnover in cities based on a potential New Economic Geography (NEG) model, addressing how (the distribution of) sales turnover is explained by the spatial structure of cities. This also takes into account the population distribution, by treating the spatial distribution of population and retail sales turnover in the cities by district and street (cho and chome) data. The cities covered are prefectural cities excluding government ordinance cities l...

  5. Modeling of Subsurface Lagrangian Sensor Swarms for Spatially Distributed Current Measurements in High Energy Coastal Environments

    Science.gov (United States)

    Harrison, T. W.; Polagye, B. L.

    2016-02-01

    Coastal ecosystems are characterized by spatially and temporally varying hydrodynamics. In marine renewable energy applications, these variations strongly influence project economics and in oceanographic studies, they impact accuracy of biological transport and pollutant dispersion models. While stationary point or profile measurements are relatively straight forward, spatial representativeness of point measurements can be poor due to strong gradients. Moving platforms, such as AUVs or surface vessels, offer better coverage, but suffer from energetic constraints (AUVs) and resolvable scales (vessels). A system of sub-surface, drifting sensor packages is being developed to provide spatially distributed, synoptic data sets of coastal hydrodynamics with meter-scale resolution over a regional extent of a kilometer. Computational investigation has informed system parameters such as drifter size and shape, necessary position accuracy, number of drifters, and deployment methods. A hydrodynamic domain with complex flow features was created using a computational fluid dynamics code. A simple model of drifter dynamics propagate the drifters through the domain in post-processing. System parameters are evaluated relative to their ability to accurately recreate domain hydrodynamics. Implications of these results for an inexpensive, depth-controlled Lagrangian drifter system is presented.

  6. 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)

  7. 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

  8. 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

  9. 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

  10. Modelling climate change impact on the spatial distribution of fresh water snails hosting trematodes in Zimbabwe.

    Science.gov (United States)

    Pedersen, Ulrik B; Stendel, Martin; Midzi, Nicholas; Mduluza, Takafira; Soko, White; Stensgaard, Anna-Sofie; Vennervald, Birgitte J; Mukaratirwa, Samson; Kristensen, Thomas K

    2014-12-12

    Freshwater snails are intermediate hosts for a number of trematodes of which some are of medical and veterinary importance. The trematodes rely on specific species of snails to complete their life cycle; hence the ecology of the snails is a key element in transmission of the parasites. More than 200 million people are infected with schistosomes of which 95% live in sub-Saharan Africa and many more are living in areas where transmission is on-going. Human infection with the Fasciola parasite, usually considered more of veterinary concern, has recently been recognised as a human health problem. Many countries have implemented health programmes to reduce morbidity and prevalence of schistosomiasis, and control programmes to mitigate food-borne fascioliasis. As these programmes are resource demanding, baseline information on disease prevalence and distribution becomes of great importance. Such information can be made available and put into practice through maps depicting spatial distribution of the intermediate snail hosts. A biology driven model for the freshwater snails Bulinus globosus, Biomphalaria pfeifferi and Lymnaea natalensis was used to make predictions of snail habitat suitability by including potential underlying environmental and climatic drivers. The snail observation data originated from a nationwide survey in Zimbabwe and the prediction model was parameterised with a high resolution Regional Climate Model. Georeferenced prevalence data on urinary and intestinal schistosomiasis and fascioliasis was used to calibrate the snail habitat suitability predictions to produce binary maps of snail presence and absence. Predicted snail habitat suitability across Zimbabwe, as well as the spatial distribution of snails, is reported for three time slices representative for present (1980-1999) and future climate (2046-2065 and 2080-2099). It is shown from the current study that snail habitat suitability is highly variable in Zimbabwe, with distinct high- and low

  11. A three-dimensional point process model for the spatial distribution of disease occurrence in relation to an exposure source

    DEFF Research Database (Denmark)

    Grell, Kathrine; Diggle, Peter J; Frederiksen, Kirsten

    2015-01-01

    We study methods for how to include the spatial distribution of tumours when investigating the relation between brain tumours and the exposure from radio frequency electromagnetic fields caused by mobile phone use. Our suggested point process model is adapted from studies investigating spatial...... the Interphone Study, a large multinational case-control study on the association between brain tumours and mobile phone use....

  12. Spatial modelling of arsenic distribution and human health effects in Lake Victoria basin, Tanzania

    Science.gov (United States)

    Ijumulana, Julian; Mtalo, Felix; Bhattacharya, Prosun

    2016-04-01

    Increasing incidences of naturally occurring geogenic pollutants in drinking water sources and associated human health risks are the two major challenges requiring detailed knowledge to support decision making process at various levels. The presence, location and extent of environmental contamination is needed towards developing mitigation measures to achieve required standards. In this study we are developing a GIS-based model to detect and predict drinking water pollutants at the identified hotspots and monitor its variation in space. In addition, the mobility of pollutants within the affected region needs to be evaluated using topographic and hydrogeological data. Based on these geospatial data on contaminant distribution, spatial relationship of As and F contamination and reported human health effects such as dental caries, dental fluorosis, skeletal fluorosis and bone crippling, skin and other cancers etc. can be modeled for potential interventions for safe drinking water supplies.

  13. 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.

  14. Modelling the spatial distribution of the nuisance mosquito species Anopheles plumbeus (Diptera: Culicidae) in the Netherlands.

    Science.gov (United States)

    Ibañez-Justicia, Adolfo; Cianci, Daniela

    2015-05-01

    Landscape modifications, urbanization or changes of use of rural-agricultural areas can create more favourable conditions for certain mosquito species and therefore indirectly cause nuisance problems for humans. This could potentially result in mosquito-borne disease outbreaks when the nuisance is caused by mosquito species that can transmit pathogens. Anopheles plumbeus is a nuisance mosquito species and a potential malaria vector. It is one of the most frequently observed species in the Netherlands. Information on the distribution of this species is essential for risk assessments. The purpose of the study was to investigate the potential spatial distribution of An. plumbeus in the Netherlands. Random forest models were used to link the occurrence and the abundance of An. plumbeus with environmental features and to produce distribution maps in the Netherlands. Mosquito data were collected using a cross-sectional study design in the Netherlands, from April to October 2010-2013. The environmental data were obtained from satellite imagery and weather stations. Statistical measures (accuracy for the occurrence model and mean squared error for the abundance model) were used to evaluate the models performance. The models were externally validated. The maps show that forested areas (centre of the Netherlands) and the east of the country were predicted as suitable for An. plumbeus. In particular high suitability and high abundance was predicted in the south-eastern provinces Limburg and North Brabant. Elevation, precipitation, day and night temperature and vegetation indices were important predictors for calculating the probability of occurrence for An. plumbeus. The probability of occurrence, vegetation indices and precipitation were important for predicting its abundance. The AUC value was 0.73 and the error in the validation was 0.29; the mean squared error value was 0.12. The areas identified by the model as suitable and with high abundance of An. plumbeus, are

  15. Accounting for Forest Harvest and Wildfire in a Spatially-distributed Carbon Cycle Process Model

    Science.gov (United States)

    Turner, D. P.; Ritts, W.; Kennedy, R. E.; Yang, Z.; Law, B. E.

    2009-12-01

    Forests are subject to natural disturbances in the form of wildfire, as well as management-related disturbances in the form of timber harvest. These disturbance events have strong impacts on local and regional carbon budgets, but quantifying the associated carbon fluxes remains challenging. The ORCA Project aims to quantify regional net ecosystem production (NEP) and net biome production (NBP) in Oregon, California, and Washington, and we have adopted an integrated approach based on Landsat imagery and ecosystem modeling. To account for stand-level carbon fluxes, the Biome-BGC model has been adapted to simulate multiple severities of fire and harvest. New variables include snags, direct fire emissions, and harvest removals. New parameters include fire-intensity-specific combustion factors for each carbon pool (based on field measurements) and proportional removal rates for harvest events. To quantify regional fluxes, the model is applied in a spatially-distributed mode over the domain of interest, with disturbance history derived from a time series of Landsat images. In stand-level simulations, the post disturbance transition from negative (source) to positive (sink) NEP is delayed approximately a decade in the case of high severity fire compared to harvest. Simulated direct pyrogenic emissions range from 11 to 25 % of total non-soil ecosystem carbon. In spatial mode application over Oregon and California, the sum of annual pyrogenic emissions and harvest removals was generally less that half of total NEP, resulting in significant carbon sequestration on the land base. Spatially and temporally explicit simulation of disturbance-related carbon fluxes will contribute to our ability to evaluate effects of management on regional carbon flux, and in our ability to assess potential biospheric feedbacks to climate change mediated by changing disturbance regimes.

  16. [Prediction and spatial distribution of recruitment trees of natural secondary forest based on geographically weighted Poisson model].

    Science.gov (United States)

    Zhang, Ling Yu; Liu, Zhao Gang

    2017-12-01

    Based on the data collected from 108 permanent plots of the forest resources survey in Maoershan Experimental Forest Farm during 2004-2016, this study investigated the spatial distribution of recruitment trees in natural secondary forest by global Poisson regression and geographically weighted Poisson regression (GWPR) with four bandwidths of 2.5, 5, 10 and 15 km. The simulation effects of the 5 regressions and the factors influencing the recruitment trees in stands were analyzed, a description was given to the spatial autocorrelation of the regression residuals on global and local levels using Moran's I. The results showed that the spatial distribution of the number of natural secondary forest recruitment was significantly influenced by stands and topographic factors, especially average DBH. The GWPR model with small scale (2.5 km) had high accuracy of model fitting, a large range of model parameter estimates was generated, and the localized spatial distribution effect of the model parameters was obtained. The GWPR model at small scale (2.5 and 5 km) had produced a small range of model residuals, and the stability of the model was improved. The global spatial auto-correlation of the GWPR model residual at the small scale (2.5 km) was the lowe-st, and the local spatial auto-correlation was significantly reduced, in which an ideal spatial distribution pattern of small clusters with different observations was formed. The local model at small scale (2.5 km) was much better than the global model in the simulation effect on the spatial distribution of recruitment tree number.

  17. 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.

  18. 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

  19. 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...

  20. 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.

  1. 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

  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. Determinants of the geographical distribution of endemic giardiasis in Ontario, Canada: a spatial modelling approach.

    Science.gov (United States)

    Odoi, A; Martin, S W; Michel, P; Holt, J; Middleton, D; Wilson, J

    2004-10-01

    Giardiasis surveillance data as well as drinking water, socioeconomic and land-use data were used in spatial regression models to investigate determinants of the geographic distribution of endemic giardiasis in southern Ontario. Higher giardiasis rates were observed in areas using surface water [rate ratio (RR) 2.36, 95 % CI 1.38-4.05] and in rural areas (RR 1.79, 95 % CI 1.32-2.37). Lower rates were observed in areas using filtered water (RR 0.55, 95 % CI 0.42-0.94) and in those with high median income (RR 0.62, 95 % CI 0.42-0.92). Chlorination of drinking water, cattle density and intensity of manure application on farmland were not significant determinants. The study shows that waterborne transmission plays an important role in giardiasis distribution in southern Ontario and that well-collected routine surveillance data could be useful for investigation of disease determinants and identification of high-risk communities. This information is useful in guiding decisions on control strategies.

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

    DEFF Research Database (Denmark)

    Lewy, Peter; Kristensen, Kasper

    2009-01-01

    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...

  5. 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

  6. 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

  7. Inverse modelling of fluvial sediment connectivity identifies characteristics and spatial distribution of sediment sources in a large river network.

    Science.gov (United States)

    Schmitt, R. J. P.; Bizzi, S.; Kondolf, G. M.; Rubin, Z.; Castelletti, A.

    2016-12-01

    Field and laboratory evidence indicates that the spatial distribution of transport in both alluvial and bedrock rivers is an adaptation to sediment supply. Sediment supply, in turn, depends on spatial distribution and properties (e.g., grain sizes and supply rates) of individual sediment sources. Analyzing the distribution of transport capacity in a river network could hence clarify the spatial distribution and properties of sediment sources. Yet, challenges include a) identifying magnitude and spatial distribution of transport capacity for each of multiple grain sizes being simultaneously transported, and b) estimating source grain sizes and supply rates, both at network scales. Herein, we approach the problem of identifying the spatial distribution of sediment sources and the resulting network sediment fluxes in a major, poorly monitored tributary (80,000 km2) of the Mekong. Therefore, we apply the CASCADE modeling framework (Schmitt et al. (2016)). CASCADE calculates transport capacities and sediment fluxes for multiple grainsizes on the network scale based on remotely-sensed morphology and modelled hydrology. CASCADE is run in an inverse Monte Carlo approach for 7500 random initializations of source grain sizes. In all runs, supply of each source is inferred from the minimum downstream transport capacity for the source grain size. Results for each realization are compared to sparse available sedimentary records. Only 1 % of initializations reproduced the sedimentary record. Results for these realizations revealed a spatial pattern in source supply rates, grain sizes, and network sediment fluxes that correlated well with map-derived patterns in lithology and river-morphology. Hence, we propose that observable river hydro-morphology contains information on upstream source properties that can be back-calculated using an inverse modeling approach. Such an approach could be coupled to more detailed models of hillslope processes in future to derive integrated models

  8. Using large hydrological datasets to create a robust, physically based, spatially distributed model for Great Britain

    Science.gov (United States)

    Lewis, Elizabeth; Kilsby, Chris; Fowler, Hayley

    2014-05-01

    The impact of climate change on hydrological systems requires further quantification in order to inform water management. This study intends to conduct such analysis using hydrological models. Such models are of varying forms, of which conceptual, lumped parameter models and physically-based models are two important types. The majority of hydrological studies use conceptual models calibrated against measured river flow time series in order to represent catchment behaviour. This method often shows impressive results for specific problems in gauged catchments. However, the results may not be robust under non-stationary conditions such as climate change, as physical processes and relationships amenable to change are not accounted for explicitly. Moreover, conceptual models are less readily applicable to ungauged catchments, in which hydrological predictions are also required. As such, the physically based, spatially distributed model SHETRAN is used in this study to develop a robust and reliable framework for modelling historic and future behaviour of gauged and ungauged catchments across the whole of Great Britain. In order to achieve this, a large array of data completely covering Great Britain for the period 1960-2006 has been collated and efficiently stored ready for model input. The data processed include a DEM, rainfall, PE and maps of geology, soil and land cover. A desire to make the modelling system easy for others to work with led to the development of a user-friendly graphical interface. This allows non-experts to set up and run a catchment model in a few seconds, a process that can normally take weeks or months. The quality and reliability of the extensive dataset for modelling hydrological processes has also been evaluated. One aspect of this has been an assessment of error and uncertainty in rainfall input data, as well as the effects of temporal resolution in precipitation inputs on model calibration. SHETRAN has been updated to accept gridded rainfall

  9. 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.

  10. Modeling the spatial distribution of Chagas disease vectors using environmental variables and people´s knowledge.

    Science.gov (United States)

    Hernández, Jaime; Núñez, Ignacia; Bacigalupo, Antonella; Cattan, Pedro E

    2013-05-31

    Chagas disease is caused by the protozoan Trypanosoma cruzi, which is transmitted to mammal hosts by triatomine insect vectors. The goal of this study was to model the spatial distribution of triatomine species in an endemic area. Vector's locations were obtained with a rural householders' survey. This information was combined with environmental data obtained from remote sensors, land use maps and topographic SRTM data, using the machine learning algorithm Random Forests to model species distribution. We analysed the combination of variables on three scales: 10 km, 5 km and 2.5 km cell size grids. The best estimation, explaining 46.2% of the triatomines spatial distribution, was obtained for 5 km of spatial resolution. Presence probability distribution increases from central Chile towards the north, tending to cover the central-coastal region and avoiding areas of the Andes range. The methodology presented here was useful to model the distribution of triatomines in an endemic area; it is best explained using 5 km of spatial resolution, and their presence increases in the northern part of the study area. This study's methodology can be replicated in other countries with Chagas disease or other vectorial transmitted diseases, and be used to locate high risk areas and to optimize resource allocation, for prevention and control of vectorial diseases.

  11. 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

  12. Modeling the Spatial Distribution and Fruiting Pattern of a Key Tree Species in a Neotropical Forest: Methodology and Potential Applications

    NARCIS (Netherlands)

    Caillaud, D.; Crofoot, M.C.; Scarpino, S.V.; Jansen, P.A.; Garzon-Lopez, C.X.; Winkelhagen, A.J.S.; Bohlman, S.A.; Walsh, P.D.

    2010-01-01

    Background - The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we

  13. Modeling the Spatial Distribution and Fruiting Pattern of a Key Tree Species in a Neotropical Forest : Methodology and Potential Applications

    NARCIS (Netherlands)

    Caillaud, Damien; Crofoot, Margaret C.; Scarpino, Samuel V.; Jansen, Patrick A.; Garzon-Lopez, Carol X.; Winkelhagen, Annemarie J. S.; Bohlman, Stephanie A.; Walsh, Peter D.

    2010-01-01

    Background: The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we

  14. Effect of precipitation spatial distribution uncertainty on the uncertainty bounds of a snowmelt runoff model output

    Science.gov (United States)

    Jacquin, A. P.

    2012-04-01

    This study analyses the effect of precipitation spatial distribution uncertainty on the uncertainty bounds of a snowmelt runoff model's discharge estimates. Prediction uncertainty bounds are derived using the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. The model analysed is a conceptual watershed model operating at a monthly time step. The model divides the catchment into five elevation zones, where the fifth zone corresponds to the catchment glaciers. Precipitation amounts at each elevation zone i are estimated as the product between observed precipitation (at a single station within the catchment) and a precipitation factor FPi. Thus, these factors provide a simplified representation of the spatial variation of precipitation, specifically the shape of the functional relationship between precipitation and height. In the absence of information about appropriate values of the precipitation factors FPi, these are estimated through standard calibration procedures. The catchment case study is Aconcagua River at Chacabuquito, located in the Andean region of Central Chile. Monte Carlo samples of the model output are obtained by randomly varying the model parameters within their feasible ranges. In the first experiment, the precipitation factors FPi are considered unknown and thus included in the sampling process. The total number of unknown parameters in this case is 16. In the second experiment, precipitation factors FPi are estimated a priori, by means of a long term water balance between observed discharge at the catchment outlet, evapotranspiration estimates and observed precipitation. In this case, the number of unknown parameters reduces to 11. The feasible ranges assigned to the precipitation factors in the first experiment are slightly wider than the range of fixed precipitation factors used in the second experiment. The mean squared error of the Box-Cox transformed discharge during the calibration period is used for the evaluation of the

  15. Spatial distributions of Cu polycrystal sputtered atoms

    International Nuclear Information System (INIS)

    Abgaryan, V.K.; Semenov, A.A.; Shkarban, I.I.

    2004-01-01

    The results of the experimental determination of the Cu atoms spatial distribution, sputtered from the polycrystalline copper target, irradiated by the Xe + ions with the energy of 300 eV, are presented. The spatial distributions of the sputtered particles, calculated through the quasistable-dynamic model of the cascade modeling (CAMO) are presented also for the case of the polycrystalline copper irradiation by the Ar + and Xe + ions with the energy of 300-1000 eV [ru

  16. 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

    to naturalists but also of importance to human and animal health. The spatial distribution of freshwater snail intermediate hosts involved in the transmission of schistosomiasis, fascioliasis and paramphistomiasis (i.e. Bulinus globosus, Biomphalaria pfeifferi and Lymnaea natalensis) were modelled by the use...

  17. 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.

  18. 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

  19. Uncertainty quantification in flux balance analysis of spatially lumped and distributed models of neuron-astrocyte metabolism.

    Science.gov (United States)

    Calvetti, Daniela; Cheng, Yougan; Somersalo, Erkki

    2016-12-01

    Identifying feasible steady state solutions of a brain energy metabolism model is an inverse problem that allows infinitely many solutions. The characterization of the non-uniqueness, or the uncertainty quantification of the flux balance analysis, is tantamount to identifying the degrees of freedom of the solution. The degrees of freedom of multi-compartment mathematical models for energy metabolism of a neuron-astrocyte complex may offer a key to understand the different ways in which the energetic needs of the brain are met. In this paper we study the uncertainty in the solution, using techniques of linear algebra to identify the degrees of freedom in a lumped model, and Markov chain Monte Carlo methods in its extension to a spatially distributed case. The interpretation of the degrees of freedom in metabolic terms, more specifically, glucose and oxygen partitioning, is then leveraged to derive constraints on the free parameters to guarantee that the model is energetically feasible. We demonstrate how the model can be used to estimate the stoichiometric energy needs of the cells as well as the household energy based on the measured oxidative cerebral metabolic rate of glucose and glutamate cycling. Moreover, our analysis shows that in the lumped model the net direction of lactate dehydrogenase (LDH) in the cells can be deduced from the glucose partitioning between the compartments. The extension of the lumped model to a spatially distributed multi-compartment setting that includes diffusion fluxes from capillary to tissue increases the number of degrees of freedom, requiring the use of statistical sampling techniques. The analysis of the distributed model reveals that some of the conclusions valid for the spatially lumped model, e.g., concerning the LDH activity and glucose partitioning, may no longer hold.

  20. 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

    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...... 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...

  1. 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 (analysis.

  2. 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.

  3. 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.

  4. Cell size spatial convergence analysis on GOTHIC distributed parameter models for studying hydrogen mixing behaviour in CANDU containments

    International Nuclear Information System (INIS)

    Yim, K.; Wong, R.C.

    1995-01-01

    Gas mixing phenomena can be modelled using distributed parameter codes such as GOTHIC, but the selection of the optimum cell size is an important user input. The tradeoff between accuracy and practical computation times affect the choice of cell sizes, where small cells provide better accuracy at the expense of longer computing time. A study on cell size effect on hydrogen distribution is presented for the problem of hydrogen mixing behaviour in a typical CANDU reactor containment following a severe reactor accident. Optimal cell sizes were found for different room volumes, hydrogen release profiles and elevations using spatial convergence criteria. The findings of this study provide the technical basis for the cell size selection in the GOTHIC distributed parameter models used for analysing hydrogen mixing behaviour. (author). 1 ref., 1 tab., 13 figs

  5. Modelling the distributions and spatial coincidence of bluetongue vectors Culicoides imicola and the Culicoides obsoletus group throughout the Iberian peninsula.

    Science.gov (United States)

    Calvete, C; Estrada, R; Miranda, M A; Borrás, D; Calvo, J H; Lucientes, J

    2008-06-01

    Data obtained by a Spanish national surveillance programme in 2005 were used to develop climatic models for predictions of the distribution of the bluetongue virus (BTV) vectors Culicoides imicola Kieffer (Diptera: Ceratopogonidae) and the Culicoides obsoletus group Meigen throughout the Iberian peninsula. Models were generated using logistic regression to predict the probability of species occurrence at an 8-km spatial resolution. Predictor variables included the annual mean values and seasonalities of a remotely sensed normalized difference vegetation index (NDVI), a sun index, interpolated precipitation and temperature. Using an information-theoretic paradigm based on Akaike's criterion, a set of best models accounting for 95% of model selection certainty were selected and used to generate an average predictive model for each vector. The predictive performances (i.e. the discrimination capacity and calibration) of the average models were evaluated by both internal and external validation. External validation was achieved by comparing average model predictions with surveillance programme data obtained in 2004 and 2006. The discriminatory capacity of both models was found to be reasonably high. The estimated areas under the receiver operating characteristic (ROC) curve (AUC) were 0.78 and 0.70 for the C. imicola and C. obsoletus group models, respectively, in external validation, and 0.81 and 0.75, respectively, in internal validation. The predictions of both models were in close agreement with the observed distribution patterns of both vectors. Both models, however, showed a systematic bias in their predicted probability of occurrence: observed occurrence was systematically overestimated for C. imicola and underestimated for the C. obsoletus group. Average models were used to determine the areas of spatial coincidence of the two vectors. Although their spatial distributions were highly complementary, areas of spatial coincidence were identified, mainly in

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

    Directory of Open Access Journals (Sweden)

    Ulrik B. Pedersen

    2014-05-01

    Full Text Available 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 to naturalists but also of importance to human and animal health. The spatial distribution of freshwater snail intermediate hosts involved in the transmission of schistosomiasis, fascioliasis and paramphistomiasis (i.e. Bulinus globosus, Biomphalaria pfeifferi and Lymnaea natalensis were modelled by the use of a maximum entropy algorithm (Maxent. Two snail observation datasets from Zimbabwe, from 1988 and 2012, were com- pared in terms of geospatial distribution and potential distributional change over this 24-year period investigated. Climate data, from the two years were identified and used in a species distribution modelling framework to produce maps of pre- dicted suitable snail habitats. Having both climate- and snail observation data spaced 24 years in time represent a unique opportunity to evaluate biological response of snails to changes in climate variables. The study shows that snail habitat suit- ability is highly variable in Zimbabwe with foci mainly in the central Highveld but also in areas to the South and West. It is further demonstrated that the spatial distribution of suitable habitats changes with variation in the climatic conditions, and that this parallels that of the predicted climate change.

  7. Two-terminal reliability of a mobile ad hoc network under the asymptotic spatial distribution of the random waypoint model

    International Nuclear Information System (INIS)

    Chen, Binchao; Phillips, Aaron; Matis, Timothy I.

    2012-01-01

    The random waypoint (RWP) mobility model is frequently used in describing the movement pattern of mobile users in a mobile ad hoc network (MANET). As the asymptotic spatial distribution of nodes under a RWP model exhibits central tendency, the two-terminal reliability of the MANET is investigated as a function of the source node location. In particular, analytical expressions for one and two hop connectivities are developed as well as an efficient simulation methodology for two-terminal reliability. A study is then performed to assess the effect of nodal density and network topology on network reliability.

  8. 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).

  9. Spatial distribution of aquatic insects

    DEFF Research Database (Denmark)

    Iversen, Lars Lønsmann

    (time since glacial disturbance and habitat stability) and question the generality of these processes for the understanding of species richness gradients in European rivers. Using regional distributions of European mayflies, stoneflies, and caddisflies this chapter demonstrates that differences...... 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...

  10. Constructing the reduced dynamical models of interannual climate variability from spatial-distributed time series

    Science.gov (United States)

    Mukhin, Dmitry; Gavrilov, Andrey; Loskutov, Evgeny; Feigin, Alexander

    2016-04-01

    dynamical models from time series," Phys. Rev. E, vol. 85, no. 3, p. 036216, 2012. [2] D. Mukhin, D. Kondrashov, E. Loskutov, A. Gavrilov, A. Feigin, and M. Ghil, "Predicting Critical Transitions in ENSO models. Part II: Spatially Dependent Models," J. Clim., vol. 28, no. 5, pp. 1962-1976, 2015.

  11. Using semi-variogram analysis for providing spatially distributed information on soil surface condition for land surface modeling

    Science.gov (United States)

    Croft, Holly; Anderson, Karen; Kuhn, Nikolaus J.

    2010-05-01

    The ability to quantitatively and spatially assess soil surface roughness is important in geomorphology and land degradation studies. Soils can experience rapid structural degradation in response to land cover changes, resulting in increased susceptibility to erosion and a loss of Soil Organic Matter (SOM). Changes in soil surface condition can also alter sediment detachment, transport and deposition processes, infiltration rates and surface runoff characteristics. Deriving spatially distributed quantitative information on soil surface condition for inclusion in hydrological and soil erosion models is therefore paramount. However, due to the time and resources involved in using traditional field sampling techniques, there is a lack of spatially distributed information on soil surface condition. Laser techniques can provide data for a rapid three dimensional representation of the soil surface at a fine spatial resolution. This provides the ability to capture changes at the soil surface associated with aggregate breakdown, flow routing, erosion and sediment re-distribution. Semi-variogram analysis of the laser data can be used to represent spatial dependence within the dataset; providing information about the spatial character of soil surface structure. This experiment details the ability of semi-variogram analysis to spatially describe changes in soil surface condition. Soil for three soil types (silt, silt loam and silty clay) was sieved to produce aggregates between 1 mm and 16 mm in size and placed evenly in sample trays (25 x 20 x 2 cm). Soil samples for each soil type were exposed to five different durations of artificial rainfall, to produce progressively structurally degraded soil states. A calibrated laser profiling instrument was used to measure surface roughness over a central 10 x 10 cm plot of each soil state, at 2 mm sample spacing. The laser data were analysed within a geostatistical framework, where semi-variogram analysis quantitatively represented

  12. 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.

  13. Conceptualisation of Snowpack Isotope Dynamics in Spatially Distributed Tracer-Aided Runoff Models in Snow Influenced Northern Cathments

    Science.gov (United States)

    Ala-aho, P. O. A.; Tetzlaff, D.; Laudon, H.; McNamara, J. P.; Soulsby, C.

    2016-12-01

    We use the Spatially distributed Tracer-Aided Rainfall-Runoff (STARR) modelling framework to explore non-stationary flow and isotope response in three northern headwater catchments. The model simulates dynamic, spatially variable tracer concentration in different water stores and fluxes within a catchment, which can constrain internal catchment mixing processes, flow paths and associated water ages. To date, a major limitation in using such models in snow-dominated catchments has been the difficulties in paramaterising the isotopic transformations in snowpack accumulation and melt. We use high quality long term datasets for hydrometrics and stable water isotopes collected in three northern study catchments for model calibration and testing. The three catchments exhibit different hydroclimatic conditions, soil and vegetation types, and topographic relief, which brings about variable degree of snow dominance across the catchments. To account for the snow influence we develop novel formulations to estimate the isotope evolution in the snowpack and melt. Algorithms for the isotopic evolution parameterize an isotopic offset between snow evaporation and melt fluxes and the remaining snow storage. The model for each catchment is calibrated to match both streamflow and tracer concentration at the stream outlet to ensure internal consistency of the system behaviour. The model is able to reproduce the streamflow along with the spatio-temporal differences in tracer concentrations across the three studies catchments reasonably well. Incorporating the spatially distributed snowmelt processes and associated isotope transformations proved essential in capturing the stream tracer reponse for strongly snow-influenced cathments. This provides a transferrable tool which can be used to understand spatio-temporal variability of mixing and water ages for different storages and flow paths in other snow influenced, environments.

  14. 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.

  15. Spatial distribution of block falls using volumetric GIS-decision-tree models

    Science.gov (United States)

    Abdallah, C.

    2010-10-01

    Block falls are considered a significant aspect of surficial instability contributing to losses in land and socio-economic aspects through their damaging effects to natural and human environments. This paper predicts and maps the geographic distribution and volumes of block falls in central Lebanon using remote sensing, geographic information systems (GIS) and decision-tree modeling (un-pruned and pruned trees). Eleven terrain parameters (lithology, proximity to fault line, karst type, soil type, distance to drainage line, elevation, slope gradient, slope aspect, slope curvature, land cover/use, and proximity to roads) were generated to statistically explain the occurrence of block falls. The latter were discriminated using SPOT4 satellite imageries, and their dimensions were determined during field surveys. The un-pruned tree model based on all considered parameters explained 86% of the variability in field block fall measurements. Once pruned, it classifies 50% in block falls' volumes by selecting just four parameters (lithology, slope gradient, soil type, and land cover/use). Both tree models (un-pruned and pruned) were converted to quantitative 1:50,000 block falls' maps with different classes; starting from Nil (no block falls) to more than 4000 m 3. These maps are fairly matching with coincidence value equal to 45%; however, both can be used to prioritize the choice of specific zones for further measurement and modeling, as well as for land-use management. The proposed tree models are relatively simple, and may also be applied to other areas (i.e. the choice of un-pruned or pruned model is related to the availability of terrain parameters in a given area).

  16. 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.

  17. 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)

  18. Examining the Suitability of a Sparse In Situ Soil Moisture Monitoring Network for Assimilation into a Spatially Distributed Hydrologic Model

    Science.gov (United States)

    De Vleeschouwer, N.; Verhoest, N.; Pauwels, V. R. N.

    2015-12-01

    The continuous monitoring of soil moisture in a permanent network can yield an interesting data product for use in hydrological data assimilation. Major advantages of in situ observations compared to remote sensing products are the potential vertical extent of the measurements, the finer temporal resolution of the observation time series, the smaller impact of land cover variability on the observation bias, etc. However, two major disadvantages are the typical small integration volume of in situ measurements and the often large spacing between monitoring locations. This causes only a small part of the modelling domain to be directly observed. Furthermore, the spatial configuration of the monitoring network is typically temporally non-dynamic. Therefore two questions can be raised. Do spatially sparse in situ soil moisture observations contain a sufficient data representativeness to successfully assimilate them into the largely unobserved spatial extent of a distributed hydrological model? And if so, how is this assimilation best performed? Consequently two important factors that can influence the success of assimilating in situ monitored soil moisture are the spatial configuration of the monitoring network and the applied assimilation algorithm. In this research the influence of those factors is examined by means of synthetic data-assimilation experiments. The study area is the ± 100 km² catchment of the Bellebeek in Flanders, Belgium. The influence of the spatial configuration is examined by varying the amount of locations and their position in the landscape. The latter is performed using several techniques including temporal stability analysis and clustering. Furthermore the observation depth is considered by comparing assimilation of surface layer (5 cm) and deeper layer (50 cm) observations. The impact of the assimilation algorithm is assessed by comparing the performance obtained with two well-known algorithms: Newtonian nudging and the Ensemble Kalman

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

    KAUST Repository

    Tagle, Felipe; Castruccio, Stefano; Genton, Marc G.

    2017-01-01

    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

  20. Retrieval of spatially distributed hydrological properties from satellite observations for spatial evaluation of a national water resources model.

    Science.gov (United States)

    Mendiguren González, G.; Stisen, S.; Koch, J.

    2016-12-01

    The NASA Cyclone Global Navigation Satellite System (CYNSS) mission provides high temporal resolution observations of cyclones from a constellation of eight low-Earth orbiting satellites. Using the relatively new technique of Global Navigation Satellite System reflectometry (GNSS-R), all-weather observations are possible, penetrating even deep convection within hurricane eye walls. The compact nature of the GNSS-R receivers permits the use of small satellites, which in turn enables the launch of a constellation of satellites from a single launch vehicle. Launched in December of 2016, the eight CYGNSS satellites provide 25 km resolution observations of mean square slope (surface roughness) and surface winds with a 2.8 hour median revisit time from 38 S to 38 N degrees latitude. In addition to the calibration and validation of CYGNSS sea state observations, the CYGNSS science team is assessing the ability of the mission to provide estimates of cyclone size, intensity, and integrated kinetic energy. With its all-weather ability and high temporal resolution, the CYGNSS mission will add significantly to our ability to monitor cyclone genesis and intensification and will significantly reduce uncertainties in our ability to estimate cyclone intensity, a key variable in predicting its destructive potential. Members of the CYGNSS Science Team are also assessing the assimilation of CYGNSS data into hurricane forecast models to determine the impact of the data on forecast skill, using the data to study extra-tropical cyclones, and looking at connections between tropical cyclones and global scale weather, including the global hydrologic cycle. This presentation will focus on the assessment of early on-orbit observations of cyclones with respect to these various applications.

  1. Modeling of spatial distribution for scorpions of medical importance in the São Paulo State, Brazil

    Directory of Open Access Journals (Sweden)

    José Brites-Neto

    2015-07-01

    Full Text Available Aim: In this work, we aimed to develop maps of modeling geographic distribution correlating to environmental suitability for the two species of scorpions of medical importance at São Paulo State and to develop spatial configuration parameters for epidemiological surveillance of these species of venomous animals. Materials and Methods: In this study, 54 georeferenced points for Tityus serrulatus and 86 points for Tityus bahiensis and eight environmental indicators, were used to generate species distribution models in Maxent (maximum entropy modeling of species geographic distributions version 3.3.3k using 70% of data for training (n=38 to T. serrulatus and n=60 to T. bahiensis and 30% to test the models (n=16 for T. serrulatus and n=26 for T. bahiensis. The logistic threshold used to cut models in converting the continuous probability model into a binary model was the “maximum test sensitivity plus specificity,” provided by Maxent, with results of 0.4143 to T. serrulatus and of 0.3401 to T. bahiensis. The models were evaluated by the area under the curve (AUC, using the omission error and the binomial probability. With the data generated by Maxent, distribution maps were produced using the “ESRI® ArcGIS 10.2.2 for Desktop” software. Results: The models had high predictive success (AUC=0.7698±0.0533, omission error=0.2467 and p<0.001 for T. serrulatus and AUC=0.8205±0.0390, omission error=0.1917 and p<0.001 for T. bahiensis and the resultant maps showed a high environmental suitability in the north, central, and southeast of the state, confirming the increasing spread of these species. The environmental variables that mostly contributed to the scorpions species distribution model were rain precipitation (28.9% and tree cover (28.2% for the T. serrulatus and temperature (45.8% and thermal amplitude (12.6% for the T. bahiensis. Conclusion: The distribution model of these species of medical importance scorpions in São Paulo State

  2. Characterisation of dispersion mechanisms in an urban catchment using a deterministic spatially distributed direct hydrograph travel time model

    Science.gov (United States)

    Rossel, F.; Gironas, J. A.

    2012-12-01

    The link between stream network structure and hydrologic response for natural basins has been extensively studied. It is well known that stream network organization and flow dynamics in the reaches combine to shape the hydrologic response of natural basins. Geomorphologic dispersion and hydrodynamic dispersion along with hillslope processes control to a large extent the overall variance of the hydrograph, particularly under the assumption of constant celerity throughout the basin. In addition, a third mechanism referred as to kinematic dispersion becomes relevant when considering spatial variations of celerity. On contrary, the link between the drainage network structure and overall urban terrain, and the hydrologic response in urban catchments has been much less studied. In particular, the characterization of the different dispersion mechanisms within urban areas remains to be better understood. In such areas artificial elements are expected to contribute to the total dispersion due to the variety of geometries and the spatial distribution of imperviousness. This work quantifies the different dispersion mechanisms in an urban catchment, focusing on their relevance and the spatial scales involved. For this purpose we use the Urban Morpho-climatic Instantaneous Unit Hydrograph model, a deterministic spatially distributed direct hydrograph travel time model, which computes travel times in hillslope, pipe, street and channel cells using formulations derived from kinematic wave theory. The model was applied to the Aubeniere catchment, located in Nantes, France. Unlike stochastic models, this deterministic model allows the quantification of dispersion mechanism at the local scale (i.e. the grid-cell). We found that kinematic dispersion is more relevant for small storm events, whereas geomorphologic dispersion becomes more significant for larger storms, as the mean celerity within the catchment increases. In addition, the total dispersion relates to the drainage area in

  3. 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.

  4. Modeling Spatial Distribution of Some Contamination within the Lower Reaches of Diyala River Using IDW Interpolation

    Directory of Open Access Journals (Sweden)

    Huda M. Madhloom

    2017-12-01

    Full Text Available The aim of this research was to simulate the water quality along the lower course of the Diyala River using Geographic Information Systems (GIS techniques. For this purpose, the samples were taken at 24 sites along the study area. The parameters: total dissolved solids (T.D.S, total suspended solids (T.S.S, iron (Fe, copper (Cu, chromium (Cr, and manganese (Mn were considered. Water samples were collected on a monthly basis for a duration of five years. The adopted analyzing approach was tested by calculating the mean absolute error (MAE and the correlation coefficient (R between observed water samples and predicted results. The result showed a percentage error less than 10% and significant correlation at R > 89% for all pollutant indicators. It was concluded that the accuracy of the applied model to simulate the river pollutants can decrease the number of monitoring station to 50%. Additionally, a distribution map for the concentrations’ results indicated that many of the major pollution indicators did not satisfy the river water quality standards.

  5. 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.

  6. 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

  7. 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)...

  8. Spatial models to predict ash pH and Electrical Conductivity distribution after a grassland fire in Lithuania

    Science.gov (United States)

    Pereira, Paulo; Cerda, Artemi; Misiūnė, Ieva

    2015-04-01

    Fire mineralizes the organic matter, increasing the pH level and the amount of dissolved ions (Pereira et al., 2014). The degree of mineralization depends among other factors on fire temperature, burned specie, moisture content, and contact time. The impact of wildland fires it is assessed using the fire severity, an index used in the absence of direct measures (e.g temperature), important to estimate the fire effects in the ecosystems. This impact is observed through the loss of soil organic matter, crown volume, twig diameter, ash colour, among others (Keeley et al., 2009). The effects of fire are highly variable, especially at short spatial scales (Pereira et al., in press), due the different fuel conditions (e.g. moisture, specie distribution, flammability, connectivity, arrangement, etc). This variability poses important challenges to identify the best spatial predictor and have the most accurate spatial visualization of the data. Considering this, the test of several interpolation methods it is assumed to be relevant to have the most reliable map. The aims of this work are I) study the ash pH and Electrical Conductivity (EC) after a grassland fire according to ash colour and II) test several interpolation methods in order to identify the best spatial predictor of pH and EC distribution. The study area is located near Vilnius at 54.42° N and 25.26°E and 154 ma.s.l. After the fire it was designed a plot with a 27 x 9 m space grid. Samples were taken every 3 meters for a total of 40 (Pereira et al., 2013). Ash color was classified according to Úbeda et al. (2009). Ash pH and EC laboratory analysis were carried out according to Pereira et al. (2014). Previous to data comparison and modelling, normality and homogeneity were assessed with the Shapiro-wilk and Levene test. pH data respected the normality and homogeneity, while EC only followed the Gaussian distribution and the homogeneity criteria after a logarithmic transformation. Data spatial correlation was

  9. Which spatial discretization for distributed hydrological models? Proposition of a methodology and illustration for medium to large-scale catchments

    Directory of Open Access Journals (Sweden)

    J. Dehotin

    2008-05-01

    Full Text Available Distributed hydrological models are valuable tools to derive distributed estimation of water balance components or to study the impact of land-use or climate change on water resources and water quality. In these models, the choice of an appropriate spatial discretization is a crucial issue. It is obviously linked to the available data, their spatial resolution and the dominant hydrological processes. For a given catchment and a given data set, the "optimal" spatial discretization should be adapted to the modelling objectives, as the latter determine the dominant hydrological processes considered in the modelling. For small catchments, landscape heterogeneity can be represented explicitly, whereas for large catchments such fine representation is not feasible and simplification is needed. The question is thus: is it possible to design a flexible methodology to represent landscape heterogeneity efficiently, according to the problem to be solved? This methodology should allow a controlled and objective trade-off between available data, the scale of the dominant water cycle components and the modelling objectives.

    In this paper, we propose a general methodology for such catchment discretization. It is based on the use of nested discretizations. The first level of discretization is composed of the sub-catchments, organised by the river network topology. The sub-catchment variability can be described using a second level of discretizations, which is called hydro-landscape units. This level of discretization is only performed if it is consistent with the modelling objectives, the active hydrological processes and data availability. The hydro-landscapes take into account different geophysical factors such as topography, land-use, pedology, but also suitable hydrological discontinuities such as ditches, hedges, dams, etc. For numerical reasons these hydro-landscapes can be further subdivided into smaller elements that will constitute the

  10. 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.

  11. Thermodynamic Model of Spatial Memory

    Science.gov (United States)

    Kaufman, Miron; Allen, P.

    1998-03-01

    We develop and test a thermodynamic model of spatial memory. Our model is an application of statistical thermodynamics to cognitive science. It is related to applications of the statistical mechanics framework in parallel distributed processes research. Our macroscopic model allows us to evaluate an entropy associated with spatial memory tasks. We find that older adults exhibit higher levels of entropy than younger adults. Thurstone's Law of Categorical Judgment, according to which the discriminal processes along the psychological continuum produced by presentations of a single stimulus are normally distributed, is explained by using a Hooke spring model of spatial memory. We have also analyzed a nonlinear modification of the ideal spring model of spatial memory. This work is supported by NIH/NIA grant AG09282-06.

  12. Quantification of the impact of precipitation spatial distribution uncertainty on predictive uncertainty of a snowmelt runoff model

    Science.gov (United States)

    Jacquin, A. P.

    2012-04-01

    This study is intended to quantify the impact of uncertainty about precipitation spatial distribution on predictive uncertainty of a snowmelt runoff model. This problem is especially relevant in mountain catchments with a sparse precipitation observation network and relative short precipitation records. The model analysed is a conceptual watershed model operating at a monthly time step. The model divides the catchment into five elevation zones, where the fifth zone corresponds to the catchment's glaciers. Precipitation amounts at each elevation zone i are estimated as the product between observed precipitation at a station and a precipitation factor FPi. If other precipitation data are not available, these precipitation factors must be adjusted during the calibration process and are thus seen as parameters of the model. In the case of the fifth zone, glaciers are seen as an inexhaustible source of water that melts when the snow cover is depleted.The catchment case study is Aconcagua River at Chacabuquito, located in the Andean region of Central Chile. The model's predictive uncertainty is measured in terms of the output variance of the mean squared error of the Box-Cox transformed discharge, the relative volumetric error, and the weighted average of snow water equivalent in the elevation zones at the end of the simulation period. Sobol's variance decomposition (SVD) method is used for assessing the impact of precipitation spatial distribution, represented by the precipitation factors FPi, on the models' predictive uncertainty. In the SVD method, the first order effect of a parameter (or group of parameters) indicates the fraction of predictive uncertainty that could be reduced if the true value of this parameter (or group) was known. Similarly, the total effect of a parameter (or group) measures the fraction of predictive uncertainty that would remain if the true value of this parameter (or group) was unknown, but all the remaining model parameters could be fixed

  13. 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.

  14. 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...

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. Spatial Distribution of Lactococcus lactis Colonies Modulates the Production of Major Metabolites during the Ripening of a Model Cheese.

    Science.gov (United States)

    Le Boucher, Clémentine; Gagnaire, Valérie; Briard-Bion, Valérie; Jardin, Julien; Maillard, Marie-Bernadette; Dervilly-Pinel, Gaud; Le Bizec, Bruno; Lortal, Sylvie; Jeanson, Sophie; Thierry, Anne

    2016-01-01

    In cheese, lactic acid bacteria are immobilized at the coagulation step and grow as colonies. The spatial distribution of bacterial colonies is characterized by the size and number of colonies for a given bacterial population within cheese. Our objective was to demonstrate that different spatial distributions, which lead to differences in the exchange surface between the colonies and the cheese matrix, can influence the ripening process. The strategy was to generate cheeses with the same growth and acidification of a Lactococcus lactis strain with two different spatial distributions, big and small colonies, to monitor the production of the major ripening metabolites, including sugars, organic acids, peptides, free amino acids, and volatile metabolites, over 1 month of ripening. The monitored metabolites were qualitatively the same for both cheeses, but many of them were more abundant in the small-colony cheeses than in the big-colony cheeses over 1 month of ripening. Therefore, the results obtained showed that two different spatial distributions of L. lactis modulated the ripening time course by generating moderate but significant differences in the rates of production or consumption for many of the metabolites commonly monitored throughout ripening. The present work further explores the immobilization of bacteria as colonies within cheese and highlights the consequences of this immobilization on cheese ripening. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

  1. Spatially Distributed Social Complex Networks

    Directory of Open Access Journals (Sweden)

    Gerald F. Frasco

    2014-01-01

    Full Text Available We propose a bare-bones stochastic model that takes into account both the geographical distribution of people within a country and their complex network of connections. The model, which is designed to give rise to a scale-free network of social connections and to visually resemble the geographical spread seen in satellite pictures of the Earth at night, gives rise to a power-law distribution for the ranking of cities by population size (but for the largest cities and reflects the notion that highly connected individuals tend to live in highly populated areas. It also yields some interesting insights regarding Gibrat’s law for the rates of city growth (by population size, in partial support of the findings in a recent analysis of real data [Rozenfeld et al., Proc. Natl. Acad. Sci. U.S.A. 105, 18702 (2008.]. The model produces a nontrivial relation between city population and city population density and a superlinear relationship between social connectivity and city population, both of which seem quite in line with real data.

  2. Spatially Distributed Social Complex Networks

    Science.gov (United States)

    Frasco, Gerald F.; Sun, Jie; Rozenfeld, Hernán D.; ben-Avraham, Daniel

    2014-01-01

    We propose a bare-bones stochastic model that takes into account both the geographical distribution of people within a country and their complex network of connections. The model, which is designed to give rise to a scale-free network of social connections and to visually resemble the geographical spread seen in satellite pictures of the Earth at night, gives rise to a power-law distribution for the ranking of cities by population size (but for the largest cities) and reflects the notion that highly connected individuals tend to live in highly populated areas. It also yields some interesting insights regarding Gibrat's law for the rates of city growth (by population size), in partial support of the findings in a recent analysis of real data [Rozenfeld et al., Proc. Natl. Acad. Sci. U.S.A. 105, 18702 (2008).]. The model produces a nontrivial relation between city population and city population density and a superlinear relationship between social connectivity and city population, both of which seem quite in line with real data.

  3. 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 ...

  4. 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.

  5. 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.

  6. 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.

  7. Three-dimensional analytical model for the spatial variation of the foreshock electron distribution function - Systematics and comparisons with ISEE observations

    Science.gov (United States)

    Fitzenreiter, R. J.; Scudder, J. D.; Klimas, A. J.

    1990-01-01

    A model which is consistent with the solar wind and shock surface boundary conditions for the foreshock electron distribution in the absence of wave-particle effects is formulated for an arbitrary location behind the magnetic tangent to the earth's bow shock. Variations of the gyrophase-averaged velocity distribution are compared and contrasted with in situ ISEE observations. It is found that magnetic mirroring of solar wind electrons is the most important process by which nonmonotonic reduced electron distributions in the foreshock are produced. Leakage of particles from the magnetosheath is shown to be relatively unimportant in determining reduced distributions that are nonmonotonic. The two-dimensional distribution function off the magnetic field direction is the crucial contribution in producing reduced distributions which have beams. The time scale for modification of the electron velocity distribution in velocity space can be significantly influenced by steady state spatial gradients in the background imposed by the curved shock geometry.

  8. 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

  9. 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

  10. 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

  11. 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)

  12. 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.

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

    Science.gov (United States)

    Sarlikioti, V.; de Visser, 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 heterogeneity of an explicitly described tomato canopy in relation to temporal dynamics of horizontal and vertical light distribution and photosynthesis under direct- and diffuse-light conditions. Methods Detailed measurements of canopy architecture, light interception and leaf photosynthesis were carried out on a tomato crop. These data were used for the development and calibration of a functional–structural tomato model. The model consisted of an architectural static virtual plant coupled with a nested radiosity model for light calculations and a leaf photosynthesis module. Different scenarios of horizontal and vertical distribution of light interception, incident light and photosynthesis were investigated under diffuse and direct light conditions. Key Results Simulated light interception showed a good correspondence to the measured values. Explicitly described leaf angles resulted in higher light interception in the middle of the plant canopy compared with fixed and ellipsoidal leaf-angle distribution models, although the total light interception remained the same. The fraction of light intercepted at a north–south orientation of rows differed from east–west orientation by 10 % on winter and 23 % on summer days. The horizontal distribution of photosynthesis differed significantly between the top, middle and lower canopy layer. Taking into account the vertical variation of leaf photosynthetic parameters in the canopy, led to approx. 8 % increase on simulated canopy photosynthesis. Conclusions Leaf angles of heterogeneous canopies should be explicitly described as they have a big impact both on light distribution and photosynthesis. Especially, the vertical

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

    Science.gov (United States)

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

    2011-04-01

    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 heterogeneity of an explicitly described tomato canopy in relation to temporal dynamics of horizontal and vertical light distribution and photosynthesis under direct- and diffuse-light conditions. Detailed measurements of canopy architecture, light interception and leaf photosynthesis were carried out on a tomato crop. These data were used for the development and calibration of a functional-structural tomato model. The model consisted of an architectural static virtual plant coupled with a nested radiosity model for light calculations and a leaf photosynthesis module. Different scenarios of horizontal and vertical distribution of light interception, incident light and photosynthesis were investigated under diffuse and direct light conditions. Simulated light interception showed a good correspondence to the measured values. Explicitly described leaf angles resulted in higher light interception in the middle of the plant canopy compared with fixed and ellipsoidal leaf-angle distribution models, although the total light interception remained the same. The fraction of light intercepted at a north-south orientation of rows differed from east-west orientation by 10 % on winter and 23 % on summer days. The horizontal distribution of photosynthesis differed significantly between the top, middle and lower canopy layer. Taking into account the vertical variation of leaf photosynthetic parameters in the canopy, led to approx. 8 % increase on simulated canopy photosynthesis. Leaf angles of heterogeneous canopies should be explicitly described as they have a big impact both on light distribution and photosynthesis. Especially, the vertical variation of photosynthesis in canopy is such that the

  15. 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.

  16. 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.

  17. 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 2MASS galaxies.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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

  6. Probabilistic, sediment-geochemical parameterisation of the groundwater compartment of the Netherlands for spatially distributed, reactive transport modelling

    Science.gov (United States)

    Janssen, Gijs; Gunnink, Jan; van Vliet, Marielle; Goldberg, Tanya; Griffioen, Jasper

    2017-04-01

    Pollution of groundwater aquifers with contaminants as nitrate is a common problem. Reactive transport models are useful to predict the fate of such contaminants and to characterise the efficiency of mitigating or preventive measures. Parameterisation of a groundwater transport model on reaction capacity is a necessary step during building the model. Two Dutch, national programs are combined to establish a methodology for building a probabilistic model on reaction capacity of the groundwater compartment at the national scale: the Geological Survey program and the NHI Netherlands Hydrological Instrument program. Reaction capacity is considered as a series of geochemical characteristics that control acid/base condition, redox condition and sorption capacity. Five primary reaction capacity variables are characterised: 1. pyrite, 2. non-pyrite, reactive iron (oxides, siderite and glauconite), 3. clay fraction, 4. organic matter and 5. Ca-carbonate. Important reaction capacity variables that are determined by more than one solid compound are also deduced: 1. potential reduction capacity (PRC) by pyrite and organic matter, 2. cation-exchange capacity (CEC) by organic matter and clay content, 3. carbonate buffering upon pyrite oxidation (CPBO) by carbonate and pyrite. Statistical properties of these variables are established based on c. 16,000 sediment geochemical analyses. The first tens of meters are characterised based on 25 regions using combinations of lithological class and geological formation as strata. Because of both less data and more geochemical uniformity, the deeper subsurface is characterised in a similar way based on 3 regions. The statistical data is used as input in an algoritm that probabilistically calculates the reaction capacity per grid cell. First, the cumulative frequency distribution (cfd) functions are calculated from the statistical data for the geochemical strata. Second, all voxel cells are classified into the geochemical strata. Third, the

  7. 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.

  8. Three-dimensional analytical model for the spatial variation of the foreshock electron distribution function: Systematics and comparisons with ISEE observations

    International Nuclear Information System (INIS)

    Fitzenreiter, R.J.; Scudder, J.D.; Klimas, A.J.

    1990-01-01

    A model of the gyrophase-averaged electron distribution in the Earth's foreshock consistent with boundary conditions at the bow shock and in the solar wind has been constructed according to the reversible guiding center characteristics and compared with ISEE electron and wave observations. This model demonstrates (1) that the basic features and morphology of beams in the observed and reduced distributions F(υ parallel ) are determined almost exclusively by the solar wind electrons mirrored at the shock's magnetic ramp and are relatively insensitive to the leakage fluxes from the magnetosheath, (2) that the wave particle modifications have been detected by contrasting the reversible model with the direct observations, (3) that the nonmonotonic reduced distributions F(υ parallel ) are rarely the result of a nonmonotonic energy spectra but are rather the result of the transverse velocity space integration necessary to produce F(υ parallel ) from the directly observed electron distribution function f(v), (4) that the time scale for beam resupply to F(υ parallel ) from the dc spatial gradients of the self-consistent reversible distribution function can have a factor of 100 variation across the foreshock, being shortest within a few degrees of the magnetic tangent surface, (5) that the beams predicted by the model have strongly varying and correlated variations of mean energy, thermal spread, and number density with angular departure from the magnetic tangent with the coldest, most tenuous, and lowest mean energy beams suggested to be present deep behind the magnetic tangent (≅5 degree-10 degree), and (6) that the lowest-energy beams have low contrast to the background solar wind distributing and although difficult to detect have beam density and temperature parameters compatible with ω pe growth of electrostatic waves

  9. Simulation of temporal and spatial distribution of required irrigation water by crop models and the pan evaporation coefficient method

    Science.gov (United States)

    Yang, Yan-min; Yang, Yonghui; Han, Shu-min; Hu, Yu-kun

    2009-07-01

    Hebei Plain is the most important agricultural belt in North China. Intensive irrigation, low and uneven precipitation have led to severe water shortage on the plain. This study is an attempt to resolve this crucial issue of water shortage for sustainable agricultural production and water resources management. The paper models distributed regional irrigation requirement for a range of cultivated crops on the plain. Classic crop models like DSSAT- wheat/maize and COTTON2K are used in combination with pan-evaporation coefficient method to estimate water requirements for wheat, corn, cotton, fruit-trees and vegetables. The approach is more accurate than the static approach adopted in previous studies. This is because the combination use of crop models and pan-evaporation coefficient method dynamically accounts for irrigation requirement at different growth stages of crops, agronomic practices, and field and climatic conditions. The simulation results show increasing Required Irrigation Amount (RIA) with time. RIA ranges from 5.08×109 m3 to 14.42×109 m3 for the period 1986~2006, with an annual average of 10.6×109 m3. Percent average water use by wheat, fruit trees, vegetable, corn and cotton is 41%, 12%, 12%, 11%, 7% and 17% respectively. RIA for April and May (the period with the highest irrigation water use) is 1.78×109 m3 and 2.41×109 m3 respectively. The counties in the piedmont regions of Mount Taihang have high RIA while the central and eastern regions/counties have low irrigation requirement.

  10. Spatial distribution of cold antihydrogen formation

    International Nuclear Information System (INIS)

    Madsen, N.; Hangst, J.S.; Amoretti, M.; Carraro, C.; Macri, M.; Testera, G.; Variola, A.; Amsler, C.; Pruys, H.; Regenfus, C.; Bonomi, G.; Doser, M.; Kellerbauer, A.; Landua, R.; Bowe, P.D.; Charlton, M.; Joergensen, L.V.; Mitchard, D.; Werf, D.P. van der; Cesar, C.L.

    2005-01-01

    Antihydrogen is formed when antiprotons are mixed with cold positrons in a nested Penning trap. We present experimental evidence, obtained using our antihydrogen annihilation detector, that the spatial distribution of the emerging antihydrogen atoms is independent of the positron temperature and axially enhanced. This indicates that antihydrogen is formed before the antiprotons are in thermal equilibrium with the positron plasma. This result has important implications for the trapping and spectroscopy of antihydrogen

  11. Modeling the spatial distribution of crop cultivated areas at a large regional scale combining system dynamics and a modified Dyna-CLUE: A case from Iran

    Energy Technology Data Exchange (ETDEWEB)

    Mesgari, I.; Saeed Jabalameli, M.

    2017-07-01

    Agricultural land use pattern is affected by many factors at different scales and effects that are separated by time and space. This will lead to simulation models that optimize or project the cropping pattern changes and incorporate complexities in terms of details and dynamics. Combining System Dynamics (SD) and a modified Conversion of Land Use and its Effects (CLUE) modelling framework, this paper suggests a new dynamic approach for assessing the demand of different crops at country-level and for predicting the spatial distribution of cultivated areas at provincial scale. As example, a case study is presented for Iran, where we have simulated a scenario of future cropping pattern changes during 2015–2040.The results indicated a change in the spatial distribution of cultivated areas during the next years. An increase in the proportion of rice is expected in northern Iran, whereas the proportion of wheat is increasing in the mountainous western areas. Wheat and barley crops are expected to become dominant within the cropping system throughout the country regions.

  12. 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 @csir.co.za; 14 15 Keywords: Bioenergy crops, Land suitability, Biodiversity, Spatial analysis, MaxEnt, 16 Conflict, Agricultural land, Spatial filters 17 18 Primary research article 19 Page 1 of 48 GCB Bioenergy 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17... habitat transformation and provides 21 an objective means of mitigating potential conflict with existing land use and biodiversity. 22 23 Page 2 of 48GCB Bioenergy 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32...

  13. 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.

  14. 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

  15. 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.

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

    Directory of Open Access Journals (Sweden)

    P. Ala-aho

    2017-10-01

    Full Text Available 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

  17. 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.

  18. 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.

  19. Experimental study of spatial distribution of Ar glow discharge plasma

    International Nuclear Information System (INIS)

    Guo, X.M.; Zhou, T.D.; Pai, S.T.

    1996-01-01

    The characteristics of the spatial distribution of Ar glow discharge plasma were experimentally investigated. By means of direct comparisons between theory and experiment, the effects of the variation of gap separation, gas pressure, and electrode radius on the spatial distributions of electron density and electric field were studied. Results indicate that the maximum electron density moves toward the cathode as the gap separation or gas pressure increases while variation of electrode radius produces little effect. Predictions from a theoretical model have been experimentally verified. General agreements between theory and experiment were found to be reasonably good except in the cathode region, where discrepancy exists. copyright 1996 American Institute of Physics

  20. A digital elevation analysis: Spatially distributed flow apportioning algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sang-Hyun; Kim, Kyung-Hyun [Pusan National University, Pusan(Korea); Jung, Sun-Hee [Korea Environment Institute, (Korea)

    2001-06-30

    A flow determination algorithm is proposed for the distributed hydrologic model. The advantages of a single flow direction scheme and multiple flow direction schemes are selectively considered to address the drawbacks of existing algorithms. A spatially varied flow apportioning factor is introduced in order to accommodate the accumulated area from upslope cells. The channel initiation threshold area(CIT) concept is expanded and integrated into the spatially distributed flow apportioning algorithm in order to delineate a realistic channel network. An application of a field example suggests that the linearly distributed flow apportioning scheme provides some advantages over existing approaches, such as the relaxation of over-dissipation problems near channel cells, the connectivity feature of river cells, the continuity of saturated areas and the negligence of the optimization of few parameters in existing algorithms. The effects of grid sizes are explored spatially as well as statistically. (author). 28 refs., 7 figs.

  1. Spatial distribution of suicide in Queensland, Australia

    Directory of Open Access Journals (Sweden)

    Tong Shilu

    2010-12-01

    Full Text Available Abstract Background There has been a lack of investigation into the spatial distribution and clustering of suicide in Australia, where the population density is lower than many countries and varies dramatically among urban, rural and remote areas. This study aims to examine the spatial distribution of suicide at a Local Governmental Area (LGA level and identify the LGAs with a high relative risk of suicide in Queensland, Australia, using geographical information system (GIS techniques. Methods Data on suicide and demographic variables in each LGA between 1999 and 2003 were acquired from the Australian Bureau of Statistics. An age standardised mortality (ASM rate for suicide was calculated at the LGA level. GIS techniques were used to examine the geographical difference of suicide across different areas. Results Far north and north-eastern Queensland (i.e., Cook and Mornington Shires had the highest suicide incidence in both genders, while the south-western areas (i.e., Barcoo and Bauhinia Shires had the lowest incidence in both genders. In different age groups (≤24 years, 25 to 44 years, 45 to 64 years, and ≥65 years, ASM rates of suicide varied with gender at the LGA level. Mornington and six other LGAs with low socioeconomic status in the upper Southeast had significant spatial clusters of high suicide risk. Conclusions There was a notable difference in ASM rates of suicide at the LGA level in Queensland. Some LGAs had significant spatial clusters of high suicide risk. The determinants of the geographical difference of suicide should be addressed in future research.

  2. 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

  3. 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

  4. 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

  5. Impact of wind on the spatial distribution of rain over micro-scale topography : numerical modelling and experimental verification

    NARCIS (Netherlands)

    Blocken, B.J.E.; Poesen, J.; Carmeliet, J.

    2006-01-01

    The wind-driven-rain effect refers to the redistribution of rainfall over micro-scale topography due to the existence of local perturbed wind-flow patterns. Rainfall measurements reported in the literature point to the fact that the wind-driven-rain distribution can show large variations over

  6. 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.

  7. 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.

  8. 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.

  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. 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

  11. 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...

  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. 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

  14. 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

  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. 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.

  17. 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...

  18. Modeling winter wheat phenological responses to water deficits in the Unified Plant Growth Model (UPGM) component of the spatially distributed Agricultural Ecosystem Services (AgES) model

    Science.gov (United States)

    Accurately predicting phenology in crop simulation models is critical for correctly simulating crop production. While extensive work in modeling phenology has focused on the temperature response function (resulting in robust phenology models), limited work on quantifying the phenological responses t...

  19. 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

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

    International Nuclear Information System (INIS)

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

    2010-01-01

    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. - GIS regression-tree analysis explained 88% of the variability in field/laboratory Zinc concentrations.

  1. 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.

  2. 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.

  3. 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.

  4. Spatial and Temporal Extrapolation of Disdrometer Size Distributions Based on a Lagrangian Trajectory Model of Falling Rain

    Science.gov (United States)

    Lane, John E.; Kasparis, Takis; Jones, W. Linwood; Metzger, Philip T.

    2009-01-01

    Methodologies to improve disdrometer processing, loosely based on mathematical techniques common to the field of particle flow and fluid mechanics, are examined and tested. The inclusion of advection and vertical wind field estimates appear to produce significantly improved results in a Lagrangian hydrometeor trajectory model, in spite of very strict assumptions of noninteracting hydrometeors, constant vertical air velocity, and time independent advection during the scan time interval. Wind field data can be extracted from each radar elevation scan by plotting and analyzing reflectivity contours over the disdrometer site and by collecting the radar radial velocity data to obtain estimates of advection. Specific regions of disdrometer spectra (drop size versus time) often exhibit strong gravitational sorting signatures, from which estimates of vertical velocity can be extracted. These independent wind field estimates become inputs and initial conditions to the Lagrangian trajectory simulation of falling hydrometeors.

  5. 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...

  6. 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...

  7. The seven sisters DANCe. III. Projected spatial distribution

    Science.gov (United States)

    Olivares, J.; Moraux, E.; Sarro, L. M.; Bouy, H.; Berihuete, A.; Barrado, D.; Huelamo, N.; Bertin, E.; Bouvier, J.

    2018-04-01

    Context. Membership analyses of the DANCe and Tycho + DANCe data sets provide the largest and least contaminated sample of Pleiades candidate members to date. Aims: We aim at reassessing the different proposals for the number surface density of the Pleiades in the light of the new and most complete list of candidate members, and inferring the parameters of the most adequate model. Methods: We compute the Bayesian evidence and Bayes Factors for variations of the classical radial models. These include elliptical symmetry, and luminosity segregation. As a by-product of the model comparison, we obtain posterior distributions for each set of model parameters. Results: We find that the model comparison results depend on the spatial extent of the region used for the analysis. For a circle of 11.5 parsecs around the cluster centre (the most homogeneous and complete region), we find no compelling reason to abandon King's model, although the Generalised King model introduced here has slightly better fitting properties. Furthermore, we find strong evidence against radially symmetric models when compared to the elliptic extensions. Finally, we find that including mass segregation in the form of luminosity segregation in the J band is strongly supported in all our models. Conclusions: We have put the question of the projected spatial distribution of the Pleiades cluster on a solid probabilistic framework, and inferred its properties using the most exhaustive and least contaminated list of Pleiades candidate members available to date. Our results suggest however that this sample may still lack about 20% of the expected number of cluster members. Therefore, this study should be revised when the completeness and homogeneity of the data can be extended beyond the 11.5 parsecs limit. Such a study will allow for more precise determination of the Pleiades spatial distribution, its tidal radius, ellipticity, number of objects and total mass.

  8. 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....

  9. 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.

  10. Nonparametric Bayesian models for a spatial covariance.

    Science.gov (United States)

    Reich, Brian J; Fuentes, Montserrat

    2012-01-01

    A crucial step in the analysis of spatial data is to estimate the spatial correlation function that determines the relationship between a spatial process at two locations. The standard approach to selecting the appropriate correlation function is to use prior knowledge or exploratory analysis, such as a variogram analysis, to select the correct parametric correlation function. Rather that selecting a particular parametric correlation function, we treat the covariance function as an unknown function to be estimated from the data. We propose a flexible prior for the correlation function to provide robustness to the choice of correlation function. We specify the prior for the correlation function using spectral methods and the Dirichlet process prior, which is a common prior for an unknown distribution function. Our model does not require Gaussian data or spatial locations on a regular grid. The approach is demonstrated using a simulation study as well as an analysis of California air pollution data.

  11. 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

  12. Spatial distribution maps for benthic communities

    DEFF Research Database (Denmark)

    Sørensen, Per S.

    1999-01-01

    ecosystems, were selected. These species are supposed to be good indicators of marine ecosystem health. The hydroacoustic measurements comprise preprocessed echo sounder recordings and side-scan sonar data forming a large and unique collection of datasets based on 4 field campaigns in Øresund...... of the distribution maps and to be combined with biogeochemical models describing spatiotemporal population dynamics. Finally, the use of side-scan sonar data is illustrated in a data fusion exercise combining side-scan sonar data with the results based on echo sounder measurements. The feasible use of side......-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...

  13. 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)

  14. Multi-scale modeling for prediction of distributed cellular properties in response to substrate spatial gradients in a continuously run microreactor

    DEFF Research Database (Denmark)

    Lencastre Fernandes, Rita; Krühne, Ulrich; Nopens, Ingmar

    2012-01-01

    microbioreactor is simulated. A multiscale model consisting of the coupling of a population balance model, a kinetic model and a flow model was developed in order to predict simultaneously local concentrations of substrate (glucose), product (ethanol) and biomass, as well as the local cell size distributions....

  15. Consequences of spatial autocorrelation for niche-based models

    DEFF Research Database (Denmark)

    Segurado, P.; Araújo, Miguel B.; Kunin, W. E.

    2006-01-01

    1.  Spatial autocorrelation is an important source of bias in most spatial analyses. We explored the bias introduced by spatial autocorrelation on the explanatory and predictive power of species' distribution models, and make recommendations for dealing with the problem. 2.  Analyses were based o...

  16. Competition in spatial location models

    NARCIS (Netherlands)

    Webers, H.M.

    1996-01-01

    Models of spatial competition are designed and analyzed to describe the fact that space, by its very nature, is a source of market power. This field of research, lying at the interface of game theory and economics, has attracted much interest because location problems are related to many aspects of

  17. 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.

  18. 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

  19. 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)

  20. Spatial Distribution Analysis of Scrub Typhus in Korea

    OpenAIRE

    Jin, Hong Sung; Chu, Chaeshin; Han, Dong Yeob

    2013-01-01

    Objective: This study analyzes the spatial distribution of scrub typhus in Korea. Methods: A spatial distribution of Orientia tsutsugamushi occurrence using a geographic information system (GIS) is presented, and analyzed by means of spatial clustering and correlations. Results: The provinces of Gangwon-do and Gyeongsangbuk-do show a low incidence throughout the year. Some districts have almost identical environmental conditions of scrub typhus incidence. The land use change of districts does...

  1. 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

  2. Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation

    International Nuclear Information System (INIS)

    Churmakov, D Y; Meglinski, I V; Piletsky, S A; Greenhalgh, D A

    2003-01-01

    A novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account the spatial distribution of fluorophores, which would arise due to the structure of collagen fibres, compared to the epidermis and stratum corneum where the distribution of fluorophores is assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the near-infrared spectral region, whereas the spatial distribution of fluorescence sources within a sensor layer embedded in the epidermis is localized at an 'effective' depth

  3. Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation

    Energy Technology Data Exchange (ETDEWEB)

    Churmakov, D Y [School of Engineering, Cranfield University, Cranfield, MK43 0AL (United Kingdom); Meglinski, I V [School of Engineering, Cranfield University, Cranfield, MK43 0AL (United Kingdom); Piletsky, S A [Institute of BioScience and Technology, Cranfield University, Silsoe, MK45 4DT (United Kingdom); Greenhalgh, D A [School of Engineering, Cranfield University, Cranfield, MK43 0AL (United Kingdom)

    2003-07-21

    A novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account the spatial distribution of fluorophores, which would arise due to the structure of collagen fibres, compared to the epidermis and stratum corneum where the distribution of fluorophores is assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the near-infrared spectral region, whereas the spatial distribution of fluorescence sources within a sensor layer embedded in the epidermis is localized at an 'effective' depth.

  4. Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation

    Science.gov (United States)

    Y Churmakov, D.; Meglinski, I. V.; Piletsky, S. A.; Greenhalgh, D. A.

    2003-07-01

    A novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account the spatial distribution of fluorophores, which would arise due to the structure of collagen fibres, compared to the epidermis and stratum corneum where the distribution of fluorophores is assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the near-infrared spectral region, whereas the spatial distribution of fluorescence sources within a sensor layer embedded in the epidermis is localized at an `effective' depth.

  5. 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.

  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. The spatial limitations of current neutral models of biodiversity.

    Directory of Open Access Journals (Sweden)

    Rampal S Etienne

    Full Text Available The unified neutral theory of biodiversity and biogeography is increasingly accepted as an informative null model of community composition and dynamics. It has successfully produced macro-ecological patterns such as species-area relationships and species abundance distributions. However, the models employed make many unrealistic auxiliary assumptions. For example, the popular spatially implicit version assumes a local plot exchanging migrants with a large panmictic regional source pool. This simple structure allows rigorous testing of its fit to data. In contrast, spatially explicit models assume that offspring disperse only limited distances from their parents, but one cannot as yet test the significance of their fit to data. Here we compare the spatially explicit and the spatially implicit model, fitting the most-used implicit model (with two levels, local and regional to data simulated by the most-used spatially explicit model (where offspring are distributed about their parent on a grid according to either a radially symmetric Gaussian or a 'fat-tailed' distribution. Based on these fits, we express spatially implicit parameters in terms of spatially explicit parameters. This suggests how we may obtain estimates of spatially explicit parameters from spatially implicit ones. The relationship between these parameters, however, makes no intuitive sense. Furthermore, the spatially implicit model usually fits observed species-abundance distributions better than those calculated from the spatially explicit model's simulated data. Current spatially explicit neutral models therefore have limited descriptive power. However, our results suggest that a fatter tail of the dispersal kernel seems to improve the fit, suggesting that dispersal kernels with even fatter tails should be studied in future. We conclude that more advanced spatially explicit models and tools to analyze them need to be developed.

  8. 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

  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. Model for Atmospheric Propagation of Spatially Combined Laser Beams

    Science.gov (United States)

    2016-09-01

    NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS MODEL FOR ATMOSPHERIC PROPAGATION OF SPATIALLY COMBINED LASER BEAMS by Kum Leong Lee September...MODEL FOR ATMOSPHERIC PROPAGATION OF SPATIALLY COMBINED LASER BEAMS 5. FUNDING NUMBERS 6. AUTHOR(S) Kum Leong Lee 7. PERFORMING ORGANIZATION NAME(S) AND...BLANK ii Approved for public release. Distribution is unlimited. MODEL FOR ATMOSPHERIC PROPAGATION OF SPATIALLY COMBINED LASER BEAMS Kum Leong Lee

  11. The spatial distribution of infrared radiation from visible reflection nebulae

    Science.gov (United States)

    Luan, Ling; Werner, Michael W.; Dwek, Eli; Sellgren, Kris

    1989-01-01

    The emission at IRAS 12 and 25 micron bands of reflection nebulae is far in excess of that expected from the longer wavelength equilibrium thermal emission. The excess emission in the IRAS 12 micron band is a general phenomenon, seen in various components of interstellar medium such as IR cirrus clouds, H II regions, atomic and molecular clouds, and also normal spiral galaxies. This excess emission has been attributed to UV excited fluorescence in polycyclic aromatic hydrocarbon (PAH) molecules or to the effect of temperature fluctuations in very small grains. Results are presented of studies of IRAS data on reflection nebulae selected from the van den Bergh reflection nebulae sample. Detailed scans of flux ratio and color temperature across the nebulae were obtained in order to study the spatial distribution of IR emission. A model was used to predict the spatial distribution of IR emission from dust grains illuminated by a B type star. The model was also used to explore the excitation of the IRAS 12 micron band emission as a function of stellar temperature. The model predictions are in good agreement with the analysis of reflection nebulae, illuminated by stars with stellar temperature ranging from 21,000 down to 3,000 K.

  12. 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

  13. 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

  14. 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

  15. Modelling deep water habitats to develop a spatially explicit, fine scale understanding of the distribution of the western rock lobster, Panulirus cygnus.

    Directory of Open Access Journals (Sweden)

    Renae K Hovey

    Full Text Available 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 km(2 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 D(2 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

  16. 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

    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. 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 km(2) 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 D(2) of 64 and an 80% correct classification. 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.

  17. 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

  18. 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...

  19. 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

  20. 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.

  1. 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

  2. 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.

  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. Daily Based Morgan–Morgan–Finney (DMMF Model: A Spatially Distributed Conceptual Soil Erosion Model to Simulate Complex Soil Surface Configurations

    Directory of Open Access Journals (Sweden)

    Kwanghun Choi

    2017-04-01

    Full Text Available In this paper, we present the Daily based Morgan–Morgan–Finney model. The main processes in this model are based on the Morgan–Morgan–Finney soil erosion model, and it is suitable for estimating surface runoff and sediment redistribution patterns in seasonal climate regions with complex surface configurations. We achieved temporal flexibility by utilizing daily time steps, which is suitable for regions with concentrated seasonal rainfall. We introduce the proportion of impervious surface cover as a parameter to reflect its impacts on soil erosion through blocking water infiltration and protecting the soil from detachment. Also, several equations and sequences of sub-processes are modified from the previous model to better represent physical processes. From the sensitivity analysis using the Sobol’ method, the DMMF model shows the rational response to the input parameters which is consistent with the result from the previous versions. To evaluate the model performance, we applied the model to two potato fields in South Korea that had complex surface configurations using plastic covered ridges at various temporal periods during the monsoon season. Our new model shows acceptable performance for runoff and the sediment loss estimation ( NSE ≥ 0.63 , | PBIAS | ≤ 17.00 , and RSR ≤ 0.57 . Our findings demonstrate that the DMMF model is able to predict the surface runoff and sediment redistribution patterns for cropland with complex surface configurations.

  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. Spatial distribution and landuse planning of informal automobile ...

    African Journals Online (AJOL)

    Spatial distribution and landuse planning of informal automobile workshops in Osogbo, ... data pertaining to the activities and other related issues of their workshops. ... The study therefore, recommends the establishment of mechanic complex, ...

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

    African Journals Online (AJOL)

    The spatial distribution of aquatic macroinvertebrates in the Okavango River ... of taxa was recorded in marginal vegetation in the channels and lagoons, ... highlights the importance of maintaining a mosaic of aquatic habitats in the Delta.

  8. 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, ... seasonally-flooded pools and temporary rain-filled pools in MGR and CI. ... biodiversity of the Okavango Delta, thereby contributing to its conservation.

  9. 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].

  10. 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].

  11. Mapping the spatial distribution of Aedes aegypti and Aedes albopictus.

    Science.gov (United States)

    Ding, Fangyu; Fu, Jingying; Jiang, Dong; Hao, Mengmeng; Lin, Gang

    2018-02-01

    Mosquito-borne infectious diseases, such as Rift Valley fever, Dengue, Chikungunya and Zika, have caused mass human death with the transnational expansion fueled by economic globalization. Simulating the distribution of the disease vectors is of great importance in formulating public health planning and disease control strategies. In the present study, we simulated the global distribution of Aedes aegypti and Aedes albopictus at a 5×5km spatial resolution with high-dimensional multidisciplinary datasets and machine learning methods Three relatively popular and robust machine learning models, including support vector machine (SVM), gradient boosting machine (GBM) and random forest (RF), were used. During the fine-tuning process based on training datasets of A. aegypti and A. albopictus, RF models achieved the highest performance with an area under the curve (AUC) of 0.973 and 0.974, respectively, followed by GBM (AUC of 0.971 and 0.972, respectively) and SVM (AUC of 0.963 and 0.964, respectively) models. The simulation difference between RF and GBM models was not statistically significant (p>0.05) based on the validation datasets, whereas statistically significant differences (p<0.05) were observed for RF and GBM simulations compared with SVM simulations. From the simulated maps derived from RF models, we observed that the distribution of A. albopictus was wider than that of A. aegypti along a latitudinal gradient. The discriminatory power of each factor in simulating the global distribution of the two species was also analyzed. Our results provided fundamental information for further study on disease transmission simulation and risk assessment. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. 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

    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...

  13. Influence of sawtooth oscillations of fast ion spatial distribution

    International Nuclear Information System (INIS)

    Anderson, D.; Lisak, M.; Wising, F.

    1992-01-01

    Recent measurements of global as well as line integrated neutron emission generated during NBI heating on JET have provided significant information on the influence of sawtooth oscillations on injected ions. The measurements have been analysed tomographically to deduce the spatial distribution of the neutron emission before and after the sawtooth crash, and the results indicate that the fast ions are expelled from the plasma core during crashes. The present report summarizes the theoretical work performed within the JET contract JTI/13435, the final aim of which is to try to interpret the mentioned experimental results. The analysis involves analytical as well as numerical calculations. A new model of sawtooth crashes with q o below unity is presented, based on the models of Kadomtsev and Wesson. The analytical results for the changes in global and local neutron emissivity at the sawtooth crash are in qualitative agreement with experimental results. The new model predicts stronger redistribution of the neutron emissivity, but a smaller change of global emissivity than the Kadomtsev model. A detailed numerical investigation of the sawtooth induced change in neutron emissivity is also made. The Fokker-Planck equation is used to calculate the distribution function of the injected fast ions before the crash and the models are used to find the change of both beam and plasma parameters due to the crash. The radial distributions of the neutron emissivity before and after the crash are then calculated and used for integration along the lines-of-sight of the neutron profile monitor on JET. The flux surface geometry obtained from MHD equilibrium calculations is used during the integration. In addition, the change of the global neutron emission is also calculated and compared with experimental results. Both the Kadomtsev model and the model suggested here are found to be consistent with the experimentally observed change in neutron emissivity provided the q(r)-profile is

  14. Perceived loudness of spatially distributed sound sources

    DEFF Research Database (Denmark)

    Song, Woo-keun; Ellermeier, Wolfgang; Minnaar, Pauli

    2005-01-01

    psychoacoustic attributes into account. Therefore, a method for deriving loudness maps was developed in an earlier study [Song, Internoise2004, paper 271]. The present experiment investigates to which extent perceived loudness depends on the distribution of individual sound sources. Three loudspeakers were...... positioned 1.5 m from the centre of the listener’s head, one straight ahead, and two 10 degrees to the right and left, respectively. Six participants matched the loudness of either one, or two simultaneous sounds (narrow-band noises with 1-kHz, and 3.15-kHz centre frequencies) to a 2-kHz, 60-dB SPL narrow......-band noise placed in the frontal loudspeaker. The two sounds were either originating from the central speaker, or from the two offset loudspeakers. It turned out that the subjects perceived the noises to be softer when they were distributed in space. In addition, loudness was calculated from the recordings...

  15. Spatial distribution of Dermacentor reticulatus in Romania.

    Science.gov (United States)

    Chitimia-Dobler, Lidia

    2015-11-30

    Dermacentor reticulatus (Fabricius, 1794), also known as the marsh tick or ornate dog tick is the second most significant vector (next to Ixodes ricinus) of protozoan, rickettsial and viral pathogens in Europe. Until now, only limited information on the distribution of D. reticulatus in Romania is available. A study was conducted on the distribution of D. reticulatus in Romania during 2012-2014. In this study, D. reticulatus was detected in 17 counties, in 14 of which the species was recorded for the first time. Tick activity was evident throughout the year, except during July and August. Additionally, D. reticulatus was recorded for the first time in Romania from wild boar, foxes and humans. These data suggest that this tick species has a broader geographic range and may have more veterinary and medical importance than previously known. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. 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.

  17. 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

  18. Vaginal drug distribution modeling.

    Science.gov (United States)

    Katz, David F; Yuan, Andrew; Gao, Yajing

    2015-09-15

    This review presents and applies fundamental mass transport theory describing the diffusion and convection driven mass transport of drugs to the vaginal environment. It considers sources of variability in the predictions of the models. It illustrates use of model predictions of microbicide drug concentration distribution (pharmacokinetics) to gain insights about drug effectiveness in preventing HIV infection (pharmacodynamics). The modeling compares vaginal drug distributions after different gel dosage regimens, and it evaluates consequences of changes in gel viscosity due to aging. It compares vaginal mucosal concentration distributions of drugs delivered by gels vs. intravaginal rings. Finally, the modeling approach is used to compare vaginal drug distributions across species with differing vaginal dimensions. Deterministic models of drug mass transport into and throughout the vaginal environment can provide critical insights about the mechanisms and determinants of such transport. This knowledge, and the methodology that obtains it, can be applied and translated to multiple applications, involving the scientific underpinnings of vaginal drug distribution and the performance evaluation and design of products, and their dosage regimens, that achieve it. Copyright © 2015 Elsevier B.V. All rights reserved.

  19. Spatially distributed multipartite entanglement enables EPR steering of atomic clouds

    Science.gov (United States)

    Kunkel, Philipp; Prüfer, Maximilian; Strobel, Helmut; Linnemann, Daniel; Frölian, Anika; Gasenzer, Thomas; Gärttner, Martin; Oberthaler, Markus K.

    2018-04-01

    A key resource for distributed quantum-enhanced protocols is entanglement between spatially separated modes. However, the robust generation and detection of entanglement between spatially separated regions of an ultracold atomic system remain a challenge. We used spin mixing in a tightly confined Bose-Einstein condensate to generate an entangled state of indistinguishable particles in a single spatial mode. We show experimentally that this entanglement can be spatially distributed by self-similar expansion of the atomic cloud. We used spatially resolved spin read-out to reveal a particularly strong form of quantum correlations known as Einstein-Podolsky-Rosen (EPR) steering between distinct parts of the expanded cloud. Based on the strength of EPR steering, we constructed a witness, which confirmed genuine 5-partite entanglement.

  20. Ionizing nightglow: sources, intensity, and spatial distribution

    International Nuclear Information System (INIS)

    Young, J.M.; Troy, B.E. Jr.; Johnson, C.Y.; Holmes, J.C.

    1975-01-01

    Photometers carried aboard an Aerobee rocket mapped the ultraviolet night sky at White Sands, New Mexico. Maps for five 300 A passbands in the wavelength range 170 to 1400 A reveal spatial radiation patterns unique to each spectral subregion. The major ultraviolet features seen in these maps are ascribed to a variety of sources: 1) solar Lyman α (1216 A) and Lyman β (1026 A), resonantly scattered by geocoronal hydrogen; 2) solar HeII (304 A) resonantly scattered by ionized helium in the Earth's plasmasphere; 3) solar HeI (584 A) resonantly scattered by neutral helium in the interstellar wind and Doppler shifted so that it penetrates the Earth's helium blanket; and 4) starlight in the 912 to 1400 A band, primarily from early-type stars in the Orion region. Not explained are the presence of small, but measurable, albedo signals observed near the peak of flight. Intensities vary from several kilorayleighs for Lyman α to a few rayleighs for HeII. (auth)

  1. Continuous Spatial Process Models for Spatial Extreme Values

    KAUST Repository

    Sang, Huiyan; Gelfand, Alan E.

    2010-01-01

    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

  2. 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.

  3. 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, ...

  4. Spatial distribution of soluble insulin in pig subcutaneous tissue

    DEFF Research Database (Denmark)

    Thomsen, Maria; Rasmussen, Christian Hove; Refsgaard, Hanne H F

    2015-01-01

    in the tomographic reconstructions and the amount of drug in each tissue class was quantified. With a scan time of about 45min per sample, and a robust segmentation it was possible to analyze differences in the spatial drug distribution between several similar injections. It was studied how the drug distribution...

  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. 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.

  7. 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

  8. 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

  9. 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.

  10. Combining MODIS, MISR, CALIOP, OMI, AERONET, and Models to Identify the Spatial and Temporal Distribution, Characterization, and Magnitude of Missing Urban and Wildfire Emissions Sources throughout Asia.

    Science.gov (United States)

    Cohen, J. B.

    2016-12-01

    Due to intense and changing levels of emissions as well as highly non-linear chemical processing, the concentrations of aerosols and thus their impacts are not well known. Urban areas consist of the majority of the emissions of these species and their precursors over large periods of time, while wildfires contribute very large spikes, concentrated in space and over a period of weeks to months. Yet due to urban and economic expansion, as well as clouds amd low intensity burning, the spatial and temporal profiles of these species are changing, with both new sources appearing and old sources decreasing. New work incorporates measurements at different spatial andboptical resolutions from MODIS, MISR, and OMI, coupled with new sampling approaches with CALIOP and AERONET to search for, characterize, and spatially and temporally constrain aerosols. An advanced modeling system including aerosol chemistry, physics, optics, and transport, using a multi-modal and both externally mixed and core-shell mixing is used to quantify the magnitudes of these missing sources. Comparisons between the model and additional dozens of ground stations show extreme improvement when these new sources are included. This new approach is shown to identify new source regions of emissions, many of which were previously non-urbanized or were not found to contain any fire hotspots. In addition, the use of new models run under conditions including both missing local sources from regions such as the expanded urban areas in Southeast and East Asia and advanced chemical and aerosol routines, allow for a comprehensive analysis to be performed. The impacts of insitu chemistry, horizontal, and vertical transport of species, both on the Regional and Continental scale are also included. It is shown that for proper identification, especially on intra-annual and inter-annual variations, this approach is a large improvement throughout Asia, ranging from India, to Indonesia, to China and Japan. Results specific

  11. Pedestrian count estimation using texture feature with spatial distribution

    Directory of Open Access Journals (Sweden)

    Hongyu Hu

    2016-12-01

    Full Text Available We present a novel pedestrian count estimation approach based on global image descriptors formed from multi-scale texture features that considers spatial distribution. For regions of interest, local texture features are represented based on histograms of multi-scale block local binary pattern, which jointly constitute the feature vector of the whole image. Therefore, to achieve an effective estimation of pedestrian count, principal component analysis is used to reduce the dimension of the global representation features, and a fitting model between image global features and pedestrian count is constructed via support vector regression. The experimental result shows that the proposed method exhibits high accuracy on pedestrian count estimation and can be applied well in the real world.

  12. 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.

  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 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

  15. 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

  16. 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.

  17. Spatial distribution of carbon sources and sinks in Canada's forests

    International Nuclear Information System (INIS)

    Chen, Jing M.; Weimin, Ju; Liu, Jane; Cihlar, Josef; Chen, Wenjun

    2003-01-01

    Annual spatial distributions of carbon sources and sinks in Canada's forests at 1 km resolution are computed for the period from 1901 to 1998 using ecosystem models that integrate remote sensing images, gridded climate, soils and forest inventory data. GIS-based fire scar maps for most regions of Canada are used to develop a remote sensing algorithm for mapping and dating forest burned areas in the 25 yr prior to 1998. These mapped and dated burned areas are used in combination with inventory data to produce a complete image of forest stand age in 1998. Empirical NPP age relationships were used to simulate the annual variations of forest growth and carbon balance in 1 km pixels, each treated as a homogeneous forest stand. Annual CO 2 flux data from four sites were used for model validation. Averaged over the period 1990-1998, the carbon source and sink map for Canada's forests show the following features: (i) large spatial variations corresponding to the patchiness of recent fire scars and productive forests and (ii) a general south-to-north gradient of decreasing carbon sink strength and increasing source strength. This gradient results mostly from differential effects of temperature increase on growing season length, nutrient mineralization and heterotrophic respiration at different latitudes as well as from uneven nitrogen deposition. The results from the present study are compared with those of two previous studies. The comparison suggests that the overall positive effects of non-disturbance factors (climate, CO 2 and nitrogen) outweighed the effects of increased disturbances in the last two decades, making Canada's forests a carbon sink in the 1980s and 1990s. Comparisons of the modeled results with tower-based eddy covariance measurements of net ecosystem exchange at four forest stands indicate that the sink values from the present study may be underestimated

  18. 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

    -pattern by Acinetobacter sp. C6. Ecological spatial pattern analyses revealed that the microcolonies were not entirely randomly distributed, and instead arranged in a uniform pattern. Detailed time-lapse confocal microscopy at the single cell level demonstrated that the spatial pattern was the result of an intriguing self......-organization: Small multicellular clusters moved along the surface to fuse with one another to form microcolonies. This active distribution capability was dependent on environmental factors (carbon source, oxygen) and historical contingency (formation of phenotypic variants). The findings of this study are discussed...

  19. Spatially-Distributed Stream Flow and Nutrient Dynamics Simulations Using the Component-Based AgroEcoSystem-Watershed (AgES-W) Model

    Science.gov (United States)

    Ascough, J. C.; David, O.; Heathman, G. C.; Smith, D. R.; Green, T. R.; Krause, P.; Kipka, H.; Fink, M.

    2010-12-01

    The Object Modeling System 3 (OMS3), currently being developed by the USDA-ARS Agricultural Systems Research Unit and Colorado State University (Fort Collins, CO), provides a component-based environmental modeling framework which allows the implementation of single- or multi-process modules that can be developed and applied as custom-tailored model configurations. OMS3 as a “lightweight” modeling framework contains four primary foundations: modeling resources (e.g., components) annotated with modeling metadata; domain specific knowledge bases and ontologies; tools for calibration, sensitivity analysis, and model optimization; and methods for model integration and performance scalability. The core is able to manage modeling resources and development tools for model and simulation creation, execution, evaluation, and documentation. OMS3 is based on the Java platform but is highly interoperable with C, C++, and FORTRAN on all major operating systems and architectures. The ARS Conservation Effects Assessment Project (CEAP) Watershed Assessment Study (WAS) Project Plan provides detailed descriptions of ongoing research studies at 14 benchmark watersheds in the United States. In order to satisfy the requirements of CEAP WAS Objective 5 (“develop and verify regional watershed models that quantify environmental outcomes of conservation practices in major agricultural regions”), a new watershed model development approach was initiated to take advantage of OMS3 modeling framework capabilities. Specific objectives of this study were to: 1) disaggregate and refactor various agroecosystem models (e.g., J2K-S, SWAT, WEPP) and implement hydrological, N dynamics, and crop growth science components under OMS3, 2) assemble a new modular watershed scale model for fully-distributed transfer of water and N loading between land units and stream channels, and 3) evaluate the accuracy and applicability of the modular watershed model for estimating stream flow and N dynamics. The

  20. Non-homogeneous Behaviour of the Spatial Distribution of Macrospicules

    Science.gov (United States)

    Gyenge, N.; Bennett, S.; Erdélyi, R.

    2015-03-01

    In this paper the longitudinal and latitudinal spatial distribution of macrospicules is examined. We found a statistical relationship between the active longitude (determined by sunspot groups) and the longitudinal distribution of macrospicules. This distribution of macrospicules shows an inhomogeneity and non-axisymmetrical behaviour in the time interval between June 2010 and December 2012, covered by observations of the Solar Dynamic Observatory (SDO) satellite. The enhanced positions of the activity and its time variation have been calculated. The migration of the longitudinal distribution of macrospicules shows a similar behaviour to that of the sunspot groups.

  1. 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

  2. Sediment spatial distribution evaluated by three methods and its relation to some soil properties

    Energy Technology Data Exchange (ETDEWEB)

    Bacchi, O O.S. . [Centro de Energia Nuclear na Agricultura-CENA/USP, Laboratorio de Fisica do Solo, Piracicaba, SP (Brazil); Reichardt, K [Centro de Energia Nuclear na Agricultura-CENA/USP, Laboratorio de Fisica do Solo, Piracicaba, SP (Brazil); Departamento de Ciencias Exatas, Escola Superior de Agricultura ' Luiz de Queiroz' ESALQ/USP, Piracicaba, SP (Brazil); Sparovek, G [Departamento de Solos e Nutricao de Plantas, Escola Superior de Agricultura ' Luiz de Queiroz' ESALQ/USP, Piracicaba, SP (Brazil)

    2003-02-15

    An investigation of rates and spatial distribution of sediments on an agricultural field cultivated with sugarcane was undertaken using the {sup 137}Cs technique, USLE and WEPP models. The study was carried out on the Ceveiro watershed of the Piracicaba river basin, state of Sao Paulo, Brazil, experiencing severe soil degradation due to soil erosion. The objectives of the study were to compare the spatial distribution of sediments evaluated by the three methods and its relation to some soil properties. Erosion and sedimentation rates and their spatial distribution estimated by the three methods were completely different. Although not able to show sediment deposition, the spatial distribution of erosion rates evaluated by USLE presented the best correlation with other studied soil properties. (author)

  3. Structural Constraints On The Spatial Distribution of Aftershocks

    Science.gov (United States)

    McCloskey, J.; Nalbant, S. S.; Steacy, S.; Nostro, C.; Scotti, O.; Baumont, D.

    Real-time, forward modelling of spatial distributions of potentially damaging after- shocks by calculating stress perturbations due to large earthquakes may produce so- cially useful, time- dependent hazard estimates in the foreseeable future. Such calcula- tions, however, rely on the resolution of a stress perturbation tensor (SPT) onto planes whose geometry is unknown and decisions as to the orientations of these planes have a first order effect on the geometry of the resulting hazard distributions. Commonly, these decisions are based on the assumption that structures optimally oriented for fail- ure in the regional stress field, exist everywhere and stress maps are produced by resolving onto these orientations. Here we investigate this proposition using a 3D cal- culation for the optimally oriented planes (OOPs) for the 1992 Landers earthquake (M = 7.3). We examine the encouraged mechanisms as a function of location and show that enhancement for failure exists over a much wider area than in the equivalent, and more usual, 2.5D calculations. Mechanisms predicted in these areas are not consistent with the local structural geology, however, and corresponding aftershocks are gener- ally not observed. We argue that best hazard estimates will result from geometrically restricted versions of the OOP concept in which observed structure constrains possible orientations for failure.

  4. Multivariate Non-Symmetric Stochastic Models for Spatial Dependence Models

    Science.gov (United States)

    Haslauer, C. P.; Bárdossy, A.

    2017-12-01

    A copula based multivariate framework allows more flexibility to describe different kind of dependences than what is possible using models relying on the confining assumption of symmetric Gaussian models: different quantiles can be modelled with a different degree of dependence; it will be demonstrated how this can be expected given process understanding. maximum likelihood based multivariate quantitative parameter estimation yields stable and reliable results; not only improved results in cross-validation based measures of uncertainty are obtained but also a more realistic spatial structure of uncertainty compared to second order models of dependence; as much information as is available is included in the parameter estimation: incorporation of censored measurements (e.g., below detection limit, or ones that are above the sensitive range of the measurement device) yield to more realistic spatial models; the proportion of true zeros can be jointly estimated with and distinguished from censored measurements which allow estimates about the age of a contaminant in the system; secondary information (categorical and on the rational scale) has been used to improve the estimation of the primary variable; These copula based multivariate statistical techniques are demonstrated based on hydraulic conductivity observations at the Borden (Canada) site, the MADE site (USA), and a large regional groundwater quality data-set in south-west Germany. Fields of spatially distributed K were simulated with identical marginal simulation, identical second order spatial moments, yet substantially differing solute transport characteristics when numerical tracer tests were performed. A statistical methodology is shown that allows the delineation of a boundary layer separating homogenous parts of a spatial data-set. The effects of this boundary layer (macro structure) and the spatial dependence of K (micro structure) on solute transport behaviour is shown.

  5. An Innovative Metric to Evaluate Satellite Precipitation's Spatial Distribution

    Science.gov (United States)

    Liu, H.; Chu, W.; Gao, X.; Sorooshian, S.

    2011-12-01

    Thanks to its capability to cover the mountains, where ground measurement instruments cannot reach, satellites provide a good means of estimating precipitation over mountainous regions. In regions with complex terrains, accurate information on high-resolution spatial distribution of precipitation is critical for many important issues, such as flood/landslide warning, reservoir operation, water system planning, etc. Therefore, in order to be useful in many practical applications, satellite precipitation products should possess high quality in characterizing spatial distribution. However, most existing validation metrics, which are based on point/grid comparison using simple statistics, cannot effectively measure satellite's skill of capturing the spatial patterns of precipitation fields. This deficiency results from the fact that point/grid-wised comparison does not take into account of the spatial coherence of precipitation fields. Furth more, another weakness of many metrics is that they can barely provide information on why satellite products perform well or poor. Motivated by our recent findings of the consistent spatial patterns of the precipitation field over the western U.S., we developed a new metric utilizing EOF analysis and Shannon entropy. The metric can be derived through two steps: 1) capture the dominant spatial patterns of precipitation fields from both satellite products and reference data through EOF analysis, and 2) compute the similarities between the corresponding dominant patterns using mutual information measurement defined with Shannon entropy. Instead of individual point/grid, the new metric treat the entire precipitation field simultaneously, naturally taking advantage of spatial dependence. Since the dominant spatial patterns are shaped by physical processes, the new metric can shed light on why satellite product can or cannot capture the spatial patterns. For demonstration, a experiment was carried out to evaluate a satellite

  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. Mapping the spatial distribution of chloride deposition across Australia

    Science.gov (United States)

    Davies, P. J.; Crosbie, R. S.

    2018-06-01

    The high solubility and conservative behaviour of chloride make it ideal for use as an environmental tracer of water and salt movement through the hydrologic cycle. For such use the spatial distribution of chloride deposition in rainfall at a suitable scale must be known. A number of authors have used point data acquired from field studies of chloride deposition around Australia to construct relationships to characterise chloride deposition as a function of distance from the coast; these relationships have allowed chloride deposition to be interpolated in different regions around Australia. In this paper we took this a step further and developed a chloride deposition map for all of Australia which includes a quantification of uncertainty. A previously developed four parameter model of chloride deposition as a function of distance from the coast for Australia was used as the basis for producing a continental scale chloride deposition map. Each of the four model parameters were made spatially variable by creating parameter surfaces that were interpolated using a pilot point regularisation approach within a parameter estimation software. The observations of chloride deposition were drawn from a literature review that identified 291 point measurements of chloride deposition over a period of 80 years spread unevenly across all Australian States and Territories. A best estimate chloride deposition map was developed from the resulting surfaces on a 0.05 degree grid. The uncertainty in the chloride deposition map was quantified as the 5th and 95th percentile of 1000 calibrated models produced via Null Space Monte Carlo analysis and the spatial variability of chloride deposition across the continent was consistent with landscape morphology. The temporal variability in chloride deposition on a decadal scale was investigated in the Murray-Darling Basin, this highlighted the need for long-term monitoring of chloride deposition if the uncertainty of the continental scale map is

  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. 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)

    Energy Technology Data Exchange (ETDEWEB)

    Yokogawa, D., E-mail: d.yokogawa@chem.nagoya-u.ac.jp [Department of Chemistry, Graduate School of Science, Nagoya University, Chikusa, Nagoya 464-8602 (Japan); Institute of Transformative Bio-Molecules (WPI-ITbM), Nagoya University, Chikusa, Nagoya 464-8602 (Japan)

    2016-09-07

    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.

  10. Unbiased estimators for spatial distribution functions of classical fluids

    Science.gov (United States)

    Adib, Artur B.; Jarzynski, Christopher

    2005-01-01

    We use a statistical-mechanical identity closely related to the familiar virial theorem, to derive unbiased estimators for spatial distribution functions of classical fluids. In particular, we obtain estimators for both the fluid density ρ(r) in the vicinity of a fixed solute and the pair correlation g(r) of a homogeneous classical fluid. We illustrate the utility of our estimators with numerical examples, which reveal advantages over traditional histogram-based methods of computing such distributions.

  11. Spatial data quality and coastal spill modelling

    International Nuclear Information System (INIS)

    Li, Y.; Brimicombe, A.J.; Ralphs, M.P.

    1998-01-01

    Issues of spatial data quality are central to the whole oil spill modelling process. Both model and data quality performance issues should be considered as indispensable parts of a complete oil spill model specification and testing procedure. This paper presents initial results of research that will emphasise to modeler and manager alike the practical issues of spatial data quality for coastal oil spill modelling. It is centred around a case study of Jiao Zhou Bay in the People's Republic of China. The implications for coastal oil spill modelling are discussed and some strategies for managing the effects of spatial data quality in the outputs of oil spill modelling are explored. (author)

  12. 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...

  13. 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.

  14. 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…

  15. 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, ...

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

    African Journals Online (AJOL)

    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 of ...

  17. 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.

  18. 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 ...

  19. 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 ...

  20. Analysis of thrips distribution: application of spatial statistics and Kriging

    Science.gov (United States)

    John Aleong; Bruce L. Parker; Margaret Skinner; Diantha Howard

    1991-01-01

    Kriging is a statistical technique that provides predictions for spatially and temporally correlated data. Observations of thrips distribution and density in Vermont soils are made in both space and time. Traditional statistical analysis of such data assumes that the counts taken over space and time are independent, which is not necessarily true. Therefore, to analyze...

  1. 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 ...

  2. 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

  3. Bayesian Spatial Modelling with R-INLA

    Directory of Open Access Journals (Sweden)

    Finn Lindgren

    2015-02-01

    Full Text Available The principles behind the interface to continuous domain spatial models in the R- INLA software package for R are described. The integrated nested Laplace approximation (INLA approach proposed by Rue, Martino, and Chopin (2009 is a computationally effective alternative to MCMC for Bayesian inference. INLA is designed for latent Gaussian models, a very wide and flexible class of models ranging from (generalized linear mixed to spatial and spatio-temporal models. Combined with the stochastic partial differential equation approach (SPDE, Lindgren, Rue, and Lindstrm 2011, one can accommodate all kinds of geographically referenced data, including areal and geostatistical ones, as well as spatial point process data. The implementation interface covers stationary spatial mod- els, non-stationary spatial models, and also spatio-temporal models, and is applicable in epidemiology, ecology, environmental risk assessment, as well as general geostatistics.

  4. 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.

  5. 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...

  6. Intelligent spatial ecosystem modeling using parallel processors

    International Nuclear Information System (INIS)

    Maxwell, T.; Costanza, R.

    1993-01-01

    Spatial modeling of ecosystems is essential if one's modeling goals include developing a relatively realistic description of past behavior and predictions of the impacts of alternative management policies on future ecosystem behavior. Development of these models has been limited in the past by the large amount of input data required and the difficulty of even large mainframe serial computers in dealing with large spatial arrays. These two limitations have begun to erode with the increasing availability of remote sensing data and GIS systems to manipulate it, and the development of parallel computer systems which allow computation of large, complex, spatial arrays. Although many forms of dynamic spatial modeling are highly amenable to parallel processing, the primary focus in this project is on process-based landscape models. These models simulate spatial structure by first compartmentalizing the landscape into some geometric design and then describing flows within compartments and spatial processes between compartments according to location-specific algorithms. The authors are currently building and running parallel spatial models at the regional scale for the Patuxent River region in Maryland, the Everglades in Florida, and Barataria Basin in Louisiana. The authors are also planning a project to construct a series of spatially explicit linked ecological and economic simulation models aimed at assessing the long-term potential impacts of global climate change

  7. 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

  8. Spherical Process Models for Global Spatial Statistics

    KAUST Repository

    Jeong, Jaehong; Jun, Mikyoung; Genton, Marc G.

    2017-01-01

    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

  9. 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

  10. 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.

  11. Spatial Distribution of Flower Color Induced by Interspecific Sexual Interaction.

    Directory of Open Access Journals (Sweden)

    Yuma Takahashi

    Full Text Available Understanding the mechanisms shaping the spatiotemporal distribution of species has long been a central concern of ecology and evolutionary biology. Contemporary patterns of plant assemblies suggest that sexual interactions among species, i.e., reproductive interference, lead to the exclusive distributions of closely related species that share pollinators. However, the fitness consequences and the initial ecological/evolutionary responses to reproductive interference remain unclear in nature, since reproductive isolation or allopatric distribution has already been achieved in the natural community. In Japan, three species of blue-eyed grasses (Sisyrinchium with incomplete reproductive isolation have recently colonized and occur sympatrically. Two of them are monomorphic with white flowers, whereas the other exhibits heritable color polymorphism (white and purple morphs. Here we investigated the effects of the presence of two monomorphic species on the distribution and reproductive success of color morphs. The frequency and reproductive success of white morphs decreased in area where monomorphic species were abundant, while those of purple morphs did not. The rate of hybridization between species was higher in white morphs than in the purple ones. Resource competition and habitat preference seemed not to contribute to the spatial distribution and reproductive success of two morphs. Our results supported that color-dependent reproductive interference determines the distribution of flower color polymorphism in a habitat, implying ecological sorting promoted by pollinator-mediated reproductive interference. Our study helps us to understand the evolution and spatial structure of flower color in a community.

  12. 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

  13. 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

  14. 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.

  15. 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...

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. Stellar bars and the spatial distribution of infrared luminosity

    International Nuclear Information System (INIS)

    Devereux, N.

    1987-01-01

    Ground-based 10 micron observations of the central region of over 100 infrared luminous galaxies are presented. A first order estimate of the spatial distribution of infrared emission in galaxies is obtained through a combination of ground-based and Infrared Astronomy Satellite (IRAS) data. The galaxies are nearby and primarily noninteracting, permitting an unbiased investigation of correlations with Hubble type. Approximately 40% of the early-type barred galaxies in this sample are associated with enhanced luminosity in the central (approximately 1 kpc diameter) region. The underlying luminosity source is attributed to both Seyfert and star formation activity. Late-type spirals are different in that the spatial distribution of infrared emission and the infrared luminoisty are not strongly dependent on barred morphology

  1. 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

  2. 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.

  3. 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.

  4. 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).

  5. Variability of the raindrop size distribution at small spatial scales

    Science.gov (United States)

    Berne, A.; Jaffrain, J.

    2010-12-01

    Because of the interactions between atmospheric turbulence and cloud microphysics, the raindrop size distribution (DSD) is strongly variable in space and time. The spatial variability of the DSD at small spatial scales (below a few km) is not well documented and not well understood, mainly because of a lack of adequate measurements at the appropriate resolutions. A network of 16 disdrometers (Parsivels) has been designed and set up over EPFL campus in Lausanne, Switzerland. This network covers a typical operational weather radar pixel of 1x1 km2. The question of the significance of the variability of the DSD at such small scales is relevant for radar remote sensing of rainfall because the DSD is often assumed to be uniform within a radar sample volume and because the Z-R relationships used to convert the measured radar reflectivity Z into rain rate R are usually derived from point measurements. Thanks to the number of disdrometers, it was possible to quantify the spatial variability of the DSD at the radar pixel scale and to show that it can be significant. In this contribution, we show that the variability of the total drop concentration, of the median volume diameter and of the rain rate are significant, taking into account the sampling uncertainty associated with disdrometer measurements. The influence of this variability on the Z-R relationship can be non-negligible. Finally, the spatial structure of the DSD is quantified using a geostatistical tool, the variogram, and indicates high spatial correlation within a radar pixel.

  6. 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.

  7. 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

  8. 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...

  9. Spatial distribution of H II regions in NGC 4321

    International Nuclear Information System (INIS)

    Anderson, S.; Hodge, P.; Kennicutt, R.C. Jr.

    1983-01-01

    A catalog of 286 H II regions in the giant Sc Virgo Cluster spiral galaxy NGC 4321 is used to analyze some aspects of this galaxy's spiral structure. The H II region distribution is rectified to face-on by least-squares fitting to a logarithmic spiral, and the radial distribution, the across-arm distribution, and the along-arm distribution of H II regions are determined. Comparison of the circular distribution with a simple shock wave model of the density wave theory does not clearly support the model. Arm 1 shows no obvious structure, and arm 2, although it has a clear peak, does not show the expected asymmetrical distribution. Agreement is reasonably good, however, with the somewhat more elaborate density wave model of Bash. Tests for clumping of the H II regions were negative

  10. 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

  11. Bilinear reduced order approximate model of parabolic distributed solar collectors

    KAUST Repository

    Elmetennani, Shahrazed; Laleg-Kirati, Taous-Meriem

    2015-01-01

    This paper proposes a novel, low dimensional and accurate approximate model for the distributed parabolic solar collector, by means of a modified gaussian interpolation along the spatial domain. The proposed reduced model, taking the form of a low

  12. THE IMPACT OF SPATIAL AND TEMPORAL RESOLUTIONS IN TROPICAL SUMMER RAINFALL DISTRIBUTION: PRELIMINARY RESULTS

    Directory of Open Access Journals (Sweden)

    Q. Liu

    2017-10-01

    Full Text Available 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.

  13. 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.

  14. Disease spread across multiple scales in a spatial hierarchy: effect of host spatial structure and of inoculum quantity and distribution.

    Science.gov (United States)

    Gosme, Marie; Lucas, Philippe

    2009-07-01

    Spatial patterns of both the host and the disease influence disease spread and crop losses. Therefore, the manipulation of these patterns might help improve control strategies. Considering disease spread across multiple scales in a spatial hierarchy allows one to capture important features of epidemics developing in space without using explicitly spatialized variables. Thus, if the system under study is composed of roots, plants, and planting hills, the effect of host spatial pattern can be studied by varying the number of plants per planting hill. A simulation model based on hierarchy theory was used to simulate the effects of large versus small planting hills, low versus high level of initial infections, and aggregated versus uniform distribution of initial infections. The results showed that aggregating the initially infected plants always resulted in slower epidemics than spreading out the initial infections uniformly. Simulation results also showed that, in most cases, disease epidemics were slower in the case of large host aggregates (100 plants/hill) than with smaller aggregates (25 plants/hill), except when the initially infected plants were both numerous and spread out uniformly. The optimal strategy for disease control depends on several factors, including initial conditions. More importantly, the model offers a framework to account for the interplay between the spatial characteristics of the system, rates of infection, and aggregation of the disease.

  15. Spatial occupancy models for large data sets

    Science.gov (United States)

    Johnson, Devin S.; Conn, Paul B.; Hooten, Mevin B.; Ray, Justina C.; Pond, Bruce A.

    2013-01-01

    Since its development, occupancy modeling has become a popular and useful tool for ecologists wishing to learn about the dynamics of species occurrence over time and space. Such models require presence–absence data to be collected at spatially indexed survey units. However, only recently have researchers recognized the need to correct for spatially induced overdisperison by explicitly accounting for spatial autocorrelation in occupancy probability. Previous efforts to incorporate such autocorrelation have largely focused on logit-normal formulations for occupancy, with spatial autocorrelation induced by a random effect within a hierarchical modeling framework. Although useful, computational time generally limits such an approach to relatively small data sets, and there are often problems with algorithm instability, yielding unsatisfactory results. Further, recent research has revealed a hidden form of multicollinearity in such applications, which may lead to parameter bias if not explicitly addressed. Combining several techniques, we present a unifying hierarchical spatial occupancy model specification that is particularly effective over large spatial extents. This approach employs a probit mixture framework for occupancy and can easily accommodate a reduced-dimensional spatial process to resolve issues with multicollinearity and spatial confounding while improving algorithm convergence. Using open-source software, we demonstrate this new model specification using a case study involving occupancy of caribou (Rangifer tarandus) over a set of 1080 survey units spanning a large contiguous region (108 000 km2) in northern Ontario, Canada. Overall, the combination of a more efficient specification and open-source software allows for a facile and stable implementation of spatial occupancy models for large data sets.

  16. 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

    of the Caesalpinioideae that are endemic in Central Africa (Democratic Republic of the Congo, Burundi and Rwanda). The objectives of this study were to identify the environmental factors that constrain their distribution, to determine the potential areas where each species could be present, to assess the current...

  17. Graphic display of spatially distributed binary-state experimental data

    International Nuclear Information System (INIS)

    Watson, B.L.

    1981-01-01

    Experimental data collected from a large number of transducers spatially distributed throughout a three-dimensional volume has typically posed a difficult interpretation task for the analyst. This paper describes one approach to alleviating this problem by presenting color graphic displays of experimental data; specifically, data representing the dynamic three-dimensional distribution of cooling fluid collected during the reflood and refill of simulated nuclear reactor vessels. Color-coded binary data (wet/dry) are integrated with a graphic representation of the reactor vessel and displayed on a high-resolution color CRT. The display is updated with successive data sets and made into 16-mm movies for distribution and analysis. Specific display formats are presented and extension to other applications discussed

  18. Evaluating spatial patterns in hydrological modelling

    DEFF Research Database (Denmark)

    Koch, Julian

    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...... 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...

  19. Improving the accuracy of livestock distribution estimates through spatial interpolation.

    Science.gov (United States)

    Bryssinckx, Ward; Ducheyne, Els; Muhwezi, Bernard; Godfrey, Sunday; Mintiens, Koen; Leirs, Herwig; Hendrickx, Guy

    2012-11-01

    Animal distribution maps serve many purposes such as estimating transmission risk of zoonotic pathogens to both animals and humans. The reliability and usability of such maps is highly dependent on the quality of the input data. However, decisions on how to perform livestock surveys are often based on previous work without considering possible consequences. A better understanding of the impact of using different sample designs and processing steps on the accuracy of livestock distribution estimates was acquired through iterative experiments using detailed survey. The importance of sample size, sample design and aggregation is demonstrated and spatial interpolation is presented as a potential way to improve cattle number estimates. As expected, results show that an increasing sample size increased the precision of cattle number estimates but these improvements were mainly seen when the initial sample size was relatively low (e.g. a median relative error decrease of 0.04% per sampled parish for sample sizes below 500 parishes). For higher sample sizes, the added value of further increasing the number of samples declined rapidly (e.g. a median relative error decrease of 0.01% per sampled parish for sample sizes above 500 parishes. When a two-stage stratified sample design was applied to yield more evenly distributed samples, accuracy levels were higher for low sample densities and stabilised at lower sample sizes compared to one-stage stratified sampling. Aggregating the resulting cattle number estimates yielded significantly more accurate results because of averaging under- and over-estimates (e.g. when aggregating cattle number estimates from subcounty to district level, P interpolation to fill in missing values in non-sampled areas, accuracy is improved remarkably. This counts especially for low sample sizes and spatially even distributed samples (e.g. P <0.001 for a sample of 170 parishes using one-stage stratified sampling and aggregation on district level

  20. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-07-01

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

  2. Behavioral correlates of the distributed coding of spatial context.

    Science.gov (United States)

    Anderson, Michael I; Killing, Sarah; Morris, Caitlin; O'Donoghue, Alan; Onyiagha, Dikennam; Stevenson, Rosemary; Verriotis, Madeleine; Jeffery, Kathryn J

    2006-01-01

    Hippocampal place cells respond heterogeneously to elemental changes of a compound spatial context, suggesting that they form a distributed code of context, whereby context information is shared across a population of neurons. The question arises as to what this distributed code might be useful for. The present study explored two possibilities: one, that it allows contexts with common elements to be disambiguated, and the other, that it allows a given context to be associated with more than one outcome. We used two naturalistic measures of context processing in rats, rearing and thigmotaxis (boundary-hugging), to explore how rats responded to contextual novelty and to relate this to the behavior of place cells. In experiment 1, rats showed dishabituation of rearing to a novel reconfiguration of familiar context elements, suggesting that they perceived the reconfiguration as novel, a behavior that parallels that of place cells in a similar situation. In experiment 2, rats were trained in a place preference task on an open-field arena. A change in the arena context triggered renewed thigmotaxis, and yet navigation continued unimpaired, indicating simultaneous representation of both the altered contextual and constant spatial cues. Place cells similarly exhibited a dual population of responses, consistent with the hypothesis that their activity underlies spatial behavior. Together, these experiments suggest that heterogeneous context encoding (or "partial remapping") by place cells may function to allow the flexible assignment of associations to contexts, a faculty that could be useful in episodic memory encoding. Copyright (c) 2006 Wiley-Liss, Inc.

  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. 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.

  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. Reducing Spatial Data Complexity for Classification Models

    Science.gov (United States)

    Ruta, Dymitr; Gabrys, Bogdan

    2007-11-01

    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

  7. Bayesian spatial transformation models with applications in neuroimaging data.

    Science.gov (United States)

    Miranda, Michelle F; Zhu, Hongtu; Ibrahim, Joseph G

    2013-12-01

    The aim of this article is to develop a class of spatial transformation models (STM) to spatially model the varying association between imaging measures in a three-dimensional (3D) volume (or 2D surface) and a set of covariates. The proposed STM include a varying Box-Cox transformation model for dealing with the issue of non-Gaussian distributed imaging data and a Gaussian Markov random field model for incorporating spatial smoothness of the imaging data. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. Simulations and real data analysis demonstrate that the STM significantly outperforms the voxel-wise linear model with Gaussian noise in recovering meaningful geometric patterns. Our STM is able to reveal important brain regions with morphological changes in children with attention deficit hyperactivity disorder. © 2013, The International Biometric Society.

  8. Precise Mapping Of A Spatially Distributed Radioactive Source

    International Nuclear Information System (INIS)

    Beck, A.; Caras, I.; Piestum, S.; Sheli, E.; Melamud, Y.; Berant, S.; Kadmon, Y.; Tirosh, D.

    1999-01-01

    Spatial distribution measurement of radioactive sources is a routine task in the nuclear industry. The precision of each measurement depends upon the specific application. However, the technological edge of this precision is motivated by the production of standards for calibration. Within this definition, the most demanding field is the calibration of standards for medical equipment. In this paper, a semi-empirical method for controlling the measurement precision is demonstrated, using a relatively simple laboratory apparatus. The spatial distribution of the source radioactivity is measured as part of the quality assurance tests, during the production of flood sources. These sources are further used in calibration of medical gamma cameras. A typical flood source is a 40 x 60 cm 2 plate with an activity of 10 mCi (or more) of 57 Co isotope. The measurement set-up is based on a single NaI(Tl) scintillator with a photomultiplier tube, moving on an X Y table which scans the flood source. In this application the source is required to have a uniform activity distribution over its surface

  9. 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.

  10. From Logical to Distributional Models

    Directory of Open Access Journals (Sweden)

    Anne Preller

    2014-12-01

    Full Text Available The paper relates two variants of semantic models for natural language, logical functional models and compositional distributional vector space models, by transferring the logic and reasoning from the logical to the distributional models. The geometrical operations of quantum logic are reformulated as algebraic operations on vectors. A map from functional models to vector space models makes it possible to compare the meaning of sentences word by word.

  11. 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

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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)

  18. Spatial and temporal distribution of tropical biomass burning

    Science.gov (United States)

    Hao, Wei Min; Liu, Mei-Huey

    1994-12-01

    A database for the spatial and temporal distribution of the amount of biomass burned in tropical America, Africa, and Asia during the late 1970s is presented with a resolution of 5° latitude × 5° longitude. The sources of burning in each grid cell have been quantified. Savanna fires, shifting cultivation, deforestation, fuel wood use, and burning of agricultural residues contribute about 50, 24, 10, 11, and 5%, respectively, of total biomass burned in the tropics. Savanna fires dominate in tropical Africa, and forest fires dominate in tropical Asia. A similar amount of biomass is burned from forest and savanna fires in tropical America. The distribution of biomass burned monthly during the dry season has been derived for each grid cell using the seasonal cycles of surface ozone concentrations. Land use changes during the last decade could have a profound impact on the amount of biomass burned and the amount of trace gases and aerosol particles emitted.

  19. Social disorganization, social capital, collective efficacy and the spatial distribution of crime and offenders: An empirical test of six neighbourhood models

    NARCIS (Netherlands)

    Bruinsma, G.J.N.; Pauwels, L.J.R; Weerman, F.M.; Bernasco, W.

    2013-01-01

    Six different social disorganization models of neighbourhood crime and offender rates were tested using data from multiple sources in the city of The Hague, in the Netherlands. The sources included a community survey among 3,575 residents in 86 neighbourhoods measuring the central concepts of the

  20. Enhanced effects of biotic interactions on predicting multispecies spatial distribution of submerged macrophytes after eutrophication.

    Science.gov (United States)

    Song, Kun; Cui, Yichong; Zhang, Xijin; Pan, Yingji; Xu, Junli; Xu, Kaiqin; Da, Liangjun

    2017-10-01

    Water eutrophication creates unfavorable environmental conditions for submerged macrophytes. In these situations, biotic interactions may be particularly important for explaining and predicting the submerged macrophytes occurrence. Here, we evaluate the roles of biotic interactions in predicting spatial occurrence of submerged macrophytes in 1959 and 2009 for Dianshan Lake in eastern China, which became eutrophic since the 1980s. For the four common species occurred in 1959 and 2009, null species distribution models based on abiotic variables and full models based on both abiotic and biotic variables were developed using generalized linear model (GLM) and boosted regression trees (BRT) to determine whether the biotic variables improved the model performance. Hierarchical Bayesian-based joint species distribution models capable of detecting paired biotic interactions were established for each species in both periods to evaluate the changes in the biotic interactions. In most of the GLM and BRT models, the full models showed better performance than the null models in predicting the species presence/absence, and the relative importance of the biotic variables in the full models increased from less than 50% in 1959 to more than 50% in 2009 for each species. Moreover, co-occurrence correlation of each paired species interaction was higher in 2009 than that in 1959. The findings suggest biotic interactions that tend to be positive play more important roles in the spatial distribution of multispecies assemblages of macrophytes and should be included in prediction models to improve prediction accuracy when forecasting macrophytes' distribution under eutrophication stress.

  1. The Spatial Variability of Beryllium-7 Depth Distribution Study

    International Nuclear Information System (INIS)

    Jalal Sharib; Zainudin Othman; Dainee Nor Fardzila Ahmad Tugi; Noor Fadzilah Yusof; Mohd Tarmizi Ishak

    2015-01-01

    The objective of this paper is to study the spatial variability of 7 Be depth evolution in soil profile at two different sampling sites. The soil samples have been collected by using metal core in bare area in Bangi, Selangor and Timah Tasoh, Perlis , Malaysia. Two composite core samples for each sampling sites has been sectioned into 2 mm increments to a depth of 4 cm and oven dried at 45- 60 degree Celsius and gently desegregated. These two composite spatial samples are passed through a < 2 mm sieve and packed into proper geometry plastic container for 7 Be analysis by using gamma spectrometry with a 24-hour count time. From the findings, the 7 Be content in the soil samples from Bangi, Selangor study area is distributed lower depth penetration into the soil profile than Timah Tasoh, Perlis catchment due to many factors such as precipitation (fallout) and others. However, the spatial variability from both samples study area is also decreases exponentially with depth and is confined within the top few centimeters and similar with other works been reported (Blake et al., (2000) and Walling et al.,(2008). Furthermore, a detailed discussion from this study findings will be in full papers. (author)

  2. A simplified spatial model for BWR stability

    International Nuclear Information System (INIS)

    Berman, Y.; Lederer, Y.; Meron, E.

    2012-01-01

    A spatial reduced order model for the study of BWR stability, based on the phenomenological model of March-Leuba et al., is presented. As one dimensional spatial dependence of the neutron flux, fuel temperature and void fraction is introduced, it is possible to describe both global and regional oscillations of the reactor power. Both linear stability analysis and numerical analysis were applied in order to describe the parameters which govern the model stability. The results were found qualitatively similar to past results. Doppler reactivity feedback was found essential for the explanation of the different regions of the flow-power stability map. (authors)

  3. Modelling the Spatial Isotope Variability of Precipitation in Syria

    Energy Technology Data Exchange (ETDEWEB)

    Kattan, Z.; Kattaa, B. [Department of Geology, Atomic Energy Commission of Syria (AECS), Damascus (Syrian Arab Republic)

    2013-07-15

    Attempts were made to model the spatial variability of environmental isotope ({sup 18}O, {sup 2}H and {sup 3}H) compositions of precipitation in syria. Rainfall samples periodically collected on a monthly basis from 16 different stations were used for processing and demonstrating the spatial distributions of these isotopes, together with those of deuterium excess (d) values. Mathematically, the modelling process was based on applying simple polynomial models that take into consideration the effects of major geographic factors (Lon.E., Lat.N., and altitude). The modelling results of spatial distribution of stable isotopes ({sup 18}O and {sup 2}H) were generally good, as shown from the high correlation coefficients (R{sup 2} = 0.7-0.8), calculated between the observed and predicted values. In the case of deuterium excess and tritium distributions, the results were most likely approximates (R{sup 2} = 0.5-0.6). Improving the simulation of spatial isotope variability probably requires the incorporation of other local meteorological factors, such as relative air humidity, precipitation amount and vapour pressure, which are supposed to play an important role in such an arid country. (author)

  4. Modeling human-water-systems: towards a comprehensive and spatially distributed assessment of co-evolutions for river basins in Central Europe

    Directory of Open Access Journals (Sweden)

    P. Krahe

    2016-05-01

    Full Text Available In the context of river basin and flood risk management there is a growing need to improve the understanding of and the feedbacks between the driving forces “climate and socio-economy” and water systems. We make use of a variety of data resources to illustrate interrelationships between different constituents of the human-water-systems. Taking water storage for energy production as an example we present a first analysis on the co-evolution of socio-economic and hydrological indicators. The findings will serve as for the development of conceptual, but fully coupled socio-hydrological models for selected sectors and regions. These models will be used to generate integrated scenarios of the climate and socio-economic change.

  5. 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.

  6. Research on spatial distribution of photosynthetic characteristics of Winter Wheat

    Science.gov (United States)

    Yan, Q. Q.; Zhou, Q. Y.; Zhang, B. Z.; Han, X.; Han, N. N.; Li, S. M.

    2018-03-01

    In order to explore the spatial distribution of photosynthetic characteristics of winter wheat leaf, the photosynthetic rate on different parts of leaf (leaf base-leaf middle-leaf apex) and that on each canopy (top layer-middle layer-bottom layer) leaf during the whole growth period of winter wheat were measured. The variation of photosynthetic rate with PAR and the spatial distribution of winter wheat leaf during the whole growth periods were analysed. The results showed that the photosynthetic rate of different parts of winter wheat increased with the increase of PAR, which was showed as leaf base>leaf middle>leaf apex. In the same growth period, photosynthetic rate in different parts of the tablet was showed as leaf middle>leaf base>leaf apex. For the different canopy layer of winter wheat, the photosynthetic rate of the top layer leaf was significantly greater than that of the middle layer and lower layer leaf. The photosynthetic rate of the top layer leaf was the largest in the leaf base position. The photosynthetic rate of leaf of the same canopy layer at different growth stages were showed as tasseling stage >grain filling stage > maturation stage.

  7. Reduction of spatial distribution of risk factors for transportation of contaminants released by coal mining activities.

    Science.gov (United States)

    Karan, Shivesh Kishore; Samadder, Sukha Ranjan

    2016-09-15

    It is reported that water-energy nexus composes two of the biggest development and human health challenges. In the present study we presented a Risk Potential Index (RPI) model which encapsulates Source, Vector (Transport), and Target risks for forecasting surface water contamination. The main aim of the model is to identify critical surface water risk zones for an open cast mining environment, taking Jharia Coalfield, India as the study area. The model also helps in feasible sampling design. Based on spatial analysis various risk zones were successfully delineated. Monthly RPI distribution revealed that the risk of surface water contamination was highest during the monsoon months. Surface water samples were analysed to validate the model. A GIS based alternative management option was proposed to reduce surface water contamination risk and observed 96% and 86% decrease in the spatial distribution of very high risk areas for the months June and July respectively. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. Spatial distribution of small-leaved forests in Kuznetskaya depression

    Directory of Open Access Journals (Sweden)

    A. F. Gulyaeva

    2016-03-01

    Full Text Available The article is devoted to the spatial distribution of small-leaved forests in Kuznetskaya depression where they are forest component of zonal forest-steppe vegetation. Two levels of spatial organization were determined. According to mesorelief communities of different associations are organized into topo-ecological series. These series differ by length and set of communities. On higher level spatial distribution is controlled by climate and reflects zonal structure. Central part of the depression is occupied by Artemisio–Betuletum communities in combination with communities of Calamagrostio–Betuletum which occur in more humid habitats. Near the eastern edge of the depres­sion forest vegetation is represented by combination of Trollio–Populetum and Campanulo–Betuletum communities where the first one is more typical for the plain conditions and second one – for the mountainous environment. In south­ern part of the depression communities of Campanulo–Betuletum are widespread in combination with Saussureo–Populetum communities which localized on higher well-moisturized slopes. In north-western part syntaxonomical diversity drops down to one association – Primulo–Betuletum, and communities of Carici–Betuletum association occur across the whole depression in lowest relief positions. Climatically it is possible to distinguish two belts – forest-steppe and subtaiga. Forest-steppe is represented by two types – typical plain forest-steppe in north-western part and submountainous forest-steppe in the central part of depression. Subtaiga belt in the depression is developed on eastern edge, but in western part it exists only on mountain slopes.

  9. Experimental measurements of spatial dose distributions in radiosurgery treatments

    International Nuclear Information System (INIS)

    Avila-Rodriguez, M. A.; Rodriguez-Villafuerte, M.; Diaz-Perches, R.; Perez-Pastenes, M. A.

    2001-01-01

    The measurement of stereotactic radiosurgery dose distributions requires an integrating, high-resolution dosimeter capable of providing a spatial map of absorbed dose. This paper describes the use of a commercial radiochromic dye film (GafChromic MD-55-2) to measure radiosurgery dose distributions with 6 MV X-rays in a head phantom. The response of the MD-55-2 was evaluated by digitizing and analyzing the films with conventional computer systems. Radiosurgery dose distributions were measured using the radiochromic film in a spherical acrylic phantom of 16 cm diameter undergoing a typical SRS treatment as a patient, and were compared with dose distributions provided by the treatment planning system. The comparison lead to mean radial differences of ±0.6 mm, ±0.9 mm, ±1.3 mm, ±1.9 mm, and ±2.8 mm, for the 80, 60, 50, 40, and 30% isodose curves, respectively. It is concluded that the radiochromic film is a convenient and useful tool for radiosurgery treatment planning validation

  10. 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

  11. Distributed Parameter Modelling Applications

    DEFF Research Database (Denmark)

    Sales-Cruz, Mauricio; Cameron, Ian; Gani, Rafiqul

    2011-01-01

    and the development of a short-path evaporator. The oil shale processing problem illustrates the interplay amongst particle flows in rotating drums, heat and mass transfer between solid and gas phases. The industrial application considers the dynamics of an Alberta-Taciuk processor, commonly used in shale oil and oil...... the steady state, distributed behaviour of a short-path evaporator....

  12. 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

    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......, realistic and practical, and it can be applied to other areas, thereby providing a tool to facilitate the implementation of pedological/hydrological plans for conservation and sustainable management. It is particularly useful when information about soil properties from conventional field surveys is limited....

  13. Analysing earthquake slip models with the spatial prediction comparison test

    KAUST Repository

    Zhang, L.; Mai, Paul Martin; Thingbaijam, Kiran Kumar; Razafindrakoto, H. N. T.; Genton, Marc G.

    2014-01-01

    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.

  14. 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.

  15. 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

  16. Incorporating uncertainty in predictive species distribution modelling.

    Science.gov (United States)

    Beale, Colin M; Lennon, Jack J

    2012-01-19

    Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and process-based models. We identify sources of uncertainty for each class and discuss how uncertainty can be minimized or included in the modelling process to give realistic measures of confidence around predictions. Because this has typically not been performed, we conclude that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution. We identify areas where development of new statistical tools will improve predictions from distribution models, notably the development of hierarchical models that link different types of distribution model and their attendant uncertainties across spatial scales. Finally, we discuss the need to develop more defensible methods for assessing predictive performance, quantifying model goodness-of-fit and for assessing the significance of model covariates.

  17. Spatial scale separation in regional climate modelling

    Energy Technology Data Exchange (ETDEWEB)

    Feser, F.

    2005-07-01

    In this thesis the concept of scale separation is introduced as a tool for first improving regional climate model simulations and, secondly, to explicitly detect and describe the added value obtained by regional modelling. The basic idea behind this is that global and regional climate models have their best performance at different spatial scales. Therefore the regional model should not alter the global model's results at large scales. The for this purpose designed concept of nudging of large scales controls the large scales within the regional model domain and keeps them close to the global forcing model whereby the regional scales are left unchanged. For ensemble simulations nudging of large scales strongly reduces the divergence of the different simulations compared to the standard approach ensemble that occasionally shows large differences for the individual realisations. For climate hindcasts this method leads to results which are on average closer to observed states than the standard approach. Also the analysis of the regional climate model simulation can be improved by separating the results into different spatial domains. This was done by developing and applying digital filters that perform the scale separation effectively without great computational effort. The separation of the results into different spatial scales simplifies model validation and process studies. The search for 'added value' can be conducted on the spatial scales the regional climate model was designed for giving clearer results than by analysing unfiltered meteorological fields. To examine the skill of the different simulations pattern correlation coefficients were calculated between the global reanalyses, the regional climate model simulation and, as a reference, of an operational regional weather analysis. The regional climate model simulation driven with large-scale constraints achieved a high increase in similarity to the operational analyses for medium-scale 2 meter

  18. Non-monotonic spatial distribution of the interstellar dust in astrospheres: finite gyroradius effect

    Science.gov (United States)

    Katushkina, O. A.; Alexashov, D. B.; Izmodenov, V. V.; Gvaramadze, V. V.

    2017-02-01

    High-resolution mid-infrared observations of astrospheres show that many of them have filamentary (cirrus-like) structure. Using numerical models of dust dynamics in astrospheres, we suggest that their filamentary structure might be related to specific spatial distribution of the interstellar dust around the stars, caused by a gyrorotation of charged dust grains in the interstellar magnetic field. Our numerical model describes the dust dynamics in astrospheres under an influence of the Lorentz force and assumption of a constant dust charge. Calculations are performed for the dust grains with different sizes separately. It is shown that non-monotonic spatial dust distribution (viewed as filaments) appears for dust grains with the period of gyromotion comparable with the characteristic time-scale of the dust motion in the astrosphere. Numerical modelling demonstrates that the number of filaments depends on charge-to-mass ratio of dust.

  19. 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

  20. 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...

  1. 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.

  2. A spatial emergy model for Alachua County, Florida

    Science.gov (United States)

    Lambert, James David

    A spatial model of the distribution of energy flows and storages in Alachua County, Florida, was created and used to analyze spatial patterns of energy transformation hierarchy in relation to spatial patterns of human settlement. Emergy, the available energy of one kind previously required directly or indirectly to make a product or service, was used as a measure of the quality of the different forms of energy flows and storages. Emergy provides a common unit of measure for comparing the productive contributions of natural processes with those of economic and social processes---it is an alternative to using money for measuring value. A geographic information system was used to create a spatial model and make maps that show the distribution and magnitude of different types of energy and emergy flows and storages occurring in one-hectare land units. Energy transformities were used to convert individual energy flows and storages into emergy units. Maps of transformities were created that reveal a clear spatial pattern of energy transformation hierarchy. The maps display patterns of widely-dispersed areas with lower transformity energy flows and storages, and smaller, centrally-located areas with higher transformities. Energy signature graphs and spatial unit transformities were used to characterize and compare the types and amounts of energy being consumed and stored according to land use classification, planning unit, and neighborhood categories. Emergy ratio maps and spatial unit ratios were created by dividing the values for specific emergy flows or storages by the values for other emergy flows or storages. Spatial context analysis was used to analyze the spatial distribution patterns of mean and maximum values for emergy flows and storages. The modeling method developed for this study is general and applicable to all types of landscapes and could be applied at any scale. An advantage of this general approach is that the results of other studies using this method

  3. 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.

  4. 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

  5. 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.

  6. Single-server queues with spatially distributed arrivals

    NARCIS (Netherlands)

    Kroese, Dirk; Schmidt, Volker

    1994-01-01

    Consider a queueing system where customers arrive at a circle according to a homogeneous Poisson process. After choosing their positions on the circle, according to a uniform distribution, they wait for a single server who travels on the circle. The server's movement is modelled by a Brownian motion

  7. Can Bt maize change the spatial distribution of predator Cycloneda ...

    African Journals Online (AJOL)

    Cultivation of Bt crops is an important tactic in integrated pest management. The effect of Bt maize on arthropod predators needs to be investigated because of the important role of these natural enemies in the absence of target pests. The objective of the present study was to generate information on the distribution model of ...

  8. Detection of endolithic spatial distribution in marble stone.

    Science.gov (United States)

    Casanova Municchia, A; Percario, Z; Caneva, G

    2014-10-01

    The penetration of endolithic microorganisms, which develop to depths of several millimetres or even centimetres into the stone, and the diffusion of their extracellular substances speeds up the stone deterioration process. The aim of this study was to investigate, using a confocal laser scanning microscopy with a double-staining, a marble rock sample by observing the endolithic spatial distribution and quantifying the volume they occupied within the stone, in order to understand the real impact of these microorganisms on the conservation of stone monuments. Often the only factors taken into account by biodeterioration studies regarding endolithic microorganisms, are spread and depth of penetration. Despite the knowledge of three-dimensional spatial distribution and quantification of volume, it is indispensable to understand the real damage caused by endolithic microorganisms to stone monuments. In this work, we analyze a marble rock sample using a confocal laser scanning microscopy stained with propidium iodide and Concavalin-A conjugate with the fluorophore Alexa Fluor 488, comparing these results with other techniques (SEM microscope, microphotographs of polished cross-sections and thin-section, PAS staining methods), An image analysis approach has also been applied. The use of confocal laser scanning microscopy with double staining shows clear evidence of the presence of endolithic microorganisms (cyanobacteria and fungi) as well as the extracellular polymeric substance matrix in a three-dimensional architecture as part of the rock sample, this technique, therefore, seems very useful when applied to restoration interventions on stone monuments when endolithic growth is suspected. © 2014 The Authors Journal of Microscopy © 2014 Royal Microscopical Society.

  9. Spatial distribution of conduction disorders during sinus rhythm.

    Science.gov (United States)

    Lanters, Eva A H; Yaksh, Ameeta; Teuwen, Christophe P; van der Does, Lisette J M E; Kik, Charles; Knops, Paul; van Marion, Denise M S; Brundel, Bianca J J M; Bogers, Ad J J C; Allessie, Maurits A; de Groot, Natasja M S

    2017-12-15

    Length of lines of conduction block (CB) during sinus rhythm (SR) at Bachmann's bundle (BB) is associated with atrial fibrillation (AF). However, it is unknown whether extensiveness of CB at BB represents CB elsewhere in the atria. We aim to investigate during SR 1) the spatial distribution and extensiveness of CB 2) whether there is a predilection site for CB and 3) the association between CB and incidence of post-operative AF. During SR, epicardial mapping of the right atrium (RA), BB and left atrium was performed in 209 patients with coronary artery disease. The amount of conduction delay (CD, Δlocal activation time ≥7ms) and CB (Δ≥12ms) was quantified as % of the mapping area. Atrial regions were compared to identify potential predilection sites for CD/CB. Correlations between CD/CB and clinical characteristics were tested. Areas with CD or CB were present in all patients, overall prevalence was respectively 1.4(0.2-4.0) % and 1.3(0.1-4.3) %. Extensiveness and spatial distribution of CD/CB varied considerably, however occurred mainly at the superior intercaval RA. Of all clinicalcharacteristics, CD/CB only correlated weakly with age and diabetes (P<0.05). A 1% increase in CD or CB caused a 1.1-1.5ms prolongation of the activation time (P<0.001). There was no correlation between CD/CB and post-operative AF. CD/CB during SR in CABG patients with electrically non-remodeled atria show considerable intra-atrial, but also inter-individual variation. Despite these differences, a predilection site is present at the superior intercaval RA. Extensiveness of CB at the superior intercaval RA or BB does not reflect CB elsewhere in the atria and is not associated with post-operative AF. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. 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...

  11. Towards a 3d Spatial Urban Energy Modelling Approach

    Science.gov (United States)

    Bahu, J.-M.; Koch, A.; Kremers, E.; Murshed, S. M.

    2013-09-01

    Today's needs to reduce the environmental impact of energy use impose dramatic changes for energy infrastructure and existing demand patterns (e.g. buildings) corresponding to their specific context. In addition, future energy systems are expected to integrate a considerable share of fluctuating power sources and equally a high share of distributed generation of electricity. Energy system models capable of describing such future systems and allowing the simulation of the impact of these developments thus require a spatial representation in order to reflect the local context and the boundary conditions. This paper describes two recent research approaches developed at EIFER in the fields of (a) geo-localised simulation of heat energy demand in cities based on 3D morphological data and (b) spatially explicit Agent-Based Models (ABM) for the simulation of smart grids. 3D city models were used to assess solar potential and heat energy demand of residential buildings which enable cities to target the building refurbishment potentials. Distributed energy systems require innovative modelling techniques where individual components are represented and can interact. With this approach, several smart grid demonstrators were simulated, where heterogeneous models are spatially represented. Coupling 3D geodata with energy system ABMs holds different advantages for both approaches. On one hand, energy system models can be enhanced with high resolution data from 3D city models and their semantic relations. Furthermore, they allow for spatial analysis and visualisation of the results, with emphasis on spatially and structurally correlations among the different layers (e.g. infrastructure, buildings, administrative zones) to provide an integrated approach. On the other hand, 3D models can benefit from more detailed system description of energy infrastructure, representing dynamic phenomena and high resolution models for energy use at component level. The proposed modelling strategies

  12. 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.

  13. A Non-Gaussian Spatial Generalized Linear Latent Variable Model

    KAUST Repository

    Irincheeva, Irina; Cantoni, Eva; Genton, Marc G.

    2012-01-01

    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.

  14. A physically based analytical spatial air temperature and humidity model

    Science.gov (United States)

    Yang, Yang; Endreny, Theodore A.; Nowak, David J.

    2013-09-01

    Spatial variation of urban surface air temperature and humidity influences human thermal comfort, the settling rate of atmospheric pollutants, and plant physiology and growth. Given the lack of observations, we developed a Physically based Analytical Spatial Air Temperature and Humidity (PASATH) model. The PASATH model calculates spatial solar radiation and heat storage based on semiempirical functions and generates spatially distributed estimates based on inputs of topography, land cover, and the weather data measured at a reference site. The model assumes that for all grids under the same mesoscale climate, grid air temperature and humidity are modified by local variation in absorbed solar radiation and the partitioning of sensible and latent heat. The model uses a reference grid site for time series meteorological data and the air temperature and humidity of any other grid can be obtained by solving the heat flux network equations. PASATH was coupled with the USDA iTree-Hydro water balance model to obtain evapotranspiration terms and run from 20 to 29 August 2010 at a 360 m by 360 m grid scale and hourly time step across a 285 km2 watershed including the urban area of Syracuse, NY. PASATH predictions were tested at nine urban weather stations representing variability in urban topography and land cover. The PASATH model predictive efficiency R2 ranged from 0.81 to 0.99 for air temperature and 0.77 to 0.97 for dew point temperature. PASATH is expected to have broad applications on environmental and ecological models.

  15. 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.

  16. Spatial distribution of psychotic disorders in an urban area of France: an ecological study.

    Science.gov (United States)

    Pignon, Baptiste; Schürhoff, Franck; Baudin, Grégoire; Ferchiou, Aziz; Richard, Jean-Romain; Saba, Ghassen; Leboyer, Marion; Kirkbride, James B; Szöke, Andrei

    2016-05-18

    Previous analyses of neighbourhood variations of non-affective psychotic disorders (NAPD) have focused mainly on incidence. However, prevalence studies provide important insights on factors associated with disease evolution as well as for healthcare resource allocation. This study aimed to investigate the distribution of prevalent NAPD cases in an urban area in France. The number of cases in each neighbourhood was modelled as a function of potential confounders and ecological variables, namely: migrant density, economic deprivation and social fragmentation. This was modelled using statistical models of increasing complexity: frequentist models (using Poisson and negative binomial regressions), and several Bayesian models. For each model, assumptions validity were checked and compared as to how this fitted to the data, in order to test for possible spatial variation in prevalence. Data showed significant overdispersion (invalidating the Poisson regression model) and residual autocorrelation (suggesting the need to use Bayesian models). The best Bayesian model was Leroux's model (i.e. a model with both strong correlation between neighbouring areas and weaker correlation between areas further apart), with economic deprivation as an explanatory variable (OR = 1.13, 95% CI [1.02-1.25]). In comparison with frequentist methods, the Bayesian model showed a better fit. The number of cases showed non-random spatial distribution and was linked to economic deprivation.

  17. Impacts of C-uptake by plants on the spatial distribution of 14C accumulated in vegetation around a nuclear facility-Application of a sophisticated land surface 14C 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.

  18. A Modeling Framework for Schedulability Analysis of Distributed Avionics Systems

    DEFF Research Database (Denmark)

    Han, Pujie; Zhai, Zhengjun; Nielsen, Brian

    2018-01-01

    This paper presents a modeling framework for schedulability analysis of distributed integrated modular avionics (DIMA) systems that consist of spatially distributed ARINC-653 modules connected by a unified AFDX network. We model a DIMA system as a set of stopwatch automata (SWA) in UPPAAL...

  19. 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.

  20. GEMAS: Molybdenum Spatial Distribution Patterns in European Soil

    Science.gov (United States)

    Cicchella, Domenico; Zuzolo, Daniela; Demetriades, Alecos; De Vivo, Benedetto; Eklund, Mikael; Ladenberger, Anna; Negrel, Philippe; O'Connor, Patrick

    2017-04-01

    Molybdenum is an essential trace element for both plants and animals as well as for human being. It is one such trace element for which potential health concerns have been raised but for which few data exist and little investigation or interpretation of distributions in soils has been made. The main goal of this study was to fill this gap. Molybdenum (Mo) concentrations are reported for the similar spatial distribution patterns mainly governed by geology (parent material and mineralisation), as well as weathering, soil formation and climate since the last glaciations period. The dominant feature is represented by low Mo concentrations over the coarse-grained sandy deposits of the last glaciations in central northern Europe while the most extensive anomalies occur in Scandinavian soils. The highest Mo concentration value occurs to the North of Oslo close to one of the largest porphyry Mo deposit of the World. Some interesting anomalous patterns occur also in Italy in correspondence with alkaline volcanics, in Spain and Greece associated with sulfides mineralizations and in Slovenia and Croatia where are probably related to the long weathering history of karstic residual soils. Anomalous concentrations in some areas of Ireland represent a clear example of how an excess of molybdenum has produced potentially toxic pastures. In fact, these give rise to problems particularly in young cattle when excess molybdenum in the herbage acts as an antagonist, which militates against efficient copper absorption by the animal.

  1. 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

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. Analysis of the spatial distribution of infant mortality by cause of death in Austria in 1984 to 2006

    Directory of Open Access Journals (Sweden)

    Heinzl Harald

    2008-05-01

    Full Text Available Abstract Background In Austria, over the last 20 years infant mortality declined from 11.2 per 1,000 life births (1985 to 4.7 per 1,000 in1997 but remained rather constant since then. In addition to this time trend we already reported a non-random spatial distribution of infant mortality rates in a recent study covering the time period 1984 to 2002. This present study includes four additional years and now covers about 1.9 million individual birth certificates. It aimes to elucidate the observed non-random spatial distribution in more detail. We split up infant mortality into six groups according to the underlying cause of death. The underlying spatial distribution of standardized mortality ratios (SMR is estimated by univariate models as well as by two models incorporating all six groups simultaneously. Results We observe strong correlations between the individual spatial patterns of SMR's except for "Sudden Infant Death Syndrome" and to some extent for "Peripartal Problems". The spatial distribution of SMR's is non-random with an area of decreased risk in the South-East of Austria. The group "Sudden Infant Death Syndrome" clearly and the group "Peripartal Problems" slightly show deviations from the common pattern. When comparing univariate and multivariate SMR estimates we observe that the resulting spatial distributions are very similar. Conclusion We observe different non-random spatial distributions of infant mortality rates when grouped by cause of death. The models applied were based on individual data thereby avoiding ecological regression bias. The estimated spatial distributions do not substantially depend on the employed estimation method. The observed non-random spatial patterns of Austrian infant mortality remain to appear ambiguous.

  7. Control of spatial discretisation in coastal oil spill modelling

    OpenAIRE

    Li, Yang

    2007-01-01

    Spatial discretisation plays an important role in many numerical environmental models. This paper studies the control of spatial discretisation in coastal oil spill modelling with a view to assure the quality of modelling outputs for given spatial data inputs. Spatial data analysis techniques are effective for investigating and improving the spatial discretisation in different phases of the modelling. Proposed methods are implemented and tested with experimental models. A new “Automatic Searc...

  8. 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

  9. Spatial Models and Networks of Living Systems

    DEFF Research Database (Denmark)

    Juul, Jeppe Søgaard

    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...... variables of the system. However, this approach disregards any spatial structure of the system, which may potentially change the behaviour drastically. An alternative approach is to construct a cellular automaton with nearest neighbour interactions, or even to model the system as a complex network...... 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...

  10. A nonlocal spatial model for Lyme disease

    Science.gov (United States)

    Yu, Xiao; Zhao, Xiao-Qiang

    2016-07-01

    This paper is devoted to the study of a nonlocal and time-delayed reaction-diffusion model for Lyme disease with a spatially heterogeneous structure. In the case of a bounded domain, we first prove the existence of the positive steady state and a threshold type result for the disease-free system, and then establish the global dynamics for the model system in terms of the basic reproduction number. In the case of an unbound domain, we obtain the existence of the disease spreading speed and its coincidence with the minimal wave speed. At last, we use numerical simulations to verify our analytic results and investigate the influence of model parameters and spatial heterogeneity on the disease infection risk.

  11. 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.

  12. 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.

  13. 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.

  14. The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological models

    Science.gov (United States)

    Koch, Julian; Cüneyd Demirel, Mehmet; Stisen, Simon

    2018-05-01

    The process of model evaluation is not only an integral part of model development and calibration but also of paramount importance when communicating modelling results to the scientific community and stakeholders. The modelling community has a large and well-tested toolbox of metrics to evaluate temporal model performance. In contrast, spatial performance evaluation does not correspond 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 makes a contribution towards advancing spatial-pattern-oriented model calibration by rigorously testing a multiple-component performance metric. The promoted SPAtial EFficiency (SPAEF) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multiple-component approach is found to be advantageous in order to achieve the complex task of comparing spatial patterns. SPAEF, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are applied in a spatial-pattern-oriented model calibration of a catchment model in Denmark. Results suggest the importance of multiple-component metrics because stand-alone metrics tend to fail to provide holistic pattern information. The three SPAEF components are found to be independent, which allows them to complement each other in a meaningful way. In order to optimally exploit spatial observations made available by remote sensing platforms, this study suggests applying bias insensitive metrics which further allow for a comparison of variables which are related but may differ in unit. This study applies SPAEF in the hydrological context using the mesoscale Hydrologic Model (mHM; version 5.8), but we see great potential across disciplines related to spatially distributed earth system modelling.

  15. 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...

  16. Developing a modelling for the spatial data infrastructure

    CSIR Research Space (South Africa)

    Hjelmager, J

    2005-07-01

    Full Text Available The Commission on Spatial Data Standards of the International Cartographic Association (ICA) is working on defining spatial models and technical characteristics of a Spatial Data Infrastructure (SDI). To date, this work has been restricted...

  17. 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.

  18. Factor Copula Models for Replicated Spatial Data

    KAUST Repository

    Krupskii, Pavel; Huser, Raphaë l; Genton, Marc G.

    2016-01-01

    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.

  19. Modeling Spatially Unrestricted Pedestrian Traffic on Footbridges

    DEFF Research Database (Denmark)

    Zivanovic, Stana; Pavic, Aleksandar; Ingólfsson, Einar Thór

    2010-01-01

    restricted movement of pedestrians, has kept attracting attention of researchers. However, it is the normal spatially unrestricted pedestrian traffic, and its vertical dynamic loading component, that are most relevant for vibration serviceability checks for most footbridges. Despite the existence of numerous...... design procedures concerned with this loading, the current confidence in its modelling is low due to lack of verification of the models on as-built structures. This is the motivation behind reviewing the existing design procedures for modelling normal pedestrian traffic in this paper and evaluating...

  20. Spatial Distribution of Stable Isotopes of Precipitation in Kumamoto, Japan

    Energy Technology Data Exchange (ETDEWEB)

    Anoue, M. T.; Shimada, J. [Graduate School of Science and Technology, Kumamoto University (Japan); Ichiyanagi, K. [Graduate School of Science and Technology, Kumamoto University and Japan Agency for Marine-Earth Science and Technology (Japan)

    2013-07-15

    To understand the spatial distribution of stable isotopic compositions in precipitation, precipitation samples were collected every two weeks from november 2009 to december 2010 at 6 points in Kumamoto, Japan. The {delta}{sup 18}O and {delta}{sup 2}H of precipitation samples were measured by isotope ratio mass spectrometry (Delta-S) with CO{sub 2}/H2{sub O} equivalent method for {delta}{sup 18}O and the chromium reduction method for {delta}2H. The range of {delta}{sup 18}O and d-excess (= {delta}{sup 2}H - 8 {delta}{sup 18}O) in precipitation is from -13.4 per mille to -3.5 per mille and from 2.6 per mille to 35.6 per mille , respectively. Seasonal variability of {delta}{sup 18}O (d-excess) in precipitation was low (high) in winter and high (low) in summer. The seasonal wind of this study area was dominated by south-westerly in summer (from June to August) and north-westerly in winter (from December to February). These wind regimes indicate seasonal variabilities of the water vapour pathway from the origin. In this paper the trend of inland effect to the {delta}{sup 18}O for both south-westerly and north-westerly are also considered. As a result, significant correlation between distances from the coastal line at south-westerly or north-westerly and {delta}{sup 18}O in precipitation was recognized, particularly from 18 February to 7 March and from 29 September to 19 October in 2010 (statistically significant with 5% level). Furthermore, in order to evaluate the course of precipitation, the column total of water vapour flux was considered in the whole period by using JRA-25 and JCDAS. It is interesting that the inland effect corresponded to the column total of water vapour flux at south-westerly (north-westerly). Hence, it is conceivable that the spatial distribution of {delta}{sup 18}O in precipitation was controlled by a column total of water vapour flux in this area. (author)

  1. 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.

  2. 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

  3. 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)

  4. A spatial structural derivative model for ultraslow diffusion

    Directory of Open Access Journals (Sweden)

    Xu Wei

    2017-01-01

    Full Text Available This study investigates the ultraslow diffusion by a spatial structural derivative, in which the exponential function ex is selected as the structural function to construct the local structural derivative diffusion equation model. The analytical solution of the diffusion equation is a form of Biexponential distribution. Its corresponding mean squared displacement is numerically calculated, and increases more slowly than the logarithmic function of time. The local structural derivative diffusion equation with the structural function ex in space is an alternative physical and mathematical modeling model to characterize a kind of ultraslow diffusion.

  5. Spatial Distribution of the Coefficient of Variation for the Paleo-Earthquakes in Japan

    Science.gov (United States)

    Nomura, S.; Ogata, Y.

    2015-12-01

    Renewal processes, point prccesses in which intervals between consecutive events are independently and identically distributed, are frequently used to describe this repeating earthquake mechanism and forecast the next earthquakes. However, one of the difficulties in applying recurrent earthquake models is the scarcity of the historical data. Most studied fault segments have few, or only one observed earthquake that often have poorly constrained historic and/or radiocarbon ages. The maximum likelihood estimate from such a small data set can have a large bias and error, which tends to yield high probability for the next event in a very short time span when the recurrence intervals have similar lengths. On the other hand, recurrence intervals at a fault depend on the long-term slip rate caused by the tectonic motion in average. In addition, recurrence times are also fluctuated by nearby earthquakes or fault activities which encourage or discourage surrounding seismicity. These factors have spatial trends due to the heterogeneity of tectonic motion and seismicity. Thus, this paper introduces a spatial structure on the key parameters of renewal processes for recurrent earthquakes and estimates it by using spatial statistics. Spatial variation of mean and variance parameters of recurrence times are estimated in Bayesian framework and the next earthquakes are forecasted by Bayesian predictive distributions. The proposal model is applied for recurrent earthquake catalog in Japan and its result is compared with the current forecast adopted by the Earthquake Research Committee of Japan.

  6. Human Plague Risk: Spatial-Temporal Models

    Science.gov (United States)

    Pinzon, Jorge E.

    2010-01-01

    This chpater reviews the use of spatial-temporal models in identifying potential risks of plague outbreaks into the human population. Using earth observations by satellites remote sensing there has been a systematic analysis and mapping of the close coupling between the vectors of the disease and climate variability. The overall result is that incidence of plague is correlated to positive El Nino/Southem Oscillation (ENSO).

  7. 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

  8. 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.

  9. 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

  10. The quantitative modelling of human spatial habitability

    Science.gov (United States)

    Wise, James A.

    1988-01-01

    A theoretical model for evaluating human spatial habitability (HuSH) in the proposed U.S. Space Station is developed. Optimizing the fitness of the space station environment for human occupancy will help reduce environmental stress due to long-term isolation and confinement in its small habitable volume. The development of tools that operationalize the behavioral bases of spatial volume for visual kinesthetic, and social logic considerations is suggested. This report further calls for systematic scientific investigations of how much real and how much perceived volume people need in order to function normally and with minimal stress in space-based settings. The theoretical model presented in this report can be applied to any size or shape interior, at any scale of consideration, for the Space Station as a whole to an individual enclosure or work station. Using as a point of departure the Isovist model developed by Dr. Michael Benedikt of the U. of Texas, the report suggests that spatial habitability can become as amenable to careful assessment as engineering and life support concerns.

  11. Modeled ground water age distributions

    Science.gov (United States)

    Woolfenden, Linda R.; Ginn, Timothy R.

    2009-01-01

    The age of ground water in any given sample is a distributed quantity representing distributed provenance (in space and time) of the water. Conventional analysis of tracers such as unstable isotopes or anthropogenic chemical species gives discrete or binary measures of the presence of water of a given age. Modeled ground water age distributions provide a continuous measure of contributions from different recharge sources to aquifers. A numerical solution of the ground water age equation of Ginn (1999) was tested both on a hypothetical simplified one-dimensional flow system and under real world conditions. Results from these simulations yield the first continuous distributions of ground water age using this model. Complete age distributions as a function of one and two space dimensions were obtained from both numerical experiments. Simulations in the test problem produced mean ages that were consistent with the expected value at the end of the model domain for all dispersivity values tested, although the mean ages for the two highest dispersivity values deviated slightly from the expected value. Mean ages in the dispersionless case also were consistent with the expected mean ages throughout the physical model domain. Simulations under real world conditions for three dispersivity values resulted in decreasing mean age with increasing dispersivity. This likely is a consequence of an edge effect. However, simulations for all three dispersivity values tested were mass balanced and stable demonstrating that the solution of the ground water age equation can provide estimates of water mass density distributions over age under real world conditions.

  12. 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

  13. Coded aperture imaging of alpha source spatial distribution

    International Nuclear Information System (INIS)

    Talebitaher, Alireza; Shutler, Paul M.E.; Springham, Stuart V.; Rawat, Rajdeep S.; Lee, Paul

    2012-01-01

    The Coded Aperture Imaging (CAI) technique has been applied with CR-39 nuclear track detectors to image alpha particle source spatial distributions. The experimental setup comprised: a 226 Ra source of alpha particles, a laser-machined CAI mask, and CR-39 detectors, arranged inside a vacuum enclosure. Three different alpha particle source shapes were synthesized by using a linear translator to move the 226 Ra source within the vacuum enclosure. The coded mask pattern used is based on a Singer Cyclic Difference Set, with 400 pixels and 57 open square holes (representing ρ = 1/7 = 14.3% open fraction). After etching of the CR-39 detectors, the area, circularity, mean optical density and positions of all candidate tracks were measured by an automated scanning system. Appropriate criteria were used to select alpha particle tracks, and a decoding algorithm applied to the (x, y) data produced the de-coded image of the source. Signal to Noise Ratio (SNR) values obtained for alpha particle CAI images were found to be substantially better than those for corresponding pinhole images, although the CAI-SNR values were below the predictions of theoretical formulae. Monte Carlo simulations of CAI and pinhole imaging were performed in order to validate the theoretical SNR formulae and also our CAI decoding algorithm. There was found to be good agreement between the theoretical formulae and SNR values obtained from simulations. Possible reasons for the lower SNR obtained for the experimental CAI study are discussed.

  14. Formation and spatial distribution of hypervelocity stars in AGN outflows

    Science.gov (United States)

    Wang, Xiawei; Loeb, Abraham

    2018-05-01

    We study star formation within outflows driven by active galactic nuclei (AGN) as a new source of hypervelocity stars (HVSs). Recent observations revealed active star formation inside a galactic outflow at a rate of ∼ 15M⊙yr-1 . We verify that the shells swept up by an AGN outflow are capable of cooling and fragmentation into cold clumps embedded in a hot tenuous gas via thermal instabilities. We show that cold clumps of ∼ 103 M⊙ are formed within ∼ 105 yrs. As a result, stars are produced along outflow's path, endowed with the outflow speed at their formation site. These HVSs travel through the galactic halo and eventually escape into the intergalactic medium. The expected instantaneous rate of star formation inside the outflow is ∼ 4 - 5 orders of magnitude greater than the average rate associated with previously proposed mechanisms for producing HVSs, such as the Hills mechanism and three-body interaction between a star and a black hole binary. We predict the spatial distribution of HVSs formed in AGN outflows for future observational probe.

  15. Adaptive spatial filtering for daytime satellite quantum key distribution

    Science.gov (United States)

    Gruneisen, Mark T.; Sickmiller, Brett A.; Flanagan, Michael B.; Black, James P.; Stoltenberg, Kurt E.; Duchane, Alexander W.

    2014-11-01

    The rate of secure key generation (SKG) in quantum key distribution (QKD) is adversely affected by optical noise and loss in the quantum channel. In a free-space atmospheric channel, the scattering of sunlight into the channel can lead to quantum bit error ratios (QBERs) sufficiently large to preclude SKG. Furthermore, atmospheric turbulence limits the degree to which spatial filtering can reduce sky noise without introducing signal losses. A system simulation quantifies the potential benefit of tracking and higher-order adaptive optics (AO) technologies to SKG rates in a daytime satellite engagement scenario. The simulations are performed assuming propagation from a low-Earth orbit (LEO) satellite to a terrestrial receiver that includes an AO system comprised of a Shack-Hartmann wave-front sensor (SHWFS) and a continuous-face-sheet deformable mirror (DM). The effects of atmospheric turbulence, tracking, and higher-order AO on the photon capture efficiency are simulated using statistical representations of turbulence and a time-domain waveoptics hardware emulator. Secure key generation rates are then calculated for the decoy state QKD protocol as a function of the receiver field of view (FOV) for various pointing angles. The results show that at FOVs smaller than previously considered, AO technologies can enhance SKG rates in daylight and even enable SKG where it would otherwise be prohibited as a consequence of either background optical noise or signal loss due to turbulence effects.

  16. 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

  17. Modelling the distribution of pig production and diseases in Thailand

    OpenAIRE

    Thanapongtharm, Weerapong

    2015-01-01

    This thesis, entitled “Modelling the distribution of pig production and diseases in Thailand”, presents many aspects of pig production in Thailand including the characteristics of pig farming system, distribution of pig population and pig farms, spatio-temporal distribution and risk of most important diseases in pig at present, and the suitability area for pig farming. Spatial distribution and characteristics of pig farming in Thailand were studied using time-series pig population data to des...

  18. Spatial Distribution of Transgenic Protein After Gene Electrotransfer to Porcine Muscle

    DEFF Research Database (Denmark)

    Spanggaard, Iben; Corydon, Thomas; Hojman, Pernille

    2012-01-01

    Abstract Gene electrotransfer is an effective nonviral technique for delivery of plasmid DNA into tissues. From a clinical perspective, muscle is an attractive target tissue as long-term, high-level transgenic expression can be achieved. Spatial distribution of the transgenic protein following gene...... electrotransfer to muscle in a large animal model has not yet been investigated. In this study, 17 different doses of plasmid DNA (1-1500 μg firefly luciferase pCMV-Luc) were delivered in vivo to porcine gluteal muscle using electroporation. Forty-eight hours post treatment several biopsies were obtained from...... each transfection site in order to examine the spatial distribution of the transgenic product. We found a significantly higher luciferase activity in biopsies from the center of the transfection site compared to biopsies taken adjacent to the center, 1 and 2 cm along muscle fiber orientation (p...

  19. 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)

  20. 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

  1. 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)

  2. 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

  3. Hair mercury levels in Amazonian populations: spatial distribution and trends

    Directory of Open Access Journals (Sweden)

    Barbieri Flavia L

    2009-12-01

    Full Text Available Abstract Background Mercury is present in the Amazonian aquatic environments from both natural and anthropogenic sources. As a consequence, many riverside populations are exposed to methylmercury, a highly toxic organic form of mercury, because of their intense fish consumption. Many studies have analysed this exposure from different approaches since the early nineties. This review aims to systematize the information in spatial distribution, comparing hair mercury levels by studied population and Amazonian river basin, looking for exposure trends. Methods The reviewed papers were selected from scientific databases and online libraries. We included studies with a direct measure of hair mercury concentrations in a sample size larger than 10 people, without considering the objectives, approach of the study or mercury speciation. The results are presented in tables and maps by river basin, displaying hair mercury levels and specifying the studied population and health impact, if any. Results The majority of the studies have been carried out in communities from the central Amazonian regions, particularly on the Tapajós River basin. The results seem quite variable; hair mercury means range from 1.1 to 34.2 μg/g. Most studies did not show any significant difference in hair mercury levels by gender or age. Overall, authors emphasized fish consumption frequency as the main risk factor of exposure. The most studied adverse health effect is by far the neurological performance, especially motricity. However, it is not possible to conclude on the relation between hair mercury levels and health impact in the Amazonian situation because of the relatively small number of studies. Conclusions Hair mercury levels in the Amazonian regions seem to be very heterogenic, depending on several factors. There is no obvious spatial trend and there are many areas that have never been studied. Taking into account the low mercury levels currently handled as acceptable, the

  4. The spatial distribution and evolution characteristics of North Atlantic cyclones

    Science.gov (United States)

    Dacre, H.; Gray, S.

    2009-09-01

    Mid-latitude cyclones play a large role in determining the day-to-day weather conditions in western Europe through their associated wind and precipitation patterns. Thus, their typical spatial and evolution characteristics are of great interest to meteorologists, insurance and risk management companies. In this study a feature tracking algorithm is applied to a cyclone database produced using the Hewson-method of cyclone identification, based on low-level gradients of wet-bulb potential temperature, to produce a climatology of mid-latitude cyclones. The aim of this work is to compare the cyclone track and density statistics found in this study with previous climatologies and to determine reasons for any differences. This method is found to compare well with other cyclone identification methods; the north Atlantic storm track is reproduced along with the major regions of genesis. Differences are attributed to cyclone lifetime and strength thresholds, dataset resolution and cyclone identification and tracking methods. Previous work on cyclone development has been largely limited to case studies as opposed to analysis of climatological data, and does not distinguish between the different stages of cyclone evolution. The cyclone database used in this study allows cyclone characteristics to be tracked throughout the cyclone lifecycle. This enables the evaluation of the characteristics of cyclone evolution for systems forming in different genesis regions and a calculation of the spatial distribution and evolution of these characteristics in composite cyclones. It was found that most of the cyclones that cross western Europe originate in the east Atlantic where the baroclinicity and sea surface temperature gradients are weak compared to the west Atlantic. East Atlantic cyclones also have higher low-level relative vorticity and lower mean sea level pressure at their genesis point than west Atlantic cyclones. This is consistent with the hypothesis that they are secondary

  5. Factors Impacting Spatial Patterns of Snow Distribution in a Small Catchment near Nome, AK

    Science.gov (United States)

    Chen, M.; Wilson, C. J.; Charsley-Groffman, L.; Busey, R.; Bolton, W. R.

    2017-12-01

    Snow cover plays an important role in the climate, hydrology and ecological systems of the Arctic due to its influence on the water balance, thermal regimes, vegetation and carbon flux. Thus, snow depth and coverage have been key components in all the earth system models but are often poorly represented for arctic regions, where fine scale snow distribution data is sparse. The snow data currently used in the models is at coarse resolution, which in turn leads to high uncertainty in model predictions. Through the DOE Office of Science Next Generation Ecosystem Experiment, NGEE-Arctic, high resolution snow distribution data is being developed and applied in catchment scale models to ultimately improve representation of snow and its interactions with other model components in the earth system models . To improve these models, it is important to identify key factors that control snow distribution and quantify the impacts of those factors on snow distribution. In this study, two intensive snow depth surveys (1 to 10 meters scale) were conducted for a 2.3 km2 catchment on the Teller road, near Nome, AK in the winter of 2016 and 2017. We used a statistical model to quantify the impacts of vegetation types, macro-topography, micro-topography, and meteorological parameters on measured snow depth. The results show that snow spatial distribution was similar between 2016 and 2017, snow depth was spatially auto correlated over small distance (2-5 meters), but not spatially auto correlated over larger distance (more than 2-5 meters). The coefficients of variation of snow depth was above 0.3 for all the snow survey transects (500-800 meters long). Variation of snow depth is governed by vegetation height, aspect, slope, surface curvature, elevation and wind speed and direction. We expect that this empirical statistical model can be used to estimate end of winter snow depth for the whole watershed and will further develop the model using data from other arctic regions to estimate

  6. 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).

  7. 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.

  8. 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

  9. 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.

  10. Assessing fit in Bayesian models for spatial processes

    KAUST Repository

    Jun, M.; Katzfuss, M.; Hu, J.; Johnson, V. E.

    2014-01-01

    © 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.

  11. Statistical analysis of the spatial distribution of galaxies and clusters

    International Nuclear Information System (INIS)

    Cappi, Alberto

    1993-01-01

    This thesis deals with the analysis of the distribution of galaxies and clusters, describing some observational problems and statistical results. First chapter gives a theoretical introduction, aiming to describe the framework of the formation of structures, tracing the history of the Universe from the Planck time, t_p = 10"-"4"3 sec and temperature corresponding to 10"1"9 GeV, to the present epoch. The most usual statistical tools and models of the galaxy distribution, with their advantages and limitations, are described in chapter two. A study of the main observed properties of galaxy clustering, together with a detailed statistical analysis of the effects of selecting galaxies according to apparent magnitude or diameter, is reported in chapter three. Chapter four delineates some properties of groups of galaxies, explaining the reasons of discrepant results on group distributions. Chapter five is a study of the distribution of galaxy clusters, with different statistical tools, like correlations, percolation, void probability function and counts in cells; it is found the same scaling-invariant behaviour of galaxies. Chapter six describes our finding that rich galaxy clusters too belong to the fundamental plane of elliptical galaxies, and gives a discussion of its possible implications. Finally chapter seven reviews the possibilities offered by multi-slit and multi-fibre spectrographs, and I present some observational work on nearby and distant galaxy clusters. In particular, I show the opportunities offered by ongoing surveys of galaxies coupled with multi-object fibre spectrographs, focusing on the ESO Key Programme A galaxy redshift survey in the south galactic pole region to which I collaborate and on MEFOS, a multi-fibre instrument with automatic positioning. Published papers related to the work described in this thesis are reported in the last appendix. (author) [fr

  12. The spatial distribution and birth-rate of pulsars

    International Nuclear Information System (INIS)

    Guseinov, O.H.; Kasumov, F.K.

    1978-01-01

    The distribution of pulsars in the wide range of observed luminosities has been obtained. It is shown that the function of luminosity (FL) within 3 x 10 26 30 erg s -1 conforms to the power law dN/dL - c 1 Lsup(-γ), where γ = 1.76 +- 0.06. For L 26 erg s -1 , FL changes its inclination and may be approximated as dN/dL approximately Lsup(-γ 1 ), where γ 1 = 0.7 +- 0.2. On the basis of statistical selection, including all pulsars with L > 3 x 10 28 erg s -1 , the distribution of pulsars has been investigated as a function of the distance to the centre R and galactic plane Z. The obtained laws of the radial and Z-distribution of pulsars and galactic supernova remnants and also the radial distribution of types I and II supernovae in the models Sb and Sc support the hypothesis of their origin from the objects of the flat subsystem of Population I. Since there are some arguments in favour of a possible connection between supernovae I and the objects of the intermediate component of the Galaxy, one cannot exclude the possibility of supernovae explosions at the end of the evolution of stars with masses of 1.5-2 Msub(sun). It is also shown that pulsars and supernovae are evidently objects that are connected genetically, and, within the limits of statistical error, they have a similar birth-rate. The empirical law of the evolution of a pulsar's luminosity as a function of its true age has been obtained, according to which L = c 2 tsup(-β), where c 2 = (3.69+- 3.4) x 10 35 ,β = 1.32 +- 0.11. (Auth.)

  13. Assessing spatial and temporal variability of phytoplankton communities' composition in the Iroise Sea ecosystem (Brittany, France): A 3D modeling approach. Part 2: Linking summer mesoscale distribution of phenotypic diversity to hydrodynamism

    Science.gov (United States)

    Cadier, Mathilde; Sourisseau, Marc; Gorgues, Thomas; Edwards, Christopher A.; Memery, Laurent

    2017-05-01

    Tidal front ecosystems are especially dynamic environments usually characterized by high phytoplankton biomass and high primary production. However, the description of functional microbial diversity occurring in these regions remains only partially documented. In this article, we use a numerical model, simulating a large number of phytoplankton phenotypes to explore the three-dimensional spatial patterns of phytoplankton abundance and diversity in the Iroise Sea (western Brittany). Our results suggest that, in boreal summer, a seasonally marked tidal front shapes the phytoplankton species richness. A diversity maximum is found in the surface mixed layer located slightly west of the tidal front (i.e., not strictly co-localized with high biomass concentrations) which separates tidally mixed from stratified waters. Differences in phenotypic composition between sub-regions with distinct hydrodynamic regimes (defined by vertical mixing, nutrients gradients and light penetration) are discussed. Local growth and/or physical transport of phytoplankton phenotypes are shown to explain our simulated diversity distribution. We find that a large fraction (64%) of phenotypes present during the considered period of September are ubiquitous, found in the frontal area and on both sides of the front (i.e., over the full simulated domain). The frontal area does not exhibit significant differences between its community composition and that of either the well-mixed region or an offshore Deep Chlorophyll Maximum (DCM). Only three phenotypes (out of 77) specifically grow locally and are found at substantial concentration only in the surface diversity maximum. Thus, this diversity maximum is composed of a combination of ubiquitous phenotypes with specific picoplankton deriving from offshore, stratified waters (including specific phenotypes from both the surface and the DCM) and imported through physical transport, completed by a few local phenotypes. These results are discussed in light

  14. 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

  15. Spatially varying coefficient models in real estate: Eigenvector spatial filtering and alternative approaches

    NARCIS (Netherlands)

    Helbich, M; Griffith, D

    2016-01-01

    Real estate policies in urban areas require the recognition of spatial heterogeneity in housing prices to account for local settings. In response to the growing number of spatially varying coefficient models in housing applications, this study evaluated four models in terms of their spatial patterns

  16. 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.

  17. 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.

  18. 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.

  19. On the spatial and temporal distribution of global thunderstorm cells

    International Nuclear Information System (INIS)

    Mezuman, Keren; Price, Colin; Galanti, Eli

    2014-01-01

    Estimates of global thunderstorm activity have been made predominately by direct measurements of lightning discharges around the globe, either by optical measurements from satellites, or using ground-based radio antennas. In this paper we propose a new methodology in which thunderstorm clusters are constructed based on the lightning strokes detected by the World Wide Lightning Location Network (WWLLN) in the very low frequency range. We find that even with low lightning detection efficiency on a global scale, the spatial and temporal distribution of global thunderstorm cells is well reproduced. This is validated by comparing the global diurnal variations of the thunderstorm cells, and the currents produced by these storms, with the well-known Carnegie Curve, which represents the mean diurnal variability of the global atmospheric electric circuit, driven by thunderstorm activity. While the Carnegie Curve agrees well with our diurnal thunderstorm cluster variations, there is little agreement between the Carnegie Curve and the diurnal variation in the number of lightning strokes detected by the WWLLN. When multiplying the number of clusters we detect by the mean thunderstorm conduction current for land and ocean thunderstorms (Mach et al 2011 J. Geophys. Res. 116 D05201) we get a total average current of about 760 A. Our results show that thunderstorms alone explain more than 90% in the variability of the global electric circuit. However, while it has been previously shown that 90% of the global lightning occurs over continental landmasses, we show that around 50% of the thunderstorms are over the oceans, and from 00-09UTC there are more thunderstorm cells globally over the oceans than over the continents. Since the detection efficiency of the WWLLN system has increased over time, we estimate that the lower bound of the mean number of global thunderstorm cells in 2012 was around 1050 per hour, varying from around 840 at 03UTC to 1150 storms at 19UTC. (letter)

  20. 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

  1. Spatial Data Exploring by Satellite Image Distributed Processing

    Science.gov (United States)

    Mihon, V. D.; Colceriu, V.; Bektas, F.; Allenbach, K.; Gvilava, M.; Gorgan, D.

    2012-04-01

    Our society needs and environmental predictions encourage the applications development, oriented on supervising and analyzing different Earth Science related phenomena. Satellite images could be explored for discovering information concerning land cover, hydrology, air quality, and water and soil pollution. Spatial and environment related data could be acquired by imagery classification consisting of data mining throughout the multispectral bands. The process takes in account a large set of variables such as satellite image types (e.g. MODIS, Landsat), particular geographic area, soil composition, vegetation cover, and generally the context (e.g. clouds, snow, and season). All these specific and variable conditions require flexible tools and applications to support an optimal search for the appropriate solutions, and high power computation resources. The research concerns with experiments on solutions of using the flexible and visual descriptions of the satellite image processing over distributed infrastructures (e.g. Grid, Cloud, and GPU clusters). This presentation highlights the Grid based implementation of the GreenLand application. The GreenLand application development is based on simple, but powerful, notions of mathematical operators and workflows that are used in distributed and parallel executions over the Grid infrastructure. Currently it is used in three major case studies concerning with Istanbul geographical area, Rioni River in Georgia, and Black Sea catchment region. The GreenLand application offers a friendly user interface for viewing and editing workflows and operators. The description involves the basic operators provided by GRASS [1] library as well as many other image related operators supported by the ESIP platform [2]. The processing workflows are represented as directed graphs giving the user a fast and easy way to describe complex parallel algorithms, without having any prior knowledge of any programming language or application commands

  2. 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.

  3. Spatial power distribution in the SR-0 experimental module of the SPHINX nuclear transmutation system - 2006 and 2007 variants

    International Nuclear Information System (INIS)

    Rypar, Vojtech; Svadlenkova, Marie; Novak, Evzen; Viererbl, Ladislav; Lahodova, Zdena; Bily, Tomas

    2007-11-01

    Experiments were performed with various assemblies modelling the SPHINX transmutation system with the aim to investigate the effect of materials in the SR-0 modules, i.e. LiF, NaF, graphite, on the spatial power distribution of the reaction rates of the activation detectors, axial and radial distribution of the fission products of the fuel pins located in some points of the reactor core, and photon dose distribution by using thermoluminescent dosemeters

  4. Spatial distribution and optimal harvesting of an age-structured population in a fluctuating environment.

    Science.gov (United States)

    Engen, Steinar; Lee, Aline Magdalena; Sæther, Bernt-Erik

    2018-02-01

    We analyze a spatial age-structured model with density regulation, age specific dispersal, stochasticity in vital rates and proportional harvesting. We include two age classes, juveniles and adults, where juveniles are subject to logistic density dependence. There are environmental stochastic effects with arbitrary spatial scales on all birth and death rates, and individuals of both age classes are subject to density independent dispersal with given rates and specified distributions of dispersal distances. We show how to simulate the joint density fields of the age classes and derive results for the spatial scales of all spatial autocovariance functions for densities. A general result is that the squared scale has an additive term equal to the squared scale of the environmental noise, corresponding to the Moran effect, as well as additive terms proportional to the dispersal rate and variance of dispersal distance for the age classes and approximately inversely proportional to the strength of density regulation. We show that the optimal harvesting strategy in the deterministic case is to harvest only juveniles when their relative value (e.g. financial) is large, and otherwise only adults. With increasing environmental stochasticity there is an interval of increasing length of values of juveniles relative to adults where both age classes should be harvested. Harvesting generally tends to increase all spatial scales of the autocovariances of densities. Copyright © 2017. Published by Elsevier Inc.

  5. 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.

  6. Spatially varying dispersion to model breakthrough curves.

    Science.gov (United States)

    Li, Guangquan

    2011-01-01

    Often the water flowing in a karst conduit is a combination of contaminated water entering at a sinkhole and cleaner water released from the limestone matrix. Transport processes in the conduit are controlled by advection, mixing (dilution and dispersion), and retention-release. In this article, a karst transport model considering advection, spatially varying dispersion, and dilution (from matrix seepage) is developed. Two approximate Green's functions are obtained using transformation of variables, respectively, for the initial-value problem and for the boundary-value problem. A numerical example illustrates that mixing associated with strong spatially varying conduit dispersion can cause strong skewness and long tailing in spring breakthrough curves. Comparison of the predicted breakthrough curve against that measured from a dye-tracing experiment between Ames Sink and Indian Spring, Northwest Florida, shows that the conduit dispersivity can be as large as 400 m. Such a large number is believed to imply strong solute interaction between the conduit and the matrix and/or multiple flow paths in a conduit network. It is concluded that Taylor dispersion is not dominant in transport in a karst conduit, and the complicated retention-release process between mobile- and immobile waters may be described by strong spatially varying conduit dispersion. Copyright © 2010 The Author(s). Journal compilation © 2010 National Ground Water Association.

  7. 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 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.

  8. Temporal and spatial distribution characteristics in the natural plague foci of Chinese Mongolian gerbils based on spatial autocorrelation.

    Science.gov (United States)

    Du, Hai-Wen; Wang, Yong; Zhuang, Da-Fang; Jiang, Xiao-San

    2017-08-07

    The nest flea index of Meriones unguiculatus is a critical indicator for the prevention and control of plague, which can be used not only to detect the spatial and temporal distributions of Meriones unguiculatus, but also to reveal its cluster rule. This research detected the temporal and spatial distribution characteristics of the plague natural foci of Mongolian gerbils by body flea index from 2005 to 2014, in order to predict plague outbreaks. Global spatial autocorrelation was used to describe the entire spatial distribution pattern of the body flea index in the natural plague foci of typical Chinese Mongolian gerbils. Cluster and outlier analysis and hot spot analysis were also used to detect the intensity of clusters based on geographic information system methods. The quantity of M. unguiculatus nest fleas in the sentinel surveillance sites from 2005 to 2014 and host density data of the study area from 2005 to 2010 used in this study were provided by Chinese Center for Disease Control and Prevention. The epidemic focus regions of the Mongolian gerbils remain the same as the hot spot regions relating to the body flea index. High clustering areas possess a similar pattern as the distribution pattern of the body flea index indicating that the transmission risk of plague is relatively high. In terms of time series, the area of the epidemic focus gradually increased from 2005 to 2007, declined rapidly in 2008 and 2009, and then decreased slowly and began trending towards stability from 2009 to 2014. For the spatial change, the epidemic focus regions began moving northward from the southwest epidemic focus of the Mongolian gerbils from 2005 to 2007, and then moved from north to south in 2007 and 2008. The body flea index of Chinese gerbil foci reveals significant spatial and temporal aggregation characteristics through the employing of spatial autocorrelation. The diversity of temporary and spatial distribution is mainly affected by seasonal variation, the human

  9. An Evolutionary Model of Spatial Competition

    DEFF Research Database (Denmark)

    Knudsen, Thorbjørn; Winter, Sidney G.

      This paper sets forth an evolutionary model in which diverse businesses, with diverse offerings, compete in a stylized physical space.  When a business firm attempts to expand its activity, so as to profit further from the capabilities it has developed, it necessarily does so in a "new location...... as well in the new environment as they did in the old; the firm may respond with effort to locate appropriate environments or by modification of its routines.  Tradeoffs are presented between the complexity of a business model and its replication costs,  as well as issues involving response....... Randomly generated firm policies are tested first by a local market environment, and then, if success leads the firm to grow spatially, in a gradually expanding environment.  In the initial experiments reported here, we show that the model generates configurations that reflect features of the exogenous...

  10. Spatial distribution pattern of vanadium in hydric landscapes

    Science.gov (United States)

    Fiedler, Sabine; Breuer, Jörn; Palmer, Iris; Berger, Jochen

    2010-05-01

    landscapes. Independent from the parent material, we found a distinct spatial pattern of V, which reflected that of the local redox environment: Horizons/pedons with oxic conditions revealed a positive correlation between V content and Fe content. In this case, iron oxides act as an important sink for dissolved V which originated from other locations of the catena. Poorly drained soils, such as Stagnosols for example, promote both Fe and V reduction, which is coupled to their removal from the pedons by leaching. It can be demonstrated that the element-specific Eh window for differential reduction is very narrow. The spatial distribution of both elements shows that high V contents are often associated with low Fe contents. It is therefore assumed that a reducing environment promotes Fe3+ reduction, while maintaining while maintaining V stable.

  11. Analysis of spatial distribution and inventory of radioactivity within the uranium mill tailings impoundment

    Directory of Open Access Journals (Sweden)

    D. O. Bugai

    2015-10-01

    Full Text Available Results are presented of the characterization of radioactivity inventory of Zapadnoe uranium mill tailings impoundment situated at Pridneprovsky Chemical Plant (PChP; Dneprodzerzhinsk, Ukraine. Analyses of radioactivity data set based on analytical studies of core material from 15 characterization boreholes allowed significantly refining waste volume and radioactivity inventory estimates. Geostatistical analyses using variogram function have established that radioactivity distribution in Zapadnoe tailings is characterized by regular spatial correlation patterns. Ordinary kriging method was applied to assess distribution of radioactivity in 3D. Results of statistical analyses suggest significant redistribution of uranium in the dissolved form in the residues (presumably due to water infiltration process. The developed structural model for radioactivity distribution is used for further risk assessment analyses. Derived radioactivity correlation scales can be used for optimization of sample collection when characterizing the PChP Site and similar contaminated sites elsewhere.

  12. Characterizing short-range vs. long-range spatial correlations in dislocation distributions

    Energy Technology Data Exchange (ETDEWEB)

    Chevy, Juliette, E-mail: juliette.chevy@gmail.com [Laboratoire de Glaciologie et Geophysique de l' Environnement-CNRS, 54 rue Moliere, 38402 St. Martin d' Heres (France)] [Laboratoire Science et Ingenierie des Materiaux et Procedes, Grenoble INP-CNRS-UJF, BP 75, 38402 St. Martin d' Heres Cedex (France); Fressengeas, Claude; Lebyodkin, Mikhail; Taupin, Vincent [Laboratoire de Physique et Mecanique des Materiaux, Universite Paul Verlaine-Metz/CNRS, Ile du Saulcy, 57045 Metz Cedex (France); Bastie, Pierre [Laboratoire de Spectrometrie Physique, BP 87, 38402 St. Martin d' Heres Cedex (France)] [Institut Laue Langevin, BP 156, 38042 Grenoble Cedex 9 (France); Duval, Paul [Laboratoire de Glaciologie et Geophysique de l' Environnement-CNRS, 54 rue Moliere, 38402 St. Martin d' Heres (France)

    2010-03-15

    Hard X-ray diffraction experiments have provided evidence of a strongly heterogeneous distribution of dislocation densities along the axis of cylindrical ice single crystals oriented for basal slip in torsion creep. The dislocation arrangements showed a complex scale-invariant character, which was analyzed by means of statistical and multifractal techniques. A trend to decreasing autocorrelation of the dislocation distribution was observed as deformation proceeds. At low strain levels, long-range spatial correlations control the distribution, but short-range correlations in relation with cross-slip progressively prevail when strain increases. This trend was reproduced by a model based on field dislocation dynamics, a theory accounting for both long-range elastic interactions and short-range interactions through transport of dislocation densities.

  13. Characterizing short-range vs. long-range spatial correlations in dislocation distributions

    International Nuclear Information System (INIS)

    Chevy, Juliette; Fressengeas, Claude; Lebyodkin, Mikhail; Taupin, Vincent; Bastie, Pierre; Duval, Paul

    2010-01-01

    Hard X-ray diffraction experiments have provided evidence of a strongly heterogeneous distribution of dislocation densities along the axis of cylindrical ice single crystals oriented for basal slip in torsion creep. The dislocation arrangements showed a complex scale-invariant character, which was analyzed by means of statistical and multifractal techniques. A trend to decreasing autocorrelation of the dislocation distribution was observed as deformation proceeds. At low strain levels, long-range spatial correlations control the distribution, but short-range correlations in relation with cross-slip progressively prevail when strain increases. This trend was reproduced by a model based on field dislocation dynamics, a theory accounting for both long-range elastic interactions and short-range interactions through transport of dislocation densities.

  14. Panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable

    NARCIS (Netherlands)

    Elhorst, J. Paul

    2001-01-01

    This paper surveys panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable. In particular, it focuses on the specification and estimation of four panel data models commonly used in applied research: the fixed effects model, the random effects model, the

  15. Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage.

    Directory of Open Access Journals (Sweden)

    Brady J Mattsson

    Full Text Available Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.

  16. Video distribution system cost model

    Science.gov (United States)

    Gershkoff, I.; Haspert, J. K.; Morgenstern, B.

    1980-01-01

    A cost model that can be used to systematically identify the costs of procuring and operating satellite linked communications systems is described. The user defines a network configuration by specifying the location of each participating site, the interconnection requirements, and the transmission paths available for the uplink (studio to satellite), downlink (satellite to audience), and voice talkback (between audience and studio) segments of the network. The model uses this information to calculate the least expensive signal distribution path for each participating site. Cost estimates are broken downy by capital, installation, lease, operations and maintenance. The design of the model permits flexibility in specifying network and cost structure.

  17. Data set: 31 years of spatially distributed air temperature, humidity, precipitation amount and precipitation phase from a mountain catchment in the rain-snow transition zone

    Science.gov (United States)

    Thirty one years of spatially distributed air temperature, relative humidity, dew point temperature, precipitation amount, and precipitation phase data are presented for the Reynolds Creek Experimental Watershed. The data are spatially distributed over a 10m Lidar-derived digital elevation model at ...

  18. Tapered composite likelihood for spatial max-stable models

    KAUST Repository

    Sang, Huiyan

    2014-05-01

    Spatial extreme value analysis is useful to environmental studies, in which extreme value phenomena are of interest and meaningful spatial patterns can be discerned. Max-stable process mod