Canopies to Continents: What spatial scales are needed to represent landcover distributions in earth system models?

NASA Astrophysics Data System (ADS)

Guenther, A. B.; Duhl, T.

2011-12-01

Increasing computational resources have enabled a steady improvement in the spatial resolution used for earth system models. Land surface models and landcover distributions have kept ahead by providing higher spatial resolution than typically used in these models. Satellite observations have played a major role in providing high resolution landcover distributions over large regions or the entire earth surface but ground observations are needed to calibrate these data and provide accurate inputs for models. As our ability to resolve individual landscape components improves, it is important to consider what scale is sufficient for providing inputs to earth system models. The required spatial scale is dependent on the processes being represented and the scientific questions being addressed. This presentation will describe the development a contiguous U.S. landcover database using high resolution imagery (1 to 1000 meters) and surface observations of species composition and other landcover characteristics. The database includes plant functional types and species composition and is suitable for driving land surface models (CLM and MEGAN) that predict land surface exchange of carbon, water, energy and biogenic reactive gases (e.g., isoprene, sesquiterpenes, and NO). We investigate the sensitivity of model results to landcover distributions with spatial scales ranging over six orders of magnitude (1 meter to 1000000 meters). The implications for predictions of regional climate and air quality will be discussed along with recommendations for regional and global earth system modeling.

A Spatial Allocation Procedure to Downscale Regional Crop Production Estimates from an Integrated Assessment Model

NASA Astrophysics Data System (ADS)

Moulds, S.; Djordjevic, S.; Savic, D.

2017-12-01

The Global Change Assessment Model (GCAM), an integrated assessment model, provides insight into the interactions and feedbacks between physical and human systems. The land system component of GCAM, which simulates land use activities and the production of major crops, produces output at the subregional level which must be spatially downscaled in order to use with gridded impact assessment models. However, existing downscaling routines typically consider cropland as a homogeneous class and do not provide information about land use intensity or specific management practices such as irrigation and multiple cropping. This paper presents a spatial allocation procedure to downscale crop production data from GCAM to a spatial grid, producing a time series of maps which show the spatial distribution of specific crops (e.g. rice, wheat, maize) at four input levels (subsistence, low input rainfed, high input rainfed and high input irrigated). The model algorithm is constrained by available cropland at each time point and therefore implicitly balances extensification and intensification processes in order to meet global food demand. It utilises a stochastic approach such that an increase in production of a particular crop is more likely to occur in grid cells with a high biophysical suitability and neighbourhood influence, while a fall in production will occur more often in cells with lower suitability. User-supplied rules define the order in which specific crops are downscaled as well as allowable transitions. A regional case study demonstrates the ability of the model to reproduce historical trends in India by comparing the model output with district-level agricultural inventory data. Lastly, the model is used to predict the spatial distribution of crops globally under various GCAM scenarios.

A Study on the Effects of Spatial Scale on Snow Process in Hyper-Resolution Hydrological Modelling over Mountainous Areas

NASA Astrophysics Data System (ADS)

Garousi Nejad, I.; He, S.; Tang, Q.; Ogden, F. L.; Steinke, R. C.; Frazier, N.; Tarboton, D. G.; Ohara, N.; Lin, H.

2017-12-01

Spatial scale is one of the main considerations in hydrological modeling of snowmelt in mountainous areas. The size of model elements controls the degree to which variability can be explicitly represented versus what needs to be parameterized using effective properties such as averages or other subgrid variability parameterizations that may degrade the quality of model simulations. For snowmelt modeling terrain parameters such as slope, aspect, vegetation and elevation play an important role in the timing and quantity of snowmelt that serves as an input to hydrologic runoff generation processes. In general, higher resolution enhances the accuracy of the simulation since fine meshes represent and preserve the spatial variability of atmospheric and surface characteristics better than coarse resolution. However, this increases computational cost and there may be a scale beyond which the model response does not improve due to diminishing sensitivity to variability and irreducible uncertainty associated with the spatial interpolation of inputs. This paper examines the influence of spatial resolution on the snowmelt process using simulations of and data from the Animas River watershed, an alpine mountainous area in Colorado, USA, using an unstructured distributed physically based hydrological model developed for a parallel computing environment, ADHydro. Five spatial resolutions (30 m, 100 m, 250 m, 500 m, and 1 km) were used to investigate the variations in hydrologic response. This study demonstrated the importance of choosing the appropriate spatial scale in the implementation of ADHydro to obtain a balance between representing spatial variability and the computational cost. According to the results, variation in the input variables and parameters due to using different spatial resolution resulted in changes in the obtained hydrological variables, especially snowmelt, both at the basin-scale and distributed across the model mesh.

SPATIAL FOREST SOIL PROPERTIES FOR ECOLOGICAL MODELING IN THE WESTERN OREGON CASCADES

EPA Science Inventory

The ultimate objective of this work is to provide a spatially distributed database of soil properties to serve as inputs to model ecological processes in western forests at the landscape scale. The Central Western Oregon Cascades are rich in biodiversity and they are a fascinati...

Response of a shell structure subject to distributed harmonic excitation

NASA Astrophysics Data System (ADS)

Cao, Rui; Bolton, J. Stuart

2016-09-01

Previously, a coupled, two-dimensional structural-acoustic ring model was constructed to simulate the dynamic and acoustical behavior of pneumatic tires. Analytical forced solutions were obtained and were experimentally verified through laser velocimeter measurement made using automobile tires. However, the two-dimensional ring model is incapable of representing higher order, in-plane modal motion in either the circumferential or axial directions. Therefore, in this paper, a three-dimensional pressurized circular shell model is proposed to study the in-plane shearing motion and the effect of different forcing conditions. Closed form analytical solutions were obtained for both free and forced vibrations of the shell under simply supported boundary conditions. Dispersion relations were calculated and different wave types were identified by their different speeds. Shell surface mobility results under various input distributions were also studied and compared. Spatial Fourier series decompositions were also performed on the spatial mobility results to give the forced dispersion relations, which illustrate clearly the influence of input force spatial distribution. Such a model has practical application in identifying the sources of noise and vibration problems in automotive tires.

Development of a distributed air pollutant dry deposition modeling framework

Treesearch

Satoshi Hirabayashi; Charles N. Kroll; David J. Nowak

2012-01-01

A distributed air pollutant dry deposition modeling systemwas developed with a geographic information system (GIS) to enhance the functionality of i-Tree Eco (i-Tree, 2011). With the developed system, temperature, leaf area index (LAI) and air pollutant concentration in a spatially distributed form can be estimated, and based on these and other input variables, dry...

Modelling the spatial distribution of ammonia emissions in the UK.

PubMed

Hellsten, S; Dragosits, U; Place, C J; Vieno, M; Dore, A J; Misselbrook, T H; Tang, Y S; Sutton, M A

2008-08-01

Ammonia emissions (NH3) are characterised by a high spatial variability at a local scale. When modelling the spatial distribution of NH3 emissions, it is important to provide robust emission estimates, since the model output is used to assess potential environmental impacts, e.g. exceedance of critical loads. The aim of this study was to provide a new, updated spatial NH3 emission inventory for the UK for the year 2000, based on an improved modelling approach and the use of updated input datasets. The AENEID model distributes NH3 emissions from a range of agricultural activities, such as grazing and housing of livestock, storage and spreading of manures, and fertilizer application, at a 1-km grid resolution over the most suitable landcover types. The results of the emission calculation for the year 2000 are analysed and the methodology is compared with a previous spatial emission inventory for 1996.

A priori discretization quality metrics for distributed hydrologic modeling applications

NASA Astrophysics Data System (ADS)

Liu, Hongli; Tolson, Bryan; Craig, James; Shafii, Mahyar; Basu, Nandita

2016-04-01

In distributed hydrologic modelling, a watershed is treated as a set of small homogeneous units that address the spatial heterogeneity of the watershed being simulated. The ability of models to reproduce observed spatial patterns firstly depends on the spatial discretization, which is the process of defining homogeneous units in the form of grid cells, subwatersheds, or hydrologic response units etc. It is common for hydrologic modelling studies to simply adopt a nominal or default discretization strategy without formally assessing alternative discretization levels. This approach lacks formal justifications and is thus problematic. More formalized discretization strategies are either a priori or a posteriori with respect to building and running a hydrologic simulation model. A posteriori approaches tend to be ad-hoc and compare model calibration and/or validation performance under various watershed discretizations. The construction and calibration of multiple versions of a distributed model can become a seriously limiting computational burden. Current a priori approaches are more formalized and compare overall heterogeneity statistics of dominant variables between candidate discretization schemes and input data or reference zones. While a priori approaches are efficient and do not require running a hydrologic model, they do not fully investigate the internal spatial pattern changes of variables of interest. Furthermore, the existing a priori approaches focus on landscape and soil data and do not assess impacts of discretization on stream channel definition even though its significance has been noted by numerous studies. The primary goals of this study are to (1) introduce new a priori discretization quality metrics considering the spatial pattern changes of model input data; (2) introduce a two-step discretization decision-making approach to compress extreme errors and meet user-specified discretization expectations through non-uniform discretization threshold modification. The metrics for the first time provides quantification of the routing relevant information loss due to discretization according to the relationship between in-channel routing length and flow velocity. Moreover, it identifies and counts the spatial pattern changes of dominant hydrological variables by overlaying candidate discretization schemes upon input data and accumulating variable changes in area-weighted way. The metrics are straightforward and applicable to any semi-distributed or fully distributed hydrological model with grid scales are greater than input data resolutions. The discretization metrics and decision-making approach are applied to the Grand River watershed located in southwestern Ontario, Canada where discretization decisions are required for a semi-distributed modelling application. Results show that discretization induced information loss monotonically increases as discretization gets rougher. With regards to routing information loss in subbasin discretization, multiple interesting points rather than just the watershed outlet should be considered. Moreover, subbasin and HRU discretization decisions should not be considered independently since subbasin input significantly influences the complexity of HRU discretization result. Finally, results show that the common and convenient approach of making uniform discretization decisions across the watershed domain performs worse compared to a metric informed non-uniform discretization approach as the later since is able to conserve more watershed heterogeneity under the same model complexity (number of computational units).

Spatial interpolation of hourly precipitation and dew point temperature for the identification of precipitation phase and hydrologic response in a mountainous catchment

NASA Astrophysics Data System (ADS)

Garen, D. C.; Kahl, A.; Marks, D. G.; Winstral, A. H.

2012-12-01

In mountainous catchments, it is well known that meteorological inputs, such as precipitation, air temperature, humidity, etc. vary greatly with elevation, spatial location, and time. Understanding and monitoring catchment inputs is necessary in characterizing and predicting hydrologic response to these inputs. This is true all of the time, but it is the most dramatically critical during large storms, when the input to the stream system due to rain and snowmelt creates the potential for flooding. Besides such crisis events, however, proper estimation of catchment inputs and their spatial distribution is also needed in more prosaic but no less important water and related resource management activities. The first objective of this study is to apply a geostatistical spatial interpolation technique (elevationally detrended kriging) to precipitation and dew point temperature on an hourly basis and explore its characteristics, accuracy, and other issues. The second objective is to use these spatial fields to determine precipitation phase (rain or snow) during a large, dynamic winter storm. The catchment studied is the data-rich Reynolds Creek Experimental Watershed near Boise, Idaho. As part of this analysis, precipitation-elevation lapse rates are examined for spatial and temporal consistency. A clear dependence of lapse rate on precipitation amount exists. Certain stations, however, are outliers from these relationships, showing that significant local effects can be present and raising the question of whether such stations should be used for spatial interpolation. Experiments with selecting subsets of stations demonstrate the importance of elevation range and spatial placement on the interpolated fields. Hourly spatial fields of precipitation and dew point temperature are used to distinguish precipitation phase during a large rain-on-snow storm in December 2005. This application demonstrates the feasibility of producing hourly spatial fields and the importance of doing so to support an accurate determination of precipitation phase for assessing catchment hydrologic response to the storm.

Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation

USGS Publications Warehouse

Zajac, Zuzanna; Stith, Bradley M.; Bowling, Andrea C.; Langtimm, Catherine A.; Swain, Eric D.

2015-01-01

Habitat suitability index (HSI) models are commonly used to predict habitat quality and species distributions and are used to develop biological surveys, assess reserve and management priorities, and anticipate possible change under different management or climate change scenarios. Important management decisions may be based on model results, often without a clear understanding of the level of uncertainty associated with model outputs. We present an integrated methodology to assess the propagation of uncertainty from both inputs and structure of the HSI models on model outputs (uncertainty analysis: UA) and relative importance of uncertain model inputs and their interactions on the model output uncertainty (global sensitivity analysis: GSA). We illustrate the GSA/UA framework using simulated hydrology input data from a hydrodynamic model representing sea level changes and HSI models for two species of submerged aquatic vegetation (SAV) in southwest Everglades National Park: Vallisneria americana (tape grass) and Halodule wrightii (shoal grass). We found considerable spatial variation in uncertainty for both species, but distributions of HSI scores still allowed discrimination of sites with good versus poor conditions. Ranking of input parameter sensitivities also varied spatially for both species, with high habitat quality sites showing higher sensitivity to different parameters than low-quality sites. HSI models may be especially useful when species distribution data are unavailable, providing means of exploiting widely available environmental datasets to model past, current, and future habitat conditions. The GSA/UA approach provides a general method for better understanding HSI model dynamics, the spatial and temporal variation in uncertainties, and the parameters that contribute most to model uncertainty. Including an uncertainty and sensitivity analysis in modeling efforts as part of the decision-making framework will result in better-informed, more robust decisions.

Direct statistical modeling and its implications for predictive mapping in mining exploration

NASA Astrophysics Data System (ADS)

Sterligov, Boris; Gumiaux, Charles; Barbanson, Luc; Chen, Yan; Cassard, Daniel; Cherkasov, Sergey; Zolotaya, Ludmila

2010-05-01

Recent advances in geosciences make more and more multidisciplinary data available for mining exploration. This allowed developing methodologies for computing forecast ore maps from the statistical combination of such different input parameters, all based on an inverse problem theory. Numerous statistical methods (e.g. algebraic method, weight of evidence, Siris method, etc) with varying degrees of complexity in their development and implementation, have been proposed and/or adapted for ore geology purposes. In literature, such approaches are often presented through applications on natural examples and the results obtained can present specificities due to local characteristics. Moreover, though crucial for statistical computations, "minimum requirements" needed for input parameters (number of minimum data points, spatial distribution of objects, etc) are often only poorly expressed. From these, problems often arise when one has to choose between one and the other method for her/his specific question. In this study, a direct statistical modeling approach is developed in order to i) evaluate the constraints on the input parameters and ii) test the validity of different existing inversion methods. The approach particularly focused on the analysis of spatial relationships between location of points and various objects (e.g. polygons and /or polylines) which is particularly well adapted to constrain the influence of intrusive bodies - such as a granite - and faults or ductile shear-zones on spatial location of ore deposits (point objects). The method is designed in a way to insure a-dimensionality with respect to scale. In this approach, both spatial distribution and topology of objects (polygons and polylines) can be parametrized by the user (e.g. density of objects, length, surface, orientation, clustering). Then, the distance of points with respect to a given type of objects (polygons or polylines) is given using a probability distribution. The location of points is computed assuming either independency or different grades of dependency between the two probability distributions. The results show that i)polygons surface mean value, polylines length mean value, the number of objects and their clustering are critical and ii) the validity of the different tested inversion methods strongly depends on the relative importance and on the dependency between the parameters used. In addition, this combined approach of direct and inverse modeling offers an opportunity to test the robustness of the inferred distribution point laws with respect to the quality of the input data set.

The role of the staff MFF in distributing NHS funding: taking account of differences in local labour market conditions.

PubMed

Elliott, Robert; Ma, Ada; Sutton, Matt; Skatun, Diane; Rice, Nigel; Morris, Stephen; McConnachie, Alex

2010-05-01

The National Health Service (NHS) in England distributes substantial funds to health-care providers in different geographical areas to pay for the health care required by the populations they serve. The formulae that determine this distribution reflect populations' health needs and local differences in the prices of inputs. Labour is the most important input and area differences in the price of labour are measured by the Staff Market Forces Factor (MFF). This Staff MFF has been the subject of much debate. Though the Staff MFF has operated for almost 30 years this is the first academic paper to evaluate and test the theory and method that underpin the MFF. The theory underpinning the Staff MFF is the General Labour Market method. The analysis reported here reveals empirical support for this theory in the case of nursing staff employed by NHS hospitals, but fails to identify similar support for its application to medical staff. The paper demonstrates the extent of spatial variation in private sector and NHS wages, considers the choice of comparators and spatial geography, incorporates vacancy modelling and illustrates the effect of spatial smoothing.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

Distributed hydrologic models are typically calibrated against streamflow observations at the outlet of the basin. Along with these observations from gauging stations, satellite based estimates offer independent evaluation data such as remotely sensed actual evapotranspiration (aET) and land surface temperature. The primary objective of the study is to compare model calibrations against traditional downstream discharge measurements with calibrations against simulated spatial patterns and combinations of both types of observations. While the discharge based model calibration typically improves the temporal dynamics of the model, it seems to give rise to minimum improvement of the simulated spatial patterns. In contrast, objective functions specifically targeting the spatial pattern performance could potentially increase the spatial model performance. However, most modeling studies, including the model formulations and parameterization, are not designed to actually change the simulated spatial pattern during calibration. This study investigates the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale hydrologic model (mHM). This model is selected as it allows for a change in the spatial distribution of key soil parameters through the optimization of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) values directly as input. In addition the simulated aET can be estimated at a spatial resolution suitable for comparison to the spatial patterns observed with MODIS data. To increase our control on spatial calibration we introduced three additional parameters to the model. These new parameters are part of an empirical equation to the calculate crop coefficient (Kc) from daily LAI maps and used to update potential evapotranspiration (PET) as model inputs. This is done instead of correcting/updating PET with just a uniform (or aspect driven) factor used in the mHM model (version 5.3). We selected the 20 most important parameters out of 53 mHM parameters based on a comprehensive sensitivity analysis (Cuntz et al., 2015). We calibrated 1km-daily mHM for the Skjern basin in Denmark using the Shuffled Complex Evolution (SCE) algorithm and inputs at different spatial scales i.e. meteorological data at 10km and morphological data at 250 meters. We used correlation coefficients between observed monthly (summer months only) MODIS data calculated from cloud free days over the calibration period from 2001 to 2008 and simulated aET from mHM over the same period. Similarly other metrics, e.g mapcurves and fraction skill-score, are also included in our objective function to assess the co-location of the grid-cells. The preliminary results show that multi-objective calibration of mHM against observed streamflow and spatial patterns together does not significantly reduce the spatial errors in aET while it improves the streamflow simulations. This is a strong signal for further investigation of the multi parameter regionalization affecting spatial aET patterns and weighting the spatial metrics in the objective function relative to the streamflow metrics.

Methods used to parameterize the spatially-explicit components of a state-and-transition simulation model

USGS Publications Warehouse

Sleeter, Rachel; Acevedo, William; Soulard, Christopher E.; Sleeter, Benjamin M.

2015-01-01

Spatially-explicit state-and-transition simulation models of land use and land cover (LULC) increase our ability to assess regional landscape characteristics and associated carbon dynamics across multiple scenarios. By characterizing appropriate spatial attributes such as forest age and land-use distribution, a state-and-transition model can more effectively simulate the pattern and spread of LULC changes. This manuscript describes the methods and input parameters of the Land Use and Carbon Scenario Simulator (LUCAS), a customized state-and-transition simulation model utilized to assess the relative impacts of LULC on carbon stocks for the conterminous U.S. The methods and input parameters are spatially explicit and describe initial conditions (strata, state classes and forest age), spatial multipliers, and carbon stock density. Initial conditions were derived from harmonization of multi-temporal data characterizing changes in land use as well as land cover. Harmonization combines numerous national-level datasets through a cell-based data fusion process to generate maps of primary LULC categories. Forest age was parameterized using data from the North American Carbon Program and spatially-explicit maps showing the locations of past disturbances (i.e. wildfire and harvest). Spatial multipliers were developed to spatially constrain the location of future LULC transitions. Based on distance-decay theory, maps were generated to guide the placement of changes related to forest harvest, agricultural intensification/extensification, and urbanization. We analyze the spatially-explicit input parameters with a sensitivity analysis, by showing how LUCAS responds to variations in the model input. This manuscript uses Mediterranean California as a regional subset to highlight local to regional aspects of land change, which demonstrates the utility of LUCAS at many scales and applications.

Development of an automated procedure for estimation of the spatial variation of runoff in large river basins

USDA-ARS?s Scientific Manuscript database

The use of distributed parameter models to address water resource management problems has increased in recent years. Calibration is necessary to reduce the uncertainties associated with model input parameters. Manual calibration of a distributed parameter model is a very time consuming effort. There...

THE DISTRIBUTION OF 137CESIUM AND OTHER TRACE CONSTITUENTS IN GREEN BAY, LAKE MICHIGAN

EPA Science Inventory

137Cs, Cadmium, and PCBs were measured in a series of sediment cores collected in Green Bay between 1987 and 1989. Analysis of the spatial distribution of the chemicals can be shown to be dependent on the nature of the input - totally from the atmosphere, totally riverine, and a ...

Spatial and temporal variability of trace element concentrations in an urban subtropical watershed, Honolulu, Hawaii

USGS Publications Warehouse

Heinen, De Carlo E.; Anthony, S.S.

2002-01-01

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. ?? 2002 Elsevier Science Ltd. All rights reserved.

Integrating satellite actual evapotranspiration patterns into distributed model parametrization and evaluation for a mesoscale catchment

NASA Astrophysics Data System (ADS)

Demirel, M. C.; Mai, J.; Stisen, S.; Mendiguren González, G.; Koch, J.; Samaniego, L. E.

2016-12-01

Distributed hydrologic models are traditionally calibrated and evaluated against observations of streamflow. Spatially distributed remote sensing observations offer a great opportunity to enhance spatial model calibration schemes. For that it is important to identify the model parameters that can change spatial patterns before the satellite based hydrologic model calibration. Our study is based on two main pillars: first we use spatial sensitivity analysis to identify the key parameters controlling the spatial distribution of actual evapotranspiration (AET). Second, we investigate the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale Hydrologic Model (mHM). This distributed model is selected as it allows for a change in the spatial distribution of key soil parameters through the calibration of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) directly as input. In addition the simulated AET can be estimated at the spatial resolution suitable for comparison to the spatial patterns observed using MODIS data. We introduce a new dynamic scaling function employing remotely sensed vegetation to downscale coarse reference evapotranspiration. In total, 17 parameters of 47 mHM parameters are identified using both sequential screening and Latin hypercube one-at-a-time sampling methods. The spatial patterns are found to be sensitive to the vegetation parameters whereas streamflow dynamics are sensitive to the PTF parameters. The results of multi-objective model calibration show that calibration of mHM against observed streamflow does not reduce the spatial errors in AET while they improve only the streamflow simulations. We will further examine the results of model calibration using only multi spatial objective functions measuring the association between observed AET and simulated AET maps and another case including spatial and streamflow metrics together.

Spatial heterogeneity of mobilization processes and input pathways of herbicides into a brook in a small agricultural catchment

NASA Astrophysics Data System (ADS)

Doppler, Tobias; Lück, Alfred; Popow, Gabriel; Strahm, Ivo; Winiger, Luca; Gaj, Marcel; Singer, Heinz; Stamm, Christian

2010-05-01

Soil applied herbicides can be transported from their point of application (agricultural field) to surface waters during rain events. There they can have harmful effects on aquatic species. Since the spatial distribution of mobilization and transport processes is very heterogeneous, the contributions of different fields to the total load in a surface water body may differ considerably. The localization of especially critical areas (contributing areas) can help to efficiently minimize herbicide inputs to surface waters. An agricultural field becomes a contributing area when three conditions are met: 1) herbicides are applied, 2) herbicides are mobilized on the field and 3) the mobilized herbicides are transported rapidly to the surface water. In spring 2009, a controlled herbicide application was performed on corn fields in a small (ca 1 km2) catchment with intensive crop production in the Swiss plateau. Subsequently water samples were taken at different locations in the catchment with a high temporal resolution during rain events. We observed both saturation excess and hortonian overland flow during the field campaign. Both can be important mobilization processes depending on the intensity and quantity of the rain. This can lead to different contributing areas during different types of rain events. We will show data on the spatial distribution of herbicide loads during different types of rain events. Also the connectivity of the fields with the brook is spatially heterogeneous. Most of the fields are disconnected from the brook by internal sinks in the catchment, which prevents surface runoff from entering the brook directly. Surface runoff from these disconnected areas can only enter the brook rapidly via macropore-flow into tile drains beneath the internal sinks or via direct shortcuts to the drainage system (maintenance manholes, farmyard or road drains). We will show spatially distributed data on herbicide concentration in purely subsurface systems which shows how important such input pathways can be.

Construction of a Distributed-network Digital Watershed Management System with B/S Techniques

NASA Astrophysics Data System (ADS)

Zhang, W. C.; Liu, Y. M.; Fang, J.

2017-07-01

Integrated watershed assessment tools for supporting land management and hydrologic research are becoming established tools in both basic and applied research. The core of these tools are mainly spatially distributed hydrologic models as they can provide a mechanism for investigating interactions among climate, topography, vegetation, and soil. However, the extensive data requirements and the difficult task of building input parameter files for driving these distributed models, have long been an obstacle to the timely and cost-effective use of such complex models by watershed managers and policy-makers. Recently, a web based geographic information system (GIS) tool to facilitate this process has been developed for a large watersheds of Jinghe and Weihe catchments located in the loess plateau of the Huanghe River basin in north-western China. A web-based GIS provides the framework within which spatially distributed data are collected and used to prepare model input files of these two watersheds and evaluate model results as well as to provide the various clients for watershed information inquiring, visualizing and assessment analysis. This Web-based Automated Geospatial Watershed Assessment GIS (WAGWA-GIS) tool uses widely available standardized spatial datasets that can be obtained via the internet oracle databank designed with association of Map Guide platform to develop input parameter files for online simulation at different spatial and temporal scales with Xing’anjiang and TOPMODEL that integrated with web-based digital watershed. WAGWA-GIS automates the process of transforming both digital data including remote sensing data, DEM, Land use/cover, soil digital maps and meteorological and hydrological station geo-location digital maps and text files containing meteorological and hydrological data obtained from stations of the watershed into hydrological models for online simulation and geo-spatial analysis and provides a visualization tool to help the user interpret results. The utility of WAGWA-GIS in jointing hydrologic and ecological investigations has been demonstrated on such diverse landscapes as Jinhe and Weihe watersheds, and will be extended to be utilized in the other watersheds in China step by step in coming years

A Dasymetric-Based Monte Carlo Simulation Approach to the Probabilistic Analysis of Spatial Variables

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morton, April M; Piburn, Jesse O; McManamay, Ryan A

2017-01-01

Monte Carlo simulation is a popular numerical experimentation technique used in a range of scientific fields to obtain the statistics of unknown random output variables. Despite its widespread applicability, it can be difficult to infer required input probability distributions when they are related to population counts unknown at desired spatial resolutions. To overcome this challenge, we propose a framework that uses a dasymetric model to infer the probability distributions needed for a specific class of Monte Carlo simulations which depend on population counts.

Forecasting tidal marsh elevation and habitat change through fusion of Earth observations and a process model

USGS Publications Warehouse

Byrd, Kristin B.; Windham-Myers, Lisamarie; Leeuw, Thomas; Downing, Bryan D.; Morris, James T.; Ferner, Matthew C.

2016-01-01

Reducing uncertainty in data inputs at relevant spatial scales can improve tidal marsh forecasting models, and their usefulness in coastal climate change adaptation decisions. The Marsh Equilibrium Model (MEM), a one-dimensional mechanistic elevation model, incorporates feedbacks of organic and inorganic inputs to project elevations under sea-level rise scenarios. We tested the feasibility of deriving two key MEM inputs—average annual suspended sediment concentration (SSC) and aboveground peak biomass—from remote sensing data in order to apply MEM across a broader geographic region. We analyzed the precision and representativeness (spatial distribution) of these remote sensing inputs to improve understanding of our study region, a brackish tidal marsh in San Francisco Bay, and to test the applicable spatial extent for coastal modeling. We compared biomass and SSC models derived from Landsat 8, DigitalGlobe WorldView-2, and hyperspectral airborne imagery. Landsat 8-derived inputs were evaluated in a MEM sensitivity analysis. Biomass models were comparable although peak biomass from Landsat 8 best matched field-measured values. The Portable Remote Imaging Spectrometer SSC model was most accurate, although a Landsat 8 time series provided annual average SSC estimates. Landsat 8-measured peak biomass values were randomly distributed, and annual average SSC (30 mg/L) was well represented in the main channels (IQR: 29–32 mg/L), illustrating the suitability of these inputs across the model domain. Trend response surface analysis identified significant diversion between field and remote sensing-based model runs at 60 yr due to model sensitivity at the marsh edge (80–140 cm NAVD88), although at 100 yr, elevation forecasts differed less than 10 cm across 97% of the marsh surface (150–200 cm NAVD88). Results demonstrate the utility of Landsat 8 for landscape-scale tidal marsh elevation projections due to its comparable performance with the other sensors, temporal frequency, and cost. Integration of remote sensing data with MEM should advance regional projections of marsh vegetation change by better parameterizing MEM inputs spatially. Improving information for coastal modeling will support planning for ecosystem services, including habitat, carbon storage, and flood protection.

Wrapping Python around MODFLOW/MT3DMS based groundwater models

NASA Astrophysics Data System (ADS)

Post, V.

2008-12-01

Numerical models that simulate groundwater flow and solute transport require a great amount of input data that is often organized into different files. A large proportion of the input data consists of spatially-distributed model parameters. The model output consists of a variety data such as heads, fluxes and concentrations. Typically all files have different formats. Consequently, preparing input and managing output is a complex and error-prone task. Proprietary software tools are available that facilitate the preparation of input files and analysis of model outcomes. The use of such software may be limited if it does not support all the features of the groundwater model or when the costs of such tools are prohibitive. Therefore a Python library was developed that contains routines to generate input files and process output files of MODFLOW/MT3DMS based models. The library is freely available and has an open structure so that the routines can be customized and linked into other scripts and libraries. The current set of functions supports the generation of input files for MODFLOW and MT3DMS, including the capability to read spatially-distributed input parameters (e.g. hydraulic conductivity) from PNG files. Both ASCII and binary output files can be read efficiently allowing for visualization of, for example, solute concentration patterns in contour plots with superimposed flow vectors using matplotlib. Series of contour plots are then easily saved as an animation. The subroutines can also be used within scripts to calculate derived quantities such as the mass of a solute within a particular region of the model domain. Using Python as a wrapper around groundwater models provides an efficient and flexible way of processing input and output data, which is not constrained by limitations of third-party products.

Improving the Non-Hydrostatic Numerical Dust Model by Integrating Soil Moisture and Greenness Vegetation Fraction Data with Different Spatiotemporal Resolutions.

PubMed

Yu, Manzhu; Yang, Chaowei

2016-01-01

Dust storms are devastating natural disasters that cost billions of dollars and many human lives every year. Using the Non-Hydrostatic Mesoscale Dust Model (NMM-dust), this research studies how different spatiotemporal resolutions of two input parameters (soil moisture and greenness vegetation fraction) impact the sensitivity and accuracy of a dust model. Experiments are conducted by simulating dust concentration during July 1-7, 2014, for the target area covering part of Arizona and California (31, 37, -118, -112), with a resolution of ~ 3 km. Using ground-based and satellite observations, this research validates the temporal evolution and spatial distribution of dust storm output from the NMM-dust, and quantifies model error using measurements of four evaluation metrics (mean bias error, root mean square error, correlation coefficient and fractional gross error). Results showed that the default configuration of NMM-dust (with a low spatiotemporal resolution of both input parameters) generates an overestimation of Aerosol Optical Depth (AOD). Although it is able to qualitatively reproduce the temporal trend of the dust event, the default configuration of NMM-dust cannot fully capture its actual spatial distribution. Adjusting the spatiotemporal resolution of soil moisture and vegetation cover datasets showed that the model is sensitive to both parameters. Increasing the spatiotemporal resolution of soil moisture effectively reduces model's overestimation of AOD, while increasing the spatiotemporal resolution of vegetation cover changes the spatial distribution of reproduced dust storm. The adjustment of both parameters enables NMM-dust to capture the spatial distribution of dust storms, as well as reproducing more accurate dust concentration.

Development of inhibitory synaptic inputs on layer 2/3 pyramidal neurons in the rat medial prefrontal cortex.

PubMed

Virtanen, Mari A; Lacoh, Claudia Marvine; Fiumelli, Hubert; Kosel, Markus; Tyagarajan, Shiva; de Roo, Mathias; Vutskits, Laszlo

2018-05-01

Inhibitory control of pyramidal neurons plays a major role in governing the excitability in the brain. While spatial mapping of inhibitory inputs onto pyramidal neurons would provide important structural data on neuronal signaling, studying their distribution at the single cell level is difficult due to the lack of easily identifiable anatomical proxies. Here, we describe an approach where in utero electroporation of a plasmid encoding for fluorescently tagged gephyrin into the precursors of pyramidal cells along with ionotophoretic injection of Lucifer Yellow can reliably and specifically detect GABAergic synapses on the dendritic arbour of single pyramidal neurons. Using this technique and focusing on the basal dendritic arbour of layer 2/3 pyramidal cells of the medial prefrontal cortex, we demonstrate an intense development of GABAergic inputs onto these cells between postnatal days 10 and 20. While the spatial distribution of gephyrin clusters was not affected by the distance from the cell body at postnatal day 10, we found that distal dendritic segments appeared to have a higher gephyrin density at later developmental stages. We also show a transient increase around postnatal day 20 in the percentage of spines that are carrying a gephyrin cluster, indicative of innervation by a GABAergic terminal. Since the precise spatial arrangement of synaptic inputs is an important determinant of neuronal responses, we believe that the method described in this work may allow a better understanding of how inhibition settles together with excitation, and serve as basics for further modelling studies focusing on the geometry of dendritic inhibition during development.

ViSA: a neurodynamic model for visuo-spatial working memory, attentional blink, and conscious access.

PubMed

Simione, Luca; Raffone, Antonino; Wolters, Gezinus; Salmas, Paola; Nakatani, Chie; Belardinelli, Marta Olivetti; van Leeuwen, Cees

2012-10-01

Two separate lines of study have clarified the role of selectivity in conscious access to visual information. Both involve presenting multiple targets and distracters: one simultaneously in a spatially distributed fashion, the other sequentially at a single location. To understand their findings in a unified framework, we propose a neurodynamic model for Visual Selection and Awareness (ViSA). ViSA supports the view that neural representations for conscious access and visuo-spatial working memory are globally distributed and are based on recurrent interactions between perceptual and access control processors. Its flexible global workspace mechanisms enable a unitary account of a broad range of effects: It accounts for the limited storage capacity of visuo-spatial working memory, attentional cueing, and efficient selection with multi-object displays, as well as for the attentional blink and associated sparing and masking effects. In particular, the speed of consolidation for storage in visuo-spatial working memory in ViSA is not fixed but depends adaptively on the input and recurrent signaling. Slowing down of consolidation due to weak bottom-up and recurrent input as a result of brief presentation and masking leads to the attentional blink. Thus, ViSA goes beyond earlier 2-stage and neuronal global workspace accounts of conscious processing limitations. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Spatial Light Modulators as Optical Crossbar Switches

NASA Technical Reports Server (NTRS)

Juday, Richard

2003-01-01

A proposed method of implementing cross connections in an optical communication network is based on the use of a spatial light modulator (SLM) to form controlled diffraction patterns that connect inputs (light sources) and outputs (light sinks). Sources would typically include optical fibers and/or light-emitting diodes; sinks would typically include optical fibers and/or photodetectors. The sources and/or sinks could be distributed in two dimensions; that is, on planes. Alternatively or in addition, sources and/or sinks could be distributed in three dimensions -- for example, on curved surfaces or in more complex (including random) three-dimensional patterns.

Monitoring and modeling as a continuing learning process: the use of hydrological models in a general probabilistic framework.

NASA Astrophysics Data System (ADS)

Baroni, G.; Gräff, T.; Reinstorf, F.; Oswald, S. E.

2012-04-01

Nowadays uncertainty and sensitivity analysis are considered basic tools for the assessment of hydrological models and the evaluation of the most important sources of uncertainty. In this context, in the last decades several methods have been developed and applied in different hydrological conditions. However, in most of the cases, the studies have been done by investigating mainly the influence of the parameter uncertainty on the simulated outputs and few approaches tried to consider also other sources of uncertainty i.e. input and model structure. Moreover, several constrains arise when spatially distributed parameters are involved. To overcome these limitations a general probabilistic framework based on Monte Carlo simulations and the Sobol method has been proposed. In this study, the general probabilistic framework was applied at field scale using a 1D physical-based hydrological model (SWAP). Furthermore, the framework was extended at catchment scale in combination with a spatially distributed hydrological model (SHETRAN). The models are applied in two different experimental sites in Germany: a relatively flat cropped field close to Potsdam (Brandenburg) and a small mountainous catchment with agricultural land use (Schaefertal, Harz Mountains). For both cases, input and parameters are considered as major sources of uncertainty. Evaluation of the models was based on soil moisture detected at plot scale in different depths and, for the catchment site, also with daily discharge values. The study shows how the framework can take into account all the various sources of uncertainty i.e. input data, parameters (either in scalar or spatially distributed form) and model structures. The framework can be used in a loop in order to optimize further monitoring activities used to improve the performance of the model. In the particular applications, the results show how the sources of uncertainty are specific for each process considered. The influence of the input data as well as the presence of compensating errors become clear by the different processes simulated.

Measurement of the Spatial Distribution of the Spectral Response Variation in the Field of View of the ASD Spectrometer Input Optics

DTIC Science & Technology

2014-12-01

development. It will be used for the measurement of the spectro-polarimetric BRDF (Bidirectional Reflectance Distribution function). For practical reasons...goniomètre est en développement. Il sera utilisé pour les mesures de BRDF (fonction de distribution de réflectance bidirectionnelle) spectrales et...by the independent measurements of the spectral and Bidirectional Reflectance Distribution Function ( BRDF ). The BRDF is the measurement of the

Sonochemiluminescence observation of lipid- and polymer-shelled ultrasound contrast agents in 1.2 MHz focused ultrasound field.

PubMed

Qiao, Yangzi; Cao, Hua; Zhang, Shusheng; Yin, Hui; Wan, Mingxi

2013-01-01

Ultrasound contrast agents (UCAs) are frequently added into the focused ultrasound field as cavitation nuclei to enhance the therapeutic efficiency. Since their presence will distort the pressure field and make the process unpredictable, comprehension of their behaviors especially the active zone spatial distribution is an important part of better monitoring and using of UCAs. As shell materials can strongly alter the acoustic behavior of UCAs, two different shells coated UCAs, lipid-shelled and polymer-shelled UCAs, in a 1.2 MHz focused ultrasound field were studied by the Sonochemiluminescence (SCL) method and compared. The SCL spatial distribution of lipid-shelled group differed from that of polymer-shelled group. The shell material and the character of focused ultrasound field work together to the SCL distribution, causing the lipid-shelled group to have a maximum SCL intensity in pre-focal region at lower input power than that of polymer-shelled group, and a brighter SCL intensity in post-focal region at high input power. The SCL inactive area of these two groups both increased with the input power. The general behavior of the UCAs can be studied by both the average SCL intensity and the backscatter signals. As polymer-shelled UCAs are more resistant to acoustic pressure, they had a higher destruction power and showed less reactivation than lipid-shelled ones. Copyright © 2012 Elsevier B.V. All rights reserved.

Influence of spatiotemporally distributed irradiance data input on temperature evolution in parabolic trough solar field simulations

NASA Astrophysics Data System (ADS)

Bubolz, K.; Schenk, H.; Hirsch, T.

2016-05-01

Concentrating solar field operation is affected by shadowing through cloud movement. For line focusing systems the impact of varying irradiance has been studied before by several authors with simulations of relevant thermodynamics assuming spatially homogeneous irradiance or using artificial test signals. While today's simulation capabilities allow more and more a higher spatiotemporal resolution of plant processes there are only few studies on influence of spatially distributed irradiance due to lack of available data. Based on recent work on generating real irradiance maps with high spatial resolution this paper demonstrates their influence on solar field thermodynamics. For a case study an irradiance time series is chosen. One solar field section with several loops and collecting header is modeled for simulation purpose of parabolic trough collectors and oil as heat transfer medium. Assuming homogeneous mass flow distribution among all loops we observe spatially varying temperature characteristics. They are analysed without and with mass flow control and their impact on solar field control design is discussed. Finally, the potential of distributed irradiance data is outlined.

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

NASA Astrophysics Data System (ADS)

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 total flow variability in the response of the urban drainage systems to heavy rainfall events.

Particle identification with neural networks using a rotational invariant moment representation

NASA Astrophysics Data System (ADS)

Sinkus, Ralph; Voss, Thomas

1997-02-01

A feed-forward neural network is used to identify electromagnetic particles based upon their showering properties within a segmented calorimeter. A preprocessing procedure is applied to the spatial energy distribution of the particle shower in order to account for the varying geometry of the calorimeter. The novel feature is the expansion of the energy distribution in terms of moments of the so-called Zernike functions which are invariant under rotation. The distributions of moments exhibit very different scales, thus the multidimensional input distribution for the neural network is transformed via a principal component analysis and rescaled by its respective variances to ensure input values of the order of one. This increases the sensitivity of the network and thus results in better performance in identifying and separating electromagnetic from hadronic particles, especially at low energies.

Temporal and spatial distributions of sediment total organic carbon in an estuary river.

PubMed

Ouyang, Y; Zhang, J E; Ou, L-T

2006-01-01

Understanding temporal and spatial distributions of naturally occurring total organic carbon (TOC) in sediments is critical because TOC is an important feature of surface water quality. This study investigated temporal and spatial distributions of sediment TOC and its relationships to sediment contaminants in the Cedar and Ortega Rivers, Florida, USA, using three-dimensional kriging analysis and field measurement. Analysis of field data showed that large temporal changes in sediment TOC concentrations occurred in the rivers, which reflected changes in the characteristics and magnitude of inputs into the rivers during approximately the last 100 yr. The average concentration of TOC in sediments from the Cedar and Ortega Rivers was 12.7% with a maximum of 22.6% and a minimum of 2.3%. In general, more TOC accumulated at the upper 1.0 m of the sediment in the southern part of the Ortega River although the TOC sedimentation varied with locations and depths. In contrast, high concentrations of sediment contaminants, that is, total polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs), were found in sediments from the Cedar River. There was no correlation between TOC and PAHs or PCBs in these river sediments. This finding is in contradiction to some other studies which reported that the sorption of hydrocarbons is highly related to the organic matter content of sediments. This discrepancy occurred because of the differences in TOC and hydrocarbon source input locations. It was found that more TOC loaded into the southern part of the Ortega River, while almost all of the hydrocarbons entered into the Cedar River. This study suggested that the locations of their input sources as well as the land use patterns should also be considered when relating hydrocarbons to sediment TOC.

Landscape-Scale water balance of cotton fields

USDA-ARS?s Scientific Manuscript database

Information on the temporal and spatial distribution of the components of the water balance of a production field is necessary to manage agronomic inputs. Furthermore, factors that determine crop yield require knowledge of the energy, water, nutrient and carbon balance and their interaction. The in...

Remotely sensed soil moisture input to a hydrologic model

NASA Technical Reports Server (NTRS)

Engman, E. T.; Kustas, W. P.; Wang, J. R.

1989-01-01

The possibility of using detailed spatial soil moisture maps as input to a runoff model was investigated. The water balance of a small drainage basin was simulated using a simple storage model. Aircraft microwave measurements of soil moisture were used to construct two-dimensional maps of the spatial distribution of the soil moisture. Data from overflights on different dates provided the temporal changes resulting from soil drainage and evapotranspiration. The study site and data collection are described, and the soil measurement data are given. The model selection is discussed, and the simulation results are summarized. It is concluded that a time series of soil moisture is a valuable new type of data for verifying model performance and for updating and correcting simulated streamflow.

Contribution of intrinsic properties and synaptic inputs to motoneuron discharge patterns: a simulation study

PubMed Central

ElBasiouny, Sherif M.; Rymer, W. Zev; Heckman, C. J.

2012-01-01

Motoneuron discharge patterns reflect the interaction of synaptic inputs with intrinsic conductances. Recent work has focused on the contribution of conductances mediating persistent inward currents (PICs), which amplify and prolong the effects of synaptic inputs on motoneuron discharge. Certain features of human motor unit discharge are thought to reflect a relatively stereotyped activation of PICs by excitatory synaptic inputs; these features include rate saturation and de-recruitment at a lower level of net excitation than that required for recruitment. However, PIC activation is also influenced by the pattern and spatial distribution of inhibitory inputs that are activated concurrently with excitatory inputs. To estimate the potential contributions of PIC activation and synaptic input patterns to motor unit discharge patterns, we examined the responses of a set of cable motoneuron models to different patterns of excitatory and inhibitory inputs. The models were first tuned to approximate the current- and voltage-clamp responses of low- and medium-threshold spinal motoneurons studied in decerebrate cats and then driven with different patterns of excitatory and inhibitory inputs. The responses of the models to excitatory inputs reproduced a number of features of human motor unit discharge. However, the pattern of rate modulation was strongly influenced by the temporal and spatial pattern of concurrent inhibitory inputs. Thus, even though PIC activation is likely to exert a strong influence on firing rate modulation, PIC activation in combination with different patterns of excitatory and inhibitory synaptic inputs can produce a wide variety of motor unit discharge patterns. PMID:22031773

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition

PubMed Central

Bill, Johannes; Buesing, Lars; Habenschuss, Stefan; Nessler, Bernhard; Maass, Wolfgang; Legenstein, Robert

2015-01-01

During the last decade, Bayesian probability theory has emerged as a framework in cognitive science and neuroscience for describing perception, reasoning and learning of mammals. However, our understanding of how probabilistic computations could be organized in the brain, and how the observed connectivity structure of cortical microcircuits supports these calculations, is rudimentary at best. In this study, we investigate statistical inference and self-organized learning in a spatially extended spiking network model, that accommodates both local competitive and large-scale associative aspects of neural information processing, under a unified Bayesian account. Specifically, we show how the spiking dynamics of a recurrent network with lateral excitation and local inhibition in response to distributed spiking input, can be understood as sampling from a variational posterior distribution of a well-defined implicit probabilistic model. This interpretation further permits a rigorous analytical treatment of experience-dependent plasticity on the network level. Using machine learning theory, we derive update rules for neuron and synapse parameters which equate with Hebbian synaptic and homeostatic intrinsic plasticity rules in a neural implementation. In computer simulations, we demonstrate that the interplay of these plasticity rules leads to the emergence of probabilistic local experts that form distributed assemblies of similarly tuned cells communicating through lateral excitatory connections. The resulting sparse distributed spike code of a well-adapted network carries compressed information on salient input features combined with prior experience on correlations among them. Our theory predicts that the emergence of such efficient representations benefits from network architectures in which the range of local inhibition matches the spatial extent of pyramidal cells that share common afferent input. PMID:26284370

High resolution population distribution maps for Southeast Asia in 2010 and 2015.

PubMed

Gaughan, Andrea E; Stevens, Forrest R; Linard, Catherine; Jia, Peng; Tatem, Andrew J

2013-01-01

Spatially accurate, contemporary data on human population distributions are vitally important to many applied and theoretical researchers. The Southeast Asia region has undergone rapid urbanization and population growth over the past decade, yet existing spatial population distribution datasets covering the region are based principally on population count data from censuses circa 2000, with often insufficient spatial resolution or input data to map settlements precisely. Here we outline approaches to construct a database of GIS-linked circa 2010 census data and methods used to construct fine-scale (∼100 meters spatial resolution) population distribution datasets for each country in the Southeast Asia region. Landsat-derived settlement maps and land cover information were combined with ancillary datasets on infrastructure to model population distributions for 2010 and 2015. These products were compared with those from two other methods used to construct commonly used global population datasets. Results indicate mapping accuracies are consistently higher when incorporating land cover and settlement information into the AsiaPop modelling process. Using existing data, it is possible to produce detailed, contemporary and easily updatable population distribution datasets for Southeast Asia. The 2010 and 2015 datasets produced are freely available as a product of the AsiaPop Project and can be downloaded from: www.asiapop.org.

High Resolution Population Distribution Maps for Southeast Asia in 2010 and 2015

PubMed Central

Gaughan, Andrea E.; Stevens, Forrest R.; Linard, Catherine; Jia, Peng; Tatem, Andrew J.

2013-01-01

Spatially accurate, contemporary data on human population distributions are vitally important to many applied and theoretical researchers. The Southeast Asia region has undergone rapid urbanization and population growth over the past decade, yet existing spatial population distribution datasets covering the region are based principally on population count data from censuses circa 2000, with often insufficient spatial resolution or input data to map settlements precisely. Here we outline approaches to construct a database of GIS-linked circa 2010 census data and methods used to construct fine-scale (∼100 meters spatial resolution) population distribution datasets for each country in the Southeast Asia region. Landsat-derived settlement maps and land cover information were combined with ancillary datasets on infrastructure to model population distributions for 2010 and 2015. These products were compared with those from two other methods used to construct commonly used global population datasets. Results indicate mapping accuracies are consistently higher when incorporating land cover and settlement information into the AsiaPop modelling process. Using existing data, it is possible to produce detailed, contemporary and easily updatable population distribution datasets for Southeast Asia. The 2010 and 2015 datasets produced are freely available as a product of the AsiaPop Project and can be downloaded from: www.asiapop.org. PMID:23418469

Global Swath and Gridded Data Tiling

NASA Technical Reports Server (NTRS)

Thompson, Charles K.

2012-01-01

This software generates cylindrically projected tiles of swath-based or gridded satellite data for the purpose of dynamically generating high-resolution global images covering various time periods, scaling ranges, and colors called "tiles." It reconstructs a global image given a set of tiles covering a particular time range, scaling values, and a color table. The program is configurable in terms of tile size, spatial resolution, format of input data, location of input data (local or distributed), number of processes run in parallel, and data conditioning.

Nitrogen Fertilization Elevated Spatial Heterogeneity of Soil Microbial Biomass Carbon and Nitrogen in Switchgrass and Gamagrass Croplands

NASA Astrophysics Data System (ADS)

Jian, S.; Li, J.; Guo, C.; Hui, D.; Deng, Q.; Yu, C. L.; Dzantor, K. E.; Lane, C.

2017-12-01

Nitrogen (N) fertilizers are widely used to increase bioenergy crop yield but intensive fertilizations on spatial distributions of soil microbial processes in bioenergy croplands remains unknown. To quantify N fertilization effect on spatial heterogeneity of soil microbial biomass carbon (MBC) and N (MBN), we sampled top mineral horizon soils (0-15cm) using a spatially explicit design within two 15-m2 plots under three fertilization treatments in two bioenergy croplands in a three-year long fertilization experiment in Middle Tennessee, USA. The three fertilization treatments were no N input (NN), low N input (LN: 84 kg N ha-1 in urea) and high N input (HN: 168 kg N ha-1 in urea). The two crops were switchgrass (SG: Panicum virgatum L.) and gamagrass (GG: Tripsacum dactyloides L.). Results showed that N fertilizations little altered central tendencies of microbial variables but relative to LN, HN significantly increased MBC and MBC:MBN (GG only). HN possessed the greatest within-plot variances except for MBN (GG only). Spatial patterns were generally evident under HN and LN plots and much less so under NN plots. Substantially contrasting spatial variations were also identified between croplands (GG>SG) and among variables (MBN, MBC:MBN > MBC). No significant correlations were identified between soil pH and microbial variables. This study demonstrated that spatial heterogeneity is elevated in microbial biomass of fertilized soils likely by uneven fertilizer application, the nature of soil microbial communities and bioenergy crops. Future researchers should better match sample sizes with the heterogeneity of soil microbial property (i.e. MBN) in bioenergy croplands.

Probabilistic estimation of residential air exchange rates for ...

EPA Pesticide Factsheets

Residential air exchange rates (AERs) are a key determinant in the infiltration of ambient air pollution indoors. Population-based human exposure models using probabilistic approaches to estimate personal exposure to air pollutants have relied on input distributions from AER measurements. An algorithm for probabilistically estimating AER was developed based on the Lawrence Berkley National Laboratory Infiltration model utilizing housing characteristics and meteorological data with adjustment for window opening behavior. The algorithm was evaluated by comparing modeled and measured AERs in four US cities (Los Angeles, CA; Detroit, MI; Elizabeth, NJ; and Houston, TX) inputting study-specific data. The impact on the modeled AER of using publically available housing data representative of the region for each city was also assessed. Finally, modeled AER based on region-specific inputs was compared with those estimated using literature-based distributions. While modeled AERs were similar in magnitude to the measured AER they were consistently lower for all cities except Houston. AERs estimated using region-specific inputs were lower than those using study-specific inputs due to differences in window opening probabilities. The algorithm produced more spatially and temporally variable AERs compared with literature-based distributions reflecting within- and between-city differences, helping reduce error in estimates of air pollutant exposure. Published in the Journal of

Development of Automated Objective Meteorological Techniques.

DTIC Science & Technology

1980-11-30

differences are due largely to the nature and spatial distribution of the atmospheric data chosen as input for the model . The data for initial values and...technique. This report fo,-uses on results of theoretical investigations and data analyses performed oy SASC during the period May, 1979 to June, 1980...the sampling period, at a given point in space, the various size particles composing the particle distribution ex- hibit different velocities from each

Analysis of rainfall distribution in Kelantan river basin, Malaysia

NASA Astrophysics Data System (ADS)

Che Ros, Faizah; Tosaka, Hiroyuki

2018-03-01

Using rainfall gauge on its own as input carries great uncertainties regarding runoff estimation, especially when the area is large and the rainfall is measured and recorded at irregular spaced gauging stations. Hence spatial interpolation is the key to obtain continuous and orderly rainfall distribution at unknown points to be the input to the rainfall runoff processes for distributed and semi-distributed numerical modelling. It is crucial to study and predict the behaviour of rainfall and river runoff to reduce flood damages of the affected area along the Kelantan river. Thus, a good knowledge on rainfall distribution is essential in early flood prediction studies. Forty six rainfall stations and their daily time-series were used to interpolate gridded rainfall surfaces using inverse-distance weighting (IDW), inverse-distance and elevation weighting (IDEW) methods and average rainfall distribution. Sensitivity analysis for distance and elevation parameters were conducted to see the variation produced. The accuracy of these interpolated datasets was examined using cross-validation assessment.

[Spatial-temporal pattern of sustainable intensification of agricultural land-use in Shandong Province, China.

PubMed

Niu, Shan Dong; Lyu, Xiao; Shi, Yang Yang

2018-02-01

Under the theoretical framework of sustainable intensification of agricultural land-use (SIALU), We used material flow analysis (MFA) method to establish evaluation index system for SIALU by utilizing data in 2000, 2005, 2010 and 2015 to quantify the level of SIALU of 17 cities in Shandong Province, and analyzed the variation in input-output of resources factors of agricultural land, spatial distribution of resource productivity and environmental economic efficiency, in order to reveal spatial-temporal differentiation of SIALU. Results showed that the direct material input to agricultural lands decreased, whereas hidden flow, stock and pollutant emissions increased gradually from 2000 to 2015. The material productivity of all cities in the province showed that the coastal areas in the peninsula were relatively lower than the southern region, and the level of material productivity in the northwest region was relatively higher. Environmental economic efficiency was gradually enhanced, and the western region was relatively higher than coastal area of the peninsula. During the period examined here, the spatial pattern of SIALU of various cities showed clustered distribution change, with the western region tending to gradually increase and the eastern region tending to gradually reduce. The dynamics of SIALU among different regions were divided into six grades: Northwestern Shandong > Northern Shandong > Southwestern Shandong > Southern Shandong > Central Shandong > Coastal areas of Shandong Peninsula.

Determining Global Population Distribution: Methods, Applications and Data

PubMed Central

Balk, D.L.; Deichmann, U.; Yetman, G.; Pozzi, F.; Hay, S.I.; Nelson, A.

2011-01-01

Evaluating the total numbers of people at risk from infectious disease in the world requires not just tabular population data, but data that are spatially explicit and global in extent at a moderate resolution. This review describes the basic methods for constructing estimates of global population distribution with attention to recent advances in improving both spatial and temporal resolution. To evaluate the optimal resolution for the study of disease, the native resolution of the data inputs as well as that of the resulting outputs are discussed. Assumptions used to produce different population data sets are also described, with their implications for the study of infectious disease. Lastly, the application of these population data sets in studies to assess disease distribution and health impacts is reviewed. The data described in this review are distributed in the accompanying DVD. PMID:16647969

Improved simulation of river water and groundwater exchange in an alluvial plain using the SWAT model

USDA-ARS?s Scientific Manuscript database

Hydrological interaction between surface and subsurface water systems has a significant impact on water quality, ecosystems and biogeochemistry cycling of both systems. Distributed models have been developed to simulate this function, but they require detailed spatial inputs and extensive computati...

Simulating the Interactions Among Land Use, Transportation, and Economy to Inform Light Rail Transit Decisions

EPA Science Inventory

In most transportation studies, computer models that forecast travel behavior statistics for a future year use static projections of the spatial distribution of future population and employment growth as inputs. As a result, they are unable to account for the temporally dynamic a...

Simulating the Interactions Among Land Use, Transportation, and Economy to Inform Light Rail Transit Decisions (proceedings)

EPA Science Inventory

In most transportation studies, computer models that forecast travel behavior statistics for a future year use static projections of the spatial distribution of future population and employment growth as inputs. As a result, they are unable to account for the temporally dynamic a...

Implementation of surface soil moisture data assimilation with watershed scale distributed hydrological model

USDA-ARS?s Scientific Manuscript database

This paper aims to investigate how surface soil moisture data assimilation affects each hydrologic process and how spatially varying inputs affect the potential capability of surface soil moisture assimilation at the watershed scale. The Ensemble Kalman Filter (EnKF) is coupled with a watershed scal...

Switchgrass Compositional Variations Arising from Spatial Distribution and Legume Intercropping

USDA-ARS?s Scientific Manuscript database

Switchgrass (Panicum virgatum) is a high–yielding, second-generation feedstock that can be grown on marginal land with minimal inputs. Due to the high genetic diversity within and among cultivars of this species, there may be a great amount of genotype x environment-induced differences among seconda...

Latin hypercube approach to estimate uncertainty in ground water vulnerability

USGS Publications Warehouse

Gurdak, J.J.; McCray, J.E.; Thyne, G.; Qi, S.L.

2007-01-01

A methodology is proposed to quantify prediction uncertainty associated with ground water vulnerability models that were developed through an approach that coupled multivariate logistic regression with a geographic information system (GIS). This method uses Latin hypercube sampling (LHS) to illustrate the propagation of input error and estimate uncertainty associated with the logistic regression predictions of ground water vulnerability. Central to the proposed method is the assumption that prediction uncertainty in ground water vulnerability models is a function of input error propagation from uncertainty in the estimated logistic regression model coefficients (model error) and the values of explanatory variables represented in the GIS (data error). Input probability distributions that represent both model and data error sources of uncertainty were simultaneously sampled using a Latin hypercube approach with logistic regression calculations of probability of elevated nonpoint source contaminants in ground water. The resulting probability distribution represents the prediction intervals and associated uncertainty of the ground water vulnerability predictions. The method is illustrated through a ground water vulnerability assessment of the High Plains regional aquifer. Results of the LHS simulations reveal significant prediction uncertainties that vary spatially across the regional aquifer. Additionally, the proposed method enables a spatial deconstruction of the prediction uncertainty that can lead to improved prediction of ground water vulnerability. ?? 2007 National Ground Water Association.

Temporal and spatial variability in thalweg profiles of a gravel-bed river

USGS Publications Warehouse

Madej, Mary Ann

1999-01-01

This study used successive longitudinal thalweg profiles in gravel-bed rivers to monitor changes in bed topography following floods and associated large sediment inputs. Variations in channel bed elevations, distributions of residual water depths, percentage of channel length occupied by riffles, and a spatial autocorrelation coefficient (Moran's I) were used to quantify changes in morphological diversity and spatial structure in Redwood Creek basin, northwestern California. Bed topography in Redwood Creek and its major tributaries consists primarily of a series of pools and riffles. The size, frequency and spatial distribution of the pools and riffles have changed significantly during the past 20 years. Following large floods and high sediment input in Redwood Creek and its tributaries in 1975, variation in channel bed elevations was low and the percentage of the channel length occupied by riffles was high. Over the next 20 years, variation in bed elevations increased while the length of channel occupied by riffles decreased. An index [(standard deviation of residual water depth/bankfull depth) × 100] was developed to compare variations in bed elevation over a range of stream sizes, with a higher index being indicative of greater morphological diversity. Spatial autocorrelation in the bed elevation data was apparent at both fine and coarse scales in many of the thalweg profiles and the observed spatial pattern of bed elevations was found to be related to the dominant channel material and the time since disturbance. River reaches in which forced pools dominated, and in which large woody debris and bed particles could not be easily mobilized, exhibited a random distribution of bed elevations. In contrast, in reaches where alternate bars dominated, and both wood and gravel were readily transported, regularly spaced bed topography developed at a spacing that increased with time since disturbance. This pattern of regularly spaced bed features was reversed following a 12-year flood when bed elevations became more randomly arranged.

County-level estimates of nitrogen and phosphorus from commercial fertilizer for the Conterminous United States, 1987–2006

USGS Publications Warehouse

Gronberg, Jo Ann M.; Spahr, Norman E.

2012-01-01

The U.S. Geological Survey’s National Water-Quality Assessment program requires nutrient input for analysis of the national and regional assessment of water quality. Detailed information on nutrient inputs to the environment are needed to understand and address the many serious problems that arise from excess nutrients in the streams and groundwater of the Nation. This report updates estimated county-level farm and nonfarm nitrogen and phosphorus input from commercial fertilizer sales for the conterminous United States for 1987 through 2006. Estimates were calculated from the Association of American Plant Food Control Officials fertilizer sales data, Census of Agriculture fertilizer expenditures, and U.S. Census Bureau county population. A previous national approach for deriving farm and nonfarm fertilizer nutrient estimates was evaluated, and a revised method for selecting representative states to calculate national farm and nonfarm proportions was developed. A national approach was used to estimate farm and nonfarm fertilizer inputs because not all states distinguish between farm and nonfarm use, and the quality of fertilizer reporting varies from year to year. For states that distinguish between farm and nonfarm use, the spatial distribution of the ratios of nonfarm-to-total fertilizer estimates for nitrogen and phosphorus calculated using the national-based farm and nonfarm proportions were similar to the spatial distribution of the ratios generated using state-based farm and nonfarm proportions. In addition, the relative highs and lows in the temporal distribution of farm and nonfarm nitrogen and phosphorus input at the state level were maintained—the periods of high and low usage coincide between national- and state-based values. With a few exceptions, nonfarm nitrogen estimates were found to be reasonable when compared to the amounts that would result if the lawn application rates recommended by state and university agricultural agencies were used. Also, states with higher nonfarm-to-total fertilizer ratios for nitrogen and phosphorus tended to have higher urban land-use percentages.

Shifts in controls on the temporal coherence of throughfall chemical flux in Acadia National Park, Maine, USA

USGS Publications Warehouse

Nelson, Sarah J.; Webster, Katherine E.; Loftin, Cynthia S.; Weathers, Kathleen C.

2013-01-01

Major ion and mercury (Hg) inputs to terrestrial ecosystems include both wet and dry deposition (total deposition). Estimating total deposition to sensitive receptor sites is hampered by limited information regarding its spatial heterogeneity and seasonality. We used measurements of throughfall flux, which includes atmospheric inputs to forests and the net effects of canopy leaching or uptake, for ten major ions and Hg collected during 35 time periods in 1999–2005 at over 70 sites within Acadia National Park, Maine to (1) quantify coherence in temporal dynamics of seasonal throughfall deposition and (2) examine controls on these patterns at multiple scales. We quantified temporal coherence as the correlation between all possible site pairs for each solute on a seasonal basis. In the summer growing season and autumn, coherence among pairs of sites with similar vegetation was stronger than for site-pairs that differed in vegetation suggesting that interaction with the canopy and leaching of solutes differed in coniferous, deciduous, mixed, and shrub or open canopy sites. The spatial pattern in throughfall hydrologic inputs across Acadia National Park was more variable during the winter snow season, suggesting that snow re-distribution affects net hydrologic input, which consequently affects chemical flux. Sea-salt corrected calcium concentrations identified a shift in air mass sources from maritime in winter to the continental industrial corridor in summer. Our results suggest that the spatial pattern of throughfall hydrologic flux, dominant seasonal air mass source, and relationship with vegetation in winter differ from the spatial pattern of throughfall flux in these solutes in summer and autumn. The coherence approach applied here made clear the strong influence of spatial heterogeneity in throughfall hydrologic inputs and a maritime air mass source on winter patterns of throughfall flux. By contrast, vegetation type was the most important influence on throughfall chemical flux in summer and autumn.

Light adaptation alters inner retinal inhibition to shape OFF retinal pathway signaling

PubMed Central

Mazade, Reece E.

2016-01-01

The retina adjusts its signaling gain over a wide range of light levels. A functional result of this is increased visual acuity at brighter luminance levels (light adaptation) due to shifts in the excitatory center-inhibitory surround receptive field parameters of ganglion cells that increases their sensitivity to smaller light stimuli. Recent work supports the idea that changes in ganglion cell spatial sensitivity with background luminance are due in part to inner retinal mechanisms, possibly including modulation of inhibition onto bipolar cells. To determine how the receptive fields of OFF cone bipolar cells may contribute to changes in ganglion cell resolution, the spatial extent and magnitude of inhibitory and excitatory inputs were measured from OFF bipolar cells under dark- and light-adapted conditions. There was no change in the OFF bipolar cell excitatory input with light adaptation; however, the spatial distributions of inhibitory inputs, including both glycinergic and GABAergic sources, became significantly narrower, smaller, and more transient. The magnitude and size of the OFF bipolar cell center-surround receptive fields as well as light-adapted changes in resting membrane potential were incorporated into a spatial model of OFF bipolar cell output to the downstream ganglion cells, which predicted an increase in signal output strength with light adaptation. We show a prominent role for inner retinal spatial signals in modulating the modeled strength of bipolar cell output to potentially play a role in ganglion cell visual sensitivity and acuity. PMID:26912599

Simulating maize yield and bomass with spatial variability of soil field capacity

USGS Publications Warehouse

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.

The significance of spatial variability of rainfall on streamflow: A synthetic analysis at the Upper Lee catchment, UK

NASA Astrophysics Data System (ADS)

Pechlivanidis, Ilias; McIntyre, Neil; Wheater, Howard

2017-04-01

Rainfall, one of the main inputs in hydrological modeling, is a highly heterogeneous process over a wide range of scales in space, and hence the ignorance of the spatial rainfall information could affect the simulated streamflow. Calibration of hydrological model parameters is rarely a straightforward task due to parameter equifinality and parameters' 'nature' to compensate for other uncertainties, i.e. structural and forcing input. In here, we analyse the significance of spatial variability of rainfall on streamflow as a function of catchment scale and type, and antecedent conditions using the continuous time, semi-distributed PDM hydrological model at the Upper Lee catchment, UK. The impact of catchment scale and type is assessed using 11 nested catchments ranging in scale from 25 to 1040 km2, and further assessed by artificially changing the catchment characteristics and translating these to model parameters with uncertainty using model regionalisation. Synthetic rainfall events are introduced to directly relate the change in simulated streamflow to the spatial variability of rainfall. Overall, we conclude that the antecedent catchment wetness and catchment type play an important role in controlling the significance of the spatial distribution of rainfall on streamflow. Results show a relationship between hydrograph characteristics (streamflow peak and volume) and the degree of spatial variability of rainfall for the impermeable catchments under dry antecedent conditions, although this decreases at larger scales; however this sensitivity is significantly undermined under wet antecedent conditions. Although there is indication that the impact of spatial rainfall on streamflow varies as a function of catchment scale, the variability of antecedent conditions between the synthetic catchments seems to mask this significance. Finally, hydrograph responses to different spatial patterns in rainfall depend on assumptions used for model parameter estimation and also the spatial variation in parameters indicating the need of an uncertainty framework in such investigation.

Site-specific management of nematodes pitfalls and practicalities.

PubMed

Evans, Ken; Webster, Richard M; Halford, Paul D; Barker, Anthony D; Russell, Michael D

2002-09-01

The greatest constraint to potato production in the United Kingdom (UK) is damage by the potato cyst nematodes (PCN) Globodera pallida and G. rostochiensis. Management of PCN depends heavily on nematicides, which are costly. Of all the inputs in UK agriculture, nematicides offer the largest potential cost savings from spatially variable application, and these savings would be accompanied by environmental benefits. We mapped PCN infestations in potato fields and monitored the changes in population density and distribution that occurred when susceptible potato crops were grown. The inverse relationship between population density before planting and multiplication rate of PCN makes it difficult to devise reliable spatial nematicide application procedures, especially when the pre-planting population density is just less than the detection threshold. Also, the spatial dependence found suggests that the coarse sampling grids used commercially are likely to produce misleading distribution maps.

Creating a spatial multi-criteria decision support system for energy related integrated environmental impact assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wanderer, Thomas, E-mail: thomas.wanderer@dlr.de; Herle, Stefan, E-mail: stefan.herle@rwth-aachen.de

2015-04-15

By their spatially very distributed nature, profitability and impacts of renewable energy resources are highly correlated with the geographic locations of power plant deployments. A web-based Spatial Decision Support System (SDSS) based on a Multi-Criteria Decision Analysis (MCDA) approach has been implemented for identifying preferable locations for solar power plants based on user preferences. The designated areas found serve for the input scenario development for a subsequent integrated Environmental Impact Assessment. The capabilities of the SDSS service get showcased for Concentrated Solar Power (CSP) plants in the region of Andalusia, Spain. The resulting spatial patterns of possible power plant sitesmore » are an important input to the procedural chain of assessing impacts of renewable energies in an integrated effort. The applied methodology and the implemented SDSS are applicable for other renewable technologies as well. - Highlights: • The proposed tool facilitates well-founded CSP plant siting decisions. • Spatial MCDA methods are implemented in a WebGIS environment. • GIS-based SDSS can contribute to a modern integrated impact assessment workflow. • The conducted case study proves the suitability of the methodology.« less

The integration of elastic wave properties and machine learning for the distribution of petrophysical properties in reservoir modeling

NASA Astrophysics Data System (ADS)

Ratnam, T. C.; Ghosh, D. P.; Negash, B. M.

2018-05-01

Conventional reservoir modeling employs variograms to predict the spatial distribution of petrophysical properties. This study aims to improve property distribution by incorporating elastic wave properties. In this study, elastic wave properties obtained from seismic inversion are used as input for an artificial neural network to predict neutron porosity in between well locations. The method employed in this study is supervised learning based on available well logs. This method converts every seismic trace into a pseudo-well log, hence reducing the uncertainty between well locations. By incorporating the seismic response, the reliance on geostatistical methods such as variograms for the distribution of petrophysical properties is reduced drastically. The results of the artificial neural network show good correlation with the neutron porosity log which gives confidence for spatial prediction in areas where well logs are not available.

Development of a distributed air pollutant dry deposition modeling framework.

PubMed

Hirabayashi, Satoshi; Kroll, Charles N; Nowak, David J

2012-12-01

A distributed air pollutant dry deposition modeling system was developed with a geographic information system (GIS) to enhance the functionality of i-Tree Eco (i-Tree, 2011). With the developed system, temperature, leaf area index (LAI) and air pollutant concentration in a spatially distributed form can be estimated, and based on these and other input variables, dry deposition of carbon monoxide (CO), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), and particulate matter less than 10 microns (PM10) to trees can be spatially quantified. Employing nationally available road network, traffic volume, air pollutant emission/measurement and meteorological data, the developed system provides a framework for the U.S. city managers to identify spatial patterns of urban forest and locate potential areas for future urban forest planting and protection to improve air quality. To exhibit the usability of the framework, a case study was performed for July and August of 2005 in Baltimore, MD. Copyright © 2012 Elsevier Ltd. All rights reserved.

A review on the sources and spatial-temporal distributions of Pb in Jiaozhou Bay

NASA Astrophysics Data System (ADS)

Yang, Dongfang; Zhang, Jie; Wang, Ming; Zhu, Sixi; Wu, Yunjie

2017-12-01

This paper provided a review on the source, spatial-distribution, temporal variations of Pb in Jiaozhou Bay based on investigation of Pb in surface and waters in different seasons during 1979-1983. The source strengths of Pb sources in Jiaozhou Bay were showing increasing trends, and the pollution level of Pb in this bay was slight or moderate in the early stage of reform and opening-up. Pb contents in the marine bay were mainly determined by the strength and frequency of Pb inputs from human activities, and Pb could be moving from high content areas to low content areas in the ocean interior. Surface waters in the ocean was polluted by human activities, and bottom waters was polluted by means of vertical water’s effect. The process of spatial distribution of Pb in waters was including three steps, i.e., 1), Pb was transferring to surface waters in the bay, 2) Pb was transferring to surface waters, and 3) Pb was transferring to and accumulating in bottom waters.

Spatial distribution of heavy metals in surficial sediments from Guanabara Bay: Rio de Janeiro, Brazil

NASA Astrophysics Data System (ADS)

Neto, José Antônio Baptista; Gingele, Franz Xaver; Leipe, Thomas; Brehme, Isa

2006-04-01

Ninety-two surface sediment samples were collected in Guanabara Bay, one of the most prominent urban bays in SE Brazil, to investigate the spatial distribution of anthropogenic pollutants. The concentrations of heavy metals, organic carbon and particle size were examined in all samples. Large spatial variations of heavy metals and particle size were observed. The highest concentrations of heavy metals were found in the muddy sediments from the north western region of the bay near the main outlets of the most polluted rivers, municipal waste drainage systems and one of the major oil refineries. Another anomalous concentration of metals was found adjacent to Rio de Janeiro Harbour. The heavy metal concentrations decrease to the northeast, due to intact rivers and the mangrove systems in this area, and to the south where the sand fraction and open-marine processes dominate. The geochemical normalization of metal data to Li or Al has also demonstrated that the anthropogenic input of heavy metals have altered the natural sediment heavy metal distribution.

The effect of the electric wind on the spatial distribution of chemical species in the positive corona discharge

NASA Astrophysics Data System (ADS)

Yanallah, K.; Pontiga, F.; Bouazza, M. R.; Chen, J. H.

2017-08-01

The electrohydrodynamic air flow generated by a positive corona discharge, and its effect on the spatial distribution of chemical species within a wire-plate corona reactor, have been numerically simulated. The computational model is based on the solutions of the Navier-Stokes equation and the continuity equation of each chemical species generated by the electrical discharge. A simplified analytical expression of the electric force density, which only requires the current density as the input parameter, has been used in the Navier-Stokes equation to obtain the velocity field. For the solution of the continuity equations, a plasma chemistry model that includes the most important reactions between electrons, atoms and molecules in air has been used. Similar to the electric force, the electron density distribution has been approximated by using a semi-analytical expression appropriate for the electrode geometry. The results of the study show that the spatial distribution of chemical species can be very different, and depends on the interplay between the electrohydrodynamic flow, the chemical kinetics of the species and its characteristic lifetime.

Market Aspects of Diffusion: A Spatial Perspective on the Diffusion of Innovations in Thailand.

ERIC Educational Resources Information Center

Pontius, Steven K.

How market factors affected the diffusion of four agricultural inputs (fertilizer, herbicide, insecticide, and fungicide) among farmers on the Central Plain of Thailand is examined. Market factors investigated were the distribution policies of the propagators and the travel behavior of the potential adopters. Data were gathered through personal…

Drawing a representative sample from the NCSS soil database: Building blocks for the national wind erosion network

USDA-ARS?s Scientific Manuscript database

Developing national wind erosion models for the continental United States requires a comprehensive spatial representation of continuous soil particle size distributions (PSD) for model input. While the current coverage of soil survey is nearly complete, the most detailed particle size classes have c...

Small-scale temporal and spatial variability in the abundance of plastic pellets on sandy beaches: Methodological considerations for estimating the input of microplastics.

PubMed

Moreira, Fabiana Tavares; Prantoni, Alessandro Lívio; Martini, Bruno; de Abreu, Michelle Alves; Stoiev, Sérgio Biato; Turra, Alexander

2016-01-15

Microplastics such as pellets have been reported for many years on sandy beaches around the globe. Nevertheless, high variability is observed in their estimates and distribution patterns across the beach environment are still to be unravelled. Here, we investigate the small-scale temporal and spatial variability in the abundance of pellets in the intertidal zone of a sandy beach and evaluate factors that can increase the variability in data sets. The abundance of pellets was estimated during twelve consecutive tidal cycles, identifying the position of the high tide between cycles and sampling drift-lines across the intertidal zone. We demonstrate that beach dynamic processes such as the overlap of strandlines and artefacts of the methods can increase the small-scale variability. The results obtained are discussed in terms of the methodological considerations needed to understand the distribution of pellets in the beach environment, with special implications for studies focused on patterns of input. Copyright © 2015 Elsevier Ltd. All rights reserved.

Attenuation and bit error rate for four co-propagating spatially multiplexed optical communication channels of exactly same wavelength in step index multimode fibers

NASA Astrophysics Data System (ADS)

Murshid, Syed H.; Chakravarty, Abhijit

2011-06-01

Spatial domain multiplexing (SDM) utilizes co-propagation of exactly the same wavelength in optical fibers to increase the bandwidth by integer multiples. Input signals from multiple independent single mode pigtail laser sources are launched at different input angles into a single multimode carrier fiber. The SDM channels follow helical paths and traverse through the carrier fiber without interfering with each other. The optical energy from the different sources is spatially distributed and takes the form of concentric circular donut shaped rings, where each ring corresponds to an independent laser source. At the output end of the fiber these donut shaped independent channels can be separated either with the help of bulk optics or integrated concentric optical detectors. This presents the experimental setup and results for a four channel SDM system. The attenuation and bit error rate for individual channels of such a system is also presented.

Improved neutron activation prediction code system development

NASA Technical Reports Server (NTRS)

Saqui, R. M.

1971-01-01

Two integrated neutron activation prediction code systems have been developed by modifying and integrating existing computer programs to perform the necessary computations to determine neutron induced activation gamma ray doses and dose rates in complex geometries. Each of the two systems is comprised of three computational modules. The first program module computes the spatial and energy distribution of the neutron flux from an input source and prepares input data for the second program which performs the reaction rate, decay chain and activation gamma source calculations. A third module then accepts input prepared by the second program to compute the cumulative gamma doses and/or dose rates at specified detector locations in complex, three-dimensional geometries.

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

NASA Astrophysics Data System (ADS)

Zhang, X.; Srinivasan, R.

2008-12-01

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

Electronic holography using binary phase modulation

NASA Astrophysics Data System (ADS)

Matoba, Osamu

2014-06-01

A 3D display system by using a phase-only distribution is presented. Especially, binary phase distribution is used to reconstruct a 3D object for wide viewing zone angle. To obtain the phase distribution to be displayed on a phase-mode spatial light modulator, both of experimental and numerical processes are available. In this paper, we present a numerical process by using a computer graphics data. A random phase distribution is attached to all polygons of an input 3D object to reconstruct a 3D object well from the binary phase distribution. Numerical and experimental results are presented to show the effectiveness of the proposed system.

Alcohol beverage control, privatization and the geographic distribution of alcohol outlets

PubMed Central

2012-01-01

Background With Pennsylvania currently considering a move away from an Alcohol Beverage Control state to a privatized alcohol distribution system, this study uses a spatial analytical approach to examine potential impacts of privatization on the number and spatial distribution of alcohol outlets in the city of Philadelphia over a long time horizon. Methods A suite of geospatial data were acquired for Philadelphia, including 1,964 alcohol outlet locations, 569,928 land parcels, and school, church, hospital, park and playground locations. These data were used as inputs for exploratory spatial analysis to estimate the expected number of outlets that would eventually operate in Philadelphia. Constraints included proximity restrictions (based on current ordinances regulating outlet distribution) of at least 200 feet between alcohol outlets and at least 300 feet between outlets and schools, churches, hospitals, parks and playgrounds. Results Findings suggest that current state policies on alcohol outlet distributions in Philadelphia are loosely enforced, with many areas exhibiting extremely high spatial densities of outlets that violate existing proximity restrictions. The spatial model indicates that an additional 1,115 outlets could open in Philadelphia if privatization was to occur and current proximity ordinances were maintained. Conclusions The study reveals that spatial analytical approaches can function as an excellent tool for contingency-based “what-if” analysis, providing an objective snapshot of potential policy outcomes prior to implementation. In this case, the likely outcome is a tremendous increase in alcohol outlets in Philadelphia, with concomitant negative health, crime and quality of life outcomes that accompany such an increase. PMID:23170899

Three-dimensional spatial modeling of spines along dendritic networks in human cortical pyramidal neurons

PubMed Central

Larrañaga, Pedro; Benavides-Piccione, Ruth; Fernaud-Espinosa, Isabel; DeFelipe, Javier; Bielza, Concha

2017-01-01

We modeled spine distribution along the dendritic networks of pyramidal neurons in both basal and apical dendrites. To do this, we applied network spatial analysis because spines can only lie on the dendritic shaft. We expanded the existing 2D computational techniques for spatial analysis along networks to perform a 3D network spatial analysis. We analyzed five detailed reconstructions of adult human pyramidal neurons of the temporal cortex with a total of more than 32,000 spines. We confirmed that there is a spatial variation in spine density that is dependent on the distance to the cell body in all dendrites. Considering the dendritic arborizations of each pyramidal cell as a group of instances of the same observation (the neuron), we used replicated point patterns together with network spatial analysis for the first time to search for significant differences in the spine distribution of basal dendrites between different cells and between all the basal and apical dendrites. To do this, we used a recent variant of Ripley’s K function defined to work along networks. The results showed that there were no significant differences in spine distribution along basal arbors of the same neuron and along basal arbors of different pyramidal neurons. This suggests that dendritic spine distribution in basal dendritic arbors adheres to common rules. However, we did find significant differences in spine distribution along basal versus apical networks. Therefore, not only do apical and basal dendritic arborizations have distinct morphologies but they also obey different rules of spine distribution. Specifically, the results suggested that spines are more clustered along apical than in basal dendrites. Collectively, the results further highlighted that synaptic input information processing is different between these two dendritic domains. PMID:28662210

Three-dimensional spatial modeling of spines along dendritic networks in human cortical pyramidal neurons.

PubMed

Anton-Sanchez, Laura; Larrañaga, Pedro; Benavides-Piccione, Ruth; Fernaud-Espinosa, Isabel; DeFelipe, Javier; Bielza, Concha

2017-01-01

We modeled spine distribution along the dendritic networks of pyramidal neurons in both basal and apical dendrites. To do this, we applied network spatial analysis because spines can only lie on the dendritic shaft. We expanded the existing 2D computational techniques for spatial analysis along networks to perform a 3D network spatial analysis. We analyzed five detailed reconstructions of adult human pyramidal neurons of the temporal cortex with a total of more than 32,000 spines. We confirmed that there is a spatial variation in spine density that is dependent on the distance to the cell body in all dendrites. Considering the dendritic arborizations of each pyramidal cell as a group of instances of the same observation (the neuron), we used replicated point patterns together with network spatial analysis for the first time to search for significant differences in the spine distribution of basal dendrites between different cells and between all the basal and apical dendrites. To do this, we used a recent variant of Ripley's K function defined to work along networks. The results showed that there were no significant differences in spine distribution along basal arbors of the same neuron and along basal arbors of different pyramidal neurons. This suggests that dendritic spine distribution in basal dendritic arbors adheres to common rules. However, we did find significant differences in spine distribution along basal versus apical networks. Therefore, not only do apical and basal dendritic arborizations have distinct morphologies but they also obey different rules of spine distribution. Specifically, the results suggested that spines are more clustered along apical than in basal dendrites. Collectively, the results further highlighted that synaptic input information processing is different between these two dendritic domains.

Information transfer in auditoria and room-acoustical quality.

PubMed

Summers, Jason E

2013-04-01

It is hypothesized that room-acoustical quality correlates with the information-transfer rate. Auditoria are considered as multiple-input multiple-output communication channels and a theory of information-transfer is outlined that accounts for time-variant multipath, spatial hearing, and distributed directional sources. Source diversity and spatial hearing are shown to be the mechanisms through which multipath increases the information-transfer rate by overcoming finite spatial resolution. In addition to predictions that are confirmed by recent and historical findings, the theory provides explanations for the influence of factors such as musical repertoire and ensemble size on subjective preference and the influence of multisource, multichannel auralization on perceived realism.

Nested Expression Domains for Odorant Receptors in Zebrafish Olfactory Epithelium

NASA Astrophysics Data System (ADS)

Weth, Franco; Nadler, Walter; Korsching, Sigrun

1996-11-01

The mapping of high-dimensional olfactory stimuli onto the two-dimensional surface of the nasal sensory epithelium constitutes the first step in the neuronal encoding of olfactory input. We have used zebrafish as a model system to analyze the spatial distribution of odorant receptor molecules in the olfactory epithelium by quantitative in situ hybridization. To this end, we have cloned 10 very divergent zebrafish odorant receptor molecules by PCR. Individual genes are expressed in sparse olfactory receptor neurons. Analysis of the position of labeled cells in a simplified coordinate system revealed three concentric, albeit overlapping, expression domains for the four odorant receptors analyzed in detail. Such regionalized expression should result in a corresponding segregation of functional response properties. This might represent the first step of spatial encoding of olfactory input or be essential for the development of the olfactory system.

Method and apparatus for eliminating coherent noise in a coherent energy imaging system without destroying spatial coherence

NASA Technical Reports Server (NTRS)

Shulman, A. R. (Inventor)

1971-01-01

A method and apparatus for substantially eliminating noise in a coherent energy imaging system, and specifically in a light imaging system of the type having a coherent light source and at least one image lens disposed between an input signal plane and an output image plane are, discussed. The input signal plane is illuminated with the light source by rotating the lens about its optical axis. In this manner, the energy density of coherent noise diffraction patterns as produced by imperfections such as dust and/or bubbles on and/or in the lens is distributed over a ring-shaped area of the output image plane and reduced to a point wherein it can be ignored. The spatial filtering capability of the coherent imaging system is not affected by this noise elimination technique.

Crop classification modelling using remote sensing and environmental data in the Greater Platte River Basin, USA

USGS Publications Warehouse

Howard, Daniel M.; Wylie, Bruce K.; Tieszen, Larry L.

2012-01-01

With an ever expanding population, potential climate variability and an increasing demand for agriculture-based alternative fuels, accurate agricultural land-cover classification for specific crops and their spatial distributions are becoming critical to researchers, policymakers, land managers and farmers. It is important to ensure the sustainability of these and other land uses and to quantify the net impacts that certain management practices have on the environment. Although other quality crop classification products are often available, temporal and spatial coverage gaps can create complications for certain regional or time-specific applications. Our goal was to develop a model capable of classifying major crops in the Greater Platte River Basin (GPRB) for the post-2000 era to supplement existing crop classification products. This study identifies annual spatial distributions and area totals of corn, soybeans, wheat and other crops across the GPRB from 2000 to 2009. We developed a regression tree classification model based on 2.5 million training data points derived from the National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) in relation to a variety of other relevant input environmental variables. The primary input variables included the weekly 250 m US Geological Survey Earth Observing System Moderate Resolution Imaging Spectroradiometer normalized differential vegetation index, average long-term growing season temperature, average long-term growing season precipitation and yearly start of growing season. An overall model accuracy rating of 78% was achieved for a test sample of roughly 215 000 independent points that were withheld from model training. Ten 250 m resolution annual crop classification maps were produced and evaluated for the GPRB region, one for each year from 2000 to 2009. In addition to the model accuracy assessment, our validation focused on spatial distribution and county-level crop area totals in comparison with the NASS CDL and county statistics from the US Department of Agriculture (USDA) Census of Agriculture. The results showed that our model produced crop classification maps that closely resembled the spatial distribution trends observed in the NASS CDL and exhibited a close linear agreement with county-by-county crop area totals from USDA census data (R 2 = 0.90).

Neuronal ensemble for visual working memory via interplay of slow and fast oscillations.

PubMed

Mizuhara, Hiroaki; Yamaguchi, Yoko

2011-05-01

The current focus of studies on neural entities for memory maintenance is on the interplay between fast neuronal oscillations in the gamma band and slow oscillations in the theta or delta band. The hierarchical coupling of slow and fast oscillations is crucial for the rehearsal of sensory inputs for short-term storage, as well as for binding sensory inputs that are represented in spatially segregated cortical areas. However, no experimental evidence for the binding of spatially segregated information has yet been presented for memory maintenance in humans. In the present study, we actively manipulated memory maintenance performance with an attentional blink procedure during human scalp electroencephalography (EEG) recordings and identified that slow oscillations are enhanced when memory maintenance is successful. These slow oscillations accompanied fast oscillations in the gamma frequency range that appeared at spatially segregated scalp sites. The amplitude of the gamma oscillation at these scalp sites was simultaneously enhanced at an EEG phase of the slow oscillation. Successful memory maintenance appears to be achieved by a rehearsal of sensory inputs together with a coordination of distributed fast oscillations at a preferred timing of the slow oscillations. © 2011 The Authors. European Journal of Neuroscience © 2011 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Modeling uncertainty and correlation in soil properties using Restricted Pairing and implications for ensemble-based hillslope-scale soil moisture and temperature estimation

NASA Astrophysics Data System (ADS)

Flores, A. N.; Entekhabi, D.; Bras, R. L.

2007-12-01

Soil hydraulic and thermal properties (SHTPs) affect both the rate of moisture redistribution in the soil column and the volumetric soil water capacity. Adequately constraining these properties through field and lab analysis to parameterize spatially-distributed hydrology models is often prohibitively expensive. Because SHTPs vary significantly at small spatial scales individual soil samples are also only reliably indicative of local conditions, and these properties remain a significant source of uncertainty in soil moisture and temperature estimation. In ensemble-based soil moisture data assimilation, uncertainty in the model-produced prior estimate due to associated uncertainty in SHTPs must be taken into account to avoid under-dispersive ensembles. To treat SHTP uncertainty for purposes of supplying inputs to a distributed watershed model we use the restricted pairing (RP) algorithm, an extension of Latin Hypercube (LH) sampling. The RP algorithm generates an arbitrary number of SHTP combinations by sampling the appropriate marginal distributions of the individual soil properties using the LH approach, while imposing a target rank correlation among the properties. A previously-published meta- database of 1309 soils representing 12 textural classes is used to fit appropriate marginal distributions to the properties and compute the target rank correlation structure, conditioned on soil texture. Given categorical soil textures, our implementation of the RP algorithm generates an arbitrarily-sized ensemble of realizations of the SHTPs required as input to the TIN-based Realtime Integrated Basin Simulator with vegetation dynamics (tRIBS+VEGGIE) distributed parameter ecohydrology model. Soil moisture ensembles simulated with RP- generated SHTPs exhibit less variance than ensembles simulated with SHTPs generated by a scheme that neglects correlation among properties. Neglecting correlation among SHTPs can lead to physically unrealistic combinations of parameters that exhibit implausible hydrologic behavior when input to the tRIBS+VEGGIE model.

Estimating Prediction Uncertainty from Geographical Information System Raster Processing: A User's Manual for the Raster Error Propagation Tool (REPTool)

USGS Publications Warehouse

Gurdak, Jason J.; Qi, Sharon L.; Geisler, Michael L.

2009-01-01

The U.S. Geological Survey Raster Error Propagation Tool (REPTool) is a custom tool for use with the Environmental System Research Institute (ESRI) ArcGIS Desktop application to estimate error propagation and prediction uncertainty in raster processing operations and geospatial modeling. REPTool is designed to introduce concepts of error and uncertainty in geospatial data and modeling and provide users of ArcGIS Desktop a geoprocessing tool and methodology to consider how error affects geospatial model output. Similar to other geoprocessing tools available in ArcGIS Desktop, REPTool can be run from a dialog window, from the ArcMap command line, or from a Python script. REPTool consists of public-domain, Python-based packages that implement Latin Hypercube Sampling within a probabilistic framework to track error propagation in geospatial models and quantitatively estimate the uncertainty of the model output. Users may specify error for each input raster or model coefficient represented in the geospatial model. The error for the input rasters may be specified as either spatially invariant or spatially variable across the spatial domain. Users may specify model output as a distribution of uncertainty for each raster cell. REPTool uses the Relative Variance Contribution method to quantify the relative error contribution from the two primary components in the geospatial model - errors in the model input data and coefficients of the model variables. REPTool is appropriate for many types of geospatial processing operations, modeling applications, and related research questions, including applications that consider spatially invariant or spatially variable error in geospatial data.

Design and analysis for thematic map accuracy assessment: Fundamental principles

Treesearch

Stephen V. Stehman; Raymond L. Czaplewski

1998-01-01

Land-cover maps are used in numerous natural resource applications to describe the spatial distribution and pattern of land-cover, to estimate areal extent of various cover classes, or as input into habitat suitability models, land-cover change analyses, hydrological models, and risk analyses. Accuracy assessment quantifies data quality so that map users may evaluate...

Estimating spatially distributed soil texture using time series of thermal remote sensing - a case study in central Europe

NASA Astrophysics Data System (ADS)

Müller, Benjamin; Bernhardt, Matthias; Jackisch, Conrad; Schulz, Karsten

2016-09-01

For understanding water and solute transport processes, knowledge about the respective hydraulic properties is necessary. Commonly, hydraulic parameters are estimated via pedo-transfer functions using soil texture data to avoid cost-intensive measurements of hydraulic parameters in the laboratory. Therefore, current soil texture information is only available at a coarse spatial resolution of 250 to 1000 m. Here, a method is presented to derive high-resolution (15 m) spatial topsoil texture patterns for the meso-scale Attert catchment (Luxembourg, 288 km2) from 28 images of ASTER (advanced spaceborne thermal emission and reflection radiometer) thermal remote sensing. A principle component analysis of the images reveals the most dominant thermal patterns (principle components, PCs) that are related to 212 fractional soil texture samples. Within a multiple linear regression framework, distributed soil texture information is estimated and related uncertainties are assessed. An overall root mean squared error (RMSE) of 12.7 percentage points (pp) lies well within and even below the range of recent studies on soil texture estimation, while requiring sparser sample setups and a less diverse set of basic spatial input. This approach will improve the generation of spatially distributed topsoil maps, particularly for hydrologic modeling purposes, and will expand the usage of thermal remote sensing products.

Analysis of temporal decay of diffuse broadband sound fields in enclosures by decomposition in powers of an absorption parameter

NASA Astrophysics Data System (ADS)

Bliss, Donald; Franzoni, Linda; Rouse, Jerry; Manning, Ben

2005-09-01

An analysis method for time-dependent broadband diffuse sound fields in enclosures is described. Beginning with a formulation utilizing time-dependent broadband intensity boundary sources, the strength of these wall sources is expanded in a series in powers of an absorption parameter, thereby giving a separate boundary integral problem for each power. The temporal behavior is characterized by a Taylor expansion in the delay time for a source to influence an evaluation point. The lowest-order problem has a uniform interior field proportional to the reciprocal of the absorption parameter, as expected, and exhibits relatively slow exponential decay. The next-order problem gives a mean-square pressure distribution that is independent of the absorption parameter and is primarily responsible for the spatial variation of the reverberant field. This problem, which is driven by input sources and the lowest-order reverberant field, depends on source location and the spatial distribution of absorption. Additional problems proceed at integer powers of the absorption parameter, but are essentially higher-order corrections to the spatial variation. Temporal behavior is expressed in terms of an eigenvalue problem, with boundary source strength distributions expressed as eigenmodes. Solutions exhibit rapid short-time spatial redistribution followed by long-time decay of a predominant spatial mode.

Hydrographic and particle distributions over the Palos Verdes continental shelf: Spatial, seasonal and daily variability

USGS Publications Warehouse

Jones, B.H.; Noble, M.A.; Dickey, T.D.

2002-01-01

Moorings and towyo mapping were used to study the temporal and spatial variability of physical processes and suspended particulate material over the continental shelf of the Palos Verdes Peninsula in southwestern Los Angeles, California during the late summer of 1992 and winter of 1992-93. Seasonal evolution of the hydrographic structure is related to seasonal atmospheric forcing. During summer, stratification results from heating of the upper layer. Summer insolation coupled with the stratification results in a slight salinity increase nearsurface due to evaporation. Winter cooling removes much of the upper layer stratification, but winter storms can introduce sufficient quantities of freshwater into the shelf water column again adding stratification through the buoyancy input. Vertical mixing of the low salinity surface water deeper into the water column decreases the sharp nearsurface stratification and reduces the overall salinity of the upper water column. Moored conductivity measurements indicate that the decreased salinity persisted for at least 2 months after a major storm with additional freshwater inputs through the period. Four particulate groups contributed to the suspended particulate load in the water column: phytoplankton, resuspended sediments, and particles in treated sewage effluent were observed in every towyo mapping cruise; terrigenous particles are introduced through runoff from winter rainstorms. Terrigenous suspended particulate material sinks from the water column in <9 days and phytoplankton respond to the stormwater input of buoyancy and nutrients within the same period. The suspended particles near the bottom have spatially patchy distributions, but are always present in hydrographic surveys of the shelf. Temporal variations in these particles do not show a significant tidal response, but they may be maintained in suspension by internal wave and tide processes impinging on the shelf. ?? 2002 Elsevier Science Ltd. All rights reserved.

Using discharge data to reduce structural deficits in a hydrological model with a Bayesian inference approach and the implications for the prediction of critical source areas

NASA Astrophysics Data System (ADS)

Frey, M. P.; Stamm, C.; Schneider, M. K.; Reichert, P.

2011-12-01

A distributed hydrological model was used to simulate the distribution of fast runoff formation as a proxy for critical source areas for herbicide pollution in a small agricultural catchment in Switzerland. We tested to what degree predictions based on prior knowledge without local measurements could be improved upon relying on observed discharge. This learning process consisted of five steps: For the prior prediction (step 1), knowledge of the model parameters was coarse and predictions were fairly uncertain. In the second step, discharge data were used to update the prior parameter distribution. Effects of uncertainty in input data and model structure were accounted for by an autoregressive error model. This step decreased the width of the marginal distributions of parameters describing the lower boundary (percolation rates) but hardly affected soil hydraulic parameters. Residual analysis (step 3) revealed model structure deficits. We modified the model, and in the subsequent Bayesian updating (step 4) the widths of the posterior marginal distributions were reduced for most parameters compared to those of the prior. This incremental procedure led to a strong reduction in the uncertainty of the spatial prediction. Thus, despite only using spatially integrated data (discharge), the spatially distributed effect of the improved model structure can be expected to improve the spatially distributed predictions also. The fifth step consisted of a test with independent spatial data on herbicide losses and revealed ambiguous results. The comparison depended critically on the ratio of event to preevent water that was discharged. This ratio cannot be estimated from hydrological data only. The results demonstrate that the value of local data is strongly dependent on a correct model structure. An iterative procedure of Bayesian updating, model testing, and model modification is suggested.

Spatial heterogeneity of leaf area index across scales from simulation and remote sensing

NASA Astrophysics Data System (ADS)

Reichenau, Tim G.; Korres, Wolfgang; Montzka, Carsten; Schneider, Karl

2016-04-01

Leaf area index (LAI, single sided leaf area per ground area) influences mass and energy exchange of vegetated surfaces. Therefore LAI is an input variable for many land surface schemes of coupled large scale models, which do not simulate LAI. Since these models typically run on rather coarse resolution grids, LAI is often inferred from coarse resolution remote sensing. However, especially in agriculturally used areas, a grid cell of these products often covers more than a single land-use. In that case, the given LAI does not apply to any single land-use. Therefore, the overall spatial heterogeneity in these datasets differs from that on resolutions high enough to distinguish areas with differing land-use. Detailed process-based plant growth models simulate LAI for separate plant functional types or specific species. However, limited availability of observations causes reduced spatial heterogeneity of model input data (soil, weather, land-use). Since LAI is strongly heterogeneous in space and time and since processes depend on LAI in a nonlinear way, a correct representation of LAI spatial heterogeneity is also desirable on coarse resolutions. The current study assesses this issue by comparing the spatial heterogeneity of LAI from remote sensing (RapidEye) and process-based simulations (DANUBIA simulation system) across scales. Spatial heterogeneity is assessed by analyzing LAI frequency distributions (spatial variability) and semivariograms (spatial structure). Test case is the arable land in the fertile loess plain of the Rur catchment near the Germany-Netherlands border.

Statistical self-similarity of hotspot seamount volumes modeled as self-similar criticality

USGS Publications Warehouse

Tebbens, S.F.; Burroughs, S.M.; Barton, C.C.; Naar, D.F.

2001-01-01

The processes responsible for hotspot seamount formation are complex, yet the cumulative frequency-volume distribution of hotspot seamounts in the Easter Island/Salas y Gomez Chain (ESC) is found to be well-described by an upper-truncated power law. We develop a model for hotspot seamount formation where uniform energy input produces events initiated on a self-similar distribution of critical cells. We call this model Self-Similar Criticality (SSC). By allowing the spatial distribution of magma migration to be self-similar, the SSC model recreates the observed ESC seamount volume distribution. The SSC model may have broad applicability to other natural systems.

Spatial Estimation of Soil Moisture Using Synthetic Aperture Radar in Alaska

NASA Astrophysics Data System (ADS)

Meade, N. G.; Hinzman, L. D.; Kane, D. L.

1999-01-01

A spatially distributed Model of Arctic Thermal and Hydrologic processes (MATH) has been developed. One of the attributes of this model is the spatial and temporal prediction of soil moisture in the active layer. The spatially distributed output from this model required verification data obtained through remote sensing to assess performance at the watershed scale independently. Therefore, a neural network was trained to predict soil moisture contents near the ground surface. The input to train the neural network is synthetic aperture radar (SAR) pixel value, and field measurements of soil moisture, and vegetation, which were used as a surrogate for surface roughness. Once the network was trained, soil moisture predictions were made based on SAR pixel value and vegetation. These results were then used for comparison with results from the hydrologic model. The quality of neural network input was less than anticipated. Our digital elevation model (DEM) was not of high enough resolution to allow exact co-registration with soil moisture measurements; therefore, the statistical correlations were not as good as hoped. However, the spatial pattern of the SAR derived soil moisture contents compares favorably with the hydrologic MATH model results. Primary surface parameters that effect SAR include topography, surface roughness, vegetation cover and soil texture. Single parameters that are considered to influence SAR include incident angle of the radar, polarization of the radiation, signal strength and returning signal integration, to name a few. These factors influence the reflectance, but if one adequately quantifies the influences of terrain and roughness, it is considered possible to extract information on soil moisture from SAR imagery analysis and in turn use SAR imagery to validate hydrologic models

Stars and Stripes in the Cerebellar Cortex: A Voltage Sensitive Dye Study

PubMed Central

Rokni, Dan; Llinas, Rodolfo; Yarom, Yosef

2007-01-01

The lattice-like structure of the cerebellar cortex and its anatomical organization in two perpendicular axes provided the foundations for many theories of cerebellar function. However, the functional organization does not always match the anatomical organization. Thus direct measurement of the functional organization is central to our understanding of cerebellar processing. Here we use voltage sensitive dye imaging in the isolated cerebellar preparation to characterize the spatio-temporal organization of the climbing and mossy fiber (MF) inputs to the cerebellar cortex. Spatial and temporal parameters were used to develop reliable criteria to distinguish climbing fiber (CF) responses from MF responses. CF activation excited postsynaptic neurons along a parasagittal cortical band. These responses were composed of slow (∼25 ms), monophasic depolarizing signals. Neither the duration nor the spatial distribution of CF responses were affected by inhibition. Activation of MF generated responses that were organized in radial patches, and were composed of a fast (∼5 ms) depolarizing phase followed by a prolonged (∼100 ms) negative wave. Application of a GABAA blocker eliminated the hyperpolarizing phase and prolonged the depolarizing phase, but did not affect the spatial distribution of the response, thus suggesting that it is not the inhibitory system that is responsible for the inability of the MF input to generate beams of activity that propagate along the parallel fiber system. PMID:18958242

A study of optimal model lag and spatial inputs to artificial neural network for rainfall forecasting

NASA Astrophysics Data System (ADS)

Luk, K. C.; Ball, J. E.; Sharma, A.

2000-01-01

Artificial neural networks (ANNs), which emulate the parallel distributed processing of the human nervous system, have proven to be very successful in dealing with complicated problems, such as function approximation and pattern recognition. Due to their powerful capability and functionality, ANNs provide an alternative approach for many engineering problems that are difficult to solve by conventional approaches. Rainfall forecasting has been a difficult subject in hydrology due to the complexity of the physical processes involved and the variability of rainfall in space and time. In this study, ANNs were adopted to forecast short-term rainfall for an urban catchment. The ANNs were trained to recognise historical rainfall patterns as recorded from a number of gauges in the study catchment for reproduction of relevant patterns for new rainstorm events. The primary objective of this paper is to investigate the effect of temporal and spatial information on short-term rainfall forecasting. To achieve this aim, a comparison test on the forecast accuracy was made among the ANNs configured with different orders of lag and different numbers of spatial inputs. In developing the ANNs with alternative configurations, the ANNs were trained to an optimal level to achieve good generalisation of data. It was found in this study that the ANNs provided the most accurate predictions when an optimum number of spatial inputs was included into the network, and that the network with lower lag consistently produced better performance.

Optimal control of first order distributed systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Johnson, T. L.

1972-01-01

The problem of characterizing optimal controls for a class of distributed-parameter systems is considered. The system dynamics are characterized mathematically by a finite number of coupled partial differential equations involving first-order time and space derivatives of the state variables, which are constrained at the boundary by a finite number of algebraic relations. Multiple control inputs, extending over the entire spatial region occupied by the system ("distributed controls') are to be designed so that the response of the system is optimal. A major example involving boundary control of an unstable low-density plasma is developed from physical laws.

'spup' - an R package for uncertainty propagation in spatial environmental modelling

NASA Astrophysics Data System (ADS)

Sawicka, Kasia; Heuvelink, Gerard

2016-04-01

Computer models have become a crucial tool in engineering and environmental sciences for simulating the behaviour of complex static and dynamic systems. However, while many models are deterministic, the uncertainty in their predictions needs to be estimated before they are used for decision support. Currently, advances in uncertainty propagation and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability, including case studies with spatial models and spatial model inputs. Due to the growing popularity and applicability of the open source R programming language we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. In particular, the 'spup' package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model predictions. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques, as well as several uncertainty visualization functions. Uncertain environmental variables are represented in the package as objects whose attribute values may be uncertain and described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is also accommodated for. For uncertainty propagation the package has implemented the MC approach with efficient sampling algorithms, i.e. stratified random sampling and Latin hypercube sampling. The design includes facilitation of parallel computing to speed up MC computation. The MC realizations may be used as an input to the environmental models called from R, or externally. Selected static and interactive visualization methods that are understandable by non-experts with limited background in statistics can be used to summarize and visualize uncertainty about the measured input, model parameters and output of the uncertainty propagation. We demonstrate that the 'spup' package is an effective and easy tool to apply and can be used in multi-disciplinary research and model-based decision support.

'spup' - an R package for uncertainty propagation analysis in spatial environmental modelling

NASA Astrophysics Data System (ADS)

Sawicka, Kasia; Heuvelink, Gerard

2017-04-01

Computer models have become a crucial tool in engineering and environmental sciences for simulating the behaviour of complex static and dynamic systems. However, while many models are deterministic, the uncertainty in their predictions needs to be estimated before they are used for decision support. Currently, advances in uncertainty propagation and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability and being able to deal with case studies with spatial models and spatial model inputs. Due to the growing popularity and applicability of the open source R programming language we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. In particular, the 'spup' package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model predictions. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques, as well as several uncertainty visualization functions. Uncertain environmental variables are represented in the package as objects whose attribute values may be uncertain and described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is also accommodated for. For uncertainty propagation the package has implemented the MC approach with efficient sampling algorithms, i.e. stratified random sampling and Latin hypercube sampling. The design includes facilitation of parallel computing to speed up MC computation. The MC realizations may be used as an input to the environmental models called from R, or externally. Selected visualization methods that are understandable by non-experts with limited background in statistics can be used to summarize and visualize uncertainty about the measured input, model parameters and output of the uncertainty propagation. We demonstrate that the 'spup' package is an effective and easy tool to apply and can be used in multi-disciplinary research and model-based decision support.

Modeling the spatially dynamic distribution of humans in the Oregon (USA) coast range.

Treesearch

Jeffrey D. Kline; David L. Azuma; Alissa Moses

2003-01-01

A common approach to land use change analyses in multidisciplinary landscape-level studies is to delineate discrete forest and non-forest or urban and non-urban land use categories to serve as inputs into sets of integrated sub-models describing socioeconomic and ecological processes. Such discrete land use categories, however, may be inappropriate when the...

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

Treesearch

Eric J. Gustafson; Thomas R. Crow

1994-01-01

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

Mapping local and global variability in plant trait distributions

DOE PAGES

Butler, Ethan E.; Datta, Abhirup; Flores-Moreno, Habacuc; ...

2017-12-01

Accurate trait-environment relationships and global maps of plant trait distributions represent a needed stepping stone in global biogeography and are critical constraints of key parameters for land models. Here, we use a global data set of plant traits to map trait distributions closely coupled to photosynthesis and foliar respiration: specific leaf area (SLA), and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm); We propose two models to extrapolate geographically sparse point data to continuous spatial surfaces. The first is a categorical model using species mean trait values, categorized into plant functional types (PFTs) and extrapolating to PFT occurrencemore » ranges identified by remote sensing. The second is a Bayesian spatial model that incorporates information about PFT, location and environmental covariates to estimate trait distributions. Both models are further stratified by varying the number of PFTs; The performance of the models was evaluated based on their explanatory and predictive ability. The Bayesian spatial model leveraging the largest number of PFTs produced the best maps; The interpolation of full trait distributions enables a wider diversity of vegetation to be represented across the land surface. These maps may be used as input to Earth System Models and to evaluate other estimates of functional diversity.« less

Mapping local and global variability in plant trait distributions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Butler, Ethan E.; Datta, Abhirup; Flores-Moreno, Habacuc

Accurate trait-environment relationships and global maps of plant trait distributions represent a needed stepping stone in global biogeography and are critical constraints of key parameters for land models. Here, we use a global data set of plant traits to map trait distributions closely coupled to photosynthesis and foliar respiration: specific leaf area (SLA), and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm); We propose two models to extrapolate geographically sparse point data to continuous spatial surfaces. The first is a categorical model using species mean trait values, categorized into plant functional types (PFTs) and extrapolating to PFT occurrencemore » ranges identified by remote sensing. The second is a Bayesian spatial model that incorporates information about PFT, location and environmental covariates to estimate trait distributions. Both models are further stratified by varying the number of PFTs; The performance of the models was evaluated based on their explanatory and predictive ability. The Bayesian spatial model leveraging the largest number of PFTs produced the best maps; The interpolation of full trait distributions enables a wider diversity of vegetation to be represented across the land surface. These maps may be used as input to Earth System Models and to evaluate other estimates of functional diversity.« less

Location-dependent excitatory synaptic interactions in pyramidal neuron dendrites.

PubMed

Behabadi, Bardia F; Polsky, Alon; Jadi, Monika; Schiller, Jackie; Mel, Bartlett W

2012-01-01

Neocortical pyramidal neurons (PNs) receive thousands of excitatory synaptic contacts on their basal dendrites. Some act as classical driver inputs while others are thought to modulate PN responses based on sensory or behavioral context, but the biophysical mechanisms that mediate classical-contextual interactions in these dendrites remain poorly understood. We hypothesized that if two excitatory pathways bias their synaptic projections towards proximal vs. distal ends of the basal branches, the very different local spike thresholds and attenuation factors for inputs near and far from the soma might provide the basis for a classical-contextual functional asymmetry. Supporting this possibility, we found both in compartmental models and electrophysiological recordings in brain slices that the responses of basal dendrites to spatially separated inputs are indeed strongly asymmetric. Distal excitation lowers the local spike threshold for more proximal inputs, while having little effect on peak responses at the soma. In contrast, proximal excitation lowers the threshold, but also substantially increases the gain of distally-driven responses. Our findings support the view that PN basal dendrites possess significant analog computing capabilities, and suggest that the diverse forms of nonlinear response modulation seen in the neocortex, including uni-modal, cross-modal, and attentional effects, could depend in part on pathway-specific biases in the spatial distribution of excitatory synaptic contacts onto PN basal dendritic arbors.

Measurement of ozone production scaling in a helium plasma jet with oxygen admixture

NASA Astrophysics Data System (ADS)

Sands, Brian; Ganguly, Biswa

2012-10-01

Capillary dielectric barrier plasma jet devices that generate confined streamer-like discharges along a rare gas flow can produce significant quantities of reactive oxygen species with average input powers ranging from 100 mW to >1 W. We have measured spatially-resolved ozone production in a He plasma jet with O2 admixture concentrations up to 5% using absorption spectroscopy of the O3 Hartley band system. A 20-ns risetime, 10-13 kV positive unipolar voltage pulse train was used to power the discharge, with pulse repetition rates varied from 1-20 kHz. The discharge was operated in a transient glow mode to scale the input power by adjusting the gap width between the anode and downstream cathodic plane. Peak ozone number densities in the range of 10^16 - 10^17 cm-3 were measured. At a given voltage, the density of ozone increased monotonically up to 3% O2 admixture (6 mm gap) as the peak discharge current decreased by an order of magnitude. Ozone production increased with distance from the capillary, consistent with observations by other groups. Atomic oxygen production inferred from O-atom 777 nm emission intensity did not scale with ozone as the input power was increased. The spatial distribution of ozone and scaling with input power will be presented.

Searching for the right scale in catchment hydrology: the effect of soil spatial variability in simulated states and fluxes

NASA Astrophysics Data System (ADS)

Baroni, Gabriele; Zink, Matthias; Kumar, Rohini; Samaniego, Luis; Attinger, Sabine

2017-04-01

The advances in computer science and the availability of new detailed data-sets have led to a growing number of distributed hydrological models applied to finer and finer grid resolutions for larger and larger catchment areas. It was argued, however, that this trend does not necessarily guarantee better understanding of the hydrological processes or it is even not necessary for specific modelling applications. In the present study, this topic is further discussed in relation to the soil spatial heterogeneity and its effect on simulated hydrological state and fluxes. To this end, three methods are developed and used for the characterization of the soil heterogeneity at different spatial scales. The methods are applied at the soil map of the upper Neckar catchment (Germany), as example. The different soil realizations are assessed regarding their impact on simulated state and fluxes using the distributed hydrological model mHM. The results are analysed by aggregating the model outputs at different spatial scales based on the Representative Elementary Scale concept (RES) proposed by Refsgaard et al. (2016). The analysis is further extended in the present study by aggregating the model output also at different temporal scales. The results show that small scale soil variabilities are not relevant when the integrated hydrological responses are considered e.g., simulated streamflow or average soil moisture over sub-catchments. On the contrary, these small scale soil variabilities strongly affect locally simulated states and fluxes i.e., soil moisture and evapotranspiration simulated at the grid resolution. A clear trade-off is also detected by aggregating the model output by spatial and temporal scales. Despite the scale at which the soil variabilities are (or are not) relevant is not universal, the RES concept provides a simple and effective framework to quantify the predictive capability of distributed models and to identify the need for further model improvements e.g., finer resolution input. For this reason, the integration in this analysis of all the relevant input factors (e.g., precipitation, vegetation, geology) could provide a strong support for the definition of the right scale for each specific model application. In this context, however, the main challenge for a proper model assessment will be the correct characterization of the spatio- temporal variability of each input factor. Refsgaard, J.C., Højberg, A.L., He, X., Hansen, A.L., Rasmussen, S.H., Stisen, S., 2016. Where are the limits of model predictive capabilities?: Representative Elementary Scale - RES. Hydrol. Process. doi:10.1002/hyp.11029

Image enhancement by non-linear extrapolation in frequency space

NASA Technical Reports Server (NTRS)

Anderson, Charles H. (Inventor); Greenspan, Hayit K. (Inventor)

1998-01-01

An input image is enhanced to include spatial frequency components having frequencies higher than those in an input image. To this end, an edge map is generated from the input image using a high band pass filtering technique. An enhancing map is subsequently generated from the edge map, with the enhanced map having spatial frequencies exceeding an initial maximum spatial frequency of the input image. The enhanced map is generated by applying a non-linear operator to the edge map in a manner which preserves the phase transitions of the edges of the input image. The enhanced map is added to the input image to achieve a resulting image having spatial frequencies greater than those in the input image. Simplicity of computations and ease of implementation allow for image sharpening after enlargement and for real-time applications such as videophones, advanced definition television, zooming, and restoration of old motion pictures.

Projecting Future Urbanization with Prescott College's Spatial Growth Model to Promote Environmental Sustainability and Smart Growth, A Case Study in Atlanta, Georgia

NASA Technical Reports Server (NTRS)

Estes, Maurice G., Jr.; Crosson, William; Limaye, Ashutosh; Johnson, Hoyt; Quattrochi, Dale; Lapenta, William; Khan, Maudood

2006-01-01

Planning is an integral element of good management and necessary to anticipate events not merely respond to them. Projecting the quantity and spatial distribution of urban growth is essential to effectively plan for the delivery of city services and to evaluate potential environmental impacts. The major drivers of growth in large urban areas are increasing population, employment opportunities, and quality of life attractors such as a favorable climate and recreation opportunities. The spatial distribution of urban growth is dictated by the amount and location of developable land, topography, energy and water resources, transportation network, climate change, and the existing land use configuration. The Atlanta region is growing very rapidly both in population and the consumption of forestland or low-density residential development. Air pollution and water availability are significant ongoing environmental issues. The Prescott Spatial Growth Model (SGM) was used to make growth projections for the metropolitan Atlanta region to 2010,2020 and 2030 and results used for environmental assessment in both business as usual and smart growth scenarios. The Prescott SGM is a tool that uses an ESRI ArcView extension and can be applied at the parcel level or more coarse spatial scales and can accommodate a wide range of user inputs to develop any number of growth rules each of which can be weighted depending on growth assumptions. These projections were used in conjunction with meteorological and air quality models to evaluate future environmental impacts. This presentation will focus on the application of the SGM to the 13-County Atlanta Regional Commission planning jurisdiction as a case study. The SGM will be described, including how rule sets are developed and the decision process for allocation of future development to available land use categories. Data inputs required to effectively run the model will be discussed. Spatial growth projections for ten, twenty, and thirty year planning horizons will be presented and results discussed, including regional climate and air quality impacts.

Sensitivity of a Bayesian atmospheric-transport inversion model to spatio-temporal sensor resolution applied to the 2006 North Korean nuclear test

NASA Astrophysics Data System (ADS)

Lundquist, K. A.; Jensen, D. D.; Lucas, D. D.

2017-12-01

Atmospheric source reconstruction allows for the probabilistic estimate of source characteristics of an atmospheric release using observations of the release. Performance of the inversion depends partially on the temporal frequency and spatial scale of the observations. The objective of this study is to quantify the sensitivity of the source reconstruction method to sparse spatial and temporal observations. To this end, simulations of atmospheric transport of noble gasses are created for the 2006 nuclear test at the Punggye-ri nuclear test site. Synthetic observations are collected from the simulation, and are taken as "ground truth". Data denial techniques are used to progressively coarsen the temporal and spatial resolution of the synthetic observations, while the source reconstruction model seeks to recover the true input parameters from the synthetic observations. Reconstructed parameters considered here are source location, source timing and source quantity. Reconstruction is achieved by running an ensemble of thousands of dispersion model runs that sample from a uniform distribution of the input parameters. Machine learning is used to train a computationally-efficient surrogate model from the ensemble simulations. Monte Carlo sampling and Bayesian inversion are then used in conjunction with the surrogate model to quantify the posterior probability density functions of source input parameters. This research seeks to inform decision makers of the tradeoffs between more expensive, high frequency observations and less expensive, low frequency observations.

SutraPrep, a pre-processor for SUTRA, a model for ground-water flow with solute or energy transport

USGS Publications Warehouse

Provost, Alden M.

2002-01-01

SutraPrep facilitates the creation of three-dimensional (3D) input datasets for the USGS ground-water flow and transport model SUTRA Version 2D3D.1. It is most useful for applications in which the geometry of the 3D model domain and the spatial distribution of physical properties and boundary conditions is relatively simple. SutraPrep can be used to create a SUTRA main input (?.inp?) file, an initial conditions (?.ics?) file, and a 3D plot of the finite-element mesh in Virtual Reality Modeling Language (VRML) format. Input and output are text-based. The code can be run on any platform that has a standard FORTRAN-90 compiler. Executable code is available for Microsoft Windows.

Information entropy to measure the spatial and temporal complexity of solute transport in heterogeneous porous media

NASA Astrophysics Data System (ADS)

Li, Weiyao; Huang, Guanhua; Xiong, Yunwu

2016-04-01

The complexity of the spatial structure of porous media, randomness of groundwater recharge and discharge (rainfall, runoff, etc.) has led to groundwater movement complexity, physical and chemical interaction between groundwater and porous media cause solute transport in the medium more complicated. An appropriate method to describe the complexity of features is essential when study on solute transport and conversion in porous media. Information entropy could measure uncertainty and disorder, therefore we attempted to investigate complexity, explore the contact between the information entropy and complexity of solute transport in heterogeneous porous media using information entropy theory. Based on Markov theory, two-dimensional stochastic field of hydraulic conductivity (K) was generated by transition probability. Flow and solute transport model were established under four conditions (instantaneous point source, continuous point source, instantaneous line source and continuous line source). The spatial and temporal complexity of solute transport process was characterized and evaluated using spatial moment and information entropy. Results indicated that the entropy increased as the increase of complexity of solute transport process. For the point source, the one-dimensional entropy of solute concentration increased at first and then decreased along X and Y directions. As time increased, entropy peak value basically unchanged, peak position migrated along the flow direction (X direction) and approximately coincided with the centroid position. With the increase of time, spatial variability and complexity of solute concentration increase, which result in the increases of the second-order spatial moment and the two-dimensional entropy. Information entropy of line source was higher than point source. Solute entropy obtained from continuous input was higher than instantaneous input. Due to the increase of average length of lithoface, media continuity increased, flow and solute transport complexity weakened, and the corresponding information entropy also decreased. Longitudinal macro dispersivity declined slightly at early time then rose. Solute spatial and temporal distribution had significant impacts on the information entropy. Information entropy could reflect the change of solute distribution. Information entropy appears a tool to characterize the spatial and temporal complexity of solute migration and provides a reference for future research.

Contextual classification of multispectral image data: An unbiased estimator for the context distribution

NASA Technical Reports Server (NTRS)

Tilton, J. C.; Swain, P. H. (Principal Investigator); Vardeman, S. B.

1981-01-01

A key input to a statistical classification algorithm, which exploits the tendency of certain ground cover classes to occur more frequently in some spatial context than in others, is a statistical characterization of the context: the context distribution. An unbiased estimator of the context distribution is discussed which, besides having the advantage of statistical unbiasedness, has the additional advantage over other estimation techniques of being amenable to an adaptive implementation in which the context distribution estimate varies according to local contextual information. Results from applying the unbiased estimator to the contextual classification of three real LANDSAT data sets are presented and contrasted with results from non-contextual classifications and from contextual classifications utilizing other context distribution estimation techniques.

Assessment of spatial distribution of soil loss over the upper basin of Miyun reservoir in China based on RS and GIS techniques.

PubMed

Chen, Tao; Niu, Rui-qing; Wang, Yi; Li, Ping-xiang; Zhang, Liang-pei; Du, Bo

2011-08-01

Soil conservation planning often requires estimates of the spatial distribution of soil erosion at a catchment or regional scale. This paper applied the Revised Universal Soil Loss Equation (RUSLE) to investigate the spatial distribution of annual soil loss over the upper basin of Miyun reservoir in China. Among the soil erosion factors, which are rainfall erosivity (R), soil erodibility (K), slope length (L), slope steepness (S), vegetation cover (C), and support practice factor (P), the vegetative cover or C factor, which represents the effects of vegetation canopy and ground covers in reducing soil loss, has been one of the most difficult to estimate over broad geographic areas. In this paper, the C factor was estimated based on back propagation neural network and the results were compared with the values measured in the field. The correlation coefficient (r) obtained was 0.929. Then the C factor and the other factors were used as the input to RUSLE model. By integrating the six factor maps in geographical information system (GIS) through pixel-based computing, the spatial distribution of soil loss over the upper basin of Miyun reservoir was obtained. The results showed that the annual average soil loss for the upper basin of Miyun reservoir was 9.86 t ha(-1) ya(-1) in 2005, and the area of 46.61 km(2) (0.3%) experiences extremely severe erosion risk, which needs suitable conservation measures to be adopted on a priority basis. The spatial distribution of erosion risk classes was 66.9% very low, 21.89% low, 6.18% moderate, 2.89% severe, and 1.84% very severe. Thus, by using RUSLE in a GIS environment, the spatial distribution of water erosion can be obtained and the regions which susceptible to water erosion and need immediate soil conservation planning and application over the upper watershed of Miyun reservoir in China can be identified.

Parameterized approximation of lacunarity functions derived from airborne laser scanning point clouds of forested areas

NASA Astrophysics Data System (ADS)

Székely, Balázs; Kania, Adam; Varga, Katalin; Heilmeier, Hermann

2017-04-01

Lacunarity, a measure of the spatial distribution of the empty space is found to be a useful descriptive quantity of the forest structure. Its calculation, based on laser-scanned point clouds, results in a four-dimensional data set. The evaluation of results needs sophisticated tools and visualization techniques. To simplify the evaluation, it is straightforward to use approximation functions fitted to the results. The lacunarity function L(r), being a measure of scale-independent structural properties, has a power-law character. Previous studies showed that log(log(L(r))) transformation is suitable for analysis of spatial patterns. Accordingly, transformed lacunarity functions can be approximated by appropriate functions either in the original or in the transformed domain. As input data we have used a number of laser-scanned point clouds of various forests. The lacunarity distribution has been calculated along a regular horizontal grid at various (relative) elevations. The lacunarity data cube then has been logarithm-transformed and the resulting values became the input of parameter estimation at each point (point of interest, POI). This way at each POI a parameter set is generated that is suitable for spatial analysis. The expectation is that the horizontal variation and vertical layering of the vegetation can be characterized by this procedure. The results show that the transformed L(r) functions can be typically approximated by exponentials individually, and the residual values remain low in most cases. However, (1) in most cases the residuals may vary considerably, and (2) neighbouring POIs often give rather differing estimates both in horizontal and in vertical directions, of them the vertical variation seems to be more characteristic. In the vertical sense, the distribution of estimates shows abrupt changes at places, presumably related to the vertical structure of the forest. In low relief areas horizontal similarity is more typical, in higher relief areas horizontal similarity fades out in short distances. Some of the input data have been acquired in the framework of the ChangeHabitats2 project financed by the European Union. BS contributed as an Alexander von Humboldt Research Fellow.

An Updating System for the Gridded Population Database of China Based on Remote Sensing, GIS and Spatial Database Technologies.

PubMed

Yang, Xiaohuan; Huang, Yaohuan; Dong, Pinliang; Jiang, Dong; Liu, Honghui

2009-01-01

The spatial distribution of population is closely related to land use and land cover (LULC) patterns on both regional and global scales. Population can be redistributed onto geo-referenced square grids according to this relation. In the past decades, various approaches to monitoring LULC using remote sensing and Geographic Information Systems (GIS) have been developed, which makes it possible for efficient updating of geo-referenced population data. A Spatial Population Updating System (SPUS) is developed for updating the gridded population database of China based on remote sensing, GIS and spatial database technologies, with a spatial resolution of 1 km by 1 km. The SPUS can process standard Moderate Resolution Imaging Spectroradiometer (MODIS L1B) data integrated with a Pattern Decomposition Method (PDM) and an LULC-Conversion Model to obtain patterns of land use and land cover, and provide input parameters for a Population Spatialization Model (PSM). The PSM embedded in SPUS is used for generating 1 km by 1 km gridded population data in each population distribution region based on natural and socio-economic variables. Validation results from finer township-level census data of Yishui County suggest that the gridded population database produced by the SPUS is reliable.

Temperature variability is integrated by a spatially embedded decision-making center to break dormancy in Arabidopsis seeds.

PubMed

Topham, Alexander T; Taylor, Rachel E; Yan, Dawei; Nambara, Eiji; Johnston, Iain G; Bassel, George W

2017-06-20

Plants perceive and integrate information from the environment to time critical transitions in their life cycle. Some mechanisms underlying this quantitative signal processing have been described, whereas others await discovery. Seeds have evolved a mechanism to integrate environmental information by regulating the abundance of the antagonistically acting hormones abscisic acid (ABA) and gibberellin (GA). Here, we show that hormone metabolic interactions and their feedbacks are sufficient to create a bistable developmental fate switch in Arabidopsis seeds. A digital single-cell atlas mapping the distribution of hormone metabolic and response components revealed their enrichment within the embryonic radicle, identifying the presence of a decision-making center within dormant seeds. The responses to both GA and ABA were found to occur within distinct cell types, suggesting cross-talk occurs at the level of hormone transport between these signaling centers. We describe theoretically, and demonstrate experimentally, that this spatial separation within the decision-making center is required to process variable temperature inputs from the environment to promote the breaking of dormancy. In contrast to other noise-filtering systems, including human neurons, the functional role of this spatial embedding is to leverage variability in temperature to transduce a fate-switching signal within this biological system. Fluctuating inputs therefore act as an instructive signal for seeds, enhancing the accuracy with which plants are established in ecosystems, and distributed computation within the radicle underlies this signal integration mechanism.

Temperature variability is integrated by a spatially embedded decision-making center to break dormancy in Arabidopsis seeds

PubMed Central

Topham, Alexander T.; Taylor, Rachel E.; Yan, Dawei; Nambara, Eiji; Johnston, Iain G.

2017-01-01

Plants perceive and integrate information from the environment to time critical transitions in their life cycle. Some mechanisms underlying this quantitative signal processing have been described, whereas others await discovery. Seeds have evolved a mechanism to integrate environmental information by regulating the abundance of the antagonistically acting hormones abscisic acid (ABA) and gibberellin (GA). Here, we show that hormone metabolic interactions and their feedbacks are sufficient to create a bistable developmental fate switch in Arabidopsis seeds. A digital single-cell atlas mapping the distribution of hormone metabolic and response components revealed their enrichment within the embryonic radicle, identifying the presence of a decision-making center within dormant seeds. The responses to both GA and ABA were found to occur within distinct cell types, suggesting cross-talk occurs at the level of hormone transport between these signaling centers. We describe theoretically, and demonstrate experimentally, that this spatial separation within the decision-making center is required to process variable temperature inputs from the environment to promote the breaking of dormancy. In contrast to other noise-filtering systems, including human neurons, the functional role of this spatial embedding is to leverage variability in temperature to transduce a fate-switching signal within this biological system. Fluctuating inputs therefore act as an instructive signal for seeds, enhancing the accuracy with which plants are established in ecosystems, and distributed computation within the radicle underlies this signal integration mechanism. PMID:28584126

EXTREME-ULTRAVIOLET OBSERVATIONAL CONSEQUENCES OF THE SPATIAL LOCALIZATION OF NANOFLARE HEATING WITHIN A MULTISTRANDED ATMOSPHERIC LOOP

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sarkar, Aveek; Walsh, Robert W.

2009-07-10

Determining the preferred spatial location of the energy input to solar coronal loops would be an important step forward toward a more complete understanding of the coronal heating problem. Following from the 2008 paper of Sarkar and Walsh, this paper presents a short (10{sup 9} cm {identical_to}10 Mm) 'global loop' as 125 individual strands, where each strand is modeled independently by a one-dimensional hydrodynamic simulation. The strands undergo small-scale episodic heating and are coupled together through the frequency distribution of the total energy input to the loop which follows a power-law distribution with index {approx}2.29. The spatial preference of themore » swarm of heating events from apex to footpoint is investigated. From a theoretical perspective, the resulting emission-measure-weighted temperature profiles along these two extreme cases do demonstrate a possible observable difference. Subsequently, the simulated output is folded through the Transition Region and Coronal Explorer (TRACE) instrument response functions and a rederivation of the temperature using different filter ratio techniques is performed. Given the multithermal scenario created by this many-strand loop model, a broad differential emission measure results; the subsequent double and triple filter ratios are very similar to those obtained from observations. However, any potential observational signature to differentiate between apex and footpoint dominant heating is possibly below instrumental thresholds. The consequences of using a broadband instrument like TRACE and Hinode-XRT in this way are discussed.« less

Double Wigner distribution function of a first-order optical system with a hard-edge aperture.

PubMed

Pan, Weiqing

2008-01-01

The effect of an apertured optical system on Wigner distribution can be expressed as a superposition integral of the input Wigner distribution function and the double Wigner distribution function of the apertured optical system. By introducing a hard aperture function into a finite sum of complex Gaussian functions, the double Wigner distribution functions of a first-order optical system with a hard aperture outside and inside it are derived. As an example of application, the analytical expressions of the Wigner distribution for a Gaussian beam passing through a spatial filtering optical system with an internal hard aperture are obtained. The analytical results are also compared with the numerical integral results, and they show that the analytical results are proper and ascendant.

Optical design of transmitter lens for asymmetric distributed free space optical networks

NASA Astrophysics Data System (ADS)

Wojtanowski, Jacek; Traczyk, Maciej

2018-05-01

We present a method of transmitter lens design dedicated for light distribution shaping on a curved and asymmetric target. In this context, target is understood as a surface determined by hypothetical optical detectors locations. In the proposed method, ribbon-like surfaces of arbitrary shape are considered. The designed lens has the task to transform collimated and generally non-uniform input beam into desired irradiance distribution on such irregular targets. Desired irradiance is associated with space-dependant efficiency of power flow between the source and receivers distributed on the target surface. This unconventional nonimaging task is different from most illumination or beam shaping objectives, where constant or prescribed irradiance has to be produced on a flat target screen. The discussed optical challenge comes from the applications where single transmitter cooperates with multitude of receivers located in various positions in space and oriented in various directions. The proposed approach is not limited to optical networks, but can be applied in a variety of other applications where nonconventional irradiance distribution has to be engineered. The described method of lens design is based on geometrical optics, radiometry and ray mapping philosophy. Rays are processed as a vector field, each of them carrying a certain amount of power. Having the target surface shape and orientation of receivers distribution, the rays-surface crossings map is calculated. It corresponds to the output rays vector field, which is referred to the calculated input rays spatial distribution on the designed optical surface. The application of Snell's law in a vector form allows one to obtain surface local normal vector and calculate lens profile. In the paper, we also present the case study dealing with exemplary optical network. The designed freeform lens is implemented in commercially available optical design software and irradiance three-dimensional spatial distribution is examined, showing perfect agreement with expectations.

A new approach for implementation of associative memory using volume holographic materials

NASA Astrophysics Data System (ADS)

Habibi, Mohammad; Pashaie, Ramin

2012-02-01

Associative memory, also known as fault tolerant or content-addressable memory, has gained considerable attention in last few decades. This memory possesses important advantages over the more common random access memories since it provides the capability to correct faults and/or partially missing information in a given input pattern. There is general consensus that optical implementation of connectionist models and parallel processors including associative memory has a better record of success compared to their electronic counterparts. In this article, we describe a novel optical implementation of associative memory which not only has the advantage of all optical learning and recalling capabilities, it can also be realized easily. We present a new approach, inspired by tomographic imaging techniques, for holographic implementation of associative memories. In this approach, a volume holographic material is sandwiched within a matrix of inputs (optical point sources) and outputs (photodetectors). The memory capacity is realized by the spatial modulation of refractive index of the holographic material. Constructing the spatial distribution of the refractive index from an array of known inputs and outputs is formulated as an inverse problem consisting a set of linear integral equations.

Spatial distribution and sources of heavy metals in natural pasture soil around copper-molybdenum mine in Northeast China.

PubMed

Wang, Zhiqiang; Hong, Chen; Xing, Yi; Wang, Kang; Li, Yifei; Feng, Lihui; Ma, Silu

2018-06-15

The characterization of the content and source of heavy metals are essential to assess the potential threat of metals to human health. The present study collected 140 topsoil samples around a Cu-Mo mine (Wunugetushan, China) and investigated the concentrations and spatial distribution pattern of Cr, Ni, Zn, Cu, Mo and Cd in soil using multivariate and geostatistical analytical methods. Results indicated that the average concentrations of six heavy metals, especially Cu and Mo, were obviously higher than the local background values. Correlation analysis and principal component analysis divided these metals into three groups, including Cr and Ni, Cu and Mo, Zn and Cd. Meanwhile, the spatial distribution maps of heavy metals indicated that Cr and Ni in soil were no notable anthropogenic inputs and mainly controlled by natural factors because their spatial maps exhibited non-point source contamination. The concentrations of Cu and Mo gradually decreased with distance away from the mine area, suggesting that human mining activities may be crucial in the spreading of contaminants. Soil contamination of Zn were associated with livestock manure produced from grazing. In addition, the environmental risk of heavy metal pollution was assessed by geo-accumulation index. All the results revealed that the spatial distribution of heavy metals in soil were in agreement with the local human activities. Investigating and identifying the origin of heavy metals in pasture soil will lay the foundation for taking effective measures to preserve soil from the long-term accumulation of heavy metals. Copyright © 2018 Elsevier Inc. All rights reserved.

Impact of spatial and temporal aggregation of input parameters on the assessment of irrigation scheme performance

NASA Astrophysics Data System (ADS)

Lorite, I. J.; Mateos, L.; Fereres, E.

2005-01-01

SummaryThe simulations of dynamic, spatially distributed non-linear models are impacted by the degree of spatial and temporal aggregation of their input parameters and variables. This paper deals with the impact of these aggregations on the assessment of irrigation scheme performance by simulating water use and crop yield. The analysis was carried out on a 7000 ha irrigation scheme located in Southern Spain. Four irrigation seasons differing in rainfall patterns were simulated (from 1996/1997 to 1999/2000) with the actual soil parameters and with hypothetical soil parameters representing wider ranges of soil variability. Three spatial aggregation levels were considered: (I) individual parcels (about 800), (II) command areas (83) and (III) the whole irrigation scheme. Equally, five temporal aggregation levels were defined: daily, weekly, monthly, quarterly and annually. The results showed little impact of spatial aggregation in the predictions of irrigation requirements and of crop yield for the scheme. The impact of aggregation was greater in rainy years, for deep-rooted crops (sunflower) and in scenarios with heterogeneous soils. The highest impact on irrigation requirement estimations was in the scenario of most heterogeneous soil and in 1999/2000, a year with frequent rainfall during the irrigation season: difference of 7% between aggregation levels I and III was found. Equally, it was found that temporal aggregation had only significant impact on irrigation requirements predictions for time steps longer than 4 months. In general, simulated annual irrigation requirements decreased as the time step increased. The impact was greater in rainy years (specially with abundant and concentrated rain events) and in crops which cycles coincide in part with the rainy season (garlic, winter cereals and olive). It is concluded that in this case, average, representative values for the main inputs of the model (crop, soil properties and sowing dates) can generate results within 1% of those obtained by providing spatially specific values for about 800 parcels.

A Bayesian approach to model structural error and input variability in groundwater modeling

NASA Astrophysics Data System (ADS)

Xu, T.; Valocchi, A. J.; Lin, Y. F. F.; Liang, F.

2015-12-01

Effective water resource management typically relies on numerical models to analyze groundwater flow and solute transport processes. Model structural error (due to simplification and/or misrepresentation of the "true" environmental system) and input forcing variability (which commonly arises since some inputs are uncontrolled or estimated with high uncertainty) are ubiquitous in groundwater models. Calibration that overlooks errors in model structure and input data can lead to biased parameter estimates and compromised predictions. We present a fully Bayesian approach for a complete assessment of uncertainty for spatially distributed groundwater models. The approach explicitly recognizes stochastic input and uses data-driven error models based on nonparametric kernel methods to account for model structural error. We employ exploratory data analysis to assist in specifying informative prior for error models to improve identifiability. The inference is facilitated by an efficient sampling algorithm based on DREAM-ZS and a parameter subspace multiple-try strategy to reduce the required number of forward simulations of the groundwater model. We demonstrate the Bayesian approach through a synthetic case study of surface-ground water interaction under changing pumping conditions. It is found that explicit treatment of errors in model structure and input data (groundwater pumping rate) has substantial impact on the posterior distribution of groundwater model parameters. Using error models reduces predictive bias caused by parameter compensation. In addition, input variability increases parametric and predictive uncertainty. The Bayesian approach allows for a comparison among the contributions from various error sources, which could inform future model improvement and data collection efforts on how to best direct resources towards reducing predictive uncertainty.

Grain Growth and Precipitation Behavior of Iridium Alloy DOP-26 During Long Term Aging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pierce, Dean T.; Muralidharan, Govindarajan; Fox, Ethan E.

The influence of long term aging on grain growth and precipitate sizes and spatial distribution in iridium alloy DOP-26 was studied. Samples of DOP-26 were fabricated using the new process, recrystallized for 1 hour (h) at 1375 C, then aged at either 1300, 1400, or 1500 C for times ranging from 50 to 10,000 h. Grain size measurements (vertical and horizontal mean linear intercept and horizontal and vertical projection) and analyses of iridium-thorium precipitates (size and spacing) were made on the longitudinal, transverse, and rolling surfaces of the as-recrystallized and aged specimens from which the two-dimensional spatial distribution and meanmore » sizes of the precipitates were obtained. The results obtained from this study are intended to provide input to grain growth models.« less

A spatial scaling relationship for soil moisture in a semiarid landscape, using spatial scaling relationships for pedology

NASA Astrophysics Data System (ADS)

Willgoose, G. R.; Chen, M.; Cohen, S.; Saco, P. M.; Hancock, G. R.

2013-12-01

In humid areas it is generally considered that soil moisture scales spatially according to the wetness index of the landscape. This scaling arises from lateral flow downslope of ground water within the soil zone. However, in semi-arid and drier regions, this lateral flow is small and fluxes are dominated by vertical flows driven by infiltration and evapotranspiration. Thus, in the absence of runon processes, soil moisture at a location is more driven by local factors such as soil and vegetation properties at that location rather than upstream processes draining to that point. The 'apparent' spatial randomness of soil and vegetation properties generally suggests that soil moisture for semi-arid regions is spatially random. In this presentation a new analysis of neutron probe data during summer from the Tarrawarra site near Melbourne, Australia shows persistent spatial organisation of soil moisture over several years. This suggests a link between permanent features of the catchment (e.g. soil properties) and soil moisture distribution, even though the spatial pattern of soil moisture during the 4 summers monitored appears spatially random. This and other data establishes a prima facie case that soil variations drive spatial variation in soil moisture. Accordingly, we used a previously published spatial scaling relationship for soil properties derived using the mARM pedogenesis model to simulate the spatial variation of soil grading. This soil grading distribution was used in the Rosetta pedotransfer model to derive a spatial distribution of soil functional properties (e.g. saturated hydraulic conductivity, porosity). These functional properties were then input into the HYDRUS-1D soil moisture model and soil moisture simulated for 3 years at daily resolution. The HYDRUS model used had previously been calibrated to field observed soil moisture data at our SASMAS field site. The scaling behaviour of soil moisture derived from this modelling will be discussed and compared with observed data from our SASMAS field sites.

Connections between residence time distributions and watershed characteristics across the continental US

NASA Astrophysics Data System (ADS)

Condon, L. E.; Maxwell, R. M.; Kollet, S. J.; Maher, K.; Haggerty, R.; Forrester, M. M.

2016-12-01

Although previous studies have demonstrated fractal residence time distributions in small watersheds, analyzing residence time scaling over large spatial areas is difficult with existing observational methods. For this study we use a fully integrated groundwater surface water simulation combined with Lagrangian particle tracking to evaluate connections between residence time distributions and watershed characteristics such as geology, topography and climate. Our simulation spans more than six million square kilometers of the continental US, encompassing a broad range of watershed sizes and physiographic settings. Simulated results demonstrate power law residence time distributions with peak age rages from 1.5 to 10.5 years. These ranges agree well with previous observational work and demonstrate the feasibility of using integrated models to simulate residence times. Comparing behavior between eight major watersheds, we show spatial variability in both the peak and the variance of the residence time distributions that can be related to model inputs. Peak age is well correlated with basin averaged hydraulic conductivity and the semi-variance corresponds to aridity. While power law age distributions have previously been attributed to fractal topography, these results illustrate the importance of subsurface characteristics and macro climate as additional controls on groundwater configuration and residence times.

Spatial light modulators for full cross-connections in optical networks

NASA Technical Reports Server (NTRS)

Juday, Richard D. (Inventor)

2004-01-01

A polarization-independent optical switch is disclosed for switching at least one incoming beam from at least one input source to at least one output drain. The switch includes a polarizing beam splitter to split each of the at least one incoming beam into a first input beam and a second input beam, wherein the first input beam and the second input beams are independently polarized; a wave plate optically coupled to the second input beam for converting the polarization of the second input beam to an appropriately polarized second input beam; a beam combiner optically coupled to the first input beam and the modified second input beam, wherein the beam combiner accepts the first input beam and the modified second input beam to produce a combined beam; the combined beam is invariant to the polarization state of the input source's polarization; and a controllable spatial light modulator optically coupled to the combined beam, wherein the combined beam is diffracted by the controllable spatial light modulator to place light at a plurality of output locations.

RockFall analyst: A GIS extension for three-dimensional and spatially distributed rockfall hazard modeling

NASA Astrophysics Data System (ADS)

Lan, Hengxing; Derek Martin, C.; Lim, C. H.

2007-02-01

Geographic information system (GIS) modeling is used in combination with three-dimensional (3D) rockfall process modeling to assess rockfall hazards. A GIS extension, RockFall Analyst (RA), which is capable of effectively handling large amounts of geospatial information relative to rockfall behaviors, has been developed in ArcGIS using ArcObjects and C#. The 3D rockfall model considers dynamic processes on a cell plane basis. It uses inputs of distributed parameters in terms of raster and polygon features created in GIS. Two major components are included in RA: particle-based rockfall process modeling and geostatistics-based rockfall raster modeling. Rockfall process simulation results, 3D rockfall trajectories and their velocity features either for point seeders or polyline seeders are stored in 3D shape files. Distributed raster modeling, based on 3D rockfall trajectories and a spatial geostatistical technique, represents the distribution of spatial frequency, the flying and/or bouncing height, and the kinetic energy of falling rocks. A distribution of rockfall hazard can be created by taking these rockfall characteristics into account. A barrier analysis tool is also provided in RA to aid barrier design. An application of these modeling techniques to a case study is provided. The RA has been tested in ArcGIS 8.2, 8.3, 9.0 and 9.1.

Evaluating agricultural nonpoint-source pollution using integrated geographic information systems and hydrologic/water quality model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tim, U.S.; Jolly, R.

1994-01-01

Considerable progress has been made in developing physically based, distributed parameter, hydrologic/water quality (HIWQ) models for planning and control of nonpoint-source pollution. The widespread use of these models is often constrained by the excessive and time-consuming input data demands and the lack of computing efficiencies necessary for iterative simulation of alternative management strategies. Recent developments in geographic information systems (GIS) provide techniques for handling large amounts of spatial data for modeling nonpoint-source pollution problems. Because a GIS can be used to combine information from several sources to form an array of model input data and to examine any combinations ofmore » spatial input/output data, it represents a highly effective tool for HiWQ modeling. This paper describes the integration of a distributed-parameter model (AGNPS) with a GIS (ARC/INFO) to examine nonpoint sources of pollution in an agricultural watershed. The ARC/INFO GIS provided the tools to generate and spatially organize the disparate data to support modeling, while the AGNPS model was used to predict several water quality variables including soil erosion and sedimentation within a watershed. The integrated system was used to evaluate the effectiveness of several alternative management strategies in reducing sediment pollution in a 417-ha watershed located in southern Iowa. The implementation of vegetative filter strips and contour buffer (grass) strips resulted in a 41 and 47% reduction in sediment yield at the watershed outlet, respectively. In addition, when the integrated system was used, the combination of the above management strategies resulted in a 71% reduction in sediment yield. In general, the study demonstrated the utility of integrating a simulation model with GIS for nonpoini-source pollution control and planning. Such techniques can help characterize the diffuse sources of pollution at the landscape level. 52 refs., 6 figs., 1 tab.« less

Sources and distribution of aliphatic and polyaromatic hydrocarbons in sediments from the Neuquen River, Argentine Patagonia.

PubMed

Monza, Liliana B; Loewy, Ruth M; Savini, Mónica C; Pechen de d'Angelo, Ana M

2013-01-01

Spatial distribution and probable sources of aliphatic and polyaromatic hydrocarbons (AHs, PAHs) were investigated in surface sediments collected along the bank of the Neuquen River, Argentina. Total concentrations of aliphatic hydrocarbons ranged between 0.41 and 125 μg/g dw. Six stations presented low values of resolved aliphatic hydrocarbons and the n-alkane distribution indexes applied suggested a clear biogenic source. These values can be considered the baseline levels of aliphatic hydrocarbons for the river sediments. This constitutes important information for the assessment of future impacts since a strong impulse in the exploitation of shale gas and shale oil in these zones is nowadays undergoing. For the other 11 stations, a mixture of aliphatic hydrocarbons of petrogenic and biogenic origin was observed. The spatial distribution reflects local inputs of these pollutants with a significant increase in concentrations in the lower course, where two major cities are located. The highest values of total aliphatic hydrocarbons were found in this sector which, in turn, was the only one where individual PAHs were detected.

Three-dimensional analysis of flow-chemical interaction within a single square channel of a lean NO x trap catalyst.

PubMed

Fornarelli, Francesco; Dadduzio, Ruggiero; Torresi, Marco; Camporeale, Sergio Mario; Fortunato, Bernardo

2018-02-01

A fully 3D unsteady Computational Fluid Dynamics (CFD) approach coupled with heterogeneous reaction chemistry is presented in order to study the behavior of a single square channel as part of a Lean [Formula: see text] Traps. The reliability of the numerical tool has been validated against literature data considering only active BaO site. Even though the input/output performance of such catalyst has been well known, here the spatial distribution within a single channel is investigated in details. The square channel geometry influences the flow field and the catalyst performance being the flow velocity distribution on the cross section non homogeneous. The mutual interaction between the flow and the active catalyst walls influences the spatial distribution of the volumetric species. Low velocity regions near the square corners and transversal secondary flows are shown in several cross-sections along the streamwise direction at different instants. The results shed light on the three-dimensional characteristic of both the flow field and species distribution within a single square channel of the catalyst with respect to 0-1D approaches.

Functional correlates of the lateral and medial entorhinal cortex: objects, path integration and local-global reference frames.

PubMed

Knierim, James J; Neunuebel, Joshua P; Deshmukh, Sachin S

2014-02-05

The hippocampus receives its major cortical input from the medial entorhinal cortex (MEC) and the lateral entorhinal cortex (LEC). It is commonly believed that the MEC provides spatial input to the hippocampus, whereas the LEC provides non-spatial input. We review new data which suggest that this simple dichotomy between 'where' versus 'what' needs revision. We propose a refinement of this model, which is more complex than the simple spatial-non-spatial dichotomy. MEC is proposed to be involved in path integration computations based on a global frame of reference, primarily using internally generated, self-motion cues and external input about environmental boundaries and scenes; it provides the hippocampus with a coordinate system that underlies the spatial context of an experience. LEC is proposed to process information about individual items and locations based on a local frame of reference, primarily using external sensory input; it provides the hippocampus with information about the content of an experience.

GREAT: a gradient-based color-sampling scheme for Retinex.

PubMed

Lecca, Michela; Rizzi, Alessandro; Serapioni, Raul Paolo

2017-04-01

Modeling the local color spatial distribution is a crucial step for the algorithms of the Milano Retinex family. Here we present GREAT, a novel, noise-free Milano Retinex implementation based on an image-aware spatial color sampling. For each channel of a color input image, GREAT computes a 2D set of edges whose magnitude exceeds a pre-defined threshold. Then GREAT re-scales the channel intensity of each image pixel, called target, by the average of the intensities of the selected edges weighted by a function of their positions, gradient magnitudes, and intensities relative to the target. In this way, GREAT enhances the input image, adjusting its brightness, contrast and dynamic range. The use of the edges as pixels relevant to color filtering is justified by the importance that edges play in human color sensation. The name GREAT comes from the expression "Gradient RElevAnce for ReTinex," which refers to the threshold-based definition of a gradient relevance map for edge selection and thus for image color filtering.

Temporal and spatial changes in persistent organic pollutants in Vietnamese coastal waters detected from plastic resin pellets.

PubMed

Le, Dung Quang; Takada, Hideshige; Yamashita, Rei; Mizukawa, Kaoruko; Hosoda, Junki; Tuyet, Dao Anh

2016-08-15

Plastic resin pellets collected at Minh Chau island and Ba Lat estuary between 2007 and 2014 in Vietnam were analyzed for dichloro-diphenyl-trichloroethanes (DDTs), polychlorinated biphenyls (PCBs) and hexachlorocyclohexanes (HCHs). The study was carried out as part of the International Pellet Watch program for monitoring the global distribution of persistent organic pollutants (POPs). Higher levels of DDTs compared to PCBs indicated agricultural inputs rather than industrial discharges in the region. Most POP concentrations on both beaches decreased over the period, with the exception of HCH isomers. Though the concentration of DDTs showed a drastic decline on both beaches between 2007/2008 and 2014, DDTs accounted for 60-80% of total DDTs, suggesting that there is still a fresh input of these chemicals in the region. This study strongly recommends further investigations to track temporal and spatial patterns of POP levels in the marine environment using plastic resin pellets. Copyright © 2016 Elsevier Ltd. All rights reserved.

Performance analysis of MIMO wireless optical communication system with Q-ary PPM over correlated log-normal fading channel

NASA Astrophysics Data System (ADS)

Wang, Huiqin; Wang, Xue; Lynette, Kibe; Cao, Minghua

2018-06-01

The performance of multiple-input multiple-output wireless optical communication systems that adopt Q-ary pulse position modulation over spatial correlated log-normal fading channel is analyzed in terms of its un-coded bit error rate and ergodic channel capacity. The analysis is based on the Wilkinson's method which approximates the distribution of a sum of correlated log-normal random variables to a log-normal random variable. The analytical and simulation results corroborate the increment of correlation coefficients among sub-channels lead to system performance degradation. Moreover, the receiver diversity has better performance in resistance of spatial correlation caused channel fading.

Simulation of net infiltration and potential recharge using a distributed-parameter watershed model of the Death Valley region, Nevada and California

USGS Publications Warehouse

Hevesi, Joseph A.; Flint, Alan L.; Flint, Lorraine E.

2003-01-01

This report presents the development and application of the distributed-parameter watershed model, INFILv3, for estimating the temporal and spatial distribution of net infiltration and potential recharge in the Death Valley region, Nevada and California. The estimates of net infiltration quantify the downward drainage of water across the lower boundary of the root zone and are used to indicate potential recharge under variable climate conditions and drainage basin characteristics. Spatial variability in recharge in the Death Valley region likely is high owing to large differences in precipitation, potential evapotranspiration, bedrock permeability, soil thickness, vegetation characteristics, and contributions to recharge along active stream channels. The quantity and spatial distribution of recharge representing the effects of variable climatic conditions and drainage basin characteristics on recharge are needed to reduce uncertainty in modeling ground-water flow. The U.S. Geological Survey, in cooperation with the Department of Energy, developed a regional saturated-zone ground-water flow model of the Death Valley regional ground-water flow system to help evaluate the current hydrogeologic system and the potential effects of natural or human-induced changes. Although previous estimates of recharge have been made for most areas of the Death Valley region, including the area defined by the boundary of the Death Valley regional ground-water flow system, the uncertainty of these estimates is high, and the spatial and temporal variability of the recharge in these basins has not been quantified. To estimate the magnitude and distribution of potential recharge in response to variable climate and spatially varying drainage basin characteristics, the INFILv3 model uses a daily water-balance model of the root zone with a primarily deterministic representation of the processes controlling net infiltration and potential recharge. The daily water balance includes precipitation (as either rain or snow), snow accumulation, sublimation, snowmelt, infiltration into the root zone, evapotranspiration, drainage, water content change throughout the root-zone profile (represented as a 6-layered system), runoff (defined as excess rainfall and snowmelt) and surface water run-on (defined as runoff that is routed downstream), and net infiltration (simulated as drainage from the bottom root-zone layer). Potential evapotranspiration is simulated using an hourly solar radiation model to simulate daily net radiation, and daily evapotranspiration is simulated as an empirical function of root zone water content and potential evapotranspiration. The model uses daily climate records of precipitation and air temperature from a regionally distributed network of 132 climate stations and a spatially distributed representation of drainage basin characteristics defined by topography, geology, soils, and vegetation to simulate daily net infiltration at all locations, including stream channels with intermittent streamflow in response to runoff from rain and snowmelt. The temporal distribution of daily, monthly, and annual net infiltration can be used to evaluate the potential effect of future climatic conditions on potential recharge. The INFILv3 model inputs representing drainage basin characteristics were developed using a geographic information system (GIS) to define a set of spatially distributed input parameters uniquely assigned to each grid cell of the INFILv3 model grid. The model grid, which was defined by a digital elevation model (DEM) of the Death Valley region, consists of 1,252,418 model grid cells with a uniform grid cell dimension of 278.5 meters in the north-south and east-west directions. The elevation values from the DEM were used with monthly regression models developed from the daily climate data to estimate the spatial distribution of daily precipitation and air temperature. The elevation values were also used to simulate atmosp

Respiration and heartbeat monitoring using a distributed pulsed MIMO radar.

PubMed

Walterscheid, Ingo; Smith, Graeme E

2017-07-01

This paper addresses non-contact monitoring of physiological signals induced by respiration and heartbeat. To detect the tiny physiological movements of the chest or other parts of the torso, a Mulitple-Input Multiple-Output (MIMO) radar is used. The spatially distributed transmitters and receivers are able to detect the chest surface movements of one or multiple persons in a room. Due to several bistatic measurements at the same time a robust detection and measuring of the breathing and heartbeat rate is possible. Using an appropriate geometrical configuration of the sensors even a localization of the person is feasible.

The pitch-heave dynamics of transportation vehicles

NASA Technical Reports Server (NTRS)

Sweet, L. M.; Richardson, H. H.

1975-01-01

The analysis and design of suspensions for vehicles of finite length using pitch-heave models is presented. Dynamic models for the finite length vehicle include the spatial distribution of the guideway input disturbance over the vehicle length, as well as both pitch and heave degrees-of-freedom. Analytical results relate the vehicle front and rear accelerations to the pitch and heave natural frequencies, which are functions of vehicle suspension geometry and mass distribution. The effects of vehicle asymmetry and suspension contact area are evaluated. Design guidelines are presented for the modification of vehicle and suspension parameters to meet alternative ride quality criteria.

A geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling

NASA Astrophysics Data System (ADS)

Dai, Heng; Chen, Xingyuan; Ye, Ming; Song, Xuehang; Zachara, John M.

2017-05-01

Sensitivity analysis is an important tool for development and improvement of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study, we developed a new sensitivity analysis method that integrates the concept of variance-based method with a hierarchical uncertainty quantification framework. Different uncertain inputs are grouped and organized into a multilayer framework based on their characteristics and dependency relationships to reduce the dimensionality of the sensitivity analysis. A set of new sensitivity indices are defined for the grouped inputs using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially distributed input variables.

A Geostatistics-Informed Hierarchical Sensitivity Analysis Method for Complex Groundwater Flow and Transport Modeling

NASA Astrophysics Data System (ADS)

Dai, H.; Chen, X.; Ye, M.; Song, X.; Zachara, J. M.

2017-12-01

Sensitivity analysis is an important tool for development and improvement of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study we developed a new sensitivity analysis method that integrates the concept of variance-based method with a hierarchical uncertainty quantification framework. Different uncertain inputs are grouped and organized into a multi-layer framework based on their characteristics and dependency relationships to reduce the dimensionality of the sensitivity analysis. A set of new sensitivity indices are defined for the grouped inputs using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially-distributed input variables.

QKD Via a Quantum Wavelength Router Using Spatial Soliton

NASA Astrophysics Data System (ADS)

Kouhnavard, M.; Amiri, I. S.; Afroozeh, A.; Jalil, M. A.; Ali, J.; Yupapin, P. P.

2011-05-01

A system for continuous variable quantum key distribution via a wavelength router is proposed. The Kerr type of light in the nonlinear microring resonator (NMRR) induces the chaotic behavior. In this proposed system chaotic signals are generated by an optical soliton or Gaussian pulse within a NMRR system. The parameters, such as input power, MRRs radii and coupling coefficients can change and plays important role in determining the results in which the continuous signals are generated spreading over the spectrum. Large bandwidth signals of optical soliton are generated by the input pulse propagating within the MRRs, which is allowed to form the continuous wavelength or frequency with large tunable channel capacity. The continuous variable QKD is formed by using the localized spatial soliton pulses via a quantum router and networks. The selected optical spatial pulse can be used to perform the secure communication network. Here the entangled photon generated by chaotic signals has been analyzed. The continuous entangled photon is generated by using the polarization control unit incorporating into the MRRs, required to provide the continuous variable QKD. Results obtained have shown that the application of such a system for the simultaneous continuous variable quantum cryptography can be used in the mobile telephone hand set and networks. In this study frequency band of 500 MHz and 2.0 GHz and wavelengths of 775 nm, 2,325 nm and 1.55 μm can be obtained for QKD use with input optical soliton and Gaussian beam respectively.

Impact of input data uncertainty on environmental exposure assessment models: A case study for electromagnetic field modelling from mobile phone base stations.

PubMed

Beekhuizen, Johan; Heuvelink, Gerard B M; Huss, Anke; Bürgi, Alfred; Kromhout, Hans; Vermeulen, Roel

2014-11-01

With the increased availability of spatial data and computing power, spatial prediction approaches have become a standard tool for exposure assessment in environmental epidemiology. However, such models are largely dependent on accurate input data. Uncertainties in the input data can therefore have a large effect on model predictions, but are rarely quantified. With Monte Carlo simulation we assessed the effect of input uncertainty on the prediction of radio-frequency electromagnetic fields (RF-EMF) from mobile phone base stations at 252 receptor sites in Amsterdam, The Netherlands. The impact on ranking and classification was determined by computing the Spearman correlations and weighted Cohen's Kappas (based on tertiles of the RF-EMF exposure distribution) between modelled values and RF-EMF measurements performed at the receptor sites. The uncertainty in modelled RF-EMF levels was large with a median coefficient of variation of 1.5. Uncertainty in receptor site height, building damping and building height contributed most to model output uncertainty. For exposure ranking and classification, the heights of buildings and receptor sites were the most important sources of uncertainty, followed by building damping, antenna- and site location. Uncertainty in antenna power, tilt, height and direction had a smaller impact on model performance. We quantified the effect of input data uncertainty on the prediction accuracy of an RF-EMF environmental exposure model, thereby identifying the most important sources of uncertainty and estimating the total uncertainty stemming from potential errors in the input data. This approach can be used to optimize the model and better interpret model output. Copyright © 2014 Elsevier Inc. All rights reserved.

Soil process-oriented modelling of within-field variability based on high-resolution 3D soil type distribution maps.

NASA Astrophysics Data System (ADS)

Bönecke, Eric; Lück, Erika; Gründling, Ralf; Rühlmann, Jörg; Franko, Uwe

2016-04-01

Today, the knowledge of within-field variability is essential for numerous purposes, including practical issues, such as precision and sustainable soil management. Therefore, process-oriented soil models have been applied for a considerable time to answer question of spatial soil nutrient and water dynamics, although, they can only be as consistent as their variation and resolution of soil input data. Traditional approaches, describe distribution of soil types, soil texture or other soil properties for greater soil units through generalised point information, e.g. from classical soil survey maps. Those simplifications are known to be afflicted with large uncertainties. Varying soil, crop or yield conditions are detected even within such homogenised soil units. However, recent advances of non-invasive soil survey and on-the-go monitoring techniques, made it possible to obtain vertical and horizontal dense information (3D) about various soil properties, particularly soil texture distribution which serves as an essential soil key variable affecting various other soil properties. Thus, in this study we based our simulations on detailed 3D soil type distribution (STD) maps (4x4 m) to adjacently built-up sufficient informative soil profiles including various soil physical and chemical properties. Our estimates of spatial STD are based on high-resolution lateral and vertical changes of electrical resistivity (ER), detected by a relatively new multi-sensor on-the-go ER monitoring device. We performed an algorithm including fuzzy-c-mean (FCM) logic and traditional soil classification to estimate STD from those inverted and layer-wise available ER data. STD is then used as key input parameter for our carbon, nitrogen and water transport model. We identified Pedological horizon depths and inferred hydrological soil variables (field capacity, permanent wilting point) from pedotransferfunctions (PTF) for each horizon. Furthermore, the spatial distribution of soil organic carbon (SOC), as essential input variable, was predicted by measured soil samples and associated to STD of the upper 30 cm. The comprehensive and high-resolution (4x4 m) soil profile information (up to 2 m soil depth) were then used to initialise a soil process model (Carbon and Nitrogen Dynamics - CANDY) for soil functional modelling (daily steps of matter fluxes, soil temperature and water balances). Our study was conducted on a practical field (~32,000 m²) of an agricultural farm in Central Germany with Chernozem soils under arid conditions (average rainfall < 550 mm). This soil region is known to have differences in soil structure mainly occurring within the subsoil, since topsoil conditions are described as homogenous. The modelled soil functions considered local climate information and practical farming activities. Results show, as expected, distinguished functional variability, both on spatial and temporal resolution for subsoil evident structures, e.g. visible differences for available water capacity within 0-100 cm but homogenous conditions for the topsoil.

Motor–sensory convergence in object localization: a comparative study in rats and humans

PubMed Central

Horev, Guy; Saig, Avraham; Knutsen, Per Magne; Pietr, Maciej; Yu, Chunxiu; Ahissar, Ehud

2011-01-01

In order to identify basic aspects in the process of tactile perception, we trained rats and humans in similar object localization tasks and compared the strategies used by the two species. We found that rats integrated temporally related sensory inputs (‘temporal inputs’) from early whisk cycles with spatially related inputs (‘spatial inputs’) to align their whiskers with the objects; their perceptual reports appeared to be based primarily on this spatial alignment. In a similar manner, human subjects also integrated temporal and spatial inputs, but relied mainly on temporal inputs for object localization. These results suggest that during tactile object localization, an iterative motor–sensory process gradually converges on a stable percept of object location in both species. PMID:21969688

Using pixel intensity as a self-regulating threshold for deterministic image sampling in Milano Retinex: the T-Rex algorithm

NASA Astrophysics Data System (ADS)

Lecca, Michela; Modena, Carla Maria; Rizzi, Alessandro

2018-01-01

Milano Retinexes are spatial color algorithms, part of the Retinex family, usually employed for image enhancement. They modify the color of each pixel taking into account the surrounding colors and their position, catching in this way the local spatial color distribution relevant to image enhancement. We present T-Rex (from the words threshold and Retinex), an implementation of Milano Retinex, whose main novelty is the use of the pixel intensity as a self-regulating threshold to deterministically sample local color information. The experiments, carried out on real-world pictures, show that T-Rex image enhancement performance are in line with those of the Milano Retinex family: T-Rex increases the brightness, the contrast, and the flatness of the channel distributions of the input image, making more intelligible the content of pictures acquired under difficult light conditions.

Spatial distribution of mercury in southeastern Alaskan streams influenced by glaciers, wetlands, and salmon

USGS Publications Warehouse

Nagorski, Sonia A.; Engstrom, Daniel R.; Hudson, John P.; Krabbenhoft, David P.; Hood, Eran; DeWild, John F.; Aiken, George R.

2014-01-01

Southeastern Alaska is a remote coastal-maritime ecosystem that is experiencing increased deposition of mercury (Hg) as well as rapid glacier loss. Here we present the results of the first reported survey of total and methyl Hg (MeHg) concentrations in regional streams and biota. Overall, streams draining large wetland areas had higher Hg concentrations in water, mayflies, and juvenile salmon than those from glacially-influenced or recently deglaciated watersheds. Filtered MeHg was positively correlated with wetland abundance. Aqueous Hg occurred predominantly in the particulate fraction of glacier streams but in the filtered fraction of wetland-rich streams. Colonization by anadromous salmon in both glacier and wetland-rich streams may be contributing additional marine-derived Hg. The spatial distribution of Hg in the range of streams presented here shows that watersheds are variably, yet fairly predictably, sensitive to atmospheric and marine inputs of Hg.

Optical signal processing of spatially distributed sensor data in smart structures

NASA Technical Reports Server (NTRS)

Bennett, K. D.; Claus, R. O.; Murphy, K. A.; Goette, A. M.

1989-01-01

Smart structures which contain dense two- or three-dimensional arrays of attached or embedded sensor elements inherently require signal multiplexing and processing capabilities to permit good spatial data resolution as well as the adequately short calculation times demanded by real time active feedback actuator drive circuitry. This paper reports the implementation of an in-line optical signal processor and its application in a structural sensing system which incorporates multiple discrete optical fiber sensor elements. The signal processor consists of an array of optical fiber couplers having tailored s-parameters and arranged to allow gray code amplitude scaling of sensor inputs. The use of this signal processor in systems designed to indicate the location of distributed strain and damage in composite materials, as well as to quantitatively characterize that damage, is described. Extension of similar signal processing methods to more complicated smart materials and structures applications are discussed.

Modification of a rainfall-runoff model for distributed modeling in a GIS and its validation

NASA Astrophysics Data System (ADS)

Nyabeze, W. R.

A rainfall-runoff model, which can be inter-faced with a Geographical Information System (GIS) to integrate definition, measurement, calculating parameter values for spatial features, presents considerable advantages. The modification of the GWBasic Wits Rainfall-Runoff Erosion Model (GWBRafler) to enable parameter value estimation in a GIS (GISRafler) is presented in this paper. Algorithms are applied to estimate parameter values reducing the number of input parameters and the effort to populate them. The use of a GIS makes the relationship between parameter estimates and cover characteristics more evident. This paper has been produced as part of research to generalize the GWBRafler on a spatially distributed basis. Modular data structures are assumed and parameter values are weighted relative to the module area and centroid properties. Modifications to the GWBRafler enable better estimation of low flows, which are typical in drought conditions.

Geostatistical borehole image-based mapping of karst-carbonate aquifer pores

USGS Publications Warehouse

Michael Sukop,; Cunningham, Kevin J.

2016-01-01

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

Distribution of soil selenium in China is potentially controlled by deposition and volatilization?

PubMed Central

Sun, Guo-Xin; Meharg, Andrew A.; Li, Gang; Chen, Zheng; Yang, Lei; Chen, Song-Can; Zhu, Yong-Guan

2016-01-01

Elucidating the environmental drivers of selenium (Se) spatial distribution in soils at a continental scale is essential to better understand it’s biogeochemical cycling to improve Se transfer into diets. Through modelling Se biogeochemistry in China we found that deposition and volatilization are key factors controlling distribution in surface soil, rather than bedrock-derived Se (<0.1 mg/kg). Wet deposition associated with the East Asian summer monsoon, and dry deposition associated with the East Asian winter monsoon, are responsible for dominant Se inputs into northwest and southeast China, respectively. In Central China the rate of soil Se volatilization is similar to that of Se deposition, suggesting that Se volatilization offsets it’s deposition, resulting in negligible net Se input in soil. Selenium in surface soil at Central China is roughly equal to low petrogenic Se, which is the main reason for the presence of the Se poor belt. We suggest that both deposition and volatilization of Se could play a key role in Se balance in other terrestrial environments worldwide. PMID:26883576

Effects of uncertain topographic input data on two-dimensional flow modeling in a gravel-bed river

USGS Publications Warehouse

Legleiter, C.J.; Kyriakidis, P.C.; McDonald, R.R.; Nelson, J.M.

2011-01-01

Many applications in river research and management rely upon two-dimensional (2D) numerical models to characterize flow fields, assess habitat conditions, and evaluate channel stability. Predictions from such models are potentially highly uncertain due to the uncertainty associated with the topographic data provided as input. This study used a spatial stochastic simulation strategy to examine the effects of topographic uncertainty on flow modeling. Many, equally likely bed elevation realizations for a simple meander bend were generated and propagated through a typical 2D model to produce distributions of water-surface elevation, depth, velocity, and boundary shear stress at each node of the model's computational grid. Ensemble summary statistics were used to characterize the uncertainty associated with these predictions and to examine the spatial structure of this uncertainty in relation to channel morphology. Simulations conditioned to different data configurations indicated that model predictions became increasingly uncertain as the spacing between surveyed cross sections increased. Model sensitivity to topographic uncertainty was greater for base flow conditions than for a higher, subbankfull flow (75% of bankfull discharge). The degree of sensitivity also varied spatially throughout the bend, with the greatest uncertainty occurring over the point bar where the flow field was influenced by topographic steering effects. Uncertain topography can therefore introduce significant uncertainty to analyses of habitat suitability and bed mobility based on flow model output. In the presence of such uncertainty, the results of these studies are most appropriately represented in probabilistic terms using distributions of model predictions derived from a series of topographic realizations. Copyright 2011 by the American Geophysical Union.

Generating Within-Plant Spatial Distributions of an Insect Herbivore Based on Aggregation Patterns and Per-Node Infestation Probabilities.

PubMed

Rincon, Diego F; Hoy, Casey W; Cañas, Luis A

2015-04-01

Most predator-prey models extrapolate functional responses from small-scale experiments assuming spatially uniform within-plant predator-prey interactions. However, some predators focus their search in certain plant regions, and herbivores tend to select leaves to balance their nutrient uptake and exposure to plant defenses. Individual-based models that account for heterogeneous within-plant predator-prey interactions can be used to scale-up functional responses, but they would require the generation of explicit prey spatial distributions within-plant architecture models. The silverleaf whitefly, Bemisia tabaci biotype B (Gennadius) (Hemiptera: Aleyrodidae), is a significant pest of tomato crops worldwide that exhibits highly aggregated populations at several spatial scales, including within the plant. As part of an analytical framework to understand predator-silverleaf whitefly interactions, the objective of this research was to develop an algorithm to generate explicit spatial counts of silverleaf whitefly nymphs within tomato plants. The algorithm requires the plant size and the number of silverleaf whitefly individuals to distribute as inputs, and includes models that describe infestation probabilities per leaf nodal position and the aggregation pattern of the silverleaf whitefly within tomato plants and leaves. The output is a simulated number of silverleaf whitefly individuals for each leaf and leaflet on one or more plants. Parameter estimation was performed using nymph counts per leaflet censused from 30 artificially infested tomato plants. Validation revealed a substantial agreement between algorithm outputs and independent data that included the distribution of counts of both eggs and nymphs. This algorithm can be used in simulation models that explore the effect of local heterogeneity on whitefly-predator dynamics. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

cluster trials v. 1.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mitchell, John; Castillo, Andrew

2016-09-21

This software contains a set of python modules – input, search, cluster, analysis; these modules read input files containing spatial coordinates and associated attributes which can be used to perform nearest neighbor search (spatial indexing via kdtree), cluster analysis/identification, and calculation of spatial statistics for analysis.

Quantifying the Number of Discriminable Coincident Dendritic Input Patterns through Dendritic Tree Morphology

PubMed Central

Zippo, Antonio G.; Biella, Gabriele E. M.

2015-01-01

Current developments in neuronal physiology are unveiling novel roles for dendrites. Experiments have shown mechanisms of non-linear synaptic NMDA dependent activations, able to discriminate input patterns through the waveforms of the excitatory postsynaptic potentials. Contextually, the synaptic clustering of inputs is the principal cellular strategy to separate groups of common correlated inputs. Dendritic branches appear to work as independent discriminating units of inputs potentially reflecting an extraordinary repertoire of pattern memories. However, it is unclear how these observations could impact our comprehension of the structural correlates of memory at the cellular level. This work investigates the discrimination capabilities of neurons through computational biophysical models to extract a predicting law for the dendritic input discrimination capability (M). By this rule we compared neurons from a neuron reconstruction repository (neuromorpho.org). Comparisons showed that primate neurons were not supported by an equivalent M preeminence and that M is not uniformly distributed among neuron types. Remarkably, neocortical neurons had substantially less memory capacity in comparison to those from non-cortical regions. In conclusion, the proposed rule predicts the inherent neuronal spatial memory gathering potentially relevant anatomical and evolutionary considerations about the brain cytoarchitecture. PMID:26100354

Prediction of hourly PM2.5 using a space-time support vector regression model

NASA Astrophysics Data System (ADS)

Yang, Wentao; Deng, Min; Xu, Feng; Wang, Hang

2018-05-01

Real-time air quality prediction has been an active field of research in atmospheric environmental science. The existing methods of machine learning are widely used to predict pollutant concentrations because of their enhanced ability to handle complex non-linear relationships. However, because pollutant concentration data, as typical geospatial data, also exhibit spatial heterogeneity and spatial dependence, they may violate the assumptions of independent and identically distributed random variables in most of the machine learning methods. As a result, a space-time support vector regression model is proposed to predict hourly PM2.5 concentrations. First, to address spatial heterogeneity, spatial clustering is executed to divide the study area into several homogeneous or quasi-homogeneous subareas. To handle spatial dependence, a Gauss vector weight function is then developed to determine spatial autocorrelation variables as part of the input features. Finally, a local support vector regression model with spatial autocorrelation variables is established for each subarea. Experimental data on PM2.5 concentrations in Beijing are used to verify whether the results of the proposed model are superior to those of other methods.

Spatial pulses of water inputs in deciduous and hemlock forest stands

NASA Astrophysics Data System (ADS)

Guswa, A. J.; Mussehl, M.; Pecht, A.; Spence, C.

2010-12-01

Trees intercept and redistribute precipitation in time and space. While spatial patterns of throughfall are challenging to link to plant and canopy characteristics, many studies have shown that the spatial patterns persist through time. This persistence leads to wet and dry spots under the trees, creating spatial pulses of moisture that can affect infiltration, transpiration, and biogeochemical processes. In the northeast, the invasive hemlock woolly adelgid poses a significant threat to eastern hemlock (Tsuga canadensis), and replacement of hemlock forests by other species, such as birch, maple, and oak, has the potential to alter throughfall patterns and hydrologic processes. During the summers of 2009 and 2010, we measured throughfall in both hemlock and deciduous plots to assess its spatial distribution and temporal persistence. From 3 June to 25 July 2009, we measured throughfall in one hemlock and one deciduous plot over fourteen events with rainfall totaling 311 mm. From 8 June through 28 July 2010, we measured throughfall in the same two plots plus an additional hemlock stand and a young black birch stand, and rainfall totaled 148 mm over eight events. Averaged over space and time, throughfall was 81% of open precipitation in the hemlock stands, 88% in the mixed deciduous stand, and 100% in the young black birch stand. On an event basis, spatial coefficients of variation are similar among the stands and range from 11% to 49% for rain events greater than 5 mm. With the exception of very light events, coefficients of variation are insensitive to precipitation amount. Spatial patterns of throughfall persist through time, and seasonal coefficients of variation range from 13% to 33%. All stands indicate localized concentrations of water inputs, and there were individual collectors in the deciduous stands that regularly received more than twice the stand-average throughfall.

Development of a Sediment Transport Component for DHSVM

NASA Astrophysics Data System (ADS)

Doten, C. O.; Bowling, L. C.; Maurer, E. P.; Voisin, N.; Lettenmaier, D. P.

2003-12-01

The effect of forest management and disturbance on aquatic resources is a problem of considerable, contemporary, scientific and public concern in the West. Sediment generation is one of the factors linking land surface conditions with aquatic systems, with implications for fisheries protection and enhancement. Better predictive techniques that allow assessment of the effects of fire and logging, in particular, on sediment transport could help to provide a more scientific basis for the management of forests in the West. We describe the development of a sediment transport component for the Distributed Hydrology Soil Vegetation Model (DHSVM), a spatially distributed hydrologic model that was developed specifically for assessment of the hydrologic consequences of forest management. The sediment transport module extends the hydrologic dynamics of DHSVM to predict sediment generation in response to dynamic meteorological inputs and hydrologic conditions via mass wasting and surface erosion from forest roads and hillslopes. The mass wasting component builds on existing stochastic slope stability models, by incorporating distributed basin hydrology (from DHSVM), and post-failure, rule-based redistribution of sediment downslope. The stochastic nature of the mass wasting component allows specification of probability distributions that describe the spatial variability of soil and vegetation characteristics used in the infinite slope model. The forest roads and hillslope surface erosion algorithms account for erosion from rain drop impact and overland erosion. A simple routing scheme is used to transport eroded sediment from mass wasting and forest roads surface erosion that reaches the channel system to the basin outlet. A sensitivity analysis of the model input parameters and forest cover conditions is described for the Little Wenatchee River basin in the northeastern Washington Cascades.

Validating a spatially distributed hydrological model with soil morphology data

NASA Astrophysics Data System (ADS)

Doppler, T.; Honti, M.; Zihlmann, U.; Weisskopf, P.; Stamm, C.

2014-09-01

Spatially distributed models are popular tools in hydrology claimed to be useful to support management decisions. Despite the high spatial resolution of the computed variables, calibration and validation is often carried out only on discharge time series at specific locations due to the lack of spatially distributed reference data. Because of this restriction, the predictive power of these models, with regard to predicted spatial patterns, can usually not be judged. An example of spatial predictions in hydrology is the prediction of saturated areas in agricultural catchments. These areas can be important source areas for inputs of agrochemicals to the stream. We set up a spatially distributed model to predict saturated areas in a 1.2 km2 catchment in Switzerland with moderate topography and artificial drainage. We translated soil morphological data available from soil maps into an estimate of the duration of soil saturation in the soil horizons. This resulted in a data set with high spatial coverage on which the model predictions were validated. In general, these saturation estimates corresponded well to the measured groundwater levels. We worked with a model that would be applicable for management decisions because of its fast calculation speed and rather low data requirements. We simultaneously calibrated the model to observed groundwater levels and discharge. The model was able to reproduce the general hydrological behavior of the catchment in terms of discharge and absolute groundwater levels. However, the the groundwater level predictions were not accurate enough to be used for the prediction of saturated areas. Groundwater level dynamics were not adequately reproduced and the predicted spatial saturation patterns did not correspond to those estimated from the soil map. Our results indicate that an accurate prediction of the groundwater level dynamics of the shallow groundwater in our catchment that is subject to artificial drainage would require a model that better represents processes at the boundary between the unsaturated and the saturated zone. However, data needed for such a more detailed model are not generally available. This severely hampers the practical use of such models despite their usefulness for scientific purposes.

Distributed snow modeling suitable for use with operational data for the American River watershed.

NASA Astrophysics Data System (ADS)

Shamir, E.; Georgakakos, K. P.

2004-12-01

The mountainous terrain of the American River watershed (~4300 km2) at the Western slope of the Northern Sierra Nevada is subject to significant variability in the atmospheric forcing that controls the snow accumulation and ablations processes (i.e., precipitation, surface temperature, and radiation). For a hydrologic model that attempts to predict both short- and long-term streamflow discharges, a plausible description of the seasonal and intermittent winter snow pack accumulation and ablation is crucial. At present the NWS-CNRFC operational snow model is implemented in a semi distributed manner (modeling unit of about 100-1000 km2) and therefore lump distinct spatial variability of snow processes. In this study we attempt to account for the precipitation, temperature, and radiation spatial variability by constructing a distributed snow accumulation and melting model suitable for use with commonly available sparse data. An adaptation of the NWS-Snow17 energy and mass balance that is used operationally at the NWS River Forecast Centers is implemented at 1 km2 grid cells with distributed input and model parameters. The input to the model (i.e., precipitation and surface temperature) is interpolated from observed point data. The surface temperature was interpolated over the basin based on adiabatic lapse rates using topographic information whereas the precipitation was interpolated based on maps of climatic mean annual rainfall distribution acquired from PRISM. The model parameters that control the melting rate due to radiation were interpolated based on aspect. The study was conducted for the entire American basin for the snow seasons of 1999-2000. Validation of the Snow Water Equivalent (SWE) prediction is done by comparing to observation from 12 snow Sensors. The Snow Cover Area (SCA) prediction was evaluated by comparing to remotely sensed 500m daily snow cover derived from MODIS. The results that the distribution of snow over the area is well captured and the quantity compared to the snow gauges are well estimated in the high elevation.

Distribution and sources of carbon, nitrogen, phosphorus and biogenic silica in the sediments of Chilika lagoon

NASA Astrophysics Data System (ADS)

Nazneen, Sadaf; Raju, N. Janardhana

2017-02-01

The present study investigated the spatial and vertical distribution of organic carbon (OC), total nitrogen (TN), total phosphorus (TP) and biogenic silica (BSi) in the sedimentary environments of Asia's largest brackish water lagoon. Surface and core sediments were collected from various locations of the Chilika lagoon and were analysed for grain-size distribution and major elements in order to understand their distribution and sources. Sand is the dominant fraction followed by silt + clay. Primary production within the lagoon, terrestrial input from river discharge and anthropogenic activities in the vicinity of the lagoon control the distribution of OC, TN, TP and BSi in the surface as well as in the core sediments. Low C/N ratios in the surface sediments (3.49-3.41) and cores (4-11.86) suggest that phytoplankton and macroalgae may be major contributors of organic matter (OM) in the lagoon. BSi is mainly associated with the mud fraction. Core C5 from Balugaon region shows the highest concentration of OC ranging from 0.58-2.34%, especially in the upper 30 cm, due to direct discharge of large amounts of untreated sewage into the lagoon. The study highlights that Chilika is a dynamic ecosystem with a large contribution of OM by autochthonous sources with some input from anthropogenic sources as well.

Analytically-derived sensitivities in one-dimensional models of solute transport in porous media

USGS Publications Warehouse

Knopman, D.S.

1987-01-01

Analytically-derived sensitivities are presented for parameters in one-dimensional models of solute transport in porous media. Sensitivities were derived by direct differentiation of closed form solutions for each of the odel, and by a time integral method for two of the models. Models are based on the advection-dispersion equation and include adsorption and first-order chemical decay. Boundary conditions considered are: a constant step input of solute, constant flux input of solute, and exponentially decaying input of solute at the upstream boundary. A zero flux is assumed at the downstream boundary. Initial conditions include a constant and spatially varying distribution of solute. One model simulates the mixing of solute in an observation well from individual layers in a multilayer aquifer system. Computer programs produce output files compatible with graphics software in which sensitivities are plotted as a function of either time or space. (USGS)

Attributing Crop Production in the United States Using Artificial Neural Network

NASA Astrophysics Data System (ADS)

Ma, Y.; Zhang, Z.; Pan, B.

2017-12-01

Crop production plays key role in supporting life, economy and shaping environment. It is on one hand influenced by natural factors including precipitation, temperature, energy, and on the other hand shaped by the investment of fertilizers, pesticides and human power. Successful attributing of crop production to different factors can help optimize resources and improve productivity. Based on the meteorological records from National Center for Environmental Prediction and state-wise crop production related data provided by the United States Department of Agriculture Economic Research Service, an artificial neural network was constructed to connect crop production with precipitation and temperature anormlies, capital input, labor input, energy input, pesticide consumption and fertilizer consumption. Sensitivity analysis were carried out to attribute their specific influence on crop production for each grid. Results confirmed that the listed factors can generally determine the crop production. Different state response differently to the pertubation of predictands. Their spatial distribution is visulized and discussed.

Comparison of MODIS and SWAT evapotranspiration over a complex terrain at different spatial scales

NASA Astrophysics Data System (ADS)

Abiodun, Olanrewaju O.; Guan, Huade; Post, Vincent E. A.; Batelaan, Okke

2018-05-01

In most hydrological systems, evapotranspiration (ET) and precipitation are the largest components of the water balance, which are difficult to estimate, particularly over complex terrain. In recent decades, the advent of remotely sensed data based ET algorithms and distributed hydrological models has provided improved spatially upscaled ET estimates. However, information on the performance of these methods at various spatial scales is limited. This study compares the ET from the MODIS remotely sensed ET dataset (MOD16) with the ET estimates from a SWAT hydrological model on graduated spatial scales for the complex terrain of the Sixth Creek Catchment of the Western Mount Lofty Ranges, South Australia. ET from both models was further compared with the coarser-resolution AWRA-L model at catchment scale. The SWAT model analyses are performed on daily timescales with a 6-year calibration period (2000-2005) and 7-year validation period (2007-2013). Differences in ET estimation between the SWAT and MOD16 methods of up to 31, 19, 15, 11 and 9 % were observed at respectively 1, 4, 9, 16 and 25 km2 spatial resolutions. Based on the results of the study, a spatial scale of confidence of 4 km2 for catchment-scale evapotranspiration is suggested in complex terrain. Land cover differences, HRU parameterisation in AWRA-L and catchment-scale averaging of input climate data in the SWAT semi-distributed model were identified as the principal sources of weaker correlations at higher spatial resolution.

Dem Local Accuracy Patterns in Land-Use/Land-Cover Classification

NASA Astrophysics Data System (ADS)

Katerji, Wassim; Farjas Abadia, Mercedes; Morillo Balsera, Maria del Carmen

2016-01-01

Global and nation-wide DEM do not preserve the same height accuracy throughout the area of study. Instead of assuming a single RMSE value for the whole area, this study proposes a vario-model that divides the area into sub-regions depending on the land-use / landcover (LULC) classification, and assigns a local accuracy per each zone, as these areas share similar terrain formation and roughness, and tend to have similar DEM accuracies. A pilot study over Lebanon using the SRTM and ASTER DEMs, combined with a set of 1,105 randomly distributed ground control points (GCPs) showed that even though the inputDEMs have different spatial and temporal resolution, and were collected using difierent techniques, their accuracy varied similarly when changing over difierent LULC classes. Furthermore, validating the generated vario-models proved that they provide a closer representation of the accuracy to the validating GCPs than the conventional RMSE, by 94% and 86% for the SRTMand ASTER respectively. Geostatistical analysis of the input and output datasets showed that the results have a normal distribution, which support the generalization of the proven hypothesis, making this finding applicable to other input datasets anywhere around the world.

Feedback Loop of Data Infilling Using Model Result of Actual Evapotranspiration from Satellites and Hydrological Model

NASA Astrophysics Data System (ADS)

Murdi Hartanto, Isnaeni; Alexandridis, Thomas K.; van Andel, Schalk Jan; Solomatine, Dimitri

2014-05-01

Using satellite data in a hydrological model has long been occurring in modelling of hydrological processes, as a source of low cost regular data. The methods range from using satellite products as direct input, model validation, and data assimilation. However, the satellite data frequently face the missing value problem, whether due to the cloud cover or the limited temporal coverage. The problem could seriously affect its usefulness in hydrological model, especially if the model uses it as direct input, so data infilling becomes one of the important parts in the whole modelling exercise. In this research, actual evapotranspiration product from satellite is directly used as input into a spatially distributed hydrological model, and validated by comparing the catchment's end discharge with measured data. The instantaneous actual evapotranspiration is estimated from MODIS satellite images using a variation of the energy balance model for land (SEBAL). The eight-day cumulative actual evapotranspiration is then obtained by a temporal integration that uses the reference evapotranspiration calculated from meteorological data [1]. However, the above method cannot fill in a cell if the cell is constantly having no-data value during the eight-day periods. The hydrological model requires full set of data without no-data cells, hence, the no-data cells in the satellite's evapotranspiration map need to be filled in. In order to fills the no-data cells, an output of hydrological model is used. The hydrological model is firstly run with reference evapotranspiration as input to calculate discharge and actual evapotranspiration. The no-data cells in the eight-day cumulative map from the satellite are then filled in with the output of the first run of hydrological model. The final data is then used as input in a hydrological model to calculate discharge, thus creating a loop. The method is applied in the case study of Rijnland, the Netherlands where in the winter, cloud cover is persistent and leads to many no-data cells in the satellite products. The Rijnland area is a low-lying area with tight water system control. The satellite data is used as input in a SIMGRO model, a spatially distributed hydrological model that is able to handle the controlled water system and that is suitable for the low-lying areas in the Netherlands. The application in the Rijnland area gives overall a good result of total discharge. By using the method, the hydrological model is improved in term of spatial hydrological state, where the original model is only calibrated to discharge in one location. [1] Alexandridis, T.K., Cherif, I., Chemin, Y., Silleos, G.N., Stavrinos, E. & Zalidis, G.C. (2009). Integrated Methodology for Estimating Water Use in Mediterranean Agricultural Areas. Remote Sensing. 1

User interface for ground-water modeling: Arcview extension

USGS Publications Warehouse

Tsou, Ming‐shu; Whittemore, Donald O.

2001-01-01

Numerical simulation for ground-water modeling often involves handling large input and output data sets. A geographic information system (GIS) provides an integrated platform to manage, analyze, and display disparate data and can greatly facilitate modeling efforts in data compilation, model calibration, and display of model parameters and results. Furthermore, GIS can be used to generate information for decision making through spatial overlay and processing of model results. Arc View is the most widely used Windows-based GIS software that provides a robust user-friendly interface to facilitate data handling and display. An extension is an add-on program to Arc View that provides additional specialized functions. An Arc View interface for the ground-water flow and transport models MODFLOW and MT3D was built as an extension for facilitating modeling. The extension includes preprocessing of spatially distributed (point, line, and polygon) data for model input and postprocessing of model output. An object database is used for linking user dialogs and model input files. The Arc View interface utilizes the capabilities of the 3D Analyst extension. Models can be automatically calibrated through the Arc View interface by external linking to such programs as PEST. The efficient pre- and postprocessing capabilities and calibration link were demonstrated for ground-water modeling in southwest Kansas.

Cloud and fog interactions with coastal forests in the California Channel Islands

NASA Astrophysics Data System (ADS)

Still, C. J.; Baguskas, S. A.; Williams, P.; Fischer, D. T.; Carbone, M. S.; Rastogi, B.

2015-12-01

Coastal forests in California are frequently covered by clouds or immersed in fog in the rain-free summer. Scientists have long surmised that fog might provide critical water inputs to these forests. However, until recently, there has been little ecophysiological research to support how or why plants should prefer foggy regions; similarly, there is very little work quantifying water delivered to ecosystems by fog drip except for a few notable sites along the California coast. However, without spatial datasets of summer cloudcover and fog inundation, combined with detailed process studies, questions regarding the roles of cloud shading and fog drip in dictating plant distributions and ecosystem physiology cannot be addressed effectively. The overall objective of this project is to better understand how cloudcover and fog influence forest metabolism, growth, and distribution. Across a range of sites in California's Channel Islands National Park we measured a wide variety of ecosystem processes and properties. We then related these to cloudcover and fog immersion maps created using satellite datasets and airport and radiosonde observations. We compiled a spatially continuous dataset of summertime cloudcover frequency of the Southern California bight using satellite imagery from the NOAA geostationary GOES-11 Imager. We also created map of summertime cloudcover frequency of this area using MODIS imagery. To assess the ability of our mapping approach to predict spatial and temporal fog inundation patterns, we compared our monthly average daytime fog maps for GOES pixels corresponding to stations where fog inputs were measured with fog collectors in a Bishop pine forest. We also compared our cloudcover maps to measurements of irradiance measurements. Our results demonstrate that cloudcover and fog strongly modulate radiation, water, and carbon budgets, as well as forest distributions, in this semi-arid environment. Measurements of summertime fog drip, pine sapflow and growth, and soil respiration are strongly related to variations in cloudcover and fog drip. Importantly, spatial variations in cloud cover and fog immersion drive large changes in modeled water budgets and correspond closely to patterns of tree growth and mortality.

Improving predictive power of physically based rainfall-induced shallow landslide models: a probablistic approach

USGS Publications Warehouse

Raia, S.; Alvioli, M.; Rossi, M.; Baum, R.L.; Godt, J.W.; Guzzetti, F.

2013-01-01

Distributed models to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides are deterministic. These models extend spatially the static stability models adopted in geotechnical engineering and adopt an infinite-slope geometry to balance the resisting and the driving forces acting on the sliding mass. An infiltration model is used to determine how rainfall changes pore-water conditions, modulating the local stability/instability conditions. A problem with the existing models is the difficulty in obtaining accurate values for the several variables that describe the material properties of the slopes. The problem is particularly severe when the models are applied over large areas, for which sufficient information on the geotechnical and hydrological conditions of the slopes is not generally available. To help solve the problem, we propose a probabilistic Monte Carlo approach to the distributed modeling of shallow rainfall-induced landslides. For the purpose, we have modified the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis (TRIGRS) code. The new code (TRIGRS-P) adopts a stochastic approach to compute, on a cell-by-cell basis, transient pore-pressure changes and related changes in the factor of safety due to rainfall infiltration. Infiltration is modeled using analytical solutions of partial differential equations describing one-dimensional vertical flow in isotropic, homogeneous materials. Both saturated and unsaturated soil conditions can be considered. TRIGRS-P copes with the natural variability inherent to the mechanical and hydrological properties of the slope materials by allowing values of the TRIGRS model input parameters to be sampled randomly from a given probability distribution. The range of variation and the mean value of the parameters can be determined by the usual methods used for preparing the TRIGRS input parameters. The outputs of several model runs obtained varying the input parameters are analyzed statistically, and compared to the original (deterministic) model output. The comparison suggests an improvement of the predictive power of the model of about 10% and 16% in two small test areas, i.e. the Frontignano (Italy) and the Mukilteo (USA) areas, respectively. We discuss the computational requirements of TRIGRS-P to determine the potential use of the numerical model to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides in very large areas, extending for several hundreds or thousands of square kilometers. Parallel execution of the code using a simple process distribution and the Message Passing Interface (MPI) on multi-processor machines was successful, opening the possibly of testing the use of TRIGRS-P for the operational forecasting of rainfall-induced shallow landslides over large regions.

Temporal and spatial evolution of nanosecond microwave-driven plasma

NASA Astrophysics Data System (ADS)

Chang, C.; Chen, X. Q.; Zhu, M.; Pu, Y. K.

2018-06-01

In this paper, a method for simultaneously acquiring the temporal and spatial evolution of characteristic plasma spectra in a single microwave pulse is proposed and studied. By using multi-sub-beam fiber bundles coupled with a spectrometer and EMICCD (Electron-multiplying intensified charge-coupled device), the spatial distribution and time evolution of characteristic spectra of desorbed gases at the dielectric/vacuum interface during nanosecond microwave-driven plasma discharge are observed. Arrays of small align tubes punctured with metal walls of feed horn are filled with separate fibers of matched sizes and equal lengths. The output ends of fibers arranged in a single longitudinal column are connected to the entrance slit of a spectrometer, where the optical spectrum inputs to a high-speed EMICCD, to detect the rapid-varying time and space spectra of nanosecond giga-watt microwave discharges. The evolution of spectral clusters of N2 (C-B), N2+ (B-X), and the hydrogen atoms is discovered and monitored. The whole duration of light emission is much longer than the microwave pulse, and the intensities of ion N2+ (B-X) spectra increase after microwave pulses with rise times of 25-50 ns. The brightness distribution of plasma spectra in different space is observed and approximately consistent with the simulated E-field distribution.

Climatological Downscaling and Evaluation of AGRMET Precipitation Analyses Over the Continental U.S.

NASA Astrophysics Data System (ADS)

Garcia, M.; Peters-Lidard, C. D.; Eylander, J. B.; Daly, C.; Tian, Y.; Zeng, J.

2007-05-01

The spatially distributed application of a land surface model (LSM) over a region of interest requires the application of similarly distributed precipitation fields that can be derived from various sources, including surface gauge networks, surface-based radar, and orbital platforms. The spatial variability of precipitation influences the spatial organization of soil temperature and moisture states and, consequently, the spatial variability of land- atmosphere fluxes. The accuracy of spatially-distributed precipitation fields can contribute significantly to the uncertainty of model-based hydrological states and fluxes at the land surface. Collaborations between the Air Force Weather Agency (AFWA), NASA, and Oregon State University have led to improvements in the processing of meteorological forcing inputs for the NASA-GSFC Land Information System (LIS; Kumar et al. 2006), a sophisticated framework for LSM operation and model coupling experiments. Efforts at AFWA toward the production of surface hydrometeorological products are currently in transition from the legacy Agricultural Meteorology modeling system (AGRMET) to use of the LIS framework and procedures. Recent enhancements to meteorological input processing for application to land surface models in LIS include the assimilation of climate-based information for the spatial interpolation and downscaling of precipitation fields. Climatological information included in the LIS-based downscaling procedure for North America is provided by a monthly high-resolution PRISM (Daly et al. 1994, 2002; Daly 2006) dataset based on a 30-year analysis period. The combination of these sources and methods attempts to address the strengths and weaknesses of available legacy products, objective interpolation methods, and the PRISM knowledge-based methodology. All of these efforts are oriented on an operational need for timely estimation of spatial precipitation fields at adequate spatial resolution for customer dissemination and near-real-time simulations in regions of interest. This work focuses on value added to the AGRMET precipitation product by the inclusion of high-quality climatological information on a monthly time scale. The AGRMET method uses microwave-based satellite precipitation estimates from various polar-orbiting platforms (NOAA POES and DMSP), infrared-based estimates from geostationary platforms (GOES, METEOSAT, etc.), related cloud analysis products, and surface gauge observations in a complex and hierarchical blending process. Results from processing of the legacy AGRMET precipitation products over the U.S. using LIS-based methods for downscaling, both with and without climatological factors, are evaluated against high-resolution monthly analyses using the PRISM knowledge- based method (Daly et al. 2002). It is demonstrated that the incorporation of climatological information in a downscaling procedure can significantly enhance the accuracy, and potential utility, of AFWA precipitation products for military and civilian customer applications.

Modelling the spatial distribution of Fasciola hepatica in dairy cattle in Europe.

PubMed

Ducheyne, Els; Charlier, Johannes; Vercruysse, Jozef; Rinaldi, Laura; Biggeri, Annibale; Demeler, Janina; Brandt, Christina; De Waal, Theo; Selemetas, Nikolaos; Höglund, Johan; Kaba, Jaroslaw; Kowalczyk, Slawomir J; Hendrickx, Guy

2015-03-26

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

fMR-adaptation indicates selectivity to audiovisual content congruency in distributed clusters in human superior temporal cortex.

PubMed

van Atteveldt, Nienke M; Blau, Vera C; Blomert, Leo; Goebel, Rainer

2010-02-02

Efficient multisensory integration is of vital importance for adequate interaction with the environment. In addition to basic binding cues like temporal and spatial coherence, meaningful multisensory information is also bound together by content-based associations. Many functional Magnetic Resonance Imaging (fMRI) studies propose the (posterior) superior temporal cortex (STC) as the key structure for integrating meaningful multisensory information. However, a still unanswered question is how superior temporal cortex encodes content-based associations, especially in light of inconsistent results from studies comparing brain activation to semantically matching (congruent) versus nonmatching (incongruent) multisensory inputs. Here, we used fMR-adaptation (fMR-A) in order to circumvent potential problems with standard fMRI approaches, including spatial averaging and amplitude saturation confounds. We presented repetitions of audiovisual stimuli (letter-speech sound pairs) and manipulated the associative relation between the auditory and visual inputs (congruent/incongruent pairs). We predicted that if multisensory neuronal populations exist in STC and encode audiovisual content relatedness, adaptation should be affected by the manipulated audiovisual relation. The results revealed an occipital-temporal network that adapted independently of the audiovisual relation. Interestingly, several smaller clusters distributed over superior temporal cortex within that network, adapted stronger to congruent than to incongruent audiovisual repetitions, indicating sensitivity to content congruency. These results suggest that the revealed clusters contain multisensory neuronal populations that encode content relatedness by selectively responding to congruent audiovisual inputs, since unisensory neuronal populations are assumed to be insensitive to the audiovisual relation. These findings extend our previously revealed mechanism for the integration of letters and speech sounds and demonstrate that fMR-A is sensitive to multisensory congruency effects that may not be revealed in BOLD amplitude per se.

Stability of Spatial Distributions of Stink Bugs, Boll Injury, and NDVI in Cotton.

PubMed

Reay-Jones, Francis P F; Greene, Jeremy K; Bauer, Philip J

2016-10-01

A 3-yr study was conducted to determine the degree of aggregation of stink bugs and boll injury in cotton, Gossypium hirsutum L., and their spatial association with a multispectral vegetation index (normalized difference vegetation index [NDVI]). Using the spatial analysis by distance indices analyses, stink bugs were less frequently aggregated (17% for adults and 4% for nymphs) than boll injury (36%). NDVI values were also significantly aggregated within fields in 19 of 48 analyses (40%), with the majority of significant indices occurring in July and August. Paired NDVI datasets from different sampling dates were frequently associated (86.5% for weekly intervals among datasets). Spatial distributions of both stink bugs and boll injury were less stable than for NDVI, with positive associations varying from 12.5 to 25% for adult stink bugs for weekly intervals, depending on species. Spatial distributions of boll injury from stink bug feeding were more stable than stink bugs, with 46% positive associations among paired datasets with weekly intervals. NDVI values were positively associated with boll injury from stink bug feeding in 11 out of 22 analyses, with no significant negative associations. This indicates that NDVI has potential as a component of site-specific management. Future work should continue to examine the value of remote sensing for insect management in cotton, with an aim to develop tools such as risk assessment maps that will help growers to reduce insecticide inputs. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Three-Dimensional Radiobiologic Dosimetry: Application of Radiobiologic Modeling to Patient-Specific 3-Dimensional Imaging–Based Internal Dosimetry

PubMed Central

Prideaux, Andrew R.; Song, Hong; Hobbs, Robert F.; He, Bin; Frey, Eric C.; Ladenson, Paul W.; Wahl, Richard L.; Sgouros, George

2010-01-01

Phantom-based and patient-specific imaging-based dosimetry methodologies have traditionally yielded mean organ-absorbed doses or spatial dose distributions over tumors and normal organs. In this work, radiobiologic modeling is introduced to convert the spatial distribution of absorbed dose into biologically effective dose and equivalent uniform dose parameters. The methodology is illustrated using data from a thyroid cancer patient treated with radioiodine. Methods Three registered SPECT/CT scans were used to generate 3-dimensional images of radionuclide kinetics (clearance rate) and cumulated activity. The cumulated activity image and corresponding CT scan were provided as input into an EGSnrc-based Monte Carlo calculation: The cumulated activity image was used to define the distribution of decays, and an attenuation image derived from CT was used to define the corresponding spatial tissue density and composition distribution. The rate images were used to convert the spatial absorbed dose distribution to a biologically effective dose distribution, which was then used to estimate a single equivalent uniform dose for segmented volumes of interest. Equivalent uniform dose was also calculated from the absorbed dose distribution directly. Results We validate the method using simple models; compare the dose-volume histogram with a previously analyzed clinical case; and give the mean absorbed dose, mean biologically effective dose, and equivalent uniform dose for an illustrative case of a pediatric thyroid cancer patient with diffuse lung metastases. The mean absorbed dose, mean biologically effective dose, and equivalent uniform dose for the tumor were 57.7, 58.5, and 25.0 Gy, respectively. Corresponding values for normal lung tissue were 9.5, 9.8, and 8.3 Gy, respectively. Conclusion The analysis demonstrates the impact of radiobiologic modeling on response prediction. The 57% reduction in the equivalent dose value for the tumor reflects a high level of dose nonuniformity in the tumor and a corresponding reduced likelihood of achieving a tumor response. Such analyses are expected to be useful in treatment planning for radionuclide therapy. PMID:17504874

Hemifield columns co-opt ocular dominance column structure in human achiasma.

PubMed

Olman, Cheryl A; Bao, Pinglei; Engel, Stephen A; Grant, Andrea N; Purington, Chris; Qiu, Cheng; Schallmo, Michael-Paul; Tjan, Bosco S

2018-01-01

In the absence of an optic chiasm, visual input to the right eye is represented in primary visual cortex (V1) in the right hemisphere, while visual input to the left eye activates V1 in the left hemisphere. Retinotopic mapping In V1 reveals that in each hemisphere left and right visual hemifield representations are overlaid (Hoffmann et al., 2012). To explain how overlapping hemifield representations in V1 do not impair vision, we tested the hypothesis that visual projections from nasal and temporal retina create interdigitated left and right visual hemifield representations in V1, similar to the ocular dominance columns observed in neurotypical subjects (Victor et al., 2000). We used high-resolution fMRI at 7T to measure the spatial distribution of responses to left- and right-hemifield stimulation in one achiasmic subject. T 2 -weighted 2D Spin Echo images were acquired at 0.8mm isotropic resolution. The left eye was occluded. To the right eye, a presentation of flickering checkerboards alternated between the left and right visual fields in a blocked stimulus design. The participant performed a demanding orientation-discrimination task at fixation. A general linear model was used to estimate the preference of voxels in V1 to left- and right-hemifield stimulation. The spatial distribution of voxels with significant preference for each hemifield showed interdigitated clusters which densely packed V1 in the right hemisphere. The spatial distribution of hemifield-preference voxels in the achiasmic subject was stable between two days of testing and comparable in scale to that of human ocular dominance columns. These results are the first in vivo evidence showing that visual hemifield representations interdigitate in achiasmic V1 following a similar developmental course to that of ocular dominance columns in V1 with intact optic chiasm. Copyright © 2017 Elsevier Inc. All rights reserved.

A model for the distribution of dark matter, galaxies, and the intergalactic medium in a cold dark matter-dominated universe

NASA Technical Reports Server (NTRS)

Ryu, Dongsu; Vishniac, Ethan T.; Chiang, Wei-Hwan

1989-01-01

The spatial distribution of the cold-dark-matter (CDM) and baryonic components of CDM-dominated cosmological models are characterized, summarizing the results of recent theoretical investigations. The evolution and distribution of matter in an Einstein-de Sitter universe on length scales small enough so that the Newtonian approximation is valid is followed chronologically, assuming (1) that the galaxies, CDM, and the intergalactic medium (IGM) are coupled by gravity, (2) that galaxies form by taking mass and momentum from the IGM, and (3) that the IGM responds to the energy input from the galaxies. The results of the numerical computations are presented in extensive graphs and discussed in detail.

Spatially Distributed Characterization of Catchment Dynamics Using Travel-Time Distributions

NASA Astrophysics Data System (ADS)

Heße, F.; Zink, M.; Attinger, S.

2015-12-01

The description of storage and transport of both water and solved contaminants in catchments is very difficult due to the high heterogeneity of the subsurface properties that govern their fate. This heterogeneity, combined with a generally limited knowledge about the subsurface, results in high degrees of uncertainty. As a result, stochastic methods are increasingly applied, where the relevant processes are modeled as being random. Within these methods, quantities like the catchment travel or residence time of a water parcel are described using probability density functions (PDF). The derivation of these PDF's is typically done by using the water fluxes and states of the catchment. A successful application of such frameworks is therefore contingent on a good quantification of these fluxes and states across the different spatial scales. The objective of this study is to use travel times for the characterization of an ca. 1000 square kilometer, humid catchment in Central Germany. To determine the states and fluxes, we apply the mesoscale Hydrological Model mHM, a spatially distributed hydrological model to the catchment. Using detailed data of precipitation, land cover, morphology and soil type as inputs, mHM is able to determine fluxes like recharge and evapotranspiration and states like soil moisture as outputs. Using these data, we apply the above theoretical framework to our catchment. By virtue of the aforementioned properties of mHM, we are able to describe the storage and release of water with a high spatial resolution. This allows for a comprehensive description of the flow and transport dynamics taking place in the catchment. The spatial distribution of such dynamics is then compared with land cover and soil moisture maps as well as driving forces like precipitation and temperature to determine the most predictive factors. In addition, we investigate how non-local data like the age distribution of discharge flows are impacted by, and therefore allow to infer, local properties of the catchment.

Single-photon-level quantum image memory based on cold atomic ensembles

PubMed Central

Ding, Dong-Sheng; Zhou, Zhi-Yuan; Shi, Bao-Sen; Guo, Guang-Can

2013-01-01

A quantum memory is a key component for quantum networks, which will enable the distribution of quantum information. Its successful development requires storage of single-photon light. Encoding photons with spatial shape through higher-dimensional states significantly increases their information-carrying capability and network capacity. However, constructing such quantum memories is challenging. Here we report the first experimental realization of a true single-photon-carrying orbital angular momentum stored via electromagnetically induced transparency in a cold atomic ensemble. Our experiments show that the non-classical pair correlation between trigger photon and retrieved photon is retained, and the spatial structure of input and retrieved photons exhibits strong similarity. More importantly, we demonstrate that single-photon coherence is preserved during storage. The ability to store spatial structure at the single-photon level opens the possibility for high-dimensional quantum memories. PMID:24084711

Functional correlates of the lateral and medial entorhinal cortex: objects, path integration and local–global reference frames

PubMed Central

Knierim, James J.; Neunuebel, Joshua P.; Deshmukh, Sachin S.

2014-01-01

The hippocampus receives its major cortical input from the medial entorhinal cortex (MEC) and the lateral entorhinal cortex (LEC). It is commonly believed that the MEC provides spatial input to the hippocampus, whereas the LEC provides non-spatial input. We review new data which suggest that this simple dichotomy between ‘where’ versus ‘what’ needs revision. We propose a refinement of this model, which is more complex than the simple spatial–non-spatial dichotomy. MEC is proposed to be involved in path integration computations based on a global frame of reference, primarily using internally generated, self-motion cues and external input about environmental boundaries and scenes; it provides the hippocampus with a coordinate system that underlies the spatial context of an experience. LEC is proposed to process information about individual items and locations based on a local frame of reference, primarily using external sensory input; it provides the hippocampus with information about the content of an experience. PMID:24366146

Transient deterministic shallow landslide modeling: Requirements for susceptibility and hazard assessments in a GIS framework

USGS Publications Warehouse

Godt, J.W.; Baum, R.L.; Savage, W.Z.; Salciarini, D.; Schulz, W.H.; Harp, E.L.

2008-01-01

Application of transient deterministic shallow landslide models over broad regions for hazard and susceptibility assessments requires information on rainfall, topography and the distribution and properties of hillside materials. We survey techniques for generating the spatial and temporal input data for such models and present an example using a transient deterministic model that combines an analytic solution to assess the pore-pressure response to rainfall infiltration with an infinite-slope stability calculation. Pore-pressures and factors of safety are computed on a cell-by-cell basis and can be displayed or manipulated in a grid-based GIS. Input data are high-resolution (1.8??m) topographic information derived from LiDAR data and simple descriptions of initial pore-pressure distribution and boundary conditions for a study area north of Seattle, Washington. Rainfall information is taken from a previously defined empirical rainfall intensity-duration threshold and material strength and hydraulic properties were measured both in the field and laboratory. Results are tested by comparison with a shallow landslide inventory. Comparison of results with those from static infinite-slope stability analyses assuming fixed water-table heights shows that the spatial prediction of shallow landslide susceptibility is improved using the transient analyses; moreover, results can be depicted in terms of the rainfall intensity and duration known to trigger shallow landslides in the study area.

The overlap between false belief and spatial reorientation in the temporo-parietal junction: The role of input modality and task.

PubMed

Özdem, Ceylan; Brass, Marcel; Van der Cruyssen, Laurens; Van Overwalle, Frank

2017-04-01

Neuroimaging research has demonstrated that the temporo-parietal junction (TPJ) is activated when unexpected stimuli appear in spatial reorientation tasks as well as during thinking about the beliefs of other people triggered by verbal scenarios. While the role of potential common component processes subserved by the TPJ has been extensively studied to explain this common activation, the potential confounding role of input modality (spatial vs. verbal) has been largely ignored. To investigate the role of input modality apart from task processes, we developed a novel spatial false belief task based on moving shapes. We explored the overlap in TPJ activation across this novel task and traditional tasks of spatial reorientation (Posner) and verbal belief (False Belief vs. Photo stories). The results show substantial overlap across the same spatial input modality (both reorientation and false belief) as well as across the common task process (verbal and spatial belief), but no triple overlap. This suggests the potential for an overarching function of the TPJ, with some degree of specialization in different subregions due to modality, function and connectivity. The results are discussed with respect to recent theoretical models of the TPJ.

Catchment-scale Validation of a Physically-based, Post-fire Runoff and Erosion Model

NASA Astrophysics Data System (ADS)

Quinn, D.; Brooks, E. S.; Robichaud, P. R.; Dobre, M.; Brown, R. E.; Wagenbrenner, J.

2017-12-01

The cascading consequences of fire-induced ecological changes have profound impacts on both natural and managed forest ecosystems. Forest managers tasked with implementing post-fire mitigation strategies need robust tools to evaluate the effectiveness of their decisions, particularly those affecting hydrological recovery. Various hillslope-scale interfaces of the physically-based Water Erosion Prediction Project (WEPP) model have been successfully validated for this purpose using fire-effected plot experiments, however these interfaces are explicitly designed to simulate single hillslopes. Spatially-distributed, catchment-scale WEPP interfaces have been developed over the past decade, however none have been validated for post-fire simulations, posing a barrier to adoption for forest managers. In this validation study, we compare WEPP simulations with pre- and post-fire hydrological records for three forested catchments (W. Willow, N. Thomas, and S. Thomas) that burned in the 2011 Wallow Fire in Northeastern Arizona, USA. Simulations were conducted using two approaches; the first using automatically created inputs from an online, spatial, post-fire WEPP interface, and the second using manually created inputs which incorporate the spatial variability of fire effects observed in the field. Both approaches were compared to five years of observed post-fire sediment and flow data to assess goodness of fit.

Learning spatially coherent properties of the visual world in connectionist networks

NASA Astrophysics Data System (ADS)

Becker, Suzanna; Hinton, Geoffrey E.

1991-10-01

In the unsupervised learning paradigm, a network of neuron-like units is presented with an ensemble of input patterns from a structured environment, such as the visual world, and learns to represent the regularities in that input. The major goal in developing unsupervised learning algorithms is to find objective functions that characterize the quality of the network's representation without explicitly specifying the desired outputs of any of the units. The sort of objective functions considered cause a unit to become tuned to spatially coherent features of visual images (such as texture, depth, shading, and surface orientation), by learning to predict the outputs of other units which have spatially adjacent receptive fields. Simulations show that using an information-theoretic algorithm called IMAX, a network can be trained to represent depth by observing random dot stereograms of surfaces with continuously varying disparities. Once a layer of depth-tuned units has developed, subsequent layers are trained to perform surface interpolation of curved surfaces, by learning to predict the depth of one image region based on depth measurements in surrounding regions. An extension of the basic model allows a population of competing neurons to learn a distributed code for disparity, which naturally gives rise to a representation of discontinuities.

An approach for modelling snowcover ablation and snowmelt runoff in cold region environments

NASA Astrophysics Data System (ADS)

Dornes, Pablo Fernando

Reliable hydrological model simulations are the result of numerous complex interactions among hydrological inputs, landscape properties, and initial conditions. Determination of the effects of these factors is one of the main challenges in hydrological modelling. This situation becomes even more difficult in cold regions due to the ungauged nature of subarctic and arctic environments. This research work is an attempt to apply a new approach for modelling snowcover ablation and snowmelt runoff in complex subarctic environments with limited data while retaining integrity in the process representations. The modelling strategy is based on the incorporation of both detailed process understanding and inputs along with information gained from observations of basin-wide streamflow phenomenon; essentially a combination of deductive and inductive approaches. The study was conducted in the Wolf Creek Research Basin, Yukon Territory, using three models, a small-scale physically based hydrological model, a land surface scheme, and a land surface hydrological model. The spatial representation was based on previous research studies and observations, and was accomplished by incorporating landscape units, defined according to topography and vegetation, as the spatial model elements. Comparisons between distributed and aggregated modelling approaches showed that simulations incorporating distributed initial snowcover and corrected solar radiation were able to properly simulate snowcover ablation and snowmelt runoff whereas the aggregated modelling approaches were unable to represent the differential snowmelt rates and complex snowmelt runoff dynamics. Similarly, the inclusion of spatially distributed information in a land surface scheme clearly improved simulations of snowcover ablation. Application of the same modelling approach at a larger scale using the same landscape based parameterisation showed satisfactory results in simulating snowcover ablation and snowmelt runoff with minimal calibration. Verification of this approach in an arctic basin illustrated that landscape based parameters are a feasible regionalisation framework for distributed and physically based models. In summary, the proposed modelling philosophy, based on the combination of an inductive and deductive reasoning, is a suitable strategy for reliable predictions of snowcover ablation and snowmelt runoff in cold regions and complex environments.

Forecasting the spatial and seasonal dynamic of Aedes albopictus oviposition activity in Albania and Balkan countries.

PubMed

Tisseuil, Clément; Velo, Enkelejda; Bino, Silvia; Kadriaj, Perparim; Mersini, Kujtim; Shukullari, Ada; Simaku, Artan; Rogozi, Elton; Caputo, Beniamino; Ducheyne, Els; Della Torre, Alessandra; Reiter, Paul; Gilbert, Marius

2018-02-01

The increasing spread of the Asian tiger mosquito, Aedes albopictus, in Europe and US raises public health concern due to the species competence to transmit several exotic human arboviruses, among which dengue, chikungunya and Zika, and urges the development of suitable modeling approach to forecast the spatial and temporal distribution of the mosquito. Here we developed a dynamical species distribution modeling approach forecasting Ae. albopictus eggs abundance at high spatial (0.01 degree WGS84) and temporal (weekly) resolution over 10 Balkan countries, using temperature times series of Modis data products and altitude as input predictors. The model was satisfactorily calibrated and validated over Albania based observed eggs abundance data weekly monitored during three years. For a given week of the year, eggs abundance was mainly predicted by the number of eggs and the mean temperature recorded in the preceding weeks. That is, results are in agreement with the biological cycle of the mosquito, reflecting the effect temperature on eggs spawning, maturation and hatching. The model, seeded by initial egg values derived from a second model, was then used to forecast the spatial and temporal distribution of eggs abundance over the selected Balkan countries, weekly in 2011, 2012 and 2013. The present study is a baseline to develop an easy-handling forecasting model able to provide information useful for promoting active surveillance and possibly prevention of Ae. albopictus colonization in presently non-infested areas in the Balkans as well as in other temperate regions.

The Effect of Rainfall Measurement Technique and Its Spatiotemporal Resolution on Discharge Predictions in the Netherlands

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; Brauer, C.; Overeem, A.; Sassi, M.; Rios Gaona, M. F.

2014-12-01

Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of these spatiotemporal resolutions on discharge simulations in lowland catchments by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in a freely draining lowland catchment and a polder with controlled water levels. We used rain gauge networks with automatic (hourly resolution but low spatial density) and manual gauges (high spatial density but daily resolution). Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. We also investigated the effect of spatiotemporal resolution with a high-resolution X-band radar data set for catchments with different sizes. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. When catchments are divided into sub-catchments, rainfall spatial variability can become more important, especially during convective rainfall events, leading to spatially varying catchment wetness and spatially varying contribution of quick flow routes. Improving rainfall measurements and their spatiotemporal resolution can improve the performance of rainfall-runoff models, indicating their potential for reducing flood damage through real-time control.

Spatial embedding of structural similarity in the cerebral cortex

PubMed Central

Song, H. Francis; Kennedy, Henry; Wang, Xiao-Jing

2014-01-01

Recent anatomical tracing studies have yielded substantial amounts of data on the areal connectivity underlying distributed processing in cortex, yet the fundamental principles that govern the large-scale organization of cortex remain unknown. Here we show that functional similarity between areas as defined by the pattern of shared inputs or outputs is a key to understanding the areal network of cortex. In particular, we report a systematic relation in the monkey, human, and mouse cortex between the occurrence of connections from one area to another and their similarity distance. This characteristic relation is rooted in the wiring distance dependence of connections in the brain. We introduce a weighted, spatially embedded random network model that robustly gives rise to this structure, as well as many other spatial and topological properties observed in cortex. These include features that were not accounted for in any previous model, such as the wide range of interareal connection weights. Connections in the model emerge from an underlying distribution of spatially embedded axons, thereby integrating the two scales of cortical connectivity—individual axons and interareal pathways—into a common geometric framework. These results provide insights into the origin of large-scale connectivity in cortex and have important implications for theories of cortical organization. PMID:25368200

The response of cortical neurons to in vivo-like input current: theory and experiment: II. Time-varying and spatially distributed inputs.

PubMed

Giugliano, Michele; La Camera, Giancarlo; Fusi, Stefano; Senn, Walter

2008-11-01

The response of a population of neurons to time-varying synaptic inputs can show a rich phenomenology, hardly predictable from the dynamical properties of the membrane's inherent time constants. For example, a network of neurons in a state of spontaneous activity can respond significantly more rapidly than each single neuron taken individually. Under the assumption that the statistics of the synaptic input is the same for a population of similarly behaving neurons (mean field approximation), it is possible to greatly simplify the study of neural circuits, both in the case in which the statistics of the input are stationary (reviewed in La Camera et al. in Biol Cybern, 2008) and in the case in which they are time varying and unevenly distributed over the dendritic tree. Here, we review theoretical and experimental results on the single-neuron properties that are relevant for the dynamical collective behavior of a population of neurons. We focus on the response of integrate-and-fire neurons and real cortical neurons to long-lasting, noisy, in vivo-like stationary inputs and show how the theory can predict the observed rhythmic activity of cultures of neurons. We then show how cortical neurons adapt on multiple time scales in response to input with stationary statistics in vitro. Next, we review how it is possible to study the general response properties of a neural circuit to time-varying inputs by estimating the response of single neurons to noisy sinusoidal currents. Finally, we address the dendrite-soma interactions in cortical neurons leading to gain modulation and spike bursts, and show how these effects can be captured by a two-compartment integrate-and-fire neuron. Most of the experimental results reviewed in this article have been successfully reproduced by simple integrate-and-fire model neurons.

Total Nitrogen Sources of the Three Gorges Reservoir — A Spatio-Temporal Approach

PubMed Central

Ren, Chunping; Wang, Lijing; Zheng, Binghui; Holbach, Andreas

2015-01-01

Understanding the spatial and temporal variation of nutrient concentrations, loads, and their distribution from upstream tributaries is important for the management of large lakes and reservoirs. The Three Gorges Dam was built on the Yangtze River in China, the world’s third longest river, and impounded the famous Three Gorges Reservoir (TGR). In this study, we analyzed total nitrogen (TN) concentrations and inflow data from 2003 till 2010 for the main upstream tributaries of the TGR that contribute about 82% of the TGR’s total inflow. We used time series analysis for seasonal decomposition of TN concentrations and used non-parametric statistical tests (Kruskal-Walli H, Mann-Whitney U) as well as base flow segmentation to analyze significant spatial and temporal patterns of TN pollution input into the TGR. Our results show that TN concentrations had significant spatial heterogeneity across the study area (Tuo River> Yangtze River> Wu River> Min River> Jialing River>Jinsha River). Furthermore, we derived apparent seasonal changes in three out of five upstream tributaries of the TGR rivers (Kruskal-Walli H ρ = 0.009, 0.030 and 0.029 for Tuo River, Jinsha River and Min River in sequence). TN pollution from non-point sources in the upstream tributaries accounted for 68.9% of the total TN input into the TGR. Non-point source pollution of TN revealed increasing trends for 4 out of five upstream tributaries of the TGR. Land use/cover and soil type were identified as the dominant driving factors for the spatial distribution of TN. Intensifying agriculture and increasing urbanization in the upstream catchments of the TGR were the main driving factors for non-point source pollution of TN increase from 2003 till 2010. Land use and land cover management as well as chemical fertilizer use restriction were needed to overcome the threats of increasing TN pollution. PMID:26510158

Agro-hydrology and multi-temporal high-resolution remote sensing: toward an explicit spatial processes calibration

NASA Astrophysics Data System (ADS)

Ferrant, S.; Gascoin, S.; Veloso, A.; Salmon-Monviola, J.; Claverie, M.; Rivalland, V.; Dedieu, G.; Demarez, V.; Ceschia, E.; Probst, J.-L.; Durand, P.; Bustillo, V.

2014-12-01

The growing availability of high-resolution satellite image series offers new opportunities in agro-hydrological research and modeling. We investigated the possibilities offered for improving crop-growth dynamic simulation with the distributed agro-hydrological model: topography-based nitrogen transfer and transformation (TNT2). We used a leaf area index (LAI) map series derived from 105 Formosat-2 (F2) images covering the period 2006-2010. The TNT2 model (Beaujouan et al., 2002), calibrated against discharge and in-stream nitrate fluxes for the period 1985-2001, was tested on the 2005-2010 data set (climate, land use, agricultural practices, and discharge and nitrate fluxes at the outlet). Data from the first year (2005) were used to initialize the hydrological model. A priori agricultural practices obtained from an extensive field survey, such as seeding date, crop cultivar, and amount of fertilizer, were used as input variables. Continuous values of LAI as a function of cumulative daily temperature were obtained at the crop-field level by fitting a double logistic equation against discrete satellite-derived LAI. Model predictions of LAI dynamics using the a priori input parameters displayed temporal shifts from those observed LAI profiles that are irregularly distributed in space (between field crops) and time (between years). By resetting the seeding date at the crop-field level, we have developed an optimization method designed to efficiently minimize this temporal shift and better fit the crop growth against both the spatial observations and crop production. This optimization of simulated LAI has a negligible impact on water budgets at the catchment scale (1 mm yr-1 on average) but a noticeable impact on in-stream nitrogen fluxes (around 12%), which is of interest when considering nitrate stream contamination issues and the objectives of TNT2 modeling. This study demonstrates the potential contribution of the forthcoming high spatial and temporal resolution products from the Sentinel-2 satellite mission for improving agro-hydrological modeling by constraining the spatial representation of crop productivity.

Agro-hydrology and multi temporal high resolution remote sensing: toward an explicit spatial processes calibration

NASA Astrophysics Data System (ADS)

Ferrant, S.; Gascoin, S.; Veloso, A.; Salmon-Monviola, J.; Claverie, M.; Rivalland, V.; Dedieu, G.; Demarez, V.; Ceschia, E.; Probst, J.-L.; Durand, P.; Bustillo, V.

2014-07-01

The recent and forthcoming availability of high resolution satellite image series offers new opportunities in agro-hydrological research and modeling. We investigated the perspective offered by improving the crop growth dynamic simulation using the distributed agro-hydrological model, Topography based Nitrogen transfer and Transformation (TNT2), using LAI map series derived from 105 Formosat-2 (F2) images during the period 2006-2010. The TNT2 model (Beaujouan et al., 2002), calibrated with discharge and in-stream nitrate fluxes for the period 1985-2001, was tested on the 2006-2010 dataset (climate, land use, agricultural practices, discharge and nitrate fluxes at the outlet). A priori agricultural practices obtained from an extensive field survey such as seeding date, crop cultivar, and fertilizer amount were used as input variables. Continuous values of LAI as a function of cumulative daily temperature were obtained at the crop field level by fitting a double logistic equation against discrete satellite-derived LAI. Model predictions of LAI dynamics with a priori input parameters showed an temporal shift with observed LAI profiles irregularly distributed in space (between field crops) and time (between years). By re-setting seeding date at the crop field level, we proposed an optimization method to minimize efficiently this temporal shift and better fit the crop growth against the spatial observations as well as crop production. This optimization of simulated LAI has a negligible impact on water budget at the catchment scale (1 mm yr-1 in average) but a noticeable impact on in-stream nitrogen fluxes (around 12%) which is of interest considering nitrate stream contamination issues and TNT2 model objectives. This study demonstrates the contribution of forthcoming high spatial and temporal resolution products of Sentinel-2 satellite mission in improving agro-hydrological modeling by constraining the spatial representation of crop productivity.

Spatial Modeling for Resources Framework (SMRF): A modular framework for developing spatial forcing data for snow modeling in mountain basins

NASA Astrophysics Data System (ADS)

Havens, Scott; Marks, Danny; Kormos, Patrick; Hedrick, Andrew

2017-12-01

In the Western US and many mountainous regions of the world, critical water resources and climate conditions are difficult to monitor because the observation network is generally very sparse. The critical resource from the mountain snowpack is water flowing into streams and reservoirs that will provide for irrigation, flood control, power generation, and ecosystem services. Water supply forecasting in a rapidly changing climate has become increasingly difficult because of non-stationary conditions. In response, operational water supply managers have begun to move from statistical techniques towards the use of physically based models. As we begin to transition physically based models from research to operational use, we must address the most difficult and time-consuming aspect of model initiation: the need for robust methods to develop and distribute the input forcing data. In this paper, we present a new open source framework, the Spatial Modeling for Resources Framework (SMRF), which automates and simplifies the common forcing data distribution methods. It is computationally efficient and can be implemented for both research and operational applications. We present an example of how SMRF is able to generate all of the forcing data required to a run physically based snow model at 50-100 m resolution over regions of 1000-7000 km2. The approach has been successfully applied in real time and historical applications for both the Boise River Basin in Idaho, USA and the Tuolumne River Basin in California, USA. These applications use meteorological station measurements and numerical weather prediction model outputs as input. SMRF has significantly streamlined the modeling workflow, decreased model set up time from weeks to days, and made near real-time application of a physically based snow model possible.

An assessment of the feasibility of the use of satellite-only rainfall estimates for the hydrological monitoring in central Italy

NASA Astrophysics Data System (ADS)

Campo, Lorenzo; Caparrini, Francesca

2013-04-01

The need for accurate distributed hydrological modelling has constantly increased in last years for several purposes: agricultural applications, water resources management, hydrological balance at watershed scale, floods forecast. The main input for the hydrological numerical models is rainfall data that present, at the same time, a large availability of measures (in gauged regions, with respect to other micro-meteorological variables) and the most complex spatial patterns. While also in presence of densely gauged watersheds the spatial interpolation of the rainfall is a non-trivial problem, due to the spatial intermittence of the variable (especially at finer temporal scales), ungauged regions need an alternative source of rainfall data in order to perform the hydrological modelling. Such source can be constituted by the satellite-estimated rainfall fields, with reference to both geostationary and polar-orbit platforms. In this work the rainfall product obtained by the Aqua-AIRS sensor were used in order to assess the feasibility of the use of satellite-based rainfall as input for distributed hydrological modelling. The MOBIDIC (MOdello di BIlancio Distribuito e Continuo) model, developed at the Department of civil and Environmental Engineering of the University of Florence and operationally used by Tuscany Region and Umbria Region for flood prediction and management, was used for the experiments. In particular three experiments were carried on: a) hydrological simulation with the use of rain-gauges data, b) simulation with the use of satellite-only rainfall estimates, c) simulation with the combined use of the two sources of data in order to obtain an optimal estimate of the actual rainfall fields. The domain of the study was the central Italy. Several critical events occurred in the area were analyzed. A discussion of the results is provided.

An application to model traffic intensity of agricultural machinery at field scale

NASA Astrophysics Data System (ADS)

Augustin, Katja; Kuhwald, Michael; Duttmann, Rainer

2017-04-01

Several soil-pressure-models deal with the impact of agricultural machines on soils. In many cases, these models were used for single spots and consider a static machine configuration. Therefore, a statement about the spatial distribution of soil compaction risk for entire working processes is limited. The aim of the study is the development of an application for the spatial modelling of traffic lanes from agricultural vehicles including wheel load, ground pressure and wheel passages at the field scale. The application is based on Open Source software, application and data formats, using python programming language. Minimum input parameters are GPS-positions, vehicles and tires (producer and model) and the tire inflation pressure. Five working processes were distinguished: soil tillage, manuring, plant protection, sowing and harvest. Currently, two different models (Diserens 2009, Rücknagel et al. 2015) were implemented to calculate the soil pressure. The application was tested at a study site in Lower Saxony, Germany. Since 2015, field traffic were recorded by RTK-GPS and used machine set ups were noted. Using these input information the traffic lanes, wheel load and soil pressure were calculated for all working processes. For instance, the maize harvest in 2016 with a crop chopper and one transport vehicle crossed about 55 % of the total field area. At some places the machines rolled over up to 46 times. Approximately 35 % of the total area was affected by wheel loads over 7 tons and soil pressures between 163 and 193 kPa. With the information about the spatial distribution of wheel passages, wheel load and soil pressure it is possible to identify hot spots of intensive field traffic. Additionally, the use of the application enables the analysis of soil compaction risk induced by agricultural machines for long- and short-term periods.

Large scale snow water status monitoring: comparison of different snow water products in the upper Colorado basins

USGS Publications Warehouse

Artan, G.A.; Verdin, J.P.; Lietzow, R.

2013-01-01

We illustrate the ability to monitor the status of snowpack over large areas by using a~spatially distributed snow accumulation and ablation model in the Upper Colorado Basin. The model was forced with precipitation fields from the National Weather Service (NWS) Multi-sensor Precipitation Estimator (MPE) and the Tropical Rainfall Measuring Mission (TRMM) datasets; remaining meteorological model input data was from NOAA's Global Forecast System (GFS) model output fields. The simulated snow water equivalent (SWE) was compared to SWEs from the Snow Data Assimilation System (SNODAS) and SNOwpack TELemetry system (SNOTEL) over a~region of the Western United States that covers parts of the Upper Colorado Basin. We also compared the SWE product estimated from the Special Sensor Microwave Imager (SSM/I) and Scanning Multichannel Microwave Radiometer (SMMR) to the SNODAS and SNOTEL SWE datasets. Agreement between the spatial distribution of the simulated SWE with both SNODAS and SNOTEL was high for the two model runs for the entire snow accumulation period. Model-simulated SWEs, both with MPE and TRMM, were significantly correlated spatially on average with the SNODAS (r = 0.81 and r = 0.54; d.f. = 543) and the SNOTEL SWE (r = 0.85 and r = 0.55; d.f. = 543), when monthly basinwide simulated average SWE the correlation was also highly significant (r = 0.95 and r = 0.73; d.f. = 12). The SWE estimated from the passive microwave imagery was not correlated either with the SNODAS SWE or (r = 0.14, d.f. = 7) SNOTEL-reported SWE values (r = 0.08, d.f. = 7). The agreement between modeled SWE and the SWE recorded by SNODAS and SNOTEL weakened during the snowmelt period due to an underestimation bias of the air temperature that was used as model input forcing.

Tap, Swipe, and Build: Parental Spatial Input during iPad® and Toy Play

ERIC Educational Resources Information Center

Ho, Ariel; Lee, Joanne; Wood, Eileen; Kassies, Samantha; Heinbuck, Carissa

2018-01-01

Despite the increase in the use of interactive technological devices, little is known about the impact that play context has on the production of spatial language by parents. To investigate whether there is differential parental spatial input afforded by play contexts with their preschoolers, 34 children (20 girls, 14 boys) and their primary…

Experimental investigation of conical bubble structure and acoustic flow structure in ultrasonic field.

PubMed

Ma, Xiaojian; Huang, Biao; Wang, Guoyu; Zhang, Mindi

2017-01-01

The objective of this paper is to investigate the transient conical bubble structure (CBS) and acoustic flow structure in ultrasonic field. In the experiment, the high-speed video and particle image velocimetry (PIV) techniques are used to measure the acoustic cavitation patterns, as well as the flow velocity and vorticity fields. Results are presented for a high power ultrasound with a frequency of 18kHz, and the range of the input power is from 50W to 250W. The results of the experiment show the input power significantly affects the structures of CBS, with the increase of input power, the cavity region of CBS and the velocity of bubbles increase evidently. For the transient motion of bubbles on radiating surface, two different types could be classified, namely the formation, aggregation and coalescence of cavitation bubbles, and the aggregation, shrink, expansion and collapse of bubble cluster. Furthermore, the thickness of turbulent boundary layer near the sonotrode region is found to be much thicker, and the turbulent intensities are much higher for relatively higher input power. The vorticity distribution is prominently affected by the spatial position and input power. Copyright © 2016 Elsevier B.V. All rights reserved.

Evaluation of flash-flood discharge forecasts in complex terrain using precipitation

USGS Publications Warehouse

Yates, D.; Warner, T.T.; Brandes, E.A.; Leavesley, G.H.; Sun, Jielun; Mueller, C.K.

2001-01-01

Operational prediction of flash floods produced by thunderstorm (convective) precipitation in mountainous areas requires accurate estimates or predictions of the precipitation distribution in space and time. The details of the spatial distribution are especially critical in complex terrain because the watersheds are generally small in size, and small position errors in the forecast or observed placement of the precipitation can distribute the rain over the wrong watershed. In addition to the need for good precipitation estimates and predictions, accurate flood prediction requires a surface-hydrologic model that is capable of predicting stream or river discharge based on the precipitation-rate input data. Different techniques for the estimation and prediction of convective precipitation will be applied to the Buffalo Creek, Colorado flash flood of July 1996, where over 75 mm of rain from a thunderstorm fell on the watershed in less than 1 h. The hydrologic impact of the precipitation was exacerbated by the fact that a significant fraction of the watershed experienced a wildfire approximately two months prior to the rain event. Precipitation estimates from the National Weather Service's operational Weather Surveillance Radar-Doppler 1988 and the National Center for Atmospheric Research S-band, research, dual-polarization radar, colocated to the east of Denver, are compared. In addition, very short range forecasts from a convection-resolving dynamic model, which is initialized variationally using the radar reflectivity and Doppler winds, are compared with forecasts from an automated-algorithmic forecast system that also employs the radar data. The radar estimates of rain rate, and the two forecasting systems that employ the radar data, have degraded accuracy by virtue of the fact that they are applied in complex terrain. Nevertheless, the radar data and forecasts from the dynamic model and the automated algorithm could be operationally useful for input to surface-hydrologic models employed for flood warning. Precipitation data provided by these various techniques at short time scales and at fine spatial resolutions are employed as detailed input to a distributed-parameter hydrologic model for flash-flood prediction and analysis. With the radar-based precipitation estimates employed as input, the simulated flood discharge was similar to that observed. The dynamic-model precipitation forecast showed the most promise in providing a significant discharge-forecast lead time. The algorithmic system's precipitation forecast did not demonstrate as much skill, but the associated discharge forecast would still have been sufficient to have provided an alert of impending flood danger.

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

PubMed Central

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

2015-01-01

Background and Aims In mountain ecosystems, predicting root density in three dimensions (3-D) is highly challenging due to the spatial heterogeneity of forest communities. This study presents a simple and semi-mechanistic model, named ChaMRoots, that predicts root interception density (RID, number of roots m–2). ChaMRoots hypothesizes that RID at a given point is affected by the presence of roots from surrounding trees forming a polygon shape. Methods The model comprises three sub-models for predicting: (1) the spatial heterogeneity – RID of the finest roots in the top soil layer as a function of tree basal area at breast height, and the distance between the tree and a given point; (2) the diameter spectrum – the distribution of RID as a function of root diameter up to 50 mm thick; and (3) the vertical profile – the distribution of RID as a function of soil depth. The RID data used for fitting in the model were measured in two uneven-aged mountain forest ecosystems in the French Alps. These sites differ in tree density and species composition. Key Results In general, the validation of each sub-model indicated that all sub-models of ChaMRoots had good fits. The model achieved a highly satisfactory compromise between the number of aerial input parameters and the fit to the observed data. Conclusions The semi-mechanistic ChaMRoots model focuses on the spatial distribution of root density at the tree cluster scale, in contrast to the majority of published root models, which function at the level of the individual. Based on easy-to-measure characteristics, simple forest inventory protocols and three sub-models, it achieves a good compromise between the complexity of the case study area and that of the global model structure. ChaMRoots can be easily coupled with spatially explicit individual-based forest dynamics models and thus provides a highly transferable approach for modelling 3-D root spatial distribution in complex forest ecosystems. PMID:26173892

Assessment of anthropogenic inputs in the surface waters of the southern coastal area of Sfax during spring (Tunisia, Southern Mediterranean Sea).

PubMed

Drira, Zaher; Kmiha-Megdiche, Salma; Sahnoun, Houda; Hammami, Ahmed; Allouche, Noureddine; Tedetti, Marc; Ayadi, Habib

2016-03-15

The coastal marine area of Sfax (Tunisia), which is well-known for its high productivity and fisheries, is also subjected to anthropogenic inputs from diverse industrial, urban and agriculture activities. We investigated the spatial distribution of physical, chemical and biogeochemical parameters in the surface waters of the southern coastal area of Sfax. Pertinent tracers of anthropogenic inputs were identified. Twenty stations were sampled during March 2013 in the vicinity of the coastal areas reserved for waste discharge. Phosphogypsum wastes dumped close to the beaches were the main source of PO4(3-), Cl(-) and SO4(2-) in seawater. The high content in total polyphenolic compounds was due to the olive oil treatment waste water released from margins. These inorganic and organic inputs in the surface waters were associated with elevated COD. The BOD5/COD (<0.5) and COD/BOD5 (>3) ratios highlighted a chemical pollution with organic load of a low biodegradability. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Liodakis, Stylianos; Kyriakidis, Phaedon; Gaganis, Petros

2015-04-01

In hydrogeological applications involving flow and transport of in heterogeneous porous media the spatial distribution of hydraulic conductivity is often parameterized in terms of a lognormal random field based on a histogram and variogram model inferred from data and/or synthesized from relevant knowledge. Realizations of simulated conductivity fields are then generated using geostatistical simulation involving simple random (SR) sampling and are subsequently used as inputs to physically-based simulators of flow and transport in a Monte Carlo framework for evaluating the uncertainty in the spatial distribution of solute concentration due to the uncertainty in the spatial distribution of hydraulic con- ductivity [1]. Realistic uncertainty analysis, however, calls for a large number of simulated concentration fields; hence, can become expensive in terms of both time and computer re- sources. A more efficient alternative to SR sampling is Latin hypercube (LH) sampling, a special case of stratified random sampling, which yields a more representative distribution of simulated attribute values with fewer realizations [2]. Here, term representative implies realizations spanning efficiently the range of possible conductivity values corresponding to the lognormal random field. In this work we investigate the efficiency of alternative methods to classical LH sampling within the context of simulation of flow and transport in a heterogeneous porous medium. More precisely, we consider the stratified likelihood (SL) sampling method of [3], in which attribute realizations are generated using the polar simulation method by exploring the geometrical properties of the multivariate Gaussian distribution function. In addition, we propose a more efficient version of the above method, here termed minimum energy (ME) sampling, whereby a set of N representative conductivity realizations at M locations is constructed by: (i) generating a representative set of N points distributed on the surface of a M-dimensional, unit radius hyper-sphere, (ii) relocating the N points on a representative set of N hyper-spheres of different radii, and (iii) transforming the coordinates of those points to lie on N different hyper-ellipsoids spanning the multivariate Gaussian distribution. The above method is applied in a dimensionality reduction context by defining flow-controlling points over which representative sampling of hydraulic conductivity is performed, thus also accounting for the sensitivity of the flow and transport model to the input hydraulic conductivity field. The performance of the various stratified sampling methods, LH, SL, and ME, is compared to that of SR sampling in terms of reproduction of ensemble statistics of hydraulic conductivity and solute concentration for different sample sizes N (numbers of realizations). The results indicate that ME sampling constitutes an equally if not more efficient simulation method than LH and SL sampling, as it can reproduce to a similar extent statistics of the conductivity and concentration fields, yet with smaller sampling variability than SR sampling. References [1] Gutjahr A.L. and Bras R.L. Spatial variability in subsurface flow and transport: A review. Reliability Engineering & System Safety, 42, 293-316, (1993). [2] Helton J.C. and Davis F.J. Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems. Reliability Engineering & System Safety, 81, 23-69, (2003). [3] Switzer P. Multiple simulation of spatial fields. In: Heuvelink G, Lemmens M (eds) Proceedings of the 4th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Coronet Books Inc., pp 629?635 (2000).

Uncovering the spatially distant feedback loops of global trade: A network and input-output approach.

PubMed

Prell, Christina; Sun, Laixiang; Feng, Kuishuang; He, Jiaying; Hubacek, Klaus

2017-05-15

Land-use change is increasingly driven by global trade. The term "telecoupling" has been gaining ground as a means to describe how human actions in one part of the world can have spatially distant impacts on land and land-use in another. These interactions can, over time, create both direct and spatially distant feedback loops, in which human activity and land use mutually impact one another over great expanses. In this paper, we develop an analytical framework to clarify spatially distant feedbacks in the case of land use and global trade. We use an innovative mix of multi-regional input-output (MRIO) analysis and stochastic actor-oriented models (SAOMs) for analyzing the co-evolution of changes in trade network patterns with those of land use, as embodied in trade. Our results indicate that the formation of trade ties and changes in embodied land use mutually impact one another, and further, that these changes are linked to disparities in countries' wealth. Through identifying this feedback loop, our results support ongoing discussions about the unequal trade patterns between rich and poor countries that result in uneven distributions of negative environmental impacts. Finally, evidence for this feedback loop is present even when controlling for a number of underlying mechanisms, such as countries' land endowments, their geographical distance from one another, and a number of endogenous network tendencies. Copyright © 2017 Elsevier B.V. All rights reserved.

Calculating distributed glacier mass balance for the Swiss Alps from RCM output: Development and testing of downscaling and validation methods

NASA Astrophysics Data System (ADS)

Machguth, H.; Paul, F.; Kotlarski, S.; Hoelzle, M.

2009-04-01

Climate model output has been applied in several studies on glacier mass balance calculation. Hereby, computation of mass balance has mostly been performed at the native resolution of the climate model output or data from individual cells were selected and statistically downscaled. Little attention has been given to the issue of downscaling entire fields of climate model output to a resolution fine enough to compute glacier mass balance in rugged high-mountain terrain. In this study we explore the use of gridded output from a regional climate model (RCM) to drive a distributed mass balance model for the perimeter of the Swiss Alps and the time frame 1979-2003. Our focus lies on the development and testing of downscaling and validation methods. The mass balance model runs at daily steps and 100 m spatial resolution while the RCM REMO provides daily grids (approx. 18 km resolution) of dynamically downscaled re-analysis data. Interpolation techniques and sub-grid parametrizations are combined to bridge the gap in spatial resolution and to obtain daily input fields of air temperature, global radiation and precipitation. The meteorological input fields are compared to measurements at 14 high-elevation weather stations. Computed mass balances are compared to various sets of direct measurements, including stake readings and mass balances for entire glaciers. The validation procedure is performed separately for annual, winter and summer balances. Time series of mass balances for entire glaciers obtained from the model run agree well with observed time series. On the one hand, summer melt measured at stakes on several glaciers is well reproduced by the model, on the other hand, observed accumulation is either over- or underestimated. It is shown that these shifts are systematic and correlated to regional biases in the meteorological input fields. We conclude that the gap in spatial resolution is not a large drawback, while biases in RCM output are a major limitation to model performance. The development and testing of methods to reduce regionally variable biases in entire fields of RCM output should be a focus of pursuing studies.

computer land use mapping via TV waveform analysis of space photography

NASA Technical Reports Server (NTRS)

1972-01-01

An instrumentation and computer system which offers the potential for analyzing photogeographic distributions is described. To satisfy the requirement for computer acceptance, a television and waveform system was developed to transpose pictorial or iconic photo forms to the analytic. A video conversion was accomplished, and each pattern visible on the original photography was represented by a certain range of percentages. With spatial occurrences in digital form, a computer program was developed that could identify, analyze, and map geographic inputs.

Miniature integrated-optical wavelength analyzer chip

NASA Astrophysics Data System (ADS)

Kunz, R. E.; Dübendorfer, J.

1995-11-01

A novel integrated-optical chip suitable for realizing compact miniature wavelength analyzers with high linear dispersion is presented. The chip performs the complete task of converting the spectrum of an input beam into a corresponding spatial irradiance distribution without the need for an imaging function. We demonstrate the feasibility of this approach experimentally by monitoring the changes in the mode spectrum of a laser diode on varying its case temperature. Comparing the results with simultaneous measurements by a commercial spectrometer yielded a rms wavelength deviation of 0.01 nm.

Documentation of Computer Program INFIL3.0 - A Distributed-Parameter Watershed Model to Estimate Net Infiltration Below the Root Zone

USGS Publications Warehouse

,

2008-01-01

This report documents the computer program INFIL3.0, which is a grid-based, distributed-parameter, deterministic water-balance watershed model that calculates the temporal and spatial distribution of daily net infiltration of water across the lower boundary of the root zone. The bottom of the root zone is the estimated maximum depth below ground surface affected by evapotranspiration. In many field applications, net infiltration below the bottom of the root zone can be assumed to equal net recharge to an underlying water-table aquifer. The daily water balance simulated by INFIL3.0 includes precipitation as either rain or snow; snowfall accumulation, sublimation, and snowmelt; infiltration into the root zone; evapotranspiration from the root zone; drainage and water-content redistribution within the root-zone profile; surface-water runoff from, and run-on to, adjacent grid cells; and net infiltration across the bottom of the root zone. The water-balance model uses daily climate records of precipitation and air temperature and a spatially distributed representation of drainage-basin characteristics defined by topography, geology, soils, and vegetation to simulate daily net infiltration at all locations, including stream channels with intermittent streamflow in response to runoff from rain and snowmelt. The model does not simulate streamflow originating as ground-water discharge. Drainage-basin characteristics are represented in the model by a set of spatially distributed input variables uniquely assigned to each grid cell of a model grid. The report provides a description of the conceptual model of net infiltration on which the INFIL3.0 computer code is based and a detailed discussion of the methods by which INFIL3.0 simulates the net-infiltration process. The report also includes instructions for preparing input files necessary for an INFIL3.0 simulation, a description of the output files that are created as part of an INFIL3.0 simulation, and a sample problem that illustrates application of the code to a field setting. Brief descriptions of the main program routine and of each of the modules and subroutines of the INFIL3.0 code, as well as definitions of the variables used in each subroutine, are provided in an appendix.

Assessing the importance of rainfall uncertainty on hydrological models with different spatial and temporal scale

NASA Astrophysics Data System (ADS)

Nossent, Jiri; Pereira, Fernando; Bauwens, Willy

2015-04-01

Precipitation is one of the key inputs for hydrological models. As long as the values of the hydrological model parameters are fixed, a variation of the rainfall input is expected to induce a change in the model output. Given the increased awareness of uncertainty on rainfall records, it becomes more important to understand the impact of this input - output dynamic. Yet, modellers often still have the intention to mimic the observed flow, whatever the deviation of the employed records from the actual rainfall might be, by recklessly adapting the model parameter values. But is it actually possible to vary the model parameter values in such a way that a certain (observed) model output can be generated based on inaccurate rainfall inputs? Thus, how important is the rainfall uncertainty for the model output with respect to the model parameter importance? To address this question, we apply the Sobol' sensitivity analysis method to assess and compare the importance of the rainfall uncertainty and the model parameters on the output of the hydrological model. In order to be able to treat the regular model parameters and input uncertainty in the same way, and to allow a comparison of their influence, a possible approach is to represent the rainfall uncertainty by a parameter. To tackle the latter issue, we apply so called rainfall multipliers on hydrological independent storm events, as a probabilistic parameter representation of the possible rainfall variation. As available rainfall records are very often point measurements at a discrete time step (hourly, daily, monthly,…), they contain uncertainty due to a latent lack of spatial and temporal variability. The influence of the latter variability can also be different for hydrological models with different spatial and temporal scale. Therefore, we perform the sensitivity analyses on a semi-distributed model (SWAT) and a lumped model (NAM). The assessment and comparison of the importance of the rainfall uncertainty and the model parameters is achieved by considering different scenarios for the included parameters and the state of the models.

Spatial variability of summer Florida precipitation and its impact on microwave radiometer rainfall-measurement systems

NASA Technical Reports Server (NTRS)

Turner, B. J.; Austin, G. L.

1993-01-01

Three-dimensional radar data for three summer Florida storms are used as input to a microwave radiative transfer model. The model simulates microwave brightness observations by a 19-GHz, nadir-pointing, satellite-borne microwave radiometer. The statistical distribution of rainfall rates for the storms studied, and therefore the optimal conversion between microwave brightness temperatures and rainfall rates, was found to be highly sensitive to the spatial resolution at which observations were made. The optimum relation between the two quantities was less sensitive to the details of the vertical profile of precipitation. Rainfall retrievals were made for a range of microwave sensor footprint sizes. From these simulations, spatial sampling-error estimates were made for microwave radiometers over a range of field-of-view sizes. The necessity of matching the spatial resolution of ground truth to radiometer footprint size is emphasized. A strategy for the combined use of raingages, ground-based radar, microwave, and visible-infrared (VIS-IR) satellite sensors is discussed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mirzaei, B.; Silva, J. R. G.; Hayton, D.

We present an 8-beam local oscillator (LO) for the astronomically significant [OI] line at 4.7 THz. The beams are generated using a quantum cascade laser (QCL) in combination with a Fourier phase grating. The grating is fully characterized using a third order distributed feedback (DFB) QCL with a single mode emission at 4.7 THz as the input. The measured diffraction efficiency of 74.3% is in an excellent agreement with the calculated result of 75.4% using a 3D simulation. We show that the power distribution among the diffracted beams is uniform enough for pumping an array receiver. To validate the gratingmore » bandwidth, we apply a far-infrared (FIR) gas laser emission at 5.3 THz as the input and find a very similar performance in terms of efficiency, power distribution, and spatial configuration of the diffracted beams. Both results represent the highest operating frequencies of THz phase gratings reported in the literature. By injecting one of the eight diffracted 4.7 THz beams into a superconducting hot electron bolometer (HEB) mixer, we find that the coupled power, taking the optical loss into account, is in consistency with the QCL power value.« less

8-beam local oscillator array at 4.7 THz generated by a phase grating and a quantum cascade laser.

PubMed

Mirzaei, B; Silva, J R G; Hayton, D; Groppi, C; Kao, T Y; Hu, Q; Reno, J L; Gao, J R

2017-11-27

We present an 8-beam local oscillator (LO) for the astronomically significant [OI] line at 4.7 THz. The beams are generated using a quantum cascade laser (QCL) in combination with a Fourier phase grating. The grating is fully characterized using a third order distributed feedback (DFB) QCL with a single mode emission at 4.7 THz as the input. The measured diffraction efficiency of 74.3% is in an excellent agreement with the calculated result of 75.4% using a 3D simulation. We show that the power distribution among the diffracted beams is uniform enough for pumping an array receiver. To validate the grating bandwidth, we apply a far-infrared (FIR) gas laser emission at 5.3 THz as the input and find a very similar performance in terms of efficiency, power distribution, and spatial configuration of the diffracted beams. Both results represent the highest operating frequencies of THz phase gratings reported in the literature. By injecting one of the eight diffracted 4.7 THz beams into a superconducting hot electron bolometer (HEB) mixer, we find that the coupled power, taking the optical loss into account, is in consistency with the QCL power value.

Analysis of haptic information in the cerebral cortex

PubMed Central

2016-01-01

Haptic sensing of objects acquires information about a number of properties. This review summarizes current understanding about how these properties are processed in the cerebral cortex of macaques and humans. Nonnoxious somatosensory inputs, after initial processing in primary somatosensory cortex, are partially segregated into different pathways. A ventrally directed pathway carries information about surface texture into parietal opercular cortex and thence to medial occipital cortex. A dorsally directed pathway transmits information regarding the location of features on objects to the intraparietal sulcus and frontal eye fields. Shape processing occurs mainly in the intraparietal sulcus and lateral occipital complex, while orientation processing is distributed across primary somatosensory cortex, the parietal operculum, the anterior intraparietal sulcus, and a parieto-occipital region. For each of these properties, the respective areas outside primary somatosensory cortex also process corresponding visual information and are thus multisensory. Consistent with the distributed neural processing of haptic object properties, tactile spatial acuity depends on interaction between bottom-up tactile inputs and top-down attentional signals in a distributed neural network. Future work should clarify the roles of the various brain regions and how they interact at the network level. PMID:27440247

The development of the rhizosphere: simulation of root exudation for two contrasting exudates: citrate and mucilage

NASA Astrophysics Data System (ADS)

Sheng, Cheng; Bol, Roland; Vetterlein, Doris; Vanderborght, Jan; Schnepf, Andrea

2017-04-01

Different types of root exudates and their effect on soil/rhizosphere properties have received a lot of attention. Since their influence of rhizosphere properties and processes depends on their concentration in the soil, the assessment of the spatial-temporal exudate concentration distribution around roots is of key importance for understanding the functioning of the rhizosphere. Different root systems have different root architectures. Different types of root exudates diffuse in the rhizosphere with different diffusion coefficient. Both of them are responsible for the dynamics of exudate concentration distribution in the rhizosphere. Hence, simulations of root exudation involving four kinds of plant root systems (Vicia faba, Lupinus albus, Triticum aestivum and Zea mays) and two kinds of root exudates (citrate and mucilage) were conducted. We consider a simplified root architecture where each root is represented by a straight line. Assuming that root tips move at a constant velocity and that mucilage transport is linear, concentration distributions can be obtained from a convolution of the analytical solution of the transport equation in a stationary flow field for an instantaneous point source injection with the spatial-temporal distribution of the source strength. By coupling the analytical equation with a root growth model that delivers the spatial-temporal source term, we simulated exudate concentration distributions for citrate and mucilage with MATLAB. From the simulation results, we inferred the following information about the rhizosphere: (a) the dynamics of the root architecture development is the main effect of exudate distribution in the root zone; (b) a steady rhizosphere with constant width is more likely to develop for individual roots when the diffusion coefficient is small. The simulations suggest that rhizosphere development depends in the following way on the root and exudate properties: the dynamics of the root architecture result in various development patterns of the rhizosphere. Meanwhile, Results improve our understanding of the impact of the spatial and temporal heterogeneity of exudate input on rhizosphere development for different root system types and substances. In future work, we will use the simulation tool to infer critical parameters that determine the spatial-temporal extent of the rhizosphere from experimental data.

Revised spatially distributed global livestock emissions

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Structure and Spatial Distribution of the Chironomidae Community in Mesohabitats in a First Order Stream at the Poço D'Anta Municipal Biological Reserve in Brazil

PubMed Central

Vescovi Rosa, Beatriz Figueiraujo Jabour; de Oliveira, Vívian Campos; Alves, Roberto da Gama

2011-01-01

The Chironomidae occupy different habitats along the lotic system with their distribution determined by different factors such as the substrate characteristics and water speed. The input of vegetable material from the riparian forest allows a higher habitat diversity and food to the benthic fauna. The main aim of this paper is to verify the structure and spatial distribution of the Chironomidae fauna in different mesohabitats in a first order stream located at a Biological Reserve in the southeast of Brazil. In the months of July, August, and September 2007, and in January, February, and March 2008, samples were collected with a hand net (250 µm) in the following mesohabitats: litter from riffles, litter from pools, and sediment from pools. The community structure of each mesohabitat was analyzed through the abundance of organisms, taxa richness, Pielou's evenness, Shannon's diversity, and taxa dominance. Similarity among the mesohabitats was obtained by Cluster analysis, and Chironomidae larvae distribution through the Correspondence analysis. Indicator species analysis was used to identify possible taxa preference for a determined mesohabitat. The analyzed mesohabitats showed high species richness and diversity favored by the large environmental heterogeneity. Some taxa were indicators of the type of mesohabitat. The substrate was the main factor that determined taxa distribution in relation to water flow differences (riffle and pool). Stream characteristics such as low water speed and the presence of natural mechanisms of retention may have provided a higher faunistic similarity between the areas with different flows. The results showed that the physical characteristics of each environment presented a close relationship with the structure and spatial distribution of the Chironomidae fauna in lotic systems. PMID:21529258

Localized direction selective responses in the dendrites of visual interneurons of the fly

PubMed Central

2010-01-01

Background The various tasks of visual systems, including course control, collision avoidance and the detection of small objects, require at the neuronal level the dendritic integration and subsequent processing of many spatially distributed visual motion inputs. While much is known about the pooled output in these systems, as in the medial superior temporal cortex of monkeys or in the lobula plate of the insect visual system, the motion tuning of the elements that provide the input has yet received little attention. In order to visualize the motion tuning of these inputs we examined the dendritic activation patterns of neurons that are selective for the characteristic patterns of wide-field motion, the lobula-plate tangential cells (LPTCs) of the blowfly. These neurons are known to sample direction-selective motion information from large parts of the visual field and combine these signals into axonal and dendro-dendritic outputs. Results Fluorescence imaging of intracellular calcium concentration allowed us to take a direct look at the local dendritic activity and the resulting local preferred directions in LPTC dendrites during activation by wide-field motion in different directions. These 'calcium response fields' resembled a retinotopic dendritic map of local preferred directions in the receptive field, the layout of which is a distinguishing feature of different LPTCs. Conclusions Our study reveals how neurons acquire selectivity for distinct visual motion patterns by dendritic integration of the local inputs with different preferred directions. With their spatial layout of directional responses, the dendrites of the LPTCs we investigated thus served as matched filters for wide-field motion patterns. PMID:20384983

A Froude-scaled model of a bedrock-alluvial channel reach: 2. Sediment cover

NASA Astrophysics Data System (ADS)

Hodge, Rebecca A.; Hoey, Trevor B.

2016-09-01

Previous research into sediment cover in bedrock-alluvial channels has focussed on total sediment cover, rather than the spatial distribution of cover within the channel. The latter is important because it determines the bedrock areas that are protected from erosion and the start and end of sediment transport pathways. We use a 1:10 Froude-scaled model of an 18 by 9 m reach of a bedrock-alluvial channel to study the production and erosion of sediment patches and hence the spatial relationships between flow, bed topography, and sediment dynamics. The hydraulic data from this bed are presented in the companion paper. In these experiments specified volumes of sediment were supplied at the upstream edge of the model reach as single inputs, at each of a range of discharges. This sediment formed patches, and once these stabilized, flow was steadily increased to erode the patches. In summary: (1) patches tend to initiate in the lowest areas of the bed, but areas of topographically induced high flow velocity can inhibit patch development; (2) at low sediment inputs the extent of sediment patches is determined by the bed topography and can be insensitive to the exact volume of sediment supplied; and (3) at higher sediment inputs more extensive patches are produced, stabilized by grain-grain and grain-flow interactions and less influenced by the bed topography. Bedrock topography can therefore be an important constraint on sediment patch dynamics, and topographic metrics are required that incorporate its within-reach variability. The magnitude and timing of sediment input events controls reach-scale sediment cover.

Structural Basis of Cerebellar Microcircuits in the Rat

PubMed Central

Cerminara, Nadia L.; Aoki, Hanako; Loft, Michaela; Apps, Richard

2013-01-01

The topography of the cerebellar cortex is described by at least three different maps, with the basic units of each map termed “microzones,” “patches,” and “bands.” These are defined, respectively, by different patterns of climbing fiber input, mossy fiber input, and Purkinje cell (PC) phenotype. Based on embryological development, the “one-map” hypothesis proposes that the basic units of each map align in the adult animal and the aim of the present study was to test this possibility. In barbiturate anesthetized adult rats, nanoinjections of bidirectional tracer (Retrobeads and biotinylated dextran amine) were made into somatotopically identified regions within the hindlimb C1 zone in copula pyramidis. Injection sites were mapped relative to PC bands defined by the molecular marker zebrin II and were correlated with the pattern of retrograde cell labeling within the inferior olive and in the basilar pontine nuclei to determine connectivity of microzones and patches, respectively, and also with the distributions of biotinylated dextran amine-labeled PC terminals in the cerebellar nuclei. Zebrin bands were found to be related to both climbing fiber and mossy fiber inputs and also to cortical representation of different parts of the ipsilateral hindpaw, indicating a precise spatial organization within cerebellar microcircuitry. This precise connectivity extends to PC terminal fields in the cerebellar nuclei and olivonuclear projections. These findings strongly support the one-map hypothesis and suggest that, at the microcircuit level of resolution, the cerebellar cortex has a common plan of spatial organization for major inputs, outputs, and PC phenotype. PMID:24133249

Microlens array processor with programmable weight mask and direct optical input

NASA Astrophysics Data System (ADS)

Schmid, Volker R.; Lueder, Ernst H.; Bader, Gerhard; Maier, Gert; Siegordner, Jochen

1999-03-01

We present an optical feature extraction system with a microlens array processor. The system is suitable for online implementation of a variety of transforms such as the Walsh transform and DCT. Operating with incoherent light, our processor accepts direct optical input. Employing a sandwich- like architecture, we obtain a very compact design of the optical system. The key elements of the microlens array processor are a square array of 15 X 15 spherical microlenses on acrylic substrate and a spatial light modulator as transmissive mask. The light distribution behind the mask is imaged onto the pixels of a customized a-Si image sensor with adjustable gain. We obtain one output sample for each microlens image and its corresponding weight mask area as summation of the transmitted intensity within one sensor pixel. The resulting architecture is very compact and robust like a conventional camera lens while incorporating a high degree of parallelism. We successfully demonstrate a Walsh transform into the spatial frequency domain as well as the implementation of a discrete cosine transform with digitized gray values. We provide results showing the transformation performance for both synthetic image patterns and images of natural texture samples. The extracted frequency features are suitable for neural classification of the input image. Other transforms and correlations can be implemented in real-time allowing adaptive optical signal processing.

Investigation of Soil Erosion and Phosphorus Transport within an Agricultural Watershed

NASA Astrophysics Data System (ADS)

Klik, A.; Jester, W.; Muhar, A.; Peinsitt, A.; Rampazzo, N.; Mentler, A.; Staudinger, B.; Eder, M.

2003-04-01

In a 40 ha agricultural used watershed in Austria, surface runoff, soil erosion and nutrient losses are measured spatially distributed with 12 small erosion plots. Crops during growing season 2002 are canola, corn, sunflower, winter wheat, winter barley, rye, sugar beets, and pasture. Canopy height and canopy cover are observed in 14-day intervals. Four times per year soil water content, shear stress and random roughness of the surface are measured in a 25 x 25 m grid (140 points). The same raster is sampled for soil texture analyses and content of different phosphorus fractions in the 0-10 cm soil depth. Spatially distributed data are used for geostatistical analysis. Along three transects hydrologic conditions of the hillslope position (top, middle, foot) are investigated by measuring soil water content and soil matrix potential. After erosive events erosion features (rills, deposition, ...) are mapped using GPS. All measured data will be used as input parameters for the Limburg Soil Erosion Model (LISEM).

Distance-dependent gradient in NMDAR-driven spine calcium signals along tapering dendrites

PubMed Central

Walker, Alison S.; Grillo, Federico; Jackson, Rachel E.; Rigby, Mark; Lowe, Andrew S.; Vizcay-Barrena, Gema; Fleck, Roland A.; Burrone, Juan

2017-01-01

Neurons receive a multitude of synaptic inputs along their dendritic arbor, but how this highly heterogeneous population of synaptic compartments is spatially organized remains unclear. By measuring N-methyl-d-aspartic acid receptor (NMDAR)-driven calcium responses in single spines, we provide a spatial map of synaptic calcium signals along dendritic arbors of hippocampal neurons and relate this to measures of synapse structure. We find that quantal NMDAR calcium signals increase in amplitude as they approach a thinning dendritic tip end. Based on a compartmental model of spine calcium dynamics, we propose that this biased distribution in calcium signals is governed by a gradual, distance-dependent decline in spine size, which we visualized using serial block-face scanning electron microscopy. Our data describe a cell-autonomous feature of principal neurons, where tapering dendrites show an inverse distribution of spine size and NMDAR-driven calcium signals along dendritic trees, with important implications for synaptic plasticity rules and spine function. PMID:28209776

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

PubMed

Sukop, Michael C; Cunningham, Kevin J

2016-03-01

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

Ecosystem properties self-organize in response to a directional fog-vegetation interaction.

PubMed

Stanton, Daniel E; Armesto, Juan J; Hedin, Lars O

2014-05-01

Feedbacks between vegetation and resource inputs can lead to the local, self-organization of ecosystem properties. In particular, feedbacks in response to directional resources (e.g., coastal fog, slope runoff) can create complex spatial patterns, such as vegetation banding. Although similar feedbacks are thought to be involved in the development of ecosystems, clear empirical examples are rare. We created a simple model of a fog-influenced, temperate rainforest in central Chile, which allows the comparison of natural banding patterns to simulations of various putative mechanisms. We show that only feedbacks between plants and fog were able to replicate the characteristic distributions of vegetation, soil water, and soil nutrients observed in field transects. Other processes, such as rainfall, were unable to match these diagnostic distributions. Furthermore, fog interception by windward trees leads to increased downwind mortality, leading to progressive extinction of the leeward edge. This pattern of ecosystem development and decay through self-organized processes illustrates, on a relatively small spatial and temporal scale, the patterns predicted for ecosystem evolution.

Using a GIS to link digital spatial data and the precipitation-runoff modeling system, Gunnison River Basin, Colorado

USGS Publications Warehouse

Battaglin, William A.; Kuhn, Gerhard; Parker, Randolph S.

1993-01-01

The U.S. Geological Survey Precipitation-Runoff Modeling System, a modular, distributed-parameter, watershed-modeling system, is being applied to 20 smaller watersheds within the Gunnison River basin. The model is used to derive a daily water balance for subareas in a watershed, ultimately producing simulated streamflows that can be input into routing and accounting models used to assess downstream water availability under current conditions, and to assess the sensitivity of water resources in the basin to alterations in climate. A geographic information system (GIS) is used to automate a method for extracting physically based hydrologic response unit (HRU) distributed parameter values from digital data sources, and for the placement of those estimates into GIS spatial datalayers. The HRU parameters extracted are: area, mean elevation, average land-surface slope, predominant aspect, predominant land-cover type, predominant soil type, average total soil water-holding capacity, and average water-holding capacity of the root zone.

Knowledge-based decision tree approach for mapping spatial distribution of rice crop using C-band synthetic aperture radar-derived information

NASA Astrophysics Data System (ADS)

Mishra, Varun Narayan; Prasad, Rajendra; Kumar, Pradeep; Srivastava, Prashant K.; Rai, Praveen Kumar

2017-10-01

Updated and accurate information of rice-growing areas is vital for food security and investigating the environmental impact of rice ecosystems. The intent of this work is to explore the feasibility of dual-polarimetric C-band Radar Imaging Satellite-1 (RISAT-1) data in delineating rice crop fields from other land cover features. A two polarization combination of RISAT-1 backscatter, namely ratio (HH/HV) and difference (HH-HV), significantly enhanced the backscatter difference between rice and nonrice categories. With these inputs, a QUEST decision tree (DT) classifier is successfully employed to extract the spatial distribution of rice crop areas. The results showed the optimal polarization combination to be HH along with HH/HV and HH-HV for rice crop mapping with an accuracy of 88.57%. Results were further compared with a Landsat-8 operational land imager (OLI) optical sensor-derived rice crop map. Spatial agreement of almost 90% was achieved between outputs produced from Landsat-8 OLI and RISAT-1 data. The simplicity of the approach used in this work may serve as an effective tool for rice crop mapping.

Automating an integrated spatial data-mining model for landfill site selection

NASA Astrophysics Data System (ADS)

Abujayyab, Sohaib K. M.; Ahamad, Mohd Sanusi S.; Yahya, Ahmad Shukri; Ahmad, Siti Zubaidah; Aziz, Hamidi Abdul

2017-10-01

An integrated programming environment represents a robust approach to building a valid model for landfill site selection. One of the main challenges in the integrated model is the complicated processing and modelling due to the programming stages and several limitations. An automation process helps avoid the limitations and improve the interoperability between integrated programming environments. This work targets the automation of a spatial data-mining model for landfill site selection by integrating between spatial programming environment (Python-ArcGIS) and non-spatial environment (MATLAB). The model was constructed using neural networks and is divided into nine stages distributed between Matlab and Python-ArcGIS. A case study was taken from the north part of Peninsular Malaysia. 22 criteria were selected to utilise as input data and to build the training and testing datasets. The outcomes show a high-performance accuracy percentage of 98.2% in the testing dataset using 10-fold cross validation. The automated spatial data mining model provides a solid platform for decision makers to performing landfill site selection and planning operations on a regional scale.

The Distribution of Basal Water Beneath the Greenland Ice Sheet from Radio-Echo Sounding

NASA Astrophysics Data System (ADS)

Jordan, T.; Williams, C.; Schroeder, D. M.; Martos, Y. M.; Cooper, M.; Siegert, M. J.; Paden, J. D.; Huybrechts, P.; Bamber, J. L.

2017-12-01

There is widespread, but often indirect, evidence that a significant fraction of the Greenland Ice Sheet is thawed at the bed. This includes major outlet glaciers and around the NorthGRIP ice-core in the interior. However, the ice-sheet-wide distribution of basal water is poorly constrained by existing observations, and the spatial relationship between basal water and other ice-sheet and subglacial properties is therefore largely unexplored. In principle, airborne radio-echo sounding (RES) surveys provide the necessary information and spatial coverage to infer the presence of basal water at the ice-sheet scale. However, due to uncertainty and spatial variation in radar signal attenuation, the commonly used water diagnostic, bed-echo reflectivity, is highly ambiguous and prone to spatial bias. Here we introduce a new RES diagnostic for the presence of basal water which incorporates both sharp step-transitions and rapid fluctuations in bed-echo reflectivity. This has the advantage of being (near) independent of attenuation model, and enables a decade of recent Operation Ice Bride RES survey data to be combined in a single map for basal water. The ice-sheet-wide water predictions are compared with: bed topography and drainage network structure, existing knowledge of the thermal state and geothermal heat flux, and ice velocity. In addition to the fast flowing ice-sheet margins, we also demonstrate widespread water routing and storage in parts of the slow-flowing northern interior. Notably, this includes a quasi-linear `corridor' of basal water, extending from NorthGRIP to Petermann glacier, which spatially correlates with a region of locally high (magnetic-derived) geothermal heat flux. The predicted water distribution places a new constraint upon the basal thermal state of the Greenland Ice Sheet, and could be used as an input for ice-sheet model simulations.

An egalitarian network model for the emergence of simple and complex cells in visual cortex

PubMed Central

Tao, Louis; Shelley, Michael; McLaughlin, David; Shapley, Robert

2004-01-01

We explain how simple and complex cells arise in a large-scale neuronal network model of the primary visual cortex of the macaque. Our model consists of ≈4,000 integrate-and-fire, conductance-based point neurons, representing the cells in a small, 1-mm2 patch of an input layer of the primary visual cortex. In the model the local connections are isotropic and nonspecific, and convergent input from the lateral geniculate nucleus confers cortical cells with orientation and spatial phase preference. The balance between lateral connections and lateral geniculate nucleus drive determines whether individual neurons in this recurrent circuit are simple or complex. The model reproduces qualitatively the experimentally observed distributions of both extracellular and intracellular measures of simple and complex response. PMID:14695891

Effects of spatial resolution ratio in image fusion

USGS Publications Warehouse

Ling, Y.; Ehlers, M.; Usery, E.L.; Madden, M.

2008-01-01

In image fusion, the spatial resolution ratio can be defined as the ratio between the spatial resolution of the high-resolution panchromatic image and that of the low-resolution multispectral image. This paper attempts to assess the effects of the spatial resolution ratio of the input images on the quality of the fused image. Experimental results indicate that a spatial resolution ratio of 1:10 or higher is desired for optimal multisensor image fusion provided the input panchromatic image is not downsampled to a coarser resolution. Due to the synthetic pixels generated from resampling, the quality of the fused image decreases as the spatial resolution ratio decreases (e.g. from 1:10 to 1:30). However, even with a spatial resolution ratio as small as 1:30, the quality of the fused image is still better than the original multispectral image alone for feature interpretation. In cases where the spatial resolution ratio is too small (e.g. 1:30), to obtain better spectral integrity of the fused image, one may downsample the input high-resolution panchromatic image to a slightly lower resolution before fusing it with the multispectral image.

The added value of stochastic spatial disaggregation for short-term rainfall forecasts currently available in Canada

NASA Astrophysics Data System (ADS)

Gagnon, Patrick; Rousseau, Alain N.; Charron, Dominique; Fortin, Vincent; Audet, René

2017-11-01

Several businesses and industries rely on rainfall forecasts to support their day-to-day operations. To deal with the uncertainty associated with rainfall forecast, some meteorological organisations have developed products, such as ensemble forecasts. However, due to the intensive computational requirements of ensemble forecasts, the spatial resolution remains coarse. For example, Environment and Climate Change Canada's (ECCC) Global Ensemble Prediction System (GEPS) data is freely available on a 1-degree grid (about 100 km), while those of the so-called High Resolution Deterministic Prediction System (HRDPS) are available on a 2.5-km grid (about 40 times finer). Potential users are then left with the option of using either a high-resolution rainfall forecast without uncertainty estimation and/or an ensemble with a spectrum of plausible rainfall values, but at a coarser spatial scale. The objective of this study was to evaluate the added value of coupling the Gibbs Sampling Disaggregation Model (GSDM) with ECCC products to provide accurate, precise and consistent rainfall estimates at a fine spatial resolution (10-km) within a forecast framework (6-h). For 30, 6-h, rainfall events occurring within a 40,000-km2 area (Québec, Canada), results show that, using 100-km aggregated reference rainfall depths as input, statistics of the rainfall fields generated by GSDM were close to those of the 10-km reference field. However, in forecast mode, GSDM outcomes inherit of the ECCC forecast biases, resulting in a poor performance when GEPS data were used as input, mainly due to the inherent rainfall depth distribution of the latter product. Better performance was achieved when the Regional Deterministic Prediction System (RDPS), available on a 10-km grid and aggregated at 100-km, was used as input to GSDM. Nevertheless, most of the analyzed ensemble forecasts were weakly consistent. Some areas of improvement are identified herein.

Supporting the operational use of process based hydrological models and NASA Earth Observations for use in land management and post-fire remediation through a Rapid Response Erosion Database (RRED).

NASA Astrophysics Data System (ADS)

Miller, M. E.; Elliot, W.; Billmire, M.; Robichaud, P. R.; Banach, D. M.

2017-12-01

We have built a Rapid Response Erosion Database (RRED, http://rred.mtri.org/rred/) for the continental United States to allow land managers to access properly formatted spatial model inputs for the Water Erosion Prediction Project (WEPP). Spatially-explicit process-based models like WEPP require spatial inputs that include digital elevation models (DEMs), soil, climate and land cover. The online database delivers either a 10m or 30m USGS DEM, land cover derived from the Landfire project, and soil data derived from SSURGO and STATSGO datasets. The spatial layers are projected into UTM coordinates and pre-registered for modeling. WEPP soil parameter files are also created along with linkage files to match both spatial land cover and soils data with the appropriate WEPP parameter files. Our goal is to make process-based models more accessible by preparing spatial inputs ahead of time allowing modelers to focus on addressing scenarios of concern. The database provides comprehensive support for post-fire hydrological modeling by allowing users to upload spatial soil burn severity maps, and within moments returns spatial model inputs. Rapid response is critical following natural disasters. After moderate and high severity wildfires, flooding, erosion, and debris flows are a major threat to life, property and municipal water supplies. Mitigation measures must be rapidly implemented if they are to be effective, but they are expensive and cannot be applied everywhere. Fire, runoff, and erosion risks also are highly heterogeneous in space, creating an urgent need for rapid, spatially-explicit assessment. The database has been used to help assess and plan remediation on over a dozen wildfires in the Western US. Future plans include expanding spatial coverage, improving model input data and supporting additional models. Our goal is to facilitate the use of the best possible datasets and models to support the conservation of soil and water.

The Cortex Transform as an image preprocessor for sparse distributed memory: An initial study

NASA Technical Reports Server (NTRS)

Olshausen, Bruno; Watson, Andrew

1990-01-01

An experiment is described which was designed to evaluate the use of the Cortex Transform as an image processor for Sparse Distributed Memory (SDM). In the experiment, a set of images were injected with Gaussian noise, preprocessed with the Cortex Transform, and then encoded into bit patterns. The various spatial frequency bands of the Cortex Transform were encoded separately so that they could be evaluated based on their ability to properly cluster patterns belonging to the same class. The results of this study indicate that by simply encoding the low pass band of the Cortex Transform, a very suitable input representation for the SDM can be achieved.

Regulation of spatial selectivity by crossover inhibition.

PubMed

Cafaro, Jon; Rieke, Fred

2013-04-10

Signals throughout the nervous system diverge into parallel excitatory and inhibitory pathways that later converge on downstream neurons to control their spike output. Converging excitatory and inhibitory synaptic inputs can exhibit a variety of temporal relationships. A common motif is feedforward inhibition, in which an increase (decrease) in excitatory input precedes a corresponding increase (decrease) in inhibitory input. The delay of inhibitory input relative to excitatory input originates from an extra synapse in the circuit shaping inhibitory input. Another common motif is push-pull or "crossover" inhibition, in which increases (decreases) in excitatory input occur together with decreases (increases) in inhibitory input. Primate On midget ganglion cells receive primarily feedforward inhibition and On parasol cells receive primarily crossover inhibition; this difference provides an opportunity to study how each motif shapes the light responses of cell types that play a key role in visual perception. For full-field stimuli, feedforward inhibition abbreviated and attenuated responses of On midget cells, while crossover inhibition, though plentiful, had surprisingly little impact on the responses of On parasol cells. Spatially structured stimuli, however, could cause excitatory and inhibitory inputs to On parasol cells to increase together, adopting a temporal relation very much like that for feedforward inhibition. In this case, inhibitory inputs substantially abbreviated a cell's spike output. Thus inhibitory input shapes the temporal stimulus selectivity of both midget and parasol ganglion cells, but its impact on responses of parasol cells depends strongly on the spatial structure of the light inputs.

Modeling of surface dust concentration in snow cover at industrial area using neural networks and kriging

NASA Astrophysics Data System (ADS)

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

2017-06-01

Modeling of spatial distribution of pollutants in the urbanized territories is difficult, especially if there are multiple emission sources. When monitoring such territories, it is often impossible to arrange the necessary detailed sampling. Because of this, the usual methods of analysis and forecasting based on geostatistics are often less effective. Approaches based on artificial neural networks (ANNs) demonstrate the best results under these circumstances. This study compares two models based on ANNs, which are multilayer perceptron (MLP) and generalized regression neural networks (GRNNs) with the base geostatistical method - kriging. Models of the spatial dust distribution in the snow cover around the existing copper quarry and in the area of emissions of a nickel factory were created. To assess the effectiveness of the models three indices were used: the mean absolute error (MAE), the root-mean-square error (RMSE), and the relative root-mean-square error (RRMSE). Taking into account all indices the model of GRNN proved to be the most accurate which included coordinates of the sampling points and the distance to the likely emission source as input parameters for the modeling. Maps of spatial dust distribution in the snow cover were created in the study area. It has been shown that the models based on ANNs were more accurate than the kriging, particularly in the context of a limited data set.

Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

NASA Astrophysics Data System (ADS)

Atencia, A.; Llasat, M. C.; Garrote, L.; Mediero, L.

2010-10-01

The performance of distributed hydrological models depends on the resolution, both spatial and temporal, of the rainfall surface data introduced. The estimation of quantitative precipitation from meteorological radar or satellite can improve hydrological model results, thanks to an indirect estimation at higher spatial and temporal resolution. In this work, composed radar data from a network of three C-band radars, with 6-minutal temporal and 2 × 2 km2 spatial resolution, provided by the Catalan Meteorological Service, is used to feed the RIBS distributed hydrological model. A Window Probability Matching Method (gage-adjustment method) is applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation in both convective and stratiform Z/R relations used over Catalonia. Once the rainfall field has been adequately obtained, an advection correction, based on cross-correlation between two consecutive images, was introduced to get several time resolutions from 1 min to 30 min. Each different resolution is treated as an independent event, resulting in a probable range of input rainfall data. This ensemble of rainfall data is used, together with other sources of uncertainty, such as the initial basin state or the accuracy of discharge measurements, to calibrate the RIBS model using probabilistic methodology. A sensitivity analysis of time resolutions was implemented by comparing the various results with real values from stream-flow measurement stations.

Thermal infrared remote sensing of water temperature in riverine landscapes

USGS Publications Warehouse

Handcock, Rebecca N.; Torgersen, Christian E.; Cherkauer, Keith A.; Gillespie, Alan R.; Klement, Tockner; Faux, Russell N.; Tan, Jing; Carbonneau, Patrice E.; Piégay, Hervé

2012-01-01

Water temperature in riverine landscapes is an important regional indicator of water quality that is influenced by both ground- and surface-water inputs, and indirectly by land use in the surrounding watershed (Brown and Krygier, 1970; Beschta et al., 1987; Chen et al., 1998; Poole and Berman, 2001).Coldwater fishes such as salmon and trout are sensitive to elevated water temperature; therefore, water temperature must meet management guidelines and quality standards, which aim to create a healthy environment for endangered populations (McCullough et al., 2009). For example, in the USA, the Environmental Protection Agency (EPA) has established water quality standards to identify specific temperature criteria to protect coldwater fishes (Environmental Protection Agency, 2003). Trout and salmon can survive in cool-water refugia even when temperatures at other measurement locations are at or above the recommended maximums (Ebersole et al., 2001; Baird and Krueger, 2003; High et al., 2006). Spatially extensive measurements of water temperature are necessary to locate these refugia, to identify the location of ground- and surface-water inputs to the river channel, and to identify thermal pollution sources. Regional assessment of water temperature in streams and rivers has been limited by sparse sampling in both space and time. Water temperature has typically been measured using a network of widely distributed instream gages, which record the temporal change of the bulk, or kinetic, temperature of the water (Tk) at specific locations. For example, the State of Washington (USA) recorded water quality conditions at 76 stations within the Puget Lowlands eco region, which contains 12,721 km of streams and rivers (Washington Department of Ecology, 1998). Such gages are sparsely distributed, are typically located only in larger streams and rivers, and give limited information about the spatial distribution of water temperature.

Thermal infrared remote sensing of water temperature in riverine landscapes: Chapter 5

USGS Publications Warehouse

Carbonneau, Rebecca N.; Piégay, Hervé; Handcock, R.N; Torgersen, Christian E.; Cherkauer, K.A; Gillespie, A.R; Tockner, K; Faux, R. N.; Tan, Jing

2012-01-01

Water temperature in riverine landscapes is an important regional indicator of water quality that is influenced by both ground- and surface-water inputs, and indirectly by land use in the surrounding watershed (Brown and Krygier, 1970; Beschta et al., 1987; Chen et al., 1998; Poole and Berman, 2001). Coldwater fishes such as salmon and trout are sensitive to elevated water temperature; therefore, water temperature must meet management guidelines and quality standards, which aim to create a healthy environment for endangered populations (McCullough et al., 2009). For example, in the USA, the Environmental Protection Agency (EPA) has established water quality standards to identify specific temperature criteria to protect coldwater fishes (Environmental Protection Agency, 2003). Trout and salmon can survive in cool-water refugia even when temperatures at other measurement locations are at or above the recommended maximums (Ebersole et al., 2001; Baird and Krueger, 2003; High et al., 2006). Spatially extensive measurements of water temperature are necessary to locate these refugia, to identify the location of ground- and surface-water inputs to the river channel, and to identify thermal pollution sources. Regional assessment of water temperature in streams and rivers has been limited by sparse sampling in both space and time. Water temperature has typically been measured using a network of widely distributed instream gages, which record the temporal change of the bulk, or kinetic, temperature of the water (Tk) at specific locations. For example, the State of Washington (USA) recorded water quality conditions at 76 stations within the Puget Lowlands eco region, which contains 12,721 km of streams and rivers (Washington Department of Ecology, 1998). Such gages are sparsely distributed, are typically located only in larger streams and rivers, and give limited information about the spatial distribution of water temperature (Cherkauer et al., 2005).

Synaptic integration in dendrites: exceptional need for speed

PubMed Central

Golding, Nace L; Oertel, Donata

2012-01-01

Some neurons in the mammalian auditory system are able to detect and report the coincident firing of inputs with remarkable temporal precision. A strong, low-voltage-activated potassium conductance (gKL) at the cell body and dendrites gives these neurons sensitivity to the rate of depolarization by EPSPs, allowing neurons to assess the coincidence of the rising slopes of unitary EPSPs. Two groups of neurons in the brain stem, octopus cells in the posteroventral cochlear nucleus and principal cells of the medial superior olive (MSO), extract acoustic information by assessing coincident firing of their inputs over a submillisecond timescale and convey that information at rates of up to 1000 spikes s−1. Octopus cells detect the coincident activation of groups of auditory nerve fibres by broadband transient sounds, compensating for the travelling wave delay by dendritic filtering, while MSO neurons detect coincident activation of similarly tuned neurons from each of the two ears through separate dendritic tufts. Each makes use of filtering that is introduced by the spatial distribution of inputs on dendrites. PMID:22930273

Regional Analysis of Stormwater Runoff for the Placement of Managed Aquifer Recharge Sites in Santa Cruz and Northern Monterey Counties, California

NASA Astrophysics Data System (ADS)

Young, K. S.; Beganskas, S.; Fisher, A. T.

2015-12-01

We apply a USGS surface hydrology model, Precipitation-Runoff Modeling System (PRMS), to analyze stormwater runoff in Santa Cruz and Northern Monterey Counties, CA with the goal of supplying managed aquifer recharge (MAR) sites. Under the combined threats of multiyear drought and excess drawdown, this region's aquifers face numerous sustainability challenges, including seawater intrusion, chronic overdraft, increased contamination, and subsidence. This study addresses the supply side of this resource issue by increasing our knowledge of the spatial and temporal dynamics of runoff that could provide water for MAR. Ensuring the effectiveness of MAR using stormwater requires a thorough understanding of runoff distribution and site-specific surface and subsurface aquifer conditions. In this study we use a geographic information system (GIS) and a 3-m digital elevation model (DEM) to divide the region's four primary watersheds into Hydrologic Response Units (HRUs), or topographic sub-basins, that serve as discretized input cells for PRMS. We then assign vegetation, soil, land use, slope, aspect, and other characteristics to these HRUs, from a variety of data sources, and analyze runoff spatially using PRMS under varying precipitation conditions. We are exploring methods of linking spatially continuous and high-temporal-resolution precipitation datasets to generate input precipitation catalogs, facilitating analyses of a variety of regimes. To gain an understanding of how surface hydrology has responded to land development, we will also modify our input data to represent pre-development conditions. Coupled with a concurrent MAR suitability analysis, our model results will help screen for locations of future MAR projects and will improve our understanding of how changes in land use and climate impact hydrologic runoff and aquifer recharge.

Modeling Spatial Dependencies and Semantic Concepts in Data Mining

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vatsavai, Raju

Data mining is the process of discovering new patterns and relationships in large datasets. However, several studies have shown that general data mining techniques often fail to extract meaningful patterns and relationships from the spatial data owing to the violation of fundamental geospatial principles. In this tutorial, we introduce basic principles behind explicit modeling of spatial and semantic concepts in data mining. In particular, we focus on modeling these concepts in the widely used classification, clustering, and prediction algorithms. Classification is the process of learning a structure or model (from user given inputs) and applying the known model to themore » new data. Clustering is the process of discovering groups and structures in the data that are ``similar,'' without applying any known structures in the data. Prediction is the process of finding a function that models (explains) the data with least error. One common assumption among all these methods is that the data is independent and identically distributed. Such assumptions do not hold well in spatial data, where spatial dependency and spatial heterogeneity are a norm. In addition, spatial semantics are often ignored by the data mining algorithms. In this tutorial we cover recent advances in explicitly modeling of spatial dependencies and semantic concepts in data mining.« less

Representation of Non-Spatial and Spatial Information in the Lateral Entorhinal Cortex

PubMed Central

Deshmukh, Sachin S.; Knierim, James J.

2011-01-01

Some theories of memory propose that the hippocampus integrates the individual items and events of experience within a contextual or spatial framework. The hippocampus receives cortical input from two major pathways: the medial entorhinal cortex (MEC) and the lateral entorhinal cortex (LEC). During exploration in an open field, the firing fields of MEC grid cells form a periodically repeating, triangular array. In contrast, LEC neurons show little spatial selectivity, and it has been proposed that the LEC may provide non-spatial input to the hippocampus. Here, we recorded MEC and LEC neurons while rats explored an open field that contained discrete objects. LEC cells fired selectively at locations relative to the objects, whereas MEC cells were weakly influenced by the objects. These results provide the first direct demonstration of a double dissociation between LEC and MEC inputs to the hippocampus under conditions of exploration typically used to study hippocampal place cells. PMID:22065409

Characterization of time-resolved fluorescence response measurements for distributed optical-fiber sensing.

PubMed

Sinchenko, Elena; Gibbs, W E Keith; Davis, Claire E; Stoddart, Paul R

2010-11-20

A distributed optical-fiber sensing system based on pulsed excitation and time-gated photon counting has been used to locate a fluorescent region along the fiber. The complex Alq3 and the infrared dye IR-125 were examined with 405 and 780 nm excitation, respectively. A model to characterize the response of the distributed fluorescence sensor to a Gaussian input pulse was developed and tested. Analysis of the Alq3 fluorescent response confirmed the validity of the model and enabled the fluorescence lifetime to be determined. The intrinsic lifetime obtained (18.2±0.9 ns) is in good agreement with published data. The decay rate was found to be proportional to concentration, which is indicative of collisional deactivation. The model allows the spatial resolution of a distributed sensing system to be improved for fluorophores with lifetimes that are longer than the resolution of the sensing system.

Hydrocarbon contamination of coastal sediments from the Sfax area (Tunisia), Mediterranean Sea.

PubMed

Louati, A; Elleuch, B; Kallel, M; Saliot, A; Dagaut, J; Oudot, J

2001-06-01

The coastal area off the city of Sfax (730,000 inhabitants), well-known for fisheries and industrial activities, receives high inputs of organic matter mostly anthropogenic. Eighteen stations were selected in the vicinity of the direct discharge of industrial sewage effluents in the sea in order to study the spatial distribution of the organic contamination. Surface sediments sampled in the shallow shelf were analysed for hydrocarbons by Fourier transform infrared spectroscopy, gas chromatography and gas chromatography/mass spectrometry. Total hydrocarbon distributions revealed high contamination as compared to other coastal Mediterranean sites, with an average concentration of 1865 ppm/dry weight sediment. Gas chromatographic distribution patterns, values of unresolved mixture/n-alkane ratio and distributions of steranes and hopanes confirmed a petroleum contamination of the Arabian light crude oil type. Biogenic compounds were also identified with a series of short-chain carbon-numbered n-alkenes in the carbon range 16-24.

The spatial and temporal `cost' of volcanic eruptions: assessing economic impact, business inoperability, and spatial distribution of risk in the Auckland region, New Zealand

NASA Astrophysics Data System (ADS)

McDonald, Garry W.; Smith, Nicola J.; Kim, Joon-hwan; Cronin, Shane J.; Proctor, Jon N.

2017-07-01

Volcanic risk assessment has historically concentrated on quantifying the frequency, magnitude, and potential diversity of physical processes of eruptions and their consequent impacts on life and property. A realistic socio-economic assessment of volcanic impact must however take into account dynamic properties of businesses and extend beyond only measuring direct infrastructure/property loss. The inoperability input-output model, heralded as one of the 10 most important accomplishments in risk analysis over the last 30 years (Kujawaski Syst Eng. 9:281-295, 2006), has become prominent over the last decade in the economic impact assessment of business disruptions. We develop a dynamic inoperability input-output model to assess the economic impacts of a hypothetical volcanic event occurring at each of 7270 unique spatial locations throughout the Auckland Volcanic Field, New Zealand. This field of at least 53 volcanoes underlies the country's largest urban area, the Auckland region, which is home to 1.4 million people and responsible for 35.3% (NZ201481.2 billion) of the nation's GDP (Statistics New Zealand 2015). We apply volcanic event characteristics for a small-medium-scale volcanic eruption scenario and assess the economic impacts of an `average' eruption in the Auckland region. Economic losses are quantified both with, and without, business mitigation and intervention responses in place. We combine this information with a recent spatial hazard probability map (Bebbington and Cronin Bull Volcanol. 73(1):55-72, 2011) to produce novel spatial economic activity `at risk' maps. Our approach demonstrates how business inoperability losses sit alongside potential life and property damage assessment in enhancing our understanding of volcanic risk mitigation.

Temporal variations in supraglacial debris distribution on Baltoro Glacier, Karakoram between 2001 and 2012

NASA Astrophysics Data System (ADS)

Gibson, Morgan J.; Glasser, Neil F.; Quincey, Duncan J.; Mayer, Christoph; Rowan, Ann V.; Irvine-Fynn, Tristram D. L.

2017-10-01

Distribution of supraglacial debris in a glacier system varies spatially and temporally due to differing rates of debris input, transport and deposition. Supraglacial debris distribution governs the thickness of a supraglacial debris layer, an important control on the amount of ablation that occurs under such a debris layer. Characterising supraglacial debris layer thickness on a glacier is therefore key to calculating ablation across a glacier surface. The spatial pattern of debris thickness on Baltoro Glacier has previously been calculated for one discrete point in time (2004) using satellite thermal data and an empirically based relationship between supraglacial debris layer thickness and debris surface temperature identified in the field. Here, the same empirically based relationship was applied to two further datasets (2001, 2012) to calculate debris layer thickness across Baltoro Glacier for three discrete points over an 11-year period (2001, 2004, 2012). Surface velocity and sediment flux were also calculated, as well as debris thickness change between periods. Using these outputs, alongside geomorphological maps of Baltoro Glacier produced for 2001, 2004 and 2012, spatiotemporal changes in debris distribution for a sub-decadal timescale were investigated. Sediment flux remained constant throughout the 11-year period. The greatest changes in debris thickness occurred along medial moraines, the locations of mass movement deposition and areas of interaction between tributary glaciers and the main glacier tongue. The study confirms the occurrence of spatiotemporal changes in supraglacial debris layer thickness on sub-decadal timescales, independent of variation in surface velocity. Instead, variation in rates of debris distribution are primarily attributed to frequency and magnitude of mass movement events over decadal timescales, with climate, regional uplift and erosion rates expected to control debris inputs over centurial to millennial timescales. Inclusion of such spatiotemporal variations in debris thickness in distributed surface energy balance models would increase the accuracy of calculated ablation, leading to a more accurate simulation of glacier mass balance through time, and greater precision in quantification of the response of debris-covered glaciers to climatic change.

[Spatial Distribution Characteristics of Different Species Mercury in Water Body of Changshou Lake in Three Gorges Reservoir Region].

PubMed

Bai, Wei-yang; Zhang, Cheng; Zhao, Zheng; Tang, Zhen-ya; Wang, Ding-yong

2015-08-01

An investigation on the concentrations and the spatial distribution characteristics of different species of mercury in the water body of Changshou Lake in Three Gorges Reservoir region was carried out based on the AreGIS statistics module. The results showed that the concentration of the total mercury in Changshou Lake surface water ranged from 0.50 to 3.78 ng x L(-1), with an average of 1.51 ng x L(-1); the concentration of the total MeHg (methylmercury) ranged from 0.10 to 0.75 ng x L(-1), with an average of 0.23 ng x L(-1). The nugget effect value of total mercury in surface water (50.65%), dissolved mercury (49.80%), particulate mercury (29.94%) and the activity mercury (26.95%) were moderate spatial autocorrelation. It indicated that the autocorrelation was impacted by the intrinsic properties of sediments (such as parent materials and rocks, geological mineral and terrain), and on the other hand it was also disturbed by the exogenous input factors (such as aquaculture, industrial activities, farming etc). The nugget effect value of dissolved methylmercury (DMeHg) in Changshou lake surface water (3.49%) was less than 25%, showing significant strong spatial autocorrelation. The distribution was mainly controlled by environmental factors in water. The proportion of total MeHg in total Hg in Changshou Lake water reached 30% which was the maximum ratio of the total MeHg to total Hg in freshwater lakes and rivers. It implied that mercury was easily methylated in the environment of Chanashou Lake.

Runoff simulation sensitivity to remotely sensed initial soil water content

NASA Astrophysics Data System (ADS)

Goodrich, D. C.; Schmugge, T. J.; Jackson, T. J.; Unkrich, C. L.; Keefer, T. O.; Parry, R.; Bach, L. B.; Amer, S. A.

1994-05-01

A variety of aircraft remotely sensed and conventional ground-based measurements of volumetric soil water content (SW) were made over two subwatersheds (4.4 and 631 ha) of the U.S. Department of Agriculture's Agricultural Research Service Walnut Gulch experimental watershed during the 1990 monsoon season. Spatially distributed soil water contents estimated remotely from the NASA push broom microwave radiometer (PBMR), an Institute of Radioengineering and Electronics (IRE) multifrequency radiometer, and three ground-based point methods were used to define prestorm initial SW for a distributed rainfall-runoff model (KINEROS; Woolhiser et al., 1990) at a small catchment scale (4.4 ha). At a medium catchment scale (631 ha or 6.31 km2) spatially distributed PBMR SW data were aggregated via stream order reduction. The impacts of the various spatial averages of SW on runoff simulations are discussed and are compared to runoff simulations using SW estimates derived from a simple daily water balance model. It was found that at the small catchment scale the SW data obtained from any of the measurement methods could be used to obtain reasonable runoff predictions. At the medium catchment scale, a basin-wide remotely sensed average of initial water content was sufficient for runoff simulations. This has important implications for the possible use of satellite-based microwave soil moisture data to define prestorm SW because the low spatial resolutions of such sensors may not seriously impact runoff simulations under the conditions examined. However, at both the small and medium basin scale, adequate resources must be devoted to proper definition of the input rainfall to achieve reasonable runoff simulations.

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

NASA Astrophysics Data System (ADS)

McMillan, Mitchell; Hu, Zhiyong

2017-10-01

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

Nitrogen Flux in Watersheds: The Role of Soil Distributions and Climate in Nitrogen Flux to the Coastal Ecosystems

NASA Astrophysics Data System (ADS)

Showers, W. J.; Reyes, M. M.; Genna, B. J.

2009-12-01

Quantifying the flux of nitrate from different landscape sources in watersheds is important to understand the increased flux of nitrogen to coastal ecosystems. Recent technological advances in chemical sensor networks has demonstrated that chemical variability in aquatic environments are chronically under-sampled, and that many nutrient monitoring programs with monthly or daily sampling rates are inadequate to characterize the dominate seasonal, daily or semi-diurnal fluxes in watersheds. The RiverNet program has measured the nitrate flux in the Neuse River Basin, NC on a 15 minute interval over the past eight years. Significant diurnal variation has been observed in nitrate concentrations during high and low flow periods associated with waste water treatment plants in urban watersheds that are not present in agricultural watersheds. Discharge and N flux in the basin also has significant inter-annual variations associated with El Nino oscillations modified by the North Atlantic oscillation. Positive JMA and NAO indexes are associated with increased groundwater levels, nutrient fluxes, and estuary fish kills. To understand how climate oscillation affect discharge and nutrient fluxes, we have monitored runoff/drainages and groundwater inputs adjacent to a large waste application field over the past 4 years, and used the nitrate inputs as a tracer. Surface water run off is well correlated to precipitation patterns and is the largest nutrient flux into the river. Groundwater inputs are variable spatially and temporally, and are controlled by geology and groundwater levels. Hydric soil spatial distributions are an excellent predictor of nutrient transport across landscapes, and is related to the distribution of biogeochemical “hotspots” The isotopic composition of oxygen and nitrogen in dissolved nitrate indicate that sources change with discharge state, and that atmospherically deposited nitrogen is only important to river fluxes in forested and urban watersheds. These results also indicate that the contribution of wastewater treatment plants from urban watersheds has been greatly under-estimated in current models. Prediction of future changes in discharge and nutrient flux by the modeling of climate oscillations has important implications for water resources policy and drought management for public policy and utility managers.

A multi-factor GIS method to identify optimal geographic locations for electric vehicle (EV) charging stations

NASA Astrophysics Data System (ADS)

Zhang, Yongqin; Iman, Kory

2018-05-01

Fuel-based transportation is one of the major contributors to poor air quality in the United States. Electric Vehicle (EV) is potentially the cleanest transportation technology to our environment. This research developed a spatial suitability model to identify optimal geographic locations for installing EV charging stations for travelling public. The model takes into account a variety of positive and negative factors to identify prime locations for installing EV charging stations in Wasatch Front, Utah, where automobile emission causes severe air pollution due to atmospheric inversion condition near the valley floor. A walkable factor grid was created to store index scores from input factor layers to determine prime locations. 27 input factors including land use, demographics, employment centers etc. were analyzed. Each factor layer was analyzed to produce a summary statistic table to determine the site suitability. Potential locations that exhibit high EV charging usage were identified and scored. A hot spot map was created to demonstrate high, moderate, and low suitability areas for installing EV charging stations. A spatially well distributed EV charging system was then developed, aiming to reduce "range anxiety" from traveling public. This spatial methodology addresses the complex problem of locating and establishing a robust EV charging station infrastructure for decision makers to build a clean transportation infrastructure, and eventually improve environment pollution.

Full uncertainty quantification of N2O and NO emissions using the biogeochemical model LandscapeDNDC on site and regional scale

NASA Astrophysics Data System (ADS)

Haas, Edwin; Santabarbara, Ignacio; Kiese, Ralf; Butterbach-Bahl, Klaus

2017-04-01

Numerical simulation models are increasingly used to estimate greenhouse gas emissions at site to regional / national scale and are outlined as the most advanced methodology (Tier 3) in the framework of UNFCCC reporting. Process-based models incorporate the major processes of the carbon and nitrogen cycle of terrestrial ecosystems and are thus thought to be widely applicable at various conditions and spatial scales. Process based modelling requires high spatial resolution input data on soil properties, climate drivers and management information. The acceptance of model based inventory calculations depends on the assessment of the inventory's uncertainty (model, input data and parameter induced uncertainties). In this study we fully quantify the uncertainty in modelling soil N2O and NO emissions from arable, grassland and forest soils using the biogeochemical model LandscapeDNDC. We address model induced uncertainty (MU) by contrasting two different soil biogeochemistry modules within LandscapeDNDC. The parameter induced uncertainty (PU) was assessed by using joint parameter distributions for key parameters describing microbial C and N turnover processes as obtained by different Bayesian calibration studies for each model configuration. Input data induced uncertainty (DU) was addressed by Bayesian calibration of soil properties, climate drivers and agricultural management practices data. For the MU, DU and PU we performed several hundred simulations each to contribute to the individual uncertainty assessment. For the overall uncertainty quantification we assessed the model prediction probability, followed by sampled sets of input datasets and parameter distributions. Statistical analysis of the simulation results have been used to quantify the overall full uncertainty of the modelling approach. With this study we can contrast the variation in model results to the different sources of uncertainties for each ecosystem. Further we have been able to perform a fully uncertainty analysis for modelling N2O and NO emissions from arable, grassland and forest soils necessary for the comprehensibility of modelling results. We have applied the methodology to a regional inventory to assess the overall modelling uncertainty for a regional N2O and NO emissions inventory for the state of Saxony, Germany.

Can we improve streamflow simulation by using higher resolution rainfall information?

NASA Astrophysics Data System (ADS)

Lobligeois, Florent; Andréassian, Vazken; Perrin, Charles

2013-04-01

The catchment response to rainfall is the interplay between space-time variability of precipitation, catchment characteristics and antecedent hydrological conditions. Precipitation dominates the high frequency hydrological response, and its simulation is thus dependent on the way rainfall is represented. One of the characteristics which distinguishes distributed from lumped models is their ability to represent explicitly the spatial variability of precipitation and catchment characteristics. The sensitivity of runoff hydrographs to the spatial variability of forcing data has been a major concern of researchers over the last three decades. However, although the literature on the relationship between spatial rainfall and runoff response is abundant, results are contrasted and sometimes contradictory. Several studies concluded that including information on rainfall spatial distribution improves discharge simulation (e.g. Ajami et al., 2004, among others) whereas other studies showed the lack of significant improvement in simulations with better information on rainfall spatial pattern (e.g. Andréassian et al., 2004, among others). The difficulties to reach a clear consensus is mainly due to the fact that each modeling study is implemented only on a few catchments whereas the impact of the spatial distribution of rainfall on runoff is known to be catchment and event characteristics-dependent. Many studies are virtual experiments and only compare flow simulations, which makes it difficult to reach conclusions transposable to real-life case studies. Moreover, the hydrological rainfall-runoff models differ between the studies and the parameterization strategies sometimes tend to advantage the distributed approach (or the lumped one). Recently, Météo-France developed a rainfall reanalysis over the whole French territory at the 1-kilometer resolution and the hourly time step over a 10-year period combining radar data and raingauge measurements: weather radar data were corrected and adjusted with both hourly and daily raingauge data. Based on this new high resolution product, we propose a framework to evaluate the improvements in streamflow simulation by using higher resolution rainfall information. Semi-distributed modelling is performed for different spatial resolution of precipitation forcing: from lumped to semi-distributed simulations. Here we do not work on synthetic (simulated) streamflow, but with actual measurements, on a large set of 181 French catchments representing a variety of size and climate. The rainfall-runoff model is re-calibrated for each resolution of rainfall spatial distribution over a 5-year sub-period and evaluated on the complementary sub-period in validation mode. The results are analysed by catchment classes based on catchment area and for various types of rainfall events based on the spatial variability of precipitation. References Ajami, N. K., Gupta, H. V, Wagener, T. & Sorooshian, S. (2004) Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system. Journal of Hydrology 298(1-4), 112-135. Andréassian, V., Oddos, A., Michel, C., Anctil, F., Perrin, C. & Loumagne, C. (2004) Impact of spatial aggregation of inputs and parameters on the efficiency of rainfall-runoff models: A theoretical study using chimera watersheds. Water Resources Research 40(5), 1-9.

From water use to water scarcity footprinting in environmentally extended input-output analysis.

PubMed

Ridoutt, Bradley George; Hadjikakou, Michalis; Nolan, Martin; Bryan, Brett A

2018-05-18

Environmentally extended input-output analysis (EEIOA) supports environmental policy by quantifying how demand for goods and services leads to resource use and emissions across the economy. However, some types of resource use and emissions require spatially-explicit impact assessment for meaningful interpretation, which is not possible in conventional EEIOA. For example, water use in locations of scarcity and abundance is not environmentally equivalent. Opportunities for spatially-explicit impact assessment in conventional EEIOA are limited because official input-output tables tend to be produced at the scale of political units which are not usually well aligned with environmentally relevant spatial units. In this study, spatially-explicit water scarcity factors and a spatially disaggregated Australian water use account were used to develop water scarcity extensions that were coupled with a multi-regional input-output model (MRIO). The results link demand for agricultural commodities to the problem of water scarcity in Australia and globally. Important differences were observed between the water use and water scarcity footprint results, as well as the relative importance of direct and indirect water use, with significant implications for sustainable production and consumption-related policies. The approach presented here is suggested as a feasible general approach for incorporating spatially-explicit impact assessment in EEIOA.

The Impacts of Pine Tree Die-Off on Snow Accumulation and Distribution at Plot to Catchment Scales

NASA Astrophysics Data System (ADS)

Biederman, J. A.; Harpold, A. A.; Gutmann, E. D.; Reed, D. E.; Gochis, D. J.; Brooks, P. D.

2011-12-01

Seasonal snow cover is a primary water source throughout much of Western North America, where insect-induced tree die-off is changing the montane landscape. Widespread mortality from insects or drought differs from well-studied cases of fire and logging in that tree mortality is not accompanied by other immediate biophysical changes. Much of the impacted landscape is a mosaic of stands of varying species, structure, management history and health overlain on complex terrain. To address the challenge of predicting the effects of forest die-off on snow water input, we quantified snow accumulation and ablation at scales ranging from individual trees, through forest stands, to nested small catchments. Our study sites in Northern Colorado and Southern Wyoming are dominated by lodgepole pine, but they include forest stands that are naturally developed, managed and clear-cut with varying mortality from Mountain Pine Beetle (MPB). Our record for winters 2010 and 2011 includes continuous meteorological data and snow depth in plots with varying MPB impact as well as stand- to catchment-scale snow surveys mid-winter and near maximal accumulation. At the plot scale, snow depth sensors in healthy stands recorded greater inputs during storms (21-42% of depth) and greater seasonal accumulation (15-40%) in canopy gaps than under trees, whereas no spatial effects of canopy geometry were observed in stands with heavy mortality. Similar patterns were observed in snow surveys near peak accumulation. At both impacted and thinned sites, spatial variability in snow depth was more closely associated with larger scale topography and changes in stand structure than with canopy cover. The role of aspect in ablation was observed to increase in impacted stands as both shading and wind attenuation decreased. Evidence of wind-controlled snow distribution was found 80-100 meters from exposed stand edges in impacted forest as compared to 10-15 meters in healthy forest. Integrating from the scale of stands to small catchments, maximal snow water equivalent (SWE) as a fraction of winter precipitation (P) ranged from 62 to 74%. Despite an expectation of decreased interception and increased snow accumulation with advanced mortality, surveys at stand and catchment scales found no significant increases in net snow water input between healthy and impacted forests. These observations suggest that the spatial scale of processes affecting net snow accumulation and ablation increase following die-off. Using data from our sites and other studies, this presentation will develop a predictive model of how interception, shading, and wind redistribution interact to control net snow water input following large-scale forest mortality.

Input-dependent frequency modulation of cortical gamma oscillations shapes spatial synchronization and enables phase coding.

PubMed

Lowet, Eric; Roberts, Mark; Hadjipapas, Avgis; Peter, Alina; van der Eerden, Jan; De Weerd, Peter

2015-02-01

Fine-scale temporal organization of cortical activity in the gamma range (∼25-80Hz) may play a significant role in information processing, for example by neural grouping ('binding') and phase coding. Recent experimental studies have shown that the precise frequency of gamma oscillations varies with input drive (e.g. visual contrast) and that it can differ among nearby cortical locations. This has challenged theories assuming widespread gamma synchronization at a fixed common frequency. In the present study, we investigated which principles govern gamma synchronization in the presence of input-dependent frequency modulations and whether they are detrimental for meaningful input-dependent gamma-mediated temporal organization. To this aim, we constructed a biophysically realistic excitatory-inhibitory network able to express different oscillation frequencies at nearby spatial locations. Similarly to cortical networks, the model was topographically organized with spatially local connectivity and spatially-varying input drive. We analyzed gamma synchronization with respect to phase-locking, phase-relations and frequency differences, and quantified the stimulus-related information represented by gamma phase and frequency. By stepwise simplification of our models, we found that the gamma-mediated temporal organization could be reduced to basic synchronization principles of weakly coupled oscillators, where input drive determines the intrinsic (natural) frequency of oscillators. The gamma phase-locking, the precise phase relation and the emergent (measurable) frequencies were determined by two principal factors: the detuning (intrinsic frequency difference, i.e. local input difference) and the coupling strength. In addition to frequency coding, gamma phase contained complementary stimulus information. Crucially, the phase code reflected input differences, but not the absolute input level. This property of relative input-to-phase conversion, contrasting with latency codes or slower oscillation phase codes, may resolve conflicting experimental observations on gamma phase coding. Our modeling results offer clear testable experimental predictions. We conclude that input-dependency of gamma frequencies could be essential rather than detrimental for meaningful gamma-mediated temporal organization of cortical activity.

Input-Dependent Frequency Modulation of Cortical Gamma Oscillations Shapes Spatial Synchronization and Enables Phase Coding

PubMed Central

Lowet, Eric; Roberts, Mark; Hadjipapas, Avgis; Peter, Alina; van der Eerden, Jan; De Weerd, Peter

2015-01-01

Fine-scale temporal organization of cortical activity in the gamma range (∼25–80Hz) may play a significant role in information processing, for example by neural grouping (‘binding’) and phase coding. Recent experimental studies have shown that the precise frequency of gamma oscillations varies with input drive (e.g. visual contrast) and that it can differ among nearby cortical locations. This has challenged theories assuming widespread gamma synchronization at a fixed common frequency. In the present study, we investigated which principles govern gamma synchronization in the presence of input-dependent frequency modulations and whether they are detrimental for meaningful input-dependent gamma-mediated temporal organization. To this aim, we constructed a biophysically realistic excitatory-inhibitory network able to express different oscillation frequencies at nearby spatial locations. Similarly to cortical networks, the model was topographically organized with spatially local connectivity and spatially-varying input drive. We analyzed gamma synchronization with respect to phase-locking, phase-relations and frequency differences, and quantified the stimulus-related information represented by gamma phase and frequency. By stepwise simplification of our models, we found that the gamma-mediated temporal organization could be reduced to basic synchronization principles of weakly coupled oscillators, where input drive determines the intrinsic (natural) frequency of oscillators. The gamma phase-locking, the precise phase relation and the emergent (measurable) frequencies were determined by two principal factors: the detuning (intrinsic frequency difference, i.e. local input difference) and the coupling strength. In addition to frequency coding, gamma phase contained complementary stimulus information. Crucially, the phase code reflected input differences, but not the absolute input level. This property of relative input-to-phase conversion, contrasting with latency codes or slower oscillation phase codes, may resolve conflicting experimental observations on gamma phase coding. Our modeling results offer clear testable experimental predictions. We conclude that input-dependency of gamma frequencies could be essential rather than detrimental for meaningful gamma-mediated temporal organization of cortical activity. PMID:25679780

Analysis of metal(loid)s contamination and their continuous input in soils around a zinc smelter: Development of methodology and a case study in South Korea.

PubMed

Yun, Sung-Wook; Baveye, Philippe C; Kim, Dong-Hyeon; Kang, Dong-Hyeon; Lee, Si-Young; Kong, Min-Jae; Park, Chan-Gi; Kim, Hae-Do; Son, Jinkwan; Yu, Chan

2018-07-01

Soil contamination due to atmospheric deposition of metals originating from smelters is a global environmental problem. A common problem associated with this contamination is the discrimination between anthropic and natural contributions to soil metal concentrations: In this context, we investigated the characteristics of soil contamination in the surrounding area of a world class smelter. We attempted to combine several approaches in order to identify sources of metals in soils and to examine contamination characteristics, such as pollution level, range, and spatial distribution. Soil samples were collected at 100 sites during a field survey and total concentrations of As, Cd, Cr, Cu, Fe, Hg, Ni, Pb, and Zn were analyzed. We conducted a multivariate statistical analysis, and also examined the spatial distribution by 1) identifying the horizontal variation of metals according to particular wind directions and distance from the smelter and 2) drawing a distribution map by means of a GIS tool. As, Cd, Cu, Hg, Pb, and Zn in the soil were found to originate from smelter emissions, and As also originated from other sources such as abandoned mines and waste landfill. Among anthropogenic metals, the horizontal distribution of Cd, Hg, Pb, and Zn according to the downwind direction and distance from the smelter showed a typical feature of atmospheric deposition (regression model: y = y 0  + αe -βx ). Lithogenic Fe was used as an indicator, and it revealed the continuous input and accumulation of these four elements in the surrounding soils. Our approach was effective in clearly identifying the sources of metals and analyzing their contamination characteristics. We believe this study will provide useful information to future studies on soil pollution by metals around smelters. Copyright © 2018 Elsevier Ltd. All rights reserved.

Estimating evaporation with thermal UAV data and two-source energy balance models

NASA Astrophysics Data System (ADS)

Hoffmann, H.; Nieto, H.; Jensen, R.; Guzinski, R.; Zarco-Tejada, P.; Friborg, T.

2016-02-01

Estimating evaporation is important when managing water resources and cultivating crops. Evaporation can be estimated using land surface heat flux models and remotely sensed land surface temperatures (LST), which have recently become obtainable in very high resolution using lightweight thermal cameras and Unmanned Aerial Vehicles (UAVs). In this study a thermal camera was mounted on a UAV and applied into the field of heat fluxes and hydrology by concatenating thermal images into mosaics of LST and using these as input for the two-source energy balance (TSEB) modelling scheme. Thermal images are obtained with a fixed-wing UAV overflying a barley field in western Denmark during the growing season of 2014 and a spatial resolution of 0.20 m is obtained in final LST mosaics. Two models are used: the original TSEB model (TSEB-PT) and a dual-temperature-difference (DTD) model. In contrast to the TSEB-PT model, the DTD model accounts for the bias that is likely present in remotely sensed LST. TSEB-PT and DTD have already been well tested, however only during sunny weather conditions and with satellite images serving as thermal input. The aim of this study is to assess whether a lightweight thermal camera mounted on a UAV is able to provide data of sufficient quality to constitute as model input and thus attain accurate and high spatial and temporal resolution surface energy heat fluxes, with special focus on latent heat flux (evaporation). Furthermore, this study evaluates the performance of the TSEB scheme during cloudy and overcast weather conditions, which is feasible due to the low data retrieval altitude (due to low UAV flying altitude) compared to satellite thermal data that are only available during clear-sky conditions. TSEB-PT and DTD fluxes are compared and validated against eddy covariance measurements and the comparison shows that both TSEB-PT and DTD simulations are in good agreement with eddy covariance measurements, with DTD obtaining the best results. The DTD model provides results comparable to studies estimating evaporation with similar experimental setups, but with LST retrieved from satellites instead of a UAV. Further, systematic irrigation patterns on the barley field provide confidence in the veracity of the spatially distributed evaporation revealed by model output maps. Lastly, this study outlines and discusses the thermal UAV image processing that results in mosaics suited for model input. This study shows that the UAV platform and the lightweight thermal camera provide high spatial and temporal resolution data valid for model input and for other potential applications requiring high-resolution and consistent LST.

Modelling the spatial distribution of SO2 and NOx emissions in Ireland.

PubMed

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

2001-01-01

The spatial distributions of sulphur dioxide (SO2) and nitrogen oxides (NOx) emissions are essential inputs to models of atmospheric transport and deposition. Information of this type is required for international negotiations on emission reduction through the critical load approach. High-resolution emission maps for the Republic of Ireland have been created using emission totals and a geographical information system, supported by surrogate statistics and landcover information. Data have been subsequently allocated to the EMEP 50 x 50-km grid, used in long-range transport models for the investigation of transboundary air pollution. Approximately two-thirds of SO2 emissions in Ireland emanate from two grid-squares. Over 50% of total SO2 emissions originate from one grid-square in the west of Ireland, where the largest point sources of SO2 are located. Approximately 15% of the total SO2 emissions originate from the grid-square containing Dublin. SO2 emission densities for the remaining areas are very low, < 1 t km-2 year-1 for most grid-squares. NOx emissions show a very similar distribution pattern. However, NOx emissions are more evenly spread over the country, as about 40% of total NOx emissions originate from road transport.

A distributed analysis of Human impact on global sediment dynamics

NASA Astrophysics Data System (ADS)

Cohen, S.; Kettner, A.; Syvitski, J. P.

2012-12-01

Understanding riverine sediment dynamics is an important undertaking for both socially-relevant issues such as agriculture, water security and infrastructure management and for scientific analysis of landscapes, river ecology, oceanography and other disciplines. Providing good quantitative and predictive tools in therefore timely particularly in light of predicted climate and landuse changes. Ever increasing human activity during the Anthropocene have affected sediment dynamics in two major ways: (1) an increase is hillslope erosion due to agriculture, deforestation and landscape engineering and (2) trapping of sediment in dams and other man-made reservoirs. The intensity and dynamics between these man-made factors vary widely across the globe and in time and are therefore hard to predict. Using sophisticated numerical models is therefore warranted. Here we use a distributed global riverine sediment flux and water discharge model (WBMsed) to compare a pristine (without human input) and disturbed (with human input) simulations. Using these 50 year simulations we will show and discuss the complex spatial and temporal patterns of human effect on riverine sediment flux and water discharge.

A hydrological emulator for global applications - HE v1.0.0

NASA Astrophysics Data System (ADS)

Liu, Yaling; Hejazi, Mohamad; Li, Hongyi; Zhang, Xuesong; Leng, Guoyong

2018-03-01

While global hydrological models (GHMs) are very useful in exploring water resources and interactions between the Earth and human systems, their use often requires numerous model inputs, complex model calibration, and high computation costs. To overcome these challenges, we construct an efficient open-source and ready-to-use hydrological emulator (HE) that can mimic complex GHMs at a range of spatial scales (e.g., basin, region, globe). More specifically, we construct both a lumped and a distributed scheme of the HE based on the monthly abcd model to explore the tradeoff between computational cost and model fidelity. Model predictability and computational efficiency are evaluated in simulating global runoff from 1971 to 2010 with both the lumped and distributed schemes. The results are compared against the runoff product from the widely used Variable Infiltration Capacity (VIC) model. Our evaluation indicates that the lumped and distributed schemes present comparable results regarding annual total quantity, spatial pattern, and temporal variation of the major water fluxes (e.g., total runoff, evapotranspiration) across the global 235 basins (e.g., correlation coefficient r between the annual total runoff from either of these two schemes and the VIC is > 0.96), except for several cold (e.g., Arctic, interior Tibet), dry (e.g., North Africa) and mountainous (e.g., Argentina) regions. Compared against the monthly total runoff product from the VIC (aggregated from daily runoff), the global mean Kling-Gupta efficiencies are 0.75 and 0.79 for the lumped and distributed schemes, respectively, with the distributed scheme better capturing spatial heterogeneity. Notably, the computation efficiency of the lumped scheme is 2 orders of magnitude higher than the distributed one and 7 orders more efficient than the VIC model. A case study of uncertainty analysis for the world's 16 basins with top annual streamflow is conducted using 100 000 model simulations, and it demonstrates the lumped scheme's extraordinary advantage in computational efficiency. Our results suggest that the revised lumped abcd model can serve as an efficient and reasonable HE for complex GHMs and is suitable for broad practical use, and the distributed scheme is also an efficient alternative if spatial heterogeneity is of more interest.

Spatial-Temporal Heterogeneity in Regional Watershed Phosphorus Cycles Driven by Changes in Human Activity over the Past Century

NASA Astrophysics Data System (ADS)

Hale, R. L.; Grimm, N. B.; Vorosmarty, C. J.

2014-12-01

An ongoing challenge for society is to harness the benefits of phosphorus (P) while minimizing negative effects on downstream ecosystems. To meet this challenge we must understand the controls on the delivery of anthropogenic P from landscapes to downstream ecosystems. We used a model that incorporates P inputs to watersheds, hydrology, and infrastructure (sewers, waste-water treatment plants, and reservoirs) to reconstruct historic P yields for the northeastern U.S. from 1930 to 2002. At the regional scale, increases in P inputs were paralleled by increased fractional retention, thus P loading to the coast did not increase significantly. We found that temporal variation in regional P yield was correlated with P inputs. Spatial patterns of watershed P yields were best predicted by inputs, but the correlation between inputs and yields in space weakened over time, due to infrastructure development. Although the magnitude of infrastructure effect was small, its role changed over time and was important in creating spatial and temporal heterogeneity in input-yield relationships. We then conducted a hierarchical cluster analysis to identify a typology of anthropogenic P cycling, using data on P inputs (fertilizer, livestock feed, and human food), infrastructure (dams, wastewater treatment plants, sewers), and hydrology (runoff coefficient). We identified 6 key types of watersheds that varied significantly in climate, infrastructure, and the types and amounts of P inputs. Annual watershed P yields and retention varied significantly across watershed types. Although land cover varied significantly across typologies, clusters based on land cover alone did not explain P budget patterns, suggesting that this variable is insufficient to understand patterns of P cycling across large spatial scales. Furthermore, clusters varied over time as patterns of climate, P use, and infrastructure changed. Our results demonstrate that the drivers of P cycles are spatially and temporally heterogeneous, yet they also suggest that a relatively simple typology of watersheds can be useful for understanding regional P cycles and may help inform P management approaches.

Improving the accuracy of livestock distribution estimates through spatial interpolation.

PubMed

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

2012-11-01

Animal distribution maps serve many purposes such as estimating transmission risk of zoonotic pathogens to both animals and humans. The reliability and usability of such maps is highly dependent on the quality of the input data. However, decisions on how to perform livestock surveys are often based on previous work without considering possible consequences. A better understanding of the impact of using different sample designs and processing steps on the accuracy of livestock distribution estimates was acquired through iterative experiments using detailed survey. The importance of sample size, sample design and aggregation is demonstrated and spatial interpolation is presented as a potential way to improve cattle number estimates. As expected, results show that an increasing sample size increased the precision of cattle number estimates but these improvements were mainly seen when the initial sample size was relatively low (e.g. a median relative error decrease of 0.04% per sampled parish for sample sizes below 500 parishes). For higher sample sizes, the added value of further increasing the number of samples declined rapidly (e.g. a median relative error decrease of 0.01% per sampled parish for sample sizes above 500 parishes. When a two-stage stratified sample design was applied to yield more evenly distributed samples, accuracy levels were higher for low sample densities and stabilised at lower sample sizes compared to one-stage stratified sampling. Aggregating the resulting cattle number estimates yielded significantly more accurate results because of averaging under- and over-estimates (e.g. when aggregating cattle number estimates from subcounty to district level, P <0.009 based on a sample of 2,077 parishes using one-stage stratified samples). During aggregation, area-weighted mean values were assigned to higher administrative unit levels. However, when this step is preceded by a spatial interpolation to fill in missing values in non-sampled areas, accuracy is improved remarkably. This counts especially for low sample sizes and spatially even distributed samples (e.g. P <0.001 for a sample of 170 parishes using one-stage stratified sampling and aggregation on district level). Whether the same observations apply on a lower spatial scale should be further investigated.

Can 28-Month-Old Children Learn Spatial Prepositions Robustly from Pictures? Yes, When Narrative Input Is Provided

PubMed Central

Rohlfing, Katharina J.; Nachtigäller, Kerstin

2016-01-01

The learning of spatial prepositions is assumed to be based on experience in space. In a slow mapping study, we investigated whether 31 German 28-month-old children could robustly learn the German spatial prepositions hinter [behind] and neben [next to] from pictures, and whether a narrative input can compensate for a lack of immediate experience in space. One group of children received pictures with a narrative input as a training to understand spatial prepositions. In two further groups, we controlled (a) for the narrative input by providing unconnected speech during the training and (b) for the learning material by training the children on toys rather than pictures. We assessed children’s understanding of spatial prepositions at three different time points: pretest, immediate test, and delayed posttest. Results showed improved word retention in children from the narrative but not the control group receiving unconnected speech. Neither of the trained groups succeeded in generalization to novel referents. Finally, all groups were instructed to deal with untrained material in the test to investigate the robustness of learning across tasks. None of the groups succeeded in this task transfer. PMID:27471479

Data-driven mapping of the potential mountain permafrost distribution.

PubMed

Deluigi, Nicola; Lambiel, Christophe; Kanevski, Mikhail

2017-07-15

Existing mountain permafrost distribution models generally offer a good overview of the potential extent of this phenomenon at a regional scale. They are however not always able to reproduce the high spatial discontinuity of permafrost at the micro-scale (scale of a specific landform; ten to several hundreds of meters). To overcome this lack, we tested an alternative modelling approach using three classification algorithms belonging to statistics and machine learning: Logistic regression, Support Vector Machines and Random forests. These supervised learning techniques infer a classification function from labelled training data (pixels of permafrost absence and presence) with the aim of predicting the permafrost occurrence where it is unknown. The research was carried out in a 588km 2 area of the Western Swiss Alps. Permafrost evidences were mapped from ortho-image interpretation (rock glacier inventorying) and field data (mainly geoelectrical and thermal data). The relationship between selected permafrost evidences and permafrost controlling factors was computed with the mentioned techniques. Classification performances, assessed with AUROC, range between 0.81 for Logistic regression, 0.85 with Support Vector Machines and 0.88 with Random forests. The adopted machine learning algorithms have demonstrated to be efficient for permafrost distribution modelling thanks to consistent results compared to the field reality. The high resolution of the input dataset (10m) allows elaborating maps at the micro-scale with a modelled permafrost spatial distribution less optimistic than classic spatial models. Moreover, the probability output of adopted algorithms offers a more precise overview of the potential distribution of mountain permafrost than proposing simple indexes of the permafrost favorability. These encouraging results also open the way to new possibilities of permafrost data analysis and mapping. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial and temporal resolution effects on urban catchments with different imperviousness degrees

NASA Astrophysics Data System (ADS)

Cristiano, Elena; ten Veldhuis, Marie-Claire; van de Giesen, Nick C.

2015-04-01

One of the main problems in urban hydrological analysis is to measure the rainfall at urban scale with high resolution and use these measurements to model urban runoff processes to predict flows and reduce flood risk. With the aim of building a semi-distribute hydrological sewer model for an urban catchment, high resolution rainfall data are required as input. In this study, the sensitivity of hydrological response to high resolution precipitation data for hydrodynamic models at urban scale is evaluated with different combinations of spatial and temporal resolutions. The aim is to study sensitivity in relation to catchment characteristics, especially drainage area size, imperviousness degree and hydraulic properties such as special structures (weirs, pumping stations). Rainfall data of nine storms are considered with 4 different spatial resolutions (3000m, 1000m, 500m and 100m) combined with 4 different temporal resolutions (10min, 5min, 3min and 1min). The dual polarimetric X-band weather radar, located in the Cabauw Experimental Site for Atmospheric Research (CESAR) provided the high resolution rainfall data of these rainfall events, used to improve the sewer model. The effects of spatial-temporal rainfall input resolution on response is studied in three Districts of Rotterdam (NL): Kralingen, Spaanse Polder and Centrum district. These catchments have different average drainage area size (from 2km2 to 7km2), and different general characteristics. Centrum district and Kralingen are, indeed, more various and include residential and commercial areas, big green areas and a small industrial area, while Spaanse Polder is a industrial area, densely urbanized, and presents a high percentage of imperviousness.

Extraordinary optical transmission inside a waveguide: spatial mode dependence.

PubMed

Reichel, Kimberly S; Lu, Peter Y; Backus, Sterling; Mendis, Rajind; Mittleman, Daniel M

2016-12-12

We study the influence of the input spatial mode on the extraordinary optical transmission (EOT) effect. By placing a metal screen with a 1D array of subwavelength holes inside a terahertz (THz) parallel-plate waveguide (PPWG), we can directly compare the transmission spectra with different input waveguide modes. We observe that the transmitted spectrum depends strongly on the input mode. A conventional description of EOT based on the excitation of surface plasmons is not predictive in all cases. Instead, we utilize a formalism based on impedance matching, which accurately predicts the spectral resonances for both TEM and non-TEM input modes.

Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liao, Qifeng, E-mail: liaoqf@shanghaitech.edu.cn; Lin, Guang, E-mail: guanglin@purdue.edu

2016-07-15

In this paper we present a reduced basis ANOVA approach for partial deferential equations (PDEs) with random inputs. The ANOVA method combined with stochastic collocation methods provides model reduction in high-dimensional parameter space through decomposing high-dimensional inputs into unions of low-dimensional inputs. In this work, to further reduce the computational cost, we investigate spatial low-rank structures in the ANOVA-collocation method, and develop efficient spatial model reduction techniques using hierarchically generated reduced bases. We present a general mathematical framework of the methodology, validate its accuracy and demonstrate its efficiency with numerical experiments.

Ergodic channel capacity of spatial correlated multiple-input multiple-output free space optical links using multipulse pulse-position modulation

NASA Astrophysics Data System (ADS)

Wang, Huiqin; Wang, Xue; Cao, Minghua

2017-02-01

The spatial correlation extensively exists in the multiple-input multiple-output (MIMO) free space optical (FSO) communication systems due to the channel fading and the antenna space limitation. Wilkinson's method was utilized to investigate the impact of spatial correlation on the MIMO FSO communication system employing multipulse pulse-position modulation. Simulation results show that the existence of spatial correlation reduces the ergodic channel capacity, and the reception diversity is more competent to resist this kind of performance degradation.

Distributed MIMO chaotic radar based on wavelength-division multiplexing technology.

PubMed

Yao, Tingfeng; Zhu, Dan; Ben, De; Pan, Shilong

2015-04-15

A distributed multiple-input multiple-output chaotic radar based on wavelength-division multiplexing technology (WDM) is proposed and demonstrated. The wideband quasi-orthogonal chaotic signals generated by different optoelectronic oscillators (OEOs) are emitted by separated antennas to gain spatial diversity against the fluctuation of a target's radar cross section and enhance the detection capability. The received signals collected by the receive antennas and the reference signals from the OEOs are delivered to the central station for joint processing by exploiting WDM technology. The centralized signal processing avoids precise time synchronization of the distributed system and greatly simplifies the remote units, which improves the localization accuracy of the entire system. A proof-of-concept experiment for two-dimensional localization of a metal target is demonstrated. The maximum position error is less than 6.5 cm.

Topsoil pollution forecasting using artificial neural networks on the example of the abnormally distributed heavy metal at Russian subarctic

NASA Astrophysics Data System (ADS)

Tarasov, D. A.; Buevich, A. G.; Sergeev, A. P.; Shichkin, A. V.; Baglaeva, E. M.

2017-06-01

Forecasting the soil pollution is a considerable field of study in the light of the general concern of environmental protection issues. Due to the variation of content and spatial heterogeneity of pollutants distribution at urban areas, the conventional spatial interpolation models implemented in many GIS packages mostly cannot provide appreciate interpolation accuracy. Moreover, the problem of prediction the distribution of the element with high variability in the concentration at the study site is particularly difficult. The work presents two neural networks models forecasting a spatial content of the abnormally distributed soil pollutant (Cr) at a particular location of the subarctic Novy Urengoy, Russia. A method of generalized regression neural network (GRNN) was compared to a common multilayer perceptron (MLP) model. The proposed techniques have been built, implemented and tested using ArcGIS and MATLAB. To verify the models performances, 150 scattered input data points (pollutant concentrations) have been selected from 8.5 km2 area and then split into independent training data set (105 points) and validation data set (45 points). The training data set was generated for the interpolation using ordinary kriging while the validation data set was used to test their accuracies. The networks structures have been chosen during a computer simulation based on the minimization of the RMSE. The predictive accuracy of both models was confirmed to be significantly higher than those achieved by the geostatistical approach (kriging). It is shown that MLP could achieve better accuracy than both kriging and even GRNN for interpolating surfaces.

Quantitative retrieving forest ecological parameters based on remote sensing in Liping County of China

NASA Astrophysics Data System (ADS)

Tian, Qingjiu; Chen, Jing M.; Zheng, Guang; Xia, Xueqi; Chen, Junying

2006-09-01

Forest ecosystem is an important component of terrestrial ecosystem and plays an important role in global changes. Aboveground biomass (AGB) of forest ecosystem is an important factor in global carbon cycle studies. The purpose of this study was to retrieve the yearly Net Primary Productivity (NPP) of forest from the 8-days-interval MODIS-LAI images of a year and produce a yearly NPP distribution map. The LAI, DBH (diameter at breast height), tree height, and tree age field were measured in different 80 plots for Chinese fir, Masson pine, bamboo, broadleaf, mix forest in Liping County. Based on the DEM image and Landsat TM images acquired on May 14th, 2000, the geometric correction and terrain correction were taken. In addition, the "6S"model was used to gain the surface reflectance image. Then the correlation between Leaf Area Index (LAI) and Reduced Simple Ratio (RSR) was built. Combined with the Landcover map, forest stand map, the LAI, aboveground biomass, tree age map were produced respectively. After that, the 8-days- interval LAI images of a year, meteorology data, soil data, forest stand image and Landcover image were inputted into the BEPS model to get the NPP spatial distribution. At last, the yearly NPP spatial distribution map with 30m spatial resolution was produced. The values in those forest ecological parameters distribution maps were quite consistent with those of field measurements. So it's possible, feasible and time-saving to estimate forest ecological parameters at a large scale by using remote sensing.

A powerful tool for assessing distribution and fate of potentially toxic metals (PTMs) in soils: integration of laser ablation spectrometry (LA-ICP-MS) on thin sections with soil micromorphology and geochemistry.

PubMed

Scarciglia, Fabio; Barca, Donatella

2017-04-01

The dynamic behavior and inherent spatial heterogeneity, at different hierarchic levels, of the soil system often make the spatial distribution of potentially toxic metals (PTMs) quite complex and difficult to assess correctly. This work demonstrates that the application of laser ablation spectrometry (LA-ICP-MS) to soil thin sections constitutes an ancillary powerful tool to well-established analytical methods for tracing the behavior and fate of potential soil contaminants at the microsite level. It allowed to discriminate the contribution of PTMs in distinct soil sub-components, such as parent rock fragments, neoformed, clay-enriched or humified matrix, and specific pedogenetic features of illuvial origin (unstained or iron-stained clay coatings) even at very low contents. PTMs were analyzed in three soil profiles located in the Muravera area (Sardinia, Italy), where several, now abandoned mines were exploited. Recurrent trends of increase of many PTMs from rock to pedogenic matrix and to illuvial clay coatings, traced by LA-ICP-MS compositional data, revealed a pedogenetic control on metal fractionation and distribution, based on adsorption properties of clay minerals, iron oxyhydroxides or organic matter, and downprofile illuviation processes. The main PTMs patterns coupled with SEM-EDS analyses suggest that heavy metal-bearing mineral grains were sourced from the mine plants, in addition to the natural sedimentary input. The interplay between soil-forming processes and geomorphic dynamics significantly contributed to the PTMs spatial distribution detected in the different pedogenetic horizons and soil features.

Modeling pCO2 variability in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Xue, Z.; He, R.; Fennel, K.; Cai, W.-J.; Lohrenz, S.; Huang, W.-J.; Tian, H.

2014-08-01

A three-dimensional coupled physical-biogeochemical model was used to simulate and examine temporal and spatial variability of surface pCO2 in the Gulf of Mexico (GoM). The model is driven by realistic atmospheric forcing, open boundary conditions from a data-assimilative global ocean circulation model, and observed freshwater and terrestrial nutrient and carbon input from major rivers. A seven-year model hindcast (2004-2010) was performed and was validated against in situ measurements. The model revealed clear seasonality in surface pCO2. Based on the multi-year mean of the model results, the GoM is an overall CO2 sink with a flux of 1.34 × 1012 mol C yr-1, which, together with the enormous fluvial carbon input, is balanced by the carbon export through the Loop Current. A sensitivity experiment was performed where all biological sources and sinks of carbon were disabled. In this simulation surface pCO2 was elevated by ~ 70 ppm, providing the evidence that biological uptake is a primary driver for the observed CO2 sink. The model also provided insights about factors influencing the spatial distribution of surface pCO2 and sources of uncertainty in the carbon budget.

Modeling pCO2 Variability in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Xue, Z. G.; He, R.; Fennel, K.; Cai, W. J.; Lohrenz, S. E.; Huang, W. J.; Tian, H.

2014-12-01

A three-dimensional coupled physical-biogeochemical model was used to simulate and examine temporal and spatial variability of surface pCO2 in the Gulf of Mexico (GoM). The model is driven by realistic atmospheric forcing, open boundary conditions from a data-assimilative global ocean circulation model, and observed freshwater and terrestrial nutrient and carbon input from major rivers. A seven-year model hindcast (2004-2010) was performed and was validated against in situ measurements. The model revealed clear seasonality in surface pCO2. Based on the multi-year mean of the model results, the GoM is an overall CO2 sink with a flux of 1.34 × 1012 mol C yr-1, which, together with the enormous fluvial carbon input, is balanced by the carbon export through the Loop Current. A sensitivity experiment was performed where all biological sources and sinks of carbon were disabled. In this simulation surface pCO2 was elevated by ~70 ppm, providing the evidence that biological uptake is a primary driver for the observed CO2 sink. The model also provided insights about factors influencing the spatial distribution of surface pCO2 and sources of uncertainty in the carbon budget.

Investigation of photoconductivity of individual InAs/GaAs(001) quantum dots by Scanning Near-field Optical Microscopy

NASA Astrophysics Data System (ADS)

Filatov, D. O.; Kazantseva, I. A.; Baidus', N. V.; Gorshkov, A. P.; Mishkin, V. P.

2017-10-01

The spatial distribution of the photocurrent in the input window plane of a GaAs-based p-i-n photodiode with embedded self-assembled InAs quantum dots (QDs) has been studied with the photoexcitation through a Scanning Near-field Optical Microscope (SNOM) probe at the emission wavelength greater than the intrinsic absorption edge of the host material (GaAs). The inhomogeneities related to the interband absorption in the individual InAs/GaAs(001) QDs have been observed in the photocurrent SNOM images. Thus, the possibility of imaging the individual InAs/GaAs(001) QDs in the photocurrent SNOM images with the lateral spatial resolution ˜ 100 nm (of the same order of magnitude as the SNOM probe aperture size) has been demonstrated.

Software for Simulation of Hyperspectral Images

NASA Technical Reports Server (NTRS)

Richtsmeier, Steven C.; Singer-Berk, Alexander; Bernstein, Lawrence S.

2002-01-01

A package of software generates simulated hyperspectral images for use in validating algorithms that generate estimates of Earth-surface spectral reflectance from hyperspectral images acquired by airborne and spaceborne instruments. This software is based on a direct simulation Monte Carlo approach for modeling three-dimensional atmospheric radiative transport as well as surfaces characterized by spatially inhomogeneous bidirectional reflectance distribution functions. In this approach, 'ground truth' is accurately known through input specification of surface and atmospheric properties, and it is practical to consider wide variations of these properties. The software can treat both land and ocean surfaces and the effects of finite clouds with surface shadowing. The spectral/spatial data cubes computed by use of this software can serve both as a substitute for and a supplement to field validation data.

Simulation of Hyperspectral Images

NASA Technical Reports Server (NTRS)

Richsmeier, Steven C.; Singer-Berk, Alexander; Bernstein, Lawrence S.

2004-01-01

A software package generates simulated hyperspectral imagery for use in validating algorithms that generate estimates of Earth-surface spectral reflectance from hyperspectral images acquired by airborne and spaceborne instruments. This software is based on a direct simulation Monte Carlo approach for modeling three-dimensional atmospheric radiative transport, as well as reflections from surfaces characterized by spatially inhomogeneous bidirectional reflectance distribution functions. In this approach, "ground truth" is accurately known through input specification of surface and atmospheric properties, and it is practical to consider wide variations of these properties. The software can treat both land and ocean surfaces, as well as the effects of finite clouds with surface shadowing. The spectral/spatial data cubes computed by use of this software can serve both as a substitute for, and a supplement to, field validation data.

Glomerular and Mitral-Granule Cell Microcircuits Coordinate Temporal and Spatial Information Processing in the Olfactory Bulb.

PubMed

Cavarretta, Francesco; Marasco, Addolorata; Hines, Michael L; Shepherd, Gordon M; Migliore, Michele

2016-01-01

The olfactory bulb processes inputs from olfactory receptor neurons (ORNs) through two levels: the glomerular layer at the site of input, and the granule cell level at the site of output to the olfactory cortex. The sequence of action of these two levels has not yet been examined. We analyze this issue using a novel computational framework that is scaled up, in three-dimensions (3D), with realistic representations of the interactions between layers, activated by simulated natural odors, and constrained by experimental and theoretical analyses. We suggest that the postulated functions of glomerular circuits have as their primary role transforming a complex and disorganized input into a contrast-enhanced and normalized representation, but cannot provide for synchronization of the distributed glomerular outputs. By contrast, at the granule cell layer, the dendrodendritic interactions mediate temporal decorrelation, which we show is dependent on the preceding contrast enhancement by the glomerular layer. The results provide the first insights into the successive operations in the olfactory bulb, and demonstrate the significance of the modular organization around glomeruli. This layered organization is especially important for natural odor inputs, because they activate many overlapping glomeruli.

Nonlinear multiplicative dendritic integration in neuron and network models

PubMed Central

Zhang, Danke; Li, Yuanqing; Rasch, Malte J.; Wu, Si

2013-01-01

Neurons receive inputs from thousands of synapses distributed across dendritic trees of complex morphology. It is known that dendritic integration of excitatory and inhibitory synapses can be highly non-linear in reality and can heavily depend on the exact location and spatial arrangement of inhibitory and excitatory synapses on the dendrite. Despite this known fact, most neuron models used in artificial neural networks today still only describe the voltage potential of a single somatic compartment and assume a simple linear summation of all individual synaptic inputs. We here suggest a new biophysical motivated derivation of a single compartment model that integrates the non-linear effects of shunting inhibition, where an inhibitory input on the route of an excitatory input to the soma cancels or “shunts” the excitatory potential. In particular, our integration of non-linear dendritic processing into the neuron model follows a simple multiplicative rule, suggested recently by experiments, and allows for strict mathematical treatment of network effects. Using our new formulation, we further devised a spiking network model where inhibitory neurons act as global shunting gates, and show that the network exhibits persistent activity in a low firing regime. PMID:23658543

Biogeochemical typology and temporal variability of lagoon waters in a coral reef ecosystem subject to terrigeneous and anthropogenic inputs (New Caledonia).

PubMed

Fichez, R; Chifflet, S; Douillet, P; Gérard, P; Gutierrez, F; Jouon, A; Ouillon, S; Grenz, C

2010-01-01

Considering the growing concern about the impact of anthropogenic inputs on coral reefs and coral reef lagoons, surprisingly little attention has been given to the relationship between those inputs and the trophic status of lagoon waters. The present paper describes the distribution of biogeochemical parameters in the coral reef lagoon of New Caledonia where environmental conditions allegedly range from pristine oligotrophic to anthropogenically influenced. The study objectives were to: (i) identify terrigeneous and anthropogenic inputs and propose a typology of lagoon waters, (ii) determine temporal variability of water biogeochemical parameters at time-scales ranging from hours to seasons. Combined ACP-cluster analyses revealed that over the 2000 km(2) lagoon area around the city of Nouméa, "natural" terrigeneous versus oceanic influences affecting all stations only accounted for less than 20% of the spatial variability whereas 60% of that spatial variability could be attributed to significant eutrophication of a limited number of inshore stations. ACP analysis allowed to unambiguously discriminating between the natural trophic enrichment along the offshore-inshore gradient and anthropogenically induced eutrophication. High temporal variability in dissolved inorganic nutrients concentrations strongly hindered their use as indicators of environmental status. Due to longer turn over time, particulate organic material and more specifically chlorophyll a appeared as more reliable nonconservative tracer of trophic status. Results further provided evidence that ENSO occurrences might temporarily lower the trophic status of the New Caledonia lagoon. It is concluded that, due to such high frequency temporal variability, the use of biogeochemical parameters in environmental surveys require adapted sampling strategies, data management and environmental alert methods. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Evaluation of seasonal and spatial variations of lumped water balance model sensitivity to precipitation data errors

NASA Astrophysics Data System (ADS)

Xu, Chong-yu; Tunemar, Liselotte; Chen, Yongqin David; Singh, V. P.

2006-06-01

Sensitivity of hydrological models to input data errors have been reported in the literature for particular models on a single or a few catchments. A more important issue, i.e. how model's response to input data error changes as the catchment conditions change has not been addressed previously. This study investigates the seasonal and spatial effects of precipitation data errors on the performance of conceptual hydrological models. For this study, a monthly conceptual water balance model, NOPEX-6, was applied to 26 catchments in the Mälaren basin in Central Sweden. Both systematic and random errors were considered. For the systematic errors, 5-15% of mean monthly precipitation values were added to the original precipitation to form the corrupted input scenarios. Random values were generated by Monte Carlo simulation and were assumed to be (1) independent between months, and (2) distributed according to a Gaussian law of zero mean and constant standard deviation that were taken as 5, 10, 15, 20, and 25% of the mean monthly standard deviation of precipitation. The results show that the response of the model parameters and model performance depends, among others, on the type of the error, the magnitude of the error, physical characteristics of the catchment, and the season of the year. In particular, the model appears less sensitive to the random error than to the systematic error. The catchments with smaller values of runoff coefficients were more influenced by input data errors than were the catchments with higher values. Dry months were more sensitive to precipitation errors than were wet months. Recalibration of the model with erroneous data compensated in part for the data errors by altering the model parameters.

Does model structure limit the use of satellite data as hydrologic forcing for distributed operational models?

NASA Astrophysics Data System (ADS)

Bowman, A. L.; Franz, K.; Hogue, T. S.

2015-12-01

We are investigating the implications for use of satellite data in operational streamflow prediction. Specifically, the consequence of potential hydrologic model structure deficiencies on the ability to achieve improved forecast accuracy through the use of satellite data. We want to understand why advanced data do not lead to improved streamflow simulations by exploring how various fluxes and states differ among models of increasing complexity. In a series of prior studies, we investigated the use of a daily satellite-derived potential evapotranspiration (PET) estimate as input to the National Weather Service (NWS) streamflow forecast models for watersheds in the Upper Mississippi and Red river basins. Although the spatial PET product appears to represent the day-to-day variability in PET more realistically than current climatological methods used by the NWS, the impact of the satellite data on streamflow simulations results in slightly poorer model efficiency overall. Analysis of the model states indicates the model progresses differently between simulations with baseline PET and the satellite-derived PET input, though variation in streamflow simulations overall is negligible. For instance, the upper zone states, responsible for the high flows of a hydrograph, show a profound difference, while simulation of the peak flows tend to show little variation in the timing and magnitude. Using the spatial PET input, the lower zone states show improvement with simulating the recession limb and baseflow portion of the hydrograph. We anticipate that through a better understanding of the relationship between model structure, model states, and simulated streamflow we will be able to diagnose why simulations of discharge from the forecast model have failed to improve when provided seemingly more representative input data. Identifying model limitations are critical to demonstrating the full benefit of a satellite data for operational use.

Toward Verifying Fossil Fuel CO2 Emissions with the CMAQ Model: Motivation, Model Description and Initial Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Zhen; Bambha, Ray P.; Pinto, Joseph P.

2014-03-14

Motivated by the urgent need for emission verification of CO2 and other greenhouse gases, we have developed regional CO2 simulation with CMAQ over the contiguous U.S. Model sensitivity experiments have been performed using three different sets of inputs for net ecosystem exchange (NEE) and two fossil fuel emission inventories, to understand the roles of fossil fuel emissions, atmosphere-biosphere exchange and transport in regulating the spatial and diurnal variability of CO2 near the surface, and to characterize the well-known ‘signal-to-noise’ problem, i.e. the interference from the biosphere on the interpretation of atmospheric CO2 observations. It is found that differences in themore » meteorological conditions for different urban areas strongly contribute to the contrast in concentrations. The uncertainty of NEE, as measured by the difference among the three different NEE inputs, has notable impact on regional distribution of CO2 simulated by CMAQ. Larger NEE uncertainty and impact are found over eastern U.S. urban areas than along the western coast. A comparison with tower CO2 measurements at Boulder Atmospheric Observatory (BAO) shows that the CMAQ model using hourly varied and high-resolution CO2 emission from the Vulcan inventory and CarbonTracker optimized NEE reasonably reproduce the observed diurnal profile, whereas switching to different NEE inputs significantly degrades the model performance. Spatial distribution of CO2 is found to correlate with NOx, SO2 and CO, due to their similarity in emission sources and transport processes. These initial results from CMAQ demonstrate the power of a state-of-the art CTM in helping interpret CO2 observations and verify fossil fuel emissions. The ability to simulate CO2 in CMAQ will also facilitate investigations of the utility of traditionally regulated pollutants and other species as tracers to CO2 source attribution.« less

8-beam local oscillator array at 47 THz generated by a phase grating and a quantum cascade laser

DOE PAGES

Mirzaei, B.; Silva, J. R. G.; Hayton, D.; ...

2017-11-13

We present an 8-beam local oscillator (LO) for the astronomically significant [OI] line at 4.7 THz. The beams are generated using a quantum cascade laser (QCL) in combination with a Fourier phase grating. The grating is fully characterized using a third order distributed feedback (DFB) QCL with a single mode emission at 4.7 THz as the input. The measured diffraction efficiency of 74.3% is in an excellent agreement with the calculated result of 75.4% using a 3D simulation. We show that the power distribution among the diffracted beams is uniform enough for pumping an array receiver. To validate the gratingmore » bandwidth, we apply a far-infrared (FIR) gas laser emission at 5.3 THz as the input and find a very similar performance in terms of efficiency, power distribution, and spatial configuration of the diffracted beams. Both results represent the highest operating frequencies of THz phase gratings reported in the literature. By injecting one of the eight diffracted 4.7 THz beams into a superconducting hot electron bolometer (HEB) mixer, we find that the coupled power, taking the optical loss into account, is in consistency with the QCL power value.« less

Numerical simulation of the structure of the high-latitude ionospheric F region during meridional HF propagation

NASA Astrophysics Data System (ADS)

Andreev, M. Yu.; Mingaleva, G. I.; Mingalev, V. S.

2007-08-01

A previously developed model of the high-latitude ionosphere is used to calculate the distribution of the ionospheric parameters in the polar region. A specific method for specifying input parameters of the mathematical model, using the experimental data obtained by the method of satellite radio tomography, is used in this case. The spatial distributions of the ionospheric parameters characterized by a complex inhomogeneous structure in the high-latitude region, calculated with the help of the mathematical model, are used to simulate the HF propagation along the meridionally oriented radio paths extending from middle to high latitudes. The method for improving the HF communication between a midlatitude transmitter and a polar-cap receiver is proposed.

Spatial and temporal distribution of Pu in the Northwest Pacific Ocean using modern coral archives.

PubMed

Lindahl, Patric; Andersen, Morten B; Keith-Roach, Miranda; Worsfold, Paul; Hyeong, Kiseong; Choi, Min-Seok; Lee, Sang-Hoon

2012-04-01

Historical (239)Pu activity concentrations and (240)Pu/(239)Pu atom ratios were determined in skeletons of dated modern corals collected from three locations (Chuuk Lagoon, Ishigaki Island and Iki Island) to identify spatial and temporal variations in Pu inputs to the Northwest Pacific Ocean. The main Pu source in the Northwest Pacific is fallout from atmospheric nuclear weapons testing which consists of global fallout and close-in fallout from the former US Pacific Proving Grounds (PPG) in the Marshall Islands. PPG close-in fallout dominated the Pu input in the 1950s, as was observed with higher (240)Pu/(239)Pu atom ratios (>0.30) at the Ishigaki site. Specific fallout Pu contamination from the Nagasaki atomic bomb and the Ivy Mike thermonuclear detonation at the PPG were identified at Ishigaki Island from the (240)Pu/(239)Pu atom ratios of 0.07 and 0.46, respectively. During the 1960s and 1970s, global fallout was the major Pu source to the Northwest Pacific with over 60% contribution to the total Pu. After the cessation of the atmospheric nuclear tests, the PPG again dominated the Pu input due to the continuous transport of remobilised Pu from the Marshall Islands along the North Equatorial Current and the subsequent Kuroshio Current. The Pu contributions from the PPG in recent coral bands (1984 onwards) varied over time with average estimated PPG contributions between 54% and 72% depending on location. Copyright © 2011 Elsevier Ltd. All rights reserved.

Use of MODIS Sensor Images Combined with Reanalysis Products to Retrieve Net Radiation in Amazonia

PubMed Central

de Oliveira, Gabriel; Brunsell, Nathaniel A.; Moraes, Elisabete C.; Bertani, Gabriel; dos Santos, Thiago V.; Shimabukuro, Yosio E.; Aragão, Luiz E. O. C.

2016-01-01

In the Amazon region, the estimation of radiation fluxes through remote sensing techniques is hindered by the lack of ground measurements required as input in the models, as well as the difficulty to obtain cloud-free images. Here, we assess an approach to estimate net radiation (Rn) and its components under all-sky conditions for the Amazon region through the Surface Energy Balance Algorithm for Land (SEBAL) model utilizing only remote sensing and reanalysis data. The study period comprised six years, between January 2001–December 2006, and images from MODIS sensor aboard the Terra satellite and GLDAS reanalysis products were utilized. The estimates were evaluated with flux tower measurements within the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) project. Comparison between estimates obtained by the proposed method and observations from LBA towers showed errors between 12.5% and 16.4% and 11.3% and 15.9% for instantaneous and daily Rn, respectively. Our approach was adequate to minimize the problem related to strong cloudiness over the region and allowed to map consistently the spatial distribution of net radiation components in Amazonia. We conclude that the integration of reanalysis products and satellite data, eliminating the need for surface measurements as input model, was a useful proposition for the spatialization of the radiation fluxes in the Amazon region, which may serve as input information needed by algorithms that aim to determine evapotranspiration, the most important component of the Amazon hydrological balance. PMID:27347957

Use of MODIS Sensor Images Combined with Reanalysis Products to Retrieve Net Radiation in Amazonia.

PubMed

de Oliveira, Gabriel; Brunsell, Nathaniel A; Moraes, Elisabete C; Bertani, Gabriel; Dos Santos, Thiago V; Shimabukuro, Yosio E; Aragão, Luiz E O C

2016-06-24

In the Amazon region, the estimation of radiation fluxes through remote sensing techniques is hindered by the lack of ground measurements required as input in the models, as well as the difficulty to obtain cloud-free images. Here, we assess an approach to estimate net radiation (Rn) and its components under all-sky conditions for the Amazon region through the Surface Energy Balance Algorithm for Land (SEBAL) model utilizing only remote sensing and reanalysis data. The study period comprised six years, between January 2001-December 2006, and images from MODIS sensor aboard the Terra satellite and GLDAS reanalysis products were utilized. The estimates were evaluated with flux tower measurements within the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) project. Comparison between estimates obtained by the proposed method and observations from LBA towers showed errors between 12.5% and 16.4% and 11.3% and 15.9% for instantaneous and daily Rn, respectively. Our approach was adequate to minimize the problem related to strong cloudiness over the region and allowed to map consistently the spatial distribution of net radiation components in Amazonia. We conclude that the integration of reanalysis products and satellite data, eliminating the need for surface measurements as input model, was a useful proposition for the spatialization of the radiation fluxes in the Amazon region, which may serve as input information needed by algorithms that aim to determine evapotranspiration, the most important component of the Amazon hydrological balance.

Photonic lantern adaptive spatial mode control in LMA fiber amplifiers.

PubMed

Montoya, Juan; Aleshire, Chris; Hwang, Christopher; Fontaine, Nicolas K; Velázquez-Benítez, Amado; Martz, Dale H; Fan, T Y; Ripin, Dan

2016-02-22

We demonstrate adaptive-spatial mode control (ASMC) in few-moded double-clad large mode area (LMA) fiber amplifiers by using an all-fiber-based photonic lantern. Three single-mode fiber inputs are used to adaptively inject the appropriate superposition of input modes in a multimode gain fiber to achieve the desired mode at the output. By actively adjusting the relative phase of the single-mode inputs, near-unity coherent combination resulting in a single fundamental mode at the output is achieved.

System and Method for Providing Model-Based Alerting of Spatial Disorientation to a Pilot

NASA Technical Reports Server (NTRS)

Johnson, Steve (Inventor); Conner, Kevin J (Inventor); Mathan, Santosh (Inventor)

2015-01-01

A system and method monitor aircraft state parameters, for example, aircraft movement and flight parameters, applies those inputs to a spatial disorientation model, and makes a prediction of when pilot may become spatially disoriented. Once the system predicts a potentially disoriented pilot, the sensitivity for alerting the pilot to conditions exceeding a threshold can be increased and allow for an earlier alert to mitigate the possibility of an incorrect control input.

Shaping propagation invariant laser beams

NASA Astrophysics Data System (ADS)

Soskind, Michael; Soskind, Rose; Soskind, Yakov

2015-11-01

Propagation-invariant structured laser beams possess several unique properties and play an important role in various photonics applications. The majority of propagation invariant beams are produced in the form of laser modes emanating from stable laser cavities. Therefore, their spatial structure is limited by the intracavity mode formation. We show that several types of anamorphic optical systems (AOSs) can be effectively employed to shape laser beams into a variety of propagation invariant structured fields with different shapes and phase distributions. We present a propagation matrix approach for designing AOSs and defining mode-matching conditions required for preserving propagation invariance of the output shaped fields. The propagation matrix approach was selected, as it provides a more straightforward approach in designing AOSs for shaping propagation-invariant laser beams than the alternative technique based on the Gouy phase evolution, especially in the case of multielement AOSs. Several practical configurations of optical systems that are suitable for shaping input laser beams into a diverse variety of structured propagation invariant laser beams are also presented. The laser beam shaping approach was applied by modeling propagation characteristics of several input laser beam types, including Hermite-Gaussian, Laguerre-Gaussian, and Ince-Gaussian structured field distributions. The influence of the Ince-Gaussian beam semifocal separation parameter and the azimuthal orientation between the input laser beams and the AOSs onto the resulting shape of the propagation invariant laser beams is presented as well.

Impaired hippocampal rate coding after lesions of the lateral entorhinal cortex.

PubMed

Lu, Li; Leutgeb, Jill K; Tsao, Albert; Henriksen, Espen J; Leutgeb, Stefan; Barnes, Carol A; Witter, Menno P; Moser, May-Britt; Moser, Edvard I

2013-08-01

In the hippocampus, spatial and non-spatial parameters may be represented by a dual coding scheme, in which coordinates in space are expressed by the collective firing locations of place cells and the diversity of experience at these locations is encoded by orthogonal variations in firing rates. Although the spatial signal may reflect input from medial entorhinal cortex, the sources of the variations in firing rate have not been identified. We found that rate variations in rat CA3 place cells depended on inputs from the lateral entorhinal cortex (LEC). Hippocampal rate remapping, induced by changing the shape or the color configuration of the environment, was impaired by lesions in those parts of the ipsilateral LEC that provided the densest input to the hippocampal recording position. Rate remapping was not observed in LEC itself. The findings suggest that LEC inputs are important for efficient rate coding in the hippocampus.

Cortical feedback signals generalise across different spatial frequencies of feedforward inputs.

PubMed

Revina, Yulia; Petro, Lucy S; Muckli, Lars

2017-09-22

Visual processing in cortex relies on feedback projections contextualising feedforward information flow. Primary visual cortex (V1) has small receptive fields and processes feedforward information at a fine-grained spatial scale, whereas higher visual areas have larger, spatially invariant receptive fields. Therefore, feedback could provide coarse information about the global scene structure or alternatively recover fine-grained structure by targeting small receptive fields in V1. We tested if feedback signals generalise across different spatial frequencies of feedforward inputs, or if they are tuned to the spatial scale of the visual scene. Using a partial occlusion paradigm, functional magnetic resonance imaging (fMRI) and multivoxel pattern analysis (MVPA) we investigated whether feedback to V1 contains coarse or fine-grained information by manipulating the spatial frequency of the scene surround outside an occluded image portion. We show that feedback transmits both coarse and fine-grained information as it carries information about both low (LSF) and high spatial frequencies (HSF). Further, feedback signals containing LSF information are similar to feedback signals containing HSF information, even without a large overlap in spatial frequency bands of the HSF and LSF scenes. Lastly, we found that feedback carries similar information about the spatial frequency band across different scenes. We conclude that cortical feedback signals contain information which generalises across different spatial frequencies of feedforward inputs. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Spatial Learning and Action Planning in a Prefrontal Cortical Network Model

PubMed Central

Martinet, Louis-Emmanuel; Sheynikhovich, Denis; Benchenane, Karim; Arleo, Angelo

2011-01-01

The interplay between hippocampus and prefrontal cortex (PFC) is fundamental to spatial cognition. Complementing hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive “insight” capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial planning, including prospective coding and distance-to-goal correlates. PMID:21625569

Cardiac neuronal hierarchy in health and disease.

PubMed

Armour, J Andrew

2004-08-01

The cardiac neuronal hierarchy can be represented as a redundant control system made up of spatially distributed cell stations comprising afferent, efferent, and interconnecting neurons. Its peripheral and central neurons are in constant communication with one another such that, for the most part, it behaves as a stochastic control system. Neurons distributed throughout this hierarchy interconnect via specific linkages such that each neuronal cell station is involved in temporally dependent cardio-cardiac reflexes that control overlapping, spatially organized cardiac regions. Its function depends primarily, but not exclusively, on inputs arising from afferent neurons transducing the cardiovascular milieu to directly or indirectly (via interconnecting neurons) modify cardiac motor neurons coordinating regional cardiac behavior. As the function of the whole is greater than that of its individual parts, stable cardiac control occurs most of the time in the absence of direct cause and effect. During altered cardiac status, its redundancy normally represents a stabilizing feature. However, in the presence of regional myocardial ischemia, components within the intrinsic cardiac nervous system undergo pathological change. That, along with any consequent remodeling of the cardiac neuronal hierarchy, alters its spatially and temporally organized reflexes such that populations of neurons, acting in isolation, may destabilize efferent neuronal control of regional cardiac electrical and/or mechanical events.

A Development of Nonstationary Regional Frequency Analysis Model with Large-scale Climate Information: Its Application to Korean Watershed

NASA Astrophysics Data System (ADS)

Kim, Jin-Young; Kwon, Hyun-Han; Kim, Hung-Soo

2015-04-01

The existing regional frequency analysis has disadvantages in that it is difficult to consider geographical characteristics in estimating areal rainfall. In this regard, this study aims to develop a hierarchical Bayesian model based nonstationary regional frequency analysis in that spatial patterns of the design rainfall with geographical information (e.g. latitude, longitude and altitude) are explicitly incorporated. This study assumes that the parameters of Gumbel (or GEV distribution) are a function of geographical characteristics within a general linear regression framework. Posterior distribution of the regression parameters are estimated by Bayesian Markov Chain Monte Carlo (MCMC) method, and the identified functional relationship is used to spatially interpolate the parameters of the distributions by using digital elevation models (DEM) as inputs. The proposed model is applied to derive design rainfalls over the entire Han-river watershed. It was found that the proposed Bayesian regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis. In addition, the model showed an advantage in terms of quantifying uncertainty of the design rainfall and estimating the area rainfall considering geographical information. Finally, comprehensive discussion on design rainfall in the context of nonstationary will be presented. KEYWORDS: Regional frequency analysis, Nonstationary, Spatial information, Bayesian Acknowledgement This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Hippocampal-prefrontal input supports spatial encoding in working memory.

PubMed

Spellman, Timothy; Rigotti, Mattia; Ahmari, Susanne E; Fusi, Stefano; Gogos, Joseph A; Gordon, Joshua A

2015-06-18

Spatial working memory, the caching of behaviourally relevant spatial cues on a timescale of seconds, is a fundamental constituent of cognition. Although the prefrontal cortex and hippocampus are known to contribute jointly to successful spatial working memory, the anatomical pathway and temporal window for the interaction of these structures critical to spatial working memory has not yet been established. Here we find that direct hippocampal-prefrontal afferents are critical for encoding, but not for maintenance or retrieval, of spatial cues in mice. These cues are represented by the activity of individual prefrontal units in a manner that is dependent on hippocampal input only during the cue-encoding phase of a spatial working memory task. Successful encoding of these cues appears to be mediated by gamma-frequency synchrony between the two structures. These findings indicate a critical role for the direct hippocampal-prefrontal afferent pathway in the continuous updating of task-related spatial information during spatial working memory.

Light adaptation alters the source of inhibition to the mouse retinal OFF pathway

PubMed Central

Mazade, Reece E.

2013-01-01

Sensory systems must avoid saturation to encode a wide range of stimulus intensities. One way the retina accomplishes this is by using both dim-light-sensing rod and bright-light-sensing cone photoreceptor circuits. OFF cone bipolar cells are a key point in this process, as they receive both excitatory input from cones and inhibitory input from AII amacrine cells via the rod pathway. However, in addition to AII amacrine cell input, other inhibitory inputs from cone pathways also modulate OFF cone bipolar cell light signals. It is unknown how these inhibitory inputs to OFF cone bipolar cells change when switching between rod and cone pathways or whether all OFF cone bipolar cells receive rod pathway input. We found that one group of OFF cone bipolar cells (types 1, 2, and 4) receive rod-mediated inhibitory inputs that likely come from the rod-AII amacrine cell pathway, while another group of OFF cone bipolar cells (type 3) do not. In both cases, dark-adapted rod-dominant light responses showed a significant contribution of glycinergic inhibition, which decreased with light adaptation and was, surprisingly, compensated by an increase in GABAergic inhibition. As GABAergic input has distinct timing and spatial spread from glycinergic input, a shift from glycinergic to GABAergic inhibition could significantly alter OFF cone bipolar cell signaling to downstream OFF ganglion cells. Larger GABAergic input could reflect an adjustment of OFF bipolar cell spatial inhibition, which may be one mechanism that contributes to retinal spatial sensitivity in the light. PMID:23926034

Optimizing information flow in small genetic networks. IV. Spatial coupling

NASA Astrophysics Data System (ADS)

Sokolowski, Thomas R.; Tkačik, Gašper

2015-06-01

We typically think of cells as responding to external signals independently by regulating their gene expression levels, yet they often locally exchange information and coordinate. Can such spatial coupling be of benefit for conveying signals subject to gene regulatory noise? Here we extend our information-theoretic framework for gene regulation to spatially extended systems. As an example, we consider a lattice of nuclei responding to a concentration field of a transcriptional regulator (the input) by expressing a single diffusible target gene. When input concentrations are low, diffusive coupling markedly improves information transmission; optimal gene activation functions also systematically change. A qualitatively different regulatory strategy emerges where individual cells respond to the input in a nearly steplike fashion that is subsequently averaged out by strong diffusion. While motivated by early patterning events in the Drosophila embryo, our framework is generically applicable to spatially coupled stochastic gene expression models.

High-energy Gamma Rays from the Milky Way: Three-dimensional Spatial Models for the Cosmic-Ray and Radiation Field Densities in the Interstellar Medium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Porter, T. A.; Moskalenko, I. V.; Jóhannesson, G., E-mail: tporter@stanford.edu

High-energy γ -rays of interstellar origin are produced by the interaction of cosmic-ray (CR) particles with the diffuse gas and radiation fields in the Galaxy. The main features of this emission are well understood and are reproduced by existing CR propagation models employing 2D galactocentric cylindrically symmetrical geometry. However, the high-quality data from instruments like the Fermi Large Area Telescope reveal significant deviations from the model predictions on few to tens of degrees scales, indicating the need to include the details of the Galactic spiral structure and thus requiring 3D spatial modeling. In this paper, the high-energy interstellar emissions frommore » the Galaxy are calculated using the new release of the GALPROP code employing 3D spatial models for the CR source and interstellar radiation field (ISRF) densities. Three models for the spatial distribution of CR sources are used that are differentiated by their relative proportion of input luminosity attributed to the smooth disk or spiral arms. Two ISRF models are developed based on stellar and dust spatial density distributions taken from the literature that reproduce local near- to far-infrared observations. The interstellar emission models that include arms and bulges for the CR source and ISRF densities provide plausible physical interpretations for features found in the residual maps from high-energy γ -ray data analysis. The 3D models for CR and ISRF densities provide a more realistic basis that can be used for the interpretation of the nonthermal interstellar emissions from the Galaxy.« less

Spatiotemporal Airy Ince-Gaussian wave packets in strongly nonlocal nonlinear media.

PubMed

Peng, Xi; Zhuang, Jingli; Peng, Yulian; Li, DongDong; Zhang, Liping; Chen, Xingyu; Zhao, Fang; Deng, Dongmei

2018-03-08

The self-accelerating Airy Ince-Gaussian (AiIG) and Airy helical Ince-Gaussian (AihIG) wave packets in strongly nonlocal nonlinear media (SNNM) are obtained by solving the strongly nonlocal nonlinear Schrödinger equation. For the first time, the propagation properties of three dimensional localized AiIG and AihIG breathers and solitons in the SNNM are demonstrated, these spatiotemporal wave packets maintain the self-accelerating and approximately non-dispersion properties in temporal dimension, periodically oscillating (breather state) or steady (soliton state) in spatial dimension. In particular, their numerical experiments of spatial intensity distribution, numerical simulations of spatiotemporal distribution, as well as the transverse energy flow and the angular momentum in SNNM are presented. Typical examples of the obtained solutions are based on the ratio between the input power and the critical power, the ellipticity and the strong nonlocality parameter. The comparisons of analytical solutions with numerical simulations and numerical experiments of the AiIG and AihIG optical solitons show that the numerical results agree well with the analytical solutions in the case of strong nonlocality.

Position-sensitive proportional counter with low-resistance metal-wire anode

DOEpatents

Kopp, Manfred K.

1980-01-01

A position-sensitive proportional counter circuit is provided which allows the use of a conventional (low-resistance, metal-wire anode) proportional counter for spatial resolution of an ionizing event along the anode of the counter. A pair of specially designed active-capacitance preamplifiers are used to terminate the anode ends wherein the anode is treated as an RC line. The preamplifiers act as stabilized active capacitance loads and each is composed of a series-feedback, low-noise amplifier, a unity-gain, shunt-feedback amplifier whose output is connected through a feedback capacitor to the series-feedback amplifier input. The stabilized capacitance loading of the anode allows distributed RC-line position encoding and subsequent time difference decoding by sensing the difference in rise times of pulses at the anode ends where the difference is primarily in response to the distributed capacitance along the anode. This allows the use of lower resistance wire anodes for spatial radiation detection which simplifies the counter construction and handling of the anodes, and stabilizes the anode resistivity at high count rates (>10.sup.6 counts/sec).

Development of a Bayesian Estimator for Audio-Visual Integration: A Neurocomputational Study

PubMed Central

Ursino, Mauro; Crisafulli, Andrea; di Pellegrino, Giuseppe; Magosso, Elisa; Cuppini, Cristiano

2017-01-01

The brain integrates information from different sensory modalities to generate a coherent and accurate percept of external events. Several experimental studies suggest that this integration follows the principle of Bayesian estimate. However, the neural mechanisms responsible for this behavior, and its development in a multisensory environment, are still insufficiently understood. We recently presented a neural network model of audio-visual integration (Neural Computation, 2017) to investigate how a Bayesian estimator can spontaneously develop from the statistics of external stimuli. Model assumes the presence of two unimodal areas (auditory and visual) topologically organized. Neurons in each area receive an input from the external environment, computed as the inner product of the sensory-specific stimulus and the receptive field synapses, and a cross-modal input from neurons of the other modality. Based on sensory experience, synapses were trained via Hebbian potentiation and a decay term. Aim of this work is to improve the previous model, including a more realistic distribution of visual stimuli: visual stimuli have a higher spatial accuracy at the central azimuthal coordinate and a lower accuracy at the periphery. Moreover, their prior probability is higher at the center, and decreases toward the periphery. Simulations show that, after training, the receptive fields of visual and auditory neurons shrink to reproduce the accuracy of the input (both at the center and at the periphery in the visual case), thus realizing the likelihood estimate of unimodal spatial position. Moreover, the preferred positions of visual neurons contract toward the center, thus encoding the prior probability of the visual input. Finally, a prior probability of the co-occurrence of audio-visual stimuli is encoded in the cross-modal synapses. The model is able to simulate the main properties of a Bayesian estimator and to reproduce behavioral data in all conditions examined. In particular, in unisensory conditions the visual estimates exhibit a bias toward the fovea, which increases with the level of noise. In cross modal conditions, the SD of the estimates decreases when using congruent audio-visual stimuli, and a ventriloquism effect becomes evident in case of spatially disparate stimuli. Moreover, the ventriloquism decreases with the eccentricity. PMID:29046631

Interplay between spatially explicit sediment sourcing, hierarchical river-network structure, and in-channel bed material sediment transport and storage dynamics

NASA Astrophysics Data System (ADS)

Czuba, Jonathan A.; Foufoula-Georgiou, Efi; Gran, Karen B.; Belmont, Patrick; Wilcock, Peter R.

2017-05-01

Understanding how sediment moves along source to sink pathways through watersheds—from hillslopes to channels and in and out of floodplains—is a fundamental problem in geomorphology. We contribute to advancing this understanding by modeling the transport and in-channel storage dynamics of bed material sediment on a river network over a 600 year time period. Specifically, we present spatiotemporal changes in bed sediment thickness along an entire river network to elucidate how river networks organize and process sediment supply. We apply our model to sand transport in the agricultural Greater Blue Earth River Basin in Minnesota. By casting the arrival of sediment to links of the network as a Poisson process, we derive analytically (under supply-limited conditions) the time-averaged probability distribution function of bed sediment thickness for each link of the river network for any spatial distribution of inputs. Under transport-limited conditions, the analytical assumptions of the Poisson arrival process are violated (due to in-channel storage dynamics) where we find large fluctuations and periodicity in the time series of bed sediment thickness. The time series of bed sediment thickness is the result of dynamics on a network in propagating, altering, and amalgamating sediment inputs in sometimes unexpected ways. One key insight gleaned from the model is that there can be a small fraction of reaches with relatively low-transport capacity within a nonequilibrium river network acting as "bottlenecks" that control sediment to downstream reaches, whereby fluctuations in bed elevation can dissociate from signals in sediment supply.

An integrated assessment of soil erosion dynamics with special emphasis on gully erosion: Case studies from South Africa and Iran

NASA Astrophysics Data System (ADS)

Maerker, Michael; Sommer, Christian; Zakerinejad, Reza; Cama, Elena

2017-04-01

Soil erosion by water is a significant problem in arid and semi arid areas of large parts of Iran. Water erosion is one of the most effective phenomena that leads to decreasing soil productivity and pollution of water resources. Especially in semiarid areas like in the Mazayjan watershed in the Southwestern Fars province as well as in the Mkomazi catchment in Kwa Zulu Natal, South Africa, gully erosion contributes to the sediment dynamics in a significant way. Consequently, the intention of this research is to identify the different types of soil erosion processes acting in the area with a stochastic approach and to assess the process dynamics in an integrative way. Therefore, we applied GIS, and satellite image analysis techniques to derive input information for the numeric models. For sheet and rill erosion the Unit Stream Power-based Erosion Deposition Model (USPED) was utilized. The spatial distribution of gully erosion was assessed using a statistical approach which used three variables (stream power index, slope, and flow accumulation) to predict the spatial distribution of gullies in the study area. The eroded gully volumes were estimated for a multiple years period by fieldwork and Google Earth high resolution images as well as with structure for motion algorithm. Finally, the gully retreat rates were integrated into the USPED model. The results show that the integration of the SPI approach to quantify gully erosion with the USPED model is a suitable method to qualitatively and quantitatively assess water erosion processes in data scarce areas. The application of GIS and stochastic model approaches to spatialize the USPED model input yield valuable results for the prediction of soil erosion in the test areas. The results of this research help to develop an appropriate management of soil and water resources in the study areas.

MODFLOW 2000 Head Uncertainty, a First-Order Second Moment Method

USGS Publications Warehouse

Glasgow, H.S.; Fortney, M.D.; Lee, J.; Graettinger, A.J.; Reeves, H.W.

2003-01-01

A computationally efficient method to estimate the variance and covariance in piezometric head results computed through MODFLOW 2000 using a first-order second moment (FOSM) approach is presented. This methodology employs a first-order Taylor series expansion to combine model sensitivity with uncertainty in geologic data. MODFLOW 2000 is used to calculate both the ground water head and the sensitivity of head to changes in input data. From a limited number of samples, geologic data are extrapolated and their associated uncertainties are computed through a conditional probability calculation. Combining the spatially related sensitivity and input uncertainty produces the variance-covariance matrix, the diagonal of which is used to yield the standard deviation in MODFLOW 2000 head. The variance in piezometric head can be used for calibrating the model, estimating confidence intervals, directing exploration, and evaluating the reliability of a design. A case study illustrates the approach, where aquifer transmissivity is the spatially related uncertain geologic input data. The FOSM methodology is shown to be applicable for calculating output uncertainty for (1) spatially related input and output data, and (2) multiple input parameters (transmissivity and recharge).

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

There is a notable discrepancy between detailed sediment budget studies in small headwater catchments (< 102 km2) focusing on the identification of sedimentary landforms in the field (e.g. talus cones, moraine deposits, fans) and large scale studies (> 103 km2) in higher order catchments applying modeling and/or remote sensing based approaches for major sediment storage delineation. To bridge the gap between these scales, we compiled an inventory of sediment and bedrock coverage from field mapping, remote sensing analysis and published data for five key sites in the Upper Rhone Basin (Val d'Illiez, Val de la Liène, Turtmanntal, Lötschental, Goms; 360.3 km2, equivalent to 6.7% of the Upper Rhone Basin). This inventory was used as training and testing data for the classification of sediment and bedrock cover. From a digital elevation model (2 × 2 m ground resolution) and Landsat imagery we derived 22 parameters characterizing local morphometry, topography and position, contributing area, and climatic and biotic factors on different spatial scales, which were used as inputs for different statistical models (logistic regression, principal component logistic regression, generalized additive model). Best prediction results with an excellent performance (mean AUROC: 0.8721 ± 0.0012) and both a high spatial and non-spatial transferability were achieved applying a generalized additive model. Since the model has a high thematic consistency, the independent input variables chosen based on their geomorphic relevance are suitable to model the spatial distribution of sediment. Our high-resolution classification shows that 53.5 ± 21.7% of the Upper Rhone Basin are covered with sediment. These are by no means evenly distributed: small headwaters (< 5 km2) feature a very strong variability in sediment coverage, with watersheds drowning in sediments juxtaposed to watersheds devoid of sediment cover. In contrast, larger watersheds predominantly show a bimodal distribution, with highest densities for bedrock (30-40%) being consistently lower than for sediment cover (60-65%). Earlier studies quantifying sedimentary cover and volume focus on the broad glacially overdeepened Rhone Valley that accounts for c. 9% of our study area. While our data support its importance, we conservatively estimate that the remaining 90% of sediment cover, mainly located outside trunk valleys, account for a volume of 2.6-13 km3, i.e. 2-16% of the estimated sediment volume stored in the Rhone Valley between Brig and Lake Geneva. Furthermore, our data reveal increased relative sediment cover in areas deglaciated since the Little Ice Age, as compared to headwater regions without this recent glacial imprint. We therefore conclude that sediment storage in low-order valleys, often neglected in large scale studies, constitutes a significant component of large scale sediment budgets that needs to be better included into future analysis.

Time as an Observable in Nonrelativistic Quantum Mechanics

NASA Technical Reports Server (NTRS)

Hahne, G. E.

2003-01-01

The argument follows from the viewpoint that quantum mechanics is taken not in the usual form involving vectors and linear operators in Hilbert spaces, but as a boundary value problem for a special class of partial differential equations-in the present work, the nonrelativistic Schrodinger equation for motion of a structureless particle in four- dimensional space-time in the presence of a potential energy distribution that can be time-as well as space-dependent. The domain of interest is taken to be one of two semi-infinite boxes, one bounded by two t=constant planes and the other by two t=constant planes. Each gives rise to a characteristic boundary value problem: one in which the initial, input values on one t=constant wall are given, with zero asymptotic wavefunction values in all spatial directions, the output being the values on the second t=constant wall; the second with certain input values given on both z=constant walls, with zero asymptotic values in all directions involving time and the other spatial coordinates, the output being the complementary values on the z=constant walls. The first problem corresponds to ordinary quantum mechanics; the second, to a fully time-dependent version of a problem normally considered only for the steady state (time-independent Schrodinger equation). The second problem is formulated in detail. A conserved indefinite metric is associated with space-like propagation, where the sign of the norm of a unidirectional state corresponds to its spatial direction of travel.

Human motion tracking by temporal-spatial local gaussian process experts.

PubMed

Zhao, Xu; Fu, Yun; Liu, Yuncai

2011-04-01

Human pose estimation via motion tracking systems can be considered as a regression problem within a discriminative framework. It is always a challenging task to model the mapping from observation space to state space because of the high-dimensional characteristic in the multimodal conditional distribution. In order to build the mapping, existing techniques usually involve a large set of training samples in the learning process which are limited in their capability to deal with multimodality. We propose, in this work, a novel online sparse Gaussian Process (GP) regression model to recover 3-D human motion in monocular videos. Particularly, we investigate the fact that for a given test input, its output is mainly determined by the training samples potentially residing in its local neighborhood and defined in the unified input-output space. This leads to a local mixture GP experts system composed of different local GP experts, each of which dominates a mapping behavior with the specific covariance function adapting to a local region. To handle the multimodality, we combine both temporal and spatial information therefore to obtain two categories of local experts. The temporal and spatial experts are integrated into a seamless hybrid system, which is automatically self-initialized and robust for visual tracking of nonlinear human motion. Learning and inference are extremely efficient as all the local experts are defined online within very small neighborhoods. Extensive experiments on two real-world databases, HumanEva and PEAR, demonstrate the effectiveness of our proposed model, which significantly improve the performance of existing models.

Assessing the required additional organic inputs to soils to reach the 4 per 1000 objective at the global scale: a RothC project

NASA Astrophysics Data System (ADS)

Lutfalla, Suzanne; Skalsky, Rastislav; Martin, Manuel; Balkovic, Juraj; Havlik, Petr; Soussana, Jean-François

2017-04-01

The 4 per 1000 Initiative underlines the role of soil organic matter in addressing the three-fold challenge of food security, adaptation of the land sector to climate change, and mitigation of human-induced GHG emissions. It sets an ambitious global target of a 0.4% (4/1000) annual increase in top soil organic carbon (SOC) stock. The present collaborative project between the 4 per 1000 research program, INRA and IIASA aims at providing a first global assessment of the translation of this soil organic carbon sequestration target into the equivalent organic matter inputs target. Indeed, soil organic carbon builds up in the soil through different processes leading to an increased input of carbon to the system (by increasing returns to the soil for instance) or a decreased output of carbon from the system (mainly by biodegradation and mineralization processes). Here we answer the question of how much extra organic matter must be added to agricultural soils every year (in otherwise unchanged climatic conditions) in order to guarantee a 0.4% yearly increase of total soil organic carbon stocks (40cm soil depth is considered). We use the RothC model of soil organic matter turnover on a spatial grid over 10 years to model two situations for croplands: a first situation where soil organic carbon remains constant (system at equilibrium) and a second situation where soil organic matter increases by 0.4% every year. The model accounts for the effects of soil type, temperature, moisture content and plant cover on the turnover process, it is run on a monthly time step, and it can simulate the needed organic input to sustain a certain SOC stock (or evolution of SOC stock). These two SOC conditions lead to two average yearly plant inputs over 10 years. The difference between the two simulated inputs represent the additional yearly input needed to reach the 4 per 1000 objective (input_eq for inputs needed for SOC to remain constant; input_4/1000 for inputs needed for SOC to reach the 4 per 1000 target). A spatial representation of this difference shows the distribution of the required returns to the soil. This first tool will provide the basis for the next steps: choosing and implementing practices to obtain the required additional input. Results will be presented from simulations at the regional scale (country: Slovakia) and at the global scale (0,5° grid resolution). Soil input data comes from the HWSD, climatic input data comes from AgMERRA climate dataset averaged of a 30 years period (1980-2010). They show that, at the global scale, given some data corrections which will be presented and discussed, the 4 per 1000 increase in top soil organic carbon can be reached with a median additional input of +0.89 tC/ha/year for cropland soils.

Development and Implementation of the DTOPLATS-MP land surface model over the Continental US at 30 meters

NASA Astrophysics Data System (ADS)

Chaney, N.; Wood, E. F.

2014-12-01

The increasing accessibility of high-resolution land data (< 100 m) and high performance computing allows improved parameterizations of subgrid hydrologic processes in macroscale land surface models. Continental scale fully distributed modeling at these spatial scales is possible; however, its practicality for operational use is still unknown due to uncertainties in input data, model parameters, and storage requirements. To address these concerns, we propose a modeling framework that provides the spatial detail of a fully distributed model yet maintains the benefits of a semi-distributed model. In this presentation we will introduce DTOPLATS-MP, a coupling between the NOAH-MP land surface model and the Dynamic TOPMODEL hydrologic model. This new model captures a catchment's spatial heterogeneity by clustering high-resolution land datasets (soil, topography, and land cover) into hundreds of hydrologic similar units (HSUs). A prior DEM analysis defines the connections between each HSU. At each time step, the 1D land surface model updates each HSU; the HSUs then interact laterally via the subsurface and surface. When compared to the fully distributed form of the model, this framework allows a significant decrease in computation and storage while providing most of the same information and enabling parameter transferability. As a proof of concept, we will show how this new modeling framework can be run over CONUS at a 30-meter spatial resolution. For each catchment in the WBD HUC-12 dataset, the model is run between 2002 and 2012 using available high-resolution continental scale land and meteorological datasets over CONUS (dSSURGO, NLCD, NED, and NCEP Stage IV). For each catchment, the model is run with 1000 model parameter sets obtained from a Latin hypercube sample. This exercise will illustrate the feasibility of running the model operationally at continental scales while accounting for model parameter uncertainty.

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

USGS Publications Warehouse

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

1996-01-01

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

A global approach to estimate irrigated areas - a comparison between different data and statistics

NASA Astrophysics Data System (ADS)

Meier, Jonas; Zabel, Florian; Mauser, Wolfram

2018-02-01

Agriculture is the largest global consumer of water. Irrigated areas constitute 40 % of the total area used for agricultural production (FAO, 2014a) Information on their spatial distribution is highly relevant for regional water management and food security. Spatial information on irrigation is highly important for policy and decision makers, who are facing the transition towards more efficient sustainable agriculture. However, the mapping of irrigated areas still represents a challenge for land use classifications, and existing global data sets differ strongly in their results. The following study tests an existing irrigation map based on statistics and extends the irrigated area using ancillary data. The approach processes and analyzes multi-temporal normalized difference vegetation index (NDVI) SPOT-VGT data and agricultural suitability data - both at a spatial resolution of 30 arcsec - incrementally in a multiple decision tree. It covers the period from 1999 to 2012. The results globally show a 18 % larger irrigated area than existing approaches based on statistical data. The largest differences compared to the official national statistics are found in Asia and particularly in China and India. The additional areas are mainly identified within already known irrigated regions where irrigation is more dense than previously estimated. The validation with global and regional products shows the large divergence of existing data sets with respect to size and distribution of irrigated areas caused by spatial resolution, the considered time period and the input data and assumption made.

Continuous rainfall simulation for regional flood risk assessment - application in the Austrian Alps

NASA Astrophysics Data System (ADS)

Salinas, Jose Luis; Nester, Thomas; Komma, Jürgen; Blöschl, Günter

2017-04-01

Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of the observed rainfall characteristics, such as regional intensity-duration-frequency curves, is necessary to adequately model the magnitude and frequency of the flood peaks. Furthermore, the replication of the observed rainfall spatial and temporal correlations allows to model important other hydrological features like antecedent soil moisture conditions before extreme rainfall events. In this work, we present an application in the Tirol region (Austrian alps) of a modification of the model presented by Bardossy and Platte (1992), where precipitation is modeled on a station basis as a mutivariate autoregressive model (mAr) in a Normal space, and then transformed to a Gamma-distributed space. For the sake of simplicity, the parameters of the Gamma distributions are assumed to vary monthly according to a sinusoidal function, and are calibrated trying to simultaneously reproduce i) mean annual rainfall, ii) mean daily rainfall amounts, iii) standard deviations of daily rainfall amounts, and iv) 24-hours intensity duration frequency curve. The calibration of the spatial and temporal correlation parameters is performed in a way that the intensity-duration-frequency curves aggregated at different spatial and temporal scales reproduce the measured ones. Bardossy, A., and E. J. Plate (1992), Space-time model for daily rainfall using atmospheric circulation patterns, Water Resour. Res., 28(5), 1247-1259, doi:10.1029/91WR02589.

GIS based spatial pattern analysis: Children with Hepatitis A in Turkey.

PubMed

Dogru, Ahmet Ozgur; David, Ruusa Magano; Ulugtekin, Necla; Goksel, Cigdem; Seker, Dursun Zafer; Sözen, Seval

2017-07-01

This study aimed to provide an insight into the geographic distribution of Hepatitis A incidence considering their temporal distribution, spatial patterns, hot spots and clusters identification in three different age-group (0-4, 5-9 and 10-14) in Turkey. Province based tabular data, including monthly numbers of Hepatitis A cases in children, and the populations from 2001 to 2011 were used as the basic input of the study. Time series maps were created using Geographic Information Systems (GIS) to introduce the temporal changes in the morbidity rates of Hepatitis A. The spatial variation of Hepatitis A was measured using Moran's I at the global level and the local indicators of spatial associations (LISAs) Moran's I and Getis-Ord G i *(d) in order to identify influential locations through clusters and hot spots detection of Hepatitis A cases. The morbidity rates in children under the age of 5 were found significantly lower than the other age-groups, whereas the age-group 5-9 revealed the highest morbidity rates in the study area. The morbidity of Hepatitis A was detected very high for the years 2001, and 2005-2007. The identification of the highly vulnerable provinces was conducted using local Moran's I and local Getis-Ord G i *(d). The majority of clusters and hot spots were detected to be agglomerated in the Eastern Mediterranean and South-Eastern Anatolian Regions and Ceyhan, Asi and Southeast part of Firat-Dicle river basins in Turkey. Copyright © 2017 Elsevier Inc. All rights reserved.

On the dual-cone nature of the conical refraction phenomenon.

PubMed

Turpin, A; Loiko, Yu; Kalkandjiev, T K; Tomizawa, H; Mompart, J

2015-04-15

In conical refraction (CR), a focused Gaussian input beam passing through a biaxial crystal and parallel to one of the optic axes is transformed into a pair of concentric bright rings split by a dark (Poggendorff) ring at the focal plane. Here, we show the generation of a CR transverse pattern that does not present the Poggendorff fine splitting at the focal plane, i.e., it forms a single light ring. This light ring is generated from a nonhomogeneously polarized input light beam obtained by using a spatially inhomogeneous polarizer that mimics the characteristic CR polarization distribution. This polarizer allows modulating the relative intensity between the two CR light cones in accordance with the recently proposed dual-cone model of the CR phenomenon. We show that the absence of interfering rings at the focal plane is caused by the selection of one of the two CR cones.

Multi-frequency entanglement router system

NASA Astrophysics Data System (ADS)

Erdmann, Reinhard; Hughes, David

2017-05-01

A high performance free-space Wavelength Division Multiplexed (WDM) transceiver system is assessed as to its viability for routing collinear entangled photons in place of the classical optical signals for which it was designed. Explicit calculations demonstrate that entanglement in the input state is retained through transit of the system without intrinsic loss. Introducing spatial degrees of freedom changed the entanglement so that it could be manifested at remote locations, as required in non-local Bell test measurements or Quantum Key Distribution (QKD) Protocols. It was also found that by adding proper components, the exit state could be changed from being frequency entangled to polarization entangled, with respect to the (remote) paths of the photons. Finally it was found possible to route a complete entangled state to either of the two remote users by proper selection of the discrete frequencies in the input state. Each entanglement in the photon states was maximal, hence suited for Quantum Information Processing (QIP) applications.

Quantum Correlations in Nonlocal Boson Sampling.

PubMed

Shahandeh, Farid; Lund, Austin P; Ralph, Timothy C

2017-09-22

Determination of the quantum nature of correlations between two spatially separated systems plays a crucial role in quantum information science. Of particular interest is the questions of if and how these correlations enable quantum information protocols to be more powerful. Here, we report on a distributed quantum computation protocol in which the input and output quantum states are considered to be classically correlated in quantum informatics. Nevertheless, we show that the correlations between the outcomes of the measurements on the output state cannot be efficiently simulated using classical algorithms. Crucially, at the same time, local measurement outcomes can be efficiently simulated on classical computers. We show that the only known classicality criterion violated by the input and output states in our protocol is the one used in quantum optics, namely, phase-space nonclassicality. As a result, we argue that the global phase-space nonclassicality inherent within the output state of our protocol represents true quantum correlations.

Implementation of a 3D Coupled Hydrodynamic and Contaminant Fate Model for PCDD/Fs in Thau Lagoon (France): The Importance of Atmospheric Sources of Contamination

PubMed Central

Dueri, Sibylle; Marinov, Dimitar; Fiandrino, Annie; Tronczyński, Jacek; Zaldívar, José-Manuel

2010-01-01

A 3D hydrodynamic and contaminant fate model was implemented for polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) in Thau lagoon. The hydrodynamic model was tested against temperature and salinity measurements, while the contaminant fate model was assessed against available data collected at different stations inside the lagoon. The model results allow an assessment of the spatial and temporal variability of the distribution of contaminants in the lagoon, the seasonality of loads and the role of atmospheric deposition for the input of PCDD/Fs. The outcome suggests that air is an important source of PCDD/Fs for this ecosystem, therefore the monitoring of air pollution is very appropriate for assessing the inputs of these contaminants. These results call for the development of integrated environmental protection policies. PMID:20617040

Towards a Near Real-Time Satellite-Based Flux Monitoring System for the MENA Region

NASA Astrophysics Data System (ADS)

Ershadi, A.; Houborg, R.; McCabe, M. F.; Anderson, M. C.; Hain, C.

2013-12-01

Satellite remote sensing has the potential to offer spatially and temporally distributed information on land surface characteristics, which may be used as inputs and constraints for estimating land surface fluxes of carbon, water and energy. Enhanced satellite-based monitoring systems for aiding local water resource assessments and agricultural management activities are particularly needed for the Middle East and North Africa (MENA) region. The MENA region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. To address these issues, an integrated modeling approach for near real-time monitoring of land surface states and fluxes at fine spatio-temporal scales over the MENA region is presented. This approach is based on synergistic application of multiple sensors and wavebands in the visible to shortwave infrared and thermal infrared (TIR) domain. The multi-scale flux mapping and monitoring system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and multi-sensor remotely sensed data from polar orbiting (e.g. Landsat and MODerate resolution Imaging Spectroradiometer (MODIS)) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate time-continuous (i.e. daily) estimates of field-scale water, energy and carbon fluxes. Within this modeling system, TIR satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and a detailed soil surface characterization (i.e. for prognostic modeling of soil transport processes). The STARFM fusion methodology blends aspects of high frequency (spatially coarse) and spatially fine resolution sensors and is applied directly to flux output fields to facilitate daily mapping of fluxes at sub-field scales. A complete processing infrastructure to automatically ingest and pre-process all required input data and to execute the integrated modeling system for near real-time agricultural monitoring purposes over targeted MENA sites is being developed, and initial results from this concerted effort will be discussed.

Mapping, Bayesian Geostatistical Analysis and Spatial Prediction of Lymphatic Filariasis Prevalence in Africa

PubMed Central

Slater, Hannah; Michael, Edwin

2013-01-01

There is increasing interest to control or eradicate the major neglected tropical diseases. Accurate modelling of the geographic distributions of parasitic infections will be crucial to this endeavour. We used 664 community level infection prevalence data collated from the published literature in conjunction with eight environmental variables, altitude and population density, and a multivariate Bayesian generalized linear spatial model that allows explicit accounting for spatial autocorrelation and incorporation of uncertainty in input data and model parameters, to construct the first spatially-explicit map describing LF prevalence distribution in Africa. We also ran the best-fit model against predictions made by the HADCM3 and CCCMA climate models for 2050 to predict the likely distributions of LF under future climate and population changes. We show that LF prevalence is strongly influenced by spatial autocorrelation between locations but is only weakly associated with environmental covariates. Infection prevalence, however, is found to be related to variations in population density. All associations with key environmental/demographic variables appear to be complex and non-linear. LF prevalence is predicted to be highly heterogenous across Africa, with high prevalences (>20%) estimated to occur primarily along coastal West and East Africa, and lowest prevalences predicted for the central part of the continent. Error maps, however, indicate a need for further surveys to overcome problems with data scarcity in the latter and other regions. Analysis of future changes in prevalence indicates that population growth rather than climate change per se will represent the dominant factor in the predicted increase/decrease and spread of LF on the continent. We indicate that these results could play an important role in aiding the development of strategies that are best able to achieve the goals of parasite elimination locally and globally in a manner that may also account for the effects of future climate change on parasitic infection. PMID:23951194

Spatially complex distribution of dissolved manganese in a fjord as revealed by high-resolution in situ sensing using the autonomous underwater vehicle Autosub.

PubMed

Statham, P J; Connelly, D P; German, C R; Brand, T; Overnell, J O; Bulukin, E; Millard, N; McPhail, S; Pebody, M; Perrett, J; Squire, M; Stevenson, P; Webb, A

2005-12-15

Loch Etive is a fjordic system on the west coast of Scotland. The deep waters of the upper basin are periodically isolated, and during these periods oxygen is lost through benthic respiration and concentrations of dissolved manganese increase. In April 2000 the autonomous underwater vehicle (AUV) Autosub was fitted with an in situ dissolved manganese analyzer and was used to study the spatial variability of this element together with oxygen, salinity, and temperature throughout the basin. Six along-loch transects were completed at either constant height above the seafloor or at constant depth below the surface. The ca. 4000 in situ 10-s-average dissolved Mn (Mnd) data points obtained provide a new quasi-synoptic and highly detailed view of the distribution of manganese in this fjordic environment not possible using conventional (water bottle) sampling. There is substantial variability in concentrations (<25 to >600 nM) and distributions of Mnd. Surface waters are characteristically low in Mnd reflecting mixing of riverine and marine end-member waters, both of which are low in Mnd. The deeper waters are enriched in Mnd, and as the water column always contains some oxygen, this must reflect primarily benthic inputs of reduced dissolved Mn. However, this enrichment of Mnd is spatially very variable, presumably as a result of variability in release of Mn coupled with mixing of water in the loch and removal processes. This work demonstrates how AUVs coupled with chemical sensors can reveal substantial small-scale variability of distributions of chemical species in coastal environments that would not be resolved by conventional sampling approaches. Such information is essential if we are to improve our understanding of the nature and significance of the underlying processes leading to this variability.

Effect of canopy removal on snowpack quantity and quality, fraser experimental forest, Colorado

USGS Publications Warehouse

Stottlemyer, R.; Troendle, C.A.

2001-01-01

Snowpack peak water equivalent (PWE), ion concentration, content, and spatial distribution of ion load data from spring 1987-1996 in a 1 ha clearcut and adjacent forested plots vegetated by mature Picea engelmannii and Abies lasiocarpa in the Fraser experimental forest (FEF), Colorado are presented. Our objectives were: (1) to see if a forest opening might redistribute snowfall, snowpack moisture, and snowpack chemical content, and (2) to examine the importance of canopy interception on snowpack quantity and chemistry. On an average, the canopy intercepted 36% of snowfall. Interception was correlated with snowfall amount, snowpack PWE beneath the canopy, and air temperature. Canopy removal increased snowpack PWE to >90% cumulative snowfall inputs. Snowpack K-, H-, and NH4+ concentrations on the clearcut were lower and NO3- higher than in the snowpack beneath the forested plots. Cu mulative snowfall K+ input was less than in the clearcut snowpack; H+ inputs were greater in snowfall than in the snowpack of any plot; and inorganic N (NO3- and NH4+) inputs from snowfall to the clearcut were greater than to the forested plots. Processes accounting for the differences between snowfall inputs and snowpack ion content were leaching of organic debris in the snowpack, differential elution of the snowpack, and canopy retention. There were significant trends by year in snowpack ion content at PWE without similar trends in snowfall inputs. This finding coupled with snowpack ion elution bring into question the use of snowpack chemistry as an indicator of winter atmospheric inputs in short-term studies. ?? 2001 Elsevier Science B.V.

Distributions and contamination assessment of heavy metals in the surface sediments of western Laizhou Bay: Implications for the sources and influencing factors.

PubMed

Zhang, Pan; Hu, Rijun; Zhu, Longhai; Wang, Peng; Yin, Dongxiao; Zhang, Lianjie

2017-06-15

Heavy metals (Cu, Pb, Cr, Cd and As) contents in surface sediments from western Laizhou Bay were analysed to evaluate the spatial distribution pattern and their contamination level. As was mainly concentrated in the coastal area near the estuaries and the other metals were mainly concentrated in the central part of the study area. The heavy metals were present at unpolluted levels overall evaluated by the sediment quality guidelines and geoaccumulation index. Principal component analysis suggest that Cu, Pb and Cd were mainly sourced from natural processes and As was mainly derived from anthropogenic inputs. Meanwhile, Cr originated from both natural processes and anthropogenic contributions. Tidal currents, sediments and human activities were important factors affecting the distribution of heavy metals. The heavy metal environment was divided into four subareas to provide a reference for understanding the distribution and pollution of heavy metals in the estuary-bay system. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimizing the Hydrological and Biogeochemical Simulations on a Hillslope with Stony Soil

NASA Astrophysics Data System (ADS)

Zhu, Q.

2017-12-01

Stony soils are widely distributed in the hilly area. However, traditional pedotransfer functions are not reliable in predicting the soil hydraulic parameters for these soils due to the impacts of rock fragments. Therefore, large uncertainties and errors may exist in the hillslope hydrological and biogeochemical simulations in stony soils due to poor estimations of soil hydraulic parameters. In addition, homogenous soil hydraulic parameters are usually used in traditional hillslope simulations. However, soil hydraulic parameters are spatially heterogeneous on the hillslope. This may also cause the unreliable simulations. In this study, we obtained soil hydraulic parameters using five different approaches on a tea hillslope in Taihu Lake basin, China. These five approaches included (1) Rossetta predicted and spatially homogenous, (2) Rossetta predicted and spatially heterogeneous), (3) Rossetta predicted, rock fragment corrected and spatially homogenous, (4) Rossetta predicted, rock fragment corrected and spatially heterogeneous, and (5) extracted from observed soil-water retention curves fitted by dual-pore function and spatially heterogeneous (observed). These five sets of soil hydraulic properties were then input into Hydrus-3D and DNDC to simulate the soil hydrological and biogeochemical processes. The aim of this study is testing two hypotheses. First, considering the spatial heterogeneity of soil hydraulic parameters will improve the simulations. Second, considering the impact of rock fragment on soil hydraulic parameters will improve the simulations.

Children's Spatial Thinking: Does Talk about the Spatial World Matter?

ERIC Educational Resources Information Center

Pruden, Shannon M.; Levine, Susan C.; Huttenlocher, Janellen

2011-01-01

In this paper we examine the relations between parent spatial language input, children's own production of spatial language, and children's later spatial abilities. Using a longitudinal study design, we coded the use of spatial language (i.e. words describing the spatial features and properties of objects; e.g. big, tall, circle, curvy, edge) from…

Pressure sensor to determine spatial pressure distributions on boundary layer flows

NASA Astrophysics Data System (ADS)

Sciammarella, Cesar A.; Piroozan, Parham; Corke, Thomas C.

1997-03-01

The determination of pressures along the surface of a wind tunnel proves difficult with methods that must introduce devices into the flow stream. This paper presents a sensor that is part of the wall. A special interferometric reflection moire technique is developed and used to produce signals that measures pressure both in static and dynamic settings. The sensor developed is an intelligent sensor that combines optics and electronics to analyze the pressure patterns. The sensor provides the input to a control system that is capable of modifying the shape of the wall and preserve the stability of the flow.

Evaluation of RCA thinned buried channel charge-coupled devices /CCDs/ for scientific applications

NASA Technical Reports Server (NTRS)

Zucchino, P.; Long, D.; Lowrance, J. L.; Renda, G.; Crawshaw, D. D.; Battson, D. F.

1981-01-01

An experimental version of a thinned illuminated buried-channel 512 x 320 pixel CCD with reduced amplifier input capacitance has been produced which is characterized by lower readout noise. Changes made to the amplifier are discussed, and readout noise measurements obtained by several different techniques are presented. The single energetic electron response of the CCD in the electron-bombarded mode and the single 5.9 keV X-ray pulse height distribution are reported. Results are also given on the dark current versus temperature and the spatial frequency response as a function of signal level.

Surrogate modelling for the prediction of spatial fields based on simultaneous dimensionality reduction of high-dimensional input/output spaces.

PubMed

Crevillén-García, D

2018-04-01

Time-consuming numerical simulators for solving groundwater flow and dissolution models of physico-chemical processes in deep aquifers normally require some of the model inputs to be defined in high-dimensional spaces in order to return realistic results. Sometimes, the outputs of interest are spatial fields leading to high-dimensional output spaces. Although Gaussian process emulation has been satisfactorily used for computing faithful and inexpensive approximations of complex simulators, these have been mostly applied to problems defined in low-dimensional input spaces. In this paper, we propose a method for simultaneously reducing the dimensionality of very high-dimensional input and output spaces in Gaussian process emulators for stochastic partial differential equation models while retaining the qualitative features of the original models. This allows us to build a surrogate model for the prediction of spatial fields in such time-consuming simulators. We apply the methodology to a model of convection and dissolution processes occurring during carbon capture and storage.

Heavy rainfall induced flash flood management

NASA Astrophysics Data System (ADS)

Weiler, Markus; Steinbrich, Andreas; Stölzle, Michael; Leistert, Hannes

2016-04-01

Heavy rain induced flash floods are still a serious hazard. In context of climate change even a rise of threat potential of flash flood must be suspected. To improve prediction of endangered areas hydraulic models was developed in the past that implement topography information in heigh resolution, gathered by laser scan applications. To run such models it is crucial to estimate the runoff input spatial distributed. However, this information is usually derived with relatively simple models lacking the process rigour that is required for prediction in engaged basins. Though available rain runoff models are able to model runoff response integral for measured catchments they do not indicate the spatial distribution of processes. Moreover they are commonly calibrated to measured runoff data and not applicable in other environments. Since runoff generation is commonly not measured, a calibration on it is hardly possible. In this study, we present a new approach for quantification of runoff generation in height spatial and temporal resolution. A suited model needs to work without calibration in every given environment under any given conditions. It is possible to develop such a model by combining spatial distributed input data of land surface properties (e.g. soil, geology, land use, …) with worldwide findings of runoff generation research. We developed such a model for the state of Baden-Württemberg, what has an extensive pool of spatial data. E.g. a digital elevation model of 1*1m² resolution, degree of sealing of the earth surface in 1*1m² resolution, soil properties (1:50.000) and geology (1:200.000). Within the state of Baden-Württemberg different regions are situated, with distinct environmental characteristics concerning as well climate, soil properties, land use, topography and geology. The model was tested and validated by modelling 36 observed flood events in 13 mesoscale catchments representing the different regions of Baden-Württemberg as well as by modelling 7 large area (70 m²) sprinkler experiments on 5 different plots in different regions of Switzerland. It was found, that the model was able to reproduce the temporal runoff dynamics as well as the peak discharge and the runoff volume in both, mesoscale catchments and 70 m² plots. It works in every given environment under every given conditions as antecedent moisture and precipitation characteristics. Since it works well under given different conditions in different regions and on different scales without any calibration, it is predestinated for the purpose of quantification of runoff generation for flash floods while heavy rain events in the different regions of Baden-Württemberg. Therefore we have it applied on the whole area of Baden-Württemberg on a spatial resolution of 5*5m² to model the runoff generation for one hour precipitation events of the return period 50, 100 and 1000 years and different antecedent moisture conditions. The pattern and effects are studied in detail as well as other interesting features.

Effects of input uncertainty on cross-scale crop modeling

NASA Astrophysics Data System (ADS)

Waha, Katharina; Huth, Neil; Carberry, Peter

2014-05-01

The quality of data on climate, soils and agricultural management in the tropics is in general low or data is scarce leading to uncertainty in process-based modeling of cropping systems. Process-based crop models are common tools for simulating crop yields and crop production in climate change impact studies, studies on mitigation and adaptation options or food security studies. Crop modelers are concerned about input data accuracy as this, together with an adequate representation of plant physiology processes and choice of model parameters, are the key factors for a reliable simulation. For example, assuming an error in measurements of air temperature, radiation and precipitation of ± 0.2°C, ± 2 % and ± 3 % respectively, Fodor & Kovacs (2005) estimate that this translates into an uncertainty of 5-7 % in yield and biomass simulations. In our study we seek to answer the following questions: (1) are there important uncertainties in the spatial variability of simulated crop yields on the grid-cell level displayed on maps, (2) are there important uncertainties in the temporal variability of simulated crop yields on the aggregated, national level displayed in time-series, and (3) how does the accuracy of different soil, climate and management information influence the simulated crop yields in two crop models designed for use at different spatial scales? The study will help to determine whether more detailed information improves the simulations and to advise model users on the uncertainty related to input data. We analyse the performance of the point-scale crop model APSIM (Keating et al., 2003) and the global scale crop model LPJmL (Bondeau et al., 2007) with different climate information (monthly and daily) and soil conditions (global soil map and African soil map) under different agricultural management (uniform and variable sowing dates) for the low-input maize-growing areas in Burkina Faso/West Africa. We test the models' response to different levels of input data from very little to very detailed information, and compare the models' abilities to represent the spatial variability and temporal variability in crop yields. We display the uncertainty in crop yield simulations from different input data and crop models in Taylor diagrams which are a graphical summary of the similarity between simulations and observations (Taylor, 2001). The observed spatial variability can be represented well from both models (R=0.6-0.8) but APSIM predicts higher spatial variability than LPJmL due to its sensitivity to soil parameters. Simulations with the same crop model, climate and sowing dates have similar statistics and therefore similar skill to reproduce the observed spatial variability. Soil data is less important for the skill of a crop model to reproduce the observed spatial variability. However, the uncertainty in simulated spatial variability from the two crop models is larger than from input data settings and APSIM is more sensitive to input data then LPJmL. Even with a detailed, point-scale crop model and detailed input data it is difficult to capture the complexity and diversity in maize cropping systems.

Model uncertainties do not affect observed patterns of species richness in the Amazon.

PubMed

Sales, Lilian Patrícia; Neves, Olívia Viana; De Marco, Paulo; Loyola, Rafael

2017-01-01

Climate change is arguably a major threat to biodiversity conservation and there are several methods to assess its impacts on species potential distribution. Yet the extent to which different approaches on species distribution modeling affect species richness patterns at biogeographical scale is however unaddressed in literature. In this paper, we verified if the expected responses to climate change in biogeographical scale-patterns of species richness and species vulnerability to climate change-are affected by the inputs used to model and project species distribution. We modeled the distribution of 288 vertebrate species (amphibians, birds and mammals), all endemic to the Amazon basin, using different combinations of the following inputs known to affect the outcome of species distribution models (SDMs): 1) biological data type, 2) modeling methods, 3) greenhouse gas emission scenarios and 4) climate forecasts. We calculated uncertainty with a hierarchical ANOVA in which those different inputs were considered factors. The greatest source of variation was the modeling method. Model performance interacted with data type and modeling method. Absolute values of variation on suitable climate area were not equal among predictions, but some biological patterns were still consistent. All models predicted losses on the area that is climatically suitable for species, especially for amphibians and primates. All models also indicated a current East-western gradient on endemic species richness, from the Andes foot downstream the Amazon river. Again, all models predicted future movements of species upwards the Andes mountains and overall species richness losses. From a methodological perspective, our work highlights that SDMs are a useful tool for assessing impacts of climate change on biodiversity. Uncertainty exists but biological patterns are still evident at large spatial scales. As modeling methods are the greatest source of variation, choosing the appropriate statistics according to the study objective is also essential for estimating the impacts of climate change on species distribution. Yet from a conservation perspective, we show that Amazon endemic fauna is potentially vulnerable to climate change, due to expected reductions on suitable climate area. Climate-driven faunal movements are predicted towards the Andes mountains, which might work as climate refugia for migrating species.

Model uncertainties do not affect observed patterns of species richness in the Amazon

PubMed Central

Sales, Lilian Patrícia; Neves, Olívia Viana; De Marco, Paulo

2017-01-01

Background Climate change is arguably a major threat to biodiversity conservation and there are several methods to assess its impacts on species potential distribution. Yet the extent to which different approaches on species distribution modeling affect species richness patterns at biogeographical scale is however unaddressed in literature. In this paper, we verified if the expected responses to climate change in biogeographical scale—patterns of species richness and species vulnerability to climate change—are affected by the inputs used to model and project species distribution. Methods We modeled the distribution of 288 vertebrate species (amphibians, birds and mammals), all endemic to the Amazon basin, using different combinations of the following inputs known to affect the outcome of species distribution models (SDMs): 1) biological data type, 2) modeling methods, 3) greenhouse gas emission scenarios and 4) climate forecasts. We calculated uncertainty with a hierarchical ANOVA in which those different inputs were considered factors. Results The greatest source of variation was the modeling method. Model performance interacted with data type and modeling method. Absolute values of variation on suitable climate area were not equal among predictions, but some biological patterns were still consistent. All models predicted losses on the area that is climatically suitable for species, especially for amphibians and primates. All models also indicated a current East-western gradient on endemic species richness, from the Andes foot downstream the Amazon river. Again, all models predicted future movements of species upwards the Andes mountains and overall species richness losses. Conclusions From a methodological perspective, our work highlights that SDMs are a useful tool for assessing impacts of climate change on biodiversity. Uncertainty exists but biological patterns are still evident at large spatial scales. As modeling methods are the greatest source of variation, choosing the appropriate statistics according to the study objective is also essential for estimating the impacts of climate change on species distribution. Yet from a conservation perspective, we show that Amazon endemic fauna is potentially vulnerable to climate change, due to expected reductions on suitable climate area. Climate-driven faunal movements are predicted towards the Andes mountains, which might work as climate refugia for migrating species. PMID:29023503

A hydrological emulator for global applications – HE v1.0.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Yaling; Hejazi, Mohamad; Li, Hongyi

While global hydrological models (GHMs) are very useful in exploring water resources and interactions between the Earth and human systems, their use often requires numerous model inputs, complex model calibration, and high computation costs. To overcome these challenges, we construct an efficient open-source and ready-to-use hydrological emulator (HE) that can mimic complex GHMs at a range of spatial scales (e.g., basin, region, globe). More specifically, we construct both a lumped and a distributed scheme of the HE based on the monthly abcd model to explore the tradeoff between computational cost and model fidelity. Model predictability and computational efficiency are evaluatedmore » in simulating global runoff from 1971 to 2010 with both the lumped and distributed schemes. The results are compared against the runoff product from the widely used Variable Infiltration Capacity (VIC) model. Our evaluation indicates that the lumped and distributed schemes present comparable results regarding annual total quantity, spatial pattern, and temporal variation of the major water fluxes (e.g., total runoff, evapotranspiration) across the global 235 basins (e.g., correlation coefficient r between the annual total runoff from either of these two schemes and the VIC is > 0.96), except for several cold (e.g., Arctic, interior Tibet), dry (e.g., North Africa) and mountainous (e.g., Argentina) regions. Compared against the monthly total runoff product from the VIC (aggregated from daily runoff), the global mean Kling–Gupta efficiencies are 0.75 and 0.79 for the lumped and distributed schemes, respectively, with the distributed scheme better capturing spatial heterogeneity. Notably, the computation efficiency of the lumped scheme is 2 orders of magnitude higher than the distributed one and 7 orders more efficient than the VIC model. A case study of uncertainty analysis for the world's 16 basins with top annual streamflow is conducted using 100 000 model simulations, and it demonstrates the lumped scheme's extraordinary advantage in computational efficiency. Lastly, our results suggest that the revised lumped abcd model can serve as an efficient and reasonable HE for complex GHMs and is suitable for broad practical use, and the distributed scheme is also an efficient alternative if spatial heterogeneity is of more interest.« less

Application of The Rainfall-runoff Model Topkapi For The Entire Basin of The Po River As Part of The European Project Effs

NASA Astrophysics Data System (ADS)

Todini, E.; Bartholmes, J.

The project EFFS (European Flood Forecasting System) aims at developing a flood forecasting system for the major river basins all over Europe. To extend the forecast- ing and thus the warning time in a significant way (up to 10 days) meteorological forecasting data from the ECMWF will be used as input to hydrological models. For this purpose it is fundamental to have a reliable rainfall-runoff model. For the river Po basin we chose the TOPKAPI model (Ciarapica, Todini 1998). TOPKAPI is a physi- cally based rainfall-runoff model that maintains its physical significance passing from hillslope to large basin scale. The aim of the distributed version is to reproduce the spatial variability and to lead to a better understanding of scaling effects on meteo- rological data used as well as of physical phenomena and parameters. By now the TOPKAPI model has been applied successfully to basins of smaller and medium size (up to 8000 km2). The present work also proves that TOPKAPI is a valuable flood forecasting tool for larger basins such as the Po river. An advantage of the TOPKAPI model is its physical basis. It doesn't need a "real" calibration in the common sense of the expression. The calibration work that has to be done is due to the unavoidable averaging and approximation in the input data representing various phenomena. This reduces the calibration work as well as the length of data required. The model was implemented on the Po river at spatial steps of 1km and time steps of 1 hour using available data during the year 1994. After the calibration phase, mesoscale forecasts (from ECMWF) as well as forecasts of LAM models (DWD,DMI) will be used as input to the Po river models and their behaviour will be studied as a function of the prediction quality and of the coarseness of the spatial discretisation.

DIATOM (Data Initialization and Modification) Library Version 7.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crawford, David A.; Schmitt, Robert G.; Hensinger, David M.

DIATOM is a library that provides numerical simulation software with a computational geometry front end that can be used to build up complex problem geometries from collections of simpler shapes. The library provides a parser which allows for application-independent geometry descriptions to be embedded in simulation software input decks. Descriptions take the form of collections of primitive shapes and/or CAD input files and material properties that can be used to describe complex spatial and temporal distributions of numerical quantities (often called “database variables” or “fields”) to help define starting conditions for numerical simulations. The capability is designed to be generalmore » purpose, robust and computationally efficient. By using a combination of computational geometry and recursive divide-and-conquer approximation techniques, a wide range of primitive shapes are supported to arbitrary degrees of fidelity, controllable through user input and limited only by machine resources. Through the use of call-back functions, numerical simulation software can request the value of a field at any time or location in the problem domain. Typically, this is used only for defining initial conditions, but the capability is not limited to just that use. The most recent version of DIATOM provides the ability to import the solution field from one numerical solution as input for another.« less

Finite difference time domain (FDTD) method for modeling the effect of switched gradients on the human body in MRI.

PubMed

Zhao, Huawei; Crozier, Stuart; Liu, Feng

2002-12-01

Numerical modeling of the eddy currents induced in the human body by the pulsed field gradients in MRI presents a difficult computational problem. It requires an efficient and accurate computational method for high spatial resolution analyses with a relatively low input frequency. In this article, a new technique is described which allows the finite difference time domain (FDTD) method to be efficiently applied over a very large frequency range, including low frequencies. This is not the case in conventional FDTD-based methods. A method of implementing streamline gradients in FDTD is presented, as well as comparative analyses which show that the correct source injection in the FDTD simulation plays a crucial rule in obtaining accurate solutions. In particular, making use of the derivative of the input source waveform is shown to provide distinct benefits in accuracy over direct source injection. In the method, no alterations to the properties of either the source or the transmission media are required. The method is essentially frequency independent and the source injection method has been verified against examples with analytical solutions. Results are presented showing the spatial distribution of gradient-induced electric fields and eddy currents in a complete body model. Copyright 2002 Wiley-Liss, Inc.

Modeling the direct sun component in buildings using matrix algebraic approaches: Methods and validation

DOE PAGES

Lee, Eleanor S.; Geisler-Moroder, David; Ward, Gregory

2017-12-23

Simulation tools that enable annual energy performance analysis of optically-complex fenestration systems have been widely adopted by the building industry for use in building design, code development, and the development of rating and certification programs for commercially-available shading and daylighting products. The tools rely on a three-phase matrix operation to compute solar heat gains, using as input low-resolution bidirectional scattering distribution function (BSDF) data (10–15° angular resolution; BSDF data define the angle-dependent behavior of light-scattering materials and systems). Measurement standards and product libraries for BSDF data are undergoing development to support solar heat gain calculations. Simulation of other metrics suchmore » as discomfort glare, annual solar exposure, and potentially thermal discomfort, however, require algorithms and BSDF input data that more accurately model the spatial distribution of transmitted and reflected irradiance or illuminance from the sun (0.5° resolution). This study describes such algorithms and input data, then validates the tools (i.e., an interpolation tool for measured BSDF data and the five-phase method) through comparisons with ray-tracing simulations and field monitored data from a full-scale testbed. Simulations of daylight-redirecting films, a micro-louvered screen, and venetian blinds using variable resolution, tensor tree BSDF input data derived from interpolated scanning goniophotometer measurements were shown to agree with field monitored data to within 20% for greater than 75% of the measurement period for illuminance-based performance parameters. The three-phase method delivered significantly less accurate results. We discuss the ramifications of these findings on industry and provide recommendations to increase end user awareness of the current limitations of existing software tools and BSDF product libraries.« less

Modeling the direct sun component in buildings using matrix algebraic approaches: Methods and validation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Eleanor S.; Geisler-Moroder, David; Ward, Gregory

Simulation tools that enable annual energy performance analysis of optically-complex fenestration systems have been widely adopted by the building industry for use in building design, code development, and the development of rating and certification programs for commercially-available shading and daylighting products. The tools rely on a three-phase matrix operation to compute solar heat gains, using as input low-resolution bidirectional scattering distribution function (BSDF) data (10–15° angular resolution; BSDF data define the angle-dependent behavior of light-scattering materials and systems). Measurement standards and product libraries for BSDF data are undergoing development to support solar heat gain calculations. Simulation of other metrics suchmore » as discomfort glare, annual solar exposure, and potentially thermal discomfort, however, require algorithms and BSDF input data that more accurately model the spatial distribution of transmitted and reflected irradiance or illuminance from the sun (0.5° resolution). This study describes such algorithms and input data, then validates the tools (i.e., an interpolation tool for measured BSDF data and the five-phase method) through comparisons with ray-tracing simulations and field monitored data from a full-scale testbed. Simulations of daylight-redirecting films, a micro-louvered screen, and venetian blinds using variable resolution, tensor tree BSDF input data derived from interpolated scanning goniophotometer measurements were shown to agree with field monitored data to within 20% for greater than 75% of the measurement period for illuminance-based performance parameters. The three-phase method delivered significantly less accurate results. We discuss the ramifications of these findings on industry and provide recommendations to increase end user awareness of the current limitations of existing software tools and BSDF product libraries.« less

Mapping the distribution of the main host for plague in a complex landscape in Kazakhstan: An object-based approach using SPOT-5 XS, Landsat 7 ETM+, SRTM and multiple Random Forests

NASA Astrophysics Data System (ADS)

Wilschut, L. I.; Addink, E. A.; Heesterbeek, J. A. P.; Dubyanskiy, V. M.; Davis, S. A.; Laudisoit, A.; Begon, M.; Burdelov, L. A.; Atshabar, B. B.; de Jong, S. M.

2013-08-01

Plague is a zoonotic infectious disease present in great gerbil populations in Kazakhstan. Infectious disease dynamics are influenced by the spatial distribution of the carriers (hosts) of the disease. The great gerbil, the main host in our study area, lives in burrows, which can be recognized on high resolution satellite imagery. In this study, using earth observation data at various spatial scales, we map the spatial distribution of burrows in a semi-desert landscape. The study area consists of various landscape types. To evaluate whether identification of burrows by classification is possible in these landscape types, the study area was subdivided into eight landscape units, on the basis of Landsat 7 ETM+ derived Tasselled Cap Greenness and Brightness, and SRTM derived standard deviation in elevation. In the field, 904 burrows were mapped. Using two segmented 2.5 m resolution SPOT-5 XS satellite scenes, reference object sets were created. Random Forests were built for both SPOT scenes and used to classify the images. Additionally, a stratified classification was carried out, by building separate Random Forests per landscape unit. Burrows were successfully classified in all landscape units. In the ‘steppe on floodplain’ areas, classification worked best: producer's and user's accuracy in those areas reached 88% and 100%, respectively. In the ‘floodplain’ areas with a more heterogeneous vegetation cover, classification worked least well; there, accuracies were 86 and 58% respectively. Stratified classification improved the results in all landscape units where comparison was possible (four), increasing kappa coefficients by 13, 10, 9 and 1%, respectively. In this study, an innovative stratification method using high- and medium resolution imagery was applied in order to map host distribution on a large spatial scale. The burrow maps we developed will help to detect changes in the distribution of great gerbil populations and, moreover, serve as a unique empirical data set which can be used as input for epidemiological plague models. This is an important step in understanding the dynamics of plague.

Measuring and modeling the spatial pattern of understory bamboo across landscapes: Implications for giant panda habitat

NASA Astrophysics Data System (ADS)

Linderman, Marc Alan

We examined an approach to classifying understory bamboo, the staple food of the giant panda (Ailuropoda melanoleuca), from remote sensing imagery in the Wolong Nature Reserve, China. We also used these data to estimate the landscape-scale distribution of giant panda habitat, and model the human effects on forest cover and the spatio-temporal dynamics of bamboo and the resulting implications for giant panda habitat. The spatial distribution of understory bamboo was mapped using an artificial neural network and leaf-on remote sensing data. Training on a limited set of ground truth data and using widely available Landsat TM data as input, a non-linear artificial neural network achieved a classification accuracy of 80% despite the presence of co-occurring mid-story and understory vegetation. Using information on the spatial distribution of bamboo in Wolong, we compared the results of giant panda habitat analyses with and without bamboo information. Total amount of habitat decreased by 29--56% and overall habitat patch size decreased by 16--48% after bamboo information was incorporated into the analyses. The decreases in the quantity of panda habitat and increases in habitat fragmentation resulted in decreases of 41--60% in carrying capacity. Using a spatio-temporal model of bamboo dynamics and human activities, we found that local fuelwood collection and household creation will likely reduce secondary habitat relied upon by pandas. Human impacts would likely contribute up to an additional 16% loss of habitat. Furthermore, these impacts primarily occur in the habitat relied upon by giant pandas during past bamboo die-offs. Decreased total area of habitat and increased fragmentation from human activities will likely make giant pandas increasingly sensitive to natural disturbances such as cyclical bamboo die-offs. Our studies suggest that it is necessary to further examine approaches to monitor understory vegetation and incorporate understory information into wildlife habitat research and management. The success here to map bamboo has important implications for giant panda conservation and provides a good foundation for developing methods to map the spatial distributions of understory plant species. Knowledge of the spatial distribution of bamboo is necessary to accurately measure the quantity and landscape characteristics of giant panda habitat. (Abstract shortened by UMI.)

Assessment of Hydrologic Response to Variable Precipitation Forcing: Russian River Case Study

NASA Astrophysics Data System (ADS)

Cifelli, R.; Hsu, C.; Johnson, L. E.

2014-12-01

NOAA Hydrometeorology Testbed (HMT) activities in California have involved deployment of advanced sensor networks to better track atmospheric river (AR) dynamics and inland penetration of high water vapor air masses. Numerical weather prediction models and decision support tools have been developed to provide forecasters a better basis for forecasting heavy precipitation and consequent flooding. The HMT also involves a joint project with California Department of Water Resources (CA-DWR) and the Scripps Institute for Oceanography (SIO) as part of CA-DWR's Enhanced Flood Response and Emergency Preparedness (EFREP) program. The HMT activities have included development and calibration of a distributed hydrologic model, the NWS Office of Hydrologic Development's (OHD) Research Distributed Hydrologic Model (RDHM), to prototype the distributed approach for flood and other water resources applications. HMT has applied RDHM to the Russian-Napa watersheds for research assessment of gap-filling weather radars for precipitation and hydrologic forecasting and for establishing a prototype to inform both the NWS Monterey Forecast Office and the California Nevada River Forecast Center (CNRFC) of RDHM capabilities. In this presentation, a variety of precipitation forcings generated with and without gap filling radar and rain gauge data are used as input to RDHM to assess the hydrologic response for selected case study events. Both the precipitation forcing and hydrologic model are run at different spatial and temporal resolution in order to examine the sensitivity of runoff to the precipitation inputs. Based on the timing of the events and the variations of spatial and temporal resolution, the parameters which dominate the hydrologic response are identified. The assessment is implemented at two USGS stations (Ukiah near Russian River and Austin Creek near Cazadero) that are minimally influenced by managed flows and objective evaluation can thus be derived. The results are assessed using statistical metrics, including daily Nash scores, Pearson Correlation, and sub daily timing errors.

Sensitivity analysis of urban flood flows to hydraulic controls

NASA Astrophysics Data System (ADS)

Chen, Shangzhi; Garambois, Pierre-André; Finaud-Guyot, Pascal; Dellinger, Guilhem; Terfous, Abdelali; Ghenaim, Abdallah

2017-04-01

Flooding represents one of the most significant natural hazards on each continent and particularly in highly populated areas. Improving the accuracy and robustness of prediction systems has become a priority. However, in situ measurements of floods remain difficult while a better understanding of flood flow spatiotemporal dynamics along with dataset for model validations appear essential. The present contribution is based on a unique experimental device at the scale 1/200, able to produce urban flooding with flood flows corresponding to frequent to rare return periods. The influence of 1D Saint Venant and 2D Shallow water model input parameters on simulated flows is assessed using global sensitivity analysis (GSA). The tested parameters are: global and local boundary conditions (water heights and discharge), spatially uniform or distributed friction coefficient and or porosity respectively tested in various ranges centered around their nominal values - calibrated thanks to accurate experimental data and related uncertainties. For various experimental configurations a variance decomposition method (ANOVA) is used to calculate spatially distributed Sobol' sensitivity indices (Si's). The sensitivity of water depth to input parameters on two main streets of the experimental device is presented here. Results show that the closer from the downstream boundary condition on water height, the higher the Sobol' index as predicted by hydraulic theory for subcritical flow, while interestingly the sensitivity to friction decreases. The sensitivity indices of all lateral inflows, representing crossroads in 1D, are also quantified in this study along with their asymptotic trends along flow distance. The relationship between lateral discharge magnitude and resulting sensitivity index of water depth is investigated. Concerning simulations with distributed friction coefficients, crossroad friction is shown to have much higher influence on upstream water depth profile than street friction coefficients. This methodology could be applied to any urban flood configuration in order to better understand flow dynamics and repartition but also guide model calibration in the light of flow controls.

Modelling ecosystem service flows under uncertainty with stochiastic SPAN

USGS Publications Warehouse

Johnson, Gary W.; Snapp, Robert R.; Villa, Ferdinando; Bagstad, Kenneth J.

2012-01-01

Ecosystem service models are increasingly in demand for decision making. However, the data required to run these models are often patchy, missing, outdated, or untrustworthy. Further, communication of data and model uncertainty to decision makers is often either absent or unintuitive. In this work, we introduce a systematic approach to addressing both the data gap and the difficulty in communicating uncertainty through a stochastic adaptation of the Service Path Attribution Networks (SPAN) framework. The SPAN formalism assesses ecosystem services through a set of up to 16 maps, which characterize the services in a study area in terms of flow pathways between ecosystems and human beneficiaries. Although the SPAN algorithms were originally defined deterministically, we present them here in a stochastic framework which combines probabilistic input data with a stochastic transport model in order to generate probabilistic spatial outputs. This enables a novel feature among ecosystem service models: the ability to spatially visualize uncertainty in the model results. The stochastic SPAN model can analyze areas where data limitations are prohibitive for deterministic models. Greater uncertainty in the model inputs (including missing data) should lead to greater uncertainty expressed in the model’s output distributions. By using Bayesian belief networks to fill data gaps and expert-provided trust assignments to augment untrustworthy or outdated information, we can account for uncertainty in input data, producing a model that is still able to run and provide information where strictly deterministic models could not. Taken together, these attributes enable more robust and intuitive modelling of ecosystem services under uncertainty.

Scheme of Optical Image Encryption with Digital Information Input and Dynamic Encryption Key based on Two LC SLMs

NASA Astrophysics Data System (ADS)

Bondareva, A. P.; Cheremkhin, P. A.; Evtikhiev, N. N.; Krasnov, V. V.; Starikov, S. N.

Scheme of optical image encryption with digital information input and dynamic encryption key based on two liquid crystal spatial light modulators and operating with spatially-incoherent monochromatic illumination is experimentally implemented. Results of experiments on images optical encryption and numerical decryption are presented. Satisfactory decryption error of 0.20÷0.27 is achieved.

A sprinkling experiment to quantify celerity-velocity differences at the hillslope scale.

PubMed

van Verseveld, Willem J; Barnard, Holly R; Graham, Chris B; McDonnell, Jeffrey J; Brooks, J Renée; Weiler, Markus

2017-01-01

Few studies have quantified the differences between celerity and velocity of hillslope water flow and explained the processes that control these differences. Here, we asses these differences by combining a 24-day hillslope sprinkling experiment with a spatially explicit hydrologic model analysis. We focused our work on Watershed 10 at the H. J. Andrews Experimental Forest in western Oregon. Celerities estimated from wetting front arrival times were generally much faster than average vertical velocities of δ 2 H. In the model analysis, this was consistent with an identifiable effective porosity (fraction of total porosity available for mass transfer) parameter, indicating that subsurface mixing was controlled by an immobile soil fraction, resulting in the attenuation of the δ 2 H input signal in lateral subsurface flow. In addition to the immobile soil fraction, exfiltrating deep groundwater that mixed with lateral subsurface flow captured at the experimental hillslope trench caused further reduction in the δ 2 H input signal. Finally, our results suggest that soil depth variability played a significant role in the celerity-velocity responses. Deeper upslope soils damped the δ 2 H input signal, while a shallow soil near the trench controlled the δ 2 H peak in lateral subsurface flow response. Simulated exit time and residence time distributions with our hillslope hydrologic model showed that water captured at the trench did not represent the entire modeled hillslope domain; the exit time distribution for lateral subsurface flow captured at the trench showed more early time weighting.

A sprinkling experiment to quantify celerity-velocity differences at the hillslope scale

NASA Astrophysics Data System (ADS)

van Verseveld, Willem J.; Barnard, Holly R.; Graham, Chris B.; McDonnell, Jeffrey J.; Renée Brooks, J.; Weiler, Markus

2017-11-01

Few studies have quantified the differences between celerity and velocity of hillslope water flow and explained the processes that control these differences. Here, we asses these differences by combining a 24-day hillslope sprinkling experiment with a spatially explicit hydrologic model analysis. We focused our work on Watershed 10 at the H. J. Andrews Experimental Forest in western Oregon. Celerities estimated from wetting front arrival times were generally much faster than average vertical velocities of δ2H. In the model analysis, this was consistent with an identifiable effective porosity (fraction of total porosity available for mass transfer) parameter, indicating that subsurface mixing was controlled by an immobile soil fraction, resulting in the attenuation of the δ2H input signal in lateral subsurface flow. In addition to the immobile soil fraction, exfiltrating deep groundwater that mixed with lateral subsurface flow captured at the experimental hillslope trench caused further reduction in the δ2H input signal. Finally, our results suggest that soil depth variability played a significant role in the celerity-velocity responses. Deeper upslope soils damped the δ2H input signal, while a shallow soil near the trench controlled the δ2H peak in lateral subsurface flow response. Simulated exit time and residence time distributions with our hillslope hydrologic model showed that water captured at the trench did not represent the entire modeled hillslope domain; the exit time distribution for lateral subsurface flow captured at the trench showed more early time weighting.

Predicting Cortical Dark/Bright Asymmetries from Natural Image Statistics and Early Visual Transforms

PubMed Central

Cooper, Emily A.; Norcia, Anthony M.

2015-01-01

The nervous system has evolved in an environment with structure and predictability. One of the ubiquitous principles of sensory systems is the creation of circuits that capitalize on this predictability. Previous work has identified predictable non-uniformities in the distributions of basic visual features in natural images that are relevant to the encoding tasks of the visual system. Here, we report that the well-established statistical distributions of visual features -- such as visual contrast, spatial scale, and depth -- differ between bright and dark image components. Following this analysis, we go on to trace how these differences in natural images translate into different patterns of cortical input that arise from the separate bright (ON) and dark (OFF) pathways originating in the retina. We use models of these early visual pathways to transform natural images into statistical patterns of cortical input. The models include the receptive fields and non-linear response properties of the magnocellular (M) and parvocellular (P) pathways, with their ON and OFF pathway divisions. The results indicate that there are regularities in visual cortical input beyond those that have previously been appreciated from the direct analysis of natural images. In particular, several dark/bright asymmetries provide a potential account for recently discovered asymmetries in how the brain processes visual features, such as violations of classic energy-type models. On the basis of our analysis, we expect that the dark/bright dichotomy in natural images plays a key role in the generation of both cortical and perceptual asymmetries. PMID:26020624

Abiotic and biotic factors influencing nanoflagellate abundance and distribution in three different seasons in PRE, South China Sea

NASA Astrophysics Data System (ADS)

Zhang, Xia; Shi, Zhen; Huang, Xiaoping; Li, Xiangfu

2017-07-01

Spatial distribution characteristics of two nanoflagellate groups, together with physico-chemical and biological factors, were studied in three seasons in the Pearl River Estuary (PRE), South China Sea. Nanoflagellates were more abundant in warm periods than that in winter. The average abundance in the three observations (spring, summer and winter) was as follow: 1.28 ± 1.17, 0.88 ± 1.02 and 0.28 ± 0.23 × 103 cells ml-1 of heterotrophic nanoflagellate (HNF), and 1.26 ± 0.85, 0.89 ± 0.77 and 0.65 ± 0.52 × 103 cells ml-1 of pigmented nanoflagellate (PNF). In our three studied seasons, NF density was generally higher in the inner estuary and decreasing to the lowest in the outer estuary. Our results suggested that PNF classes were more sensitive than HNF groups to freshwater discharge. The proportion of PNF gradually increased from spring (49.7%) to winter (67.7%), with the river flow was accordingly decreasing. Moreover, spatial distribution pattern in three seasons showed the response of PNF populations to freshwater input was similar to phytoplankton assemblages in the PRE. Total bacterial and live bacterial abundance (measured by LIVE/DEAD kit) were associated with both two NF components, which implied that NF was a potential predator controlling the bulk abundance of bacteria and proportion of active cells. These results revealed the seasonal and spatial variations of NF abundance in diverse conditions in the PRE and how their response to different ecological processes.

Identification of land use and other anthropogenic impacts on nitrogen cycling using stable isotopes and distributed hydrologic modeling

NASA Astrophysics Data System (ADS)

O'Connell, M. T.; Macko, S. A.

2017-12-01

Reactive modeling of sources and processes affecting the concentration of NO3- and NH4+ in natural and anthropogenically influenced surface water can reveal unexpected characteristics of the systems. A distributed hydrologic model, TREX, is presented that provides opportunities to study multiscale effects of nitrogen inputs, outputs, and changes. The model is adapted to run on parallel computing architecture and includes the geochemical reaction module PhreeqcRM, which enables calculation of δ15N and δ18O from biologically mediated transformation reactions in addition to mixing and equilibration. Management practices intended to attenuate nitrate in surface and subsurface waters, in particular the establishment of riparian buffer zones, are variably effective due to spatial heterogeneity of soils and preferential flow through buffers. Accounting for this heterogeneity in a fully distributed biogeochemical model allows for more efficient planning and management practices. Highly sensitive areas within a watershed can be identified based on a number of spatially variable parameters, and by varying those parameters systematically to determine conditions under which those areas are under more or less critical stress. Responses can be predicted at various scales to stimuli ranging from local changes in cropping regimes to global shifts in climate. This work presents simulations of conditions showing low antecedent nitrogen retention versus significant contribution of old nitrate. Nitrogen sources are partitioned using dual isotope ratios and temporally varying concentrations. In these two scenarios, we can evaluate the efficiency of source identification based on spatially explicit information, and model effects of increasing urban land use on N biogeochemical cycling.

Rare earth element distributions in the West Pacific: Trace element sources and conservative vs. non-conservative behavior

NASA Astrophysics Data System (ADS)

Behrens, Melanie K.; Pahnke, Katharina; Paffrath, Ronja; Schnetger, Bernhard; Brumsack, Hans-Jürgen

2018-03-01

Recent studies suggest that transport and water mass mixing may play a dominant role in controlling the distribution of dissolved rare earth element concentrations ([REE]) at least in parts of the North and South Atlantic and the Pacific Southern Ocean. Here we report vertically and spatially high-resolution profiles of dissolved REE concentrations ([REE]) along a NW-SE transect in the West Pacific and examine the processes affecting the [REE] distributions in this area. Surface water REE patterns reveal sources of trace element (TE) input near South Korea and in the tropical equatorial West Pacific. Positive europium anomalies and middle REE enrichments in surface and subsurface waters are indicative of TE input from volcanic islands and fingerprint in detail small-scale equatorial zonal eastward transport of TEs to the iron-limited tropical East Pacific. The low [REE] of North and South Pacific Tropical Waters and Antarctic Intermediate Water are a long-range (i.e., preformed) laterally advected signal, whereas increasing [REE] with depth within North Pacific Intermediate Water result from release from particles. Optimum multiparameter analysis of deep to bottom waters indicates a dominant control of lateral transport and mixing on [REE] at the depth of Lower Circumpolar Deep Water (≥3000 m water depth; ∼75-100% explained by water mass mixing), allowing the northward tracing of LCDW to ∼28°N in the Northwest Pacific. In contrast, scavenging in the hydrothermal plumes of the Lau Basin and Tonga-Fiji area at 1500-2000 m water depth leads to [REE] deficits (∼40-60% removal) and marked REE fractionation in the tropical West Pacific. Overall, our data provide evidence for active trace element input both near South Korea and Papua New Guinea, and for a strong lateral transport component in the distribution of dissolved REEs in large parts of the West Pacific.

Uncertainties and implications of applying aggregated data for spatial modelling of atmospheric ammonia emissions.

PubMed

Hellsten, S; Dragosits, U; Place, C J; Dore, A J; Tang, Y S; Sutton, M A

2018-05-09

Ammonia emissions vary greatly at a local scale, and effects (eutrophication, acidification) occur primarily close to sources. Therefore it is important that spatially distributed emission estimates are located as accurately as possible. The main source of ammonia emissions is agriculture, and therefore agricultural survey statistics are the most important input data to an ammonia emission inventory alongside per activity estimates of emission potential. In the UK, agricultural statistics are collected at farm level, but are aggregated to parish level, NUTS-3 level or regular grid resolution for distribution to users. In this study, the Modifiable Areal Unit Problem (MAUP), associated with such amalgamation, is investigated in the context of assessing the spatial distribution of ammonia sources for emission inventories. England was used as a test area to study the effects of the MAUP. Agricultural survey data at farm level (point data) were obtained under license and amalgamated to different areal units or zones: regular 1-km, 5-km, 10-km grids and parish level, before they were imported into the emission model. The results of using the survey data at different levels of amalgamation were assessed to estimate the effects of the MAUP on the spatial inventory. The analysis showed that the size and shape of aggregation zones applied to the farm-level agricultural statistics strongly affect the location of the emissions estimated by the model. If the zones are too small, this may result in false emission "hot spots", i.e., artificially high emission values that are in reality not confined to the zone to which they are allocated. Conversely, if the zones are too large, detail may be lost and emissions smoothed out, which may give a false impression of the spatial patterns and magnitude of emissions in those zones. The results of the study indicate that the MAUP has a significant effect on the location and local magnitude of emissions in spatial inventories where amalgamated, zonal data are used. Copyright © 2018 Elsevier Ltd. All rights reserved.

How pattern formation in ring networks of excitatory and inhibitory spiking neurons depends on the input current regime.

PubMed

Kriener, Birgit; Helias, Moritz; Rotter, Stefan; Diesmann, Markus; Einevoll, Gaute T

2013-01-01

Pattern formation, i.e., the generation of an inhomogeneous spatial activity distribution in a dynamical system with translation invariant structure, is a well-studied phenomenon in neuronal network dynamics, specifically in neural field models. These are population models to describe the spatio-temporal dynamics of large groups of neurons in terms of macroscopic variables such as population firing rates. Though neural field models are often deduced from and equipped with biophysically meaningful properties, a direct mapping to simulations of individual spiking neuron populations is rarely considered. Neurons have a distinct identity defined by their action on their postsynaptic targets. In its simplest form they act either excitatorily or inhibitorily. When the distribution of neuron identities is assumed to be periodic, pattern formation can be observed, given the coupling strength is supracritical, i.e., larger than a critical weight. We find that this critical weight is strongly dependent on the characteristics of the neuronal input, i.e., depends on whether neurons are mean- or fluctuation driven, and different limits in linearizing the full non-linear system apply in order to assess stability. In particular, if neurons are mean-driven, the linearization has a very simple form and becomes independent of both the fixed point firing rate and the variance of the input current, while in the very strongly fluctuation-driven regime the fixed point rate, as well as the input mean and variance are important parameters in the determination of the critical weight. We demonstrate that interestingly even in "intermediate" regimes, when the system is technically fluctuation-driven, the simple linearization neglecting the variance of the input can yield the better prediction of the critical coupling strength. We moreover analyze the effects of structural randomness by rewiring individual synapses or redistributing weights, as well as coarse-graining on the formation of inhomogeneous activity patterns.

How pattern formation in ring networks of excitatory and inhibitory spiking neurons depends on the input current regime

PubMed Central

Kriener, Birgit; Helias, Moritz; Rotter, Stefan; Diesmann, Markus; Einevoll, Gaute T.

2014-01-01

Pattern formation, i.e., the generation of an inhomogeneous spatial activity distribution in a dynamical system with translation invariant structure, is a well-studied phenomenon in neuronal network dynamics, specifically in neural field models. These are population models to describe the spatio-temporal dynamics of large groups of neurons in terms of macroscopic variables such as population firing rates. Though neural field models are often deduced from and equipped with biophysically meaningful properties, a direct mapping to simulations of individual spiking neuron populations is rarely considered. Neurons have a distinct identity defined by their action on their postsynaptic targets. In its simplest form they act either excitatorily or inhibitorily. When the distribution of neuron identities is assumed to be periodic, pattern formation can be observed, given the coupling strength is supracritical, i.e., larger than a critical weight. We find that this critical weight is strongly dependent on the characteristics of the neuronal input, i.e., depends on whether neurons are mean- or fluctuation driven, and different limits in linearizing the full non-linear system apply in order to assess stability. In particular, if neurons are mean-driven, the linearization has a very simple form and becomes independent of both the fixed point firing rate and the variance of the input current, while in the very strongly fluctuation-driven regime the fixed point rate, as well as the input mean and variance are important parameters in the determination of the critical weight. We demonstrate that interestingly even in “intermediate” regimes, when the system is technically fluctuation-driven, the simple linearization neglecting the variance of the input can yield the better prediction of the critical coupling strength. We moreover analyze the effects of structural randomness by rewiring individual synapses or redistributing weights, as well as coarse-graining on the formation of inhomogeneous activity patterns. PMID:24501591

Spatial modeling of litter and soil carbon stocks with associated uncertainty on forest land in the conterminous United States

NASA Astrophysics Data System (ADS)

Cao, B.; Domke, G. M.; Russell, M.; McRoberts, R. E.; Walters, B. F.

2017-12-01

Forest ecosystems contribute substantially to carbon (C) storage. The dynamics of litter decomposition, translocation and stabilization into soil layers are essential processes in the functioning of forest ecosystems, as they control the cycling of soil organic matter and the accumulation and release of C to the atmosphere. Therefore, the spatial distributions of litter and soil C stocks are important in greenhouse gas estimation and reporting and inform land management decisions, policy, and climate change mitigation strategies. In this study, we explored the effects of spatial aggregation of climatic, biotic, topographic and soil input data on national estimates of litter and soil C stocks and characterized the spatial distribution of litter and soil C stocks in the conterminous United States. Data from the Forest Inventory and Analysis (FIA) program within the US Forest Service were used with vegetation phenology data estimated from LANDSAT imagery (30 m) and raster data describing relevant environmental parameters (e.g. temperature, precipitation, topographic properties) for the entire conterminous US. Litter and soil C stocks were estimated and mapped through geostatistical analysis and statistical uncertainty bounds on the pixel level predictions were constructed using a Monte Carlo-bootstrap technique, by which credible variance estimates for the C stocks were calculated. The sensitivity of model estimates to spatial aggregation depends on geographic region. Further, using long-term (30-year) climate averages during periods with strong climatic trends results in large differences in litter and soil C stock estimates. In addition, results suggest that local topographic aspect is an important variable in litter and soil C estimation at the continental scale.

Spatial exposure-hazard and landscape models for assessing the impact of GM crops on non-target organisms.

PubMed

Leclerc, Melen; Walker, Emily; Messéan, Antoine; Soubeyrand, Samuel

2018-05-15

The cultivation of Genetically Modified (GM) crops may have substantial impacts on populations of non-target organisms (NTOs) in agroecosystems. These impacts should be assessed at larger spatial scales than the cultivated field, and, as landscape-scale experiments are difficult, if not impossible, modelling approaches are needed to address landscape risk management. We present an original stochastic and spatially explicit modelling framework for assessing the risk at the landscape level. We use techniques from spatial statistics for simulating simplified landscapes made up of (aggregated or non-aggregated) GM fields, neutral fields and NTO's habitat areas. The dispersal of toxic pollen grains is obtained by convolving the emission of GM plants and validated dispersal kernel functions while the locations of exposed individuals are drawn from a point process. By taking into account the adherence of the ambient pollen on plants, the loss of pollen due to climatic events, and, an experimentally-validated mortality-dose function we predict risk maps and provide a distribution giving how the risk varies within exposed individuals in the landscape. Then, we consider the impact of the Bt maize on Inachis io in worst-case scenarii where exposed individuals are located in the vicinity of GM fields and pollen shedding overlaps with larval emergence. We perform a Global Sensitivity Analysis (GSA) to explore numerically how our input parameters influence the risk. Our results confirm the important effects of pollen emission and loss. Most interestingly they highlight that the optimal spatial distribution of GM fields that mitigates the risk depends on our knowledge of the habitats of NTOs, and finally, moderate the influence of the dispersal kernel function. Copyright © 2017 Elsevier B.V. All rights reserved.

Study of indoor radon distribution using measurements and CFD modeling.

PubMed

Chauhan, Neetika; Chauhan, R P; Joshi, M; Agarwal, T K; Aggarwal, Praveen; Sahoo, B K

2014-10-01

Measurement and/or prediction of indoor radon ((222)Rn) concentration are important due to the impact of radon on indoor air quality and consequent inhalation hazard. In recent times, computational fluid dynamics (CFD) based modeling has become the cost effective replacement of experimental methods for the prediction and visualization of indoor pollutant distribution. The aim of this study is to implement CFD based modeling for studying indoor radon gas distribution. This study focuses on comparison of experimentally measured and CFD modeling predicted spatial distribution of radon concentration for a model test room. The key inputs for simulation viz. radon exhalation rate and ventilation rate were measured as a part of this study. Validation experiments were performed by measuring radon concentration at different locations of test room using active (continuous radon monitor) and passive (pin-hole dosimeters) techniques. Modeling predictions have been found to be reasonably matching with the measurement results. The validated model can be used to understand and study factors affecting indoor radon distribution for more realistic indoor environment. Copyright © 2014 Elsevier Ltd. All rights reserved.

Atmospheric Nitrogen Inputs to the Ocean and their Impact

NASA Astrophysics Data System (ADS)

Jickells, Tim D.

2016-04-01

Atmospheric Nitrogen Inputs to the Ocean and their Impact T Jickells (1), K. Altieri (2), D. Capone (3), E. Buitenhuis (1), R. Duce (4), F. Dentener (5), K. Fennel (6), J. Galloway (7), M. Kanakidou (8), J. LaRoche (9), K. Lee (10), P. Liss (1), J. Middleburg (11), K. Moore (12), S. Nickovic (13), G. Okin (14), A. Oschilies (15), J. Prospero (16), M. Sarin (17), S. Seitzinger (18), J. Scharples (19), P. Suntharalingram (1), M. Uematsu (20), L. Zamora (21) Atmospheric nitrogen inputs to the ocean have been identified as an important source of nitrogen to the oceans which has increased greatly as a result of human activity. The significance of atmospheric inputs for ocean biogeochemistry were evaluated in a seminal paper by Duce et al., 2008 (Science 320, 893-7). In this presentation we will update the Duce et al 2008 study estimating the impact of atmospheric deposition on the oceans. We will summarise the latest model estimates of total atmospheric nitrogen deposition to the ocean, their chemical form (nitrate, ammonium and organic nitrogen) and spatial distribution from the TM4 model. The model estimates are somewhat smaller than the Duce et al estimate, but with similar spatial distributions. We will compare these flux estimates with a new estimate of the impact of fluvial nitrogen inputs on the open ocean (Sharples submitted) which estimates some transfer of fluvial nitrogen to the open ocean, particularly at low latitudes, compared to the complete trapping of fluvial inputs on the continental shelf assumed by Duce et al. We will then estimate the impact of atmospheric deposition on ocean primary productivity and N2O emissions from the oceans using the PlankTOM10 model. The impacts of atmospheric deposition we estimate on ocean productivity here are smaller than those predicted by Duce et al impacts, consistent with the smaller atmospheric deposition estimates. However, the atmospheric input is still larger than the estimated fluvial inputs to the open ocean, even with the increased transport across shelf to the open ocean from low latitude fluvial systems identified. 1. School of Environmental Science University of East Anglia UK 2. Energy Research Centre University of Cape Town SA 3. Department of Biological Sciences University of S California USA 4. Departments of Oceanography and Atmospheric Sciences Texas A&M University USA 5. JRC Ispra Italy 6. Department of Oceanography Dalhousie University Canada 7. Department of Environmental Sciences U. Virginia USA 8. Department of Chemistry, University of Crete, Greece 9. Department of Biology Dalhousie University, Canada 10. School of Environmental Science and Engineering Pohang University S Korea. 11. Faculty of Geosciences University of Utrecht Netherlands 12. Department of Earth System Science University of California at Irvine USA 13. WMO Geneva 14. Department of Geography University of California USA 15. GEOMAR Keil Germany 16. Department of Atmospheric Sciences, University of Miami, USA 17. Geosciences Division at Physical Research Laboratory, Ahmedabad, India 18. Department of Environmental Studies, University of Victoria, Canada 19. School of Environmentak Sciences, U Liverpool UK 20. Center for International Collaboration, Atmosphere and Ocean Research Institute, The University of Tokyo Japan 21. Oak Ridge Associated Universities USA

Multivariate Statistical Postprocessing of Ensemble Forcasts of Precipitation and Temperature over four River Basins in California

NASA Astrophysics Data System (ADS)

Scheuerer, Michael; Hamill, Thomas M.; Whitin, Brett; He, Minxue; Henkel, Arthur

2017-04-01

Hydrological forecasts strongly rely on predictions of precipitation amounts and temperature as meteorological inputs to hydrological models. Ensemble weather predictions provide a number of different scenarios that reflect the uncertainty about these meteorological inputs, but are often biased and underdispersive, and therefore require statistical postprocessing. In hydrological applications it is crucial that spatial and temporal (i.e. between different forecast lead times) dependencies as well as dependence between the two weather variables is adequately represented by the recalibrated forecasts. We present a study with temperature and precipitation forecasts over four river basins over California that are postprocessed with a variant of the nonhomogeneous Gaussian regression method (Gneiting et al., 2005) and the censored, shifted gamma distribution approach (Scheuerer and Hamill, 2015) respectively. For modelling spatial, temporal and inter-variable dependence we propose a variant of the Schaake Shuffle (Clark et al., 2005) that uses spatio-temporal trajectories of observed temperture and precipitation as a dependence template, and chooses the historic dates in such a way that the divergence between the marginal distributions of these trajectories and the univariate forecast distributions is minimized. For the four river basins considered in our study, this new multivariate modelling technique consistently improves upon the Schaake Shuffle and yields reliable spatio-temporal forecast trajectories of temperature and precipitation that can be used to force hydrological forecast systems. References: Clark, M., Gangopadhyay, S., Hay, L., Rajagopalan, B., Wilby, R., 2004. The Schaake Shuffle: A method for reconstructing space-time variability in forecasted precipitation and temperature fields. Journal of Hydrometeorology, 5, pp.243-262. Gneiting, T., Raftery, A.E., Westveld, A.H., Goldman, T., 2005. Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS. Monthly Weather Review, 133, pp.1098-1118. Scheuerer, M., Hamill, T.M., 2015. Statistical postprocessing of ensemble precipitation forecasts by fitting censored, shifted gamma distributions. Monthly Weather Review, 143, pp.4578-4596. Scheuerer, M., Hamill, T.M., Whitin, B., He, M., and Henkel, A., 2016: A method for preferential selection of dates in the Schaake shuffle approach to constructing spatio-temporal forecast fields of temperature and precipitation. Water Resources Research, submitted.

Terrestrial and marine biomarker estimates of organic matter sources and distributions in surface sediments from the East China Sea shelf

NASA Astrophysics Data System (ADS)

Xing, Lei; Zhang, Hailong; Yuan, Zineng; Sun, Yao; Zhao, Meixun

2011-07-01

Revealing of the sources and distributions of sedimentary organic matter in the East China Sea (ECS) is important for understanding its carbon cycle, which has significant temporal and spatial variability due to the influences of recent climate changes and anthropogenic activities. In this study, we report the contents of both terrestrial and marine biomarkers including ∑C 27+C 29+C 31n-alkanes (38.6-580 ng/g), C 37 alkenones (5.6-124.6 ng/g), brassicasterol (98-913 ng/g) and dinosterol (125-1521 ng/g) from the surface sediments in the Changjiang River Estuary (CRE) and shelf areas of the ECS. Several indices based on biomarker contents and ratios are calculated to assess the spatial distributions of both terrestrial and marine organic matter in the ECS surface sediments, and these results are compared with organic matter distribution patterns revealed by the δ13C (-20.1‰ to -22.7‰) and C/N ratio (5-7.5) of total organic matter. The contents of terrestrial biomarkers in the ECS surface sediments decrease seaward, controlled mostly by Changjiang River (CR) inputs and surface currents; while higher contents of the two marine biomarkers (brassicasterol and dinosterol) occur in upwelling areas outside the CRE and in the Zhejiang-Fujian coastal zone, controlled mostly by marine productivity. Four proxies, fTerr( δ13C) (the fraction of terrestrial organic matter in TOC estimated by TOC δ13C), odd-alkanes (∑C 27+C 29+C 31n-alkanes), 1/ Pmar-aq ((C 23+C 25+C 29+C 31)/(C 23+C 25) n-alkanes) and TMBR (terrestrial and marine biomarker ratio) (C 27+C 29+C 31n-alkanes)/((C 27+C 29+C 31) n-alkanes+(brassicasterol+dinosterol+alkenones)), reveal a consistent pattern showing the relative contribution of terrestrial organic matter (TOM) is higher in the CRE and along the Zhejiang-Fujian coastline, controlled mostly by CR inputs and currents, but the TOM contribution decreases seaward, as the influences of the CR discharge decrease.

BaTMAn: Bayesian Technique for Multi-image Analysis

NASA Astrophysics Data System (ADS)

Casado, J.; Ascasibar, Y.; García-Benito, R.; Guidi, G.; Choudhury, O. S.; Bellocchi, E.; Sánchez, S. F.; Díaz, A. I.

2016-12-01

Bayesian Technique for Multi-image Analysis (BaTMAn) characterizes any astronomical dataset containing spatial information and performs a tessellation based on the measurements and errors provided as input. The algorithm iteratively merges spatial elements as long as they are statistically consistent with carrying the same information (i.e. identical signal within the errors). The output segmentations successfully adapt to the underlying spatial structure, regardless of its morphology and/or the statistical properties of the noise. BaTMAn identifies (and keeps) all the statistically-significant information contained in the input multi-image (e.g. an IFS datacube). The main aim of the algorithm is to characterize spatially-resolved data prior to their analysis.

Multi-scales and multi-satellites estimates of evapotranspiration with a residual energy balance model in the Muzza agricultural district in Northern Italy

NASA Astrophysics Data System (ADS)

Corbari, C.; Bissolati, M.; Mancini, M.

2015-05-01

Evapotranspiration estimates were performed with a residual energy balance model (REB) over an agricultural area using remote sensing data. REB uses land surface temperature (LST) as main input parameter so that energy fluxes were computed instantaneously at the time of data acquisition. Data from MODIS and SEVIRI sensors were used and downscaling techniques were implemented to improve their spatial resolutions. Energy fluxes at the original spatial resolutions (1000 m for MODIS and 5000 m for SEVIRI) as well as at the downscaled resolutions (250 m for MODIS and 1000 m for SEVIRI) were calculated with the REB model. Ground eddy covariance data and remote sensing information from the Muzza agricultural irrigation district in Italy from 2010 to 2012 gave the opportunity to validate and compare spatially distributed energy fluxes. The model outputs matched quite well ground observations when ground LST data were used, while differences increased when MODIS and SEVIRI LST were used. The spatial analysis revealed significant differences between the two sensors both in term of LST (around 2.8 °C) and of latent heat fluxes with values (around 100 W m-2).

Continuous Variable Cluster State Generation over the Optical Spatial Mode Comb

DOE PAGES

Pooser, Raphael C.; Jing, Jietai

2014-10-20

One way quantum computing uses single qubit projective measurements performed on a cluster state (a highly entangled state of multiple qubits) in order to enact quantum gates. The model is promising due to its potential scalability; the cluster state may be produced at the beginning of the computation and operated on over time. Continuous variables (CV) offer another potential benefit in the form of deterministic entanglement generation. This determinism can lead to robust cluster states and scalable quantum computation. Recent demonstrations of CV cluster states have made great strides on the path to scalability utilizing either time or frequency multiplexingmore » in optical parametric oscillators (OPO) both above and below threshold. The techniques relied on a combination of entangling operators and beam splitter transformations. Here we show that an analogous transformation exists for amplifiers with Gaussian inputs states operating on multiple spatial modes. By judicious selection of local oscillators (LOs), the spatial mode distribution is analogous to the optical frequency comb consisting of axial modes in an OPO cavity. We outline an experimental system that generates cluster states across the spatial frequency comb which can also scale the amount of quantum noise reduction to potentially larger than in other systems.« less

High Resolution MALDI Imaging Mass Spectrometry of Retinal Tissue Lipids

NASA Astrophysics Data System (ADS)

Anderson, David M. G.; Ablonczy, Zsolt; Koutalos, Yiannis; Spraggins, Jeffrey; Crouch, Rosalie K.; Caprioli, Richard M.; Schey, Kevin L.

2014-08-01

Matrix assisted laser desorption ionization imaging mass spectrometry (MALDI IMS) has the ability to provide an enormous amount of information on the abundances and spatial distributions of molecules within biological tissues. The rapid progress in the development of this technology significantly improves our ability to analyze smaller and smaller areas and features within tissues. The mammalian eye has evolved over millions of years to become an essential asset for survival, providing important sensory input of an organism's surroundings. The highly complex sensory retina of the eye is comprised of numerous cell types organized into specific layers with varying dimensions, the thinnest of which is the 10 μm retinal pigment epithelium (RPE). This single cell layer and the photoreceptor layer contain the complex biochemical machinery required to convert photons of light into electrical signals that are transported to the brain by axons of retinal ganglion cells. Diseases of the retina, including age-related macular degeneration (AMD), retinitis pigmentosa, and diabetic retinopathy, occur when the functions of these cells are interrupted by molecular processes that are not fully understood. In this report, we demonstrate the use of high spatial resolution MALDI IMS and FT-ICR tandem mass spectrometry in the Abca4 -/- knockout mouse model of Stargardt disease, a juvenile onset form of macular degeneration. The spatial distributions and identity of lipid and retinoid metabolites are shown to be unique to specific retinal cell layers.

Virtual mission stage I: Implications of a spaceborne surface water mission

NASA Astrophysics Data System (ADS)

Clark, E. A.; Alsdorf, D. E.; Bates, P.; Wilson, M. D.; Lettenmaier, D. P.

2004-12-01

The interannual and interseasonal variability of the land surface water cycle depend on the distribution of surface water in lakes, wetlands, reservoirs, and river systems; however, measurements of hydrologic variables are sparsely distributed, even in industrialized nations. Moreover, the spatial extent and storage variations of lakes, reservoirs, and wetlands are poorly known. We are developing a virtual mission to demonstrate the feasibility of observing surface water extent and variations from a spaceborne platform. In the first stage of the virtual mission, on which we report here, surface water area and fluxes are emulated using simulation modeling over three continental scale river basins, including the Ohio River, the Amazon River and an Arctic river. The Variable Infiltration Capacity (VIC) macroscale hydrologic model is used to simulate evapotranspiration, soil moisture, snow accumulation and ablation, and runoff and streamflow over each basin at one-eighth degree resolution. The runoff from this model is routed using a linear transfer model to provide input to a much more detailed flow hydraulics model. The flow hydraulics model then routes runoff through various channel and floodplain morphologies at a 250 m spatial and 20 second temporal resolution over a 100 km by 500 km domain. This information is used to evaluate trade-offs between spatial and temporal resolutions of a hypothetical high resolution spaceborne altimeter by synthetically sampling the resultant model-predicted water surface elevations.

Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

USGS Publications Warehouse

Shrestha, M.S.; Artan, G.A.; Bajracharya, S.R.; Gautam, D.K.; Tokar, S.A.

2011-01-01

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32000km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC-RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC-RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC-RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction. ?? 2011 The Authors. Journal of Flood Risk Management ?? 2011 The Chartered Institution of Water and Environmental Management.

Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

USGS Publications Warehouse

Artan, Guleid A.; Tokar, S.A.; Gautam, D.K.; Bajracharya, S.R.; Shrestha, M.S.

2011-01-01

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32 000 km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC_RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC_RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC_RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction.

Impacts of Non-Stationarity in Climate on Flood Intensity-Duration-Frequency: Case Studies in Mountainous Areas with Snowmelt

NASA Astrophysics Data System (ADS)

Hou, Z.; Ren, H.; Sun, N.; Leung, L. R.; Liu, Y.; Coleman, A. M.; Skaggs, R.; Wigmosta, M. S.

2017-12-01

Hydrologic engineering design usually involves intensity-duration-frequency (IDF) analysis for calculating runoff from a design storm of specified precipitation frequency and duration using event-based hydrologic rainfall-runoff models. Traditionally, the procedure assumes climate stationarity and neglects snowmelt-driven runoff contribution to floods. In this study, we used high resolution climate simulations to provide inputs to the physics-based Distributed Hydrology Soil and Vegetation Model (DHSVM) to determine the spatially distributed precipitation and snowmelt available for runoff. Climate model outputs were extracted around different mountainous field sites in Colorado and California. IDF curves were generated at each numerical grid of DHSVM based on the simulated precipitation, temperature, and available water for runoff. Quantitative evaluation of trending and stationarity tests were conducted to identify (quasi-)stationary time periods for reliable IDF analysis. The impact of stationarity was evaluated by comparing the derived IDF attributes with respect to time windows of different length and level of stationarity. Spatial mapping of event return-period was performed for various design storms, and spatial mapping of event intensity was performed for given duration and return periods. IDF characteristics were systematically compared (historical vs RCP4.5 vs RCP8.5) using annual maximum series vs partial duration series data with the goal of providing reliable IDF analyses to support hydrologic engineering design.

Modeling Soil Carbon Dynamics in Northern Forests: Effects of Spatial and Temporal Aggregation of Climatic Input Data.

PubMed

Dalsgaard, Lise; Astrup, Rasmus; Antón-Fernández, Clara; Borgen, Signe Kynding; Breidenbach, Johannes; Lange, Holger; Lehtonen, Aleksi; Liski, Jari

2016-01-01

Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting of greenhouse gas emissions. Organic matter decomposition varies with climate in complex nonlinear ways, rendering data aggregation nontrivial. Here, we explored the effects of temporal and spatial aggregation of climatic and litter input data on regional estimates of soil organic carbon stocks and changes for upland forests. We used the soil carbon and decomposition model Yasso07 with input from the Norwegian National Forest Inventory (11275 plots, 1960-2012). Estimates were produced at three spatial and three temporal scales. Results showed that a national level average soil carbon stock estimate varied by 10% depending on the applied spatial and temporal scale of aggregation. Higher stocks were found when applying plot-level input compared to country-level input and when long-term climate was used as compared to annual or 5-year mean values. A national level estimate for soil carbon change was similar across spatial scales, but was considerably (60-70%) lower when applying annual or 5-year mean climate compared to long-term mean climate reflecting the recent climatic changes in Norway. This was particularly evident for the forest-dominated districts in the southeastern and central parts of Norway and in the far north. We concluded that the sensitivity of model estimates to spatial aggregation will depend on the region of interest. Further, that using long-term climate averages during periods with strong climatic trends results in large differences in soil carbon estimates. The largest differences in this study were observed in central and northern regions with strongly increasing temperatures.

Modeling Soil Carbon Dynamics in Northern Forests: Effects of Spatial and Temporal Aggregation of Climatic Input Data

PubMed Central

Dalsgaard, Lise; Astrup, Rasmus; Antón-Fernández, Clara; Borgen, Signe Kynding; Breidenbach, Johannes; Lange, Holger; Lehtonen, Aleksi; Liski, Jari

2016-01-01

Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting of greenhouse gas emissions. Organic matter decomposition varies with climate in complex nonlinear ways, rendering data aggregation nontrivial. Here, we explored the effects of temporal and spatial aggregation of climatic and litter input data on regional estimates of soil organic carbon stocks and changes for upland forests. We used the soil carbon and decomposition model Yasso07 with input from the Norwegian National Forest Inventory (11275 plots, 1960–2012). Estimates were produced at three spatial and three temporal scales. Results showed that a national level average soil carbon stock estimate varied by 10% depending on the applied spatial and temporal scale of aggregation. Higher stocks were found when applying plot-level input compared to country-level input and when long-term climate was used as compared to annual or 5-year mean values. A national level estimate for soil carbon change was similar across spatial scales, but was considerably (60–70%) lower when applying annual or 5-year mean climate compared to long-term mean climate reflecting the recent climatic changes in Norway. This was particularly evident for the forest-dominated districts in the southeastern and central parts of Norway and in the far north. We concluded that the sensitivity of model estimates to spatial aggregation will depend on the region of interest. Further, that using long-term climate averages during periods with strong climatic trends results in large differences in soil carbon estimates. The largest differences in this study were observed in central and northern regions with strongly increasing temperatures. PMID:26901763

Phytoplankton standing crops within an Antarctic ice edge assessed by satellite remote sensing

NASA Technical Reports Server (NTRS)

Sullivan, C. W.; Mcclain, C. R.; Comiso, J. C.; Smith, W. O., Jr.

1988-01-01

The dynamic interactions between the pack-ice recession and the occurrence of ice blooms of phytoplankton in waters of the marginal ice zone within an Antarctic ice edge were investigated using CZCS and SMMR imageries from the Nimbus 7 satellite (September 16-December 17, 1983), together with in situ measurements of pigments and sea ice concentration carried out from November 7 to December 2. A substantial amount of spatial variability in pigment concentration was observed to occur along the ice edge in the Weddell Sea. The relationships among light, ice distribution, and vertical stability and their effects on observed spatial variations in phytoplankton biomass are discussed. The results of this investigation suggest that the retreat of ice provides an input of significant volumes of meltwater which creates vertical stability for a period necessary to permit growth and accumulation of phytoplankton.

Vibration Response Models of a Stiffened Aluminum Plate Excited by a Shaker

NASA Technical Reports Server (NTRS)

Cabell, Randolph H.

2008-01-01

Numerical models of structural-acoustic interactions are of interest to aircraft designers and the space program. This paper describes a comparison between two energy finite element codes, a statistical energy analysis code, a structural finite element code, and the experimentally measured response of a stiffened aluminum plate excited by a shaker. Different methods for modeling the stiffeners and the power input from the shaker are discussed. The results show that the energy codes (energy finite element and statistical energy analysis) accurately predicted the measured mean square velocity of the plate. In addition, predictions from an energy finite element code had the best spatial correlation with measured velocities. However, predictions from a considerably simpler, single subsystem, statistical energy analysis model also correlated well with the spatial velocity distribution. The results highlight a need for further work to understand the relationship between modeling assumptions and the prediction results.

Probing Atomic Dynamics and Structures Using Optical Patterns

NASA Astrophysics Data System (ADS)

Schmittberger, Bonnie L.; Gauthier, Daniel J.

2015-05-01

Pattern formation is a widely studied phenomenon that can provide fundamental insights into nonlinear systems. Emergent patterns in cold atoms are of particular interest in condensed matter physics and quantum information science because one can relate optical patterns to spatial structures in the atoms. In our experimental system, we study multimode optical patterns generated from a sample of cold, thermal atoms. We observe this nonlinear optical phenomenon at record low input powers due to the highly nonlinear nature of the spatial bunching of atoms in an optical lattice. We present a detailed study of the dynamics of these bunched atoms during optical pattern formation. We show how small changes in the atomic density distribution affect the symmetry of the generated patterns as well as the nature of the nonlinearity that describes the light-atom interaction. We gratefully acknowledge the financial support of the National Science Foundation through Grant #PHY-1206040.

Power-controlled transition from standard to negative refraction in reorientational soft matter.

PubMed

Piccardi, Armando; Alberucci, Alessandro; Kravets, Nina; Buchnev, Oleksandr; Assanto, Gaetano

2014-11-25

Refraction at a dielectric interface can take an anomalous character in anisotropic crystals, when light is negatively refracted with incident and refracted beams emerging on the same side of the interface normal. In soft matter subject to reorientation, such as nematic liquid crystals, the nonlinear interaction with light allows tuning of the optical properties. We demonstrate that in such material a beam of light can experience either positive or negative refraction depending on input power, as it can alter the spatial distribution of the optic axis and, in turn, the direction of the energy flow when traveling across an interface. Moreover, the nonlinear optical response yields beam self-focusing and spatial localization into a self-confined solitary wave through the formation of a graded-index waveguide, linking the refractive transition to power-driven readdressing of copolarized guided-wave signals, with a number of output ports not limited by diffraction.

An Overview of the GIS Weasel

USGS Publications Warehouse

Viger, Roland J.

2008-01-01

This fact sheet provides a high-level description of the GIS Weasel, a software system designed to aid users in preparing spatial information as input to lumped and distributed parameter environmental simulation models (ESMs). The GIS Weasel provides geographic information system (GIS) tools to help create maps of geographic features relevant to the application of a user?s ESM and to generate parameters from those maps. The operation of the GIS Weasel does not require a user to be a GIS expert, only that a user has an understanding of the spatial information requirements of the model. The GIS Weasel software system provides a GIS-based graphical user interface (GUI), C programming language executables, and general utility scripts. The software will run on any computing platform where ArcInfo Workstation (version 8.1 or later) and the GRID extension are accessible. The user controls the GIS Weasel by interacting with menus, maps, and tables.

Implementation of Complex Biological Logic Circuits Using Spatially Distributed Multicellular Consortia

PubMed Central

Urrios, Arturo; de Nadal, Eulàlia; Solé, Ricard; Posas, Francesc

2016-01-01

Engineered synthetic biological devices have been designed to perform a variety of functions from sensing molecules and bioremediation to energy production and biomedicine. Notwithstanding, a major limitation of in vivo circuit implementation is the constraint associated to the use of standard methodologies for circuit design. Thus, future success of these devices depends on obtaining circuits with scalable complexity and reusable parts. Here we show how to build complex computational devices using multicellular consortia and space as key computational elements. This spatial modular design grants scalability since its general architecture is independent of the circuit’s complexity, minimizes wiring requirements and allows component reusability with minimal genetic engineering. The potential use of this approach is demonstrated by implementation of complex logical functions with up to six inputs, thus demonstrating the scalability and flexibility of this method. The potential implications of our results are outlined. PMID:26829588

TMPA Products 3B42RT & 3B42V6: Evaluation and Application in Qinghai-Tibet Plateau

NASA Astrophysics Data System (ADS)

Hao, Z.; Sun, L.; Wang, J.

2012-04-01

Hydrological researchers in Qinghai-Tibet Plateau tend to be haunted by deficiency of station gauged precipitation data for the sparse and uneven distribution of local meteorological stations. Fortunately, alternative data can be obtained from TRMM (Tropic Rainfall Measurement Mission) satellite. Preliminary evaluation and necessary correction of TRMM satellite rainfall products is required for the sake of reliability and suitability considering that TRMM precipitation is unconventional and natural condition in Qinghai-Tibet Plateau is unusually complicated. 3B42RT and 3B42V6 products from TRMM Multisatellite Precipitation Analysis(TMPA) are evaluated in northeast Qinghai-Tibet Plateau with 50 stations quality-controlled gauged daily precipitation as the benchmark precipitation set. It is found that the RT data overestimates the actual precipitation greatly while V6 only overestimates it slightly. RT data shows different seasonal and inter-annual accuracies. Summer and autumn see better accuracies than winter and spring and wet years see higher accuracies than dry years. Latitude is believed to be an important factor that influences the accuracy of satellite precipitation. Both RT and V6 can reflect the general pattern of the spatial distribution of precipitation even though RT overestimates the quantity greatly. A new parameter, accumulated precipitation weight point (APWP), was introduced to describe the temporal-spatial pattern evolution of precipitation. The APWP of both RT and V6 were moving from south to north in the past decade, but they are all in the west of station gauged precipitation APWP(s).V6 APWP track fit gauged precipitation perfectly while RT APWP track has over-exaggerated legs, indicating that spatial distribution of RT precipitation experienced unreasonable sharp changes. A practical and operational procedure to correct satellite precipitation data is developed. For RT, there are two steps. Step 1, the downscaling, original daily precipitation was multiplied by a ratio of its monthly satellite/station precipitation gauged precipitation. Step2, objective analysis, Barnes/Cressman successive correction as well as Optimal Interpolation was applied to refine the processed daily results. Step 1 is unnecessary for V6 correction. The accuracy of RT can be improved significantly and the spatial details of satellite precipitation can be obtained as much as possible while quite little improvement showed in V6 correction. Besides, the iteration of successive correction should not be more than twice and the ideal influence radius for Optimal Interpolation is R=5. The original/corrected RT and V6 data sets were used as precipitation inputs to drive a newly developed hydrological model DHM-SP in the headwater region of the Yellow river so as to assess their applicability in simulating the daily runoff. V6 simulation result is qualified even though it is uncorrected. The bias in RT is too much to make use of RT as model input directly while quite satisfied results can be derived from corrected RT input. The simulation results of corrected RT are even better than that of station gauged and V6.

Forebrain pathway for auditory space processing in the barn owl.

PubMed

Cohen, Y E; Miller, G L; Knudsen, E I

1998-02-01

The forebrain plays an important role in many aspects of sound localization behavior. Yet, the forebrain pathway that processes auditory spatial information is not known for any species. Using standard anatomic labeling techniques, we used a "top-down" approach to trace the flow of auditory spatial information from an output area of the forebrain sound localization pathway (the auditory archistriatum, AAr), back through the forebrain, and into the auditory midbrain. Previous work has demonstrated that AAr units are specialized for auditory space processing. The results presented here show that the AAr receives afferent input from Field L both directly and indirectly via the caudolateral neostriatum. Afferent input to Field L originates mainly in the auditory thalamus, nucleus ovoidalis, which, in turn, receives input from the central nucleus of the inferior colliculus. In addition, we confirmed previously reported projections of the AAr to the basal ganglia, the external nucleus of the inferior colliculus (ICX), the deep layers of the optic tectum, and various brain stem nuclei. A series of inactivation experiments demonstrated that the sharp tuning of AAr sites for binaural spatial cues depends on Field L input but not on input from the auditory space map in the midbrain ICX: pharmacological inactivation of Field L eliminated completely auditory responses in the AAr, whereas bilateral ablation of the midbrain ICX had no appreciable effect on AAr responses. We conclude, therefore, that the forebrain sound localization pathway can process auditory spatial information independently of the midbrain localization pathway.

Experience-dependent shaping of hippocampal CA1 intracellular activity in novel and familiar environments

PubMed Central

Cohen, Jeremy D; Bolstad, Mark; Lee, Albert K

2017-01-01

The hippocampus is critical for producing stable representations of familiar spaces. How these representations arise is poorly understood, largely because changes to hippocampal inputs have not been measured during spatial learning. Here, using intracellular recording, we monitored inputs and plasticity-inducing complex spikes (CSs) in CA1 neurons while mice explored novel and familiar virtual environments. Inputs driving place field spiking increased in amplitude – often suddenly – during novel environment exploration. However, these increases were not sustained in familiar environments. Rather, the spatial tuning of inputs became increasingly similar across repeated traversals of the environment with experience – both within fields and throughout the whole environment. In novel environments, CSs were not necessary for place field formation. Our findings support a model in which initial inhomogeneities in inputs are amplified to produce robust place field activity, then plasticity refines this representation into one with less strongly modulated, but more stable, inputs for long-term storage. DOI: http://dx.doi.org/10.7554/eLife.23040.001 PMID:28742496

Entorhinal-CA3 Dual-Input Control of Spike Timing in the Hippocampus by Theta-Gamma Coupling.

PubMed

Fernández-Ruiz, Antonio; Oliva, Azahara; Nagy, Gergő A; Maurer, Andrew P; Berényi, Antal; Buzsáki, György

2017-03-08

Theta-gamma phase coupling and spike timing within theta oscillations are prominent features of the hippocampus and are often related to navigation and memory. However, the mechanisms that give rise to these relationships are not well understood. Using high spatial resolution electrophysiology, we investigated the influence of CA3 and entorhinal inputs on the timing of CA1 neurons. The theta-phase preference and excitatory strength of the afferent CA3 and entorhinal inputs effectively timed the principal neuron activity, as well as regulated distinct CA1 interneuron populations in multiple tasks and behavioral states. Feedback potentiation of distal dendritic inhibition by CA1 place cells attenuated the excitatory entorhinal input at place field entry, coupled with feedback depression of proximal dendritic and perisomatic inhibition, allowing the CA3 input to gain control toward the exit. Thus, upstream inputs interact with local mechanisms to determine theta-phase timing of hippocampal neurons to support memory and spatial navigation. Copyright © 2017 Elsevier Inc. All rights reserved.

Orientation selectivity and the functional clustering of synaptic inputs in primary visual cortex

PubMed Central

Wilson, Daniel E.; Whitney, David E.; Scholl, Benjamin; Fitzpatrick, David

2016-01-01

The majority of neurons in primary visual cortex are tuned for stimulus orientation, but the factors that account for the range of orientation selectivities exhibited by cortical neurons remain unclear. To address this issue, we used in vivo 2-photon calcium imaging to characterize the orientation tuning and spatial arrangement of synaptic inputs to the dendritic spines of individual pyramidal neurons in layer 2/3 of ferret visual cortex. The summed synaptic input to individual neurons reliably predicted the neuron’s orientation preference, but did not account for differences in orientation selectivity among neurons. These differences reflected a robust input-output nonlinearity that could not be explained by spike threshold alone, and was strongly correlated with the spatial clustering of co-tuned synaptic inputs within the dendritic field. Dendritic branches with more co-tuned synaptic clusters exhibited greater rates of local dendritic calcium events supporting a prominent role for functional clustering of synaptic inputs in dendritic nonlinearities that shape orientation selectivity. PMID:27294510

Does a Flatter General Gradient of Visual Attention Explain Peripheral Advantages and Central Deficits in Deaf Adults?

PubMed Central

Samar, Vincent J.; Berger, Lauren

2017-01-01

Individuals deaf from early age often outperform hearing individuals in the visual periphery on attention-dependent dorsal stream tasks (e.g., spatial localization or movement detection), but sometimes show central visual attention deficits, usually on ventral stream object identification tasks. It has been proposed that early deafness adaptively redirects attentional resources from central to peripheral vision to monitor extrapersonal space in the absence of auditory cues, producing a more evenly distributed attention gradient across visual space. However, little direct evidence exists that peripheral advantages are functionally tied to central deficits, rather than determined by independent mechanisms, and previous studies using several attention tasks typically report peripheral advantages or central deficits, not both. To test the general altered attentional gradient proposal, we employed a novel divided attention paradigm that measured target localization performance along a gradient from parafoveal to peripheral locations, independent of concurrent central object identification performance in prelingually deaf and hearing groups who differed in access to auditory input. Deaf participants without cochlear implants (No-CI), with cochlear implants (CI), and hearing participants identified vehicles presented centrally, and concurrently reported the location of parafoveal (1.4°) and peripheral (13.3°) targets among distractors. No-CI participants but not CI participants showed a central identification accuracy deficit. However, all groups displayed equivalent target localization accuracy at peripheral and parafoveal locations and nearly parallel parafoveal-peripheral gradients. Furthermore, the No-CI group’s central identification deficit remained after statistically controlling peripheral performance; conversely, the parafoveal and peripheral group performance equivalencies remained after controlling central identification accuracy. These results suggest that, in the absence of auditory input, reduced central attentional capacity is not necessarily associated with enhanced peripheral attentional capacity or with flattening of a general attention gradient. Our findings converge with earlier studies suggesting that a general graded trade-off of attentional resources across the visual field does not adequately explain the complex task-dependent spatial distribution of deaf-hearing performance differences reported in the literature. Rather, growing evidence suggests that the spatial distribution of attention-mediated performance in deaf people is determined by sophisticated cross-modal plasticity mechanisms that recruit specific sensory and polymodal cortex to achieve specific compensatory processing goals. PMID:28559861

Modeling emissions for three-dimensional atmospheric chemistry transport models.

PubMed

Matthias, Volker; Arndt, Jan A; Aulinger, Armin; Bieser, Johannes; Denier Van Der Gon, Hugo; Kranenburg, Richard; Kuenen, Jeroen; Neumann, Daniel; Pouliot, George; Quante, Markus

2018-01-24

Poor air quality is still a threat for human health in many parts of the world. In order to assess measures for emission reductions and improved air quality, three-dimensional atmospheric chemistry transport modeling systems are used in numerous research institutions and public authorities. These models need accurate emission data in appropriate spatial and temporal resolution as input. This paper reviews the most widely used emission inventories on global and regional scale and looks into the methods used to make the inventory data model ready. Shortcomings of using standard temporal profiles for each emission sector are discussed and new methods to improve the spatio-temporal distribution of the emissions are presented. These methods are often neither top-down nor bottom-up approaches but can be seen as hybrid methods that use detailed information about the emission process to derive spatially varying temporal emission profiles. These profiles are subsequently used to distribute bulk emissions like national totals on appropriate grids. The wide area of natural emissions is also summarized and the calculation methods are described. Almost all types of natural emissions depend on meteorological information, which is why they are highly variable in time and space and frequently calculated within the chemistry transport models themselves. The paper closes with an outlook for new ways to improve model ready emission data, for example by using external databases about road traffic flow or satellite data to determine actual land use or leaf area. In a world where emission patterns change rapidly, it seems appropriate to use new types of statistical and observational data to create detailed emission data sets and keep emission inventories up-to-date. Emission data is probably the most important input for chemistry transport model (CTM) systems. It needs to be provided in high temporal and spatial resolution and on a grid that is in agreement with the CTM grid. Simple methods to distribute the emissions in time and space need to be replaced by sophisticated emission models in order to improve the CTM results. New methods, e.g. for ammonia emissions, provide grid cell dependent temporal profiles. In the future, large data fields from traffic observations or satellite observations could be used for more detailed emission data.

Spatial variability in acoustic backscatter as an indicator of tissue homogenate production in pulsed cavitational ultrasound therapy.

PubMed

Parsons, Jessica E; Cain, Charles A; Fowlkes, J Brian

2007-03-01

Spatial variability in acoustic backscatter is investigated as a potential feedback metric for assessment of lesion morphology during cavitation-mediated mechanical tissue disruption ("histotripsy"). A 750-kHz annular array was aligned confocally with a 4.5 MHz passive backscatter receiver during ex vivo insonation of porcine myocardium. Various exposure conditions were used to elicit a range of damage morphologies and backscatter characteristics [pulse duration = 14 micros, pulse repetition frequency (PRF) = 0.07-3.1 kHz, average I(SPPA) = 22-44 kW/cm2]. Variability in backscatter spatial localization was quantified by tracking the lag required to achieve peak correlation between sequential RF A-lines received. Mean spatial variability was observed to be significantly higher when damage morphology consisted of mechanically disrupted tissue homogenate versus mechanically intact coagulation necrosis (2.35 +/- 1.59 mm versus 0.067 +/- 0.054 mm, p < 0.025). Statistics from these variability distributions were used as the basis for selecting a threshold variability level to identify the onset of homogenate formation via an abrupt, sustained increase in spatially dynamic backscatter activity. Specific indices indicative of the state of the homogenization process were quantified as a function of acoustic input conditions. The prevalence of backscatter spatial variability was observed to scale with the amount of homogenate produced for various PRFs and acoustic intensities.

Distributed encoding of spatial and object categories in primate hippocampal microcircuits

PubMed Central

Opris, Ioan; Santos, Lucas M.; Gerhardt, Greg A.; Song, Dong; Berger, Theodore W.; Hampson, Robert E.; Deadwyler, Sam A.

2015-01-01

The primate hippocampus plays critical roles in the encoding, representation, categorization and retrieval of cognitive information. Such cognitive abilities may use the transformational input-output properties of hippocampal laminar microcircuitry to generate spatial representations and to categorize features of objects, images, and their numeric characteristics. Four nonhuman primates were trained in a delayed-match-to-sample (DMS) task while multi-neuron activity was simultaneously recorded from the CA1 and CA3 hippocampal cell fields. The results show differential encoding of spatial location and categorization of images presented as relevant stimuli in the task. Individual hippocampal cells encoded visual stimuli only on specific types of trials in which retention of either, the Sample image, or the spatial position of the Sample image indicated at the beginning of the trial, was required. Consistent with such encoding, it was shown that patterned microstimulation applied during Sample image presentation facilitated selection of either Sample image spatial locations or types of images, during the Match phase of the task. These findings support the existence of specific codes for spatial and numeric object representations in primate hippocampus which can be applied on differentially signaled trials. Moreover, the transformational properties of hippocampal microcircuitry, together with the patterned microstimulation are supporting the practical importance of this approach for cognitive enhancement and rehabilitation, needed for memory neuroprosthetics. PMID:26500473

Declining spatial efficiency of global cropland nitrogen allocation

NASA Astrophysics Data System (ADS)

Mueller, Nathaniel D.; Lassaletta, Luis; Runck, Bryan C.; Billen, Gilles; Garnier, Josette; Gerber, James S.

2017-02-01

Efficiently allocating nitrogen (N) across space maximizes crop productivity for a given amount of N input and reduces N losses to the environment. Here we quantify changes in the global spatial efficiency of cropland N use by calculating historical trade-off frontiers relating N inputs to possible N yield assuming efficient allocation. Time series cropland N budgets from 1961 to 2009 characterize the evolution of N input-yield response functions across 12 regions and are the basis for constructing trade-off frontiers. Improvements in agronomic technology have substantially increased cropping system yield potentials and expanded N-driven crop production possibilities. However, we find that these gains are compromised by the declining spatial efficiency of N use across regions. Since the start of the Green Revolution, N inputs and yields have moved farther from the optimal frontier over time; in recent years (1994-2009), global N surplus has grown to a value that is 69% greater than what is possible with efficient N allocation between regions. To reflect regional pollution and agricultural development goals, we construct scenarios that restrict reallocation, finding that these changes only slightly decrease potential gains in nitrogen use efficiency. Our results are inherently conservative due to the regional unit of analysis, meaning a larger potential exists than is quantified here for cross-scale policies to promote spatially efficient N use.

Functional recovery of odor representations in regenerated sensory inputs to the olfactory bulb

PubMed Central

Cheung, Man C.; Jang, Woochan; Schwob, James E.; Wachowiak, Matt

2014-01-01

The olfactory system has a unique capacity for recovery from peripheral damage. After injury to the olfactory epithelium (OE), olfactory sensory neurons (OSNs) regenerate and re-converge on target glomeruli of the olfactory bulb (OB). Thus far, this process has been described anatomically for only a few defined populations of OSNs. Here we characterize this regeneration at a functional level by assessing how odor representations carried by OSN inputs to the OB recover after massive loss and regeneration of the sensory neuron population. We used chronic imaging of mice expressing synaptopHluorin in OSNs to monitor odor representations in the dorsal OB before lesion by the olfactotoxin methyl bromide and after a 12 week recovery period. Methyl bromide eliminated functional inputs to the OB, and these inputs recovered to near-normal levels of response magnitude within 12 weeks. We also found that the functional topography of odor representations recovered after lesion, with odorants evoking OSN input to glomerular foci within the same functional domains as before lesion. At a finer spatial scale, however, we found evidence for mistargeting of regenerated OSN axons onto OB targets, with odorants evoking synaptopHluorin signals in small foci that did not conform to a typical glomerular structure but whose distribution was nonetheless odorant-specific. These results indicate that OSNs have a robust ability to reestablish functional inputs to the OB and that the mechanisms underlying the topography of bulbar reinnervation during development persist in the adult and allow primary sensory representations to be largely restored after massive sensory neuron loss. PMID:24431990

Spatial Statistics of the Clark County Parcel Map, Trial Geotechnical Models, and Effects on Ground Motions in Las Vegas Valley

NASA Astrophysics Data System (ADS)

Savran, W. H.; Louie, J. N.; Pullammanappallil, S.; Pancha, A.

2011-12-01

When deterministically modeling the propagation of seismic waves, shallow shear-wave velocity plays a crucial role in predicting shaking effects such as peak ground velocity (PGV). The Clark County Parcel Map provides us with a data set of geotechnical velocities in Las Vegas Valley, at an unprecedented level of detail. Las Vegas Valley is a basin with similar geologic properties to some areas of Southern California. We analyze elementary spatial statistical properties of the Parcel Map, along with calculating its spatial variability. We then investigate these spatial statistics from the PGV results computed from two geotechnical models that incorporate the Parcel Map as parameters. Plotting a histogram of the Parcel Map 30-meter depth-averaged shear velocity (Vs30) values shows the data to approximately fit a bimodal normal distribution with μ1 = 400 m/s, σ1 = 76 m/s, μ2 = 790 m/s, σ2 = 149 m/s, and p = 0.49., where μ is the mean, σ is standard deviation, and p is the probability mixing factor for the bimodal distribution. Based on plots of spatial power spectra, the Parcel Map appears to be fractal over the second and third decades, in kilometers. The spatial spectra possess the same fractal dimension in the N-S and the E-W directions, indicating isotropic scale invariance. We configured finite-difference wave propagation models at 0.5 Hz with LLNL's E3D code, utilizing the Parcel Map as input parameters to compute a PGV data set from a scenario earthquake (Black Hills M6.5). The resulting PGV is fractal over the same spatial frequencies as the Vs30 data sets associated with their respective models. The fractal dimension is systematically lower in all of the PGV maps as opposed to the Vs30 maps, showing that the PGV maps are richer in higher spatial frequencies. This is potentially caused by a lens focusing effects on seismic waves due to spatial heterogeneity in site conditions.

Estimation of Global 1km-grid Terrestrial Carbon Exchange Part II: Evaluations and Applications

NASA Astrophysics Data System (ADS)

Murakami, K.; Sasai, T.; Kato, S.; Niwa, Y.; Saito, M.; Takagi, H.; Matsunaga, T.; Hiraki, K.; Maksyutov, S. S.; Yokota, T.

2015-12-01

Global terrestrial carbon cycle largely depends on a spatial pattern in land cover type, which is heterogeneously-distributed over regional and global scales. Many studies have been trying to reveal distribution of carbon exchanges between terrestrial ecosystems and atmosphere for understanding global carbon cycle dynamics by using terrestrial biosphere models, satellite data, inventory data, and so on. However, most studies remained within several tens of kilometers grid spatial resolution, and the results have not been enough to understand the detailed pattern of carbon exchanges based on ecological community and to evaluate the carbon stocks by forest ecosystems in each countries. Improving the sophistication of spatial resolution is obviously necessary to enhance the accuracy of carbon exchanges. Moreover, the improvement may contribute to global warming awareness, policy makers and other social activities. We show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. The methodology for these estimations are shown in the 2015 AGU FM poster "Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling". In this study, we evaluated the carbon exchanges in various regions with other approaches. We used the satellite-driven biosphere model (BEAMS) as our estimations, GOSAT L4A CO2 flux data, NEP retrieved by NICAM and CarbonTracer2013 flux data, for period from Jun 2001 to Dec 2012. The temporal patterns for this period were indicated similar trends between BEAMS, GOSAT, NICAM, and CT2013 in many sub-continental regions. Then, we estimated the terrestrial carbon exchanges in each countries, and could indicated the temporal patterns of the exchanges in large carbon stock regions.Global terrestrial carbon cycle largely depends on a spatial pattern of land cover type, which is heterogeneously-distributed over regional and global scales. Many studies have been trying to reveal distribution of carbon exchanges between terrestrial ecosystems and atmosphere for understanding global carbon cycle dynamics by using terrestrial biosphere models, satellite data, inventory data, and so on. However, most studies remained within several tens of kilometers grid spatial resolution, and the results have not been enough to understand the detailed pattern of carbon exchanges based on ecological community and to evaluate the carbon stocks by forest ecosystems in each countries. Improving the sophistication of spatial resolution is obviously necessary to enhance the accuracy of carbon exchanges. Moreover, the improvement may contribute to global warming awareness, policy makers and other social activities. We show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. The methodology for these estimations are shown in the 2015 AGU FM poster "Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling". In this study, we evaluated the carbon exchanges in various regions with other approaches. We used the satellite-driven biosphere model (BEAMS) as our estimations, GOSAT L4A CO2 flux data, NEP retrieved by NICAM and CarbonTracer2013 flux data, for period from Jun 2001 to Dec 2012. The temporal patterns for this period were indicated similar trends between BEAMS, GOSAT, NICAM, and CT2013 in many sub-continental regions. Then, we estimated the terrestrial carbon exchanges in each countries, and could indicated the temporal patterns of the exchanges in large carbon stock regions.

Spatial distribution of organochlorine pesticides (OCPs) and effect of soil characters: a case study of a pesticide producing factory.

PubMed

Zhao, Congcong; Xie, Huijun; Zhang, Jian; Xu, Jingtao; Liang, Shuang

2013-03-01

The distribution and concentration of some organochlorine pesticides (OCPs) in the soil around a pesticide factory in Zibo, China, were examined, including dichlorodiphenyltrichloroethane (DDT) and its metabolites, isomers of hexachlorocyclohexane (HCH) and endosulfan (ENDO). The results showed that the OCPs concentrations were extraordinary high in this region. The concentrations of DDTs, HCHs, and ENDO were measured in the range of 0.775-226.711, 0.248-42.838, and 0.081-1.644 mg kg(-1), respectively. DDT and its isomers were identified to be the dominate contaminants in most of the sampling sites. In the vertical direction, the distribution pattern of the total OCPs was in order of DDTs, HCHs, and ENDO in the 0-20 cm, but in 20-40 and 40-60 cm the trends were unobvious. Although no recent input occurred in most areas, the residues of OCPs remained in deep soil due to their persistence. Unlike ENDO, DDTs and HCHs appeared to have the similar property in terms of not only the migration pattern in soil, but also the relationship to the same dominant impact factor (i.e. organic matter). DDTs and HCHs were affected positively by the organic matter, whereas ENDO was affected negatively. Due to the interrelationship among various impact factors, the spatial distribution of pesticides in the soil was considered to be a combined result. Copyright © 2012 Elsevier Ltd. All rights reserved.

High organic inputs explain shallow and deep SOC storage in a long-term agroforestry system - combining experimental and modeling approaches

NASA Astrophysics Data System (ADS)

Cardinael, Rémi; Guenet, Bertrand; Chevallier, Tiphaine; Dupraz, Christian; Cozzi, Thomas; Chenu, Claire

2018-01-01

Agroforestry is an increasingly popular farming system enabling agricultural diversification and providing several ecosystem services. In agroforestry systems, soil organic carbon (SOC) stocks are generally increased, but it is difficult to disentangle the different factors responsible for this storage. Organic carbon (OC) inputs to the soil may be larger, but SOC decomposition rates may be modified owing to microclimate, physical protection, or priming effect from roots, especially at depth. We used an 18-year-old silvoarable system associating hybrid walnut trees (Juglans regia × nigra) and durum wheat (Triticum turgidum L. subsp. durum) and an adjacent agricultural control plot to quantify all OC inputs to the soil - leaf litter, tree fine root senescence, crop residues, and tree row herbaceous vegetation - and measured SOC stocks down to 2 m of depth at varying distances from the trees. We then proposed a model that simulates SOC dynamics in agroforestry accounting for both the whole soil profile and the lateral spatial heterogeneity. The model was calibrated to the control plot only. Measured OC inputs to soil were increased by about 40 % (+ 1.11 t C ha-1 yr-1) down to 2 m of depth in the agroforestry plot compared to the control, resulting in an additional SOC stock of 6.3 t C ha-1 down to 1 m of depth. However, most of the SOC storage occurred in the first 30 cm of soil and in the tree rows. The model was strongly validated, properly describing the measured SOC stocks and distribution with depth in agroforestry tree rows and alleys. It showed that the increased inputs of fresh biomass to soil explained the observed additional SOC storage in the agroforestry plot. Moreover, only a priming effect variant of the model was able to capture the depth distribution of SOC stocks, suggesting the priming effect as a possible mechanism driving deep SOC dynamics. This result questions the potential of soils to store large amounts of carbon, especially at depth. Deep-rooted trees modify OC inputs to soil, a process that deserves further study given its potential effects on SOC dynamics.

A comparative study of mixed exponential and Weibull distributions in a stochastic model replicating a tropical rainfall process

NASA Astrophysics Data System (ADS)

Abas, Norzaida; Daud, Zalina M.; Yusof, Fadhilah

2014-11-01

A stochastic rainfall model is presented for the generation of hourly rainfall data in an urban area in Malaysia. In view of the high temporal and spatial variability of rainfall within the tropical rain belt, the Spatial-Temporal Neyman-Scott Rectangular Pulse model was used. The model, which is governed by the Neyman-Scott process, employs a reasonable number of parameters to represent the physical attributes of rainfall. A common approach is to attach each attribute to a mathematical distribution. With respect to rain cell intensity, this study proposes the use of a mixed exponential distribution. The performance of the proposed model was compared to a model that employs the Weibull distribution. Hourly and daily rainfall data from four stations in the Damansara River basin in Malaysia were used as input to the models, and simulations of hourly series were performed for an independent site within the basin. The performance of the models was assessed based on how closely the statistical characteristics of the simulated series resembled the statistics of the observed series. The findings obtained based on graphical representation revealed that the statistical characteristics of the simulated series for both models compared reasonably well with the observed series. However, a further assessment using the AIC, BIC and RMSE showed that the proposed model yields better results. The results of this study indicate that for tropical climates, the proposed model, using a mixed exponential distribution, is the best choice for generation of synthetic data for ungauged sites or for sites with insufficient data within the limit of the fitted region.

Physical Processes Controlling the Spatial Distributions of Relative Humidity in the Tropical Tropopause Layer Over the Pacific

NASA Technical Reports Server (NTRS)

Jensen, Eric J.; Thornberry, Troy D.; Rollins, Andrew W.; Ueyama, Rei; Pfister, Leonhard; Bui, Thaopaul; Diskin, Glenn S.; Digangi, Joshua P.; Hintsa, Eric; Gao, Ru-Shan;

Spatially explicit global population scenarios consistent with the Shared Socioeconomic Pathways

DOE PAGES

Jones, B.; O’Neill, B. C.

2016-07-29

Here we report that the projected size and spatial distribution of the future population are important drivers of global change and key determinants of exposure and vulnerability to hazards. Spatial demographic projections are widely used as inputs to spatial projections of land use, energy use, and emissions, as well as to assessments of the impacts of extreme events, sea level rise, and other climate-related outcomes. To date, however, there are very few global-scale, spatially explicit population projections, and those that do exist are often based on simple scaling or trend extrapolation. Here we present a new set of global, spatiallymore » explicit population scenarios that are consistent with the new Shared Socioeconomic Pathways (SSPs) developed to facilitate global change research. We use a parameterized gravity-based downscaling model to produce projections of spatial population change that are quantitatively consistent with national population and urbanization projections for the SSPs and qualitatively consistent with assumptions in the SSP narratives regarding spatial development patterns. We show that the five SSPs lead to substantially different spatial population outcomes at the continental, national, and sub-national scale. In general, grid cell-level outcomes are most influenced by national-level population change, second by urbanization rate, and third by assumptions about the spatial style of development. However, the relative importance of these factors is a function of the magnitude of the projected change in total population and urbanization for each country and across SSPs. We also demonstrate variation in outcomes considering the example of population existing in a low-elevation coastal zone under alternative scenarios.« less

Spatially explicit global population scenarios consistent with the Shared Socioeconomic Pathways

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, B.; O’Neill, B. C.

Here we report that the projected size and spatial distribution of the future population are important drivers of global change and key determinants of exposure and vulnerability to hazards. Spatial demographic projections are widely used as inputs to spatial projections of land use, energy use, and emissions, as well as to assessments of the impacts of extreme events, sea level rise, and other climate-related outcomes. To date, however, there are very few global-scale, spatially explicit population projections, and those that do exist are often based on simple scaling or trend extrapolation. Here we present a new set of global, spatiallymore » explicit population scenarios that are consistent with the new Shared Socioeconomic Pathways (SSPs) developed to facilitate global change research. We use a parameterized gravity-based downscaling model to produce projections of spatial population change that are quantitatively consistent with national population and urbanization projections for the SSPs and qualitatively consistent with assumptions in the SSP narratives regarding spatial development patterns. We show that the five SSPs lead to substantially different spatial population outcomes at the continental, national, and sub-national scale. In general, grid cell-level outcomes are most influenced by national-level population change, second by urbanization rate, and third by assumptions about the spatial style of development. However, the relative importance of these factors is a function of the magnitude of the projected change in total population and urbanization for each country and across SSPs. We also demonstrate variation in outcomes considering the example of population existing in a low-elevation coastal zone under alternative scenarios.« less

Malaysia.

PubMed

1980-10-01

The official government policy in Malaysia is to reduce the rate of population growth through decreasing fertility levels and a program of economic and social restructuring. Population policy was conceived as encompassing wider dimensions than family planning, with emphasis on spatial distribution policies. The first Population and Housing Census was undertaken by the government in 1970. Regular decennial census taking occurred between 1891 and 1957. Birth and death registrations are considered incomplete. Population issues are integrated by various organizations into their ongoing programs such as those of the Ministries of Health, Education or Agriculture. The National Family Planning Board, an interministerial body in the Prime Minister's Department, has input from development planning units. A population studies group was established within the Economic Planning Unit. The total 1980 population was 13,640,000; the rate of population growth was 2.6 from 1975-80. Life expectancy was 61.3. Morbidity and mortality rates have dropped because of disease control and malnutrition reduction. 7.4% of the population are foreign born. Spatial distribution is to be adjusted through rural land development and resettlement; promotion of industrial development in low-income states; development of new growth centers and towns; and, urban development and renewal.

Paths of Improving the Technological Process of Manufacture of GTE Turbine Blades

NASA Astrophysics Data System (ADS)

Vdovin, R. A.; Smelov, V. G.; Bolotov, M. A.; Pronichev, N. D.

2016-08-01

The article provides an analysis of the problems at manufacture of blades of the turbine of gas-turbine engines and power stations is provided in article, and also paths of perfecting of technological process of manufacture of blades are offered. The analysis of the main systems of basing of blades in the course of machining and the control methods of the processed blades existing at the enterprises with the indication of merits and demerits is carried out. In work criteria in the form of the mathematical models of a spatial distribution of an allowance considering the uniform distribution of an allowance on a feather profile are developed. The considered methods allow to reduce percent of release of marriage and to reduce labor input when polishing path part of a feather of blades of the turbine.

Subgrid spatial variability of soil hydraulic functions for hydrological modelling

NASA Astrophysics Data System (ADS)

Kreye, Phillip; Meon, Günter

2016-07-01

State-of-the-art hydrological applications require a process-based, spatially distributed hydrological model. Runoff characteristics are demanded to be well reproduced by the model. Despite that, the model should be able to describe the processes at a subcatchment scale in a physically credible way. The objective of this study is to present a robust procedure to generate various sets of parameterisations of soil hydraulic functions for the description of soil heterogeneity on a subgrid scale. Relations between Rosetta-generated values of saturated hydraulic conductivity (Ks) and van Genuchten's parameters of soil hydraulic functions were statistically analysed. An universal function that is valid for the complete bandwidth of Ks values could not be found. After concentrating on natural texture classes, strong correlations were identified for all parameters. The obtained regression results were used to parameterise sets of hydraulic functions for each soil class. The methodology presented in this study is applicable on a wide range of spatial scales and does not need input data from field studies. The developments were implemented into a hydrological modelling system.

Combining a Spatial Model and Demand Forecasts to Map Future Surface Coal Mining in Appalachia

PubMed Central

Strager, Michael P.; Strager, Jacquelyn M.; Evans, Jeffrey S.; Dunscomb, Judy K.; Kreps, Brad J.; Maxwell, Aaron E.

2015-01-01

Predicting the locations of future surface coal mining in Appalachia is challenging for a number of reasons. Economic and regulatory factors impact the coal mining industry and forecasts of future coal production do not specifically predict changes in location of future coal production. With the potential environmental impacts from surface coal mining, prediction of the location of future activity would be valuable to decision makers. The goal of this study was to provide a method for predicting future surface coal mining extents under changing economic and regulatory forecasts through the year 2035. This was accomplished by integrating a spatial model with production demand forecasts to predict (1 km2) gridded cell size land cover change. Combining these two inputs was possible with a ratio which linked coal extraction quantities to a unit area extent. The result was a spatial distribution of probabilities allocated over forecasted demand for the Appalachian region including northern, central, southern, and eastern Illinois coal regions. The results can be used to better plan for land use alterations and potential cumulative impacts. PMID:26090883

Spatial Patterns in the Efficiency of the Biological Pump: What Controls Export Ratios at the Global Scale?

NASA Astrophysics Data System (ADS)

Moore, J. K.

2016-02-01

The efficiency of the biological pump is influenced by complex interactions between chemical, biological, and physical processes. The efficiency of export out of surface waters and down through the water column to the deep ocean has been linked to a number of factors including biota community composition, production of mineral ballast components, physical aggregation and disaggregation processes, and ocean oxygen concentrations. I will examine spatial patterns in the export ratio and the efficiency of the biological pump at the global scale using the Community Earth System Model (CESM). There are strong spatial variations in the export efficiency as simulated by the CESM, which are strongly correlated with new nutrient inputs to the euphotic zone and their impacts on phytoplankton community structure. I will compare CESM simulations that include dynamic, variable export ratios driven by the phytoplankton community structure, with simulations that impose a near-constant export ratio to examine the effects of export efficiency on nutrient and surface chlorophyll distributions. The model predicted export ratios will also be compared with recent satellite-based estimates.

Carbon Cycling of Lake Kivu (East Africa): Net Autotrophy in the Epilimnion and Emission of CO2 to the Atmosphere Sustained by Geogenic Inputs

PubMed Central

Borges, Alberto V.; Morana, Cédric; Bouillon, Steven; Servais, Pierre; Descy, Jean-Pierre; Darchambeau, François

2014-01-01

We report organic and inorganic carbon distributions and fluxes in a large (>2000 km2) oligotrophic, tropical lake (Lake Kivu, East Africa), acquired during four field surveys, that captured the seasonal variations (March 2007–mid rainy season, September 2007–late dry season, June 2008–early dry season, and April 2009–late rainy season). The partial pressure of CO2 (pCO2) in surface waters of the main basin of Lake Kivu showed modest spatial (coefficient of variation between 3% and 6%), and seasonal variations with an amplitude of 163 ppm (between 579±23 ppm on average in March 2007 and 742±28 ppm on average in September 2007). The most prominent spatial feature of the pCO2 distribution was the very high pCO2 values in Kabuno Bay (a small sub-basin with little connection to the main lake) ranging between 11213 ppm and 14213 ppm (between 18 and 26 times higher than in the main basin). Surface waters of the main basin of Lake Kivu were a net source of CO2 to the atmosphere at an average rate of 10.8 mmol m−2 d−1, which is lower than the global average reported for freshwater, saline, and volcanic lakes. In Kabuno Bay, the CO2 emission to the atmosphere was on average 500.7 mmol m−2 d−1 (∼46 times higher than in the main basin). Based on whole-lake mass balance of dissolved inorganic carbon (DIC) bulk concentrations and of its stable carbon isotope composition, we show that the epilimnion of Lake Kivu was net autotrophic. This is due to the modest river inputs of organic carbon owing to the small ratio of catchment area to lake surface area (2.15). The carbon budget implies that the CO2 emission to the atmosphere must be sustained by DIC inputs of geogenic origin from deep geothermal springs. PMID:25314144

Multi-perspective analysis and spatiotemporal mapping of air pollution monitoring data.

PubMed

Kolovos, Alexander; Skupin, André; Jerrett, Michael; Christakos, George

2010-09-01

Space-time data analysis and assimilation techniques in atmospheric sciences typically consider input from monitoring measurements. The input is often processed in a manner that acknowledges characteristics of the measurements (e.g., underlying patterns, fluctuation features) under conditions of uncertainty; it also leads to the derivation of secondary information that serves study-oriented goals, and provides input to space-time prediction techniques. We present a novel approach that blends a rigorous space-time prediction model (Bayesian maximum entropy, BME) with a cognitively informed visualization of high-dimensional data (spatialization). The combined BME and spatialization approach (BME-S) is used to study monthly averaged NO2 and mean annual SO4 measurements in California over the 15-year period 1988-2002. Using the original scattered measurements of these two pollutants BME generates spatiotemporal predictions on a regular grid across the state. Subsequently, the prediction network undergoes the spatialization transformation into a lower-dimensional geometric representation, aimed at revealing patterns and relationships that exist within the input data. The proposed BME-S provides a powerful spatiotemporal framework to study a variety of air pollution data sources.

Encoding of Spatio-Temporal Input Characteristics by a CA1 Pyramidal Neuron Model

PubMed Central

Pissadaki, Eleftheria Kyriaki; Sidiropoulou, Kyriaki; Reczko, Martin; Poirazi, Panayiota

2010-01-01

The in vivo activity of CA1 pyramidal neurons alternates between regular spiking and bursting, but how these changes affect information processing remains unclear. Using a detailed CA1 pyramidal neuron model, we investigate how timing and spatial arrangement variations in synaptic inputs to the distal and proximal dendritic layers influence the information content of model responses. We find that the temporal delay between activation of the two layers acts as a switch between excitability modes: short delays induce bursting while long delays decrease firing. For long delays, the average firing frequency of the model response discriminates spatially clustered from diffused inputs to the distal dendritic tree. For short delays, the onset latency and inter-spike-interval succession of model responses can accurately classify input signals as temporally close or distant and spatially clustered or diffused across different stimulation protocols. These findings suggest that a CA1 pyramidal neuron may be capable of encoding and transmitting presynaptic spatiotemporal information about the activity of the entorhinal cortex-hippocampal network to higher brain regions via the selective use of either a temporal or a rate code. PMID:21187899

Uncertainty propagation by using spectral methods: A practical application to a two-dimensional turbulence fluid model

NASA Astrophysics Data System (ADS)

Riva, Fabio; Milanese, Lucio; Ricci, Paolo

2017-10-01

To reduce the computational cost of the uncertainty propagation analysis, which is used to study the impact of input parameter variations on the results of a simulation, a general and simple to apply methodology based on decomposing the solution to the model equations in terms of Chebyshev polynomials is discussed. This methodology, based on the work by Scheffel [Am. J. Comput. Math. 2, 173-193 (2012)], approximates the model equation solution with a semi-analytic expression that depends explicitly on time, spatial coordinates, and input parameters. By employing a weighted residual method, a set of nonlinear algebraic equations for the coefficients appearing in the Chebyshev decomposition is then obtained. The methodology is applied to a two-dimensional Braginskii model used to simulate plasma turbulence in basic plasma physics experiments and in the scrape-off layer of tokamaks, in order to study the impact on the simulation results of the input parameter that describes the parallel losses. The uncertainty that characterizes the time-averaged density gradient lengths, time-averaged densities, and fluctuation density level are evaluated. A reasonable estimate of the uncertainty of these distributions can be obtained with a single reduced-cost simulation.

Joint transform correlators with spatially incoherent illumination

NASA Astrophysics Data System (ADS)

Bykovsky, Yuri A.; Karpiouk, Andrey B.; Markilov, Anatoly A.; Rodin, Vladislav G.; Starikov, Sergey N.

1997-03-01

Two variants of joint transform correlators with monochromatic spatially incoherent illumination are considered. The Fourier-holograms of the reference and recognized images are recorded simultaneously or apart in a time on the same spatial light modulator directly by monochromatic spatially incoherent light. To create the signal of mutual correlation of the images it is necessary to execute nonlinear transformation when the hologram is illuminated by coherent light. In the first scheme of the correlator this aim was achieved by using double pas of a restoring coherent wave through the hologram. In the second variant of the correlator the non-linearity of the characteristic of the spatial light modulator for hologram recording was used. Experimental schemes and results on processing teste images by both variants of joint transform correlators with monochromatic spatially incoherent illumination. The use of spatially incoherent light on the input of joint transform correlators permits to reduce the requirements to optical quality of elements, to reduce accuracy requirements on elements positioning and to expand a number of devices suitable to input images in correlators.

Mice lacking hippocampal left-right asymmetry show non-spatial learning deficits.

PubMed

Shimbo, Akihiro; Kosaki, Yutaka; Ito, Isao; Watanabe, Shigeru

2018-01-15

Left-right asymmetry is known to exist at several anatomical levels in the brain and recent studies have provided further evidence to show that it also exists at a molecular level in the hippocampal CA3-CA1 circuit. The distribution of N-methyl-d-aspartate (NMDA) receptor NR2B subunits in the apical and basal synapses of CA1 pyramidal neurons is asymmetrical if the input arrives from the left or right CA3 pyramidal neurons. In the present study, we examined the role of hippocampal asymmetry in cognitive function using β2-microglobulin knock-out (β2m KO) mice, which lack hippocampal asymmetry. We tested β2m KO mice in a series of spatial and non-spatial learning tasks and compared the performances of β2m KO and C57BL6/J wild-type (WT) mice. The β2m KO mice appeared normal in both spatial reference memory and spatial working memory tasks but they took more time than WT mice in learning the two non-spatial learning tasks (i.e., a differential reinforcement of lower rates of behavior (DRL) task and a straight runway task). The β2m KO mice also showed less precision in their response timing in the DRL task and showed weaker spontaneous recovery during extinction in the straight runway task. These results indicate that hippocampal asymmetry is important for certain characteristics of non-spatial learning. Copyright © 2017 Elsevier B.V. All rights reserved.

Variation in watershed nitrogen input and export across the Willamette River Basin

EPA Science Inventory

Nitrogen (N) export from watersheds is influenced by hydrology, land use/cover, and the timing and spatial arrangement of N inputs and removal within basins. We examined the relationship between N input and watershed N export for 25 monitoring stations between 1996 and 2006 with...

Comparison of climate envelope models developed using expert-selected variables versus statistical selection

USGS Publications Warehouse

Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romañach, Stephanie; Watling, James I.; Mazzotti, Frank J.

2017-01-01

Climate envelope models are widely used to describe potential future distribution of species under different climate change scenarios. It is broadly recognized that there are both strengths and limitations to using climate envelope models and that outcomes are sensitive to initial assumptions, inputs, and modeling methods Selection of predictor variables, a central step in modeling, is one of the areas where different techniques can yield varying results. Selection of climate variables to use as predictors is often done using statistical approaches that develop correlations between occurrences and climate data. These approaches have received criticism in that they rely on the statistical properties of the data rather than directly incorporating biological information about species responses to temperature and precipitation. We evaluated and compared models and prediction maps for 15 threatened or endangered species in Florida based on two variable selection techniques: expert opinion and a statistical method. We compared model performance between these two approaches for contemporary predictions, and the spatial correlation, spatial overlap and area predicted for contemporary and future climate predictions. In general, experts identified more variables as being important than the statistical method and there was low overlap in the variable sets (<40%) between the two methods Despite these differences in variable sets (expert versus statistical), models had high performance metrics (>0.9 for area under the curve (AUC) and >0.7 for true skill statistic (TSS). Spatial overlap, which compares the spatial configuration between maps constructed using the different variable selection techniques, was only moderate overall (about 60%), with a great deal of variability across species. Difference in spatial overlap was even greater under future climate projections, indicating additional divergence of model outputs from different variable selection techniques. Our work is in agreement with other studies which have found that for broad-scale species distribution modeling, using statistical methods of variable selection is a useful first step, especially when there is a need to model a large number of species or expert knowledge of the species is limited. Expert input can then be used to refine models that seem unrealistic or for species that experts believe are particularly sensitive to change. It also emphasizes the importance of using multiple models to reduce uncertainty and improve map outputs for conservation planning. Where outputs overlap or show the same direction of change there is greater certainty in the predictions. Areas of disagreement can be used for learning by asking why the models do not agree, and may highlight areas where additional on-the-ground data collection could improve the models.

Analysis of microstrip patch antennas using finite difference time domain method

NASA Astrophysics Data System (ADS)

Reineix, Alain; Jecko, Bernard

1989-11-01

The study of microstrip patch antennas is directly treated in the time domain, using a modified finite-difference time-domain (FDTD) method. Assuming an appropriate choice of excitation, the frequency dependence of the relevant parameters can readily be found using the Fourier transform of the transient current. The FDTD method allows a rigorous treatment of one or several dielectric interfaces. Different types of excitation can be taken into consideration (coaxial, microstrip lines, etc.). Plotting the spatial distribution of the current density gives information about the resonance modes. The usual frequency-depedent parameters (input impedance, radiation pattern) are given for several examples.

Assessment of space sensors for ocean pollution monitoring

NASA Technical Reports Server (NTRS)

Alvarado, U. R.; Tomiyasu, K.; Gulatsi, R. L.

1980-01-01

Several passive and active microwave, as well as passive optical remote sensors, applicable to the monitoring of oil spills and waste discharges at sea, are considered. The discussed types of measurements relate to: (1) spatial distribution and properties of the pollutant, and (2) oceanic parameters needed to predict the movement of the pollutants and their impact upon land. The sensors, operating from satellite platforms at 700-900 km altitudes, are found to be useful in mapping the spread of oil in major oil spills and in addition, can be effective in producing wind and ocean parameters as inputs to oil trajectory and dispersion models. These capabilities can be used in countermeasures.

Fast-axial turbulent flow CO2 laser output characteristics and scaling parameters

NASA Astrophysics Data System (ADS)

Dembovetsky, V. V.; Zavalova, Valentina Y.; Zavalov, Yuri N.

1996-04-01

The paper presents the experimental results of evaluating the output characteristics of TLA- 600 carbon-dioxide laser with axial turbulent gas flow, as well as the results of numerical modeling. The output characteristic and spatial distribution of laser beam were measured with regard to specific energy input, working mixture pressure, active media length and output mirror reflection. The paper presents the results of experimental and theoretical study and design decisions on a succession of similar type industrial carbon-dioxide lasers with fast-axial gas-flow and dc discharge excitation of active medium developed at NICTL RAN. As an illustration, characteristics of the TLA-600 laser are cited.

[Spatial-temporal distributions of dissolved inorganic carbon and its affecting factors in the Yellow River estuary].

PubMed

Guo, Xing-Sen; Lü, Ying-Chun; Sun, Zhi-Gao; Wang, Chuan-Yuan; Zhao, Quan-Sheng

2015-02-01

Estuary is an important area contributing to the global carbon cycle. In order to analyze the spatial-temporal distribution characteristics of the dissolved inorganic carbon (DIC) in the surface water of Yellow River estuary. Samples were collected in spring, summer, fall, winter of 2013, and discussed the correlation between the content of DIC and environmental factors. The results show that, the DIC concentration of the surface water in Yellow River estuary is in a range of 26.34-39.43 mg x L(-1), and the DIC concentration in freshwater side is higher than that in the sea side. In some areas where the salinity is less than 15 per thousand, the DIC concentration appears significant losses-the maximum loss is 20.46%. Seasonal distribution of performance in descending order is spring, fall, winter, summer. Through principal component analysis, it shows that water temperature, suspended solids, salinity and chlorophyll a are the main factors affecting the variation of the DIC concentration in surface water, their contribution rate is as high as 83% , and alkalinity, pH, dissolved organic carbon, dissolved oxygen and other factors can not be ignored. The loss of DIC in the low area is due to the calcium carbonate sedimentation. DIC presents a gradually increasing trend, which is mainly due to the effects of water retention time, temperature, outside input and environmental conditions.

An assessment of equity in the distribution of non-financial health care inputs across public primary health care facilities in Tanzania.

PubMed

Kuwawenaruwa, August; Borghi, Josephine; Remme, Michelle; Mtei, Gemini

2017-07-11

There is limited evidence on how health care inputs are distributed from the sub-national level down to health facilities and their potential influence on promoting health equity. To address this gap, this paper assesses equity in the distribution of health care inputs across public primary health facilities at the district level in Tanzania. This is a quantitative assessment of equity in the distribution of health care inputs (staff, drugs, medical supplies and equipment) from district to facility level. The study was carried out in three districts (Kinondoni, Singida Rural and Manyoni district) in Tanzania. These districts were selected because they were implementing primary care reforms. We administered 729 exit surveys with patients seeking out-patient care; and health facility surveys at 69 facilities in early 2014. A total of seventeen indices of input availability were constructed with the collected data. The distribution of inputs was considered in relation to (i) the wealth of patients accessing the facilities, which was taken as a proxy for the wealth of the population in the catchment area; and (ii) facility distance from the district headquarters. We assessed equity in the distribution of inputs through the use of equity ratios, concentration indices and curves. We found a significant pro-rich distribution of clinical staff and nurses per 1000 population. Facilities with the poorest patients (most remote facilities) have fewer staff per 1000 population than those with the least poor patients (least remote facilities): 0.6 staff per 1000 among the poorest, compared to 0.9 among the least poor; 0.7 staff per 1000 among the most remote facilities compared to 0.9 among the least remote. The negative concentration index for support staff suggests a pro-poor distribution of this cadre but the 45 degree dominated the concentration curve. The distribution of vaccines, antibiotics, anti-diarrhoeal, anti-malarials and medical supplies was approximately proportional (non dominance), whereas the distribution of oxytocics, anti-retroviral therapy (ART) and anti-hypertensive drugs was pro-rich, with the 45 degree line dominating the concentration curve for ART. This study has shown there are inequities in the distribution of health care inputs across public primary care facilities. This highlights the need to ensure a better coordinated and equitable distribution of inputs through regular monitoring of the availability of health care inputs and strengthening of reporting systems.

Beyond input-output computings: error-driven emergence with parallel non-distributed slime mold computer.

PubMed

Aono, Masashi; Gunji, Yukio-Pegio

2003-10-01

The emergence derived from errors is the key importance for both novel computing and novel usage of the computer. In this paper, we propose an implementable experimental plan for the biological computing so as to elicit the emergent property of complex systems. An individual plasmodium of the true slime mold Physarum polycephalum acts in the slime mold computer. Modifying the Elementary Cellular Automaton as it entails the global synchronization problem upon the parallel computing provides the NP-complete problem solved by the slime mold computer. The possibility to solve the problem by giving neither all possible results nor explicit prescription of solution-seeking is discussed. In slime mold computing, the distributivity in the local computing logic can change dynamically, and its parallel non-distributed computing cannot be reduced into the spatial addition of multiple serial computings. The computing system based on exhaustive absence of the super-system may produce, something more than filling the vacancy.

Using the Quantile Mapping to improve a weather generator

NASA Astrophysics Data System (ADS)

Chen, Y.; Themessl, M.; Gobiet, A.

2012-04-01

We developed a weather generator (WG) by using statistical and stochastic methods, among them are quantile mapping (QM), Monte-Carlo, auto-regression, empirical orthogonal function (EOF). One of the important steps in the WG is using QM, through which all the variables, no matter what distribution they originally are, are transformed into normal distributed variables. Therefore, the WG can work on normally distributed variables, which greatly facilitates the treatment of random numbers in the WG. Monte-Carlo and auto-regression are used to generate the realization; EOFs are employed for preserving spatial relationships and the relationships between different meteorological variables. We have established a complete model named WGQM (weather generator and quantile mapping), which can be applied flexibly to generate daily or hourly time series. For example, with 30-year daily (hourly) data and 100-year monthly (daily) data as input, the 100-year daily (hourly) data would be relatively reasonably produced. Some evaluation experiments with WGQM have been carried out in the area of Austria and the evaluation results will be presented.

Using agricultural practices information for multiscale environmental assessment of phosphorus risk

NASA Astrophysics Data System (ADS)

Matos Moreira, Mariana; Lemercier, Blandine; Michot, Didier; Dupas, Rémi; Gascuel-Odoux, Chantal

2015-04-01

Phosphorus (P) is an essential nutrient for plant growth. In intensively farmed areas, excessive applications of animal manure and mineral P fertilizers to soils have raised both economic and ecological concerns. P accumulation in agricultural soils leads to increased P losses to surface waterbodies contributing to eutrophication. Increasing soil P content over time in agricultural soils is often correlated with agricultural practices; in Brittany (NW France), an intensive livestock farming region, soil P content is well correlated with animal density (Lemercier et al.,2008). Thus, a better understanding of the factors controlling P distribution is required to enable environmental assessment of P risk. The aim of this study was to understand spatial distribution of extractable (Olsen method) and total P contents and its controlling factors at the catchment scale in order to predict P contents at regional scale (Brittany). Data on soil morphology, soil tests (including P status, particles size, organic carbon…) for 198 punctual positions, crops succession since 20 years, agricultural systems, field and animal manure management were obtained on a well-characterized catchment (ORE Agrhys, 10 km²). A multivariate analysis with mixed quantitative variables and factors and a digital soil mapping approach were performed to identify variables playing a significant role in soil total and extractable P contents and distribution. Spatial analysis was performed by means of the Cubist model, a decision tree-based algorithm. Different scenarios were assessed, considering various panels of predictive variables: soil data, terrain attributes derived from digital elevation model, gamma-ray spectrometry (from airborne geophysical survey) and agricultural practices information. In the research catchment, mean extractable and total P content were 140.0 ± 63.4 mg/kg and 2862.7 ± 773.0 mg/kg, respectively. Organic and mineral P inputs, P balance, soil pH, and Al contents were positively correlated with soil P contents. Also land use, crop rotation and livestock production system influenced P contents. The highest mean values of P were found in croplands and close to pig farms. The lowest mean values of P were found in pastures and nearby dairy farms. The spatial analysis showed that sand content, geophysical parameters and P input by organic fertilization were the most significant variables for the linear predictive model of extractable P contents. For total P, geophysical parameters and P balance had the highest importance for the respective linear predictive model. This study revealed that agricultural practices information plays a significant role in soil P distribution. Once controlling factors of P spatial distribution were identified, relationships could be extrapolated at regional scale using the National Soil Test Database providing information on extractable P content and available information on agricultural practices in order to improve predictions of total P content at regional scale. Lemercier B., Gaudin, L., Walter C., Aurousseau P., Arrouays D., Schvartz C., Saby N., Follain S., Abrassart J., 2008. Soil phosphorus monitoring at the regional level by means of a soil test database. Soil Use and Management, 24, 131-138.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Using Mental Transformation Strategies for Spatial Scaling: Evidence from a Discrimination Task

ERIC Educational Resources Information Center

Möhring, Wenke; Newcombe, Nora S.; Frick, Andrea

2016-01-01

Spatial scaling, or an understanding of how distances in different-sized spaces relate to each other, is fundamental for many spatial tasks and relevant for success in numerous professions. Previous research has suggested that adults use mental transformation strategies to mentally scale spatial input, as indicated by linear increases in response…

Spatial and temporal features of superordinate semantic processing studied with fMRI and EEG.

PubMed

Costanzo, Michelle E; McArdle, Joseph J; Swett, Bruce; Nechaev, Vladimir; Kemeny, Stefan; Xu, Jiang; Braun, Allen R

2013-01-01

The relationships between the anatomical representation of semantic knowledge in the human brain and the timing of neurophysiological mechanisms involved in manipulating such information remain unclear. This is the case for superordinate semantic categorization-the extraction of general features shared by broad classes of exemplars (e.g., living vs. non-living semantic categories). We proposed that, because of the abstract nature of this information, input from diverse input modalities (visual or auditory, lexical or non-lexical) should converge and be processed in the same regions of the brain, at similar time scales during superordinate categorization-specifically in a network of heteromodal regions, and late in the course of the categorization process. In order to test this hypothesis, we utilized electroencephalography and event related potentials (EEG/ERP) with functional magnetic resonance imaging (fMRI) to characterize subjects' responses as they made superordinate categorical decisions (living vs. non-living) about objects presented as visual pictures or auditory words. Our results reveal that, consistent with our hypothesis, during the course of superordinate categorization, information provided by these diverse inputs appears to converge in both time and space: fMRI showed that heteromodal areas of the parietal and temporal cortices are active during categorization of both classes of stimuli. The ERP results suggest that superordinate categorization is reflected as a late positive component (LPC) with a parietal distribution and long latencies for both stimulus types. Within the areas and times in which modality independent responses were identified, some differences between living and non-living categories were observed, with a more widespread spatial extent and longer latency responses for categorization of non-living items.

Spatial and temporal features of superordinate semantic processing studied with fMRI and EEG

PubMed Central

Costanzo, Michelle E.; McArdle, Joseph J.; Swett, Bruce; Nechaev, Vladimir; Kemeny, Stefan; Xu, Jiang; Braun, Allen R.

2013-01-01

The relationships between the anatomical representation of semantic knowledge in the human brain and the timing of neurophysiological mechanisms involved in manipulating such information remain unclear. This is the case for superordinate semantic categorization—the extraction of general features shared by broad classes of exemplars (e.g., living vs. non-living semantic categories). We proposed that, because of the abstract nature of this information, input from diverse input modalities (visual or auditory, lexical or non-lexical) should converge and be processed in the same regions of the brain, at similar time scales during superordinate categorization—specifically in a network of heteromodal regions, and late in the course of the categorization process. In order to test this hypothesis, we utilized electroencephalography and event related potentials (EEG/ERP) with functional magnetic resonance imaging (fMRI) to characterize subjects' responses as they made superordinate categorical decisions (living vs. non-living) about objects presented as visual pictures or auditory words. Our results reveal that, consistent with our hypothesis, during the course of superordinate categorization, information provided by these diverse inputs appears to converge in both time and space: fMRI showed that heteromodal areas of the parietal and temporal cortices are active during categorization of both classes of stimuli. The ERP results suggest that superordinate categorization is reflected as a late positive component (LPC) with a parietal distribution and long latencies for both stimulus types. Within the areas and times in which modality independent responses were identified, some differences between living and non-living categories were observed, with a more widespread spatial extent and longer latency responses for categorization of non-living items. PMID:23847490

An analysis of cropland mask choice and ancillary data for annual corn yield forecasting using MODIS data

NASA Astrophysics Data System (ADS)

Shao, Yang; Campbell, James B.; Taff, Gregory N.; Zheng, Baojuan

2015-06-01

The Midwestern United States is one of the world's most important corn-producing regions. Monitoring and forecasting of corn yields in this intensive agricultural region are important activities to support food security, commodity markets, bioenergy industries, and formation of national policies. This study aims to develop forecasting models that have the capability to provide mid-season prediction of county-level corn yields for the entire Midwestern United States. We used multi-temporal MODIS NDVI (normalized difference vegetation index) 16-day composite data as the primary input, with digital elevation model (DEM) and parameter-elevation relationships on independent slopes model (PRISM) climate data as additional inputs. The DEM and PRISM data, along with three types of cropland masks were tested and compared to evaluate their impacts on model predictive accuracy. Our results suggested that the use of general cropland masks (e.g., summer crop or cultivated crops) generated similar results compared with use of an annual corn-specific mask. Leave-one-year-out cross-validation resulted in an average R2 of 0.75 and RMSE value of 1.10 t/ha. Using a DEM as an additional model input slightly improved performance, while inclusion of PRISM climate data appeared not to be important for our regional corn-yield model. Furthermore, our model has potential for real-time/early prediction. Our corn yield esitmates are available as early as late July, which is an improvement upon previous corn-yield prediction models. In addition to annual corn yield forecasting, we examined model uncertainties through spatial and temporal analysis of the model's predictive error distribution. The magnitude of predictive error (by county) appears to be associated with the spatial patterns of corn fields in the study area.

Anthropogenic activities have contributed moderately to increased inputs of organic materials in marginal seas off China.

PubMed

Liu, Liang-Ying; Wei, Gao-Ling; Wang, Ji-Zhong; Guan, Yu-Feng; Wong, Charles S; Wu, Feng-Chang; Zeng, Eddy Y

2013-10-15

Sediment has been recognized as a gigantic sink of organic materials and therefore can record temporal input trends. To examine the impact of anthropogenic activities on the marginal seas off China, sediment cores were collected from the Yellow Sea, the inner shelf of the East China Sea (ECS), and the South China Sea (SCS) to investigate the sources and spatial and temporal variations of organic materials, i.e., total organic carbon (TOC) and aliphatic hydrocarbons. The concentration ranges of TOC were 0.5-1.29, 0.63-0.83, and 0.33-0.85%, while those of Σn-C14-35 (sum of n-alkanes with carbon numbers of 14-35) were 0.08-1.5, 0.13-1.97, and 0.35-0.96 μg/g dry weight in sediment cores from the Yellow Sea, ECS inner shelf, and the SCS, respectively. Terrestrial higher plants were an important source of aliphatic hydrocarbons in marine sediments off China. The spatial distribution of Σn-C14-35 concentrations and source diagnostic ratios suggested a greater load of terrestrial organic materials in the Yellow Sea than in the ECS and SCS. Temporally, TOC and Σn-C14-35 concentrations increased with time and peaked at either the surface or immediate subsurface layers. This increase was probably reflective of elevated inputs of organic materials to marginal seas off China in recent years, and attributed partly to the impacts of intensified anthropogenic activities in mainland China. Source diagnostics also suggested that aliphatic hydrocarbons were mainly derived from biogenic sources, with a minority in surface sediment layers from petroleum sources, consistent with the above-mentioned postulation.

A reconfigurable NAND/NOR genetic logic gate

PubMed Central

2012-01-01

Background Engineering genetic Boolean logic circuits is a major research theme of synthetic biology. By altering or introducing connections between genetic components, novel regulatory networks are built in order to mimic the behaviour of electronic devices such as logic gates. While electronics is a highly standardized science, genetic logic is still in its infancy, with few agreed standards. In this paper we focus on the interpretation of logical values in terms of molecular concentrations. Results We describe the results of computational investigations of a novel circuit that is able to trigger specific differential responses depending on the input standard used. The circuit can therefore be dynamically reconfigured (without modification) to serve as both a NAND/NOR logic gate. This multi-functional behaviour is achieved by a) varying the meanings of inputs, and b) using branch predictions (as in computer science) to display a constrained output. A thorough computational study is performed, which provides valuable insights for the future laboratory validation. The simulations focus on both single-cell and population behaviours. The latter give particular insights into the spatial behaviour of our engineered cells on a surface with a non-homogeneous distribution of inputs. Conclusions We present a dynamically-reconfigurable NAND/NOR genetic logic circuit that can be switched between modes of operation via a simple shift in input signal concentration. The circuit addresses important issues in genetic logic that will have significance for more complex synthetic biology applications. PMID:22989145

A reconfigurable NAND/NOR genetic logic gate.

PubMed

Goñi-Moreno, Angel; Amos, Martyn

2012-09-18

Engineering genetic Boolean logic circuits is a major research theme of synthetic biology. By altering or introducing connections between genetic components, novel regulatory networks are built in order to mimic the behaviour of electronic devices such as logic gates. While electronics is a highly standardized science, genetic logic is still in its infancy, with few agreed standards. In this paper we focus on the interpretation of logical values in terms of molecular concentrations. We describe the results of computational investigations of a novel circuit that is able to trigger specific differential responses depending on the input standard used. The circuit can therefore be dynamically reconfigured (without modification) to serve as both a NAND/NOR logic gate. This multi-functional behaviour is achieved by a) varying the meanings of inputs, and b) using branch predictions (as in computer science) to display a constrained output. A thorough computational study is performed, which provides valuable insights for the future laboratory validation. The simulations focus on both single-cell and population behaviours. The latter give particular insights into the spatial behaviour of our engineered cells on a surface with a non-homogeneous distribution of inputs. We present a dynamically-reconfigurable NAND/NOR genetic logic circuit that can be switched between modes of operation via a simple shift in input signal concentration. The circuit addresses important issues in genetic logic that will have significance for more complex synthetic biology applications.

Distributed optical fiber vibration sensor based on Sagnac interference in conjunction with OTDR.

PubMed

Pan, Chao; Liu, Xiaorui; Zhu, Hui; Shan, Xuekang; Sun, Xiaohan

2017-08-21

A real-time distributed optical fiber vibration sensing prototype based on the Sagnac interference in conjunction with the optical time domain reflectometry (OTDR) was developed. The sensing mechanism for single- and multi-points vibrations along the sensing fiber was analyzed theoretically and demonstrated experimentally. The experimental results show excellent agreement with the theoretical models. It is verified that single-point vibration induces a significantly abrupt and monotonous power change in the corresponding position of OTDR trace. As to multi-points vibrations, the detection of the following vibration is influenced by all previous ones. However, if the distance between the adjacent two vibrations is larger than half of the input optical pulse width, abrupt power changes induced by them are separate and still monotonous. A time-shifting differential module was developed and carried out to convert vibration-induced power changes to pulses. Consequently, vibrations can be located accurately by measuring peak or valley positions of the vibration-induced pulses. It is demonstrated that when the width and peak power of input optical pulse are set to 1 μs and 35 mW, respectively, the position error is less than ± 0.5 m in a sensing range of more than 16 km, with the spatial resolution of ~110 m.

The spatial distribution, accumulation and potential source of seldom monitored trace elements in sediments of Three Gorges Reservoir, China

PubMed Central

Han, Lanfang; Gao, Bo; Zhou, Huaidong; Xu, Dongyu; Wei, Xin; Gao, Li

2015-01-01

The alteration of hydrologic condition of Three Gorges Reservoir (TGR) after impoundment has caused numerous environmental changes. This study investigated the distribution, accumulation and potential sources of the seldom monitored trace elements (SMTEs) in sediments from three tributaries (ZY, MX and CT) and one mainstream (CJ) in TGR during different seasons. The average contents of most SMTEs excluding Sb in the winter were similar to that in the summer. For Sb, its average concentrations in the summer and winter were roughly six and three times higher than its background value, respectively. Contamination factor (CF) and geoaccumulation index (Igeo) demonstrated that most of the sediments were obviously contaminated by Sb. The enrichment factors (EF) of Ga and Sb were higher than 2.0, revealing the possible anthropogenic inputs; However, the EFs of other SMTEs were lower than 1.5, indicating the natural inputs. Correlation and principal component analysis suggested the most SMTEs were positively correlated with major elements (Cr, Mn, Cu, Zn, As, Cd and Pb) and clay contents, which implies that SMTEs had the same sources with these major metals, and the fine particles might be a major carrier for transporting SMTEs from the rivers to the TGR. PMID:26538153

Absorption and fluorescence characteristics of chromophoric dissolved organic matter in the Yangtze Estuary.

PubMed

Sun, Qiyuan; Wang, Chao; Wang, Peifang; Hou, Jun; Ao, Yanhui

2014-03-01

The Yangtze Estuary is heavily influenced by coast-continent geochemical processes and anthropogenic activity; thus, the source and distribution of chromophoric dissolved organic matter (CDOM) in the estuary are strongly impacted by these processes. Here, a series of samples were collected from across the Yangtze Estuary to investigate the source and spatial dynamics of CDOM and its components throughout the system. Three indices (a(355), spectral slope, and fluorescence) were then calculated and interpreted. The results indicated that the distribution of CDOM was dominated by allochthonous input, conservative mixing, and phase transfer. The contribution of biogenic CDOM to total CDOM increased with salinity, and three individual CDOM components were identified upon fluorescence excitation emission matrix spectroscopy and parallel factor analysis of the water samples: C1, corresponding to humic substance-like CDOM, C2, corresponding to tryptophan-like CDOM, and C3, corresponding to tyrosine-like CDOM. C1 primarily originated from a terrestrial source, C2 had widespread origins, none of which played a dominant role, and C3 mainly originated from allochthonous input in the medium salinity area. Unexpectedly, no marine humic-like component was found in the surface water of the Yangtze Estuary, possibly because turbidity decreased the depth of sunlight penetration, limiting production of this component.

Hanford Site Composite Analysis Technical Approach Description: Groundwater

DOE Office of Scientific and Technical Information (OSTI.GOV)

Budge, T. J.

The groundwater facet of the revised CA is responsible for generating predicted contaminant concentration values over the entire analysis spatial and temporal domain. These estimates will be used as part of the groundwater pathway dose calculation facet to estimate dose for exposure scenarios. Based on the analysis of existing models and available information, the P2R Model was selected as the numerical simulator to provide these estimates over the 10,000-year temporal domain of the CA. The P2R Model will use inputs from initial plume distributions, updated for a start date of 1/1/2017, and inputs from the vadose zone facet, created bymore » a tool under development as part of the ICF, to produce estimates of hydraulic head, transmissivity, and contaminant concentration over time. A recommendation of acquiring 12 computer processors and 2 TB of hard drive space is made to ensure that the work can be completed within the anticipated schedule of the revised CA.« less

A Hybrid dasymetric and machine learning approach to high-resolution residential electricity consumption modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morton, April M; Nagle, Nicholas N; Piburn, Jesse O

As urban areas continue to grow and evolve in a world of increasing environmental awareness, the need for detailed information regarding residential energy consumption patterns has become increasingly important. Though current modeling efforts mark significant progress in the effort to better understand the spatial distribution of energy consumption, the majority of techniques are highly dependent on region-specific data sources and often require building- or dwelling-level details that are not publicly available for many regions in the United States. Furthermore, many existing methods do not account for errors in input data sources and may not accurately reflect inherent uncertainties in modelmore » outputs. We propose an alternative and more general hybrid approach to high-resolution residential electricity consumption modeling by merging a dasymetric model with a complementary machine learning algorithm. The method s flexible data requirement and statistical framework ensure that the model both is applicable to a wide range of regions and considers errors in input data sources.« less

GEM-CEDAR Study of Ionospheric Energy Input and Joule Dissipation

NASA Technical Reports Server (NTRS)

Rastaetter, Lutz; Kuznetsova, Maria M.; Shim, Jasoon

2012-01-01

We are studying ionospheric model performance for six events selected for the GEM-CEDAR modeling challenge. DMSP measurements of electric and magnetic fields are converted into Poynting Flux values that estimate the energy input into the ionosphere. Models generate rates of ionospheric Joule dissipation that are compared to the energy influx. Models include the ionosphere models CTIPe and Weimer and the ionospheric electrodynamic outputs of global magnetosphere models SWMF, LFM, and OpenGGCM. This study evaluates the model performance in terms of overall balance between energy influx and dissipation and tests the assumption that Joule dissipation occurs locally where electromagnetic energy flux enters the ionosphere. We present results in terms of skill scores now commonly used in metrics and validation studies and we can measure the agreement in terms of temporal and spatial distribution of dissipation (i.e, location of auroral activity) along passes of the DMSP satellite with the passes' proximity to the magnetic pole and solar wind activity level.

Variability and distribution of spatial evapotranspiration in semi arid Inner Mongolian grasslands from 2002 to 2011.

PubMed

Schaffrath, David; Bernhofer, Christian

2013-01-01

Grasslands in Inner Mongolia are important for livestock farming while ecosystem functioning and water consumption are dominated by evapotranspiration (ET). In this paper we studied the spatiotemporal distribution and variability of ET and its components in Inner Mongolian grasslands over a period of 10 years, from 2002 to 2011. ET was modelled pixel-wise for more than 3000 1 km(2) pixels with the physically-based hydrological model BROOK90. The model was parameterised from eddy-covariance measurements and daily input was generated from MODIS leaf area index and surface temperatures. Modelled ET was also compared with the ET provided by the MODIS MOD16 ET data. The study showed ET to be highly variable in both time and space in Inner Mongolian grasslands. The mean coefficient of variation of 8-day ET in the study area varied between 25% and 40% and was up to 75% for individual pixels indicating a high innerannual variability of ET. Generally, ET equals or exceeds P during the vegetation period, but high precipitation in 2003 clearly exceeded ET in this year indicating a recharge of soil moisture and groundwater. Despite the high interannual and innerannual variations of spatial ET, the study also showed the existence of an intrinsic long-term spatial pattern of ET distribution, which can be explained partly by altitude and longitude (R(2) = 0.49). In conclusion, the results of this research suggest the development of dynamic and productive rangeland management systems according to the inherent variability of rainfall, productivity and ET in order to restore and protect Inner Mongolian grasslands.

A hydroclimatological approach to predicting regional landslide probability using Landlab

NASA Astrophysics Data System (ADS)

Strauch, Ronda; Istanbulluoglu, Erkan; Nudurupati, Sai Siddhartha; Bandaragoda, Christina; Gasparini, Nicole M.; Tucker, Gregory E.

2018-02-01

We develop a hydroclimatological approach to the modeling of regional shallow landslide initiation that integrates spatial and temporal dimensions of parameter uncertainty to estimate an annual probability of landslide initiation based on Monte Carlo simulations. The physically based model couples the infinite-slope stability model with a steady-state subsurface flow representation and operates in a digital elevation model. Spatially distributed gridded data for soil properties and vegetation classification are used for parameter estimation of probability distributions that characterize model input uncertainty. Hydrologic forcing to the model is through annual maximum daily recharge to subsurface flow obtained from a macroscale hydrologic model. We demonstrate the model in a steep mountainous region in northern Washington, USA, over 2700 km2. The influence of soil depth on the probability of landslide initiation is investigated through comparisons among model output produced using three different soil depth scenarios reflecting the uncertainty of soil depth and its potential long-term variability. We found elevation-dependent patterns in probability of landslide initiation that showed the stabilizing effects of forests at low elevations, an increased landslide probability with forest decline at mid-elevations (1400 to 2400 m), and soil limitation and steep topographic controls at high alpine elevations and in post-glacial landscapes. These dominant controls manifest themselves in a bimodal distribution of spatial annual landslide probability. Model testing with limited observations revealed similarly moderate model confidence for the three hazard maps, suggesting suitable use as relative hazard products. The model is available as a component in Landlab, an open-source, Python-based landscape earth systems modeling environment, and is designed to be easily reproduced utilizing HydroShare cyberinfrastructure.

Geostatistical interpolation of available copper in orchard soil as influenced by planting duration.

PubMed

Fu, Chuancheng; Zhang, Haibo; Tu, Chen; Li, Lianzhen; Luo, Yongming

2018-01-01

Mapping the spatial distribution of available copper (A-Cu) in orchard soils is important in agriculture and environmental management. However, data on the distribution of A-Cu in orchard soils is usually highly variable and severely skewed due to the continuous input of fungicides. In this study, ordinary kriging combined with planting duration (OK_PD) is proposed as a method for improving the interpolation of soil A-Cu. Four normal distribution transformation methods, namely, the Box-Cox, Johnson, rank order, and normal score methods, were utilized prior to interpolation. A total of 317 soil samples were collected in the orchards of the Northeast Jiaodong Peninsula. Moreover, 1472 orchards were investigated to obtain a map of planting duration using Voronoi tessellations. The soil A-Cu content ranged from 0.09 to 106.05 with a mean of 18.10 mg kg -1 , reflecting the high availability of Cu in the soils. Soil A-Cu concentrations exhibited a moderate spatial dependency and increased significantly with increasing planting duration. All the normal transformation methods successfully decreased the skewness and kurtosis of the soil A-Cu and the associated residuals, and also computed more robust variograms. OK_PD could generate better spatial prediction accuracy than ordinary kriging (OK) for all transformation methods tested, and it also provided a more detailed map of soil A-Cu. Normal score transformation produced satisfactory accuracy and showed an advantage in ameliorating smoothing effect derived from the interpolation methods. Thus, normal score transformation prior to kriging combined with planting duration (NSOK_PD) is recommended for the interpolation of soil A-Cu in this area.

Land Cover Change Detection using Neural Network and Grid Cells Techniques

NASA Astrophysics Data System (ADS)

Bagan, H.; Li, Z.; Tangud, T.; Yamagata, Y.

2017-12-01

In recent years, many advanced neural network methods have been applied in land cover classification, each of which has both strengths and limitations. In which, the self-organizing map (SOM) neural network method have been used to solve remote sensing data classification problems and have shown potential for efficient classification of remote sensing data. In SOM, both the distribution and the topology of features of the input layer are identified by using an unsupervised, competitive, neighborhood learning method. The high-dimensional data are then projected onto a low-dimensional map (competitive layer), usually as a two-dimensional map. The neurons (nodes) in the competitive layer are arranged by topological order in the input space. Spatio-temporal analyses of land cover change based on grid cells have demonstrated that gridded data are useful for obtaining spatial and temporal information about areas that are smaller than municipal scale and are uniform in size. Analysis based on grid cells has many advantages: grid cells all have the same size allowing for easy comparison; grids integrate easily with other scientific data; grids are stable over time and thus facilitate the modelling and analysis of very large multivariate spatial data sets. This study chose time-series MODIS and Landsat images as data sources, applied SOM neural network method to identify the land utilization in Inner Mongolia Autonomous Region of China. Then the results were integrated into grid cell to get the dynamic change maps. Land cover change using MODIS data in Inner Mongolia showed that urban area increased more than fivefold in recent 15 years, along with the growth of mining area. In terms of geographical distribution, the most obvious place of urban expansion is Ordos in southwest Inner Mongolia. The results using Landsat images from 1986 to 2014 in northeastern part of the Inner Mongolia show degradation in grassland from 1986 to 2014. Grid-cell-based spatial correlation analysis also confirmed a strong negative correlation between grassland and barren land, indicating that grassland degradation in this region is due to the urbanization and coal mining activities over the past three decades.

An Eye Tracking Study on the Perception and Comprehension of Unimodal and Bimodal Linguistic Inputs by Deaf Adolescents

PubMed Central

Mastrantuono, Eliana; Saldaña, David; Rodríguez-Ortiz, Isabel R.

2017-01-01

An eye tracking experiment explored the gaze behavior of deaf individuals when perceiving language in spoken and sign language only, and in sign-supported speech (SSS). Participants were deaf (n = 25) and hearing (n = 25) Spanish adolescents. Deaf students were prelingually profoundly deaf individuals with cochlear implants (CIs) used by age 5 or earlier, or prelingually profoundly deaf native signers with deaf parents. The effectiveness of SSS has rarely been tested within the same group of children for discourse-level comprehension. Here, video-recorded texts, including spatial descriptions, were alternately transmitted in spoken language, sign language and SSS. The capacity of these communicative systems to equalize comprehension in deaf participants with that of spoken language in hearing participants was tested. Within-group analyses of deaf participants tested if the bimodal linguistic input of SSS favored discourse comprehension compared to unimodal languages. Deaf participants with CIs achieved equal comprehension to hearing controls in all communicative systems while deaf native signers with no CIs achieved equal comprehension to hearing participants if tested in their native sign language. Comprehension of SSS was not increased compared to spoken language, even when spatial information was communicated. Eye movements of deaf and hearing participants were tracked and data of dwell times spent looking at the face or body area of the sign model were analyzed. Within-group analyses focused on differences between native and non-native signers. Dwell times of hearing participants were equally distributed across upper and lower areas of the face while deaf participants mainly looked at the mouth area; this could enable information to be obtained from mouthings in sign language and from lip-reading in SSS and spoken language. Few fixations were directed toward the signs, although these were more frequent when spatial language was transmitted. Both native and non-native signers looked mainly at the face when perceiving sign language, although non-native signers looked significantly more at the body than native signers. This distribution of gaze fixations suggested that deaf individuals – particularly native signers – mainly perceived signs through peripheral vision. PMID:28680416

An Eye Tracking Study on the Perception and Comprehension of Unimodal and Bimodal Linguistic Inputs by Deaf Adolescents.

PubMed

Mastrantuono, Eliana; Saldaña, David; Rodríguez-Ortiz, Isabel R

2017-01-01

An eye tracking experiment explored the gaze behavior of deaf individuals when perceiving language in spoken and sign language only, and in sign-supported speech (SSS). Participants were deaf ( n = 25) and hearing ( n = 25) Spanish adolescents. Deaf students were prelingually profoundly deaf individuals with cochlear implants (CIs) used by age 5 or earlier, or prelingually profoundly deaf native signers with deaf parents. The effectiveness of SSS has rarely been tested within the same group of children for discourse-level comprehension. Here, video-recorded texts, including spatial descriptions, were alternately transmitted in spoken language, sign language and SSS. The capacity of these communicative systems to equalize comprehension in deaf participants with that of spoken language in hearing participants was tested. Within-group analyses of deaf participants tested if the bimodal linguistic input of SSS favored discourse comprehension compared to unimodal languages. Deaf participants with CIs achieved equal comprehension to hearing controls in all communicative systems while deaf native signers with no CIs achieved equal comprehension to hearing participants if tested in their native sign language. Comprehension of SSS was not increased compared to spoken language, even when spatial information was communicated. Eye movements of deaf and hearing participants were tracked and data of dwell times spent looking at the face or body area of the sign model were analyzed. Within-group analyses focused on differences between native and non-native signers. Dwell times of hearing participants were equally distributed across upper and lower areas of the face while deaf participants mainly looked at the mouth area; this could enable information to be obtained from mouthings in sign language and from lip-reading in SSS and spoken language. Few fixations were directed toward the signs, although these were more frequent when spatial language was transmitted. Both native and non-native signers looked mainly at the face when perceiving sign language, although non-native signers looked significantly more at the body than native signers. This distribution of gaze fixations suggested that deaf individuals - particularly native signers - mainly perceived signs through peripheral vision.

LPJ-GUESS Simulated North America Vegetation for 21-0 ka Using the TraCE-21ka Climate Simulation

NASA Astrophysics Data System (ADS)

Shafer, S. L.; Bartlein, P. J.

2016-12-01

Transient climate simulations that span multiple millennia (e.g., TraCE-21ka) have become more common as computing power has increased, allowing climate models to complete long simulations in relatively short periods of time (i.e., months). These climate simulations provide information on the potential rate, variability, and spatial expression of past climate changes. They also can be used as input data for other environmental models to simulate transient changes for different components of paleoenvironmental systems, such as vegetation. Long, transient paleovegetation simulations can provide information on a range of ecological processes, describe the spatial and temporal patterns of changes in species distributions, and identify the potential locations of past species refugia. Paleovegetation simulations also can be used to fill in spatial and temporal gaps in observed paleovegetation data (e.g., pollen records from lake sediments) and to test hypotheses of past vegetation change. We used the TraCE-21ka transient climate simulation for 21-0 ka from CCSM3, a coupled atmosphere-ocean general circulation model. The TraCE-21ka simulated temperature, precipitation, and cloud data were regridded onto a 10-minute grid of North America. These regridded climate data, along with soil data and atmospheric carbon dioxide concentrations, were used as input to LPJ-GUESS, a general ecosystem model, to simulate North America vegetation from 21-0 ka. LPJ-GUESS simulates many of the processes controlling the distribution of vegetation (e.g., competition), although some important processes (e.g., dispersal) are not simulated. We evaluate the LPJ-GUESS-simulated vegetation (in the form of plant functional types and biomes) for key time periods and compare the simulated vegetation with observed paleovegetation data, such as data archived in the Neotoma Paleoecology Database. In general, vegetation simulated by LPJ-GUESS reproduces the major North America vegetation patterns (e.g., forest, grassland) with regional areas of disagreement between simulated and observed vegetation. We describe the regions and time periods with the greatest data-model agreement and disagreement, and discuss some of the strengths and weaknesses of both the simulated climate and simulated vegetation data.

The Role of Extra-Vestibular Inputs in Maintaining Spatial Orientation in Military Vehicles

DTIC Science & Technology

2003-02-01

flow contribute to spatial orientation. Disordered regulation of any of these factors can be identified in land based tests and allows us to study pre...adaptation disorders . 1,2 The sensory conflict theory of motion sickness states that motion sickness arises when one or several inputs from the body’s sensory...several episodes of severe motion sickness during an operational military assignment (usually aboard ship), but demonstrate no balance disorder or ear

Development a computer codes to couple PWR-GALE output and PC-CREAM input

NASA Astrophysics Data System (ADS)

Kuntjoro, S.; Budi Setiawan, M.; Nursinta Adi, W.; Deswandri; Sunaryo, G. R.

2018-02-01

Radionuclide dispersion analysis is part of an important reactor safety analysis. From the analysis it can be obtained the amount of doses received by radiation workers and communities around nuclear reactor. The radionuclide dispersion analysis under normal operating conditions is carried out using the PC-CREAM code, and it requires input data such as source term and population distribution. Input data is derived from the output of another program that is PWR-GALE and written Population Distribution data in certain format. Compiling inputs for PC-CREAM programs manually requires high accuracy, as it involves large amounts of data in certain formats and often errors in compiling inputs manually. To minimize errors in input generation, than it is make coupling program for PWR-GALE and PC-CREAM programs and a program for writing population distribution according to the PC-CREAM input format. This work was conducted to create the coupling programming between PWR-GALE output and PC-CREAM input and programming to written population data in the required formats. Programming is done by using Python programming language which has advantages of multiplatform, object-oriented and interactive. The result of this work is software for coupling data of source term and written population distribution data. So that input to PC-CREAM program can be done easily and avoid formatting errors. Programming sourceterm coupling program PWR-GALE and PC-CREAM is completed, so that the creation of PC-CREAM inputs in souceterm and distribution data can be done easily and according to the desired format.

Computer Generated Holography with Intensity-Graded Patterns

PubMed Central

Conti, Rossella; Assayag, Osnath; de Sars, Vincent; Guillon, Marc; Emiliani, Valentina

2016-01-01

Computer Generated Holography achieves patterned illumination at the sample plane through phase modulation of the laser beam at the objective back aperture. This is obtained by using liquid crystal-based spatial light modulators (LC-SLMs), which modulate the spatial phase of the incident laser beam. A variety of algorithms is employed to calculate the phase modulation masks addressed to the LC-SLM. These algorithms range from simple gratings-and-lenses to generate multiple diffraction-limited spots, to iterative Fourier-transform algorithms capable of generating arbitrary illumination shapes perfectly tailored on the base of the target contour. Applications for holographic light patterning include multi-trap optical tweezers, patterned voltage imaging and optical control of neuronal excitation using uncaging or optogenetics. These past implementations of computer generated holography used binary input profile to generate binary light distribution at the sample plane. Here we demonstrate that using graded input sources, enables generating intensity graded light patterns and extend the range of application of holographic light illumination. At first, we use intensity-graded holograms to compensate for LC-SLM position dependent diffraction efficiency or sample fluorescence inhomogeneity. Finally we show that intensity-graded holography can be used to equalize photo evoked currents from cells expressing different levels of chanelrhodopsin2 (ChR2), one of the most commonly used optogenetics light gated channels, taking into account the non-linear dependence of channel opening on incident light. PMID:27799896

Review of modelling air pollution from traffic at street-level - The state of the science.

PubMed

Forehead, H; Huynh, N

2018-06-13

Traffic emissions are a complex and variable cocktail of toxic chemicals. They are the major source of atmospheric pollution in the parts of cities where people live, commute and work. Reducing exposure requires information about the distribution and nature of emissions. Spatially and temporally detailed data are required, because both the rate of production and the composition of emissions vary significantly with time of day and with local changes in wind, traffic composition and flow. Increasing computer processing power means that models can accept highly detailed inputs of fleet, fuels and road networks. The state of the science models can simulate the behaviour and emissions of all the individual vehicles on a road network, with resolution of a second and tens of metres. The chemistry of the simulated emissions is also highly resolved, due to consideration of multiple engine processes, fuel evaporation and tyre wear. Good results can be achieved with both commercially available and open source models. The extent of a simulation is usually limited by processing capacity; the accuracy by the quality of traffic data. Recent studies have generated real time, detailed emissions data by using inputs from novel traffic sensing technologies and data from intelligent traffic systems (ITS). Increasingly, detailed pollution data is being combined with spatially resolved demographic or epidemiological data for targeted risk analyses. Copyright © 2018 Elsevier Ltd. All rights reserved.

Analysis of the precipitation and streamflow extremes in Northern Italy using high resolution reanalysis dataset Express-Hydro

NASA Astrophysics Data System (ADS)

Silvestro, Francesco; Parodi, Antonio; Campo, Lorenzo

2017-04-01

The characterization of the hydrometeorological extremes, both in terms of rainfall and streamflow, in a given region plays a key role in the environmental monitoring provided by the flood alert services. In last years meteorological simulations (both near real-time and historical reanalysis) were available at increasing spatial and temporal resolutions, making possible long-period hydrological reanalysis in which the meteo dataset is used as input in distributed hydrological models. In this work, a very high resolution meteorological reanalysis dataset, namely Express-Hydro (CIMA, ISAC-CNR, GAUSS Special Project PR45DE), was employed as input in the hydrological model Continuum in order to produce long time series of streamflows in the Liguria territory, located in the Northern part of Italy. The original dataset covers the whole Europe territory in the 1979-2008 period, at 4 km of spatial resolution and 3 hours of time resolution. Analyses in terms of comparison between the rainfall estimated by the dataset and the observations (available from the local raingauges network) were carried out, and a bias correction was also performed in order to better match the observed climatology. An extreme analysis was eventually carried on the streamflows time series obtained by the simulations, by comparing them with the results of the same hydrological model fed with the observed time series of rainfall. The results of the analysis are shown and discussed.

Quantifying the importance of spatial resolution and other factors through global sensitivity analysis of a flood inundation model

NASA Astrophysics Data System (ADS)

Thomas Steven Savage, James; Pianosi, Francesca; Bates, Paul; Freer, Jim; Wagener, Thorsten

2016-11-01

Where high-resolution topographic data are available, modelers are faced with the decision of whether it is better to spend computational resource on resolving topography at finer resolutions or on running more simulations to account for various uncertain input factors (e.g., model parameters). In this paper we apply global sensitivity analysis to explore how influential the choice of spatial resolution is when compared to uncertainties in the Manning's friction coefficient parameters, the inflow hydrograph, and those stemming from the coarsening of topographic data used to produce Digital Elevation Models (DEMs). We apply the hydraulic model LISFLOOD-FP to produce several temporally and spatially variable model outputs that represent different aspects of flood inundation processes, including flood extent, water depth, and time of inundation. We find that the most influential input factor for flood extent predictions changes during the flood event, starting with the inflow hydrograph during the rising limb before switching to the channel friction parameter during peak flood inundation, and finally to the floodplain friction parameter during the drying phase of the flood event. Spatial resolution and uncertainty introduced by resampling topographic data to coarser resolutions are much more important for water depth predictions, which are also sensitive to different input factors spatially and temporally. Our findings indicate that the sensitivity of LISFLOOD-FP predictions is more complex than previously thought. Consequently, the input factors that modelers should prioritize will differ depending on the model output assessed, and the location and time of when and where this output is most relevant.

Parameterizing a Large-scale Water Balance Model in Regions with Sparse Data: The Tigris-Euphrates River Basins as an Example

NASA Astrophysics Data System (ADS)

Flint, A. L.; Flint, L. E.

2010-12-01

The characterization of hydrologic response to current and future climates is of increasing importance to many countries around the world that rely heavily on changing and uncertain water supplies. Large-scale models that can calculate a spatially distributed water balance and elucidate groundwater recharge and surface water flows for large river basins provide a basis of estimates of changes due to future climate projections. Unfortunately many regions in the world have very sparse data for parameterization or calibration of hydrologic models. For this study, the Tigris and Euphrates River basins were used for the development of a regional water balance model at 180-m spatial scale, using the Basin Characterization Model, to estimate historical changes in groundwater recharge and surface water flows in the countries of Turkey, Syria, Iraq, Iran, and Saudi Arabia. Necessary input parameters include precipitation, air temperature, potential evapotranspiration (PET), soil properties and thickness, and estimates of bulk permeability from geologic units. Data necessary for calibration includes snow cover, reservoir volumes (from satellite data and historic, pre-reservoir elevation data) and streamflow measurements. Global datasets for precipitation, air temperature, and PET were available at very large spatial scales (50 km) through the world scale databases, finer scale WorldClim climate data, and required downscaling to fine scales for model input. Soils data were available through world scale soil maps but required parameterization on the basis of textural data to estimate soil hydrologic properties. Soil depth was interpreted from geomorphologic interpretation and maps of quaternary deposits, and geologic materials were categorized from generalized geologic maps of each country. Estimates of bedrock permeability were made on the basis of literature and data on driller’s logs and adjusted during calibration of the model to streamflow measurements where available. Results of historical water balance calculations throughout the Tigris and Euphrates River basins will be shown along with details of processing input data to provide spatial continuity and downscaling. Basic water availability analysis for recharge and runoff is readily available from a determinisitic solar radiation energy balance model and a global potential evapotranspiration model and global estimates of precipitation and air temperature. Future climate estimates can be readily applied to the same water and energy balance models to evaluate future water availability for countries around the globe.

Multi-scale analysis of a household level agent-based model of landcover change.

PubMed

Evans, Tom P; Kelley, Hugh

2004-08-01

Scale issues have significant implications for the analysis of social and biophysical processes in complex systems. These same scale implications are likewise considerations for the design and application of models of landcover change. Scale issues have wide-ranging effects from the representativeness of data used to validate models to aggregation errors introduced in the model structure. This paper presents an analysis of how scale issues affect an agent-based model (ABM) of landcover change developed for a research area in the Midwest, USA. The research presented here explores how scale factors affect the design and application of agent-based landcover change models. The ABM is composed of a series of heterogeneous agents who make landuse decisions on a portfolio of cells in a raster-based programming environment. The model is calibrated using measures of fit derived from both spatial composition and spatial pattern metrics from multi-temporal landcover data interpreted from historical aerial photography. A model calibration process is used to find a best-fit set of parameter weights assigned to agents' preferences for different landuses (agriculture, pasture, timber production, and non-harvested forest). Previous research using this model has shown how a heterogeneous set of agents with differing preferences for a portfolio of landuses produces the best fit to landcover changes observed in the study area. The scale dependence of the model is explored by varying the resolution of the input data used to calibrate the model (observed landcover), ancillary datasets that affect land suitability (topography), and the resolution of the model landscape on which agents make decisions. To explore the impact of these scale relationships the model is run with input datasets constructed at the following spatial resolutions: 60, 90, 120, 150, 240, 300 and 480 m. The results show that the distribution of landuse-preference weights differs as a function of scale. In addition, with the gradient descent model fitting method used in this analysis the model was not able to converge to an acceptable fit at the 300 and 480 m spatial resolutions. This is a product of the ratio of the input cell resolution to the average parcel size in the landscape. This paper uses these findings to identify scale considerations in the design, development, validation and application of ABMs of landcover change.

Mapping soil texture targeting predefined depth range or synthetizing from standard layers?

NASA Astrophysics Data System (ADS)

Laborczi, Annamária; Dezső Kaposi, András; Szatmári, Gábor; Takács, Katalin; Pásztor, László

2017-04-01

There are increasing demands nowadays on spatial soil information in order to support environmental related and land use management decisions. Physical soil properties, especially particle size distribution play important role in this context. A few of the requirements can be satisfied by the sand-, silt-, and clay content maps compiled according to global standards such as GlobalSoilMap (GSM) or Soil Grids. Soil texture classes (e. g. according to USDA classification) can be derived from these three fraction data, in this way texture map can be compiled based on the proper separate maps. Soil texture class as well as fraction information represent direct input of crop-, meteorological- and hydrological models. The model inputs frequently require maps representing soil features of 0-30 cm depth, which is covered by three consecutive depth intervals according to standard specifications: 0-5 cm, 5-15 cm, 15-30 cm. Becoming GSM and SoilGrids the most detailed freely available spatial soil data sources, the common model users (e. g. meteorologists, agronomists, or hydrologists) would produce input map from (the weighted mean of) these three layers. However, if the basic soil data and proper knowledge is obtainable, a soil texture map targeting directly the 0-30 cm layer could be independently compiled. In our work we compared Hungary's soil texture maps compiled using the same reference and auxiliary data and inference methods but for differing layer distribution. We produced the 0-30 cm clay, silt and sand map as well as the maps for the three standard layers (0-5 cm, 5-15 cm, 15-30 cm). Maps of sand, silt and clay percentage were computed through regression kriging (RK) applying Additive Log-Ratio (alr) transformation. In addition to the Hungarian Soil Information and Monitoring System as reference soil data, digital elevation model and its derived components, soil physical property maps, remotely sensed images, land use -, geological-, as well as meteorological data were applied as auxiliary variables. We compared the directly compiled and the synthetized clay-, sand content, and texture class maps by different tools. In addition to pairwise comparison of basic statistical features (histograms, scatter plots), we examined the spatial distribution of the differences. We quantified the taxonomical distances of the textural classes, in order to investigate the differences of the map-pairs. We concluded that the directly computed and the synthetized maps show various differences. In the case of clay-, and sand content maps, the map-pairs have to be considered statistically different. On the other hand, the differences of the texture class maps are not significant. However, in all cases, the differences rather concern the extreme ranges and categories. Using of synthetized maps can intensify extremities by error propagation in models and scenarios. Based on our results, we suggest the usage of the directly composed maps.

Sensory-evoked perturbations of locomotor activity by sparse sensory input: a computational study

PubMed Central

Brownstone, Robert M.

2015-01-01

Sensory inputs from muscle, cutaneous, and joint afferents project to the spinal cord, where they are able to affect ongoing locomotor activity. Activation of sensory input can initiate or prolong bouts of locomotor activity depending on the identity of the sensory afferent activated and the timing of the activation within the locomotor cycle. However, the mechanisms by which afferent activity modifies locomotor rhythm and the distribution of sensory afferents to the spinal locomotor networks have not been determined. Considering the many sources of sensory inputs to the spinal cord, determining this distribution would provide insights into how sensory inputs are integrated to adjust ongoing locomotor activity. We asked whether a sparsely distributed set of sensory inputs could modify ongoing locomotor activity. To address this question, several computational models of locomotor central pattern generators (CPGs) that were mechanistically diverse and generated locomotor-like rhythmic activity were developed. We show that sensory inputs restricted to a small subset of the network neurons can perturb locomotor activity in the same manner as seen experimentally. Furthermore, we show that an architecture with sparse sensory input improves the capacity to gate sensory information by selectively modulating sensory channels. These data demonstrate that sensory input to rhythm-generating networks need not be extensively distributed. PMID:25673740

Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps.

PubMed

Mitchard, Edward Ta; Saatchi, Sassan S; Baccini, Alessandro; Asner, Gregory P; Goetz, Scott J; Harris, Nancy L; Brown, Sandra

2013-10-26

Mapping the aboveground biomass of tropical forests is essential both for implementing conservation policy and reducing uncertainties in the global carbon cycle. Two medium resolution (500 m - 1000 m) pantropical maps of vegetation biomass have been recently published, and have been widely used by sub-national and national-level activities in relation to Reducing Emissions from Deforestation and forest Degradation (REDD+). Both maps use similar input data layers, and are driven by the same spaceborne LiDAR dataset providing systematic forest height and canopy structure estimates, but use different ground datasets for calibration and different spatial modelling methodologies. Here, we compare these two maps to each other, to the FAO's Forest Resource Assessment (FRA) 2010 country-level data, and to a high resolution (100 m) biomass map generated for a portion of the Colombian Amazon. We find substantial differences between the two maps, in particular in central Amazonia, the Congo basin, the south of Papua New Guinea, the Miombo woodlands of Africa, and the dry forests and savannas of South America. There is little consistency in the direction of the difference. However, when the maps are aggregated to the country or biome scale there is greater agreement, with differences cancelling out to a certain extent. When comparing country level biomass stocks, the two maps agree with each other to a much greater extent than to the FRA 2010 estimates. In the Colombian Amazon, both pantropical maps estimate higher biomass than the independent high resolution map, but show a similar spatial distribution of this biomass. Biomass mapping has progressed enormously over the past decade, to the stage where we can produce globally consistent maps of aboveground biomass. We show that there are still large uncertainties in these maps, in particular in areas with little field data. However, when used at a regional scale, different maps appear to converge, suggesting we can provide reasonable stock estimates when aggregated over large regions. Therefore we believe the largest uncertainties for REDD+ activities relate to the spatial distribution of biomass and to the spatial pattern of forest cover change, rather than to total globally or nationally summed carbon density.

Spatially- explicit Fossil Fuel Carbon Dioxide Inventories for Transportation in the U.S.

NASA Astrophysics Data System (ADS)

Hutchins, M.; Gurney, K. R.

2016-12-01

The transportation sector is the second largest source of Fossil Fuel CO2 (FFCO2) emissions, and is unique in that federal, state, and municipal levels of government are all able to enact transportation policy. However, since data related to transportation activities are reported by multiple different government agencies, the data are not always consistent. As a result, the methods and data used to inventory and account for transportation related FFCO2 emissions have important implications for both science and policy. Aggregate estimates of transportation related FFCO2 emissions can be spatially distributed using traffic data, such as the Highway Performance Monitoring System (HPMS) Average Annual Daily Traffic (AADT). There are currently two datasets that estimate the spatial distribution of transportation related FFCO2 in the United States- Vulcan 3.0 and the Database of Road Transportation Emissions (DARTE). Both datasets are at 1 km resolution, for the year 2011, and utilize HPMS AADT traffic data. However, Vulcan 3.0 and DARTE spatially distribute emissions using different methods and inputs, resulting in a number of differences. Vulcan 3.0 and DARTE estimate national transportation related FFCO2 emissions within 2.5% of each other, with more significant differences at the county and state level. The differences are most notable in urban versus rural regions, and for specific road classes. The origin of these differences are explored in depth to understand the implication of using specific data sources, such as the National Emissions Inventory and other aggregate transportation statistics from the Federal Highway Administration (FHWA). In addition to comparing Vulcan 3.0 and DARTE to each other, the results from both data sets are compared to independent traffic volume measurements acquired from the FHWA Continuous Count Station (CCS) network. The CCS records hourly traffic counts at fixed locations in space throughout the U.S. We calculate transportation related FFCO2 emissions at a CCS stations using fuel specific emissions factors combined with the raw traffic counts. The CCS network provides a unique opportunity to compare spatially explicit, "bottom-up" models of transportation related FFCO2 emissions to measured traffic volume at over 300 specific locations.

The effects of spatial population dataset choice on estimates of population at risk of disease

PubMed Central

2011-01-01

Background The spatial modeling of infectious disease distributions and dynamics is increasingly being undertaken for health services planning and disease control monitoring, implementation, and evaluation. Where risks are heterogeneous in space or dependent on person-to-person transmission, spatial data on human population distributions are required to estimate infectious disease risks, burdens, and dynamics. Several different modeled human population distribution datasets are available and widely used, but the disparities among them and the implications for enumerating disease burdens and populations at risk have not been considered systematically. Here, we quantify some of these effects using global estimates of populations at risk (PAR) of P. falciparum malaria as an example. Methods The recent construction of a global map of P. falciparum malaria endemicity enabled the testing of different gridded population datasets for providing estimates of PAR by endemicity class. The estimated population numbers within each class were calculated for each country using four different global gridded human population datasets: GRUMP (~1 km spatial resolution), LandScan (~1 km), UNEP Global Population Databases (~5 km), and GPW3 (~5 km). More detailed assessments of PAR variation and accuracy were conducted for three African countries where census data were available at a higher administrative-unit level than used by any of the four gridded population datasets. Results The estimates of PAR based on the datasets varied by more than 10 million people for some countries, even accounting for the fact that estimates of population totals made by different agencies are used to correct national totals in these datasets and can vary by more than 5% for many low-income countries. In many cases, these variations in PAR estimates comprised more than 10% of the total national population. The detailed country-level assessments suggested that none of the datasets was consistently more accurate than the others in estimating PAR. The sizes of such differences among modeled human populations were related to variations in the methods, input resolution, and date of the census data underlying each dataset. Data quality varied from country to country within the spatial population datasets. Conclusions Detailed, highly spatially resolved human population data are an essential resource for planning health service delivery for disease control, for the spatial modeling of epidemics, and for decision-making processes related to public health. However, our results highlight that for the low-income regions of the world where disease burden is greatest, existing datasets display substantial variations in estimated population distributions, resulting in uncertainty in disease assessments that utilize them. Increased efforts are required to gather contemporary and spatially detailed demographic data to reduce this uncertainty, particularly in Africa, and to develop population distribution modeling methods that match the rigor, sophistication, and ability to handle uncertainty of contemporary disease mapping and spread modeling. In the meantime, studies that utilize a particular spatial population dataset need to acknowledge the uncertainties inherent within them and consider how the methods and data that comprise each will affect conclusions. PMID:21299885

Active subthreshold dendritic conductances shape the local field potential

PubMed Central

Ness, Torbjørn V.; Remme, Michiel W. H.

2016-01-01

Key points The local field potential (LFP), the low‐frequency part of extracellular potentials recorded in neural tissue, is often used for probing neural circuit activity. Interpreting the LFP signal is difficult, however.While the cortical LFP is thought mainly to reflect synaptic inputs onto pyramidal neurons, little is known about the role of the various subthreshold active conductances in shaping the LFP.By means of biophysical modelling we obtain a comprehensive qualitative understanding of how the LFP generated by a single pyramidal neuron depends on the type and spatial distribution of active subthreshold currents.For pyramidal neurons, the h‐type channels probably play a key role and can cause a distinct resonance in the LFP power spectrum.Our results show that the LFP signal can give information about the active properties of neurons and imply that preferred frequencies in the LFP can result from those cellular properties instead of, for example, network dynamics. Abstract The main contribution to the local field potential (LFP) is thought to stem from synaptic input to neurons and the ensuing subthreshold dendritic processing. The role of active dendritic conductances in shaping the LFP has received little attention, even though such ion channels are known to affect the subthreshold neuron dynamics. Here we used a modelling approach to investigate the effects of subthreshold dendritic conductances on the LFP. Using a biophysically detailed, experimentally constrained model of a cortical pyramidal neuron, we identified conditions under which subthreshold active conductances are a major factor in shaping the LFP. We found that, in particular, the hyperpolarization‐activated inward current, I h, can have a sizable effect and cause a resonance in the LFP power spectral density. To get a general, qualitative understanding of how any subthreshold active dendritic conductance and its cellular distribution can affect the LFP, we next performed a systematic study with a simplified model. We found that the effect on the LFP is most pronounced when (1) the synaptic drive to the cell is asymmetrically distributed (i.e. either basal or apical), (2) the active conductances are distributed non‐uniformly with the highest channel densities near the synaptic input and (3) when the LFP is measured at the opposite pole of the cell relative to the synaptic input. In summary, we show that subthreshold active conductances can be strongly reflected in LFP signals, opening up the possibility that the LFP can be used to characterize the properties and cellular distributions of active conductances. PMID:27079755

The computational worm: spatial orientation and its neuronal basis in C. elegans.

PubMed

Lockery, Shawn R

2011-10-01

Spatial orientation behaviors in animals are fundamental for survival but poorly understood at the neuronal level. The nematode Caenorhabditis elegans orients to a wide range of stimuli and has a numerically small and well-described nervous system making it advantageous for investigating the mechanisms of spatial orientation. Recent work by the C. elegans research community has identified essential computational elements of the neural circuits underlying two orientation strategies that operate in five different sensory modalities. Analysis of these circuits reveals novel motifs including simple circuits for computing temporal derivatives of sensory input and for integrating sensory input with behavioral state to generate adaptive behavior. These motifs constitute hypotheses concerning the identity and functionality of circuits controlling spatial orientation in higher organisms. Copyright © 2011 Elsevier Ltd. All rights reserved.

Are fractal dimensions of the spatial distribution of mineral deposits meaningful?

USGS Publications Warehouse

Raines, G.L.

2008-01-01

It has been proposed that the spatial distribution of mineral deposits is bifractal. An implication of this property is that the number of deposits in a permissive area is a function of the shape of the area. This is because the fractal density functions of deposits are dependent on the distance from known deposits. A long thin permissive area with most of the deposits in one end, such as the Alaskan porphyry permissive area, has a major portion of the area far from known deposits and consequently a low density of deposits associated with most of the permissive area. On the other hand, a more equi-dimensioned permissive area, such as the Arizona porphyry permissive area, has a more uniform density of deposits. Another implication of the fractal distribution is that the Poisson assumption typically used for estimating deposit numbers is invalid. Based on datasets of mineral deposits classified by type as inputs, the distributions of many different deposit types are found to have characteristically two fractal dimensions over separate non-overlapping spatial scales in the range of 5-1000 km. In particular, one typically observes a local dimension at spatial scales less than 30-60 km, and a regional dimension at larger spatial scales. The deposit type, geologic setting, and sample size influence the fractal dimensions. The consequence of the geologic setting can be diminished by using deposits classified by type. The crossover point between the two fractal domains is proportional to the median size of the deposit type. A plot of the crossover points for porphyry copper deposits from different geologic domains against median deposit sizes defines linear relationships and identifies regions that are significantly underexplored. Plots of the fractal dimension can also be used to define density functions from which the number of undiscovered deposits can be estimated. This density function is only dependent on the distribution of deposits and is independent of the definition of the permissive area. Density functions for porphyry copper deposits appear to be significantly different for regions in the Andes, Mexico, United States, and western Canada. Consequently, depending on which regional density function is used, quite different estimates of numbers of undiscovered deposits can be obtained. These fractal properties suggest that geologic studies based on mapping at scales of 1:24,000 to 1:100,000 may not recognize processes that are important in the formation of mineral deposits at scales larger than the crossover points at 30-60 km. ?? 2008 International Association for Mathematical Geology.

A dynamic aerodynamic resistance approach to calculate high resolution sensible heat fluxes in urban areas

NASA Astrophysics Data System (ADS)

Crawford, Ben; Grimmond, Sue; Kent, Christoph; Gabey, Andrew; Ward, Helen; Sun, Ting; Morrison, William

2017-04-01

Remotely sensed data from satellites have potential to enable high-resolution, automated calculation of urban surface energy balance terms and inform decisions about urban adaptations to environmental change. However, aerodynamic resistance methods to estimate sensible heat flux (QH) in cities using satellite-derived observations of surface temperature are difficult in part due to spatial and temporal variability of the thermal aerodynamic resistance term (rah). In this work, we extend an empirical function to estimate rah using observational data from several cities with a broad range of surface vegetation land cover properties. We then use this function to calculate spatially and temporally variable rah in London based on high-resolution (100 m) land cover datasets and in situ meteorological observations. In order to calculate high-resolution QH based on satellite-observed land surface temperatures, we also develop and employ novel methods to i) apply source area-weighted averaging of surface and meteorological variables across the study spatial domain, ii) calculate spatially variable, high-resolution meteorological variables (wind speed, friction velocity, and Obukhov length), iii) incorporate spatially interpolated urban air temperatures from a distributed sensor network, and iv) apply a modified Monte Carlo approach to assess uncertainties with our results, methods, and input variables. Modeled QH using the aerodynamic resistance method is then compared to in situ observations in central London from a unique network of scintillometers and eddy-covariance measurements.

Dengue: recent past and future threats

PubMed Central

Rogers, David J.

2015-01-01

This article explores four key questions about statistical models developed to describe the recent past and future of vector-borne diseases, with special emphasis on dengue: (1) How many variables should be used to make predictions about the future of vector-borne diseases?(2) Is the spatial resolution of a climate dataset an important determinant of model accuracy?(3) Does inclusion of the future distributions of vectors affect predictions of the futures of the diseases they transmit?(4) Which are the key predictor variables involved in determining the distributions of vector-borne diseases in the present and future?Examples are given of dengue models using one, five or 10 meteorological variables and at spatial resolutions of from one-sixth to two degrees. Model accuracy is improved with a greater number of descriptor variables, but is surprisingly unaffected by the spatial resolution of the data. Dengue models with a reduced set of climate variables derived from the HadCM3 global circulation model predictions for the 1980s are improved when risk maps for dengue's two main vectors (Aedes aegypti and Aedes albopictus) are also included as predictor variables; disease and vector models are projected into the future using the global circulation model predictions for the 2020s, 2040s and 2080s. The Garthwaite–Koch corr-max transformation is presented as a novel way of showing the relative contribution of each of the input predictor variables to the map predictions. PMID:25688021

Biomechanics meets the ecological niche: the importance of temporal data resolution.

PubMed

Kearney, Michael R; Matzelle, Allison; Helmuth, Brian

2012-03-15

The emerging field of mechanistic niche modelling aims to link the functional traits of organisms to their environments to predict survival, reproduction, distribution and abundance. This approach has great potential to increase our understanding of the impacts of environmental change on individuals, populations and communities by providing functional connections between physiological and ecological response to increasingly available spatial environmental data. By their nature, such mechanistic models are more data intensive in comparison with the more widely applied correlative approaches but can potentially provide more spatially and temporally explicit predictions, which are often needed by decision makers. A poorly explored issue in this context is the appropriate level of temporal resolution of input data required for these models, and specifically the error in predictions that can be incurred through the use of temporally averaged data. Here, we review how biomechanical principles from heat-transfer and metabolic theory are currently being used as foundations for mechanistic niche models and consider the consequences of different temporal resolutions of environmental data for modelling the niche of a behaviourally thermoregulating terrestrial lizard. We show that fine-scale temporal resolution (daily) data can be crucial for unbiased inference of climatic impacts on survival, growth and reproduction. This is especially so for species with little capacity for behavioural buffering, because of behavioural or habitat constraints, and for detecting temporal trends. However, coarser-resolution data (long-term monthly averages) can be appropriate for mechanistic studies of climatic constraints on distribution and abundance limits in thermoregulating species at broad spatial scales.

Spatial Analysis in Determining Physical Factors of Pedestrian Space Livability, Case Study: Pedestrian Space on Jalan Kemasan, Yogyakarta

NASA Astrophysics Data System (ADS)

Fauzi, A. F.; Aditianata, A.

2018-02-01

The existence of street as a place to perform various human activities becomes an important issue nowadays. In the last few decades, cars and motorcycles dominate streets in various cities in the world. On the other hand, human activity on the street is the determinant of the city livability. Previous research has pointed out that if there is lots of human activity in the street, then the city will be interesting. Otherwise, if the street has no activity, then the city will be boring. Learning from that statement, now various cities in the world are developing the concept of livable streets. Livable streets shown by diversity of human activities conducted in the streets’ pedestrian space. In Yogyakarta, one of the streets shown diversity of human activities is Jalan Kemasan. This study attempts to determine the physical factors of pedestrian space affecting the livability in Jalan Kemasan Yogyakarta through spatial analysis. Spatial analysis was performed by overlay technique between liveable point (activity diversity) distribution map and variable distribution map. Those physical pedestrian space research variable included element of shading, street vendors, building setback, seat location, divider between street and pedestrian way, and mixed use building function. More diverse the activity of one variable, then those variable are more affected then others. Overlay result then strengthened by field observation to qualitatively ensure the deduction. In the end, this research will provide valuable input for street and pedestrian space planning that is comfortable for human activities.

The multisensor payload 'Structura' for the observation of atmospheric night glows from the ISS board

NASA Astrophysics Data System (ADS)

Krot, Yury; Beliaev, Boris; Katkovsky, Leonid

2016-10-01

Aerospace Research Department of the Institute of Applied Physical Problems at Belarusian State University has developed a prototype of the optical payload intended for a space experiment on the ISS board. The prototype includes four optical modules for the night glows observation, in particular spatial-brightness and spectral characteristics in the altitude range of 80-320 km. Objects of the interest are emitting top layers of the atmosphere including exited OH radicals, atomic and molecular oxygen and sodium layers. The goal of the space experiment is a research of night glows over different regions of the Earth and a connection with natural disasters like earthquakes, cyclones, etc. Two optical modules for spatial distribution of atomic oxygen layers along the altitude consist of input lenses, spectral interferential filters and line CCD detectors. The optical module for registration of exited OH radical emissions is formed from CCD array spectrometer. The payload includes also a panchromatic (400-900 nm) high sensitive imaging camera for observing of the glows general picture. The optical modules of the prototype have been tested and general optical characteristics were determined in laboratory conditions. A solution of an astigmatism reducing of a concave diffraction grating and a method of the second diffraction order correction were applied and improved spectrometer's optical characteristics. Laboratory equipment and software were developed to imitate a dynamic scene of the night glows in laboratory conditions including an imitation of linear spectra and the spatial distribution of emissions.

Mapping and Analysis of the Connectome of Sympathetic Premotor Neurons in the Rostral Ventrolateral Medulla of the Rat Using a Volumetric Brain Atlas

PubMed Central

Dempsey, Bowen; Le, Sheng; Turner, Anita; Bokiniec, Phil; Ramadas, Radhika; Bjaalie, Jan G.; Menuet, Clement; Neve, Rachael; Allen, Andrew M.; Goodchild, Ann K.; McMullan, Simon

2017-01-01

Spinally projecting neurons in the rostral ventrolateral medulla (RVLM) play a critical role in the generation of vasomotor sympathetic tone and are thought to receive convergent input from neurons at every level of the neuraxis; the factors that determine their ongoing activity remain unresolved. In this study we use a genetically restricted viral tracing strategy to definitively map their spatially diffuse connectome. We infected bulbospinal RVLM neurons with a recombinant rabies variant that drives reporter expression in monosynaptically connected input neurons and mapped their distribution using an MRI-based volumetric atlas and a novel image alignment and visualization tool that efficiently translates the positions of neurons captured in conventional photomicrographs to Cartesian coordinates. We identified prominent inputs from well-established neurohumoral and viscero-sympathetic sensory actuators, medullary autonomic and respiratory subnuclei, and supramedullary autonomic nuclei. The majority of inputs lay within the brainstem (88–94%), and included putative respiratory neurons in the pre-Bötzinger Complex and post-inspiratory complex that are therefore likely to underlie respiratory-sympathetic coupling. We also discovered a substantial and previously unrecognized input from the region immediately ventral to nucleus prepositus hypoglossi. In contrast, RVLM sympathetic premotor neurons were only sparsely innervated by suprapontine structures including the paraventricular nucleus, lateral hypothalamus, periaqueductal gray, and superior colliculus, and we found almost no evidence of direct inputs from the cortex or amygdala. Our approach can be used to quantify, standardize and share complete neuroanatomical datasets, and therefore provides researchers with a platform for presentation, analysis and independent reanalysis of connectomic data. PMID:28298886

Spatial Language Facilitates Spatial Cognition: Evidence from Children Who Lack Language Input

ERIC Educational Resources Information Center

Gentner, Dedre; Ozyurek, Asli; Gurcanli, Ozge; Goldin-Meadow, Susan

2013-01-01

Does spatial language influence how people think about space? To address this question, we observed children who did not know a conventional language, and tested their performance on nonlinguistic spatial tasks. We studied deaf children living in Istanbul whose hearing losses prevented them from acquiring speech and whose hearing parents had not…

Improved Satellite Retrievals of NO2 and SO2 over the Canadian Oil Sands and Comparisons with Surface Measurements

NASA Technical Reports Server (NTRS)

McLinden, C. A.; Fioletov, V.; Boersma, K. F.; Kharol, S. K.; Krotkov, N.; Lamsal, L.; Makar, P. A.; Martin, R. V.; Veefkind, J. P.; Yang, K.

2014-01-01

Satellite remote sensing is increasingly being used to monitor air quality over localized sources such as the Canadian oil sands. Following an initial study, significantly low biases have been identified in current NO2 and SO2 retrieval products from the Ozone Monitoring Instrument (OMI) satellite sensor over this location resulting from a combination of its rapid development and small spatial scale. Air mass factors (AMFs) used to convert line-of-sight "slant" columns to vertical columns were re-calculated for this region based on updated and higher resolution input information including absorber profiles from a regional-scale (15 km × 15 km resolution) air quality model, higher spatial and temporal resolution surface reflectivity, and an improved treatment of snow. The overall impact of these new Environment Canada (EC) AMFs led to substantial increases in the peak NO2 and SO2 average vertical column density (VCD), occurring over an area of intensive surface mining, by factors of 2 and 1.4, respectively, relative to estimates made with previous AMFs. Comparisons are made with long-term averages of NO2 and SO2 (2005-2011) from in situ surface monitors by using the air quality model to map the OMI VCDs to surface concentrations. This new OMI-EC product is able to capture the spatial distribution of the in situ instruments (slopes of 0.65 to 1.0, correlation coefficients of greater than 0.9). The concentration absolute values from surface network observations were in reasonable agreement, with OMI-EC NO2 and SO2 biased low by roughly 30%. Several complications were addressed including correction for the interference effect in the surface NO2 instruments and smoothing and clear-sky biases in the OMI measurements. Overall these results highlight the importance of using input information that accounts for the spatial and temporal variability of the location of interest when performing retrievals.

Characterizing regional soil mineral composition using spectroscopyand geostatistics

USGS Publications Warehouse

Mulder, V.L.; de Bruin, S.; Weyermann, J.; Kokaly, Raymond F.; Schaepman, M.E.

2013-01-01

This work aims at improving the mapping of major mineral variability at regional scale using scale-dependent spatial variability observed in remote sensing data. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data and statistical methods were combined with laboratory-based mineral characterization of field samples to create maps of the distributions of clay, mica and carbonate minerals and their abundances. The Material Identification and Characterization Algorithm (MICA) was used to identify the spectrally-dominant minerals in field samples; these results were combined with ASTER data using multinomial logistic regression to map mineral distributions. X-ray diffraction (XRD)was used to quantify mineral composition in field samples. XRD results were combined with ASTER data using multiple linear regression to map mineral abundances. We testedwhether smoothing of the ASTER data to match the scale of variability of the target sample would improve model correlations. Smoothing was donewith Fixed Rank Kriging (FRK) to represent the mediumand long-range spatial variability in the ASTER data. Stronger correlations resulted using the smoothed data compared to results obtained with the original data. Highest model accuracies came from using both medium and long-range scaled ASTER data as input to the statistical models. High correlation coefficients were obtained for the abundances of calcite and mica (R2 = 0.71 and 0.70, respectively). Moderately-high correlation coefficients were found for smectite and kaolinite (R2 = 0.57 and 0.45, respectively). Maps of mineral distributions, obtained by relating ASTER data to MICA analysis of field samples, were found to characterize major soil mineral variability (overall accuracies for mica, smectite and kaolinite were 76%, 89% and 86% respectively). The results of this study suggest that the distributions of minerals and their abundances derived using FRK-smoothed ASTER data more closely match the spatial variability of soil and environmental properties at regional scale.

When Content Matters: The Role of Processing Code in Tactile Display Design.

PubMed

Ferris, Thomas K; Sarter, Nadine

2010-01-01

The distribution of tasks and stimuli across multiple modalities has been proposed as a means to support multitasking in data-rich environments. Recently, the tactile channel and, more specifically, communication via the use of tactile/haptic icons have received considerable interest. Past research has examined primarily the impact of concurrent task modality on the effectiveness of tactile information presentation. However, it is not well known to what extent the interpretation of iconic tactile patterns is affected by another attribute of information: the information processing codes of concurrent tasks. In two driving simulation studies (n = 25 for each), participants decoded icons composed of either spatial or nonspatial patterns of vibrations (engaging spatial and nonspatial processing code resources, respectively) while concurrently interpreting spatial or nonspatial visual task stimuli. As predicted by Multiple Resource Theory, performance was significantly worse (approximately 5-10 percent worse) when the tactile icons and visual tasks engaged the same processing code, with the overall worst performance in the spatial-spatial task pairing. The findings from these studies contribute to an improved understanding of information processing and can serve as input to multidimensional quantitative models of timesharing performance. From an applied perspective, the results suggest that competition for processing code resources warrants consideration, alongside other factors such as the naturalness of signal-message mapping, when designing iconic tactile displays. Nonspatially encoded tactile icons may be preferable in environments which already rely heavily on spatial processing, such as car cockpits.

Modulation of microsaccades by spatial frequency during object categorization.

PubMed

Craddock, Matt; Oppermann, Frank; Müller, Matthias M; Martinovic, Jasna

2017-01-01

The organization of visual processing into a coarse-to-fine information processing based on the spatial frequency properties of the input forms an important facet of the object recognition process. During visual object categorization tasks, microsaccades occur frequently. One potential functional role of these eye movements is to resolve high spatial frequency information. To assess this hypothesis, we examined the rate, amplitude and speed of microsaccades in an object categorization task in which participants viewed object and non-object images and classified them as showing either natural objects, man-made objects or non-objects. Images were presented unfiltered (broadband; BB) or filtered to contain only low (LSF) or high spatial frequency (HSF) information. This allowed us to examine whether microsaccades were modulated independently by the presence of a high-level feature - the presence of an object - and by low-level stimulus characteristics - spatial frequency. We found a bimodal distribution of saccades based on their amplitude, with a split between smaller and larger microsaccades at 0.4° of visual angle. The rate of larger saccades (⩾0.4°) was higher for objects than non-objects, and higher for objects with high spatial frequency content (HSF and BB objects) than for LSF objects. No effects were observed for smaller microsaccades (<0.4°). This is consistent with a role for larger microsaccades in resolving HSF information for object identification, and previous evidence that more microsaccades are directed towards informative image regions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatial patterns of throughfall isotopic composition at the event and seasonal timescales

NASA Astrophysics Data System (ADS)

Allen, Scott T.; Keim, Richard F.; McDonnell, Jeffrey J.

2015-03-01

Spatial variability of throughfall isotopic composition in forests is indicative of complex processes occurring in the canopy and remains insufficiently understood to properly characterize precipitation inputs to the catchment water balance. Here we investigate variability of throughfall isotopic composition with the objectives: (1) to quantify the spatial variability in event-scale samples, (2) to determine if there are persistent controls over the variability and how these affect variability of seasonally accumulated throughfall, and (3) to analyze the distribution of measured throughfall isotopic composition associated with varying sampling regimes. We measured throughfall over two, three-month periods in western Oregon, USA under a Douglas-fir canopy. The mean spatial range of δ18O for each event was 1.6‰ and 1.2‰ through Fall 2009 (11 events) and Spring 2010 (7 events), respectively. However, the spatial pattern of isotopic composition was not temporally stable causing season-total throughfall to be less variable than event throughfall (1.0‰; range of cumulative δ18O for Fall 2009). Isotopic composition was not spatially autocorrelated and not explained by location relative to tree stems. Sampling error analysis for both field measurements and Monte-Carlo simulated datasets representing different sampling schemes revealed the standard deviation of differences from the true mean as high as 0.45‰ (δ18O) and 1.29‰ (d-excess). The magnitude of this isotopic variation suggests that small sample sizes are a source of substantial experimental error.

Seasonal-Spatial Distribution and Long-Term Variation of Transparency in Xin'anjiang Reservoir: Implications for Reservoir Management.

PubMed

Wu, Zhixu; Zhang, Yunlin; Zhou, Yongqiang; Liu, Mingliang; Shi, Kun; Yu, Zuoming

2015-08-12

Water transparency is a useful indicator of water quality or productivity and is widely used to detect long-term changes in the water quality and eutrophication of lake ecosystems. Based on short-term spatial observations in the spring, summer, and winter and on long-term site-specific observation from 1988 to 2013, the spatial, seasonal, long-term variations, and the factors affecting transparency are presented for Xin'anjiang Reservoir (China). Spatially, transparency was high in the open water but low in the bays and the inflowing river mouths, reflecting the effect of river runoff. The seasonal effects were distinct, with lower values in the summer than in the winter, most likely due to river runoff and phytoplankton biomass increases. The transparency decreased significantly with a linear slope of 0.079 m/year, indicating a 2.05 m decrease and a marked decrease in water quality. A marked increase occurred in chlorophyll a (Chla) concentration, and a significant correlation was found between the transparency and Chla concentration, indicating that phytoplankton biomass can partially explain the long-term trend of transparency in Xin'anjiang Reservoir. The river input and phytoplankton biomass increase were associated with soil erosion and nutrient loss in the catchment. Our study will support future management of water quality in Xin'anjiang Reservoir.

Optimised Iteration in Coupled Monte Carlo - Thermal-Hydraulics Calculations

NASA Astrophysics Data System (ADS)

Hoogenboom, J. Eduard; Dufek, Jan

2014-06-01

This paper describes an optimised iteration scheme for the number of neutron histories and the relaxation factor in successive iterations of coupled Monte Carlo and thermal-hydraulic reactor calculations based on the stochastic iteration method. The scheme results in an increasing number of neutron histories for the Monte Carlo calculation in successive iteration steps and a decreasing relaxation factor for the spatial power distribution to be used as input to the thermal-hydraulics calculation. The theoretical basis is discussed in detail and practical consequences of the scheme are shown, among which a nearly linear increase per iteration of the number of cycles in the Monte Carlo calculation. The scheme is demonstrated for a full PWR type fuel assembly. Results are shown for the axial power distribution during several iteration steps. A few alternative iteration method are also tested and it is concluded that the presented iteration method is near optimal.

Distribution of Potential Hydrothermally Altered Rocks in Central Colorado Derived From Landsat Thematic Mapper Data: A Geographic Information System Data Set

USGS Publications Warehouse

Knepper, Daniel H.

2010-01-01

As part of the Central Colorado Mineral Resource Assessment Project, the digital image data for four Landsat Thematic Mapper scenes covering central Colorado between Wyoming and New Mexico were acquired and band ratios were calculated after masking pixels dominated by vegetation, snow, and terrain shadows. Ratio values were visually enhanced by contrast stretching, revealing only those areas with strong responses (high ratio values). A color-ratio composite mosaic was prepared for the four scenes so that the distribution of potentially hydrothermally altered rocks could be visually evaluated. To provide a more useful input to a Geographic Information System-based mineral resource assessment, the information contained in the color-ratio composite raster image mosaic was converted to vector-based polygons after thresholding to isolate the strongest ratio responses and spatial filtering to reduce vector complexity and isolate the largest occurrences of potentially hydrothermally altered rocks.

Tidal dissipation, surface heat flow, and figure of viscoelastic models of Io

NASA Technical Reports Server (NTRS)

Segatz, M.; Spohn, T.; Ross, M. N.; Schubert, G.

1988-01-01

The deformation of Io, the tidal dissipation rate, and its interior spatial distribution are investigated by means of numerical simulations based on (1) a three-layer model (with dissipation in the mantle) or (2) a four-layer model (with dissipation in the asthenosphere). The mathematical derivation of the models is outlined; the selection of the input-parameter values is explained; the results are presented in extensive graphs and contour maps; and the constraints imposed on the models by observational data on the hot-spot distribution, tidal deformation, and gravity field are discussed in detail. It is found that both dissipation mechanisms may play a role on Io: model (2) is better able to explain the concentration of hot spots near the equator, while the presence of a large hot spot near the south pole (if confirmed by observations) would favor model (1).

Effects of temperature distribution on boundary layer stability for a circular cone at Mach 10

NASA Astrophysics Data System (ADS)

Rigney, Jeffrey M.

A CFD analysis was conducted on a circular cone at 3 degrees angle of attack at Mach 10 using US3D and STABL 3D to determine the effect of wall temperature on the stability characteristics that lead to laminar-to-turbulent transition. Wall temperature distributions were manipulated while all other flow inputs and geometric qualities were held constant. Laminar-to-turbulent transition was analyzed for isothermal and adiabatic wall conditions, a simulated short-duration wind tunnel case, and several hot-nose temperature distributions. For this study, stability characteristics include maximum N-factor growth and the corresponding frequency range, disturbance spatial amplification rate and the corresponding modal frequency, and stability neutral point location. STABL 3D analysis indicates that temperature distributions typical of those in short-duration hypersonic wind tunnels do not result in any significant difference on the stability characteristics, as compared to an isothermal wall boundary condition. Hypothetical distributions of much greater temperatures at and past the nose tip do show a trend of dampening of second-mode disturbances, most notably on the leeward ray. The most pronounced differences existed between the isothermal and adiabatic cases.

Sustainable management of agriculture activity on areas with soil vulnerability to compaction trough a developed decision support system (DSS)

NASA Astrophysics Data System (ADS)

Moretto, Johnny; Fantinato, Luciano; Rasera, Roberto

2017-04-01

One of the main environmental effects of agriculture is the negative impacts on areas with soil vulnerability to compaction and undersurface water derived from inputs and treatment distributions. A solution may represented from the "Precision Farming". Precision Farming refers to a management concept focusing on (near-real time) observation, measurement and responses to inter- and intra-variability in crops, fields and animals. Potential benefits may include increasing crop yields and animal performance, cost and labour reduction and optimisation of process inputs, all of which would increase profitability. At the same time, Precision Farming should increase work safety and reduce the environmental impacts of agriculture and farming practices, thus contributing to the sustainability of agricultural production. The concept has been made possible by the rapid development of ICT-based sensor technologies and procedures along with dedicated software that, in the case of arable farming, provides the link between spatially-distributed variables and appropriate farming practices such as tillage, seeding, fertilisation, herbicide and pesticide application, and harvesting. Much progress has been made in terms of technical solutions, but major steps are still required for the introduction of this approach over the common agricultural practices. There are currently a large number of sensors capable of collecting data for various applications (e.g. Index of vegetation vigor, soil moisture, Digital Elevation Models, meteorology, etc.). The resulting large volumes of data need to be standardised, processed and integrated using metadata analysis of spatial information, to generate useful input for decision-support systems. In this context, a user-friendly IT applications has been developed, for organizing and processing large volumes of data from different types of remote sensing and meteorological sensors, and for integrating these data into user-friendly farm management support systems able to support the farm manager. In this applications will be possible to implement numerical models to support the farm manager on the best time to work in field and/or the best trajectory to follow with a GPS navigation system on soil vulnerability to compaction. In addition to provide "as applied map" to indicate in each part of the field the exact needed quantity of inputs and treatments. This new working models for data management will allow to a most efficient resource usage contributing in a more sustainable agriculture both for a more economic benefits for the farmers and for reduction of environmental soil and undersurface water impacts.

Accounting for groundwater in stream fish thermal habitat responses to climate change

USGS Publications Warehouse

Snyder, Craig D.; Hitt, Nathaniel P.; Young, John A.

2015-01-01

Forecasting climate change effects on aquatic fauna and their habitat requires an understanding of how water temperature responds to changing air temperature (i.e., thermal sensitivity). Previous efforts to forecast climate effects on brook trout habitat have generally assumed uniform air-water temperature relationships over large areas that cannot account for groundwater inputs and other processes that operate at finer spatial scales. We developed regression models that accounted for groundwater influences on thermal sensitivity from measured air-water temperature relationships within forested watersheds in eastern North America (Shenandoah National Park, USA, 78 sites in 9 watersheds). We used these reach-scale models to forecast climate change effects on stream temperature and brook trout thermal habitat, and compared our results to previous forecasts based upon large-scale models. Observed stream temperatures were generally less sensitive to air temperature than previously assumed, and we attribute this to the moderating effect of shallow groundwater inputs. Predicted groundwater temperatures from air-water regression models corresponded well to observed groundwater temperatures elsewhere in the study area. Predictions of brook trout future habitat loss derived from our fine-grained models were far less pessimistic than those from prior models developed at coarser spatial resolutions. However, our models also revealed spatial variation in thermal sensitivity within and among catchments resulting in a patchy distribution of thermally suitable habitat. Habitat fragmentation due to thermal barriers therefore may have an increasingly important role for trout population viability in headwater streams. Our results demonstrate that simple adjustments to air-water temperature regression models can provide a powerful and cost-effective approach for predicting future stream temperatures while accounting for effects of groundwater.

[Spatio-temporal changes of nitrogen balance in 1980-2005 for agricultural land in Three Gorges Reservoir Area].

PubMed

Xu, Xi-bao; Yang, Gui-shan; Li, Heng-peng

2009-08-15

Based on the long-term agricultural statistics data at the county scale, the estimation of nitrogen balance from 1980 to 2005 for agricultural land in Three Gorges Reservoir Area was made by the OECD soil surface nitrogen balance model with some suitable modification. The spatio-temporal changes of nitrogen balance and its drivers were analyzed. The results showed that the total inputs and total surplus of nitrogen from 1980 to 2005 presented increasing trends continuously, from 23.4 x 10(4) t and 14.4 x 104 t to 45.6 x 10(4) t and 30 x 10(4) t respectively. The total output of nitrogen in 1980-1995 was at the increasing trend, from 9.0 x 10(4) t to 16.7 x 10(4) t, while that of 1996-2005 was keeping steady. The average unit surplus of nitrogen in 1980-1998 was also at the increasing trend, from 133.4 kg/hm2 to 310.3 kg/hm(2); and the trend inclined to be steady after 1998, while the spatial differential pattern toned up. The great spatial changes for nitrogen surplus from 1980 to 2005, mainly centralized at the head and the middle of the Three Gorges Reservoir Area, similar to the spatial distribution of the resettlement. Fertilizer, manure and biological fixation were the main contributors of nitrogen input sources, accumulatively totaled for above 90%. Nitrogen balance changes were mainly influenced by the macro-environment of fertilizer utilization before 1995, while which were influenced by the large amounts of the resettlement for Three Gorges Project after 1995. However, how much the effects of the resettlement on nitrogen balance need to be further explored. Developing sideline, agricultural structure transition or ecological resettlement should be considered to control nitrogen emission.

Global assessment of shipping emissions in 2015 on a high spatial and temporal resolution

NASA Astrophysics Data System (ADS)

Johansson, Lasse; Jalkanen, Jukka-Pekka; Kukkonen, Jaakko

2017-10-01

We present a comprehensive global shipping emission inventory and the global activities of ships for the year 2015. The emissions were evaluated using the Ship Traffic Emission Assessment Model (STEAM3), which uses Automatic Identification System data to describe the traffic activities of ships. We have improved the model regarding (i) the evaluation of the missing technical specifications of ships, and (ii) the treatment of shipping activities in case of sparse satellite AIS-data. We have developed a model for the collection and processing of available information on the technical specifications, using data assimilation techniques. We have also developed a path regeneration model that constructs, whenever necessary, the detailed geometry of the ship routes. The presented results for fuel consumption were qualitatively in agreement both with those in the 3rd Greenhouse Gas Study of the International Maritime Organisation and those reported by the International Energy Agency. We have also presented high-resolution global spatial distributions of the shipping emissions of NOx, CO2, SO2 and PM2.5. The emissions were also analysed in terms of selected sea areas, ship categories, the sizes of ships and flag states. The emission datasets provided by this study are available upon request; the datasets produced by the model can be utilized as input data for air quality modelling on a global scale, including the full temporal and spatial variation of shipping emissions for the first time. Dispersion modelling using this inventory as input can be used to assess the impacts of various emission abatement scenarios. The emission computation methods presented in this paper could also be used, e.g., to provide annual updates of the global ship emissions.

Spatial variability of chlorophyll and nitrogen content of rice from hyperspectral imagery

NASA Astrophysics Data System (ADS)

Moharana, Shreedevi; Dutta, Subashisa

2016-12-01

Chlorophyll and nitrogen are the most essential parameters for paddy crop growth. Spectroradiometric measurements were collected at canopy level during critical growth period of rice. Chemical analysis was performed to quantify the total leaf content. By exploiting the ground based measurements, regression models were established for chlorophyll and nitrogen aimed indices with their corresponding crop growth variables. Vegetation index models were developed for mapping these parameters from Hyperion imagery in an agriculture system. It was inferred that the present Simple Ratio (SR) and Leaf Nitrogen Concentration (LNC) indices, which followed a linear and nonlinear relationship respectively, were completely different from published Tian et al. (2011). The nitrogen content varied widely from 1 to 4% and only 2 to 3% for paddy crop using present modified index models and Tian et al. (2011) respectively. The modified LNC index model performed better than the established Tian et al. (2011) model as far as estimated nitrogen content from Hyperion imagery was concerned. Furthermore, within the observed chlorophyll range obtained from the studied rice varieties grown in the rice agriculture system, the index models (LNC, OASVI, Gitelson, mSR and MTCI) performed well in the spatial distribution of rice chlorophyll content from Hyperion imagery. Spatial distribution of total chlorophyll content varied widely from 1.77 to 5.81 mg/g (LNC), 3.0 to 13 mg/g (OASVI), 0.5 to 10.43 mg/g (Gitelson), 2.18 to 10.61 mg/g (mSR) and 2.90 to 5.40 mg/g (MTCI). The spatial information of these parameters will help in proper nutrient management, yield forecasting, and will serve as inputs for crop growth and forecasting models for a precision rice agriculture system.

Scale effect challenges in urban hydrology highlighted with a distributed hydrological model

NASA Astrophysics Data System (ADS)

Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Bompard, Philippe; Ten Veldhuis, Marie-Claire

2018-01-01

Hydrological models are extensively used in urban water management, development and evaluation of future scenarios and research activities. There is a growing interest in the development of fully distributed and grid-based models. However, some complex questions related to scale effects are not yet fully understood and still remain open issues in urban hydrology. In this paper we propose a two-step investigation framework to illustrate the extent of scale effects in urban hydrology. First, fractal tools are used to highlight the scale dependence observed within distributed data input into urban hydrological models. Then an intensive multi-scale modelling work is carried out to understand scale effects on hydrological model performance. Investigations are conducted using a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech. The model is implemented at 17 spatial resolutions ranging from 100 to 5 m. Results clearly exhibit scale effect challenges in urban hydrology modelling. The applicability of fractal concepts highlights the scale dependence observed within distributed data. Patterns of geophysical data change when the size of the observation pixel changes. The multi-scale modelling investigation confirms scale effects on hydrological model performance. Results are analysed over three ranges of scales identified in the fractal analysis and confirmed through modelling. This work also discusses some remaining issues in urban hydrology modelling related to the availability of high-quality data at high resolutions, and model numerical instabilities as well as the computation time requirements. The main findings of this paper enable a replacement of traditional methods of model calibration by innovative methods of model resolution alteration based on the spatial data variability and scaling of flows in urban hydrology.

Sensory experience modifies feature map relationships in visual cortex

PubMed Central

Cloherty, Shaun L; Hughes, Nicholas J; Hietanen, Markus A; Bhagavatula, Partha S

2016-01-01

The extent to which brain structure is influenced by sensory input during development is a critical but controversial question. A paradigmatic system for studying this is the mammalian visual cortex. Maps of orientation preference (OP) and ocular dominance (OD) in the primary visual cortex of ferrets, cats and monkeys can be individually changed by altered visual input. However, the spatial relationship between OP and OD maps has appeared immutable. Using a computational model we predicted that biasing the visual input to orthogonal orientation in the two eyes should cause a shift of OP pinwheels towards the border of OD columns. We then confirmed this prediction by rearing cats wearing orthogonally oriented cylindrical lenses over each eye. Thus, the spatial relationship between OP and OD maps can be modified by visual experience, revealing a previously unknown degree of brain plasticity in response to sensory input. DOI: http://dx.doi.org/10.7554/eLife.13911.001 PMID:27310531

Effects of Subbasin Size on Topographic Characteristics and Simulated Flow Paths in Sleepers River Watershed, Vermont

NASA Astrophysics Data System (ADS)

Wolock, David M.

1995-08-01

The effects of subbasin size on topographic characteristics and simulated flow paths were determined for the 111.5-km2 Sleepers River Research Watershed in Vermont using the watershed model TOPMODEL. Topography is parameterized in TOPMODEL as the spatial and statistical distribution of the index ln (a/tan B), where In is the Napierian logarithm, a is the upslope area per unit contour length, and tan B is the slope gradient. The mean, variance, and skew of the ln (a/tan B) distribution were computed for several sets of nested subbasins (0.05 to 111.5 km2)) along streams in the watershed and used as input to TOPMODEL. In general, the statistics of the ln (a/tan B) distribution and the simulated percentage of overland flow in total streamflow increased rapidly for some nested subbasins and decreased rapidly for others as subbasin size increased from 0.05 to 1 km2, generally increased up to a subbasin size of 5 km2, and remained relatively constant at a subbasin size greater than 5 km2. Differences in simulated flow paths among subbasins of all sizes (0.05 to 111.5 km2) were caused by differences in the statistics of the ln (a/tan B) distribution, not by differences in the explicit spatial arrangement of ln (a/tan B) values within the subbasins. Analysis of streamflow chemistry data from the Neversink River watershed in southeastern New York supports the hypothesis that subbasin size affects flow-path characteristics.

Assessment of the sources of sedimentary organic matter in the Bohai Sea and the northern Yellow Sea using biomarker proxies

NASA Astrophysics Data System (ADS)

Xing, Lei; Hou, Di; Wang, Xinchen; Li, Li; Zhao, Meixun

2016-07-01

To evaluate the applicability of source proxies and to assess the sources of sedimentary organic matter in the Bohai Sea (BS) and the northern Yellow Sea (NYS), we analyzed total organic carbon (TOC), total nitrogen (TN), δ13C of TOC, n-alkanes, phytoplankton biomarkers, and glycerol dialkyl glycerol tetraethers (GDGTs) including branched GDGTs (brGDGTs) in 60 surface sediment samples covering the BS and the NYS. Spatial distribution comparison and principal component analysis indicate that with the exception of brGDGTs, terrestrial biomarkers have different spatial distribution pattern from marine biomarkers, suggesting that the sources control the distributions of these biomarkers in spite of hydrodynamic forcing. Significantly positive correlation (R2 = 0.5) between TOC normalized brGDGTs content and TOC normalized crenarchaeol content suggested in situ production of brGDGTs in the BS and the NYS. The δ13C values, TMBR [terrestrial and marine biomarker ratio: (C27 + C29 + C31n-alkanes)/[(C27 + C29 + C31n-alkanes) + (brassicasterol + dinosterol + alkenones)] ] and BIT (branched isoprenoid tetratether index) proxy indicated high terrestrial organic matter (TOM) input near the Huanghe River Estuary, while TOC/TON did not reveal similar distribution pattern. Quantitative estimates of TOM using a binary model revealed much higher TOM percentage from δ13C (avg. 58%) and TMBR (avg. 31%) than from BIT (avg. 7.4%). Our results suggest that, owing to significant in situ production of brGDGTs, the BIT is not a good proxy for indicating soil OM contribution in marine sediments from the BS and the NYS.

Spatio-temporal analysis of agricultural land-use intensity across the Western Siberian grain belt.

PubMed

Kühling, Insa; Broll, Gabriele; Trautz, Dieter

2016-02-15

The Western Siberian grain belt covers 1millionkm² in Asiatic Russia and is of global importance for agriculture. Massive land-use changes took place in that region after the dissolution of the Soviet Union and the collapse of the state farm system. Decreasing land-use intensity (LUI) in post-Soviet Western Siberia was observed on grassland due to declining livestock whilst on cropland trends of land abandonment reversed in the early 2000s. Recultivation of abandoned cropland as well as increasing fertilizer inputs and narrowing crop rotations led to increasing LUI on cropland during the last two decades. Beyond that general trend, no information is available about spatial distribution and magnitude but a crucial precondition for the development of strategies for sustainable land management. To quantify changes and patterns in LUI, we developed an intensity index that reflects the impacts of land-based agricultural production. Based on subnational yearly statistical data, we calculated two separate input-orientated indices for cropland and grassland, respectively. The indices were applied on two spatial scale: at seven provinces covering the Western Siberian grain belt (Altay Kray, Chelyabinsk, Kurgan, Novosibirsk, Omsk, Sverdlovsk and Tyumen) and at all districts of the central province Tyumen. The spatio-temporal analysis clearly showed opposite trends for the two land-use types: decreasing intensity on grassland (-0.015 LUI units per year) and intensification on cropland (+0.014 LUI units per year). Furthermore, a spatial concentration towards intensity centres occurred during transition from a planned to a market economy. A principal component analysis enabled the individual calculations of both land-use types to be combined and revealed a strong link between biophysical conditions and LUI. The findings clearly showed the need for having a different strategy for future sustainable land management for grassland (predominantly used by livestock of households) and cropland (predominantly managed by large agricultural enterprises), which have to be addressed specifically by the different land users. As all input data are publicly available, the approach described is readily transferable to other regions or countries of the former Soviet Union. Copyright © 2015 Elsevier B.V. All rights reserved.

Shift-variant linear system modeling for multispectral scanners

NASA Astrophysics Data System (ADS)

Amini, Abolfazl M.; Ioup, George E.; Ioup, Juliette W.

1995-07-01

Multispectral scanner data are affected both by the spatial impulse response of the sensor and the spectral response of each channel. To achieve a realistic representation for the output data for a given scene spectral input, both of these effects must be incorporated into a forward model. Each channel can have a different spatial response and each has its characteristic spectral response. A forward model is built which includes the shift invariant spatial broadening of the input for the channels and the shift variant spectral response across channels. The model is applied to the calibrated airborne multispectral scanner as well as the airborne terrestrial applications sensor developed at NASA Stennis Space Center.

Spatial distribution and temporal variability of arsenic in irrigated rice fields in Bangladesh. 2. Paddy soil.

PubMed

Dittmar, Jessica; Voegelin, Andreas; Roberts, Linda C; Hug, Stephan J; Saha, Ganesh C; Ali, M Ashraf; Badruzzaman, A Borhan M; Kretzschmar, Ruben

2007-09-01

Arsenic-rich groundwater from shallow tube wells is widely used for the irrigation of boro rice in Bangladesh and West Bengal. In the long term this may lead to the accumulation of As in paddy soils and potentially have adverse effects on rice yield and quality. In the companion article in this issue, we have shown that As input into paddy fields with irrigation water is laterally heterogeneous. To assess the potential for As accumulation in soil, we investigated the lateral and vertical distribution of As in rice field soils near Sreenagar (Munshiganj, Bangladesh) and its changes over a 1 year cycle of irrigation and monsoon flooding. At the study site, 18 paddy fields are irrigated with water from a shallow tube well containing 397 +/- 7 microg L(-1) As. The analysis of soil samples collected before irrigation in December 2004 showed that soil As concentrations in paddy fields did not depend on the length of the irrigation channel between well and field inlet. Within individual fields, however, soil As contents decreased with increasing distance to the water inlet, leading to highly variable topsoil As contents (11-35 mg kg(-1), 0-10 cm). Soil As contents after irrigation (May 2005) showed that most As input occurred close to the water inlet and that most As was retained in the top few centimeters of soil. After monsoon flooding (December 2005), topsoil As contents were again close to levels measured before irrigation. Thus, As input during irrigation was at least partly counteracted by As mobilization during monsoon flooding. However, the persisting lateral As distribution suggests net arsenic accumulation over the past 15 years. More pronounced As accumulation may occur in regions with several rice crops per year, less intense monsoon flooding, or different irrigation schemes. The high lateral and vertical heterogeneity of soil As contents must be taken into account in future studies related to As accumulation in paddy soils and potential As transfer into rice.