WorldWideScience

Sample records for random spatial variability

  1. Testing in a Random Effects Panel Data Model with Spatially Correlated Error Components and Spatially Lagged Dependent Variables

    Directory of Open Access Journals (Sweden)

    Ming He

    2015-11-01

    Full Text Available We propose a random effects panel data model with both spatially correlated error components and spatially lagged dependent variables. We focus on diagnostic testing procedures and derive Lagrange multiplier (LM test statistics for a variety of hypotheses within this model. We first construct the joint LM test for both the individual random effects and the two spatial effects (spatial error correlation and spatial lag dependence. We then provide LM tests for the individual random effects and for the two spatial effects separately. In addition, in order to guard against local model misspecification, we derive locally adjusted (robust LM tests based on the Bera and Yoon principle (Bera and Yoon, 1993. We conduct a small Monte Carlo simulation to show the good finite sample performances of these LM test statistics and revisit the cigarette demand example in Baltagi and Levin (1992 to illustrate our testing procedures.

  2. Random forest variable selection in spatial malaria transmission modelling in Mpumalanga Province, South Africa.

    Science.gov (United States)

    Kapwata, Thandi; Gebreslasie, Michael T

    2016-11-16

    Malaria is an environmentally driven disease. In order to quantify the spatial variability of malaria transmission, it is imperative to understand the interactions between environmental variables and malaria epidemiology at a micro-geographic level using a novel statistical approach. The random forest (RF) statistical learning method, a relatively new variable-importance ranking method, measures the variable importance of potentially influential parameters through the percent increase of the mean squared error. As this value increases, so does the relative importance of the associated variable. The principal aim of this study was to create predictive malaria maps generated using the selected variables based on the RF algorithm in the Ehlanzeni District of Mpumalanga Province, South Africa. From the seven environmental variables used [temperature, lag temperature, rainfall, lag rainfall, humidity, altitude, and the normalized difference vegetation index (NDVI)], altitude was identified as the most influential predictor variable due its high selection frequency. It was selected as the top predictor for 4 out of 12 months of the year, followed by NDVI, temperature and lag rainfall, which were each selected twice. The combination of climatic variables that produced the highest prediction accuracy was altitude, NDVI, and temperature. This suggests that these three variables have high predictive capabilities in relation to malaria transmission. Furthermore, it is anticipated that the predictive maps generated from predictions made by the RF algorithm could be used to monitor the progression of malaria and assist in intervention and prevention efforts with respect to malaria.

  3. Random forest variable selection in spatial malaria transmission modelling in Mpumalanga Province, South Africa

    Directory of Open Access Journals (Sweden)

    Thandi Kapwata

    2016-11-01

    Full Text Available Malaria is an environmentally driven disease. In order to quantify the spatial variability of malaria transmission, it is imperative to understand the interactions between environmental variables and malaria epidemiology at a micro-geographic level using a novel statistical approach. The random forest (RF statistical learning method, a relatively new variable-importance ranking method, measures the variable importance of potentially influential parameters through the percent increase of the mean squared error. As this value increases, so does the relative importance of the associated variable. The principal aim of this study was to create predictive malaria maps generated using the selected variables based on the RF algorithm in the Ehlanzeni District of Mpumalanga Province, South Africa. From the seven environmental variables used [temperature, lag temperature, rainfall, lag rainfall, humidity, altitude, and the normalized difference vegetation index (NDVI], altitude was identified as the most influential predictor variable due its high selection frequency. It was selected as the top predictor for 4 out of 12 months of the year, followed by NDVI, temperature and lag rainfall, which were each selected twice. The combination of climatic variables that produced the highest prediction accuracy was altitude, NDVI, and temperature. This suggests that these three variables have high predictive capabilities in relation to malaria transmission. Furthermore, it is anticipated that the predictive maps generated from predictions made by the RF algorithm could be used to monitor the progression of malaria and assist in intervention and prevention efforts with respect to malaria.

  4. Random and systematic spatial variability of 137Cs inventories at reference sites in South-Central Brazil

    Directory of Open Access Journals (Sweden)

    Correchel Vladia

    2005-01-01

    Full Text Available The precision of the 137Cs fallout redistribution technique for the evaluation of soil erosion rates is strongly dependent on the quality of an average inventory taken at a representative reference site. The knowledge of the sources and of the degree of variation of the 137Cs fallout spatial distribution plays an important role on its use. Four reference sites were selected in the South-Central region of Brazil which were characterized in terms of soil chemical, physical and mineralogical aspects as well as the spatial variability of 137Cs inventories. Some important differences in the patterns of 137Cs depth distribution in the soil profiles of the different sites were found. They are probably associated to chemical, physical, mineralogical and biological differences of the soils but many questions still remain open for future investigation, mainly those regarding the adsorption and dynamics of the 137Cs ions in soil profiles under tropical conditions. The random spatial variability (inside each reference site was higher than the systematic spatial variability (between reference sites but their causes were not clearly identified as possible consequences of chemical, physical, mineralogical variability, and/or precipitation.

  5. Spatial Variability of Rainfall

    DEFF Research Database (Denmark)

    Jensen, N.E.; Pedersen, Lisbeth

    2005-01-01

    As a part of a Local Area Weather Radar (LAWR) calibration exercise 15 km south of Århus, Denmark, the variability in accumulated rainfall within a single radar pixel (500 by 500 m) was measured using nine high-resolution rain gauges. The measured values indicate up to a 100% variation between ne...

  6. Strong Decomposition of Random Variables

    DEFF Research Database (Denmark)

    Hoffmann-Jørgensen, Jørgen; Kagan, Abram M.; Pitt, Loren D.

    2007-01-01

    A random variable X is stongly decomposable if X=Y+Z where Y=Φ(X) and Z=X-Φ(X) are independent non-degenerated random variables (called the components). It is shown that at least one of the components is singular, and we derive a necessary and sufficient condition for strong decomposability...... of a discrete random variable....

  7. Students' Misconceptions about Random Variables

    Science.gov (United States)

    Kachapova, Farida; Kachapov, Ilias

    2012-01-01

    This article describes some misconceptions about random variables and related counter-examples, and makes suggestions about teaching initial topics on random variables in general form instead of doing it separately for discrete and continuous cases. The focus is on post-calculus probability courses. (Contains 2 figures.)

  8. Free random variables

    CERN Document Server

    Voiculescu, Dan; Nica, Alexandru

    1992-01-01

    This book presents the first comprehensive introduction to free probability theory, a highly noncommutative probability theory with independence based on free products instead of tensor products. Basic examples of this kind of theory are provided by convolution operators on free groups and by the asymptotic behavior of large Gaussian random matrices. The probabilistic approach to free products has led to a recent surge of new results on the von Neumann algebras of free groups. The book is ideally suited as a textbook for an advanced graduate course and could also provide material for a seminar. In addition to researchers and graduate students in mathematics, this book will be of interest to physicists and others who use random matrices.

  9. Symmetrization of binary random variables

    OpenAIRE

    Kagan, Abram; Mallows, Colin L.; Shepp, Larry A.; Vanderbei, Robert J.; Vardi, Yehuda

    1999-01-01

    A random variable [math] is called an independent symmetrizer of a given random variable [math] if (a) it is independent of [math] and (b) the distribution of [math] is symmetric about [math] . In cases where the distribution of [math] is symmetric about its mean, it is easy to see that the constant random variable [math] is a minimum-variance independent symmetrizer. Taking [math] to have the same distribution as [math] clearly produces a symmetric sum, but it may not be of minimum variance....

  10. Spatial variability of groundwater recharge - I. Is it really variable?

    OpenAIRE

    De Silva, RP

    2004-01-01

    The spatial variability of recharge is an important consideration in estimating recharge especially as all methods of estimating it are 'point' estimates and in most places recharge varies in space. This paper along with the accompanying paper attempts to find a suitable answer to the question of taking this variability into account in estimating groundwater recharge. This paper attempts to determine if recharge is actually varying in space and that this is 'true' variability and that it is n...

  11. Spatial Extent of Random Laser Modes

    NARCIS (Netherlands)

    van der Molen, K.L.; Tjerkstra, R.W.; Mosk, Allard; Lagendijk, Aart

    2007-01-01

    We have experimentally studied the distribution of the spatial extent of modes and the crossover from essentially single-mode to distinctly multimode behavior inside a porous gallium phosphide random laser. This system serves as a paragon for random lasers due to its exemplary high index contrast.

  12. Mesoscale spatial variability in seawater cavitation thresholds

    Science.gov (United States)

    Mel'nikov, N. P.; Elistratov, V. P.

    2017-03-01

    The paper presents the spatial variability of cavitation thresholds and some hydrological and hydrochemical parameters of seawater in the interfrontal zone of the Pacific Subarctic Front, in the Drake Passage, and in the equatorial part of the Pacific Ocean, measured in the near-surface layer to a depth of 70 m.

  13. Spatial variability in macroinvertebrate assemblages: comparing ...

    African Journals Online (AJOL)

    Spatial variability in macroinvertebrate assemblages was examined with the aim of evaluating the utility of regional classification systems in aquatic ... process that allows for subjective a priori regional classifications to be modified on the basis of independent, objective a posteriori classification of biological assemblages.

  14. Spatial ascariasis risk estimation using socioeconomic variables.

    Science.gov (United States)

    Valencia, Luis Iván Ortiz; Fortes, Bruno de Paula Menezes Drumond; Medronho, Roberto de Andrade

    2005-12-01

    Frequently, disease incidence is mapped as area data, for example, census tracts, districts or states. Spatial disease incidence can be highly heterogeneous inside these areas. Ascariasis is a highly prevalent disease, which is associated with poor sanitation and hygiene. Geostatistics was applied to model spatial distribution of Ascariasis risk and socioeconomic risk events in a poor community in Rio de Janeiro, Brazil. Data were gathered from a coproparasitologic and a domiciliary survey in 1550 children aged 1-9. Ascariasis risk and socioeconomic risk events were spatially estimated using Indicator Kriging. Cokriging models with a Linear Model of Coregionalization incorporating one socioeconomic variable were implemented. If a housewife attended school for less than four years, the non-use of a home water filter, a household density greater than one, and a household income lower than one Brazilian minimum wage increased the risk of Ascariasis. Cokriging improved spatial estimation of Ascariasis risk areas when compared to Indicator Kriging and detected more Ascariasis very-high risk areas than the GIS Overlay method.

  15. The Spatial Variability of Supraglacial Channel Network Morphology

    Science.gov (United States)

    King, L.

    2016-12-01

    Supraglacial streams are widespread and ubiquitous features of glacial ice surfaces around the world and in the solar system. They play an important role in the spatial and temporal distribution of meltwater on a glacier, moderating the flux of meltwater to the bed, and are of increasing interest to the glaciological and fluvial geomorphological communities. However, little is known about the variability of their characteristics through space and time, how these characteristics reflect external driving forces, and what their variability implies in terms of glacial dynamics. This research characterizes the spatial variability of supraglacial stream morphology across a range of glacier types and environmental conditions with the ultimate goal of identifying ice and climate characteristics that control channel form. High resolution topographic data was analyzed from a range of glacier surface types including icesheets, pocket alpine glaciers, and outlet valley glaciers spanning a range of latitudes and elevations, comprising glaciers from Greenland, British Columbia, Alaska, Iceland and Sweden. Supraglacial channel networks were derived from the topographic data, and the spatial variability of channel and network morphometrics was analyzed. Supraglacial channel morphometrics vary widely in space, but the variability in the data is not random - rather, trends in morphometrics group according to ice surface type and characteristics, suggesting that ice characteristics and local conditions are measurably expressed in supraglacial channel evolution and form.

  16. Contextuality in canonical systems of random variables.

    Science.gov (United States)

    Dzhafarov, Ehtibar N; Cervantes, Víctor H; Kujala, Janne V

    2017-11-13

    Random variables representing measurements, broadly understood to include any responses to any inputs, form a system in which each of them is uniquely identified by its content (that which it measures) and its context (the conditions under which it is recorded). Two random variables are jointly distributed if and only if they share a context. In a canonical representation of a system, all random variables are binary, and every content-sharing pair of random variables has a unique maximal coupling (the joint distribution imposed on them so that they coincide with maximal possible probability). The system is contextual if these maximal couplings are incompatible with the joint distributions of the context-sharing random variables. We propose to represent any system of measurements in a canonical form and to consider the system contextual if and only if its canonical representation is contextual. As an illustration, we establish a criterion for contextuality of the canonical system consisting of all dichotomizations of a single pair of content-sharing categorical random variables.This article is part of the themed issue 'Second quantum revolution: foundational questions'. © 2017 The Author(s).

  17. Contextuality in canonical systems of random variables

    Science.gov (United States)

    Dzhafarov, Ehtibar N.; Cervantes, Víctor H.; Kujala, Janne V.

    2017-10-01

    Random variables representing measurements, broadly understood to include any responses to any inputs, form a system in which each of them is uniquely identified by its content (that which it measures) and its context (the conditions under which it is recorded). Two random variables are jointly distributed if and only if they share a context. In a canonical representation of a system, all random variables are binary, and every content-sharing pair of random variables has a unique maximal coupling (the joint distribution imposed on them so that they coincide with maximal possible probability). The system is contextual if these maximal couplings are incompatible with the joint distributions of the context-sharing random variables. We propose to represent any system of measurements in a canonical form and to consider the system contextual if and only if its canonical representation is contextual. As an illustration, we establish a criterion for contextuality of the canonical system consisting of all dichotomizations of a single pair of content-sharing categorical random variables. This article is part of the themed issue `Second quantum revolution: foundational questions'.

  18. SPATIAL VARIABILITY OF PEDOZEMS MECHANICAL IMPEDANCE

    Directory of Open Access Journals (Sweden)

    Zhukov A.V.

    2013-04-01

    Full Text Available We studied the spatial variability of pedozem mechanical impedance in ResearchRemediation Center of the Dnipropetrovsk State Agrarian University in Ordzhonikidze. Thestatistical distribution of the soil mechanical impedance within the studied area is characterized by deviation from the normal law in 0–10 and 30–50 cm layers from the surface. 2D and 3D modeling shows the structural design of the soil as locations of high mechanical impedance which found in the soils with less hardness.

  19. Probabilistic graphs using coupled random variables

    Science.gov (United States)

    Nelson, Kenric P.; Barbu, Madalina; Scannell, Brian J.

    2014-05-01

    Neural network design has utilized flexible nonlinear processes which can mimic biological systems, but has suffered from a lack of traceability in the resulting network. Graphical probabilistic models ground network design in probabilistic reasoning, but the restrictions reduce the expressive capability of each node making network designs complex. The ability to model coupled random variables using the calculus of nonextensive statistical mechanics provides a neural node design incorporating nonlinear coupling between input states while maintaining the rigor of probabilistic reasoning. A generalization of Bayes rule using the coupled product enables a single node to model correlation between hundreds of random variables. A coupled Markov random field is designed for the inferencing and classification of UCI's MLR `Multiple Features Data Set' such that thousands of linear correlation parameters can be replaced with a single coupling parameter with just a (3%, 4%) reduction in (classification, inference) performance.

  20. Comparison of the spatial and temporal variability of drought indices ...

    African Journals Online (AJOL)

    Comparison of the spatial and temporal variability of drought indices in Somalia and ... annual precipitation, aridity index and spatial distribution of surface water bodies. ... The lessons from the current drought in Horn of Africa are however, ...

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

    Science.gov (United States)

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

    2014-11-01

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

  2. Maximal Inequalities for Dependent Random Variables

    DEFF Research Database (Denmark)

    Hoffmann-Jorgensen, Jorgen

    2016-01-01

    Maximal inequalities play a crucial role in many probabilistic limit theorem; for instance, the law of large numbers, the law of the iterated logarithm, the martingale limit theorem and the central limit theorem. Let X-1, X-2,... be random variables with partial sums S-k = X-1 + ... + X......-k. Then a maximal inequality gives conditions ensuring that the maximal partial sum M-n = max(1) (...

  3. Fast Generation of Discrete Random Variables

    Directory of Open Access Journals (Sweden)

    George Marsaglia

    2004-07-01

    Full Text Available We describe two methods and provide C programs for generating discrete random variables with functions that are simple and fast, averaging ten times as fast as published methods and more than five times as fast as the fastest of those. We provide general procedures for implementing the two methods, as well as specific procedures for three of the most important discrete distributions: Poisson, binomial and hypergeometric.

  4. Spatially Resolved Images and Solar Irradiance Variability

    Indian Academy of Sciences (India)

    Variations in UV irradiances seen at earth are the sum of global (solar dynamo) to regional (active region, plage, network, bright points and background) solar magnetic activities that can be identified through spatially resolved photospheric, chromospheric and coronal features. In this research, the images of CaII K-line ...

  5. Statistical Downscaling Based on Spartan Spatial Random Fields

    Science.gov (United States)

    Hristopulos, Dionissios

    2010-05-01

    Stochastic methods of space-time interpolation and conditional simulation have been used in statistical downscaling approaches to increase the resolution of measured fields. One of the popular interpolation methods in geostatistics is kriging, also known as optimal interpolation in data assimilation. Kriging is a stochastic, linear interpolator which incorporates time/space variability by means of the variogram function. However, estimation of the variogram from data involves various assumptions and simplifications. At the same time, the high numerical complexity of kriging makes it difficult to use for very large data sets. We present a different approach based on the so-called Spartan Spatial Random Fields (SSRFs). SSRFs were motivated from classical field theories of statistical physics [1]. The SSRFs provide a different approach of parametrizing spatial dependence based on 'effective interactions,' which can be formulated based on general statistical principles or even incorporate physical constraints. This framework leads to a broad family of covariance functions [2], and it provides new perspectives in covariance parameter estimation and interpolation [3]. A significant advantage offered by SSRFs is reduced numerical complexity, which can lead to much faster codes for spatial interpolation and conditional simulation. In addition, on grids composed of rectangular cells, the SSRF representation leads to an explicit expression for the precision matrix (the inverse covariance). Therefore SSRFs could provide useful models of error covariance for data assimilation methods. We use simulated and real data to demonstrate SSRF properties and downscaled fields. keywords: interpolation, conditional simulation, precision matrix References [1] Hristopulos, D.T., 2003. Spartan Gibbs random field models for geostatistical applications, SIAM Journal in Scientific Computation, 24, 2125-2162. [2] Hristopulos, D.T., Elogne, S. N. 2007. Analytic properties and covariance

  6. Relevance of anisotropy and spatial variability of gas diffusivity for soil-gas transport

    Science.gov (United States)

    Schack-Kirchner, Helmer; Kühne, Anke; Lang, Friederike

    2017-04-01

    Models of soil gas transport generally do not consider neither direction dependence of gas diffusivity, nor its small-scale variability. However, in a recent study, we could provide evidence for anisotropy favouring vertical gas diffusion in natural soils. We hypothesize that gas transport models based on gas diffusion data measured with soil rings are strongly influenced by both, anisotropy and spatial variability and the use of averaged diffusivities could be misleading. To test this we used a 2-dimensional model of soil gas transport to under compacted wheel tracks to model the soil-air oxygen distribution in the soil. The model was parametrized with data obtained from soil-ring measurements with its central tendency and variability. The model includes vertical parameter variability as well as variation perpendicular to the elongated wheel track. Different parametrization types have been tested: [i)]Averaged values for wheel track and undisturbed. em [ii)]Random distribution of soil cells with normally distributed variability within the strata. em [iii)]Random distributed soil cells with uniformly distributed variability within the strata. All three types of small-scale variability has been tested for [j)] isotropic gas diffusivity and em [jj)]reduced horizontal gas diffusivity (constant factor), yielding in total six models. As expected the different parametrizations had an important influence to the aeration state under wheel tracks with the strongest oxygen depletion in case of uniformly distributed variability and anisotropy towards higher vertical diffusivity. The simple simulation approach clearly showed the relevance of anisotropy and spatial variability in case of identical central tendency measures of gas diffusivity. However, until now it did not consider spatial dependency of variability, that could even aggravate effects. To consider anisotropy and spatial variability in gas transport models we recommend a) to measure soil-gas transport parameters

  7. Examining environmental drivers of spatial variability in aflatoxin ...

    African Journals Online (AJOL)

    Examining environmental drivers of spatial variability in aflatoxin accumulation in Kenyan maize: potential utility in risk prediction models. L.E. Smith, M Stasiewicz, R Hestrin, L Morales, S Mutiga, R.J. Nelson ...

  8. Impact of spatial variability and sampling design on model performance

    Science.gov (United States)

    Schrape, Charlotte; Schneider, Anne-Kathrin; Schröder, Boris; van Schaik, Loes

    2017-04-01

    Many environmental physical and chemical parameters as well as species distributions display a spatial variability at different scales. In case measurements are very costly in labour time or money a choice has to be made between a high sampling resolution at small scales and a low spatial cover of the study area or a lower sampling resolution at the small scales resulting in local data uncertainties with a better spatial cover of the whole area. This dilemma is often faced in the design of field sampling campaigns for large scale studies. When the gathered field data are subsequently used for modelling purposes the choice of sampling design and resulting data quality influence the model performance criteria. We studied this influence with a virtual model study based on a large dataset of field information on spatial variation of earthworms at different scales. Therefore we built a virtual map of anecic earthworm distributions over the Weiherbach catchment (Baden-Württemberg in Germany). First of all the field scale abundance of earthworms was estimated using a catchment scale model based on 65 field measurements. Subsequently the high small scale variability was added using semi-variograms, based on five fields with a total of 430 measurements divided in a spatially nested sampling design over these fields, to estimate the nugget, range and standard deviation of measurements within the fields. With the produced maps, we performed virtual samplings of one up to 50 random points per field. We then used these data to rebuild the catchment scale models of anecic earthworm abundance with the same model parameters as in the work by Palm et al. (2013). The results of the models show clearly that a large part of the non-explained deviance of the models is due to the very high small scale variability in earthworm abundance: the models based on single virtual sampling points on average obtain an explained deviance of 0.20 and a correlation coefficient of 0.64. With

  9. Response of Fish Communities to Various Environmental Variables across Multiple Spatial Scales

    Science.gov (United States)

    Kwon, Yong-Su; Li, Fengqing; Chung, Namil; Bae, Mi-Jung; Hwang, Soon-Jin; Byoen, Myeong-Seop; Park, Sang-Jung; Park, Young-Seuk

    2012-01-01

    A better understanding of the relative importance of different spatial scale determinants on fish communities will eventually increase the accuracy and precision of their bioassessments. Many studies have described the influence of environmental variables on fish communities on multiple spatial scales. However, there is very limited information available on this topic for the East Asian monsoon region, including Korea. In this study, we evaluated the relationship between fish communities and environmental variables at multiple spatial scales using self-organizing map (SOM), random forest, and theoretical path models. The SOM explored differences among fish communities, reflecting environmental gradients, such as a longitudinal gradient from upstream to downstream, and differences in land cover types and water quality. The random forest model for predicting fish community patterns that used all 14 environmental variables was more powerful than a model using any single variable or other combination of environmental variables, and the random forest model was effective at predicting the occurrence of species and evaluating the contribution of environmental variables to that prediction. The theoretical path model described the responses of different species to their environment at multiple spatial scales, showing the importance of altitude, forest, and water quality factors to fish assemblages. PMID:23202766

  10. 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.

  11. Partitioning the impacts of spatial rainfall variability and climate variability in urban drainage flow modelling

    Science.gov (United States)

    Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

    2017-04-01

    The performance of urban drainage systems is typically examined using hydrological and hydrodynamic models where rainfall is uniformly distributed and derived from a single rain gauge, or spatially distributed and obtained from a weather radar system. When models are fed with a single realization, the response of the urban drainage system to the spatiotemporal variability of rainfall remains unexplored. High resolution stochastic rainfall generators allow studying the response and sensitivity of urban drainage networks to these spatial and climatological rainfall variabilities. The goal in this study was to understand how climate variability and spatial rainfall variability affect the response of a calibrated hydrodynamic urban drainage model. A stochastic high resolution rainfall generator (STREAP) was used to simulate many realizations of rainfall, accounting for both climate variability and spatial rainfall variability. The generated rainfall was then used as input into a calibrated hydrodynamic model (EPA SWMM) to simulate surface runoff and channel flow for a small urban catchment. The variability of peak flows at three different locations in the urban drainage network in response to rainfall of different return periods was evaluated and partitioned among it sources. We found that the main contribution to the total flow variability originates from the natural climate variability. In addition, the contribution of spatial rainfall variability to the total flow variability was found to increase with longer return periods.

  12. Joint Estimation of Spatial Variable Transmissivities and Recharge

    Science.gov (United States)

    Hendricks Franssen, H. J. W. M.; Stauffer, F.; Kinzelbach, W.

    Uncertainty in the input parameters of groundwater flow and mass transport models is an important cause of model prediction uncertainty. On one side, it is important to characterise this uncertainty in a stochastic approach. On the other side, it is fundamental to reduce the uncertainty by efficient use of available measurement data. The sequential self-calibrated approach, a Monte-Carlo type inverse modelling approach, is able to generate a large number of multiple equally likely solutions to a groundwater flow and mass transport problem that are conditioned to conductivity, storativity, head and concentration data, among others. Frequently the calibration is limited to the spatially variable transmissivities. In other cases it may be necessary to estimate also spatially variable storativities, recharge rates, boundary conditions or porosities. In practical problems such as the determination of a, possibly time-dependent, drinking water well capture zone usually recharge and transmissivities have to be estimated jointly. A synthetic study that mimics such a practical problem illustrates the joint estimation of spatially variable transmissivities and recharge. It is found that in most practical situations it is not necessary to estimate the detailed spatial pattern of recharge. However, it is important to consider the uncertainty in the mean recharge. With respect to transmissivities on the other hand, the mean is of little relevance for the estimation of capture zones, while the spatial variability is important. In the example, transmissivities and recharge could successfully be estimated jointly, improving both the characterisation of the spatially variable transmissivities and the spatially variable recharge. Conditioning to hydraulic head data, correlated with both the recharges and the transmissivities through the groundwater flow equation, allows to improve the estimation of transmissivities and recharge.

  13. Revealing cryptic spatial patterns in genetic variability by a new multivariate method.

    Science.gov (United States)

    Jombart, T; Devillard, S; Dufour, A-B; Pontier, D

    2008-07-01

    Increasing attention is being devoted to taking landscape information into account in genetic studies. Among landscape variables, space is often considered as one of the most important. To reveal spatial patterns, a statistical method should be spatially explicit, that is, it should directly take spatial information into account as a component of the adjusted model or of the optimized criterion. In this paper we propose a new spatially explicit multivariate method, spatial principal component analysis (sPCA), to investigate the spatial pattern of genetic variability using allelic frequency data of individuals or populations. This analysis does not require data to meet Hardy-Weinberg expectations or linkage equilibrium to exist between loci. The sPCA yields scores summarizing both the genetic variability and the spatial structure among individuals (or populations). Global structures (patches, clines and intermediates) are disentangled from local ones (strong genetic differences between neighbors) and from random noise. Two statistical tests are proposed to detect the existence of both types of patterns. As an illustration, the results of principal component analysis (PCA) and sPCA are compared using simulated datasets and real georeferenced microsatellite data of Scandinavian brown bear individuals (Ursus arctos). sPCA performed better than PCA to reveal spatial genetic patterns. The proposed methodology is implemented in the adegenet package of the free software R.

  14. The Common Information of N Dependent Random Variables

    CERN Document Server

    Liu, Wei; Chen, Biao

    2010-01-01

    This paper generalizes Wyner's definition of common information of a pair of random variables to that of $N$ random variables. We prove coding theorems that show the same operational meanings for the common information of two random variables generalize to that of $N$ random variables. As a byproduct of our proof, we show that the Gray-Wyner source coding network can be generalized to $N$ source squences with $N$ decoders. We also establish a monotone property of Wyner's common information which is in contrast to other notions of the common information, specifically Shannon's mutual information and G\\'{a}cs and K\\"{o}rner's common randomness. Examples about the computation of Wyner's common information of $N$ random variables are also given.

  15. Spatial and temporal variability of chlorophyll in Bay of Bengal.

    Science.gov (United States)

    Jutla, A.; Akanda, S.; Islam, S.

    2009-04-01

    The Bay of Bengal (BoB) receives approximately 628 km3/ year of freshwater discharge from the Ganges and Brahmaputra rivers. Freshwater discharge from rivers increases the nutrient load and thereby enhances phytoplankton production in the BoB. Cholera, an infectious water-borne disease caused by bacterium Vibrio cholerae, remains endemic in the BoB region. Phytoplankton provides favorable environment for survival of cholera bacteria. Therefore, for development of any predictive model for cholera, it is important to quantify the spatial and temporal variability of phytoplankton in the BoB. Satellite remote sensing is the most effective way to quantify this variability over a range of space and time scales. Using ten years (1998-2007) of daily, weekly and monthly SeaWiFs chlorophyll, a surrogate variable for measuring phytoplankton, imagery we explore the spatial pattern and dominant temporal variability of chlorophyll over the BoB region. We find that chlorophyll in the coastal waters has more variability, both in temporal and spatial scales, than the offshore waters. Mechanism of production and space-time variability of coastal chlorophyll is different from those of offshore chlorophyll. While coastal chlorophyll is dominated by influx of terrestrial nutrients through river discharge, chlorophyll in the offshore region is primarily controlled by oceanic processes. We will also explore issues related to dominant space and time scales of chlorophyll variations in the entire bay.

  16. Spatial Variability of Wet Troposphere Delays Over Inland Water Bodies

    Science.gov (United States)

    Mehran, Ali; Clark, Elizabeth A.; Lettenmaier, Dennis P.

    2017-11-01

    Satellite radar altimetry has enabled the study of water levels in large lakes and reservoirs at a global scale. The upcoming Surface Water and Ocean Topography (SWOT) satellite mission (scheduled launch 2020) will simultaneously measure water surface extent and elevation at an unprecedented accuracy and resolution. However, SWOT retrieval accuracy will be affected by a number of factors, including wet tropospheric delay—the delay in the signal's passage through the atmosphere due to atmospheric water content. In past applications, the wet tropospheric delay over large inland water bodies has been corrected using atmospheric moisture profiles based on atmospheric reanalysis data at relatively coarse (tens to hundreds of kilometers) spatial resolution. These products cannot resolve subgrid variations in wet tropospheric delays at the spatial resolutions (of 1 km and finer) that SWOT is intended to resolve. We calculate zenith wet tropospheric delays (ZWDs) and their spatial variability from Weather Research and Forecasting (WRF) numerical weather prediction model simulations at 2.33 km spatial resolution over the southwestern U.S., with attention in particular to Sam Rayburn, Ray Hubbard, and Elephant Butte Reservoirs which have width and length dimensions that are of order or larger than the WRF spatial resolution. We find that spatiotemporal variability of ZWD over the inland reservoirs depends on climatic conditions at the reservoir location, as well as distance from ocean, elevation, and surface area of the reservoir, but that the magnitude of subgrid variability (relative to analysis and reanalysis products) is generally less than 10 mm.

  17. Fuzzy random variables — I. definitions and theorems

    NARCIS (Netherlands)

    Kwakernaak, H.

    1978-01-01

    Fuzziness is discussed in the context of multivalued logic, and a corresponding view of fuzzy sets is given. Fuzzy random variables are introduced as random variables whose values are not real but fuzzy numbers, and subsequently redefined as a particular kind of fuzzy set. Expectations of fuzzy

  18. On complete moment convergence for nonstationary negatively associated random variables

    Directory of Open Access Journals (Sweden)

    Mi-Hwa Ko

    2016-05-01

    Full Text Available Abstract The purpose of this paper is to establish the complete moment convergence for nonstationary negatively associated random variables satisfying the weak mean domination condition. The result is an improvement of complete convergence in Marcinkiewicz-Zygmund-type SLLN for negatively associated random variables in Kuczmaszewska (Acta Math. Hung. 128:116-130, 2010.

  19. Characterizations of Distributions of Ratios of Certain Independent Random Variables

    Directory of Open Access Journals (Sweden)

    Hamedani G.G.

    2013-05-01

    Full Text Available Various characterizations of the distributions of the ratio of two independent gamma and exponential random variables as well as that of two independent Weibull random variables are presented. These characterizations are based, on a simple relationship between two truncated moments ; on hazard function ; and on functions of order statistics.

  20. On the product and ratio of Bessel random variables

    Directory of Open Access Journals (Sweden)

    Saralees Nadarajah

    2005-01-01

    Full Text Available The distributions of products and ratios of random variables are of interest in many areas of the sciences. In this paper, the exact distributions of the product |XY| and the ratio |X/Y| are derived when X and Y are independent Bessel function random variables. An application of the results is provided by tabulating the associated percentage points.

  1. Probabilistic and spatially variable niches inferred from demography

    Science.gov (United States)

    Jeffrey M. Diez; Itamar Giladi; Robert Warren; H. Ronald. Pulliam

    2014-01-01

    Summary 1. Mismatches between species distributions and habitat suitability are predicted by niche theory and have important implications for forecasting how species may respond to environmental changes. Quantifying these mismatches is challenging, however, due to the high dimensionality of species niches and the large spatial and temporal variability in population...

  2. Variable spatial structure of schooling pelagic fish off Namibia ...

    African Journals Online (AJOL)

    The influence of aggregation patterns of the different species on the precision of the acoustic estimates was analysed with respect to spatial variability and diurnal effects. Isotropic variograms computed from values of acoustic back-scattering strength showed little or no structure for all three species. Indicator variograms ...

  3. Measured spatial variability of beach erosion due to aeolian processes.

    NARCIS (Netherlands)

    de Vries, S.; Verheijen, A.H.; Hoonhout, B.M.; Vos, S.E.; Cohn, Nicholas; Ruggiero, P; Aagaard, T.; Deigaard, R.; Fuhrman, D.

    2017-01-01

    This paper shows the first results of measured spatial variability of beach erosion due to aeolian processes during the recently conducted SEDEX2 field experiment at Long Beach, Washington, U.S.A.. Beach erosion and sedimentation were derived using series of detailed terrestrial LIDAR measurements

  4. Monitoring spatial-temporal variability of aerosol over Kenya ...

    African Journals Online (AJOL)

    A Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model was used for trajectory analysis in order to reconstruct the origins of air masses and understand the Spatial and temporal variability of aerosol concentrations. Validation of MODIS AOD using Aerosol Robotic Network (AERONET) indicated that ...

  5. Probability, random variables, and random processes theory and signal processing applications

    CERN Document Server

    Shynk, John J

    2012-01-01

    Probability, Random Variables, and Random Processes is a comprehensive textbook on probability theory for engineers that provides a more rigorous mathematical framework than is usually encountered in undergraduate courses. It is intended for first-year graduate students who have some familiarity with probability and random variables, though not necessarily of random processes and systems that operate on random signals. It is also appropriate for advanced undergraduate students who have a strong mathematical background. The book has the following features: Several app

  6. Spatial panel data models of aquaculture production in West Sumatra province with random-effects

    Science.gov (United States)

    Sartika, Wimi; Susetyo, Budi; Syafitri, Utami Dyah

    2017-03-01

    Spatial Panel Regression is a statistical model that used to analyze the effect of several independent variables on the dependent variable based on using panel data and take the spatial effect into account. There are two approaches on predicting spatial panel data, Fixed Effect Spatial Autoregressive (SAR-FE) and Random Effect Spatial Autoregressive (SAR-RE). SAR-FE has the assumption that the intercept has vary acrros spatial unit, while the SAR-RE's assumption is the interception is on residual model and it only has a general intercept. The purpose of this study is to modeling the production of West Sumatra fishery using Spatial Panel Regression. The model uses secondary data which is published by "Badan Pusat Statistik" on the results of aquaculture production in West Sumatra. The test results shown that the level of West Sumatra 2004-2012 aquaculture production was precisely modeled by the approach of Spatial Autoregressive Random Effect. From SAR-RE model, the most influence factors on aquaculture production in West Sumatra province in 2004-2012 was the number of motor boats, the area of fish seeds, fish seed production, and the number of fishermen public waters.

  7. Spatial variability in streambed hydraulic conductivity of contrasting stream morphologies

    DEFF Research Database (Denmark)

    Sebök, Éva; Calvache, Carlos Duque; Engesgaard, Peter Knudegaard

    2015-01-01

    Streambed hydraulic conductivity is one of the main factors controlling variability in surface water-groundwater interactions, but only few studies aim at quantifying its spatial and temporal variability in different stream morphologies. Streambed horizontal hydraulic conductivities (Kh) were...... therefore determined from in-stream slug tests, vertical hydraulic conductivities (Kv) were calculated with in-stream permeameter tests and hydraulic heads were measured to obtain vertical head gradients at eight transects, each comprising five test locations, in a groundwater-dominated stream. Seasonal...... small-scale measurements were taken in December 2011 and August 2012, both in a straight stream channel with homogeneous elevation and downstream of a channel meander with heterogeneous elevation. All streambed attributes showed large spatial variability. Kh values were the highest at the depositional...

  8. Stochastic geometry, spatial statistics and random fields models and algorithms

    CERN Document Server

    2015-01-01

    Providing a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, this volume places a special emphasis on fundamental classes of models and algorithms as well as on their applications, for example in materials science, biology and genetics. This book has a strong focus on simulations and includes extensive codes in Matlab and R, which are widely used in the mathematical community. It can be regarded as a continuation of the recent volume 2068 of Lecture Notes in Mathematics, where other issues of stochastic geometry, spatial statistics and random fields were considered, with a focus on asymptotic methods.

  9. Spatial variability of chemical properties of soil under pasture

    Directory of Open Access Journals (Sweden)

    Samuel Ferreira da Silva

    2016-04-01

    Full Text Available The objective of this study was to analyze the spatial variability of soil chemical attributes under pasture, as well as lime and fertilizer recommendations based on the interpretation of soil chemical analysis from two sampling methods: conventional and systematic depths of 0 to 10 and 10 to 20 cm. The study was conducted at IFES-campus Alegre-ES. Data analysis was performed using descriptive statistics and geostatistics. Results indicate that the spatial method enabled the identification of deficit areas and excessive liming and fertilization, which could not be defined by the conventional method.

  10. Analytical model of reactive transport processes with spatially variable coefficients.

    Science.gov (United States)

    Simpson, Matthew J; Morrow, Liam C

    2015-05-01

    Analytical solutions of partial differential equation (PDE) models describing reactive transport phenomena in saturated porous media are often used as screening tools to provide insight into contaminant fate and transport processes. While many practical modelling scenarios involve spatially variable coefficients, such as spatially variable flow velocity, v(x), or spatially variable decay rate, k(x), most analytical models deal with constant coefficients. Here we present a framework for constructing exact solutions of PDE models of reactive transport. Our approach is relevant for advection-dominant problems, and is based on a regular perturbation technique. We present a description of the solution technique for a range of one-dimensional scenarios involving constant and variable coefficients, and we show that the solutions compare well with numerical approximations. Our general approach applies to a range of initial conditions and various forms of v(x) and k(x). Instead of simply documenting specific solutions for particular cases, we present a symbolic worksheet, as supplementary material, which enables the solution to be evaluated for different choices of the initial condition, v(x) and k(x). We also discuss how the technique generalizes to apply to models of coupled multispecies reactive transport as well as higher dimensional problems.

  11. Stochastic Modeling of Macrodispersion in Variably Saturated, Spatially Heterogeneous Formations

    Science.gov (United States)

    Russo, David

    2015-04-01

    The macrodispersion tensor, D, plays an important role in solute transport on the field scale. A key problem is how to relate D to the properties of the spatially heterogeneous formation. Under unsaturated flow conditions, the problem is further complicated inasmuch as the relevant flow parameters, the hydraulic conductivity and the water capacity, which depend on the formation properties, depend also on flow-controlled attributes in a highly nonlinear fashion. Consequently, under variably saturated conditions, quantification of D requires several simplifying assumptions regarding the constitutive relationships for unsaturated flow, the flow regime, and the spatial structure of the formation heterogeneity. The present talk focuses on the quantification of D in a variably saturated, spatially heterogeneous formation, accomplished by using a two-stage approach. The approach combines a stochastic, continuum description of a steady-state unsaturated flow, based on small-perturbation, first-order approximation of Darcy's law and the continuity equation for unsaturated flow, with a general Lagrangian description of the motion of an indivisible particle of a passive solute that is carried by the steady-state flow. The resultant, time-dependent D depends on the covariances of the water saturation and the components of the water flux vector, and their cross-covariances, which, in turn, depend on the (cross-)covariances of the relevant formation properties and the pressure head. The effect of few characteristics of the spatially heterogeneous, variably saturated flow system, on D is analyzed and discussed. Main findings reveal that under variably saturated flow conditions, the travel distance required for the principal components of D to approach their asymptotic values may be exceedingly large, particularly in relatively wet formations with significant stratification and with coarse-textured soil material associated with small capillary forces. Hence, in many practical

  12. In-Situ Spatial Variability Of Thermal Conductivity And Volumetric ...

    African Journals Online (AJOL)

    Studies of spatial variability of thermal conductivity and volumetric water content of silty topsoil were conduct-ed on a 0.6 ha site at Abeokuta, South-Western Nigeria. The thermal conductivity (k) was measured at depths of up to 0.06 m along four parallel profiles of 200 m long and at an average temperature of 25 C, using ...

  13. Spatial and temporal variability of lightings over Greece

    Science.gov (United States)

    Nastos, P. T.; Matsangouras, J. T.

    2010-09-01

    Lightings are the most powerful and spectacular natural phenomena in the lower atmosphere, being a major cause of storm related deaths. Cloud-to-ground lightning can kill and injure people by direct or indirect means. Lightning affects the many electrochemical systems in the body causing nerve damage, memory loss, personality change, and emotional problems. Besides, among the various nitrogen oxides sources, the contribution from lightning likely represents the largest uncertainty. In this study, the spatial and temporal variability of recorded lightings over Greece during the period from January 1, 2008 to December 31, 2009, were analyzed. The data for retrieving the location and time-of-occurrence of lightning were acquired from Hellenic National Meteorological Service (HNMS) archive dataset. An operational lighting detector network was established in 2007 by HNMS consisted of eight time-of-arrival sensors (TOA), spatially distributed across Greek territory. The spatial variability of lightings revealed their incidence within specific geographical sub-regions while the temporal variability concerning the seasonal, monthly and daily distributions resulted in better understanding of the time of lightings’ occurrence. All the analyses were carried out with respect to cloud to cloud, cloud to ground and ground to cloud lightings, within the examined time period.

  14. Uncertainty in Random Forests: What does it mean in a spatial context?

    Science.gov (United States)

    Klump, Jens; Fouedjio, Francky

    2017-04-01

    Geochemical surveys are an important part of exploration for mineral resources and in environmental studies. The samples and chemical analyses are often laborious and difficult to obtain and therefore come at a high cost. As a consequence, these surveys are characterised by datasets with large numbers of variables but relatively few data points when compared to conventional big data problems. With more remote sensing platforms and sensor networks being deployed, large volumes of auxiliary data of the surveyed areas are becoming available. The use of these auxiliary data has the potential to improve the prediction of chemical element concentrations over the whole study area. Kriging is a well established geostatistical method for the prediction of spatial data but requires significant pre-processing and makes some basic assumptions about the underlying distribution of the data. Some machine learning algorithms, on the other hand, may require less data pre-processing and are non-parametric. In this study we used a dataset provided by Kirkwood et al. [1] to explore the potential use of Random Forest in geochemical mapping. We chose Random Forest because it is a well understood machine learning method and has the advantage that it provides us with a measure of uncertainty. By comparing Random Forest to Kriging we found that both methods produced comparable maps of estimated values for our variables of interest. Kriging outperformed Random Forest for variables of interest with relatively strong spatial correlation. The measure of uncertainty provided by Random Forest seems to be quite different to the measure of uncertainty provided by Kriging. In particular, the lack of spatial context can give misleading results in areas without ground truth data. In conclusion, our preliminary results show that the model driven approach in geostatistics gives us more reliable estimates for our target variables than Random Forest for variables with relatively strong spatial

  15. Estimation of the Scale of Fluctuation for Spatial Variables of RC Structures

    Directory of Open Access Journals (Sweden)

    Hilyati S.

    2017-01-01

    Full Text Available Dimensional and structural properties of RC structures are nonhomogenous due to the quality of workmanship, environmental and material variability. One of the required statistical information for spatial variability analysis of RC structures includes the scale of fluctuation, θ. This paper discusses the estimation of θ for two spatial variables; concrete compressive strength and concrete cover. Methods used to estimate the θ are the Curve fitting method and the Kriging Method. Kriging is an optimal interpolation method which uses the concept of randomness that allows the uncertainty of the predicted values to be calculated. Data measurements for concrete compressive strength and concrete cover were obtained from Peterson (1964 and Public Work Department of Malaysia respectively. The most reliable value for θ of fcu was determined and the value obtained for θ of c was found unreliable due to the insufficient of data points from the available data.

  16. Reduction of the Random Variables of the Turbulent Wind Field

    DEFF Research Database (Denmark)

    Sichani, Mahdi Teimouri; Nielsen, Søren R.K.

    2012-01-01

    Applicability of the Probability Density Evolution Method (PDEM) for realizing evolution of the probability density for the wind turbines has rather strict bounds on the basic number of the random variables involved in the model. The efficiency of most of the Advanced Monte Carlo (AMC) methods, i.......e. Importance Sampling (IS) or Subset Simulation (SS), will be deteriorated on problems with many random variables. The problem with PDEM is that a multidimensional integral has to be carried out over the space defined by the random variables of the system. The numerical procedure requires discretization...... of the integral domain; this becomes increasingly difficult as the dimensions of the integral domain increase. On the other hand efficiency of the AMC methods is closely dependent on the design points of the problem. Presence of many random variables may increase the number of the design points, hence affects...

  17. Exponential Inequalities for Positively Associated Random Variables and Applications

    Directory of Open Access Journals (Sweden)

    Yang Shanchao

    2008-01-01

    Full Text Available Abstract We establish some exponential inequalities for positively associated random variables without the boundedness assumption. These inequalities improve the corresponding results obtained by Oliveira (2005. By one of the inequalities, we obtain the convergence rate for the case of geometrically decreasing covariances, which closes to the optimal achievable convergence rate for independent random variables under the Hartman-Wintner law of the iterated logarithm and improves the convergence rate derived by Oliveira (2005 for the above case.

  18. Separation metrics for real-valued random variables

    Directory of Open Access Journals (Sweden)

    Michael D. Taylor

    1984-01-01

    Full Text Available If W is a fixed, real-valued random variable, then there are simple and easily satisfied conditions under which the function dW, where dW(X,Y= the probability that W “separates” the real-valued random variables X and Y, turns out to be a metric. The observation was suggested by work done in [1].

  19. Spatial and temporal variability in urban fine particulate matter concentrations.

    Science.gov (United States)

    Levy, Jonathan I; Hanna, Steven R

    2011-01-01

    Identification of hot spots for urban fine particulate matter (PM(2.5)) concentrations is complicated by the significant contributions from regional atmospheric transport and the dependence of spatial and temporal variability on averaging time. We focus on PM(2.5) patterns in New York City, which includes significant local sources, street canyons, and upwind contributions to concentrations. A literature synthesis demonstrates that long-term (e.g., one-year) average PM(2.5) concentrations at a small number of widely-distributed monitoring sites would not show substantial variability, whereas short-term (e.g., 1-h) average measurements with high spatial density would show significant variability. Statistical analyses of ambient monitoring data as a function of wind speed and direction reinforce the significance of regional transport but show evidence of local contributions. We conclude that current monitor siting may not adequately capture PM(2.5) variability in an urban area, especially in a mega-city, reinforcing the necessity of dispersion modeling and methods for analyzing high-resolution monitoring observations. Copyright © 2010 Elsevier Ltd. All rights reserved.

  20. Randomly weighted sums of subexponential random variables with application to ruin theory

    NARCIS (Netherlands)

    Tang, Q.; Tsitsiashvili, G.

    2003-01-01

    Let {X k , 1 k n} be n independent and real-valued random variables with common subexponential distribution function, and let {k, 1 k n} be other n random variables independent of {X k , 1 k n} and satisfying a k b for some 0 < a b < for all 1 k n. This paper proves that the asymptotic relations P

  1. Chapman Conference on Spatial Variability in Hydrologic Modeling

    Science.gov (United States)

    Woolhiser, D. A.; Morel-Seytoux, H. J.

    The AGU Chapman Conference on Spatial Variability in Hydrologic Modeling was held July 21-23, 1981, at the Colorado State University Pingree Park Campus, located in the mountains some 88.5 km (55 miles) west of Fort Collins, Colorado. The conference was attended by experimentalists and theoreticians from a wide range of disciplines, including geology, hydrology, civil engineering, watershed science, chemical engineering, geography, statistics, mathematics, meteorology, and soil science. The attendees included researchers at various levels of research experience, including a large contingent of graduate students and many senior scientists.The conference goal was to review progress and discuss research approaches to the spatial variability of catchment surface and subsurface properties in a distributed modeling context. Mathematical models of water movement dynamics within a catchment consist of linked partial differential equations that describe free surface flow and unsaturated and saturated flow in porous media. Such models are utilized extensively in attempts to understand and predict the environmental consequences of human activities such as agricultural land management, waste disposal, urbanization, etc. We are concerned with the spatial structure of the parameters in such models, the precipitation input, and the geometric complexity of the system boundaries. The emphasis of this conference was on surface and subsurface hydrological process and their interactions.

  2. Accounting for Rainfall Spatial Variability in Prediction of Flash Floods

    Science.gov (United States)

    Saharia, M.; Kirstetter, P. E.; Gourley, J. J.; Hong, Y.; Vergara, H. J.

    2016-12-01

    Flash floods are a particularly damaging natural hazard worldwide in terms of both fatalities and property damage. In the United States, the lack of a comprehensive database that catalogues information related to flash flood timing, location, causative rainfall, and basin geomorphology has hindered broad characterization studies. First a representative and long archive of more than 20,000 flooding events during 2002-2011 is used to analyze the spatial and temporal variability of flash floods. We also derive large number of spatially distributed geomorphological and climatological parameters such as basin area, mean annual precipitation, basin slope etc. to identify static basin characteristics that influence flood response. For the same period, the National Severe Storms Laboratory (NSSL) has produced a decadal archive of Multi-Radar/Multi-Sensor (MRMS) radar-only precipitation rates at 1-km spatial resolution with 5-min temporal resolution. This provides an unprecedented opportunity to analyze the impact of event-level precipitation variability on flooding using a big data approach. To analyze the impact of sub-basin scale rainfall spatial variability on flooding, certain indices such as the first and second scaled moment of rainfall, horizontal gap, vertical gap etc. are computed from the MRMS dataset. Finally, flooding characteristics such as rise time, lag time, and peak discharge are linked to derived geomorphologic, climatologic, and rainfall indices to identify basin characteristics that drive flash floods. Next the model is used to predict flash flooding characteristics all over the continental U.S., specifically over regions poorly covered by hydrological observations. So far studies involving rainfall variability indices have only been performed on a case study basis, and a large scale approach is expected to provide a deeper insight into how sub-basin scale precipitation variability affects flooding. Finally, these findings are validated using the

  3. Effects of rainfall spatial variability and intermittency on shallow landslide triggering patterns at a catchment scale

    National Research Council Canada - National Science Library

    von Ruette, J; Lehmann, P; Or, D

    2014-01-01

    ...., hourly radar data at spatial resolution of a few kilometers). To quantify potential effects of rainfall variability on failure dynamics, spatial patterns, landslide numbers and volumes, we employed...

  4. Spatial and temporal variability of precipitation and drought in Portugal

    Directory of Open Access Journals (Sweden)

    D. S. Martins

    2012-05-01

    Full Text Available The spatial variability of precipitation and drought are investigated for Portugal using monthly precipitation from 74 stations and minimum and maximum temperature from 27 stations, covering the common period of 1941–2006. Seasonal precipitation and the corresponding percentages in the year, as well as the precipitation concentration index (PCI, was computed for all 74 stations and then used as an input matrix for an R-mode principal component analysis to identify the precipitation patterns. The standardized precipitation index at 3 and 12 month time scales were computed for all stations, whereas the Palmer Drought Severity Index (PDSI and the modified PDSI for Mediterranean conditions (MedPDSI were computed for the stations with temperature data. The spatial patterns of drought over Portugal were identified by applying the S-mode principal component analysis coupled with varimax rotation to the drought indices matrices. The result revealed two distinct sub-regions in the country relative to both precipitation regimes and drought variability. The analysis of time variability of the PC scores of all drought indices allowed verifying that there is no linear trend indicating drought aggravation or decrease. In addition, the analysis shows that results for SPI-3, SPI-12, PDSI and MedPDSI are coherent among them.

  5. Rainfall interception and spatial variability of throughfall in spruce stand

    Directory of Open Access Journals (Sweden)

    Dohnal Michal

    2014-12-01

    Full Text Available The interception was recognized as an important part of the catchment water balance in temperate climate. The mountainous forest ecosystem at experimental headwater catchment Liz has been subject of long-term monitoring. Unique dataset in terms of time resolution serves to determine canopy storage capacity and free throughfall. Spatial variability of throughfall was studied using one weighing and five tipping bucket rain gauges. The basic characteristics of forest affecting interception process were determined for the Norway spruce stand at the experimental area - the leaf area index was 5.66 - 6.00 m2 m-2, the basal area was 55.7 m2 ha-1, and the crown closure above individual rain gauges was between 19 and 95%. The total interception loss in both growing seasons analyzed was 34.5%. The mean value of the interception capacity determined was about 2 mm. Throughfall exhibited high variability from place to place and it was strongly affected by character of rainfall. On the other hand, spatial pattern of throughfall in average showed low variability.

  6. Spatial-mode conversion using random diffuser and spatial light modulator for reduction of modal crosstalk

    Science.gov (United States)

    Ishii, Koki; Okamoto, Atsushi; Tsuritani, Takehiro; Wakayama, Yuta; Goto, Yuta; Tomita, Akihisa

    2016-02-01

    The mode-division multiplexing (MDM) technique enables the transmission of multiple signals within a multi-mode fiber (MMF) or a few-mode fiber (FMF). To construct an efficient and flexible MDM network in the same way as a wavelength-division multiplexing network, a mode conversion method with low modal crosstalk is required for switching between arbitrary spatial modes. However, in general, modal crosstalk is strongly dependent on the intensity pattern before mode conversion, and it is increased particularly for higher order modes. In order to reduce modal crosstalk, we propose a method using a random diffuser and a spatial light modulator (SLM). In the proposed method, firstly, the input spatial mode is dispersed uniformly by the random diffuser. Subsequently, the diffused phase distribution is canceled and converted into the desired spatial mode by the SLM, which displays phase difference between desired and diffused modes. Consequently, every spatial mode can be evenly converted into a desired mode. Here, we numerically simulate and confirm that the proposed method can reduce modal crosstalk compared to the conversion method without the random diffuser.

  7. Spatial variability of extreme rainfall at radar subpixel scale

    Science.gov (United States)

    Peleg, Nadav; Marra, Francesco; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

    2018-01-01

    Extreme rainfall is quantified in engineering practice using Intensity-Duration-Frequency curves (IDF) that are traditionally derived from rain-gauges and more recently also from remote sensing instruments, such as weather radars. These instruments measure rainfall at different spatial scales: rain-gauge samples rainfall at the point scale while weather radar averages precipitation on a relatively large area, generally around 1 km2. As such, a radar derived IDF curve is representative of the mean areal rainfall over a given radar pixel and neglects the within-pixel rainfall variability. In this study, we quantify subpixel variability of extreme rainfall by using a novel space-time rainfall generator (STREAP model) that downscales in space the rainfall within a given radar pixel. The study was conducted using a unique radar data record (23 years) and a very dense rain-gauge network in the Eastern Mediterranean area (northern Israel). Radar-IDF curves, together with an ensemble of point-based IDF curves representing the radar subpixel extreme rainfall variability, were developed fitting Generalized Extreme Value (GEV) distributions to annual rainfall maxima. It was found that the mean areal extreme rainfall derived from the radar underestimate most of the extreme values computed for point locations within the radar pixel (on average, ∼70%). The subpixel variability of rainfall extreme was found to increase with longer return periods and shorter durations (e.g. from a maximum variability of 10% for a return period of 2 years and a duration of 4 h to 30% for 50 years return period and 20 min duration). For the longer return periods, a considerable enhancement of extreme rainfall variability was found when stochastic (natural) climate variability was taken into account. Bounding the range of the subpixel extreme rainfall derived from radar-IDF can be of major importance for different applications that require very local estimates of rainfall extremes.

  8. Spatially random models, estimation theory, and robot arm dynamics

    Science.gov (United States)

    Rodriguez, G.

    1987-01-01

    Spatially random models provide an alternative to the more traditional deterministic models used to describe robot arm dynamics. These alternative models can be used to establish a relationship between the methodologies of estimation theory and robot dynamics. A new class of algorithms for many of the fundamental robotics problems of inverse and forward dynamics, inverse kinematics, etc. can be developed that use computations typical in estimation theory. The algorithms make extensive use of the difference equations of Kalman filtering and Bryson-Frazier smoothing to conduct spatial recursions. The spatially random models are very easy to describe and are based on the assumption that all of the inertial (D'Alembert) forces in the system are represented by a spatially distributed white-noise model. The models can also be used to generate numerically the composite multibody system inertia matrix. This is done without resorting to the more common methods of deterministic modeling involving Lagrangian dynamics, Newton-Euler equations, etc. These methods make substantial use of human knowledge in derivation and minipulation of equations of motion for complex mechanical systems.

  9. Cascading failures in spatially-embedded random networks.

    Science.gov (United States)

    Asztalos, Andrea; Sreenivasan, Sameet; Szymanski, Boleslaw K; Korniss, Gyorgy

    2014-01-01

    Cascading failures constitute an important vulnerability of interconnected systems. Here we focus on the study of such failures on networks in which the connectivity of nodes is constrained by geographical distance. Specifically, we use random geometric graphs as representative examples of such spatial networks, and study the properties of cascading failures on them in the presence of distributed flow. The key finding of this study is that the process of cascading failures is non-self-averaging on spatial networks, and thus, aggregate inferences made from analyzing an ensemble of such networks lead to incorrect conclusions when applied to a single network, no matter how large the network is. We demonstrate that this lack of self-averaging disappears with the introduction of a small fraction of long-range links into the network. We simulate the well studied preemptive node removal strategy for cascade mitigation and show that it is largely ineffective in the case of spatial networks. We introduce an altruistic strategy designed to limit the loss of network nodes in the event of a cascade triggering failure and show that it performs better than the preemptive strategy. Finally, we consider a real-world spatial network viz. a European power transmission network and validate that our findings from the study of random geometric graphs are also borne out by simulations of cascading failures on the empirical network.

  10. Variable impact of chronic stress on spatial learning and memory in BXD mice.

    Science.gov (United States)

    Shea, Chloe J A; Carhuatanta, Kimberly A K; Wagner, Jessica; Bechmann, Naomi; Moore, Raquel; Herman, James P; Jankord, Ryan

    2015-10-15

    The effects of chronic stress on learning are highly variable across individuals. This variability stems from gene-environment interactions. However, the mechanisms by which stress affects genetic predictors of learning are unclear. Thus, we aim to determine whether the genetic pathways that predict spatial memory performance are altered by previous exposure to chronic stress. Sixty-two BXD recombinant inbred strains of mice, as well as parent strains C57BL/6J and DBA/2J, were randomly assigned as behavioral control or to a chronic variable stress paradigm and then underwent behavioral testing to assess spatial memory and learning performance using the Morris water maze. Quantitative trait loci (QTL) mapping was completed for average escape latency times for both control and stress animals. Loci on chromosomes 5 and 10 were found in both control and stress environmental populations; eight additional loci were found to be unique to either the control or stress environment. In sum, results indicate that certain genetic loci predict spatial memory performance regardless of prior stress exposure, while exposure to stress also reveals unique genetic predictors of training during the memory task. Thus, we find that genetic predictors contributing to spatial learning and memory are susceptible to the presence of chronic stress. Published by Elsevier Inc.

  11. Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes

    National Research Council Canada - National Science Library

    Ghosh, Subimal; Vittal, H; Sharma, Tarul; Karmakar, Subhankar; Kasiviswanathan, K S; Dhanesh, Y; Sudheer, K P; Gunthe, S S

    2016-01-01

    .... Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability...

  12. Spatial impacts of urban structures on micrometeorological variables

    Science.gov (United States)

    Koelbing, Merle; Schuetz, Tobias; Weiler, Markus

    2016-04-01

    The heterogeneity of urban surfaces including buildings and the urban vegetation causes high variability of micrometeorological variables on small spatial scales which makes it hard to observe or even predict climate conditions and in particular evapotranspiration with high resolution on the scale of entire cities. Regarding future climate changes and their impacts on urban climate and hydrology the predictability of these small scale variations becomes more and more relevant i.e. for city planners to improve the development of appropriate mitigation strategies. Therefore, new transfer functions for meteorological variables are needed, which consider the structural variability in urban areas and its impacts on the energy balance (shading effects, ventilation, lateral longwave energy fluxes). We approach this goal by testing a mobile meteorological station (the station is mounted on a bicycle trailer and transported by an E-Bike) as a means to derive empirical spatial transfer functions for specific urban structures. We observe air temperature and relative air humidity at 2 different heights, wind direction and speed, incoming and outgoing shortwave radiation as well as infrared temperature from above and below and the four directions. First measurements have been performed in December 2015 at 22 locations in four clusters, which represent manifold different characteristics of urban areas within the city of Freiburg. Every location has been monitored two to six times. Overall, nearly 200 measurements of each variable have been taken. Each measurement takes five minutes. Values are logged every 15 seconds. These measurements were analyzed with regard to a climate station mounted on a rooftop in the proximity of all clusters. Results show a systematic pattern in the differences between the values taken with the fixed and those taken with the mobile climate station, depending on the measurement locations. For example, lower air temperature and higher relative air

  13. Spatial Random Sampling: A Structure-Preserving Data Sketching Tool

    Science.gov (United States)

    Rahmani, Mostafa; Atia, George K.

    2017-09-01

    Random column sampling is not guaranteed to yield data sketches that preserve the underlying structures of the data and may not sample sufficiently from less-populated data clusters. Also, adaptive sampling can often provide accurate low rank approximations, yet may fall short of producing descriptive data sketches, especially when the cluster centers are linearly dependent. Motivated by that, this paper introduces a novel randomized column sampling tool dubbed Spatial Random Sampling (SRS), in which data points are sampled based on their proximity to randomly sampled points on the unit sphere. The most compelling feature of SRS is that the corresponding probability of sampling from a given data cluster is proportional to the surface area the cluster occupies on the unit sphere, independently from the size of the cluster population. Although it is fully randomized, SRS is shown to provide descriptive and balanced data representations. The proposed idea addresses a pressing need in data science and holds potential to inspire many novel approaches for analysis of big data.

  14. Assessment of spatial rainfall variability in Lake Victoria Basin

    Science.gov (United States)

    Kizza, M.; Westerberg, I.; Rodhe, A.; Ntale, H. K.

    2011-12-01

    A gridded monthly rainfall dataset having a spatial resolution of 2 km and covering the period 1960-2004 was derived for the Lake Victoria basin. Such a dataset is useful for hydrological modelling aimed at resource utilisation and for estimation of catchment inflow to Lake Victoria. The lake and its basin support more than 30 million people and also contribute substantially to the River Nile flow. The major challenge in analysing the lake water balance is the estimation of the rainfall over the lake which is complicated by the varying quality and spatial coverage of rain-gauge data in the basin. In this study we addressed these problems by using satellite-derived precipitation data from two products and rain-gauge data for 362 stations around the basin to derive a monthly precipitation dataset for the entire basin, including the lake. First, the rain-gauge data were quality controlled; resulting in a rejection of 13% of the stations while 12% needed corrective actions. These results emphasise the importance of a systematic quality control of rain-guage data in this region. Thereafter we filled short gaps in the daily data series which resulted in 9,429 additional months of data. Two interpolation methods were then assessed for spatial interpolation and the universal kriging method performed slightly better than the inverse distance weighting method. The rainfall patterns in the interpolated dataset were shown to be consistent with the spatial and temporal patterns expected at the large scale as a result of the climate variability in the basin. The key problem of how to account for the enhancement of rainfall over the lake surface because of the lake-land thermal contrasts was addressed by estimating a relationship between rain-gauge and satellite data. Two satellite rainfall products, TRMM 3B43 and PERSIANN were compared to the interpolated monthly rain-gauge data for the land part of the basin. The bias in the TRMM 3B43 rainfall estimates was higher than the bias

  15. Spatial variability of Chinook salmon spawning distribution and habitat preferences

    Science.gov (United States)

    Cram, Jeremy M.; Torgersen, Christian; Klett, Ryan S.; Pess, George R.; May, Darran; Pearsons, Todd N.; Dittman, Andrew H.

    2017-01-01

    We investigated physical habitat conditions associated with the spawning sites of Chinook Salmon Oncorhynchus tshawytscha and the interannual consistency of spawning distribution across multiple spatial scales using a combination of spatially continuous and discrete sampling methods. We conducted a census of aquatic habitat in 76 km of the upper main-stem Yakima River in Washington and evaluated spawning site distribution using redd survey data from 2004 to 2008. Interannual reoccupation of spawning areas was high, ranging from an average Pearson’s correlation of 0.62 to 0.98 in channel subunits and 10-km reaches, respectively. Annual variance in the interannual correlation of spawning distribution was highest in channel units and subunits, but it was low at reach scales. In 13 of 15 models developed for individual years (2004–2008) and reach lengths (800 m, 3 km, 6 km), stream power and depth were the primary predictors of redd abundance. Multiple channels and overhead cover were patchy but were important secondary and tertiary predictors of reach-scale spawning site selection. Within channel units and subunits, pool tails and thermal variability, which may be associated with hyporheic exchange, were important predictors of spawning. We identified spawning habitat preferences within reaches and channel units that are relevant for salmonid habitat restoration planning. We also identified a threshold (i.e., 2-km reaches) beyond which interannual spawning distribution was markedly consistent, which may be informative for prioritizing habitat restoration or conservation. Management actions may be improved through enhanced understanding of spawning habitat preferences and the consistency with which Chinook Salmon reoccupy spawning areas at different spatial scales.

  16. Controls of Soil Spatial Variability in a Dry Tropical Forest.

    Directory of Open Access Journals (Sweden)

    Sandeep Pulla

    Full Text Available We examined the roles of lithology, topography, vegetation and fire in generating local-scale (<1 km2 soil spatial variability in a seasonally dry tropical forest (SDTF in southern India. For this, we mapped soil (available nutrients, Al, total C, pH, moisture and texture in the top 10 cm, rock outcrops, topography, all native woody plants ≥1 cm diameter at breast height (DBH, and spatial variation in fire frequency (times burnt during the 17 years preceding soil sampling in a permanent 50-ha plot. Unlike classic catenas, lower elevation soils had lesser moisture, plant-available Ca, Cu, Mn, Mg, Zn, B, clay and total C. The distribution of plant-available Ca, Cu, Mn and Mg appeared to largely be determined by the whole-rock chemical composition differences between amphibolites and hornblende-biotite gneisses. Amphibolites were associated with summit positions, while gneisses dominated lower elevations, an observation that concurs with other studies in the region which suggest that hillslope-scale topography has been shaped by differential weathering of lithologies. Neither NO3(--N nor NH4(+-N was explained by the basal area of trees belonging to Fabaceae, a family associated with N-fixing species, and no long-term effects of fire on soil parameters were detected. Local-scale lithological variation is an important first-order control over soil variability at the hillslope scale in this SDTF, by both direct influence on nutrient stocks and indirect influence via control of local relief.

  17. Study on genetic variability of Cassidula aurisfelis (snail) by random ...

    African Journals Online (AJOL)

    The genetic variability among individuals of Cassidula aurisfelis from Setiu Wetland, Terengganu Darul Iman was examined by using the random amplified polymorphic DNA (RAPD) technique. Ten oligonucleotide primers were screened and three primers were selected (OPA 02, OPA 04 and OPA 10) to amplify DNA from ...

  18. Variability in response to albuminuria lowering drugs : true or random?

    NARCIS (Netherlands)

    Petrykiv, Sergei I.; de Zeeuw, Dick; Persson, Frederik; Rossing, Peter; Gansevoort, Ron T.; Laverman, Gozewijn D.; Heerspink, Hiddo J. L.

    AIMS Albuminuria-lowering drugs have shown different effect size in different individuals. Since urine albumin levels are known to vary considerably from day- to-day, we questioned whether the between-individual variability in albuminuria response after therapy initiation reflects a random

  19. How a dependent's variable non-randomness affects taper equation ...

    African Journals Online (AJOL)

    Regression results, for the two methods, were compared using the confidence interval estimates for the regression coefficients, the multicollinearity tests and Fit Index (FI) values as criteria. The comparison of results showed that randomness of the dependent variable (second method) did not improve the estimates, in any of ...

  20. Study on genetic variability of Cassidula aurisfelis (snail) by random ...

    African Journals Online (AJOL)

    PRECIOUS

    2009-11-16

    Nov 16, 2009 ... genetic variability is Random Amplified Polymorphic. DNAs (RAPD) (Williams et al., 1990). The technique requires no prior knowledge of the genome and it needs ... quantity of DNA was measured by obtaining the absorbance read- ... 1994) and Numerical taxonomy and Multivariate Analysis System.

  1. An infinite-dimensional weak KAM theory via random variables

    KAUST Repository

    Gomes, Diogo A.

    2016-08-31

    We develop several aspects of the infinite-dimensional Weak KAM theory using a random variables\\' approach. We prove that the infinite-dimensional cell problem admits a viscosity solution that is a fixed point of the Lax-Oleinik semigroup. Furthermore, we show the existence of invariant minimizing measures and calibrated curves defined on R.

  2. Limit theorems for multi-indexed sums of random variables

    CERN Document Server

    Klesov, Oleg

    2014-01-01

    Presenting the first unified treatment of limit theorems for multiple sums of independent random variables, this volume fills an important gap in the field. Several new results are introduced, even in the classical setting, as well as some new approaches that are simpler than those already established in the literature. In particular, new proofs of the strong law of large numbers and the Hajek-Renyi inequality are detailed. Applications of the described theory include Gibbs fields, spin glasses, polymer models, image analysis and random shapes. Limit theorems form the backbone of probability theory and statistical theory alike. The theory of multiple sums of random variables is a direct generalization of the classical study of limit theorems, whose importance and wide application in science is unquestionable. However, to date, the subject of multiple sums has only been treated in journals. The results described in this book will be of interest to advanced undergraduates, graduate students and researchers who ...

  3. A review of instrumental variable estimators for Mendelian randomization.

    Science.gov (United States)

    Burgess, Stephen; Small, Dylan S; Thompson, Simon G

    2017-10-01

    Instrumental variable analysis is an approach for obtaining causal inferences on the effect of an exposure (risk factor) on an outcome from observational data. It has gained in popularity over the past decade with the use of genetic variants as instrumental variables, known as Mendelian randomization. An instrumental variable is associated with the exposure, but not associated with any confounder of the exposure-outcome association, nor is there any causal pathway from the instrumental variable to the outcome other than via the exposure. Under the assumption that a single instrumental variable or a set of instrumental variables for the exposure is available, the causal effect of the exposure on the outcome can be estimated. There are several methods available for instrumental variable estimation; we consider the ratio method, two-stage methods, likelihood-based methods, and semi-parametric methods. Techniques for obtaining statistical inferences and confidence intervals are presented. The statistical properties of estimates from these methods are compared, and practical advice is given about choosing a suitable analysis method. In particular, bias and coverage properties of estimators are considered, especially with weak instruments. Settings particularly relevant to Mendelian randomization are prioritized in the paper, notably the scenario of a continuous exposure and a continuous or binary outcome.

  4. A random spatial sampling method in a rural developing nation.

    Science.gov (United States)

    Kondo, Michelle C; Bream, Kent D W; Barg, Frances K; Branas, Charles C

    2014-04-10

    Nonrandom sampling of populations in developing nations has limitations and can inaccurately estimate health phenomena, especially among hard-to-reach populations such as rural residents. However, random sampling of rural populations in developing nations can be challenged by incomplete enumeration of the base population. We describe a stratified random sampling method using geographical information system (GIS) software and global positioning system (GPS) technology for application in a health survey in a rural region of Guatemala, as well as a qualitative study of the enumeration process. This method offers an alternative sampling technique that could reduce opportunities for bias in household selection compared to cluster methods. However, its use is subject to issues surrounding survey preparation, technological limitations and in-the-field household selection. Application of this method in remote areas will raise challenges surrounding the boundary delineation process, use and translation of satellite imagery between GIS and GPS, and household selection at each survey point in varying field conditions. This method favors household selection in denser urban areas and in new residential developments. Random spatial sampling methodology can be used to survey a random sample of population in a remote region of a developing nation. Although this method should be further validated and compared with more established methods to determine its utility in social survey applications, it shows promise for use in developing nations with resource-challenged environments where detailed geographic and human census data are less available.

  5. Temporal and Spatial Variability along the Deep Western Boundary Current

    Science.gov (United States)

    Schmidtko, Sunke; Fischer, Jürgen

    2017-04-01

    The North Atlantic Deep Western Boundary Current (DWBC) connects the polar and subpolar regions, where the ocean is ventilated to greater depth, with the tropical oceans and beyond. It is part of the global ocean circulation as the deep branch of the Atlantic meridional overturning circulation (AMOC). It has a core depth between 1500-4500m with water mass properties varying by origin and decade. We analyze all publically available CTD data from Porcupine Abyssal Plain along Denmark Straight, Labrador Sea, Cape Cod, Cape Hatteras and Bahamas to the equator. The spatial and temporal development is analyzed for the past five decades. Waters originating from the overflow regions between Greenland and Scotland and from the Labrador Sea merge along the pathway but show distinct temporal variability and trends. We distinguish between local and large-scale variability and relate our results with the atmospheric forcing of the North Atlantic. This gives insight into new key aspects to be validated with state of the art ocean circulation models.

  6. Coastal upwelling south of Madagascar: Temporal and spatial variability

    Science.gov (United States)

    Ramanantsoa, Juliano D.; Krug, M.; Penven, P.; Rouault, M.; Gula, J.

    2018-02-01

    Madagascar's southern coastal marine zone is a region of high biological productivity which supports a wide range of marine ecosystems, including fisheries. This high biological productivity is attributed to coastal upwelling. This paper provides new insights on the structure, variability and drivers of the coastal upwelling south of Madagascar. Satellite remote sensing is used to characterize the spatial extent and strength of the coastal upwelling. A front detection algorithm is applied to thirteen years of Multi-scale Ultra-high Resolution (MUR) Sea Surface Temperatures (SST) and an upwelling index is calculated. The influence of winds and ocean currents as drivers of the upwelling is investigated using satellite, in-situ observations, and a numerical model. Results reveal the presence of two well-defined upwelling cells. The first cell (Core 1) is located in the southeastern corner of Madagascar, and the second cell (Core 2) is west of the southern tip of Madagascar. These two cores are characterized by different seasonal variability, different intensities, different upwelled water mass origins, and distinct forcing mechanisms. Core 1 is associated with a dynamical upwelling forced by the detachment of the East Madagascar Current (EMC), which is reinforced by upwelling favourable winds. Core 2 appears to be primarily forced by upwelling favourable winds, but is also influenced by a poleward eastern boundary flow coming from the Mozambique Channel. The intrusion of Mozambique Channel warm waters could result in an asynchronicity in seasonality between upwelling surface signature and upwelling favourables winds.

  7. Spatial and temporal variability of Mediterranean drought events

    Science.gov (United States)

    Trigo, R.; Sousa, P.; Nieto, R.; Gimeno, L.

    2009-04-01

    The original Palmer Drought Severity Index (PDSI) and a recent adaptation to European soil characteristics, the Self Calibrated PDSI (or scPDSI) proposed by Schrier et al (2005) were used. We have computed monthly, seasonal and annual trends between 1901 and 2000 but also for the first and second halves of the 20th century. Results were represented only when achieving a minimum level of statistical significance (either 5% or 10% using a Mann-Kendall test) and confirm that the majority of the western and central Mediterranean is getting drier in the last decades of the 20th century while Turkey is generally getting wetter (Trigo et al., 2006). The spatio-temporal variability of these indices was evaluated with an EOF analysis, in order to reduce the large dimensionality of the fields under analysis. Spatial representation of the first EOF patterns shows that EOF 1 covers the entire Mediterranean basin (16.4% of EV), while EOF2 is dominated by a W-E dipole (10% EV). The following EOF patterns present smaller scale features, and explain smaller amounts of variance. The EOF patterns have also facilitated the definition of four sub-regions with large socio-economic relevance: 1) Iberia, 2) Italian Peninsula, 3) Balkans and 4) Turkey. The inter-annual variability of the regional spatial droughts indices for each region was analyzed separately. We have also performed an evaluation of their eventual links with large-scale atmospheric circulation indices that affect the Mediterranean basin, namely the NAO, EA, and SCAND. Finally we have evaluated the main sources of moisture affecting two drought prone areas in the western (Iberia) and eastern (Balkans) Mediterranean. This analysis was performed by means of backward tracking the air masses that ultimately reach these two regions using the Lagrangian particle dispersion model FLEXPART (Stohl et al., 1998) and meteorological analysis data from the ECMWF to track atmospheric moisture. This was done for a five-year period (2000

  8. Fine scale spatial variability of microbial pesticide degradation in soil: scales, controlling factors, and implications

    Science.gov (United States)

    Dechesne, Arnaud; Badawi, Nora; Aamand, Jens; Smets, Barth F.

    2014-01-01

    Pesticide biodegradation is a soil microbial function of critical importance for modern agriculture and its environmental impact. While it was once assumed that this activity was homogeneously distributed at the field scale, mounting evidence indicates that this is rarely the case. Here, we critically examine the literature on spatial variability of pesticide biodegradation in agricultural soil. We discuss the motivations, methods, and main findings of the primary literature. We found significant diversity in the approaches used to describe and quantify spatial heterogeneity, which complicates inter-studies comparisons. However, it is clear that the presence and activity of pesticide degraders is often highly spatially variable with coefficients of variation often exceeding 50% and frequently displays non-random spatial patterns. A few controlling factors have tentatively been identified across pesticide classes: they include some soil characteristics (pH) and some agricultural management practices (pesticide application, tillage), while other potential controlling factors have more conflicting effects depending on the site or the pesticide. Evidence demonstrating the importance of spatial heterogeneity on the fate of pesticides in soil has been difficult to obtain but modeling and experimental systems that do not include soil's full complexity reveal that this heterogeneity must be considered to improve prediction of pesticide biodegradation rates or of leaching risks. Overall, studying the spatial heterogeneity of pesticide biodegradation is a relatively new field at the interface of agronomy, microbial ecology, and geosciences and a wealth of novel data is being collected from these different disciplinary perspectives. We make suggestions on possible avenues to take full advantage of these investigations for a better understanding and prediction of the fate of pesticides in soil. PMID:25538691

  9. Visibility graphs of random scalar fields and spatial data

    Science.gov (United States)

    Lacasa, Lucas; Iacovacci, Jacopo

    2017-07-01

    We extend the family of visibility algorithms to map scalar fields of arbitrary dimension into graphs, enabling the analysis of spatially extended data structures as networks. We introduce several possible extensions and provide analytical results on the topological properties of the graphs associated to different types of real-valued matrices, which can be understood as the high and low disorder limits of real-valued scalar fields. In particular, we find a closed expression for the degree distribution of these graphs associated to uncorrelated random fields of generic dimension. This result holds independently of the field's marginal distribution and it directly yields a statistical randomness test, applicable in any dimension. We showcase its usefulness by discriminating spatial snapshots of two-dimensional white noise from snapshots of a two-dimensional lattice of diffusively coupled chaotic maps, a system that generates high dimensional spatiotemporal chaos. The range of potential applications of this combinatorial framework includes image processing in engineering, the description of surface growth in material science, soft matter or medicine, and the characterization of potential energy surfaces in chemistry, disordered systems, and high energy physics. An illustration on the applicability of this method for the classification of the different stages involved in carcinogenesis is briefly discussed.

  10. Custom-tailored spatial mode sorting by controlled random scattering

    Science.gov (United States)

    Fickler, Robert; Ginoya, Manit; Boyd, Robert W.

    2017-04-01

    The need to increase data transfer rates constitutes a key challenge in modern information-driven societies. Taking advantage of the transverse spatial modes of light to encode more information is a promising avenue for both classical and quantum photonics. However, to ease access to the encoded information, it is essential to be able to sort spatial modes into different output channels. Here, we introduce a way to customize the sorting of arbitrary spatial light modes. Our method relies on the high degree of control over random scattering processes by preshaping of the phase structure of the incident light. We demonstrate experimentally that various sets of modes, irrespective of their specific modal structure, can be transformed to a broad range of output channel arrangements. Thus, our method enables full access to all of the information encoded in the transverse structure of the field; for example, azimuthal and radial modes. We also demonstrate that coherence is retained in this complex mode transformation, which opens up applications in quantum and classical information science.

  11. Instrumental variable analyses. Exploiting natural randomness to understand causal mechanisms.

    Science.gov (United States)

    Iwashyna, Theodore J; Kennedy, Edward H

    2013-06-01

    Instrumental variable analysis is a technique commonly used in the social sciences to provide evidence that a treatment causes an outcome, as contrasted with evidence that a treatment is merely associated with differences in an outcome. To extract such strong evidence from observational data, instrumental variable analysis exploits situations where some degree of randomness affects how patients are selected for a treatment. An instrumental variable is a characteristic of the world that leads some people to be more likely to get the specific treatment we want to study but does not otherwise change those patients' outcomes. This seminar explains, in nonmathematical language, the logic behind instrumental variable analyses, including several examples. It also provides three key questions that readers of instrumental variable analyses should ask to evaluate the quality of the evidence. (1) Does the instrumental variable lead to meaningful differences in the treatment being tested? (2) Other than through the specific treatment being tested, is there any other way the instrumental variable could influence the outcome? (3) Does anything cause patients to both receive the instrumental variable and receive the outcome?

  12. Do we need a spatially and temporally variable observation error?

    Science.gov (United States)

    Mladenova, I. E.; Bolten, J. D.; Crow, W. T.; de Jeu, R. A. M.; Cosh, M. H.; Walker, J. P.

    2016-12-01

    It is well known that the accuracy of hydrologic models is highly dependent on the quality of the precipitation data used to force the model. Data assimilation (DA) enables us to address this limitation through the integration of independent observations derived from satellite-based systems into the model. In a way, DA can be regarded as a merging technique where the model predictions and the satellite observations are combined through a set of error parameters that inform the system how much weight should be put on the observations. For example, a small observation error would put less weight to the model forecast and make the analysis to draw closer to the observation. There are a number of ways to model the observation error. The simplest approach is to assume a global average, which results into a temporally and spatially stable value. However, the accuracy of passive-based soil moisture (SM) retrievals is variable in space and time and strongly depends on the density of the overlying canopy layer. Thus, conceptually, a more appropriate approach is to model the observation error as a function of some vegetation-related parameter. Here we explore a new methodology modeling the observation error as a function of vegetation optical depth data (VOD), which provides information on not only the spatial, but also the seasonal and possibly the inter-annual variability of the observation error. Thus, our objectives are (1) to evaluate the potential to use VOD to model the observation error and (2) to examine the benefit of dynamically adjusting the error in both space and time scales consistent with the SM observations. The analysis was done using Land Parameter Retrieval Model-based SM and VOD retrievals obtained from the Advanced Microwave Scanning Radiometer 2 (AMSR2) mission (C-/X-band) and the Soil Moisture Ocean Salinity (SMOS) instrument (L-band; theoretically it should offer higher sensitivity to soil moisture as compared to C-/X-band). Thus, an additional

  13. Generation of correlated finite alphabet waveforms using gaussian random variables

    KAUST Repository

    Ahmed, Sajid

    2016-01-13

    Various examples of methods and systems are provided for generation of correlated finite alphabet waveforms using Gaussian random variables in, e.g., radar and communication applications. In one example, a method includes mapping an input signal comprising Gaussian random variables (RVs) onto finite-alphabet non-constant-envelope (FANCE) symbols using a predetermined mapping function, and transmitting FANCE waveforms through a uniform linear array of antenna elements to obtain a corresponding beampattern. The FANCE waveforms can be based upon the mapping of the Gaussian RVs onto the FANCE symbols. In another example, a system includes a memory unit that can store a plurality of digital bit streams corresponding to FANCE symbols and a front end unit that can transmit FANCE waveforms through a uniform linear array of antenna elements to obtain a corresponding beampattern. The system can include a processing unit that can encode the input signal and/or determine the mapping function.

  14. Physically-based parameterization of spatially variable soil and vegetation using satellite multispectral data

    Science.gov (United States)

    Jasinski, Michael F.; Eagleson, Peter S.

    1989-01-01

    A stochastic-geometric landsurface reflectance model is formulated and tested for the parameterization of spatially variable vegetation and soil at subpixel scales using satellite multispectral images without ground truth. Landscapes are conceptualized as 3-D Lambertian reflecting surfaces consisting of plant canopies, represented by solid geometric figures, superposed on a flat soil background. A computer simulation program is developed to investigate image characteristics at various spatial aggregations representative of satellite observational scales, or pixels. The evolution of the shape and structure of the red-infrared space, or scattergram, of typical semivegetated scenes is investigated by sequentially introducing model variables into the simulation. The analytical moments of the total pixel reflectance, including the mean, variance, spatial covariance, and cross-spectral covariance, are derived in terms of the moments of the individual fractional cover and reflectance components. The moments are applied to the solution of the inverse problem: The estimation of subpixel landscape properties on a pixel-by-pixel basis, given only one multispectral image and limited assumptions on the structure of the landscape. The landsurface reflectance model and inversion technique are tested using actual aerial radiometric data collected over regularly spaced pecan trees, and using both aerial and LANDSAT Thematic Mapper data obtained over discontinuous, randomly spaced conifer canopies in a natural forested watershed. Different amounts of solar backscattered diffuse radiation are assumed and the sensitivity of the estimated landsurface parameters to those amounts is examined.

  15. Tools for Optimizing Management of a Spatially Variable Organic Field

    Directory of Open Access Journals (Sweden)

    Thomas Panagopoulos

    2015-03-01

    Full Text Available Geostatistical tools were used to estimate spatial relations between wheat yield and soil parameters under organic farming field conditions. Thematic maps of each factor were created as raster images in R software using kriging. The Geographic Resources Analysis Support System (GRASS calculated the principal component analysis raster images for soil parameters and yield. The correlation between the raster arising from the PC1 of soil and yield parameters showed high linear correlation (r = 0.75 and explained 48.50% of the data variance. The data show that durum wheat yield is strongly affected by soil parameter variability, and thus, the average production can be substantially lower than its potential. Soil water content was the limiting factor to grain yield and not nitrate as in other similar studies. The use of precision agriculture tools helped reduce the level of complexity between the measured parameters by the grouping of several parameters and demonstrating that precision agriculture tools can be applied in small organic fields, reducing costs and increasing wheat yield. Consequently, site-specific applications could be expected to improve the yield without increasing excessively the cost for farmers and enhance environmental and economic benefits.

  16. Higher moments of Banach space valued random variables

    CERN Document Server

    Janson, Svante

    2015-01-01

    The authors define the k:th moment of a Banach space valued random variable as the expectation of its k:th tensor power; thus the moment (if it exists) is an element of a tensor power of the original Banach space. The authors study both the projective and injective tensor products, and their relation. Moreover, in order to be general and flexible, we study three different types of expectations: Bochner integrals, Pettis integrals and Dunford integrals.

  17. Entropy power inequality for a family of discrete random variables

    CERN Document Server

    Sharma, Naresh; Muthukrishnan, Siddharth

    2010-01-01

    It is known that the Entropy Power Inequality (EPI) always holds if the random variables have density. Not much work has been done to identify discrete distributions for which the inequality holds with the differential entropy replaced by the discrete entropy. Harremo\\"{e}s and Vignat showed that it holds for the pair (B(m,p), B(n,p)), m,n \\in \\mathbb{N}, (where B(n,p) is a Binomial distribution with n trials each with success probability p) for p = 0.5. In this paper, we considerably expand the set of Binomial distributions for which the inequality holds and, in particular, identify n_0(p) such that for all m,n \\geq n_0(p), the EPI holds for (B(m,p), B(n,p)). We further show that the EPI holds for the discrete random variables that can be expressed as the sum of n independent identical distributed (IID) discrete random variables for large n.

  18. Factor analysis of soil spatial variability in gully erosion area of ...

    African Journals Online (AJOL)

    The effect of soil characteristics on gully development and distribution has made it desirable to determine the spatial variability of its physical and chemical properties. This paper examines the spatial variability of soil properties and factors contributing to the general pattern of variability in Agulu- Nanka- Oko gully complex, ...

  19. Non-Shannon Information Inequalities in Four Random Variables

    CERN Document Server

    Dougherty, Randall; Zeger, Kenneth

    2011-01-01

    Any unconstrained information inequality in three or fewer random variables can be written as a linear combination of instances of Shannon's inequality I(A;B|C) >= 0 . Such inequalities are sometimes referred to as "Shannon" inequalities. In 1998, Zhang and Yeung gave the first example of a "non-Shannon" information inequality in four variables. Their technique was to add two auxiliary variables with special properties and then apply Shannon inequalities to the enlarged list. Here we will show that the Zhang-Yeung inequality can actually be derived from just one auxiliary variable. Then we use their same basic technique of adding auxiliary variables to give many other non-Shannon inequalities in four variables. Our list includes the inequalities found by Xu, Wang, and Sun, but it is by no means exhaustive. Furthermore, some of the inequalities obtained may be superseded by stronger inequalities that have yet to be found. Indeed, we show that the Zhang-Yeung inequality is one of those that is superseded. We al...

  20. Observations on the spatial variability of the Prut river discharges

    Directory of Open Access Journals (Sweden)

    Emil-Andrei BRICIU

    2011-06-01

    Full Text Available Liquid and solid discharges of the Prut River were analysed based on measurementsperformed in 7 points from the Romanian national network of water monitoring during aperiod of 30 years. The analyses were performed on flows for the period after theconstruction of the Stânca-Costeşti dam and show the influence of the dam for the entireanalysed time. The analysis from upstream to downstream of the spatial variability of thePrut River annual discharges showed their steady increase downstream and then adecrease in the sector next to Oancea station. A statistical minority of the annualdischarges showed a continuous increase of them until the flowing of Prut into Danube.Knowing that the lower basin of the river is characterized by a low amount of rainfall anda higher evapo(transpiration than the remaining basin, the decreasing flows to the rivermouth is explicable; but the increasing flows to the river mouth cannot be justified, underthese conditions of water balance, than by certain climatological parameters of thermodynamicalnature which generate, with increased frequency, more intense and rich rainfall, with a torrential character. The analyses on couples of three months showed thatthe Oancea flows are higher than the upstream stations (opposite than usual in yearswhen the flows of the upstream hydrometrical stations are lower than the multiannualaverage and that supports the mentioned pluviometrical character. A plausible cause for"Oancea phenomenon" is the increase and the decrease of the sunspots number, whosecycles are relatively well fold on the increase and decrease of annual average flow atOancea hydrometrical station. The strongest increased discharges of the Prut River overthe discharges at the upstream stations occur from May to July (MJJ, the months with thehighest amount of rainfall. Seasonal analysis of MJJ and other couples of 3 monthsshowed that there are also growing flows at Prisăcani station relative to the adjacentstations, but

  1. Spatial variability of leaf wetness duration in different crop canopies

    Science.gov (United States)

    Sentelhas, Paulo C.; Gillespie, Terry J.; Batzer, Jean C.; Gleason, Mark L.; Monteiro, José Eduardo B. A.; Pezzopane, José Ricardo M.; Pedro, Mário J.

    2005-07-01

    The spatial variability of leaf wetness duration (LWD) was evaluated in four different height-structure crop canopies: apple, coffee, maize, and grape. LWD measurements were made using painted flat plate, printed-circuit wetness sensors deployed in different positions above and inside the crops, with inclination angles ranging from 30 to 45°. For apple trees, the sensors were installed in 12 east-west positions: 4 at each of the top (3.3 m), middle (2.1 m), and bottom (1.1 m) levels. For young coffee plants (80 cm tall), four sensors were installed close to the leaves at heights of 20, 40, 60, and 80 cm. For the maize and grape crops, LWD sensors were installed in two positions, one just below the canopy top and another inside the canopy. Adjacent to each experiment, LWD was measured above nearby mowed turfgrass with the same kind of flat plate sensor, deployed at 30 cm and between 30 and 45°. We found average LWD varied by canopy position for apple and maize (P<0.05). In these cases, LWD was longer at the top, particularly when dew was the source of wetness. For grapes, cultivated in a hedgerow system and for young coffee plants, average LWD did not differ between the top and inside the canopy. The comparison by geometric mean regression analysis between crop and turfgrass LWD measurements showed that sensors at 30 cm over turfgrass provided quite accurate estimates of LWD at the top of the crops, despite large differences in crop height and structure, but poorer estimates for wetness within leaf canopies.

  2. Ionospheric total electron content: Spatial patterns of variability

    Science.gov (United States)

    Lean, J. L.; Meier, R. R.; Picone, J. M.; Sassi, F.; Emmert, J. T.; Richards, P. G.

    2016-10-01

    The distinctive spatial patterns of the ionosphere's total electron content (TEC) response to solar, seasonal, diurnal, and geomagnetic influences are determined across the globe using a new statistical model constructed from 2-hourly TEC observations from 1998 to 2015. The model combines representations of the physical solar EUV photon and geomagnetic activity drivers with solar-modulated sinusoidal parameterizations of four seasonal cycles and solar-modulated and seasonally modulated parameterizations of three diurnal cycles. The average absolute residual of the data-model differences is 2.1 total electron content unit, 1 TECU = 1016 el m-2 (TECU) (9%) and the root-mean-square error is 3.5 TECU (15%). Solar and geomagnetic variability, the semiannual oscillation and the diurnal and semidiurnal oscillations all impact TEC most at low magnetic latitudes where TEC itself maximizes, with differing degrees of longitudinal inhomogeneity. In contrast, the annual oscillation manifests primarily in the Southern Hemisphere with maximum amplitude over midlatitude South America, extending to higher southern latitudes in the vicinity of the Weddell Sea. Nighttime TEC levels in the vicinity of the Weddell Sea exceed daytime levels every year in Southern Hemisphere summer as a consequence of the modulation of the diurnal oscillations by the seasonal oscillations. The anomaly, which is present at all phases of the solar cycle, commences sooner and ends later under solar minimum conditions. The model minus data residuals maximize at tropical magnetic latitudes in four geographical regions similar to the ionosphere pattern generated by lower atmospheric meteorology. Enhanced residuals at northern midlatitudes during winter are consistent with an influence of atmospheric gravity waves.

  3. Spatial and temporal variability of biophysical variables in southwestern France from airborne L-band radiometry

    Directory of Open Access Journals (Sweden)

    E. Zakharova

    2012-06-01

    ISBA-A-gs grid cells tended to increase the CAROLS SSM spatial variability, up to 0.10 m3 m−3. Also, the grid cells characterised by a high vegetation cover heterogeneity presented higher standard deviation values, for both SSM and VOD.

  4. Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology.

    Science.gov (United States)

    Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H

    2017-07-01

    Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in

  5. Spectral and spatial variability of undisturbed and disturbed grass under different view and illumination directions

    Science.gov (United States)

    Borel-Donohue, Christoph C.; Shivers, Sarah Wells; Conover, Damon

    2017-05-01

    It is well known that disturbed grass covered surfaces show variability with view and illumination conditions. A good example is a grass field in a soccer stadium that shows stripes indicating in which direction the grass was mowed. These spatial variations are due to a complex interplay of spectral characteristics of grass blades, density, their length and orientations. Viewing a grass surface from nadir or near horizontal directions results in observing different components. Views from a vertical direction show more variations due to reflections from the randomly oriented grass blades and their shadows. Views from near horizontal show a mixture of reflected and transmitted light from grass blades. An experiment was performed on a mowed grass surface which had paths of simulated heavy foot traffic laid down in different directions. High spatial resolution hyperspectral data cubes were taken by an imaging spectrometer covering the visible through near infrared over a period of time covering several hours. Ground truth grass reflectance spectra with a hand held spectrometer were obtained of undisturbed and disturbed areas. Close range images were taken of selected areas with a hand held camera which were then used to reconstruct the 3D geometry of the grass using structure-from-motion algorithms. Computer graphics rendering using raytracing of reconstructed and procedurally created grass surfaces were used to compute BRDF models. In this paper, we discuss differences between observed and simulated spectral and spatial variability. Based on the measurements and/or simulations, we derive simple spectral index methods to detect spatial disturbances and apply scattering models.

  6. Wave speed in excitable random networks with spatially constrained connections.

    Directory of Open Access Journals (Sweden)

    Nikita Vladimirov

    Full Text Available Very fast oscillations (VFO in neocortex are widely observed before epileptic seizures, and there is growing evidence that they are caused by networks of pyramidal neurons connected by gap junctions between their axons. We are motivated by the spatio-temporal waves of activity recorded using electrocorticography (ECoG, and study the speed of activity propagation through a network of neurons axonally coupled by gap junctions. We simulate wave propagation by excitable cellular automata (CA on random (Erdös-Rényi networks of special type, with spatially constrained connections. From the cellular automaton model, we derive a mean field theory to predict wave propagation. The governing equation resolved by the Fisher-Kolmogorov PDE fails to describe wave speed. A new (hyperbolic PDE is suggested, which provides adequate wave speed v( that saturates with network degree , in agreement with intuitive expectations and CA simulations. We further show that the maximum length of connection is a much better predictor of the wave speed than the mean length. When tested in networks with various degree distributions, wave speeds are found to strongly depend on the ratio of network moments / rather than on mean degree , which is explained by general network theory. The wave speeds are strikingly similar in a diverse set of networks, including regular, Poisson, exponential and power law distributions, supporting our theory for various network topologies. Our results suggest practical predictions for networks of electrically coupled neurons, and our mean field method can be readily applied for a wide class of similar problems, such as spread of epidemics through spatial networks.

  7. A Permutation-Randomization Approach to Test the Spatial Distribution of Plant Diseases.

    Science.gov (United States)

    Lione, G; Gonthier, P

    2016-01-01

    The analysis of the spatial distribution of plant diseases requires the availability of trustworthy geostatistical methods. The mean distance tests (MDT) are here proposed as a series of permutation and randomization tests to assess the spatial distribution of plant diseases when the variable of phytopathological interest is categorical. A user-friendly software to perform the tests is provided. Estimates of power and type I error, obtained with Monte Carlo simulations, showed the reliability of the MDT (power > 0.80; type I error pathogens causing root rot on conifers was successfully performed by verifying the consistency between the MDT responses and previously published data. An application of the MDT was carried out to analyze the relation between the plantation density and the distribution of the infection of Gnomoniopsis castanea, an emerging fungal pathogen causing nut rot on sweet chestnut. Trees carrying nuts infected by the pathogen were randomly distributed in areas with different plantation densities, suggesting that the distribution of G. castanea was not related to the plantation density. The MDT could be used to analyze the spatial distribution of plant diseases both in agricultural and natural ecosystems.

  8. The active liquid Earth - importance of temporal and spatial variability

    Science.gov (United States)

    Arheimer, Berit

    2016-04-01

    The Planet Earth is indeed liquid and active - 71 percent of its surface is water-covered and this water never rests. Thanks to the water cycle, our planet's water supply is constantly moving from one place to another and from one form to another. Only 2.5% of the water is freshwater and it exists in the air as water vapor; it hits the ground as rain and snow; it flows on the surface from higher to lower altitudes in rivers, lakes, and glaciers; and it flows in the ground in soil, aquifers, and in all living organisms until it reaches the sea. On its way over the Earth's crust, some returns quickly to vapor again, while some is trapped and exposed to many "fill and spill" situations for a long journey. The variability in the water balance is crucial for hydrological understanding and modelling. The water cycle may appear simple, but magnitudes and rates in fluxes are very different from one place to another, resulting from variable drivers such as solar energy, precipitation and gravity in co-evolution with geology, soil, vegetation and fauna. The historical evolution, the temporal fluxes and diversity in space continue to fascinate hydrological scientists. Specific physical processes may be well known, but their boundary conditions, interactions and rate often remain unknown at a specific site and are difficult to monitor in nature. This results in mysterious features where trends in drivers do not match runoff, like the Sahelian Paradox or discharge to the Arctic Ocean. Humans have always interfered with the water cycle and engineering is fundamental for water regulation and re-allocation. Some 80% of the river flow from the northern part of the Earth is affected by fragmentation of the river channels by dams. In water management, there is always a tradeoff between upstream and downstream activities, not only regarding total water quantities but also for temporal patterns and water quality aspects. Sharing a water resource can generate conflicts but geopolitical

  9. Determinants of spatial variability of methane emissions from wet grasslands on peat soil

    NARCIS (Netherlands)

    Pol-Van Dasselaar, van den A.; Beusichem, van M.L.; Oenema, O.

    1999-01-01

    Methane (CH4) emissions from soils, representing the consequence of CH4 production, CH4 consumption and CH4 transport, are poorly characterised and show a large spatial variability. This study aimed to assess the determinants of field-scale spatial variability of CH4 emissions from wet grasslands on

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

    DEFF Research Database (Denmark)

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

    2012-01-01

    is performed using ArcGIS Geostatistical Analyst. Results show that BFs of copper span a range of 6 orders of magnitude, and have signifficant spatial variability at local and continental scales. The model nugget variance is signifficantly higher than zero, suggesting the presence of spatial variability...

  11. Spatial and temporal variability of guinea grass (Megathyrsus maximus) fuel loads and moisture on Oahu, Hawaii

    Science.gov (United States)

    Lisa M. Ellsworth; Creighton M. Litton; Andrew D. Taylor; J. Boone Kauffman

    2013-01-01

    Frequent wildfires in tropical landscapes dominated by non-native invasive grasses threaten surrounding ecosystems and developed areas. To better manage fire, accurate estimates of the spatial and temporal variability in fuels are urgently needed. We quantified the spatial variability in live and dead fine fuel loads and moistures at four guinea grass (...

  12. Generation of correlated finite alphabet waveforms using gaussian random variables

    KAUST Repository

    Jardak, Seifallah

    2014-09-01

    Correlated waveforms have a number of applications in different fields, such as radar and communication. It is very easy to generate correlated waveforms using infinite alphabets, but for some of the applications, it is very challenging to use them in practice. Moreover, to generate infinite alphabet constant envelope correlated waveforms, the available research uses iterative algorithms, which are computationally very expensive. In this work, we propose simple novel methods to generate correlated waveforms using finite alphabet constant and non-constant-envelope symbols. To generate finite alphabet waveforms, the proposed method map the Gaussian random variables onto the phase-shift-keying, pulse-amplitude, and quadrature-amplitude modulation schemes. For such mapping, the probability-density-function of Gaussian random variables is divided into M regions, where M is the number of alphabets in the corresponding modulation scheme. By exploiting the mapping function, the relationship between the cross-correlation of Gaussian and finite alphabet symbols is derived. To generate equiprobable symbols, the area of each region is kept same. If the requirement is to have each symbol with its own unique probability, the proposed scheme allows us that as well. Although, the proposed scheme is general, the main focus of this paper is to generate finite alphabet waveforms for multiple-input multiple-output radar, where correlated waveforms are used to achieve desired beampatterns. © 2014 IEEE.

  13. Spatial-time variability of particulate material content and its composition: From mesoscale to interannual variability

    Science.gov (United States)

    Dudarev, Oleg; Charkin, Alexander; Semiletov, Igor; Gustafsson, Örjan; Vonk, Jorien; Sánchez-García, Laura

    2010-05-01

    The role of the coastal zone in lateral transport and fate of terrestrial organic carbon in the East Siberian Arctic Shelf (ESAS) has not been well studied to date because most recent activities have focused on onshore geomorphologic and geochemical features, while biogeochemical and sedimentation consequences of coastal erosion and riverine runoff into the sea were not studied sufficiently. Here we present the data obtained on joint Russian-US cruises (NOAA and NSF funded) in 2003, 2004, 2005, and in the International Siberian Shelf Study-2008 (ISSS-2008, supported by the Wallenberg Foundation, FEBRAS, NOAA, and the Russian NSF), which characterized a spatial and interannual variability in distribution of particulate material (PM), and its organic carbon and stable isotopes content. Dynamics and composition of PM were studied twice along the Lena River in summer-fall of 2003. Here, the spatial-time dynamics of PM composition (particulate organic carbon (POC), isotopes and mineralogical composition) is considered in connection with changing river runoff and wind patterns. It has been found that the dominant source of POC into the ESAS is coastal erosion, rather than input from the rivers (Lena, Yana, Indigirka, Kolyma). A sharp PM concentration gradient from "freshened/high PM" to "Pacific/low PM" waters was found across the frontal zone. The position of the frontal zone varies significantly from year to year; this difference is mainly attributed to the difference in atmospheric circulation patterns driving the Arctic Ocean circulation. During storms and surges the PM concentration in a single area was increased by 10 times or more (up to 80-242 mg/l) in 2000 and 2005 compared to the 2003 and 2004 PM concentration.

  14. Analysis of Secret Key Randomness Exploiting the Radio Channel Variability

    Directory of Open Access Journals (Sweden)

    Taghrid Mazloum

    2015-01-01

    Full Text Available A few years ago, physical layer based techniques have started to be considered as a way to improve security in wireless communications. A well known problem is the management of ciphering keys, both regarding the generation and distribution of these keys. A way to alleviate such difficulties is to use a common source of randomness for the legitimate terminals, not accessible to an eavesdropper. This is the case of the fading propagation channel, when exact or approximate reciprocity applies. Although this principle has been known for long, not so many works have evaluated the effect of radio channel properties in practical environments on the degree of randomness of the generated keys. To this end, we here investigate indoor radio channel measurements in different environments and settings at either 2.4625 GHz or 5.4 GHz band, of particular interest for WIFI related standards. Key bits are extracted by quantizing the complex channel coefficients and their randomness is evaluated using the NIST test suite. We then look at the impact of the carrier frequency, the channel variability in the space, time, and frequency degrees of freedom used to construct a long secret key, in relation to the nature of the radio environment such as the LOS/NLOS character.

  15. Selection for altruism through random drift in variable size populations.

    Science.gov (United States)

    Houchmandzadeh, Bahram; Vallade, Marcel

    2012-05-10

    Altruistic behavior is defined as helping others at a cost to oneself and a lowered fitness. The lower fitness implies that altruists should be selected against, which is in contradiction with their widespread presence is nature. Present models of selection for altruism (kin or multilevel) show that altruistic behaviors can have 'hidden' advantages if the 'common good' produced by altruists is restricted to some related or unrelated groups. These models are mostly deterministic, or assume a frequency dependent fitness. Evolutionary dynamics is a competition between deterministic selection pressure and stochastic events due to random sampling from one generation to the next. We show here that an altruistic allele extending the carrying capacity of the habitat can win by increasing the random drift of "selfish" alleles. In other terms, the fixation probability of altruistic genes can be higher than those of a selfish ones, even though altruists have a smaller fitness. Moreover when populations are geographically structured, the altruists advantage can be highly amplified and the fixation probability of selfish genes can tend toward zero. The above results are obtained both by numerical and analytical calculations. Analytical results are obtained in the limit of large populations. The theory we present does not involve kin or multilevel selection, but is based on the existence of random drift in variable size populations. The model is a generalization of the original Fisher-Wright and Moran models where the carrying capacity depends on the number of altruists.

  16. Selection for altruism through random drift in variable size populations

    Directory of Open Access Journals (Sweden)

    Houchmandzadeh Bahram

    2012-05-01

    Full Text Available Abstract Background Altruistic behavior is defined as helping others at a cost to oneself and a lowered fitness. The lower fitness implies that altruists should be selected against, which is in contradiction with their widespread presence is nature. Present models of selection for altruism (kin or multilevel show that altruistic behaviors can have ‘hidden’ advantages if the ‘common good’ produced by altruists is restricted to some related or unrelated groups. These models are mostly deterministic, or assume a frequency dependent fitness. Results Evolutionary dynamics is a competition between deterministic selection pressure and stochastic events due to random sampling from one generation to the next. We show here that an altruistic allele extending the carrying capacity of the habitat can win by increasing the random drift of “selfish” alleles. In other terms, the fixation probability of altruistic genes can be higher than those of a selfish ones, even though altruists have a smaller fitness. Moreover when populations are geographically structured, the altruists advantage can be highly amplified and the fixation probability of selfish genes can tend toward zero. The above results are obtained both by numerical and analytical calculations. Analytical results are obtained in the limit of large populations. Conclusions The theory we present does not involve kin or multilevel selection, but is based on the existence of random drift in variable size populations. The model is a generalization of the original Fisher-Wright and Moran models where the carrying capacity depends on the number of altruists.

  17. A lower bound on the probability that a binomial random variable is exceeding its mean

    OpenAIRE

    Pelekis, Christos; Ramon, Jan

    2016-01-01

    We provide a lower bound on the probability that a binomial random variable is exceeding its mean. Our proof employs estimates on the mean absolute deviation and the tail conditional expectation of binomial random variables.

  18. Generating Variable and Random Schedules of Reinforcement Using Microsoft Excel Macros

    Science.gov (United States)

    Bancroft, Stacie L; Bourret, Jason C

    2008-01-01

    Variable reinforcement schedules are used to arrange the availability of reinforcement following varying response ratios or intervals of time. Random reinforcement schedules are subtypes of variable reinforcement schedules that can be used to arrange the availability of reinforcement at a constant probability across number of responses or time. Generating schedule values for variable and random reinforcement schedules can be difficult. The present article describes the steps necessary to write macros in Microsoft Excel that will generate variable-ratio, variable-interval, variable-time, random-ratio, random-interval, and random-time reinforcement schedule values. PMID:18595286

  19. Local-scale spatial modelling for interpolating climatic temperature variables to predict agricultural plant suitability

    Science.gov (United States)

    Webb, Mathew A.; Hall, Andrew; Kidd, Darren; Minansy, Budiman

    2016-05-01

    Assessment of local spatial climatic variability is important in the planning of planting locations for horticultural crops. This study investigated three regression-based calibration methods (i.e. traditional versus two optimized methods) to relate short-term 12-month data series from 170 temperature loggers and 4 weather station sites with data series from nearby long-term Australian Bureau of Meteorology climate stations. The techniques trialled to interpolate climatic temperature variables, such as frost risk, growing degree days (GDDs) and chill hours, were regression kriging (RK), regression trees (RTs) and random forests (RFs). All three calibration methods produced accurate results, with the RK-based calibration method delivering the most accurate validation measures: coefficients of determination ( R 2) of 0.92, 0.97 and 0.95 and root-mean-square errors of 1.30, 0.80 and 1.31 °C, for daily minimum, daily maximum and hourly temperatures, respectively. Compared with the traditional method of calibration using direct linear regression between short-term and long-term stations, the RK-based calibration method improved R 2 and reduced root-mean-square error (RMSE) by at least 5 % and 0.47 °C for daily minimum temperature, 1 % and 0.23 °C for daily maximum temperature and 3 % and 0.33 °C for hourly temperature. Spatial modelling indicated insignificant differences between the interpolation methods, with the RK technique tending to be the slightly better method due to the high degree of spatial autocorrelation between logger sites.

  20. Design and Development of an Open Source Software Application for the Characterization of Spatially Variable Fields

    Science.gov (United States)

    Gunnell, D. K.; Osorio-Murillo, C. A.; Over, M. W.; Frystacky, H.; Ames, D. P.; Rubin, Y.

    2013-12-01

    The characterization of the structural parameters of spatially variable fields (SVFs) is essential to understanding the variability of hydrological processes such as infiltration, evapotranspiration, groundwater contaminant transport, etc. SVFs can be characterized using a Bayesian inverse method called Method of Anchored Distributions (MAD). This method characterizes the structural parameters of SVFs using prior information of structural parameter fields, indirect measurements, and simulation models allowing the transfer of valuable information to a target variable field. An example SVF in hydrology is hydraulic conductivity, which may be characterized by head pressure measurements through a simulation model such as MODFLOW. This poster will present the design and development of a free and open source inverse modeling desktop software application and extension framework called MAD# for the characterization of the structural parameters of SVFs using MAD. The developed software is designed with a flexible architecture to support different simulation models and random field generators and includes geographic information system (GIS) interfaces for representing, analyzing, and understanding SVFs. This framework has also been made compatible with Mono, a cross-platform implementation of C#, for a wider usability.

  1. Bayesian principal component regression model with spatial effects for forest inventory variables under small field sample size

    Science.gov (United States)

    Junttila, Virpi; Laine, Marko

    2017-04-01

    Remote sensing observations are extensively used for analysis of environmental variables. These variables often exhibit spatial correlation, which has to be accounted for in the calibration models used in predictions, either by direct modelling of the dependencies or by allowing for spatially correlated stochastic effects. Another feature in many remote sensing instruments is that the derived predictor variables are highly correlated, which can lead to unnecessary model over-training and at worst, singularities in the estimates. Both of these affect the prediction accuracy, especially when the training set for model calibration is small. To overcome these modelling challenges, we present a general model calibration procedure for remotely sensed data and apply it to airborne laser scanning data for forest inventory. We use a linear regression model that accounts for multicollinearity in the predictors by principal components and Bayesian regularization. It has a spatial random effect component for the spatial correlations that are not explained by a simple linear model. An efficient Markov chain Monte Carlo sampling scheme is used to account for the uncertainty in all the model parameters. We tested the proposed model against several alternatives and it outperformed the other linear calibration models, especially when there were spatial effects, multicollinearity and the training set size was small.

  2. Preliminary analysis of interannual Caribbean Current spatial variability

    OpenAIRE

    Bryce Corlett, W.; Ezer, Tal

    2014-01-01

    2012 Poster Presentation - Old Dominion University The preliminary results shown here are an initial attempt to connect spatial variations of the Caribbean Current to eddy activity at the Meso-American Barrier Reef, as is an important driver for currents around the reef during spawning.

  3. Spatial variability of expansive soil properties at different scales ...

    African Journals Online (AJOL)

    This paper applies statistical and geostatistical procedures to analyse the spatial distribution of several soil properties and use the contribution of ge ostatistics to plan optimal soil sampling and management schemes in. Kibaha, Tanzania. Particle-size distribution, Atterberg limits and potential swell were analysed.

  4. Spatial and temporal variability in recruitment of intertidal mussels ...

    African Journals Online (AJOL)

    IntenSity of intertidal mussel recruitment was compared across a range of different spatial and temporal scales around the coast of southern Africa between June 1995 and October 1996. Comparison of the east and west coasts revealed significantly higher recruit densities on the west coast, corresponding to larger adult ...

  5. Spatial and temporal variability in recruitment of intertidal mussels ...

    African Journals Online (AJOL)

    Intensity of intertidal mussel recruitment was compared across a range of different spatial and temporal scales around the coast of southern Africa between June 1995 and October 1996. Comparison of the east and west coasts revealed significantly higher recruit densities on the west coast, corresponding to larger adult ...

  6. Spatial variability of fine particle concentrations in three European areas

    Science.gov (United States)

    Hoek, Gerard; Meliefste, Kees; Cyrys, Josef; Lewné, Marie; Bellander, Tom; Brauer, Mike; Fischer, Paul; Gehring, Ulrike; Heinrich, Joachim; van Vliet, Patricia; Brunekreef, Bert

    Epidemiological studies of long-term air pollution effects have been hampered by difficulties in characterizing the spatial variation in air pollution. We conducted a study to assess the risk of long-term exposure to traffic-related air pollution for the development of inhalant allergy and asthma in children in Stockholm county, Munich and the Netherlands. Exposure to traffic-related air pollution was assessed through a 1-year monitoring program and regression modeling using exposure indicators. This paper documents the performance of the exposure monitoring strategy and the spatial variation of ambient particle concentrations. We measured the ambient concentration of PM2.5 and the reflectance of PM2.5 filters ('soot') at 40-42 sites representative of different exposure conditions of the three study populations. Each site was measured during four 14-day average sampling periods spread over one year (spring 1999 to summer 2000). In each study area, a continuous measurement site was operated to remove potential bias due to temporal variation. The selected approach was an efficient method to characterize spatial differences in annual average concentration between a large number of sites in each study area. Adjustment with data from the continuous measurement site improved the precision of the calculated annual averages, especially for PM2.5. Annual average PM2.5 concentrations ranged from 11 to 20 μg/m 3 in Munich, from 8 to 16 μg/m 3 in Stockholm and from 14 to 26 μg/m 3 in the Netherlands. Larger spatial contrasts were found for the absorption coefficient of PM2.5. PM2.5 concentrations were on average 17-18% higher at traffic sites than at urban background sites, but PM2.5 absorption coefficients at traffic sites were between 31% and 55% increased above background. This suggests that spatial variation of traffic-related air pollution may be underestimated if PM2.5 only is measured.

  7. Spatial Variability of Dielectric Properties in Field Soils

    National Research Council Canada - National Science Library

    Hendrickx, J

    2001-01-01

    ... since it directly influences the three other properties The variability of these properties may be such that either potential land mine signatures are overshadowed or false alarms result In this paper...

  8. Generating Correlated QPSK Waveforms By Exploiting Real Gaussian Random Variables

    KAUST Repository

    Jardak, Seifallah

    2012-11-01

    The design of waveforms with specified auto- and cross-correlation properties has a number of applications in multiple-input multiple-output (MIMO) radar, one of them is the desired transmit beampattern design. In this work, an algorithm is proposed to generate quadrature phase shift- keying (QPSK) waveforms with required cross-correlation properties using real Gaussian random-variables (RV’s). This work can be considered as the extension of what was presented in [1] to generate BPSK waveforms. This work will be extended for the generation of correlated higher-order phase shift-keying (PSK) and quadrature amplitude modulation (QAM) schemes that can better approximate the desired beampattern.

  9. Spatial Variability of Flow in Coarse, Unsaturated Mining Material: Results from Field-Scale Infiltration Experiments

    Science.gov (United States)

    Webb, G. G.; Tyler, S. W.; van Zyl, D. J.; Collord, J.

    2003-12-01

    The spatial distribution of fluid flow during unsaturated conditions within an active gold mining heap-leach facility was studied. Flow and percolate chemistry data was recorded from free-drainage lysimeters. Highly variable flow was observed between lysimeters during steady-state infiltration conditions. The cause of the variability was determined to be more the result of highly spatially variable hydraulic properties than the variable distribution of applied flux to the surface. Using stochastically distributed hydraulic conductivity scaling factors, the variability of flow was reasonably reproduced with numerical simulations (HYDRUS-2D).

  10. Effects of attentional and cognitive variables on unilateral spatial neglect.

    Science.gov (United States)

    Ricci, Raffaella; Salatino, Adriana; Garbarini, Francesca; Ronga, Irene; Genero, Rosanna; Berti, Anna; Neppi-Mòdona, Marco

    2016-11-01

    Patients with visuospatial neglect when asked to cancel targets partially or totally omit to cancel contralesional stimuli. It has been shown that increasing the attentional demands of the cancellation task aggravates neglect contralesionally. However, some preliminary evidence also suggests that neglect might be worsened by engaging the patient in a demanding, non-spatial, cognitive activity (i.e. a mathematical task). We studied cancellation performance of 16 patients with right-hemisphere lesions, 8 with neglect, 8 without neglect, and 8 age-matched healthy control participants by means of five cancellation tasks which varied for the degree of attentional and/or high level cognitive demands (preattentive and attentive search of a visual target, searching for numbers containing the digit 3, even numbers, and multiples of 3). Results showed that attentive search of visual targets, relative to the preattentive search condition, aggravated neglect patients' performance. Moreover, searching for multiples not only worsened spatial neglect contralesionally, but also slowed down performance of patients with right-hemisphere lesions without neglect. Our findings further demonstrate the presence of specific deficits of attention in neglect. In addition, the worse performance of patients without neglect in the 'multiples of 3' task is consistent with the evidence that right-hemisphere lesions per se impair the ability to maintain attention (i.e. sustained attention). This suggests that the exacerbation of neglect during execution of a demanding, non-spatial, cognitive task might be explained by a deficit of sustained attention in addition to a selective deficit of spatial attention. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Indian Summer Monsoon Rainfall: Implications of Contrasting Trends in the Spatial Variability of Means and Extremes.

    Directory of Open Access Journals (Sweden)

    Subimal Ghosh

    Full Text Available India's agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins.

  12. Spatial variability of POPs in European background air

    Directory of Open Access Journals (Sweden)

    A. K. Halse

    2011-02-01

    Full Text Available Passive air samplers (PAS were deployed at 86 European background sites during summer 2006 in order (i to gain further insight into spatial patterns of persistent organic pollutants (POPs in European background air and, (ii to evaluate PAS as an alternative sampling technique under EMEP (Co-operative programme for monitoring and evaluation of the long-range transmissions of air pollutants in Europe. The samples were analyzed for selected PCBs, HCHs, DDTs, HCB, PAHs and chlordanes, and air concentrations were calculated on the basis of losses of performance reference compounds. Air concentrations of PCBs were generally lowest in more remote areas of northern Europe with elevated levels in more densely populated areas. γ-HCH was found at elevated levels in more central parts of Europe, whereas α-HCH, β-HCH and DDTs showed higher concentrations in the south-eastern part. There was no clear spatial pattern in the concentrations for PAHs, indicative of influence by local sources, rather than long range atmospheric transport (LRAT. HCB was evenly distributed across Europe, while the concentrations of chlordanes were typically low or non-detectable. A comparison of results obtained on the basis of PAS and active air sampling (AAS illustrated that coordinated PAS campaigns have the potential serve as useful inter-comparison exercises within and across existing monitoring networks. The results also highlighted limitations of the current EMEP measurement network with respect to spatial coverage. We finally adopted an existing Lagrangian transport model (FLEXPART as recently modified to incorporate key processes relevant for POPs to evaluate potential source regions affecting observed concentrations at selected sites. Using PCB-28 as an example, the model predicted concentrations which agreed within a factor of 3 with PAS measurements for all except 1 out of the 17 sites selected for this analysis.

  13. Monitoring spatial-temporal variability of aerosol over Kenya ...

    African Journals Online (AJOL)

    Validation of MODIS AOD using Aerosol Robotic Network (AERONET) indicated that MODIS overestimated the aerosol loading over the study region. Space time variability of MODIS AOD measurements over Kenya showed a decreasing trend in aerosol loading with a long term mean of between 0.02 and 0.56.

  14. Measuring spatial variability of land use associated with ...

    African Journals Online (AJOL)

    2011-06-07

    use system is linked to orderly .... i.e., the probability of an urban area occurring around a city centre (Chen et al., 2010). ..... represents around 53% of the maximum degree of land-use spa- tial variability. This means that ...

  15. Crown fuel spatial variability and predictability of fire spread

    Science.gov (United States)

    Russell A. Parsons; Jeremy Sauer; Rodman R. Linn

    2010-01-01

    Fire behavior predictions, as well as measures of uncertainty in those predictions, are essential in operational and strategic fire management decisions. While it is becoming common practice to assess uncertainty in fire behavior predictions arising from variability in weather inputs, uncertainty arising from the fire models themselves is difficult to assess. This is...

  16. Spatial variability in the density, distribution and vectorial capacity of ...

    African Journals Online (AJOL)

    Malaria transmission varies from one area to another and there are also local difference in time and space. The objective of the study was to determine the local variability of entomological parameters namely, mosquito abundance, human biting rate (HBR), sporozoite rate for Plasmodium falciparum and entomological ...

  17. Measuring spatial variability of land use associated with ...

    African Journals Online (AJOL)

    2011-06-07

    Jun 7, 2011 ... Decision making for water resources is needed for land-use change due to urbanisation, which impacts hydrological variables such as ...... Values showing relationships between return period, risk of failure, increase in runoff and entropy. T = return period. (years). R = Risk (of failure due to flooding). URB ( ...

  18. Temporal and spatial variability of rainfall distribution and ...

    African Journals Online (AJOL)

    Analysis of rainfall variability is made by the rainfall anomaly index, coefficient of variance and precipitation concentration index. The FAO-56 reference ET (ETo) approach was used to determine the amount of evapotranspiration. Estimation of the onset, end of growing season and length of growing period was done using ...

  19. Possible spatial asymmetry in semiregular variable UZ Arietis

    Science.gov (United States)

    Baug, Tapas; Chandrasekhar, T.; Ganesh, Shashikiran

    2014-10-01

    Semiregular variables (SRVs) though closely related to Mira variables, are a less studied class of asymptotic giant branch stars. While asymmetry in the brightness distribution of many Mira variables is fairly well known, it is detected only in a few SRVs. Asymmetry in the brightness distribution at the level of a few milliarcsecond can be detected by high angular resolution techniques like lunar occultations (LO), long baseline interferometry and aperture masking interferometry. Multi-epoch LO observations have the potential to detect a departure of brightness profile from spherical symmetry. Each LO event provides a uniform disc (UD) angular diameter along the position angle of the occultation. Any significant difference in the UD angular diameter values of multi-epoch LO observations signifies a brightness asymmetry. In this paper, we report for the first time three-epoch UD angular diameter values of a SRV UZ Arietis using the LO technique at 2.2 μm. Optical linear polarization of the source observed by us recently is also reported. The asymmetric brightness distribution of UZ Ari suggested by a small difference in the fitted UD values for the three epochs, is discussed in the context of optical polarization exhibited by the source and the direction of polarization axis in the plane of the sky.

  20. Spatial variability in the coefficient of thermal expansion induces pre-service stresses in computer models of virgin Gilsocarbon bricks

    Energy Technology Data Exchange (ETDEWEB)

    Arregui-Mena, José David, E-mail: jose.arreguimena@postgrad.manchester.ac.uk [School of Mechanical, Aerospace, and Civil Engineering, University of Manchester, Oxford Road, Manchester, M13 9PL (United Kingdom); Margetts, Lee, E-mail: lee.margetts@manchester.ac.uk [School of Mechanical, Aerospace, and Civil Engineering, University of Manchester, Oxford Road, Manchester, M13 9PL (United Kingdom); Griffiths, D.V., E-mail: d.v.griffiths@mines.edu [Colorado School of Mines, 1500 Illinois St, Golden, CO 80401 (United States); Lever, Louise, E-mail: louise.lever@manchester.ac.uk [Research Computing, University of Manchester, Oxford Road, Manchester, M13 9PL (United Kingdom); Hall, Graham, E-mail: graham.n.hall@manchester.ac.uk [School of Mechanical, Aerospace, and Civil Engineering, University of Manchester, Oxford Road, Manchester, M13 9PL (United Kingdom); Mummery, Paul M., E-mail: paul.m.mummery@manchester.ac.uk [School of Mechanical, Aerospace, and Civil Engineering, University of Manchester, Oxford Road, Manchester, M13 9PL (United Kingdom)

    2015-10-15

    In this paper, the authors test the hypothesis that tiny spatial variations in material properties may lead to significant pre-service stresses in virgin graphite bricks. To do this, they have customised ParaFEM, an open source parallel finite element package, adding support for stochastic thermo-mechanical analysis using the Monte Carlo Simulation method. For an Advanced Gas-cooled Reactor brick, three heating cases have been examined: a uniform temperature change; a uniform temperature gradient applied through the thickness of the brick and a simulated temperature profile from an operating reactor. Results are compared for mean and stochastic properties. These show that, for the proof-of-concept analyses carried out, the pre-service von Mises stress is around twenty times higher when spatial variability of material properties is introduced. The paper demonstrates that thermal gradients coupled with material incompatibilities may be important in the generation of stress in nuclear graphite reactor bricks. Tiny spatial variations in coefficient of thermal expansion (CTE) and Young's modulus can lead to the presence of thermal stresses in bricks that are free to expand. - Highlights: • Open source software has been modified to include random variability in CTE and Young's modulus. • The new software closely agrees with analytical solutions and commercial software. • Spatial variations in CTE and Young's modulus produce stresses that do not occur with mean values. • Material variability may induce pre-service stress in virgin graphite.

  1. Spatial and temporal variability of climate extremes in Romania and associated large‐scale mechanisms

    National Research Council Canada - National Science Library

    Busuioc, Aristita; Dobrinescu, Andreea; Birsan, Marius‐Victor; Dumitrescu, Alexandru; Orzan, Alina

    2015-01-01

    ...‐scale mechanisms responsible for this variability on the other are examined. Ten indices associated with temperature and precipitation extremes computed at high spatial resolution for the period 1961–2010 are analysed...

  2. Spatial and temporal variability of tropospheric ozone over Europe

    Energy Technology Data Exchange (ETDEWEB)

    Scheel, H.E.; Sladkovic, R. [Fraunhofer Inst. (IFU), Garmisch-Partenkirchen (Germany); Ancellet, G. [Universite Paris 6 (France). Service d`Aeronomie du CNRS; Areskoug, H. [Air Pollution Lab., Inst. of Applied Environmental Research, Stockholm Univ. (Sweden); Beck, J.; Waal, L. de [RIVM-LLO, Bilthoven (Netherlands); Boesenberg, J.; Grabbe, G. [Max-Planck-Institut fuer Meteorologie, Hamburg (Germany); Muer, D. de [Meteorological Inst. of Belgium (KMI), Brussels (Belgium); Dutot, A.L.; Etienne, A.; Perros, P.; Toupance, G. [Universite Paris XII-Creteil (France). Lab. de Physico-Chimie de l`Environment; Egelov, A.H.; Granby, K. [National Environmental Research Inst., Roskilde (Denmark); Esser, P.; Roemer, M. [IMW-TNO, Delft (Netherlands); Ferenczi, Z.; Haszpra, L. [Institute for Atmospheric Physics, Budapest (Hungary); Geiss, H.; Smit, H. [Forschungszentrum Juelich (Germany). Inst. fuer Chemie und Dynamik der Geosphaere (ICG-2); Gomiscek, B. [Ljubljana Univ. (Slovenia). Faculty of Chemistry and Chemical Technology; Kezele, N.; Klasinc, L. [Institut Rudjer Boskovic, Zagreb (Croatia); Laurila, T. [Finnish Meteorological Inst., Helsinki (Finland). Dept. of Air Quality; Lindskog, A.; Mowrer, J. [Swedish Environmental Research Inst. (IVL), Goeteborg (Sweden); Nielsen, T. [Risoe National Laboratory, Roskilde (Denmark); Schmitt, R. [Meteorologie Consult GmbH, Glashuetten (Germany); Simmonds, P. [International Science Consultants, Ringwood (United Kingdom); Solberg, S. [NILU, Kjeller (Norway); Varotsos, C. [Athens Univ. (Greece); TOR Task Group 1

    1997-12-31

    The first section is concerned with the characteristics of the TOR-measurement sites and the data used. It describes the methodologies employed for the selection of data in order to obtain representative ozone concentrations with minimum bias caused by the individual location. The question of representativeness of the O{sub 3} concentrations at the TOR sites was given special attention, since it is a crucial point for all conclusions drawn from the observations. Therefore several studies were focused on this issue. The further sections of the report deal with results on the spatial and seasonal variations of ozone concentrations over Europe. Results obtained from in-situ measurements in the boundary layer/lower free troposphere and from vertical soundings in the free troposphere are regarded separately. Finally, trend estimates are presented for ozone as well as for some of its precursors. (orig./KW)

  3. Instrumental variables and Mendelian randomization with invalid instruments

    Science.gov (United States)

    Kang, Hyunseung

    Instrumental variables (IV) methods have been widely used to determine the causal effect of a treatment, exposure, policy, or an intervention on an outcome of interest. The IV method relies on having a valid instrument, a variable that is (A1) associated with the exposure, (A2) has no direct effect on the outcome, and (A3) is unrelated to the unmeasured confounders associated with the exposure and the outcome. However, in practice, finding a valid instrument, especially those that satisfy (A2) and (A3), can be challenging. For example, in Mendelian randomization studies where genetic markers are used as instruments, complete knowledge about instruments' validity is equivalent to complete knowledge about the involved genes' functions. The dissertation explores the theory, methods, and application of IV methods when invalid instruments are present. First, when we have multiple candidate instruments, we establish a theoretical bound whereby causal effects are only identified as long as less than 50% of instruments are invalid, without knowing which of the instruments are invalid. We also propose a fast penalized method, called sisVIVE, to estimate the causal effect. We find that sisVIVE outperforms traditional IV methods when invalid instruments are present both in simulation studies as well as in real data analysis. Second, we propose a robust confidence interval under the multiple invalid IV setting. This work is an extension of our work on sisVIVE. However, unlike sisVIVE which is robust to violations of (A2) and (A3), our confidence interval procedure provides honest coverage even if all three assumptions, (A1)-(A3), are violated. Third, we study the single IV setting where the one IV we have may actually be invalid. We propose a nonparametric IV estimation method based on full matching, a technique popular in causal inference for observational data, that leverages observed covariates to make the instrument more valid. We propose an estimator along with

  4. A random spatial sampling method in a rural developing nation

    Science.gov (United States)

    Michelle C. Kondo; Kent D.W. Bream; Frances K. Barg; Charles C. Branas

    2014-01-01

    Nonrandom sampling of populations in developing nations has limitations and can inaccurately estimate health phenomena, especially among hard-to-reach populations such as rural residents. However, random sampling of rural populations in developing nations can be challenged by incomplete enumeration of the base population. We describe a stratified random sampling method...

  5. Spatial variability of soil hydraulic properties on a steep slope in the loess plateau of China

    OpenAIRE

    Wei Hu; Ming An Shao; Quan Jiu Wang; Jun Fan; Klaus Reichardt

    2008-01-01

    The understanding of the structure of the spatial variability of soil surface hydraulic properties on steep slopes is important for modeling infiltration and runoff processes. The objective of this study was to investigate the spatial variability of these properties on a steep slope of the Loess Plateau in northwest China. A 9600 m² area was systematically sampled in a grid of 106 points spaced 10 m x 10 m. Hydraulic properties were determined with a disc infiltrometer under multiple pressure...

  6. Decadal Climate Variability and the Spatial Organization of Deep Drought

    Science.gov (United States)

    Barros, A. P.; Hodes, J.; Arulraj, M.

    2016-12-01

    Baseflow analysis of long-term (> 50 years) records of river discharge in the SE US followed by Principal Component, Wavelet and Coherence analysis reveals three key modes of space-time variability linked to 1) annual precipitation, 2) the Atlantic Multidecadal Oscillation (AMO) and track and frequency of tropical storms, and 3) physiographic controls separating basins with headwaters in the Appalachians from lowland basins in the Piedmont and in the Coastal Plain. These results highlight regional-scale hydrogeological controls of baseflow connectivity on hydrologic drought beyond topographic surface boundaries.

  7. Spatial and temporal variability of the Black Sea suboxic zone

    Science.gov (United States)

    Glazer, Brian T.; Luther, George W.; Konovalov, Sergey K.; Friederich, Gernot E.; Trouwborst, Robert E.; Romanov, Alexander S.

    2006-08-01

    We coupled an in situ electrochemical analyzer to a CTD to conduct high-resolution, real-time profiling of redox species across the oxic-anoxic transition zone of the Black Sea water column. Voltammetry was performed using gold-amalgam working electrodes to measure simultaneously soluble oxygen and sulfur species (H 2S/HS -, Sx2-, S 8) at a resolution of greater than one measurement per meter. In situ data agreed with measurements made in an on-deck voltammetry flow cell coupled to a pump profiling system, and from water samples collected with conventional CTD rosette bottle casts. In situ voltammetric analyses provided rapid redox information, thus enabling more accurate targeting of specific geochemical features by the CTD rosette package. We observed much less lateral oxygen injection from the Bosphorus in 2003 (less than 95 km from Bosphorus) than in 2001 (up to 150 km). This difference can be attributed to variability in physical processes including seasonal temperature and wind variations between winter conditions (2003) and early summer conditions (2001). Furthermore, suboxic zone thickness varied basin-wide, exhibiting changes in the depth of oxygen extinction (minimum detection limit=3 μM) and sulfide onset (minimum detection limit=30 nM). The density surface for oxygen extinction was more variable than the density for the onset of sulfide. Vertical shifts in oxygen extinction and sulfide onset also were observed at the western central gyre station for seven profiles measured over 21 days in 2003.

  8. Spatial and temporal variability in seasonal snow density

    KAUST Repository

    Bormann, Kathryn J.

    2013-03-01

    Snow density is a fundamental physical property of snowpacks used in many aspects of snow research. As an integral component in the remote sensing of snow water equivalent and parameterisation of snow models, snow density may be used to describe many important features of snowpack behaviour. The present study draws on a significant dataset of snow density and climate observations from the United States, Australia and the former Soviet Union and uses regression-based techniques to identify the dominant climatological drivers for snow densification rates, characterise densification rate variability and estimate spring snow densities from more readily available climate data. Total winter precipitation was shown to be the most prominent driver of snow densification rates, with mean air temperature and melt-refreeze events also found to be locally significant. Densification rate variance is very high at Australian sites, very low throughout the former Soviet Union and between these extremes throughout much of the US. Spring snow densities were estimated using a statistical model with climate variable inputs and best results were achieved when snow types were treated differently. Given the importance of snow density information in many snow-related research disciplines, this work has implications for current methods of converting snow depths to snow water equivalent, the representation of snow dynamics in snow models and remote sensing applications globally. © 2013 Elsevier B.V.

  9. Spatial and temporal variability of rainfall erosivity factor for Switzerland

    Directory of Open Access Journals (Sweden)

    K. Meusburger

    2012-01-01

    Full Text Available Rainfall erosivity, considering rainfall amount and intensity, is an important parameter for soil erosion risk assessment under future land use and climate change. Despite its importance, rainfall erosivity is usually implemented in models with a low spatial and temporal resolution. The purpose of this study is to assess the temporal- and spatial distribution of rainfall erosivity in form of the (Revised Universal Soil Loss Equation R-factor for Switzerland. Time series of 22 yr for rainfall (10 min resolution and temperature (1 h resolution data were analysed for 71 automatic gauging stations distributed throughout Switzerland. Regression-kriging was used to interpolate the rainfall erosivity values of single stations and to generate a map for Switzerland. Latitude, longitude, average annual precipitation, biogeographic units (Jura, Midland, etc., aspect and elevation were used as covariates, of which average annual precipitation, elevation and the biographic unit (Western Central Alps were significant (p<0.01 predictors. The mean value of long-term rainfall erosivity is 1330 MJ mm ha−1 h−1 yr−1 with a range of lowest values of 124 MJ mm ha−1 h−1 yr−1 at an elevated station in Grisons to highest values of 5611 MJ mm ha−1 h−1 yr−1 in Ticino. All stations have highest erosivity values from July to August and lowest values in the winter months. Swiss-wide the month May to October show significantly increasing trends of rainfall erosivity for the observed period (p<0.005. Only in February a significantly decreasing trend of rainfall erosivity is found (p<0.01. The increasing trends of rainfall erosivity in May, September and October when vegetation cover is scarce are likely to enhance soil erosion risk for certain agricultural crops and alpine grasslands in Switzerland.

  10. Spatial variability and sources of ammonia in three European cities

    Science.gov (United States)

    Prevot, Andre S. H.; Elser, Miriam; El Haddad, Imad; Maasikmets, Marek; Bozzetti, Carlo; Robert, Wolf; Richter, Rene; Slowik, Jay; Teinemaa, Erik; Hueglin, Christoph; Baltensperger, Urs

    2017-04-01

    For the assessment of ammonia (NH3) effects on ecosystems and climate, one would ideally know the emission sources and also the spatial distributions. Agriculture is the largest global source of NH3. However traffic, especially gasoline vehicles, biomass burning or waste management can be significant in urban areas. Ambient NH3 measurements using cavity ring-down spectroscopy were performed online at high time resolution on a moving vehicle in three cities: Zurich (Switzerland), Tartu (Estonia) and Tallinn (Estonia). Initial tests showed that a regular inlet cannot be used. A heated line including an auxiliary flow was finally deployed to minimize NH3 adsorption onto the inlet walls. We will present the characterization of the response and recovery times of the measurement system which was used to deconvolve the true NH3 signal from the remaining adsorption-induced hysteresis. Parallel measurements with an Aerodyne aerosol mass spectrometer were used to correct the observed NH3 for the contribution of ammonium nitrate (NH4NO3) which completely evaporated to NH3 and nitric acid (HNO3) in the heated line at the chosen temperature, in contrast to ammonium sulfate. Finally, quantitative measurements of ambient NH3 are possible with sufficient time resolution to enable measurement of NH3 point or line sources with a mobile sampling platform. The NH3 analyzer and the aerosol mass spectrometer were complemented by an aethalometer to measure black carbon and various gas-phase analyzers to enable a complete characterization of the sources of air pollution, including the spatial distributions and the regional background concentrations and urban increments of all measured components. Although at all three locations similar urban increment levels of organic aerosols were attributed to biomass burning and traffic, traffic emissions clearly dominated the city enhancements of NH3, equivalent black carbon (eBC) and carbon dioxide (CO2). Concentration gradients in areas strongly

  11. Automatic Probabilistic Program Verification through Random Variable Abstraction

    Directory of Open Access Journals (Sweden)

    Damián Barsotti

    2010-06-01

    Full Text Available The weakest pre-expectation calculus has been proved to be a mature theory to analyze quantitative properties of probabilistic and nondeterministic programs. We present an automatic method for proving quantitative linear properties on any denumerable state space using iterative backwards fixed point calculation in the general framework of abstract interpretation. In order to accomplish this task we present the technique of random variable abstraction (RVA and we also postulate a sufficient condition to achieve exact fixed point computation in the abstract domain. The feasibility of our approach is shown with two examples, one obtaining the expected running time of a probabilistic program, and the other the expected gain of a gambling strategy. Our method works on general guarded probabilistic and nondeterministic transition systems instead of plain pGCL programs, allowing us to easily model a wide range of systems including distributed ones and unstructured programs. We present the operational and weakest precondition semantics for this programs and prove its equivalence.

  12. Rates of profit as correlated sums of random variables

    Science.gov (United States)

    Greenblatt, R. E.

    2013-10-01

    Profit realization is the dominant feature of market-based economic systems, determining their dynamics to a large extent. Rather than attaining an equilibrium, profit rates vary widely across firms, and the variation persists over time. Differing definitions of profit result in differing empirical distributions. To study the statistical properties of profit rates, I used data from a publicly available database for the US Economy for 2009-2010 (Risk Management Association). For each of three profit rate measures, the sample space consists of 771 points. Each point represents aggregate data from a small number of US manufacturing firms of similar size and type (NAICS code of principal product). When comparing the empirical distributions of profit rates, significant ‘heavy tails’ were observed, corresponding principally to a number of firms with larger profit rates than would be expected from simple models. An apparently novel correlated sum of random variables statistical model was used to model the data. In the case of operating and net profit rates, a number of firms show negative profits (losses), ruling out simple gamma or lognormal distributions as complete models for these data.

  13. The spatial and temporal variability of groundwater recharge in a forested basin in northern Wisconsin

    Science.gov (United States)

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

    2010-01-01

    Recharge varies spatially and temporally as it depends on a wide variety of factors (e.g. vegetation, precipitation, climate, topography, geology, and soil type), making it one of the most difficult, complex, and uncertain hydrologic parameters to quantify. Despite its inherent variability, groundwater modellers, planners, and policy makers often ignore recharge variability and assume a single average recharge value for an entire watershed. Relatively few attempts have been made to quantify or incorporate spatial and temporal recharge variability into water resource planning or groundwater modelling efforts. In this study, a simple, daily soil-water balance model was developed and used to estimate the spatial and temporal distribution of groundwater recharge of the Trout Lake basin of northern Wisconsin for 1996-2000 as a means to quantify recharge variability. For the 5 years of study, annual recharge varied spatially by as much as 18 cm across the basin; vegetation was the predominant control on this variability. Recharge also varied temporally with a threefold annual difference over the 5-year period. Intra-annually, recharge was limited to a few isolated events each year and exhibited a distinct seasonal pattern. The results suggest that ignoring recharge variability may not only be inappropriate, but also, depending on the application, may invalidate model results and predictions for regional and local water budget calculations, water resource management, nutrient cycling, and contaminant transport studies. Recharge is spatially and temporally variable, and should be modelled as such. Copyright ?? 2009 John Wiley & Sons, Ltd.

  14. The Trade-Off between Spatial and Temporal Variabilities in Reciprocal Upper-Limb Aiming Movements of Different Durations

    NARCIS (Netherlands)

    Danion, Frederic; Bongers, Raoul M.; Bootsma, Reinoud J.

    2014-01-01

    The spatial and temporal aspects of movement variability have typically been studied separately. As a result the relationship between spatial and temporal variabilities remains largely unknown. In two experiments we examined the evolution and covariation of spatial and temporal variabilities over

  15. Spatial and temporal variability of periglaciation of the Iberian Peninsula

    Science.gov (United States)

    Oliva, M.; Serrano, E.; Gómez-Ortiz, A.; González-Amuchastegui, M. J.; Nieuwendam, A.; Palacios, D.; Pérez-Alberti, A.; Pellitero-Ondicol, R.; Ruiz-Fernández, J.; Valcárcel, M.; Vieira, G.; Antoniades, D.

    2016-04-01

    Active periglacial processes are currently marginal in the Iberian Peninsula, spatially limited to the highest mountain ranges. However, a wide variety of periglacial deposits and landforms are distributed in low and mid-altitude environments, which shows evidence of past periods of enhanced periglacial activity. The purpose of this paper is to summarize the present knowledge of past periglacial activity in the Iberian Peninsula. The chronological framework takes four main stages into account: the last glaciation, deglaciation, Holocene and present-day processes. This study focuses on the highest massifs (Pyrenees, Cantabrian Range, NW ranges, Central Range, Iberian Range, Sierra Nevada) as well as other lower elevation environments, namely the central Iberian Meseta. During the last glaciation the periglacial belt extended to much lower altitudes than today, reaching current sea level in the NW corner of the Iberian Peninsula. A wide range of geomorphological landforms and sedimentary records is indicative of very active periglacial processes during that phase, in some cases related to permafrost conditions (i.e., block streams, rock glaciers). Most of the inactive landforms and deposits in low and mid-elevations in Iberia are also related to this phase. The massive deglaciation of the Iberian massifs was caused by a gradual increase in temperatures. The deglaciation phase was only interrupted by a short period with colder conditions (the Younger Dryas) that reactivated periglacial processes in the formerly glaciated cirques of the highest lands, specifically with the widespread development of rock glaciers. During the Holocene, periglacial processes have been only active in the highest ranges, shifting in altitude according to temperature regimes and moisture conditions. The Little Ice Age saw the reactivation of periglacial activity in lower elevations than today. Currently, periglacial processes are only active in elevations exceeding 2500 m in the southern

  16. Transforming spatial point processes into Poisson processes using random superposition

    DEFF Research Database (Denmark)

    Møller, Jesper; Berthelsen, Kasper Klitgaaard

    with a complementary spatial point process Y  to obtain a Poisson process X∪Y  with intensity function β. Underlying this is a bivariate spatial birth-death process (Xt,Yt) which converges towards the distribution of (X,Y). We study the joint distribution of X and Y, and their marginal and conditional distributions....... In particular, we introduce a fast and easy simulation procedure for Y conditional on X. This may be used for model checking: given a model for the Papangelou intensity of the original spatial point process, this model is used to generate the complementary process, and the resulting superposition is a Poisson...... process with intensity function β if and only if the true Papangelou intensity is used. Whether the superposition is actually such a Poisson process can easily be examined using well known results and fast simulation procedures for Poisson processes. We illustrate this approach to model checking...

  17. A spatial error model with continuous random effects and an application to growth convergence

    Science.gov (United States)

    Laurini, Márcio Poletti

    2017-10-01

    We propose a spatial error model with continuous random effects based on Matérn covariance functions and apply this model for the analysis of income convergence processes (β -convergence). The use of a model with continuous random effects permits a clearer visualization and interpretation of the spatial dependency patterns, avoids the problems of defining neighborhoods in spatial econometrics models, and allows projecting the spatial effects for every possible location in the continuous space, circumventing the existing aggregations in discrete lattice representations. We apply this model approach to analyze the economic growth of Brazilian municipalities between 1991 and 2010 using unconditional and conditional formulations and a spatiotemporal model of convergence. The results indicate that the estimated spatial random effects are consistent with the existence of income convergence clubs for Brazilian municipalities in this period.

  18. Partitioning the impacts of spatial and climatological rainfall variability in urban drainage modeling

    Science.gov (United States)

    Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

    2017-03-01

    The performance of urban drainage systems is typically examined using hydrological and hydrodynamic models where rainfall input is uniformly distributed, i.e., derived from a single or very few rain gauges. When models are fed with a single uniformly distributed rainfall realization, the response of the urban drainage system to the rainfall variability remains unexplored. The goal of this study was to understand how climate variability and spatial rainfall variability, jointly or individually considered, affect the response of a calibrated hydrodynamic urban drainage model. A stochastic spatially distributed rainfall generator (STREAP - Space-Time Realizations of Areal Precipitation) was used to simulate many realizations of rainfall for a 30-year period, accounting for both climate variability and spatial rainfall variability. The generated rainfall ensemble was used as input into a calibrated hydrodynamic model (EPA SWMM - the US EPA's Storm Water Management Model) to simulate surface runoff and channel flow in a small urban catchment in the city of Lucerne, Switzerland. The variability of peak flows in response to rainfall of different return periods was evaluated at three different locations in the urban drainage network and partitioned among its sources. The main contribution to the total flow variability was found to originate from the natural climate variability (on average over 74 %). In addition, the relative contribution of the spatial rainfall variability to the total flow variability was found to increase with longer return periods. This suggests that while the use of spatially distributed rainfall data can supply valuable information for sewer network design (typically based on rainfall with return periods from 5 to 15 years), there is a more pronounced relevance when conducting flood risk assessments for larger return periods. The results show the importance of using multiple distributed rainfall realizations in urban hydrology studies to capture the

  19. On the Inference of Spatial Continuity using Spartan Random Field Models

    OpenAIRE

    Elogne, Samuel; Hristopulos, Dionisis

    2006-01-01

    This paper addresses the inference of spatial dependence in the context of a recently proposed framework. More specifically, the paper focuses on the estimation of model parameters for a class of generalized Gibbs random fields, i.e., Spartan Spatial Random Fields (SSRFs). The problem of parameter inference is based on the minimization of a distance metric. The latter involves a specifically designed distance between sample constraints (variance, generalized ``gradient'' and ``curvature'') an...

  20. Prioritising Mangrove Ecosystem Services Results in Spatially Variable Management Priorities.

    Directory of Open Access Journals (Sweden)

    Scott C Atkinson

    Full Text Available Incorporating the values of the services that ecosystems provide into decision making is becoming increasingly common in nature conservation and resource management policies, both locally and globally. Yet with limited funds for conservation of threatened species and ecosystems there is a desire to identify priority areas where investment efficiently conserves multiple ecosystem services. We mapped four mangrove ecosystems services (coastal protection, fisheries, biodiversity, and carbon storage across Fiji. Using a cost-effectiveness analysis, we prioritised mangrove areas for each service, where the effectiveness was a function of the benefits provided to the local communities, and the costs were associated with restricting specific uses of mangroves. We demonstrate that, although priority mangrove areas (top 20% for each service can be managed at relatively low opportunity costs (ranging from 4.5 to 11.3% of overall opportunity costs, prioritising for a single service yields relatively low co-benefits due to limited geographical overlap with priority areas for other services. None-the-less, prioritisation of mangrove areas provides greater overlap of benefits than if sites were selected randomly for most ecosystem services. We discuss deficiencies in the mapping of ecosystems services in data poor regions and how this may impact upon the equity of managing mangroves for particular services across the urban-rural divide in developing countries. Finally we discuss how our maps may aid decision-makers to direct funding for mangrove management from various sources to localities that best meet funding objectives, as well as how this knowledge can aid in creating a national mangrove zoning scheme.

  1. High-speed limnology: using advanced sensors to investigate spatial variability in biogeochemistry and hydrology.

    Science.gov (United States)

    Crawford, John T; Loken, Luke C; Casson, Nora J; Smith, Colin; Stone, Amanda G; Winslow, Luke A

    2015-01-06

    Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h(-1)) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial-aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data.

  2. High-speed limnology: Using advanced sensors to investigate spatial variability in biogeochemistry and hydrology

    Science.gov (United States)

    Crawford, John T.; Loken, Luke C.; Casson, Nora J.; Smith, Collin; Stone, Amanda G.; Winslow, Luke A.

    2015-01-01

    Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h–1) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial–aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data.

  3. Spatial and temporal variability of winds in the Northern European Seas

    DEFF Research Database (Denmark)

    Karagali, Ioanna; Badger, Merete; Hahmann, Andrea N.

    2013-01-01

    the spatial and temporal variability of the near-surface wind field, including the inter- and intra-annual variability for resource assessment purposes. This study demonstrates the applicability of satellite observations as the means to provide information useful for selecting areas to perform higher...

  4. Preliminary results of spatial modeling of selected forest health variables in Georgia

    Science.gov (United States)

    Brock Stewart; Chris J. Cieszewski; Eric L. Smith

    2009-01-01

    Variables relating to forest health monitoring, such as mortality, are difficult to predict and model. We present here the results of fitting various spatial regression models to these variables. We interpolate plot-level values compiled from the Forest Inventory and Analysis National Information Management System (FIA-NIMS) data that are related to forest health....

  5. Multi-technique assessment of spatial and temporal variability of methane fluxes in a peat meadow

    NARCIS (Netherlands)

    Hendriks, D.M.D.; van Huissteden, J.; Dolman, A.J.

    2010-01-01

    Methane fluxes measured in a eutrophic peat meadow in The Netherlands dominated by vascular plants showed high spatial and temporal variability. To elucidate this variability as well as the underlying processes, various measurement techniques were used: soil gradients of methane concentrations, the

  6. Spatial variability in forest growth—climate relationships in the Olympic Mountains, Washington.

    Science.gov (United States)

    Jill M. Nakawatase; David L. Peterson

    2006-01-01

    For many Pacific Northwest forests, little is known about the spatial and temporal variability in tree growth - climate relationships, yet it is this information that is needed to predict how forests will respond to future climatic change. We studied the effects of climatic variability on forest growth at 74 plots in the western and northeastern Olympic Mountains....

  7. Small Scale Spatial Variability of Soil Properties and Nutrients in a Ferralsol under Corn

    Science.gov (United States)

    Alves, M. C.; Vidal Vázquez, E.; Pereira de Almeida, V.; Paz-Ferreiro, J.

    2012-04-01

    Spatial variability of soil attributes, both in natural and agricultural landscapes can be rather large. This heterogeneity results from interactions between pedogenetic processes and soil formation factors. In cultivated soils much variability can also occur as a result of land use and management effect, i.e. agricultural systems and practices. Therefore, the main objectives of this work were to investigate the statistical and geostatistical variability of selected properties in a soil cultivated with corn. The experimental work was carried out in Ilha Solteira, São Paulostate, Brazil and the soil was classified as an Oxisol (SSA), i.e. "Latossolo Vermelho" according to the Brazilian Soil Classification System. Eighty-four soil samples were collected at each of two different depths (0-10 and 10-20 cm) from the one-hectare plot studied. Sampling included a combination of grid and nesting schemes in order to allow description of the spatial variability at different scales. Soil texture fractions (sand, silt clay), organic matter content and pH (CaCl2) were determined using standard methods. Moreover, exchangeable bases (Ca, Mg, K), cation exchange capacity (CEC) and P were determined after exchange resin extraction. In the two depths studied, extractable P, K and Mg contents were found to be highly variable (C.V. > 30%), organic matter content and CEC showed a medium variability (C.V. ≈ 15-30%) and base percent saturation and pH exhibited a low variation (map the spatial variability of the study properties. Semivariograms provided a description of the pattern of spatial variability and some insight into possible process affecting the spatial distribution of the assessed soil properties. Sensitivity of nutrient spatial requirements to between field variability was discussed on the basis of the results obtained. In addition, the usefulness of kriging maps to improve and optimize productivity of this soil under intensive agricultural land use was considered.

  8. Tannat grape composition responses to spatial variability of temperature in an Uruguay's coastal wine region

    Science.gov (United States)

    Fourment, Mercedes; Ferrer, Milka; González-Neves, Gustavo; Barbeau, Gérard; Bonnardot, Valérie; Quénol, Hervé

    2017-09-01

    Spatial variability of temperature was studied in relation to the berry basic composition and secondary compounds of the Tannat cultivar at harvest from vineyards located in Canelones and Montevideo, the most important wine region of Uruguay. Monitoring of berries and recording of temperature were performed in 10 commercial vineyards of Tannat situated in the southern coastal wine region of the country for three vintages (2012, 2013, and 2014). Results from a multivariate correlation analysis between berry composition and temperature over the three vintages showed that (1) Tannat responses to spatial variability of temperature were different over the vintages, (2) correlations between secondary metabolites and temperature were higher than those between primary metabolites, and (3) correlation values between berry composition and climate variables increased when ripening occurred under dry conditions (below average rainfall). For a particular studied vintage (2013), temperatures explained 82.5% of the spatial variability of the berry composition. Daily thermal amplitude was found to be the most important spatial mode of variability with lower values recorded at plots nearest to the sea and more exposed to La Plata River. The highest levels in secondary compounds were found in berries issued from plots situated as far as 18.3 km from La Plata River. The increasing knowledge of temperature spatial variability and its impact on grape berry composition contributes to providing possible issues to adapt grapevine to climate change.

  9. Quantification of the spatial variability of rainfall based on a dense network of rain gauges

    DEFF Research Database (Denmark)

    Pedersen, Lisbeth; Jensen, Niels Einar; Christiansen, Lasse Engbo

    2010-01-01

    The spatial variability of rainfall within a single Local Area Weather Radar (LAWR) pixel of 500 x 500 m is quantified based on data from two locations. The work was motivated by the need to quantify the variability on this scale in order to provide an estimate of the uncertainty of using a single...... from an earlier campaign in 2003. The fact that the 20072008 dataset was almost four times larger than the original dataset from 2003 motivated this extended study. Two methods were used to describe the variability: the coefficient of variation and the spatial correlation structure of the rainfall...

  10. Equivalent Conditions of Complete Convergence for Weighted Sums of Sequences of Negatively Dependent Random Variables

    Directory of Open Access Journals (Sweden)

    Mingle Guo

    2012-01-01

    Full Text Available The complete convergence for weighted sums of sequences of negatively dependent random variables is investigated. By applying moment inequality and truncation methods, the equivalent conditions of complete convergence for weighted sums of sequences of negatively dependent random variables are established. These results not only extend the corresponding results obtained by Li et al. (1995, Gut (1993, and Liang (2000 to sequences of negatively dependent random variables, but also improve them.

  11. Fractional calculus approach to the statistical characterization of random variables and vectors

    OpenAIRE

    Cottone, D. ; Paola, M.D.

    2015-01-01

    Fractional moments have been investigated by many authors to represent the density of univariate and bivariate random variables in different contexts. Fractional moments are indeed important when the density of the random variable has inverse power-law tails and, consequently, it lacks integer order moments. In this paper, starting from the Mellin transform of the characteristic function and by fractional calculus method we present a new perspective on the statistics of random variables. Intr...

  12. Spatial Random Field Models Inspired from Statistical Physics with Applications in the Geosciences

    OpenAIRE

    Hristopulos, D. T.

    2005-01-01

    The spatial structure of fluctuations in spatially inhomogeneous processes can be modeled in terms of Gibbs random fields. A local low energy estimator (LLEE) is proposed for the interpolation (prediction) of such processes at points where observations are not available. The LLEE approximates the spatial dependence of the data and the unknown values at the estimation points by low-lying excitations of a suitable energy functional. It is shown that the LLEE is a linear, unbiased, non-exact est...

  13. Spatial and temporal variability of consanguinity in the French Cerdagne

    Directory of Open Access Journals (Sweden)

    Vigo, Marta

    1993-12-01

    Full Text Available In this paper we have studied consanguinity in the population of the French Cerdagne (a Pyrenean valley from 1836 until 1990. Calculation of consanguineous marriage frequencies and of the coefficient a reveals that consanguinity in this population is slightly lower than in other Pyrenean populations. Analysis of variability over time shows a decrease in the consanguinity levels during the above-mentioned period. The consanguinity pattern is similar in all parts of the area considered.

    [es] En este trabajo se ha estudiado la consanguinidad de la comarca pirenaica de la Cerdaña francesa desde 1836 a 1990. El cálculo de las frecuencias de matrimonios consanguíneos y del coeficiente a muestra que la consanguinidad de esta población es inferior, aunque no excesivamente, a la de otras poblaciones pirenaicas. El análisis de la evolución a lo largo del tiempo muestra un descenso de los niveles de consanguinidad durante todo el período estudiado. El modelo de consanguinidad es parecido en todas las zonas del área estudiada.
    [fr] Dans ce travail nous avons étudié la consanguinité de la région de la Cerdagne française dans les Pyrénées depuis 1836 jusqu'à 1990. Le calcule de la fréquence des mariages consanguins et de le coefficient a montrent que la consanguinité de cette population est inférieure, quoique pas excessivement, à celle d'autres populations des Pyrénées. L'analyse de l'évolution à travers le temps a démontré une réduction des niveaux de consanguinité pendant la période étudiée. Ce modèle de consanguinité est semblable dans toutes les zones de la région étudiée.

  14. Dryland Precipitation Variability and Desertification Processes: An Assessment of Spatial and Temporal Rain Variability within the Grand Canyon, Arizona

    Science.gov (United States)

    Caster, J.; Sankey, J. B.; Draut, A.; Fairley, H.; Collins, B. D.; Bedford, D.

    2014-12-01

    In drylands, spatial and temporal rain variability can result from natural climatic cycles, weather patterns, and physiographic factors. In these environments, minor differences in rainfall distribution can invoke significant ecosystem response. The Grand Canyon, Arizona is an iconic dryland environment that receives less than 430 mm of annual rainfall. Recent monitoring of desertification processes at culturally sensitive landscapes in Grand Canyon has examined variability in vegetation, soil crusts, and runoff induced erosion, and identified a lack of knowledge about the nature, drivers and effects of local rainfall variability. We examine rainfall variability using five years of high resolution data collected from 11 weather stations distributed along the Colorado River within Grand Canyon, coupled with 60 years of lower resolution data from National Weather Service Cooperative Observer (NOAA COOP) stations. We characterize spatial and temporal variability in 10-minute rainfall intensity, an important predictor of soil erosion, and daily rainfall depth, an important predictor of biotic cover. We quantify the intensity-daily depth relationship to infer long-term variability in rainfall intensity from the NOAA COOP data that only record rainfall depth. Results confirm findings from previous studies showing a bi-seasonally rainfall pattern with longer duration-lower intensity storms in the cool season and shorter duration-higher intensity storms during the North American Monsoon (NAM).Seasonal differences in rainfall intensity-depth relationships are significant, and suggest NAM storms have greater potential to produce erosion-generating intensities. As NAM rainfall is spatially and inter-annually more variable than cool season rain, yearly rain depths are strongly influenced by NAM fluctuations. These findings will be useful in future efforts to track desertification processes in this and other drylands characterized by complex topography and extreme rainfall

  15. Spatial Variability of Soil Properties and its Impact on Simulated Surface Soil Moisture Patterns

    Science.gov (United States)

    Korres, W.; Bothe, T.; Reichenau, T. G.; Schneider, K.

    2015-12-01

    The spatial variability of soil properties (particle size distribution, PSD, and bulk density, BD) has large effects on the spatial variability of soil moisture and therefore on plant growth and surface exchange processes. In model studies, soil properties from soil maps are considered homogeneous over mapping units, which neglects the small scale variability of soil properties and leads to underestimated small scale variability of simulated soil moisture. This study focuses on the validation of spatial variability of simulated surface soil moisture (SSM) in a winter wheat field in Western Germany using the eco-hydrological simulation system DANUBIA. SSM measurements were conducted at 20 different sampling points and nine different dates in 2008. Frequency distributions of BD and PSD were derived from an independent dataset (n = 486) of soil physical properties from Germany and the USA. In the simulations, BD and PSD were parameterized according to these frequency distributions. Mean values, coefficients of variation and frequency distributions of simulated SSM were compared to the field measurements. Using the heterogeneous model parameterization, up to 76 % of the frequency distribution of the measured SSM can be explained. Furthermore, the results show that BD has a larger impact on the variability of SSM than PSD. The introduced approach can be used for simulating mean SSM and SSM variability more accurately and can form the basis for a spatially heterogeneous parameterization of soil properties in mesoscale models.

  16. Spatial and Seasonal Variability of Extreme Soil Temperature in Croatia

    Science.gov (United States)

    Sviličić, Petra; Vučetić, Višnja

    2015-04-01

    In terms of taking the temperature of the Earth in Croatia, first measurements began in 1898 in Križevci, but systematic measurements of soil temperature started in 1951. Today, the measurements are performed at 55 meteorological stations. The process of setting up, calibration, measurement, input, control and data processing is done entirely within the Meteorological and Hydrological Service. Due to the lack of funds, but also as a consequence of the Homeland War, network density in some areas is very rare, leading to aggravating circumstances during analysis. Also, certain temperature series are incomplete or are interrupted and therefore the number of long-term temperature series is very small. This particularly presents problems in coastal area, which is geographically diversified and is very difficult to do a thorough analysis of the area. Using mercury angle geothermometer daily at 7, 14 and 21 h CET, thermal state of soil is measured at 2, 5, 10, 20, 30, 50 and 100 cm depth. Thermometers are placed on the bare ground within the meteorological circle and facing north to reduce the direct impact of solar radiation. Lack of term measurements is noticed in the analysis of extreme soil temperatures, which are not real extreme values, but derived from three observational times. On the basis of fifty year series (1961-2010) at 23 stations, the analysis of trends of the surface maximal and minimal soil temperature, as well as the appearance of freezing is presented. Trends were determined by Sen's slope estimator, and statistical significance on 5% level was determined using the Mann-Kendall test. It was observed that the variability of the surface maximal soil temperature on an annual and seasonal level is much higher than those for surface minimal soil temperature. Trends in the recent period show a statistically significant increase in the maximal soil temperature in the eastern and the coastal regions, especially in the spring and summer season. Also, the

  17. A Family of Estimators of a Sensitive Variable Using Auxiliary Information in Stratified Random Sampling

    National Research Council Canada - National Science Library

    Nadia Mushtaq; Noor Ul Amin; Muhammad Hanif

    2017-01-01

    In this article, a combined general family of estimators is proposed for estimating finite population mean of a sensitive variable in stratified random sampling with non-sensitive auxiliary variable...

  18. Exploring the spatial variability of soil properties in an Alfisol Catena

    Energy Technology Data Exchange (ETDEWEB)

    Rosemary, F.; Vitharana, U. W. A.; Indraratne, S. P.; Weerasooriya, R.; Mishra, U.

    2016-11-10

    Detailed digital soil maps showing the spatial heterogeneity of soil properties consistent with the landscape are required for site-specific management of plant nutrients, land use planning and process-based environmental modeling. We characterized the short-scale spatial heterogeneity of soil properties in an Alfisol catena in a tropical landscape of Sri Lanka. The impact of different land-uses (paddy, vegetable and un-cultivated) was examined to assess the impact of anthropogenic activities on the variability of soil properties at the catenary level. Conditioned Latin hypercube sampling was used to collect 58 geo-referenced topsoil samples (0–30 cm) from the study area. Soil samples were analyzed for pH, electrical conductivity (EC), organic carbon (OC), cation exchange capacity (CEC) and texture. The spatial correlation between soil properties was analyzed by computing crossvariograms and subsequent fitting of theoretical model. Spatial distribution maps were developed using ordinary kriging. The range of soil properties, pH: 4.3–7.9; EC: 0.01–0.18 dS m–1 ; OC: 0.1–1.37%; CEC: 0.44– 11.51 cmol (+) kg–1 ; clay: 1.5–25% and sand: 59.1–84.4% and their coefficient of variations indicated a large variability in the study area. Electrical conductivity and pH showed a strong spatial correlation which was reflected by the cross-variogram close to the hull of the perfect correlation. Moreover, cross-variograms calculated for EC and Clay, CEC and OC, CEC and clay and CEC and pH indicated weak positive spatial correlation between these properties. Relative nugget effect (RNE) calculated from variograms showed strongly structured spatial variability for pH, EC and sand content (RNE < 25%) while CEC, organic carbon and clay content showed moderately structured spatial variability (25% < RNE < 75%). Spatial dependencies for examined soil properties ranged from 48 to 984 m. The mixed effects model fitting followed by Tukey's post

  19. Eastern Mediterranean Sea Spatial and Temporal Variability of Thermohaline Structure and Circulation Identified from Observational (T, S) Profiles

    Science.gov (United States)

    2015-12-01

    MEDITERRANEAN SEA SPATIAL AND TEMPORAL VARIABILITY OF THERMOHALINE STRUCTURE AND CIRCULATION IDENTIFIED FROM OBSERVATIONAL (T, S) PROFILES by Nuri...MEDITERRANEAN SEA SPATIAL AND TEMPORAL VARIABILITY OF THERMOHALINE STRUCTURE AND CIRCULATION IDENTIFIED FROM OBSERVATIONAL (T, S) PROFILES 5. FUNDING NUMBERS...variability of thermohaline structure and circulation were investigated. Surface depth shows high seasonal temperature variability through the year

  20. Spatial quantum correlations induced by random multiple scattering of quadrature squeezed light

    DEFF Research Database (Denmark)

    Lodahl, Peter

    2007-01-01

    The authors demonstrates that spatial quantum correlations are induced by multiple scattering of quadrature squeezed light through a random medium. As a consequence, light scattered along two different directions by the random medium will not be independent, but be correlated to an extent that ca...... only be described by a quantum mechanical theory for multiple scattering. The spatial quantum correlation is revealed in the fluctuations of the total intensity transmission or reflection through the multiple scattering medium.......The authors demonstrates that spatial quantum correlations are induced by multiple scattering of quadrature squeezed light through a random medium. As a consequence, light scattered along two different directions by the random medium will not be independent, but be correlated to an extent that can...

  1. Spatial and temporal variability of mobile macro-invertebrate assemblages associated to coralligenous habitat

    Directory of Open Access Journals (Sweden)

    R. BEDINI

    2014-03-01

    Full Text Available The study aimed to investigate patterns of spatial and temporal variability of mobile macroinvertebrate assemblages associated to coralligenous habitat. A multi-factorial sampling design was used to test the hypotheses that the structure of assemblages and their spatial and temporal variability changed in relation to substrate inclination. Moreover, macroalgae and sessile macro-invertebrates were also investigated in order to detect eventual relationship between sessile and mobile assemblages. A total of 236 mobile macro-invertebrate taxa were identified, among them 2 Platyhelminthes, 4 Sipuncula, 6 Nemertea, 27 Mollusca, 86 Annelida, 103 Arthropoda, 8 Echinodermata. Results of the study showed that mobile macro-invertebrate assemblages of coralligenous habitat were little influenced by the inclination of substrate and by the morphology of sessile organisms, as patterns of variation were different between the two assemblages. Mobile macro-invertebrate assemblages changed among sampling dates within one year period and they showed high variability at the spatial scale examined.

  2. Monte Carlo simulations of multiphase flow incorporating spatial variability of hydraulic properties

    Science.gov (United States)

    Essaid, Hedeff I.; Hess, Kathryn M.

    1993-01-01

    To study the effect of spatial variability of sediment hydraulic properties on multiphase flow, oil infiltration into a hypothetical glacial outwash aquifer, followed by oil extraction, was simulated using a cross-sectional multiphase flow model. The analysis was simplified by neglecting capillary hysteresis. The first simulation used a uniform mean permeability and mean retention curve. This was followed by 50 Monte Carlo simulations conducted using 50 spatially variable permeability realizations and corresponding spatially variable retention curves. For the type of correlation structure considered in this study, which is similar to that of glacial outwash deposits, use of mean hydraulic properties reproduces the ensemble average oil saturation distribution obtained from the Monte Carlo simulations. However, spatial variability causes the oil saturation distribution in an individual oil lens to differ significantly from that of the mean lens. Oil saturations at a given location may be considerably higher than would be predicted using uniform mean properties. During cleanup by oil extraction from a well, considerably more oil may remain behind in the heterogeneous case than in the spatially uniform case.

  3. Distributed hydrological models for addressing effects of spatial variability of roughness on overland flow

    Directory of Open Access Journals (Sweden)

    Sheng-tang Zhang

    2016-07-01

    Full Text Available In this study, we investigated the origin of the overland flow roughness problem and divided the current overland flow roughness research into three types, as follows: the first type of research takes into account the effects of roughness on the volume and velocity of surface runoff, flood peaks, and the scouring capability of flows, but has not addressed the spatial variability of roughness in detail; the second type of research considers that surface roughness varies spatially with different land usage types, land-cover conditions, and different tillage forms, but lacks a quantitative study of the spatial variability; and the third type of research simply deals with the spatial variability of roughness in each grid cell or land type. We present three shortcomings of the current overland flow roughness research, including (1 the neglect of roughness in distributed hydrological models when simulating the overland flow direction and distribution, (2 the lack of consideration of spatial variability of roughness in hydrological models, and (3 the failure to distinguish the roughness formulas in different overland flow regimes. To solve these problems, distributed hydrological model research should focus on four aspects in regard to overland flow: velocity field observations, flow regime mechanisms, a basic roughness theory, and scale problems.

  4. A Novel Method for Increasing the Entropy of a Sequence of Independent, Discrete Random Variables

    Directory of Open Access Journals (Sweden)

    Mieczyslaw Jessa

    2015-10-01

    Full Text Available In this paper, we propose a novel method for increasing the entropy of a sequence of independent, discrete random variables with arbitrary distributions. The method uses an auxiliary table and a novel theorem that concerns the entropy of a sequence in which the elements are a bitwise exclusive-or sum of independent discrete random variables.

  5. Fuzzy random variables — II. Algorithms and examples for the discrete case

    NARCIS (Netherlands)

    Kwakernaak, H.

    1979-01-01

    The results obtained in part I of the paper are specialized to the case of discrete fuzzy random variables. A more intuitive interpretation is given of the notion of fuzzy random variables. Algorithms are derived for determining expectations, fuzzy probabilities, fuzzy conditional expectations and

  6. Complete Moment Convergence and Mean Convergence for Arrays of Rowwise Extended Negatively Dependent Random Variables

    Directory of Open Access Journals (Sweden)

    Yongfeng Wu

    2014-01-01

    Full Text Available The authors first present a Rosenthal inequality for sequence of extended negatively dependent (END random variables. By means of the Rosenthal inequality, the authors obtain some complete moment convergence and mean convergence results for arrays of rowwise END random variables. The results in this paper extend and improve the corresponding theorems by Hu and Taylor (1997.

  7. Raw and Central Moments of Binomial Random Variables via Stirling Numbers

    Science.gov (United States)

    Griffiths, Martin

    2013-01-01

    We consider here the problem of calculating the moments of binomial random variables. It is shown how formulae for both the raw and the central moments of such random variables may be obtained in a recursive manner utilizing Stirling numbers of the first kind. Suggestions are also provided as to how students might be encouraged to explore this…

  8. CONVERGENCE OF THE FRACTIONAL PARTS OF THE RANDOM VARIABLES TO THE TRUNCATED EXPONENTIAL DISTRIBUTION

    Directory of Open Access Journals (Sweden)

    Bogdan Gheorghe Munteanu

    2013-01-01

    Full Text Available Using the stochastic approximations, in this paper it was studiedthe convergence in distribution of the fractional parts of the sum of random variables to the truncated exponential distribution with parameter lambda. This fact is feasible by means of the Fourier-Stieltjes sequence (FSS of the random variable.

  9. Strong Laws of Large Numbers for Arrays of Rowwise NA and LNQD Random Variables

    Directory of Open Access Journals (Sweden)

    Jiangfeng Wang

    2011-01-01

    Full Text Available Some strong laws of large numbers and strong convergence properties for arrays of rowwise negatively associated and linearly negative quadrant dependent random variables are obtained. The results obtained not only generalize the result of Hu and Taylor to negatively associated and linearly negative quadrant dependent random variables, but also improve it.

  10. Spatial location identification of structural nonlinearities from random data

    Science.gov (United States)

    Josefsson, A.; Magnevall, M.; Ahlin, K.; Broman, G.

    2012-02-01

    With growing demands on product performance and growing complexity of engineering structures, efficient tools for analyzing their dynamic behavior are essential. Linear techniques are well developed and often utilized. However, sometimes the errors due to linearization are too large to be acceptable, making it necessary to take nonlinear effects into account. In many practical applications it is common and reasonable to assume that the nonlinearities are highly local and thus only affect a limited set of spatial coordinates. The purpose of this paper is to present an approach to finding the spatial location of nonlinearities from measurement data, as this may not always be known beforehand. This information can be used to separate the underlying linear system from the nonlinear parts and create mathematical models for efficient parameter estimation and simulation. The presented approach builds on the reverse-path methodology and utilizes the coherence functions to determine the location of nonlinear elements. A systematic search with Multiple Input/Single Output models is conducted in order to find the nonlinear functions that best describe the nonlinear restoring forces. The obtained results indicate that the presented approach works well for identifying the location of local nonlinearities in structures. It is verified by simulation data from a cantilever beam model with two local nonlinearities and experimental data from a T-beam experimental set-up with a single local nonlinearity. A possible drawback is that a relatively large amount of data is needed. Advantages of the approach are that it only needs a single excitation point that response data at varying force amplitudes is not needed and that no prior information about the underlying linear system is needed.

  11. A Family of Estimators of a Sensitive Variable Using Auxiliary Information in Stratified Random Sampling

    Directory of Open Access Journals (Sweden)

    Nadia Mushtaq

    2017-03-01

    Full Text Available In this article, a combined general family of estimators is proposed for estimating finite population mean of a sensitive variable in stratified random sampling with non-sensitive auxiliary variable based on randomized response technique. Under stratified random sampling without replacement scheme, the expression of bias and mean square error (MSE up to the first-order approximations are derived. Theoretical and empirical results through a simulation study show that the proposed class of estimators is more efficient than the existing estimators, i.e., usual stratified random sample mean estimator, Sousa et al (2014 ratio and regression estimator of the sensitive variable in stratified sampling.

  12. Spatial and temporal variability in VOC levels within a commercial retail building.

    Science.gov (United States)

    Eklund, B M; Burkes, S; Morris, P; Mosconi, L

    2008-10-01

    A study was performed to characterize the concentration of dozens of volatile organic compounds (VOCs) at 10 locations within a single large building and track these concentrations over a 2-year period. The study was performed at a shopping center (strip mall) in New Jersey. A total of 130 indoor air samples were collected from 10 retail stores within the shopping center and analyzed for 60 VOCs by US EPA Method TO-15. Indoor concentrations of up to 55,100 microg/m(3) were measured for individual VOCs. The indoor/outdoor ratio (I/O) was as high as 1500 for acetone and exceeded 100 at times for various compounds, indicating that significant indoor air sources were present. A large degree of spatial variability was observed between stores within the building, with concentrations varying by three to four orders of magnitude for some compounds. The spatial variability was dependent on the proximity of the sampling locations to the indoor sources. A large degree of temporal variability also was observed for compounds emitted from indoor sources, but the temporal variability generally did not exceed two standard deviations (sigma). For compounds not emitted from indoor sources at significant rates, both the spatial and temporal variability tended to range within an order of magnitude at each location. Many cross-sectional studies have been published where the levels of volatile organic compounds (VOCs) were measured in indoor air at one or two locations for houses or offices. This study provides longitudinal data for a commercial retail building and also addresses spatial variability within the building. The data suggest that spatial and temporal variability are important considerations for compounds emitted from indoor sources. Elevated concentrations were found in retail spaces with no apparent emission sources due to their proximity to other retail spaces with emission sources.

  13. Fractional calculus approach to the statistical characterization of random variables and vectors

    Science.gov (United States)

    Cottone, Giulio; Di Paola, Mario; Metzler, Ralf

    2010-03-01

    Fractional moments have been investigated by many authors to represent the density of univariate and bivariate random variables in different contexts. Fractional moments are indeed important when the density of the random variable has inverse power-law tails and, consequently, it lacks integer order moments. In this paper, starting from the Mellin transform of the characteristic function and by fractional calculus method we present a new perspective on the statistics of random variables. Introducing the class of complex moments, that include both integer and fractional moments, we show that every random variable can be represented within this approach, even if its integer moments diverge. Applications to the statistical characterization of raw data and in the representation of both random variables and vectors are provided, showing that the good numerical convergence makes the proposed approach a good and reliable tool also for practical data analysis.

  14. Modeling the Spatial and Temporal Variability of Precipitation in Northwest Iran

    Directory of Open Access Journals (Sweden)

    Mohammad Arab Amiri

    2017-12-01

    Full Text Available Spatial and temporal variability analysis of precipitation is an important task in water resources planning and management. This study aims to analyze the spatial and temporal variability of precipitation in the northeastern corner of Iran using data from 24 well-distributed weather stations between 1991 and 2015. The mean annual rainfall, precipitation concentration index (PCI, and their coefficients of variation were mapped to examine the spatial variability of rainfall. An artificial neural network (ANN in association with the inverse distance weighted (IDW method was proposed as a hybrid interpolation method to map the spatial distribution of the detected trends of mean annual rainfall and PCI over the study region. In addition, principal component analysis (PCA was applied to annual precipitation time series in order to verify the results of the analysis using the mean annual rainfall and PCI data sets. Results show high variation in inter-annual precipitation in the west, and a moderate to high intra-annual variability over the whole region. Irregular year-to-year precipitation concentration is also observed in the northeastern and northwestern parts. All in all, the highest variations in inter-annual and intra-annual precipitation occurred over the western and northern parts, while the lowest variability was observed in the eastern part (i.e., the coastal region.

  15. Damage Spreading in Spatial and Small-world Random Boolean Networks

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Qiming [Fermilab; Teuscher, Christof [Portland State U.

    2014-02-18

    The study of the response of complex dynamical social, biological, or technological networks to external perturbations has numerous applications. Random Boolean Networks (RBNs) are commonly used a simple generic model for certain dynamics of complex systems. Traditionally, RBNs are interconnected randomly and without considering any spatial extension and arrangement of the links and nodes. However, most real-world networks are spatially extended and arranged with regular, power-law, small-world, or other non-random connections. Here we explore the RBN network topology between extreme local connections, random small-world, and pure random networks, and study the damage spreading with small perturbations. We find that spatially local connections change the scaling of the relevant component at very low connectivities ($\\bar{K} \\ll 1$) and that the critical connectivity of stability $K_s$ changes compared to random networks. At higher $\\bar{K}$, this scaling remains unchanged. We also show that the relevant component of spatially local networks scales with a power-law as the system size N increases, but with a different exponent for local and small-world networks. The scaling behaviors are obtained by finite-size scaling. We further investigate the wiring cost of the networks. From an engineering perspective, our new findings provide the key design trade-offs between damage spreading (robustness), the network's wiring cost, and the network's communication characteristics.

  16. Impact of precipitation and physical characteristics spatial variabilities on hydrological response at large catchment scale

    Science.gov (United States)

    Rouhier, Laura; Garavaglia, Federico; Le Lay, Matthieu; Le Moine, Nicolas; Ribstein, Pierre; Hendrickx, Frédéric

    2017-04-01

    The spatial variability of the hydrological response is controlled by the interaction of two spatial variabilities: (i) meteorological forcing and (ii) physical characteristics. This work aims at evaluating their relative impact on streamflow modeling throughout a catchment. To tackle the issue, a spatially distributed rainfall-runoff model, named MORDOR-TS, is used. It is a distributed version of the conceptual rainfall-runoff model currently used at Électricité de France (EDF, French electric utility company) for operational applications. The analysis is conducted at large catchment scale, on the French Loire catchment at Gien (35 707 km2) discretised at the maximum into 387 hydrological meshes of about 100km2. Within this one, 106 streamflow time series are available between 1980 and 2012. According to a spatial split-sample test scheme, the data is split into two similar parts: a calibration and a validation sample of 53 gauges each. For a model calibrated on the catchment outlet only, the impact of the rainfall pattern is assessed by testing several aggregations of the precipitation field, from uniform to mesh scale. Then, the spatial physical information is added in two steps. Firstly, the valuable information about interior gauges is taken into account by calibrating a uniform set of parameters on the whole calibration sample. Secondly, the parameters are spatialised to represent the physiographic and pedologic spatial variabilities. Dividing the catchment into sub-basins, there could be as many parameter sets calibrated as there are calibration sites. Regarding the validation sample, the worst performance is provided by a unique lumped model, while the best is given by a set of 53 independent distributed models calibrated on each validation station. The main progress from the worst towards the best case is obtained with the precipitation spatial variability (around 85% of the total progress). Interior gauges and parameters spatialisation bring some

  17. Investigation of Hillslope-Scale Soil Moisture Spatial and Temporal Variability

    Science.gov (United States)

    Martini, E.; Kögler, S.; Wollschlaeger, U.; Zacharias, S.; Werban, U.; Dietrich, P.

    2013-12-01

    Soil moisture is a key state variable that controls hydrological and energy fluxes at various spatial and temporal scales. Understanding and characterizing this variability is one of the major challenges within hydrological sciences. Understanding soil moisture dynamics at the hillslope scale is important to link point- and catchment-scale studies, and for up- and down-scaling of hydrological processes. Nevertheless, deriving generalizable process understanding is not trivial, because of the non-linearity of hillslope response to rainfall. The overall aim of this work was to describe the soil moisture variability at different spatial and temporal scales within a hillslope area with varying topography and soil type but homogeneous land use. Recent developments of wireless sensor technology allow for the long-term monitoring of soil water content with high spatial and temporal resolution, hence facilitate a better understanding of soil moisture spatial variability and the related hydrological processes. Geophysical techniques such as electromagnetic induction (EMI) methods have been widely used during the last decades to map soil properties at the field scale, because of their suitability for fast and precise mapping of soil apparent electrical conductivity (ECa) over large areas. In the Harz Mountains (Central Germany), a 2.5 ha hillslope area was permanently instrumented with a wireless soil moisture and soil temperature monitoring network (SoilNet). It comprises 40 measurement nodes, and 30 of them were located according to a geostatitstical sampling strategy based on ancillary information. At each of the network nodes, 6 sensors measure hourly the soil water content and soil temperature at three depths within the vadose zone. Time-lapse EMI measurements were carried out to map spatial patterns of ECa over several depths. The one-year high-resolution SoilNet time-series is described, and the soil moisture spatial variability is discussed.

  18. Spatial and temporal variability of mean daily wind speeds in the Czech Republic, 1961-2015

    Czech Academy of Sciences Publication Activity Database

    Brázdil, Rudolf; Zahradníček, Pavel; Řezníčková, Ladislava; Tolasz, R.; Štěpánek, Petr; Dobrovolný, Petr

    2017-01-01

    Roč. 72 (2017), s. 197-216 ISSN 0936-577X R&D Projects: GA MŠk(CZ) LO1415; GA ČR(CZ) GA15-11805S Institutional support: RVO:67179843 Keywords : mean daily wind speed * spatial variability * temporal variability * wind stilling * Czech Republic Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.578, year: 2016

  19. Generating Variable and Random Schedules of Reinforcement Using Microsoft Excel Macros

    OpenAIRE

    Bancroft, Stacie L; Bourret, Jason C

    2008-01-01

    Variable reinforcement schedules are used to arrange the availability of reinforcement following varying response ratios or intervals of time. Random reinforcement schedules are subtypes of variable reinforcement schedules that can be used to arrange the availability of reinforcement at a constant probability across number of responses or time. Generating schedule values for variable and random reinforcement schedules can be difficult. The present article describes the steps necessary to writ...

  20. A New Estimator For Population Mean Using Two Auxiliary Variables in Stratified random Sampling

    OpenAIRE

    Singh, Rajesh; Malik, Sachin

    2014-01-01

    In this paper, we suggest an estimator using two auxiliary variables in stratified random sampling. The propose estimator has an improvement over mean per unit estimator as well as some other considered estimators. Expressions for bias and MSE of the estimator are derived up to first degree of approximation. Moreover, these theoretical findings are supported by a numerical example with original data. Key words: Study variable, auxiliary variable, stratified random sampling, bias and mean squa...

  1. Groundwater Variability Across Temporal and Spatial Scales in the Central and Northeastern U.S.

    Science.gov (United States)

    Li, Bailing; Rodell, Matthew; Famiglietti, James S.

    2015-01-01

    Depth-to-water measurements from 181 monitoring wells in unconfined or semi-confined aquifers in nine regions of the central and northeastern U.S. were analyzed. Groundwater storage exhibited strong seasonal variations in all regions, with peaks in spring and lows in autumn, and its interannual variability was nearly unbounded, such that the impacts of droughts, floods, and excessive pumping could persist for many years. We found that the spatial variability of groundwater storage anomalies (deviations from the long term mean) increases as a power function of extent scale (square root of area). That relationship, which is linear on a log-log graph, is common to other hydrological variables but had never before been shown with groundwater data. We describe how the derived power function can be used to determine the number of wells needed to estimate regional mean groundwater storage anomalies with a desired level of accuracy, or to assess uncertainty in regional mean estimates from a set number of observations. We found that the spatial variability of groundwater storage anomalies within a region often increases with the absolute value of the regional mean anomaly, the opposite of the relationship between soil moisture spatial variability and mean. Recharge (drainage from the lowest model soil layer) simulated by the Variable Infiltration Capacity (VIC) model was compatible with observed monthly groundwater storage anomalies and month-to-month changes in groundwater storage.

  2. Concentrated Hitting Times of Randomized Search Heuristics with Variable Drift

    DEFF Research Database (Denmark)

    Lehre, Per Kristian; Witt, Carsten

    2014-01-01

    Drift analysis is one of the state-of-the-art techniques for the runtime analysis of randomized search heuristics (RSHs) such as evolutionary algorithms (EAs), simulated annealing etc. The vast majority of existing drift theorems yield bounds on the expected value of the hitting time for a target...

  3. Some limit theorems for negatively associated random variables

    Indian Academy of Sciences (India)

    Abstract. Let {Xn,n ≥ 1} be a sequence of negatively associated random vari- ables. The aim of this paper is to establish some limit theorems of negatively associated sequence, which include the Lp-convergence theorem and Marcinkiewicz–Zygmund strong law of large numbers. Furthermore, we consider the strong law of ...

  4. Local search methods based on variable focusing for random K -satisfiability

    Science.gov (United States)

    Lemoy, Rémi; Alava, Mikko; Aurell, Erik

    2015-01-01

    We introduce variable focused local search algorithms for satisfiabiliity problems. Usual approaches focus uniformly on unsatisfied clauses. The methods described here work by focusing on random variables in unsatisfied clauses. Variants are considered where variables are selected uniformly and randomly or by introducing a bias towards picking variables participating in several unsatistified clauses. These are studied in the case of the random 3-SAT problem, together with an alternative energy definition, the number of variables in unsatisfied constraints. The variable-based focused Metropolis search (V-FMS) is found to be quite close in performance to the standard clause-based FMS at optimal noise. At infinite noise, instead, the threshold for the linearity of solution times with instance size is improved by picking preferably variables in several UNSAT clauses. Consequences for algorithmic design are discussed.

  5. Addressing Spatial Variability of Surface-Layer Wind with Long-Range WindScanners

    DEFF Research Database (Denmark)

    Berg, Jacob; Vasiljevic, Nikola; Kelly, Mark C.

    2015-01-01

    This paper presents an analysis of mean wind measurements from a coordinated system of long-range WindScanners. From individual scan patterns the mean wind field was reconstructed over a large area, and hence it highlights the spatial variability. From comparison with sonic anemometers, the quality...

  6. Path-averaged rainfall estimation using microwave links : uncertainty due to spatial rainfall variability

    NARCIS (Netherlands)

    Berne, A.D.; Uijlenhoet, R.

    2007-01-01

    Microwave links can be used to estimate the path-averaged rain rate along the link when precipitation occurs. They take advantage of the near proportionality between the specific attenuation affecting the link signal and the rain rate. This paper deals with the influence of the spatial variability

  7. Spatial variability of wildland fuel characteristics in northern Rocky Mountain ecosystems

    Science.gov (United States)

    Robert E. Keane; Kathy Gray; Valentina Bacciu

    2012-01-01

    We investigated the spatial variability of a number of wildland fuel characteristics for the major fuel components found in six common northern Rocky Mountain ecosystems. Surface fuel characteristics of loading, particle density, bulk density, and mineral content were measured for eight fuel components - four downed dead woody fuel size classes (1, 10, 100, 1000 hr),...

  8. A descriptive analysis of temporal and spatial patterns of variability in Puget Sound oceanographic properties

    Science.gov (United States)

    Stephanie Moore; Nathan J. Mantua; Jan A. Newton; Mitsuhiro Kawase; Mark J. Warner; Jonathan P. Kellogg

    2008-01-01

    Temporal and spatial patterns of variability in Puget Sound's oceanographic properties are determined using continuous vertical profile data from two long-term monitoring programs; monthly observations at 16 stations from 1993 to 2002, and biannual observations at 40 stations from 1998 to 2003. Climatological monthly means of temperature, salinity, and density...

  9. [Factors influencing the spatial variability in soil respiration under different land use regimes].

    Science.gov (United States)

    Chen, Shu-Tao; Liu, Qiao-Hui; Hu, Zheng-Hua; Liu, Yan; Ren, Jing-Quan; Xie, Wei

    2013-03-01

    In order to investigate the factors influencing the spatial variability in soil respiration under different land use regimes, field experiments were performed. Soil respiration and relevant environment, vegetation and soil factors were measured. The spatial variability in soil respiration and the relationship between soil respiration and these measured factors were investigated. Results indicated that land use regimes had significant effects on soil respiration. Soil respiration varied significantly (P Soil respiration rates ranged from 1.82 to 7.46 micromol x (m2 x s)(-1), with a difference of 5.62 micromol x (m2 x s)(-1) between the highest and lowest respiration rates. Soil organic carbon was a key factor controlling the spatial variability in soil respiration. In all, ecosystems studied, the relationship between soil respiration and soil organic carbon content can be described by a power function. Soil respiration increased with the increase of soil organic carbon. In forest ecosystem, the relationship between soil respiration and diameter at breast height (DBH) of trees can be explained by a natural logarithmic function. A model composed of soil organic carbon (C, %), available phosphorous (AP, g x kg(-1)) and diameter at breast height (DBH, cm) explained 92.8% spatial variability in soil respiration for forest ecosystems.

  10. Temporal and spatial variability of urban heat island and thermal comfort within the Rotterdam agglomeration

    NARCIS (Netherlands)

    Hove, van B.; Jacobs, C.M.J.; Heusinkveld, B.G.; Elbers, J.A.; Driel, van B.L.; Holtslag, A.A.M.

    2015-01-01

    This paper reports on temporal and spatial variability of local climate and outdoor human thermal comfort within the Rotterdam agglomeration. We analyse three years of meteorological observations (2010–2012) from a monitoring network. Focus is on the atmospheric urban heat island (UHI); the

  11. Spatial Variability of Particle Sizes of Coastal Plain Sands Soils of ...

    African Journals Online (AJOL)

    ... assess the extent of variability, spatial dependence and structure of soil particle sizes, pedological and management implications in the coastal plain sands soils of southeastern Nigeria. Surface (0 – 15cm) and subsurface (15 – 30cm) soil samples were collected at 10m2 intervals (rigid grid nodes) in a 100m by 100m plot ...

  12. Spatial variability of arsenic in relation with some soil forming factors ...

    African Journals Online (AJOL)

    Soil and water samples collected from Bijar area were analyzed in order to investigate arsenic contamination sources and their human risk potentiality assessment. Routine physical and chemical characteristics, iron oxides and arsenic contents were measured in 227 soil samples. Spatial variability of arsenic was ...

  13. Impact of spatial-temporal variations of climatic variables onsummer maize yield in North China Plain

    NARCIS (Netherlands)

    Wu, D.; Yu, Q.; Wang, E.; Hengsdijk, H.

    2008-01-01

    Summer maize (Zea mays L.) is one of the dominant crops in the North China Plain (NCP). Itsgrowth is greatly influenced by the spatial-temporal variation of climatic variables, especially solar radiation, temperature and rainfall. The WOFOST (version 7.1) model was applied to evaluate the impact of

  14. Spatial and Temporal Variability of Macronutrients in a Lime-amended Acid Paddy Field

    Science.gov (United States)

    Vidal Vázquez, E.; Morales, L. A.; Paz González, A.

    2012-04-01

    Soil spatial variability is a natural occurring and or management induced feature that is important for site-specific management practices such as variable rate fertilization. Since rice paddy fields are flat and flooded, apparently they should be homogeneous and subsequently it could be thought that spatial variability in yields and soil attributes might be negligible. However, significant levels of variability in soil general properties, soil nutrients and rice yields have been observed even in small paddy fields. Describing spatial variability of within-field properties is a fundamental first step toward determining management strategies. The aim of this study was to analyze patterns of spatial variability in available macronutrients (NH4+-N, P and K) from an acid rice soil submitted to lime amendment. The experimental site was located at Corrientes province, Argentina. The climate is warm, subtropical with abundant rainfall the whole year round. The study soil was typic Plintacualf. Field trials were set up involving three treatments: control, without lime addition, plus two different dolomite doses of 625 and 1250 kg.ha-1. Before lime addition, soil pH was 3.7; organic matter content was 2.14 % and cation exchange capacity (CEC) was 21.7 Cmolc kg -1. Soil was sampled at three different stages, first before sowing in aerobic conditions and them two more times in anaerobiosis, i.e. by bunch formation and flowering. Ninety-six soil samples per treatment were taken during each of the three sampling periods. NH4+-N, P and K were routinely determined. Spatial variability was assessed through the analysis of semivariograms. Next, kriging maps were constructed and compared for successive sampling dates. The statistical variability of NH4+-N, P and K over the study period was low to medium, depending on treatment and sampling dates. Lime application produced a positive effect on the NH4+ availability at sowing time. Increased Olsen-P availability during sowing and

  15. Prediction of the spatial occurrence of fire induced spalling in concrete slabs using random fields

    Directory of Open Access Journals (Sweden)

    Van Coile R.

    2013-09-01

    Full Text Available As the loss of concrete cover can significantly influence the reliability of concrete elements during fire, spalling should be taken into account when performing reliability calculations. However, the occurrence and spatial variation of spalling are highly uncertain. A first step towards a probabilistic analysis of spalling is made by combining existing deterministic models with a stochastic representation of the concrete tensile strength and by using random fields to model the tensile strength spatial variation.

  16. Variable versus conventional lung protective mechanical ventilation during open abdominal surgery: study protocol for a randomized controlled trial.

    Science.gov (United States)

    Spieth, Peter M; Güldner, Andreas; Uhlig, Christopher; Bluth, Thomas; Kiss, Thomas; Schultz, Marcus J; Pelosi, Paolo; Koch, Thea; Gama de Abreu, Marcelo

    2014-05-02

    General anesthesia usually requires mechanical ventilation, which is traditionally accomplished with constant tidal volumes in volume- or pressure-controlled modes. Experimental studies suggest that the use of variable tidal volumes (variable ventilation) recruits lung tissue, improves pulmonary function and reduces systemic inflammatory response. However, it is currently not known whether patients undergoing open abdominal surgery might benefit from intraoperative variable ventilation. The PROtective VARiable ventilation trial ('PROVAR') is a single center, randomized controlled trial enrolling 50 patients who are planning for open abdominal surgery expected to last longer than 3 hours. PROVAR compares conventional (non-variable) lung protective ventilation (CV) with variable lung protective ventilation (VV) regarding pulmonary function and inflammatory response. The primary endpoint of the study is the forced vital capacity on the first postoperative day. Secondary endpoints include further lung function tests, plasma cytokine levels, spatial distribution of ventilation assessed by means of electrical impedance tomography and postoperative pulmonary complications. We hypothesize that VV improves lung function and reduces systemic inflammatory response compared to CV in patients receiving mechanical ventilation during general anesthesia for open abdominal surgery longer than 3 hours. PROVAR is the first randomized controlled trial aiming at intra- and postoperative effects of VV on lung function. This study may help to define the role of VV during general anesthesia requiring mechanical ventilation. Clinicaltrials.gov NCT01683578 (registered on September 3 3012).

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

    Directory of Open Access Journals (Sweden)

    Ali Akbar Moosavi

    2017-02-01

    calculated in various directions and their surface semivariograms were also prepared to determine the isotropic or anisotropic behavior of each studied soil attributes. Since all of studied soil hydraulic attributes were isotropic variables, therefore, the omnidirectional semivariograms were calculated and different theoretical models were fitted to them. The best fitted semivariogram models were determined using the determination coefficient, R2, and the residual sum of the square, RSS. The parameters of the best fitted models to the experimental semivariograms were also determined. The prediction of study hydraulic attributes was carried out using the parameters of semivariogram models by applying the ordinary Kriging approach. Predictions were also carried out using the Inverse Distance Weighing approach. The results of predictions were compared to each other using the Jackknifing evaluation approach and the suitable prediction method was determined and zoning was performed using the results of introducing prediction method. All of the semivariogram calculations and modeling, prediction of zoning of study hydraulic attributes were performed using the GS+ 5.1 software packages. Results and Discussion: Results indicated that all of the studied soil hydraulic attributes belonged to the weak to moderated spatial correlation classes and the spherical model was the best fitted model for their semivariograms (except for Kfs and D that their best semivariogram models were exponential. The sill of all semivariograms ranged between 0.0003 to 0.419 for the S and Kfs, respectively. The nugget effects and the Range parameter of all semivariograms were located between 0.00015 to 0.108 for the S and Фm, and 211 to 6.4 m for Ks and D, respectively. Results also indicated that 3.5 and 50% of total variation of D and Ks was spatially structured and the other was random, respectively. The spatial correlation classes of near saturated soil hydraulic conductivity and soil hydraulic

  18. Spatial Variability of Soil Characteristics along a Landscape Gradient in Bellanwila-Attidiya Area

    Directory of Open Access Journals (Sweden)

    S. Cooray

    2012-05-01

    Full Text Available Wetlands are comprised of unique components of soil, water and biodiversity which are interconnected. Although water and biodiversity components of wetlands are being somewhat investigated, a very few research have been carried out to investigate soil properties.This study focused on spatial variability of soil chemical and physical parameters in a land use gradient around the Bellanwila-Attidiya Sanctuary, This study was carried out for a period of 3 months and several random soil samples were obtained from all land use areas. Selected physical and chemical properties of soil were analyzed according to the Standard Methods and the GIS maps were developed using ArcView GIS 3.2. The results indicated that all chemical and physical parameters of soil varied across the land use gradient, except for temperature. According to the GIS maps there are apparent variations in distribution of soil properties. On the surface, the highest level of each parameter was found as follows: - NO3- – industrial area, PO4 3- - functioning paddy fields, SO4 2- - residential area, Cl- - residential area, Fe3+ - functioning paddy fields, moisture content - wetland, pH – industrial area, salinity- residential area, electrical conductivity – residential area. At a 1 m depth the pattern was different: NO3- – abandoned paddy fields, PO4 3- – functioning paddy fields, SO4 2- - wetland, Cl- - wetland, Fe3+ - residential area, moisture content - wetland, pH – industrial area, salinity - wetland, electrical conductivity - wetland. The findings clearly exhibit the increases in anthropogenic pressure have resulted in wide-scale alternation of soil properties, at least in the surface soil, across a land use gradient. Managing land use in the watershed of the wetland thus needs adequate attention to conserve this natural ecosystem.

  19. A mobile system for quantifying the spatial variability of the surface energy balance: design and application.

    Science.gov (United States)

    Wohlfahrt, Georg; Tasser, Erich

    2015-05-01

    We present a mobile device for the quantification of the small-scale (a few square meters) spatial variability in the surface energy balance components and several auxiliary variables of short-statured (ecological research questions. The potential of the new device is demonstrated through four selected case studies, which cover the issues of net radiation heterogeneity within the footprint of eddy covariance flux measurements due to (1) land use and (2) slope and aspect of the underlying surface, (3) controls on landscape-scale variability in soil temperature and albedo and (4) the estimation of evapotranspiration based exclusively on measurements with the mobile device.

  20. PaCAL: A Python Package for Arithmetic Computations with Random Variables

    Directory of Open Access Journals (Sweden)

    Marcin Korze?

    2014-05-01

    Full Text Available In this paper we present PaCAL, a Python package for arithmetical computations on random variables. The package is capable of performing the four arithmetic operations: addition, subtraction, multiplication and division, as well as computing many standard functions of random variables. Summary statistics, random number generation, plots, and histograms of the resulting distributions can easily be obtained and distribution parameter ?tting is also available. The operations are performed numerically and their results interpolated allowing for arbitrary arithmetic operations on random variables following practically any probability distribution encountered in practice. The package is easy to use, as operations on random variables are performed just as they are on standard Python variables. Independence of random variables is, by default, assumed on each step but some computations on dependent random variables are also possible. We demonstrate on several examples that the results are very accurate, often close to machine precision. Practical applications include statistics, physical measurements or estimation of error distributions in scienti?c computations.

  1. Determining the spatial variability of crop yields of two different climatic regions in Southwest Germany

    Science.gov (United States)

    Eshonkulov, Ravshan; Poyda, Arne; Ingwersen, Joachim; Streck, Thilo

    2017-04-01

    Assessing the spatial variability of soil physical properties is crucial for agricultural land management. We determined the spatial variability within two agricultural fields in the regions of Kraichgau and Swabian Jura in Southwest Germany. We determined soil physical properties and recorded the temporal development of soil mineral nitrogen (N) and water content as well as that of plant variables (phenology, biomass, leaf area index (LAI), N content, green vegetation fraction (GVF). The work was conducted during the vegetation periods of 2015 and 2016 in winter wheat, and winter rapeseed in Kraichgau and winter barley and silage maize on Swabian Jura. Measurements were taken in three-weekly intervals. On each field, we identified three plots with reduced plant development using high-resolution (RapidEye) satellite images ("cold spots"). Measurements taken on these cold spots were compared to those from five established (long-term) reference plots representing the average field variability. The software EXPERT-N was used to simulate the soil crop system at both cold spots and reference plots. Sensitivity analyses were conducted to identify the most important parameters for the determination of spatial variability in crop growth dynamics.

  2. Spatial random field models inspired from statistical physics with applications in the geosciences

    Science.gov (United States)

    Hristopulos, Dionissios T.

    2006-06-01

    The spatial structure of fluctuations in spatially inhomogeneous processes can be modeled in terms of Gibbs random fields. A local low energy estimator (LLEE) is proposed for the interpolation (prediction) of such processes at points where observations are not available. The LLEE approximates the spatial dependence of the data and the unknown values at the estimation points by low-lying excitations of a suitable energy functional. It is shown that the LLEE is a linear, unbiased, non-exact estimator. In addition, an expression for the uncertainty (standard deviation) of the estimate is derived.

  3. Influence of rainfall spatial variability on rainfall-runoff modelling: Benefit of a simulation approach?

    Science.gov (United States)

    Emmanuel, I.; Andrieu, H.; Leblois, E.; Janey, N.; Payrastre, O.

    2015-12-01

    No consensus has yet been reached regarding the influence of rainfall spatial variability on runoff modelling at catchment outlets. To eliminate modelling and measurement errors, in addition to controlling rainfall variability and both the characteristics and hydrological behaviour of catchments, we propose to proceed by simulation. We have developed a simulation chain that combines a stream network model, a rainfall simulator and a distributed hydrological model (with four production functions and a distributed transfer function). Our objective here is to use this simulation chain as a simplified test bed in order to better understand the impact of the spatial variability of rainfall forcing. We applied the chain to contrasted situations involving catchments ranging from a few tens to several hundreds of square km2, thus corresponding to urban and peri-urban catchments for which surface runoff constitutes the dominant process. The results obtained confirm that the proposed simulation approach is helpful to better understand the influence of rainfall spatial variability on the catchment response. We have shown that significant dispersion exists not only between the various simulation scenarios (defined by a rainfall configuration and a catchment configuration), but also within each simulation scenario. These results show that the organisation of rainfall during the study event over the study catchment plays an important role, leading us to examine rainfall variability indexes capable of summarising the influence of rainfall spatial organisation on the catchment response. Thanks to the simulation chain, we have tested the variability indexes of Zoccatelli et al. (2010) and improved them by proposing two other indexes.

  4. The spatial distribution of known predictors of autism spectrum disorders impacts geographic variability in prevalence in central North Carolina

    Directory of Open Access Journals (Sweden)

    Hoffman Kate

    2012-10-01

    Full Text Available Abstract Background The causes of autism spectrum disorders (ASD remain largely unknown and widely debated; however, evidence increasingly points to the importance of environmental exposures. A growing number of studies use geographic variability in ASD prevalence or exposure patterns to investigate the association between environmental factors and ASD. However, differences in the geographic distribution of established risk and predictive factors for ASD, such as maternal education or age, can interfere with investigations of ASD etiology. We evaluated geographic variability in the prevalence of ASD in central North Carolina and the impact of spatial confounding by known risk and predictive factors. Methods Children meeting a standardized case definition for ASD at 8 years of age were identified through records-based surveillance for 8 counties biennially from 2002 to 2008 (n=532. Vital records were used to identify the underlying cohort (15% random sample of children born in the same years as children with an ASD, n=11,034, and to obtain birth addresses. We used generalized additive models (GAMs to estimate the prevalence of ASD across the region by smoothing latitude and longitude. GAMs, unlike methods used in previous spatial analyses of ASD, allow for extensive adjustment of individual-level risk factors (e.g. maternal age and education when evaluating spatial variability of disease prevalence. Results Unadjusted maps revealed geographic variation in surveillance-recognized ASD. Children born in certain regions of the study area were up to 1.27 times as likely to be recognized as having ASD compared to children born in the study area as a whole (prevalence ratio (PR range across the study area 0.57-1.27; global P=0.003. However, geographic gradients of ASD prevalence were attenuated after adjusting for spatial confounders (adjusted PR range 0.72-1.12 across the study area; global P=0.052. Conclusions In these data, spatial variation of ASD

  5. A Study of the Groundwater Level Spatial Variability in the Messara Valley of Crete

    Science.gov (United States)

    Varouchakis, E. A.; Hristopulos, D. T.; Karatzas, G. P.

    2009-04-01

    The island of Crete (Greece) has a dry sub-humid climate and marginal groundwater resources, which are extensively used for agricultural activities and human consumption. The Messara valley is located in the south of the Heraklion prefecture, it covers an area of 398 km2, and it is the largest and most productive valley of the island. Over-exploitation during the past thirty (30) years has led to a dramatic decrease of thirty five (35) meters in the groundwater level. Possible future climatic changes in the Mediterranean region, potential desertification, population increase, and extensive agricultural activity generate concern over the sustainability of the water resources of the area. The accurate estimation of the water table depth is important for an integrated groundwater resource management plan. This study focuses on the Mires basin of the Messara valley for reasons of hydro-geological data availability and geological homogeneity. The research goal is to model and map the spatial variability of the basin's groundwater level accurately. The data used in this study consist of seventy (70) piezometric head measurements for the hydrological year 2001-2002. These are unevenly distributed and mostly concentrated along a temporary river that crosses the basin. The range of piezometric heads varies from an extreme low value of 9.4 meters above sea level (masl) to 62 masl, for the wet period of the year (October to April). An initial goal of the study is to develop spatial models for the accurate generation of static maps of groundwater level. At a second stage, these maps should extend the models to dynamic (space-time) situations for the prediction of future water levels. Preliminary data analysis shows that the piezometric head variations are not normally distributed. Several methods including Box-Cox transformation and a modified version of it, transgaussian Kriging, and Gaussian anamorphosis have been used to obtain a spatial model for the piezometric head. A

  6. Spatial variability of soil nutrient in paddy plantation: Sites FELCRA Seberang Perak

    Science.gov (United States)

    Kamarudin, H.; Adnan, N. A.; Mispan, M. R.; Athirah. A, A.

    2016-06-01

    The conventional methods currently used for rice cultivation in Malaysia are unable to give maximum yield although the yield production of paddy is increasing. This is due to the conversional method being unable to include soil properties as one of their parameters in agriculture management. Soil properties vary spatially in farm scale due to differences in topography, parent material, vegetation or land management and soil characteristics; also plantation productivity varies significantly over small spatial scales. Knowledge of spatial variability in soil fertility is important for site specific nutrient management. Analysis of spatial variability of soil nutrient of nitrogen (N), phosphorus (P) and potassium (K) were conducted in this study with the aid of GIS (i.e ArcGIS) and statistical softwares. In this study different temporal and depths of soil nutrient were extracted on the field and further analysis of N,P,K content were analysed in the chemical laboratory and using spatially technique in GIS sofware. The result indicated that for the Seberang Perak site of 58 hactares area, N and K are met minimum requirements nutrient content as outlines by the MARDI for paddy cultivation. However, P indicated poor condition in the study area; therefore the soil needs further attention and treatment.

  7. The Spatial Heterogeneity between Japanese Encephalitis Incidence Distribution and Environmental Variables in Nepal

    Science.gov (United States)

    Impoinvil, Daniel E.; Solomon, Tom; Schluter, W. William; Rayamajhi, Ajit; Bichha, Ram Padarath; Shakya, Geeta; Caminade, Cyril; Baylis, Matthew

    2011-01-01

    Background 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. Methods 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. Results 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. Conclusion 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

  8. 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

  9. Field Scale Studies on the Spatial Variability of Soil Quality Indicators in Washington State, USA

    Directory of Open Access Journals (Sweden)

    Jeffrey L. Smith

    2011-01-01

    Full Text Available Arable lands are needed for sustainable agricultural systems to support an ever-growing human population. Soil quality needs to be defined to assure that new land brought into crop production is sustainable. To evaluate soil quality, a number of soil attributes will need to be measured, evaluated, and integrated into a soil-quality index using the multivariable indicator kriging (MVIK procedure. This study was conducted to determine the spatial variability and correlation of indicator parameters on a field scale with respect to soil quality and suitability for use with MVIK. The variability of the biological parameters decreased in the order of respiration > enzyme assays and qCO2 > microbial biomass C. The distribution frequency of all parameters except respiration were normal although the spatial distribution across the landscape was highly variable. The biological parameters showed little correlation with each other when all data points were considered; however, when grouped in smaller sections, the correlations were more consistent with observed patterns across the field. To accurately assess soil quality, and arable land use, consideration of spatial and temporal variability, soil conditions, and other controlling factors must be taken into account.

  10. Spatial and Temporal Variability of Soil CO2 Flux in Sugarcane Green Harvest Systems

    Directory of Open Access Journals (Sweden)

    Rose Luiza Moraes Tavares

    2016-01-01

    Full Text Available ABSTRACT The sugarcane green harvest system, characterized by mechanized harvesting and the absence of crop burning, affects soil quality by increasing crop residue on the soil surface after harvest; thus, it contributes to improving the physical, chemical, and microbiological properties and influences the soil carbon content and CO2 flux (FCO2. This study aimed to evaluate the spatial and temporal variability of soil FCO2 in sugarcane green harvest systems. The experiment was conducted in two areas of sugarcane in São Paulo, Brazil: the first had a 5-year history of sugarcane green harvest (SG-5 and the second had a longer history of 10 years (SG-10. The temporal FCO2 were evaluated in the dry and rainy periods, and spatial variability in the dry period, and related to soil chemical and physical properties, including organic C porosity, bulk density, soil penetration resistance, mean weight diameter of soil aggregates, clay, P, S, Ca, Mg and Fe. The temporal variability indicated no differences between the dry and rainy periods in SG-10, while in SG-5 soil moisture was increased by 33 % in the rainy period. The spatial variability indicated a different pattern from the temporal one, where FCO2 in SG-10 was correlated with soil temperature, air-filled pore space, total porosity, soil moisture, and the Ca and Mg contents; in the SG-5 area, FCO2 was correlated with soil mean weight diameter of soil aggregates and the sulfur content.

  11. [Spatial pattern of soil fertility in Bashan tea garden: a prediction based on environmental auxiliary variables].

    Science.gov (United States)

    Qin, Le-feng; Yang, Chao; Lin, Fen-fang; Yang, Ning; Zheng, Xin-yu; Xu, Hong-wei; Wang, Ke

    2010-12-01

    Taking topographic factors and NDVI as auxiliary variables, and by using regression-kriging method, the spatial variation pattern of soil fertility in Bashan tea garden in the hilly area of Fuyang City was explored. The spatial variability of the soil fertility was mainly attributed to the structural factors such as relative elevation and flat/vertical curvature. The lower the relative elevation, the worse the soil fertility was. The overall soil fertility level was relatively high, and the area with lower soil fertility only accounted for 5% of the total. By using regression-kriging method with relative elevation as auxiliary variable, the prediction accuracy of soil fertility was obviously higher than that by using ordinary kriging method, with the mean error and root mean square error being 0. 028 and 0. 108, respectively. It was suggested that the prediction method used in this paper could fully reflect the effects of environmental variables on soil fertility , improve the prediction accuracy about the spatial pattern of soil fertility, and provide scientific basis for the precise management of tea garden.

  12. Spatial variability of soil potassium in sugarcane areas subjected to the application of vinasse.

    Science.gov (United States)

    De Carvalho, Laércio A; Meurer, Ismael; Da Silva Junior, Carlos A; Santos, Cristiane F B; Libardi, Paulo L

    2014-12-01

    When deposited on land the vinasse can promote improvement in fertility, however, often fertilizer application occurs in areas considered homogeneous, without taking into account the variability of the soil. The objective of this study was to evaluate the effect of vinasse application on potassium content in two classes of soils cultivated with sugarcane, and characterize the spatial variability of soil using geostatistical techniques. In the 2010 and 2011 crop year, soil samples were collected from an experimental grid at 0-0.2 and 0.2-0.4 m depth in three soils cultivated with sugarcane, totaling 90 samplings in each grid, for the determination of pH, calcium (Ca), magnesium (Mg), potassium (K), phosphorus (P), aluminum (Al) and potential acidity (H + Al). The data have been submitted to analysis of descriptive statistics and the K attribute was subjected to geostatistical analysis. The coefficient of variation indicated medium and high variability of K for the three soils. The results showed that the spatial dependence of K increased in depth to FRce and decreased to PHlv, indicating that the attribute could have followed the pattern of distribution of clay in depth. The investigation of the spatial variability of K on the surface and subsurface soils provided the definition of management zones with different levels of fertility, which can be organized into sub-areas for a more efficient management of the resources and the environment.

  13. Spatial variability of soil potassium in sugarcane areas subjected to the application of vinasse

    Directory of Open Access Journals (Sweden)

    LAÉRCIO A. DE CARVALHO

    2014-12-01

    Full Text Available When deposited on land the vinasse can promote improvement in fertility, however, often fertilizer application occurs in areas considered homogeneous, without taking into account the variability of the soil. The objective of this study was to evaluate the effect of vinasse application on potassium content in two classes of soils cultivated with sugarcane, and characterize the spatial variability of soil using geostatistical techniques. In the 2010 and 2011 crop year, soil samples were collected from an experimental grid at 0-0.2 and 0.2-0.4 m depth in three soils cultivated with sugarcane, totaling 90 samplings in each grid, for the determination of pH, calcium (Ca, magnesium (Mg, potassium (K, phosphorus (P, aluminum (Al and potential acidity (H + Al. The data have been submitted to analysis of descriptive statistics and the K attribute was subjected to geostatistical analysis. The coefficient of variation indicated medium and high variability of K for the three soils. The results showed that the spatial dependence of K increased in depth to FRce and decreased to PHlv, indicating that the attribute could have followed the pattern of distribution of clay in depth. The investigation of the spatial variability of K on the surface and subsurface soils provided the definition of management zones with different levels of fertility, which can be organized into sub-areas for a more efficient management of the resources and the environment.

  14. Spatial variability of δ18O-PO4 in soils.

    Science.gov (United States)

    Granger, Steve; Blackwell, Martin; Tamburini, Federica; Guo, Rongrong; Peukert, Sabine; McGrath, Steve

    2014-05-01

    There is growing interest in the potential for using the δ18OPO4 values of different phosphate sources in the environment to enable identification of sources of phosphate in surface waters. The basis of the study is the belief that different sources of PO4 may have different δ18O values. One of the primary sources of PO4 in runoff from agricultural land is the soil itself. Therefore, in order to account for the PO4 derived from soils in surface waters, it is vital that the degree of spatial variability of its δ18O isotopic values are known, in order that suitable soil sampling approaches can be taken when assessing the soil as a source in future studies. A spatial study of the variability of the δ18OPO4 variability of soils collected from a grazed pasture on the North Wyke Farm Platform was carried out incorporating grid-sampling at a range of spatial scales. Results show that variability across a range of scales is minimal, meaning that, in this case, a relatively small number of samples would be required in order to identify accurately the mean δ18OPO4 value of the soil. This study represents an important contribution towards the methodological development studies required in this field of research in order that the full potential of the δ18OPO4 technique for biological and environmental research can be achieved.

  15. Characterization of spatial variability of soil physicochemical properties and its impact on Rhodes grass productivity.

    Science.gov (United States)

    Tola, E; Al-Gaadi, K A; Madugundu, R; Zeyada, A M; Kayad, A G; Biradar, C M

    2017-02-01

    Characterization of soil properties is a key step in understanding the source of spatial variability in the productivity across agricultural fields. A study on a 16 ha field located in the eastern region of Saudi Arabia was undertaken to investigate the spatial variability of selected soil properties, such as soil compaction 'SC', electrical conductivity 'EC', pH (acidity or alkalinity of soil) and soil texture and its impact on the productivity of Rhodes grass (Chloris gayana L.). The productivity of Rhodes grass was investigated using the Cumulative Normalized Difference Vegetation Index (CNDVI), which was determined from Landsat-8 (OLI) images. The statistical analysis showed high spatial variability across the experimental field based on SC, clay and silt; indicated by values of the coefficient of variation (CV) of 22.08%, 21.89% and 21.02%, respectively. However, low to very low variability was observed for soil EC, sand and pH; with CV values of 13.94%, 7.20% and 0.53%, respectively. Results of the CNDVI of two successive harvests showed a relatively similar trend of Rhodes grass productivity across the experimental area (r = 0.74, p = 0.0001). Soil physicochemical layers of a considerable spatial variability (SC, clay, silt and EC) were utilized to delineate the experimental field into three management zones (MZ-1, MZ-2 and MZ-3); which covered 30.23%, 33.85% and 35.92% of the total area, respectively. The results of CNDVI indicated that the MZ-1 was the most productive zone, as its major areas of 50.28% and 45.09% were occupied by the highest CNDVI classes of 0.97-1.08 and 4.26-4.72, for the first and second harvests, respectively.

  16. Spatial variability of detrended soil plow layer penetrometer resistance transect in a sugarcane field

    Science.gov (United States)

    Pérez, Luis D.; Cumbrera, Ramiro; Mato, Juan; Millán, Humberto; Tarquis, Ana M.

    2015-04-01

    Spatial variability of soil properties is relevant for identifying those zones with physical degradation. In this sense, one has to face the problem of identifying the origin and distribution of spatial variability patterns (Brouder et al., 2001; Millán et al., 2012). The objective of the present work was to quantify the spatial structure of soil penetrometer resistance (PR) collected from a transect data consisted of 221 points equidistant. In each sampling, readings were obtained from 0 cm till 70 cm of depth, with an interval of 5 cm (Pérez, 2012). The study was conducted on a Vertisol (Typic Hapludert) dedicated to sugarcane (Saccharum officinarum L.) production during the last sixty years (Pérez et al., 2010). Recently, scaling approach has been applied on the determination of the scaling data properties (Tarquis et al., 2008; Millán et al., 2012; Pérez, 2012). We focus in the Hurst analysis to characterize the data variability for each depth. Previously a detrended analysis was conducted in order to better study de intrinsic variability of the series. The Hurst exponent (H) for each depth was estimated showing a characteristic pattern and differentiating PR evolution in depth. References Brouder, S., Hofmann, B., Reetz, H.F., 2001. Evaluating spatial variability of soil parameters for input management. Better Crops 85, 8-11. Millán, H; AM Tarquís, Luís D. Pérez, Juan Mato, Mario González-Posada, 2012. Spatial variability patterns of some Vertisol properties at a field scale using standardized data. Soil and Tillage Research, 120, 76-84. Pérez, Luís D. 2012. Influencia de la maquinaria agrícola sobre la variabilidad espacial de la compactación del suelo. Aplicación de la metodología geoestadística-fractal. PhD thesis, UPM (In Spanish). Pérez, Luís D., Humberto Millán, Mario González-Posada 2010. Spatial complexity of soil plow layer penetrometer resistance as influenced by sugarcane harvesting: A prefractal approach. Soil and Tillage

  17. New Results on the Sum of Two Generalized Gaussian Random Variables

    KAUST Repository

    Soury, Hamza

    2016-01-06

    We propose in this paper a new method to compute the characteristic function (CF) of generalized Gaussian (GG) random variable in terms of the Fox H function. The CF of the sum of two independent GG random variables is then deduced. Based on this results, the probability density function (PDF) and the cumulative distribution function (CDF) of the sum distribution are obtained. These functions are expressed in terms of the bivariate Fox H function. Next, the statistics of the distribution of the sum, such as the moments, the cumulant, and the kurtosis, are analyzed and computed. Due to the complexity of bivariate Fox H function, a solution to reduce such complexity is to approximate the sum of two independent GG random variables by one GG random variable with suitable shape factor. The approximation method depends on the utility of the system so three methods of estimate the shape factor are studied and presented [1].

  18. Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology

    Science.gov (United States)

    Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, e...

  19. New Results On the Sum of Two Generalized Gaussian Random Variables

    KAUST Repository

    Soury, Hamza

    2015-01-01

    We propose in this paper a new method to compute the characteristic function (CF) of generalized Gaussian (GG) random variable in terms of the Fox H function. The CF of the sum of two independent GG random variables is then deduced. Based on this results, the probability density function (PDF) and the cumulative distribution function (CDF) of the sum distribution are obtained. These functions are expressed in terms of the bivariate Fox H function. Next, the statistics of the distribution of the sum, such as the moments, the cumulant, and the kurtosis, are analyzed and computed. Due to the complexity of bivariate Fox H function, a solution to reduce such complexity is to approximate the sum of two independent GG random variables by one GG random variable with suitable shape factor. The approximation method depends on the utility of the system so three methods of estimate the shape factor are studied and presented.

  20. CONVERGENCE OF THE FRACTIONAL PARTS OF THE RANDOM VARIABLES TO THE TRUNCATED EXPONENTIAL DISTRIBUTION

    National Research Council Canada - National Science Library

    Bogdan Gheorghe Munteanu

    2013-01-01

    Using the stochastic approximations, in this paper it was studiedthe convergence in distribution of the fractional parts of the sum of random variables to the truncated exponential distribution with parameter lambda...

  1. On bounds in Poisson approximation for distributions of independent negative-binomial distributed random variables.

    Science.gov (United States)

    Hung, Tran Loc; Giang, Le Truong

    2016-01-01

    Using the Stein-Chen method some upper bounds in Poisson approximation for distributions of row-wise triangular arrays of independent negative-binomial distributed random variables are established in this note.

  2. A quick and inexpensive method to quantify spatially variable infiltration capacity for artificial recharge ponds using photographic images

    Science.gov (United States)

    Pedretti, Daniele; Barahona-Palomo, Marco; Bolster, Diogo; Sanchez-Vila, Xavier; Fernàndez-Garcia, Daniel

    2012-04-01

    SummaryThe efficiency of artificial surface ponds (SPs) for managed aquifer recharge (MAR) is mostly controlled by the topmost portion of the soil. The most significant soil property controlling recharge is the infiltration capacity (Ic), which is highly variable in space. Assessing its spatial distribution in detail is prohibitive in practice due to high costs, time effort, and limited site accessibility. We present an alternative method for a quick and low-cost quantitative estimation of the spatial distribution of Ic based on satellite images. The fact that hydraulic properties of topsoils and color intensities of digital images depend on some common factors such as moisture content, nature and organization of grains, proportion of iron, and organic and clay content among others, allow us to infer infiltration capacities from color intensities. The relationship between these two variables is site specific and requires calibration. A pilot SP site in Catalonia (Spain) is used as an application example. Two high-resolution digital images of the site are provided at no cost by the local cartographic institute as well as from a popular Internet-based map server. An initial set of local infiltration experiments, randomly located, were found to correlate to color intensities of the digital images. This relationship was then validated against additional independent measurements. The resulting maps of infiltration were then used to estimate the total maximum infiltration of the artificial pond area, the results being consistent with an independent flooding test performed at the site.

  3. Testing of hypothesis of two-dimensional random variables independence on the basis of algorithm of pattern recognition

    Science.gov (United States)

    Lapko, A. V.; Lapko, V. A.; Yuronen, E. A.

    2016-11-01

    The new technique of testing of hypothesis of random variables independence is offered. Its basis is made by nonparametric algorithm of pattern recognition. The considered technique doesn't demand sampling of area of values of random variables.

  4. 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

  5. Mapping spatial variability of soil salinity in a coastal paddy field based on electromagnetic sensors.

    Science.gov (United States)

    Guo, Yan; Huang, Jingyi; Shi, Zhou; Li, Hongyi

    2015-01-01

    In coastal China, there is an urgent need to increase land area for agricultural production and urban development, where there is a rapid growing population. One solution is land reclamation from coastal tidelands, but soil salinization is problematic. As such, it is very important to characterize and map the within-field variability of soil salinity in space and time. Conventional methods are often time-consuming, expensive, labor-intensive, and unpractical. Fortunately, proximal sensing has become an important technology in characterizing within-field spatial variability. In this study, we employed the EM38 to study spatial variability of soil salinity in a coastal paddy field. Significant correlation relationship between ECa and EC1:5 (i.e. r >0.9) allowed us to use EM38 data to characterize the spatial variability of soil salinity. Geostatistical methods were used to determine the horizontal spatio-temporal variability of soil salinity over three consecutive years. The study found that the distribution of salinity was heterogeneous and the leaching of salts was more significant in the edges of the study field. By inverting the EM38 data using a Quasi-3D inversion algorithm, the vertical spatio-temporal variability of soil salinity was determined and the leaching of salts over time was easily identified. The methodology of this study can be used as guidance for researchers interested in understanding soil salinity development as well as land managers aiming for effective soil salinity monitoring and management practices. In order to better characterize the variations in soil salinity to a deeper soil profile, the deeper mode of EM38 (i.e., EM38v) as well as other EMI instruments (e.g. DUALEM-421) can be incorporated to conduct Quasi-3D inversions for deeper soil profiles.

  6. Mapping spatial variability of soil salinity in a coastal paddy field based on electromagnetic sensors.

    Directory of Open Access Journals (Sweden)

    Yan Guo

    Full Text Available In coastal China, there is an urgent need to increase land area for agricultural production and urban development, where there is a rapid growing population. One solution is land reclamation from coastal tidelands, but soil salinization is problematic. As such, it is very important to characterize and map the within-field variability of soil salinity in space and time. Conventional methods are often time-consuming, expensive, labor-intensive, and unpractical. Fortunately, proximal sensing has become an important technology in characterizing within-field spatial variability. In this study, we employed the EM38 to study spatial variability of soil salinity in a coastal paddy field. Significant correlation relationship between ECa and EC1:5 (i.e. r >0.9 allowed us to use EM38 data to characterize the spatial variability of soil salinity. Geostatistical methods were used to determine the horizontal spatio-temporal variability of soil salinity over three consecutive years. The study found that the distribution of salinity was heterogeneous and the leaching of salts was more significant in the edges of the study field. By inverting the EM38 data using a Quasi-3D inversion algorithm, the vertical spatio-temporal variability of soil salinity was determined and the leaching of salts over time was easily identified. The methodology of this study can be used as guidance for researchers interested in understanding soil salinity development as well as land managers aiming for effective soil salinity monitoring and management practices. In order to better characterize the variations in soil salinity to a deeper soil profile, the deeper mode of EM38 (i.e., EM38v as well as other EMI instruments (e.g. DUALEM-421 can be incorporated to conduct Quasi-3D inversions for deeper soil profiles.

  7. The Sum and Difference of Two Lognormal Random Variables

    Directory of Open Access Journals (Sweden)

    C. F. Lo

    2012-01-01

    Full Text Available We have presented a new unified approach to model the dynamics of both the sum and difference of two correlated lognormal stochastic variables. By the Lie-Trotter operator splitting method, both the sum and difference are shown to follow a shifted lognormal stochastic process, and approximate probability distributions are determined in closed form. Illustrative numerical examples are presented to demonstrate the validity and accuracy of these approximate distributions. In terms of the approximate probability distributions, we have also obtained an analytical series expansion of the exact solutions, which can allow us to improve the approximation in a systematic manner. Moreover, we believe that this new approach can be extended to study both (1 the algebraic sum of N lognormals, and (2 the sum and difference of other correlated stochastic processes, for example, two correlated CEV processes, two correlated CIR processes, and two correlated lognormal processes with mean-reversion.

  8. Spatial variability studies in São Paulo, Brazil along the last twenty five years

    Directory of Open Access Journals (Sweden)

    Sidney Rosa Vieira

    2010-01-01

    Full Text Available Soil properties vary in space due to many causes. For this reason it is wise to know the magnitude and behaviour of the variability for adequate data analysis and decision making. Our work on spatial variability of soil properties in São Paulo, Brazil began in 1982 with a very simple soil sampling in a small field. Much progress has been made since then on sampling designs, field equipment and methods, and mostly on computation equipment and softwares. This paper reports the results corresponding to some aspects of this progress, as far as the field, analysis and computation work are concerned. The objective of this study was to illustrate the use of geostatistics in data analysis for three sampling conditions on long term no-tillage system. The analysis is done on a wide range of field scales, variables, sampling schemes as well as repeating sampling scheme for the same variable in different years. Semivariograms are compared for the same variables in different scales and sampling dates and depths as to provide a guide for sampling spacing and number of samples. Normalized crop yield parameters for many years are used in the discussion of time variability and on the use of yield maps to locate management zones. The time of the year in which measurements of soil physical properties are made affected the results both in terms of descriptive statistical and spatial dependence parameters. Crop yields changed (soybean decrease and maize increase with time of no-tillage but the real cause was not identified. The length of time with no-tillage affected the range of dependence for the main crops (increased for soybean, maize and oats and therefore increased the size of the homogeneous management zones. The evolution of the sampling grid from 20 m with 63 sampling points to 10 m with 302 sampling points allowed for a much better knowledge of the spatial variability of crop yields but it had the reverse effect on the spatial variability of soil physical

  9. Importance of variable time-step algorithms in spatial kinetics calculations

    Energy Technology Data Exchange (ETDEWEB)

    Aviles, B.N.

    1994-12-31

    The use of spatial kinetics codes in conjunction with advanced thermal-hydraulics codes is becoming more widespread as better methods and faster computers appear. The integrated code packages are being used for routine nuclear power plant design and analysis, including simulations with instrumentation and control systems initiating system perturbations such as rod motion and scrams. As a result, it is important to include a robust variable time-step algorithm that can accurately and efficiently follow widely varying plant neutronic behavior. This paper describes the variable time-step algorithm in SPANDEX and compares the automatic time-step scheme with a more traditional fixed time-step scheme.

  10. Land agroecological quality assessment in conditions of high spatial soil cover variability at the Pereslavskoye Opolye.

    Science.gov (United States)

    Morev, Dmitriy; Vasenev, Ivan

    2015-04-01

    The essential spatial variability is mutual feature for most natural and man-changed soils at the Central region of European territory of Russia. The original spatial heterogeneity of forest soils has been further complicated by a specific land-use history and human impacts. For demand-driven land-use planning and decision making the quantitative analysis and agroecological interpretation of representative soil cover spatial variability is an important and challenging task that receives increasing attention from private companies, governmental and environmental bodies. Pereslavskoye Opolye is traditionally actively used in agriculture due to dominated high-quality cultivated soddy-podzoluvisols which are relatively reached in organic matter (especially for conditions of the North part at the European territory of Russia). However, the soil cover patterns are often very complicated even within the field that significantly influences on crop yield variability and have to be considered in farming system development and land agroecological quality evaluation. The detailed investigations of soil regimes and mapping of the winter rye yield have been carried in conditions of two representative fields with slopes sharply contrasted both in aspects and degrees. Rye biological productivity and weed infestation have been measured in elementary plots of 0.25 m2 with the following analysis the quality of the yield. In the same plot soil temperature and moisture have been measured by portable devices. Soil sampling was provided from three upper layers by drilling. The results of ray yield detailed mapping shown high differences both in average values and within-field variability on different slopes. In case of low-gradient slope (field 1) there is variability of ray yield from 39.4 to 44.8 dt/ha. In case of expressed slope (field 2) the same species of winter rye grown with the same technology has essentially lower yield and within-field variability from 20 to 29.6 dt/ha. The

  11. Characterization of spatial soil variability and its effect on Millet yield on Sudano-Sahelian coversands in SW Niger

    NARCIS (Netherlands)

    Voortman, R.L.; Brouwer, J.; Albersen, P.J.

    2004-01-01

    Very local spatial soil variability on Sudano-Sahelian coversands hampers the interpretation of agronomic research and is an obstacle for the dissemination of research findings. In an earlier paper, we specifically accounted for this spatial soil variability: Using novel tools for data exploration,

  12. Spatial variability of surface fuels in treated and untreated ponderosa pine forests of the southern Rocky Mountains

    Science.gov (United States)

    Emma Vakili; Chad M. Hoffman; Robert E. Keane; Wade T. Tinkham; Yvette Dickinson

    2016-01-01

    There is growing consensus that spatial variability in fuel loading at scales down to 0.5 m may govern fire behaviour and effects. However, there remains a lack of understanding of how fuels vary through space in wildland settings. This study quantifies surface fuel loading and its spatial variability in ponderosa pine sites before and after fuels treatment in the...

  13. Temporal and spatial variability of wind resources in the United States as derived from the Climate Forecast System Reanalysis

    Science.gov (United States)

    Lejiang Yu; Shiyuan Zhong; Xindi Bian; Warren E. Heilman

    2015-01-01

    This study examines the spatial and temporal variability of wind speed at 80m above ground (the average hub height of most modern wind turbines) in the contiguous United States using Climate Forecast System Reanalysis (CFSR) data from 1979 to 2011. The mean 80-m wind exhibits strong seasonality and large spatial variability, with higher (lower) wind speeds in the...

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

    Science.gov (United States)

    Li, Jin; Tran, Maggie; Siwabessy, Justy

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jin Li

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

  16. Fine scale spatial variability of microbial pesticide degradation in soil: scales, controlling factors, and implications

    Directory of Open Access Journals (Sweden)

    Arnaud eDechesne

    2014-12-01

    Full Text Available Pesticide biodegradation is a soil microbial function of critical importance for modern agriculture and its environmental impact. While it was once assumed that this activity was homogeneously distributed at the field scale, mounting evidence indicates that this is rarely the case. Here, we critically examine the literature on spatial variability of pesticide biodegradation in agricultural soil. We discuss the motivations, methods, and main findings of the primary literature. We found significant diversity in the approaches used to describe and quantify spatial heterogeneity, which complicates inter-studies comparisons. However, it is clear that the presence and activity of pesticide degraders is often highly spatially variable with coefficients of variation often exceeding 50% and frequently displays nonrandom spatial patterns. A few controlling factors have tentatively been identified across pesticide classes: they include some soil characteristics (pH and some agricultural management practices (pesticide application, tillage, while other potential controlling factors have more conflicting effects depending on the site or the pesticide. Evidence demonstrating the importance of spatial heterogeneity on the fate of pesticides in soil has been difficult to obtain but modelling and experimental systems that do not include soil’s full complexity reveal that this heterogeneity must be considered to improve prediction of pesticide biodegradation rates or of leaching risks. Overall, studying the spatial heterogeneity of pesticide biodegradation is a relatively new field at the interface of agronomy, microbial ecology, and geosciences and a wealth of novel data is being collected from these different disciplinary perspectives. We make suggestions on possible avenues to take full advantage of these investigations for a better understanding and prediction of the fate of pesticides in soil.

  17. Spatial variability of soil aggregate stability at the scale of an agricultural region in Tunisia

    OpenAIRE

    Annabi, M.; Raclot, Damien; Bahri, H.; Bailly, J. S.; Gomez, Cécile; Le Bissonnais, Y.

    2017-01-01

    International audience; Soil aggregate stability is a key factor in soil resistance to water erosion, which is a threat to soils in a large part of northern Tunisia. The analysis of the spatial variability of soil aggregate stability provides both agronomic and environmentally useful information. However, extensive measurements of soil aggregate stability remain tedious and expensive. This study explores two different approaches as alternative to measurements of soil aggregate stability. One ...

  18. Distribution patterns of epilithic diatoms along climatic, spatial and physicochemical variables in the Baltic Sea

    OpenAIRE

    Virta, Leena; Soininen, Janne

    2017-01-01

    Abstract The species richness and community composition of the diatom communities were studied in the Baltic Sea, Northern Europe, to enhance knowledge about the diversity of these organisms in a brackish water ecosystem. Many organisms in the Baltic Sea have been studied extensively, but studies investigating littoral diatoms are scarce. The goal of this study was to examine the importance of climatic, spatial and water physicochemical variables as drivers of epilithic diato...

  19. Distribution patterns of epilithic diatoms along climatic, spatial and physicochemical variables in the Baltic Sea

    OpenAIRE

    Virta, Leena; Soininen, Janne

    2017-01-01

    The species richness and community composition of the diatom communities were studied in the Baltic Sea, Northern Europe, to enhance knowledge about the diversity of these organisms in a brackish water ecosystem. Many organisms in the Baltic Sea have been studied extensively, but studies investigating littoral diatoms are scarce. The goal of this study was to examine the importance of climatic, spatial and water physicochemical variables as drivers of epilithic diatoms in the Gulf of Finland ...

  20. Spatial variability and stocks of soil organic carbon in the Gobi desert of Northwestern China.

    Directory of Open Access Journals (Sweden)

    Pingping Zhang

    Full Text Available Soil organic carbon (SOC plays an important role in improving soil properties and the C global cycle. Limited attention, though, has been given to assessing the spatial patterns and stocks of SOC in desert ecosystems. In this study, we quantitatively evaluated the spatial variability of SOC and its influencing factors and estimated SOC storage in a region (40 km2 of the Gobi desert. SOC exhibited a log-normal depth distribution with means of 1.6, 1.5, 1.4, and 1.4 g kg(-1 for the 0-10, 10-20, 20-30, and 30-40 cm layers, respectively, and was moderately variable according to the coefficients of variation (37-42%. Variability of SOC increased as the sampling area expanded and could be well parameterized as a power function of the sampling area. Significant correlations were detected between SOC and soil physical properties, i.e. stone, sand, silt, and clay contents and soil bulk density. The relatively coarse fractions, i.e. sand, silt, and stone contents, had the largest effects on SOC variability. Experimental semivariograms of SOC were best fitted by exponential models. Nugget-to-sill ratios indicated a strong spatial dependence for SOC concentrations at all depths in the study area. The surface layer (0-10 cm had the largest spatial dependency compared with the other layers. The mapping revealed a decreasing trend of SOC concentrations from south to north across this region of the Gobi desert, with higher levels close to an oasis and lower levels surrounded by mountains and near the desert. SOC density to depths of 20 and 40 cm for this 40 km2 area was estimated at 0.42 and 0.68 kg C m(-2, respectively. This study provides an important contribution to understanding the role of the Gobi desert in the global carbon cycle.

  1. Spatial and temporal CH4 flux variability in a shallow tropical floodplain lake, Pantanal, South America

    Science.gov (United States)

    Peixoto, R.; Enrich Prast, A.; Silva, E. C.; Pontual, L.; Marotta, H.; Pinho, L.; Bastviken, D.

    2012-04-01

    Spatial and temporal CH4 flux variability in a shallow tropical floodplain lake, Pantanal, South America Peixoto, R, Enrich-Prast, A., Silva, E. C., Pontual, L., Marotta, H., Pinho, L. Q. and Bastviken, D. Methane (CH4) is an important greenhouse gas produced during anaerobic decomposition of organic matter (OM). It can play a significant role in carbon emissions from tropical aquatic ecosystems to the atmosphere and have a substantial participation in greenhouse gas balances. However, most studies report low numbers of short-term (≤ 24h) measurements in each system and the spatial and temporal variability is poorly understood. In this study we analyzed the temporal and spatial variability of CH4 emissions from a shallow Pantanal lake. Pantanal is the world's largest savanna tropical floodplain with a significant input of organic matter from the drainage area around and an annual inundation pulse. Methane fluxes were measured in September 2008 with floating chambers over 24 hour periods for five consecutive days. We used > 20 chambers along transects from the marginal vegetated regions of the lake to the central parts of the lake. Methane fluxes were determined as described by Bastviken et al. 2010 (doi: 10.1021/es1005048). There was no significant difference of methane fluxes among sampling days. Methane fluxes at the vegetated area and the margin were significantly higher than at central parts of the lake showing clearly the importance of different compartments within lakes. This study indicates that a) 24 hour measurements may be representative for time perspectives of a week given similar weather conditions, while b) spatial variability within lakes must be considered to correctly evaluate CH4 emissions from aquatic systems.

  2. Fine scale spatial variability of microbial pesticide degradation in soil: scales, controlling factors, and implications

    OpenAIRE

    Arnaud eDechesne; Nora eBadawi; Jens eAamand; Smets, Barth F.

    2014-01-01

    Pesticide biodegradation is a soil microbial function of critical importance for modern agriculture and its environmental impact. While it was once assumed that this activity was homogeneously distributed at the field scale, mounting evidence indicates that this is rarely the case. Here, we critically examine the literature on spatial variability of pesticide biodegradation in agricultural soil. We discuss the motivations, methods, and main findings of the primary literature. We found signifi...

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

    Science.gov (United States)

    Chen, Zhicheng; Bao, Yuequan; Li, Hui

    2016-04-01

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

  4. Spatial variability of chemical and physical attributes of dystrophic Red-Yellow Latosol in no tillage

    Directory of Open Access Journals (Sweden)

    João Vidal de Negreiros Neto

    2014-02-01

    Full Text Available Knowledge of spatial variability in chemical and physical properties of the soil is very important, especially for precision agriculture. Geostatistics is seeking to improve techniques that can enable the correct and responsible use of soil. So during the agricultural year 2011/2012 in an area of direct planting the corn crop in the municipality of Gurupi (TO, in the Brazilian Cerrado, aimed to analyze the spatial variability of chemical and physical properties in a Typic Dystrophic tillage. Was installed sampling grid for the collection of soil, with 100 sampling points in an area of 1755m2. The contents of available phosphorus, organic matter, pH (H2O, concentrations of K +, Ca2+, Mg2+, the sum of values and base saturation (BS, V at depths of 0-0.20 m, and resistance to penetration (RP at depths 0-0.05 m, 0.05-0.10 m, 0.10-0.20 m and 0.20-0.40 m and bulk density (Ds. We conducted a descriptive analysis classic, with the aid of statistical software ASSISTAT, and then were modeled semivariograms for all attributes, resulting in their cross-validation and kriging maps. The chemical and physical properties of soil, except the base saturation (V, spatial dependence. Probably the discontinuity of the spatial dependence of Vvalue, is due to fertility management over the years.

  5. Modeling inter-subject variability in fMRI activation location: A Bayesian hierarchical spatial model

    Science.gov (United States)

    Xu, Lei; Johnson, Timothy D.; Nichols, Thomas E.; Nee, Derek E.

    2010-01-01

    Summary The aim of this work is to develop a spatial model for multi-subject fMRI data. There has been extensive work on univariate modeling of each voxel for single and multi-subject data, some work on spatial modeling of single-subject data, and some recent work on spatial modeling of multi-subject data. However, there has been no work on spatial models that explicitly account for inter-subject variability in activation locations. In this work, we use the idea of activation centers and model the inter-subject variability in activation locations directly. Our model is specified in a Bayesian hierarchical frame work which allows us to draw inferences at all levels: the population level, the individual level and the voxel level. We use Gaussian mixtures for the probability that an individual has a particular activation. This helps answer an important question which is not addressed by any of the previous methods: What proportion of subjects had a significant activity in a given region. Our approach incorporates the unknown number of mixture components into the model as a parameter whose posterior distribution is estimated by reversible jump Markov Chain Monte Carlo. We demonstrate our method with a fMRI study of resolving proactive interference and show dramatically better precision of localization with our method relative to the standard mass-univariate method. Although we are motivated by fMRI data, this model could easily be modified to handle other types of imaging data. PMID:19210732

  6. Summer temperature and spatial variability of all-cause mortality in Surat city, India

    Directory of Open Access Journals (Sweden)

    S K Rathi

    2017-01-01

    Full Text Available Background: Ample information is available on extreme heat associated mortality for few Indian cities, but scant literature is available on effect of temperature on spatial variability of all-cause mortality for coastal cities. Objective: To assess the effect of daily maximum temperature, relative humidity and heat index on spatial variability of all-cause mortality for summer months (March to May from 2014 to 2015 for the urban population of Surat (coastal city. Materials and Methods: Retrospective analysis of the all-cause mortality data with temperature and humidity was performed on a total of 9,237 deaths for 184 summer days (2014-2015. Climatic and all-cause mortality data were obtained through Tutiempo website and Surat Municipal Corporation respectively. Bivariate analysis performed through SPSS. Observations: Mean daily mortality was estimated at 50.2 ± 8.5 for the study period with a rise of 20% all-cause mortality at temperature ≥ 40°C and rise of 10% deaths per day during extreme danger level (HI: > 54°C days. Spatial (Zone wise analysis revealed rise of 61% all-cause mortality for Southeast and 30% for East zones at temperature ≥ 40°C. Conclusions: All-cause mortality increased on high summer temperature days. Presence of spatial variation in all-cause mortality provided the evidence for high risk zones. Findings may be helpful in designing the interventions at micro level.

  7. Spatial variability of vegetation index and soil properties in an integrated crop-livestock system

    Directory of Open Access Journals (Sweden)

    Alberto C. de C. Bernardi

    Full Text Available ABSTRACT The knowledge of soil property spatial variability is useful for determining the rational use of inputs, such as the site-specific application of lime and fertilizer. The objective of this study was to evaluate the vegetation index and spatial variability of physical and chemical soil properties in an integrated crop-livestock system (ICLS. Soil samples were taken from a 6.9 ha area in a regular hexagon grid at 0-0.20 m depths. Soil P, K, Ca, Mg, and cation exchange capacity - CEC; base saturation; clay and sand were analyzed. Soil electrical conductivity (ECa was measured with a contact sensor. The site was evaluated at the end of the corn season (April and during forage production (October using Landsat 5 images, remote sensing techniques and a geographic information system (GIS. Results showed that the normalized difference vegetation index (NDVI was associated with ECa and soil parameters, indicating crop and pasture variations in the ICLS. Geostatistics and GIS were effective tools for collecting data regarding the spatial variability of soil and crop indicators, identifying variation trends in the data, and assisting data interpretation to determine adequate management strategies.

  8. Spatially Variable Geothermal Heat Flux in West Antarctica: Evidence and Implications

    Science.gov (United States)

    Begeman, Carolyn Branecky; Tulaczyk, Slawek M.; Fisher, Andrew T.

    2017-10-01

    Geothermal heat flux (GHF) is an important part of the basal heat budget of continental ice sheets. The difficulty of measuring GHF below ice sheets has directly hindered progress in the understanding of ice sheet dynamics. We present a new GHF measurement from below the West Antarctic Ice Sheet, made in subglacial sediment near the grounding zone of the Whillans Ice Stream. The measured GHF is 88 ± 7 mW m-2, a relatively high value compared to other continental settings and to other GHF measurements along the eastern Ross Sea of 55 mW m-2 and 69 ± 21 mW m-2 but within the range of regional values indicated by geophysical estimates. The new GHF measurement was made 100 km from the only other direct GHF measurement below the ice sheet, which was considerably higher at 285 ± 80 mW m-2, suggesting spatial variability that could be explained by shallow magmatic intrusions or the advection of heat by crustal fluids. Analytical calculations suggest that spatial variability in GHF exceeds spatial variability in the conductive heat flux through ice along the Siple Coast. Accurate GHF measurements and high-resolution GHF models may be necessary to reliably predict ice sheet evolution, including responses to ongoing and future climate change.

  9. Characterization of spatial variability of the relative chlorophyll index in wheat crop

    Directory of Open Access Journals (Sweden)

    Osmar Henrique de Castro Pias

    2014-09-01

    Full Text Available Site-specific nitrogen application, based on relative chlorophyll index from leaves, may provide many economic and environmental benefits, however, the knowledge on sampling methodologies is still incipient. Thus, this study aimed to evaluate the use of different sampling grids to characterize the spatial variability of relative chlorophyll index of leaves from wheat crop and elaborate thematic maps for site-specific nitrogen application. For determining the relative chlorophyll index, a CFL 1030 chlorophyll meter was used on a regular sampling grid of 10 m x 10 m with 472 sampling points. Based on the initial sampling grid, by using the point elimination method, the simulation was performed in the following sampling grids: 10 m x 20 m; 20 m x 20 m; 20 m x 30 m; 30 m x 30 m; 30 m x 40 m; and 40 m x 40 m. The increase of the sampling grid reduced the diagnostic accuracy of relative chlorophyll index in wheat leaves. As the sampling grid increased, the maps became more general and information on the spatial variability of the relative chlorophyll index were lost. Sampling grids smaller or equal to 20 m x 20 m were effective to detect the spatial variability of the relative chlorophyll index in wheat leaves and enable the elaboration of thematic maps for site-specific nitrogen application.

  10. Separating variability in healthcare practice patterns from random error.

    Science.gov (United States)

    Thomas, Laine E; Schulte, Phillip J

    2018-01-01

    Improving the quality of care that patients receive is a major focus of clinical research, particularly in the setting of cardiovascular hospitalization. Quality improvement studies seek to estimate and visualize the degree of variability in dichotomous treatment patterns and outcomes across different providers, whereby naive techniques either over-estimate or under-estimate the actual degree of variation. Various statistical methods have been proposed for similar applications including (1) the Gaussian hierarchical model, (2) the semi-parametric Bayesian hierarchical model with a Dirichlet process prior and (3) the non-parametric empirical Bayes approach of smoothing by roughening. Alternatively, we propose that a recently developed method for density estimation in the presence of measurement error, moment-adjusted imputation, can be adapted for this problem. The methods are compared by an extensive simulation study. In the present context, we find that the Bayesian methods are sensitive to the choice of prior and tuning parameters, whereas moment-adjusted imputation performs well with modest sample size requirements. The alternative approaches are applied to identify disparities in the receipt of early physician follow-up after myocardial infarction across 225 hospitals in the CRUSADE registry.

  11. Generating Variable and Random Schedules of Reinforcement Using Microsoft Excel Macros

    Science.gov (United States)

    Bancroft, Stacie L.; Bourret, Jason C.

    2008-01-01

    Variable reinforcement schedules are used to arrange the availability of reinforcement following varying response ratios or intervals of time. Random reinforcement schedules are subtypes of variable reinforcement schedules that can be used to arrange the availability of reinforcement at a constant probability across number of responses or time.…

  12. Capturing temporal and spatial variability in the chemistry of shallow permafrost ponds

    Science.gov (United States)

    Morison, Matthew Q.; Macrae, Merrin L.; Petrone, Richard M.; Fishback, LeeAnn

    2017-12-01

    Across the circumpolar north, the fate of small freshwater ponds and lakes (climates through sediment records. A changing climate has implications for the capacity of ponds and lakes to support organisms and store carbon, which in turn has important feedbacks to climate change. Thus, an improved understanding of pond biogeochemistry is needed. To characterize spatial and temporal patterns in water column chemistry, a suite of tundra ponds were examined to answer the following research questions: (1) does temporal variability exceed spatial variability? (2) If temporal variability exists, do all ponds (or groups of ponds) behave in a similar temporal pattern, linked to seasonal hydrologic drivers or precipitation events? Six shallow ponds located in the Hudson Bay Lowlands region were monitored between May and October 2015 (inclusive, spanning the entire open-water period). The ponds span a range of biophysical conditions including pond area, perimeter, depth, and shoreline development. Water samples were collected regularly, both bimonthly over the ice-free season and intensively during and following a large summer storm event. Samples were analysed for nitrogen speciation (NO3-, NH4+, dissolved organic nitrogen) and major ions (Cl-, SO42-, K+, Ca2+, Mg2+, Na+). Across all ponds, temporal variability (across the season and within a single rain event) exceeded spatial variability (variation among ponds) in concentrations of several major species (Cl-, SO42-, K+, Ca2+, Na+). Evapoconcentration and dilution of pond water with precipitation and runoff inputs were the dominant processes influencing a set of chemical species which are hydrologically driven (Cl-, Na+, K+, Mg2+, dissolved organic nitrogen), whereas the dissolved inorganic nitrogen species were likely mediated by processes within ponds. This work demonstrates the importance of understanding hydrologically driven chemodynamics in permafrost ponds on multiple scales (seasonal and event scale).

  13. Graffiti for science - erosion painting reveals spatially variable erosivity of sediment-laden flows

    Science.gov (United States)

    Beer, Alexander R.; Kirchner, James W.; Turowski, Jens M.

    2016-12-01

    Spatially distributed detection of bedrock erosion is a long-standing challenge. Here we show how the spatial distribution of surface erosion can be visualized and analysed by observing the erosion of paint from natural bedrock surfaces. If the paint is evenly applied, it creates a surface with relatively uniform erodibility, such that spatial variability in the erosion of the paint reflects variations in the erosivity of the flow and its entrained sediment. In a proof-of-concept study, this approach provided direct visual verification that sediment impacts were focused on upstream-facing surfaces in a natural bedrock gorge. Further, erosion painting demonstrated strong cross-stream variations in bedrock erosion, even in the relatively narrow (5 m wide) gorge that we studied. The left side of the gorge experienced high sediment throughput with abundant lateral erosion on the painted wall up to 80 cm above the bed, but the right side of the gorge only showed a narrow erosion band 15-40 cm above the bed, likely due to deposited sediment shielding the lower part of the wall. This erosion pattern therefore reveals spatial stream bed aggradation that occurs during flood events in this channel. The erosion painting method provides a simple technique for mapping sediment impact intensities and qualitatively observing spatially distributed erosion in bedrock stream reaches. It can potentially find wide application in both laboratory and field studies.

  14. Graffiti for science – erosion painting reveals spatially variable erosivity of sediment-laden flows

    Directory of Open Access Journals (Sweden)

    A. R. Beer

    2016-12-01

    Full Text Available Spatially distributed detection of bedrock erosion is a long-standing challenge. Here we show how the spatial distribution of surface erosion can be visualized and analysed by observing the erosion of paint from natural bedrock surfaces. If the paint is evenly applied, it creates a surface with relatively uniform erodibility, such that spatial variability in the erosion of the paint reflects variations in the erosivity of the flow and its entrained sediment. In a proof-of-concept study, this approach provided direct visual verification that sediment impacts were focused on upstream-facing surfaces in a natural bedrock gorge. Further, erosion painting demonstrated strong cross-stream variations in bedrock erosion, even in the relatively narrow (5 m wide gorge that we studied. The left side of the gorge experienced high sediment throughput with abundant lateral erosion on the painted wall up to 80 cm above the bed, but the right side of the gorge only showed a narrow erosion band 15–40 cm above the bed, likely due to deposited sediment shielding the lower part of the wall. This erosion pattern therefore reveals spatial stream bed aggradation that occurs during flood events in this channel. The erosion painting method provides a simple technique for mapping sediment impact intensities and qualitatively observing spatially distributed erosion in bedrock stream reaches. It can potentially find wide application in both laboratory and field studies.

  15. Anomalous transport in disordered fracture networks: Spatial Markov model for dispersion with variable injection modes

    Science.gov (United States)

    Kang, Peter K.; Dentz, Marco; Le Borgne, Tanguy; Lee, Seunghak; Juanes, Ruben

    2017-08-01

    We investigate tracer transport on random discrete fracture networks that are characterized by the statistics of the fracture geometry and hydraulic conductivity. While it is well known that tracer transport through fractured media can be anomalous and particle injection modes can have major impact on dispersion, the incorporation of injection modes into effective transport modeling has remained an open issue. The fundamental reason behind this challenge is that-even if the Eulerian fluid velocity is steady-the Lagrangian velocity distribution experienced by tracer particles evolves with time from its initial distribution, which is dictated by the injection mode, to a stationary velocity distribution. We quantify this evolution by a Markov model for particle velocities that are equidistantly sampled along trajectories. This stochastic approach allows for the systematic incorporation of the initial velocity distribution and quantifies the interplay between velocity distribution and spatial and temporal correlation. The proposed spatial Markov model is characterized by the initial velocity distribution, which is determined by the particle injection mode, the stationary Lagrangian velocity distribution, which is derived from the Eulerian velocity distribution, and the spatial velocity correlation length, which is related to the characteristic fracture length. This effective model leads to a time-domain random walk for the evolution of particle positions and velocities, whose joint distribution follows a Boltzmann equation. Finally, we demonstrate that the proposed model can successfully predict anomalous transport through discrete fracture networks with different levels of heterogeneity and arbitrary tracer injection modes.

  16. The trade-off between spatial and temporal variabilities in reciprocal upper-limb aiming movements of different durations.

    Science.gov (United States)

    Danion, Frederic; Bongers, Raoul M; Bootsma, Reinoud J

    2014-01-01

    The spatial and temporal aspects of movement variability have typically been studied separately. As a result the relationship between spatial and temporal variabilities remains largely unknown. In two experiments we examined the evolution and covariation of spatial and temporal variabilities over variations in the duration of reciprocal aiming movements. Experiments differed in settings: In Experiment 1 participants moved unperturbed whereas in Experiment 2 they were confronted with an elastic force field. Different movement durations-for a constant inter-target distance-were either evoked by imposing spatial accuracy constraints while requiring participants to move as fast as possible, or prescribed by means of an auditory metronome while requiring participants to maximize spatial accuracy. Analyses focused on absolute and relative variabilities, respectively captured by the standard deviation (SD) and the coefficient of variation (CV = SD/mean). Spatial variability (both SDspace and CVspace) decreased with movement duration, while temporal variability (both SDtime and CVtime) increased with movement duration. We found strong negative correlations between spatial and temporal variabilities over variations in movement duration, whether the variability examined was absolute or relative. These findings observed at the level of the full movement contrasted with the findings observed at the level of the separate acceleration and deceleration phases of movement. During the separate acceleration and deceleration phases both spatial and temporal variabilities (SD and CV) were found to increase with their respective durations, leading to positive correlations between them. Moreover, variability was generally larger at the level of the constituent movement phases than at the level of the full movement. The general pattern of results was robust, as it emerged in both tasks in each of the two experiments. We conclude that feedback mechanisms operating to maximize task

  17. Spatial variability in biodegradation rates as evidenced by methane production from an aquifer

    Science.gov (United States)

    Adrian, Neal R.; Robinson, Joseph A.; Suflita, Joseph M.

    1994-01-01

    Accurate predictions of carbon and energy cycling rates in the environment depend on sampling frequencies and on the spatial variability associated with biological activities. We examined the variability associated with anaerobic biodegradation rates at two sites in an alluvial sand aquifer polluted by municipal landfill leachate. In situ rates of methane production were measured for almost a year, using anaerobic wells installed at two sites. Methane production ranged from 0 to 560 μmol · m-2 · day-1 at one site (A), while a range of 0 to 120,000 μmol · m-2 · day-1 was measured at site B. The mean and standard deviations associated with methane production at site A were 17 and 57 μmol · m-2 · day-1, respectively. The comparable summary statistics for site B were 2,000 and 9,900 μmol · m-2 · day-1. The coefficients of variation at sites A and B were 340 and 490%, respectively. Despite these differences, the two sites had similar seasonal trends, with the maximal rate of methane production occurring in summer. However, the relative variability associated with the seasonal rates changed very little. Our results suggest that (i) two spatially distinct sites exist in the aquifer, (ii) methanogenesis is a highly variable process, (iii) the coefficient of variation varied little with the rate of methane production, and (iv) in situ anaerobic biodegradation rates are lognormally distributed.

  18. Heat and Laplace type equations with complex spatial variables in weighted Bergman spaces

    Directory of Open Access Journals (Sweden)

    Ciprian G. Gal

    2017-09-01

    Full Text Available In a recent book, the authors of this paper have studied the classical heat and Laplace equations with real time variable and complex spatial variable by the semigroup theory methods, under the hypothesis that the boundary function belongs to the space of analytic functions in the open unit disk and continuous in the closed unit disk, endowed with the uniform norm. The purpose of the present note is to show that the semigroup theory methods works for these evolution equations of complex spatial variables, under the hypothesis that the boundary function belongs to the much larger weighted Bergman space $B_{\\alpha }^p(D$ with $1\\leq p<+\\infty $, endowed with a $L^p$-norm. Also, the case of several complex variables is considered. The proofs require some new changes appealing to Jensen's inequality, Fubini's theorem for integrals and the $L^p$-integral modulus of continuity. The results obtained can be considered as complex analogues of those for the classical heat and Laplace equations in $L^p(\\mathbb{R}$ spaces.

  19. Spatial and temporal variability of snow depth and ablation rates in a small mountain catchment

    Directory of Open Access Journals (Sweden)

    T. Grünewald

    2010-05-01

    Full Text Available The spatio-temporal variability of the mountain snow cover determines the avalanche danger, snow water storage, permafrost distribution and the local distribution of fauna and flora. Using a new type of terrestrial laser scanner, which is particularly suited for measurements of snow covered surfaces, snow depth was monitored in a high alpine catchment during an ablation period. From these measurements snow water equivalents and ablation rates were calculated. This allowed us for the first time to obtain a high resolution (2.5 m cell size picture of spatial variability of the snow cover and its temporal development. A very high variability of the snow cover with snow depths between 0–9 m at the end of the accumulation season was observed. This variability decreased during the ablation phase, while the dominant snow deposition features remained intact. The average daily ablation rate was between 15 mm/d snow water equivalent at the beginning of the ablation period and 30 mm/d at the end. The spatial variation of ablation rates increased during the ablation season and could not be explained in a simple manner by geographical or meteorological parameters, which suggests significant lateral energy fluxes contributing to observed melt. It is qualitatively shown that the effect of the lateral energy transport must increase as the fraction of snow free surfaces increases during the ablation period.

  20. Computer simulation of random variables and vectors with arbitrary probability distribution laws

    Science.gov (United States)

    Bogdan, V. M.

    1981-01-01

    Assume that there is given an arbitrary n-dimensional probability distribution F. A recursive construction is found for a sequence of functions x sub 1 = f sub 1 (U sub 1, ..., U sub n), ..., x sub n = f sub n (U sub 1, ..., U sub n) such that if U sub 1, ..., U sub n are independent random variables having uniform distribution over the open interval (0,1), then the joint distribution of the variables x sub 1, ..., x sub n coincides with the distribution F. Since uniform independent random variables can be well simulated by means of a computer, this result allows one to simulate arbitrary n-random variables if their joint probability distribution is known.

  1. Spatial-temporal variability in GHG fluxes and their functional interpretation in RusFluxNet

    Science.gov (United States)

    Vasenev, Ivan; Meshalkina, Julia; Sarzhanov, Dmitriy; Mazirov, Ilia; Yaroslavtsev, Alex; Komarova, Tatiana; Tikhonova, Maria

    2016-04-01

    High spatial and temporal variability is mutual feature for most modern boreal landscapes in the European Territory of Russia. This variability is result of their relatively young natural and land-use age with very complicated development stories. RusFluxNet includes a functionally-zonal set of representative natural, agricultural and urban ecosystems from the Central Forest Reserve in the north till the Central Chernozemic Reserve in the south (more than 1000 km distance). Especial attention has been traditionally given to their soil cover and land-use detailed variability, morphogenetic and functional dynamics. Central Forest Biosphere Reserve (360 km to North-West from Moscow) is the principal southern-taiga one in the European territory of Russia with long history of mature spruce ecosystem structure and dynamics investigation. Our studies (in frame of RF Governmental projects #11.G34.31.0079 and #14.120.14.4266) have been concentrated on the soil carbon stocks and GHG fluxes spatial variability and dynamics due to dominated there windthrow and fallow-forest successions. In Moscow RTSAU campus gives a good possibility to develop the ecosystem and soil monitoring of GHG fluxes in the comparable sites of urban forest, field crops and lawn ecosystems taking especial attention on their meso- and micro-relief, soil cover patterns and subsoil, vegetation and land-use technologies, temperature and moisture spatial and temporal variability. In the Central Chernozemic Biosphere Reserve and adjacent areas we do the comparative analysis of GHG fluxes and balances in the virgin and mowed meadow-steppe, forest, pasture, cropland and three types of urban ecosystems with similar subsoil and relief conditions. The carried out researches have shown not only sharp (in 2-5 times) changes in GHG ecosystem and soil fluxes and balances due to seasonal and daily microclimate variation, vegetation and crop development but their essential (in 2-4 times) spatial variability due to

  2. Spatial variability of harmful algal blooms in Milford Lake, Kansas, July and August 2015

    Science.gov (United States)

    Foster, Guy M.; Graham, Jennifer L.; Stiles, Tom C.; Boyer, Marvin G.; King, Lindsey R.; Loftin, Keith A.

    2017-01-09

    Cyanobacterial harmful algal blooms (CyanoHABs) tend to be spatially variable vertically in the water column and horizontally across the lake surface because of in-lake and weather-driven processes and can vary by orders of magnitude in concentration across relatively short distances (meters or less). Extreme spatial variability in cyanobacteria and associated compounds poses unique challenges to collecting representative samples for scientific study and public-health protection. The objective of this study was to assess the spatial variability of cyanobacteria and microcystin in Milford Lake, Kansas, using data collected on July 27 and August 31, 2015. Spatially dense near-surface data were collected by the U.S. Geological Survey, nearshore data were collected by the Kansas Department of Health and Environment, and open-water data were collected by U.S. Army Corps of Engineers. CyanoHABs are known to be spatially variable, but that variability is rarely quantified. A better understanding of the spatial variability of cyanobacteria and microcystin will inform sampling and management strategies for Milford Lake and for other lakes with CyanoHAB issues throughout the Nation.The CyanoHABs in Milford Lake during July and August 2015 displayed the extreme spatial variability characteristic of cyanobacterial blooms. The phytoplankton community was almost exclusively cyanobacteria (greater than 90 percent) during July and August. Cyanobacteria (measured directly by cell counts and indirectly by regression-estimated chlorophyll) and microcystin (measured directly by enzyme-linked immunosorbent assay [ELISA] and indirectly by regression estimates) concentrations varied by orders of magnitude throughout the lake. During July and August 2015, cyanobacteria and microcystin concentrations decreased in the downlake (towards the outlet) direction.Nearshore and open-water surface grabs were collected and analyzed for microcystin as part of this study. Samples were collected in the

  3. Temporal and spatial characteristics of sea surface height variability in the North Atlantic Ocean

    Directory of Open Access Journals (Sweden)

    D. Cromwell

    2006-01-01

    Full Text Available We investigate the spatial and temporal variability of sea surface height (SSH in the North Atlantic basin using satellite altimeter data from October 1992–January 2004. Our primary aim is to provide a detailed description of such variability, including that associated with propagating signals. We also investigate possible correlations between SSH variability and atmospheric pressure changes as represented by climate indices. We first investigate interannual SSH variations by deriving the complex empirical orthogonal functions (CEOFs of altimeter data lowpass-filtered at 18 months. We determine the spatial structure of the leading four modes (both in amplitude and phase and also the associated principal component (PC time series. Using wavelet analysis we derive the time-varying spectral density of the PCs, revealing when particular modes were strongest between 1992–2004. The spatial pattern of the leading CEOF, comprising 30% of the total variability, displays a 5-year periodicity in phase; signal propagation is particularly marked in the Labrador Sea. The second mode, with a dominant 3-year signal, has strong variability in the eastern basin. Secondly, we focus on the Azores subtropical frontal zone. The leading mode (35% is strong in the south and east of this region with strong variations at 3- and 5-year periods. The second mode (21% has a near-zonal band of low variance between  22°–27° N, sandwiched between two regions of high variance. Thirdly, we lowpass filter the altimeter data at a cutoff of 30 days, instead of 18 months, in order to retain signals associated with propagating baroclinic Rossby waves and/or eddies. The leading mode is the annual steric signal, around 46% of the SSH variability. The third and fourth CEOFs,  11% of the remaining variability, are associated with westward propagation which is particularly dominant in a "waveband" between 32°–36° N. For all three cases considered above, no significant cross

  4. Short-term spatial and temporal variability in greenhouse gas fluxes in riparian zones.

    Science.gov (United States)

    Vidon, P; Marchese, S; Welsh, M; McMillan, S

    2015-08-01

    Recent research indicates that riparian zones have the potential to contribute significant amounts of greenhouse gases (GHG: N2O, CO2, CH4) to the atmosphere. Yet, the short-term spatial and temporal variability in GHG emission in these systems is poorly understood. Using two transects of three static chambers at two North Carolina agricultural riparian zones (one restored, one unrestored), we show that estimates of the average GHG flux at the site scale can vary by one order of magnitude depending on whether the mean or the median is used as a measure of central tendency. Because the median tends to mute the effect of outlier points (hot spots and hot moments), we propose that both must be reported or that other more advanced spatial averaging techniques (e.g., kriging, area-weighted average) should be used to estimate GHG fluxes at the site scale. Results also indicate that short-term temporal variability in GHG fluxes (a few days) under seemingly constant temperature and hydrological conditions can be as large as spatial variability at the site scale, suggesting that the scientific community should rethink sampling protocols for GHG at the soil-atmosphere interface to include repeated measures over short periods of time at select chambers to estimate GHG emissions in the field. Although recent advances in technology provide tools to address these challenges, their cost is often too high for widespread implementation. Until technology improves, sampling design strategies will need to be carefully considered to balance cost, time, and spatial and temporal representativeness of measurements.

  5. Variability of apparently homogeneous soilscapes in São Paulo state, Brazil: I. spatial analysis

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    M. van Den Berg

    2000-06-01

    Full Text Available The spatial variability of strongly weathered soils under sugarcane and soybean/wheat rotation was quantitatively assessed on 33 fields in two regions in São Paulo State, Brazil: Araras (15 fields with sugarcane and Assis (11 fields with sugarcane and seven fields with soybean/wheat rotation. Statistical methods used were: nested analysis of variance (for 11 fields, semivariance analysis and analysis of variance within and between fields. Spatial levels from 50 m to several km were analyzed. Results are discussed with reference to a previously published study carried out in the surroundings of Passo Fundo (RS. Similar variability patterns were found for clay content, organic C content and cation exchange capacity. The fields studied are quite homogeneous with respect to these relatively stable soil characteristics. Spatial variability of other characteristics (resin extractable P, pH, base- and Al-saturation and also soil colour, varies with region and, or land use management. Soil management for sugarcane seems to have induced modifications to greater depths than for soybean/wheat rotation. Surface layers of soils under soybean/wheat present relatively little variation, apparently as a result of very intensive soil management. The major part of within-field variation occurs at short distances (< 50 m in all study areas. Hence, little extra information would be gained by increasing sampling density from, say, 1/km² to 1/50 m². For many purposes, the soils in the study regions can be mapped with the same observation density, but residual variance will not be the same in all areas. Bulk sampling may help to reveal spatial patterns between 50 and 1.000 m.

  6. The Effect of Restoration Treatments on the Spatial Variability of Soil Processes under Longleaf Pine Trees

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    John K. Hiers

    2012-08-01

    Full Text Available The objectives of this study were to (1 characterize tree-based spatial patterning of soil properties and understory vegetation in frequently burned (“reference state” and fire-suppressed longleaf pine forests; and (2 determine how restoration treatments affected patterning. To attain these objectives, we used an experimental manipulation of management types implemented 15 years ago in Florida. We randomly located six mature longleaf pine trees in one reference and four restoration treatments (i.e., burn, control, herbicide, and mechanical, for a total of 36 trees. In addition to the original treatments and as part of a monitoring program, all plots were subjected to several prescribed fires during these 15 years. Under each tree, we sampled mineral soil and understory vegetation at 1 m, 2 m, 3 m and 4 m (vegetation only away from the tree. At these sites, soil carbon and nitrogen were higher near the trunk while graminoids, forbs and saw palmetto covers showed an opposite trend. Our results confirmed that longleaf pine trees affect the spatial patterning of soil and understory vegetation, and this patterning was mostly limited to the restoration sites. We suggest frequent burning as a probable cause for a lack of spatial structure in the “reference state”. We attribute the presence of spatial patterning in the restoration sites to accumulation of organic materials near the base of mature trees.

  7. Richly parameterized linear models additive, time series, and spatial models using random effects

    CERN Document Server

    Hodges, James S

    2013-01-01

    A First Step toward a Unified Theory of Richly Parameterized Linear ModelsUsing mixed linear models to analyze data often leads to results that are mysterious, inconvenient, or wrong. Further compounding the problem, statisticians lack a cohesive resource to acquire a systematic, theory-based understanding of models with random effects.Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects takes a first step in developing a full theory of richly parameterized models, which would allow statisticians to better understand their analysis results. The aut

  8. Decadal climate variability and the spatial organization of deep hydrological drought

    Science.gov (United States)

    Barros, Ana P.; Hodes, Jared L.; Arulraj, Malarvizhi

    2017-10-01

    Empirical Orthogonal Function (EOF), wavelet, and wavelet coherence analysis of baseflow time-series from 126 streamgauges (record-length > 50 years; small and mid-size watersheds) in the US South Atlantic (USSA) region reveal three principal modes of space-time variability: (1) a region-wide dominant mode tied to annual precipitation that exhibits non-stationary decadal variability after the mid 1990s concurrent with the warming of the AMO (Atlantic Multidecadal Oscillation); (2) two spatial modes, east and west of the Blue Ridge, exhibiting nonstationary seasonal to sub-decadal variability before and after 1990 attributed to complex nonlinear interactions between ENSO and AMO impacting precipitation and recharge; and (3) deep (decadal) and shallow (modes of groundwater variability separating basins with high and low annual mean baseflow fraction (MBF) by physiographic region. The results explain the propagation of multiscale climate variability into the regional groundwater system through recharge modulated by topography, geomorphology, and geology to determine the spatial organization of baseflow variability at decadal (and longer) time-scales, that is, deep hydrologic drought. Further, these findings suggest potential for long-range predictability of hydrological drought in small and mid-size watersheds, where baseflow is a robust indicator of nonstationary yield capacity of the underlying groundwater basins. Predictive associations between climate mode indices and deep baseflow (e.g. persistent decreases of the decadal-scale components of baseflow during the cold phase of the AMO in the USSA) can be instrumental toward improving forecast lead-times and long-range mitigation of severe drought.

  9. Spatial-temporal gait variability poststroke: variations in measurement and implications for measuring change.

    Science.gov (United States)

    Chisholm, Amanda E; Makepeace, Shelley; Inness, Elizabeth L; Perry, Stephen D; McIlroy, William E; Mansfield, Avril

    2014-07-01

    To determine the responsiveness to change of spatial-temporal gait parameters among stroke survivors for 3 different variability measures: SD, coefficient of variation (CV), and median absolute deviation (MAD). Retrospective chart review. Clinical laboratory in a Canadian hospital. Stroke survivors (N=74) receiving inpatient rehabilitation. Not applicable. Spatial-temporal gait variability was calculated for step length, step width, stance time, swing time, and double support time. Responsiveness to change was determined by comparing (1) trials without versus trials with a concurrent cognitive task and (2) admission to discharge from rehabilitation. Variability estimators (SD, CV, and MAD) increased with the addition of a cognitive task and decreased from admission to discharge of rehabilitation. However, these changes were not statistically significant when change in gait velocity was included as a covariate. The effect size values were similar for all variability estimators with a trend toward a greater SD response to temporal parameters. The CV displayed a larger response to change for step length than did the SD and MAD. Although gait variability decreased between admission and discharge, the effect size was larger for the condition without the cognitive task than for the condition with the cognitive task. Our results show that gait variability estimators demonstrate a similar responsiveness to a concurrent cognitive task and improved walking ability with recovery from stroke. Future work may focus on evaluating the clinical utility of these measures in relation to informing therapy and response to gait-specific training protocols. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  10. Heterogeneity of gaseous emissions in soils-spatial vs temporal variability

    Science.gov (United States)

    Cardenas, Laura; Chadwick, David; Misselbrook, Tom; Donovan, Neil; Dunn, Rob; Griffith, Bruce; Orr, Robert; Smith, Keith; Rees, Robert M.; Bell, Madeleine; Watson, Catherine; McGeough, Karen; McNeill, Gavin; Williams, John; Cloy, Joanna; Thorman, Rachel; Dhanoa, Dan

    2015-04-01

    Nitrous oxide (N2O) plays a dual role in the atmosphere as a greenhouse gas and via its influence on stratospheric ozone chemistry. The main source of N2O is agricultural soil, with an estimated 96 kt emitted from this source in the UK in 2012 (ca. 83% of the total UK N2O emissions). Microbial transformations such as nitrification, denitrification and chemodenitrification are responsible for these emissions. Soil texture and structure and land management practices (including presence of livestock) -- soil wetness, aeration, temperature and mineral N content -- influence the magnitude of the emissions. Heterogeneity in nutrient distribution and moisture, i.e. hot spots, create spatial variations in the main drivers of these transformations. Studies at laboratory scale are aimed to minimize the variability encountered in the field but although they provide important information on the controlling factors of the soil processes, they are not useful for real quantification. Daily and seasonal variation (temporal) in soil conditions (chemistry, physics and biology) and thus in emissions also occurs. This variability makes it a difficult challenge to quantify emissions and currently makes the soil source the largest contributor to the overall uncertainty of the UK greenhouse gas inventory. Here we present results of a statistical study on the variability of N2O emissions from measurements using the static chamber technique for a variety of N sources. Results from measurements using automated chambers are also presented. Part of the work was funded by the UK government to improve the quantification of this source by measuring emissions from sites with contrasting soil, climate and land management combinations. We also include results from measurements carried out with automated chambers on the UK National Capability Farm Platform in the South West of England. The results show that spatial variability largely contributes to the uncertainty of emissions but temporal

  11. Detecting high spatial variability of ice shelf basal mass balance, Roi Baudouin Ice Shelf, Antarctica

    Directory of Open Access Journals (Sweden)

    S. Berger

    2017-11-01

    Full Text Available Ice shelves control the dynamic mass loss of ice sheets through buttressing and their integrity depends on the spatial variability of their basal mass balance (BMB, i.e. the difference between refreezing and melting. Here, we present an improved technique – based on satellite observations – to capture the small-scale variability in the BMB of ice shelves. As a case study, we apply the methodology to the Roi Baudouin Ice Shelf, Dronning Maud Land, East Antarctica, and derive its yearly averaged BMB at 10 m horizontal gridding. We use mass conservation in a Lagrangian framework based on high-resolution surface velocities, atmospheric-model surface mass balance and hydrostatic ice-thickness fields (derived from TanDEM-X surface elevation. Spatial derivatives are implemented using the total-variation differentiation, which preserves abrupt changes in flow velocities and their spatial gradients. Such changes may reflect a dynamic response to localized basal melting and should be included in the mass budget. Our BMB field exhibits much spatial detail and ranges from −14.7 to 8.6 m a−1 ice equivalent. Highest melt rates are found close to the grounding line where the pressure melting point is high, and the ice shelf slope is steep. The BMB field agrees well with on-site measurements from phase-sensitive radar, although independent radar profiling indicates unresolved spatial variations in firn density. We show that an elliptical surface depression (10 m deep and with an extent of 0.7 km × 1.3 km lowers by 0.5 to 1.4 m a−1, which we tentatively attribute to a transient adaptation to hydrostatic equilibrium. We find evidence for elevated melting beneath ice shelf channels (with melting being concentrated on the channel's flanks. However, farther downstream from the grounding line, the majority of ice shelf channels advect passively (i.e. no melting nor refreezing toward the ice shelf front. Although the absolute, satellite

  12. Detecting high spatial variability of ice shelf basal mass balance, Roi Baudouin Ice Shelf, Antarctica

    Science.gov (United States)

    Berger, Sophie; Drews, Reinhard; Helm, Veit; Sun, Sainan; Pattyn, Frank

    2017-11-01

    Ice shelves control the dynamic mass loss of ice sheets through buttressing and their integrity depends on the spatial variability of their basal mass balance (BMB), i.e. the difference between refreezing and melting. Here, we present an improved technique - based on satellite observations - to capture the small-scale variability in the BMB of ice shelves. As a case study, we apply the methodology to the Roi Baudouin Ice Shelf, Dronning Maud Land, East Antarctica, and derive its yearly averaged BMB at 10 m horizontal gridding. We use mass conservation in a Lagrangian framework based on high-resolution surface velocities, atmospheric-model surface mass balance and hydrostatic ice-thickness fields (derived from TanDEM-X surface elevation). Spatial derivatives are implemented using the total-variation differentiation, which preserves abrupt changes in flow velocities and their spatial gradients. Such changes may reflect a dynamic response to localized basal melting and should be included in the mass budget. Our BMB field exhibits much spatial detail and ranges from -14.7 to 8.6 m a-1 ice equivalent. Highest melt rates are found close to the grounding line where the pressure melting point is high, and the ice shelf slope is steep. The BMB field agrees well with on-site measurements from phase-sensitive radar, although independent radar profiling indicates unresolved spatial variations in firn density. We show that an elliptical surface depression (10 m deep and with an extent of 0.7 km × 1.3 km) lowers by 0.5 to 1.4 m a-1, which we tentatively attribute to a transient adaptation to hydrostatic equilibrium. We find evidence for elevated melting beneath ice shelf channels (with melting being concentrated on the channel's flanks). However, farther downstream from the grounding line, the majority of ice shelf channels advect passively (i.e. no melting nor refreezing) toward the ice shelf front. Although the absolute, satellite-based BMB values remain uncertain, we have

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

    Directory of Open Access Journals (Sweden)

    T. Skaugen

    2016-09-01

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

  14. The effect of spatial randomness on the average fixation time of mutants

    Science.gov (United States)

    Farhang-Sardroodi, Suzan; Darooneh, Amir H.; Nikbakht, Moladad; Kohandel, Mohammad

    2017-01-01

    The mean conditional fixation time of a mutant is an important measure of stochastic population dynamics, widely studied in ecology and evolution. Here, we investigate the effect of spatial randomness on the mean conditional fixation time of mutants in a constant population of cells, N. Specifically, we assume that fitness values of wild type cells and mutants at different locations come from given probability distributions and do not change in time. We study spatial arrangements of cells on regular graphs with different degrees, from the circle to the complete graph, and vary assumptions on the fitness probability distributions. Some examples include: identical probability distributions for wild types and mutants; cases when only one of the cell types has random fitness values while the other has deterministic fitness; and cases where the mutants are advantaged or disadvantaged. Using analytical calculations and stochastic numerical simulations, we find that randomness has a strong impact on fixation time. In the case of complete graphs, randomness accelerates mutant fixation for all population sizes, and in the case of circular graphs, randomness delays mutant fixation for N larger than a threshold value (for small values of N, different behaviors are observed depending on the fitness distribution functions). These results emphasize fundamental differences in population dynamics under different assumptions on cell connectedness. They are explained by the existence of randomly occurring “dead zones” that can significantly delay fixation on networks with low connectivity; and by the existence of randomly occurring “lucky zones” that can facilitate fixation on networks of high connectivity. Results for death-birth and birth-death formulations of the Moran process, as well as for the (haploid) Wright Fisher model are presented. PMID:29176825

  15. A simple model for the spatially-variable coastal response to hurricanes

    Science.gov (United States)

    Stockdon, H.F.; Sallenger, A.H.; Holman, R.A.; Howd, P.A.

    2007-01-01

    The vulnerability of a beach to extreme coastal change during a hurricane can be estimated by comparing the relative elevations of storm-induced water levels to those of the dune or berm. A simple model that defines the coastal response based on these elevations was used to hindcast the potential impact regime along a 50-km stretch of the North Carolina coast to the landfalls of Hurricane Bonnie on August 27, 1998, and Hurricane Floyd on September 16, 1999. Maximum total water levels at the shoreline were calculated as the sum of modeled storm surge, astronomical tide, and wave runup, estimated from offshore wave conditions and the local beach slope using an empirical parameterization. Storm surge and wave runup each accounted for ∼ 48% of the signal (the remaining 4% is attributed to astronomical tides), indicating that wave-driven process are a significant contributor to hurricane-induced water levels. Expected water levels and lidar-derived measures of pre-storm dune and berm elevation were used to predict the spatially-varying storm-impact regime: swash, collision, or overwash. Predictions were compared to the observed response quantified using a lidar topography survey collected following hurricane landfall. The storm-averaged mean accuracy of the model in predicting the observed impact regime was 55.4%, a significant improvement over the 33.3% accuracy associated with random chance. Model sensitivity varied between regimes and was highest within the overwash regime where the accuracies were 84.2% and 89.7% for Hurricanes Bonnie and Floyd, respectively. The model not only allows for prediction of the general coastal response to storms, but also provides a framework for examining the longshore-variable magnitudes of observed coastal change. For Hurricane Bonnie, shoreline and beach volume changes within locations that experienced overwash or dune erosion were two times greater than locations where wave runup was confined to the foreshore (swash regime

  16. Accounting for rainfall spatial variability in the prediction of flash floods

    Science.gov (United States)

    Saharia, Manabendra; Kirstetter, Pierre-Emmanuel; Gourley, Jonathan J.; Hong, Yang; Vergara, Humberto; Flamig, Zachary L.

    2017-04-01

    Flash floods are a particularly damaging natural hazard worldwide in terms of both fatalities and property damage. In the United States, the lack of a comprehensive database that catalogues information related to flash flood timing, location, causative rainfall, and basin geomorphology has hindered broad characterization studies. First a representative and long archive of more than 15,000 flooding events during 2002-2011 is used to analyze the spatial and temporal variability of flash floods. We also derive large number of spatially distributed geomorphological and climatological parameters such as basin area, mean annual precipitation, basin slope etc. to identify static basin characteristics that influence flood response. For the same period, the National Severe Storms Laboratory (NSSL) has produced a decadal archive of Multi-Radar/Multi-Sensor (MRMS) radar-only precipitation rates at 1-km spatial resolution with 5-min temporal resolution. This provides an unprecedented opportunity to analyze the impact of event-level precipitation variability on flooding using a big data approach. To analyze the impact of sub-basin scale rainfall spatial variability on flooding, certain indices such as the first and second scaled moment of rainfall, horizontal gap, vertical gap etc. are computed from the MRMS dataset. Finally, flooding characteristics such as rise time, lag time, and peak discharge are linked to derived geomorphologic, climatologic, and rainfall indices to identify basin characteristics that drive flash floods. The database has been subjected to rigorous quality control by accounting for radar beam height and percentage snow in basins. So far studies involving rainfall variability indices have only been performed on a case study basis, and a large scale approach is expected to provide a deeper insight into how sub-basin scale precipitation variability affects flooding. Finally, these findings are validated using the National Weather Service storm reports and a

  17. Properties of a new small-world network with spatially biased random shortcuts

    Science.gov (United States)

    Matsuzawa, Ryo; Tanimoto, Jun; Fukuda, Eriko

    2017-11-01

    This paper introduces a small-world (SW) network with a power-law distance distribution that differs from conventional models in that it uses completely random shortcuts. By incorporating spatial constraints, we analyze the divergence of the proposed model from conventional models in terms of fundamental network properties such as clustering coefficient, average path length, and degree distribution. We find that when the spatial constraint more strongly prohibits a long shortcut, the clustering coefficient is improved and the average path length increases. We also analyze the spatial prisoner's dilemma (SPD) games played on our new SW network in order to understand its dynamical characteristics. Depending on the basis graph, i.e., whether it is a one-dimensional ring or a two-dimensional lattice, and the parameter controlling the prohibition of long-distance shortcuts, the emergent results can vastly differ.

  18. Spatial distribution of random velocity inhomogeneities in the western part of Nankai subduction zone

    Science.gov (United States)

    Takahashi, T.; Obana, K.; Yamamoto, Y.; Nakanishi, A.; Kodaira, S.; Kaneda, Y.

    2011-12-01

    In the Nankai trough, there are three seismogenic zones of megathrust earthquakes (Tokai, Tonankai and Nankai earthquakes). Lithospheric structures in and around these seismogenic zones are important for the studies on mutual interactions and synchronization of their fault ruptures. Recent studies on seismic wave scattering at high frequencies (>1Hz) make it possible to estimate 3D distributions of random inhomogeneities (or scattering coefficient) in the lithosphere, and clarified that random inhomogeneity is one of the important medium properties related to microseismicity and damaged structure near the fault zone [Asano & Hasegawa, 2004; Takahashi et al. 2009]. This study estimates the spatial distribution of the power spectral density function (PSDF) of random inhomogeneities the western part of Nankai subduction zone, and examines the relations with crustal velocity structure and seismic activity. Seismic waveform data used in this study are those recorded at seismic stations of Hi-net & F-net operated by NIED, and 160 ocean bottom seismographs (OBSs) deployed at Hyuga-nada region from Dec. 2008 to Jan. 2009. This OBS observation was conducted by JAMSTEC as a part of "Research concerning Interaction Between the Tokai, Tonankai and Nankai Earthquakes" funded by Ministry of Education, Culture, Sports, Science and Technology, Japan. Spatial distribution of random inhomogeneities is estimated by the inversion analysis of the peak delay time of small earthquakes [Takahashi et al. 2009], where the peak delay time is defined as the time lag from the S-wave onset to its maximal amplitude arrival. We assumed the von Karman type functional form for the PSDF. Peak delay times are measured from root mean squared envelopes at 4-8Hz, 8-16Hz and 16-32Hz. Inversion result can be summarized as follows. Random inhomogeneities beneath the Quaternary volcanoes are characterized by strong inhomogeneities at small spatial scale (~ a few hundreds meter) and weak spectral gradient

  19. Non-random spatial relationships between mast cells and microvessels in human endometrial carcinoma.

    Science.gov (United States)

    Guidolin, Diego; Marinaccio, Christian; Tortorella, Cinzia; Annese, Tiziana; Ruggieri, Simona; Finato, Nicoletta; Crivellato, Enrico; Ribatti, Domenico

    2017-02-01

    Mast cells (MCs) accumulate in the stroma surrounding tumors, where they secrete angiogenic cytokines and proteases, and an increased number of MCs have been demonstrated in angiogenesis associated with solid and hematological tumors. The aim of this study is to contribute to the knowledge of distribution of MCs in tumors, investigating the pattern of distribution of tryptase-positive MCs around the blood vessels in human endometrial carcinoma samples by introducing a quantitative approach to characterize their spatial distribution. The results have shown that in human endometrial cancer bioptic specimens the spatial distribution of MCs shows significant deviation from randomness as compared with control group in which, instead, the spatial distribution of MCs is consistent with a random distribution. These findings confirm that MCs enhance tumor angiogenesis and their preferential localization along blood vessels and sites of new vessel formation sustaining the suggestion for an association between MCs and angiogenesis. However, this spatial association between vessels and MCs might simply reflect migrating MCs from the blood stream at vessel growing sites.

  20. Random sets and random fuzzy sets as ill-perceived random variables an introduction for Ph.D. students and practitioners

    CERN Document Server

    Couso, Inés; Sánchez, Luciano

    2014-01-01

    This short book provides a unified view of the history and theory of random sets and fuzzy random variables, with special emphasis on its use for representing higher-order non-statistical uncertainty about statistical experiments. The authors lay bare the existence of two streams of works using the same mathematical ground, but differing form their use of sets, according to whether they represent objects of interest naturally taking the form of sets, or imprecise knowledge about such objects. Random (fuzzy) sets can be used in many fields ranging from mathematical morphology, economics, artificial intelligence, information processing and statistics per se, especially in areas where the outcomes of random experiments cannot be observed with full precision. This book also emphasizes the link between random sets and fuzzy sets with some techniques related to the theory of imprecise probabilities. This small book is intended for graduate and doctoral students in mathematics or engineering, but also provides an i...

  1. Temporal and spatial variability in the Guadalquivir estuary: a challenge for real-time telemetry

    Science.gov (United States)

    Navarro, Gabriel; Gutiérrez, Francisco Javier; Díez-Minguito, Manuel; Losada, Miguel Angel; Ruiz, Javier

    2011-06-01

    Meteorological, hydrological, and hydrodynamic data for 3 years (2008-2010) have been used to document and explain the temporal and spatial variability of the physical-biogeochemical interactions in the Guadalquivir River Estuary. A real-time, remote monitoring network has been deployed along the course of the river between its mouth and Seville to study a broad range of temporal scales (semidiurnal, diurnal, fortnightly, and seasonal). This network consists of eight hydrological monitoring stations capable of measuring temperature, conductivity, dissolved oxygen, turbidity, and chlorophyll fluorescence at four depths. In addition, six stations have been deployed to study hydrodynamics, obtaining 20-cell water column current profiles, and there is a meteorological station at the river mouth providing data for understanding atmospheric interactions. Completing this data-gathering network, there are several moorings (tide gauges, current/wave sensors, and a thermistor chain) deployed in the estuary and river mouth. Various sources of physical forcing, such as wind, tide-associated currents, and river discharge, are responsible for the particular temporal and spatial patterns of turbidity and salinity found in the estuary. These variables force the distribution of biogeochemical variables, such as dissolved oxygen and chlorophyll fluorescence. In particular, episodes of elevated turbidity (when suspended particle matter concentration >3,000 mg/l) have been detected by the network, together with episodes of declining values of salinity and dissolved oxygen. All these patterns are related to river discharge and tidal dynamics (spring/neap and high/low tide).

  2. Spatial variability of selected physicochemical parameters within peat deposits in small valley mire: a geostatistical approach

    Directory of Open Access Journals (Sweden)

    Pawłowski Dominik

    2014-12-01

    Full Text Available Geostatistical methods for 2D and 3D modelling spatial variability of selected physicochemical properties of biogenic sediments were applied to a small valley mire in order to identify the processes that lead to the formation of various types of peat. A sequential Gaussian simulation was performed to reproduce the statistical distribution of the input data (pH and organic matter and their semivariances, as well as to honouring of data values, yielding more ‘realistic’ models that show microscale spatial variability, despite the fact that the input sample cores were sparsely distributed in the X-Y space of the study area. The stratigraphy of peat deposits in the Ldzań mire shows a record of long-term evolution of water conditions, which is associated with the variability in water supply over time. Ldzań is a fen (a rheotrophic mire with a through-flow of groundwater. Additionally, the vicinity of the Grabia River is marked by seasonal inundations of the southwest part of the mire and increased participation of mineral matter in the peat. In turn, the upper peat layers of some of the central part of Ldzań mire are rather spongy, and these peat-forming phytocoenoses probably formed during permanent waterlogging.

  3. A protocol for measuring spatial variables in soft-sediment tide pools

    Directory of Open Access Journals (Sweden)

    Marina R. Brenha-Nunes

    2016-01-01

    Full Text Available ABSTRACT We present a protocol for measuring spatial variables in large (>50 m2 soft-sediment tide pool. Secondarily, we present the fish capture efficiency of a sampling protocol that based on such spatial variables to calculate relative abundances. The area of the pool is estimated by summing areas of basic geometric forms; the depth, by taken representative measurements of the depth variability of each pool's sector, previously determined according to its perimeter; and the volume, by considering the pool as a prism. These procedures were a trade-off between the acquisition of reliable estimates and the minimization of both the cost of operating and the time spent in field. The fish sampling protocol is based on two con secutive stages: 1 two people search for fishes under structures (e.g., rocks and litters on the pool and capture them with hand seines; 2 these structures are removed and then a beach-seine is hauled over the whole pool. Our method is cheaper than others and fast to operate considering the time in low tides. The method to sample fish is quite efficient resulting in a capture efficiency of 89%.

  4. A mobile system for quantifying the spatial variability of the surface energy balance: design and application

    Science.gov (United States)

    Wohlfahrt, Georg; Tasser, Erich

    2015-05-01

    We present a mobile device for the quantification of the small-scale (a few square meters) spatial variability in the surface energy balance components and several auxiliary variables of short-statured (wind speed, soil temperature and soil water content. Data are acquired by a battery-powered data logger, which is mounted on a backpack together with the auxiliary sensors. The proposed device was developed to bridge between the spatial scales of satellite/airborne remote sensing and fixed, stationary tower-based measurements with an emphasis on micrometeorological, catchment hydrological and landscape-ecological research questions. The potential of the new device is demonstrated through four selected case studies, which cover the issues of net radiation heterogeneity within the footprint of eddy covariance flux measurements due to (1) land use and (2) slope and aspect of the underlying surface, (3) controls on landscape-scale variability in soil temperature and albedo and (4) the estimation of evapotranspiration based exclusively on measurements with the mobile device.

  5. Fine scale spatial variability of microbial pesticide degradation in soil: scales, controlling factors, and implications

    DEFF Research Database (Denmark)

    Dechesne, Arnaud; Badawi, N.; Aamand, Jens

    2014-01-01

    Pesticide biodegradation is a soil microbial function of critical importance for modern agriculture and its environmental impact. While it was once assumed that this activity was homogeneously distributed at the field scale, mounting evidence indicates that this is rarely the case. Here, we...... critically examine the literature on spatial variability of pesticide biodegradation in agricultural soil. We discuss the motivations, methods, and main findings of the primary literature. We found significant diversity in the approaches used to describe and quantify spatial heterogeneity, which complicates...... across pesticide classes: they include some soil characteristics (pH) and some agricultural management practices (pesticide application, tillage), while other potential controlling factors have more conflicting effects depending on the site or the pesticide. Evidence demonstrating the importance...

  6. Do existing classification systems capture mountain snowpack heterogeneity? Accounting for spatial variability in a changing environment

    Science.gov (United States)

    Tennant, C.; Godsey, S.; Harpold, A. A.; Link, T. E.; Rajagopal, S.; Larsen, L.

    2016-12-01

    Spatial patterns of snow accumulation and melt control water and nutrient fluxes from mountain landscapes and determine the dynamics of resource availability for nearby human and ecological communities. Because seasonal snowpack is sensitive to changes in regional climate, there is a growing need for a snowpack classification system that (1) recognizes salient processes, (2) captures the variance of the system, (3) recognizes temporal and/or spatial change, and (4) has application to predicting snowmelt runoff regimes. Previous classification systems have focused on textural and stratigraphic snow characteristics or climatological observations to map broad geographic classes (e.g. maritime, continental, ephemeral, etc.). While these approaches have revealed general patterns, they may not capture the spatial heterogeneity of snowpack characteristics that are common across high relief terrain. Here, we use 1 km resolution gridded outputs from a physically based, spatially-distributed energy- and mass-balance snow model (SNODAS) to produce a snow classification system for the western U.S. and Great Plains. To meet the outlined criterion, we initially explored the ability of a large number of metrics (13) to characterize the amount, timing, and melt-rate of snowpack. Principal components analysis and pairwise correlations were used to identify a subset of metrics (6) that captured the variance of the system but also contributed unique information. K-means was used to delineate 12 process-based groups that reveal both climatic and orographic influences on snowpack accumulation, timing, and melt rate. The important effects of elevation-mediated processes in our classification system suggest a greater spatial diversity in snowpack patterns than suggested by previous characterizations (e.g. maritime-to-continental). Application of the system from the early 2000's to present reveals that interannual temporal and spatial variability have been greatest in the Columbia Plateau

  7. Spatial and temporal variability of groundwater recharge in Geba basin, Northern Ethiopia

    Science.gov (United States)

    Yenehun, Alemu; Walraevens, Kristine; Batelaan, Okke

    2017-10-01

    WetSpa, a physically based, spatially distributed watershed model, has been used to study the spatial and temporal variation of recharge in the Geba basin, Northern Ethiopia. The model covers an area of about 4, 249 km2 and integrates elevation, soil and land-use data, hydrometeorological and river discharge data. The Geba basin has a highly variable topography ranging from 1000 to 3280 m with an average slope of 12.9%. The area is characterized by a distinct wet and long dry season with a mean annual precipitation of 681 mm and temperatures ranging between 6.5 °C and 32 °C. The model was simulated on daily basis for nearly four years (January 1, 2000 to December 18, 2003). It resulted in a good agreement between measured and simulated streamflow hydrographs with Nash-Sutcliffe efficiency of almost 70% and 85% for, respectively, the calibration and validation. The water balance terms show very strong spatial and temporal variability, about 3.8% of the total precipitation is intercepted by the plant canopy; 87.5% infiltrates into the soil (of which 13% percolates, 2.7% flows laterally off and 84.2% evapotranspired from the root zone), and 7.2% is surface runoff. The mean annual recharge varies from about 45 mm (2003) to 208 mm (2001), with average of 98.6 mm/yr. On monthly basis, August has the maximum (73 mm) and December the lowest (0.1 mm) recharge. The mean annual groundwater recharge spatially varies from 0 to 371 mm; mainly controlled by the distribution of rainfall amount, followed by soil and land-use, and to a certain extent, slope. About 21% of Geba has a recharge larger than 120 mm and 1% less than 5 mm.

  8. Groundwater Quality: Analysis of Its Temporal and Spatial Variability in a Karst Aquifer.

    Science.gov (United States)

    Pacheco Castro, Roger; Pacheco Ávila, Julia; Ye, Ming; Cabrera Sansores, Armando

    2017-06-15

    This study develops an approach based on hierarchical cluster analysis for investigating the spatial and temporal variation of water quality governing processes. The water quality data used in this study were collected in the karst aquifer of Yucatan, Mexico, the only source of drinking water for a population of nearly two million people. Hierarchical cluster analysis was applied to the quality data of all the sampling periods lumped together. This was motivated by the observation that, if water quality does not vary significantly in time, two samples from the same sampling site will belong to the same cluster. The resulting distribution maps of clusters and box-plots of the major chemical components reveal the spatial and temporal variability of groundwater quality. Principal component analysis was used to verify the results of cluster analysis and to derive the variables that explained most of the variation of the groundwater quality data. Results of this work increase the knowledge about how precipitation and human contamination impact groundwater quality in Yucatan. Spatial variability of groundwater quality in the study area is caused by: a) seawater intrusion and groundwater rich in sulfates at the west and in the coast, b) water rock interactions and the average annual precipitation at the middle and east zones respectively, and c) human contamination present in two localized zones. Changes in the amount and distribution of precipitation cause temporal variation by diluting groundwater in the aquifer. This approach allows to analyze the variation of groundwater quality controlling processes efficiently and simultaneously. © 2017, National Ground Water Association.

  9. Possibility/Necessity-Based Probabilistic Expectation Models for Linear Programming Problems with Discrete Fuzzy Random Variables

    Directory of Open Access Journals (Sweden)

    Hideki Katagiri

    2017-10-01

    Full Text Available This paper considers linear programming problems (LPPs where the objective functions involve discrete fuzzy random variables (fuzzy set-valued discrete random variables. New decision making models, which are useful in fuzzy stochastic environments, are proposed based on both possibility theory and probability theory. In multi-objective cases, Pareto optimal solutions of the proposed models are newly defined. Computational algorithms for obtaining the Pareto optimal solutions of the proposed models are provided. It is shown that problems involving discrete fuzzy random variables can be transformed into deterministic nonlinear mathematical programming problems which can be solved through a conventional mathematical programming solver under practically reasonable assumptions. A numerical example of agriculture production problems is given to demonstrate the applicability of the proposed models to real-world problems in fuzzy stochastic environments.

  10. Unbiased split variable selection for random survival forests using maximally selected rank statistics.

    Science.gov (United States)

    Wright, Marvin N; Dankowski, Theresa; Ziegler, Andreas

    2017-04-15

    The most popular approach for analyzing survival data is the Cox regression model. The Cox model may, however, be misspecified, and its proportionality assumption may not always be fulfilled. An alternative approach for survival prediction is random forests for survival outcomes. The standard split criterion for random survival forests is the log-rank test statistic, which favors splitting variables with many possible split points. Conditional inference forests avoid this split variable selection bias. However, linear rank statistics are utilized by default in conditional inference forests to select the optimal splitting variable, which cannot detect non-linear effects in the independent variables. An alternative is to use maximally selected rank statistics for the split point selection. As in conditional inference forests, splitting variables are compared on the p-value scale. However, instead of the conditional Monte-Carlo approach used in conditional inference forests, p-value approximations are employed. We describe several p-value approximations and the implementation of the proposed random forest approach. A simulation study demonstrates that unbiased split variable selection is possible. However, there is a trade-off between unbiased split variable selection and runtime. In benchmark studies of prediction performance on simulated and real datasets, the new method performs better than random survival forests if informative dichotomous variables are combined with uninformative variables with more categories and better than conditional inference forests if non-linear covariate effects are included. In a runtime comparison, the method proves to be computationally faster than both alternatives, if a simple p-value approximation is used. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  11. Diurnal spatial variability of soil respiration estimated by ordinary kriging and sequential Gaussian simulation

    Science.gov (United States)

    de Bortoli Teixeira, Daniel; Rodrigo Panosso, Alan; Tadeu Pereira, Gener; Pelegrino Cerri, Carlos Eduardo; La Scala, Newton, Jr.

    2010-05-01

    The role of greenhouse gases in the climate change is well know, however, the balance of greenhouse gases due to land use and management is still lacking. Hence it is important to characterize the main aspects of soil respiration (or soil CO2 emission) in agricultural areas, including its spatial variability, as quantitatively as possible. The objective of this work was to study the diurnal spatial variability of the soil respiration including their estimations by different methods: ordinary kriging and sequential Gaussian simulation. Evaluations were conducted in a regular grid having 64 points installed over a bare Eutrustox clay texture during the morning and afternoon periods. Measurements were conducted from 7:30 - 10:30 am (morning) and 13:30 - 16:30 pm (afternoon) using a portable soil respiration system (LI-8100), Lincoln, NE, USA. In order to estimate the best interpolation method it was applied the so-called external validation, where the respiration values of 5 points in grid were removed from interpolation process and after were estimated in the same points by kriging or sequential Gaussian simulation methods. This evaluation was also based on the sum of the square of residues, comparing observed with predicted respiration values in each of the 5 points selected for external validation. The highest CO2 emission was observed in the afternoon period, with mean value of 6.24 µmol m-2 s-1, when compared to the morning (4.54 µmol m-2 s-1). Our results indicate that the measurement period (morning or afternoon) did not interfere into the definition of emission spatial variability structure, as coefficient of variation, spatial variability models and their parameters were quite similar in morning and afternoon. However, despite the high correlation between kriging and sequential Gaussian simulation respiration maps (R2 =0.99) sequential Gaussian simulation showed to be more efficient into the estimations of non-sampled emissions in both periods, mornings and

  12. Understanding the Temporal and Spatial Variability of New Generation Gridded TMYs

    Energy Technology Data Exchange (ETDEWEB)

    Lopez, Anthony

    2017-04-26

    Presentation at ASHRAE about the spatial and temporal variability of gridded TMYs, discussing advanced GIS and Web services that allow for direct access to data, surface-based observations for thousands of stations, climate reanalysis data, and products derived from satellite data; new developments in NREL's solar databases based on both observed data and satellite-derived gridded data, status of TMY3 weather files, and NREL's plans for the next-generation TMY weather files; and also covers what is new and different in the Climatic Design Conditions Table in the 2013 ASHRAE Handbook of Fundamentals.

  13. Assessment of spatial variability of soil thermal properties in cultivated field

    Science.gov (United States)

    Usowicz, Boguslaw; Lipiec, Jerzy

    2017-04-01

    Most of soil physical properties are spatially variable both in regional and field scale. Spatial heterogeneity of soil properties in the field is related to the nature of the soil itself, but some of the variation is caused by tillage and other management practices. The aim of this work was to determine spatial variability of thermal properties on the cultivated field (40 x 350 m) using geostatistical method. The present work used data obtained from the measurements of topsoil soil texture (sand, silt and clay content), organic carbon, water content, bulk density, particle density, thermal conductivity, heat capacity and thermal diffusivity after harvest of triticale. The measurements were done in 45 points using TDR and KD2Pro for soil water content and thermal properties, respectively. Moreover, measurements of the thermal properties were performed in the laboratory at dry and saturated soil. The coefficient of variations (CV) varied from 1.6% for the particle density to 67% for the clay content. Among the thermal properties the most variable was thermal diffusivity at saturation (24%) and the least variable thermal conductivity in dry state (8.4%). The exponential semivariogram models matched well with empirical semivariogram. The range of the thermal properties measured in the field varied from 10 m for the thermal diffusivity to 23 m for the thermal conductivity. The ranges in dry and saturated soil were greater than at field water content. Among the remaining properties the largest range of the semivariograms was for soil textural fractions (100-250 m) and bulk density (145 m) and the lowest water content (14 m). This indicates that the thermal properties were resultant of both soil water content and bulk density. Most of the soil properties exhibited strong and moderate spatial dependency. Heterogeneity and variation of soil physical and thermal parameters in a field due to soil cultivation should be taken into consideration for a successful agricultural

  14. Including slope length in stochastic representations of runoff generation and connectivity under spatially variable conditions

    Science.gov (United States)

    Sheridan, Gary; Jones, Owen; Lane, Patrick; Noske, Philip; Smith, Hugh

    2010-05-01

    Hydrologic connectivity describes the influence of the intrinsic organisation of heterogeneities on the global behaviour of the hydrologic system that contains those heterogeneities. Connectivity can be usefully divided into structural connectivity, the description of continuum properties of state variables, and functional connectivity, describing the effect of heterogeneities on the rate of water transfer within such a system. In this paper we further develop and test functional connectivity equations, developed from stochastic theory, that quantify the effect of the spatial variability and arrangement of rainfall and soil properties on steady-state; i) infiltration-excess runoff delivery at a downslope boundary, and ii) the distribution of the "connected length", the upslope length with a continuous runoff pathway adjacent to the downslope boundary. The accumulation and loss of runoff down a slope is represented as a first-in first-out (FIFO) GI/G/1 queuing system; the new solutions incorporating slope length effects are analytic approximations. Inspection of the resulting equations reveals many interesting relationships between spatial variability and runoff connectivity: for example, the runoff rate scales approximately linearly with both the square of the coefficient of variation of infiltration capacity and rainfall intensity. The connected length increases as a sigmoid function of the ratio of mean rainfall to mean infiltration capacity (known as the "traffic rate" in queue theory), with a steeper function when the spatial correlation scale is small. The analytic approximations are in excellent agreement with numerical simulations of runoff and connectivity under spatially variable conditions. The new analytic approximations are also compared with a range of data from field runoff and erosion experiments, including; • rainfall simulations at different plot lengths (0.1, 0.25, 0.5, 1.0, & 2m) and rainfall intensities (25, 50 100, 175mm h-1) for two

  15. Physical Activity, Mindfulness Meditation, or Heart Rate Variability Biofeedback for Stress Reduction: A Randomized Controlled Trial

    OpenAIRE

    van der Zwan, Judith Esi; de Vente, Wieke; Huizink, Anja C.; B?gels, Susan M.; de Bruin, Esther I.

    2015-01-01

    In contemporary western societies stress is highly prevalent, therefore the need for stress-reducing methods is great. This randomized controlled trial compared the efficacy of self-help physical activity (PA), mindfulness meditation (MM), and heart rate variability biofeedback (HRV-BF) in reducing stress and its related symptoms. We randomly allocated 126 participants to PA, MM, or HRV-BF upon enrollment, of whom 76 agreed to participate. The interventions consisted of psycho-education and a...

  16. SPATIAL VARIABILITY AND VITALITY OF EPIGEOUS TERMITE MOUNDS IN PASTURES OF MATO GROSSO DO SUL, BRAZIL

    Directory of Open Access Journals (Sweden)

    Sandra Santana Lima

    2015-02-01

    Full Text Available Epigeous termite mounds are frequently observed in pasture areas, but the processes regulating their population dynamics are poorly known. This study evaluated epigeous termite mounds in cultivated grasslands used as pastures, assessing their spatial distribution by means of geostatistics and evaluating their vitality. The study was conducted in the Cerrado biome in the municipality of Rio Brilhante, Mato Grosso do Sul, Brazil. In two pasture areas (Pasture 1 and Pasture 2, epigeous mounds (nests were georeferenced and analyzed for height, circumference and vitality (inhabited or not. The area occupied by the mounds was calculated and termite specimens were collected for taxonomic identification. The spatial distribution pattern of the mounds was analyzed with geostatistical procedures. In both pasture areas, all epigeous mounds were built by the same species, Cornitermes cumulans. The mean number of mounds per hectare was 68 in Pasture 1 and 127 in Pasture 2, representing 0.4 and 1 % of the entire area, respectively. A large majority of the mounds were active (vitality, 91 % in Pasture 1 and 84 % in Pasture 2. A “pure nugget effect” was observed in the semivariograms of height and nest circumference in both pastures reflecting randomized spatial distribution and confirming that the distribution of termite mounds in pastures had a non-standard distribution.

  17. APPROXIMATION TO OPTIMAL STOPPING RULES FOR GUMBEL RANDOM VARIABLES WITH UNKNOWN LOCATION AND SCALE PARAMETERS

    OpenAIRE

    Yeh, Tzu-Sheng; Lee, Shen-Ming

    2006-01-01

    An optimal stopping rule is a rule that stops the sampling process at a sample size n that maximizes the expected reward. In this paper we will study the approximation to optimal stopping rule for Gumbel random variables, because the Gumbel-type distribution is the most commonly referred to in discussions of extreme values. Let $X_1, X_2,\\cdots X_n,\\cdots$ be independent, identically distributed Gumbel random variables with unknown location and scale parameters,$\\alpha$ and $\\beta$. If we def...

  18. $\\Phi$-moment inequalities for independent and freely independent random variables

    OpenAIRE

    Jiao, Yong; Sukochev, Fedor; Xie, Guangheng; Zanin, Dmitriy

    2016-01-01

    This paper is devoted to the study of $\\Phi$-moments of sums of independent/freely independent random variables. More precisely, let $(f_k)_{k=1}^n$ be a sequence of positive (symmetrically distributed) independent random variables and let $\\Phi$ be an Orlicz function with $\\Delta_2$-condition. We provide an equivalent expression for the quantity $\\mathbb{E}(\\Phi(\\sum_{k=1}^n f_k))$ in term of the sum of disjoint copies of the sequence $(f_k)_{k=1}^n.$ We also prove an analogous result in the...

  19. Spatial representation and cognitive modulation of response variability in the lateral intraparietal area priority map.

    Science.gov (United States)

    Falkner, Annegret L; Goldberg, Michael E; Krishna, B Suresh

    2013-10-09

    The lateral intraparietal area (LIP) in the macaque contains a priority-based representation of the visual scene. We previously showed that the mean spike rate of LIP neurons is strongly influenced by spatially wide-ranging surround suppression in a manner that effectively sharpens the priority map. Reducing response variability can also improve the precision of LIP's priority map. We show that when a monkey plans a visually guided delayed saccade with an intervening distractor, variability (measured by the Fano factor) decreases both for neurons representing the saccade goal and for neurons representing the broad spatial surround. The reduction in Fano factor is maximal for neurons representing the saccade goal and steadily decreases for neurons representing more distant locations. LIP Fano factor changes are behaviorally significant: increasing expected reward leads to lower variability for the LIP representation of both the target and distractor locations, and trials with shorter latency saccades are associated with lower Fano factors in neurons representing the surround. Thus, the LIP Fano factor reflects both stimulus and behavioral engagement. Quantitative modeling shows that the interaction between mean spike count and target-receptive field (RF) distance in the surround during the predistractor epoch is multiplicative: the Fano factor increases more steeply with mean spike count further away from the RF. A negative-binomial model for LIP spike counts captures these findings quantitatively, suggests underlying mechanisms based on trial-by-trial variations in mean spike rate or burst-firing patterns, and potentially provides a principled framework to account simultaneously for the previously observed unsystematic relationships between spike rate and variability in different brain areas.

  20. Environmental controls on the spatial variability of soil water dynamics in a small watershed

    Science.gov (United States)

    Hu, Wei; Chau, Henry Wai; Qiu, Weiwen; Si, Bingcheng

    2017-08-01

    Soil water content (SWC) in the root zone is controlled by a suite of environmental variables. Complication arises from the cross-correlation between these environmental variables. Therefore, there is still a poor understanding on the controls of root zone SWC dynamics due, in part, to a lack of an appropriate method to untangle the controls. The objective of this study was to reveal the dominant controls of root zone soil water dynamics in a small watershed using an appropriate method based on empirical orthogonal function (EOF). For this purpose, SWC of 0-0.8 m layer in a small watershed on the Chinese Loess Plateau was used. The space-variant temporal anomaly (Rtn) of SWC, which is responsible for the spatial variability of soil water dynamics, was decomposed using the EOF. Results indicated that 86% of the total variations of Rtn were explained by three significant spatial structures (EOFs). Sand content and grass yield dominated the EOF1 of Rtn and elevation and aspect dominated EOF2 and EOF3 of Rtn , respectively. Moreover, their effects on soil water dynamics were time-dependent. The EOF analysis showed that three independent groups of factors (i.e., soil and vegetation dominated earth surface condition, elevation related near surface air humidity, and aspect regulated energy input) may drive the variability in soil water dynamics. Traditional correlation analysis, however, indicated that SWC was greater at higher elevation and sun-facing slopes, which distorted the soil water dynamics controls. Although original SWC-based partial correlation basically supported our findings, the results highly depended on the controlling factors selected. This study implied that Rtn rather than original SWC should be preferred for understanding soil water dynamics controls.

  1. Assessment of some soil properties by spatial variability in saline and sodic soils in Arsanjan plain, Southern Iran.

    Science.gov (United States)

    Emadi, Mostafa; Baghernejad, Majid; Emadi, Mehdi; Maftoun, Manouchehr

    2008-01-15

    Spatial patterns for several soil parameters such soil texture, Exchangeable Sodium Percentage (ESP), Electrical Conductivity (ECe), soil pH, Cation Exchange Capacity (CEC) were examined in saline and sodic soils in Arsanjan plain, Southern Iran, in order to identify their spatial distribution for implementation of a site-specific management. Soil samples were collected from 0-30, 30-60 and 60-90 cm soil depths at 85 sampling sites. Data were analyzed both statistically and geostatistically on the basis of the semivariogram. The spatial distribution model and spatial dependence level varied between soil parameters. Soil pH and ESP had the minimum and maximum variability at all depths, respectively. Soil properties indicated moderate to strong spatial dependence. ECe exhibited moderate spatial dependence at three depths; pH and ESP had a moderate spatial dependence at 0-30 cm and strong spatial dependence at 30-60 and 60-90 cm depths. Clay and CEC exhibited strong spatial dependence for the 0-30 cm and weak spatial dependence at 30-60 and 60-90 cm depths. Sand and silt had a non-spatial dependence at 0-30 cm and weak spatial dependency at 30-60 and 60-90 cm depths. The spatial variability in small distances of ECe, CEC, pH and ESP generally increased with depth. All geostatistical range values were greater than 1168 m. The results reported herein indicated that the strong spatial dependency of soil properties would lead to the extrinsic factors such as ground water level and drainage. It is important to know the spatial dependence of soil parameters, as management parameters with strong spatial dependence will be more readily managed and an accurate site-specific scheme for precision farming more easily developed.

  2. Multilevel discretized random field models with 'spin' correlations for the simulation of environmental spatial data

    Science.gov (United States)

    Žukovič, Milan; Hristopulos, Dionissios T.

    2009-02-01

    A current problem of practical significance is how to analyze large, spatially distributed, environmental data sets. The problem is more challenging for variables that follow non-Gaussian distributions. We show by means of numerical simulations that the spatial correlations between variables can be captured by interactions between 'spins'. The spins represent multilevel discretizations of environmental variables with respect to a number of pre-defined thresholds. The spatial dependence between the 'spins' is imposed by means of short-range interactions. We present two approaches, inspired by the Ising and Potts models, that generate conditional simulations of spatially distributed variables from samples with missing data. Currently, the sampling and simulation points are assumed to be at the nodes of a regular grid. The conditional simulations of the 'spin system' are forced to respect locally the sample values and the system statistics globally. The second constraint is enforced by minimizing a cost function representing the deviation between normalized correlation energies of the simulated and the sample distributions. In the approach based on the Nc-state Potts model, each point is assigned to one of Nc classes. The interactions involve all the points simultaneously. In the Ising model approach, a sequential simulation scheme is used: the discretization at each simulation level is binomial (i.e., ± 1). Information propagates from lower to higher levels as the simulation proceeds. We compare the two approaches in terms of their ability to reproduce the target statistics (e.g., the histogram and the variogram of the sample distribution), to predict data at unsampled locations, as well as in terms of their computational complexity. The comparison is based on a non-Gaussian data set (derived from a digital elevation model of the Walker Lake area, Nevada, USA). We discuss the impact of relevant simulation parameters, such as the domain size, the number of

  3. Higher order moments of a sum of random variables: remarks and applications.

    Directory of Open Access Journals (Sweden)

    Luisa Tibiletti

    1996-02-01

    Full Text Available The moments of a sum of random variables depend on both the pure moments of each random addendum and on the addendum mixed moments. In this note we introduce a simple measure to evaluate the relative impedance to attach to the latter. Once the pure moments are fixed, the functional relation between the random addenda leading to the extreme values is also provided. Applications to Finance, Decision Theory and Actuarial Sciences are also suggested.

  4. An analysis of noise reduction in variable reluctance motors using pulse position randomization

    Science.gov (United States)

    Smoot, Melissa C.

    1994-05-01

    The design and implementation of a control system to introduce randomization into the control of a variable reluctance motor (VRM) is presented. The goal is to reduce noise generated by radial vibrations of the stator. Motor phase commutation angles are dithered by 1 or 2 mechanical degrees to investigate the effect of randomization on acoustic noise. VRM commutation points are varied using a uniform probability density function and a 4 state Markov chain among other methods. The theory of VRM and inverter operation and a derivation of the major source of acoustic noise are developed. The experimental results show the effects of randomization. Uniform dithering and Markov chain dithering both tend to spread the noise spectrum, reducing peak noise components. No clear evidence is found to determine which is the optimum randomization scheme. The benefit of commutation angle randomization in reducing VRM loudness as perceived by humans is found to be questionable.

  5. Small Scale Spatial Variability of Apparent Electrical Conductivity within a Paddy Field

    Directory of Open Access Journals (Sweden)

    W. Aimrun

    2009-01-01

    Full Text Available Quick variability description is an important component for zone management practices. Precision farming requires topping up of only the nutrients that are lacking in the soil to attain the highest yield with the least input. The apparent soil electrical conductivity (ECa sensor is a useful tool in mapping to identify areas of contrasting soil properties. In nonsaline soils, ECa is a substitute measurement for soil texture. It is directly related to both water holding capacity and Cation Exchange Capacity (CEC, which are key ingredients of productivity. This sensor measures the ECa across a field quickly and gives detailed soil features (one-second interval with few operators. Hence, a dense sampling is possible and therefore a high-resolution ECa map can be produced. This study aims to characterize the variability of soil ECa within a Malaysian paddy field with respect to the spatial and seasonal variability. The study was conducted at Block C, Sawah Sempadan, Selangor, Malaysia, for three continuous seasons. Soil ECa was collected after harvesting period. The results showed that deep ECa visualized the pattern of the former river routes clearly as continuous lines (about 45 m width at the northern and central regions of the study area. This exploration has shown different maps with higher contrast as compared to the existing soil series map for the study area. Seasonal variability test showed that the ECa that was acquired during rainy season (collected after harvest in December to January has the highest value as compared to another season.

  6. Sulfur dioxide in the Venus Atmosphere: II. Spatial and temporal variability

    Science.gov (United States)

    Vandaele, A. C.; Korablev, O.; Belyaev, D.; Chamberlain, S.; Evdokimova, D.; Encrenaz, Th.; Esposito, L.; Jessup, K. L.; Lefèvre, F.; Limaye, S.; Mahieux, A.; Marcq, E.; Mills, F. P.; Montmessin, F.; Parkinson, C. D.; Robert, S.; Roman, T.; Sandor, B.; Stolzenbach, A.; Wilson, C.; Wilquet, V.

    2017-10-01

    The vertical distribution of sulfur species in the Venus atmosphere has been investigated and discussed in Part I of this series of papers dealing with the variability of SO2 on Venus. In this second part, we focus our attention on the spatial (horizontal) and temporal variability exhibited by SO2. Appropriate data sets - SPICAV/UV nadir observations from Venus Express, ground-based ALMA and TEXES, as well as UV observation on the Hubble Space Telescope - have been considered for this analysis. High variability both on short-term and short-scale are observed. The long-term trend observed by these instruments shows a succession of rapid increases followed by slow decreases in the SO2 abundance at the cloud top level, implying that the transport of air from lower altitudes plays an important role. The origins of the larger amplitude short-scale, short-term variability observed at the cloud tops are not yet known but are likely also connected to variations in vertical transport of SO2 and possibly to variations in the abundance and production and loss of H2O, H2SO4, and Sx.

  7. Spatial and temporal variability in summer snow pack in Dronning Maud Land, Antarctica

    Directory of Open Access Journals (Sweden)

    T. Vihma

    2011-03-01

    Full Text Available To quantify the spatial and temporal variability in the snow pack, field measurements were carried out during four summers in Dronning Maud Land, Antarctica. Data from a 310-km-long transect revealed the largest horizontal gradients in snow density, temperature, and hardness in the escarpment region. On the local scale, day-to-day temporal variability dominated the standard deviation of snow temperature, while the diurnal cycle was of second significance, and horizontal variability on the scale of 0.4 to 10 m was least important. In the uppermost 0.2 m, the snow temperature was correlated with the air temperature over the previous 6–12 h, whereas at the depths of 0.3 to 0.5 m the most important time scale was 3 days. Cloud cover and radiative fluxes affected the snow temperature in the uppermost 0.30 m and the snow density in the uppermost 0.10 m. Both on the intra-pit and transect scales, the ratio of horizontal to temporal variability increased with depth. The horizontal standard deviation of snow density increased rapidly between the scales of 0.4 and 2 m, and more gradually from 10 to 100 m. Inter-annual variations in snow temperature and density were due to inter-annual differences in air temperature and the timing of the precipitation events.

  8. On accommodating spatial interactions in a Generalized Heterogeneous Data Model (GHDM) of mixed types of dependent variables.

    Science.gov (United States)

    2015-12-01

    We develop an econometric framework for incorporating spatial dependence in integrated model systems of latent variables and multidimensional mixed data outcomes. The framework combines Bhats Generalized Heterogeneous Data Model (GHDM) with a spat...

  9. Assessing scales of spatial & temporal variability in radiocarbon contents of soil organic carbon

    Science.gov (United States)

    van der Voort, Tessa Sophia; Feng, Xiaojuan; Hagedorn, Frank; Eglinton, Timothy

    2014-05-01

    Soil organic matter (SOM) forms the largest terrestrial reservoir of carbon outside of sedimentary rocks and it provides the fundamental reservoir for nutrients that sustains vegetation and the microbial communities. With ongoing changes in land-use and climate, SOM is also subject to change, with potentially major consequences for soil as a resource and for global biogeochemical cycles. Radiocarbon is a powerful tool for assessing SOM dynamics and is increasingly used in studies of carbon turnover. However, due to the nature of the measurement, comprehensive 14C studies of soils systems are rare. In particular, information on spatial variability in the radiocarbon contents of soils is limited. The present study aims to develop and apply a comprehensive four-dimensional approach to explore heterogeneity in bulk SOM 14C, with a broader goal of assessing controls on organic matter stability and vulnerability in soils across Switzerland. Focusing on range of Swiss soil types, we examine lateral variability in 14C over plot (decimeter to meter) to regional scales, vertical variability from surface to deeper soil horizons, and temporal variability by comparing present-day with archived (legacy) samples. Preliminary results show that there are large differences in SOM 14C age across small lateral and vertical distances within soil systems. Ultimately, studies of bulk variability will be followed up with analyses of SOM sub-fractions, including 14C measurements at the molecular level. Investigating 14C variability over various space and time domains may shed light on the scales of processes that dictate the composition and vulnerability of SOM, and provide valuable constraints on models of SOM turnover.

  10. Spatial variability of microbial biomass and organic matter labile pools in a haplic planosol soil

    Directory of Open Access Journals (Sweden)

    Diego Campana Loureiro

    2010-01-01

    Full Text Available The objective of this work was to study the spatial variability of soil microbial biomass (SMB and labile soil organic matter pools (labile SOM, under different management systems and plant cover. The experiment was conducted in a Haplic Planosol soil on an Integrated Agroecological Production System (SIPA, in Seropédica, Rio de Janeiro. The evaluated management systems were: alley cropping, pasture, and bush garden, the late one was used as reference area. Three grids of regular spacing of 2.5 x 2.5 meters were used for sampling, consisting of 25 georeferenced points each, where soil samples were taken at 0-10 cm depth. The following labile constituents of soil organic matter were determined: free light fraction (FLF, water soluble C and N, C and N of SMB (SMB-C and SMB-N, and glomalin content. The textural fractions (sand, silt, and clay, pH in water, and chemical attributes (organic C, total N, Ca, Mg, Al, P, K, and CEC-cation exchange capacity were also determined. The areas of alley cropping and pasture showed spatial dependence to the attributes of SOM. The occurrence of high spatial dependence for the attributes associated to microbial biomass in the alley cropping system (C, FLF, SMB-N and respiration, probably was due to external factors related to management, such as: intensive rotational cropping system, diversity of crops and different inputs of organic matter to soil such as pruning material and organic compost.

  11. Temporal and Spatial Variability of Droughts in Southwest China from 1961 to 2012

    Directory of Open Access Journals (Sweden)

    Yaohuan Huang

    2015-10-01

    Full Text Available Southwest China (SC has suffered a series of super extreme droughts in the last decade. This study analyzed the temporal and spatial variations of drought in SC from 1961 to 2012. Based on precipitation anomaly index (PAI that was derived from 1 km gridded precipitation data, three time scales (month, year and decade for the drought frequency (DF and drought area were applied to estimate the spatio-temporal structure of droughts. A time-series analysis showed that winter droughts and spring droughts occurred frequently for almost half of the year from November to March. Summer droughts occasionally occurred in severe drought decades: the 1960s, 1980s and 2000s. During the period of observation, the percent of drought area in SC increased from the 1960s (<5% to the 2000s (>25%. A total of 57% of the area was affected by drought in 2011, when the area experienced its most severe drought both in terms of area and severity. The spatial analysis, which benefitted from the gridded data, detailed that all of SC is at drought risk except for the central Sichuan Basin. The area at high risk for severe and extreme droughts was localized in the mountains of the junction of Sichuan and Yunnan. The temporal and spatial variability can be prerequisites for drought resistance planning and drought risk management of SC.

  12. Implications of temporal variability for uncertainty in spatial interpretations of stream geochemistry data

    Science.gov (United States)

    Bearcock, Jenny; Lark, Murray

    2016-04-01

    Stream water is a key medium for regional geochemical survey. Stream water geochemical data have many potential applications, including mineral exploration, environmental monitoring and protection, catchment management and modelling potential impacts of climate or land use changes. However, stream waters are transient, and measurements are susceptible to various sources of temporal variation. In a regional geochemical survey stream water data comprise "snapshots" of the state of the medium at a sample time. For this reason the British Geological Survey (BGS) has included monitoring streams in its regional geochemical baseline surveys (GBASE) at which daily stream water samples are collected to supplement the spatial data collected in once-off sampling events. In this study we present results from spatio-temporal analysis of spatial stream water surveys and the associated monitoring stream data. We show how the interpretation of the temporal variability as a source of uncertainty depends on how the spatial data are interpreted (as estimates of a summer-time mean concentration, or as point measurements), and explore the implications of this uncertainty in the interpretation of stream water data in a regulatory context.

  13. A method for estimating spatially variable seepage and hydrualic conductivity in channels with very mild slopes

    Science.gov (United States)

    Shanafield, Margaret; Niswonger, Richard G.; Prudic, David E.; Pohll, Greg; Susfalk, Richard; Panday, Sorab

    2014-01-01

    Infiltration along ephemeral channels plays an important role in groundwater recharge in arid regions. A model is presented for estimating spatial variability of seepage due to streambed heterogeneity along channels based on measurements of streamflow-front velocities in initially dry channels. The diffusion-wave approximation to the Saint-Venant equations, coupled with Philip's equation for infiltration, is connected to the groundwater model MODFLOW and is calibrated by adjusting the saturated hydraulic conductivity of the channel bed. The model is applied to portions of two large water delivery canals, which serve as proxies for natural ephemeral streams. Estimated seepage rates compare well with previously published values. Possible sources of error stem from uncertainty in Manning's roughness coefficients, soil hydraulic properties and channel geometry. Model performance would be most improved through more frequent longitudinal estimates of channel geometry and thalweg elevation, and with measurements of stream stage over time to constrain wave timing and shape. This model is a potentially valuable tool for estimating spatial variability in longitudinal seepage along intermittent and ephemeral channels over a wide range of bed slopes and the influence of seepage rates on groundwater levels.

  14. Soil Moisture Controls for Spatial Variability for a Humid Forest Hillslope

    Science.gov (United States)

    Kim, S.; Gwak, Y.

    2016-12-01

    Soil moisture is an important variable in explaining hydrological processes at hillslope scale. The distribution of soil moisture along a hillslope is related to the spatial distribution of the soil properties, the topography, the soil depth, and the vegetation. In order to investigate the factors affecting soil moisture, various environmental data were collected from a humid forest hillslope in this study. Several factors (the wetness index; the contributing area; the local slope; the soil depth; the composition of sand, silt, and clay; the scaling parameter; the hydraulic conductivity; the tree diameter at breast height; and the total weighted basal area) were evaluated for their effect on soil moisture and its distribution over the hillslope at depths of 10, 30, and 60 cm. The relationships of the various factors with the spatial variability of soil moisture indicated the existence of a threshold soil moisture which is related to the composition of the soil and the factors related to the distribution of water in the study area.

  15. Providing a non-deterministic representation of spatial variability of precipitation in the Everest region

    Science.gov (United States)

    Eeckman, Judith; Chevallier, Pierre; Boone, Aaron; Neppel, Luc; De Rouw, Anneke; Delclaux, Francois; Koirala, Devesh

    2017-09-01

    This paper provides a new representation of the effect of altitude on precipitation that represents spatial and temporal variability in precipitation in the Everest region. Exclusive observation data are used to infer a piecewise linear function for the relation between altitude and precipitation and significant seasonal variations are highlighted. An original ensemble approach is applied to provide non-deterministic water budgets for middle and high-mountain catchments. Physical processes at the soil-atmosphere interface are represented through the Interactions Soil-Biosphere-Atmosphere (ISBA) surface scheme. Uncertainties associated with the model parametrization are limited by the integration of in situ measurements of soils and vegetation properties. Uncertainties associated with the representation of the orographic effect are shown to account for up to 16 % of annual total precipitation. Annual evapotranspiration is shown to represent 26 % ± 1 % of annual total precipitation for the mid-altitude catchment and 34% ± 3 % for the high-altitude catchment. Snowfall contribution is shown to be neglectable for the mid-altitude catchment, and it represents up to 44 % ± 8 % of total precipitation for the high-altitude catchment. These simulations on the local scale enhance current knowledge of the spatial variability in hydroclimatic processes in high- and mid-altitude mountain environments.

  16. Quantifying Spatial Variability of Selected Soil Trace Elements and Their Scaling Relationships Using Multifractal Techniques

    Science.gov (United States)

    Zhang, Fasheng; Yin, Guanghua; Wang, Zhenying; McLaughlin, Neil; Geng, Xiaoyuan; Liu, Zuoxin

    2013-01-01

    Multifractal techniques were utilized to quantify the spatial variability of selected soil trace elements and their scaling relationships in a 10.24-ha agricultural field in northeast China. 1024 soil samples were collected from the field and available Fe, Mn, Cu and Zn were measured in each sample. Descriptive results showed that Mn deficiencies were widespread throughout the field while Fe and Zn deficiencies tended to occur in patches. By estimating single multifractal spectra, we found that available Fe, Cu and Zn in the study soils exhibited high spatial variability and the existence of anomalies ([α(q)max−α(q)min]≥0.54), whereas available Mn had a relatively uniform distribution ([α(q)max−α(q)min]≈0.10). The joint multifractal spectra revealed that the strong positive relationships (r≥0.86, Ptrace elements as well as their scaling relationships can be characterized by single and joint multifractal parameters. The findings presented in this study could be extended to predict selected soil trace elements at larger regional scales with the aid of geographic information systems. PMID:23874944

  17. Spatial variability of N, P, and K in rice field in Sawah Sempadan, Malaysia

    Directory of Open Access Journals (Sweden)

    Saeed Mohamed Eltaib

    2002-04-01

    Full Text Available The variability of soil chemical properties such as total N, available P, and exchangeable K were examined on a 1.2 ha rice (Oryza sativa field. The soil (n = 72 samples were systematically taken from individual fields in Sawah Sempadan in thirty-six locations at two depths (0-20 and 20-30 cm. The Differential Global Positioning System (DGPS was used for locating the sample position. Geostatistical techniques were used to analyze the soil chemical properties variability of the samples that assist in site-specific management of the field. Results showed that areas of similarity were much greater for the soil chemical properties measured at the depth of (0-20 cm than that of the second lower (20- 30 cm. The ranges of the semivariogram for total N, available P, and exchangeable K were 12, and 13 m (0-20 cm, 12 and 38 m (20-30 cm, respectively. Point kriging calculated from the semivariogram was employed for spatial distribution map. The results suggested that soil chemical properties measured may be spatially dependent even within the small.

  18. Spatial variability of enthalpy in broiler house during the heating phase

    Directory of Open Access Journals (Sweden)

    Patrícia F. P. Ferraz

    2016-06-01

    Full Text Available ABSTRACT The thermal environment inside a broiler house has a great influence on animal welfare and productivity during the production phase. Enthalpy is a thermodynamic property that has been proposed to evaluate the internal broiler house environment, for being an indicator of the amount of energy contained in a mixture of water vapor and dry air. Therefore, this study aimed to characterize the spatial variability of enthalpy in a broiler house during the heating phase using geostatistics. The experiment was conducted in the spring season, in a commercial broiler house with heating system consisting of two furnaces that heat the air indirectly, in the first 14 days of the birds' life. It was possible to characterize enthalpy variability using geostatistical techniques, which allowed observing the spatial dependence through kriging maps. The analyses of the maps allowed observing problems in the heating system in regions inside the broiler house, which may cause a thermal discomfort to the animals besides productive and economic losses.

  19. Providing a non-deterministic representation of spatial variability of precipitation in the Everest region

    Directory of Open Access Journals (Sweden)

    J. Eeckman

    2017-09-01

    Full Text Available This paper provides a new representation of the effect of altitude on precipitation that represents spatial and temporal variability in precipitation in the Everest region. Exclusive observation data are used to infer a piecewise linear function for the relation between altitude and precipitation and significant seasonal variations are highlighted. An original ensemble approach is applied to provide non-deterministic water budgets for middle and high-mountain catchments. Physical processes at the soil–atmosphere interface are represented through the Interactions Soil–Biosphere–Atmosphere (ISBA surface scheme. Uncertainties associated with the model parametrization are limited by the integration of in situ measurements of soils and vegetation properties. Uncertainties associated with the representation of the orographic effect are shown to account for up to 16 % of annual total precipitation. Annual evapotranspiration is shown to represent 26 % ± 1 % of annual total precipitation for the mid-altitude catchment and 34% ± 3 % for the high-altitude catchment. Snowfall contribution is shown to be neglectable for the mid-altitude catchment, and it represents up to 44 % ± 8 % of total precipitation for the high-altitude catchment. These simulations on the local scale enhance current knowledge of the spatial variability in hydroclimatic processes in high- and mid-altitude mountain environments.

  20. Spatial and Temporal Variability of Winter Accumulation on Taku Glacier, Southeast Alaska, between 2012 and 2015

    Science.gov (United States)

    Smith, B.; Campbell, S. W.; Hollander, J.; Slavin, B. V.; Wolf, J.; Wilner, J.; Moore, T.

    2015-12-01

    Glacier mass balance is an integral part of understanding a glacier's health and dynamics. A key component of determining mass balance is winter accumulation which is traditionally estimated by digging and measuring snow densities from within snow pits. However, this method represents a labor-intensive point measurement which may not fully capture spatial variability of accumulation. To more efficiently estimate spatial variability of winter accumulation across Taku Glacier and its main tributaries in southeastern Alaska in 2015, we used a 400 MHz Ground Penetrating Radar (GPR) Common Offset (CO) surveys along centerline transects which were also collected during a 2012 study. We used common midpoint (CMP) surveys, migration, snow pits, and probing to improve depth estimates and provide ground truth of winter accumulation depth measurements from CO surveys. We determined that the winter accumulation was significantly lower in 2015 than in 2012. However, gradients in accumulation versus elevation were consistent from year to year along centerline transects. We suggest that this low accumulation may be influencing the recent two year stall of Taku Glacier which has exhibited an advancing terminus for nearly a century. We recommend that further studies be conducted to extend the reach of this dataset beyond 2 years. This data would be invaluable to future models and mass balance studies on the Icefield and may capture key components that suggest a tipping point from advance to retreat of Taku Glacier.

  1. Spatial variability of oceanic phycoerythrin spectral types derived from airborne laser-induced fluorescence emissions

    Science.gov (United States)

    Hoge, Frank E.; Wright, C. Wayne; Kana, Todd M.; Swift, Robert N.; Yungel, James K.

    1998-07-01

    We report spatial variability of oceanic phycoerythrin spectral types detected by means of a blue spectral shift in airborne laser-induced fluorescence emission. The blue shift of the phycoerythrobilin fluorescence is known from laboratory studies to be induced by phycourobilin chromophore substitution at phycoerythrobilin chromophore sites in some strains of phycoerythrin-containing marine cyanobacteria. The airborne 532-nm laser-induced phycoerythrin fluorescence of the upper oceanic volume showed distinct segregation of cyanobacterial chromophore types in a flight transect from coastal water to the Sargasso Sea in the western North Atlantic. High phycourobilin levels were restricted to the oceanic (oligotrophic) end of the flight transect, in agreement with historical ship findings. These remotely observed phycoerythrin spectral fluorescence shifts have the potential to permit rapid, wide-area studies of the spatial variability of spectrally distinct cyanobacteria, especially across interfacial regions of coastal and oceanic water masses. Airborne laser-induced phytoplankton spectral fluorescence observations also further the development of satellite algorithms for passive detection of phytoplankton pigments. Optical modifications to the NASA Airborne Oceanographic Lidar are briefly described that permitted observation of the fluorescence spectral shifts.

  2. The Significance of the Spatial Variability of Rainfall on the Numerical Simulation of Urban Floods

    Directory of Open Access Journals (Sweden)

    Laurent Guillaume Courty

    2018-02-01

    Full Text Available The growth of urban population, combined with an increase of extreme events due to climate change call for a better understanding and representation of urban floods. The uncertainty in rainfall distribution is one of the most important factors that affects the watershed response to a given precipitation event. However, most of the investigations on this topic have considered theoretical scenarios, with little reference to case studies in the real world. This paper incorporates the use of spatially-variable precipitation data from a long-range radar in the simulation of the severe floods that impacted the city of Hull, U.K., in June 2007. This radar-based rainfall field is merged with rain gauge data using a Kriging with External Drift interpolation technique. The utility of this spatially-variable information is investigated through the comparison of computed flooded areas (uniform and radar against those registered by public authorities. Both results show similar skills at reproducing the real event, but differences in the total precipitated volumes, water depths and flooded areas are illustrated. It is envisaged that in urban areas and with the advent of higher resolution radars, these differences will be more important and call for further investigation.

  3. Hot spots of mercury methylation in northern peatlands : spatial and seasonal variability

    Energy Technology Data Exchange (ETDEWEB)

    Mitchell, C.P.J.; Branfireun, B.A. [Toronto Univ., ON (Canada). Dept. of Geography; Heyes, A. [Maryland Univ., Solomons, MD (United States). Center for Environmental Science, Chesapeake Biological Lab; Kolka, R.K. [USDA Forest Service, North Central Research Station, Grand Rapids, MN (United States)

    2006-07-01

    Studies have shown that peatlands are an important sources of methylmercury (MeHg) to downstream aquatic ecosystems at the watershed scale. Hot spots of overly high MeHg concentration have been found to occur periodically in zones of groundwater upwelling. However, the spatiotemporal distribution, size, and importance of these MeHg hot spots to peatland MeHg export are not currently understood. For that reason, peat pore waters were sampled extensively throughout 4 small, northern peatlands in order to assess the spatial patterns of total mercury (HgT) and MeHg. The transferability of findings among peatlands was also assessed. Sampling took place during the spring, mid-summer and fall of 2005 at 2 peatlands in north central Minnesota and 2 in northwestern Ontario. In addition to this spatial survey, 4 high-resolution sampling grids were also established at the Minnesota sites in order to investigate the size of hot spots and the effects of upland runoff. In all cases, spatial variability in pore water MeHg concentration was much higher than the variability in HgT concentration, with standard deviations typically exceeding mean values. The spatial pattern of pore water MeHg concentration was characterized into the following 2 distinct zones: (1) the upland-peatland interface, where MeHg concentrations higher than 2 ng/L occur consistently, (2) the peatland interior, where concentrations rarely exceed 0.5 ng/L. In addition, extremely high concentrations of up to 12 ng/L were only found at the upland-peatland interface. These values corresponded to MeHg:HgT ratios greater than 65 per cent, while these ratios rarely exceeded 5 to 10 per cent elsewhere. It was concluded that these hot spots can be attributed to the limited reactants in zones where the in-situ biogeochemical milieu is conducive to mercury methylation. The uniform patterns noted across the peatlands indicate that spatial patterns of HgT and MeHg are important for mechanistic modelling and landscape

  4. Spatial variability of forest infection with Yellow Mistletoe (Loranthus europaeus) in Zagros forests of Iran using IDW and Kriging methods

    OpenAIRE

    SARAJ, Bahareh Sohrabi; KIADALIRI, Hadi; KAFAKI, Sasan Babaei; Akhavan, Reza

    2015-01-01

    Abstract. Yellow Mistletoe (Loranthus europaeus) is one of the impacting pathogens in the Zagros forests of Iran. Spatial variability and mapping of this agent are important for its control and management. For this purpose, a forest patch of 37 ha in the Ilam province of Iran was selected, and 541 individual trees in 27 transects for species, severity and density of infections with Yellow Mistletoe as well as Cartesian coordinates were considered. To investigate the spatial variability and ma...

  5. Spatial prediction of the variability of Early Pleistocene subsurface sediments in the Netherlands - Part 1 : Heavy minerals

    NARCIS (Netherlands)

    Huisman, D.J.; Weijers, J.P.; Dijkshoorn, L.; Veldkamp, A.

    2000-01-01

    We investigated the spatial variability of the heavy-mineral composition in the Early Pleistocene fluviatile Kedichem Formation in the Netherlands in order to meet the demand for more information about subsurface sediment composition. We first determined the spatial extension and thickness of the

  6. Spatial prediction of the variability of early pleistocene subsurface sediments in the Netherlands - part 1: Heavy minerals

    NARCIS (Netherlands)

    Huisman, D.J.; Weijers, J.P.; Dijkshoorn, L.; Veldkamp, A.

    2000-01-01

    We investigated the spatial variability of the heavy-mineral composition in the Early Pleistocene fluviatile Kedichem Formation in the Netherlands in order to meet the demand for more information about subsurface sediment composition.We first determined the spatial extension and thickness of the

  7. Spatial analysis and modeling of climate variables in the Cuitzeo Basin, Mexico

    Directory of Open Access Journals (Sweden)

    Oscar Adrián Leal Nares

    2010-09-01

    Full Text Available Climatic information with sufficient quality and spatially distributed is an essential requirement for developing research in several disciplines, such as Hydrology, Agronomy, Climatology and Ecology. In the present paper we attempt to reach to a model of the spatial distribution of precipitation and temperature in the lake Cuitzeo basin, based on interpolation methods using climatic and geographic variables and supported by the application of correlation analysis, simple and multiple regression and the use of geographic information systems. Three models were developed: one including 17 stations within the basin (Basin model; a second including 24 stations located at less than 10 km from the basin’s water shed (Buffer 10 model; and a third using 30 stations located at less than 20 km from the catchment’s water divide (Buffer 20 model. Based on the results of confidence analysis, the final average temperature map was the regression map resulting from the Buffer 20 model corrected by the addition of the anomaly map, with R2=0.72 and RMSE of 0.64 oC. In precipitation maps, the highest confidence results were derived from the data from the Buffer 20 model. The final annual precipitation map was obtained from the regression map without correction by residuals, with R2=0.746 and RMSE=55.51 oC. Confidence analysis shows that both models had statistically significant determination coefficients (Prob. > F=0.05, however, models could be improved by the availability of more stations within the basin, given that the quantity and quality of data is a variable having an effect on the output of model application. The resulting final maps are relevant for modeling the spatial distribution of types of vegetation cover and of plant species, because climate, together with altitude, slope, exposure and other factors, is fundamental for determining the distribution of plant communities and of their component species.

  8. Spatial variability of shortwave radiative fluxes in the context of snowmelt

    Science.gov (United States)

    Pinker, Rachel T.; Ma, Yingtao; Hinkelman, Laura; Lundquist, Jessica

    2014-05-01

    Snow-covered mountain ranges are a major source of water supply for run-off and groundwater recharge. Snowmelt supplies as much as 75% of surface water in basins of the western United States. Factors that affect the rate of snow melt include incoming shortwave and longwave radiation, surface albedo, snow emissivity, snow surface temperature, sensible and latent heat fluxes, ground heat flux, and energy transferred to the snowpack from deposited snow or rain. The net radiation generally makes up about 80% of the energy balance and is dominated by the shortwave radiation. Complex terrain poses a great challenge for obtaining the needed information on radiative fluxes from satellites due to elevation issues, spatially-variable cloud cover, rapidly changing surface conditions during snow fall and snow melt, lack of high quality ground truth for evaluation of the satellite based estimates, as well as scale issues between the ground observations and the satellite footprint. In this study we utilize observations of high spatial resolution (5-km) as available from the Moderate Resolution Imaging Spectro-radiometer (MODIS) to derive surface shortwave radiative fluxes in complex terrain, with attention to the impact of slopes on the amount of radiation received. The methodology developed has been applied to several water years (January to July during 2003, 2004, 2005 and 2009) over the western part of the United States, and the available information was used to derive metrics on spatial and temporal variability in the shortwave fluxes. It is planned to apply the findings from this study for testing improvements in Snow Water Equivalent (SWE) estimates.

  9. Drivers for spatial variability in agricultural soil organic carbon stocks in Germany

    Science.gov (United States)

    Vos, Cora; Don, Axel; Hobley, Eleanor; Prietz, Roland; Heidkamp, Arne; Freibauer, Annette

    2017-04-01

    Soil organic carbon is one of the largest components of the global carbon cycle. It has recently gained importance in global efforts to mitigate climate change through carbon sequestration. In order to find locations suitable for carbon sequestration, and estimate the sequestration potential, however, it is necessary to understand the factors influencing the high spatial variability of soil organic carbon stocks. Due to numerous interacting factors that influence its dynamics, soil organic carbon stocks are difficult to predict. In the course of the German Agricultural Soil Inventory over 2500 agricultural sites were sampled and their soil organic carbon stocks determined. Data relating to more than 200 potential drivers of SOC stocks were compiled from laboratory measurements, farmer questionnaires and climate stations. The aims of this study were to 1) give an overview of soil organic carbon stocks in Germany's agricultural soils, 2) to quantify and explain the influence of explanatory variables on soil organic carbon stocks. Two different machine learning algorithms were used to identify the most important variables and multiple regression models were used to explore the influence of those variables. Models for predicting carbon stocks in different depth increments between 0-100 cm were developed, explaining up to 62% (validation, 98% calibration) of total variance. Land-use, land-use history, clay content and electrical conductivity were main predictors in the topsoil, while bedrock material, relief and electrical conductivity governed the variability of subsoil carbon stocks. We found 32% of all soils to be deeply anthropogenically transformed. The influence of climate related variables was surprisingly small (≤5% of explained variance), while site variables explained a large share of soil carbon variability (46-100% of explained variance), in particular in the subsoil. Thus, the understanding of SOC dynamics at regional scale requires a thorough description

  10. Hydrological response to changing climate conditions: Spatial streamflow variability in the boreal region

    Science.gov (United States)

    Teutschbein, Claudia; Grabs, Thomas; Karlsen, Reinert H.; Laudon, Hjalmar; Bishop, Kevin

    2016-04-01

    It has long been recognized that streamflow-generating processes are not only dependent on climatic conditions, but also affected by physical catchment properties such as topography, geology, soils and land cover. We hypothesize that these landscape characteristics do not only lead to highly variable hydrologic behavior of rather similar catchments under the same stationary climate conditions (Karlsen et al., 2014), but that they also play a fundamental role for the sensitivity of a catchment to a changing climate (Teutschbein et al., 2015). A multi-model ensemble based on 15 regional climate models was combined with a multi-catchment approach to explore the hydrologic sensitivity of 14 partially nested and rather similar catchments in Northern Sweden to changing climate conditions and the importance of small-scale spatial variability. Current (1981-2010) and future (2061-2090) streamflow was simulated with the HBV model. As expected, projected increases in temperature and precipitation resulted in increased total available streamflow, with lower spring and summer flows, but substantially higher winter streamflow. Furthermore, significant changes in flow durations with lower chances of both high and low flows can be expected in boreal Sweden in the future. This overall trend in projected streamflow pattern changes was comparable among the analyzed catchments while the magnitude of change differed considerably. This suggests that catchments belonging to the same region can show distinctly different degrees of hydrological responses to the same external climate change signal. We reason that differences in spatially distributed physical catchment properties at smaller scales are not only of great importance for current streamflow behavior, but also play a major role as first-order control for the sensitivity of catchments to changing climate conditions. References Karlsen, R.H., T. Grabs, K. Bishop, H. Laudon, and J. Seibert (2014). Landscape controls on

  11. Assimilation of temperature and hydraulic gradients for quantifying the spatial variability of streambed hydraulics

    Science.gov (United States)

    Huang, Xiang; Andrews, Charles B.; Liu, Jie; Yao, Yingying; Liu, Chuankun; Tyler, Scott W.; Selker, John S.; Zheng, Chunmiao

    2016-08-01

    Understanding the spatial and temporal characteristics of water flux into or out of shallow aquifers is imperative for water resources management and eco-environmental conservation. In this study, the spatial variability in the vertical specific fluxes and hydraulic conductivities in a streambed were evaluated by integrating distributed temperature sensing (DTS) data and vertical hydraulic gradients into an ensemble Kalman filter (EnKF) and smoother (EnKS) and an empirical thermal-mixing model. The formulation of the EnKF/EnKS assimilation scheme is based on a discretized 1D advection-conduction equation of heat transfer in the streambed. We first systematically tested a synthetic case and performed quantitative and statistical analyses to evaluate the performance of the assimilation schemes. Then a real-world case was evaluated to calculate assimilated specific flux. An initial estimate of the spatial distributions of the vertical hydraulic gradients was obtained from an empirical thermal-mixing model under steady-state conditions using a constant vertical hydraulic conductivity. Then, this initial estimate was updated by repeatedly dividing the assimilated specific flux by estimates of the vertical hydraulic gradients to obtain a refined spatial distribution of vertical hydraulic gradients and vertical hydraulic conductivities. Our results indicate that optimal parameters can be derived with fewer iterations but greater simulation effort using the EnKS compared with the EnKF. For the field application in a stream segment of the Heihe River Basin in northwest China, the average vertical hydraulic conductivities in the streambed varied over three orders of magnitude (5 × 10-1 to 5 × 102 m/d). The specific fluxes ranged from near zero (qz fish spawning and other wildlife incubation, regional flow and hyporheic solute transport models in the Heihe River Basin, as well as in other similar hydrologic settings.

  12. Mineralogy of the clay fraction of Alfisols in two slope curvatures: III - spatial variability

    Directory of Open Access Journals (Sweden)

    Livia Arantes Camargo

    2013-04-01

    Full Text Available A good knowledge of the spatial distribution of clay minerals in the landscape facilitates the understanding of the influence of relief on the content and crystallographic attributes of soil minerals such as goethite, hematite, kaolinite and gibbsite. This study aimed at describing the relationships between the mineral properties of the clay fraction and landscape shapes by determining the mineral properties of goethite, hematite, kaolinite and gibbsite, and assessing their dependence and spatial variability, in two slope curvatures. To this end, two 100 × 100 m grids were used to establish a total of 121 regularly spaced georeferenced sampling nodes 10 m apart. Samples were collected from the layer 0.0-0.2 m and analysed for iron oxides, and kaolinite and gibbsite in the clay fraction. Minerals in the clay fraction were characterized from their X-ray diffraction (XRD patterns, which were interpreted and used to calculate the width at half height (WHH and mean crystallite dimension (MCD of iron oxides, kaolinite, and gibbsite, as well as aluminium substitution and specific surface area (SSA in hematite and goethite. Additional calculations included the goethite and hematite contents, and the goethite/(goethite+hematite [Gt/(Gt+Hm] and kaolinite/(kaolinite+gibbsite [Kt/(Kt+Gb] ratios. Mineral properties were established by statistical analysis of the XRD data, and spatial dependence was assessed geostatistically. Mineralogical properties differed significantly between the convex area and concave area. The geostatistical analysis showed a greater number of mineralogical properties with spatial dependence and a higher range in the convex than in the concave area.

  13. Spatial Variability in Enceladus' Plume Material: Convergence of Evidence or Coincidence?

    Science.gov (United States)

    Dhingra, Deepak; Hedman, Matthew M.; Clark, Roger Nelson

    2016-10-01

    Systematic spatial trends in the properties of the plume material emerging from Enceladus' tiger stripes can be observed in multiple observations from the Cassini mission. Subtle near infrared spectral differences within the plume have been reported across tiger stripes based on Visual and Infrared Mapping Spectrometer (VIMS) observations at high spatial resolution [1]. These spectral differences are likely due to variable water-ice grain size distribution along the source fissures (i.e. tiger stripes) and perhaps by the presence/absence of water vapor emission [2]. We now report a correlation of this spatial trend (along tiger stripes) with several other published results including (a) differences in the ice particle sizes across tiger stripes on Enceladus' surface [3, 4], (b) the surface abundance of organic material [3] and finally, (c) the relative proportion of type II grains (associated with organic/siliceous material) in the plume [5] from Damascus to Alexandria as measured by the Cosmic Dust Analyzer (CDA) instrument.The general trend indicates that at least some of the plume properties (viz. particle size, organic abundance) achieve a peak over Damascus and then become gradually subtle towards Alexandria. The observed differences between tiger stripes eruptions and the nature of correlations (trends from Damascus to Alexandria) hold important clues to the subsurface environment at Enceladus including differences in the geological setting of the individual tiger stripes [6]. The latter is a likely possibility given the large spatial spread of eruptions in Encealdus' South Polar Terrain (SPT).[1] Dhingra et al., (2015) 46th Lunar Planet. Sci. Conf., Abstract#1648[2] Dhingra et al. (2016) Icarus, submitted[3] Brown et al. (2006) Science, 311, 1425-1428[4] Jaumann et al. (2008) Icarus, 193, 407-419[5] Postberg et al. (2011) Nature, doi:10.1038/nature10175[6] Yin and Pappalardo (2015) Icarus, 260, 409-439

  14. Spatial variability of soil available phosphorous and potassium at three different soils located in Pannonian Croatia

    Science.gov (United States)

    Bogunović, Igor; Pereira, Paulo; Đurđević, Boris

    2017-04-01

    Information on spatial distribution of soil nutrients in agroecosystems is critical for improving productivity and reducing environmental pressures in intensive farmed soils. In this context, spatial prediction of soil properties should be accurate. In this study we analyse 704 data of soil available phosphorus (AP) and potassium (AK); the data derive from soil samples collected across three arable fields in Baranja region (Croatia) in correspondence of different soil types: Cambisols (169 samples), Chernozems (131 samples) and Gleysoils (404 samples). The samples are collected in a regular sampling grid (distance 225 x 225 m). Several geostatistical techniques (Inverse Distance to a Weight (IDW) with the power of 1, 2 and 3; Radial Basis Functions (RBF) - Inverse Multiquadratic (IMT), Multiquadratic (MTQ), Completely Regularized Spline (CRS), Spline with Tension (SPT) and Thin Plate Spline (TPS); and Local Polynomial (LP) with the power of 1 and 2; two geostatistical techniques -Ordinary Kriging - OK and Simple Kriging - SK) were tested in order to evaluate the most accurate spatial variability maps using criteria of lowest RMSE during cross validation technique. Soil parameters varied considerably throughout the studied fields and their coefficient of variations ranged from 31.4% to 37.7% and from 19.3% to 27.1% for soil AP and AK, respectively. The experimental variograms indicate a moderate spatial dependence for AP and strong spatial dependence for all three locations. The best spatial predictor for AP at Chernozem field was Simple kriging (RMSE=61.711), and for AK inverse multiquadratic (RMSE=44.689). The least accurate technique was Thin plate spline (AP) and Inverse distance to a weight with a power of 1 (AK). Radial basis function models (Spline with Tension for AP at Gleysoil and Cambisol and Completely Regularized Spline for AK at Gleysol) were the best predictors, while Thin Plate Spline models were the least accurate in all three cases. The best

  15. Saddlepoint approximations for the sum of independent non-identically distributed binomial random variables

    NARCIS (Netherlands)

    Eisinga, R.N.; Grotenhuis, H.F. te; Pelzer, B.J.

    2013-01-01

    We discuss saddlepoint approximations to the distribution of the sum of independent non-identically distributed binomial random variables. We examine the accuracy of the saddlepoint methods for a sum of 10 binomials with different sets of parameter values. The numerical results indicate that the

  16. Physical activity, mindfulness meditation, or heart rate variability biofeedback for stress reduction: a randomized controlled trial

    NARCIS (Netherlands)

    van der Zwan, J.E.; de Vente, W.; Huizink, A.C.; Bögels, S.M.; de Bruin, E.I.

    2015-01-01

    In contemporary western societies stress is highly prevalent, therefore the need for stress-reducing methods is great. This randomized controlled trial compared the efficacy of self-help physical activity (PA), mindfulness meditation (MM), and heart rate variability biofeedback (HRV-BF) in reducing

  17. Some Generalized Inequalities Involving Local Fractional Integrals and their Applications for Random Variables and Numerical Integration

    Directory of Open Access Journals (Sweden)

    Erden S.

    2016-12-01

    Full Text Available We establish generalized pre-Grüss inequality for local fractional integrals. Then, we obtain some inequalities involving generalized expectation, p−moment, variance and cumulative distribution function of random variable whose probability density function is bounded. Finally, some applications for generalized Ostrowski-Grüss inequality in numerical integration are given.

  18. Bounds for right tails of deterministic and stochastic sums of random variables

    NARCIS (Netherlands)

    Darkiewicz, G.; Deelstra, G.; Dhaene, J.; Hoedemakers, T.; Vanmaele, M.

    2009-01-01

    We investigate lower and upper bounds for right tails (stop-loss premiums) of deterministic and stochastic sums of nonindependent random variables. The bounds are derived using the concepts of comonotonicity, convex order, and conditioning. The performance of the presented approximations is

  19. Spatial and Temporal Variability of Surface Energy Fluxes During Autumn Ice Advance: Observations and Model Validation

    Science.gov (United States)

    Persson, O. P. G.; Blomquist, B.; Grachev, A. A.; Guest, P. S.; Stammerjohn, S. E.; Solomon, A.; Cox, C. J.; Capotondi, A.; Fairall, C. W.; Intrieri, J. M.

    2016-12-01

    From Oct 4 to Nov 5, 2015, the Office of Naval Research - sponsored Sea State cruise in the Beaufort Sea with the new National Science Foundation R/V Sikuliaq obtained extensive in-situ and remote sensing observations of the lower troposphere, the advancing sea ice, wave state, and upper ocean conditions. In addition, a coupled atmosphere, sea ice, upper-ocean model, based on the RASM model, was run at NOAA/PSD in a hindcast mode for this same time period, providing a 10-day simulation of the atmosphere/ice/ocean evolution. Surface energy fluxes quantitatively represent the air-ice, air-ocean, and ice-ocean interaction processes, determining the cooling (warming) rate of the upper ocean and the growth (melting) rate of sea ice. These fluxes also impact the stratification of the lower troposphere and the upper ocean. In this presentation, both direct and indirect measurements of the energy fluxes during Sea State will be used to explore the spatial and temporal variability of these fluxes and the impacts of this variability on the upper ocean, ice, and lower atmosphere during the autumn ice advance. Analyses have suggested that these fluxes are impacted by atmospheric synoptic evolution, proximity to existing ice, ice-relative wind direction, ice thickness and snow depth. In turn, these fluxes impact upper-ocean heat loss and timing of ice formation, as well as stability in the lower troposphere and upper ocean, and hence heat transport to the free troposphere and ocean mixed-layer. Therefore, the atmospheric structure over the advancing first-year ice differs from that over the nearby open water. Finally, these observational analyses will be used to provide a preliminary validation of the spatial and temporal variability of the surface energy fluxes and the associated lower-tropospheric and upper-ocean structures in the simulations.

  20. Bayesian Clustering Using Hidden Markov Random Fields in Spatial Population Genetics

    Science.gov (United States)

    François, Olivier; Ancelet, Sophie; Guillot, Gilles

    2006-01-01

    We introduce a new Bayesian clustering algorithm for studying population structure using individually geo-referenced multilocus data sets. The algorithm is based on the concept of hidden Markov random field, which models the spatial dependencies at the cluster membership level. We argue that (i) a Markov chain Monte Carlo procedure can implement the algorithm efficiently, (ii) it can detect significant geographical discontinuities in allele frequencies and regulate the number of clusters, (iii) it can check whether the clusters obtained without the use of spatial priors are robust to the hypothesis of discontinuous geographical variation in allele frequencies, and (iv) it can reduce the number of loci required to obtain accurate assignments. We illustrate and discuss the implementation issues with the Scandinavian brown bear and the human CEPH diversity panel data set. PMID:16888334

  1. Spatial variability of solutes in stream water of the Anoia river basin

    Science.gov (United States)

    Rallo, Elena; Pacheco, Edinson; Úbeda, Xavier; Farguell, Joaquim

    2013-04-01

    The main aim of this study is to describe and understand the spatial variability of dissolved sediment in the Anoia river stream water: a Mediterranean basin under different land uses and economical activities. The Anoia river (926 km2) is a tributary basin of the Llobregat river (4900 km2), located in Catalonia, in the northeastern part of the Iberian Peninsula. Mediterranean climate type dominates the study area. The average flow near the river mouth is 2.37 m3/s and closely follows the rainfall pattern: monthly maximum discharges occur during spring months, while in summer they decrease drastically. Instantaneous peak discharges are the highest during autumn months (highest peak of the last ten years was 92 m3/s, registered in November 2011). Lithology is mainly sedimentary, being mostly marls, sandstones and gypsum in the upper part, and limestone and conglomerates domain the lower part. Land uses are varied: headwaters are basically occupied by lawns, dry winter cereal, and well structured riparian forests. The lower part of the basin is influenced by intensive vineyard agriculture, industry and major urban areas. Water sampling has been made on a fortnightly basis at five gauging stations during the hydrological year 2011-2012. Flow and water temperature were measured in situ, while electrical conductivity, total dissolved solids, pH, suspended sediment concentration and NO3-, NO22-, PO43- and HCO32- contents were determined at the Physical Geography laboratory of the University of Barcelona. Major cations are derived from analysis by ICP-MS technique by the Scientific-Technical Services of the University of Barcelona. Preliminary results show that there exists a remarkable spatial variability of solutes throughout the basin: maximum electrical conductivity values nearly reach 4000 µS/cm at headwaters, while close to the outlet the highest levels do not exceed 2400 µS/cm. However, tributaries coming from groundwater sources always keep rates around 1000 µ

  2. Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

    Science.gov (United States)

    Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef; Hu, Aixue; Hamlington, Benjamin; Kenigson, Jessica; Palanisamy, Hindumathi; Thompson, Philip

    2017-01-01

    Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth's climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modes and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this paper, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.

  3. Spatial patterns of North Atlantic Oscillation influence on mass balance variability of European glaciers

    Directory of Open Access Journals (Sweden)

    B. Marzeion

    2012-06-01

    Full Text Available We present and validate a set of minimal models of glacier mass balance variability. The most skillful model is then applied to reconstruct 7735 individual time series of mass balance variability for all glaciers in the European Alps and Scandinavia. Subsequently, we investigate the influence of atmospheric variability associated with the North Atlantic Oscillation (NAO on the glaciers' mass balances.

    We find a spatial coherence in the glaciers' sensitivity to NAO forcing which is caused by regionally similar mechanisms relating the NAO forcing to the mass balance: in southwestern Scandinavia, winter precipitation causes a correlation of mass balances with the NAO. In northern Scandinavia, temperature anomalies outside the core winter season cause an anti-correlation between NAO and mass balances. In the western Alps, both temperature and winter precipitation anomalies lead to a weak anti-correlation of mass balances with the NAO, while in the eastern Alps, the influences of winter precipitation and temperature anomalies tend to cancel each other, and only on the southern side a slight anti-correlation of mass balances with the NAO prevails.

  4. Explaining Spatial Variability in Wellbore Impairment Risk for Pennsylvania Oil and Gas Wells, 2000-2014

    Science.gov (United States)

    Santoro, R.; Ingraffea, A. R.

    2015-12-01

    Previous modeling (ingraffea et al. PNAS, 2014) indicated roughly two-times higher cumulative risk for wellbore impairment in unconventional wells, relative to conventional wells, and large spatial variation in risk for oil and gas wells drilled in the state of Pennsylvania. Impairment risk for wells in the northeast portion of the state were found to be 8.5-times greater than that of wells drilled in the rest of the state. Here, we set out to explain this apparent regional variability through Boosted Regression Tree (BRT) analysis of geographic, developmental, and general well attributes. We find that regional variability is largely driven by the nature of the development, i.e. whether conventional or unconventional development is dominant. Oil and natural gas market prices and total well depths present as major influences in wellbore impairment, with moderate influences from well densities and geologic factors. The figure depicts influence paths for predictors of impairments for the state (top left), SW region (top right), unconventional/NE region (bottom left) and conventional/NW region (bottom right) models. Influences are scaled to reflect percent contributions in explaining variability in the model.

  5. Influence of monsoons on atmospheric CO2 spatial variability and ground-based monitoring over India.

    Science.gov (United States)

    Tiwari, Yogesh K; Vellore, Ramesh K; Ravi Kumar, K; van der Schoot, Marcel; Cho, Chun-Ho

    2014-08-15

    This study examines the role of Asian monsoons on transport and spatial variability of atmospheric CO2 over the Indian subcontinent, using transport modeling tools and available surface observations from two atmospheric CO2 monitoring sites Sinhagad (SNG) and Cape Rama (CRI) in the western part of peninsular India. The regional source contributions to these sites arise from the horizontal flow in conduits within the planetary boundary layer. Greater CO2 variability, greater than 15 ppm, is observed during winter, while it is reduced nearly by half during summer. The SNG air sampling site is more susceptible to narrow regional terrestrial fluxes transported from the Indo-Gangetic Plains in January, and to wider upwind marine source regions from the Arabian Sea in July. The Western Ghats mountains appear to play a role in the seasonal variability at SNG by trapping polluted air masses associated with weak monsoonal winds. A Lagrangian back-trajectory analysis further suggests that the horizontal extent of regional sensitivity increases from north to south over the Indian subcontinent in January (Boreal winter). Copyright © 2014 Elsevier B.V. All rights reserved.

  6. Impact of Porous Media and NAPL Spatial Variability at the Pore Scale on Interphase Mass Transfer

    Science.gov (United States)

    Copty, N. K.; Agaoglu, B.; Scheytt, T.

    2015-12-01

    Sherwood number expressions are often used to model NAPL dissolution in porous media. Such expressions are generally derived from meso-scale experiments and expressed in terms of fluid and porous medium properties averaged over some representative volume. In this work a pore network model is used to examine the influence of porous media and NAPL pore scale variability on interphase mass transfer. The focus was on assessing the impact of (i) NAPL saturation, (ii) interfacial area (iii) NAPL spatial distribution at the pore scale, (iv) grain size heterogeneity and (v) REV or domain size on the apparent interphase mass transfer. Variability of both the mass transfer coefficient that explicitly accounts for the interfacial area and the mass transfer coefficient that lumps the interfacial area was examined. It was shown that pore scale NAPL distribution and its orientation relative to the flow direction have significant impact on flow bypassing and the interphase mass transfer coefficient. This results in a complex non-linear relationship between interfacial area and the REV-based interphase mass transfer rate. In other words, explicitly accounting for the interfacial area does not eliminate the variability of the mass transfer coefficient. Moreover, grain size heterogeneity can also lead to a decrease in the interphase mass transfer. It was also shown that, even for explicitly defined flow patterns, changing the domain size over which the mass transfer process is average influences the extent of NAPL bypassing and dilution and, consequently, the interphase mass transfer.

  7. A Survey of Spatial and Seasonal Water Isotope Variability on the Juneau Icefield, Alaksa

    Science.gov (United States)

    Dennis, D.; Carter, A.; Clinger, A. E.; Eads, O. L.; Gotwals, S.; Gunderson, J.; Hollyday, A. E.; Klein, E. S.; Markle, B. R.; Timms, J. R.

    2015-12-01

    The depletion of stable oxygen-hydrogen isotopes (δ18O and δH) is well correlated with temperature change, which is driven by variation in topography, climate, and atmospheric circulation. This study presents a survey of the spatial and seasonal variability of isotopic signatures on the Juneau Icefield (JI), Alaska, USA which spans over 3,000 square-kilometers. To examine small scale variability in the previous year's accumulation, samples were taken at regular intervals from snow pits and a one square-kilometer surficial grid. Surface snow samples were collected across the icefield to evaluate large scale variability, ranging approximately 1,000 meters in elevation and 100 kilometers in distance. Individual precipitation events were also sampled to track percolation throughout the snowpack and temperature correlations. A survey of this extent has never been undertaken on the JI. Samples were analyzed in the field using a Los Gatos laser isotope analyzer. This survey helps us better understand isotope fractionation on temperate glaciers in coastal environments and provides preliminary information on the suitability of the JI for a future ice core drilling project.

  8. Space Technology 5 Multipoint Observations of Temporal and Spatial Variability of Field-Aligned Currents

    Science.gov (United States)

    Le, G.; Wang, Y.; Slavin, J. A.; Strangeway, R. L.

    2009-01-01

    Space Technology 5 (ST5) is a constellation mission consisting of three microsatellites. It provides the first multipoint magnetic field measurements in low Earth orbit, which enables us to separate spatial and temporal variations. In this paper, we present a study of the temporal variability of field-aligned currents using the ST5 data. We examine the field-aligned current observations during and after a geomagnetic storm and compare the magnetic field profiles at the three spacecraft. The multipoint data demonstrate that mesoscale current structures, commonly embedded within large-scale current sheets, are very dynamic with highly variable current density and/or polarity in approx.10 min time scales. On the other hand, the data also show that the time scales for the currents to be relatively stable are approx.1 min for mesoscale currents and approx.10 min for large-scale currents. These temporal features are very likely associated with dynamic variations of their charge carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of mesoscale field-aligned currents are found to be consistent with those of auroral parallel electric field.

  9. Partial summations of stationary sequences of non-Gaussian random variables

    DEFF Research Database (Denmark)

    Mohr, Gunnar; Ditlevsen, Ove Dalager

    1996-01-01

    The distribution of the sum of a finite number of identically distributed random variables is in many cases easily determined given that the variables are independent. The moments of any order of the sum can always be expressed by the moments of the single term without computational problems...... of convergence of the distribution of a sum (or an integral) of mutually dependent random variables to the Gaussian distribution. The paper is closely related to the work in Ditlevsen el al. [Ditlevsen, O., Mohr, G. & Hoffmeyer, P. Integration of non-Gaussian fields. Prob. Engng Mech 11 (1996) 15-23](2)........ However, in the case of dependency between the terms even calculation of a few of the first moments of the sum presents serious computational problems. By use of computerized symbol manipulations it is practicable to obtain exact moments of partial sums of stationary sequences of mutually dependent...

  10. Spatial variability of soil carbon stock in the Urucu river basin, Central Amazon-Brazil

    Energy Technology Data Exchange (ETDEWEB)

    Ceddia, Marcos Bacis, E-mail: marcosceddia@gmail.com [Department of Soil, Institute of Agronomy, Universidade Federal Rural do Rio de Janeiro (UFRRJ), Seropédica, RJ 23890-000 (Brazil); Villela, André Luis Oliveira [Colégio Técnico da UFRRJ, RJ, Seropédica 23890-000 (Brazil); Pinheiro, Érika Flávia Machado [Department of Soil, Institute of Agronomy, Universidade Federal Rural do Rio de Janeiro (UFRRJ), Seropédica, RJ 23890-000 (Brazil); Wendroth, Ole [Department of Plant & Soil Sciences, University of Kentucky, College of Agriculture, Lexington, KY (United States)

    2015-09-01

    The Amazon Forest plays a major role in C sequestration and release. However, few regional estimates of soil organic carbon (SOC) stock in this ecoregion exist. One of the barriers to improve SOC estimates is the lack of recent soil data at high spatial resolution, which hampers the application of new methods for mapping SOC stock. The aims of this work were: (i) to quantify SOC stock under undisturbed vegetation for the 0–30 and the 0–100 cm under Amazon Forest; (ii) to correlate the SOC stock with soil mapping units and relief attributes and (iii) to evaluate three geostatistical techniques to generate maps of SOC stock (ordinary, isotopic and heterotopic cokriging). The study site is located in the Central region of Amazon State, Brazil. The soil survey covered the study site that has an area of 80 km{sup 2} and resulted in a 1:10,000 soil map. It consisted of 315 field observations (96 complete soil profiles and 219 boreholes). SOC stock was calculated by summing C stocks by horizon, determined as a product of BD, SOC and the horizon thickness. For each one of the 315 soil observations, relief attributes were derived from a topographic map to understand SOC dynamics. The SOC stocks across 30 and 100 cm soil depth were 3.28 and 7.32 kg C m{sup −2}, respectively, which is, 34 and 16%, lower than other studies. The SOC stock is higher in soils developed in relief forms exhibiting well-drained soils, which are covered by Upland Dense Tropical Rainforest. Only SOC stock in the upper 100 cm exhibited spatial dependence allowing the generation of spatial variability maps based on spatial (co)-regionalization. The CTI was inversely correlated with SOC stock and was the only auxiliary variable feasible to be used in cokriging interpolation. The heterotopic cokriging presented the best performance for mapping SOC stock. - Highlights: • The SOC stocks across 30 and 100 cm depth were 3.28 and 7.32 kg C m{sup −2}, respectively. • SOC stocks were 34 and 16

  11. Advances in catchment scale bank erosion modelling - quantifying the improved representation of temporal and spatial variability

    Science.gov (United States)

    Janes, Victoria; Holman, Ian; O'Donnell, Greg; Birkinshaw, Stephen; Kilsby, Chris

    2015-04-01

    Channel bank erosion processes are influenced by numerous factors resulting in high spatial and temporal variability of sediment production. The representation of channel bank erosion is overly simplistic within most catchment models, despite its significance to catchment sediment budgets. Within this study, the physically-based distributed SHETRAN model is modified to incorporate bank vegetation and channel sinuosity factors that influence spatial and temporal bank erosion rates. The modified model simulates the temporal variation of bank erosion in response to high magnitude events with the potential to remove bank vegetation and de-stabilise banks, thereby increasing erodibility. As vegetation re-establishes, simulated bank erodibility decreases. During the recovery period, banks have increased vulnerability to further high magnitude events that will result in increased bank erosion. This enables the model to represent the impact of flood clustering on sediment generation. The modified model also represents the spatial variation of bank erosion as a result of varying channel planform. Channel geometry has also been linked to bank erosion rates as a result of flow circulation within channels. Channel sinuosity shows a non-linear relationship with bank erosion, with bank erosion increasing up to a threshold value of sinuosity and decreasing as sinuosity increases above this point. The original and modified models have been applied to the Eden catchment in north east England. Bank erosion data derived from a GIS overlay methodology covering 150 years has been used to validate the models, indicating annual sediment generation from bank erosion processes within the catchment is 410-4500 t yr-1, equivalent to 2-11% of the catchment sediment budget. Comparison of the original and modified models highlights the improved ability of the modified model to simulate annual variation of bank eroded sediment production; annual sediment production from the original model ranged

  12. Alaskan soil carbon stocks: spatial variability and dependence on environmental factors

    Directory of Open Access Journals (Sweden)

    U. Mishra

    2012-09-01

    Full Text Available The direction and magnitude of soil organic carbon (SOC changes in response to climate change depend on the spatial and vertical distributions of SOC. We estimated spatially resolved SOC stocks from surface to C horizon, distinguishing active-layer and permafrost-layer stocks, based on geospatial analysis of 472 soil profiles and spatially referenced environmental variables for Alaska. Total Alaska state-wide SOC stock was estimated to be 77 Pg, with 61% in the active-layer, 27% in permafrost, and 12% in non-permafrost soils. Prediction accuracy was highest for the active-layer as demonstrated by highest ratio of performance to deviation (1.5. Large spatial variability was predicted, with whole-profile, active-layer, and permafrost-layer stocks ranging from 1–296 kg C m−2, 2–166 kg m−2, and 0–232 kg m−2, respectively. Temperature and soil wetness were found to be primary controllers of whole-profile, active-layer, and permafrost-layer SOC stocks. Secondary controllers, in order of importance, were found to be land cover type, topographic attributes, and bedrock geology. The observed importance of soil wetness rather than precipitation on SOC stocks implies that the poor representation of high-latitude soil wetness in Earth system models may lead to large uncertainty in predicted SOC stocks under future climate change scenarios. Under strict caveats described in the text and assuming temperature changes from the A1B Intergovernmental Panel on Climate Change emissions scenario, our geospatial model indicates that the equilibrium average 2100 Alaska active-layer depth could deepen by 11 cm, resulting in a thawing of 13 Pg C currently in permafrost. The equilibrium SOC loss associated with this warming would be highest under continuous permafrost (31%, followed by discontinuous (28%, isolated (24.3%, and sporadic (23.6% permafrost areas. Our high-resolution mapping of soil carbon stock reveals the

  13. Spatial and temporal variability of greenhouse gas emissions from a small and shallow temperate lake

    Science.gov (United States)

    Praetzel, Leandra; Schmiedeskamp, Marcel; Broder, Tanja; Hüttemann, Caroline; Jansen, Laura; Metzelder, Ulrike; Wallis, Ronya; Knorr, Klaus-Holger; Blodau, Christian

    2017-04-01

    Small inland waters (lakes. They are further expected to be susceptible to changing climate conditions. So far, little is known about the spatial and temporal variability of carbon dioxide (CO2) and methane (CH4) emissions and in-lake dynamics of CH4 production and oxidation in small, epilimnetic lakes in the temperate zone. Of particular interest is the potential occurrence of "hot spots" and "hot moments" that could contribute significantly to total emissions. To address this knowledge gap, we determined CO2 and CH4 emissions and dynamics to identify their controlling environmental factors in a polymictic small (1.4 ha) and shallow (max. depth approx. 1.5 m) crater lake ("Windsborn") in the Eifel uplands in south-west Germany. As Lake Windsborn has a small catchment area (8 ha) and no surficial inflows, it serves well as a model system for the identification of factors and processes controlling emissions. In 2015, 2016 and 2017 we measured CO2 and CH4 gas fluxes with different techniques across the sediment/water and water/atmosphere interface. Atmospheric exchange was measured using mini-chambers equipped with CO2 sensors and with an infra-red greenhouse gas analyzer for high temporal resolution flux measurements. Ebullition of CH4 was quantified with funnel traps. Sediment properties were examined using pore-water peepers. All measurements were carried out along a transect covering both littoral and central parts of the lake. Moreover, a weather station on a floating platform in the center of the lake recorded meteorological data as well as CO2 concentration in different depths of the water column. So far, Lake Windsborn seems to be a source for both CO2 and CH4 on an annual scale. CO2 emissions generally increased from spring to summer. Even though CO2 uptake could be observed during some periods in spring and fall, CO2 emissions in the summer exceeded the uptake. CO2 and CH4 emissions also appeared to be spatially variable between littoral areas and the inner

  14. Testing pairwise association between spatially autocorrelated variables: a new approach using surrogate lattice data.

    Directory of Open Access Journals (Sweden)

    Vincent Deblauwe

    Full Text Available BACKGROUND: Independence between observations is a standard prerequisite of traditional statistical tests of association. This condition is, however, violated when autocorrelation is present within the data. In the case of variables that are regularly sampled in space (i.e. lattice data or images, such as those provided by remote-sensing or geographical databases, this problem is particularly acute. Because analytic derivation of the null probability distribution of the test statistic (e.g. Pearson's r is not always possible when autocorrelation is present, we propose instead the use of a Monte Carlo simulation with surrogate data. METHODOLOGY/PRINCIPAL FINDINGS: The null hypothesis that two observed mapped variables are the result of independent pattern generating processes is tested here by generating sets of random image data while preserving the autocorrelation function of the original images. Surrogates are generated by matching the dual-tree complex wavelet spectra (and hence the autocorrelation functions of white noise images with the spectra of the original images. The generated images can then be used to build the probability distribution function of any statistic of association under the null hypothesis. We demonstrate the validity of a statistical test of association based on these surrogates with both actual and synthetic data and compare it with a corrected parametric test and three existing methods that generate surrogates (randomization, random rotations and shifts, and iterative amplitude adjusted Fourier transform. Type I error control was excellent, even with strong and long-range autocorrelation, which is not the case for alternative methods. CONCLUSIONS/SIGNIFICANCE: The wavelet-based surrogates are particularly appropriate in cases where autocorrelation appears at all scales or is direction-dependent (anisotropy. We explore the potential of the method for association tests involving a lattice of binary data and discuss its

  15. Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas - A review

    NARCIS (Netherlands)

    Cristiano, E.; ten Veldhuis, J.A.E.; van de Giesen, N.C.

    2017-01-01

    In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological

  16. Spatial and temporal variability in the ratio of trace gases emitted from biomass burning

    Directory of Open Access Journals (Sweden)

    T. T. van Leeuwen

    2011-04-01

    Full Text Available Fires are a major source of trace gases and aerosols to the atmosphere. The amount of biomass burned is becoming better known, most importantly due to improved burned area datasets and a better representation of fuel consumption. The spatial and temporal variability in the partitioning of biomass burned into emitted trace gases and aerosols, however, has received relatively little attention. To convert estimates of biomass burned to trace gas and aerosol emissions, most studies have used emission ratios (or emission factors (EFs based on the arithmetic mean of field measurement outcomes, stratified by biome. However, EFs vary substantially in time and space, even within a single biome. In addition, it is unknown whether the available field measurement locations provide a representative sample for the various biomes. Here we used the available body of EF literature in combination with satellite-derived information on vegetation characteristics and climatic conditions to better understand the spatio-temporal variability in EFs. While focusing on CO, CH4, and CO2, our findings are also applicable to other trace gases and aerosols. We explored relations between EFs and different measurements of environmental variables that may correlate with part of the variability in EFs (tree cover density, vegetation greenness, temperature, precipitation, and the length of the dry season. Although reasonable correlations were found for specific case studies, correlations based on the full suite of available measurements were lower and explained about 33%, 38%, 19%, and 34% of the variability for respectively CO, CH4, CO2, and the Modified Combustion Efficiency (MCE. This may be partly due to uncertainties in the environmental variables, differences in measurement techniques for EFs, assumptions on the ratio between flaming and smoldering combustion, and incomplete information on the location and timing of EF

  17. Quantifying the spatial variability in critical zone architecture through surface mapping and near-surface geophysics

    Science.gov (United States)

    DiBiase, R.; Del Vecchio, J.; Mount, G.; Hayes, J. L.; Comas, X.; Guo, L.; Lin, H.; Zarif, F.; Forsythe, B.; Brantley, S. L.

    2016-12-01

    The composition and structure of Earth's surface and shallow subsurface control the flux of water, solutes, and sediment from hillslopes into rivers. Additionally, bedrock weathering profiles and the stratigraphy of soil and colluvium preserve a record of past surface processes. However, landscapes often exhibit heterogeneity in critical zone architecture that is difficult to capture with remote sensing and costly to characterize through direct measurement in soil pits or drill cores. Here we present results from a multifaceted approach to quantifying spatial variability in critical zone architecture using airborne lidar topography, surface mapping, and a suite of geophysical surveys. We focus on Garner Run, a first order sandstone catchment in the Susquehanna Shale Hills Critical Zone Observatory situated in the valley and ridge province of central Pennsylvania, 80 km southwest of the last glacial maximum ice limit. Results from lidar topographic analysis and detailed mapping of surface cover (e.g., soil versus boulder-mantled) reveal a pattern of relict periglacial landforms and deposits that vary depending on slope position and aspect. Additionally, a drill core taken from an unchanneled valley at the head of Garner Run indicates at least 9 meters of alternating sand- and boulder-rich colluvial fill sourced from adjacent hillslopes, indicating the potential preservation of multiple cycles of periglacial climate conditions. Through the use of shallow geophysical techniques, including cross-valley transects of seismic refraction, multiple frequency ground-penetrating radar (GPR), and electrical resistivity tomography (ERT), we image spatial patterns in subsurface architecture at a range of scales (10-1,000 m), and high spatial resolution (cm). Notably, despite challenging environmental conditions, there is agreement among diverse subsurface methods in highlighting aspect-dependent controls on weathering zone thickness that furthermore can be directly connected to

  18. Spatial variability of the topsoil organic carbon in the Moso bamboo forests of southern China in association with soil properties.

    Science.gov (United States)

    Zhang, Houxi; Zhuang, Shunyao; Qian, Haiyan; Wang, Feng; Ji, Haibao

    2015-01-01

    Understanding the spatial variability of soil organic carbon (SOC) must be enhanced to improve sampling design and to develop soil management strategies in terrestrial ecosystems. Moso bamboo (Phyllostachys pubescens Mazel ex Houz.) forests have a high SOC storage potential; however, they also vary significantly spatially. This study investigated the spatial variability of SOC (0-20 cm) in association with other soil properties and with spatial variables in the Moso bamboo forests of Jian'ou City, which is a typical bamboo hometown in China. 209 soil samples were collected from Moso bamboo stands and then analyzed for SOC, bulk density (BD), pH, cation exchange capacity (CEC), and gravel content (GC) based on spatial distribution. The spatial variability of SOC was then examined using geostatistics. A Kriging map was produced through ordinary interpolation and required sample numbers were calculated by classical and Kriging methods. An aggregated boosted tree (ABT) analysis was also conducted. A semivariogram analysis indicated that ln(SOC) was best fitted with an exponential model and that it exhibited moderate spatial dependence, with a nugget/sill ratio of 0.462. SOC was significantly and linearly correlated with BD (r = -0.373**), pH (r = -0.429**), GC (r = -0.163*), CEC (r = 0.263**), and elevation (r = 0.192**). Moreover, the Kriging method requires fewer samples than the classical method given an expected standard error level as per a variance analysis. ABT analysis indicated that the physicochemical variables of soil affected SOC variation more significantly than spatial variables did, thus suggesting that the SOC in Moso bamboo forests can be strongly influenced by management practices. Thus, this study provides valuable information in relation to sampling strategy and insight into the potential of adjustments in agronomic measure, such as in fertilization for Moso bamboo production.

  19. Spatial Models for Prediction and Early Warning of Aedes aegypti Proliferation from Data on Climate Change and Variability in Cuba.

    Science.gov (United States)

    Ortiz, Paulo L; Rivero, Alina; Linares, Yzenia; Pérez, Alina; Vázquez, Juan R

    2015-04-01

    Climate variability, the primary expression of climate change, is one of the most important environmental problems affecting human health, particularly vector-borne diseases. Despite research efforts worldwide, there are few studies addressing the use of information on climate variability for prevention and early warning of vector-borne infectious diseases. Show the utility of climate information for vector surveillance by developing spatial models using an entomological indicator and information on predicted climate variability in Cuba to provide early warning of danger of increased risk of dengue transmission. An ecological study was carried out using retrospective and prospective analyses of time series combined with spatial statistics. Several entomological and climatic indicators were considered using complex Bultó indices -1 and -2. Moran's I spatial autocorrelation coefficient specified for a matrix of neighbors with a radius of 20 km, was used to identify the spatial structure. Spatial structure simulation was based on simultaneous autoregressive and conditional autoregressive models; agreement between predicted and observed values for number of Aedes aegypti foci was determined by the concordance index Di and skill factor Bi. Spatial and temporal distributions of populations of Aedes aegypti were obtained. Models for describing, simulating and predicting spatial patterns of Aedes aegypti populations associated with climate variability patterns were put forward. The ranges of climate variability affecting Aedes aegypti populations were identified. Forecast maps were generated for the municipal level. Using the Bultó indices of climate variability, it is possible to construct spatial models for predicting increased Aedes aegypti populations in Cuba. At 20 x 20 km resolution, the models are able to provide warning of potential changes in vector populations in rainy and dry seasons and by month, thus demonstrating the usefulness of climate information for

  20. Spatial variability of the topsoil organic carbon in the Moso bamboo forests of southern China in association with soil properties.

    Directory of Open Access Journals (Sweden)

    Houxi Zhang

    Full Text Available Understanding the spatial variability of soil organic carbon (SOC must be enhanced to improve sampling design and to develop soil management strategies in terrestrial ecosystems. Moso bamboo (Phyllostachys pubescens Mazel ex Houz. forests have a high SOC storage potential; however, they also vary significantly spatially. This study investigated the spatial variability of SOC (0-20 cm in association with other soil properties and with spatial variables in the Moso bamboo forests of Jian'ou City, which is a typical bamboo hometown in China. 209 soil samples were collected from Moso bamboo stands and then analyzed for SOC, bulk density (BD, pH, cation exchange capacity (CEC, and gravel content (GC based on spatial distribution. The spatial variability of SOC was then examined using geostatistics. A Kriging map was produced through ordinary interpolation and required sample numbers were calculated by classical and Kriging methods. An aggregated boosted tree (ABT analysis was also conducted. A semivariogram analysis indicated that ln(SOC was best fitted with an exponential model and that it exhibited moderate spatial dependence, with a nugget/sill ratio of 0.462. SOC was significantly and linearly correlated with BD (r = -0.373**, pH (r = -0.429**, GC (r = -0.163*, CEC (r = 0.263**, and elevation (r = 0.192**. Moreover, the Kriging method requires fewer samples than the classical method given an expected standard error level as per a variance analysis. ABT analysis indicated that the physicochemical variables of soil affected SOC variation more significantly than spatial variables did, thus suggesting that the SOC in Moso bamboo forests can be strongly influenced by management practices. Thus, this study provides valuable information in relation to sampling strategy and insight into the potential of adjustments in agronomic measure, such as in fertilization for Moso bamboo production.

  1. A BAYESIAN HIERARCHICAL SPATIAL MODEL FOR DENTAL CARIES ASSESSMENT USING NON-GAUSSIAN MARKOV RANDOM FIELDS.

    Science.gov (United States)

    Jin, Ick Hoon; Yuan, Ying; Bandyopadhyay, Dipankar

    2016-01-01

    Research in dental caries generates data with two levels of hierarchy: that of a tooth overall and that of the different surfaces of the tooth. The outcomes often exhibit spatial referencing among neighboring teeth and surfaces, i.e., the disease status of a tooth or surface might be influenced by the status of a set of proximal teeth/surfaces. Assessments of dental caries (tooth decay) at the tooth level yield binary outcomes indicating the presence/absence of teeth, and trinary outcomes at the surface level indicating healthy, decayed, or filled surfaces. The presence of these mixed discrete responses complicates the data analysis under a unified framework. To mitigate complications, we develop a Bayesian two-level hierarchical model under suitable (spatial) Markov random field assumptions that accommodates the natural hierarchy within the mixed responses. At the first level, we utilize an autologistic model to accommodate the spatial dependence for the tooth-level binary outcomes. For the second level and conditioned on a tooth being non-missing, we utilize a Potts model to accommodate the spatial referencing for the surface-level trinary outcomes. The regression models at both levels were controlled for plausible covariates (risk factors) of caries, and remain connected through shared parameters. To tackle the computational challenges in our Bayesian estimation scheme caused due to the doubly-intractable normalizing constant, we employ a double Metropolis-Hastings sampler. We compare and contrast our model performances to the standard non-spatial (naive) model using a small simulation study, and illustrate via an application to a clinical dataset on dental caries.

  2. Influence of correspondence noise and spatial scaling on the upper limit for spatial displacement in fully-coherent random-dot kinematogram stimuli.

    Directory of Open Access Journals (Sweden)

    Srimant P Tripathy

    Full Text Available Correspondence noise is a major factor limiting direction discrimination performance in random-dot kinematograms. In the current study we investigated the influence of correspondence noise on Dmax, which is the upper limit for the spatial displacement of the dots for which coherent motion is still perceived. Human direction discrimination performance was measured, using 2-frame kinematograms having leftward/rightward motion, over a 200-fold range of dot-densities and a four-fold range of dot displacements. From this data Dmax was estimated for the different dot densities tested. A model was proposed to evaluate the correspondence noise in the stimulus. This model summed the outputs of a set of elementary Reichardt-type local detectors that had receptive fields tiling the stimulus and were tuned to the two directions of motion in the stimulus. A key assumption of the model was that the local detectors would have the radius of their catchment areas scaled with the displacement that they were tuned to detect; the scaling factor k linking the radius to the displacement was the only free parameter in the model and a single value of k was used to fit all of the psychophysical data collected. This minimal, correspondence-noise based model was able to account for 91% of the variability in the human performance across all of the conditions tested. The results highlight the importance of correspondence noise in constraining the largest displacement that can be detected.

  3. Gradual stiffness versus magnetic imaging-guided variable stiffness colonoscopes: A randomized noninferiority trial.

    Science.gov (United States)

    Garborg, Kjetil; Wiig, Håvard; Hasund, Audun; Matre, Jon; Holme, Øyvind; Noraberg, Geir; Løberg, Magnus; Kalager, Mette; Adami, Hans-Olov; Bretthauer, Michael

    2017-02-01

    Colonoscopes with gradual stiffness have recently been developed to enhance cecal intubation. We aimed to determine if the performance of gradual stiffness colonoscopes is noninferior to that of magnetic endoscopic imaging (MEI)-guided variable stiffness colonoscopes. Consecutive patients were randomized to screening colonoscopy with Fujifilm gradual stiffness or Olympus MEI-guided variable stiffness colonoscopes. The primary endpoint was cecal intubation rate (noninferiority limit 5%). Secondary endpoints included cecal intubation time. We estimated absolute risk differences with 95% confidence intervals (CIs). We enrolled 475 patients: 222 randomized to the gradual stiffness instrument, and 253 to the MEI-guided variable stiffness instrument. Cecal intubation rate was 91.7% in the gradual stiffness group versus 95.6% in the variable stiffness group. The adjusted absolute risk for cecal intubation failure was 4.3% higher in the gradual stiffness group than in the variable stiffness group (upper CI border 8.1%). Median cecal intubation time was 13 minutes in the gradual stiffness group and 10 minutes in the variable stiffness group (p < 0.001). The study is inconclusive with regard to noninferiority because the 95% CI for the difference in cecal intubation rate between the groups crosses the noninferiority margin. (ClinicalTrials.gov identifier: NCT01895504).

  4. Fine-scale distribution and spatial variability of benthic invertebrate larvae in an open coastal embayment in Nova Scotia, Canada.

    Science.gov (United States)

    Daigle, Rémi M; Metaxas, Anna; deYoung, Brad

    2014-01-01

    This study quantified the fine- scale (0.5 km) of variability in the horizontal distributions of benthic invertebrate larvae and related this variability to that in physical and biological variables, such as density, temperature, salinity, fluorescence and current velocity. Larvae were sampled in contiguous 500-m transects along two perpendicular 10-km transects with a 200-µm plankton ring net (0.75-m diameter) in St. George's Bay, Nova Scotia, Canada, in Aug 2009. Temperature, conductivity, pressure and fluorescence were measured with a CTD cast at each station, and currents were measured with an Acoustic Doppler Current Profiler moored at the intersection of the 2 transects. Gastropod, bivalve and, to a lesser extent, bryozoan larvae had very similar spatial distributions, but the distribution of decapod larvae had a different pattern. These findings suggest that taxonomic groups with functionally similar larvae have similar dispersive properties such as distribution and spatial variability, while the opposite is true for groups with functionally dissimilar larvae. The spatial variability in larval distributions was anisotropic and matched the temporal/spatial variability in the current velocity. We postulate that in a system with no strong oceanographic features, the scale of spatially coherent physical forcing (e.g. tidal periodicity) can regulate the formation or maintenance of larval patches; however, swimming ability may modulate it.

  5. Seasonal and Spatial Variability of Virioplanktonic Abundance in Haihe River, China

    Directory of Open Access Journals (Sweden)

    Lili Ma

    2013-01-01

    Full Text Available In order to understand the composition and dynamics of planktonic viruses and their relationship with environmental parameters in natural freshwater, flow cytometry was optimized with filtration/fixation/staining/dilution and then applied to the analysis of samples collected from 9 stations (covering urban, rural, and estuarial areas along the Haihe River, China, over a one-year period of study. The total viral abundance exhibited an apparent peak in the spring. Spatially, the highest viral abundance was recorded in estuarial areas. The correlation analysis indicated that the bacteria in the Haihe River significantly influenced viral abundance. The relationship between abiotic variables and viral abundance remained the same as with bacterial abundance, indicating that environmental parameters could possibly influence viral abundance in virtue of their bacterial host cells. The influence of environmental factors on viral abundance differed in the three sampling areas, suggesting different drivers of viral abundance in different stretches of the river associated with their utilization and surroundings.

  6. Spatial variability of hydraulic conductivity of an unconfined sandy aquifer determined by a mini slug test

    DEFF Research Database (Denmark)

    Bjerg, Poul Løgstrup; Hinsby, Klaus; Christensen, Thomas Højlund

    1992-01-01

    The spatial variability of the hydraulic conductivity in a sandy aquifer has been determined by a mini slug test method. The hydraulic conductivity (K) of the aquifer has a geometric mean of 5.05 × 10−4 m s−1, and an overall variance of 1n K equal to 0.37 which corresponds quite well to the results...... obtained by two large scale tracer experiments performed in the aquifer. A geological model of the aquifer based on 31 sediment cores, proposed three hydrogeological layers in the aquifer concurrent with the vertical variations observed with respect to hydraulic conductivity. The horizontal correlation...... length of the hydraulic conductivity has been determined for each of the three hydrogeological layers and is found to be small (1–2.5 m). The asymptotic longitudinal dispersivity of the aquifer has been estimated from the variance in hydraulic conductivity and the horizontal correlation length...

  7. Spatial and temporal variability of trace element concentrations in an urban subtropical watershed, Honolulu, Hawaii

    Energy Technology Data Exchange (ETDEWEB)

    Heinen de Carlo, E. [University of Hawaii, Honolulu, HI (United States). Dept. of Oceanography; U.S. Geological Survey, Honolulu, HI (United States); Anthony, S.S. [U.S. Geological Survey, Honolulu, HI (United States)

    2002-07-01

    Trace metal concentrations in soils and in stream and estuarine sediments from a subtropical urban watershed in Hawaii are presented. The results are placed in the context of historical studies of environmental quality (water, soils, and sediment) in Hawaii to elucidate sources of trace elements and the processes responsible for their distribution. This work builds on earlier studies on sediments of Ala Wai Canal of urban Honolulu by examining spatial and temporal variations in the trace elements throughout the watershed. Natural processes and anthropogenic activity in urban Honolulu contribute to spatial and temporal variations of trace element concentrations throughout the watershed. Enrichment of trace elements in watershed soils result, in some cases, from contributions attributed to the weathering of volcanic rocks, as well as to a more variable anthropogenic input that reflects changes in land use in Honolulu. Varying concentrations of As, Cd, Cu, Pb and Zn in sediments reflect about 60 a of anthropogenic activity in Honolulu. Land use has a strong impact on the spatial distribution and abundance of selected trace elements in soils and stream sediments. As noted in continental US settings, the phasing out of Pb-alkyl fuel additives has decreased Pb inputs to recently deposited estuarine sediments. Yet, a substantial historical anthropogenic Pb inventory remains in soils of the watershed and erosion of surface soils continues to contribute to its enrichment in estuarine sediments. Concentrations of other elements (e.g., Cu, Zn, Cd), however, have not decreased with time, suggesting continued active inputs. Concentrations of Ba, Co, Cr, Ni, V and U, although elevated in some cases, typically reflect greater proportions attributed to natural sources rather than anthropogenic input. (author)

  8. Seasonal changes, spatial variability and origin of suspended organic matter in Hornsund, Spitsbergen

    Science.gov (United States)

    Apolinarska, Karina; Szczuciński, Witold; Moskalik, Mateusz; Dominiczak, Aleksander

    2017-04-01

    Carbon stable isotope composition (δ13C) of suspended organic matter (SOM) was investigated to recognize temporal and spatial variability, as well as sources of particulate carbon delivered to the sediments of Hornsund fjord, Spitsbergen. Sampling was carried out between May 2015, when most of the investigated area was covered with sea-ice, and late August 2015. Samples were taken from a number of sites in central part of Hornsund, Burgerbukta, Samarinvegen and Brepolen bay in the innermost part of the fjord. One litre water volume, sampled from a range of depths between the water surface and 100 m, was filtered using GFF filters. δ13C values of the SOM were measured after acid treatment of the filters to remove carbonates. δ13C values of SOM varied both temporarily and spatially reflecting the variable sources of organic carbon, namely the marine production in situ, fresh marine organic carbon brought from the shelf with currents and "old" carbon delivered from land. The samples were most 13C-enriched (-22.4‰) in June, at the time of an intensive primary productivity within the fjord. Later, during the warm season, with the more intensive glaciers melting and thus supply of the suspended sediment load containing the old terrigenous carbon, δ13C values of SOM decreased in all the localities studied towards the carbon isotope values of the local terrestrial end-member, i.e., δ13C values of the old organic carbon in the bedrock. Change in δ13C values of SOM was also observed with increasing distance from glaciers, e.g. in front of the Samarinbreen and reflect changes in the intensity of primary production and supply of the old carbon. The study was supported from National Science Center grant No. 2013/10/E/ST10/00166.

  9. Spatial variability of meteorological observations and impacts on regional estimates of soybean grain productivity

    Directory of Open Access Journals (Sweden)

    Rodrigo Cornacini Ferreira

    2017-08-01

    Full Text Available Brazil requires a fully representative weather network station; it is common to use data observed in locations distant from the region of interest. However, few studies have evaluated the efficiency and precision associated with the use of climate data, either estimated or interpolated, from stations far from the agricultural area of interest. Hence, this study aimed to demonstrate the impacts of spatial variability of the main meteorological elements on the regional estimate of soybean productivity. Regression analysis was used to compare data recorded at three weather stations located throughout Londrina, PR, Brazil. The water balance of the soybean crop was calculated at 10-day periods and grain productivity losses estimated using the Agro-Ecological Zones (AEZ methodology. Temperatures at the three locations were similar, while the relative air humidity, and particularly, the rainfall data, were less correlated. A high degree of caution is recommended in the use and choice of a single weather station to represent a municipality or region, particularly in countries, such as Brazil, with multiple regions of agricultural and environmental importance. Models and crop season estimates that do not consider such a recommendation are vulnerable to errors in their forecasts. The volumetric and temporal variability in the spatial rainfall distribution resulted in soybean yield discrepancies, estimated at the municipal level. The consistency of the data series, the location of weather stations and their distance to the location of interest determine the ability of crop models to accurately estimate soybean production based on meteorological data, particularly the rainfall data. This study contributes to future regional research using climate data, and highlights the importance of a weather station network throughout Brazil, demonstrating the urgent need to increase the number of weather stations, particularly for recording rainfall data.

  10. Spatial modelling of marine organisms in Forsmark and Oskarshamn. Including calculation of physical predictor variables

    Energy Technology Data Exchange (ETDEWEB)

    Carlen, Ida; Nikolopoulos, Anna; Isaeus, Martin (AquaBiota Water Research, Stockholm (SE))

    2007-06-15

    GIS grids (maps) of marine parameters were created using point data from previous site investigations in the Forsmark and Oskarshamn areas. The proportion of global radiation reaching the sea bottom in Forsmark and Oskarshamn was calculated in ArcView, using Secchi depth measurements and the digital elevation models for the respective area. The number of days per year when the incoming light exceeds 5 MJ/m2 at the bottom was then calculated using the result of the previous calculations together with measured global radiation. Existing modelled grid-point data on bottom and pelagic temperature for Forsmark were interpolated to create surface covering grids. Bottom and pelagic temperature grids for Oskarshamn were calculated using point measurements to achieve yearly averages for a few points and then using regressions with existing grids to create new maps. Phytoplankton primary production in Forsmark was calculated using point measurements of chlorophyll and irradiance, and a regression with a modelled grid of Secchi depth. Distribution of biomass of macrophyte communities in Forsmark and Oskarshamn was calculated using spatial modelling in GRASP, based on field data from previous surveys. Physical parameters such as those described above were used as predictor variables. Distribution of biomass of different functional groups of fish in Forsmark was calculated using spatial modelling based on previous surveys and with predictor variables such as physical parameters and results from macrophyte modelling. All results are presented as maps in the report. The quality of the modelled predictions varies as a consequence of the quality and amount of the input data, the ecology and knowledge of the predicted phenomena, and by the modelling technique used. A substantial part of the variation is not described by the models, which should be expected for biological modelling. Therefore, the resulting grids should be used with caution and with this uncertainty kept in mind. All

  11. Spatial distribution and temporal variability of solar radiant over southern Thailand

    Energy Technology Data Exchange (ETDEWEB)

    Waewsak, J.; Chancham, C. [Thaksin Univ., Phatthalung (Thailand). Dept. of Physics, Renewable Energy System Research and Demonstration Center, Solar and Wind Energy Research Lab

    2009-07-01

    The potential for solar energy in Thailand has been estimated at over 50,000 MW for power generation. However, existing power plants in the country produce only 32 MW. Most the the systems have been installed in rural areas, islands and other off-grid sites. The availability and variability of global solar radiant intensity and its spatial distribution are key parameters for designing and testing outdoor solar energy systems. These parameters must be well understood in order to evaluate system efficiency at specific locations. Therefore, this study examined the spatial distribution and temporal variability of solar radiant over southern Thailand using the Surfer computer program. The incident of solar radiation on a horizontal plane was estimated at 14 synoptic stations using the Angstrom's correlation which was obtained from meteorological data. Rainfall quantity at 3 main meteorological stations was used to correlate the hours of sunshine and to predict them in meteorological stations where sunshine recorders were absent but where rainfall data were present. The 3 stations were at the Surat Thani, Phuket and Hat Yai airports. Angstrom's correlation coefficients were obtained using the correlation between the hours of sunshine and day length. The solar radiant was obtained once the extraterrestrial solar radiation was known. The study showed that the solar radiant over southern Thailand varies between 12.51 to 24.54 MJ per m{sup 2} per day. It was concluded that the temporal variation of solar radiant over southern Thailand is highly influenced by the North-East and South-West monsoons. 16 refs., 1 tab., 17 figs.

  12. Simulating maize yield and bomass with spatial variability of soil field capacity

    Science.gov (United States)

    Ma, Liwang; Ahuja, Lajpat; Trout, Thomas; Nolan, Bernard T.; Malone, Robert W.

    2015-01-01

    Spatial variability in field soil properties is a challenge for system modelers who use single representative values, such as means, for model inputs, rather than their distributions. In this study, the root zone water quality model (RZWQM2) was first calibrated for 4 yr of maize (Zea mays L.) data at six irrigation levels in northern Colorado and then used to study spatial variability of soil field capacity (FC) estimated in 96 plots on maize yield and biomass. The best results were obtained when the crop parameters were fitted along with FCs, with a root mean squared error (RMSE) of 354 kg ha–1 for yield and 1202 kg ha–1 for biomass. When running the model using each of the 96 sets of field-estimated FC values, instead of calibrating FCs, the average simulated yield and biomass from the 96 runs were close to measured values with a RMSE of 376 kg ha–1 for yield and 1504 kg ha–1 for biomass. When an average of the 96 FC values for each soil layer was used, simulated yield and biomass were also acceptable with a RMSE of 438 kg ha–1 for yield and 1627 kg ha–1 for biomass. Therefore, when there are large numbers of FC measurements, an average value might be sufficient for model inputs. However, when the ranges of FC measurements were known for each soil layer, a sampled distribution of FCs using the Latin hypercube sampling (LHS) might be used for model inputs.

  13. Spatial Variability of Physical Soil Quality Index of an Agricultural Field

    Directory of Open Access Journals (Sweden)

    Sheikh M. Fazle Rabbi

    2014-01-01

    Full Text Available A field investigation was carried out to evaluate the spatial variability of physical indicators of soil quality of an agricultural field and to construct a physical soil quality index (SQIP map. Surface soil samples were collected using 10  m×10 m grid from an Inceptisol on Ganges Tidal Floodplain of Bangladesh. Five physical soil quality indicators, soil texture, bulk density, porosity, saturated hydraulic conductivity (KS, and aggregate stability (measured as mean weight diameter, MWD were determined. The spatial structures of sand, clay, and KS were moderate but the structure was strong for silt, bulk density, porosity, and MWD. Each of the physical soil quality indicators was transformed into 0 and 1 using threshold criteria which are required for crop production. The transformed indicators were the combined into SQIP. The kriged SQIP map showed that the agricultural field studied could be divided into two parts having “good physical quality” and “poor physical soil quality.”

  14. SATELLITE-MEASURED SPATIAL AND TEMPORAL CHLOROPHYLL-A VARIABILITY IN THE GULF OF TOMINI, SULAWESI

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    I Nyoman Radiarta

    2009-12-01

    Full Text Available Chlorophyll-a concentration, an index of phytoplankton biomass, is an important parameter for fisheries resources and marine aquaculture development. Spatial and temporal variability of surface cholophyll-a (chl-a concentration and water condition in the Gulf of Tomini were investigated using monthly climatologies the Sea-viewing Wide Field-of-view sensor (SeaWiFS, sea surface temperature (SST, and wind data from January 2000 to December 2007. The results showed seasonal variation of chla and SST in the Gulf of Tomini. High chl-a concentrations located in the eastern part of the gulf were observed during the southeast monsoon in August. During the northwest monsoon, chl-a concentrations were relatively low ( 28oC during the northwest monsoon, but low during the southeast monsoon. High wind speed was coincided with high chl-a concentrations. Local forcing such as sea surface heating and wind condition are the mechanisms that controlled the spatial and temporal variations of chlorophyll concentrations.

  15. Variable chromatin structure revealed by in situ spatially correlated DNA cleavage mapping.

    Science.gov (United States)

    Risca, Viviana I; Denny, Sarah K; Straight, Aaron F; Greenleaf, William J

    2017-01-12

    Chromatin structure at the length scale encompassing local nucleosome-nucleosome interactions is thought to play a crucial role in regulating transcription and access to DNA. However, this secondary structure of chromatin remains poorly understood compared with the primary structure of single nucleosomes or the tertiary structure of long-range looping interactions. Here we report the first genome-wide map of chromatin conformation in human cells at the 1-3 nucleosome (50-500 bp) scale, obtained using ionizing radiation-induced spatially correlated cleavage of DNA with sequencing (RICC-seq) to identify DNA-DNA contacts that are spatially proximal. Unbiased analysis of RICC-seq signal reveals regional enrichment of DNA fragments characteristic of alternating rather than adjacent nucleosome interactions in tri-nucleosome units, particularly in H3K9me3-marked heterochromatin. We infer differences in the likelihood of nucleosome-nucleosome contacts among open chromatin, H3K27me3-marked, and H3K9me3-marked repressed chromatin regions. After calibrating RICC-seq signal to three-dimensional distances, we show that compact two-start helical fibre structures with stacked alternating nucleosomes are consistent with RICC-seq fragmentation patterns from H3K9me3-marked chromatin, while non-compact structures and solenoid structures are consistent with open chromatin. Our data support a model of chromatin architecture in intact interphase nuclei consistent with variable longitudinal compaction of two-start helical fibres.

  16. Spatial variability of aggregate stability and carbon stock in Cambisol and Argisol

    Directory of Open Access Journals (Sweden)

    Leandro Coutinho Alho

    2014-09-01

    Full Text Available The advancement of agricultural activities without considering the soil structural conditions ceases at the expense of those environments. This study aimed at evaluating the spatial variability of aggregate stability, bulk density, total organic carbon (TOC and carbon stock in areas of natural grassland and forest, in the region of Humaitá, Amazonas State, Brazil. The soils were sampled at the crossing points of a grid with 70 m x 70 m, at regular intervals of 10 m, at the depths of 0.0-0.05 m, 0.05-0.10 m and 0.10-0.20 m, totaling 64 samples per depth. The results of the geostatistical analysis showed spatial dependence of attributes. The smaller ranges resulted from the constant variations in the relief of the natural grassland area. The mean values for mean weight diameter (MWD and TOC were respectively around 3.0 mm and 29.0 g kg-1 of the surface layer, similarly to natural grassland and forest areas, confirming the proportional correlation between TOC and MWD. However, the bulk density greater than 1.40 kg dm-3 expresses the inefficiency of soil structural functions in the natural grassland area. The carbon stock contents at the different depths were more favored by TOC than by the different densification levels of the soils evaluated.

  17. Comparison of stochastic and deterministic methods for mapping groundwater level spatial variability in sparsely monitored basins.

    Science.gov (United States)

    Varouchakis, Epsilon A; Hristopulos, D T

    2013-01-01

    In sparsely monitored basins, accurate mapping of the spatial variability of groundwater level requires the interpolation of scattered data. This paper presents a comparison of deterministic interpolation methods, i.e. inverse distance weight (IDW) and minimum curvature (MC), with stochastic methods, i.e. ordinary kriging (OK), universal kriging (UK) and kriging with Delaunay triangulation (DK). The study area is the Mires Basin of Mesara Valley in Crete (Greece). This sparsely sampled basin has limited groundwater resources which are vital for the island's economy; spatial variations of the groundwater level are important for developing management and monitoring strategies. We evaluate the performance of the interpolation methods with respect to different statistical measures. The Spartan variogram family is applied for the first time to hydrological data and is shown to be optimal with respect to stochastic interpolation of this dataset. The three stochastic methods (OK, DK and UK) perform overall better than the deterministic counterparts (IDW and MC). DK, which is herein for the first time applied to hydrological data, yields the most accurate cross-validation estimate for the lowest value in the dataset. OK and UK lead to smooth isolevel contours, whilst DK and IDW generate more edges. The stochastic methods deliver estimates of prediction uncertainty which becomes highest near the southeastern border of the basin.

  18. Head lice prevalence among households in Norway: importance of spatial variables and individual and household characteristics.

    Science.gov (United States)

    Rukke, Bjørn Arne; Birkemoe, Tone; Soleng, Arnulf; Lindstedt, Heidi Heggen; Ottesen, Preben

    2011-09-01

    Head lice prevalence varies greatly between and within countries, and more knowledge is needed to approach causes of this variation. In the present study, we investigated head lice prevalence among elementary school students and their households in relation to individual and household characteristics as well as spatial variables. The investigation included households from 5 geographically separated municipalities. Present infestations among household members as well as previous infestations in the household were reported in a questionnaire. In elementary school students prevalence was low (1·63%), but more than one-third of the households (36·43%) had previously experienced pediculosis. Prevalence was higher in elementary school students than in other household members, and highest in third-grade children. Prevalence was also influenced by the school attended, which suggested that interactions between children in the same school are important for head lice transmission. Previous occurrence of head lice in homes also increased the risk of present infestation. Prevalence of previous infestations was higher in households with more children and in more densely populated municipalities, indicating that the density of hosts or groups of hosts influences transmission rates. These results demonstrate that information of hosts' spatial distribution as well as household and individual characteristics is needed to better understand head lice population dynamics.

  19. Spatial variability in the diagnosis of nutritional status in the papaya

    Directory of Open Access Journals (Sweden)

    Julião Soares de Sousa Lima

    2016-06-01

    Full Text Available ABSTRACT Leaf analysis is widely used to study the nutritional status of plants, based on the fact of there being a direct correlation between rate of growth and the nutrient levels in leaf tissue. This study was carried out on a commercial crop of Golden THB papaya, in the north of the State of Espirito Santo, Brazil, to determine the spatial variability of nutrients in the petiole of leaf samples collected when carrying out sexing in a regular grid of 129 georeferenced points. Harvesting was carried out manually 270-365 days after transplanting. All the characteristics displayed a strong spatial dependence, the spherical and exponential semivariograms being adjusted for the data. The greatest and smallest ranges were found for the micronutrients Mn and Zn respectively. Mean productivity was considered to be low at 13.6 Mg ha-1. Geostatistical analysis of the data aided in the preparation of thematic maps showing the different areas of productivity and foliar application of fertiliser in the papaya. However, the largest regions in the area were displayed by those classes which included the mean value for an attribute, indicating the use of the mean values in the recommendation of foliar fertilisation, with the exception of P and K.

  20. East Sea Spatial and Temporal Variability of Thermohaline Structure and Circulation Identified From Observational (T, S) Profiles

    Science.gov (United States)

    2015-12-01

    VARIABILITY OF THERMOHALINE STRUCTURE AND CIRCULATION IDENTIFIED FROM OBSERVATIONAL (T, S) PROFILES by Hyewon Choi December 2015 Thesis Advisor...the gridded data, seasonal and inter-annual variability of thermohaline structure and circulation of the East Sea were analyzed. Found was a low...unlimited EAST SEA SPATIAL AND TEMPORAL VARIABILITY OF THERMOHALINE STRUCTURE AND CIRCULATION IDENTIFIED FROM OBSERVATIONAL (T, S) PROFILES Hyewon Choi

  1. Variabilidad espacial y diaria del contenido de humedad en el suelo en tres sistemas agroforestales Spatial and daily variability of soil moisture content in three agroforestry systems

    Directory of Open Access Journals (Sweden)

    Mariela Rivera Peña

    2009-04-01

    Full Text Available En seis puntos de tres transectos (102 m paralelos (9 m en tres sistemas de uso del terreno (Quesungual menor de dos años, SAQThe objective of this study was to determine the level of soil spatial variability in an area consisting of the land uses: Quesungual slash and mulch agroforestry system with less than two years (QSMAS<2, Slash-and-burn traditional system (SB and Secondary forest (SF. Soil samples were taken in three parallel transects of 102 m in length, separated 9 meters. The profile was sampled in the depths from 0 to 5 cm, 5 to 10 cm, 10 to 20 cm and 20 to 40 cm in 6 points (09, 11 am and 05 during 9 days. Coefficient of variation for soil properties varied for bulk density (0.76 and 15.1%, organic carbon (30.4 and 54.3%, volumetric moisture (9.5 and 23.5%, sand (12.8 and 22.5% and clay (14.0 and 29.2%. The geo-statistical analysis showed that the random component of the spatial dependence was predominant over the nugget effect. The functions of semivariograms, structured for each variable were used to generate maps of interpolated contours at a fine scale. The Moran (I autocorrelation indicated that sampling ranges less than 9 m would be adequate to detect spatial structure of the volumetric moisture variable.

  2. Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review

    Directory of Open Access Journals (Sweden)

    E. Cristiano

    2017-07-01

    Full Text Available In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological response, based on small-scale representation of urban catchment spatial variability. Despite these efforts, interactions between rainfall variability, catchment heterogeneity, and hydrological response remain poorly understood. This paper presents a review of our current understanding of hydrological processes in urban environments as reported in the literature, focusing on their spatial and temporal variability aspects. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge needs to be further developed to improve our understanding of and capability to predict urban hydrological response.

  3. The geovisualisation window of the temporal and spatial variability for Volunteered Geographic Information activities

    Science.gov (United States)

    Medynska-Gulij, Beata; Myszczuk, Miłosz

    2012-11-01

    This study presents an attempt to design geographical visualisation tools that allow to tackle the immensity of spatial data provided by Volunteered Geographic Information (VGI), both in terms of temporal and spatial aspects. In accordance with the assumptions made at the conceptual stage, the final action was the implementation of the window entitled ‘Geovisualisation of the Panoramio.com Activities in District of Poznan 2011’ into the web browser. The concept has been based on a division of the geovisualisation window into three panels, of which the most important - in order to capture spatial variability - have statistical maps at the general level (dot map and choropleth map), while at the detailed level - a dot map on a topographic reference map or tourist map. For two ranges, temporal variability is presented by graphs, while a review of attributes of individual activities of the social website in question is set forward in the table panel. The element that visually interlinks all of the panels is the emphasised individual activity. Problemem podjetym w tych badaniach stało sie wykorzystanie metod z nurtu geograficznej wizualizacji do wskazania cech fenomenu VGI w zakresie zmiennosci czasowo-przestrzennej. Zgodnie z załozeniami poczynionymi w etapie koncepcyjnym finalnym działaniem stało sie zaimplementowanie do przegladarki internetowej okna pod tytułem: ”Geowizualizacja aktywnosci społecznosci Panoramio.com w powiecie poznanskim w 2011 roku”. Koncepcja została oparta na podziale okna geowizualizacji na trzy panele, z których najwazniejsze znaczenie dla uchwycenia zmiennosci przestrzennej na poziomie ogólnym ma kartogram, natomiast na poziomie szczegółowym mapa kropkowa wyswietlana na podkładzie mapy topograficznej lub turystycznej. Zmiennosc czasowa w dwóch zakresach prezentuja wykresy, a przeglad atrybutów poszczególnych aktywnosci prezentowanego portalu społecznosciowego zapewnia tabela. Elementem spajajacym wizualnie wszystkie

  4. Albedo Spatial Variability and Causes on the Western Greenland Ice Sheet Percolation Zone

    Science.gov (United States)

    Lewis, G.; Osterberg, E. C.; Hawley, R. L.; Koffman, B. G.; Marshall, H. P.; Birkel, S. D.; Dibb, J. E.

    2016-12-01

    Many recent studies have concluded that Greenland Ice Sheet (GIS) mass loss has been accelerating over recent decades, but spatial and temporal variations in GIS mass balance remain poorly understood due to a complex relationship among precipitation and temperature changes, increasing melt and runoff, ice discharge, and surface albedo. Satellite measurements from MODerate resolution Imaging Spectroradiometer (MODIS) indicate that albedo has been declining over the past decade, but the cause and extent of GIS albedo change remains poorly constrained by field data. As fresh snow (albedo > 0.85) warms and melts, its albedo decreases due to snow grain growth, promoting solar absorption, higher snowpack temperatures and further melt. However, dark impurities like soot and dust can also significantly reduce snow albedo, even in the dry snow zone. While many regional climate models (e.g. the Regional Atmospheric Climate MOdel - RACMO2) calculate albedo spatial resolutions on the order of 10-30 km, and MODIS averages albedo over 500 m, surface features like sastrugi can affect albedo on much smaller scales. Here we assess the relative importance of grain size and shape vs. impurity concentrations on albedo in the western GIS percolation zone. We collected broadband albedo measurements (300-2500 nm at 3-8 nm resolution) at 35 locations using an ASD FieldSpec4 spectroradiometer to simultaneously quantify radiative fluxes and spectral reflectance. Measurements were collected on 10 x 10 m, 1 x 1 km, 5 x 5 km, and 10 x 10 km grids to determine the spatial variability of albedo as part of the 850-km Greenland Traverse for Accumulation and Climate Studies (GreenTrACS) traverse from Raven/Dye 2 to Summit. Additionally, we collected shallow (0-50 cm) snow pit samples every 5 cm at ASD measurement sites to quantify black carbon and mineral dust concentrations and size distributions using a Single Particle Soot Photometer and Coulter Counter, respectively. Preliminary results

  5. Spatial and seasonal variability of tap water disinfection by-products within distribution pipe networks.

    Science.gov (United States)

    Charisiadis, Pantelis; Andra, Syam S; Makris, Konstantinos C; Christophi, Costas A; Skarlatos, Dimitrios; Vamvakousis, Vasilis; Kargaki, Sophia; Stephanou, Euripides G

    2015-02-15

    Gradually-changing shocks associated with potable water quality deficiencies are anticipated for urban drinking-water distribution systems (UDWDS). The impact of structural UDWDS features such as, the number of pipe leaking incidences on the formation of water trihalomethanes (THM) at the geocoded household level has never been studied before. The objectives were to: (i) characterize the distribution of water THM concentrations in households from two district-metered areas (DMAs) with contrasting UDWDS characteristics sampled in two seasons (summer and winter), and (ii) assess the within- and between-household, spatial variability of water THM accounting for UDWDS characteristics (household distance from chlorination tank and service pipe leaking incidences). A total of 383 tap water samples were collected from 193 households located in two DMAs within the UDWDS of Nicosia city, Cyprus, and analyzed for the four THM species. The higher intraclass correlation coefficient (ICC) values for water tribromomethane (TBM) (0.75) followed by trichloromethane (0.42) suggested that the two DMAs differed with respect to these analytes. On the other hand, the low ICC values for total THM levels between the two DMAs suggested a large variance between households. The effect of households nested under each DMA remained significant (pnetwork characteristics. Our results could find use by water utilities in overcoming techno-economic difficulties associated with the large spatiotemporal variability of THM, while accounting for the influence of UDWDS features at points of water use. Copyright © 2014 Elsevier B.V. All rights reserved.

  6. Drought intensity and spatial variability in Gabes Watershed, south-eastern Tunisia

    Directory of Open Access Journals (Sweden)

    Jemai Sabrine

    2016-12-01

    Full Text Available Chronological series of monthly and annual precipitation data recorded in Gabes Watershed, south-eastern Tunisia, were analyzed. The study is based on the standardized precipitation index (SPI values, computed for 10 rainfall stations over the period 1987–2012, which corresponds to an observatory period of 25 hydrologic years (from September to August. The results obtained show a great variability in SPI values. The historical evolution of the SPI made it possible to define the periods of excess and deficit, corresponding to wet and dry periods respectively. The wet years were found to be 1989–1990, 1995–1996 and 2006–2007 while the dry years were 1987–1988, 1996–1997, 2000–2001, 2001–2002, 2007–2008, 2008–2009 and 2009–2010. This clearly shows alternating wet and dry periods, but with drought episodes taking prevalence over rainy fronts throughout the study period. Indeed, a high tendency towards a drop in precipitation and important sequences of drought were observed. Spatial variability of drought throughout Gabes Watershed was examined by geostatistical analysis of SPI, as drought and rainfall distribution vary with latitude, longitude, topography and proximity to the Mediterranean Sea. The results obtained showed that, compared to coastal and southern areas, drought was observed to be more important in the West and the North of Gabes Watershed. The SPI showed that moderate droughts are generally more frequent than severe or extreme droughts in most of the Watershed.

  7. Estimation of the temperature spatial variability in confined spaces based on thermal imaging

    Directory of Open Access Journals (Sweden)

    Augustyn Grzegorz

    2017-01-01

    Full Text Available In developed countries the salaries of office workers are several times higher than the total cost of maintaining and operating the building. Therefore even a small improvement in human work productivity and performance as a result of enhancing the quality of their work environment may lead to a meaningful economic benefits. The air temperature is the most commonly used indicator in assessing the indoor environment quality. What is more, it is well known that thermal comfort has the biggest impact on employees performance and their ability to work efficiently. In majority of office buildings, indoor temperature is managed by heating, ventilation and air conditioning (HVAC appliances. However the way how they are currently managed and controlled leads to the nonhomogeneous distribution of temperature in certain space. An approach to determining the spatial variability of temperature in confined spaces was introduced based on thermal imaging temperature measurements. The conducted research and obtained results enabled positive verification of the method and creation of surface plot illustrating the temperature variability.

  8. Spatial contexts for temporal variability in alpine vegetation under ongoing climate change

    Science.gov (United States)

    Fagre, Daniel B.; ,; George P. Malanson,

    2013-01-01

    A framework to monitor mountain summit vegetation (The Global Observation Research Initiative in Alpine Environments, GLORIA) was initiated in 1997. GLORIA results should be taken within a regional context of the spatial variability of alpine tundra. Changes observed at GLORIA sites in Glacier National Park, Montana, USA are quantified within the context of the range of variability observed in alpine tundra across much of western North America. Dissimilarity is calculated and used in nonmetric multidimensional scaling for repeated measures of vascular species cover at 14 GLORIA sites with 525 nearby sites and with 436 sites in western North America. The lengths of the trajectories of the GLORIA sites in ordination space are compared to the dimensions of the space created by the larger datasets. The absolute amount of change on the GLORIA summits over 5 years is high, but the degree of change is small relative to the geographical context. The GLORIA sites are on the margin of the ordination volumes with the large datasets. The GLORIA summit vegetation appears to be specialized, arguing for the intrinsic value of early observed change in limited niche space.

  9. Spatial and temporal variability in a stratified hypersaline microbial mat community.

    Science.gov (United States)

    Dillon, Jesse G; Miller, Scott; Bebout, Brad; Hullar, Meredith; Pinel, Nicolás; Stahl, David A

    2009-04-01

    Hypersaline microbial mat communities have recently been shown to be more diverse than once thought. The variability in community composition of hypersaline mats, both in terms of spatial and temporal dimensions, is still poorly understood. Because this information is essential to understanding the complex biotic and abiotic interactions within these communities, terminal restriction fragment analysis and 16S rRNA gene sequencing were used to characterize the near-surface community of a hypersaline microbial mat in Guerrero Negro, Mexico. Core samples were analyzed to assay community variability over large regional scales (centimeter to kilometer) and to track depth-related changes in population distribution at 250-microm intervals over a diel period. Significant changes in total species diversity were observed at increasing distances across the mat surface; however, key species (e.g. Microcoleus sp.) were identified throughout the mat. The vertical position and abundance of >50% of the 60 peaks detected varied dramatically over a diel cycle, including Beggiatoa sp., cyanobacteria, Chloroflexus sp., Halochromatium sp., Bacteroidetes sp. and several as-yet-identified bacteria. Many of these migrations correlated strongly with diel changes in redox conditions within the mat, contributing to strong day-night community structure differences.

  10. Estimation of the temperature spatial variability in confined spaces based on thermal imaging

    Science.gov (United States)

    Augustyn, Grzegorz; Jurasz, Jakub; Jurczyk, Krzysztof; Korbiel, Tomasz; Mikulik, Jerzy; Pawlik, Marcin; Rumin, Rafał

    2017-11-01

    In developed countries the salaries of office workers are several times higher than the total cost of maintaining and operating the building. Therefore even a small improvement in human work productivity and performance as a result of enhancing the quality of their work environment may lead to a meaningful economic benefits. The air temperature is the most commonly used indicator in assessing the indoor environment quality. What is more, it is well known that thermal comfort has the biggest impact on employees performance and their ability to work efficiently. In majority of office buildings, indoor temperature is managed by heating, ventilation and air conditioning (HVAC) appliances. However the way how they are currently managed and controlled leads to the nonhomogeneous distribution of temperature in certain space. An approach to determining the spatial variability of temperature in confined spaces was introduced based on thermal imaging temperature measurements. The conducted research and obtained results enabled positive verification of the method and creation of surface plot illustrating the temperature variability.

  11. Evolution of dispersal in spatially and temporally variable environments: The importance of life cycles.

    Science.gov (United States)

    Massol, François; Débarre, Florence

    2015-07-01

    Spatiotemporal variability of the environment is bound to affect the evolution of dispersal, and yet model predictions strongly differ on this particular effect. Recent studies on the evolution of local adaptation have shown that the life cycle chosen to model the selective effects of spatiotemporal variability of the environment is a critical factor determining evolutionary outcomes. Here, we investigate the effect of the order of events in the life cycle on the evolution of unconditional dispersal in a spatially heterogeneous, temporally varying landscape. Our results show that the occurrence of intermediate singular strategies and disruptive selection are conditioned by the temporal autocorrelation of the environment and by the life cycle. Life cycles with dispersal of adults versus dispersal of juveniles, local versus global density regulation, give radically different evolutionary outcomes that include selection for total philopatry, evolutionary bistability, selection for intermediate stable states, and evolutionary branching points. Our results highlight the importance of accounting for life-cycle specifics when predicting the effects of the environment on evolutionarily selected trait values, such as dispersal, as well as the need to check the robustness of model conclusions against modifications of the life cycle. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

  12. Integrating spatial and temporal variability into the analysis of fish food web linkages in Tijuana Estuary.

    Energy Technology Data Exchange (ETDEWEB)

    West, Janelle M.; Williams, Greg D.; Madon, Sharook P.; Zedler, Joy B.

    2003-05-14

    Our understanding of fish feeding interactions at Tijuana Estuary was improved by incorporating estimates of spatial and temporal variability into diet analyses. We examined the stomach contents of 7 dominant species (n=579 total fish) collected between 1994 and 1999. General feeding patterns pooled over time produced a basic food web consisting of 3 major trophic levels: (1) primary consumers (Atherinops affinis, Mugil cephalus) that ingested substantial amounts of plant material and detritus; (2) benthic carnivores (Clevelandia ios, Hypsopsetta guttulata, Gillichthys mirabilis, and Fundulus parvipinnis) that ingested high numbers of calanoid copepods and exotic amphipods (Grandidierella japonica); and (3) piscivores (Paralichthys californicus and Leptocottus armatus) that often preyed on smaller gobiids. Similarity-based groupings of individual species' diets were identified using nonmetric multidimensional scaling to characterize their variability within and between species, and in s pace and time. This allowed us to identify major shifts and recognize events (i.e., modified prey abundance during 1997-98 El Nino floods) that likely caused these shifts.

  13. Spatial aggregation for crop modelling at regional scales: the effects of soil variability

    Science.gov (United States)

    Coucheney, Elsa; Villa, Ana; Eckersten, Henrik; Hoffmann, Holger; Jansson, Per-Erik; Gaiser, Thomas; Ewert, Franck; Lewan, Elisabet

    2017-04-01

    Modelling agriculture production and adaptation to the environment at regional or global scale receives much interest in the context of climate change. Process-based soil-crop models describe the flows of mass (i.e. water, carbon and nitrogen) and energy in the soil-plant-atmosphere system. As such, they represent valuable tools for predicting agricultural production in diverse agro-environmental contexts as well as for assessing impacts on the environment; e.g. leaching of nitrates, changes in soil carbon content and GHGs emissions. However, their application at regional and global scales for climate change impact studies raises new challenges related to model input data, calibration and evaluation. One major concern is to take into account the spatial variability of the environmental conditions (e.g. climate, soils, management practices) used as model input and because the impacts of climate change on cropping systems depend strongly on the site conditions and properties (1). For example climate change effects on yield can be either negative or positive depending on the soil type (2). Additionally, the use of different methods of upscaling and downscaling adds new sources of modelling uncertainties (3). In the present study, the effect of aggregating soil input data by area majority of soil mapping units was explored for spatially gridded simulations with the soil-vegetation model CoupModel for a region in Germany (North Rhine-Westphalia, NRW). The data aggregation effect (DAE) was analysed for wheat yield, water drainage, soil carbon mineralisation and nitrogen leaching below the root zone. DAE was higher for soil C and N variables than for yield and drainage and were strongly related to the spatial coverage of specific soils within the study region. These 'key soils' were identified by a model sensitivity analysis to soils present in the NRW region. The spatial aggregation of the key soils additionally influenced the DAE. Our results suggest that a spatial

  14. Spatiotemporal estimation of historical PM2.5 concentrations using PM10, meteorological variables, and spatial effect

    Science.gov (United States)

    Li, Lianfa; Wu, Anna H.; Cheng, Iona; Chen, Jiu-Chiuan; Wu, Jun

    2017-10-01

    Monitoring of fine particulate matter with diameter estimate historical PM2.5 concentrations by incorporating spatial effect and the measurements of existing co-pollutants such as particulate matter with diameter PM10) and meteorological variables. Monitoring data of PM10, PM2.5, and meteorological variables covering the entire state of California were obtained from 1999 through 2013. We developed a spatiotemporal model that quantified non-linear associations between PM2.5 concentrations and the following predictor variables: spatiotemporal factors (PM10 and meteorological variables), spatial factors (land-use patterns, traffic, elevation, distance to shorelines, and spatial autocorrelation), and season. Our model accounted for regional-(county) scale spatial autocorrelation, using spatial weight matrix, and local-scale spatiotemporal variability, using local covariates in additive non-linear model. The spatiotemporal model was evaluated, using leaving-one-site-month-out cross validation. Our final daily model had an R2 of 0.81, with PM10, meteorological variables, and spatial autocorrelation, explaining 55%, 10%, and 10% of the variance in PM2.5 concentrations, respectively. The model had a cross-validation R2 of 0.83 for monthly PM2.5 concentrations (N = 8170) and 0.79 for daily PM2.5 concentrations (N = 51,421) with few extreme values in prediction. Further, the incorporation of spatial effects reduced bias in predictions. Our approach achieved a cross validation R2 of 0.61 for the daily model when PM10 was replaced by total suspended particulate. Our model can robustly estimate historical PM2.5 concentrations in California when PM2.5 measurements were not available.

  15. Effects of Yoga on Heart Rate Variability and Mood in Women: A Randomized Controlled Trial.

    Science.gov (United States)

    Chu, I-Hua; Lin, Yuh-Jen; Wu, Wen-Lan; Chang, Yu-Kai; Lin, I-Mei

    2015-12-01

    To examine the effects of an 8-week yoga program on heart rate variability and mood in generally healthy women. Randomized controlled trial. Fifty-two healthy women were randomly assigned to a yoga group or a control group. Participants in the yoga group completed an 8-week yoga program, which comprised a 60-minute session twice a week. Each session consisted of breathing exercises, yoga pose practice, and supine meditation/relaxation. The control group was instructed not to engage in any yoga practice and to maintain their usual level of physical activity during the study. Participants' heart rate variability, perceived stress, depressive symptoms, and state and trait anxiety were assessed at baseline (week 0) and after the intervention (week 9). No measures of heart rate variability changed significantly in either the yoga or control group after intervention. State anxiety was reduced significantly in the yoga group but not in the control group. No significant changes were noted in perceived stress, depression, or trait anxiety in either group. An 8-week yoga program was not sufficient to improve heart rate variability. However, such a program appears to be effective in reducing state anxiety in generally healthy women. Future research should involve longer periods of yoga training, include heart rate variability measures both at rest and during yoga practice, and enroll women with higher levels of stress and trait anxiety.

  16. Spatial variability of air temperature in a free-stall in the Northeastern semi-arid region of Brazil

    Directory of Open Access Journals (Sweden)

    Indira C. M. Gonçalves

    2016-01-01

    Full Text Available ABSTRACT The knowledge on the spatial variability of climatic attributes and the building of Kriging maps can assist in the design and management of confined animal facilities, by allowing a spatial visualization that is helpful for the planning and control of information from the production environment. The study aimed to characterize the spatial variability of air temperature in a free-stall barn used for dairy cattle confinement located in Petrolina-PE, Brazil, in different seasons and at different times. The variable air temperature was recorded at 136 points distributed in the areas under the shed and the shade cloth for the study of spatial variability and the construction of maps by Kriging. Air temperature data was collected in the winter and in the summer, in the months of July and August (2013 and January and February (2014, at different times (9 and 15 h. According to the results, the use of geostatistics enabled to define areas with different spatial variabilities in air temperature and specific areas in the free-stall with values higher than the recommended levels for thermal comfort. In addition, the central part of the facility is the region with the lowest values of air temperatures, due to the presence of a ridge vent.

  17. Fine-Scale Spatial Variability of Precipitation, Soil, and Plant Water Isotopes

    Science.gov (United States)

    Goldsmith, G. R.; Braun, S.; Romero, C.; Engbersen, N.; Gessler, A.; Siegwolf, R. T.; Schmid, L.

    2015-12-01

    Introduction: The measurement of stable isotope ratios of water has become fundamental in advancing our understanding of environmental patterns and processes, particularly with respect to understanding the movement of water within the soil-plant-atmosphere continuum. While considerable research has explored the temporal variation in stable isotope ratios of water in the environment, our understanding of the spatial variability of these isotopes remains poorly understood. Methods: We collected spatially explicit samples of throughfall and soil water (n=150 locations) from a 1 ha plot delineated in a mixed deciduous forest in the northern Alps of Switzerland. We complemented this with fully sunlit branch and leaf samples (n = 60 individuals) collected from Picea abies and Fagus sylvatica between 14:00 and 16:00 on the same day by means of a helicopter. Soil and plant waters were extracted using cryogenic vacuum distillation and all samples were analyzed for δ18O using an isotope ratio mass spectrometer. Results: The mean δ18O of throughfall (-3.3 ± 0.8‰) indicated some evaporative enrichment associated with passage through the canopy, but this did not significantly differ from the precipitation collected in nearby open sites (-4.05‰). However, soil was depleted (-7.0 ± 1.8‰) compared to throughfall and there was no significant relationship between the two, suggesting that the sampling for precipitation inputs did not capture all the sources (e.g. stream water, which was -11.5‰) contributing to soil water δ18O ratios. Evaporative enrichment of δ18O was higher in leaves of Fagus (14.8 ± 1.8‰) than in leaves of Picea (11.8 ± 1.7‰). Sampling within crowns of each species (n = 5 branches each from 5 individuals) indicated that variability in a single individual is similar to that among individuals. Discussion: Stable isotopes of water are frequently engaged for studies of ecohydrology, plant ecophysiology, and paleoclimatology. Our results help

  18. Monitoring meteorological spatial variability in viticulture using a low-cost Wireless Sensor Network

    Science.gov (United States)

    Matese, Alessandro; Crisci, Alfonso; Di Gennaro, Filippo; Primicerio, Jacopo; Tomasi, Diego; Guidoni, Silvia

    2014-05-01

    In a long-term perspective, the current global agricultural scenario will be characterize by critical issues in terms of water resource management and environmental protection. The concept of sustainable agriculture would become crucial at reducing waste, optimizing the use of pesticides and fertilizers to crops real needs. This can be achieved through a minimum-scale monitoring of the crop physiologic status and the environmental parameters that characterize the microclimate. Viticulture is often subject to high variability within the same vineyard, thus becomes important to monitor this heterogeneity to allow a site-specific management and maximize the sustainability and quality of production. Meteorological variability expressed both at vineyard scale (mesoclimate) and at single plant level (microclimate) plays an important role during the grape ripening process. The aim of this work was to compare temperature, humidity and solar radiation measurements at different spatial scales. The measurements were assessed for two seasons (2011, 2012) in two vineyards of the Veneto region (North-East Italy), planted with Pinot gris and Cabernet Sauvignon using a specially designed and developed Wireless Sensor Network (WSN). The WSN consists of various levels: the Master/Gateway level coordinates the WSN and performs data aggregation; the Farm/Server level takes care of storing data on a server, data processing and graphic rendering. Nodes level is based on a network of peripheral nodes consisting of a sensor board equipped with sensors and wireless module. The system was able to monitor the agrometeorological parameters in the vineyard: solar radiation, air temperature and air humidity. Different sources of spatial variation were studied, from meso-scale to micro-scale. A widespread investigation was conducted, building a factorial design able to evidence the role played by any factor influencing the physical environment in the vineyard, such as the surrounding climate

  19. Investigation into the Horizontal Spatial Variability of Dew at Field-Scale

    Science.gov (United States)

    Rowlandson, T. L.; Hornbuckle, B. K.; Patton, J.; Russell, E.; Seier, K.; Spoth, K.

    2009-12-01

    The occurrence of free moisture on a crop canopy, whether in the form of intercepted precipitation or dew, has implications for both plant disease development and sensing of soil moisture by microwave remote sensing. In agriculture, the duration of leaf wetness can impact disease development, and with microwave remote sensing, free water on the canopy can influence the detection of soil moisture by increasing or decreasing the measured brightness temperature, depending on the canopy being investigated. Research has been conducted on the variability of dew vertically within a crop canopy; however the horizontal spatial variability of dew at the field scale had not yet been examined. We conducted a study in a maize field during the growing season of 2009 to investigate variations in dew duration and amount at 4 locations in a 1km2 with varying topography and soil characteristics. At each of the four sites, two leaf wetness sensors were installed at both 1/3- and 2/3-canopy height, providing insight into variations in dew duration between the four locations. Above canopy temperature and relative humidity were measured, in addition to in-canopy temperature and relative humidity, measured at half-canopy height. Soil moisture was measured continuously at each of the four locations. Physical samples were taken 11 times during the months of July and August, 2009. Sampling began at sunrise, and was conducted 3 times at each measurement location at both 1/3- and 2/3-canopy height. In addition to samples taken at sunrise, on three occasions, samples were taken at sunset, 11pm and 3am in order to monitor the progression of dew development. A sample at three of the locations occurred at the end of August to determine how dew varies at each location by taking simultaneous measurements. Leaf area index (LAI) was measured throughout the growing season at 1/3- and 2/3-canopy height at each measurement location. This information was utilized to investigate how dew measurements taken

  20. Spatial and temporal scales of satellite sea surface salinity variability in the Tropical Atlantic

    Science.gov (United States)

    Tzortzi, E.

    2016-02-01

    Taking advantage of the different coverage of satellite-derived sea surface salinity (SSS), concurrent SMOS and Aquarius observations are used for the first time for the quantification of the spatial and temporal decorrelation scales of SSS in the Tropical Atlantic. Different 7-10 days composite SSS products from the two missions are used to examine any potential effects of varying resolution, bias corrections and averaging characteristics. Given the dominance of the seasonal cycle in SSS variability in the region, the scales are calculated both for the mean and anomaly SSS fields. With the seasonal cycle retained, homogeneous SSS variations are strongly anisotropic, with the longest zonal scales in the Tropics reaching over 2000 km and long temporal scales of up to 70-80 days, as seen by both SMOS and Aquarius. The longest meridional scales of over 1000 km occur in the South Atlantic ( 10°-25°S), most discernible in Aquarius data. SSS variability has the longest persistence in time of up to 150-200 days at the Southern Sargasso Sea in the N.W. Atlantic. The removal of the seasonal cycle decreases noticeably the spatio-temporal scales over most of the basin. Overall, with the exception of differences in the S. Atlantic, there is good consistency between the spatio-temporal scales of SSS from the two satellites and different products, despite their individual calibration and resolution characteristics. The new estimates of decorrelation scales of SSS improve our knowledge of the processes and mechanisms controlling the Tropical Atlantic SSS variability, and represent a powerful new investigative tool equally applicable to other regions, SSS products and other ocean geophysical properties. This work has also important applications for the evaluation of the impact of satellite SSS in assimilation systems, the development of optimally interpolated products, as well as the definition of appropriate validation procedures of the various satellite SSS products.

  1. The Importance of Freshwater to Spatial Variability of Aragonite Saturation State in the Gulf of Alaska

    Science.gov (United States)

    Siedlecki, Samantha A.; Pilcher, Darren J.; Hermann, Albert J.; Coyle, Ken; Mathis, Jeremy

    2017-11-01

    High-latitude and subpolar regions like the Gulf of Alaska (GOA) are more vulnerable than equatorial regions to rising carbon dioxide (CO2) levels, in part due to local processes that amplify the global signal. Recent field observations have shown that the shelf of the GOA is currently experiencing seasonal corrosive events (carbonate mineral saturation states Ω, Ω < 1), including suppressed Ω in response to ocean acidification as well as local processes like increased low-alkalinity glacial meltwater discharge. While the glacial discharge mainly influences the inner shelf, on the outer shelf, upwelling brings corrosive waters from the deep GOA. In this work, we develop a high-resolution model for carbon dynamics in the GOA, identify regions of high variability of Ω, and test the sensitivity of those regions to changes in the chemistry of glacial meltwater discharge. Results indicate the importance of this climatically sensitive and relatively unconstrained regional freshwater forcing for Ω variability in the nearshore. The increase was nearly linear at 0.002 Ω per 100 µmol/kg increase in alkalinity in the freshwater runoff. We find that the local winds, biological processes, and freshwater forcing all contribute to the spatial distribution of Ω and identify which of these three is highly correlated to the variability in Ω. Given that the timing and magnitude of these processes will likely change during the next few decades, it is critical to elucidate the effect of local processes on the background ocean acidification signal using robust models, such as the one described here.

  2. Shoulder pain and cycle to cycle kinematic spatial variability during recovery phase in manual wheelchair users: a pilot investigation.

    Directory of Open Access Journals (Sweden)

    Chandrasekaran Jayaraman

    Full Text Available Wheelchair propulsion plays a significant role in the development of shoulder pain in manual wheelchair users (MWU. However wheelchair propulsion metrics related to shoulder pain are not clearly understood. This investigation examined intra-individual kinematic spatial variability during semi-circular wheelchair propulsion as a function of shoulder pain in MWU. Data from 10 experienced adult MWU with spinal cord injury (5 with shoulder pain; 5 without shoulder pain were analyzed in this study. Participants propelled their own wheelchairs on a dynamometer at 3 distinct speeds (self-selected, 0.7 m/s, 1.1 m/s for 3 minutes at each speed. Motion capture data of the upper limbs were recorded. Intra-individual kinematic spatial variability of the steady state wrist motion during the recovery phase was determined using principal component analysis (PCA. The kinematic spatial variability was calculated at every 10% intervals (i.e at 11 interval points, from 0% to 100% along the wrist recovery path.Overall, spatial variability was found to be highest at the start and end of the recovery phase and lowest during the middle of the recovery path. Individuals with shoulder pain displayed significantly higher kinematic spatial variability than individuals without shoulder pain at the start (at 10% interval of the recovery phase (p<.004.Analysis of intra-individual kinematic spatial variability during the recovery phase of manual wheelchair propulsion distinguished between those with and without shoulder pain. Variability analysis of wheelchair propulsion may offer a new approach to monitor the development and rehabilitation of shoulder pain.

  3. Shoulder pain and cycle to cycle kinematic spatial variability during recovery phase in manual wheelchair users: a pilot investigation.

    Science.gov (United States)

    Jayaraman, Chandrasekaran; Moon, Yaejin; Rice, Ian M; Hsiao Wecksler, Elizabeth T; Beck, Carolyn L; Sosnoff, Jacob J

    2014-01-01

    Wheelchair propulsion plays a significant role in the development of shoulder pain in manual wheelchair users (MWU). However wheelchair propulsion metrics related to shoulder pain are not clearly understood. This investigation examined intra-individual kinematic spatial variability during semi-circular wheelchair propulsion as a function of shoulder pain in MWU. Data from 10 experienced adult MWU with spinal cord injury (5 with shoulder pain; 5 without shoulder pain) were analyzed in this study. Participants propelled their own wheelchairs on a dynamometer at 3 distinct speeds (self-selected, 0.7 m/s, 1.1 m/s) for 3 minutes at each speed. Motion capture data of the upper limbs were recorded. Intra-individual kinematic spatial variability of the steady state wrist motion during the recovery phase was determined using principal component analysis (PCA). The kinematic spatial variability was calculated at every 10% intervals (i.e at 11 interval points, from 0% to 100%) along the wrist recovery path. Overall, spatial variability was found to be highest at the start and end of the recovery phase and lowest during the middle of the recovery path. Individuals with shoulder pain displayed significantly higher kinematic spatial variability than individuals without shoulder pain at the start (at 10% interval) of the recovery phase (p<.004). Analysis of intra-individual kinematic spatial variability during the recovery phase of manual wheelchair propulsion distinguished between those with and without shoulder pain. Variability analysis of wheelchair propulsion may offer a new approach to monitor the development and rehabilitation of shoulder pain.

  4. Robust design with imprecise random variables and its application in hydrokinetic turbine optimization

    Science.gov (United States)

    Hu, Zhen; Du, Xiaoping; Kolekar, Nitin S.; Banerjee, Arindam

    2014-03-01

    In robust design, uncertainty is commonly modelled with precise probability distributions. In reality, the distribution types and distribution parameters may not always be available owing to limited data. This research develops a robust design methodology to accommodate the mixture of both precise and imprecise random variables. By incorporating the Taguchi quality loss function and the minimax regret criterion, the methodology mitigates the effects of not only uncertain parameters but also uncertainties in the models of the uncertain parameters. Hydrokinetic turbine systems are a relatively new alternative energy technology, and both precise and imprecise random variables exist in the design of such systems. The developed methodology is applied to the robust design optimization of a hydrokinetic turbine system. The results demonstrate the effectiveness of the proposed methodology.

  5. Modified Exponential Type Estimator for Population Mean Using Auxiliary Variables in Stratified Random Sampling

    OpenAIRE

    Özel, Gamze

    2015-01-01

    In this paper, a new exponential type estimator is developed in the stratified random sampling for the population mean using auxiliary variable information. In order to evaluate efficiency of the introduced estimator, we first review some estimators and study the optimum property of the suggested strategy. To judge the merits of the suggested class of estimators over others under the optimal condition, simulation study and real data applications are conducted. The results show that the introduc...

  6. Equivalent conditions of complete moment convergence for extended negatively dependent random variables

    Directory of Open Access Journals (Sweden)

    Qunying Wu

    2017-05-01

    Full Text Available Abstract In this paper, we study the equivalent conditions of complete moment convergence for sequences of identically distributed extended negatively dependent random variables. As a result, we extend and generalize some results of complete moment convergence obtained by Chow (Bull. Inst. Math. Acad. Sin. 16:177-201, 1988 and Li and Spătaru (J. Theor. Probab. 18:933-947, 2005 from the i.i.d. case to extended negatively dependent sequences.

  7. An edgeworth expansion for a sum of M-Dependent random variables

    Directory of Open Access Journals (Sweden)

    Wan Soo Rhee

    1985-01-01

    Full Text Available Given a sequence X1,X2,…,Xn of m-dependent random variables with moments of order 3+α (0<α≦1, we give an Edgeworth expansion of the distribution of Sσ−1(S=X1+X2+…+Xn, σ2=ES2 under the assumption that E[exp(it Sσ1] is small away from the origin. The result is of the best possible order.

  8. Residual and Past Entropy for Concomitants of Ordered Random Variables of Morgenstern Family

    Directory of Open Access Journals (Sweden)

    M. M. Mohie EL-Din

    2015-01-01

    Full Text Available For a system, which is observed at time t, the residual and past entropies measure the uncertainty about the remaining and the past life of the distribution, respectively. In this paper, we have presented the residual and past entropy of Morgenstern family based on the concomitants of the different types of generalized order statistics (gos and give the linear transformation of such model. Characterization results for these dynamic entropies for concomitants of ordered random variables have been considered.

  9. The effect of cluster size variability on statistical power in cluster-randomized trials.

    Directory of Open Access Journals (Sweden)

    Stephen A Lauer

    Full Text Available The frequency of cluster-randomized trials (CRTs in peer-reviewed literature has increased exponentially over the past two decades. CRTs are a valuable tool for studying interventions that cannot be effectively implemented or randomized at the individual level. However, some aspects of the design and analysis of data from CRTs are more complex than those for individually randomized controlled trials. One of the key components to designing a successful CRT is calculating the proper sample size (i.e. number of clusters needed to attain an acceptable level of statistical power. In order to do this, a researcher must make assumptions about the value of several variables, including a fixed mean cluster size. In practice, cluster size can often vary dramatically. Few studies account for the effect of cluster size variation when assessing the statistical power for a given trial. We conducted a simulation study to investigate how the statistical power of CRTs changes with variable cluster sizes. In general, we observed that increases in cluster size variability lead to a decrease in power.

  10. High temporal and spatial variability of atmospheric-methane oxidation in Alpine glacier-forefield soils.

    Science.gov (United States)

    Chiri, Eleonora; Nauer, Philipp A; Rainer, Edda-Marie; Zeyer, Josef; Schroth, Martin H

    2017-07-07

    Glacier-forefield soils can provide a substantial sink for atmospheric CH4, facilitated by aerobic methane-oxidizing bacteria (MOB). However, MOB activity, abundance, and community structure may be affected by soil age, location in different forefield landforms, and temporal fluctuations in soil-physical parameters. We assessed spatial and temporal variability of atmospheric CH4 oxidation in an Alpine glacier forefield during the snow-free season 2013. We quantified CH4 flux in soils of increasing age and in different landforms (sandhill, terrace, floodplain) using soil-gas-profile and static flux-chamber methods. To determine MOB abundance and community structure, we employed pmoA-gene-based quantitative PCR and targeted-amplicon sequencing. Uptake of CH4 increased in magnitude and decreased in variability with increasing soil age. Sandhill soils exhibited CH4 uptake ranging from -0.03- -3.7 mg CH4 m-2 d-1 Floodplain and terrace soils exhibited smaller uptake and even intermittent CH4 emissions. Linear mixed-effect models indicated that soil age and landform were dominating factors shaping CH4 flux, followed by cumulative rainfall (weighted sum ≤ 4 d prior to sampling). Of 31 MOB operational taxonomic units retrieved, ∼30% were potentially novel, and ∼50% were affiliated with Upland Soil Clusters gamma and alpha. The MOB community structures in floodplain and terrace soils were nearly identical, but differed significantly from highly variable sandhill-soil communities. We conclude that soil age and landform modulate the soil CH4 sink strength in glacier forefields, and recent rainfall affects its short-term variability. This should be taken into account when including this environment in future CH4 inventories.Importance Oxidation of methane (CH4) in well-drained, "upland" soils is an important mechanism for the removal of this potent greenhouse gas from the atmosphere. It is largely mediated by aerobic, methane-oxidizing bacteria (MOB). Whereas there is

  11. Spatial and temporal variability of spring ecosystems in Cuatro Ciénegas, MX

    Science.gov (United States)

    Corman, J. R.; Ramos, J.; Childers, D. L.; Elser, J. J.

    2013-12-01

    Springs in desert ecosystems provide vital water resources and are often hotspots of biodiversity. Indeed, the Cuatro Ciénegas (CC) Valley, México, which hosts >300 springs, lakes, streams, and ponds, has the highest rate of endemism in North America. This region of the Chihuahuan Desert and its aquatic ecosystems are thought to be supported by both precipitation events and local and regional aquifers, however, the hydrologic influence and connectivity of the springs are not well understood. We have been monitoring the physicochemical characteristics of this system since 1998 and yearly since 2011. Our basin-wide study of 15 different aquatic features provides an opportunity to (1) characterize the physicochemical and nutrient landscape of the aquatic ecosystems and (2) test the assumptions of hypothesized hydrologic dynamics. The aquatic ecosystems of CC have an impressive spatial diversity in their physicochemical properties and support a locally-connected hydrologic model of the valley. Aqueous specific conductivity spanned 1.1 - 9.6 mS/cm2, with the highest values found in the eastern lobe and lowest values in the southeastern and northern regions. Dissolved organic carbon concentrations ranged over two orders of magnitude (max: 5.3 mM), with a similar spatial variability as specific conductivity. Nutrient data also showed geographic trends, however patterns differed for nitrogen (N) and phosphorus (P). While total dissolved N and P were highest in the eastern lobe, the highest values of each were not found at the same sites. Rancho las Pozas had the highest N (>500 uM N), while Los Hundidos had the highest P concentrations (as high as 10.8 uM P). Atomic N:P ratios ranged from 7 - 997 across CC, with a mean of 139. Both the highest (>500) and lowest (27 cm of rain in some regions. A comparison of our longest record from Río Mesquites, a spring-fed stream, and Los Hundidos, a collection of spring-fed and evaporitic ponds, shows the spatial dissimilarity of CC

  12. High-resolution mapping and spatial variability of soil organic carbon storage of permafrost-affected soils

    Science.gov (United States)

    Siewert, Matthias; Hugelius, Gustaf

    2017-04-01

    Permafrost-affected soils store large amounts of soil organic carbon (SOC). Mapping of this SOC provides a first order spatial input variable for research that relates carbon stored in permafrost regions to carbon cycle dynamics. High-resolution satellite imagery is becoming increasingly available even in circum-polar regions. The presented research highlights findings of high-resolution mapping efforts of SOC from five study areas in the northern circum-polar permafrost region. These study areas are located in Siberia (Kytalyk, Spasskaya Pad /Neleger, Lena delta), Northern Sweden (Abisko) and Northwestern Canada (Herschel Island). Our high spatial resolution analyses show how geomorphology has a strong influence on the distribution of SOC. This is organized at different spatial scales. Periglacial landforms and processes dictate local scale SOC distribution due to patterned ground. Such landforms are non-sorted circles and ice-wedge polygons of different age and scale. Palsas and peat plateaus are formed and can cover larger areas in Sub-Arctic environments. Study areas that have not been affected by Pleistocene glaciation feature ice-rich Yedoma sediments that dominate the local relief through thermokarst formation and create landscape scale macro environments that dictate the distribution of SOC. A general trend indicates higher SOC storage in Arctic tundra soils compared to forested Boreal or Sub-Arctic taiga soils. Yet, due to the shallower active layer depth in the Arctic, much of the SOC may be permanently frozen and thus not be available to ecosystem processes. Significantly more SOC is stored in soils compared to vegetation, indicating that vegetation growth and incorporation of the carbon into the plant phytomass alone will not be able to offset SOC released from permafrost. This contribution also addresses advances in thematic mapping methods and digital soil mapping of SOC in permafrost terrain. In particular machine-learning methods, such as support

  13. Evaluating environmental drivers of spatial variability in free-living nematode assemblages along the Portuguese margin

    Science.gov (United States)

    Lins, Lidia; Leliaert, Frederik; Riehl, Torben; Pinto Ramalho, Sofia; Alfaro Cordova, Eliana; Morgado Esteves, André; Vanreusel, Ann

    2017-02-01

    Understanding processes responsible for shaping biodiversity patterns on continental margins is an important requirement for comprehending anthropogenic impacts in these environments and further management of biodiversity. Continental margins perform crucial functions linked to key ecological processes which are mainly structured by surface primary productivity and particulate organic matter flux to the seafloor, but also by heterogeneity in seafloor characteristics. However, to what extent these processes control local and regional biodiversity remains unclear. In this study, two isobathic parallel transects located at the shelf break (300-400 m) and upper slope (1000 m) of the western Iberian margin were used to test how food input and sediment heterogeneity affect nematode diversity independently from the spatial factors geographical distance and water depth. We also examined the potential role of connectedness between both depth transects through molecular phylogenetic analyses. Regional generic diversity and turnover were investigated at three levels: within a station, between stations from the same depth transect, and between transects. High variability in food availability and high sediment heterogeneity at the shelf-break transect were directly linked to high diversity within stations and higher variation in community structure across stations compared to the upper slope transect. Contrastingly, environmental factors (food availability and sediment) did not vary significantly between stations located at the upper slope, and this lack of differences were also reflected in a low community turnover between these deeper stations. Finally, differences in nematode communities between both transects were more pronounced than differences within each of the isobathic transects, but these changes were paralleled by the previously mentioned environmental changes. These results suggest that changes in community structure are mainly dictated by environmental factors

  14. Temporal changes in spatial variability of plant available water at the watershed scale

    Science.gov (United States)

    de Alwis, D. A.; Gerard-Merchant, P.; Philpot, W. D.; Steenhuis, T. S.

    2004-05-01

    Identification of soil moisture distribution patterns by remote-sensing at the basin scale has become a major challenge for variable source hydrology. On time scales of a few days, water uptake from plants and evaporation can change significantly as a result of soil moisture dynamics, while on a time scales of a few weeks vegetation dynamics may represent a strong relationship with soil moisture. This study explores the relationship between vegetation dynamics and soil water content/ subsurface storage. Multi-temporal, multi-spectral Remotely Sensed Landsat images are used to identify spatial differences and temporal changes of vegetative cover over a subbasin of the Cannonsville reservoir, in the Catskills mountains region of New York state. Vegetation indices are processed and compared for six months (April,May June, July, September and October) in 2001. For each month, three classes of vegetation indices were determined from the frequency distribution of indices over the study area. The histogram of the vegetation indices revealed hypothetical Gaussians corresponding with generic land uses (forest, open grass/shrublands, pasture/crops and plowed land), and were well correlated with land uses estimated by from other sources. Comparison from one month to another of the actual position in the landscape of these three index classes led to the identification of different zones sharing the same index distribution. These zones were also seen to follow the temporal growth curve characteristic of its particular vegetation types. The spatial variations patterns of vegetation indices within each land use zone were then compared with the patterns of soil moisture distribution, as output by a fully distributed hydrological model, SMDR.

  15. Spatial and temporal variability of canopy cover and understory light in a Cerrado of Southern Brazil

    Directory of Open Access Journals (Sweden)

    JP. Lemos-Filho

    Full Text Available Canopy cover has significant effects on the understory environment, including upon light availability for seedling growth. The aim of the present study was to verify spatial heterogeneity and seasonal changes in the canopy cover of a dense Cerrado area, and their relationship to understory photosynthetic active radiation availability. Leaf area index (LAI values in the rainy season varied from 0.9 to 4.83, with 40% of the values ranging from 4.0 to 5.0, while in the dry season LAI varied from 0.74 to 3.3, with 53% of the values oscilating from 2.0 to 3.0. Understory light (Qi and the Lambert-Beer ratio (Qi/Qo were taken around noon on sunny days (between 11:00 AM and 1:00 PM. They were also statistically different (p < 0.01 between the dry and wet seasons, with 72% of sampled points in the rainy season presenting photosynthetic photon flux density (PPFD values lower than 250 μmol.m-2/s around noon, whereas in the dry season, most PPFD values varied from 1500 to 1817 μmol.m-2/s , thus providing high light availability for understory plants. In most of the studied sites, understory plants did not even receive enough light for 50% of their photosynthetic capacity in the wet season. In contrast during the dry season, Qi/Qo values of 0.8 to 1.0 were observed in more than 50% of the points, thereby allowing for photosynthetic light saturation. Thus, light variability around noon was higher during the dry season than in the wet season, its heterogeneity being related to spatial complexity in the canopy cover.

  16. Spatial variability of suspended sediment concentration within a tidal marsh in San Francisco Estuary

    Science.gov (United States)

    Swanson, K.; Drexler, J. Z.; Schoellhamer, D. H.; Buffington, K.; Takekawa, J.

    2012-12-01

    The sustainability of existing marshes and feasibility of future marsh restoration projects in San Francisco Estuary and elsewhere are threatened by a potential imbalance between accelerating sea-level rise and tidal marsh accretion rates. Marsh accretion is, in large part, dependent upon the availability of suspended sediment supplied from adjacent waterways. As water and sediment move across a marsh plain, suspended sediment settles and is trapped by vegetation near the source, resulting in less suspended-sediment concentration (SSC) and deposition in the interior of the marsh. Measurements of deposition and limited observations of SSC within marshes have confirmed a decrease in sediment supply and accumulation from the marsh edge to the marsh interiors, but the spatial variability of SSC has not been quantified in a manner that allows for comparison to a theoretical sediment transport model. For this study, transects of SSC were collected within a marsh at China Camp State Park in the San Francisco Estuary which demonstrate that a dominant pattern of settling can be quantified and generally matches the exponentially decreasing pattern of SSC predicted by a simple advection-settling model. The observed pattern suggests that sediment settling and marsh flow characteristics are consistent both spatially (between transects) and temporally (between monthly sampling events). However, deviations from the predicted pattern occurred systematically at some locations and are likely related to resuspension of sediment from the marsh surface or small, unmapped creek channels that supply sediment to the marsh. Despite these deviations, our data show this simple 1-D model of advection and settling can be used to generalize within-marsh sediment transport as a function of distance from the nearest sediment source.

  17. Spatial variability in mercury cycling and relevant biogeochemical controls in the Florida Everglades.

    Science.gov (United States)

    Liu, Guangliang; Cai, Yong; Mao, Yuxiang; Scheidt, Daniel; Kalla, Peter; Richards, Jennifer; Scinto, Leonard J; Tachiev, Georgio; Roelant, David; Appleby, Charlie

    2009-06-15

    Spatial patterns in mercury cycling and bioaccumulation at the landscape level in the Everglades were investigated by collecting and analyzing multimedia samples for mercury species and biogeochemical characteristics from 228 randomly located stations. Higher total mercury (THg) in environmental compartments (surface water, soil, flocculent detrital material (floc), and periphyton) generally occurred in the northern and central Everglades, but higher THg in water and periphyton in the Everglades National Park was an exception. Multiple biogeochemical characteristics, such as surface water dissolved organic matter (DOC(sw)), pH, chloride, and compositional properties of solid compartments (soil and floc), were identified to be important factors controlling THg distribution. Methylmercury (MeHg) was also higher in the northern Everglades for water, soil, and floc, but not for periphyton. Higher mosquitofish THg and bioaccumulation factor were observed in the central and southern Everglades, partially in accordance with periphyton MeHg distribution, but not in the "hot spot" areas of water, soil, or floc MeHg. The discrepancy in mercury bioaccumulation and mercury distribution in environmental compartments suggests that in addition to MeHg production, biogeochemical controls that make MeHg available to aquatic organisms, such as DOC(sw) and compositional properties of soil and floc, are important in mercury bioaccumulation.

  18. Spatial and temporal variability in growth of southern flounder (Paralichthys lethostigma)

    Science.gov (United States)

    Midway, Stephen R.; Wagner, Tyler; Arnott, Stephen A.; Biondo, Patrick; Martinez-Andrade, Fernando; Wadsworth, Thomas F.

    2015-01-01

    Delineation of stock structure is important for understanding the ecology and management of many fish populations, particularly those with wide-ranging distributions and high levels of harvest. Southern flounder (Paralichthys lethostigma) is a popular commercial and recreational species along the southeast Atlantic coast and Gulf of Mexico, USA. Recent studies have provided genetic and otolith morphology evidence that the Gulf of Mexico and Atlantic Ocean stocks differ. Using age and growth data from four states (Texas, Alabama, South Carolina, and North Carolina) we expanded upon the traditional von Bertalanffy model in order to compare growth rates of putative geographic stocks of southern flounder. We improved the model fitting process by adding a hierarchical Bayesian framework to allow each parameter to vary spatially or temporally as a random effect, as well as log transforming the three model parameters (L∞, K, andt0). Multiple comparisons of parameters showed that growth rates varied (even within states) for females, but less for males. Growth rates were also consistent through time, when long-term data were available. Since within-basin populations are thought to be genetically well-mixed, our results suggest that consistent small-scale environmental conditions (i.e., within estuaries) likely drive growth rates and should be considered when developing broader scale management plans.

  19. Temporal and spatial variability of ammonia in urban and agricultural regions of northern Colorado, United States

    Science.gov (United States)

    Li, Yi; Thompson, Tammy M.; Van Damme, Martin; Chen, Xi; Benedict, Katherine B.; Shao, Yixing; Day, Derek; Boris, Alexandra; Sullivan, Amy P.; Ham, Jay; Whitburn, Simon; Clarisse, Lieven; Coheur, Pierre-François; Collett, Jeffrey L., Jr.

    2017-05-01

    Concentrated agricultural activities and animal feeding operations in the northeastern plains of Colorado represent an important source of atmospheric ammonia (NH3). The NH3 from these sources contributes to regional fine particle formation and to nitrogen deposition to sensitive ecosystems in Rocky Mountain National Park (RMNP), located ˜ 80 km to the west. In order to better understand temporal and spatial differences in NH3 concentrations in this source region, weekly concentrations of NH3 were measured at 14 locations during the summers of 2010 to 2015 using Radiello passive NH3 samplers. Weekly (biweekly in 2015) average NH3 concentrations ranged from 2.66 to 42.7 µg m-3, with the highest concentrations near large concentrated animal feeding operations (CAFOs). The annual summertime mean NH3 concentrations were stable in this region from 2010 to 2015, providing a baseline against which concentration changes associated with future changes in regional NH3 emissions can be assessed. Vertical profiles of NH3 were also measured on the 300 m Boulder Atmospheric Observatory (BAO) tower throughout 2012. The highest NH3 concentration along the vertical profile was always observed at the 10 m height (annual average concentration of 4.63 µg m-3), decreasing toward the surface (4.35 µg m-3) and toward higher altitudes (1.93 µg m-3). The NH3 spatial distributions measured using the passive samplers are compared with NH3 columns retrieved by the Infrared Atmospheric Sounding Interferometer (IASI) satellite and concentrations simulated by the Comprehensive Air Quality Model with Extensions (CAMx). The satellite comparison adds to a growing body of evidence that IASI column retrievals of NH3 provide very useful insight into regional variability in atmospheric NH3, in this case even in a region with strong local sources and sharp spatial gradients. The CAMx comparison indicates that the model does a reasonable job simulating NH3 concentrations near sources but tends to

  20. Characterizing spatial variability of air pollution from vehicle traffic around the Houston Ship Channel area

    Science.gov (United States)

    Zhang, Xueying; Craft, Elena; Zhang, Kai

    2017-07-01

    Mobile emissions are a major source of urban air pollution and have been associated with a variety of adverse health outcomes. The Houston Ship Channel area is the home of a large number of diesel-powered vehicles emitting fine particulate matter (PM2.5; ≤2.5 μm in aerodynamic diameter) and nitrogen oxides (NOx). However, the spatial variability of traffic-related air pollutants in the Houston Ship Channel area has rarely been investigated. The objective of this study is to characterize spatial variability of PM2.5 and NOx concentrations attributable to on-road traffic in the Houston Ship Channel area in the year of 2011. We extracted the road network from the Texas Department of Transportation Road Inventory, and calculated emission rates using the Motor Vehicle Emission Simulator version 2014a (MOVES2014a). These parameters and preprocessed meteorological parameters were entered into a Research LINE-source Dispersion Model (RLINE) to conduct a simulation. Receptors were placed at 50 m resolution within 300 m to major roads and at 150 m resolution in the rest of the area. Our findings include that traffic-related PM2.5 were mainly emitted from trucks, while traffic-related NOx were emitted from both trucks and cars. The traffic contributed 0.90 μg/m3 PM2.5 and 29.23 μg/m3 NOx to the annual average mass concentrations of on-road air pollution, and the concentrations of the two pollutants decreased by nearly 40% within 500 m distance to major roads. The pollution level of traffic-related PM2.5 and NOx was higher in winter than those in the other three seasons. The Houston Ship Channel has earlier morning peak hours and relative late afternoon hours, which indicates the influence of goods movement from port activity. The varied near-road gradients illustrate that proximities to major roads are not an accurate surrogate of traffic-related air pollution.

  1. Understanding spatial variability in extreme estuarine water levels to inform better coastal management practise.

    Science.gov (United States)

    Lyddon, Charlotte; Plater, Andy, ,, Prof.; Brown, Jenny, ,, Dr.; Leonardi, Nicoletta, ,, Dr.

    2017-04-01

    Coastal zones worldwide are subject to short term, local variations in sea-level, particularly communities and industries developed on estuaries. Astronomical high tides, meteorological storm surges and increased river flow present a combined flood hazard. This can elevate water level at the coast above predicted levels, generating extreme water levels. These contributions can also interact to alter the phase and amplitude of tides and surges, and thus cause significant mismatches between the predicted and observed water level. The combined effect of tide, surge, river flow and their interactions are the key to understanding and assessing flood risk in estuarine environments for design purposes. Delft3D-FLOW, a hydrodynamic model which solves the unsteady shallow-water equation, is used to access spatial variability in extreme water levels for a range of historical events of different severity within the Severn Estuary, southwest England. Long-term tide gauge records from Ilfracombe and Mumbles and river level data from Sandhurst are analysed to generate a series of extreme water level events, representing the 90th, 95th and 99th percentile conditions, to force the model boundaries. To separate out the time-varying contributions of tidal, fluvial, meteorological processes and their interactions the model is run with different physical forcing. A low pass filter is applied to "de-tide" the residual water elevation, to separate out the time-varying meteorological residual and the tide-surge interactions within the surge. The filtered surge is recombined with the predicted tide so the peak occurs at different times relative to high water. The resulting time series are used to force the model boundary to identify how the interactive processes influence the timing of extreme water level across the estuarine domain. This methodology is first validated using the most extreme event on record to ensure that modelled extreme water levels can be predicted with confidence

  2. The Role of Auxiliary Variables in Deterministic and Deterministic-Stochastic Spatial Models of Air Temperature in Poland

    Science.gov (United States)

    Szymanowski, Mariusz; Kryza, Maciej

    2017-02-01

    Our study examines the role of auxiliary variables in the process of spatial modelling and mapping of climatological elements, with air temperature in Poland used as an example. The multivariable algorithms are the most frequently applied for spatialization of air temperature, and their results in many studies are proved to be better in comparison to those obtained by various one-dimensional techniques. In most of the previous studies, two main strategies were used to perform multidimensional spatial interpolation of air temperature. First, it was accepted that all variables significantly correlated with air temperature should be incorporated into the model. Second, it was assumed that the more spatial variation of air temperature was deterministically explained, the better was the quality of spatial interpolation. The main goal of the paper was to examine both above-mentioned assumptions. The analysis was performed using data from 250 meteorological stations and for 69 air temperature cases aggregated on different levels: from daily means to 10-year annual mean. Two cases were considered for detailed analysis. The set of potential auxiliary variables covered 11 environmental predictors of air temperature. Another purpose of the study was to compare the results of interpolation given by various multivariable methods using the same set of explanatory variables. Two regression models: multiple linear (MLR) and geographically weighted (GWR) method, as well as their extensions to the regression-kriging form, MLRK and GWRK, respectively, were examined. Stepwise regression was used to select variables for the individual models and the cross-validation method was used to validate the results with a special attention paid to statistically significant improvement of the model using the mean absolute error (MAE) criterion. The main results of this study led to rejection of both assumptions considered. Usually, including more than two or three of the most significantly

  3. Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways.

    Science.gov (United States)

    Burgess, Stephen; Daniel, Rhian M; Butterworth, Adam S; Thompson, Simon G

    2015-04-01

    Mendelian randomization uses genetic variants, assumed to be instrumental variables for a particular exposure, to estimate the causal effect of that exposure on an outcome. If the instrumental variable criteria are satisfied, the resulting estimator is consistent even in the presence of unmeasured confounding and reverse causation. We extend the Mendelian randomization paradigm to investigate more complex networks of relationships between variables, in particular where some of the effect of an exposure on the outcome may operate through an intermediate variable (a mediator). If instrumental variables for the exposure and mediator are available, direct and indirect effects of the exposure on the outcome can be estimated, for example using either a regression-based method or structural equation models. The direction of effect between the exposure and a possible mediator can also be assessed. Methods are illustrated in an applied example considering causal relationships between body mass index, C-reactive protein and uric acid. These estimators are consistent in the presence of unmeasured confounding if, in addition to the instrumental variable assumptions, the effects of both the exposure on the mediator and the mediator on the outcome are homogeneous across individuals and linear without interactions. Nevertheless, a simulation study demonstrates that even considerable heterogeneity in these effects does not lead to bias in the estimates. These methods can be used to estimate direct and indirect causal effects in a mediation setting, and have potential for the investigation of more complex networks between multiple interrelated exposures and disease outcomes. © The Author 2014. Published by Oxford University Press on behalf of the International Epidemiological Association.

  4. Small-scale spatial variability of soil microbial community composition and functional diversity in a mixed forest

    Science.gov (United States)

    Wang, Qiufeng; Tian, Jing; Yu, Guirui

    2014-05-01

    Patterns in the spatial distribution of organisms provide important information about mechanisms that regulate the diversity and complexity of soil ecosystems. Therefore, information on spatial distribution of microbial community composition and functional diversity is urgently necessary. The spatial variability on a 26×36 m plot and vertical distribution (0-10 cm and 10-20 cm) of soil microbial community composition and functional diversity were studied in a natural broad-leaved Korean pine (Pinus koraiensis) mixed forest soil in Changbai Mountain. The phospholipid fatty acid (PLFA) pattern was used to characterize the soil microbial community composition and was compared with the community substrate utilization pattern using Biolog. Bacterial biomass dominated and showed higher variability than fungal biomass at all scales examined. The microbial biomass decreased with soil depths increased and showed less variability in lower 10-20 cm soil layer. The Shannon-Weaver index value for microbial functional diversity showed higher variability in upper 0-10 cm than lower 10-20 cm soil layer. Carbohydrates, carboxylic acids, polymers and amino acids are the main carbon sources possessing higher utilization efficiency or utilization intensity. At the same time, the four carbon source types contributed to the differentiation of soil microbial communities. This study suggests the higher diversity and complexity for this mix forest ecosystem. To determine the driving factors that affect this spatial variability of microorganism is the next step for our study.

  5. Spatial and historic variability of benthic nitrogen cycling in an anthropogenically impacted estuary

    Directory of Open Access Journals (Sweden)

    Sarah Quinn Foster

    2014-11-01

    Full Text Available Human activities have dramatically altered reactive nitrogen (N availability in coastal ecosystems globally. Here we used a gradient of N loading found in a shallow temperate estuary (Waquoit Bay, Massachusetts, USA to examine how key biogeochemical processes respond to environmental change over time. Using a space-for-time substitution we measured sediment oxygen uptake, dissolved inorganic nitrogen, and di-nitrogen (N2 gas fluxes from sediments collected at four stations. For two stations we compared measurements to those made at the same locations 20 years ago. Spatial variability was not directly correlated to N loading, however the results indicate significant changes in crucial ecosystem processes over time. Sediment oxygen uptake was only 46% of the historic rate and ammonium flux only 34%. The current rate of net denitrification (36 μmol N2-N m-2 h-1 was also lower than the mean historic rate (181 μmol N2-N m-2 h-1. Additionally, at one of the stations we measured a negative average N2 flux rate, indicating that the sediments may be a net source of reactive N. These changes in benthic flux rates are concurrent with a 39% decline in net ecosystem productivity determined from long-term dissolved oxygen data. Although we cannot rule out year-to-year variability we propose that the differences measured between current and historic rates may be explained in part by concurrent changes found in water temperature, precipitation, and freshwater discharge. These regional forcings have the potential to impact N inputs to the estuary, primary producer biomass, and benthic fluxes by altering the supply of organic matter to the sediments. This work highlights the dynamic nature of biogeochemical cycling in coastal ecosystems and underscores the need to better understand long-term changes.

  6. Parallelization of a spatial random field characterization process using the Method of Anchored Distributions and the HTCondor high throughput computing system

    Science.gov (United States)

    Osorio-Murillo, C. A.; Over, M. W.; Frystacky, H.; Ames, D. P.; Rubin, Y.

    2013-12-01

    A new software application called MAD# has been coupled with the HTCondor high throughput computing system to aid scientists and educators with the characterization of spatial random fields and enable understanding the spatial distribution of parameters used in hydrogeologic and related modeling. MAD# is an open source desktop software application used to characterize spatial random fields using direct and indirect information through Bayesian inverse modeling technique called the Method of Anchored Distributions (MAD). MAD relates indirect information with a target spatial random field via a forward simulation model. MAD# executes inverse process running the forward model multiple times to transfer information from indirect information to the target variable. MAD# uses two parallelization profiles according to computational resources available: one computer with multiple cores and multiple computers - multiple cores through HTCondor. HTCondor is a system that manages a cluster of desktop computers for submits serial or parallel jobs using scheduling policies, resources monitoring, job queuing mechanism. This poster will show how MAD# reduces the time execution of the characterization of random fields using these two parallel approaches in different case studies. A test of the approach was conducted using 1D problem with 400 cells to characterize saturated conductivity, residual water content, and shape parameters of the Mualem-van Genuchten model in four materials via the HYDRUS model. The number of simulations evaluated in the inversion was 10 million. Using the one computer approach (eight cores) were evaluated 100,000 simulations in 12 hours (10 million - 1200 hours approximately). In the evaluation on HTCondor, 32 desktop computers (132 cores) were used, with a processing time of 60 hours non-continuous in five days. HTCondor reduced the processing time for uncertainty characterization by a factor of 20 (1200 hours reduced to 60 hours.)

  7. Spatial variability of soil magnetic susceptibility in an agricultural field located in Eastern Ukraine

    Science.gov (United States)

    Menshov, Oleksandr; Pereira, Paulo; Kruglov, Oleksandr

    2015-04-01

    Magnetic susceptibility (MS) have been used to characterize soil properties. It gives an indirect information about heavy metals content and degree of human impacts on soil contamination derived from atmospheric pollution (Girault et al., 2011). This method is inexpensive in relation to chemical analysis and very useful to track soil pollution, since several toxic components deposited on soil surface are rich in particulates produced by oxidation processes (Boyko et al., 2004; Morton-Bernea et al., 2009). Thus, identify the spatial distribution of MS is of major importance, since can give an indirect information of high metals content (Dankoub et al., 2012). This allows also to distinguish the pedogenic and technogenic origin magnetic signal. For example Ukraine chernozems contain fine-grained oxidized magnetite and maghemite of pedogenic origin formed by weathering of the parent material (Jeleńska et al., 2004). However, to a correct understanding of variables distribution, the identification of the most accurate interpolation method is fundamental for a better interpretation of map information (Pereira et al., 2013). The objective of this work is to study the spatial variability of soil MS in an agricultural fields located in the Tcherkascy Tishki area (50.11°N, 36.43 °E, 162 m a.s.l), Ukraine. Soil MS was measured in 77 sampling points in a north facing slope. To estimate the best interpolation method, several interpolation methods were tested, as inverse distance to a weight (IDW) with the power of 1,2,3,4 and 5, Local Polynomial (LP) with the power of 1 and 2, Global Polynomial (GP), radial basis functions - spline with tension (SPT), completely regularized spline (CRS), multiquatratic (MTQ), inverse multiquatratic (IMTQ), and thin plate spline (TPS) - and some geostatistical methods as, ordinary kriging (OK), Simple Kriging (SK) and Universal Kriging (UK), used in previous works (Pereira et al., 2014). On average, the soil MS of the studied plot had 686

  8. Small-scale spatial variability of atrazine and dinoseb adsorption parameters in an alluvial soil.

    Science.gov (United States)

    Mermoud, A; Martins, J M F; Zhang, D; Favre, A C

    2008-01-01

    Soil sorption processes largely control the environmental fate of herbicides. Therefore, accuracy of sorption parameters is crucial for accurate prediction of herbicide mobility in agricultural soils. A combined experimental and statistical study was performed to investigate the small-scale spatial variability of sorption parameters for atrazine and dinoseb in soils and to establish the number of samples needed to provide a value of the distribution coefficient (K(d)) next to the mean, with a given precision. The study explored sorption properties of the two herbicides in subsurface samples collected from four pits distributed along a transect of an alluvial soil; two to four samples were taken at about 30 cm apart at each sampling location. When considering all the data, the distribution coefficients were found to be normally and log-normally distributed for atrazine and dinoseb, respectively; the CVs were relatively high (close to 50% for dinoseb and 40% for atrazine). When analyzed horizon by horizon, the data revealed distribution coefficients normally distributed for both herbicides, whatever the soil layer, with lower CVs. The K(d) values were shown to vary considerably between samples collected at very short distance (a few centimeters), suggesting that taking a single soil sample to determine sorption properties through batch experiments can lead to highly unrepresentative results and to poor sorption/mobility predictions.

  9. A bayesian integrative model for genetical genomics with spatially informed variable selection.

    Science.gov (United States)

    Cassese, Alberto; Guindani, Michele; Vannucci, Marina

    2014-01-01

    We consider a Bayesian hierarchical model for the integration of gene expression levels with comparative genomic hybridization (CGH) array measurements collected on the same subjects. The approach defines a measurement error model that relates the gene expression levels to latent copy number states. In turn, the latent states are related to the observed surrogate CGH measurements via a hidden Markov model. The model further incorporates variable selection with a spatial prior based on a probit link that exploits dependencies across adjacent DNA segments. Posterior inference is carried out via Markov chain Monte Carlo stochastic search techniques. We study the performance of the model in simulations and show better results than those achieved with recently proposed alternative priors. We also show an application to data from a genomic study on lung squamous cell carcinoma, where we identify potential candidates of associations between copy number variants and the transcriptional activity of target genes. Gene ontology (GO) analyses of our findings reveal enrichments in genes that code for proteins involved in cancer. Our model also identifies a number of potential candidate biomarkers for further experimental validation.

  10. Spatial and Seasonal Variability of Temperature in CO2 Emission from Mars' Mesosphere

    Science.gov (United States)

    Livengood, Timothy A.; Kostiuk, Theodor; Hewagama, Tilak; Kolasinski, John R.; Henning, Wade; Fast, Kelly Elizabeth; Sonnabend, Guido; Sornig, Manuela

    2017-10-01

    We have observed non-local thermodynamic equilibrium (non-LTE) emission of carbon dioxide that probes Mars’ mesosphere in 2001, 2003, 2007, 2012, 2014, and 2016. These measurements were conducted at 10.6 μm wavelength using the Goddard Space Flight Center Heterodyne Instrument for Planetary Winds and Composition (HIPWAC) from the NASA Infrared Telescope Facility (IRTF) at resolving power (1-33)×106. The Maxwellian broadening of the emission line can be measured at this resolution, providing a direct determination of temperature in the mesosphere. The nonLTE line appears as a narrow emission core within a broad absorption formed by tropospheric CO2, which provides temperature information reaching down to the martian surface, while the mesospheric line probes temperature at about 60-80 km altitude. We will report on the spatial distribution of temperature and emission line strength with local solar time on Mars, with latitude, as well as long-term variability including seasonal effects that modify the overall thermal structure of the atmosphere. These remote measurements complement results from orbital spacecraft through access to a broad range of local solar time on each occasion.This work has been supported by the NASA Planetary Astronomy and Solar Systems Observations Programs

  11. Evolution of learning strategies in temporally and spatially variable environments: A review of theory

    Science.gov (United States)

    Aoki, Kenichi; Feldman, Marcus W.

    2013-01-01

    The theoretical literature from 1985 to the present on the evolution of learning strategies in variable environments is reviewed, with the focus on deterministic dynamical models that are amenable to local stability analysis, and on deterministic models yielding evolutionarily stable strategies. Individual learning, unbiased and biased social learning, mixed learning, and learning schedules are considered. A rapidly changing environment or frequent migration in a spatially heterogeneous environment favors individual learning over unbiased social learning. However, results are not so straightforward in the context of learning schedules or when biases in social learning are introduced. The three major methods of modeling temporal environmental change – coevolutionary, two-timescale, and information decay – are compared and shown to sometimes yield contradictory results. The so-called Rogers’ paradox is inherent in the two-timescale method as originally applied to the evolution of pure strategies, but is often eliminated when the other methods are used. Moreover, Rogers’ paradox is not observed for the mixed learning strategies and learning schedules that we review. We believe that further theoretical work is necessary on learning schedules and biased social learning, based on models that are logically consistent and empirically pertinent. PMID:24211681

  12. The implications of spatially variable pre-emergence herbicide efficacy for weed management.

    Science.gov (United States)

    Metcalfe, Helen; Milne, Alice E; Hull, Richard; Murdoch, Alistair J; Storkey, Jonathan

    2017-11-02

    The efficacy of pre-emergence herbicides within fields is spatially variable as a consequence of soil heterogeneity. We quantified the effect of soil organic matter on the efficacy of two pre-emergence herbicides, flufenacet and pendimethalin, against Alopecurus myosuroides and investigated the implications of variation in organic matter for weed management using a crop-weed competition model. Soil organic matter played a critical role in determining the level of control achieved. The high organic matter soil had more surviving weeds with higher biomass than the low organic matter soil. In the absence of competition, surviving plants recovered to produce the same amount of seed as if no herbicide had been applied. The competition model predicted that weeds surviving pre-emergence herbicides could compensate for sublethal effects even when competing with the crop. The ED50 (median effective dose) was higher for weed seed production than seedling mortality or biomass. This difference was greatest on high organic matter soil. These results show that the application rate of herbicides should be adjusted to account for within-field variation in soil organic matter. The results from the modelling emphasised the importance of crop competition in limiting the capacity of weeds surviving pre-emergence herbicides to compensate and replenish the seedbank. © 2017 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. © 2017 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

  13. Entropy Theory of Polymer Glass-Formation in Variable Spatial Dimension

    Science.gov (United States)

    Xu, Wen-Sheng; Douglas, Jack; Freed, Karl

    The importance of packing frustration is broadly appreciated to be an important aspect of glass-formation. Recently, great interest has focused on using spatial dimensionality () as a theoretical tool for exploring this and other aspects of glass-forming liquids. We explore glass-formation in variable based on the generalized entropy theory, a synthesis of the Adam-Gibbs model with direct computation of the configurational entropy of polymer fluids using an established analytical statistical thermodynamic model. We find that structural relaxation in the fluid state asymptotically becomes Arrhenius in the limit and that the fluid transforms upon sufficient cooling above a critical dimension near into a dense amorphous state with a finite positive residual configurational entropy. The GET also predicts the variation with of measures of fragility and of the characteristic temperatures of glass-formation demarking the onset , middle , and end , of the broad glass transition. Direct computations of the isothermal compressibility and thermal expansion coefficient, which are physical measures of packing frustration, demonstrate that these fluid properties strongly correlate with the fragility of glass-formation. Back to three dimensions, we deduce apparently universal relationships between , a measure of the breadth of the glass-formation and both the isothermal compressibility and thermal expansion coefficient of polymer melts at .

  14. Spatial variability and landscape controls of near-surface permafrost within the Alaskan Yukon River Basin

    Science.gov (United States)

    Pastick, Neal J.; Jorgenson, M. Torre; Wylie, Bruce K.; Rose, Joshua R.; Rigge, Matthew; Walvoord, Michelle Ann

    2014-01-01

    The distribution of permafrost is important to understand because of permafrost's influence on high-latitude ecosystem structure and functions. Moreover, near-surface (defined here as within 1 m of the Earth's surface) permafrost is particularly susceptible to a warming climate and is generally poorly mapped at regional scales. Subsequently, our objectives were to (1) develop the first-known binary and probabilistic maps of near-surface permafrost distributions at a 30 m resolution in the Alaskan Yukon River Basin by employing decision tree models, field measurements, and remotely sensed and mapped biophysical data; (2) evaluate the relative contribution of 39 biophysical variables used in the models; and (3) assess the landscape-scale factors controlling spatial variations in permafrost extent. Areas estimated to be present and absent of near-surface permafrost occupy approximately 46% and 45% of the Alaskan Yukon River Basin, respectively; masked areas (e.g., water and developed) account for the remaining 9% of the landscape. Strong predictors of near-surface permafrost include climatic indices, land cover, topography, and Landsat 7 Enhanced Thematic Mapper Plus spectral information. Our quantitative modeling approach enabled us to generate regional near-surface permafrost maps and provide essential information for resource managers and modelers to better understand near-surface permafrost distribution and how it relates to environmental factors and conditions.

  15. Spatial and temporal variability of grass cover in two olive grove catchments on contrasting soil types

    Science.gov (United States)

    Aguilera, Laura; Taguas, Encarnación V.; Gimeno, Enrique; Gómez, José A.

    2013-04-01

    Mediterranean climate conditions -characterized by the concentration of the precipitation in the seasons of autumn and spring, the low temperatures in winter and extremely warm and dry summers- determine that ground cover by adventitious (or cover crop) vegetation shows significant seasonal and annual variability. In addition, its spatial variability associates also, partially, to water availability among the landscape. This is especially relevant in olive orchards, an agricultural system under high erosion risk in the region where the establishment of herbaceous cover has proved to improve soil protection reducing erosion risk, as well as the improvement of soil properties (Gómez et al., 2009). All these benefits are based on small scale studies where full ground cover by the cover crop is relatively easy to obtain. However, few information is available about the actual ground cover achieved at farm scale, although preliminary observations suggests that this might be extremely variable (Gómez and Giráldez, 2009). This study presents the preliminary results evaluating the spatial and temporal evolution of ground cover by adventitious vegetation (the preferred option by farmers to achieve a cover crop) in two commercial olive farms during 2 hydrological years (2011-2012). The study was conducted in two farms located in the province of Cordoba, Southern Spain. Both were olive orchards grown under deficit irrigation systems and present a gauge station where rainfall, runoff and sediment loads have been measured from the year 2005. The soil management in "La Conchuela" farm was based in the use of herbicide in the line of olive trees to keep the bare soil all year round, and the application of selective herbicide in the lane between the olive trees to promote the grown of graminaceae grasses . In addition, the grass is mechanically killed in June. In the another farm, "Arroyo Blanco", the grass spontaneous cover is allowed until mid-spring in which is also

  16. Spatial variability and hotspots of soil N2O fluxes from intensively grazed grassland

    Science.gov (United States)

    Cowan, N. J.; Norman, P.; Famulari, D.; Levy, P. E.; Reay, D. S.; Skiba, U. M.

    2015-03-01

    One hundred N2O flux measurements were made from an area of intensively managed grazed grassland in central Scotland using a high-resolution dynamic chamber method. The field contained a variety of features from which N2O fluxes were measured including a manure heap, patches of decaying grass silage, and areas of increased sheep activity. Individual fluxes varied significantly across the field varying from 2 to 79 000 μg N2O-N m-2 h-1. Soil samples were collected at 55 locations to investigate relationships between soil properties and N2O flux. Fluxes of N2O correlated strongly with soil NO3- concentrations. Distribution of NO3- and the high spatial variability of N2O flux across the field are shown to be linked to the distribution of waste from grazing animals and the resultant reactive nitrogen compounds in the soil which are made available for microbiological processes. Features within the field such as shaded areas and manure heaps contained significantly higher available nitrogen than the rest of the field. Although these features only represented 1.1% of the area of the field, they contributed to over 55% of the total estimated daily N2O flux.

  17. Spatial and temporal variability of suspended-sediment concentrations in a shallow estuarine environment

    Directory of Open Access Journals (Sweden)

    Catherine A. Ruhl

    2004-05-01

    Full Text Available Shallow subembayments respond differently than deep channels to physical forces acting in estuaries. The U.S. Geological Survey measured suspended-sediment concentrations at five locations in Honker Bay, a shallow subembayment of San Francisco Bay, and the adjacent channel to investigate the spatial and temporal differences between deep and shallow estuarine environments. During the first freshwater pulse of the wet season, the channel tended to transport suspended sediments through the system, whereas the shallow area acted as off-channel storage where deposition would likely occur. Following the freshwater pulse, suspended-sediment concentrations were greater in Honker Bay than in the adjacent deep channel, due to the larger supply of erodible sediment on the bed. However, the tidal variability of suspended-sediment concentrations in both Honker Bay and in the adjacent channel was greater after the freshwater pulse than before. During wind events, suspended-sediment concentrations in the channel were not affected; however, wind played a crucial role in the resuspension of sediments in the shallows. Despite wind-wave sediment resuspension in Honker Bay, tidally averaged suspended-sediment flux was controlled by the flood-dominated currents.

  18. Seasonal and spatial variability of surface ozone over China: contributions from background and domestic pollution

    Directory of Open Access Journals (Sweden)

    Y. Wang

    2011-04-01

    Full Text Available Both observations and a 3-D chemical transport model suggest that surface ozone over populated eastern China features a summertime trough and that the month when surface ozone peaks differs by latitude and region. Source-receptor analysis is used to quantify the contributions of background ozone and Chinese anthropogenic emissions on this variability. Annual mean background ozone over China shows a spatial gradient from 55 ppbv in the northwest to 20 ppbv in the southeast, corresponding with changes in topography and ozone lifetime. Pollution background ozone (annual mean of 12.6 ppbv shows a minimum in the summer and maximum in the spring. On the monthly-mean basis, Chinese pollution ozone (CPO has a peak of 20–25 ppbv in June north of the Yangtze River and in October south of it, which explains the peaks of surface ozone in these months. The summertime trough in surface ozone over eastern China can be explained by the decrease of background ozone from spring to summer (by −15 ppbv regionally averaged over eastern China. Tagged simulations suggest that long-range transport of ozone from northern mid-latitude continents (including Europe and North America reaches a minimum in the summer, whereas ozone from Southeast Asia exhibits a maximum in the summer over eastern China. This contrast in seasonality provides clear evidence that the seasonal switch in monsoonal wind patterns plays a significant role in determining the seasonality of background ozone over China.

  19. Spatial and Temporal Variability of Rainfall in the Gandaki River Basin of Nepal Himalaya

    Directory of Open Access Journals (Sweden)

    Jeeban Panthi

    2015-03-01

    Full Text Available Landslides, floods, and droughts are recurring natural disasters in Nepal related to too much or too little water. The summer monsoon contributes more than 80% of annual rainfall, and rainfall spatial and inter-annual variation is very high. The Gandaki River, one of the three major rivers of Nepal and one of the major tributaries of the Ganges River, covers all agro-ecological zones in the central part of Nepal. Time series tests were applied for different agro-ecological zones of the Gandaki River Basin (GRB for rainfall trends of four seasons (pre-monsoon, monsoon, post-monsoon and winter from 1981 to 2012. The non-parametric Mann-Kendall and Sen’s methods were used to determine the trends. Decadal anomalies relative to the long-term average were analyzed using the APHRODITE precipitation product. Trends in number of rainy days and timing of the monsoon were also analyzed. We found that the post-monsoon, pre-monsoon and winter rainfalls are decreasing significantly in most of the zones but monsoon rainfall is increasing throughout the basin. In the hill region, the annual rainfall is increasing but the rainy days do not show any trend. There is a tendency toward later departure of monsoon from Nepal, indicating an increase in its duration. These seasonally and topographically variable trends may have significant impacts for the agriculture and livestock smallholders that form the majority of the population in the GRB.

  20. Evolution of learning strategies in temporally and spatially variable environments: a review of theory.

    Science.gov (United States)

    Aoki, Kenichi; Feldman, Marcus W

    2014-02-01

    The theoretical literature from 1985 to the present on the evolution of learning strategies in variable environments is reviewed, with the focus on deterministic dynamical models that are amenable to local stability analysis, and on deterministic models yielding evolutionarily stable strategies. Individual learning, unbiased and biased social learning, mixed learning, and learning schedules are considered. A rapidly changing environment or frequent migration in a spatially heterogeneous environment favors individual learning over unbiased social learning. However, results are not so straightforward in the context of learning schedules or when biases in social learning are introduced. The three major methods of modeling temporal environmental change--coevolutionary, two-timescale, and information decay--are compared and shown to sometimes yield contradictory results. The so-called Rogers' paradox is inherent in the two-timescale method as originally applied to the evolution of pure strategies, but is often eliminated when the other methods are used. Moreover, Rogers' paradox is not observed for the mixed learning strategies and learning schedules that we review. We believe that further theoretical work is necessary on learning schedules and biased social learning, based on models that are logically consistent and empirically pertinent. Copyright © 2013 Elsevier Inc. All rights reserved.

  1. Spatial and temporal variability of bacterial communities in high alpine water spring sediments.

    Science.gov (United States)

    Esposito, Alfonso; Engel, Michael; Ciccazzo, Sonia; Daprà, Luca; Penna, Daniele; Comiti, Francesco; Zerbe, Stefan; Brusetti, Lorenzo

    2016-05-01

    Water springs are complex, fragile and taxa-rich environments, especially in highly dynamic ecosystems such as glacier forefields experiencing glacier retreat. Bacterial communities are important actors in alpine water body metabolism, and have shown both high seasonal and spatial variations. Seven springs from a high alpine valley (Matsch Valley, South Tyrol, Italy) were examined via a multidisciplinary approach using both hydrochemical and microbiological techniques. Amplified ribosomal intergenic spacer analysis (ARISA) and electric conductivity (EC) measurements, as well as elemental composition and water stable isotopic analyses, were performed. Our target was to elucidate whether and how bacterial community structure is influenced by water chemistry, and to determine the origin and extent of variation in space and time. There existed variations in both space and time for all variables measured. Diversity values more markedly differed at the beginning of summer and then at the end; the extent of variation in space was prevalent over the time scale. Bacterial community structural variation responded to hydrochemical parameter changes; moreover, the stability of the hydrochemical parameters played an important role in shaping distinctive bacterial communities. Copyright © 2016 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

  2. DISCOVERY 2010: Spatial and temporal variability in a dynamic polar ecosystem

    Science.gov (United States)

    Tarling, G. A.; Ward, P.; Atkinson, A.; Collins, M. A.; Murphy, E. J.

    2012-01-01

    DIC deficits, the South Georgia bloom was found to contain the strongest seasonal carbon uptake in the ice-free zone of the Southern Ocean. The surveys also encountered low-production, iron-limited regions, a situation more typical of the wider Southern Ocean. The response of primary and secondary consumers to spatial and temporal heterogeneity in production was complex. Many of the life-cycles of small pelagic organisms showed a close coupling to the seasonal cycle of food availability. For instance, Antarctic krill showed a dependence on early, non-ice-associated blooms to facilitate early reproduction. Strategies to buffer against environmental variability were also examined, such as the prevalence of multiyear life-cycles and variability in energy storage levels. Such traits were seen to influence the way in which Scotia Sea communities were structured, with biomass levels in the larger size classes being higher than in other ocean regions. Seasonal development also altered trophic function, with the trophic level of higher predators increasing through the course of the year as additional predator-prey interactions emerged in the lower trophic levels. Finally, our studies re-emphasised the role that the simple phytoplankton-krill-higher predator food chain plays in this Southern Ocean region, particularly south of the SACCF. To the north, alternative food chains, such as those involving copepods, macrozooplankton and mesopelagic fish, were increasingly important. Continued ocean warming in this region is likely to increase the prevalence of such alternative such food chains with Antarctic krill predicted to move southwards.

  3. Persistent Sinai-type diffusion in Gaussian random potentials with decaying spatial correlations

    Science.gov (United States)

    Goychuk, Igor; Kharchenko, Vasyl O.; Metzler, Ralf

    2017-11-01

    Logarithmic or Sinai-type subdiffusion is usually associated with random force disorder and nonstationary potential fluctuations whose root-mean-squared amplitude grows with distance. We show here that extremely persistent, macroscopic logarithmic diffusion also universally emerges at sufficiently low temperatures in stationary Gaussian random potentials with spatially decaying correlations, known to exist in a broad range of physical systems. Combining results from extensive simulations with a scaling approach we elucidate the physical mechanism of this unusual subdiffusion. In particular, we explain why with growing temperature and/or time a first crossover occurs to standard, power-law subdiffusion, with a time-dependent power-law exponent, and then a second crossover occurs to normal diffusion with a disorder-renormalized diffusion coefficient. Interestingly, the initial, nominally ultraslow diffusion turns out to be much faster than the universal de Gennes-Bässler-Zwanzig limit of the renormalized normal diffusion, which realistically cannot be attained at sufficiently low temperatures and/or for strong disorder. The ultraslow diffusion is also shown to be nonergodic and it displays a local bias phenomenon. Our simple scaling theory not only explains our numerical findings but qualitatively also has a predictive character.

  4. Spatial Variability of Ground-Water Recharge Estimates in the Glassboro Area, New Jersey

    Science.gov (United States)

    Nolan, B. T.; Baehr, A. L.

    2001-12-01

    The spatial variability of ground-water recharge estimates in the Glassboro area, NJ, was evaluated using geostatistical methods as a preliminarily assessment of aquifer vulnerability. Recharge was estimated using Darcy's law, based on parameters obtained from pedotransfer functions applied to measured soil texture values. The recharge estimates correspond to sediments overlying the Kirkwood-Cohansey aquifer, which comprises highly permeable unconsolidated sands and gravels. Knowing which areas receive greater recharge would indicate areas of greater vulnerability, depending on overlying land use. Recharge varied from -7.3 to 722 in/yr in the study area and the median was 12.1 in/yr. Experimental variograms of untransformed recharge data were erratic and related kriged maps were dominated by extreme values (250-722 in/yr) in the data set. An indicator transform stabilized the variograms. Indicator kriging (IK) reduced the influence of extreme values in the data set and yielded maps showing the probability of exceeding threshold values of recharge in the study area. The probability of exceeding the median recharge rate of 12.1 in/yr was 0.9 in the southern portion of the study area and might represent an area of focused recharge. As a check of model fit, probabilities predicted with IK were compared with the original recharge estimates and found to be strongly related. IK predictions corresponding to quintiles of recharge were used to estimate cumulative distribution functions (cdfs) for specific locations in the study area. The cdfs indicate the probability of exceeding any recharge rate at a particular location, and are shaped differently depending on location in the study area. The IK technique estimates cdfs with a single sampling realization (i.e., without a mean and variance at a given location). Additional variables were analyzed with regression to add a deterministic aspect to the analysis and to improve predictions. These variables included land slope

  5. Spatial and Temporal Variability of Remotely Sensed Ocean Color Parameters in Coral Reef Regions

    Science.gov (United States)

    Otis, Daniel Brooks

    The variability of water-column absorption due to colored dissolved organic matter (CDOM) and phytoplankton in coral reef regions is the focus of this study. Hydrographic and CDOM absorption measurements made on the Bahamas Banks and in Exuma Sound during the spring of 1999 and 2000 showed that values of salinity and CDOM absorption at 440nm were higher on the banks (37.18 psu, 0.06 m. -1), compared to Exuma Sound (37.04 psu, 0.03 m. -1). Spatial patternsof CDOM absorption in Exuma Sound revealed that plumes of CDOM-rich water flow into Exuma Sound from the surrounding banks. To examine absorption variability in reef regions throughout the world, a thirteen-year time series of satellite-derived estimates of water-column absorption due to CDOM and phytoplankton were created from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) data. Time series data extracted adjacent to coral reef regions showed that variability in absorption depends on oceanographic conditions such as circulation patterns and winds as well as proximity to sources of light-absorbing materials that enter the water column, such as from terrestrial runoff. Waters near reef regions are generally clear, exhibiting a lower "baseline" level of CDOM absorption of approximately 0.01 m. -1 at 443nm. The main differences between regions lie in the periodsduring the year when increased levels of absorption are observed, which can be triggered by inputs of terrestrially-derived material, as in the Great Barrier Reef lagoon, or wind-driven upwelling as in the Andaman Sea and eastern Pacific Ocean near Panama. The lowest CDOM absorption levels found were approximately 0.003 m. -1 at 443nm near the islands of Palau and Yap, which are removed fromsources of colored materials. The highest absorption levels near reefs were associated with wind-driven upwelling during the northeast monsoon on the Andaman coast of Thailand where values of CDOM absorption at 443nm

  6. Fine-scale spatial and interannual cadmium isotope variability in the subarctic northeast Pacific

    Science.gov (United States)

    Janssen, D. J.; Abouchami, W.; Galer, S. J. G.; Cullen, J. T.

    2017-08-01

    We present dissolved cadmium (Cd) concentrations, [Cd], and stable isotope compositions, ε 112 / 110Cd, in high-resolution depth profiles from five stations along the Line P transect in the subarctic northeast Pacific Ocean. In addition to profiles collected in 2012, subsurface isopycnal samples and surface samples were collected in 2013 and 2014 respectively, providing both temporal and spatial coverage. Surface waters are characterized by Cd depletion relative to phosphate (4 3-PO) compared to deepwater 4 -3Cd:PO, and high inferred remineralization ratios in the nutricline (0.45nmolμmol-1) are observed, consistent with Cd enrichment relative to phosphorus (P) in surface-derived biogenic particles. The correlation between Cd and 4 3-PO weakens at depths where oxygen is highly depleted as shown by local minima in dissolved [Cd] and the tracer Cd*. The decoupling, which is driven by a deficit of Cd relative to 4 3-PO, appears consistent with the recent hypothesis of dissolved Cd removal in oxygen-depleted regions by insoluble metal sulfide formation. Dissolved ε 112 / 110Cd indicates a biologically driven fractionation in surface waters with more positive (heavy) values in the upper water column and lower (light) values in deeper waters. The highest ε 112 / 110Cd observed in our sample set (5.19 ± 0.23) is comparable to observations from the Southern Ocean but is significantly lighter than maximum reported surface values from the subtropical North Pacific of ε 112 / 110Cd ≥ 15. A global compilation of low [Cd] surface water shows similar differences in maximum ε 112 / 110Cd. A surface water intercalibration should be prioritized to help determine if these differences at low [Cd] reflect true physical or biological variability or are due to analytical artefacts. Surface samples from the 2012 sampling campaign fit a closed-system Rayleigh fractionation model; however, surface waters sampled in 2014 had much lower [Cd] with relatively constant ε 112 / 110Cd

  7. Delineation of Spatial Variability in the Temperature-Mortality Relationship on Extremely Hot Days in Greater Vancouver, Canada.

    Science.gov (United States)

    Ho, Hung Chak; Knudby, Anders; Walker, Blake Byron; Henderson, Sarah B

    2017-01-01

    Climate change has increased the frequency and intensity of extremely hot weather. The health risks associated with extemely hot weather are not uniform across affected areas owing to variability in heat exposure and social vulnerability, but these differences are challenging to map with precision. We developed a spatially and temporally stratified case-crossover approach for delineation of areas with higher and lower risks of mortality on extremely hot days and applied this approach in greater Vancouver, Canada. Records of all deaths with an extremely hot day as a case day or a control day were extracted from an administrative vital statistics database spanning the years of 1998-2014. Three heat exposure and 11 social vulnerability variables were assigned at the residential location of each decedent. Conditional logistic regression was used to estimate the odds ratio for a 1°C increase in daily mean temperature at a fixed site with an interaction term for decedents living above and below different values of the spatial variables. The heat exposure and social vulnerability variables with the strongest spatially stratified results were the apparent temperature and the labor nonparticipation rate, respectively. Areas at higher risk had values ≥ 34.4°C for the maximum apparent temperature and ≥ 60% of the population neither employed nor looking for work. These variables were combined in a composite index to quantify their interaction and to enhance visualization of high-risk areas. Our methods provide a data-driven framework for spatial delineation of the temperature--mortality relationship by heat exposure and social vulnerability. The results can be used to map and target the most vulnerable areas for public health intervention. Citation: Ho HC, Knudby A, Walker BB, Henderson SB. 2017. Delineation of spatial variability in the temperature-mortality relationship on extremely hot days in greater Vancouver, Canada. Environ Health Perspect 125:66-75;

  8. Spatial variability analysis of within-field winter wheat nitrogen and grain quality using canopy fluorescence sensor measurements

    Science.gov (United States)

    Wheat grain protein content (GPC) is a key component when evaluating wheat nutrition. It is also important to determine wheat GPC before harvest for agricultural and food process enterprises in order to optimize the wheat grading process. Wheat GPC across a field is spatially variable due to the inh...

  9. Identification of biosecurity measures and spatial variables as potential risk factors for Aleutian disease in Danish mink farms

    DEFF Research Database (Denmark)

    Themudo, Goncalo Espregueira Cruz; Houe, Hans; Agger, Jens Frederik Gramstrup

    2012-01-01

    for the infection in this region based on logistic regression of spatial (environmental, neighbourhood) variables and biosecurity measures. Information on potential biosecurity (management) risk factors in the region was obtained from interviews in 342 registered farms in the region using a structured questionnaire...

  10. Spatial variability of soil salinity at different scales in the mangrove rice agro-ecosystem in West Africa.

    NARCIS (Netherlands)

    Sylla, M.; Stein, A.; Breemen, van N.; Fresco, L.O.

    1995-01-01

    Spatial variability of soil salinity in coastal low lands results from a complex interaction of climate, river hydrology, topography and tidal flooding. The aim of this study was to determine the significant effects of these causal factors at different scales in the West African mangrove

  11. Soil salinity and acidity : spatial variabil[it]y and effects on rice production in West Africa's mangrove zone

    NARCIS (Netherlands)

    Sylla, M.

    1994-01-01

    In the mangrove environment of West Africa, high spatial and temporal variability of soil constraints (salinity and acidity) to rice production is a problem for the transfer and adoption of new agronomic techniques, for land use planning, and for soil and water management. Recently, several

  12. Spatial variability of the structure of the lower troposphere over north western Indian Ocean during 1983 summer monsoon

    Digital Repository Service at National Institute of Oceanography (India)

    RameshKumar, M.R.; Sadhuram, Y.; Michael, G.S.; Rao, L.V.G.

    The spatial variability of the structure of the lower troposphere over the north western Indian Ocean during the period 12th July to 2nd September, 1983 has been studied using the upper air data collected during the first scientific cruise of @i...

  13. Estimating Marginal Healthcare Costs Using Genetic Variants as Instrumental Variables: Mendelian Randomization in Economic Evaluation.

    Science.gov (United States)

    Dixon, Padraig; Davey Smith, George; von Hinke, Stephanie; Davies, Neil M; Hollingworth, William

    2016-11-01

    Accurate measurement of the marginal healthcare costs associated with different diseases and health conditions is important, especially for increasingly prevalent conditions such as obesity. However, existing observational study designs cannot identify the causal impact of disease on healthcare costs. This paper explores the possibilities for causal inference offered by Mendelian randomization, a form of instrumental variable analysis that uses genetic variation as a proxy for modifiable risk exposures, to estimate the effect of health conditions on cost. Well-conducted genome-wide association studies provide robust evidence of the associations of genetic variants with health conditions or disease risk factors. The subsequent causal effects of these health conditions on cost can be estimated using genetic variants as instruments for the health conditions. This is because the approximately random allocation of genotypes at conception means that many genetic variants are orthogonal to observable and unobservable confounders. Datasets with linked genotypic and resource use information obtained from electronic medical records or from routinely collected administrative data are now becoming available and will facilitate this form of analysis. We describe some of the methodological issues that arise in this type of analysis, which we illustrate by considering how Mendelian randomization could be used to estimate the causal impact of obesity, a complex trait, on healthcare costs. We describe some of the data sources that could be used for this type of analysis. We conclude by considering the challenges and opportunities offered by Mendelian randomization for economic evaluation.

  14. The BOFS 1990 spring bloom experiment: Temporal evolution and spatial variability of the hydrographic field

    Science.gov (United States)

    Savidge, G.; Turner, D. R.; Burkill, P. H.; Watson, A. J.; Angel, M. V.; Pingree, R. D.; Leach, H.; Richards, K. J.

    The overall background to the U.K. BOFS (Biogeochemical Ocean Flux Study) Project, designed to investigate oceanic carbon flux processes throughout the water column, is briefly described together with the strategy for the 1990 BOFS Spring Bloom Experiment. The Experiment involved two ships and was carried out in the northeast Atlantic between 46-50°N, 14-22°W in the period 18 April - 25 June 1990 with the objective of monitoring and quantifying the major carbon flux changes associated with the succession of the spring bloom. Sampling was carried out over a 7 week period adjacent to a Lagrangian buoy drogued at 30m. The spatial fields of the major variables were characterized from box grid surveys around the position of the marker drogue at the beginning and end of the time series observations with the time series hydrographical changes being related to features observed in the spatial surveys. The hydrographical and core biological observations made in the Experiment are described and interpreted. The reference drogue was deployed within an anticyclonic eddy in which initially there was little evidence of seasonal thermocline or phytoplankton develooment. The majority of an array of 30m drogues placed around the reference drogue drifted between 75-150km north and east of their origin, probably exiting from the original eddy system after the first 6 days of deployment. The reference drogue moved anticyclonically around the eddy centre for the first 13 days before exiting from the eddy system and becoming entrained in a discontinuity zone located between discrete warmer and cooler water bodies defined between 50-200m. During this latter period, which continued through to the end of the Experiment, the drogue tracked SE overall and alternately grazed the margins of the two water bodies with greater drift speeds being associated with the influence of the cooler water. Phytoplankton development proceeded slowly over the period that the drogue remained in the original

  15. Spatial and Temporal Variability of Rainfall over the South-West Coast of Bangladesh

    Directory of Open Access Journals (Sweden)

    Md. Sarwar Hossain

    2014-04-01

    Full Text Available This study examined the spatial and temporal rainfall variability from the 1940s to 2007 in the south west coastal region of Bangladesh. Time series statistical tests were applied to examine the spatial and temporal trends in three time segments (1948–1970, 1971–1990 and 1991–2007 and four seasons (Pre-monsoon; Monsoon; Post-Monsoon and Winter, during the period 1948–2007. Eight weather stations were divided into two zones: exposed (exposed to sea and interior (distant to sea. Overall, rainfall increased during the period 1948–2007, while the trends intensified during post-1990s. Post-monsoon and winter rainfall was observed to follow significant positive trends at most weather stations during the time period 1948–2007. The rate of change was found in exposed zone and interior zone are +12.51 and +4.86 mm/year, respectively, over post monsoon and +0.9 and +1.86 mm/year, respectively, over winter. These trends intensified both in the exposed zone (+45.81 mm/year and the interior zone (+27.09 mm/year 1990 onwards. Winter rainfall does not exhibit significant change (p > 0.1 over the exterior or interior zone, though individual stations like Jessore, Satkhira and Bhola show significant negative trends after 1990s. Although the trends were observed to weaken in the monsoon and pre-monsoon seasons, they are not significant. Moreover, an 11-year cyclicity was found within these two seasons, whilst no cyclicity was observed in the post-monsoon and winter seasons. Sequential Mann Kendal test reveals that the changes in two zones rainfall trends are started around mid-80s, where step change found only for fours season in Khulna stations and also for winter seasons in all weather stations. These changes may have a detrimental effect on rain-fed agriculture in Bangladesh. The application of palaeo-environmental techniques, threshold determination and rainfall analysis across the whole country could be useful to support adaptation planning of

  16. Spatial variability of NDVI at different seasons in the Community of Madrid (Spain)

    Science.gov (United States)

    Sotoca, Juan J. Martin; Saa-Requejo, Antonio; Borondo, Javier; Tarquis, Ana M.

    2015-04-01

    Agricultural drought quantification is one of the most important tasks in the characterization process of this natural hazard and its implications in crop insurance. Recently, several vegetation indexes based on remote-sensing data (VI) has been applied to quantify it (Dalezios et al, 2012). VIs are obtained combining several frequency bands that represent the relationship between photosynthesis and absorbed/reflected radiation. The most widely used VI is the Normalized Difference Vegetation Index (NDVI). It is based on the principle that healthy vegetation mainly absorbs visible light and reflects the near-infrared frequency band. Drought can be highly localized, and several authors have recognized the critical role of soil moisture and its spatial variability in agricultural losses (Anderson et al., 2011). Therefore, it is important to delimit locations within a homogeneous area that will share main NDVI statistics and in which the same threshold value can be applied to define drought event. In order to do so, we have applied for the first time in this context the method of singularity maps (Cheng and Agterberg, 1996) commonly used in localization of mineral deposits. The NDVI singularity maps calculated in each season through 2011/2012 are showed and discussed (Martín-Sotoca, 2014). References Anderson, M:C:, C. R. Hain, B. Wardlow, J. R. Mecikalski and W. P. Kustas (2011) Evaluation of drought indices based on thermal remote sensing of evapotranspiration over the continental United States. J. Climate, 24, 2025-2044. Dalezios, N.R., A. Blanta, N.V. Spyropoulos and A.M. Tarquis (2012) Risk identification of agricultural drought for sustainable Agroecosystems. Nat. Hazards Earth Syst. Sci., 14, 2435-2448. Cheng, Q. and F.P. Agterberg (1996) Multifractal modeling and spatial statistics. Math. Geol., 28, 1-16. Martín-Sotoca, J.J. (2014) Estructura Espacial de la Sequía en Pastos y sus Aplicaciones en el Seguro Agrario. Master Thesis, UPM (In Spanish

  17. Blind estimation of statistical properties of non-stationary random variables

    Science.gov (United States)

    Mansour, Ali; Mesleh, Raed; Aggoune, el-Hadi M.

    2014-12-01

    To identify or equalize wireless transmission channels, or alternatively to evaluate the performance of many wireless communication algorithms, coefficients or statistical properties of the used transmission channels are often assumed to be known or can be estimated at the receiver end. For most of the proposed algorithms, the knowledge of transmission channel statistical properties is essential to detect signals and retrieve data. To the best of our knowledge, most proposed approaches assume that transmission channels are static and can be modeled by stationary random variables (uniform, Gaussian, exponential, Weilbul, Rayleigh, etc.). In the majority of sensor networks or cellular systems applications, transmitters and/or receivers are in motion. Therefore, the validity of static transmission channels and the underlying assumptions may not be valid. In this case, coefficients and statistical properties change and therefore the stationary model falls short of making an accurate representation. In order to estimate the statistical properties (represented by the high-order statistics and probability density function, PDF) of dynamic channels, we firstly assume that the dynamic channels can be modeled by short-term stationary but long-term non-stationary random variable (RV), i.e., the RVs are stationary within unknown successive periods but they may suddenly change their statistical properties between two successive periods. Therefore, this manuscript proposes an algorithm to detect the transition phases of non-stationary random variables and introduces an indicator based on high-order statistics for non-stationary transmission which can be used to alter channel properties and initiate the estimation process. Additionally, PDF estimators based on kernel functions are also developed. The first part of the manuscript provides a brief introduction for unbiased estimators of the second and fourth-order cumulants. Then, the non-stationary indicators are formulated

  18. Precision Viticulture : is it relevant to manage the vineyard according to the within field spatial variability of the environment ?

    Science.gov (United States)

    Tisseyre, Bruno

    2015-04-01

    For more than 15 years, research projects are conducted in the precision viticulture (PV) area around the world. These research projects have provided new insights into the within-field variability in viticulture. Indeed, access to high spatial resolution data (remote sensing, embedded sensors, etc.) changes the knowledge we have of the fields in viticulture. In particular, the field which was until now considered as a homogeneous management unit, presents actually a high spatial variability in terms of yield, vigour an quality. This knowledge will lead (and is already causing) changes on how to manage the vineyard and the quality of the harvest at the within field scale. From the experimental results obtained in various countries of the world, the goal of the presentation is to provide figures on: - the spatial variability of the main parameters (yield, vigor, quality), and how this variability is organized spatially, - the temporal stability of the observed spatial variability and the potential link with environmental parameters like soil, topography, soil water availability, etc. - information sources available at a high spatial resolution conventionally used in precision agriculture likely to highlight this spatial variability (multi-spectral images, soil electrical conductivity, etc.) and the limitations that these information sources are likely to present in viticulture. Several strategies are currently being developed to take into account the within field variability in viticulture. They are based on the development of specific equipments, sensors, actuators and site specific strategies with the aim of adapting the vineyard operations at the within-field level. These strategies will be presented briefly in two ways : - Site specific operations (fertilization, pruning, thinning, irrigation, etc.) in order to counteract the effects of the environment and to obtain a final product with a controlled and consistent wine quality, - Differential harvesting with the

  19. Modeling the influence of preferential flow on the spatial variability and time-dependence of mineral weathering rates

    Science.gov (United States)

    Pandey, Sachin; Rajaram, Harihar

    2016-12-01

    Inferences of weathering rates from laboratory and field observations suggest significant scale and time-dependence. Preferential flow induced by heterogeneity (manifest as permeability variations or discrete fractures) has been suggested as one potential mechanism causing scale/time-dependence. We present a quantitative evaluation of the influence of preferential flow on weathering rates using reactive transport modeling. Simulations were performed in discrete fracture networks (DFNs) and correlated random permeability fields (CRPFs), and compared to simulations in homogeneous permeability fields. The simulations reveal spatial variability in the weathering rate, multidimensional distribution of reactions zones, and the formation of rough weathering interfaces and corestones due to preferential flow. In the homogeneous fields and CRPFs, the domain-averaged weathering rate is initially constant as long as the weathering front is contained within the domain, reflecting equilibrium-controlled behavior. The behavior in the CRPFs was influenced by macrodispersion, with more spread-out weathering profiles, an earlier departure from the initial constant rate and longer persistence of weathering. DFN simulations exhibited a sustained time-dependence resulting from the formation of diffusion-controlled weathering fronts in matrix blocks, which is consistent with the shrinking core mechanism. A significant decrease in the domain-averaged weathering rate is evident despite high remaining mineral volume fractions, but the decline does not follow a 1/t dependence, characteristic of diffusion, due to network s