Sample records for variability spatial variability

  1. Spatial Variability of Snowpack Properties On Small Slopes

    NASA Astrophysics Data System (ADS)

    Pielmeier, C.; Kronholm, K.; Schneebeli, M.; Schweizer, J.

    The spatial variability of alpine snowpacks is created by a variety of parameters like deposition, wind erosion, sublimation, melting, temperature, radiation and metamor- phism of the snow. Spatial variability is thought to strongly control the avalanche initi- ation and failure propagation processes. Local snowpack measurements are currently the basis for avalanche warning services and there exist contradicting hypotheses about the spatial continuity of avalanche active snow layers and interfaces. Very little about the spatial variability of the snowpack is known so far, therefore we have devel- oped a systematic and objective method to measure the spatial variability of snowpack properties, layering and its relation to stability. For a complete coverage, the analysis of the spatial variability has to entail all scales from mm to km. In this study the small to medium scale spatial variability is investigated, i.e. the range from centimeters to tenths of meters. During the winter 2000/2001 we took systematic measurements in lines and grids on a flat snow test field with grid distances from 5 cm to 0.5 m. Fur- thermore, we measured systematic grids with grid distances between 0.5 m and 2 m in undisturbed flat fields and on small slopes above the tree line at the Choerbschhorn, in the region of Davos, Switzerland. On 13 days we measured the spatial pattern of the snowpack stratigraphy with more than 110 snow micro penetrometer measure- ments at slopes and flat fields. Within this measuring grid we placed 1 rutschblock and 12 stuffblock tests to measure the stability of the snowpack. With the large num- ber of measurements we are able to use geostatistical methods to analyse the spatial variability of the snowpack. Typical correlation lengths are calculated from semivari- ograms. Discerning the systematic trends from random spatial variability is analysed using statistical models. Scale dependencies are shown and recurring scaling patterns are outlined. The importance

  2. Measuring spatial variability in soil characteristics

    DOEpatents

    Hoskinson, Reed L.; Svoboda, John M.; Sawyer, J. Wayne; Hess, John R.; Hess, J. Richard

    2002-01-01

    The present invention provides systems and methods for measuring a load force associated with pulling a farm implement through soil that is used to generate a spatially variable map that represents the spatial variability of the physical characteristics of the soil. An instrumented hitch pin configured to measure a load force is provided that measures the load force generated by a farm implement when the farm implement is connected with a tractor and pulled through or across soil. Each time a load force is measured, a global positioning system identifies the location of the measurement. This data is stored and analyzed to generate a spatially variable map of the soil. This map is representative of the physical characteristics of the soil, which are inferred from the magnitude of the load force.

  3. Characterization of the spatial variability of channel morphology

    USGS Publications Warehouse

    Moody, J.A.; Troutman, B.M.

    2002-01-01

    The spatial variability of two fundamental morphological variables is investigated for rivers having a wide range of discharge (five orders of magnitude). The variables, water-surface width and average depth, were measured at 58 to 888 equally spaced cross-sections in channel links (river reaches between major tributaries). These measurements provide data to characterize the two-dimensional structure of a channel link which is the fundamental unit of a channel network. The morphological variables have nearly log-normal probability distributions. A general relation was determined which relates the means of the log-transformed variables to the logarithm of discharge similar to previously published downstream hydraulic geometry relations. The spatial variability of the variables is described by two properties: (1) the coefficient of variation which was nearly constant (0.13-0.42) over a wide range of discharge; and (2) the integral length scale in the downstream direction which was approximately equal to one to two mean channel widths. The joint probability distribution of the morphological variables in the downstream direction was modelled as a first-order, bivariate autoregressive process. This model accounted for up to 76 per cent of the total variance. The two-dimensional morphological variables can be scaled such that the channel width-depth process is independent of discharge. The scaling properties will be valuable to modellers of both basin and channel dynamics. Published in 2002 John Wiley and Sons, Ltd.

  4. Spatial variability in plankton biomass and hydrographic variables along an axial transect in Chesapeake Bay

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Roman, M.; Kimmel, D.; McGilliard, C.; Boicourt, W.

    2006-05-01

    High-resolution, axial sampling surveys were conducted in Chesapeake Bay during April, July, and October from 1996 to 2000 using a towed sampling device equipped with sensors for depth, temperature, conductivity, oxygen, fluorescence, and an optical plankton counter (OPC). The results suggest that the axial distribution and variability of hydrographic and biological parameters in Chesapeake Bay were primarily influenced by the source and magnitude of freshwater input. Bay-wide spatial trends in the water column-averaged values of salinity were linear functions of distance from the main source of freshwater, the Susquehanna River, at the head of the bay. However, spatial trends in the water column-averaged values of temperature, dissolved oxygen, chlorophyll-a and zooplankton biomass were nonlinear along the axis of the bay. Autocorrelation analysis and the residuals of linear and quadratic regressions between each variable and latitude were used to quantify the patch sizes for each axial transect. The patch sizes of each variable depended on whether the data were detrended, and the detrending techniques applied. However, the patch size of each variable was generally larger using the original data compared to the detrended data. The patch sizes of salinity were larger than those for dissolved oxygen, chlorophyll-a and zooplankton biomass, suggesting that more localized processes influence the production and consumption of plankton. This high-resolution quantification of the zooplankton spatial variability and patch size can be used for more realistic assessments of the zooplankton forage base for larval fish species.

  5. How does spatial variability of climate affect catchment streamflow predictions?

    EPA Science Inventory

    Spatial variability of climate can negatively affect catchment streamflow predictions if it is not explicitly accounted for in hydrologic models. In this paper, we examine the changes in streamflow predictability when a hydrologic model is run with spatially variable (distribute...

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

    NASA Astrophysics Data System (ADS)

    Berne, A.; Jaffrain, J.

    2010-12-01

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

  7. One perspective on spatial variability in geologic mapping

    USGS Publications Warehouse

    Markewich, H.W.; Cooper, S.C.

    1991-01-01

    This paper discusses some of the differences between geologic mapping and soil mapping, and how the resultant maps are interpreted. The role of spatial variability in geologic mapping is addressed only indirectly because in geologic mapping there have been few attempts at quantification of spatial differences. This is largely because geologic maps deal with temporal as well as spatial variability and consider time, age, and origin, as well as composition and geometry. Both soil scientists and geologists use spatial variability to delineate mappable units; however, the classification systems from which these mappable units are defined differ greatly. Mappable soil units are derived from systematic, well-defined, highly structured sets of taxonomic criteria; whereas mappable geologic units are based on a more arbitrary heirarchy of categories that integrate many features without strict values or definitions. Soil taxonomy is a sorting tool used to reduce heterogeneity between soil units. Thus at the series level, soils in any one series are relatively homogeneous because their range of properties is small and well-defined. Soil maps show the distribution of soils on the land surface. Within a map area, soils, which are often less than 2 m thick, show a direct correlation to topography and to active surface processes as well as to parent material.

  8. Sparse modeling of spatial environmental variables associated with asthma

    PubMed Central

    Chang, Timothy S.; Gangnon, Ronald E.; Page, C. David; Buckingham, William R.; Tandias, Aman; Cowan, Kelly J.; Tomasallo, Carrie D.; Arndt, Brian G.; Hanrahan, Lawrence P.; Guilbert, Theresa W.

    2014-01-01

    Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin’s Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5–50 years over a three-year period. Each patient’s home address was geocoded to one of 3,456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin’s geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. PMID:25533437

  9. Spatial and temporal variability of interhemispheric transport times

    NASA Astrophysics Data System (ADS)

    Wu, Xiaokang; Yang, Huang; Waugh, Darryn W.; Orbe, Clara; Tilmes, Simone; Lamarque, Jean-Francois

    2018-05-01

    The seasonal and interannual variability of transport times from the northern midlatitude surface into the Southern Hemisphere is examined using simulations of three idealized age tracers: an ideal age tracer that yields the mean transit time from northern midlatitudes and two tracers with uniform 50- and 5-day decay. For all tracers the largest seasonal and interannual variability occurs near the surface within the tropics and is generally closely coupled to movement of the Intertropical Convergence Zone (ITCZ). There are, however, notable differences in variability between the different tracers. The largest seasonal and interannual variability in the mean age is generally confined to latitudes spanning the ITCZ, with very weak variability in the southern extratropics. In contrast, for tracers subject to spatially uniform exponential loss the peak variability tends to be south of the ITCZ, and there is a smaller contrast between tropical and extratropical variability. These differences in variability occur because the distribution of transit times from northern midlatitudes is very broad and tracers with more rapid loss are more sensitive to changes in fast transit times than the mean age tracer. These simulations suggest that the seasonal-interannual variability in the southern extratropics of trace gases with predominantly NH midlatitude sources may differ depending on the gases' chemical lifetimes.

  10. Sparse modeling of spatial environmental variables associated with asthma.

    PubMed

    Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W

    2015-02-01

    Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.

  11. Dissecting the multi-scale spatial relationship of earthworm assemblages with soil environmental variability.

    PubMed

    Jiménez, Juan J; Decaëns, Thibaud; Lavelle, Patrick; Rossi, Jean-Pierre

    2014-12-05

    Studying the drivers and determinants of species, population and community spatial patterns is central to ecology. The observed structure of community assemblages is the result of deterministic abiotic (environmental constraints) and biotic factors (positive and negative species interactions), as well as stochastic colonization events (historical contingency). We analyzed the role of multi-scale spatial component of soil environmental variability in structuring earthworm assemblages in a gallery forest from the Colombian "Llanos". We aimed to disentangle the spatial scales at which species assemblages are structured and determine whether these scales matched those expressed by soil environmental variables. We also tested the hypothesis of the "single tree effect" by exploring the spatial relationships between root-related variables and soil nutrient and physical variables in structuring earthworm assemblages. Multivariate ordination techniques and spatially explicit tools were used, namely cross-correlograms, Principal Coordinates of Neighbor Matrices (PCNM) and variation partitioning analyses. The relationship between the spatial organization of earthworm assemblages and soil environmental parameters revealed explicitly multi-scale responses. The soil environmental variables that explained nested population structures across the multi-spatial scale gradient differed for earthworms and assemblages at the very-fine- (<10 m) to medium-scale (10-20 m). The root traits were correlated with areas of high soil nutrient contents at a depth of 0-5 cm. Information on the scales of PCNM variables was obtained using variogram modeling. Based on the size of the plot, the PCNM variables were arbitrarily allocated to medium (>30 m), fine (10-20 m) and very fine scales (<10 m). Variation partitioning analysis revealed that the soil environmental variability explained from less than 1% to as much as 48% of the observed earthworm spatial variation. A large proportion of the

  12. Spatial Variability of Dissolved Organic Carbon in Headwater Wetlands in Central Pennsylvania

    NASA Astrophysics Data System (ADS)

    Reichert-Eberhardt, A. J.; Wardrop, D.; Boyer, E. W.

    2011-12-01

    Dissolved organic carbon (DOC) is known to be of an important factor in many microbially mediated biochemical processes, such as denitrification, that occur in wetlands. The spatial variability of DOC within a wetland could impact the microbes that fuel these processes, which in turn can affect the ecosystem services provided by wetlands. However, the amount of spatial variability of DOC in wetlands is generally unknown. Furthermore, it is unknown how disturbance to wetlands can affect spatial variability of DOC. Previous research in central Pennsylvania headwater wetland soils has shown that wetlands with increased human disturbance had decreased heterogeneity in soil biochemistry. To address groundwater chemical variability 20 monitoring wells were installed in a random pattern in a 400 meter squared plot in a low-disturbance headwater wetland and a high-disturbance headwater wetland in central Pennsylvania. Water samples from these wells will be analyzed for DOC, dissolved inorganic carbon, nitrate, ammonia, and sulfate concentrations, as well as pH, conductivity, and temperature on a seasonal basis. It is hypothesized that there will be greater spatial variability of groundwater chemistry in the low disturbance wetland than the high disturbance wetland. This poster will present the initial data concerning DOC spatial variability in both the low and high impact headwater wetlands.

  13. Spatial and temporal variability of lightings over Greece

    NASA Astrophysics Data System (ADS)

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

    2010-09-01

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

  14. Quantifying and mapping spatial variability in simulated forest plots

    Treesearch

    Gavin R. Corral; Harold E. Burkhart

    2016-01-01

    We used computer simulations to test the efficacy of multivariate statistical methods to detect, quantify, and map spatial variability of forest stands. Simulated stands were developed of regularly-spaced plantations of loblolly pine (Pinus taeda L.). We assumed no affects of competition or mortality, but random variability was added to individual tree characteristics...

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

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

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

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

  16. Impact of rainfall spatial variability on Flash Flood Forecasting

    NASA Astrophysics Data System (ADS)

    Douinot, Audrey; Roux, Hélène; Garambois, Pierre-André; Larnier, Kevin

    2014-05-01

    According to the United States National Hazard Statistics database, flooding and flash flooding have caused the largest number of deaths of any weather-related phenomenon over the last 30 years (Flash Flood Guidance Improvement Team, 2003). Like the storms that cause them, flash floods are very variable and non-linear phenomena in time and space, with the result that understanding and anticipating flash flood genesis is far from straightforward. In the U.S., the Flash Flood Guidance (FFG) estimates the average number of inches of rainfall for given durations required to produce flash flooding in the indicated county. In Europe, flash flood often occurred on small catchments (approximately 100 km2) and it has been shown that the spatial variability of rainfall has a great impact on the catchment response (Le Lay and Saulnier, 2007). Therefore, in this study, based on the Flash flood Guidance method, rainfall spatial variability information is introduced in the threshold estimation. As for FFG, the threshold is the number of millimeters of rainfall required to produce a discharge higher than the discharge corresponding to the first level (yellow) warning of the French flood warning service (SCHAPI: Service Central d'Hydrométéorologie et d'Appui à la Prévision des Inondations). The indexes δ1 and δ2 of Zoccatelli et al. (2010), based on the spatial moments of catchment rainfall, are used to characterize the rainfall spatial distribution. Rainfall spatial variability impacts on warning threshold and on hydrological processes are then studied. The spatially distributed hydrological model MARINE (Roux et al., 2011), dedicated to flash flood prediction is forced with synthetic rainfall patterns of different spatial distributions. This allows the determination of a warning threshold diagram: knowing the spatial distribution of the rainfall forecast and therefore the 2 indexes δ1 and δ2, the threshold value is read on the diagram. A warning threshold diagram is

  17. Impacts of rainfall spatial variability on hydrogeological response

    NASA Astrophysics Data System (ADS)

    Sapriza-Azuri, Gonzalo; Jódar, Jorge; Navarro, Vicente; Slooten, Luit Jan; Carrera, Jesús; Gupta, Hoshin V.

    2015-02-01

    There is currently no general consensus on how the spatial variability of rainfall impacts and propagates through complex hydrogeological systems. Most studies to date have focused on the effects of rainfall spatial variability (RSV) on river discharge, while paying little attention to other important aspects of system response. Here, we study the impacts of RSV on several responses of a hydrological model of an overexploited system. To this end, we drive a spatially distributed hydrogeological model for the semiarid Upper Guadiana basin in central Spain with stochastic daily rainfall fields defined at three different spatial resolutions (fine → 2.5 km × 2.5 km, medium → 50 km × 50 km, large → lumped). This enables us to investigate how (i) RSV at different spatial resolutions, and (ii) rainfall uncertainty, are propagated through the hydrogeological model of the system. Our results demonstrate that RSV has a significant impact on the modeled response of the system, by specifically affecting groundwater recharge and runoff generation, and thereby propagating through to various other related hydrological responses (river discharge, river-aquifer exchange, groundwater levels). These results call into question the validity of management decisions made using hydrological models calibrated or forced with spatially lumped rainfall.

  18. Quantitative analysis of spatial variability of geotechnical parameters

    NASA Astrophysics Data System (ADS)

    Fang, Xing

    2018-04-01

    Geotechnical parameters are the basic parameters of geotechnical engineering design, while the geotechnical parameters have strong regional characteristics. At the same time, the spatial variability of geotechnical parameters has been recognized. It is gradually introduced into the reliability analysis of geotechnical engineering. Based on the statistical theory of geostatistical spatial information, the spatial variability of geotechnical parameters is quantitatively analyzed. At the same time, the evaluation of geotechnical parameters and the correlation coefficient between geotechnical parameters are calculated. A residential district of Tianjin Survey Institute was selected as the research object. There are 68 boreholes in this area and 9 layers of mechanical stratification. The parameters are water content, natural gravity, void ratio, liquid limit, plasticity index, liquidity index, compressibility coefficient, compressive modulus, internal friction angle, cohesion and SP index. According to the principle of statistical correlation, the correlation coefficient of geotechnical parameters is calculated. According to the correlation coefficient, the law of geotechnical parameters is obtained.

  19. Simulating maize yield and biomass with spatial variability of soil field capacity

    USDA-ARS?s Scientific Manuscript database

    Spatial variability in field soil water and other properties is a challenge for system modelers who use only representative values for model inputs, rather than their distributions. In this study, we compared simulation results from a calibrated model with spatial variability of soil field capacity ...

  20. Spatial variability versus parameter uncertainty in freshwater fate and exposure factors of chemicals.

    PubMed

    Nijhof, Carl O P; Huijbregts, Mark A J; Golsteijn, Laura; van Zelm, Rosalie

    2016-04-01

    We compared the influence of spatial variability in environmental characteristics and the uncertainty in measured substance properties of seven chemicals on freshwater fate factors (FFs), representing the residence time in the freshwater environment, and on exposure factors (XFs), representing the dissolved fraction of a chemical. The influence of spatial variability was quantified using the SimpleBox model in which Europe was divided in 100 × 100 km regions, nested in a regional (300 × 300 km) and supra-regional (500 × 500 km) scale. Uncertainty in substance properties was quantified by means of probabilistic modelling. Spatial variability and parameter uncertainty were expressed by the ratio k of the 95%ile and 5%ile of the FF and XF. Our analysis shows that spatial variability ranges in FFs of persistent chemicals that partition predominantly into one environmental compartment was up to 2 orders of magnitude larger compared to uncertainty. For the other (less persistent) chemicals, uncertainty in the FF was up to 1 order of magnitude larger than spatial variability. Variability and uncertainty in freshwater XFs of the seven chemicals was negligible (k < 1.5). We found that, depending on the chemical and emission scenario, accounting for region-specific environmental characteristics in multimedia fate modelling, as well as accounting for parameter uncertainty, can have a significant influence on freshwater fate factor predictions. Therefore, we conclude that it is important that fate factors should not only account for parameter uncertainty, but for spatial variability as well, as this further increases the reliability of ecotoxicological impacts in LCA. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

  2. 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

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

    PubMed Central

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

    2016-01-01

    India’s agricultural output, economy, and societal well-being are strappingly dependent on the stability of summer monsoon rainfall, its variability and extremes. Spatial aggregate of intensity and frequency of extreme rainfall events over Central India are significantly increasing, while at local scale they are spatially non-uniform with increasing spatial variability. The reasons behind such increase in spatial variability of extremes are poorly understood and the trends in mean monsoon rainfall have been greatly overlooked. Here, by using multi-decadal gridded daily rainfall data over entire India, we show that the trend in spatial variability of mean monsoon rainfall is decreasing as exactly opposite to that of extremes. The spatial variability of extremes is attributed to the spatial variability of the convective rainfall component. Contrarily, the decrease in spatial variability of the mean rainfall over India poses a pertinent research question on the applicability of large scale inter-basin water transfer by river inter-linking to address the spatial variability of available water in India. We found a significant decrease in the monsoon rainfall over major water surplus river basins in India. Hydrological simulations using a Variable Infiltration Capacity (VIC) model also revealed that the water yield in surplus river basins is decreasing but it is increasing in deficit basins. These findings contradict the traditional notion of dry areas becoming drier and wet areas becoming wetter in response to climate change in India. This result also calls for a re-evaluation of planning for river inter-linking to supply water from surplus to deficit river basins. PMID:27463092

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

    PubMed

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

    2016-01-01

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

  5. The effect of short-range spatial variability on soil sampling uncertainty.

    PubMed

    Van der Perk, Marcel; de Zorzi, Paolo; Barbizzi, Sabrina; Belli, Maria; Fajgelj, Ales; Sansone, Umberto; Jeran, Zvonka; Jaćimović, Radojko

    2008-11-01

    This paper aims to quantify the soil sampling uncertainty arising from the short-range spatial variability of elemental concentrations in the topsoils of agricultural, semi-natural, and contaminated environments. For the agricultural site, the relative standard sampling uncertainty ranges between 1% and 5.5%. For the semi-natural area, the sampling uncertainties are 2-4 times larger than in the agricultural area. The contaminated site exhibited significant short-range spatial variability in elemental composition, which resulted in sampling uncertainties of 20-30%.

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  7. Shifts of environmental and phytoplankton variables in a regulated river: A spatial-driven analysis.

    PubMed

    Sabater-Liesa, Laia; Ginebreda, Antoni; Barceló, Damià

    2018-06-18

    The longitudinal structure of the environmental and phytoplankton variables was investigated in the Ebro River (NE Spain), which is heavily affected by water abstraction and regulation. A first exploration indicated that the phytoplankton community did not resist the impact of reservoirs and barely recovered downstream of them. The spatial analysis showed that the responses of the phytoplankton and environmental variables were not uniform. The two set of variables revealed spatial variability discontinuities and river fragmentation upstream and downstream from the reservoirs. Reservoirs caused the replacement of spatially heterogeneous habitats by homogeneous spatially distributed water bodies, these new environmental conditions downstream benefiting the opportunist and cosmopolitan algal taxa. The application of a spatial auto-regression model to algal biomass (chlorophyll-a) permitted to capture the relevance and contribution of extra-local influences in the river ecosystem. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

  8. Three dimensional simulation of spatial and temporal variability of stratospheric hydrogen chloride

    NASA Technical Reports Server (NTRS)

    Kaye, Jack A.; Rood, Richard B.; Jackman, Charles H.; Allen, Dale J.; Larson, Edmund M.

    1989-01-01

    Spatial and temporal variability of atmospheric HCl columns are calculated for January 1979 using a three-dimensional chemistry-transport model designed to provide the best possible representation of stratospheric transport. Large spatial and temporal variability of the HCl columns is shown to be correlated with lower stratospheric potential vorticity and thus to be of dynamical origin. Systematic longitudinal structure is correlated with planetary wave structure. These results can help place spatially and temporally isolated column and profile measurements in a regional and/or global perspective.

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

    PubMed

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

    2015-01-06

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

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

    USGS Publications Warehouse

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

    2015-01-01

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

  11. Probabilistic and spatially variable niches inferred from demography

    Treesearch

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

    2014-01-01

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

  12. Directional semivariogram analysis to identify and rank controls on the spatial variability of fracture networks

    NASA Astrophysics Data System (ADS)

    Hanke, John R.; Fischer, Mark P.; Pollyea, Ryan M.

    2018-03-01

    In this study, the directional semivariogram is deployed to investigate the spatial variability of map-scale fracture network attributes in the Paradox Basin, Utah. The relative variability ratio (R) is introduced as the ratio of integrated anisotropic semivariogram models, and R is shown to be an effective metric for quantifying the magnitude of spatial variability for any two azimuthal directions. R is applied to a GIS-based data set comprising roughly 1200 fractures, in an area which is bounded by a map-scale anticline and a km-scale normal fault. This analysis reveals that proximity to the fault strongly influences the magnitude of spatial variability for both fracture intensity and intersection density within 1-2 km. Additionally, there is significant anisotropy in the spatial variability, which is correlated with trends of the anticline and fault. The direction of minimum spatial correlation is normal to the fault at proximal distances, and gradually rotates and becomes subparallel to the fold axis over the same 1-2 km distance away from the fault. We interpret these changes to reflect varying scales of influence of the fault and the fold on fracture network development: the fault locally influences the magnitude and variability of fracture network attributes, whereas the fold sets the background level and structure of directional variability.

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

    NASA Astrophysics Data System (ADS)

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

    2017-11-01

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

  14. Temporal and spatial variability in North Carolina piedmont stream temperature

    Treesearch

    J.L. Boggs; G. Sun; S.G. McNulty; W. Swartley; Treasure E.; W. Summer

    2009-01-01

    Understanding temporal and spatial patterns of in-stream temperature can provide useful information to managing future impacts of climate change on these systems. This study will compare temporal patterns and spatial variability of headwater in-stream temperature in six catchments in the piedmont of North Carolina in two different geological regions, Carolina slate...

  15. Comparison of spatial variability in visible and near-infrared spectral images

    USGS Publications Warehouse

    Chavez, P.S.

    1992-01-01

    The visible and near-infrared bands of the Landsat Thematic Mapper (TM) and the Satellite Pour l'Observation de la Terre (SPOT) were analyzed to determine which band contained more spatial variability. It is important for applications that require spatial information, such as those dealing with mapping linear features and automatic image-to-image correlation, to know which spectral band image should be used. Statistical and visual analyses were used in the project. The amount of variance in an 11 by 11 pixel spatial filter and in the first difference at the six spacings of 1, 5, 11, 23, 47, and 95 pixels was computed for the visible and near-infrared bands. The results indicate that the near-infrared band has more spatial variability than the visible band, especially in images covering densely vegetated areas. -Author

  16. Effect of Variable Spatial Scales on USLE-GIS Computations

    NASA Astrophysics Data System (ADS)

    Patil, R. J.; Sharma, S. K.

    2017-12-01

    Use of appropriate spatial scale is very important in Universal Soil Loss Equation (USLE) based spatially distributed soil erosion modelling. This study aimed at assessment of annual rates of soil erosion at different spatial scales/grid sizes and analysing how changes in spatial scales affect USLE-GIS computations using simulation and statistical variabilities. Efforts have been made in this study to recommend an optimum spatial scale for further USLE-GIS computations for management and planning in the study area. The present research study was conducted in Shakkar River watershed, situated in Narsinghpur and Chhindwara districts of Madhya Pradesh, India. Remote Sensing and GIS techniques were integrated with Universal Soil Loss Equation (USLE) to predict spatial distribution of soil erosion in the study area at four different spatial scales viz; 30 m, 50 m, 100 m, and 200 m. Rainfall data, soil map, digital elevation model (DEM) and an executable C++ program, and satellite image of the area were used for preparation of the thematic maps for various USLE factors. Annual rates of soil erosion were estimated for 15 years (1992 to 2006) at four different grid sizes. The statistical analysis of four estimated datasets showed that sediment loss dataset at 30 m spatial scale has a minimum standard deviation (2.16), variance (4.68), percent deviation from observed values (2.68 - 18.91 %), and highest coefficient of determination (R2 = 0.874) among all the four datasets. Thus, it is recommended to adopt this spatial scale for USLE-GIS computations in the study area due to its minimum statistical variability and better agreement with the observed sediment loss data. This study also indicates large scope for use of finer spatial scales in spatially distributed soil erosion modelling.

  17. On the spatial decorrelation of stochastic solar resource variability at long timescales

    DOE PAGES

    Perez, Marc J. R.; Fthenakis, Vasilis M.

    2015-05-16

    Understanding the spatial and temporal characteristics of solar resource variability is important because it helps inform the discussion surrounding the merits of geographic dispersion and subsequent electrical interconnection of photovoltaics as part of a portfolio of future solutions for coping with this variability. The unpredictable resource variability arising from the stochastic nature of meteorological phenomena (from the passage of clouds to the movement of weather systems) is of most concern for achieving high PV penetration because unlike the passage of seasons or the shift from day to night, the uncertainty makes planning a challenge. A suitable proxy for unpredictable solarmore » resource variability at any given location is the series of variations in the clearness index from one time period to the next because the clearness index is largely independent of the predictable influence of solar geometry. At timescales shorter than one day, the correlation between these variations in clearness index at pairs of distinct geographic locations decreases with spatial extent and with timescale. As the aggregate variability across N decorrelated locations decreases as 1/√N, identifying the distance required to achieve this decorrelation is critical to quantifying the expected reduction in variability from geographic dispersion.« less

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

    USGS Publications Warehouse

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

    2010-01-01

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

  19. Can APEX Represent In-Field Spatial Variability and Simulate Its Effects On Crop Yields?

    USDA-ARS?s Scientific Manuscript database

    Precision agriculture, from variable rate nitrogen application to precision irrigation, promises improved management of resources by considering the spatial variability of topography and soil properties. Hydrologic models need to simulate the effects of this variability if they are to inform about t...

  20. Effects of spatial variability of soil hydraulic properties on water dynamics

    NASA Astrophysics Data System (ADS)

    Gumiere, Silvio Jose; Caron, Jean; Périard, Yann; Lafond, Jonathan

    2013-04-01

    Soil hydraulic properties may present spatial variability and dependence at the scale of watersheds or fields even in man-made single soil structures, such as cranberry fields. The saturated hydraulic conductivity (Ksat) and soil moisture curves were measured at two depths for three cranberry fields (about 2 ha) at three different sites near Québec city, Canada. Two of the three studied fields indicate strong spatial dependence for Ksat values and soil moisture curves both in horizontal and vertical directions. In the summer of 2012, the three fields were equipped with 55 tensiometers installed at a depth of 0.10 m in a regular grid. About 20 mm of irrigation water were applied uniformly by aspersion to the fields, raising soil water content to near saturation condition. Soil water tension was measured once every hour during seven days. Geostatistical techniques such as co-kriging and cross-correlograms estimations were used to investigate the spatial dependence between variables. The results show that soil tension varied faster in high Ksat zones than in low Ksatones in the cranberry fields. These results indicate that soil water dynamic is strongly affected by the variability of saturated soil hydraulic conductivity, even in a supposed homogenous anthropogenic soil. This information may have a strong impact in irrigation management and subsurface drainage efficiency as well as other water conservation issues. Future work will involve 3D numerical modeling of the field water dynamics with HYDRUS software. The anticipated outcome will provide valuable information for the understanding of the effect of spatial variability of soil hydraulic properties on soil water dynamics and its relationship with crop production and water conservation.

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

  2. Spatial variability of specific surface area of arable soils in Poland

    NASA Astrophysics Data System (ADS)

    Sokolowski, S.; Sokolowska, Z.; Usowicz, B.

    2012-04-01

    Evaluation of soil spatial variability is an important issue in agrophysics and in environmental research. Knowledge of spatial variability of physico-chemical properties enables a better understanding of several processes that take place in soils. In particular, it is well known that mineralogical, organic, as well as particle-size compositions of soils vary in a wide range. Specific surface area of soils is one of the most significant characteristics of soils. It can be not only related to the type of soil, mainly to the content of clay, but also largely determines several physical and chemical properties of soils and is often used as a controlling factor in numerous biological processes. Knowledge of the specific surface area is necessary in calculating certain basic soil characteristics, such as the dielectric permeability of soil, water retention curve, water transport in the soil, cation exchange capacity and pesticide adsorption. The aim of the present study is two-fold. First, we carry out recognition of soil total specific surface area patterns in the territory of Poland and perform the investigation of features of its spatial variability. Next, semivariograms and fractal analysis are used to characterize and compare the spatial variability of soil specific surface area in two soil horizons (A and B). Specific surface area of about 1000 samples was determined by analyzing water vapor adsorption isotherms via the BET method. The collected data of the values of specific surface area of mineral soil representatives for the territory of Poland were then used to describe its spatial variability by employing geostatistical techniques and fractal theory. Using the data calculated for some selected points within the entire territory and along selected directions, the values of semivariance were determined. The slope of the regression line of the log-log plot of semi-variance versus the distance was used to estimate the fractal dimension, D. Specific surface area

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

    NASA Astrophysics Data System (ADS)

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

    2017-09-01

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

  4. Spatial and temporal variability in rates of landsliding in seismically active mountain ranges

    NASA Astrophysics Data System (ADS)

    Parker, R.; Petley, D.; Rosser, N.; Densmore, A.; Gunasekera, R.; Brain, M.

    2012-04-01

    Where earthquake and precipitation driven disasters occur in steep, mountainous regions, landslides often account for a large proportion of the associated damage and losses. This research addresses spatial and temporal variability in rates of landslide occurrence in seismically active mountain ranges as a step towards developing better regional scale prediction of losses in such events. In the first part of this paper we attempt to explain reductively the variability in spatial rates of landslide occurrence, using data from five major earthquakes. This is achieved by fitting a regression-based conditional probability model to spatial probabilities of landslide occurrence, using as predictor variables proxies for spatial patterns of seismic ground motion and modelled hillslope stability. A combined model for all earthquakes performs well in hindcasting spatial probabilities of landslide occurrence as a function of readily-attainable spatial variables. We present validation of the model and demonstrate the extent to which it may be applied globally to derive landslide probabilities for future earthquakes. In part two we examine the temporal behaviour of rates of landslide occurrence. This is achieved through numerical modelling to simulate the behaviour of a hypothetical landscape. The model landscape is composed of hillslopes that continually weaken, fail and reset in response to temporally-discrete forcing events that represent earthquakes. Hillslopes with different geometries require different amounts of weakening to fail, such that they fail and reset at different temporal rates. Our results suggest that probabilities of landslide occurrence are not temporally constant, but rather vary with time, irrespective of changes in forcing event magnitudes or environmental conditions. Various parameters influencing the magnitude and temporal patterns of this variability are identified, highlighting areas where future research is needed. This model has important

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

    NASA Astrophysics Data System (ADS)

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

    2017-10-01

    Empirical Orthogonal Function (EOF), wavelet, and wavelet coherence analysis of baseflow time-series from 126 streamgauges (record-length > 50 years; small and mid-size watersheds) in the US South Atlantic (USSA) region reveal three principal modes of space-time variability: (1) a region-wide dominant mode tied to annual precipitation that exhibits non-stationary decadal variability after the mid 1990s concurrent with the warming of the AMO (Atlantic Multidecadal Oscillation); (2) two spatial modes, east and west of the Blue Ridge, exhibiting nonstationary seasonal to sub-decadal variability before and after 1990 attributed to complex nonlinear interactions between ENSO and AMO impacting precipitation and recharge; and (3) deep (decadal) and shallow (< 6 years) space-time modes of groundwater variability separating basins with high and low annual mean baseflow fraction (MBF) by physiographic region. The results explain the propagation of multiscale climate variability into the regional groundwater system through recharge modulated by topography, geomorphology, and geology to determine the spatial organization of baseflow variability at decadal (and longer) time-scales, that is, deep hydrologic drought. Further, these findings suggest potential for long-range predictability of hydrological drought in small and mid-size watersheds, where baseflow is a robust indicator of nonstationary yield capacity of the underlying groundwater basins. Predictive associations between climate mode indices and deep baseflow (e.g. persistent decreases of the decadal-scale components of baseflow during the cold phase of the AMO in the USSA) can be instrumental toward improving forecast lead-times and long-range mitigation of severe drought.

  6. Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas - a review

    NASA Astrophysics Data System (ADS)

    Cristiano, Elena; ten Veldhuis, Marie-claire; van de Giesen, Nick

    2017-07-01

    In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological response, based on small-scale representation of urban catchment spatial variability. Despite these efforts, interactions between rainfall variability, catchment heterogeneity, and hydrological response remain poorly understood. This paper presents a review of our current understanding of hydrological processes in urban environments as reported in the literature, focusing on their spatial and temporal variability aspects. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge needs to be further developed to improve our understanding of and capability to predict urban hydrological response.

  7. Variability of Soil Temperature: A Spatial and Temporal Analysis.

    ERIC Educational Resources Information Center

    Walsh, Stephen J.; And Others

    1991-01-01

    Discusses an analysis of the relationship of soil temperatures at 3 depths to various climatic variables along a 200-kilometer transect in west-central Oklahoma. Reports that temperature readings increased from east to west. Concludes that temperature variations were explained by a combination of spatial, temporal, and biophysical factors. (SG)

  8. High spatial variability of carbon dioxide and methane emission in three tropical reservoirs

    NASA Astrophysics Data System (ADS)

    Reinaldo Paranaiba, José; Barros, Nathan O.; Mendonça, Raquel F.; Linkhorst, Annika; Isidorova, Anastasija; Roland, Fabio; Sobek, Sebastian

    2017-04-01

    In the tropics, many new large hydropower dams are being built, in order to produce renewable energy for economic growth. Most inland waters, such as rivers, lakes and reservoirs, emit greenhouse gases to the atmosphere, and especially tropical reservoirs have been pointed out as strong sources of methane. However, present estimates of greenhouse gas emission from reservoirs are limited by the amount of available data. In particular, the spatial variability of greenhouse gas emission from reservoirs is insufficiently understood. In order to test the hypothesis that the diffusive emission of carbon dioxide (CO2) and methane (CH4) from tropical reservoirs is characterized by strong spatial variability and incorrectly represented by measurements at one site only, we studied three reservoirs situated in different tropical climates, during the dry period. We conducted spatially resolved measurements of surface water concentrations of dissolved carbon dioxide and methane using an on-line equilibration system, as well as of the gas exchange velocity using floating chambers. We found pronounced spatial variability of diffusive CO2 and CH4 emission in all three reservoirs. River inflow areas were more likely to have high concentrations of particularly CH4, but also CO2, than other areas in the reservoirs. Close to the dam, CH4 concentrations were comparatively low in each reservoir. The variability of CH4 concentration was linked to geographical position, which we ascribe to hot spots of methanogenesis at sites of high sediment deposition, such as river inflow areas. The variability of CO2 concentration seemed instead rather to be linked to in-situ metabolism. Also the gas exchange velocity varied pronouncedly in each reservoir, but without any detectable systematic patterns, calling for further studies. We conclude that accurate upscaling of reservoir greenhouse gas emissions requires accounting for within-reservoir spatial variability, and that the anthropogenic increase

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

    Treesearch

    Brock Stewart; Chris J. Cieszewski

    2009-01-01

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

  10. Spatial variability of extreme rainfall at radar subpixel scale

    NASA Astrophysics Data System (ADS)

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

    2018-01-01

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

  11. A Generalized Subsurface Flow Parameterization Considering Subgrid Spatial Variability of Recharge and Topography

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

    Huang, Maoyi; Liang, Xu; Leung, Lai R.

    2008-12-05

    Subsurface flow is an important hydrologic process and a key component of the water budget, especially in humid regions. In this study, a new subsurface flow formulation is developed that incorporates spatial variability of both topography and recharge. It is shown through theoretical derivation and case studies that the power law and exponential subsurface flow parameterizations and the parameterization proposed by Woods et al.[1997] are all special cases of the new formulation. The subsurface flows calculated using the new formulation compare well with values derived from observations at the Tulpehocken Creek and Walnut Creek watersheds. Sensitivity studies show that whenmore » the spatial variability of topography or recharge, or both is increased, the subsurface flows increase at the two aforementioned sites and the Maimai hillslope. This is likely due to enhancement of interactions between the groundwater table and the land surface that reduce the flow path. An important conclusion of this study is that the spatial variability of recharge alone, and/or in combination with the spatial variability of topography can substantially alter the behaviors of subsurface flows. This suggests that in macroscale hydrologic models or land surface models, subgrid variations of recharge and topography can make significant contributions to the grid mean subsurface flow and must be accounted for in regions with large surface heterogeneity. This is particularly true for regions with humid climate and relatively shallow groundwater table where the combined impacts of spatial variability of recharge and topography are shown to be more important. For regions with arid climate and relatively deep groundwater table, simpler formulations, especially the power law, for subsurface flow can work well, and the impacts of subgrid variations of recharge and topography may be ignored.« less

  12. Quantifying measurement uncertainty and spatial variability in the context of model evaluation

    NASA Astrophysics Data System (ADS)

    Choukulkar, A.; Brewer, A.; Pichugina, Y. L.; Bonin, T.; Banta, R. M.; Sandberg, S.; Weickmann, A. M.; Djalalova, I.; McCaffrey, K.; Bianco, L.; Wilczak, J. M.; Newman, J. F.; Draxl, C.; Lundquist, J. K.; Wharton, S.; Olson, J.; Kenyon, J.; Marquis, M.

    2017-12-01

    In an effort to improve wind forecasts for the wind energy sector, the Department of Energy and the NOAA funded the second Wind Forecast Improvement Project (WFIP2). As part of the WFIP2 field campaign, a large suite of in-situ and remote sensing instrumentation was deployed to the Columbia River Gorge in Oregon and Washington from October 2015 - March 2017. The array of instrumentation deployed included 915-MHz wind profiling radars, sodars, wind- profiling lidars, and scanning lidars. The role of these instruments was to provide wind measurements at high spatial and temporal resolution for model evaluation and improvement of model physics. To properly determine model errors, the uncertainties in instrument-model comparisons need to be quantified accurately. These uncertainties arise from several factors such as measurement uncertainty, spatial variability, and interpolation of model output to instrument locations, to name a few. In this presentation, we will introduce a formalism to quantify measurement uncertainty and spatial variability. The accuracy of this formalism will be tested using existing datasets such as the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) campaign. Finally, the uncertainties in wind measurement and the spatial variability estimates from the WFIP2 field campaign will be discussed to understand the challenges involved in model evaluation.

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

    NASA Technical Reports Server (NTRS)

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

    2015-01-01

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

  14. Random field theory to interpret the spatial variability of lacustrine soils

    NASA Astrophysics Data System (ADS)

    Russo, Savino; Vessia, Giovanna

    2015-04-01

    The lacustrine soils are quaternary soils, dated from Pleistocene to Holocene periods, generated in low-energy depositional environments and characterized by soil mixture of clays, sands and silts with alternations of finer and coarser grain size layers. They are often met at shallow depth filling several tens of meters of tectonic or erosive basins typically placed in internal Appenine areas. The lacustrine deposits are often locally interbedded by detritic soils resulting from the failure of surrounding reliefs. Their heterogeneous lithology is associated with high spatial variability of physical and mechanical properties both along horizontal and vertical directions. The deterministic approach is still commonly adopted to accomplish the mechanical characterization of these heterogeneous soils where undisturbed sampling is practically not feasible (if the incoherent fraction is prevalent) or not spatially representative (if the cohesive fraction prevails). The deterministic approach consists on performing in situ tests, like Standard Penetration Tests (SPT) or Cone Penetration Tests (CPT) and deriving design parameters through "expert judgment" interpretation of the measure profiles. These readings of tip and lateral resistances (Rp and RL respectively) are almost continuous but highly variable in soil classification according to Schmertmann (1978). Thus, neglecting the spatial variability cannot be the best strategy to estimated spatial representative values of physical and mechanical parameters of lacustrine soils to be used for engineering applications. Hereafter, a method to draw the spatial variability structure of the aforementioned measure profiles is presented. It is based on the theory of the Random Fields (Vanmarcke 1984) applied to vertical readings of Rp measures from mechanical CPTs. The proposed method relies on the application of the regression analysis, by which the spatial mean trend and fluctuations about this trend are derived. Moreover, the

  15. SPATIAL AND TEMPORAL VARIABILITY AND DRIVERS OF NET ECOSYSTEM METABOLISM IN WESTERN GULF OF MEXICO ESTUARIES

    EPA Science Inventory

    Net ecosystem metabolism (NEM) is becoming a commonly used ecological indicator of estuarine ecosystem metabolic rates. Estuarine ecosystem processes are spatially and temporally variable, but the corresponding variability in NEM has not been properly assessed. Spatial and temp...

  16. Snowpack spatial and temporal variability assessment using SMP high-resolution penetrometer

    NASA Astrophysics Data System (ADS)

    Komarov, Anton; Seliverstov, Yuriy; Sokratov, Sergey; Grebennikov, Pavel

    2017-04-01

    This research is focused on study of spatial and temporal variability of structure and characteristics of snowpack, quick identification of layers based on hardness and dispersion values received from snow micro penetrometer (SMP). We also discuss the detection of weak layers and definition of their parameters in non-alpine terrain. As long as it is the first SMP tool available in Russia, our intent is to test it in different climate and weather conditions. During two separate snowpack studies in plain and mountain landscapes, we derived density and grain size profiles by comparing snow density and grain size from snowpits and SMP measurements. The first case study was MSU meteorological observatory test site in Moscow. SMP data was obtained by 6 consecutive measurements along 10 m transects with a horizontal resolution of approximately 50 cm. The detailed description of snowpack structure, density, grain size, air and snow temperature was also performed. By comparing this information, the detailed scheme of snowpack evolution was created. The second case study was in Khibiny mountains. One 10-meter-long transect was made. SMP, density, grain size and snow temperature data was obtained with horizontal resolution of approximately 50 cm. The high-definition profile of snowpack density variation was acquired using received data. The analysis of data reveals high spatial and temporal variability in snow density and layer structure in both horizontal and vertical dimensions. It indicates that the spatial variability is exhibiting similar spatial patterns as surface topology. This suggests a strong influence from such factors as wind and liquid water pressure on the temporal and spatial evolution of snow structure. It was also defined, that spatial variation of snowpack characteristics is substantial even within homogeneous plain landscape, while in high-latitude mountain regions it grows significantly.

  17. Continuous-variable quantum computation with spatial degrees of freedom of photons

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

    Tasca, D. S.; Gomes, R. M.; Toscano, F.

    2011-05-15

    We discuss the use of the transverse spatial degrees of freedom of photons propagating in the paraxial approximation for continuous-variable information processing. Given the wide variety of linear optical devices available, a diverse range of operations can be performed on the spatial degrees of freedom of single photons. Here we show how to implement a set of continuous quantum logic gates which allow for universal quantum computation. In contrast with the usual quadratures of the electromagnetic field, the entire set of single-photon gates for spatial degrees of freedom does not require optical nonlinearity and, in principle, can be performed withmore » a single device: the spatial light modulator. Nevertheless, nonlinear optical processes, such as four-wave mixing, are needed in the implementation of two-photon gates. The efficiency of these gates is at present very low; however, small-scale investigations of continuous-variable quantum computation are within the reach of current technology. In this regard, we show how novel cluster states for one-way quantum computing can be produced using spontaneous parametric down-conversion.« less

  18. Evaluating shrub-associated spatial patterns of soil properties in a shrub-steppe ecosystem using multiple-variable geostatistics

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

    Halvorson, J.J.; Smith, J.L.; Bolton, H. Jr.

    1995-09-01

    Geostatistics are often calculated for a single variable at a time, even though many natural phenomena are functions of several variables. The objective of this work was to demonstrate a nonparametric approach for assessing the spatial characteristics of multiple-variable phenomena. Specifically, we analyzed the spatial characteristics of resource islands in the soil under big sagebrush (Artemisia tridentala Nutt.), a dominant shrub in the intermountain western USA. For our example, we defined resource islands as a function of six soil variables representing concentrations of soil resources, populations of microorganisms, and soil microbial physiological variables. By collectively evaluating the indicator transformations ofmore » these individual variables, we created a new data set, termed a multiple-variable indicator transform or MVIT. Alternate MVITs were obtained by varying the selection criteria. Each MVIT was analyzed with variography to characterize spatial continuity, and with indicator kriging to predict the combined probability of their occurrence at unsampled locations in the landscape. Simple graphical analysis and variography demonstrated spatial dependence for all individual soil variables. Maps derived from ordinary kriging of MVITs suggested that the combined probabilities for encountering zones of above-median resources were greatest near big sagebrush. 51 refs., 5 figs., 1 tab.« less

  19. Temporal and spatial variability in the estrogenicity of a municipal wastewater effluent.

    PubMed

    Hemming, Jon M; Allen, H Joel; Thuesen, Kevin A; Turner, Philip K; Waller, William T; Lazorchak, James M; Lattier, David; Chow, Marjorie; Denslow, Nancy; Venables, Barney

    2004-03-01

    The estrogenicity of a municipal wastewater effluent was monitored using the vitellogenin biomarker in adult male fathead minnows (Pimephales promelas). The variability in the expression of vitellogenin was evident among the monitoring periods. Significant (alpha< or =0.05) increases in plasma vitellogenin concentrations were detected in March and December, but not in August or June. Additionally, the magnitude of expression was variable. Variability in the spatial scale was also evident during the March and June exposure months. Concurrent exposures in both the creek receiving the effluent from a wastewater treatment plant and an experimental wetland showed estrogenicity to be different with distance from the respective effluent inflow sites. March exposures showed estrogenicity to be somewhat persistent in the receiving creek (>600 m), but to decrease rapidly within the experimental wetland (<40 m). Results are discussed relative to the monitoring season, to the spatial distribution of the response in both receiving systems, and to possible causative factors contributing to the effluent estrogenicity.

  20. Relative spatial soil geochemical variability along two transects across the United States and Canada

    USGS Publications Warehouse

    Garrett, Robert G.

    2009-01-01

    The patterns of relative variability differ by transect and horizon. The N–S transect A-horizon soils show significant between-40-km scale variability for 29 elements, with only 4 elements (Ca, Mg, Pb and Sr) showing in excess of 50% of their variability at the within-40-km and ‘at-site’ scales. In contrast, the C-horizon data demonstrate significant between-40-km scale variability for 26 elements, with 21 having in excess of 50% of their variability at the within-40-km and ‘at-site’ scales. In 36 instances, the ‘at-site’ variability is statistically significant in terms of the sample preparation and analysis variability. It is postulated that this contrast between the A- and C- horizons along the N–S transect, that is dominated by agricultural land uses, is due to the local homogenization of Ap-horizon soils by tillage reducing the ‘at-site’ variability. The spatial variability is distributed similarly between scales for the A- and C-horizon soils of the E–W transect. For all elements, there is significant variability at the within-40-km scale. Notwithstanding this, there is significant between-40-km variability for 28 and 20 of the elements in the A- and C-horizon data, respectively. The differences between the two transects are attributed to (1) geology, the N–S transect runs generally parallel to regional strikes, whereas the E–W transect runs across regional structures and lithologies; and (2) land use, with agricultural tillage dominating along the N–S transect. The spatial analysis of the transect data indicates that continental-scale maps demonstrating statistically significant patterns of geochemical variability may be prepared for many elements from data on soil samples collected on a 40 x 40 km grid or similar sampling designs resulting in a sample density of 1 site per 1600 km2.

  1. Spatial variability of E. coli in an urban salt-wedge estuary.

    PubMed

    Jovanovic, Dusan; Coleman, Rhys; Deletic, Ana; McCarthy, David

    2017-01-15

    This study investigated the spatial variability of a common faecal indicator organism, Escherichia coli, in an urban salt-wedge estuary in Melbourne, Australia. Data were collected through comprehensive depth profiling in the water column at four sites and included measurements of temperature, salinity, pH, dissolved oxygen, turbidity, and E. coli concentrations. Vertical variability of E. coli was closely related to the salt-wedge dynamics; in the presence of a salt-wedge, there was a significant decrease in E. coli concentrations with depth. Transverse variability was low and was most likely dwarfed by the analytical uncertainties of E. coli measurements. Longitudinal variability was also low, potentially reflecting minimal die-off, settling, and additional inputs entering along the estuary. These results were supported by a simple mixing model that predicted E. coli concentrations based on salinity measurements. Additionally, an assessment of a sentinel monitoring station suggested routine monitoring locations may produce conservative estimates of E. coli concentrations in stratified estuaries. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    Treesearch

    Jill M. Nakawatase; David L. Peterson

    2006-01-01

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

  5. Hydrological and environmental variables outperform spatial factors in structuring species, trait composition, and beta diversity of pelagic algae.

    PubMed

    Wu, Naicheng; Qu, Yueming; Guse, Björn; Makarevičiūtė, Kristė; To, Szewing; Riis, Tenna; Fohrer, Nicola

    2018-03-01

    There has been increasing interest in algae-based bioassessment, particularly, trait-based approaches are increasingly suggested. However, the main drivers, especially the contribution of hydrological variables, of species composition, trait composition, and beta diversity of algae communities are less studied. To link species and trait composition to multiple factors (i.e., hydrological variables, local environmental variables, and spatial factors) that potentially control species occurrence/abundance and to determine their relative roles in shaping species composition, trait composition, and beta diversities of pelagic algae communities, samples were collected from a German lowland catchment, where a well-proven ecohydrological modeling enabled to predict long-term discharges at each sampling site. Both trait and species composition showed significant correlations with hydrological, environmental, and spatial variables, and variation partitioning revealed that the hydrological and local environmental variables outperformed spatial variables. A higher variation of trait composition (57.0%) than species composition (37.5%) could be explained by abiotic factors. Mantel tests showed that both species and trait-based beta diversities were mostly related to hydrological and environmental heterogeneity with hydrological contributing more than environmental variables, while purely spatial impact was less important. Our findings revealed the relative importance of hydrological variables in shaping pelagic algae community and their spatial patterns of beta diversities, emphasizing the need to include hydrological variables in long-term biomonitoring campaigns and biodiversity conservation or restoration. A key implication for biodiversity conservation was that maintaining the instream flow regime and keeping various habitats among rivers are of vital importance. However, further investigations at multispatial and temporal scales are greatly needed.

  6. 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.

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

    Treesearch

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

    2013-01-01

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

  8. Spatial variability of soil moisture retrieved by SMOS satellite

    NASA Astrophysics Data System (ADS)

    Lukowski, Mateusz; Marczewski, Wojciech; Usowicz, Boguslaw; Rojek, Edyta; Slominski, Jan; Lipiec, Jerzy

    2015-04-01

    Standard statistical methods assume that the analysed variables are independent. Since the majority of the processes observed in the nature are continuous in space and time, this assumption introduces a significant limitation for understanding the examined phenomena. In classical approach, valuable information about the locations of examined observations is completely lost. However, there is a branch of statistics, called geostatistics, which is the study of random variables, but taking into account the space where they occur. A common example of so-called "regionalized variable" is soil moisture. Using in situ methods it is difficult to estimate soil moisture distribution because it is often significantly diversified. Thanks to the geostatistical methods, by employing semivariance analysis, it is possible to get the information about the nature of spatial dependences and their lengths. Since the Soil Moisture and Ocean Salinity mission launch in 2009, the estimation of soil moisture spatial distribution for regional up to continental scale started to be much easier. In this study, the SMOS L2 data for Central and Eastern Europe were examined. The statistical and geostatistical features of moisture distributions of this area were studied for selected natural soil phenomena for 2010-2014 including: freezing, thawing, rainfalls (wetting), drying and drought. Those soil water "states" were recognized employing ground data from the agro-meteorological network of ground-based stations SWEX and SMUDP2 data from SMOS. After pixel regularization, without any upscaling, the geostatistical methods were applied directly on Discrete Global Grid (15-km resolution) in ISEA 4H9 projection, on which SMOS observations are reported. Analysis of spatial distribution of SMOS soil moisture, carried out for each data set, in most cases did not show significant trends. It was therefore assumed that each of the examined distributions of soil moisture in the adopted scale satisfies

  9. Examining Impulse-Variability in Kicking.

    PubMed

    Chappell, Andrew; Molina, Sergio L; McKibben, Jonathon; Stodden, David F

    2016-07-01

    This study examined variability in kicking speed and spatial accuracy to test the impulse-variability theory prediction of an inverted-U function and the speed-accuracy trade-off. Twenty-eight 18- to 25-year-old adults kicked a playground ball at various percentages (50-100%) of their maximum speed at a wall target. Speed variability and spatial error were analyzed using repeated-measures ANOVA with built-in polynomial contrasts. Results indicated a significant inverse linear trajectory for speed variability (p < .001, η2= .345) where 50% and 60% maximum speed had significantly higher variability than the 100% condition. A significant quadratic fit was found for spatial error scores of mean radial error (p < .0001, η2 = .474) and subject-centroid radial error (p < .0001, η2 = .453). Findings suggest variability and accuracy of multijoint, ballistic skill performance may not follow the general principles of impulse-variability theory or the speed-accuracy trade-off.

  10. Evaluating spatial and temporal variability in growth and mortality for recreational fisheries with limited catch data

    USGS Publications Warehouse

    Li, Yan; Wagner, Tyler; Jiao, Yan; Lorantas, Robert M.; Murphy, Cheryl

    2018-01-01

    Understanding the spatial and temporal variability in life-history traits among populations is essential for the management of recreational fisheries. However, valuable freshwater recreational fish species often suffer from a lack of catch information. In this study, we demonstrated the use of an approach to estimate the spatial and temporal variability in growth and mortality in the absence of catch data and apply the method to riverine smallmouth bass (Micropterus dolomieu) populations in Pennsylvania, USA. Our approach included a growth analysis and a length-based analysis that estimates mortality. Using a hierarchical Bayesian approach, we examined spatial variability in growth and mortality by assuming parameters vary spatially but remain constant over time and temporal variability by assuming parameters vary spatially and temporally. The estimated growth and mortality of smallmouth bass showed substantial variability over time and across rivers. We explored the relationships of the estimated growth and mortality with spring water temperature and spring flow. Growth rate was likely to be positively correlated with these two factors, while young mortality was likely to be positively correlated with spring flow. The spatially and temporally varying growth and mortality suggest that smallmouth bass populations across rivers may respond differently to management plans and disturbance such as environmental contamination and land-use change. The analytical approach can be extended to other freshwater recreational species that also lack of catch data. The approach could also be useful in developing population assessments with erroneous catch data or be used as a model sensitivity scenario to verify traditional models even when catch data are available.

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

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

    Across the circumpolar north, the fate of small freshwater ponds and lakes (< 1 km2) has been the subject of scientific interest due to their ubiquity in the landscape, capacity to exchange carbon and energy with the atmosphere, and their potential to inform researchers about past climates through sediment records. A changing climate has implications for the capacity of ponds and lakes to support organisms and store carbon, which in turn has important feedbacks to climate change. Thus, an improved understanding of pond biogeochemistry is needed. To characterize spatial and temporal patterns in water column chemistry, a suite of tundra ponds were examined to answer the following research questions: (1) does temporal variability exceed spatial variability? (2) If temporal variability exists, do all ponds (or groups of ponds) behave in a similar temporal pattern, linked to seasonal hydrologic drivers or precipitation events? Six shallow ponds located in the Hudson Bay Lowlands region were monitored between May and October 2015 (inclusive, spanning the entire open-water period). The ponds span a range of biophysical conditions including pond area, perimeter, depth, and shoreline development. Water samples were collected regularly, both bimonthly over the ice-free season and intensively during and following a large summer storm event. Samples were analysed for nitrogen speciation (NO3-, NH4+, dissolved organic nitrogen) and major ions (Cl-, SO42-, K+, Ca2+, Mg2+, Na+). Across all ponds, temporal variability (across the season and within a single rain event) exceeded spatial variability (variation among ponds) in concentrations of several major species (Cl-, SO42-, K+, Ca2+, Na+). Evapoconcentration and dilution of pond water with precipitation and runoff inputs were the dominant processes influencing a set of chemical species which are hydrologically driven (Cl-, Na+, K+, Mg2+, dissolved organic nitrogen), whereas the dissolved inorganic nitrogen species were likely

  12. Spatial variability in intertidal macroalgal assemblages on the North Portuguese coast: consistence between species and functional group approaches

    NASA Astrophysics Data System (ADS)

    Veiga, P.; Rubal, M.; Vieira, R.; Arenas, F.; Sousa-Pinto, I.

    2013-03-01

    Natural assemblages are variable in space and time; therefore, quantification of their variability is imperative to identify relevant scales for investigating natural or anthropogenic processes shaping these assemblages. We studied the variability of intertidal macroalgal assemblages on the North Portuguese coast, considering three spatial scales (from metres to 10 s of kilometres) following a hierarchical design. We tested the hypotheses that (1) spatial pattern will be invariant at all the studied scales and (2) spatial variability of macroalgal assemblages obtained by using species will be consistent with that obtained using functional groups. This was done considering as univariate variables: total biomass and number of taxa as well as biomass of the most important species and functional groups and as multivariate variables the structure of macroalgal assemblages, both considering species and functional groups. Most of the univariate results confirmed the first hypothesis except for the total number of taxa and foliose macroalgae that showed significant variability at the scale of site and area, respectively. In contrast, when multivariate patterns were examined, the first hypothesis was rejected except at the scale of 10 s of kilometres. Both uni- and multivariate results indicated that variation was larger at the smallest scale, and thus, small-scale processes seem to have more effect on spatial variability patterns. Macroalgal assemblages, both considering species and functional groups as surrogate, showed consistent spatial patterns, and therefore, the second hypothesis was confirmed. Consequently, functional groups may be considered a reliable biological surrogate to study changes on macroalgal assemblages at least along the investigated Portuguese coastline.

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

  14. Temporal, Spatial, and Spectral Variability at Ivanpah Playa Vicarious Calibration Site

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

    Villa-Aleman, E.

    2003-01-07

    The Savannah River Technology Center (SRTC) conducted four reflectance vicarious calibrations at Ivanpah Playa, California since July 2000 in support of the MTI satellite. The multi-year study shows temporal, spatial and spectral variability at the playa. The temporal variability in the wavelength dependent reflectance and emissivity across the playa suggests a dependency with precipitation during the winter and early spring seasons. Satellite imagery acquired on September and November 2000, May 2001 and March 2002 in conjunction with ground truth during the September, May and March campaigns and water precipitation records were used to demonstrate the correlation observed at the playa

  15. Spatiotemporal estimation of historical PM2.5 concentrations using PM10, meteorological variables, and spatial effect

    NASA Astrophysics Data System (ADS)

    Li, Lianfa; Wu, Anna H.; Cheng, Iona; Chen, Jiu-Chiuan; Wu, Jun

    2017-10-01

    Monitoring of fine particulate matter with diameter <2.5 μm (PM2.5) started from 1999 in the US and even later in many other countries. The lack of historical PM2.5 data limits epidemiological studies of long-term exposure of PM2.5 and health outcomes such as cancer. In this study, we aimed to design a flexible approach to reliably estimate historical PM2.5 concentrations by incorporating spatial effect and the measurements of existing co-pollutants such as particulate matter with diameter <10 μm (PM10) and meteorological variables. Monitoring data of PM10, PM2.5, and meteorological variables covering the entire state of California were obtained from 1999 through 2013. We developed a spatiotemporal model that quantified non-linear associations between PM2.5 concentrations and the following predictor variables: spatiotemporal factors (PM10 and meteorological variables), spatial factors (land-use patterns, traffic, elevation, distance to shorelines, and spatial autocorrelation), and season. Our model accounted for regional-(county) scale spatial autocorrelation, using spatial weight matrix, and local-scale spatiotemporal variability, using local covariates in additive non-linear model. The spatiotemporal model was evaluated, using leaving-one-site-month-out cross validation. Our final daily model had an R2 of 0.81, with PM10, meteorological variables, and spatial autocorrelation, explaining 55%, 10%, and 10% of the variance in PM2.5 concentrations, respectively. The model had a cross-validation R2 of 0.83 for monthly PM2.5 concentrations (N = 8170) and 0.79 for daily PM2.5 concentrations (N = 51,421) with few extreme values in prediction. Further, the incorporation of spatial effects reduced bias in predictions. Our approach achieved a cross validation R2 of 0.61 for the daily model when PM10 was replaced by total suspended particulate. Our model can robustly estimate historical PM2.5 concentrations in California when PM2.5 measurements were not available.

  16. Mesoscale spatial variability of selected aquatic invertebrate community metrics from a minimally impaired stream segment

    USGS Publications Warehouse

    Gebler, J.B.

    2004-01-01

    The related topics of spatial variability of aquatic invertebrate community metrics, implications of spatial patterns of metric values to distributions of aquatic invertebrate communities, and ramifications of natural variability to the detection of human perturbations were investigated. Four metrics commonly used for stream assessment were computed for 9 stream reaches within a fairly homogeneous, minimally impaired stream segment of the San Pedro River, Arizona. Metric variability was assessed for differing sampling scenarios using simple permutation procedures. Spatial patterns of metric values suggest that aquatic invertebrate communities are patchily distributed on subsegment and segment scales, which causes metric variability. Wide ranges of metric values resulted in wide ranges of metric coefficients of variation (CVs) and minimum detectable differences (MDDs), and both CVs and MDDs often increased as sample size (number of reaches) increased, suggesting that any particular set of sampling reaches could yield misleading estimates of population parameters and effects that can be detected. Mean metric variabilities were substantial, with the result that only fairly large differences in metrics would be declared significant at ?? = 0.05 and ?? = 0.20. The number of reaches required to obtain MDDs of 10% and 20% varied with significance level and power, and differed for different metrics, but were generally large, ranging into tens and hundreds of reaches. Study results suggest that metric values from one or a small number of stream reach(es) may not be adequate to represent a stream segment, depending on effect sizes of interest, and that larger sample sizes are necessary to obtain reasonable estimates of metrics and sample statistics. For bioassessment to progress, spatial variability may need to be investigated in many systems and should be considered when designing studies and interpreting data.

  17. Effects Of Spatial Variability In Marshes On Coastal Erosion Under Storm Conditions

    NASA Astrophysics Data System (ADS)

    Lunghino, B.; Suckale, J.; Fringer, O. B.; Maldonado, S.; Ferreira, C.; Marras, S.; Mandel, T.

    2016-12-01

    To quantify the contribution of marshes in protecting coastlines, engineers and planners need to evaluate how variability in marsh characteristics and storm conditions affect erosion in the inundation zone. Previous studies show that spatial patterns in marshes significantly affect flow and sediment transport under normal tidal conditions [1, 2]. This study investigates the effect of spatial variability on floodplain sediment transport under a range of extreme hydrodynamic conditions that occur during storm events. We model the hydrodynamics of storm surge conditions on an idealized coastal floodplain by solving the 2D shallow water equations. We approximate the effect of vegetation on hydrodynamics as a constant drag coefficient. The model calculates suspended sediment transport with the advection-diffusion equation and updates morphology with erosional and depositional fluxes. We conduct numerical experiments in which we vary both the scale of the storm event and the spatial patterns of vegetation and evaluate the impact on erosion and deposition on the floodplain. We find that the alongshore extent of the vegetation is the primary control on the net volume of sediment eroded. Scour occurs in narrow channels between vegetated areas, but this does not significantly alter the net volume of sediment transported. Deposition occurs in vegetated areas under the full range of flow velocities we test. These results suggest that resolving all variability in vegetation is not necessary to quantify net sediment transport volumes at the floodplain scale. Increasing the scale of the storm event does not alter the role of spatial variability. References [1] Meire, D. W., Kondziolka, J. M., and Nepf, H. M. Interaction between neighboring vegetation patches: Impact on flow and deposition. Water Resources Research 50, 5 (2014), 3809-3825. [2] Temmerman, S., Bouma, T., Govers, G., Wang, Z., De Vries, M., and Her- man, P. Impact of vegetation on flow routing and sedimentation

  18. Characterizing multiscale variability of zero intermittency in spatial rainfall

    NASA Technical Reports Server (NTRS)

    Kumar, Praveen; Foufoula-Georgiou, Efi

    1994-01-01

    In this paper the authors study how zero intermittency in spatial rainfall, as described by the fraction of area covered by rainfall, changes with spatial scale of rainfall measurement or representation. A statistical measure of intermittency that describes the size distribution of 'voids' (nonrainy areas imbedded inside rainy areas) as a function of scale is also introduced. Morphological algorithms are proposed for reconstructing rainfall intermittency at fine scales given the intermittency at coarser scales. These algorithms are envisioned to be useful in hydroclimatological studies where the rainfall spatial variability at the subgrid scale needs to be reconstructed from the results of synoptic- or mesoscale meteorological numerical models. The developed methodologies are demsonstrated and tested using data from a severe springtime midlatitude squall line and a mild midlatitude winter storm monitored by a meteorological radar in Norman, Oklahoma.

  19. The Role of Auxiliary Variables in Deterministic and Deterministic-Stochastic Spatial Models of Air Temperature in Poland

    NASA Astrophysics Data System (ADS)

    Szymanowski, Mariusz; Kryza, Maciej

    2017-02-01

    Our study examines the role of auxiliary variables in the process of spatial modelling and mapping of climatological elements, with air temperature in Poland used as an example. The multivariable algorithms are the most frequently applied for spatialization of air temperature, and their results in many studies are proved to be better in comparison to those obtained by various one-dimensional techniques. In most of the previous studies, two main strategies were used to perform multidimensional spatial interpolation of air temperature. First, it was accepted that all variables significantly correlated with air temperature should be incorporated into the model. Second, it was assumed that the more spatial variation of air temperature was deterministically explained, the better was the quality of spatial interpolation. The main goal of the paper was to examine both above-mentioned assumptions. The analysis was performed using data from 250 meteorological stations and for 69 air temperature cases aggregated on different levels: from daily means to 10-year annual mean. Two cases were considered for detailed analysis. The set of potential auxiliary variables covered 11 environmental predictors of air temperature. Another purpose of the study was to compare the results of interpolation given by various multivariable methods using the same set of explanatory variables. Two regression models: multiple linear (MLR) and geographically weighted (GWR) method, as well as their extensions to the regression-kriging form, MLRK and GWRK, respectively, were examined. Stepwise regression was used to select variables for the individual models and the cross-validation method was used to validate the results with a special attention paid to statistically significant improvement of the model using the mean absolute error (MAE) criterion. The main results of this study led to rejection of both assumptions considered. Usually, including more than two or three of the most significantly

  20. Temperature and aridity regulate spatial variability of soil multifunctionality in drylands across the globe.

    PubMed

    Durán, Jorge; Delgado-Baquerizo, Manuel; Dougill, Andrew J; Guuroh, Reginald T; Linstädter, Anja; Thomas, Andrew D; Maestre, Fernando T

    2018-05-01

    The relationship between the spatial variability of soil multifunctionality (i.e., the capacity of soils to conduct multiple functions; SVM) and major climatic drivers, such as temperature and aridity, has never been assessed globally in terrestrial ecosystems. We surveyed 236 dryland ecosystems from six continents to evaluate the relative importance of aridity and mean annual temperature, and of other abiotic (e.g., texture) and biotic (e.g., plant cover) variables as drivers of SVM, calculated as the averaged coefficient of variation for multiple soil variables linked to nutrient stocks and cycling. We found that increases in temperature and aridity were globally correlated to increases in SVM. Some of these climatic effects on SVM were direct, but others were indirectly driven through reductions in the number of vegetation patches and increases in soil sand content. The predictive capacity of our structural equation modelling was clearly higher for the spatial variability of N- than for C- and P-related soil variables. In the case of N cycling, the effects of temperature and aridity were both direct and indirect via changes in soil properties. For C and P, the effect of climate was mainly indirect via changes in plant attributes. These results suggest that future changes in climate may decouple the spatial availability of these elements for plants and microbes in dryland soils. Our findings significantly advance our understanding of the patterns and mechanisms driving SVM in drylands across the globe, which is critical for predicting changes in ecosystem functioning in response to climate change. © 2018 by the Ecological Society of America.

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

    USGS Publications Warehouse

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

    2017-01-09

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

  2. Spatial Variability of Streambed Hydraulic Conductivity of a Lowland River

    NASA Astrophysics Data System (ADS)

    Schneidewind, Uwe; Thornton, Steven; Van De Vijver, Ellen; Joris, Ingeborg; Seuntjens, Piet

    2015-04-01

    Streambed hydraulic conductivity K is a key physical parameter, which describes flow processes in the hyporheic zone (HZ), i.e. the dynamic interface between aquifers and streams or rivers. Knowledge of the spatial variability of K is also important for the interpretation of contaminant transport processes in the HZ. Streambed K can vary over several magnitudes at small spatial scales. It depends mostly on streambed sediment characteristics (e.g. effective porosity, grain size, packing), streambed processes (e.g. sedimentation, colmation and erosion) and the development of stream channel geometry and streambed morphology (e.g. dunes, anti-dunes, pool-riffle sequences, etc.). Although heterogeneous in natural streambeds, streambed K is often considered to be a constant parameter due to a lack of information on its spatial distribution. Here we show the spatial variability of streambed K for a small section of the River Tern, a lowland river in the UK. Streambed K was determined for more than 120 vertically and horizontally distributed locations from grain size analyses using four empirical approaches (Hazen, Beyer, Kozeny and the USBR model). Additionally, streambed K was estimated from falling head tests in 36 piezometers installed into the streambed on a 4 m by 16 m grid, by applying the Springer-Gelhar Model. For both methods streambed K followed a log-normal distribution. Variogram analysis was used to deduce the spatial variability of the streambed K values within several streambed profiles parallel and perpendicular to the main flow direction in the stream. Hydraulic conductivity Kg estimated from grain size analyses varied between 1 m/d and 155 m/d with standard deviations of 79% to 99% depending on the empirical approach used. Kh estimated from falling head tests varied between 1 m/d and 22 m/d with a standard deviation of about 50%, depending on the degree of anisotropy assumed. After rescaling the data to obtain a common sample support, Pearson correlation

  3. Deciphering factors controlling groundwater arsenic spatial variability in Bangladesh

    NASA Astrophysics Data System (ADS)

    Tan, Z.; Yang, Q.; Zheng, C.; Zheng, Y.

    2017-12-01

    Elevated concentrations of geogenic arsenic in groundwater have been found in many countries to exceed 10 μg/L, the WHO's guideline value for drinking water. A common yet unexplained characteristic of groundwater arsenic spatial distribution is the extensive variability at various spatial scales. This study investigates factors influencing the spatial variability of groundwater arsenic in Bangladesh to improve the accuracy of models predicting arsenic exceedance rate spatially. A novel boosted regression tree method is used to establish a weak-learning ensemble model, which is compared to a linear model using a conventional stepwise logistic regression method. The boosted regression tree models offer the advantage of parametric interaction when big datasets are analyzed in comparison to the logistic regression. The point data set (n=3,538) of groundwater hydrochemistry with 19 parameters was obtained by the British Geological Survey in 2001. The spatial data sets of geological parameters (n=13) were from the Consortium for Spatial Information, Technical University of Denmark, University of East Anglia and the FAO, while the soil parameters (n=42) were from the Harmonized World Soil Database. The aforementioned parameters were regressed to categorical groundwater arsenic concentrations below or above three thresholds: 5 μg/L, 10 μg/L and 50 μg/L to identify respective controlling factors. Boosted regression tree method outperformed logistic regression methods in all three threshold levels in terms of accuracy, specificity and sensitivity, resulting in an improvement of spatial distribution map of probability of groundwater arsenic exceeding all three thresholds when compared to disjunctive-kriging interpolated spatial arsenic map using the same groundwater arsenic dataset. Boosted regression tree models also show that the most important controlling factors of groundwater arsenic distribution include groundwater iron content and well depth for all three

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

    NASA Astrophysics Data System (ADS)

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

    2017-10-01

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

  5. Soil internal drainage: temporal stability and spatial variability in succession bean-black oat

    NASA Astrophysics Data System (ADS)

    Salvador, M. M. S.; Libardi, P. L.; Moreira, N. B.; Sousa, H. H. F.; Neiverth, C. A.

    2012-04-01

    There are a variety of studies considering the soil water content, but those who consider the flow of water, which are translated by deep drainage and capillary rise are scarce, especially those who assess their spatio-temporal variability, due to its laborious obtaining. Large areas have been considered homogeneous, but show considerable spatial variability inherent in the soil, causing the appearance of zones of distinct physical properties. In deep, sandy soils where the groundwater level is far below the root zone of interference, internal drainage is one of the factors limiting the supply of water to the soil surface, and possibly one of the biggest factors that determines what kinds satisfactory development of plants present in a given landscape. The forms of relief may also be indicators of changes in soil properties, because this variability is caused by small changes that affect the slope of the pedogenetic processes and the transport and storage of water in the soil profile, i.e., the different trajectories of water flow in different forms of the landscape, is the cause of variability. The objectives of this research were: i) evaluate the spatial and temporal stability of internal soil water drainage in a place near and another distant from the root system in a bean-black-oat succession and ii) verify their spatial variability in relation to relief. With the hydraulic conductivity obtained by the instantaneous profile method and the total potential gradient obtained from the difference in readings of tensiometers installed at depths of 0.35 and 0.45 and 0.75 and 0.85 m in 60 sampling points totaling 1680 and 1200 observations during the cultivation of beans and oats, respectively, was obtained so the internal drainage / capillary rise through the Darcy-Buckingham equation. To evaluate the temporal stability the method used was the relative difference and Spearman correlation test and the spatial variability was analyzed as geostatistical methodology

  6. Comparing daily temperature averaging methods: the role of surface and atmosphere variables in determining spatial and seasonal variability

    NASA Astrophysics Data System (ADS)

    Bernhardt, Jase; Carleton, Andrew M.

    2018-05-01

    The two main methods for determining the average daily near-surface air temperature, twice-daily averaging (i.e., [Tmax+Tmin]/2) and hourly averaging (i.e., the average of 24 hourly temperature measurements), typically show differences associated with the asymmetry of the daily temperature curve. To quantify the relative influence of several land surface and atmosphere variables on the two temperature averaging methods, we correlate data for 215 weather stations across the Contiguous United States (CONUS) for the period 1981-2010 with the differences between the two temperature-averaging methods. The variables are land use-land cover (LULC) type, soil moisture, snow cover, cloud cover, atmospheric moisture (i.e., specific humidity, dew point temperature), and precipitation. Multiple linear regression models explain the spatial and monthly variations in the difference between the two temperature-averaging methods. We find statistically significant correlations between both the land surface and atmosphere variables studied with the difference between temperature-averaging methods, especially for the extreme (i.e., summer, winter) seasons (adjusted R2 > 0.50). Models considering stations with certain LULC types, particularly forest and developed land, have adjusted R2 values > 0.70, indicating that both surface and atmosphere variables control the daily temperature curve and its asymmetry. This study improves our understanding of the role of surface and near-surface conditions in modifying thermal climates of the CONUS for a wide range of environments, and their likely importance as anthropogenic forcings—notably LULC changes and greenhouse gas emissions—continues.

  7. Small-scale spatial variability of soil microbial community composition and functional diversity in a mixed forest

    NASA Astrophysics Data System (ADS)

    Wang, Qiufeng; Tian, Jing; Yu, Guirui

    2014-05-01

    Patterns in the spatial distribution of organisms provide important information about mechanisms that regulate the diversity and complexity of soil ecosystems. Therefore, information on spatial distribution of microbial community composition and functional diversity is urgently necessary. The spatial variability on a 26×36 m plot and vertical distribution (0-10 cm and 10-20 cm) of soil microbial community composition and functional diversity were studied in a natural broad-leaved Korean pine (Pinus koraiensis) mixed forest soil in Changbai Mountain. The phospholipid fatty acid (PLFA) pattern was used to characterize the soil microbial community composition and was compared with the community substrate utilization pattern using Biolog. Bacterial biomass dominated and showed higher variability than fungal biomass at all scales examined. The microbial biomass decreased with soil depths increased and showed less variability in lower 10-20 cm soil layer. The Shannon-Weaver index value for microbial functional diversity showed higher variability in upper 0-10 cm than lower 10-20 cm soil layer. Carbohydrates, carboxylic acids, polymers and amino acids are the main carbon sources possessing higher utilization efficiency or utilization intensity. At the same time, the four carbon source types contributed to the differentiation of soil microbial communities. This study suggests the higher diversity and complexity for this mix forest ecosystem. To determine the driving factors that affect this spatial variability of microorganism is the next step for our study.

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

    NASA Astrophysics Data System (ADS)

    Wang, Jun; Wang, Yang; Zeng, Hui

    2016-01-01

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

  9. Throughfall and its spatial variability beneath xerophytic shrub canopies within water-limited arid desert ecosystems

    NASA Astrophysics Data System (ADS)

    Zhang, Ya-feng; Wang, Xin-ping; Hu, Rui; Pan, Yan-xia

    2016-08-01

    Throughfall is known to be a critical component of the hydrological and biogeochemical cycles of forested ecosystems with inherently temporal and spatial variability. Yet little is understood concerning the throughfall variability of shrubs and the associated controlling factors in arid desert ecosystems. Here we systematically investigated the variability of throughfall of two morphological distinct xerophytic shrubs (Caragana korshinskii and Artemisia ordosica) within a re-vegetated arid desert ecosystem, and evaluated the effects of shrub structure and rainfall characteristics on throughfall based on heavily gauged throughfall measurements at the event scale. We found that morphological differences were not sufficient to generate significant difference (P < 0.05) in throughfall between two studied shrub species under the same rainfall and meteorological conditions in our study area, with a throughfall percentage of 69.7% for C. korshinskii and 64.3% for A. ordosica. We also observed a highly variable patchy pattern of throughfall beneath individual shrub canopies, but the spatial patterns appeared to be stable among rainfall events based on time stability analysis. Throughfall linearly increased with the increasing distance from the shrub base for both shrubs, and radial direction beneath shrub canopies had a pronounced impact on throughfall. Throughfall variability, expressed as the coefficient of variation (CV) of throughfall, tended to decline with the increase in rainfall amount, intensity and duration, and stabilized passing a certain threshold. Our findings highlight the great variability of throughfall beneath the canopies of xerophytic shrubs and the time stability of throughfall pattern among rainfall events. The spatially heterogeneous and temporally stable throughfall is expected to generate a dynamic patchy distribution of soil moisture beneath shrub canopies within arid desert ecosystems.

  10. Mapping Spatial Variability in Health and Wealth Indicators in Accra, Ghana Using High Spatial Resolution Imagery

    NASA Astrophysics Data System (ADS)

    Engstrom, R.; Ashcroft, E.

    2014-12-01

    There has been a tremendous amount of research conducted that examines disparities in health and wealth of persons between urban and rural areas however, relatively little research has been undertaken to examine variations within urban areas. A major limitation to elucidating differences with urban areas is the lack of social and demographic data at a sufficiently high spatial resolution to determine these differences. Generally the only available data that contain this information are census data which are collected at most every ten years and are often difficult to obtain at a high enough spatial resolution to allow for examining in depth variability in health and wealth indicators at high spatial resolutions, especially in developing countries. High spatial resolution satellite imagery may be able to provide timely and synoptic information that is related to health and wealth variability within a city. In this study we use two dates of Quickbird imagery (2003 and 2010) classified into the vegetation-impervious surface-soil (VIS) model introduced by Ridd (1995). For 2003 we only have partial coverage of the city, while for 2010 we have a mosaic, which covers the entire city of Accra, Ghana. Variations in the VIS values represent the physical variations within the city and these are compared to variations in economic, and/or sociodemographic data derived from the 2000 Ghanaian census at two spatial resolutions, the enumeration area (approximately US Census Tract) and the neighborhood for the city. Results indicate a significant correlation between both vegetation and impervious surface to type of cooking fuel used in the household, population density, housing density, availability of sewers, cooking space usage, and other variables. The correlations are generally stronger at the neighborhood level and the relationships are stable through time and space. Overall, the results indicate that information derived from high resolution satellite data is related to

  11. The effects of environmental variability and spatial sampling on the three-dimensional inversion problem.

    PubMed

    Bender, Christopher M; Ballard, Megan S; Wilson, Preston S

    2014-06-01

    The overall goal of this work is to quantify the effects of environmental variability and spatial sampling on the accuracy and uncertainty of estimates of the three-dimensional ocean sound-speed field. In this work, ocean sound speed estimates are obtained with acoustic data measured by a sparse autonomous observing system using a perturbative inversion scheme [Rajan, Lynch, and Frisk, J. Acoust. Soc. Am. 82, 998-1017 (1987)]. The vertical and horizontal resolution of the solution depends on the bandwidth of acoustic data and on the quantity of sources and receivers, respectively. Thus, for a simple, range-independent ocean sound speed profile, a single source-receiver pair is sufficient to estimate the water-column sound-speed field. On the other hand, an environment with significant variability may not be fully characterized by a large number of sources and receivers, resulting in uncertainty in the solution. This work explores the interrelated effects of environmental variability and spatial sampling on the accuracy and uncertainty of the inversion solution though a set of case studies. Synthetic data representative of the ocean variability on the New Jersey shelf are used.

  12. Yield variability prediction by remote sensing sensors with different spatial resolution

    NASA Astrophysics Data System (ADS)

    Kumhálová, Jitka; Matějková, Štěpánka

    2017-04-01

    Currently, remote sensing sensors are very popular for crop monitoring and yield prediction. This paper describes how satellite images with moderate (Landsat satellite data) and very high (QuickBird and WorldView-2 satellite data) spatial resolution, together with GreenSeeker hand held crop sensor, can be used to estimate yield and crop growth variability. Winter barley (2007 and 2015) and winter wheat (2009 and 2011) were chosen because of cloud-free data availability in the same time period for experimental field from Landsat satellite images and QuickBird or WorldView-2 images. Very high spatial resolution images were resampled to worse spatial resolution. Normalised difference vegetation index was derived from each satellite image data sets and it was also measured with GreenSeeker handheld crop sensor for the year 2015 only. Results showed that each satellite image data set can be used for yield and plant variability estimation. Nevertheless, better results, in comparison with crop yield, were obtained for images acquired in later phenological phases, e.g. in 2007 - BBCH 59 - average correlation coefficient 0.856, and in 2011 - BBCH 59-0.784. GreenSeeker handheld crop sensor was not suitable for yield estimation due to different measuring method.

  13. Soil variability in engineering applications

    NASA Astrophysics Data System (ADS)

    Vessia, Giovanna

    2014-05-01

    Natural geomaterials, as soils and rocks, show spatial variability and heterogeneity of physical and mechanical properties. They can be measured by in field and laboratory testing. The heterogeneity concerns different values of litho-technical parameters pertaining similar lithological units placed close to each other. On the contrary, the variability is inherent to the formation and evolution processes experienced by each geological units (homogeneous geomaterials on average) and captured as a spatial structure of fluctuation of physical property values about their mean trend, e.g. the unit weight, the hydraulic permeability, the friction angle, the cohesion, among others. The preceding spatial variations shall be managed by engineering models to accomplish reliable designing of structures and infrastructures. Materon (1962) introduced the Geostatistics as the most comprehensive tool to manage spatial correlation of parameter measures used in a wide range of earth science applications. In the field of the engineering geology, Vanmarcke (1977) developed the first pioneering attempts to describe and manage the inherent variability in geomaterials although Terzaghi (1943) already highlighted that spatial fluctuations of physical and mechanical parameters used in geotechnical designing cannot be neglected. A few years later, Mandelbrot (1983) and Turcotte (1986) interpreted the internal arrangement of geomaterial according to Fractal Theory. In the same years, Vanmarcke (1983) proposed the Random Field Theory providing mathematical tools to deal with inherent variability of each geological units or stratigraphic succession that can be resembled as one material. In this approach, measurement fluctuations of physical parameters are interpreted through the spatial variability structure consisting in the correlation function and the scale of fluctuation. Fenton and Griffiths (1992) combined random field simulation with the finite element method to produce the Random

  14. Biodiversity in canopy-forming algae: Structure and spatial variability of the Mediterranean Cystoseira assemblages

    NASA Astrophysics Data System (ADS)

    Piazzi, L.; Bonaviri, C.; Castelli, A.; Ceccherelli, G.; Costa, G.; Curini-Galletti, M.; Langeneck, J.; Manconi, R.; Montefalcone, M.; Pipitone, C.; Rosso, A.; Pinna, S.

    2018-07-01

    In the Mediterranean Sea, Cystoseira species are the most important canopy-forming algae in shallow rocky bottoms, hosting high biodiverse sessile and mobile communities. A large-scale study has been carried out to investigate the structure of the Cystoseira-dominated assemblages at different spatial scales and to test the hypotheses that alpha and beta diversity of the assemblages, the abundance and the structure of epiphytic macroalgae, epilithic macroalgae, sessile macroinvertebrates and mobile macroinvertebrates associated to Cystoseira beds changed among scales. A hierarchical sampling design in a total of five sites across the Mediterranean Sea (Croatia, Montenegro, Sardinia, Tuscany and Balearic Islands) was used. A total of 597 taxa associated to Cystoseira beds were identified with a mean number per sample ranging between 141.1 ± 6.6 (Tuscany) and 173.9 ± 8.5(Sardinia). A high variability at small (among samples) and large (among sites) scale was generally highlighted, but the studied assemblages showed different patterns of spatial variability. The relative importance of the different scales of spatial variability should be considered to optimize sampling designs and propose monitoring plans of this habitat.

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

    Treesearch

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

    2016-01-01

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

  16. Effects of spatial and temporal variability of turbidity on phytoplankton blooms

    USGS Publications Warehouse

    May, Christine L.; Koseff, Jeffrey R.; Lucas, Lisa; Cloern, James E.; Schoellhamer, David H.

    2003-01-01

    A central challenge of coastal ecology is sorting out the interacting spatial and temporal components of environmental variability that combine to drive changes in phytoplankton biomass. For 2 decades, we have combined sustained observation and experimentation in South San Francisco Bay (SSFB) with numerical modeling analyses to search for general principles that define phytoplankton population responses to physical dynamics characteristic of shallow, nutrient-rich coastal waters having complex bathymetry and influenced by tides, wind and river flow. This study is the latest contribution where we investigate light-limited phytoplankton growth using a numerical model, by modeling turbidity as a function of suspended sediment concentrations (SSC). The goal was to explore the sensitivity of estuarine phytoplankton dynamics to spatial and temporal variations in turbidity, and to synthesize outcomes of simulation experiments into a new conceptual framework for defining the combinations of physical-biological forcings that promote or preclude development of phytoplankton blooms in coastal ecosystems. The 3 main conclusions of this study are: (1) The timing of the wind with semidiurnal tides and the spring-neap cycle can significantly enhance spring-neap variability in turbidity and phytoplankton biomass; (2) Fetch is a significant factor potentially affecting phytoplankton dynamics by enhancing and/or creating spatial variability in turbidity; and (3) It is possible to parameterize the combined effect of the processes influencing turbidity‹and thus affecting potential phytoplankton bloom development‹with 2 indices for vertical and horizontal clearing of the water column. Our conceptual framework is built around these 2 indices, providing a means to determine under what conditions a phytoplankton bloom can occur, and whether a potential bloom is only locally supported or system-wide in scale. This conceptual framework provides a tool for exploring the inherent light

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

    Treesearch

    Robert E. Keane; Kathy Gray; Valentina Bacciu

    2012-01-01

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

  18. Factors influencing spatial variability in nitrogen processing in nitrogen-saturated soils

    Treesearch

    Frank S. Gilliam; Charles C. Somerville; Nikki L. Lyttle; Mary Beth Adams

    2001-01-01

    Nitrogen (N) saturation is an environmental concern for forests in the eastern U.S. Although several watersheds of the Fernow Experimental Forest (FEF), West Virginia exhibit symptoms of N saturation, many watersheds display a high degree of spatial variability in soil N processing. This study examined the effects of temperature on net N mineralization and...

  19. Documentation of programs that compute 1) static tilts for a spatially variable slip distribution, and 2) quasi-static tilts produced by an expanding dislocation loop with a spatially variable slip distribution

    USGS Publications Warehouse

    McHugh, Stuart

    1976-01-01

    The material in this report is concerned with the effects of a vertically oriented rectangular dislocation loop on the tilts observed at the free surface of an elastic half-space. Part I examines the effect of a spatially variable static strike-slip distribution across the slip surface. The tilt components as a function of distance parallel, or perpendicular, to the strike of the slip surface are displayed for different slip-versus-distance profiles. Part II examines the effect of spatially and temporally variable slip distributions across the dislocation loop on the quasi-static tilts at the free surface of an elastic half space. The model discussed in part II may be used to generate theoretical tilt versus time curves produced by creep events.

  20. Spatial and temporal variability of hyperspectral signatures of terrain

    NASA Astrophysics Data System (ADS)

    Jones, K. F.; Perovich, D. K.; Koenig, G. G.

    2008-04-01

    Electromagnetic signatures of terrain exhibit significant spatial heterogeneity on a range of scales as well as considerable temporal variability. A statistical characterization of the spatial heterogeneity and spatial scaling algorithms of terrain electromagnetic signatures are required to extrapolate measurements to larger scales. Basic terrain elements including bare soil, grass, deciduous, and coniferous trees were studied in a quasi-laboratory setting using instrumented test sites in Hanover, NH and Yuma, AZ. Observations were made using a visible and near infrared spectroradiometer (350 - 2500 nm) and hyperspectral camera (400 - 1100 nm). Results are reported illustrating: i) several difference scenes; ii) a terrain scene time series sampled over an annual cycle; and iii) the detection of artifacts in scenes. A principal component analysis indicated that the first three principal components typically explained between 90 and 99% of the variance of the 30 to 40-channel hyperspectral images. Higher order principal components of hyperspectral images are useful for detecting artifacts in scenes.

  1. Spatial variability of atrazine dissipation in an allophanic soil.

    PubMed

    Müller, Karin; Smith, Roger E; James, Trevor K; Holland, Patrick T; Rahman, Anis

    2003-08-01

    The small-scale variability (0.5 m) of atrazine (6-chloro-N2-ethyl-N4-isopropyl-1,3,5-triazine-2,4-diamine) concentrations and soil water contents in a volcanic silt loam soil (Haplic Andosol, FAO system) was studied in an area of 0.1 ha. Descriptive and spatial statistics were used to analyse the data. On average we recovered 102% of the applied atrazine 2 h after the herbicide application (CV = 35%). An increase in the CV of the concentrations with depth could be ascribed to a combination of extrinsic and intrinsic factors. Both variables, atrazine concentrations and soil water content, showed a high horizontal variability. The semivariograms of the atrazine concentrations exhibited the pure nugget effect, no pattern could be determined along the 15.5-m long transects on any of the seven sampling days over a 55-day period. Soil water content had a weak spatial autocorrelation with a range of 6-10 m. The dissipation of atrazine analysed using a high vertical sampling resolution of 0.02 m to 0.2 m showed that 70% of the applied atrazine persisted in the upper 0.02-m layer of the soil for 12 days. After 55 days and 410 mm of rainfall the centre of the pesticide mass was still at a soil depth of 0.021 m. The special characteristics of the soil (high organic carbon content, allophanic clay) had a strong influence on atrazine sorption and mobility. The mass recovery after 55 days was low. The laboratory degradation rate for atrazine, determined in a complementary incubation study and corrected for the actual field temperature using the Arrhenius equation, only accounted for about 35% of the losses that occurred in the field. Results suggest field degradation rates to be more changeable in time and much faster than under controlled conditions. Preferential flow is discussed as a component of the field transport process.

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

    PubMed

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

    2015-08-01

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

  3. Direct generation of spatial quadripartite continuous variable entanglement in an optical parametric oscillator.

    PubMed

    Liu, Kui; Guo, Jun; Cai, Chunxiao; Zhang, Junxiang; Gao, Jiangrui

    2016-11-15

    Multipartite entanglement is used for quantum information applications, such as building multipartite quantum communications. Generally, generation of multipartite entanglement is based on a complex beam-splitter network. Here, based on the spatial freedom of light, we experimentally demonstrated spatial quadripartite continuous variable entanglement among first-order Hermite-Gaussian modes using a single type II optical parametric oscillator operating below threshold with an HG0245° pump beam. The entanglement can be scalable for larger numbers of spatial modes by changing the spatial profile of the pump beam. In addition, spatial multipartite entanglement will be useful for future spatial multichannel quantum information applications.

  4. Mapping Spatial Variability of Soil Salinity in a Coastal Paddy Field Based on Electromagnetic Sensors

    PubMed Central

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

    2015-01-01

    In coastal China, there is an urgent need to increase land area for agricultural production and urban development, where there is a rapid growing population. One solution is land reclamation from coastal tidelands, but soil salinization is problematic. As such, it is very important to characterize and map the within-field variability of soil salinity in space and time. Conventional methods are often time-consuming, expensive, labor-intensive, and unpractical. Fortunately, proximal sensing has become an important technology in characterizing within-field spatial variability. In this study, we employed the EM38 to study spatial variability of soil salinity in a coastal paddy field. Significant correlation relationship between ECa and EC1:5 (i.e. r >0.9) allowed us to use EM38 data to characterize the spatial variability of soil salinity. Geostatistical methods were used to determine the horizontal spatio-temporal variability of soil salinity over three consecutive years. The study found that the distribution of salinity was heterogeneous and the leaching of salts was more significant in the edges of the study field. By inverting the EM38 data using a Quasi-3D inversion algorithm, the vertical spatio-temporal variability of soil salinity was determined and the leaching of salts over time was easily identified. The methodology of this study can be used as guidance for researchers interested in understanding soil salinity development as well as land managers aiming for effective soil salinity monitoring and management practices. In order to better characterize the variations in soil salinity to a deeper soil profile, the deeper mode of EM38 (i.e., EM38v) as well as other EMI instruments (e.g. DUALEM-421) can be incorporated to conduct Quasi-3D inversions for deeper soil profiles. PMID:26020969

  5. Using geomorphological variables to predict the spatial distribution of plant species in agricultural drainage networks.

    PubMed

    Rudi, Gabrielle; Bailly, Jean-Stéphane; Vinatier, Fabrice

    2018-01-01

    To optimize ecosystem services provided by agricultural drainage networks (ditches) in headwater catchments, we need to manage the spatial distribution of plant species living in these networks. Geomorphological variables have been shown to be important predictors of plant distribution in other ecosystems because they control the water regime, the sediment deposition rates and the sun exposure in the ditches. Whether such variables may be used to predict plant distribution in agricultural drainage networks is unknown. We collected presence and absence data for 10 herbaceous plant species in a subset of a network of drainage ditches (35 km long) within a Mediterranean agricultural catchment. We simulated their spatial distribution with GLM and Maxent model using geomorphological variables and distance to natural lands and roads. Models were validated using k-fold cross-validation. We then compared the mean Area Under the Curve (AUC) values obtained for each model and other metrics issued from the confusion matrices between observed and predicted variables. Based on the results of all metrics, the models were efficient at predicting the distribution of seven species out of ten, confirming the relevance of geomorphological variables and distance to natural lands and roads to explain the occurrence of plant species in this Mediterranean catchment. In particular, the importance of the landscape geomorphological variables, ie the importance of the geomorphological features encompassing a broad environment around the ditch, has been highlighted. This suggests that agro-ecological measures for managing ecosystem services provided by ditch plants should focus on the control of the hydrological and sedimentological connectivity at the catchment scale. For example, the density of the ditch network could be modified or the spatial distribution of vegetative filter strips used for sediment trapping could be optimized. In addition, the vegetative filter strips could constitute

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

    PubMed

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

    2015-01-01

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

  7. Using Mobile Monitoring to Assess Spatial Variability in Urban Air Pollution Levels: Opportunities and Challenges (Invited)

    NASA Astrophysics Data System (ADS)

    Larson, T.

    2010-12-01

    Measuring air pollution concentrations from a moving platform is not a new idea. Historically, however, most information on the spatial variability of air pollutants have been derived from fixed site networks operating simultaneously over space. While this approach has obvious advantages from a regulatory perspective, with the increasing need to understand ever finer scales of spatial variability in urban pollution levels, the use of mobile monitoring to supplement fixed site networks has received increasing attention. Here we present examples of the use of this approach: 1) to assess existing fixed-site fine particle networks in Seattle, WA, including the establishment of new fixed-site monitoring locations; 2) to assess the effectiveness of a regulatory intervention, a wood stove burning ban, on the reduction of fine particle levels in the greater Puget Sound region; and 3) to assess spatial variability of both wood smoke and mobile source impacts in both Vancouver, B.C. and Tacoma, WA. Deducing spatial information from the inherently spatio-temporal measurements taken from a mobile platform is an area that deserves further attention. We discuss the use of “fuzzy” points to address the fine-scale spatio-temporal variability in the concentration of mobile source pollutants, specifically to deduce the broader distribution and sources of fine particle soot in the summer in Vancouver, B.C. We also discuss the use of principal component analysis to assess the spatial variability in multivariate, source-related features deduced from simultaneous measurements of light scattering, light absorption and particle-bound PAHs in Tacoma, WA. With increasing miniaturization and decreasing power requirements of air monitoring instruments, the number of simultaneous measurements that can easily be made from a mobile platform is rapidly increasing. Hopefully the methods used to design mobile monitoring experiments for differing purposes, and the methods used to interpret those

  8. Spatial and temporal variability of Mediterranean drought events

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  9. Spatial Scaling of Environmental Variables Improves Species-Habitat Models of Fishes in a Small, Sand-Bed Lowland River

    PubMed Central

    Radinger, Johannes; Wolter, Christian; Kail, Jochem

    2015-01-01

    Habitat suitability and the distinct mobility of species depict fundamental keys for explaining and understanding the distribution of river fishes. In recent years, comprehensive data on river hydromorphology has been mapped at spatial scales down to 100 m, potentially serving high resolution species-habitat models, e.g., for fish. However, the relative importance of specific hydromorphological and in-stream habitat variables and their spatial scales of influence is poorly understood. Applying boosted regression trees, we developed species-habitat models for 13 fish species in a sand-bed lowland river based on river morphological and in-stream habitat data. First, we calculated mean values for the predictor variables in five distance classes (from the sampling site up to 4000 m up- and downstream) to identify the spatial scale that best predicts the presence of fish species. Second, we compared the suitability of measured variables and assessment scores related to natural reference conditions. Third, we identified variables which best explained the presence of fish species. The mean model quality (AUC = 0.78, area under the receiver operating characteristic curve) significantly increased when information on the habitat conditions up- and downstream of a sampling site (maximum AUC at 2500 m distance class, +0.049) and topological variables (e.g., stream order) were included (AUC = +0.014). Both measured and assessed variables were similarly well suited to predict species’ presence. Stream order variables and measured cross section features (e.g., width, depth, velocity) were best-suited predictors. In addition, measured channel-bed characteristics (e.g., substrate types) and assessed longitudinal channel features (e.g., naturalness of river planform) were also good predictors. These findings demonstrate (i) the applicability of high resolution river morphological and instream-habitat data (measured and assessed variables) to predict fish presence, (ii) the

  10. Analysis of Large Scale Spatial Variability of Soil Moisture Using a Geostatistical Method

    DTIC Science & Technology

    2010-01-25

    2010 / Accepted: 19 January 2010 / Published: 25 January 2010 Abstract: Spatial and temporal soil moisture dynamics are critically needed to...scale observed and simulated estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial... dynamics is essential in the hydrological and meteorological modeling, improves our understanding of land surface–atmosphere interactions. Spatial and

  11. Modelling Spatial Dependence Structures Between Climate Variables by Combining Mixture Models with Copula Models

    NASA Astrophysics Data System (ADS)

    Khan, F.; Pilz, J.; Spöck, G.

    2017-12-01

    Spatio-temporal dependence structures play a pivotal role in understanding the meteorological characteristics of a basin or sub-basin. This further affects the hydrological conditions and consequently will provide misleading results if these structures are not taken into account properly. In this study we modeled the spatial dependence structure between climate variables including maximum, minimum temperature and precipitation in the Monsoon dominated region of Pakistan. For temperature, six, and for precipitation four meteorological stations have been considered. For modelling the dependence structure between temperature and precipitation at multiple sites, we utilized C-Vine, D-Vine and Student t-copula models. For temperature, multivariate mixture normal distributions and for precipitation gamma distributions have been used as marginals under the copula models. A comparison was made between C-Vine, D-Vine and Student t-copula by observational and simulated spatial dependence structure to choose an appropriate model for the climate data. The results show that all copula models performed well, however, there are subtle differences in their performances. The copula models captured the patterns of spatial dependence structures between climate variables at multiple meteorological sites, however, the t-copula showed poor performance in reproducing the dependence structure with respect to magnitude. It was observed that important statistics of observed data have been closely approximated except of maximum values for temperature and minimum values for minimum temperature. Probability density functions of simulated data closely follow the probability density functions of observational data for all variables. C and D-Vines are better tools when it comes to modelling the dependence between variables, however, Student t-copulas compete closely for precipitation. Keywords: Copula model, C-Vine, D-Vine, Spatial dependence structure, Monsoon dominated region of Pakistan

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  13. Exploring the Linkage of Sea Surface Temperature Variability on Three Spatial Scales

    NASA Astrophysics Data System (ADS)

    Luo, L.; Capone, D. G.; Hutchins, D.; Kiefer, D.

    2011-12-01

    As part of a project examining climate change in the Southern California Bight at the University of Southern California, we studied the linkage of the variability of sea surface temperature across three nested spatial scales, the north Pacific Basin, the West Coast of North American, and the Southern California Bight. Specifically, we analyzed daily GHRSST images between September 1981 and July 2009. In order to remove seasonal changes in temperature and focus upon differences between years, we calculate weekly mean temperature for each pixel from the time series, and then subjected the anomalies for the 3 spatial scales to empirical orthogonal function (EOF) analysis. The corresponding temporal expansion coefficients and spatial components (eigenvector) for each EOF mode were then generated to examine the temporal and spatial patterns of SST change. The results showed that the El Nino Southern Oscillation (ENSO) has a clear influence on the SST variability across all the three spatial scales, especially the 1st EOF mode which represents the largest variance. The comparison between the time coefficients of the 1st EOF mode and the Oceanic Nino Index (ONI) suggested that the EOF mode 1 of the Pacific Basin region matched well with almost all the El Nino and La Nina signals while the West Coast of North American captured only the strong signals and the Southern California Bight captures still fewer of the signals. This clearly indicated that the Southern California Bight is relatively insensitive to ENSO signal relative to other locations along the West Coast. The 1st EOF Mode for the West Coast of North American was also clearly influenced by upwelling. The cross correlation coefficient between each pair of the EOF mode 1 temporal expansion coefficients for the three spatial scales suggested that they were significantly correlated to each other. The effect of the Pacific Decadal Oscillation (PDO) on the SST change was also demonstrated by the temporal variability of

  14. Risk assessment of groundwater level variability using variable Kriging methods

    NASA Astrophysics Data System (ADS)

    Spanoudaki, Katerina; Kampanis, Nikolaos A.

    2015-04-01

    Assessment of the water table level spatial variability in aquifers provides useful information regarding optimal groundwater management. This information becomes more important in basins where the water table level has fallen significantly. The spatial variability of the water table level in this work is estimated based on hydraulic head measured during the wet period of the hydrological year 2007-2008, in a sparsely monitored basin in Crete, Greece, which is of high socioeconomic and agricultural interest. Three Kriging-based methodologies are elaborated in Matlab environment to estimate the spatial variability of the water table level in the basin. The first methodology is based on the Ordinary Kriging approach, the second involves auxiliary information from a Digital Elevation Model in terms of Residual Kriging and the third methodology calculates the probability of the groundwater level to fall below a predefined minimum value that could cause significant problems in groundwater resources availability, by means of Indicator Kriging. The Box-Cox methodology is applied to normalize both the data and the residuals for improved prediction results. In addition, various classical variogram models are applied to determine the spatial dependence of the measurements. The Matérn model proves to be the optimal, which in combination with Kriging methodologies provides the most accurate cross validation estimations. Groundwater level and probability maps are constructed to examine the spatial variability of the groundwater level in the basin and the associated risk that certain locations exhibit regarding a predefined minimum value that has been set for the sustainability of the basin's groundwater resources. Acknowledgement The work presented in this paper has been funded by the Greek State Scholarships Foundation (IKY), Fellowships of Excellence for Postdoctoral Studies (Siemens Program), 'A simulation-optimization model for assessing the best practices for the

  15. Effect of land use on the spatial variability of organic matter and nutrient status in an Oxisol

    NASA Astrophysics Data System (ADS)

    Paz-Ferreiro, Jorge; Alves, Marlene Cristina; Vidal Vázquez, Eva

    2013-04-01

    Heterogeneity is now considered as an inherent soil property. Spatial variability of soil attributes in natural landscapes results mainly from soil formation factors. In cultivated soils much heterogeneity can additionally occur as a result of land use, agricultural systems and management practices. Organic matter content (OMC) and nutrients associated to soil exchange complex are key attribute in the maintenance of a high quality soil. Neglecting spatial heterogeneity in soil OMC and nutrient status at the field scale might result in reduced yield and in environmental damage. We analyzed the impact of land use on the pattern of spatial variability of OMC and soil macronutrients at the stand scale. The study was conducted in São Paulo state, Brazil. Land uses were pasture, mango orchard and corn field. Soil samples were taken at 0-10 cm and 10-20 cm depth in 84 points, within 100 m x 100 m plots. Texture, pH, OMC, cation exchange capacity (CEC), exchangeable cations (Ca, Mg, K, H, Al) and resin extractable phosphorus were analyzed.. Statistical variability was found to be higher in parameters defining the soil nutrient status (resin extractable P, K, Ca and Mg) than in general soil properties (OMC, CEC, base saturation and pH). Geostatistical analysis showed contrasting patterns of spatial dependence for the different soil uses, sampling depths and studied properties. Most of the studied data sets collected at two different depths exhibited spatial dependence at the sampled scale and their semivariograms were modeled by a nugget effect plus a structure. The pattern of soil spatial variability was found to be different between the three study soil uses and at the two sampling depths, as far as model type, nugget effect or ranges of spatial dependence were concerned. Both statistical and geostatistical results pointed out the importance of OMC as a driver responsible for the spatial variability of soil nutrient status.

  16. Spatial Variability in Biodegradation Rates as Evidenced by Methane Production from an Aquifer

    PubMed Central

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

    1994-01-01

    Accurate predictions of carbon and energy cycling rates in the environment depend on sampling frequencies and on the spatial variability associated with biological activities. We examined the variability associated with anaerobic biodegradation rates at two sites in an alluvial sand aquifer polluted by municipal landfill leachate. In situ rates of methane production were measured for almost a year, using anaerobic wells installed at two sites. Methane production ranged from 0 to 560 μmol · m-2 · day-1 at one site (A), while a range of 0 to 120,000 μmol · m-2 · day-1 was measured at site B. The mean and standard deviations associated with methane production at site A were 17 and 57 μmol · m-2 · day-1, respectively. The comparable summary statistics for site B were 2,000 and 9,900 μmol · m-2 · day-1. The coefficients of variation at sites A and B were 340 and 490%, respectively. Despite these differences, the two sites had similar seasonal trends, with the maximal rate of methane production occurring in summer. However, the relative variability associated with the seasonal rates changed very little. Our results suggest that (i) two spatially distinct sites exist in the aquifer, (ii) methanogenesis is a highly variable process, (iii) the coefficient of variation varied little with the rate of methane production, and (iv) in situ anaerobic biodegradation rates are lognormally distributed. PMID:16349410

  17. Identifying public water facilities with low spatial variability of disinfection by-products for epidemiological investigations

    PubMed Central

    Hinckley, A; Bachand, A; Nuckols, J; Reif, J

    2005-01-01

    Background and Aims: Epidemiological studies of disinfection by-products (DBPs) and reproductive outcomes have been hampered by misclassification of exposure. In most epidemiological studies conducted to date, all persons living within the boundaries of a water distribution system have been assigned a common exposure value based on facility-wide averages of trihalomethane (THM) concentrations. Since THMs do not develop uniformly throughout a distribution system, assignment of facility-wide averages may be inappropriate. One approach to mitigate this potential for misclassification is to select communities for epidemiological investigations that are served by distribution systems with consistently low spatial variability of THMs. Methods and Results: A feasibility study was conducted to develop methods for community selection using the Information Collection Rule (ICR) database, assembled by the US Environmental Protection Agency. The ICR database contains quarterly DBP concentrations collected between 1997 and 1998 from the distribution systems of 198 public water facilities with minimum service populations of 100 000 persons. Facilities with low spatial variation of THMs were identified using two methods; 33 facilities were found with low spatial variability based on one or both methods. Because brominated THMs may be important predictors of risk for adverse reproductive outcomes, sites were categorised into three exposure profiles according to proportion of brominated THM species and average TTHM concentration. The correlation between THMs and haloacetic acids (HAAs) in these facilities was evaluated to see whether selection by total trihalomethanes (TTHMs) corresponds to low spatial variability for HAAs. TTHMs were only moderately correlated with HAAs (r = 0.623). Conclusions: Results provide a simple method for a priori selection of sites with low spatial variability from state or national public water facility datasets as a means to reduce exposure

  18. The Effects of Spatial Stimulus-Response Compatibility on Choice Time Production Accuracy and Variability

    ERIC Educational Resources Information Center

    Rakitin, Brian C.

    2005-01-01

    Five experiments examined the relations between timing and attention using a choice time production task in which the latency of a spatial choice response is matched to a target interval (3 or 5 s). Experiments 1 and 2 indicated that spatial stimulus-response incompatibility increased nonscalar timing variability without affecting timing accuracy…

  19. Spatial and temporal variability in response to hybrid electro-optical stimulation

    NASA Astrophysics Data System (ADS)

    Duke, Austin R.; Lu, Hui; Jenkins, Michael W.; Chiel, Hillel J.; Jansen, E. Duco

    2012-06-01

    Hybrid electro-optical neural stimulation is a novel paradigm combining the advantages of optical and electrical stimulation techniques while reducing their respective limitations. However, in order to fulfill its promise, this technique requires reduced variability and improved reproducibility. Here we used a comparative physiological approach to aid the further development of this technique by identifying the spatial and temporal factors characteristic of hybrid stimulation that may contribute to experimental variability and/or a lack of reproducibility. Using transient pulses of infrared light delivered simultaneously with a bipolar electrical stimulus in either the marine mollusk Aplysia californica buccal nerve or the rat sciatic nerve, we determined the existence of a finite region of excitability with size altered by the strength of the optical stimulus and recruitment dictated by the polarity of the electrical stimulus. Hybrid stimulation radiant exposures yielding 50% probability of firing (RE50) were shown to be negatively correlated with the underlying changes in electrical stimulation threshold over time. In Aplysia, but not in the rat sciatic nerve, increasing optical radiant exposures (J cm-2) beyond the RE50 ultimately resulted in inhibition of evoked potentials. Accounting for the sources of variability identified in this study increased the reproducibility of stimulation from 35% to 93% in Aplysia and 23% to 76% in the rat with reduced variability.

  20. Contribution of geodiversity, climate and spatial variables for biodiversity across a gradient of human influence

    NASA Astrophysics Data System (ADS)

    Tukiainen, Helena; Alahuhta, Janne; Ala-Hulkko, Terhi; Field, Richard; Lampinen, Raino; Hjort, Jan

    2016-04-01

    Implementation of geodiversity may provide new perspectives for nature conservation. The relation between geodiversity and biodiversity has been established in recent studies but remains underexplored in environments with high human pressure. In this study, we explored the effect of geodiversity (i.e. geological, hydrological and geomorphological diversity), climate and spatial variables on biodiversity (vascular plant species richness) in environments with different human impact. The study area ranged trough the boreal vegetation zone in Finland and included altogether 1401 1-km2 grid cells from urban, rural and natural environments. The contribution of environmental variable groups for species diversity in different environments was statistically analyzed with variation partitioning method. According to the results, the contribution of geodiversity decreased and the contribution of climate and spatial variables increased as the land use became more human-induced. Hence, the connection between geodiversity and species richness was most pronounced in natural state environments.

  1. Developing a spatial-statistical model and map of historical malaria prevalence in Botswana using a staged variable selection procedure

    PubMed Central

    Craig, Marlies H; Sharp, Brian L; Mabaso, Musawenkosi LH; Kleinschmidt, Immo

    2007-01-01

    Background Several malaria risk maps have been developed in recent years, many from the prevalence of infection data collated by the MARA (Mapping Malaria Risk in Africa) project, and using various environmental data sets as predictors. Variable selection is a major obstacle due to analytical problems caused by over-fitting, confounding and non-independence in the data. Testing and comparing every combination of explanatory variables in a Bayesian spatial framework remains unfeasible for most researchers. The aim of this study was to develop a malaria risk map using a systematic and practicable variable selection process for spatial analysis and mapping of historical malaria risk in Botswana. Results Of 50 potential explanatory variables from eight environmental data themes, 42 were significantly associated with malaria prevalence in univariate logistic regression and were ranked by the Akaike Information Criterion. Those correlated with higher-ranking relatives of the same environmental theme, were temporarily excluded. The remaining 14 candidates were ranked by selection frequency after running automated step-wise selection procedures on 1000 bootstrap samples drawn from the data. A non-spatial multiple-variable model was developed through step-wise inclusion in order of selection frequency. Previously excluded variables were then re-evaluated for inclusion, using further step-wise bootstrap procedures, resulting in the exclusion of another variable. Finally a Bayesian geo-statistical model using Markov Chain Monte Carlo simulation was fitted to the data, resulting in a final model of three predictor variables, namely summer rainfall, mean annual temperature and altitude. Each was independently and significantly associated with malaria prevalence after allowing for spatial correlation. This model was used to predict malaria prevalence at unobserved locations, producing a smooth risk map for the whole country. Conclusion We have produced a highly plausible and

  2. Influence of spatial variability of hydraulic characteristics of soils on surface parameters obtained from remote sensing data in infrared and microwaves

    NASA Technical Reports Server (NTRS)

    Brunet, Y.; Vauclin, M.

    1985-01-01

    The correct interpretation of thermal and hydraulic soil parameters infrared from remotely sensed data (thermal infrared, microwaves) implies a good understanding of the causes of their temporal and spatial variability. Given this necessity, the sensitivity of the surface variables (temperature, moisture) to the spatial variability of hydraulic soil properties is tested with a numerical model of heat and mass transfer between bare soil and atmosphere. The spatial variability of hydraulic soil properties is taken into account in terms of the scaling factor. For a given soil, the knowledge of its frequency distribution allows a stochastic use of the model. The results are treated statistically, and the part of the variability of soil surface parameters due to that of soil hydraulic properties is evaluated quantitatively.

  3. Delineation of Spatial Variability in the Temperature-Mortality Relationship on Extremely Hot Days in Greater Vancouver, Canada.

    PubMed

    Ho, Hung Chak; Knudby, Anders; Walker, Blake Byron; Henderson, Sarah B

    2017-01-01

    Climate change has increased the frequency and intensity of extremely hot weather. The health risks associated with extemely hot weather are not uniform across affected areas owing to variability in heat exposure and social vulnerability, but these differences are challenging to map with precision. We developed a spatially and temporally stratified case-crossover approach for delineation of areas with higher and lower risks of mortality on extremely hot days and applied this approach in greater Vancouver, Canada. Records of all deaths with an extremely hot day as a case day or a control day were extracted from an administrative vital statistics database spanning the years of 1998-2014. Three heat exposure and 11 social vulnerability variables were assigned at the residential location of each decedent. Conditional logistic regression was used to estimate the odds ratio for a 1°C increase in daily mean temperature at a fixed site with an interaction term for decedents living above and below different values of the spatial variables. The heat exposure and social vulnerability variables with the strongest spatially stratified results were the apparent temperature and the labor nonparticipation rate, respectively. Areas at higher risk had values ≥ 34.4°C for the maximum apparent temperature and ≥ 60% of the population neither employed nor looking for work. These variables were combined in a composite index to quantify their interaction and to enhance visualization of high-risk areas. Our methods provide a data-driven framework for spatial delineation of the temperature--mortality relationship by heat exposure and social vulnerability. The results can be used to map and target the most vulnerable areas for public health intervention. Citation: Ho HC, Knudby A, Walker BB, Henderson SB. 2017. Delineation of spatial variability in the temperature-mortality relationship on extremely hot days in greater Vancouver, Canada. Environ Health Perspect 125:66-75;

  4. Delineation of Spatial Variability in the Temperature–Mortality Relationship on Extremely Hot Days in Greater Vancouver, Canada

    PubMed Central

    Ho, Hung Chak; Knudby, Anders; Walker, Blake Byron; Henderson, Sarah B.

    2016-01-01

    Background: Climate change has increased the frequency and intensity of extremely hot weather. The health risks associated with extemely hot weather are not uniform across affected areas owing to variability in heat exposure and social vulnerability, but these differences are challenging to map with precision. Objectives: We developed a spatially and temporally stratified case-crossover approach for delineation of areas with higher and lower risks of mortality on extremely hot days and applied this approach in greater Vancouver, Canada. Methods: Records of all deaths with an extremely hot day as a case day or a control day were extracted from an administrative vital statistics database spanning the years of 1998–2014. Three heat exposure and 11 social vulnerability variables were assigned at the residential location of each decedent. Conditional logistic regression was used to estimate the odds ratio for a 1°C increase in daily mean temperature at a fixed site with an interaction term for decedents living above and below different values of the spatial variables. Results: The heat exposure and social vulnerability variables with the strongest spatially stratified results were the apparent temperature and the labor nonparticipation rate, respectively. Areas at higher risk had values ≥ 34.4°C for the maximum apparent temperature and ≥ 60% of the population neither employed nor looking for work. These variables were combined in a composite index to quantify their interaction and to enhance visualization of high-risk areas. Conclusions: Our methods provide a data-driven framework for spatial delineation of the temperature-–mortality relationship by heat exposure and social vulnerability. The results can be used to map and target the most vulnerable areas for public health intervention. Citation: Ho HC, Knudby A, Walker BB, Henderson SB. 2017. Delineation of spatial variability in the temperature–mortality relationship on extremely hot days in greater

  5. Spatial variability of turbulent fluxes in the roughness sublayer of an even-aged pine forest

    USGS Publications Warehouse

    Katul, G.; Hsieh, C.-I.; Bowling, D.; Clark, K.; Shurpali, N.; Turnipseed, A.; Albertson, J.; Tu, K.; Hollinger, D.; Evans, B. M.; Offerle, B.; Anderson, D.; Ellsworth, D.; Vogel, C.; Oren, R.

    1999-01-01

    The spatial variability of turbulent flow statistics in the roughness sublayer (RSL) of a uniform even-aged 14 m (= h) tall loblolly pine forest was investigated experimentally. Using seven existing walkup towers at this stand, high frequency velocity, temperature, water vapour and carbon dioxide concentrations were measured at 15.5 m above the ground surface from October 6 to 10 in 1997. These seven towers were separated by at least 100 m from each other. The objective of this study was to examine whether single tower turbulence statistics measurements represent the flow properties of RSL turbulence above a uniform even-aged managed loblolly pine forest as a best-case scenario for natural forested ecosystems. From the intensive space-time series measurements, it was demonstrated that standard deviations of longitudinal and vertical velocities (??(u), ??(w)) and temperature (??(T)) are more planar homogeneous than their vertical flux of momentum (u(*)2) and sensible heat (H) counterparts. Also, the measured H is more horizontally homogeneous when compared to fluxes of other scalar entities such as CO2 and water vapour. While the spatial variability in fluxes was significant (> 15%), this unique data set confirmed that single tower measurements represent the 'canonical' structure of single-point RSL turbulence statistics, especially flux-variance relationships. Implications to extending the 'moving-equilibrium' hypothesis for RSL flows are discussed. The spatial variability in all RSL flow variables was not constant in time and varied strongly with spatially averaged friction velocity u(*), especially when u(*) was small. It is shown that flow properties derived from two-point temporal statistics such as correlation functions are more sensitive to local variability in leaf area density when compared to single point flow statistics. Specifically, that the local relationship between the reciprocal of the vertical velocity integral time scale (I(w)) and the arrival

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

    NASA Astrophysics Data System (ADS)

    Morev, Dmitriy; Vasenev, Ivan

    2015-04-01

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

  7. Longterm and spatial variability of Aerosol optical properties measured by sky radiometer in Japan sites

    NASA Astrophysics Data System (ADS)

    Aoki, K.

    2016-12-01

    Aerosols and cloud play an important role in the climate change. We started the long-term monitoring of aerosol and cloud optical properties since 1990's by using sky radiometer (POM-01, 02; Prede Co. Ltd., Japan). We provide the information, in this presentation, on the aerosol optical properties with respect to their temporal and spatial variability in Japan site (ex. Sapporo, Toyama, Kasuga and etc). The global distributions of aerosols have been derived from earth observation satellite and have been simulated in numerical models, which assume optical parameters. However, these distributions are difficult to derive because of variability in time and space. Therefore, Aerosol optical properties were investigated using the measurements from ground-based and ship-borne sky radiometer. The sky radiometer is an automatic instrument that takes observations only in daytime under the clear sky conditions. Observation of diffuse solar intensity interval was made every ten or five minutes by once. The aerosol optical properties were computed using the SKYRAD.pack version 4.2. The obtained Aerosol optical properties (Aerosol optical thickness, Ångström exponent, Single scattering albedo, and etc.) and size distribution volume clearly showed spatial and temporal variability in Japan area. In this study, we present the temporal and spatial variability of Aerosol optical properties at several Japan sites, applied to validation of satellite and numerical models. This project is validation satellite of GCOM-C, JAXA. The GCOM-C satellite scheduled to be launched in early 2017.

  8. Controls on the spatial variability of key soil properties: comparing field data with a mechanistic soilscape evolution model

    NASA Astrophysics Data System (ADS)

    Vanwalleghem, T.; Román, A.; Giraldez, J. V.

    2016-12-01

    There is a need for better understanding the processes influencing soil formation and the resulting distribution of soil properties. Soil properties can exhibit strong spatial variation, even at the small catchment scale. Especially soil carbon pools in semi-arid, mountainous areas are highly uncertain because bulk density and stoniness are very heterogeneous and rarely measured explicitly. In this study, we explore the spatial variability in key soil properties (soil carbon stocks, stoniness, bulk density and soil depth) as a function of processes shaping the critical zone (weathering, erosion, soil water fluxes and vegetation patterns). We also compare the potential of a geostatistical versus a mechanistic soil formation model (MILESD) for predicting these key soil properties. Soil core samples were collected from 67 locations at 6 depths. Total soil organic carbon stocks were 4.38 kg m-2. Solar radiation proved to be the key variable controlling soil carbon distribution. Stone content was mostly controlled by slope, indicating the importance of erosion. Spatial distribution of bulk density was found to be highly random. Finally, total carbon stocks were predicted using a random forest model whose main covariates were solar radiation and NDVI. The model predicts carbon stocks that are double as high on north versus south-facing slopes. However, validation showed that these covariates only explained 25% of the variation in the dataset. Apparently, present-day landscape and vegetation properties are not sufficient to fully explain variability in the soil carbon stocks in this complex terrain under natural vegetation. This is attributed to a high spatial variability in bulk density and stoniness, key variables controlling carbon stocks. Similar results were obtained with the mechanistic soil formation model MILESD, suggesting that more complex models might be needed to further explore this high spatial variability.

  9. Effects of spatial variability and scale on areal -average evapotranspiration

    NASA Technical Reports Server (NTRS)

    Famiglietti, J. S.; Wood, Eric F.

    1993-01-01

    This paper explores the effect of spatial variability and scale on areally-averaged evapotranspiration. A spatially-distributed water and energy balance model is employed to determine the effect of explicit patterns of model parameters and atmospheric forcing on modeled areally-averaged evapotranspiration over a range of increasing spatial scales. The analysis is performed from the local scale to the catchment scale. The study area is King's Creek catchment, an 11.7 sq km watershed located on the native tallgrass prairie of Kansas. The dominant controls on the scaling behavior of catchment-average evapotranspiration are investigated by simulation, as is the existence of a threshold scale for evapotranspiration modeling, with implications for explicit versus statistical representation of important process controls. It appears that some of our findings are fairly general, and will therefore provide a framework for understanding the scaling behavior of areally-averaged evapotranspiration at the catchment and larger scales.

  10. Using geomorphological variables to predict the spatial distribution of plant species in agricultural drainage networks

    PubMed Central

    Bailly, Jean-Stéphane; Vinatier, Fabrice

    2018-01-01

    To optimize ecosystem services provided by agricultural drainage networks (ditches) in headwater catchments, we need to manage the spatial distribution of plant species living in these networks. Geomorphological variables have been shown to be important predictors of plant distribution in other ecosystems because they control the water regime, the sediment deposition rates and the sun exposure in the ditches. Whether such variables may be used to predict plant distribution in agricultural drainage networks is unknown. We collected presence and absence data for 10 herbaceous plant species in a subset of a network of drainage ditches (35 km long) within a Mediterranean agricultural catchment. We simulated their spatial distribution with GLM and Maxent model using geomorphological variables and distance to natural lands and roads. Models were validated using k-fold cross-validation. We then compared the mean Area Under the Curve (AUC) values obtained for each model and other metrics issued from the confusion matrices between observed and predicted variables. Based on the results of all metrics, the models were efficient at predicting the distribution of seven species out of ten, confirming the relevance of geomorphological variables and distance to natural lands and roads to explain the occurrence of plant species in this Mediterranean catchment. In particular, the importance of the landscape geomorphological variables, ie the importance of the geomorphological features encompassing a broad environment around the ditch, has been highlighted. This suggests that agro-ecological measures for managing ecosystem services provided by ditch plants should focus on the control of the hydrological and sedimentological connectivity at the catchment scale. For example, the density of the ditch network could be modified or the spatial distribution of vegetative filter strips used for sediment trapping could be optimized. In addition, the vegetative filter strips could constitute

  11. Spatial variability of soil properties and soil erodibility in the Alqueva reservoir watershed

    NASA Astrophysics Data System (ADS)

    Ferreira, V.; Panagopoulos, T.; Andrade, R.; Guerrero, C.; Loures, L.

    2015-04-01

    The aim of this work is to investigate how the spatial variability of soil properties and soil erodibility (K factor) were affected by the changes in land use allowed by irrigation with water from a reservoir in a semiarid area. To this end, three areas representative of different land uses (agroforestry grassland, lucerne crop and olive orchard) were studied within a 900 ha farm. The interrelationships between variables were analyzed by multivariate techniques and extrapolated using geostatistics. The results confirmed differences between land uses for all properties analyzed, which was explained mainly by the existence of diverse management practices (tillage, fertilization and irrigation), vegetation cover and local soil characteristics. Soil organic matter, clay and nitrogen content decreased significantly, while the K factor increased with intensive cultivation. The HJ-Biplot methodology was used to represent the variation of soil erodibility properties grouped in land uses. Native grassland was the least correlated with the other land uses. The K factor demonstrated high correlation mainly with very fine sand and silt. The maps produced with geostatistics were crucial to understand the current spatial variability in the Alqueva region. Facing the intensification of land-use conversion, a sustainable management is needed to introduce protective measures to control soil erosion.

  12. Effects of Spatial Variability of Soil Properties on the Triggering of Rainfall-Induced Shallow Landslides

    NASA Astrophysics Data System (ADS)

    Fan, Linfeng; Lehmann, Peter; Or, Dani

    2015-04-01

    Naturally-occurring spatial variations in soil properties (e.g., soil depth, moisture, and texture) affect key hydrological processes and potentially the mechanical response of soil to hydromechanical loading (relative to the commonly-assumed uniform soil mantle). We quantified the effects of soil spatial variability on the triggering of rainfall-induced shallow landslides at the hillslope- and catchment-scales, using a physically-based landslide triggering model that considers interacting soil columns with mechanical strength thresholds (represented by the Fiber Bundle Model). The spatial variations in soil properties are represented as Gaussian random distributions and the level of variation is characterized by the coefficient of variation and correlation lengths of soil properties (i.e., soil depth, soil texture and initial water content in this study). The impacts of these spatial variations on landslide triggering characteristics were measured by comparing the times to triggering and landslide volumes for heterogeneous soil properties and homogeneous cases. Results at hillslope scale indicate that for spatial variations of an individual property (without cross correlation), the increasing of coefficient of variation introduces weak spots where mechanical damage is accelerated and leads to earlier onset of landslide triggering and smaller volumes. Increasing spatial correlation length of soil texture and initial water content also induces early landslide triggering and small released volumes due to the transition of failure mode from brittle to ductile failure. In contrast, increasing spatial correlation length of soil depth "reduces" local steepness and postpones landslide triggering. Cross-correlated soil properties generally promote landslide initiation, but depending on the internal structure of spatial distribution of each soil property, landslide triggering may be reduced. The effects of cross-correlation between initial water content and soil texture

  13. Spatial variability of sediment transport processes over intra‐ and subtidal timescales within a fringing coral reef system

    USGS Publications Warehouse

    Pomeroy, Andrew; Lowe, Ryan J.; Ghisalberti, Marco; Winter, Gundula; Storlazzi, Curt D.; Cuttler, Michael V. W.

    2018-01-01

    Sediment produced on fringing coral reefs that is transported along the bed or in suspension affects ecological reef communities as well as the morphological development of the reef, lagoon, and adjacent shoreline. This study quantified the physical process contribution and relative importance of incident waves, infragravity waves, and mean currents to the spatial and temporal variability of sediment in suspension. Estimates of bed shear stresses demonstrate that incident waves are the key driver of the SSC variability spatially (reef flat, lagoon, and channels) but cannot not fully describe the SSC variability alone. The comparatively small but statistically significant contribution to the bed shear stress by infragravity waves and currents, along with the spatial availability of sediment of a suitable size and volume, is also important. Although intra‐tidal variability in SSC occurs in the different reef zones, the majority of the variability occurs over longer slowly varying (subtidal) time scales, which is related to the arrival of large incident waves at a reef location. The predominant flow pathway, which can transport suspended sediment, consists of cross‐reef flow across the reef flat that diverges in the lagoon and returns offshore through channels. This pathway is primarily due to subtidal variations in wave‐driven flows, but can also be driven alongshore by wind stresses when the incident waves are small. Higher frequency (intra‐tidal) current variability also occur due to both tidal flows, as well as variations in the water depth that influence wave transmission across the reef and wave‐driven currents.

  14. Spatial Models for Prediction and Early Warning of Aedes aegypti Proliferation from Data on Climate Change and Variability in Cuba.

    PubMed

    Ortiz, Paulo L; Rivero, Alina; Linares, Yzenia; Pérez, Alina; Vázquez, Juan R

    2015-04-01

    Climate variability, the primary expression of climate change, is one of the most important environmental problems affecting human health, particularly vector-borne diseases. Despite research efforts worldwide, there are few studies addressing the use of information on climate variability for prevention and early warning of vector-borne infectious diseases. Show the utility of climate information for vector surveillance by developing spatial models using an entomological indicator and information on predicted climate variability in Cuba to provide early warning of danger of increased risk of dengue transmission. An ecological study was carried out using retrospective and prospective analyses of time series combined with spatial statistics. Several entomological and climatic indicators were considered using complex Bultó indices -1 and -2. Moran's I spatial autocorrelation coefficient specified for a matrix of neighbors with a radius of 20 km, was used to identify the spatial structure. Spatial structure simulation was based on simultaneous autoregressive and conditional autoregressive models; agreement between predicted and observed values for number of Aedes aegypti foci was determined by the concordance index Di and skill factor Bi. Spatial and temporal distributions of populations of Aedes aegypti were obtained. Models for describing, simulating and predicting spatial patterns of Aedes aegypti populations associated with climate variability patterns were put forward. The ranges of climate variability affecting Aedes aegypti populations were identified. Forecast maps were generated for the municipal level. Using the Bultó indices of climate variability, it is possible to construct spatial models for predicting increased Aedes aegypti populations in Cuba. At 20 x 20 km resolution, the models are able to provide warning of potential changes in vector populations in rainy and dry seasons and by month, thus demonstrating the usefulness of climate information for

  15. A multi-scale comparison of trait linkages to environmental and spatial variables in fish communities across a large freshwater lake.

    PubMed

    Strecker, Angela L; Casselman, John M; Fortin, Marie-Josée; Jackson, Donald A; Ridgway, Mark S; Abrams, Peter A; Shuter, Brian J

    2011-07-01

    Species present in communities are affected by the prevailing environmental conditions, and the traits that these species display may be sensitive indicators of community responses to environmental change. However, interpretation of community responses may be confounded by environmental variation at different spatial scales. Using a hierarchical approach, we assessed the spatial and temporal variation of traits in coastal fish communities in Lake Huron over a 5-year time period (2001-2005) in response to biotic and abiotic environmental factors. The association of environmental and spatial variables with trophic, life-history, and thermal traits at two spatial scales (regional basin-scale, local site-scale) was quantified using multivariate statistics and variation partitioning. We defined these two scales (regional, local) on which to measure variation and then applied this measurement framework identically in all 5 study years. With this framework, we found that there was no change in the spatial scales of fish community traits over the course of the study, although there were small inter-annual shifts in the importance of regional basin- and local site-scale variables in determining community trait composition (e.g., life-history, trophic, and thermal). The overriding effects of regional-scale variables may be related to inter-annual variation in average summer temperature. Additionally, drivers of fish community traits were highly variable among study years, with some years dominated by environmental variation and others dominated by spatially structured variation. The influence of spatial factors on trait composition was dynamic, which suggests that spatial patterns in fish communities over large landscapes are transient. Air temperature and vegetation were significant variables in most years, underscoring the importance of future climate change and shoreline development as drivers of fish community structure. Overall, a trait-based hierarchical framework may

  16. Spatial Variability of the Topsoil Organic Carbon in the Moso Bamboo Forests of Southern China in Association with Soil Properties

    PubMed Central

    Zhang, Houxi; Zhuang, Shunyao; Qian, Haiyan; Wang, Feng; Ji, Haibao

    2015-01-01

    Understanding the spatial variability of soil organic carbon (SOC) must be enhanced to improve sampling design and to develop soil management strategies in terrestrial ecosystems. Moso bamboo (Phyllostachys pubescens Mazel ex Houz.) forests have a high SOC storage potential; however, they also vary significantly spatially. This study investigated the spatial variability of SOC (0-20 cm) in association with other soil properties and with spatial variables in the Moso bamboo forests of Jian’ou City, which is a typical bamboo hometown in China. 209 soil samples were collected from Moso bamboo stands and then analyzed for SOC, bulk density (BD), pH, cation exchange capacity (CEC), and gravel content (GC) based on spatial distribution. The spatial variability of SOC was then examined using geostatistics. A Kriging map was produced through ordinary interpolation and required sample numbers were calculated by classical and Kriging methods. An aggregated boosted tree (ABT) analysis was also conducted. A semivariogram analysis indicated that ln(SOC) was best fitted with an exponential model and that it exhibited moderate spatial dependence, with a nugget/sill ratio of 0.462. SOC was significantly and linearly correlated with BD (r = −0.373**), pH (r = −0.429**), GC (r = −0.163*), CEC (r = 0.263**), and elevation (r = 0.192**). Moreover, the Kriging method requires fewer samples than the classical method given an expected standard error level as per a variance analysis. ABT analysis indicated that the physicochemical variables of soil affected SOC variation more significantly than spatial variables did, thus suggesting that the SOC in Moso bamboo forests can be strongly influenced by management practices. Thus, this study provides valuable information in relation to sampling strategy and insight into the potential of adjustments in agronomic measure, such as in fertilization for Moso bamboo production. PMID:25789615

  17. Minimizing Spatial Variability of Healthcare Spatial Accessibility-The Case of a Dengue Fever Outbreak.

    PubMed

    Chu, Hone-Jay; Lin, Bo-Cheng; Yu, Ming-Run; Chan, Ta-Chien

    2016-12-13

    Outbreaks of infectious diseases or multi-casualty incidents have the potential to generate a large number of patients. It is a challenge for the healthcare system when demand for care suddenly surges. Traditionally, valuation of heath care spatial accessibility was based on static supply and demand information. In this study, we proposed an optimal model with the three-step floating catchment area (3SFCA) to account for the supply to minimize variability in spatial accessibility. We used empirical dengue fever outbreak data in Tainan City, Taiwan in 2015 to demonstrate the dynamic change in spatial accessibility based on the epidemic trend. The x and y coordinates of dengue-infected patients with precision loss were provided publicly by the Tainan City government, and were used as our model's demand. The spatial accessibility of heath care during the dengue outbreak from August to October 2015 was analyzed spatially and temporally by producing accessibility maps, and conducting capacity change analysis. This study also utilized the particle swarm optimization (PSO) model to decrease the spatial variation in accessibility and shortage areas of healthcare resources as the epidemic went on. The proposed method in this study can help decision makers reallocate healthcare resources spatially when the ratios of demand and supply surge too quickly and form clusters in some locations.

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

    PubMed

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

    2018-01-01

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

  19. Consistent patterns of variation in macrobenthic assemblages and environmental variables over multiple spatial scales using taxonomic and functional approaches.

    PubMed

    Veiga, Puri; Torres, Ana Catarina; Aneiros, Fernando; Sousa-Pinto, Isabel; Troncoso, Jesús S; Rubal, Marcos

    2016-09-01

    Spatial variability of environmental factors and macrobenthos, using species and functional groups, was examined over the same scales (100s of cm to >100 km) in intertidal sediments of two transitional water systems. The objectives were to test if functional groups were a good species surrogate and explore the relationship between environmental variables and macrobenthos. Environmental variables, diversity and the multivariate assemblage structure showed the highest variability at the scale of 10s of km. However, abundance was more variable at 10s of m. Consistent patterns were achieved using species and functional groups therefore, these may be a good species surrogate. Total carbon, salinity and silt/clay were the strongest correlated with macrobenthic assemblages. Results are valuable for design and interpretation of future monitoring programs including detection of anthropogenic disturbances in transitional systems and propose improvements in environmental variable sampling to refine the assessment of their relationship with biological data across spatial scales. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

  1. Multiscale drivers of spatially variable grass production and loss in the Chihuahuan Desert

    USDA-ARS?s Scientific Manuscript database

    Historic regime shifts from grass- to shrub-dominated states have been widespread in the Chihuahuan Desert and other arid and semiarid regions globally. These patterns of grass production and shifts to shrub dominance are spatially variable, and show a weak correlation with precipitation, suggesting...

  2. Spatial Variability and Stocks of Soil Organic Carbon in the Gobi Desert of Northwestern China

    PubMed Central

    Zhang, Pingping; Shao, Ming'an

    2014-01-01

    Soil organic carbon (SOC) plays an important role in improving soil properties and the C global cycle. Limited attention, though, has been given to assessing the spatial patterns and stocks of SOC in desert ecosystems. In this study, we quantitatively evaluated the spatial variability of SOC and its influencing factors and estimated SOC storage in a region (40 km2) of the Gobi desert. SOC exhibited a log-normal depth distribution with means of 1.6, 1.5, 1.4, and 1.4 g kg−1 for the 0–10, 10–20, 20–30, and 30–40 cm layers, respectively, and was moderately variable according to the coefficients of variation (37–42%). Variability of SOC increased as the sampling area expanded and could be well parameterized as a power function of the sampling area. Significant correlations were detected between SOC and soil physical properties, i.e. stone, sand, silt, and clay contents and soil bulk density. The relatively coarse fractions, i.e. sand, silt, and stone contents, had the largest effects on SOC variability. Experimental semivariograms of SOC were best fitted by exponential models. Nugget-to-sill ratios indicated a strong spatial dependence for SOC concentrations at all depths in the study area. The surface layer (0–10 cm) had the largest spatial dependency compared with the other layers. The mapping revealed a decreasing trend of SOC concentrations from south to north across this region of the Gobi desert, with higher levels close to an oasis and lower levels surrounded by mountains and near the desert. SOC density to depths of 20 and 40 cm for this 40 km2 area was estimated at 0.42 and 0.68 kg C m−2, respectively. This study provides an important contribution to understanding the role of the Gobi desert in the global carbon cycle. PMID:24733073

  3. Determining the spatial variability of personal sampler inlet locations.

    PubMed

    Vinson, Robert; Volkwein, Jon; McWilliams, Linda

    2007-09-01

    This article examines the spatial variability of dust concentrations within a coal miner's breathing zone and the impact of sampling location at the cap lamp, nose, and lapel. Tests were conducted in the National Institute for Safety and Health Pittsburgh Research Laboratory full-scale, continuous miner gallery using three prototype personal dust monitors (PDM). The dust masses detected by the PDMs were used to calculate the percentage difference of dust mass between the cap lamp and the nose and between the lapel and the nose. The calculated percentage differences of the masses ranged from plus 12% to minus 25%. Breathing zone tests were also conducted in four underground coal mines using the torso of a mannequin to simulate a miner. Coal mine dust was sampled with multi-cyclone sampling cans mounted directly in front of the mannequin near the cap lamp, nose, and lapel. These four coal mine tests found that the spatial variability of dust levels and imprecision of the current personal sampler is a greater influence than the sampler location within the breathing zone. However, a one-sample t-test of this data did find that the overall mean value of the cap lamp/nose ratio was not significantly different than 1 (p-value = 0.21). However, when applied to the overall mean value of the lapel/nose ratio there was a significant difference from 1 (p-value < .0001). This finding is important because the lapel has always been the sampling location for coal mine dust samples. But these results suggest that the cap location is slightly more indicative of what is breathed through the nose area.

  4. Methane Seeps in the Gulf of Mexico: repeat acoustic surveying shows highly temporally and spatially variable venting

    NASA Astrophysics Data System (ADS)

    Beaumont, B. C.; Raineault, N.

    2016-02-01

    Scientists have recognized that natural seeps account for a large amount of methane emissions. Despite their widespread occurrence in areas like the Gulf of Mexico, little is known about the temporal variability and site-scale spatial variability of venting over time. We used repeat acoustic surveys to compare multiple days of seep activity and determine the changes in the locus of methane emission and plume height. The Sleeping Dragon site was surveyed with an EM302 multibeam sonar on three consecutive days in 2014 and 4 days within one week in 2015. The data revealed three distinctive plume regions. The locus of venting varied by 10-60 meters at each site. The plume that exhibited the least spatial variability in venting, was also the most temporally variable. This seep was present in one-third of survey dates in 2014 and three quarters of survey dates in 2015, showing high day-to-day variability. The plume height was very consistent for this plume, whereas the other plumes were more consistent temporally, but varied in maximum plume height detection by 25-85 m. The single locus of emission at the site that had high day-to-day variability may be due to a single conduit for methane release, which is sometimes closed off by carbonate or clathrate hydrate formation. In addition to day-to-day temporal variability, the locus of emission at one site was observed to shift from a point-source in 2014 to a diffuse source in 2015 at a nearby location. ROV observations showed that one of the seep sites that closed off temporarily, experienced an explosive breakthrough of gas, releasing confined methane and blowing out rock. The mechanism that causes on/off behavior of certain plumes, combined with the spatial variability of the locus of methane release shown in this study may point to carbonate or hydrate formation in the seep plumbing system and should be further investigated.

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

    PubMed

    Pulla, Sandeep; Riotte, Jean; Suresh, H S; Dattaraja, H S; Sukumar, Raman

    2016-01-01

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

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

    PubMed Central

    Pulla, Sandeep; Riotte, Jean; Suresh, H. S.; Dattaraja, H. S.; Sukumar, Raman

    2016-01-01

    We examined the roles of lithology, topography, vegetation and fire in generating local-scale (<1 km2) soil spatial variability in a seasonally dry tropical forest (SDTF) in southern India. For this, we mapped soil (available nutrients, Al, total C, pH, moisture and texture in the top 10cm), rock outcrops, topography, all native woody plants ≥1 cm diameter at breast height (DBH), and spatial variation in fire frequency (times burnt during the 17 years preceding soil sampling) in a permanent 50-ha plot. Unlike classic catenas, lower elevation soils had lesser moisture, plant-available Ca, Cu, Mn, Mg, Zn, B, clay and total C. The distribution of plant-available Ca, Cu, Mn and Mg appeared to largely be determined by the whole-rock chemical composition differences between amphibolites and hornblende-biotite gneisses. Amphibolites were associated with summit positions, while gneisses dominated lower elevations, an observation that concurs with other studies in the region which suggest that hillslope-scale topography has been shaped by differential weathering of lithologies. Neither NO3−-N nor NH4+-N was explained by the basal area of trees belonging to Fabaceae, a family associated with N-fixing species, and no long-term effects of fire on soil parameters were detected. Local-scale lithological variation is an important first-order control over soil variability at the hillslope scale in this SDTF, by both direct influence on nutrient stocks and indirect influence via control of local relief. PMID:27100088

  7. Quantifying Spatial and Seasonal Variability in Atmospheric Ammonia with In Situ and Space-Based Observations

    NASA Technical Reports Server (NTRS)

    Pinder, Robert W.; Walker, John T.; Bash, Jesse O.; Cady-Pereira, Karen E.; Henze, Daven K.; Luo, Mingzhao; Osterman, Gregory B.; Shepard, Mark W.

    2011-01-01

    Ammonia plays an important role in many biogeochemical processes, yet atmospheric mixing ratios are not well known. Recently, methods have been developed for retrieving NH3 from space-based observations, but they have not been compared to in situ measurements. We have conducted a field campaign combining co-located surface measurements and satellite special observations from the Tropospheric Emission Spectrometer (TES). Our study includes 25 surface monitoring sites spanning 350 km across eastern North Carolina, a region with large seasonal and spatial variability in NH3. From the TES spectra, we retrieve a NH3 representative volume mixing ratio (RVMR), and we restrict our analysis to times when the region of the atmosphere observed by TES is representative of the surface measurement. We find that the TES NH3 RVMR qualitatively captures the seasonal and spatial variability found in eastern North Carolina. Both surface measurements and TES NH3 show a strong correspondence with the number of livestock facilities within 10 km of the observation. Furthermore, we find that TES H3 RVMR captures the month-to-month variability present in the surface observations. The high correspondence with in situ measurements and vast spatial coverage make TES NH3 RVMR a valuable tool for understanding regional and global NH3 fluxes.

  8. Industrial implementation of spatial variability control by real-time SPC

    NASA Astrophysics Data System (ADS)

    Roule, O.; Pasqualini, F.; Borde, M.

    2016-10-01

    Advanced technology nodes require more and more information to get the wafer process well setup. The critical dimension of components decreases following Moore's law. At the same time, the intra-wafer dispersion linked to the spatial non-uniformity of tool's processes is not capable to decrease in the same proportions. APC systems (Advanced Process Control) are being developed in waferfab to automatically adjust and tune wafer processing, based on a lot of process context information. It can generate and monitor complex intrawafer process profile corrections between different process steps. It leads us to put under control the spatial variability, in real time by our SPC system (Statistical Process Control). This paper will outline the architecture of an integrated process control system for shape monitoring in 3D, implemented in waferfab.

  9. Spatio-Temporal Variability of Groundwater Storage in India

    NASA Technical Reports Server (NTRS)

    Bhanja, Soumendra; Rodell, Matthew; Li, Bailing; Mukherjee, Abhijit

    2016-01-01

    Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Ground water storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent).In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.

  10. Spatio-temporal variability of groundwater storage in India.

    PubMed

    Bhanja, Soumendra N; Rodell, Matthew; Li, Bailing; Mukherjee, Abhijit

    2017-01-01

    Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Groundwater storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent). In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.

  11. Precision Viticulture : is it relevant to manage the vineyard according to the within field spatial variability of the environment ?

    NASA Astrophysics Data System (ADS)

    Tisseyre, Bruno

    2015-04-01

    For more than 15 years, research projects are conducted in the precision viticulture (PV) area around the world. These research projects have provided new insights into the within-field variability in viticulture. Indeed, access to high spatial resolution data (remote sensing, embedded sensors, etc.) changes the knowledge we have of the fields in viticulture. In particular, the field which was until now considered as a homogeneous management unit, presents actually a high spatial variability in terms of yield, vigour an quality. This knowledge will lead (and is already causing) changes on how to manage the vineyard and the quality of the harvest at the within field scale. From the experimental results obtained in various countries of the world, the goal of the presentation is to provide figures on: - the spatial variability of the main parameters (yield, vigor, quality), and how this variability is organized spatially, - the temporal stability of the observed spatial variability and the potential link with environmental parameters like soil, topography, soil water availability, etc. - information sources available at a high spatial resolution conventionally used in precision agriculture likely to highlight this spatial variability (multi-spectral images, soil electrical conductivity, etc.) and the limitations that these information sources are likely to present in viticulture. Several strategies are currently being developed to take into account the within field variability in viticulture. They are based on the development of specific equipments, sensors, actuators and site specific strategies with the aim of adapting the vineyard operations at the within-field level. These strategies will be presented briefly in two ways : - Site specific operations (fertilization, pruning, thinning, irrigation, etc.) in order to counteract the effects of the environment and to obtain a final product with a controlled and consistent wine quality, - Differential harvesting with the

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

    Treesearch

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

    2015-01-01

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

  13. Disturbance History,Spatial Variability, and Patterns of Biodiversity

    NASA Astrophysics Data System (ADS)

    Bendix, J.; Wiley, J. J.; Commons, M.

    2012-12-01

    The intermediate disturbance hypothesis predicts that species diversity will be maximized in environments experiencing intermediate intensity disturbance, after an intermediate timespan. Because many landscapes comprise mosaics with complex disturbance histories, the theory implies that each patch in those mosaics should have a distinct level of diversity reflecting combined impact of the magnitude of disturbance and the time since it occurred. We modeled the changing patterns of species richness across a landscape experiencing varied scenarios of simulated disturbance. Model outputs show that individual landscape patches have highly variable species richness through time, with the details reflecting the timing, intensity and sequence of their disturbance history. When the results are mapped across the landscape, the resulting temporal and spatial complexity illustrates both the contingent nature of diversity and the danger of generalizing about the impacts of disturbance.

  14. Systems, methods, and software for determining spatially variable distributions of the dielectric properties of a heterogeneous material

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

    Farrington, Stephen P.

    Systems, methods, and software for measuring the spatially variable relative dielectric permittivity of materials along a linear or otherwise configured sensor element, and more specifically the spatial variability of soil moisture in one dimension as inferred from the dielectric profile of the soil matrix surrounding a linear sensor element. Various methods provided herein combine advances in the processing of time domain reflectometry data with innovations in physical sensing apparatuses. These advancements enable high temporal (and thus spatial) resolution of electrical reflectance continuously along an insulated waveguide that is permanently emplaced in contact with adjacent soils. The spatially resolved reflectance ismore » directly related to impedance changes along the waveguide that are dominated by electrical permittivity contrast due to variations in soil moisture. Various methods described herein are thus able to monitor soil moisture in profile with high spatial resolution.« less

  15. Spatial and temporal variability of chorus and hiss

    NASA Astrophysics Data System (ADS)

    Santolik, O.; Hospodarsky, G. B.; Kurth, W. S.; Kletzing, C.

    2017-12-01

    Whistler-mode electromagnetic waves, especially natural emissions of chorus and hiss, have been shown to influence the dynamics of the Van Allen radiation belts via quasi-linear or nonlinear wave particle interactions, transferring energy between different electron populations. Average intensities of chorus and hiss emissions have been found to increase with increasing levels of geomagnetic activity but their stochastic variations in individual spacecraft measurements are usually larger these large-scale temporal effects. To separate temporal and spatial variations of wave characteristics, measurements need to be simultaneously carried out in different locations by identical and/or well calibrated instrumentation. We use two-point survey measurements of the Waves instruments of the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) onboard two Van Allen Probes to asses spatial and temporal variability of chorus and hiss. We take advantage of a systematic analysis of this large data set which has been collected during 2012-2017 over a range of separation vectors of the two spacecraft. We specifically address the question whether similar variations occur at different places at the same time. Our results indicate that power variations are dominated by separations in MLT at scales larger than 0.5h.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  17. Decoding the spatial signatures of multi-scale climate variability - a climate network perspective

    NASA Astrophysics Data System (ADS)

    Donner, R. V.; Jajcay, N.; Wiedermann, M.; Ekhtiari, N.; Palus, M.

    2017-12-01

    During the last years, the application of complex networks as a versatile tool for analyzing complex spatio-temporal data has gained increasing interest. Establishing this approach as a new paradigm in climatology has already provided valuable insights into key spatio-temporal climate variability patterns across scales, including novel perspectives on the dynamics of the El Nino Southern Oscillation or the emergence of extreme precipitation patterns in monsoonal regions. In this work, we report first attempts to employ network analysis for disentangling multi-scale climate variability. Specifically, we introduce the concept of scale-specific climate networks, which comprises a sequence of networks representing the statistical association structure between variations at distinct time scales. For this purpose, we consider global surface air temperature reanalysis data and subject the corresponding time series at each grid point to a complex-valued continuous wavelet transform. From this time-scale decomposition, we obtain three types of signals per grid point and scale - amplitude, phase and reconstructed signal, the statistical similarity of which is then represented by three complex networks associated with each scale. We provide a detailed analysis of the resulting connectivity patterns reflecting the spatial organization of climate variability at each chosen time-scale. Global network characteristics like transitivity or network entropy are shown to provide a new view on the (global average) relevance of different time scales in climate dynamics. Beyond expected trends originating from the increasing smoothness of fluctuations at longer scales, network-based statistics reveal different degrees of fragmentation of spatial co-variability patterns at different scales and zonal shifts among the key players of climate variability from tropically to extra-tropically dominated patterns when moving from inter-annual to decadal scales and beyond. The obtained results

  18. Interannual and spatial variability of maple syrup yield as related to climatic factors

    PubMed Central

    Houle, Daniel

    2014-01-01

    Sugar maple syrup production is an important economic activity for eastern Canada and the northeastern United States. Since annual variations in syrup yield have been related to climate, there are concerns about the impacts of climatic change on the industry in the upcoming decades. Although the temporal variability of syrup yield has been studied for specific sites on different time scales or for large regions, a model capable of accounting for both temporal and regional differences in yield is still lacking. In the present study, we studied the factors responsible for interregional and interannual variability in maple syrup yield over the 2001–2012 period, by combining the data from 8 Quebec regions (Canada) and 10 U.S. states. The resulting model explained 44.5% of the variability in yield. It includes the effect of climatic conditions that precede the sapflow season (variables from the previous growing season and winter), the effect of climatic conditions during the current sapflow season, and terms accounting for intercountry and temporal variability. Optimal conditions for maple syrup production appear to be spatially restricted by less favourable climate conditions occurring during the growing season in the north, and in the south, by the warmer winter and earlier spring conditions. This suggests that climate change may favor maple syrup production northwards, while southern regions are more likely to be negatively affected by adverse spring conditions. PMID:24949244

  19. Spatial Variability of Soil-Water Storage in the Southern Sierra Critical Zone Observatory: Measurement and Prediction

    NASA Astrophysics Data System (ADS)

    Oroza, C.; Bales, R. C.; Zheng, Z.; Glaser, S. D.

    2017-12-01

    Predicting the spatial distribution of soil moisture in mountain environments is confounded by multiple factors, including complex topography, spatial variably of soil texture, sub-surface flow paths, and snow-soil interactions. While remote-sensing tools such as passive-microwave monitoring can measure spatial variability of soil moisture, they only capture near-surface soil layers. Large-scale sensor networks are increasingly providing soil-moisture measurements at high temporal resolution across a broader range of depths than are accessible from remote sensing. It may be possible to combine these in-situ measurements with high-resolution LIDAR topography and canopy cover to estimate the spatial distribution of soil moisture at high spatial resolution at multiple depths. We study the feasibility of this approach using six years (2009-2014) of daily volumetric water content measurements at 10-, 30-, and 60-cm depths from the Southern Sierra Critical Zone Observatory. A non-parametric, multivariate regression algorithm, Random Forest, was used to predict the spatial distribution of depth-integrated soil-water storage, based on the in-situ measurements and a combination of node attributes (topographic wetness, northness, elevation, soil texture, and location with respect to canopy cover). We observe predictable patterns of predictor accuracy and independent variable ranking during the six-year study period. Predictor accuracy is highest during the snow-cover and early recession periods but declines during the dry period. Soil texture has consistently high feature importance. Other landscape attributes exhibit seasonal trends: northness peaks during the wet-up period, and elevation and topographic-wetness index peak during the recession and dry period, respectively.

  20. Variability in Soil Properties at Different Spatial Scales (1 m to 1 km) in a Deciduous Forest Ecosystem

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

    Garten Jr, Charles T; Kang, S.; Brice, Deanne Jane

    2007-01-01

    The purpose of this research was to test the hypothesis that variability in 11 soil properties, related to soil texture and soil C and N, would increase from small (1 m) to large (1 km) spatial scales in a temperate, mixed-hardwood forest ecosystem in east Tennessee, USA. The results were somewhat surprising and indicated that a fundamental assumption in geospatial analysis, namely that variability increases with increasing spatial scale, did not apply for at least five of the 11 soil properties measured over a 0.5-km2 area. Composite mineral soil samples (15 cm deep) were collected at 1, 5, 10, 50,more » 250, and 500 m distances from a center point along transects in a north, south, east, and westerly direction. A null hypothesis of equal variance at different spatial scales was rejected (P{le}0.05) for mineral soil C concentration, silt content, and the C-to-N ratios in particulate organic matter (POM), mineral-associated organic matter (MOM), and whole surface soil. Results from different tests of spatial variation, based on coefficients of variation or a Mantel test, led to similar conclusions about measurement variability and geographic distance for eight of the 11 variables examined. Measurements of mineral soil C and N concentrations, C concentrations in MOM, extractable soil NH{sub 4}-N, and clay contents were just as variable at smaller scales (1-10 m) as they were at larger scales (50-500 m). On the other hand, measurement variation in mineral soil C-to-N ratios, MOM C-to-N ratios, and the fraction of soil C in POM clearly increased from smaller to larger spatial scales. With the exception of extractable soil NH4-N, measured soil properties in the forest ecosystem could be estimated (with 95% confidence) to within 15% of their true mean with a relatively modest number of sampling points (n{le}25). For some variables, scaling up variation from smaller to larger spatial domains within the ecosystem could be relatively easy because small-scale variation

  1. 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

  2. Spatial Variability of Grapevine Bud Burst Percentage and Its Association with Soil Properties at Field Scale

    PubMed Central

    Li, Tao; Hao, Xinmei; Kang, Shaozhong

    2016-01-01

    There is a growing interest in precision viticulture with the development of global positioning system and geographical information system technologies. Limited information is available on spatial variation of bud behavior and its possible association with soil properties. The objective of this study was to investigate spatial variability of bud burst percentage and its association with soil properties based on 2-year experiments at a vineyard of arid northwest China. Geostatistical approach was used to describe the spatial variation in bud burst percentage within the vineyard. Partial least square regressions (PLSRs) of bud burst percentage with soil properties were used to evaluate the contribution of soil properties to overall spatial variability in bud burst percentage for the high, medium and low bud burst percentage groups. Within the vineyard, the coefficient of variation (CV) of bud burst percentage was 20% and 15% for 2012 and 2013 respectively. Bud burst percentage within the vineyard showed moderate spatial variability, and the overall spatial pattern of bud burst percentage was similar between the two years. Soil properties alone explained 31% and 37% of the total spatial variation respectively for the low group of 2012 and 2013, and 16% and 24% for the high group of 2012 and 2013 respectively. For the low group, the fraction of variations explained by soil properties was found similar between the two years, while there was substantial difference for the high group. The findings are expected to lay a good foundation for developing remedy measures in the areas with low bud burst percentage, thus in turn improving the overall grape yield and quality. PMID:27798692

  3. How spatial and temporal rainfall variability affect runoff across basin scales: insights from field observations in the (semi-)urbanised Charlotte watershed

    NASA Astrophysics Data System (ADS)

    Ten Veldhuis, M. C.; Smith, J. A.; Zhou, Z.

    2017-12-01

    Impacts of rainfall variability on runoff response are highly scale-dependent. Sensitivity analyses based on hydrological model simulations have shown that impacts are likely to depend on combinations of storm type, basin versus storm scale, temporal versus spatial rainfall variability. So far, few of these conclusions have been confirmed on observational grounds, since high quality datasets of spatially variable rainfall and runoff over prolonged periods are rare. Here we investigate relationships between rainfall variability and runoff response based on 30 years of radar-rainfall datasets and flow measurements for 16 hydrological basins ranging from 7 to 111 km2. Basins vary not only in scale, but also in their degree of urbanisation. We investigated temporal and spatial variability characteristics of rainfall fields across a range of spatial and temporal scales to identify main drivers for variability in runoff response. We identified 3 ranges of basin size with different temporal versus spatial rainfall variability characteristics. Total rainfall volume proved to be the dominant agent determining runoff response at all basin scales, independent of their degree of urbanisation. Peak rainfall intensity and storm core volume are of secondary importance. This applies to all runoff parameters, including runoff volume, runoff peak, volume-to-peak and lag time. Position and movement of the storm with respect to the basin have a negligible influence on runoff response, with the exception of lag times in some of the larger basins. This highlights the importance of accuracy in rainfall estimation: getting the position right but the volume wrong will inevitably lead to large errors in runoff prediction. Our study helps to identify conditions where rainfall variability matters for correct estimation of the rainfall volume as well as the associated runoff response.

  4. Descriptive statistics and spatial distributions of geochemical variables associated with manganese oxide-rich phases in the northern Pacific

    USGS Publications Warehouse

    Botbol, Joseph Moses; Evenden, Gerald Ian

    1989-01-01

    Tables, graphs, and maps are used to portray the frequency characteristics and spatial distribution of manganese oxide-rich phase geochemical data, to characterize the northern Pacific in terms of publicly available nodule geochemical data, and to develop data portrayal methods that will facilitate data analysis. Source data are a subset of the Scripps Institute of Oceanography's Sediment Data Bank. The study area is bounded by 0° N., 40° N., 120° E., and 100° W. and is arbitrarily subdivided into 14-20°x20° geographic subregions. Frequency distributions of trace metals characterized in the original raw data are graphed as ogives, and salient parameters are tabulated. All variables are transformed to enrichment values relative to median concentration within their host subregions. Scatter plots of all pairs of original variables and their enrichment transforms are provided as an aid to the interpretation of correlations between variables. Gridded spatial distributions of all variables are portrayed as gray-scale maps. The use of tables and graphs to portray frequency statistics and gray-scale maps to portray spatial distributions is an effective way to prepare for and facilitate multivariate data analysis.

  5. Potential for tree rings to reveal spatial patterns of past drought variability across western Australia

    NASA Astrophysics Data System (ADS)

    O'Donnell, Alison J.; Cook, Edward R.; Palmer, Jonathan G.; Turney, Chris S. M.; Grierson, Pauline F.

    2018-02-01

    Proxy records have provided major insights into the variability of past climates over long timescales. However, for much of the Southern Hemisphere, the ability to identify spatial patterns of past climatic variability is constrained by the sparse distribution of proxy records. This is particularly true for mainland Australia, where relatively few proxy records are located. Here, we (1) assess the potential to use existing proxy records in the Australasian region—starting with the only two multi-century tree-ring proxies from mainland Australia—to reveal spatial patterns of past hydroclimatic variability across the western third of the continent, and (2) identify strategic locations to target for the development of new proxy records. We show that the two existing tree-ring records allow robust reconstructions of past hydroclimatic variability over spatially broad areas (i.e. > 3° × 3°) in inland north- and south-western Australia. Our results reveal synchronous periods of drought and wet conditions between the inland northern and southern regions of western Australia as well as a generally anti-phase relationship with hydroclimate in eastern Australia over the last two centuries. The inclusion of 174 tree-ring proxy records from Tasmania, New Zealand and Indonesia and a coral record from Queensland did not improve the reconstruction potential over western Australia. However, our findings suggest that the addition of relatively few new proxy records from key locations in western Australia that currently have low reconstruction skill will enable the development of a comprehensive drought atlas for the region, and provide a critical link to the drought atlases of monsoonal Asia and eastern Australia and New Zealand.

  6. Scale-dependent spatial variability in peatland lead pollution in the southern Pennines, UK.

    PubMed

    Rothwell, James J; Evans, Martin G; Lindsay, John B; Allott, Timothy E H

    2007-01-01

    Increasingly, within-site and regional comparisons of peatland lead pollution have been undertaken using the inventory approach. The peatlands of the Peak District, southern Pennines, UK, have received significant atmospheric inputs of lead over the last few hundred years. A multi-core study at three peatland sites in the Peak District demonstrates significant within-site spatial variability in industrial lead pollution. Stochastic simulations reveal that 15 peat cores are required to calculate reliable lead inventories at the within-site and within-region scale for this highly polluted area of the southern Pennines. Within-site variability in lead pollution is dominant at the within-region scale. The study demonstrates that significant errors may be associated with peatland lead inventories at sites where only a single peat core has been used to calculate an inventory. Meaningful comparisons of lead inventories at the regional or global scale can only be made if the within-site variability of lead pollution has been quantified reliably.

  7. Quantifying spatial and temporal variabilities of microwave brightness temperature over the U.S. Southern Great Plains

    NASA Technical Reports Server (NTRS)

    Choudhury, B. J.; Owe, M.; Ormsby, J. P.; Chang, A. T. C.; Wang, J. R.; Goward, S. N.; Golus, R. E.

    1987-01-01

    Spatial and temporal variabilities of microwave brightness temperature over the U.S. Southern Great Plains are quantified in terms of vegetation and soil wetness. The brightness temperatures (TB) are the daytime observations from April to October for five years (1979 to 1983) obtained by the Nimbus-7 Scanning Multichannel Microwave Radiometer at 6.6 GHz frequency, horizontal polarization. The spatial and temporal variabilities of vegetation are assessed using visible and near-infrared observations by the NOAA-7 Advanced Very High Resolution Radiometer (AVHRR), while an Antecedent Precipitation Index (API) model is used for soil wetness. The API model was able to account for more than 50 percent of the observed variability in TB, although linear correlations between TB and API were generally significant at the 1 percent level. The slope of the linear regression between TB and API is found to correlate linearly with an index for vegetation density derived from AVHRR data.

  8. Decreasing spatial variability in precipitation extremes in southwestern China and the local/large-scale influencing factors

    NASA Astrophysics Data System (ADS)

    Liu, Meixian; Xu, Xianli; Sun, Alex

    2015-07-01

    Climate extremes can cause devastating damage to human society and ecosystems. Recent studies have drawn many conclusions about trends in climate extremes, but few have focused on quantitative analysis of their spatial variability and underlying mechanisms. By using the techniques of overlapping moving windows, the Mann-Kendall trend test, correlation, and stepwise regression, this study examined the spatial-temporal variation of precipitation extremes and investigated the potential key factors influencing this variation in southwestern (SW) China, a globally important biodiversity hot spot and climate-sensitive region. Results showed that the changing trends of precipitation extremes were not spatially uniform, but the spatial variability of these precipitation extremes decreased from 1959 to 2012. Further analysis found that atmospheric circulations rather than local factors (land cover, topographic conditions, etc.) were the main cause of such precipitation extremes. This study suggests that droughts or floods may become more homogenously widespread throughout SW China. Hence, region-wide assessments and coordination are needed to help mitigate the economic and ecological impacts.

  9. Validation of spatial variability in downscaling results from the VALUE perfect predictor experiment

    NASA Astrophysics Data System (ADS)

    Widmann, Martin; Bedia, Joaquin; Gutiérrez, Jose Manuel; Maraun, Douglas; Huth, Radan; Fischer, Andreas; Keller, Denise; Hertig, Elke; Vrac, Mathieu; Wibig, Joanna; Pagé, Christian; Cardoso, Rita M.; Soares, Pedro MM; Bosshard, Thomas; Casado, Maria Jesus; Ramos, Petra

    2016-04-01

    VALUE is an open European network to validate and compare downscaling methods for climate change research. Within VALUE a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods has been developed. In the first validation experiment the downscaling methods are validated in a setup with perfect predictors taken from the ERA-interim reanalysis for the period 1997 - 2008. This allows to investigate the isolated skill of downscaling methods without further error contributions from the large-scale predictors. One aspect of the validation is the representation of spatial variability. As part of the VALUE validation we have compared various properties of the spatial variability of downscaled daily temperature and precipitation with the corresponding properties in observations. We have used two test validation datasets, one European-wide set of 86 stations, and one higher-density network of 50 stations in Germany. Here we present results based on three approaches, namely the analysis of i.) correlation matrices, ii.) pairwise joint threshold exceedances, and iii.) regions of similar variability. We summarise the information contained in correlation matrices by calculating the dependence of the correlations on distance and deriving decorrelation lengths, as well as by determining the independent degrees of freedom. Probabilities for joint threshold exceedances and (where appropriate) non-exceedances are calculated for various user-relevant thresholds related for instance to extreme precipitation or frost and heat days. The dependence of these probabilities on distance is again characterised by calculating typical length scales that separate dependent from independent exceedances. Regionalisation is based on rotated Principal Component Analysis. The results indicate which downscaling methods are preferable if the dependency of variability at different locations is relevant for the user.

  10. Spatial variability of soil properties and soil erodibility in the Alqueva dam watershed, Portugal

    NASA Astrophysics Data System (ADS)

    Ferreira, V.; Panagopoulos, T.; Andrade, R.; Guerrero, C.; Loures, L.

    2015-01-01

    The aim of this work is to investigate how the spatial variability of soil properties and soil erodibility (K factor) were affected by the changes in land use allowed by irrigation with water from a reservoir in a semiarid area. To this, three areas representative of different land uses (agroforestry grassland, Lucerne crop and olive orchard) were studied within a 900 ha farm. The interrelationships between variables were analyzed by multivariate techniques and extrapolated using geostatistics. The results confirmed differences between land uses for all properties analyzed, which was explained mainly by the existence of diverse management practices (tillage, fertilization and irrigation), vegetation cover and local soil characteristics. Soil organic matter, clay and nitrogen content decreased significantly, while K factor increased with intensive cultivation. The HJ-biplot methodology was used to represent the variation of soil erodibility properties grouped in land uses. Native grassland was the least correlated with the other land uses. K factor demonstrated high correlation mainly with very fine sand and silt. The maps produced with geostatistics were crucial to understand the current spatial variability in the Alqueva region. Facing the intensification of land-use conversion, a sustainable management is needed to introduce protective measures to control soil erosion.

  11. Inter-annual and spatial variability in hillslope runoff and mercury flux during spring snowmelt.

    PubMed

    Haynes, Kristine M; Mitchell, Carl P J

    2012-08-01

    Spring snowmelt is an important period of mercury (Hg) export from watersheds. Limited research has investigated the potential effects of climate variability on hydrologic and Hg fluxes during spring snowmelt. The purpose of this research was to assess the potential impacts of inter-annual climate variability on Hg mobility in forested uplands, as well as spatial variability in hillslope hydrology and Hg fluxes. We compared hydrological flows, Hg and solute mobility from three adjacent hillslopes in the S7 watershed of the Marcell Experimental Forest, Minnesota during two very different spring snowmelt periods: one following a winter (2009-2010) with severely diminished snow accumulation (snow water equivalent (SWE) = 48 mm) with an early melt, and a second (2010-2011) with significantly greater winter snow accumulation (SWE = 98 mm) with average to late melt timing. Observed inter-annual differences in total Hg (THg) and dissolved organic carbon (DOC) yields were predominantly flow-driven, as the proportion by which solute yields increased was the same as the increase in runoff. Accounting for inter-annual differences in flow, there was no significant difference in THg and DOC export between the two snowmelt periods. The spring 2010 snowmelt highlighted the important contribution of melting soil frost in the timing of a considerable portion of THg exported from the hillslope, accounting for nearly 30% of the THg mobilized. Differences in slope morphology and soil depths to the confining till layer were important in controlling the large observed spatial variability in hydrological flowpaths, transmissivity feedback responses, and Hg flux trends across the adjacent hillslopes.

  12. Spatial variability of soils in a seasonally dry tropical forest

    NASA Astrophysics Data System (ADS)

    Pulla, Sandeep; Riotte, Jean; Suresh, Hebbalalu; Dattaraja, Handanakere; Sukumar, Raman

    2016-04-01

    Soil structures communities of plants and soil organisms in tropical forests. Understanding the controls of soil spatial variability can therefore potentially inform efforts towards forest restoration. We studied the relationship between soils and lithology, topography, vegetation and fire in a seasonally dry tropical forest in southern India. We extensively sampled soil (available nutrients, Al, pH, and moisture), rocks, relief, woody vegetation, and spatial variation in fire burn frequency in a permanent 50-ha plot. Lower elevation soils tended to be less moist and were depleted in several nutrients and clay. The availability of several nutrients was, in turn, linked to whole-rock chemical composition differences since some lithologies were associated with higher elevations, while the others tended to dominate lower elevations. We suggest that local-scale topography in this region has been shaped by the spatial distribution of lithologies, which differ in their susceptibility to weathering. Nitrogen availability was uncorrelated with the presence of trees belonging to Fabaceae, a family associated with N-fixing species. No effect of burning on soil parameters could be discerned at this scale.

  13. The spatial heterogeneity between Japanese encephalitis incidence distribution and environmental variables in Nepal.

    PubMed

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

    2011-01-01

    To identify potential environmental drivers of Japanese Encephalitis virus (JE) transmission in Nepal, we conducted an ecological study to determine the spatial association between 2005 Nepal JE incidence, and climate, agricultural, and land-cover variables at district level. District-level data on JE cases were examined using Local Indicators of Spatial Association (LISA) analysis to identify spatial clusters from 2004 to 2008 and 2005 data was used to fit a spatial lag regression model with climate, agriculture and land-cover variables. Prior to 2006, there was a single large cluster of JE cases located in the Far-West and Mid-West terai regions of Nepal. After 2005, the distribution of JE cases in Nepal shifted with clusters found in the central hill areas. JE incidence during the 2005 epidemic had a stronger association with May mean monthly temperature and April mean monthly total precipitation compared to mean annual temperature and precipitation. A parsimonious spatial lag regression model revealed, 1) a significant negative relationship between JE incidence and April precipitation, 2) a significant positive relationship between JE incidence and percentage of irrigated land 3) a non-significant negative relationship between JE incidence and percentage of grassland cover, and 4) a unimodal non-significant relationship between JE Incidence and pig-to-human ratio. JE cases clustered in the terai prior to 2006 where it seemed to shift to the Kathmandu region in subsequent years. The spatial pattern of JE cases during the 2005 epidemic in Nepal was significantly associated with low precipitation and the percentage of irrigated land. Despite the availability of an effective vaccine, it is still important to understand environmental drivers of JEV transmission since the enzootic cycle of JEV transmission is not likely to be totally interrupted. Understanding the spatial dynamics of JE risk factors may be useful in providing important information to the Nepal

  14. Temporal and spatial variability of aeolian sand transport: Implications for field measurements

    NASA Astrophysics Data System (ADS)

    Ellis, Jean T.; Sherman, Douglas J.; Farrell, Eugene J.; Li, Bailiang

    2012-01-01

    Horizontal variability is often cited as one source of disparity between observed and predicted rates of aeolian mass flux, but few studies have quantified the magnitude of this variability. Two field projects were conducted to evaluate meter-scale spatial and temporal in the saltation field. In Shoalhaven Heads, NSW, Australia a horizontal array of passive-style sand traps were deployed on a beach for 600 or 1200 s across a horizontal span of 0.80 m. In Jericoacoara, Brazil, traps spanning 4 m were deployed for 180 and 240 s. Five saltation sensors (miniphones) spaced 1 m apart were also deployed at Jericoacoara. Spatial variation in aeolian transport rates over small spatial and short temporal scales was substantial. The measured transport rates ( Q) obtained from the passive traps ranged from 0.70 to 32.63 g/m/s. When considering all traps, the coefficient of variation ( CoV) values ranged from 16.6% to 67.8%, and minimum and maximum range of variation coefficient ( RVC) values were 106.1% to 152.5% and 75.1% to 90.8%, respectively. The miniphone Q and CoV averaged 47.1% and 4.1% for the 1260 s data series, which was subsequently sub-sampled at 60-630 s intervals to simulate shorter deployment times. A statistically significant ( p < 0.002), inverselinear relationship was found between sample duration and CoV and between Q and CoV, the latter relationship also considering data from previous studies.

  15. Spatial and temporal variability of soil moisture on the field with and without plants*

    NASA Astrophysics Data System (ADS)

    Usowicz, B.; Marczewski, W.; Usowicz, J. B.

    2012-04-01

    Spatial and temporal variability of the natural environment is its inherent and unavoidable feature. Every element of the environment is characterized by its own variability. One of the kinds of variability in the natural environment is the variability of the soil environment. To acquire better and deeper knowledge and understanding of the temporal and spatial variability of the physical, chemical and biological features of the soil environment, we should determine the causes that induce a given variability. Relatively stable features of soil include its texture and mineral composition; examples of those variables in time are the soil pH or organic matter content; an example of a feature with strong dynamics is the soil temperature and moisture content. The aim of this study was to identify the variability of soil moisture on the field with and without plants using geostatistical methods. The soil moisture measurements were taken on the object with plant canopy and without plants (as reference). The measurements of soil moisture and meteorological components were taken within the period of April-July. The TDR moisture sensors covered 5 cm soil layers and were installed in the plots in the soil layers of 0-0.05, 0.05-0.1, 0.1-0.15, 0.2-0.25, 0.3-0.35, 0.4-0.45, 0.5-0.55, 0.8-0.85 m. Measurements of soil moisture were taken once a day, in the afternoon hours. For the determination of reciprocal correlation, precipitation data and data from soil moisture measurements with the TDR meter were used. Calculations of reciprocal correlation of precipitation and soil moisture at various depths were made for three objects - spring barley, rye, and bare soil, at the level of significance of p<0.05. No significant reciprocal correlation was found between the precipitation and soil moisture in the soil profile for any of the objects studied. Although the correlation analysis indicates a lack of correlation between the variables under consideration, observation of the soil

  16. The energy balance of an urban area: Examining temporal and spatial variability through measurements, remote sensing and modeling

    NASA Astrophysics Data System (ADS)

    Offerle, Brian

    Urban environmental problems related to air quality, thermal stress, issues of water demand and quality, all of which are linked directly or indirectly to urban climate, are emerging as major environmental concerns at the start of the 21st century. Thus there are compelling social, political and economic, and scientific reasons that make the study and understanding of the fundamental causes of urban climates critically important. This research addresses these topics through an intensive study of the surface energy balance of Lodz, Poland. The research examines the temporal variability in long-term measurements of urban surface-atmosphere exchange at a downtown location and the spatial variability of this exchange over distinctly different neighborhoods using shorter-term observations. These observations provide the basis for an evaluation of surface energy balance models. Monthly patterns in energy exchange are consistent from year-to-year with variability determined by net radiation and the timing and amount of precipitation. Spatial variability can be determined from plan area fractions of vegetation and impervious surface, though heat storage exerts a strong control on shorter term variability of energy exchange, within and between locations in an urban area. Anthropogenic heat fluxes provide most of the energy driving surface-atmosphere exchange in winter, From a modeling perspective, sensible heat fluxes can be reliably determined from radiometrically sensed surface temperatures and spatially representative surface-atmosphere exchange in an urban area can be determined from satellite remote sensing products. Models of the urban surface energy balance showed good agreement with mean values of energy exchange and under most conditions represented the temporal variability due to synoptic and shorter time scale forcing well.

  17. Spatial and Temporal Variability and Trends in 2001-2016 Global Fire Activity

    NASA Astrophysics Data System (ADS)

    Earl, Nick; Simmonds, Ian

    2018-03-01

    Fire regimes across the globe have great spatial and temporal variability, and these are influence by many factors including anthropogenic management, climate, and vegetation types. Here we utilize the satellite-based "active fire" product, from Moderate Resolution Imaging Spectroradiometer (MODIS) sensors, to statistically analyze variability and trends in fire activity from the global to regional scales. We split up the regions by economic development, region/geographical land use, clusters of fire-abundant areas, or by religious/cultural influence. Weekly cycle tests are conducted to highlight and quantify part of the anthropogenic influence on fire regime across the world. We find that there is a strong statistically significant decline in 2001-2016 active fires globally linked to an increase in net primary productivity observed in northern Africa, along with global agricultural expansion and intensification, which generally reduces fire activity. There are high levels of variability, however. The large-scale regions exhibit either little change or decreasing in fire activity except for strong increasing trends in India and China, where rapid population increase is occurring, leading to agricultural intensification and increased crop residue burning. Variability in Canada has been linked to a warming global climate leading to a longer growing season and higher fuel loads. Areas with a strong weekly cycle give a good indication of where fire management is being applied most extensively, for example, the United States, where few areas retain a natural fire regime.

  18. Spatial variability of excess mortality during prolonged dust events in a high-density city: a time-stratified spatial regression approach.

    PubMed

    Wong, Man Sing; Ho, Hung Chak; Yang, Lin; Shi, Wenzhong; Yang, Jinxin; Chan, Ta-Chien

    2017-07-24

    Dust events have long been recognized to be associated with a higher mortality risk. However, no study has investigated how prolonged dust events affect the spatial variability of mortality across districts in a downwind city. In this study, we applied a spatial regression approach to estimate the district-level mortality during two extreme dust events in Hong Kong. We compared spatial and non-spatial models to evaluate the ability of each regression to estimate mortality. We also compared prolonged dust events with non-dust events to determine the influences of community factors on mortality across the city. The density of a built environment (estimated by the sky view factor) had positive association with excess mortality in each district, while socioeconomic deprivation contributed by lower income and lower education induced higher mortality impact in each territory planning unit during a prolonged dust event. Based on the model comparison, spatial error modelling with the 1st order of queen contiguity consistently outperformed other models. The high-risk areas with higher increase in mortality were located in an urban high-density environment with higher socioeconomic deprivation. Our model design shows the ability to predict spatial variability of mortality risk during an extreme weather event that is not able to be estimated based on traditional time-series analysis or ecological studies. Our spatial protocol can be used for public health surveillance, sustainable planning and disaster preparation when relevant data are available.

  19. Spatial versus Day-To-Day Within-Lake Variability in Tropical Floodplain Lake CH4 Emissions – Developing Optimized Approaches to Representative Flux Measurements

    PubMed Central

    Peixoto, Roberta B.; Machado-Silva, Fausto; Marotta, Humberto; Enrich-Prast, Alex; Bastviken, David

    2015-01-01

    Inland waters (lakes, rivers and reservoirs) are now understood to contribute large amounts of methane (CH4) to the atmosphere. However, fluxes are poorly constrained and there is a need for improved knowledge on spatiotemporal variability and on ways of optimizing sampling efforts to yield representative emission estimates for different types of aquatic ecosystems. Low-latitude floodplain lakes and wetlands are among the most high-emitting environments, and here we provide a detailed investigation of spatial and day-to-day variability in a shallow floodplain lake in the Pantanal in Brazil over a five-day period. CH4 flux was dominated by frequent and ubiquitous ebullition. A strong but predictable spatial variability (decreasing flux with increasing distance to the shore or to littoral vegetation) was found, and this pattern can be addressed by sampling along transects from the shore to the center. Although no distinct day-to-day variability were found, a significant increase in flux was identified from measurement day 1 to measurement day 5, which was likely attributable to a simultaneous increase in temperature. Our study demonstrates that representative emission assessments requires consideration of spatial variability, but also that spatial variability patterns are predictable for lakes of this type and may therefore be addressed through limited sampling efforts if designed properly (e.g., fewer chambers may be used if organized along transects). Such optimized assessments of spatial variability are beneficial by allowing more of the available sampling resources to focus on assessing temporal variability, thereby improving overall flux assessments. PMID:25860229

  20. Modeling the spatial and temporal variability in climate and primary productivity across the Luquillo Mountains, Puerto Rico.

    Treesearch

    Hongqing Wanga; Charles A.S. Halla; Frederick N. Scatenab; Ned Fetcherc; Wei Wua

    2003-01-01

    There are few studies that have examined the spatial variability of forest productivity over an entire tropical forested landscape. In this study, we used a spatially-explicit forest productivity model, TOPOPROD, which is based on the FORESTBGC model, to simulate spatial patterns of gross primary productivity (GPP), net primary productivity (NPP), and respiration over...

  1. Spatial and layer-controlled variability in fracture networks

    NASA Astrophysics Data System (ADS)

    Procter, Andrew; Sanderson, David J.

    2018-03-01

    Topological sampling, based on 1) node counting and 2) circular sampling areas, is used to measure fracture intensity in surface exposures of a layered limestone/shale sequence in north Somerset, UK. This method provides similar levels of precision as more traditional line samples, but is about 10 times quicker and allows characterization of the network topology. Georeferencing of photographs of the sample sites allows later analysis of trace lengths and orientations, and identification of joint set development. ANOVA tests support a complex interaction of within-layer, between-layer and between-location variability in fracture intensity, with the different layers showing anomalous intensity at different locations. This variation is not simply due to bed thickness, nor can it be related to any obvious compositional or textural variation between the limestone beds. These results are used to assess approaches to the spatial mapping of fracture intensity.

  2. Spatial heterogeneities and variability of karst hydro-system : insights from geophysics

    NASA Astrophysics Data System (ADS)

    Champollion, C.; Fores, B.; Lesparre, N.; Frederic, N.

    2017-12-01

    Heterogeneous systems such as karsts or fractured hydro-systems are challenging for both scientist and groundwater resources management. Karsts heterogeneities prevent the comparison and moreover the combination of data representative of different scales: borehole water level can generally not be used directly to interpret spring flow dynamic for example. The spatial heterogeneity has also an impact on the temporal variability of groundwater transfer and storage. Karst hydro-systems have characteristic non linear relation between precipitation amount and discharge at the outlets with threshold effects and a large variability of groundwater transit times In the presentation, geophysical field experiments conducted in karst hydro-system in the south of France are used to investigate groundwater transfer and storage variability at a scale of a few hundred meters. We focus on the added value of both geophysical time-lapse gravity experiments and 2D ERT imaging of the subsurface heterogeneities. Both gravity and ERT results can only be interpreted with large ambiguity or some strong a priori: the relation between resistivity and water content is not unique; almost no information about the processes can be inferred from the groundwater stock variations. The present study demonstrate how the ERT and gravity field experiments can be interpreted together in a coherent scheme with less ambiguity. First the geological and hydro-meteorological context is presented. Then the ERT field experiment including the processing and the results are detailed in the section about geophysical imaging of the heterogeneities. The gravity double difference (S2D) time-lapse experiment is described in the section about geophysical monitoring of the temporal variability. The following discussion demonstrate the impact of both experiments on the interpretation in terms of processes and heterogeneities.

  3. Modeling Spatial and Temporal Variability in Ammonia Emissions from Agricultural Fertilization

    NASA Astrophysics Data System (ADS)

    Balasubramanian, S.; Koloutsou-Vakakis, S.; Rood, M. J.

    2013-12-01

    Ammonia (NH3), is an important component of the reactive nitrogen cycle and a precursor to formation of atmospheric particulate matter (PM). Predicting regional PM concentrations and deposition of nitrogen species to ecosystems requires representative emission inventories. Emission inventories have traditionally been developed using top down approaches and more recently from data assimilation based on satellite and ground based ambient concentrations and wet deposition data. The National Emission Inventory (NEI) indicates agricultural fertilization as the predominant contributor (56%) to NH3 emissions in Midwest USA, in 2002. However, due to limited understanding of the complex interactions between fertilizer usage, farm practices, soil and meteorological conditions and absence of detailed statistical data, such emission estimates are currently based on generic emission factors, time-averaged temporal factors and coarse spatial resolution. Given the significance of this source, our study focuses on developing an improved NH3 emission inventory for agricultural fertilization at finer spatial and temporal scales for air quality modeling studies. Firstly, a high-spatial resolution 4 km x 4 km NH3 emission inventory for agricultural fertilization has been developed for Illinois by modifying spatial allocation of emissions based on combining crop-specific fertilization rates with cropland distribution in the Sparse Matrix Operator Kernel Emissions model. Net emission estimates of our method are within 2% of NEI, since both methods are constrained by fertilizer sales data. However, we identified localized crop-specific NH3 emission hotspots at sub-county resolutions absent in NEI. Secondly, we have adopted the use of the DeNitrification-DeComposition (DNDC) Biogeochemistry model to simulate the physical and chemical processes that control volatilization of nitrogen as NH3 to the atmosphere after fertilizer application and resolve the variability at the hourly scale

  4. Variability in Spatially and Temporally Resolved Emissions and Hydrocarbon Source Fingerprints for Oil and Gas Sources in Shale Gas Production Regions.

    PubMed

    Allen, David T; Cardoso-Saldaña, Felipe J; Kimura, Yosuke

    2017-10-17

    A gridded inventory for emissions of methane, ethane, propane, and butanes from oil and gas sources in the Barnett Shale production region has been developed. This inventory extends previous spatially resolved inventories of emissions by characterizing the overall variability in emission magnitudes and the composition of emissions at an hourly time resolution. The inventory is divided into continuous and intermittent emission sources. Sources are defined as continuous if hourly averaged emissions are greater than zero in every hour; otherwise, they are classified as intermittent. In the Barnett Shale, intermittent sources accounted for 14-30% of the mean emissions for methane and 10-34% for ethane, leading to spatial and temporal variability in the location of hourly emissions. The combined variability due to intermittent sources and variability in emission factors can lead to wide confidence intervals in the magnitude and composition of time and location-specific emission inventories; therefore, including temporal and spatial variability in emission inventories is important when reconciling inventories and observations. Comparisons of individual aircraft measurement flights conducted in the Barnett Shale region versus the estimated emission rates for each flight from the emission inventory indicate agreement within the expected variability of the emission inventory for all flights for methane and for all but one flight for ethane.

  5. Spatial and temporal variability in the structure of invertebrate assemblages in control stream mesocosms.

    PubMed

    Wong, Diana C L; Maltby, Lorraine; Whittle, Don; Warren, Philip; Dorn, Philip B

    2004-01-01

    Outdoor stream mesocosm studies conducted between 1992 and 1996 at two facilities enabled the investigation of structural variability in invertebrate assemblages within and between studies. Temporal variability of benthic invertebrate assemblages between eight replicate streams within a study was assessed in a 28-day mesocosm study without chemical treatment. Cluster analysis, non-metric multidimensional scaling, and principal component analysis each showed the untreated assemblages as structurally distinct groups on the three sampling days. The assemblages between the eight replicate streams showed >88% Bray-Curtis similarity at any one time during the study. In addition, pre-treatment data from a series of four studies conducted at one facility were used to examine structural variability in the starting benthic invertebrate assemblages between studies. Invertebrate assemblages were structurally distinct at the start of each mesocosm study conducted in different years at the same facility and the taxa responsible for differences in the assemblages were also different each year. The implications of temporal and spatial variability in benthic invertebrate assemblages within and between mesocosm studies with regards to species sensitivity and study repeatability should be considered when results of such studies are used in risk assessment.

  6. Spatial and temporal analysis of drought variability at several time scales in Syria during 1961-2012

    NASA Astrophysics Data System (ADS)

    Mathbout, Shifa; Lopez-Bustins, Joan A.; Martin-Vide, Javier; Bech, Joan; Rodrigo, Fernando S.

    2018-02-01

    This paper analyses the observed spatiotemporal characteristics of drought phenomenon in Syria using the Standardised Precipitation Index (SPI) and the Standardised Precipitation Evapotranspiration Index (SPEI). Temporal variability of drought is calculated for various time scales (3, 6, 9, 12, and 24 months) for 20 weather stations over the 1961-2012 period. The spatial patterns of drought were identified by applying a Principal Component Analysis (PCA) to the SPI and SPEI values at different time scales. The results revealed three heterogeneous and spatially well-defined regions with different temporal evolution of droughts: 1) Northeastern (inland desert); 2) Southern (mountainous landscape); 3) Northwestern (Mediterranean coast). The evolutionary characteristics of drought during 1961-2012 were analysed including spatial and temporal variability of SPI and SPEI, the frequency distribution, and the drought duration. The results of the non-parametric Mann-Kendall test applied to the SPI and SPEI series indicate prevailing significant negative trends (drought) at all stations. Both drought indices have been correlated both on spatial and temporal scales and they are highly comparable, especially, over a 12 and 24 month accumulation period. We concluded that the temporal and spatial characteristics of the SPI and SPEI can be used for developing a drought intensity - areal extent - and frequency curve that assesses the variability of regional droughts in Syria. The analysis of both indices suggests that all three regions had a severe drought in the 1990s, which had never been observed before in the country. Furthermore, the 2007-2010 drought was the driest period in the instrumental record, happening just before the onset of the recent conflict in Syria.

  7. The Spatial and Temporal Variability of Meltwater Flow Paths: Insights From a Grid of Over 100 Snow Lysimeters

    NASA Astrophysics Data System (ADS)

    Webb, R. W.; Williams, M. W.; Erickson, T. A.

    2018-02-01

    Snowmelt is an important part of the hydrologic cycle and ecosystem dynamics for headwater systems. However, the physical process of water flow through snow is a poorly understood aspect of snow hydrology as meltwater flow paths tend to be highly complex. Meltwater flow paths diverge and converge as percolating meltwater reaches stratigraphic layer interfaces creating high spatial variability. Additionally, a snowpack is temporally heterogeneous due to rapid localized metamorphism that occurs during melt. This study uses a snowmelt lysimeter array at tree line in the Niwot Ridge study area of northern Colorado. The array is designed to address the issue of spatial and temporal variability of basal discharge at 105 locations over an area of 1,300 m2. Observed coefficients of variation ranged from 0 to almost 10 indicating more variability than previously observed, though this variability decreased throughout each melt season. Snowmelt basal discharge also significantly increases as snow depth decreases displaying a cluster pattern that peaks during weeks 3-5 of the snowmelt season. These results are explained by the flow of meltwater along snow layer interfaces. As the snowpack becomes less stratified through the melt season, the pattern transforms from preferential flow paths to uniform matrix flow. Correlation ranges of the observed basal discharge correspond to a mean representative elementary area of 100 m2, or a characteristic length of 10 m. Snowmelt models representing processes at scales less than this will need to explicitly incorporate the spatial variability of snowmelt discharge and meltwater flow paths through snow between model pixels.

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

    NASA Astrophysics Data System (ADS)

    Yenehun, Alemu; Walraevens, Kristine; Batelaan, Okke

    2017-10-01

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

  9. Mapping the Centimeter-Scale Spatial Variability of PAHs and Microbial Populations in the Rhizosphere of Two Plants

    PubMed Central

    Bourceret, Amélia; Leyval, Corinne; de Fouquet, Chantal; Cébron, Aurélie

    2015-01-01

    Rhizoremediation uses root development and exudation to favor microbial activity. Thus it can enhance polycyclic aromatic hydrocarbon (PAH) biodegradation in contaminated soils. Spatial heterogeneity of rhizosphere processes, mainly linked to the root development stage and to the plant species, could explain the contrasted rhizoremediation efficiency levels reported in the literature. Aim of the present study was to test if spatial variability in the whole plant rhizosphere, explored at the centimetre-scale, would influence the abundance of microorganisms (bacteria and fungi), and the abundance and activity of PAH-degrading bacteria, leading to spatial variability in PAH concentrations. Two contrasted rhizospheres were compared after 37 days of alfalfa or ryegrass growth in independent rhizotron devices. Almost all spiked PAHs were degraded, and the density of the PAH-degrading bacterial populations increased in both rhizospheres during the incubation period. Mapping of multiparametric data through geostatistical estimation (kriging) revealed that although root biomass was spatially structured, PAH distribution was not. However a greater variability of the PAH content was observed in the rhizosphere of alfalfa. Yet, in the ryegrass-planted rhizotron, the Gram-positive PAH-degraders followed a reverse depth gradient to root biomass, but were positively correlated to the soil pH and carbohydrate concentrations. The two rhizospheres structured the microbial community differently: a fungus-to-bacterium depth gradient similar to the root biomass gradient only formed in the alfalfa rhizotron. PMID:26599438

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

    NASA Astrophysics Data System (ADS)

    Teutschbein, Claudia; Grabs, Thomas; Karlsen, Reinert H.; Laudon, Hjalmar; Bishop, Kevin

    2016-04-01

    It has long been recognized that streamflow-generating processes are not only dependent on climatic conditions, but also affected by physical catchment properties such as topography, geology, soils and land cover. We hypothesize that these landscape characteristics do not only lead to highly variable hydrologic behavior of rather similar catchments under the same stationary climate conditions (Karlsen et al., 2014), but that they also play a fundamental role for the sensitivity of a catchment to a changing climate (Teutschbein et al., 2015). A multi-model ensemble based on 15 regional climate models was combined with a multi-catchment approach to explore the hydrologic sensitivity of 14 partially nested and rather similar catchments in Northern Sweden to changing climate conditions and the importance of small-scale spatial variability. Current (1981-2010) and future (2061-2090) streamflow was simulated with the HBV model. As expected, projected increases in temperature and precipitation resulted in increased total available streamflow, with lower spring and summer flows, but substantially higher winter streamflow. Furthermore, significant changes in flow durations with lower chances of both high and low flows can be expected in boreal Sweden in the future. This overall trend in projected streamflow pattern changes was comparable among the analyzed catchments while the magnitude of change differed considerably. This suggests that catchments belonging to the same region can show distinctly different degrees of hydrological responses to the same external climate change signal. We reason that differences in spatially distributed physical catchment properties at smaller scales are not only of great importance for current streamflow behavior, but also play a major role as first-order control for the sensitivity of catchments to changing climate conditions. References Karlsen, R.H., T. Grabs, K. Bishop, H. Laudon, and J. Seibert (2014). Landscape controls on

  11. Monitoring Spatial Variability and Temporal Dynamics of Phragmites Using Unmanned Aerial Vehicles

    PubMed Central

    Tóth, Viktor R.

    2018-01-01

    Littoral zones of freshwater lakes are exposed to environmental impacts from both terrestrial and aquatic sides, while substantial anthropogenic pressure also affects the high spatial, and temporal variability of the ecotone. In this study, the possibility of monitoring seasonal and spatial changes in reed (Phragmites australis) stands using an unmanned aerial vehicle (UAV) based remote sensing technique was examined. Stands in eutrophic and mesotrophic parts of Lake Balaton including not deteriorating (stable) and deteriorating (die-back) patches, were tracked throughout the growing season using a UAV equipped with a Normalized Difference Vegetation Index (NDVI) camera. Photophysiological parameters of P. australis were also measured with amplitude modulated fluorescence. Parameters characterizing the dynamics of seasonal changes in NDVI data were used for phenological comparison of eutrophic and mesotrophic, stable and die-back, terrestrial and aquatic, mowed and not-mowed patches of reed. It was shown that stable Phragmites plants from the eutrophic part of the lake reached specific phenological stages up to 3.5 days earlier than plants from the mesotrophic part of the lake. The phenological changes correlated with trophic (total and nitrate-nitrite nitrogen) and physical (organic C and clay content) properties of the sediment, while only minor relationships with air and water temperature were found. Phenological differences between the stable and die-back stands were even more pronounced, with ~34% higher rates of NDVI increase in stable than die-back patches, while the period of NDVI increase was 16 days longer. Aquatic and terrestrial parts of reed stands showed no phenological differences, although intermediate areas (shallow water parts of stands) were found to be less vigorous. Winter mowing of dried Phragmites sped up sprouting and growth of reed in the spring. This study showed that remote sensing-derived photophysiological and phenological variability

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

    PubMed Central

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

    2011-01-01

    Background To identify potential environmental drivers of Japanese Encephalitis virus (JE) transmission in Nepal, we conducted an ecological study to determine the spatial association between 2005 Nepal JE incidence, and climate, agricultural, and land-cover variables at district level. Methods District-level data on JE cases were examined using Local Indicators of Spatial Association (LISA) analysis to identify spatial clusters from 2004 to 2008 and 2005 data was used to fit a spatial lag regression model with climate, agriculture and land-cover variables. Results Prior to 2006, there was a single large cluster of JE cases located in the Far-West and Mid-West terai regions of Nepal. After 2005, the distribution of JE cases in Nepal shifted with clusters found in the central hill areas. JE incidence during the 2005 epidemic had a stronger association with May mean monthly temperature and April mean monthly total precipitation compared to mean annual temperature and precipitation. A parsimonious spatial lag regression model revealed, 1) a significant negative relationship between JE incidence and April precipitation, 2) a significant positive relationship between JE incidence and percentage of irrigated land 3) a non-significant negative relationship between JE incidence and percentage of grassland cover, and 4) a unimodal non-significant relationship between JE Incidence and pig-to-human ratio. Conclusion JE cases clustered in the terai prior to 2006 where it seemed to shift to the Kathmandu region in subsequent years. The spatial pattern of JE cases during the 2005 epidemic in Nepal was significantly associated with low precipitation and the percentage of irrigated land. Despite the availability of an effective vaccine, it is still important to understand environmental drivers of JEV transmission since the enzootic cycle of JEV transmission is not likely to be totally interrupted. Understanding the spatial dynamics of JE risk factors may be useful in providing

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

    NASA Astrophysics Data System (ADS)

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

    2018-02-01

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

  14. Impact of Urbanization on Spatial Variability of Rainfall-A case study of Mumbai city with WRF Model

    NASA Astrophysics Data System (ADS)

    Mathew, M.; Paul, S.; Devanand, A.; Ghosh, S.

    2015-12-01

    Urban precipitation enhancement has been identified over many cities in India by previous studies conducted. Anthropogenic effects such as change in land cover from hilly forest areas to flat topography with solid concrete infrastructures has certain effect on the local weather, the same way the greenhouse gas has on climate change. Urbanization could alter the large scale forcings to such an extent that it may bring about temporal and spatial changes in the urban weather. The present study investigate the physical processes involved in urban forcings, such as the effect of sudden increase in wind velocity travelling through the channel space in between the dense array of buildings, which give rise to turbulence and air mass instability in urban boundary layer and in return alters the rainfall distribution as well as rainfall initiation. A numerical model study is conducted over Mumbai metropolitan city which lies on the west coast of India, to assess the effect of urban morphology on the increase in number of extreme rainfall events in specific locations. An attempt has been made to simulate twenty extreme rainfall events that occurred over the summer monsoon period of the year 2014 using high resolution WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) model to assess the urban land cover mechanisms that influences precipitation variability over this spatially varying urbanized region. The result is tested against simulations with altered land use. The correlation of precipitation with spatial variability of land use is found using a detailed urban land use classification. The initial and boundary conditions for running the model were obtained from the global model ECMWF(European Centre for Medium Range Weather Forecast) reanalysis data having a horizontal resolution of 0.75 °x 0.75°. The high resolution simulations show significant spatial variability in the accumulated rainfall, within a few kilometers itself. Understanding the spatial

  15. Spatial variability of intake fractions for Canadian emission scenarios: a comparison between three resolution scales.

    PubMed

    Manneh, Rima; Margni, Manuele; Deschênes, Louise

    2010-06-01

    Spatially differentiated intake fractions (iFs) linked to Canadian emissions of toxic organic chemicals were developed using the multimedia and multipathways fate and exposure model IMPACT 2002. The fate and exposure of chemicals released to the Canadian environment were modeled with a single regional mass-balance model and three models that provided multiple mass-balance regions within Canada. These three models were based on the Canadian subwatersheds (172 zones), ecozones (15 zones), and provinces (13 zones). Releases of 32 organic chemicals into water and air were considered. This was done in order to (i) assess and compare the spatial variability of iFs within and across the three levels of regionalization and (ii) compare the spatial iFs to nonspatial ones. Results showed that iFs calculated using the subwatershed resolution presented a higher spatial variability (up to 10 orders of magnitude for emissions into water) than the ones based on the ecozones and provinces, implying that higher spatial resolution could potentially reduce uncertainty in iFs and, therefore, increase the discriminating power when assessing and comparing toxic releases for known emission locations. Results also indicated that, for an unknown emission location, a model with high spatial resolution such as the subwatershed model could significantly improve the accuracy of a generic iF. Population weighted iFs span up to 3 orders of magnitude compared to nonspatial iFs calculated by the one-box model. Less significant differences were observed when comparing spatial versus nonspatial iFs from the ecozones and provinces, respectively.

  16. Spatial Variability and Distribution of the Metals in Surface Runoff in a Nonferrous Metal Mine

    PubMed Central

    Ren, Bozhi; Chen, Yangbo; Zhu, Guocheng; Wang, Zhenghua; Zheng, Xie

    2016-01-01

    The spatial variation and distribution features of the metals tested in the surface runoff in Xikuangshan Bao Daxing miming area were analyzed by combining statistical methods with a geographic information system (GIS). The results showed that the maximum concentrations of those five kinds of the metals (Sb, Zn, Cu, Pb, and Cd) in the surface runoff of the antimony mining area were lower than the standard value except the concentration of metal Ni. Their concentrations were 497.1, 2.0, 1.8, 22.2, and 22.1 times larger than the standard value, respectively. This metal pollution was mainly concentrated in local areas, which were seriously polluted. The variation coefficient of Sb, Zn, Cu, Ni, Pb, and Cd was between 0.4 to 0.6, wherein the Sb's spatial variability coefficient is 50.56%, indicating a strong variability. Variation coefficients of the rest of metals were less than 50%, suggesting a moderate variability. The spatial structure analysis showed that the squared correlation coefficient (R 2) of the models fitting for Sb, Zn, Cu, Ni, Pb, and Cd was between 0.721 and 0.976; the ratio of the nugget value (C 0) to the abutment value (C + C 0) was between 0.0767 and 0.559; the semivariogram of Sb, Zn, Ni, and Pb was in agreement with a spherical model, while semivariogram of Cu and Cd was in agreement with Gaussian model, and both had a strong spatial correlation. The trend and spatial distribution indicated that those pollution distributions resulting from Ni, Pb, and Cd are similar, mainly concentrated in both ends of north and south in eastern part. The main reasons for the pollution were attributed to the residents living, transportation, and industrial activities; the Sb distribution was concentrated mainly in the central part, of which the pollution was assigned to the mining and the industrial activity; the pollution distributions of Zn and Cu were similar, mainly concentrated in both ends of north and south as well as in west; the sources of the metals

  17. Spatial vs. individual variability with inheritance in a stochastic Lotka-Volterra system

    NASA Astrophysics Data System (ADS)

    Dobramysl, Ulrich; Tauber, Uwe C.

    2012-02-01

    We investigate a stochastic spatial Lotka-Volterra predator-prey model with randomized interaction rates that are either affixed to the lattice sites and quenched, and / or specific to individuals in either population. In the latter situation, we include rate inheritance with mutations from the particles' progenitors. Thus we arrive at a simple model for competitive evolution with environmental variability and selection pressure. We employ Monte Carlo simulations in zero and two dimensions to study the time evolution of both species' densities and their interaction rate distributions. The predator and prey concentrations in the ensuing steady states depend crucially on the environmental variability, whereas the temporal evolution of the individualized rate distributions leads to largely neutral optimization. Contrary to, e.g., linear gene expression models, this system does not experience fixation at extreme values. An approximate description of the resulting data is achieved by means of an effective master equation approach for the interaction rate distribution.

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

    NASA Astrophysics Data System (ADS)

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

    1998-07-01

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

  19. Multi-scale controls on spatial variability in river biogeochemical cycling

    NASA Astrophysics Data System (ADS)

    Blaen, Phillip; Kurz, Marie; Knapp, Julia; Mendoza-Lera, Clara; Lee-Cullin, Joe; Klaar, Megan; Drummond, Jennifer; Jaeger, Anna; Zarnetske, Jay; Lewandowski, Joerg; Marti, Eugenia; Ward, Adam; Fleckenstein, Jan; Datry, Thibault; Larned, Scott; Krause, Stefan

    2016-04-01

    Excessive nutrient concentrations are common in surface waters and groundwaters in agricultural catchments worldwide. Increasing geomorphological heterogeneity in river channels may help to attenuate nutrient pollution by facilitating water exchange fluxes with the hyporheic zone; a site of intense microbial activity where biogeochemical cycling rates can be high. However, the controls on spatial variability in biogeochemical cycling, particularly at scales relevant for river managers, are largely unknown. Here, we aimed to assess: 1) how differences in river geomorphological heterogeneity control solute transport and rates of biogeochemical cycling at sub-reach scales (102 m); and 2) the relative magnitude of these differences versus those relating to reach scale substrate variability (103 m). We used the reactive tracer resazurin (Raz), a weakly fluorescent dye that transforms to highly fluorescent resorufin (Rru) under mildly reducing conditions, as a proxy to assess rates of biogeochemical cycling in a lowland river in southern England. Solute tracer tests were conducted in two reaches with contrasting substrates: one sand-dominated and the other gravel-dominated. Each reach was divided into sub-reaches that varied in geomorphic complexity (e.g. by the presence of pool-riffle sequences or the abundance of large woody debris). Slug injections of Raz and the conservative tracer fluorescein were conducted in each reach during baseflow conditions (Q ≈ 80 L/s) and breakthrough curves monitored using in-situ fluorometers. Preliminary results indicate overall Raz:Rru transformation rates in the gravel-dominated reach were more than 50% higher than those in the sand-dominated reach. However, high sub-reach variability in Raz:Rru transformation rates and conservative solute transport parameters suggests small scale targeted management interventions to alter geomorphic heterogeneity may be effective in creating hotspots of river biogeochemical cycling and nutrient load

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

    NASA Technical Reports Server (NTRS)

    Jasinski, Michael F.; Eagleson, Peter S.

    1989-01-01

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

  1. Electrically tunable spatially variable switching in ferroelectric liquid crystal/water system

    NASA Astrophysics Data System (ADS)

    Choudhary, A.; Coondoo, I.; Prakash, J.; Sreenivas, K.; Biradar, A. M.

    2009-04-01

    An unusual switching phenomenon in the region outside conducting patterned area in ferroelectric liquid crystal (FLC) containing about 1-2 wt % of water has been observed. The presence of water in the studied heterogeneous system was confirmed by Fourier transform infrared spectroscopy. The observed optical studies have been emphasized on the "spatially variable switching" phenomenon of the molecules in the nonconducting region of the cell. The observed phenomenon is due to diffusion of water between the smectic layers of the FLC and the interaction of the curved electric field lines with the FLC molecules in the nonconducting region.

  2. Effect of spatial variability of storm on the optimal placement of best management practices (BMPs).

    PubMed

    Chang, C L; Chiueh, P T; Lo, S L

    2007-12-01

    It is significant to design best management practices (BMPs) and determine the proper BMPs placement for the purpose that can not only satisfy the water quantity and water quality standard, but also lower the total cost of BMPs. The spatial rainfall variability can have much effect on its relative runoff and non-point source pollution (NPSP). Meantime, the optimal design and placement of BMPs would be different as well. The objective of this study was to discuss the relationship between the spatial variability of rainfall and the optimal BMPs placements. Three synthetic rainfall storms with varied spatial distributions, including uniform rainfall, downstream rainfall and upstream rainfall, were designed. WinVAST model was applied to predict runoff and NPSP. Additionally, detention pond and swale were selected for being structural BMPs. Scatter search was applied to find the optimal BMPs placement. The results show that mostly the total cost of BMPs is higher in downstream rainfall than in upstream rainfall or uniform rainfall. Moreover, the cost of detention pond is much higher than swale. Thus, even though detention pond has larger efficiency for lowering peak flow and pollutant exports, it is not always the determined set in each subbasin.

  3. Passive Sampling to Capture the Spatial Variability of Coarse Particles by Composition in Cleveland, OH

    EPA Science Inventory

    Passive samplers deployed at 25 sites for three week-long intervals were used to characterize spatial variability in the mass and composition of coarse particulate matter (PM10-2.5) in Cleveland, OH in summer 2008. The size and composition of individual particles deter...

  4. Spatial variability of organic matter molecular composition and elemental geochemistry in surface sediments of a small boreal Swedish lake

    NASA Astrophysics Data System (ADS)

    Tolu, Julie; Rydberg, Johan; Meyer-Jacob, Carsten; Gerber, Lorenz; Bindler, Richard

    2017-04-01

    The composition of sediment organic matter (OM) exerts a strong control on biogeochemical processes in lakes, such as those involved in the fate of carbon, nutrients and trace metals. While between-lake spatial variability of OM quality is increasingly investigated, we explored in this study how the molecular composition of sediment OM varies spatially within a single lake and related this variability to physical parameters and elemental geochemistry. Surface sediment samples (0-10 cm) from 42 locations in Härsvatten - a small boreal forest lake with a complex basin morphometry - were analyzed for OM molecular composition using pyrolysis gas chromatography mass spectrometry for the contents of 23 major and trace elements and biogenic silica. We identified 162 organic compounds belonging to different biochemical classes of OM (e.g., carbohydrates, lignin and lipids). Close relationships were found between the spatial patterns of sediment OM molecular composition and elemental geochemistry. Differences in the source types of OM (i.e., terrestrial, aquatic plant and algal) were linked to the individual basin morphometries and chemical status of the lake. The variability in OM molecular composition was further driven by the degradation status of these different source pools, which appeared to be related to sedimentary physicochemical parameters (e.g., redox conditions) and to the molecular structure of the organic compounds. Given the high spatial variation in OM molecular composition within Härsvatten and its close relationship with elemental geochemistry, the potential for large spatial variability across lakes should be considered when studying biogeochemical processes involved in the cycling of carbon, nutrients and trace elements or when assessing lake budgets.

  5. Spatial Field Variability Mapping of Rice Crop using Clustering Technique from Space Borne Hyperspectral Data

    NASA Astrophysics Data System (ADS)

    Moharana, S.; Dutta, S.

    2015-12-01

    Precision farming refers to field-specific management of an agricultural crop at a spatial scale with an aim to get the highest achievable yield and to achieve this spatial information on field variability is essential. The difficulty in mapping of spatial variability occurring within an agriculture field can be revealed by employing spectral techniques in hyperspectral imagery rather than multispectral imagery. However an advanced algorithm needs to be developed to fully make use of the rich information content in hyperspectral data. In the present study, potential of hyperspectral data acquired from space platform was examined to map the field variation of paddy crop and its species discrimination. This high dimensional data comprising 242 spectral narrow bands with 30m ground resolution Hyperion L1R product acquired for Assam, India (30th Sept and 3rd Oct, 2014) were allowed for necessary pre-processing steps followed by geometric correction using Hyperion L1GST product. Finally an atmospherically corrected and spatially deduced image consisting of 112 band was obtained. By employing an advanced clustering algorithm, 12 different clusters of spectral waveforms of the crop were generated from six paddy fields for each images. The findings showed that, some clusters were well discriminated representing specific rice genotypes and some clusters were mixed treating as a single rice genotype. As vegetation index (VI) is the best indicator of vegetation mapping, three ratio based VI maps were also generated and unsupervised classification was performed for it. The so obtained 12 clusters of paddy crop were mapped spatially to the derived VI maps. From these findings, the existence of heterogeneity was clearly captured in one of the 6 rice plots (rice plot no. 1) while heterogeneity was observed in rest of the 5 rice plots. The degree of heterogeneous was found more in rice plot no.6 as compared to other plots. Subsequently, spatial variability of paddy field was

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

    NASA Astrophysics Data System (ADS)

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

    2017-11-01

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

  7. Temporal and spatial variability of global water balance

    USGS Publications Warehouse

    McCabe, Gregory J.; Wolock, David M.

    2013-01-01

    An analysis of simulated global water-balance components (precipitation [P], actual evapotranspiration [AET], runoff [R], and potential evapotranspiration [PET]) for the past century indicates that P has been the primary driver of variability in R. Additionally, since about 2000, there have been increases in P, AET, R, and PET for most of the globe. The increases in R during 2000 through 2009 have occurred despite unprecedented increases in PET. The increases in R are the result of substantial increases in P during the cool Northern Hemisphere months (i.e. October through March) when PET increases were relatively small; the largest PET increases occurred during the warm Northern Hemisphere months (April through September). Additionally, for the 2000 through 2009 period, the latitudinal distribution of P departures appears to co-vary with the mean P departures from 16 climate model projections of the latitudinal response of P to warming, except in the high latitudes. Finally, changes in water-balance variables appear large from the perspective of departures from the long-term means. However, when put into the context of the magnitudes of the raw water balance variable values, there appears to have been little change in any of the water-balance variables over the past century on a global or hemispheric scale.

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

    PubMed

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

    2013-10-09

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

  9. Hierarchical Bayesian spatial models for predicting multiple forest variables using waveform LiDAR, hyperspectral imagery, and large inventory datasets

    USGS Publications Warehouse

    Finley, Andrew O.; Banerjee, Sudipto; Cook, Bruce D.; Bradford, John B.

    2013-01-01

    In this paper we detail a multivariate spatial regression model that couples LiDAR, hyperspectral and forest inventory data to predict forest outcome variables at a high spatial resolution. The proposed model is used to analyze forest inventory data collected on the US Forest Service Penobscot Experimental Forest (PEF), ME, USA. In addition to helping meet the regression model's assumptions, results from the PEF analysis suggest that the addition of multivariate spatial random effects improves model fit and predictive ability, compared with two commonly applied modeling approaches. This improvement results from explicitly modeling the covariation among forest outcome variables and spatial dependence among observations through the random effects. Direct application of such multivariate models to even moderately large datasets is often computationally infeasible because of cubic order matrix algorithms involved in estimation. We apply a spatial dimension reduction technique to help overcome this computational hurdle without sacrificing richness in modeling.

  10. A Survey of Spatial and Seasonal Water Isotope Variability on the Juneau Icefield, Alaksa

    NASA Astrophysics Data System (ADS)

    Dennis, D.; Carter, A.; Clinger, A. E.; Eads, O. L.; Gotwals, S.; Gunderson, J.; Hollyday, A. E.; Klein, E. S.; Markle, B. R.; Timms, J. R.

    2015-12-01

    The depletion of stable oxygen-hydrogen isotopes (δ18O and δH) is well correlated with temperature change, which is driven by variation in topography, climate, and atmospheric circulation. This study presents a survey of the spatial and seasonal variability of isotopic signatures on the Juneau Icefield (JI), Alaska, USA which spans over 3,000 square-kilometers. To examine small scale variability in the previous year's accumulation, samples were taken at regular intervals from snow pits and a one square-kilometer surficial grid. Surface snow samples were collected across the icefield to evaluate large scale variability, ranging approximately 1,000 meters in elevation and 100 kilometers in distance. Individual precipitation events were also sampled to track percolation throughout the snowpack and temperature correlations. A survey of this extent has never been undertaken on the JI. Samples were analyzed in the field using a Los Gatos laser isotope analyzer. This survey helps us better understand isotope fractionation on temperate glaciers in coastal environments and provides preliminary information on the suitability of the JI for a future ice core drilling project.

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

    Treesearch

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

    2008-01-01

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

  12. Spatial variability of the effect of air pollution on term birth weight: evaluating influential factors using Bayesian hierarchical models.

    PubMed

    Li, Lianfa; Laurent, Olivier; Wu, Jun

    2016-02-05

    Epidemiological studies suggest that air pollution is adversely associated with pregnancy outcomes. Such associations may be modified by spatially-varying factors including socio-demographic characteristics, land-use patterns and unaccounted exposures. Yet, few studies have systematically investigated the impact of these factors on spatial variability of the air pollution's effects. This study aimed to examine spatial variability of the effects of air pollution on term birth weight across Census tracts and the influence of tract-level factors on such variability. We obtained over 900,000 birth records from 2001 to 2008 in Los Angeles County, California, USA. Air pollution exposure was modeled at individual level for nitrogen dioxide (NO2) and nitrogen oxides (NOx) using spatiotemporal models. Two-stage Bayesian hierarchical non-linear models were developed to (1) quantify the associations between air pollution exposure and term birth weight within each tract; and (2) examine the socio-demographic, land-use, and exposure-related factors contributing to the between-tract variability of the associations between air pollution and term birth weight. Higher air pollution exposure was associated with lower term birth weight (average posterior effects: -14.7 (95 % CI: -19.8, -9.7) g per 10 ppb increment in NO2 and -6.9 (95 % CI: -12.9, -0.9) g per 10 ppb increment in NOx). The variation of the association across Census tracts was significantly influenced by the tract-level socio-demographic, exposure-related and land-use factors. Our models captured the complex non-linear relationship between these factors and the associations between air pollution and term birth weight: we observed the thresholds from which the influence of the tract-level factors was markedly exacerbated or attenuated. Exacerbating factors might reflect additional exposure to environmental insults or lower socio-economic status with higher vulnerability, whereas attenuating factors might indicate reduced

  13. Spatial variability of mountain stream dynamics along the Ethiopian Rift Valley escarpment

    NASA Astrophysics Data System (ADS)

    Asfaha, Tesfaalem-Ghebreyohannes; Frankl, Amaury; Zenebe, Amanuel; Haile, Mitiku; Nyssen, Jan

    2014-05-01

    Changes in hydrogeomorphic characteristics of mountain streams are generally deemed to be controlled mainly by land use/cover changes and rainfall variability. This study investigates the spatial variability of peak discharge in relation to land cover, rainfall and topographic variables in eleven catchments of the Ethiopian Rift Valley escarpment (average slope gradient = 48% (± 13%). Rapid deforestation of the escarpment in the second half of the 20th century resulted in the occurrence of strong flash floods, transporting large amounts of discharge and sediment to the lower graben bottom. Due to integrated reforestation interventions as of the 1980s, many of these catchments do show improvement in vegetation cover at various degrees. Daily rainfall was measured using seven non-recording rain gauges, while peak stage discharges were measured after floods using crest stage gauges installed at eleven stream reaches. Peak discharges were calculated using the Manning's equation. Daily area-weighted rainfall was computed for each catchment using the Thiessen Polygon method. To estimate the vegetation cover of each catchment, the Normalized Difference Vegetation Index was calculated from Landsat TM imagery (mean = 0.14 ± 0.05). In the rainy season of 2012, there was a positive correlation between daily rainfall and peak discharge in each of the monitored catchments. In a multiple linear regression analysis (R² = 0.83; P<0.01), average daily peak discharge in all rivers was positively related with rainfall depth and catchment size and negatively with vegetation cover (as represented by average NDVI values). Average slope gradient of the catchments and Gravelius's compactness index did not show a statistically significant relation with peak discharge. This study shows that though the average vegetation cover of the catchments is still relatively low, differences in vegetation cover, together with rainfall variability plays a determining role in the amount of peak

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

    DOT National Transportation Integrated Search

    2015-12-01

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

  15. Characterization of meter-scale spatial variability of riverbed hydraulic conductivity in a lowland river (Aa River, Belgium)

    NASA Astrophysics Data System (ADS)

    Ghysels, Gert; Benoit, Sien; Awol, Henock; Jensen, Evan Patrick; Debele Tolche, Abebe; Anibas, Christian; Huysmans, Marijke

    2018-04-01

    An improved general understanding of riverbed heterogeneity is of importance for all groundwater modeling studies that include river-aquifer interaction processes. Riverbed hydraulic conductivity (K) is one of the main factors controlling river-aquifer exchange fluxes. However, the meter-scale spatial variability of riverbed K has not been adequately mapped as of yet. This study aims to fill this void by combining an extensive field measurement campaign focusing on both horizontal and vertical riverbed K with a detailed geostatistical analysis of the meter-scale spatial variability of riverbed K . In total, 220 slug tests and 45 standpipe tests were performed at two test sites along the Belgian Aa River. Omnidirectional and directional variograms (along and across the river) were calculated. Both horizontal and vertical riverbed K vary over several orders of magnitude and show significant meter-scale spatial variation. Horizontal K shows a bimodal distribution. Elongated zones of high horizontal K along the river course are observed at both sections, indicating a link between riverbed structures, depositional environment and flow regime. Vertical K is lognormally distributed and its spatial variability is mainly governed by the presence and thickness of a low permeable organic layer at the top of the riverbed. The absence of this layer in the center of the river leads to high vertical K and is related to scouring of the riverbed by high discharge events. Variograms of both horizontal and vertical K show a clear directional anisotropy with ranges along the river being twice as large as those across the river.

  16. Spatially variable risk factors for malaria in a geographically heterogeneous landscape, western Kenya: an explorative study.

    PubMed

    Homan, Tobias; Maire, Nicolas; Hiscox, Alexandra; Di Pasquale, Aurelio; Kiche, Ibrahim; Onoka, Kelvin; Mweresa, Collins; Mukabana, Wolfgang R; Ross, Amanda; Smith, Thomas A; Takken, Willem

    2016-01-04

    Large reductions in malaria transmission and mortality have been achieved over the last decade, and this has mainly been attributed to the scale-up of long-lasting insecticidal bed nets and indoor residual spraying with insecticides. Despite these gains considerable residual, spatially heterogeneous, transmission remains. To reduce transmission in these foci, researchers need to consider the local demographical, environmental and social context, and design an appropriate set of interventions. Exploring spatially variable risk factors for malaria can give insight into which human and environmental characteristics play important roles in sustaining malaria transmission. On Rusinga Island, western Kenya, malaria infection was tested by rapid diagnostic tests during two cross-sectional surveys conducted 3 months apart in 3632 individuals from 790 households. For all households demographic data were collected by means of questionnaires. Environmental variables were derived using Quickbird satellite images. Analyses were performed on 81 project clusters constructed by a traveling salesman algorithm, each containing 50-51 households. A standard linear regression model was fitted containing multiple variables to determine how much of the spatial variation in malaria prevalence could be explained by the demographic and environmental data. Subsequently, a geographically-weighted regression (GWR) was performed assuming non-stationarity of risk factors. Special attention was taken to investigate the effect of residual spatial autocorrelation and local multicollinearity. Combining the data from both surveys, overall malaria prevalence was 24%. Scan statistics revealed two clusters which had significantly elevated numbers of malaria cases compared to the background prevalence across the rest of the study area. A multivariable linear model including environmental and household factors revealed that higher socioeconomic status, outdoor occupation and population density were

  17. Effects of rainfall partitioning in the seasonal and spatial variability of soil water content in a Mediterranean downy oak forest

    NASA Astrophysics Data System (ADS)

    Garcia-Estringana, P.; Latron, J.; Molina, A. J.; Llorens, P.

    2012-04-01

    Rainfall partitioning fluxes (throughfall and stemflow) have a large degree of temporal and spatial variability and may consequently lead to significant changes in the volume and composition of water that reach the understory and the soil. The objective of this work is to study the effect of rainfall partitioning on the seasonal and spatial variability of the soil water content in a Mediterranean downy oak forest (Quercus pubescens), located in the Vallcebre research catchments (42° 12'N, 1° 49'E). The monitoring design, started on July 2011, consists of a set of 20 automatic rain recorders and 40 automatic soil moisture probes located below the canopy. One hundred hemispheric photographs of the canopy were used to place the instruments at representative locations (in terms of canopy cover) within the plot. Bulk rainfall, stemflow and meteorological conditions above the forest cover are also automatically recorded. Canopy cover, in leaf and leafless periods, as well as biometric characteristics of the plot, are also regularly measured. This work presents the first results describing throughfall and soil moisture spatial variability during both the leaf and leafless periods. The main drivers of throughfall variability, as canopy structure and meteorological conditions are also analysed.

  18. ISM DUST GRAINS AND N-BAND SPECTRAL VARIABILITY IN THE SPATIALLY RESOLVED SUBARCSECOND BINARY UY Aur

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

    Skemer, Andrew J.; Close, Laird M.; Hinz, Philip M.

    2010-03-10

    The 10 {mu}m silicate feature is an essential diagnostic of dust-grain growth and planet formation in young circumstellar disks. The Spitzer Space Telescope has revolutionized the study of this feature, but due to its small (85 cm) aperture, it cannot spatially resolve small/medium-separation binaries ({approx}<3''; {approx}< 420 AU) at the distances of the nearest star-forming regions ({approx}140 pc). Large, 6-10 m ground-based telescopes with mid-infrared instruments can resolve these systems. In this paper, we spatially resolve the 0.''88 binary, UY Aur, with MMTAO/BLINC-MIRAC4 mid-infrared spectroscopy. We then compare our spectra to Spitzer/IRS (unresolved) spectroscopy, and resolved images from IRTF/MIRAC2, Keck/OSCIR,more » and Gemini/Michelle, which were taken over the past decade. We find that UY Aur A has extremely pristine, interstellar medium (ISM)-like grains and that UY Aur B has an unusually shaped silicate feature, which is probably the result of blended emission and absorption from foreground extinction in its disk. We also find evidence for variability in both UY Aur A and UY Aur B by comparing synthetic photometry from our spectra with resolved imaging from previous epochs. The photometric variability of UY Aur A could be an indication that the silicate emission itself is variable, as was recently found in EX Lupi. Otherwise, the thermal continuum is variable, and either the ISM-like dust has never evolved, or it is being replenished, perhaps by UY Aur's circumbinary disk.« less

  19. Temporal and spatial variabilities of Antarctic ice mass changes inferred by GRACE in a Bayesian framework

    NASA Astrophysics Data System (ADS)

    Wang, L.; Davis, J. L.; Tamisiea, M. E.

    2017-12-01

    The Antarctic ice sheet (AIS) holds about 60% of all fresh water on the Earth, an amount equivalent to about 58 m of sea-level rise. Observation of AIS mass change is thus essential in determining and predicting its contribution to sea level. While the ice mass loss estimates for West Antarctica (WA) and the Antarctic Peninsula (AP) are in good agreement, what the mass balance over East Antarctica (EA) is, and whether or not it compensates for the mass loss is under debate. Besides the different error sources and sensitivities of different measurement types, complex spatial and temporal variabilities would be another factor complicating the accurate estimation of the AIS mass balance. Therefore, a model that allows for variabilities in both melting rate and seasonal signals would seem appropriate in the estimation of present-day AIS melting. We present a stochastic filter technique, which enables the Bayesian separation of the systematic stripe noise and mass signal in decade-length GRACE monthly gravity series, and allows the estimation of time-variable seasonal and inter-annual components in the signals. One of the primary advantages of this Bayesian method is that it yields statistically rigorous uncertainty estimates reflecting the inherent spatial resolution of the data. By applying the stochastic filter to the decade-long GRACE observations, we present the temporal variabilities of the AIS mass balance at basin scale, particularly over East Antarctica, and decipher the EA mass variations in the past decade, and their role in affecting overall AIS mass balance and sea level.

  20. Imaging Variable Stars with HST

    NASA Astrophysics Data System (ADS)

    Karovska, Margarita

    2011-05-01

    The Hubble Space Telescope (HST) observations of astronomical sources, ranging from objects in our solar system to objects in the early Universe, have revolutionized our knowledge of the Universe its origins and contents.I will highlight results from HST observations of variable stars obtained during the past twenty or so years. Multiwavelength observations of numerous variable stars and stellar systems were obtained using the superb HST imaging capabilities and its unprecedented angular resolution, especially in the UV and optical. The HST provided the first detailed images probing the structure of variable stars including their atmospheres and circumstellar environments. AAVSO observations and light curves have been critical for scheduling of many of these observations and provided important information and context for understanding of the imaging results of many variable sources. I will describe the scientific results from the imaging observations of variable stars including AGBs, Miras, Cepheids, semi-regular variables (including supergiants and giants), YSOs and interacting stellar systems with a variable stellar components. These results have led to an unprecedented understanding of the spatial and temporal characteristics of these objects and their place in the stellar evolutionary chains, and in the larger context of the dynamic evolving Universe.

  1. Imaging Variable Stars with HST

    NASA Astrophysics Data System (ADS)

    Karovska, M.

    2012-06-01

    (Abstract only) The Hubble Space Telescope (HST) observations of astronomical sources, ranging from objects in our solar system to objects in the early Universe, have revolutionized our knowledge of the Universe its origins and contents. I highlight results from HST observations of variable stars obtained during the past twenty or so years. Multiwavelength observations of numerous variable stars and stellar systems were obtained using the superb HST imaging capabilities and its unprecedented angular resolution, especially in the UV and optical. The HST provided the first detailed images probing the structure of variable stars including their atmospheres and circumstellar environments. AAVSO observations and light curves have been critical for scheduling of many of these observations and provided important information and context for understanding of the imaging results of many variable sources. I describe the scientific results from the imaging observations of variable stars including AGBs, Miras, Cepheids, semiregular variables (including supergiants and giants), YSOs and interacting stellar systems with a variable stellar components. These results have led to an unprecedented understanding of the spatial and temporal characteristics of these objects and their place in the stellar evolutionary chains, and in the larger context of the dynamic evolving Universe.

  2. Effect of spatial variability on solute velocity and dispersion in two soils of the Argentinian Pampas

    NASA Astrophysics Data System (ADS)

    Aparicio, Virginia; Costa, José; Domenech, Marisa; Castro Franco, Mauricio

    2013-04-01

    Predicting how solutes move through the unsaturated zone is essential to determine the potential risk of groundwater contamination (Costa et al., 1994). The estimation of the spatial variability of solute transport parameters, such as velocity and dispersion, enables a more accurate understanding of transport processes. Apparent electrical conductivity (ECa) has been used to characterize the spatial behavior of soil properties. The objective of this study was to characterize the spatial variability of soil transport parameters at field scale using ECa measurements. ECa measurements of 42 ha (Tres Arroyos) and 50 ha (Balcarce) farms were collected for the top 0-30 cm (ECa(s)) soil using the Veris® 3100. ECa maps were generated using geostatistical interpolation techniques. From these maps, three general areas were delineated, named high, medium, and low ECa zones. At each zone, three sub samples were collected. Soil samples were taken at 0-30 cm. Clay content and organic matter (OM) was analyzed. The transport assay was performed in the laboratory using undisturbed soil columns, under controlled conditions of T ° (22 ° C).Br- determinations were performed with a specific Br- electrode. The breakthrough curves were fitted using the model CXTFIT 2.1 (Toride et al., 1999) to estimate the transport parameters Velocity (V) and Dispersion (D). In this study we found no statistical significant differences for V and D between treatments. Also, there were no differences in V and D between sites. The average V and D value was 9.3 cm h-1 and 357.5 cm2 h-2, respectively. Despite finding statistically significant differences between treatments for the other measured physical and chemical properties, in our work it was not possible to detect the spatial variability of solute transport parameters.

  3. Variability of Relative Sea Level Rise: Spatial and Temporal Correlations in Northwest Gulf of Mexico

    NASA Astrophysics Data System (ADS)

    Tissot, P.; Reisinger, A. S.; Besonen, M. R.

    2017-12-01

    While our understanding of global sea level rise and its budget has made great progress over the past decade, the spatial and temporal variability of relative sea level rise along the coasts still needs to be better understood and quantified. We developed a technique to reduce the confidence intervals associated with relative sea level rise (RSLR) estimates for 15 tide gauges located along the Texas coast for the period 1993-2016. Seasonally detrended monthly mean water levels are highly correlated after removal of station-specific RSLR trends, which allows for the quantification of a common, low frequency oceanic signal. RSLR confidence intervals are reduced from over 1.9 mm/yr, on average 2.3mm, to less than 1.1 mm/yr, on average 0.7 mm/yr after removing this common signal. The resulting RSLR rates range from 3.0 to 8.4 mm/yr. The range is wider than the longer-term rates of 5.3, 3.8 and 1.9 mm/yr measured from north to south by the three National Water Level Observation Network (NWLON) stations covering the study area (over different and longer time spans). The results emphasize the importance of the spatial variability of the vertical land motion component of RSLR. The temporal variability of the coherent oceanic signal is not significantly correlated to the ENSO signal for the study period and is only weakly correlated to the AMO and PDO climate indices. The coherence of the signal is further investigated by comparison with other locations along the Gulf of Mexico and along the Northeast Atlantic coast. The results are discussed while considering strong local processes along the Northwest Gulf of Mexico, such as wind forcing and intermittent eddies and the spatially broader influence of the Gulf Stream. The local significance of the RSLR spatial and temporal differences are discussed in terms of the differences in inundation frequency for nuisance type flooding including comparing the time span to reach a probability of at least one nuisance flood event per

  4. Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

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

    Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef

    Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth’s climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modesmore » and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this article, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.« less

  5. Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

    DOE PAGES

    Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef; ...

    2016-10-04

    Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth’s climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modesmore » and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this article, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.« less

  6. Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

    NASA Astrophysics Data System (ADS)

    Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef; Hu, Aixue; Hamlington, Benjamin; Kenigson, Jessica; Palanisamy, Hindumathi; Thompson, Philip

    2017-01-01

    Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth's climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modes and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this paper, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.

  7. [Spatial variability of soil nutrients based on geostatistics combined with GIS--a case study in Zunghua City of Hebei Province].

    PubMed

    Guo, X; Fu, B; Ma, K; Chen, L

    2000-08-01

    Geostatistics combined with GIS was applied to analyze the spatial variability of soil nutrients in topsoil (0-20 cm) in Zunghua City of Hebei Province. GIS can integrate attribute data with geographical data of system variables, which makes the application of geostatistics technique for large spatial scale more convenient. Soil nutrient data in this study included available N (alkaline hydrolyzing nitrogen), total N, available K, available P and organic matter. The results showed that the semivariograms of soil nutrients were best described by spherical model, except for that of available K, which was best fitted by complex structure of exponential model and linear with sill model. The spatial variability of available K was mainly produced by structural factor, while that of available N, total N, available P and organic matter was primarily caused by random factor. However, their spatial heterogeneity degree was different: the degree of total N and organic matter was higher, and that of available P and available N was lower. The results also indicated that the spatial correlation of the five tested soil nutrients at this large scale was moderately dependent. The ranges of available N and available P were almost same, which were 5 km and 5.5 km, respectively. The range of total N was up to 18 km, and that of organic matter was 8.5 km. For available K, the spatial variability scale primarily expressed exponential model between 0-3.5 km, but linear with sill model between 3.5-25.5 km. In addition, five soil nutrients exhibited different isotropic ranges. Available N and available P were isotropic through the whole research range (0-28 km). The isotropic range of available K was 0-8 km, and that of total N and organic matter was 0-10 km.

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

    PubMed Central

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

    2014-01-01

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

  9. A soil-landscape framework for understanding spatial and temporal variability in biogeochemical processes in catchments

    NASA Astrophysics Data System (ADS)

    McGuire, K. J.; Bailey, S. W.; Ross, D. S.

    2017-12-01

    Heterogeneity in biophysical properties within catchments challenges how we quantify and characterize biogeochemical processes and interpret catchment outputs. Interactions between the spatiotemporal variability of hydrological states and fluxes and soil development can spatially structure catchments, leading to a framework for understanding patterns in biogeochemical processes. In an upland, glaciated landscape at the Hubbard Brook Experimental Forest (HBEF) in New Hampshire, USA, we are embracing the structure and organization of soils to understand the spatial relations between runoff production zones, distinct soil-biogeochemical environments, and solute retention and release. This presentation will use observations from the HBEF to demonstrate that a soil-landscape framework is essential in understanding the spatial and temporal variability of biogeochemical processes in this catchment. Specific examples will include how laterally developed soils reveal the location of active runoff production zones and lead to gradients in primary mineral dissolution and the distribution of weathering products along hillslopes. Soil development patterns also highlight potential carbon and nitrogen cycling hotspots, differentiate acidic conditions, and affect the regulation of surface water quality. Overall, this work demonstrates the importance of understanding the landscape-level structural organization of soils in characterizing the variation and extent of biogeochemical processes that occur in catchments.

  10. Snowpack spatial variability: Towards understanding its effect on remote sensing measurements and snow slope stability

    NASA Astrophysics Data System (ADS)

    Marshall, Hans-Peter

    The distribution of water in the snow-covered areas of the world is an important climate change indicator, and it is a vital component of the water cycle. At local and regional scales, the snow water equivalent (SWE), the amount of liquid water a given area of the snowpack represents, is very important for water resource management, flood forecasting, and prediction of available hydropower energy. Measurements from only a few automatic weather stations, such as the SNOTEL network, or sparse manual snowpack measurements are typically extrapolated for estimating SWE over an entire basin. Widespread spatial variability in the distribution of SWE and snowpack stratigraphy at local scales causes large errors in these basin estimates. Remote sensing measurements offer a promising alternative, due to their large spatial coverage and high temporal resolution. Although snow cover extent can currently be estimated from remote sensing data, accurately quantifying SWE from remote sensing measurements has remained difficult, due to a high sensitivity to variations in grain size and stratigraphy. In alpine snowpacks, the large degree of spatial variability of snowpack properties and geometry, caused by topographic, vegetative, and microclimatic effects, also makes prediction of snow avalanches very difficult. Ground-based radar and penetrometer measurements can quickly and accurately characterize snowpack properties and SWE in the field. A portable lightweight radar was developed, and allows a real-time estimate of SWE to within 10%, as well as measurements of depths of all major density transitions within the snowpack. New analysis techniques developed in this thesis allow accurate estimates of mechanical properties and an index of grain size to be retrieved from the SnowMicroPenetrometer. These two tools together allow rapid characterization of the snowpack's geometry, mechanical properties, and SWE, and are used to guide a finite element model to study the stress distribution

  11. City scale pollen concentration variability

    NASA Astrophysics Data System (ADS)

    van der Molen, Michiel; van Vliet, Arnold; Krol, Maarten

    2016-04-01

    Pollen are emitted in the atmosphere both in the country-side and in cities. Yet the majority of the population is exposed to pollen in cities. Allergic reactions may be induced by short-term exposure to pollen. This raises the question how variable pollen concentration in cities are in temporally and spatially, and how much of the pollen in cities are actually produced in the urban region itself. We built a high resolution (1 × 1 km) pollen dispersion model based on WRF-Chem to study a city's pollen budget and the spatial and temporal variability in concentration. It shows that the concentrations are highly variable, as a result of source distribution, wind direction and boundary layer mixing, as well as the release rate as a function of temperature, turbulence intensity and humidity. Hay Fever Forecasts based on such high resolution emission and physical dispersion modelling surpass traditional hay fever warning methods based on temperature sum methods. The model gives new insights in concentration variability, personal and community level exposure and prevention. The model will be developped into a new forecast tool to serve allergic people to minimize their exposure and reduce nuisance, coast of medication and sick leave. This is an innovative approach in hay fever warning systems.

  12. Optoacoustic Monitoring of Physiologic Variables

    PubMed Central

    Esenaliev, Rinat O.

    2017-01-01

    Optoacoustic (photoacoustic) technique is a novel diagnostic platform that can be used for noninvasive measurements of physiologic variables, functional imaging, and hemodynamic monitoring. This technique is based on generation and time-resolved detection of optoacoustic (thermoelastic) waves generated in tissue by short optical pulses. This provides probing of tissues and individual blood vessels with high optical contrast and ultrasound spatial resolution. Because the optoacoustic waves carry information on tissue optical and thermophysical properties, detection, and analysis of the optoacoustic waves allow for measurements of physiologic variables with high accuracy and specificity. We proposed to use the optoacoustic technique for monitoring of a number of important physiologic variables including temperature, thermal coagulation, freezing, concentration of molecular dyes, nanoparticles, oxygenation, and hemoglobin concentration. In this review we present origin of contrast and high spatial resolution in these measurements performed with optoacoustic systems developed and built by our group. We summarize data obtained in vitro, in experimental animals, and in humans on monitoring of these physiologic variables. Our data indicate that the optoacoustic technology may be used for monitoring of cerebral blood oxygenation in patients with traumatic brain injury and in neonatal patients, central venous oxygenation monitoring, total hemoglobin concentration monitoring, hematoma detection and characterization, monitoring of temperature, and coagulation and freezing boundaries during thermotherapy. PMID:29311964

  13. Optoacoustic Monitoring of Physiologic Variables.

    PubMed

    Esenaliev, Rinat O

    2017-01-01

    Optoacoustic (photoacoustic) technique is a novel diagnostic platform that can be used for noninvasive measurements of physiologic variables, functional imaging, and hemodynamic monitoring. This technique is based on generation and time-resolved detection of optoacoustic (thermoelastic) waves generated in tissue by short optical pulses. This provides probing of tissues and individual blood vessels with high optical contrast and ultrasound spatial resolution. Because the optoacoustic waves carry information on tissue optical and thermophysical properties, detection, and analysis of the optoacoustic waves allow for measurements of physiologic variables with high accuracy and specificity. We proposed to use the optoacoustic technique for monitoring of a number of important physiologic variables including temperature, thermal coagulation, freezing, concentration of molecular dyes, nanoparticles, oxygenation, and hemoglobin concentration. In this review we present origin of contrast and high spatial resolution in these measurements performed with optoacoustic systems developed and built by our group. We summarize data obtained in vitro , in experimental animals, and in humans on monitoring of these physiologic variables. Our data indicate that the optoacoustic technology may be used for monitoring of cerebral blood oxygenation in patients with traumatic brain injury and in neonatal patients, central venous oxygenation monitoring, total hemoglobin concentration monitoring, hematoma detection and characterization, monitoring of temperature, and coagulation and freezing boundaries during thermotherapy.

  14. Spatial variability of soil carbon, pH, available phosphorous and potassium in organic farm located in Mediterranean Croatia

    NASA Astrophysics Data System (ADS)

    Bogunović, Igor; Pereira, Paulo; Šeput, Miranda

    2016-04-01

    Soil organic carbon (SOC), pH, available phosphorus (P), and potassium (K) are some of the most important factors to soil fertility. These soil parameters are highly variable in space and time, with implications to crop production. The aim of this work is study the spatial variability of SOC, pH, P and K in an organic farm located in river Rasa valley (Croatia). A regular grid (100 x 100 m) was designed and 182 samples were collected on Silty Clay Loam soil. P, K and SOC showed moderate heterogeneity with coefficient of variation (CV) of 21.6%, 32.8% and 51.9%, respectively. Soil pH record low spatial variability with CV of 1.5%. Soil pH, P and SOC did not follow normal distribution. Only after a Box-Cox transformation, data respected the normality requirements. Directional exponential models were the best fitted and used to describe spatial autocorrelation. Soil pH, P and SOC showed strong spatial dependence with nugget to sill ratio with 13.78%, 0.00% and 20.29%, respectively. Only K recorded moderate spatial dependence. Semivariogram ranges indicate that future sampling interval could be 150 - 200 m in order to reduce sampling costs. Fourteen different interpolation models for mapping soil properties were tested. The method with lowest Root Mean Square Error was the most appropriated to map the variable. The results showed that radial basis function models (Spline with Tension and Completely Regularized Spline) for P and K were the best predictors, while Thin Plate Spline and inverse distance weighting models were the least accurate. The best interpolator for pH and SOC was the local polynomial with the power of 1, while the least accurate were Thin Plate Spline. According to soil nutrient maps investigated area record very rich supply with K while P supply was insufficient on largest part of area. Soil pH maps showed mostly neutral reaction while individual parts of alkaline soil indicate the possibility of penetration of seawater and salt accumulation in the

  15. Variability of hazardous air pollutants in an urban area

    NASA Astrophysics Data System (ADS)

    Spicer, Chester W.; Buxton, Bruce E.; Holdren, Michael W.; Smith, Deborah L.; Kelly, Thomas J.; Rust, Steven W.; Pate, Alan D.; Sverdrup, George M.; Chuang, Jane C.

    The variability of hazardous air pollutants (HAPs) is an important factor in determining human exposure to such chemicals, and in designing HAP measurement programs. This study has investigated the factors which contribute to HAP variability in an urban area. Six measurement sites separated by up to 12 km collected data with 3 h time resolution to examine spatial variability within neighborhoods and between neighborhoods. The measurements were made in Columbus, OH. The 3 h results also were used to study temporal variability, and duplicate samples collected at each site were used to determine the component of variability attributable to the measurement process. Hourly samples collected over 10 days at one site provided further insight into the temporal resolution needed to capture short-term peak concentrations. Measurements at the 6 spatial sites focused on 78 chemicals. Twenty-three of these species were found in at least 95% of the 3 h samples, and 39 chemicals were present at least 60% of the time. The relative standard deviations for most of these 39 frequently detected chemicals was 1.0 or lower. Variability was segmented into temporal, spatial, and measurement components. Temporal variation was the major contributor to HAP variability for 19 of the 39 frequently detected compounds, based on the 3 h data. Measurement imprecision contributed less than 25% for most of the volatile organic species, but 30% or more of the variability for carbonyl compounds, trace elements, and particle-bound extractable organic mass. Interestingly, the spatial component contributed less than 20% of the total variability for all the chemicals except sulfur. Based on the data with hourly resolution, peak to median ratios (hourly peak to 24 h median) averaged between 2 and 4 for most of the volatile organic compounds, but there were two species with peak to median ratios of about 10.

  16. Do bioclimate variables improve performance of climate envelope models?

    USGS Publications Warehouse

    Watling, James I.; Romañach, Stephanie S.; Bucklin, David N.; Speroterra, Carolina; Brandt, Laura A.; Pearlstine, Leonard G.; Mazzotti, Frank J.

    2012-01-01

    Climate envelope models are widely used to forecast potential effects of climate change on species distributions. A key issue in climate envelope modeling is the selection of predictor variables that most directly influence species. To determine whether model performance and spatial predictions were related to the selection of predictor variables, we compared models using bioclimate variables with models constructed from monthly climate data for twelve terrestrial vertebrate species in the southeastern USA using two different algorithms (random forests or generalized linear models), and two model selection techniques (using uncorrelated predictors or a subset of user-defined biologically relevant predictor variables). There were no differences in performance between models created with bioclimate or monthly variables, but one metric of model performance was significantly greater using the random forest algorithm compared with generalized linear models. Spatial predictions between maps using bioclimate and monthly variables were very consistent using the random forest algorithm with uncorrelated predictors, whereas we observed greater variability in predictions using generalized linear models.

  17. Methane emission from Minnesota peatlands: Spatial and seasonal variability

    NASA Astrophysics Data System (ADS)

    Dise, Nancy. B.

    1993-03-01

    The variability of methane flux with season, year, and habitat type was investigated in northern Minnesota peatlands from September 1988 through September 1990. Average daily fluxes calculated by integration of annual data for an open poor fen, an open bog, a forested bog hollow, a fen lagg in the forested bog and a forested bog hummock were 180,118, 38, 35, and 10 mg CH4 m-2 d-1, respectively. Fluxes among the five ecosystems were significantly different from one another, although emission from all sites was highest in July and lowest in March. Winter fluxes occurred in all sites but the fen lagg. There was no difference in fluxes measured from the same sites in the spring of 1986, 1989, or 1990, but summer fluxes were significantly higher in the wetter year of 1989 than in 1990, and a summer pulse in methane emission occurred in 1989 that was not seen the next year. Concentrations of methane in pore water, reflecting the seasonal balance of production, oxidation, and release, declined during the month of peak flux, then increased to levels of about 500 μM in December. Consistent spatial and temporal differences in flux could be ascribed to differences in water table, temperature, and peat nutrient status, although additional variability remained. Integration gave an annual average flux of 20 g CH4, m-2 ot; for the three bog ecosystems and 39 g CH4, m-2 for the two fen ecosystems. This gives an estimate of 1-2 Tg CH4, yr-1 from peatlands in the Great Lake states of Minnesota, Wisconsin, and Michigan.

  18. Spatial variability and response to anthropogenic pressures of assemblages dominated by a habitat forming seaweed sensitive to pollution (northern coast of Alboran Sea).

    PubMed

    Bermejo, Ricardo; de la Fuente, Gina; Ramírez-Romero, Eduardo; Vergara, Juan J; Hernández, Ignacio

    2016-04-15

    The Cystoseira ericaefolia group is conformed by three species: C. tamariscifolia, C. mediterranea and C. amentacea. These species are among the most important habitat forming species of the upper sublittoral rocky shores of the Mediterranean Sea and adjacent Atlantic coast. This species group is sensitive to human pressures and therefore is currently suffering important losses. This study aimed to assess the influence of anthropogenic pressures, oceanographic conditions and local spatial variability in assemblages dominated by C. ericaefolia in the Alboran Sea. The results showed the absence of significant effects of anthropogenic pressures or its interactions with environmental conditions in the Cystoseira assemblages. This fact was attributed to the high spatial variability, which is most probably masking the impact of anthropogenic pressures. The results also showed that most of the variability occurred on at local levels. A relevant spatial variability was observed at regional level, suggesting a key role of oceanographic features in these assemblages. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Spatial and temporal variability of thermohaline properties in the Bay of Koper (northern Adriatic Sea)

    NASA Astrophysics Data System (ADS)

    Soczka Mandac, Rok; Žagar, Dušan; Faganeli, Jadran

    2013-04-01

    In this study influence of fresh water discharge on the spatial and temporal variability of thermohaline (TH) conditions is explored for the Bay of Koper (Bay). The Bay is subject to different driving agents: wind stress (bora, sirocco), tidal and seiches effect, buoyancy fluxes, general circulation of the Adriatic Sea and discharge of the Rizana and Badaševica rivers. These rivers have torrential characteristics that are hard to forecast in relation to meteorological events (precipitation). Therefore, during episodic events the spatial and temporal variability of TH properties in the Bay is difficult to determine [1]. Measurements of temperature, salinity and turbidity were conducted monthly on 35 sampling points in the period: June 2011 - December 2012. The data were processed and spatial interpolated with an objective analysis method. Furthermore, empirical orthogonal function analysis (EOF) [2] was applied to investigate spatial and temporal TH variations. Strong horizontal and vertical stratification was observed in the beginning of June 2011 due to high fresh water discharge of the Rizana (31 m3/s) and Badaševica (2 m3/s) rivers. The horizontal gradient (ΔT = 6°C) was noticed near the mouth of the Rizana river. Similar pattern was identified for salinity field on the boundary of the front where the gradient was ΔS = 20 PSU. Vertical temperature gradient was ΔT = 4°C while salinity gradient was ΔS = 18 PSU in the subsurface layer at depth of 3 m. Spatial analysis of the first principal component (86% of the total variance) shows uniform temperature distribution in the surface layer (1m) during the studied period. Furthermore, temporal variability of temperature shows seasonal variation with a minimum in February and maximum in August. This confirms that episodic events have a negligible effect on spatial and temporal variation of temperature in the subsurface layer. Further analysis will include application of EOF on the salinity, density and total

  20. Analysis of biophysical and anthropogenic variables and their relation to the regional spatial variation of aboveground biomass illustrated for North and East Kalimantan, Borneo.

    PubMed

    Van der Laan, Carina; Verweij, Pita A; Quiñones, Marcela J; Faaij, André Pc

    2014-12-01

    Land use and land cover change occurring in tropical forest landscapes contributes substantially to carbon emissions. Better insights into the spatial variation of aboveground biomass is therefore needed. By means of multiple statistical tests, including geographically weighted regression, we analysed the effects of eight variables on the regional spatial variation of aboveground biomass. North and East Kalimantan were selected as the case study region; the third largest carbon emitting Indonesian provinces. Strong positive relationships were found between aboveground biomass and the tested variables; altitude, slope, land allocation zoning, soil type, and distance to the nearest fire, road, river and city. Furthermore, the results suggest that the regional spatial variation of aboveground biomass can be largely attributed to altitude, distance to nearest fire and land allocation zoning. Our study showed that in this landscape, aboveground biomass could not be explained by one single variable; the variables were interrelated, with altitude as the dominant variable. Spatial analyses should therefore integrate a variety of biophysical and anthropogenic variables to provide a better understanding of spatial variation in aboveground biomass. Efforts to minimise carbon emissions should incorporate the identified factors, by 1) the maintenance of lands with high AGB or carbon stocks, namely in the identified zones at the higher altitudes; and 2) regeneration or sustainable utilisation of lands with low AGB or carbon stocks, dependent on the regeneration capacity of the vegetation. Low aboveground biomass densities can be found in the lowlands in burned areas, and in non-forest zones and production forests.

  1. Submesoscale Sea Surface Temperature Variability from UAV and Satellite Measurements

    NASA Astrophysics Data System (ADS)

    Castro, S. L.; Emery, W. J.; Tandy, W., Jr.; Good, W. S.

    2017-12-01

    Technological advances in spatial resolution of observations have revealed the importance of short-lived ocean processes with scales of O(1km). These submesoscale processes play an important role for the transfer of energy from the meso- to small scales and for generating significant spatial and temporal intermittency in the upper ocean, critical for the mixing of the oceanic boundary layer. Submesoscales have been observed in sea surface temperatures (SST) from satellites. Satellite SST measurements are spatial averages over the footprint of the satellite. When the variance of the SST distribution within the footprint is small, the average value is representative of the SST over the whole pixel. If the variance is large, the spatial heterogeneity is a source of uncertainty in satellite derived SSTs. Here we show evidence that the submesoscale variability in SSTs at spatial scales of 1km is responsible for the spatial variability within satellite footprints. Previous studies of the spatial variability in SST, using ship-based radiometric data suggested that variability at scales smaller than 1 km is significant and affects the uncertainty of satellite-derived skin SSTs. We examine data collected by a calibrated thermal infrared radiometer, the Ball Experimental Sea Surface Temperature (BESST), flown on a UAV over the Arctic Ocean and compare them with coincident measurements from the MODIS spaceborne radiometer to assess the spatial variability of SST within 1 km pixels. By taking the standard deviation of all the BESST measurements within individual MODIS pixels we show that significant spatial variability exists within the footprints. The distribution of the surface variability measured by BESST shows a peak value of O(0.1K) with 95% of the pixels showing σ < 0.45K. More importantly, high-variability pixels are located at density fronts in the marginal ice zone, which are a primary source of submesoscale intermittency near the surface in the Arctic Ocean

  2. Space Technology 5 Multipoint Observations of Temporal and Spatial Variability of Field-Aligned Currents

    NASA Technical Reports Server (NTRS)

    Le, G.; Wang, Y.; Slavin, J. A.; Strangeway, R. L.

    2009-01-01

    Space Technology 5 (ST5) is a constellation mission consisting of three microsatellites. It provides the first multipoint magnetic field measurements in low Earth orbit, which enables us to separate spatial and temporal variations. In this paper, we present a study of the temporal variability of field-aligned currents using the ST5 data. We examine the field-aligned current observations during and after a geomagnetic storm and compare the magnetic field profiles at the three spacecraft. The multipoint data demonstrate that mesoscale current structures, commonly embedded within large-scale current sheets, are very dynamic with highly variable current density and/or polarity in approx.10 min time scales. On the other hand, the data also show that the time scales for the currents to be relatively stable are approx.1 min for mesoscale currents and approx.10 min for large-scale currents. These temporal features are very likely associated with dynamic variations of their charge carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of mesoscale field-aligned currents are found to be consistent with those of auroral parallel electric field.

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  4. Estimation of the temperature spatial variability in confined spaces based on thermal imaging

    NASA Astrophysics Data System (ADS)

    Augustyn, Grzegorz; Jurasz, Jakub; Jurczyk, Krzysztof; Korbiel, Tomasz; Mikulik, Jerzy; Pawlik, Marcin; Rumin, Rafał

    2017-11-01

    In developed countries the salaries of office workers are several times higher than the total cost of maintaining and operating the building. Therefore even a small improvement in human work productivity and performance as a result of enhancing the quality of their work environment may lead to a meaningful economic benefits. The air temperature is the most commonly used indicator in assessing the indoor environment quality. What is more, it is well known that thermal comfort has the biggest impact on employees performance and their ability to work efficiently. In majority of office buildings, indoor temperature is managed by heating, ventilation and air conditioning (HVAC) appliances. However the way how they are currently managed and controlled leads to the nonhomogeneous distribution of temperature in certain space. An approach to determining the spatial variability of temperature in confined spaces was introduced based on thermal imaging temperature measurements. The conducted research and obtained results enabled positive verification of the method and creation of surface plot illustrating the temperature variability.

  5. Fine-Scale Spatial Variability of Precipitation, Soil, and Plant Water Isotopes

    NASA Astrophysics Data System (ADS)

    Goldsmith, G. R.; Braun, S.; Romero, C.; Engbersen, N.; Gessler, A.; Siegwolf, R. T.; Schmid, L.

    2015-12-01

    Introduction: The measurement of stable isotope ratios of water has become fundamental in advancing our understanding of environmental patterns and processes, particularly with respect to understanding the movement of water within the soil-plant-atmosphere continuum. While considerable research has explored the temporal variation in stable isotope ratios of water in the environment, our understanding of the spatial variability of these isotopes remains poorly understood. Methods: We collected spatially explicit samples of throughfall and soil water (n=150 locations) from a 1 ha plot delineated in a mixed deciduous forest in the northern Alps of Switzerland. We complemented this with fully sunlit branch and leaf samples (n = 60 individuals) collected from Picea abies and Fagus sylvatica between 14:00 and 16:00 on the same day by means of a helicopter. Soil and plant waters were extracted using cryogenic vacuum distillation and all samples were analyzed for δ18O using an isotope ratio mass spectrometer. Results: The mean δ18O of throughfall (-3.3 ± 0.8‰) indicated some evaporative enrichment associated with passage through the canopy, but this did not significantly differ from the precipitation collected in nearby open sites (-4.05‰). However, soil was depleted (-7.0 ± 1.8‰) compared to throughfall and there was no significant relationship between the two, suggesting that the sampling for precipitation inputs did not capture all the sources (e.g. stream water, which was -11.5‰) contributing to soil water δ18O ratios. Evaporative enrichment of δ18O was higher in leaves of Fagus (14.8 ± 1.8‰) than in leaves of Picea (11.8 ± 1.7‰). Sampling within crowns of each species (n = 5 branches each from 5 individuals) indicated that variability in a single individual is similar to that among individuals. Discussion: Stable isotopes of water are frequently engaged for studies of ecohydrology, plant ecophysiology, and paleoclimatology. Our results help

  6. Temporal and spatial variability of soil biological activity at European scale

    NASA Astrophysics Data System (ADS)

    Mallast, Janine; Rühlmann, Jörg

    2015-04-01

    The CATCH-C project aims to identify and improve the farm-compatibility of Soil Management Practices including to promote productivity, climate change mitigation and soil quality. The focus of this work concentrates on turnover conditions for soil organic matter (SOM). SOM is fundamental for the maintenance of quality and functions of soils while SOM storage is attributed a great importance in terms of climate change mitigation. The turnover conditions depend on soil biological activity characterized by climate and soil properties. Soil biological activity was investigated using two model concepts: a) Re_clim parameter within the ICBM (Introductory Carbon Balance Model) (Andrén & Kätterer 1997) states a climatic factor summarizing soil water storage and soil temperature and its influence on soil biological activity. b) BAT (biological active time) approach derived from model CANDY (CArbon and Nitrogen Dynamic) (Franko & Oelschlägel 1995) expresses the variation of soil moisture, soil temperature and soil aeration as a time scale and an indicator of biological activity for soil organic matter (SOM) turnover. During an earlier stage both model concepts, Re_clim and BAT, were applied based on a monthly data to assess spatial variability of turnover conditions across Europe. This hampers the investigation of temporal variability (e.g. intra-annual). The improved stage integrates daily data of more than 350 weather stations across Europe presented by Klein Tank et al. (2002). All time series data (temperature, precipitation and potential evapotranspiration and soil texture derived from the European Soil Database (JRC 2006)), are used to calculate soil biological activity in the arable layer. The resulting BAT and Re_clim values were spatio-temporal investigated. While "temporal" refers to a long-term trend analysis, "spatial" includes the investigation of soil biological activity variability per environmental zone (ENZ, Metzger et al. 2005 representing similar

  7. Spatial variability assessment of soil nutrients in an intense agricultural area, a case study of Rugao County in Yangtze River Delta Region, China

    NASA Astrophysics Data System (ADS)

    Zhao, Yongcun; Xu, Xianghua; Darilek, Jeremy Landon; Huang, Biao; Sun, Weixia; Shi, Xuezheng

    2009-05-01

    Topsoil samples (0-20 cm) ( n = 237) were collected from Rugao County, China. Geostatistical variogram analysis, sequential Gaussian simulation (SGS), and principal component (PC) analysis were applied to assess spatial variability of soil nutrients, identify the possible areas of nutrient deficiency, and explore spatial scale of variability of soil nutrients in the county. High variability of soil nutrient such as soil organic matter (SOM), total nitrogen (TN), available P, K, Fe, Mn, Cu, Zn, and B concentrations were observed. Soil nutrient properties displayed significant differences in their spatial structures, with available Cu having strong spatial dependence, SOM and available P having weak spatial dependence, and other nutrient properties having moderate spatial dependence. The soil nutrient deficiency, defined here as measured nutrient concentrations which do not meet the advisory threshold values specific to the county for dominant crops, namely rice, wheat, and rape seeds, was observed in available K and Zn, and the deficient areas covered 38 and 11%, respectively. The first three PCs of the nine soil nutrient properties explained 62.40% of the total variance. TN and SOM with higher loadings on PC1 are closely related to soil texture derived from different parent materials. The PC2 combined intermediate response variables such as available Zn and P that are likely to be controlled by land use and soil pH. Available B has the highest loading on PC3 and its variability of concentrations may be primarily ascribed to localized anthropogenic influence. The amelioration of soil physical properties (i.e. soil texture) and soil pH may improve the availability of soil nutrients and the sustainability of the agricultural system of Rugao County.

  8. 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.

  9. Effect of site level environmental variables, spatial autocorrelation and sampling intensity on arthropod communities in an ancient temperate lowland woodland area.

    PubMed

    Horak, Jakub

    2013-01-01

    The interaction of arthropods with the environment and the management of their populations is a focus of the ecological agenda. Spatial autocorrelation and under-sampling may generate bias and, when they are ignored, it is hard to determine if results can in any way be trusted. Arthropod communities were studied during two seasons and using two methods: window and panel traps, in an area of ancient temperate lowland woodland of Zebracka (Czech Republic). The composition of arthropod communities was studied focusing on four site level variables (canopy openness, diameter in the breast height and height of tree, and water distance) and finally analysed using two approaches: with and without effects of spatial autocorrelation. I found that the proportion of variance explained by space cannot be ignored (≈20% in both years). Potential bias in analyses of the response of arthropods to site level variables without including spatial co-variables is well illustrated by redundancy analyses. Inclusion of space led to more accurate results, as water distance and tree diameter were significant, showing approximately the same ratio of explained variance and direction in both seasons. Results without spatial co-variables were much more disordered and were difficult to explain. This study showed that neglecting the effects of spatial autocorrelation could lead to wrong conclusions in site level studies and, furthermore, that inclusion of space may lead to more accurate and unambiguous outcomes. Rarefactions showed that lower sampling intensity, when appropriately designed, can produce sufficient results without exploitation of the environment.

  10. 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.

  11. Thaw depth spatial and temporal variability at the Limnopolar Lake CALM-S site, Byers Peninsula, Livingston Island, Antarctica.

    PubMed

    de Pablo, M A; Ramos, M; Molina, A; Prieto, M

    2018-02-15

    A new Circumpolar Active Layer Monitoring (CALM) site was established in 2009 at the Limnopolar Lake watershed in Byers Peninsula, Livingston Island, Antarctica, to provide a node in the western Antarctic Peninsula, one of the regions that recorded the highest air temperature increase in the planet during the last decades. The first detailed analysis of the temporal and spatial evolution of the thaw depth at the Limnopolar Lake CALM-S site is presented here, after eight years of monitoring. The average values range between 48 and 29cm, decreasing at a ratio of 16cm/decade. The annual thaw depth observations in the 100×100 m CALM grid are variable (Variability Index of 34 to 51%), although both the Variance Coefficient and the Climate Matrix Analysis Residual point to the internal consistency of the data. Those differences could be explained then by the terrain complexity and node-specific variability due to the ground properties. The interannual variability was about 60% during 2009-2012, increasing to 124% due to the presence of snow in 2013, 2015 and 2016. The snow has been proposed here as one of the most important factors controlling the spatial variability of ground thaw depth, since its values correlate with the snow thickness but also with the ground surface temperature and unconfined compression resistance, as measured in 2010. The topography explains the thaw depth spatial distribution pattern, being related to snowmelt water and its accumulation in low-elevation areas (downslope-flow). Patterned grounds and other surface features correlate well with high thaw depth patterns as well. The edaphic factor (E=0.05842m 2 /°C·day; R 2 =0.63) is in agreement with other permafrost environments, since frozen index (F>0.67) and MAAT (<-2°C) denote a continuous permafrost existence in the area. All these characteristics provided the basis for further comparative analyses between others nearby CALM sites. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. An Investigation on the Spatial Variability of Manning Roughness Coefficients in Continental-scale River Routing Simulations

    NASA Astrophysics Data System (ADS)

    Luo, X.; Hong, Y.; Lei, X.; Leung, L. R.; Li, H. Y.; Getirana, A.

    2017-12-01

    As one essential component of the Earth system modeling, the continental-scale river routing computation plays an important role in applications of Earth system models, such as evaluating the impacts of the global change on water resources and flood hazards. The streamflow timing, which depends on the modeled flow velocities, can be an important aspect of the model results. River flow velocities have been estimated by using the Manning's equation where the Manning roughness coefficient is a key and sensitive parameter. In some early continental-scale studies, the Manning coefficient was determined with simplified methods, such as using a constant value for the entire basin. However, large spatial variability is expected in the Manning coefficients for the numerous channels composing the river network in distributed continental-scale hydrologic modeling. In the application of a continental-scale river routing model in the Amazon Basin, we use spatially varying Manning coefficients dependent on channel sizes and attempt to represent the dominant spatial variability of Manning coefficients. Based on the comparisons of simulation results with in situ streamflow records and remotely sensed river stages, we investigate the comparatively optimal Manning coefficients and explicitly demonstrate the advantages of using spatially varying Manning coefficients. The understanding obtained in this study could be helpful in the modeling of surface hydrology at regional to continental scales.

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

    NASA Astrophysics Data System (ADS)

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

    2018-01-01

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

  14. Predictor variable resolution governs modeled soil types

    USDA-ARS?s Scientific Manuscript database

    Soil mapping identifies different soil types by compressing a unique suite of spatial patterns and processes across multiple spatial scales. It can be quite difficult to quantify spatial patterns of soil properties with remotely sensed predictor variables. More specifically, matching the right scale...

  15. Spatial variability in land-atmosphere coupling strength at the ARM Southern Great Plains site under different cloud regimes

    NASA Astrophysics Data System (ADS)

    Tang, Q.; Xie, S.; Zhang, Y.

    2016-12-01

    The paucity of land/soil observations is a long-standing limitation for land-atmosphere (LA) coupling studies, in particular for estimating the spatial variability in the coupling strengths. Spatially dense atmospheric radiation measurement (ARM) sites deployed at the U.S. Southern Great Plains (SGP) covers a wide range of vegetation, surface, and soil types, and thus allow us to observe the spatial patterns of LA coupling. The upcoming "super site" at SGP will facilitate these studies at even finer scales. While many previous studies have focused only on the observations from the central facility (CF) site or the domain mean from multiple sites, in the present work we examine the robustness of many key surface and land observations (e.g., radiation, turbulence fluxes, soil moisture, etc.) at extended sites besides the CF site for a decade. The coupling strengths are estimated with temporal covariations between important variables. We subsample the data to different categories based on different cloud regimes (e.g., clear sky, shallow cumulus, and deep cumulus. These cloud regimes are strongly impacted by local factors. The spatial variability of coupling strengths at different ARM sites is assessed with respect to dominant drivers (i.e., vegetation, land type, etc.). The results of this study will provide insights for improving the representation of LA coupling in climate models by providing observational constraints to parameterizations, e.g., shallow convective schemes. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-698523

  16. 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

  17. Relating brain signal variability to knowledge representation.

    PubMed

    Heisz, Jennifer J; Shedden, Judith M; McIntosh, Anthony R

    2012-11-15

    We assessed the hypothesis that brain signal variability is a reflection of functional network reconfiguration during memory processing. In the present experiments, we use multiscale entropy to capture the variability of human electroencephalogram (EEG) while manipulating the knowledge representation associated with faces stored in memory. Across two experiments, we observed increased variability as a function of greater knowledge representation. In Experiment 1, individuals with greater familiarity for a group of famous faces displayed more brain signal variability. In Experiment 2, brain signal variability increased with learning after multiple experimental exposures to previously unfamiliar faces. The results demonstrate that variability increases with face familiarity; cognitive processes during the perception of familiar stimuli may engage a broader network of regions, which manifests as higher complexity/variability in spatial and temporal domains. In addition, effects of repetition suppression on brain signal variability were observed, and the pattern of results is consistent with a selectivity model of neural adaptation. Crown Copyright © 2012. Published by Elsevier Inc. All rights reserved.

  18. Untangling the contribution of aspect, drainage position and elevation to the spatial variability of fine surface fuels in south east Australian forests

    NASA Astrophysics Data System (ADS)

    Sheridan, Gary; nyman, petter; Duff, Tom; Baillie, Craig; Bovill, William; Lane, Patrick; Tolhurst, Kevin

    2015-04-01

    The prediction of fuel moisture content is important for estimating the rate of spread of wildfires, the ignition probability of firebrands, and for the efficient scheduling of prescribed fire. The moisture content of fine surface fuels varies spatially at large scales (10's to 100's km) due to variation in meteorological variables (eg. temperature, relative humidity, precipitation). At smaller scales (100's of metres) in steep topography spatial variability is attributed to topographic influences that include differences in radiation due to aspect and slope, differences in precipitation, temperature and relative humidity due to elevation, and differences in soil moisture due to hillslope drainage position. Variable forest structure and canopy shading adds further to the spatial variability in surface fuel moisture. In this study we aim to combine daily 5km resolution gridded weather data with 20m resolution DEM and vegetation structure data to predict the spatial variability of fine surface fuels in steep topography. Microclimate stations were established in south east Australia to monitor surface fine fuel moisture continuously (every 15 minutes) using newly developed instrumented litter packs, in addition to temperature and relative humidity measurements inside the litter pack, and measurement of precipitation and energy inputs above and below the forest canopy. Microclimate stations were established across a gradient of aspect (5 stations), drainage position (7 stations), elevation (15 stations), and canopy cover conditions (6 stations). The data from this extensive network of microclimate stations across a broad spectrum of topographic conditions is being analysed to enable the downscaling of gridded weather data to spatial scales that are relevant to the connectivity of wildfire fuels and to the scheduling and outcome of prescribed fires. The initial results from the first year of this study are presented here.

  19. Spatial contexts for temporal variability in alpine vegetation under ongoing climate change

    USGS Publications Warehouse

    Fagre, Daniel B.; ,; George P. Malanson,

    2013-01-01

    A framework to monitor mountain summit vegetation (The Global Observation Research Initiative in Alpine Environments, GLORIA) was initiated in 1997. GLORIA results should be taken within a regional context of the spatial variability of alpine tundra. Changes observed at GLORIA sites in Glacier National Park, Montana, USA are quantified within the context of the range of variability observed in alpine tundra across much of western North America. Dissimilarity is calculated and used in nonmetric multidimensional scaling for repeated measures of vascular species cover at 14 GLORIA sites with 525 nearby sites and with 436 sites in western North America. The lengths of the trajectories of the GLORIA sites in ordination space are compared to the dimensions of the space created by the larger datasets. The absolute amount of change on the GLORIA summits over 5 years is high, but the degree of change is small relative to the geographical context. The GLORIA sites are on the margin of the ordination volumes with the large datasets. The GLORIA summit vegetation appears to be specialized, arguing for the intrinsic value of early observed change in limited niche space.

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

    PubMed Central

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

    2013-01-01

    Multifractal techniques were utilized to quantify the spatial variability of selected soil trace elements and their scaling relationships in a 10.24-ha agricultural field in northeast China. 1024 soil samples were collected from the field and available Fe, Mn, Cu and Zn were measured in each sample. Descriptive results showed that Mn deficiencies were widespread throughout the field while Fe and Zn deficiencies tended to occur in patches. By estimating single multifractal spectra, we found that available Fe, Cu and Zn in the study soils exhibited high spatial variability and the existence of anomalies ([α(q)max−α(q)min]≥0.54), whereas available Mn had a relatively uniform distribution ([α(q)max−α(q)min]≈0.10). The joint multifractal spectra revealed that the strong positive relationships (r≥0.86, P<0.001) among available Fe, Cu and Zn were all valid across a wider range of scales and over the full range of data values, whereas available Mn was weakly related to available Fe and Zn (r≥0.18, P<0.01) but not related to available Cu (r = −0.03, P = 0.40). These results show that the variability and singularities of selected soil trace elements as well as their scaling relationships can be characterized by single and joint multifractal parameters. The findings presented in this study could be extended to predict selected soil trace elements at larger regional scales with the aid of geographic information systems. PMID:23874944

  1. Land surface hydrology parameterization for atmospheric general circulation models including subgrid scale spatial variability

    NASA Technical Reports Server (NTRS)

    Entekhabi, D.; Eagleson, P. S.

    1989-01-01

    Parameterizations are developed for the representation of subgrid hydrologic processes in atmospheric general circulation models. Reasonable a priori probability density functions of the spatial variability of soil moisture and of precipitation are introduced. These are used in conjunction with the deterministic equations describing basic soil moisture physics to derive expressions for the hydrologic processes that include subgrid scale variation in parameters. The major model sensitivities to soil type and to climatic forcing are explored.

  2. Examining impulse-variability in overarm throwing.

    PubMed

    Urbin, M A; Stodden, David; Boros, Rhonda; Shannon, David

    2012-01-01

    The purpose of this study was to examine variability in overarm throwing velocity and spatial output error at various percentages of maximum to test the prediction of an inverted-U function as predicted by impulse-variability theory and a speed-accuracy trade-off as predicted by Fitts' Law Thirty subjects (16 skilled, 14 unskilled) were instructed to throw a tennis ball at seven percentages of their maximum velocity (40-100%) in random order (9 trials per condition) at a target 30 feet away. Throwing velocity was measured with a radar gun and interpreted as an index of overall systemic power output. Within-subject throwing velocity variability was examined using within-subjects repeated-measures ANOVAs (7 repeated conditions) with built-in polynomial contrasts. Spatial error was analyzed using mixed model regression. Results indicated a quadratic fit with variability in throwing velocity increasing from 40% up to 60%, where it peaked, and then decreasing at each subsequent interval to maximum (p < .001, η2 = .555). There was no linear relationship between speed and accuracy. Overall, these data support the notion of an inverted-U function in overarm throwing velocity variability as both skilled and unskilled subjects approach maximum effort. However, these data do not support the notion of a speed-accuracy trade-off. The consistent demonstration of an inverted-U function associated with systemic power output variability indicates an enhanced capability to regulate aspects of force production and relative timing between segments as individuals approach maximum effort, even in a complex ballistic skill.

  3. Characterization of soil spatial variability for site-specific management using soil electrical conductivity and other remotely sensed data

    NASA Astrophysics Data System (ADS)

    Bang, Jisu

    Field-scale characterization of soil spatial variability using remote sensing technology has potential for achieving the successful implementation of site-specific management (SSM). The objectives of this study were to: (i) examine the spatial relationships between apparent soil electrical conductivity (EC a) and soil chemical and physical properties to determine if EC a could be useful to characterize soil properties related to crop productivity in the Coastal Plain and Piedmont of North Carolina; (ii) evaluate the effects of in-situ soil moisture variation on ECa mapping as a basis for characterization of soil spatial variability and as a data layer in cluster analysis as a means of delineating sampling zones; (iii) evaluate clustering approaches using different variable sets for management zone delineation to characterize spatial variability in soil nutrient levels and crop yields. Studies were conducted in two fields in the Piedmont and three fields in the Coastal Plain of North Carolina. Spatial measurements of ECa via electromagnetic induction (EMI) were compared with soil chemical parameters (extractable P, K, and micronutrients; pH, cation exchange capacity [CEC], humic matter or soil organic matter; and physical parameters (percentage sand, silt, and clay; and plant-available water [PAW] content; bulk density; cone index; saturated hydraulic conductivity [Ksat] in one of the coastal plain fields) using correlation analysis across fields. We also collected ECa measurements in one coastal plain field on four days with significantly different naturally occurring soil moisture conditions measured in five increments to 0.75 m using profiling time-domain reflectometry probes to evaluate the temporal variability of ECa associated with changes in in-situ soil moisture content. Nonhierarchical k-means cluster analysis using sensor-based field attributes including vertical ECa, near-infrared (NIR) radiance of bare-soil from an aerial color infrared (CIR) image

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

    NASA Astrophysics Data System (ADS)

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

    2017-05-01

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

  5. Optimal estimation of spatially variable recharge and transmissivity fields under steady-state groundwater flow. Part 1. Theory

    NASA Astrophysics Data System (ADS)

    Graham, Wendy D.; Tankersley, Claude D.

    1994-05-01

    Stochastic methods are used to analyze two-dimensional steady groundwater flow subject to spatially variable recharge and transmissivity. Approximate partial differential equations are developed for the covariances and cross-covariances between the random head, transmissivity and recharge fields. Closed-form solutions of these equations are obtained using Fourier transform techniques. The resulting covariances and cross-covariances can be incorporated into a Bayesian conditioning procedure which provides optimal estimates of the recharge, transmissivity and head fields given available measurements of any or all of these random fields. Results show that head measurements contain valuable information for estimating the random recharge field. However, when recharge is treated as a spatially variable random field, the value of head measurements for estimating the transmissivity field can be reduced considerably. In a companion paper, the method is applied to a case study of the Upper Floridan Aquifer in NE Florida.

  6. Atmospheric mechanisms governing the spatial and temporal variability of phenological phases in central Europe

    NASA Astrophysics Data System (ADS)

    Scheifinger, Helfried; Menzel, Annette; Koch, Elisabeth; Peter, Christian; Ahas, Rein

    2002-11-01

    A data set of 17 phenological phases from Germany, Austria, Switzerland and Slovenia spanning the time period from 1951 to 1998 has been made available for analysis together with a gridded temperature data set (1° × 1° grid) and the North Atlantic Oscillation (NAO) index time series. The disturbances of the westerlies constitute the main atmospheric source for the temporal variability of phenological events in Europe. The trend, the standard deviation and the discontinuity of the phenological time series at the end of the 1980s can, to a great extent, be explained by the NAO. A number of factors modulate the influence of the NAO in time and space. The seasonal northward shift of the westerlies overlaps with the sequence of phenological spring phases, thereby gradually reducing its influence on the temporal variability of phenological events with progression of spring (temporal loss of influence). This temporal process is reflected by a pronounced decrease in trend and standard deviation values and common variability with the NAO with increasing year-day. The reduced influence of the NAO with increasing distance from the Atlantic coast is not only apparent in studies based on the data set of the International Phenological Gardens, but also in the data set of this study with a smaller spatial extent (large-scale loss of influence). The common variance between phenological and NAO time series displays a discontinuous drop from the European Atlantic coast towards the Alps. On a local and regional scale, mountainous terrain reduces the influence of the large-scale atmospheric flow from the Atlantic via a proposed decoupling mechanism. Valleys in mountainous terrain have the inclination to harbour temperature inversions over extended periods of time during the cold season, which isolate the valley climate from the large-scale atmospheric flow at higher altitudes. Most phenological stations reside at valley bottoms and are thus largely decoupled in their temporal

  7. Spatial variability in the structure of intertidal crab and gastropod assemblages within the Seychelles Archipelago (Indian Ocean)

    NASA Astrophysics Data System (ADS)

    Smale, Dan A.; Barnes, David K. A.; Barnes, Richard S. K.; Smith, David J.; Suggett, David J.

    2012-04-01

    Tropical nearshore ecosystems represent global hotspots of marine biodiversity and endemism but are often poorly understood and impacted by human activities. The Seychelles Archipelago (Western Indian Ocean) sustains a wealth of marine life, much of which is threatened by rapid development associated with tourism and climate change. Six marine parks exist within the Archipelago, but their biodiversity value and ecological health are poorly known, especially with regards to non-fish and coral species. Here we investigate spatial patterns of littoral biodiversity on 6 islands, 5 of which were granitic and within marine parks, including the first surveys of Curieuse and Ile Cocos. Our surveys formed a nested sampling design, to facilitate an examination of variability in species richness, faunal abundance, taxonomic distinctness and assemblage composition at multiple spatial scales, from islands (> 100 s km) to quadrats (metres). We identified (mostly to species) and enumerated two target taxa, brachyuran decapod crustaceans and gastropod molluscs, and recorded over 8300 individuals belonging to over 150 species. Crabs and gastropods exhibited different patterns of spatial variability, as crab assemblages were generally more distinct between islands, while gastropod assemblages were markedly variable at the smallest spatial scales of 'patch' and 'quadrat'. Intertidal biodiversity was greatest on Curieuse Island and least at Desroches, the latter was being the only coral atoll we surveyed and thereby differing in its geological and ecological context. We discuss likely drivers of these biodiversity patterns and highlight urgently-needed research directions. Our assessment of the status of poorly-known invertebrate assemblages across the Seychelles will complement more extensive surveys of coral and fish assemblages and, in doing so, provide a useful baseline for monitoring the effects of key stressors in the region, such as coastal development and climate change.

  8. Chlorophyll dynamic accounts for spatial and temporal variabilities in terrestrial carbon uptake and evapotranspiration

    NASA Astrophysics Data System (ADS)

    Croft, H.; Luo, X.; Chen, J. M.

    2017-12-01

    Terrestrial carbon and water fluxes are driven by a range of abiotic and biotic factors. State-of-art terrestrial biosphere models (TBMs) use numerical representations of these factors in conjunction with concise descriptions of biogeochemical processes to estimate terrestrial fluxes (i.e. gross primary productivity (GPP) and evapotranspiration(ET)). Leaf maximum carboxylation rate (Vcmax25) is a key biotic factor prescribed in TBM to determine CO2 assimilation rates and leaf stomatal conductivity for water transport, but the paucity of its measurements has long plagued the simulation of fluxes. This study uses leaf chlorophyll content (LCC) derived from remotely sensed data to account for spatial and temporal variations in Vcmax25 within a TBM framework. Results from the TBM with and without LCC were validated against measurements from 124 eddy-covariance towers (554 site-years) of FLUXNET. TBM using LCC reduced the biases of estimated GPP in 61% of the site-years and 59% for ET, with especially large improvements for biomes with strong seasonal cycles (e.g. deciduous forest, croplands and grasslands). In addition to the Vcmax25 adjustment imposed by LCC seasonal patterns, the spatial variability of LCC acts as an equally important part in reducing the errors of estimated fluxes by capturing the spatial variations of Vcmax25, especially during the summer. This study presents the first case of integrating satellite-derived LCC into a TBM at the global scale. Our results demonstrate the critical role of LCC in describing the variabilities in the terrestrial carbon uptake and ET and the necessity of including LCC in future TBMs.

  9. A geostatistical analysis of small-scale spatial variability in bacterial abundance and community structure in salt marsh creek bank sediments

    NASA Technical Reports Server (NTRS)

    Franklin, Rima B.; Blum, Linda K.; McComb, Alison C.; Mills, Aaron L.

    2002-01-01

    Small-scale variations in bacterial abundance and community structure were examined in salt marsh sediments from Virginia's eastern shore. Samples were collected at 5 cm intervals (horizontally) along a 50 cm elevation gradient, over a 215 cm horizontal transect. For each sample, bacterial abundance was determined using acridine orange direct counts and community structure was analyzed using randomly amplified polymorphic DNA fingerprinting of whole-community DNA extracts. A geostatistical analysis was used to determine the degree of spatial autocorrelation among the samples, for each variable and each direction (horizontal and vertical). The proportion of variance in bacterial abundance that could be accounted for by the spatial model was quite high (vertical: 60%, horizontal: 73%); significant autocorrelation was found among samples separated by 25 cm in the vertical direction and up to 115 cm horizontally. In contrast, most of the variability in community structure was not accounted for by simply considering the spatial separation of samples (vertical: 11%, horizontal: 22%), and must reflect variability from other parameters (e.g., variation at other spatial scales, experimental error, or environmental heterogeneity). Microbial community patch size based upon overall similarity in community structure varied between 17 cm (vertical) and 35 cm (horizontal). Overall, variability due to horizontal position (distance from the creek bank) was much smaller than that due to vertical position (elevation) for both community properties assayed. This suggests that processes more correlated with elevation (e.g., drainage and redox potential) vary at a smaller scale (therefore producing smaller patch sizes) than processes controlled by distance from the creek bank. c2002 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.

  10. ISM Dust Grains and N-band Spectral Variability in the Spatially Resolved Subarcsecond Binary UY Aur

    NASA Astrophysics Data System (ADS)

    Skemer, Andrew J.; Close, Laird M.; Hinz, Philip M.; Hoffmann, William F.; Greene, Thomas P.; Males, Jared R.; Beck, Tracy L.

    2010-03-01

    The 10 μm silicate feature is an essential diagnostic of dust-grain growth and planet formation in young circumstellar disks. The Spitzer Space Telescope has revolutionized the study of this feature, but due to its small (85 cm) aperture, it cannot spatially resolve small/medium-separation binaries (lsim3''; <~ 420 AU) at the distances of the nearest star-forming regions (~140 pc). Large, 6-10 m ground-based telescopes with mid-infrared instruments can resolve these systems. In this paper, we spatially resolve the 0farcs88 binary, UY Aur, with MMTAO/BLINC-MIRAC4 mid-infrared spectroscopy. We then compare our spectra to Spitzer/IRS (unresolved) spectroscopy, and resolved images from IRTF/MIRAC2, Keck/OSCIR, and Gemini/Michelle, which were taken over the past decade. We find that UY Aur A has extremely pristine, interstellar medium (ISM)-like grains and that UY Aur B has an unusually shaped silicate feature, which is probably the result of blended emission and absorption from foreground extinction in its disk. We also find evidence for variability in both UY Aur A and UY Aur B by comparing synthetic photometry from our spectra with resolved imaging from previous epochs. The photometric variability of UY Aur A could be an indication that the silicate emission itself is variable, as was recently found in EX Lupi. Otherwise, the thermal continuum is variable, and either the ISM-like dust has never evolved, or it is being replenished, perhaps by UY Aur's circumbinary disk. The observations reported here were partially obtained at the Infrared Telescope Facility, which is operated by the University of Hawaii under Cooperative Agreement no. NCC 5-538 with the National Aeronautics and Space Administration, Science Mission Directorate, Planetary Astronomy Program.

  11. Multi-platform validation of a high-resolution model in the Western Mediterranean Sea: insight into spatial-temporal variability

    NASA Astrophysics Data System (ADS)

    Aguiar, Eva; Mourre, Baptiste; Heslop, Emma; Juza, Mélanie; Escudier, Romain; Tintoré, Joaquín

    2017-04-01

    This study focuses on the validation of the high resolution Western Mediterranean Operational model (WMOP) developed at SOCIB, the Balearic Islands Coastal Observing and Forecasting System. The Mediterranean Sea is often seen as a small scale ocean laboratory where energetic eddies, fronts and circulation features have important ecological consequences. The Medclic project is a program between "La Caixa" Foundation and SOCIB which aims at characterizing and forecasting the "oceanic weather" in the Western Mediterranean Sea, specifically investigating the interactions between the general circulation and mesoscale processes. We use a WMOP 2009-2015 free run hindcast simulation and available observational datasets (altimetry, moorings and gliders) to both assess the numerical simulation and investigate the ocean variability. WMOP has a 2-km spatial resolution and uses CMEMS Mediterranean products as initial and boundary conditions, with surface forcing from the high-resolution Spanish Meteorological Agency model HIRLAM. Different aspects of the spatial and temporal variability in the model are validated from local to regional and basin scales: (1) the principal axis of variability of the surface circulation using altimetry and moorings along the Iberian coast, (2) the inter-annual changes of the surface flows incorporating also glider data, (3) the propagation of mesoscale eddies formed in the Algerian sub-basin using altimetry, and (4) the statistical properties of eddies (number, rotation, size) applying an eddy tracker detection method in the Western Mediterranean Sea. With these key points evaluated in the model, EOF analysis of sea surface height maps are used to investigate spatial patterns of variability associated with eddies, gyres and the basis-scale circulation and so gain insight into the interconnections between sub-basins, as well as the interactions between physical processes at different scales.

  12. Phytoplankton plasticity drives large variability in carbon fixation efficiency

    NASA Astrophysics Data System (ADS)

    Ayata, Sakina-Dorothée.; Lévy, Marina; Aumont, Olivier; Resplandy, Laure; Tagliabue, Alessandro; Sciandra, Antoine; Bernard, Olivier

    2014-12-01

    Phytoplankton C:N stoichiometry is highly flexible due to physiological plasticity, which could lead to high variations in carbon fixation efficiency (carbon consumption relative to nitrogen). However, the magnitude, as well as the spatial and temporal scales of variability, remains poorly constrained. We used a high-resolution biogeochemical model resolving various scales from small to high, spatially and temporally, in order to quantify and better understand this variability. We find that phytoplankton C:N ratio is highly variable at all spatial and temporal scales (5-12 molC/molN), from mesoscale to regional scale, and is mainly driven by nitrogen supply. Carbon fixation efficiency varies accordingly at all scales (±30%), with higher values under oligotrophic conditions and lower values under eutrophic conditions. Hence, phytoplankton plasticity may act as a buffer by attenuating carbon sequestration variability. Our results have implications for in situ estimations of C:N ratios and for future predictions under high CO2 world.

  13. Spatial variability in tree regeneration after wildfire delays and dampens future bark beetle outbreaks

    PubMed Central

    Donato, Daniel C.; Raffa, Kenneth F.; Turner, Monica G.

    2016-01-01

    Climate change is altering the frequency and severity of forest disturbances such as wildfires and bark beetle outbreaks, thereby increasing the potential for sequential disturbances to interact. Interactions can amplify or dampen disturbances, yet the direction and magnitude of future disturbance interactions are difficult to anticipate because underlying mechanisms remain poorly understood. We tested how variability in postfire forest development affects future susceptibility to bark beetle outbreaks, focusing on mountain pine beetle (Dendroctonus ponderosae) and Douglas-fir beetle (Dendroctonus pseudotsugae) in forests regenerating from the large high-severity fires that affected Yellowstone National Park in Wyoming in 1988. We combined extensive field data on postfire tree regeneration with a well-tested simulation model to assess susceptibility to bark beetle outbreaks over 130 y of stand development. Despite originating from the same fire event, among-stand variation in forest structure was very high and remained considerable for over a century. Thus, simulated emergence of stands susceptible to bark beetles was not temporally synchronized but was protracted by several decades, compared with stand development from spatially homogeneous regeneration. Furthermore, because of fire-mediated variability in forest structure, the habitat connectivity required to support broad-scale outbreaks and amplifying cross-scale feedbacks did not develop until well into the second century after the initial burn. We conclude that variability in tree regeneration after disturbance can dampen and delay future disturbance by breaking spatiotemporal synchrony on the landscape. This highlights the importance of fostering landscape variability in the context of ecosystem management given changing disturbance regimes. PMID:27821739

  14. Spatial variability in tree regeneration after wildfire delays and dampens future bark beetle outbreaks.

    PubMed

    Seidl, Rupert; Donato, Daniel C; Raffa, Kenneth F; Turner, Monica G

    2016-11-15

    Climate change is altering the frequency and severity of forest disturbances such as wildfires and bark beetle outbreaks, thereby increasing the potential for sequential disturbances to interact. Interactions can amplify or dampen disturbances, yet the direction and magnitude of future disturbance interactions are difficult to anticipate because underlying mechanisms remain poorly understood. We tested how variability in postfire forest development affects future susceptibility to bark beetle outbreaks, focusing on mountain pine beetle (Dendroctonus ponderosae) and Douglas-fir beetle (Dendroctonus pseudotsugae) in forests regenerating from the large high-severity fires that affected Yellowstone National Park in Wyoming in 1988. We combined extensive field data on postfire tree regeneration with a well-tested simulation model to assess susceptibility to bark beetle outbreaks over 130 y of stand development. Despite originating from the same fire event, among-stand variation in forest structure was very high and remained considerable for over a century. Thus, simulated emergence of stands susceptible to bark beetles was not temporally synchronized but was protracted by several decades, compared with stand development from spatially homogeneous regeneration. Furthermore, because of fire-mediated variability in forest structure, the habitat connectivity required to support broad-scale outbreaks and amplifying cross-scale feedbacks did not develop until well into the second century after the initial burn. We conclude that variability in tree regeneration after disturbance can dampen and delay future disturbance by breaking spatiotemporal synchrony on the landscape. This highlights the importance of fostering landscape variability in the context of ecosystem management given changing disturbance regimes.

  15. Spatial variability of isoproturon mineralizing activity within an agricultural field: geostatistical analysis of simple physicochemical and microbiological soil parameters.

    PubMed

    El Sebai, T; Lagacherie, B; Soulas, G; Martin-Laurent, F

    2007-02-01

    We assessed the spatial variability of isoproturon mineralization in relation to that of physicochemical and biological parameters in fifty soil samples regularly collected along a sampling grid delimited across a 0.36 ha field plot (40 x 90 m). Only faint relationships were observed between isoproturon mineralization and the soil pH, microbial C biomass, and organic nitrogen. Considerable spatial variability was observed for six of the nine parameters tested (isoproturon mineralization rates, organic nitrogen, genetic structure of the microbial communities, soil pH, microbial biomass and equivalent humidity). The map of isoproturon mineralization rates distribution was similar to that of soil pH, microbial biomass, and organic nitrogen but different from those of structure of the microbial communities and equivalent humidity. Geostatistics revealed that the spatial heterogeneity in the rate of degradation of isoproturon corresponded to that of soil pH and microbial biomass.

  16. Diffusional flux of CO2 through snow: Spatial and temporal variability among alpine-subalpine sites

    Treesearch

    Richard A. Sommerfeld; William J. Massman; Robert C. Musselman

    1996-01-01

    Three alpine and three subalpine sites were monitored for up to 4 years to acquire data on the temporal and spatial variability of CO2 flux through snowpacks. We conclude that the snow formed a passive cap which controlled the concentration of CO2 at the snow-soil interface, while the flux of CO2 into the atmosphere was controlled by CO2 production in the soil....

  17. Spatial variability of soil salinity in coastal saline soil at different scales in the Yellow River Delta, China.

    PubMed

    Wang, Zhuoran; Zhao, Gengxing; Gao, Mingxiu; Chang, Chunyan

    2017-02-01

    The objectives of this study were to explore the spatial variability of soil salinity in coastal saline soil at macro, meso and micro scales in the Yellow River delta, China. Soil electrical conductivities (ECs) were measured at 0-15, 15-30, 30-45 and 45-60 cm soil depths at 49 sampling sites during November 9 to 11, 2013. Soil salinity was converted from soil ECs based on laboratory analyses. Our results indicated that at the macro scale, soil salinity was high with strong variability in each soil layer, and the content increased and the variability weakened with increasing soil depth. From east to west in the region, the farther away from the sea, the lower the soil salinity was. The degrees of soil salinization in three deeper soil layers are 1.14, 1.24 and 1.40 times higher than that in the surface soil. At the meso scale, the sequence of soil salinity in different topographies, soil texture and vegetation decreased, respectively, as follows: depression >flatland >hillock >batture; sandy loam >light loam >medium loam >heavy loam >clay; bare land >suaeda salsa >reed >cogongrass >cotton >paddy >winter wheat. At the micro scale, soil salinity changed with elevation in natural micro-topography and with anthropogenic activities in cultivated land. As the study area narrowed down to different scales, the spatial variability of soil salinity weakened gradually in cultivated land and salt wasteland except the bare land.

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

    The occurrence of shallow landslides is often associated with intense and prolonged rainfall events, where infiltrating water reduces soil strength and may lead to abrupt mass release. Despite general understanding of the role of rainfall water in slope stability, the prediction of rainfall-induced landslides remains a challenge due to natural heterogeneity that affect hydrologic loading patterns and the largely unobservable internal progressive failures. An often overlooked and potentially important factor is the role of rainfall variability in space and time on landslide triggering that is often obscured by coarse information (e.g., hourly radar data at spatial resolution of a few kilometers). To quantify potential effects of rainfall variability on failure dynamics, spatial patterns, landslide numbers and volumes, we employed a physically based "Catchment-scale Hydromechanical Landslide Triggering" (CHLT) model for a study area where a summer storm in 2002 triggered 51 shallow landslides. In numerical experiments based on the CHLT model, we applied the measured rainfall amount of 53 mm in different artificial spatiotemporal rainfall patterns, resulting in between 30 and 100 landslides and total released soil volumes between 3000 and 60,000 m3 for the various scenarios. Results indicate that low intensity rainfall below soil's infiltration capacity resulted in the largest mechanical perturbation. This study illustrates how small-scale rainfall variability that is often overlooked by present operational rainfall data may play a key role in shaping landslide patterns.

  19. Automated support tool for variable rate irrigation prescriptions

    USDA-ARS?s Scientific Manuscript database

    Variable rate irrigation (VRI) enables center pivot management to better meet non-uniform water and fertility needs. This is accomplished through correctly matching system water application with spatial and temporal variability within the field. A computer program was modified to accommodate GIS dat...

  20. Macroalgal communities on multi-stressed coral reefs in the Caribbean: Long-term changes, spatial variations, and relationships with environmental variables

    NASA Astrophysics Data System (ADS)

    Sangil, Carlos; Guzman, Hector M.

    2016-11-01

    Long-term changes in macroalgal cover, spatial variation between macroalgal communities, and relationships with environmental variables and benthic groups were assessed in coral reefs along the Caribbean coast of Panama. Sampling was conducted in two regions: Western and Central. Data collected between 2000 and 2012 showed a continuous increase in macroalgal abundance, although patterns differed according to region and site. There were differences in macroalgal communities between regions, as well as within regions between different wave-exposure levels. There were also differences between sites within regions exposed to the same level of wave action. Multivariate analysis found that wave exposure along with herbivore density (Echinometra viridis) and sedimentation were the variables that explained most of the variability between communities. Other variables such as Echinometra lucunter and Diadema antillarum densities, fish density, productivity, and live coral cover had significant relationships with community structure, but explained less of the variability.

  1. Spatial variability in degassing at Erebus volcano, Antarctica

    NASA Astrophysics Data System (ADS)

    Ilanko, Tehnuka; Oppenheimer, Clive; Kyle, Philip; Burgisser, Alain

    2015-04-01

    Erebus volcano on Ross Island, Antarctica, hosts an active phonolitic lava lake, along with a number of persistently degassing vents in its summit crater. Flank degassing also occurs through ice caves and towers. The longevity of the lake, and its stable convection, have been the subject of numerous studies, including Fourier transform infrared (FTIR) spectroscopy of the lava lake. Two distinct gas compositions were previously identified in the main lava lake plume (Oppenheimer et al., 2009; 2011): a persistent 'conduit' gas with a more oxidised signature, ascribed to degassing through a permeable magma conduit; and a H2O- and SO2- enriched 'lake' composition that increases and decreases cyclically due to shallow degassing of incoming magma batches. During the past decade of annual field seasons on Erebus, gas compositions have been measured through FTIR spectroscopy at multiple sites around Erebus volcano, including flank degassing through an ice cave (Warren Cave). We present measurements from four such vents, and compare their compositions to those emitted from the main lava lake. Summit degassing involves variable proportions of H2O, CO2, CO, SO2, HF, HCl, OCS. Cyclicity is evident in some summit vents, but with signatures indicative of shallower magmatic degassing than that of the lava lake. By contrast, flank degassing at Warren Cave is dominated by H2O, CO2, and CH4. The spatial variability in gas compositions within the summit crater suggests an alternative origin for 'conduit' and 'lake' degassing to previous models that assume permeability in the main conduit. Rather, the two compositions observed in main lake degassing may be a result of decoupled 'conduit' gas and pulses of magma rising through discrete fractures before combining in the lake floor or the main plume. Smaller vents around the crater thus emit isolated 'lake' or 'conduit' compositions while their combined signature is observed in the lava lake. We suggest that this separation between gas

  2. Spatial and temporal synchrony in reptile population dynamics in variable environments.

    PubMed

    Greenville, Aaron C; Wardle, Glenda M; Nguyen, Vuong; Dickman, Chris R

    2016-10-01

    Resources are seldom distributed equally across space, but many species exhibit spatially synchronous population dynamics. Such synchrony suggests the operation of large-scale external drivers, such as rainfall or wildfire, or the influence of oasis sites that provide water, shelter, or other resources. However, testing the generality of these factors is not easy, especially in variable environments. Using a long-term dataset (13-22 years) from a large (8000 km(2)) study region in arid Central Australia, we tested firstly for regional synchrony in annual rainfall and the dynamics of six reptile species across nine widely separated sites. For species that showed synchronous spatial dynamics, we then used multivariate follow a multivariate auto-regressive state-space (MARSS) models to predict that regional rainfall would be positively associated with their populations. For asynchronous species, we used MARSS models to explore four other possible population structures: (1) populations were asynchronous, (2) differed between oasis and non-oasis sites, (3) differed between burnt and unburnt sites, or (4) differed between three sub-regions with different rainfall gradients. Only one species showed evidence of spatial population synchrony and our results provide little evidence that rainfall synchronizes reptile populations. The oasis or the wildfire hypotheses were the best-fitting models for the other five species. Thus, our six study species appear generally to be structured in space into one or two populations across the study region. Our findings suggest that for arid-dwelling reptile populations, spatial and temporal dynamics are structured by abiotic events, but individual responses to covariates at smaller spatial scales are complex and poorly understood.

  3. Spatial variability in plant species composition and peatland carbon exchange

    NASA Astrophysics Data System (ADS)

    Goud, E.; Moore, T. R.; Roulet, N. T.

    2015-12-01

    Plant species shifts in response to global change will have significant impacts on ecosystem carbon (C) exchange and storage arising from changes in hydrology. Spatial variation in peatland C fluxes have largely been attributed to the spatial distribution of microhabitats that arise from variation in surface topography and water table depth, but little is known about how plant species composition impacts peatland C cycling or how these impacts will be influenced by changing environmental conditions. We quantified the effect of species composition and environmental variables on carbon dioxide (CO2) and methane (CH4) fluxes over 2 years in a temperate peatland for four plant communities situated along a water table gradient from ombrotrophic bog to beaver pond. We hypothesized that (i) spatial heterogeneity in species composition would drive predictable spatial heterogeneity in C fluxes due to variation in plant traits and ecological tolerances, and (ii) increases in peat temperature would increase C fluxes. Species had different effects on C fluxes primarily due to differences in leaf traits. Differences in ecological tolerances among communities resulted in different rates of CO2 exchange in response to changes in water table depth. There was an overall reduction in ecosystem respiration (ER), gross primary productivity (GPP) and CH4 flux in response to colder peat temperatures in the second year, and the additive effects of a deeper water table in the bog margin and pond sites further reduced flux rates in these areas. These results demonstrate that different plant species can increase or decrease the flux of C into and out of peatlands based on differences in leaf traits and ecological tolerances, and that CO2 and CH4 fluxes are sensitive to changes in soil temperature, especially when coupled with changes in moisture availability.

  4. Explaining Spatial Variability in Wellbore Impairment Risk for Pennsylvania Oil and Gas Wells, 2000-2014

    NASA Astrophysics Data System (ADS)

    Santoro, R.; Ingraffea, A. R.

    2015-12-01

    Previous modeling (ingraffea et al. PNAS, 2014) indicated roughly two-times higher cumulative risk for wellbore impairment in unconventional wells, relative to conventional wells, and large spatial variation in risk for oil and gas wells drilled in the state of Pennsylvania. Impairment risk for wells in the northeast portion of the state were found to be 8.5-times greater than that of wells drilled in the rest of the state. Here, we set out to explain this apparent regional variability through Boosted Regression Tree (BRT) analysis of geographic, developmental, and general well attributes. We find that regional variability is largely driven by the nature of the development, i.e. whether conventional or unconventional development is dominant. Oil and natural gas market prices and total well depths present as major influences in wellbore impairment, with moderate influences from well densities and geologic factors. The figure depicts influence paths for predictors of impairments for the state (top left), SW region (top right), unconventional/NE region (bottom left) and conventional/NW region (bottom right) models. Influences are scaled to reflect percent contributions in explaining variability in the model.

  5. A new heat flux model for the Antarctic Peninsula incorporating spatially variable upper crustal radiogenic heat production

    NASA Astrophysics Data System (ADS)

    Burton-Johnson, A.; Halpin, J.; Whittaker, J. M.; Graham, F. S.; Watson, S. J.

    2017-12-01

    We present recently published findings (Burton-Johnson et al., 2017) on the variability of Antarctic sub-glacial heat flux and the impact from upper crustal geology. Our new method reveals that the upper crust contributes up to 70% of the Antarctic Peninsula's subglacial heat flux, and that heat flux values are more variable at smaller spatial resolutions than geophysical methods can resolve. Results indicate a higher heat flux on the east and south of the Peninsula (mean 81 mWm-2) where silicic rocks predominate, than on the west and north (mean 67 mWm-2) where volcanic arc and quartzose sediments are dominant. Whilst the data supports the contribution of HPE-enriched granitic rocks to high heat flux values, sedimentary rocks can be of comparative importance dependent on their provenance and petrography. Models of subglacial heat flux must utilize a heterogeneous upper crust with variable radioactive heat production if they are to accurately predict basal conditions of the ice sheet. Our new methodology and dataset facilitate improved numerical model simulations of ice sheet dynamics. The most significant challenge faced remains accurate determination of crustal structure, particularly the depths of the HPE-enriched sedimentary basins and the sub-glacial geology away from exposed outcrops. Continuing research (particularly detailed geophysical interpretation) will better constrain these unknowns and the effect of upper crustal geology on the Antarctic ice sheet. Burton-Johnson, A., Halpin, J.A., Whittaker, J.M., Graham, F.S., and Watson, S.J., 2017, A new heat flux model for the Antarctic Peninsula incorporating spatially variable upper crustal radiogenic heat production: Geophysical Research Letters, v. 44, doi: 10.1002/2017GL073596.

  6. Sea-level rise impacts on the temporal and spatial variability of extreme water levels: A case study for St. Peter-Ording, Germany

    NASA Astrophysics Data System (ADS)

    Santamaria-Aguilar, S.; Arns, A.; Vafeidis, A. T.

    2017-04-01

    Both the temporal and spatial variability of storm surge water level (WL) curves are usually not taken into account in flood risk assessments as observational data are often scarce. In addition, sea-level rise (SLR) can further affect the variability of WLs. We analyze the temporal and spatial variability of the WL curve of 75 historical storm surge events that have been numerically simulated for St. Peter-Ording at the German North Sea coast, considering the effects induced by three SLR scenarios (RCP 4.5, RCP 8.5, and a RCP 8.5 high end scenario). We assess potential impacts of these scenarios on two parameters related to flooding: overflow volumes and fullness. Our results indicate that due to both the temporal and spatial variability of those events the resulting overflow volume can be two or even three times greater. We observe a steepening of the WL curve with an increase of the tidal range under the three SLR scenarios, although SLR induced effects are relatively higher for the RCP 4.5. The steepening of the WL curve with SLR produces a reduction of the fullness, but the changes in overflow volumes also depend on the magnitude of the storm surge event.

  7. Assessing spatial variability of soil properties and ions associated to salinity using the multifractal approach

    NASA Astrophysics Data System (ADS)

    Machado Siqueira, Glécio; Soares da Silva, Jucicleia; Farías França e Silva, Ênio; Lado, Marcos; Paz-González, Antonio; Vidal-Vázquez, Eva

    2017-04-01

    The lowlands coastal region of the state of Pernambuco, Northeast of Brazil, was formerly covered by humid Atlantic forest (Mata Atlântica) and then has been increasingly devoted to Sugar cane production. Because the water table is near to the soil surface salinity can occur in this area. The objective of this study was to assess the scale dependence of parameters associated to soil salinity and ions responsible for salination using multifractal analysis. The field work was conducted at an experimental field located in the Goiania municipality, Pernambuco, Brazil. This site is located 10 km east from the Atlantic coast. The field has been devoted to monoculture of sugarcane (Saccharum of?cinarum sp.) since 25 years. The climate of the region is tropical, with average annual temperature of 24°C and 1800 mm of precipitation per year. Soil was sampled every 3 m at 128 locations across a 384 m transect at a depth of 0-20 cm. The soil samples were analysed for pH, electrical conductivity (EC), Na+, K+, Ca2+, Mg2+, Cl- and SO4-2; also sodium adsorption ratio (SAR) was calculated. The spatial distributions of all the studied variables associated to soil salinity exhibited multifractal behaviour. Although all the variables studied exhibited a very strong power law scaling, different degrees of multifractality, assessed by differences in the amplitude and several selected parameters of the generalized dimension and singularity spectrum curves, have been appreciated. The multifractal approach gives a good description of the patterns of spatial variability of properties and ions describing soil salinity, and allows discriminating differences between them.

  8. Local short-term variability in solar irradiance

    NASA Astrophysics Data System (ADS)

    Lohmann, Gerald M.; Monahan, Adam H.; Heinemann, Detlev

    2016-05-01

    Characterizing spatiotemporal irradiance variability is important for the successful grid integration of increasing numbers of photovoltaic (PV) power systems. Using 1 Hz data recorded by as many as 99 pyranometers during the HD(CP)2 Observational Prototype Experiment (HOPE), we analyze field variability of clear-sky index k* (i.e., irradiance normalized to clear-sky conditions) and sub-minute k* increments (i.e., changes over specified intervals of time) for distances between tens of meters and about 10 km. By means of a simple classification scheme based on k* statistics, we identify overcast, clear, and mixed sky conditions, and demonstrate that the last of these is the most potentially problematic in terms of short-term PV power fluctuations. Under mixed conditions, the probability of relatively strong k* increments of ±0.5 is approximately twice as high compared to increment statistics computed without conditioning by sky type. Additionally, spatial autocorrelation structures of k* increment fields differ considerably between sky types. While the profiles for overcast and clear skies mostly resemble the predictions of a simple model published by , this is not the case for mixed conditions. As a proxy for the smoothing effects of distributed PV, we finally show that spatial averaging mitigates variability in k* less effectively than variability in k* increments, for a spatial sensor density of 2 km-2.

  9. Influence of throughfall spatial and temporal patterns on soil moisture variability under Downy oak and Scots pine stands in Mediterranean conditions

    NASA Astrophysics Data System (ADS)

    Llorens, Pilar; Garcia-Estringana, Pablo; Cayuela, Carles; Latron, Jérôme; Molina, Antonio; Gallart, Francesc

    2015-04-01

    Temporal and spatial variability of throughfall and stemflow patterns, due to differences in forest structure and seasonality of Mediterranean climate, may lead to significant changes in the volume of water that locally reaches the soil, with a potential effect on groundwater recharge and on hydrological response of forested hillslopes. Two forest stands in Mediterranean climatic conditions were studied to explore the role of vegetation on the temporal and spatial redistribution of rainfall. One is a Downy oak forest (Quercus pubescens) and the other is a Scots pine forest (Pinus sylvestris), both located in the Vallcebre research catchments (NE Spain, 42° 12'N, 1° 49'E). These plots are representative of Mediterranean mountain areas with spontaneous afforestation by Scots pine as a consequence of the abandonment of agricultural terraces, formerly covered by Downy oaks. The monitoring design of each plot consists of 20 automatic rain recorders to measuring throughfall, 7 stemflow rings connected to tipping-buckets and 40 automatic soil moisture probes. All data were recorded each 5 min. Bulk rainfall and meteorological conditions above both forest covers were also recorded, and canopy cover and biometric characteristics of the plots were measured. Results indicate a marked temporal stability of throughfall in both stands, and a lower persistence of spatial patterns in the leafless period than in the leafed one in the oaks stand. Moreover, in the oaks plot the ranks of gauges in the leafed and leafless periods were not significantly correlated, indicating different wet and dry hotspots in each season. The spatial distribution of throughfall varied significantly depending on rainfall volume, with small events having larger variability, whereas large events tended to homogenize the relative differences in point throughfall. Soil water content spatial variability increased with increasing soil water content, but direct dependence of soil water content variability on

  10. [Spatial variability of surface soil nutrients in the landslide area of Beichuan County, South- west China, after 5 · 12 Wenchuan Earthquake].

    PubMed

    Mai, Ji-shan; Zhao, Ting-ning; Zheng, Jiang-kun; Shi, Chang-qing

    2015-12-01

    Based on grid sampling and laboratory analysis, spatial variability of surface soil nutrients was analyzed with GS⁺ and other statistics methods on the landslide area of Fenghuang Mountain, Leigu Town, Beichuan County. The results showed that except for high variability of available phosphorus, other soil nutrients exhibited moderate variability. The ratios of nugget to sill of the soil available phosphorus and soil organic carbon were 27.9% and 28.8%, respectively, showing moderate spatial correlation, while the ratios of nugget to sill of the total nitrogen (20.0%), total phosphorus (24.3%), total potassium (11.1%), available nitrogen (11.2%), and available potassium (22.7%) suggested strong spatial correlation. The total phosphorus had the maximum range (1232.7 m), followed by available nitrogen (541.27 m), total nitrogen (468.35 m), total potassium (136.0 m), available potassium (128.7 m), available phosphorus (116.6 m), and soil organic carbon (93.5 m). Soil nutrients had no significant variation with the increase of altitude, but gradually increased from the landslide area, the transition area, to the little-impacted area. The total and available phosphorus contents of the landslide area decreased by 10.3% and 79.7% compared to that of the little-impacted area, respectively. The soil nutrient contents in the transition area accounted for 31.1%-87.2% of that of the little-impacted area, with the nant reason for the spatial variability of surface soil nutrients.

  11. The role of impulse parameters in force variability

    NASA Technical Reports Server (NTRS)

    Carlton, L. G.; Newell, K. M.

    1986-01-01

    One of the principle limitations of the human motor system is the ability to produce consistent motor responses. When asked to repeatedly make the same movement, performance outcomes are characterized by a considerable amount of variability. This occurs whether variability is expressed in terms of kinetics or kinematics. Variability in performance is of considerable importance because for tasks requiring accuracy it is a critical variable in determining the skill of the performer. What has long been sought is a description of the parameter or parameters that determine the degree of variability. Two general experimental protocals were used. One protocal is to use dynamic actions and record variability in kinematic parameters such as spatial or temporal error. A second strategy was to use isometric actions and record kinetic variables such as peak force produced. What might be the important force related factors affecting variability is examined and an experimental approach to examine the influence of each of these variables is provided.

  12. Spatial variability in airborne pollen concentrations.

    PubMed

    Raynor, G S; Ogden, E C; Hayes, J V

    1975-03-01

    Tests were conducted to determine the relationship between airborne pollen concentrations and distance. Simultaneous samples were taken in 171 tests with sets of eight rotoslide samplers spaced from one to 486 M. apart in straight lines. Use of all possible pairs gave 28 separation distances. Tests were conducted over a 2-year period in urban and rural locations distant from major pollen sources during both tree and ragweed pollen seasons. Samples were taken at a height of 1.5 M. during 5-to 20-minute periods. Tests were grouped by pollen type, location, year, and direction of the wind relative to the line. Data were analyzed to evaluate variability without regard to sampler spacing and variability as a function of separation distance. The mean, standard deviation, coefficient of variation, ratio of maximum to the mean, and ratio of minimum to the mean were calculated for each test, each group of tests, and all cases. The average coefficient of variation is 0.21, the maximum over the mean, 1.39 and the minimum over the mean, 0.69. No relationship was found with experimental conditions. Samples taken at the minimum separation distance had a mean difference of 18 per cent. Differences between pairs of samples increased with distance in 10 of 13 groups. These results suggest that airborne pollens are not always well mixed in the lower atmosphere and that a sample becomes less representative with increasing distance from the sampling location.

  13. Intra-urban spatial variability of PM2.5-bound carbonaceous components

    NASA Astrophysics Data System (ADS)

    Xie, Mingjie; Coons, Teresa L.; Dutton, Steven J.; Milford, Jana B.; Miller, Shelly L.; Peel, Jennifer L.; Vedal, Sverre; Hannigan, Michael P.

    2012-12-01

    The Denver Aerosol Sources and Health (DASH) study was designed to evaluate associations between PM2.5 species and sources and adverse human health effects. The DASH study generated a five-year (2003-2007) time series of daily speciated PM2.5 concentration measurements from a single, special-purpose monitoring site in Denver, CO. To evaluate the ability of this site to adequately represent the short term temporal variability of PM2.5 concentrations in the five county Denver metropolitan area, a one year supplemental set of PM2.5 samples was collected every sixth day at the original DASH monitoring site and concurrently at three additional sites. Two of the four sites, including the original DASH site, were located in residential areas at least 1.9 km from interstate highways. The other two sites were located within 0.3 km of interstate highways. Concentrations of elemental carbon (EC), organic carbon (OC), and 58 organic molecular markers were measured at each site. To assess spatial variability, site pairs were compared using the Pearson correlation coefficient (r) and coefficient of divergence (COD), a statistic that provides information on the degree of uniformity between monitoring sites. Bi-weekly co-located samples collected from July 2004 to September 2005 were also analyzed and used to estimate the uncertainty associated with sampling and analytical measurement for each species. In general, the two near-highway sites exhibited higher concentrations of EC, OC, polycyclic aromatic hydrocarbons (PAHs), and steranes than did the more residential sites. Lower spatial heterogeneity based on r and COD was inferred for all carbonaceous species after considering their divergence and lack of perfect correlations in co-located samples. Ratio-ratio plots combined with available gasoline- and diesel-powered motor vehicle emissions profiles for the region suggested a greater impact to high molecular weight (HMW) PAHs from diesel-powered vehicles at the near-highway sites

  14. Regional co-variability of spatial and temporal soil moisture-precipitation coupling in North Africa: an observational perspective

    NASA Astrophysics Data System (ADS)

    Petrova, Irina Y.; van Heerwaarden, Chiel C.; Hohenegger, Cathy; Guichard, Françoise

    2018-06-01

    The magnitude and sign of soil moisture-precipitation coupling (SMPC) is investigated using a probability-based approach and 10 years of daily microwave satellite data across North Africa at a 1° horizontal scale. Specifically, the co-existence and co-variability of spatial (i.e. using soil moisture gradients) and temporal (i.e. using soil moisture anomaly) soil moisture effects on afternoon rainfall is explored. The analysis shows that in the semi-arid environment of the Sahel, the negative spatial and the negative temporal coupling relationships do not only co-exist, but are also dependent on one another. Hence, if afternoon rain falls over temporally drier soils, it is likely to be surrounded by a wetter environment. Two regions are identified as SMPC hot spots. These are the south-western part of the domain (7-15° N, 10° W-7° E), with the most robust negative SMPC signal, and the South Sudanese region (5-13° N, 24-34° E). The sign and significance of the coupling in the latter region is found to be largely modulated by the presence of wetlands and is susceptible to the number of long-lived propagating convective systems. The presence of wetlands and an irrigated land area is found to account for about 30 % of strong and significant spatial SMPC in the North African domain. This study provides the first insight into regional variability of SMPC in North Africa, and supports the potential relevance of mechanisms associated with enhanced sensible heat flux and mesoscale variability in surface soil moisture for deep convection development.

  15. Spatial variability of climate change impacts on yield of rice and wheat in the Indian Ganga Basin.

    PubMed

    Mishra, Ashok; Singh, R; Raghuwanshi, N S; Chatterjee, C; Froebrich, Jochen

    2013-12-01

    Indian Ganga Basin (IGB), one of the most densely populated areas in the world, is facing a significant threat to food grain production, besides increased yield gap between actual and potential production, due to climate change. We have analyzed the spatial variability of climate change impacts on rice and wheat yields at three different locations representing the upper, middle and lower IGB. The DSSAT model is used to simulate the effects of climate variability and climate change on rice and wheat yields by analyzing: (i) spatial crop yield response to current climate, and (ii) impact of a changing climate as projected by two regional climate models, REMO and HadRM3, based on SRES A1B emission scenarios for the period 2011-2040. Results for current climate demonstrate a significant gap between actual and potential yield for upper, middle and lower IGB stations. The analysis based on RCM projections shows that during 2011-2040, the largest reduction in rice and wheat yields will occur in the upper IGB (reduction of potential rice and wheat yield respectively by 43.2% and 20.9% by REMO, and 24.8% and 17.2% by HadRM3). In the lower IGB, however, contrasting results are obtained, with HadRM3 based projections showing an increase in the potential rice and wheat yields, whereas, REMO based projections show decreased potential yields. We discuss the influence of agro-climatic factors; variation in temperature, length of maturity period and leaf area index which are responsible for modeled spatial variability in crop yield response within the IGB. Copyright © 2013 Elsevier B.V. All rights reserved.

  16. 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.

  17. Post-fire reconstructions of fire intensity from fire severity data: quantifying the role of spatial variability of fire intensity on forest dynamics

    NASA Astrophysics Data System (ADS)

    Baker, Patrick; Oborne, Lisa

    2015-04-01

    Large, high-intensity fires have direct and long-lasting effects on forest ecosystems and present a serious threat to human life and property. However, even within the most catastrophic fires there is important variability in local-scale intensity that has important ramifications for forest mortality and regeneration. Quantifying this variability is difficult due to the rarity of catastrophic fire events, the extreme conditions at the time of the fires, and their large spatial extent. Instead fire severity is typically measured or estimated from observed patterns of vegetation mortality; however, differences in species- and size-specific responses to fires often makes fire severity a poor proxy for fire intensity. We developed a statistical method using simple, plot-based measurements of individual tree mortality to simultaneously estimate plot-level fire intensity and species-specific mortality patterns as a function of tree size. We applied our approach to an area of forest burned in the catastrophic Black Saturday fires that occurred near Melbourne, Australia, in February 2009. Despite being the most devastating fire in the past 70 years and our plots being located in the area that experienced some of the most intense fires in the 350,000 ha fire complex, we found that the estimated fire intensity was highly variable at multiple spatial scales. All eight tree species in our study differed in their susceptibility to fire-induced mortality, particularly among the largest size classes. We also found that seedling height and species richness of the post-fire seedling communities were both positively correlated with fire intensity. Spatial variability in disturbance intensity has important, but poorly understood, consequences for the short- and long-term dynamics of forests in the wake of catastrophic wildfires. Our study provides a tool to estimate fire intensity after a fire has passed, allowing new opportunities for linking spatial variability in fire intensity to

  18. A review of variables of urban street connectivity for spatial connection

    NASA Astrophysics Data System (ADS)

    Mohamad, W. S. N. W.; Said, I.

    2014-02-01

    Several studies on street connectivity in cities and towns have been modeled on topology, morphology, technology and psychology of people living in the urban environment. Street connectivity means the connection of streets that offers people alternative routes. However, there emerge difficulties to determine the suitable variables and analysis to be chosen in defining the accurate result for studies street connectivity. The aim of this paper is to identify variables of street connectivity by applying GIS and Space Syntax. This paper reviews the variables of street connectivity from 15 past articles done in 1990s to early 2000s from journals of nine disciplines on Environment and Behavior, Planning and Design, Computers, Environment and Urban Systems, Applied Earth Observation and Geo-information, Environment and Planning, Physica A: Statistical Mechanics and its Applications, Environmental Psychology, Social Science and Medicine and Building and Environment. From the review, there are four variables found for street connectivity: link (streets-streets, street-nodes or node-streets, nodes-nodes), accessibility, least-angle, and centrality. Space syntax and GIS are suitable tools to analyze the four variables relating to systematic street systems for pedestrians. This review implies that planners of the street systems, in the aspect of street connectivity in cities and towns, should consider these four variables.

  19. Interferometric Synthetic Aperture Radar to capture spatial variability of local land-based subsidence

    NASA Astrophysics Data System (ADS)

    Bekaert, D. P.; Hamlington, B.; Buzzanga, B. A.; Jones, C. E.

    2017-12-01

    The rate of relative sea level rise results from a combination of land subsidence and rising seas associated with global warming on long timescales and exacerbated by shifts in ocean dynamics on shorter timescales. An understanding of the current-day magnitude of each component is needed to create accurate projections of future relative sea level rise upon which to base planning efforts. Current day land-based subsidence rates derived from GPS often lack the spatial resolution to capture the local spatial variability needed when assessing the impact of relative sea-level rise. Interferometric Synthetic Aperture Radar (InSAR) is an attractive technique that has the potential to provide a measurement every 20-30m when good signal coherence is maintained. In practice, coastal regions are challenging for InSAR due to variable vegetation cover and soil moisture, which can be in part mitigated by applying advanced time-series InSAR techniques. After applying time-series InSAR, derived rates need to be combined with GPS to tie relative subsidence rates into a geodetic reference frame. Given the need to make projections of relative sea-level rise it is particularly important to propagate all uncertainties during the different processing stages. Here we provide results from ALOS and Sentinel-1 over Hampton Roads area in the Chesapeake Bay region, which is experiencing one of the highest rates of relative sea level rise on the Atlantic coast of the United States. Although the current derived subsidence rates have large uncertainties, it is expected that this will improve with the decadal observations from Sentinel-1.

  20. Decadal changes of reference crop evapotranspiration attribution: Spatial and temporal variability over China 1960-2011

    NASA Astrophysics Data System (ADS)

    Fan, Ze-Xin; Thomas, Axel

    2018-05-01

    Atmospheric evaporative demand can be used as a measure of the hydrological cycle and the global energy balance. Its long-term variation and the role of driving climatic factors have received increasingly attention in climate change studies. FAO-Penman-Monteith reference crop evapotranspiration rates were estimated for 644 meteorological stations over China for the period 1960-2011 to analyze spatial and temporal attribution variability. Attribution of climatic variables to reference crop evapotranspiration rates was not stable over the study period. While for all of China the contribution of sunshine duration remained relatively stable, the importance of relative humidity increased considerably during the last two decades, particularly in winter. Spatially distributed attribution analysis shows that the position of the center of maximum contribution of sunshine duration has shifted from Southeast to Northeast China while in West China the contribution of wind speed has decreased dramatically. In contrast relative humidity has become an important factor in most parts of China. Changes in the Asian Monsoon circulation may be responsible for altered patterns of cloudiness and a general decrease of wind speeds over China. The continuously low importance of temperature confirms that global warming does not necessarily lead to rising atmospheric evaporative demand.

  1. Inter-annual variability and spatial coherence of net primary productivity across a western Oregon Cascades landscape

    Treesearch

    Travis J. Woolley; Mark E. Harmon; Kari B. O’Connell

    2015-01-01

    Inter-annual variability (IAV) of forest Net Primary Productivity (NPP) is a function of both extrinsic (e.g., climate) and intrinsic (e.g., stand dynamics) drivers. As estimates of NPP in forests are scaled from trees to stands to the landscape, an understanding of the relative effects of these factors on spatial and temporal behavior of NPP is important. Although a...

  2. Spatial variability structure of soil CO2 emission and soil physical and chemical properties characterized by fractal dimension in sugarcane areas

    NASA Astrophysics Data System (ADS)

    Bicalho, E. S.; Teixeira, D. B.; Panosso, A. R.; Perillo, L. I.; Iamaguti, J. L.; Pereira, G. T.; La Scala, N., Jr.

    2012-04-01

    Soil CO2 emission (FCO2) is influenced by chemical, physical and biological factors that affect the production of CO2 in the soil and its transport to the atmosphere, varying in time and space depending on environmental conditions, including the management of agricultural area. The aim of this study was to investigate the structure of spatial variability of FCO2 and soil properties by using fractal dimension (DF), derived from isotropic variograms at different scales, and construction of fractograms. The experimental area consisted of a regular grid of 60 × 60 m on sugarcane area under green management, containing 141 points spaced at minimum distances ranging from 0.5 to 10 m. Soil CO2 emission, soil temperature and soil moisture were evaluated over a period of 7 days, and soil chemical and physical properties were determined by sampling at a depth of 0.0 to 0.1 m. FCO2 showed an overall average of 1.51 µmol m-2 s-1, correlated significantly (p < 0.05) with soil physical factors such as soil bulk density, air-filled pore space, macroporosity and microporosity. Significant DF values were obtained in the characterization of FCO2 in medium and large scales (from 20 m). Variations in DF with the scale, which is the fractogram, indicate that the structure of FCO2 variability is similar to that observed for the soil temperature and total pore volume, and reverse for the other soil properties, except for macroporosity, sand content, soil organic matter, carbon stock, C/N ratio and CEC, which fractograms were not significantly correlated to the FCO2 fractogram. Thus, the structure of spatial variability for most soil properties, characterized by fractogram, presents a significant relationship with the structure of spatial variability of FCO2, generally with similar or dissimilar behavior, indicating the possibility of using the fractogram as tool to better observe the behavior of the spatial dependence of the variables along the scale.

  3. Spatial variability of soil total and DTPA-extractable cadmium caused by long-term application of phosphate fertilizers, crop rotation, and soil characteristics.

    PubMed

    Jafarnejadi, A R; Sayyad, Gh; Homaee, M; Davamei, A H

    2013-05-01

    Increasing cadmium (Cd) accumulation in agricultural soils is undesirable due to its hazardous influences on human health. Thus, having more information on spatial variability of Cd and factors effective to increase its content on the cultivated soils is very important. Phosphate fertilizers are main contamination source of cadmium (Cd) in cultivated soils. Also, crop rotation is a critical management practice which can alter soil Cd content. This study was conducted to evaluate the effects of long-term consumption of the phosphate fertilizers, crop rotations, and soil characteristics on spatial variability of two soil Cd species (i.e., total and diethylene triamine pentaacetic acid (DTPA) extractable) in agricultural soils. The study was conducted in wheat farms of Khuzestan Province, Iran. Long-term (27-year period (1980 to 2006)) data including the rate and the type of phosphate fertilizers application, the respective area, and the rotation type of different regions were used. Afterwards, soil Cd content (total or DTPA extractable) and its spatial variability in study area (400,000 ha) were determined by sampling from soils of 255 fields. The results showed that the consumption rate of di-ammonium phosphate fertilizer have been varied enormously in the period study. The application rate of phosphorus fertilizers was very high in some subregions with have extensive agricultural activities (more than 95 kg/ha). The average and maximum contents of total Cd in the study region were obtained as 1.47 and 2.19 mg/kg and DTPA-extractable Cd as 0.084 and 0.35 mg/kg, respectively. The spatial variability of Cd indicated that total and DTPA-extractable Cd contents were over 0.8 and 0.1 mg/kg in 95 and 25 % of samples, respectively. The spherical model enjoys the best fitting and lowest error rate to appraise the Cd content. Comparing the phosphate fertilizer consumption rate with spatial variability of the soil cadmium (both total and DTPA extractable) revealed the high

  4. High Temporal and Spatial Variability of Atmospheric-Methane Oxidation in Alpine Glacier Forefield Soils

    PubMed Central

    Chiri, Eleonora; Nauer, Philipp A.; Rainer, Edda-Marie; Zeyer, Josef

    2017-01-01

    ABSTRACT Glacier forefield soils can provide a substantial sink for atmospheric CH4, facilitated by aerobic methane-oxidizing bacteria (MOB). However, MOB activity, abundance, and community structure may be affected by soil age, MOB location in different forefield landforms, and temporal fluctuations in soil physical parameters. We assessed the spatial and temporal variability of atmospheric-CH4 oxidation in an Alpine glacier forefield during the snow-free season of 2013. We quantified CH4 flux in soils of increasing age and in different landforms (sandhill, terrace, and floodplain forms) by using soil gas profile and static flux chamber methods. To determine MOB abundance and community structure, we employed pmoA gene-based quantitative PCR and targeted amplicon sequencing. Uptake of CH4 increased in magnitude and decreased in variability with increasing soil age. Sandhill soils exhibited CH4 uptake rates ranging from −3.7 to −0.03 mg CH4 m−2 day−1. Floodplain and terrace soils exhibited lower uptake rates and even intermittent CH4 emissions. Linear mixed-effects models indicated that soil age and landform were the dominating factors shaping CH4 flux, followed by cumulative rainfall (weighted sum ≤4 days prior to sampling). Of 31 MOB operational taxonomic units retrieved, ∼30% were potentially novel, and ∼50% were affiliated with upland soil clusters gamma and alpha. The MOB community structures in floodplain and terrace soils were nearly identical but differed significantly from the highly variable sandhill soil communities. We concluded that soil age and landform modulate the soil CH4 sink strength in glacier forefields and that recent rainfall affects its short-term variability. This should be taken into account when including this environment in future CH4 inventories. IMPORTANCE Oxidation of methane (CH4) in well-drained, “upland” soils is an important mechanism for the removal of this potent greenhouse gas from the atmosphere. It is largely

  5. High temporal and spatial variability of atmospheric-methane oxidation in Alpine glacier-forefield soils.

    PubMed

    Chiri, Eleonora; Nauer, Philipp A; Rainer, Edda-Marie; Zeyer, Josef; Schroth, Martin H

    2017-07-07

    Glacier-forefield soils can provide a substantial sink for atmospheric CH 4 , facilitated by aerobic methane-oxidizing bacteria (MOB). However, MOB activity, abundance, and community structure may be affected by soil age, location in different forefield landforms, and temporal fluctuations in soil-physical parameters. We assessed spatial and temporal variability of atmospheric CH 4 oxidation in an Alpine glacier forefield during the snow-free season 2013. We quantified CH 4 flux in soils of increasing age and in different landforms (sandhill, terrace, floodplain) using soil-gas-profile and static flux-chamber methods. To determine MOB abundance and community structure, we employed pmoA -gene-based quantitative PCR and targeted-amplicon sequencing. Uptake of CH 4 increased in magnitude and decreased in variability with increasing soil age. Sandhill soils exhibited CH 4 uptake ranging from -0.03- -3.7 mg CH 4 m -2 d -1 Floodplain and terrace soils exhibited smaller uptake and even intermittent CH 4 emissions. Linear mixed-effect models indicated that soil age and landform were dominating factors shaping CH 4 flux, followed by cumulative rainfall (weighted sum ≤ 4 d prior to sampling). Of 31 MOB operational taxonomic units retrieved, ∼30% were potentially novel, and ∼50% were affiliated with Upland Soil Clusters gamma and alpha. The MOB community structures in floodplain and terrace soils were nearly identical, but differed significantly from highly variable sandhill-soil communities. We conclude that soil age and landform modulate the soil CH 4 sink strength in glacier forefields, and recent rainfall affects its short-term variability. This should be taken into account when including this environment in future CH 4 inventories. Importance Oxidation of methane (CH 4 ) in well-drained, "upland" soils is an important mechanism for the removal of this potent greenhouse gas from the atmosphere. It is largely mediated by aerobic, methane-oxidizing bacteria (MOB

  6. Place, Poverty, and Algebra: A Statewide Comparative Spatial Analysis of Variable Relationships

    ERIC Educational Resources Information Center

    Hogrebe, Mark C.; Tate, William F.

    2012-01-01

    Place matters in moderating variable relationships between algebra performance and educational variables because there are differences on the socioeconomic (SES) poverty-affluence continuum that shape local contexts. This article examines relationships between variables for school district demographic composition, teaching and financial contexts,…

  7. Spatial variability in the soil water content of a Mediterranean agroforestry system with high soil heterogeneity

    NASA Astrophysics Data System (ADS)

    Molina, Antonio Jaime; Llorens, Pilar; Aranda, Xavier; Savé, Robert; Biel, Carmen

    2013-04-01

    Variability of soil water content is known to increase with the size of spatial domain in which measurements are taken. At field scale, heterogeneity in soil, vegetation, topography, water input volume and management affects, among other factors, hydrologic plot behaviour under different mean soil water contents. The present work studies how the spatial variability of soil water content (SWC) is affected by soil type (texture, percentage of stones and the combination of them) in a timber-orientated plantation of cherry tree (Prunus avium) under Mediterranean climatic conditions. The experimental design is a randomized block one with 3 blocks * 4 treatments, based on two factors: irrigation (6 plots irrigated versus 6 plots not irrigated) and soil management (6 plots tillaged versus 6 plots not tillaged). SWC is continuously measured at 25, 50 and 100 cm depth with FDR sensors, located at two positions in each treatment: under tree influence and 2.5 m apart. This study presents the results of the monitoring during 2012 of the 24 sensors located at the 25 cm depth. In each of the measurement point, texture and percentage of stones were measured. Sandy-loam, sandy-clay-loam and loam textures were found together with a percentage of stones ranging from 20 to 70 %. The results indicated that the relationship between the daily mean SWC and its standard deviation, a common procedure used to study spatial variability, changed with texture, percentage of stones and the estimation of field capacity from the combination of both. Temporal stability analysis of SWC showed a clear pattern related to field capacity, with the measurement points of the sandy-loam texture and the high percentage of stones showing the maximun negative diference with the global mean. The high range in the mean relative difference observed (± 75 %), could indicate that the studied plot may be considered as a good field-laboratory to extrapolate results at higher spatial scales. Furthermore, the

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

    USGS Publications Warehouse

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

    2017-01-01

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

  9. Influence of spatial and temporal variability of subsurface soil moisture and temperature on vapour intrusion

    NASA Astrophysics Data System (ADS)

    Bekele, Dawit N.; Naidu, Ravi; Chadalavada, Sreenivasulu

    2014-05-01

    A comprehensive field study was conducted at a site contaminated with chlorinated solvents, mainly trichloroethylene (TCE), to investigate the influence of subsurface soil moisture and temperature on vapour intrusion (VI) into built structures. Existing approaches to predict the risk of VI intrusion into buildings assume homogeneous or discrete layers in the vadose zone through which TCE migrates from an underlying source zone. In reality, the subsurface of the majority of contaminated sites will be subject to significant variations in moisture and temperature. Detailed site-specific data were measured contemporaneously to evaluate the impact of spatial and temporal variability of subsurface soil properties on VI exposure assessment. The results revealed that indoor air vapour concentrations would be affected by spatial and temporal variability of subsurface soil moisture and temperature. The monthly monitoring of soil-gas concentrations over a period of one year at a depth of 3 m across the study site demonstrated significant variation in TCE vapour concentrations, which ranged from 480 to 629,308 μg/m3. Soil-gas wells at 1 m depth exhibited high seasonal variability in TCE vapour concentrations with a coefficient of variation 1.02 in comparison with values of 0.88 and 0.74 in 2 m and 3 m wells, respectively. Contour plots of the soil-gas TCE plume during wet and dry seasons showed that the plume moved across the site, hence locations of soil-gas monitoring wells for human risk assessment is a site specific decision. Subsurface soil-gas vapour plume characterisation at the study site demonstrates that assessment for VI is greatly influenced by subsurface soil properties such as temperature and moisture that fluctuate with the seasons of the year.

  10. A new spatial snow distribution in hydrological models parameterized from observed spatial variability of precipitation.

    NASA Astrophysics Data System (ADS)

    Skaugen, Thomas; Weltzien, Ingunn

    2016-04-01

    The traditional catchment hydrological model with its many free calibration parameters is not a well suited tool for prediction under conditions for which is has not been calibrated. Important tasks for hydrological modelling such as prediction in ungauged basins and assessing hydrological effects of climate change are hence not solved satisfactory. In order to reduce the number of calibration parameters in hydrological models we have introduced a new model which uses a dynamic gamma distribution as the spatial frequency distribution of snow water equivalent (SWE). The parameters are estimated from observed spatial variability of precipitation and the magnitude of accumulation and melting events and are hence not subject to calibration. The relationship between spatial mean and variance of precipitation is found to follow a pattern where decreasing temporal correlation with increasing accumulation or duration of the event leads to a levelling off or even a decrease of the spatial variance. The new model for snow distribution is implemented in the, already parameter parsimonious, DDD (Distance Distribution Dynamics) hydrological model and was tested for 71 Norwegian catchments. We compared the new snow distribution model with the current operational snow distribution model where a fixed, calibrated coefficient of variation parameterizes a log-normal model for snow distribution. Results show that the precision of runoff simulations is equal, but that the new snow distribution model better simulates snow covered area (SCA) when compared with MODIS satellite derived snow cover. In addition, SWE is simulated more realistically in that seasonal snow is melted out and the building up of "snow towers" is prevented and hence spurious trends in SWE.

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

    USGS Publications Warehouse

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

    2014-01-01

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

  12. Spatial variability of soil carbon stock in the Urucu river basin, Central Amazon-Brazil.

    PubMed

    Ceddia, Marcos Bacis; Villela, André Luis Oliveira; Pinheiro, Érika Flávia Machado; Wendroth, Ole

    2015-09-01

    The Amazon Forest plays a major role in C sequestration and release. However, few regional estimates of soil organic carbon (SOC) stock in this ecoregion exist. One of the barriers to improve SOC estimates is the lack of recent soil data at high spatial resolution, which hampers the application of new methods for mapping SOC stock. The aims of this work were: (i) to quantify SOC stock under undisturbed vegetation for the 0-30 and the 0-100 cm under Amazon Forest; (ii) to correlate the SOC stock with soil mapping units and relief attributes and (iii) to evaluate three geostatistical techniques to generate maps of SOC stock (ordinary, isotopic and heterotopic cokriging). The study site is located in the Central region of Amazon State, Brazil. The soil survey covered the study site that has an area of 80 km(2) and resulted in a 1:10,000 soil map. It consisted of 315 field observations (96 complete soil profiles and 219 boreholes). SOC stock was calculated by summing C stocks by horizon, determined as a product of BD, SOC and the horizon thickness. For each one of the 315 soil observations, relief attributes were derived from a topographic map to understand SOC dynamics. The SOC stocks across 30 and 100 cm soil depth were 3.28 and 7.32 kg C m(-2), respectively, which is, 34 and 16%, lower than other studies. The SOC stock is higher in soils developed in relief forms exhibiting well-drained soils, which are covered by Upland Dense Tropical Rainforest. Only SOC stock in the upper 100 cm exhibited spatial dependence allowing the generation of spatial variability maps based on spatial (co)-regionalization. The CTI was inversely correlated with SOC stock and was the only auxiliary variable feasible to be used in cokriging interpolation. The heterotopic cokriging presented the best performance for mapping SOC stock. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. Assessing spatial and temporal variability of acid-extractable organics in oil sands process-affected waters.

    PubMed

    Frank, Richard A; Milestone, Craig B; Rowland, Steve J; Headley, John V; Kavanagh, Richard J; Lengger, Sabine K; Scarlett, Alan G; West, Charles E; Peru, Kerry M; Hewitt, L Mark

    2016-10-01

    The acid-extractable organic compounds (AEOs), including naphthenic acids (NAs), present within oil sands process-affected water (OSPW) receive great attention due to their known toxicity. While recent progress in advanced separation and analytical methodologies for AEOs has improved our understanding of the composition of these mixtures, little is known regarding any variability (i.e., spatial, temporal) inherent within, or between, tailings ponds. In this study, 5 samples were collected from the same location of one tailings pond over a 2-week period. In addition, 5 samples were collected simultaneously from different locations within a tailings pond from a different mine site, as well as its associated recycling pond. In both cases, the AEOs were analyzed using SFS, ESI-MS, HRMS, GC×GC-ToF/MS, and GC- & LC-QToF/MS (GC analyses following conversion to methyl esters). Principal component analysis of HRMS data was able to distinguish the ponds from each other, while data from GC×GC-ToF/MS, and LC- and GC-QToF/MS were used to differentiate samples from within the temporal and spatial sample sets, with the greater variability associated with the latter. Spatial differences could be attributed to pond dynamics, including differences in inputs of tailings and surface run-off. Application of novel chemometric data analyses of unknown compounds detected by LC- and GC-QToF/MS allowed further differentiation of samples both within and between data sets, providing an innovative approach for future fingerprinting studies. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  15. Assessing variability in Orbiting Carbon Observatory-2 (OCO-2) XCO2 using high spatial resolution color slices and other retrieval parameters

    NASA Astrophysics Data System (ADS)

    Merrelli, A. J.; Taylor, T.; O'Dell, C.; Cronk, H. Q.; Eldering, A.; Crisp, D.

    2017-12-01

    The Orbiting Carbon Observatory-2 (OCO-2) measures reflected sunlight in the Oxygen A-band (0.76 μm), Weak CO2 band (1.61 μm) and Strong CO2 band (2.06 μm) with resolving powers 18,000, 19,500 and 19,500, respectively. Soundings are collected at 3Hz, yielding 8 contiguous <1.3 km x 2.3 km footprints across a narrow (<0.8°) swath. After cloud screening, these high-resolution spectra are used in an optimal estimation retrieval to produce estimates of the column averaged carbon dioxide dry air mole fraction (XCO2). In the absence of strong CO2 absorbers, e.g., intense agricultural regions, or strong emitters, e.g., mega-cities, the variability of XCO2 over small scales, e.g., tens of kilometers, is expected to be less than 1 ppm. However, deviations on the order of +/- 2 ppm, or more, are often observed in the production Version 7 (B7) data product. We hypothesize that most of this variability is spurious, with contributions from both retrieval errors and undetected cloud and aerosol contamination. The contiguous nature of the OCO-2 spatial sampling allows for analysis of the variability in XCO2 and correlation with variables, such as the full spatial resolution "color slices" and other retrieved parameters. Color slices avoid the on-board averaging across the detector focal plane array, providing increased spatial information compared to the nominal spectra. This work explores the new B8 production data set using MODIS visible imagery from the CSU Vistool to provide visual context to the OCO-2 parameters. The large volume of data that has been collected since September 2014 allows for statistical analysis of parameters in relation to XCO2 variability. Some detailed case studies are presented.

  16. Climatic and physiographic controls of spatial variability in surface water balance over the contiguous United States using the Budyko relationship

    NASA Astrophysics Data System (ADS)

    Abatzoglou, John T.; Ficklin, Darren L.

    2017-09-01

    The geographic variability in the partitioning of precipitation into surface runoff (Q) and evapotranspiration (ET) is fundamental to understanding regional water availability. The Budyko equation suggests this partitioning is strictly a function of aridity, yet observed deviations from this relationship for individual watersheds impede using the framework to model surface water balance in ungauged catchments and under future climate and land use scenarios. A set of climatic, physiographic, and vegetation metrics were used to model the spatial variability in the partitioning of precipitation for 211 watersheds across the contiguous United States (CONUS) within Budyko's framework through the free parameter ω. A generalized additive model found that four widely available variables, precipitation seasonality, the ratio of soil water holding capacity to precipitation, topographic slope, and the fraction of precipitation falling as snow, explained 81.2% of the variability in ω. The ω model applied to the Budyko equation explained 97% of the spatial variability in long-term Q for an independent set of watersheds. The ω model was also applied to estimate the long-term water balance across the CONUS for both contemporary and mid-21st century conditions. The modeled partitioning of observed precipitation to Q and ET compared favorably across the CONUS with estimates from more sophisticated land-surface modeling efforts. For mid-21st century conditions, the model simulated an increase in the fraction of precipitation used by ET across the CONUS with declines in Q for much of the eastern CONUS and mountainous watersheds across the western United States.

  17. Spatial variability in distribution and prevalence of Caribbean scleractinian coral and octocoral diseases. II. Genera-level analysis.

    PubMed

    Cróquer, Aldo; Weil, Ernesto

    2009-02-25

    Geographic assessments of coral/octocoral diseases affecting major reef-building genera and abundant reef species are important to understand their local and geographic spatial-temporal variability and their impact. The status and spatial variability of major Caribbean coral/octocoral diseases affecting important reef-building coral (Montastraea, Diploria, Siderastrea, Stephanocoenia, Porites, and Agaricia) and common, widespread octocoral genera (Gorgonia and Pseudopterogorgia) was assessed along 4 permanent 10 x 2 m band-transects in each of 3 depth habitats (<4, 5-12 and >15 m) on 2 reefs in 6 countries across the wider Caribbean during the summer and fall of 2005. A permutational multivariate analysis of variance was used to test the spatial variability (countries, reef sites and depth habitats) in prevalence of major diseases in these genera. We found a significant interaction of disease prevalence in the different coral and octocoral genera between reef sites and habitats (depth intervals). Montastraea was primarily affected by both white plague (WP-II) and yellow band disease in deep (16.9 +/- SE 16% and 16.9 +/- SE 2.3%) and intermediate (8.1 +/- SE 1.6% and 15.5 +/- SE 2.3%) depth habitats of Culebrita (Puerto Rico) and Chub Cut (Bermuda), respectively. Prevalence of multiple diseases simultaneously and other compromised-health problems affecting Montastraea colonies varied between 0.2 to 2% and 0.2 to 1.8%, respectively. Agaricia and Diploria were mostly affected by WP-II (0.5 to 16%), black band disease (0.4 to 5%) and Caribbean ciliate infections (0.2 to 12%). Siderastrea and Stephanocoenia were mainly affected by dark spots disease in Curaçao, with higher prevalence in intermediate (40.5 +/- SE 6.2%) and deep (26.6 +/- SE 4.2%) habitats. Aspergillosis and other compromised-health conditions affected Gorgonia ventalina (0.2 to 8%) and other common and widespread octocoral genera (1 to 14%), respectively.

  18. Interannual rainfall variability and SOM-based circulation classification

    NASA Astrophysics Data System (ADS)

    Wolski, Piotr; Jack, Christopher; Tadross, Mark; van Aardenne, Lisa; Lennard, Christopher

    2018-01-01

    Self-Organizing Maps (SOM) based classifications of synoptic circulation patterns are increasingly being used to interpret large-scale drivers of local climate variability, and as part of statistical downscaling methodologies. These applications rely on a basic premise of synoptic climatology, i.e. that local weather is conditioned by the large-scale circulation. While it is clear that this relationship holds in principle, the implications of its implementation through SOM-based classification, particularly at interannual and longer time scales, are not well recognized. Here we use a SOM to understand the interannual synoptic drivers of climate variability at two locations in the winter and summer rainfall regimes of South Africa. We quantify the portion of variance in seasonal rainfall totals that is explained by year to year differences in the synoptic circulation, as schematized by a SOM. We furthermore test how different spatial domain sizes and synoptic variables affect the ability of the SOM to capture the dominant synoptic drivers of interannual rainfall variability. Additionally, we identify systematic synoptic forcing that is not captured by the SOM classification. The results indicate that the frequency of synoptic states, as schematized by a relatively disaggregated SOM (7 × 9) of prognostic atmospheric variables, including specific humidity, air temperature and geostrophic winds, captures only 20-45% of interannual local rainfall variability, and that the residual variance contains a strong systematic component. Utilising a multivariate linear regression framework demonstrates that this residual variance can largely be explained using synoptic variables over a particular location; even though they are used in the development of the SOM their influence, however, diminishes with the size of the SOM spatial domain. The influence of the SOM domain size, the choice of SOM atmospheric variables and grid-point explanatory variables on the levels of explained

  19. Global Variability and Changes in Ocean Total Alkalinity from Aquarius Satellite

    NASA Astrophysics Data System (ADS)

    Fine, R. A.; Willey, D. A.; Millero, F. J., Jr.

    2016-02-01

    To document effects of ocean acidification it is important to have an understanding of the processes and parameters that influence alkalinity. Alkalinity is a gauge on the ability of seawater to neutralize acids. We use Aquarius satellite data, which allow unprecedented global mapping of surface total alkalinity as it correlates strongly with salinity and to a lesser extent with temperature. Spatial variability in total alkalinity and salinity exceed temporal variability, the latter includes seasonal and differences compared to climatological data. The northern hemisphere has more spatial and monthly variability in total alkalinity and salinity, while less variability in Southern Ocean alkalinity is due to less salinity variability and upwelling of waters enriched in alkalinity. Satellite alkalinity data are providing a global baseline that can be used for comparing with future carbon data, and for evaluating spatial and temporal variability and past trends. For the first time it is shown that recent satellite derived total alkalinity in the subtropics have increased as compared with climatological data; this is reflective of large scale changes in the global water cycle. Total alkalinity increases imply increased dissolution of calcareous minerals and difficulty for calcifying organisms to make their shells.

  20. Spatial and temporal variability of soil temperature, moisture and surface soil properties

    NASA Technical Reports Server (NTRS)

    Hajek, B. F.; Dane, J. H.

    1993-01-01

    The overall objectives of this research were to: (l) Relate in-situ measured soil-water content and temperature profiles to remotely sensed surface soil-water and temperature conditions; to model simultaneous heat and water movement for spatially and temporally changing soil conditions; (2) Determine the spatial and temporal variability of surface soil properties affecting emissivity, reflectance, and material and energy flux across the soil surface. This will include physical, chemical, and mineralogical characteristics of primary soil components and aggregate systems; and (3) Develop surface soil classes of naturally occurring and distributed soil property assemblages and group classes to be tested with respect to water content, emissivity and reflectivity. This document is a report of studies conducted during the period funded by NASA grants. The project was designed to be conducted over a five year period. Since funding was discontinued after three years, some of the research started was not completed. Additional publications are planned whenever funding can be obtained to finalize data analysis for both the arid and humid locations.

  1. High spatial variability in biogeochemical rates and microbial communities across Louisiana salt marsh landscapes

    NASA Astrophysics Data System (ADS)

    Roberts, B. J.; Chelsky, A.; Bernhard, A. E.; Giblin, A. E.

    2017-12-01

    Salt marshes are important sites for retention and transformation of carbon and nutrients. Much of our current marsh biogeochemistry knowledge is based on sampling at times and in locations that are convenient, most often vegetated marsh platforms during low tide. Wetland loss rates are high in many coastal regions including Louisiana which has the highest loss rates in the US. This loss not only reduces total marsh area but also changes the relative allocation of subhabitats in the remaining marsh. Climate and other anthropogenic changes lead to further changes including inundation patterns, redox conditions, salinity regimes, and shifts in vegetation patterns across marsh landscapes. We present results from a series of studies examining biogeochemical rates, microbial communities, and soil properties along multiple edge to interior transects within Spartina alterniflora across the Louisiana coast; between expanding patches of Avicennia germinans and adjacent S. alterniflora marshes; in soils associated with the four most common Louisiana salt marsh plants species; and across six different marsh subhabitats. Spartina alterniflora marsh biogeochemistry and microbial populations display high spatial variability related to variability in soil properties which appear to be, at least in part, regulated by differences in elevation, hydrology, and redox conditions. Differences in rates between soils associated with different vegetation types were also related to soil properties with S. alterniflora soils often yielding the lowest rates. Biogeochemical process rates vary significantly across marsh subhabitats with individual process rates differing in their hotspot habitat(s) across the marsh. Distinct spatial patterns may influence the roles that marshes play in retaining and transforming nutrients in coastal regions and highlight the importance of incorporating spatial sampling when scaling up plot level measurements to landscape or regional scales.

  2. Temporal and spatial variability of dissolved organic and inorganic phosphorus, and metrics of phosphorus bioavailability in an upwelling-dominated coastal system

    NASA Astrophysics Data System (ADS)

    Ruttenberg, Kathleen C.; Dyhrman, Sonya T.

    2005-10-01

    High-frequency temporal and spatial shifts in the various dissolved P pools (total, inorganic, and organic) are linked to upwelling/relaxation events and to phytoplankton bloom dynamics in the upwelling-dominated Oregon coastal system. The presence and regulation of alkaline phosphatase activity (APA) is apparent in the bulk phytoplankton population and in studies of cell-specific APA using Enzyme Labeled Fluorescence (ELF®). Spatial and temporal variability are also evident in phytoplankton community composition and in APA. The spatial pattern of dissolved phosphorus and APA variability can be explained by bottom-controlled patterns of upwelling, and flushing times of different regions within the study area. The presence of APA in eukaryotic taxa indicates that dissolved organic phosphorus (DOP) may contribute to phytoplankton P nutrition in this system, highlighting the need for a more complete understanding of P cycling and bioavailability in the coastal ocean.

  3. Controls on the variability of net infiltration to desert sandstone

    USGS Publications Warehouse

    Heilweil, Victor M.; McKinney, Tim S.; Zhdanov, Michael S.; Watt, Dennis E.

    2007-01-01

    As populations grow in arid climates and desert bedrock aquifers are increasingly targeted for future development, understanding and quantifying the spatial variability of net infiltration becomes critically important for accurately inventorying water resources and mapping contamination vulnerability. This paper presents a conceptual model of net infiltration to desert sandstone and then develops an empirical equation for its spatial quantification at the watershed scale using linear least squares inversion methods for evaluating controlling parameters (independent variables) based on estimated net infiltration rates (dependent variables). Net infiltration rates used for this regression analysis were calculated from environmental tracers in boreholes and more than 3000 linear meters of vadose zone excavations in an upland basin in southwestern Utah underlain by Navajo sandstone. Soil coarseness, distance to upgradient outcrop, and topographic slope were shown to be the primary physical parameters controlling the spatial variability of net infiltration. Although the method should be transferable to other desert sandstone settings for determining the relative spatial distribution of net infiltration, further study is needed to evaluate the effects of other potential parameters such as slope aspect, outcrop parameters, and climate on absolute net infiltration rates.

  4. Evaluation of the spatial variability of soil water content at the spatial resolution of SMAP data products : case studies in Italy and Morocco

    NASA Astrophysics Data System (ADS)

    Menenti, Massimo; Akdim, Nadia; Alfieri, Silvia Maria; Labbassi, Kamal; De Lorenzi, Francesca; Bonfante, Antonello; Basile, Angelo

    2014-05-01

    Frequent and contiguous observations of soil water content such as the ones to be provided by SMAP are potentially useful to improve distributed models of soil water balance. This requires matching of observations and model estimates provided both sample spatial patterns consistently. The spatial resolution of SMAP soil water content data products ranges from 3 km X 3 km to 40 km X 40 km. Even the highest spatial resolution may not be sufficient to capture the spatial variability due to terrain, soil properties and precipitation. We have evaluated the SMAP spatial resolution against spatial variability of soil water content in two Mediterranean landscapes: a hilly area dominated by vineyards and olive orchards in Central Italy and a large irrigation schemes (Doukkala) in Morocco. The "Valle Telesina" is a 20,000 ha complex landscape located in South Italy in the Campania region, which has a complex geology and geomorphology and it is characterised by an E-W elongated graben where the Calore river flows. The main crops are grapevine (6,448 ha) and olive (3,390 ha). Soil information was mainly derived from an existing soil map at 1:50 000 scale (Terribile et al., 1996). The area includes 47 SMUs (Soil Mapping Units) and about 60 soil typological units (STUs). (Bonfante et al., 2011). In Doukkala, the soil water retention and unsaturated capillary conductivity were estimated from grain size distribution of a number of samples (22 pilot points, each one sampled in 3 horizons of 20cm), and combined with a soil map. The land use classification was carried out using a NDVI time series at high spatial resolution (Landsat TM and SPOT HRV). We have calculated soil water content for each soil unit in each area in response to several climate cases generating daily maps of soil water content at different depths. To reproduce spatial sampling by SMAP we have filtered these spatial patterns by calculating box averages with grid sizes of 1 km X 1 km and 5 km X 5 km. We have

  5. Analysis of the spatial and temporal variability of terrestrial water storage and snowpack in the Pacific Northwestern United States

    EPA Science Inventory

    The spatial and temporal variability of terrestrial water storage and snowpack in the Pacific Northwest (PNW) was analyzed for water years 2001–2010 using measurements from the Gravity Recovery and Climate Experiment (GRACE) instrument. GRACE provides remotely-sensed measurements...

  6. High-resolution spatial databases of monthly climate variables (1961-2010) over a complex terrain region in southwestern China

    NASA Astrophysics Data System (ADS)

    Wu, Wei; Xu, An-Ding; Liu, Hong-Bin

    2015-01-01

    Climate data in gridded format are critical for understanding climate change and its impact on eco-environment. The aim of the current study is to develop spatial databases for three climate variables (maximum, minimum temperatures, and relative humidity) over a large region with complex topography in southwestern China. Five widely used approaches including inverse distance weighting, ordinary kriging, universal kriging, co-kriging, and thin-plate smoothing spline were tested. Root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) showed that thin-plate smoothing spline with latitude, longitude, and elevation outperformed other models. Average RMSE, MAE, and MAPE of the best models were 1.16 °C, 0.74 °C, and 7.38 % for maximum temperature; 0.826 °C, 0.58 °C, and 6.41 % for minimum temperature; and 3.44, 2.28, and 3.21 % for relative humidity, respectively. Spatial datasets of annual and monthly climate variables with 1-km resolution covering the period 1961-2010 were then obtained using the best performance methods. Comparative study showed that the current outcomes were in well agreement with public datasets. Based on the gridded datasets, changes in temperature variables were investigated across the study area. Future study might be needed to capture the uncertainty induced by environmental conditions through remote sensing and knowledge-based methods.

  7. Mapping spatial variability of foliar nitrogen in coffee (Coffea arabica L.) plantations with multispectral Sentinel-2 MSI data

    NASA Astrophysics Data System (ADS)

    Chemura, Abel; Mutanga, Onisimo; Odindi, John; Kutywayo, Dumisani

    2018-04-01

    Nitrogen (N) is the most limiting factor to coffee development and productivity. Therefore, development of rapid, spatially explicit and temporal remote sensing-based approaches to determine spatial variability of coffee foliar N are imperative for increasing yields, reducing production costs and mitigating environmental impacts associated with excessive N applications. This study sought to assess the value of Sentinel-2 MSI spectral bands and vegetation indices in empirical estimation of coffee foliar N content at landscape level. Results showed that coffee foliar N is related to Sentinel-2 MSI B4 (R2 = 0.32), B6 (R2 = 0.49), B7 (R2 = 0.42), B8 (R2 = 0.57) and B12 (R2 = 0.24) bands. Vegetation indices were more related to coffee foliar N as shown by the Inverted Red-Edge Chlorophyll Index - IRECI (R2 = 0.66), Relative Normalized Difference Index - RNDVI (R2 = 0.48), CIRE1 (R2 = 0.28), and Normalized Difference Infrared Index - NDII (R2 = 0.37). These variables were also identified by the random forest variable optimisation as the most valuable in coffee foliar N prediction. Modelling coffee foliar N using vegetation indices produced better accuracy (R2 = 0.71 with RMSE = 0.27 for all and R2 = 0.73 with RMSE = 0.25 for optimized variables), compared to using spectral bands (R2 = 0.57 with RMSE = 0.32 for all and R2 = 0.58 with RMSE = 0.32 for optimized variables). Combining optimized bands and vegetation indices produced the best results in coffee foliar N modelling (R2 = 0.78, RMSE = 0.23). All the three best performing models (all vegetation indices, optimized vegetation indices and combining optimal bands and optimal vegetation indices) established that 15.2 ha (4.7%) of the total area under investigation had low foliar N levels (<2.5%). This study demonstrates the value of Sentinel-2 MSI data, particularly vegetation indices in modelling coffee foliar N at landscape scale.

  8. Modeling circulation patterns induced by spatial cross-shore wind variability in a small-size coastal embayment

    NASA Astrophysics Data System (ADS)

    Cerralbo, Pablo; Espino, Manuel; Grifoll, Manel

    2016-08-01

    This contribution shows the importance of the cross-shore spatial wind variability in the water circulation in a small-sized micro-tidal bay. The hydrodynamic wind response at Alfacs Bay (Ebro River delta, NW Mediterranean Sea) is investigated with a numerical model (ROMS) supported by in situ observations. The wind variability observed in meteorological measurements is characterized with meteorological model (WRF) outputs. From the hydrodynamic simulations of the bay, the water circulation response is affected by the cross-shore wind variability, leading to water current structures not observed in the homogeneous-wind case. If the wind heterogeneity response is considered, the water exchange in the longitudinal direction increases significantly, reducing the water exchange time by around 20%. Wind resolutions half the size of the bay (in our case around 9 km) inhibit cross-shore wind variability, which significantly affects the resultant circulation pattern. The characteristic response is also investigated using idealized test cases. These results show how the wind curl contributes to the hydrodynamic response in shallow areas and promotes the exchange between the bay and the open sea. Negative wind curl is related to the formation of an anti-cyclonic gyre at the bay's mouth. Our results highlight the importance of considering appropriate wind resolution even in small-scale domains (such as bays or harbors) to characterize the hydrodynamics, with relevant implications in the water exchange time and the consequent water quality and ecological parameters.

  9. Distribution, abundance, and diversity of stream fishes under variable environmental conditions

    Treesearch

    Christopher M. Taylor; Thomas L. Holder; Richard A. Fiorillo; Lance R. Williams; R. Brent Thomas; Melvin L. Warren

    2006-01-01

    The effects of stream size and flow regime on spatial and temporal variability of stream fish distribution, abundance, and diversity patterns were investigated. Assemblage variability and species richness were each significantly associated with a complex environmental gradient contrasting smaller, hydrologically variable stream localities with larger localities...

  10. Range expansion through fragmented landscapes under a variable climate

    PubMed Central

    Bennie, Jonathan; Hodgson, Jenny A; Lawson, Callum R; Holloway, Crispin TR; Roy, David B; Brereton, Tom; Thomas, Chris D; Wilson, Robert J

    2013-01-01

    Ecological responses to climate change may depend on complex patterns of variability in weather and local microclimate that overlay global increases in mean temperature. Here, we show that high-resolution temporal and spatial variability in temperature drives the dynamics of range expansion for an exemplar species, the butterfly Hesperia comma. Using fine-resolution (5 m) models of vegetation surface microclimate, we estimate the thermal suitability of 906 habitat patches at the species' range margin for 27 years. Population and metapopulation models that incorporate this dynamic microclimate surface improve predictions of observed annual changes to population density and patch occupancy dynamics during the species' range expansion from 1982 to 2009. Our findings reveal how fine-scale, short-term environmental variability drives rates and patterns of range expansion through spatially localised, intermittent episodes of expansion and contraction. Incorporating dynamic microclimates can thus improve models of species range shifts at spatial and temporal scales relevant to conservation interventions. PMID:23701124

  11. Assessment of the spatial variability in tall wheatgrass forage using LANDSAT 8 satellite imagery to delineate potential management zones.

    PubMed

    Cicore, Pablo; Serrano, João; Shahidian, Shakib; Sousa, Adelia; Costa, José Luis; da Silva, José Rafael Marques

    2016-09-01

    Little information is available on the degree of within-field variability of potential production of Tall wheatgrass (Thinopyrum ponticum) forage under unirrigated conditions. The aim of this study was to characterize the spatial variability of the accumulated biomass (AB) without nutritional limitations through vegetation indexes, and then use this information to determine potential management zones. A 27-×-27-m grid cell size was chosen and 84 biomass sampling areas (BSA), each 2 m(2) in size, were georeferenced. Nitrogen and phosphorus fertilizers were applied after an initial cut at 3 cm height. At 500 °C day, the AB from each sampling area, was collected and evaluated. The spatial variability of AB was estimated more accurately using the Normalized Difference Vegetation Index (NDVI), calculated from LANDSAT 8 images obtained on 24 November 2014 (NDVInov) and 10 December 2014 (NDVIdec) because the potential AB was highly associated with NDVInov and NDVIdec (r (2)  = 0.85 and 0.83, respectively). These models between the potential AB data and NDVI were evaluated by root mean squared error (RMSE) and relative root mean squared error (RRMSE). This last coefficient was 12 and 15 % for NDVInov and NDVIdec, respectively. Potential AB and NDVI spatial correlation were quantified with semivariograms. The spatial dependence of AB was low. Six classes of NDVI were analyzed for comparison, and two management zones (MZ) were established with them. In order to evaluate if the NDVI method allows us to delimit MZ with different attainable yields, the AB estimated for these MZ were compared through an ANOVA test. The potential AB had significant differences among MZ. Based on these findings, it can be concluded that NDVI obtained from LANDSAT 8 images can be reliably used for creating MZ in soils under permanent pastures dominated by Tall wheatgrass.

  12. Research into the influence of spatial variability and scale on the parameterization of hydrological processes

    NASA Technical Reports Server (NTRS)

    Wood, Eric F.

    1993-01-01

    The objectives of the research were as follows: (1) Extend the Representative Elementary Area (RE) concept, first proposed and developed in Wood et al, (1988), to the water balance fluxes of the interstorm period (redistribution, evapotranspiration and baseflow) necessary for the analysis of long-term water balance processes. (2) Derive spatially averaged water balance model equations for spatially variable soil, topography and vegetation, over A RANGE OF CLIMATES. This is a necessary step in our goal to derive consistent hydrologic results up to GCM grid scales necessary for global climate modeling. (3) Apply the above macroscale water balance equations with remotely sensed data and begin to explore the feasibility of parameterizing the water balance constitutive equations at GCM grid scale.

  13. Spatial Variability in Enceladus' Plume Material: Convergence of Evidence or Coincidence?

    NASA Astrophysics Data System (ADS)

    Dhingra, Deepak; Hedman, Matthew M.; Clark, Roger Nelson

    2016-10-01

    Systematic spatial trends in the properties of the plume material emerging from Enceladus' tiger stripes can be observed in multiple observations from the Cassini mission. Subtle near infrared spectral differences within the plume have been reported across tiger stripes based on Visual and Infrared Mapping Spectrometer (VIMS) observations at high spatial resolution [1]. These spectral differences are likely due to variable water-ice grain size distribution along the source fissures (i.e. tiger stripes) and perhaps by the presence/absence of water vapor emission [2]. We now report a correlation of this spatial trend (along tiger stripes) with several other published results including (a) differences in the ice particle sizes across tiger stripes on Enceladus' surface [3, 4], (b) the surface abundance of organic material [3] and finally, (c) the relative proportion of type II grains (associated with organic/siliceous material) in the plume [5] from Damascus to Alexandria as measured by the Cosmic Dust Analyzer (CDA) instrument.The general trend indicates that at least some of the plume properties (viz. particle size, organic abundance) achieve a peak over Damascus and then become gradually subtle towards Alexandria. The observed differences between tiger stripes eruptions and the nature of correlations (trends from Damascus to Alexandria) hold important clues to the subsurface environment at Enceladus including differences in the geological setting of the individual tiger stripes [6]. The latter is a likely possibility given the large spatial spread of eruptions in Encealdus' South Polar Terrain (SPT).[1] Dhingra et al., (2015) 46th Lunar Planet. Sci. Conf., Abstract#1648[2] Dhingra et al. (2016) Icarus, submitted[3] Brown et al. (2006) Science, 311, 1425-1428[4] Jaumann et al. (2008) Icarus, 193, 407-419[5] Postberg et al. (2011) Nature, doi:10.1038/nature10175[6] Yin and Pappalardo (2015) Icarus, 260, 409-439

  14. Spatial and temporal variability of throughfall and soil moisture in a deciduous forest in the low mountain ranges (Hesse, Germany)

    NASA Astrophysics Data System (ADS)

    Chifflard, Peter; Weishaupt, Philipp; Reiss, Martin

    2017-04-01

    Spatial and temporal patterns of throughfall can affect the heterogeneity of ecological, biogeochemical and hydrological processes at a forest floor and further the underlying soil. Previous research suggests different factors controlling the spatial and temporal patterns of throughfall, but most studies focus on coniferous forest, where the vegetation coverage is more or less constant over time. In deciduous forests the leaf area index varies due to the leaf fall in autumn which implicates a specific spatial and temporal variability of throughfall and furthermore of the soil moisture. Therefore, in the present study, the measurements of throughfall and soil moisture in a deciduous forest in the low mountain ranges focused especially on the period of leaf fall. The aims of this study were: 1) to detect the spatial and temporal variability of both the throughfall and the soil moisture, 2) to examine the temporal stability of the spatial patterns of the throughfall and soil moisture and 3) relate the soil moisture patterns to the throughfall patterns and further to the canopy characteristics. The study was carried out in a small catchment on middle Hesse (Germany) which is covered by beech forest. Annual mean air temperature is 9.4°C (48.9˚F) and annual mean precipitation is 650 mm. Base materials for soil genesis is greywacke and clay shale from Devonian deposits. The soil type at the study plot is a shallow cambisol. The study plot covers an area of about 150 m2 where 77 throughfall samplers where installed. The throughfall and the soil moisture (FDR-method, 20 cm depth) was measured immediately after every rainfall event at the 77 measurement points. During the period of October to December 2015 altogether 7 events were investigated. The geostatistical method kriging was used to interpolate between the measurements points to visualize the spatial patterns of each investigated parameter. Time-stability-plots were applied to examine temporal scatters of each

  15. Hillslope terracing effects on the spatial variability of plant development as assessed by NDVI in vineyards of the Priorat region (NE Spain).

    PubMed

    Martínez-Casasnovas, José A; Ramos, María Concepción; Espinal-Utgés, Sílvia

    2010-04-01

    The availability of heavy machinery and the vineyard restructuring and conversion plans of the European Union Common Agricultural Policy (Commission Regulation EC no. 1227/2000 of 31 May 2000) have encouraged the restructuring of many vineyards on hillslopes of Mediterranean Europe, through the creation of terraces to favor the mechanization of agricultural work. Terrace construction requires cutting and filling operations that create soil spatial variability, which affects soil properties and plant development. In the present paper, we study the effects of hillslope terracing on the spatial variability of the normalized difference vegetation index (NDVI) in fields of the Priorat region (NE Spain) during 2004, 2005, and 2006. This index was computed from high-resolution remote sensing data (Quickbird-2). Detailed digital terrain models before and after terrace construction were used to assess the earth movements. The results indicate that terracing by heavy machinery induced high variability on the NDVI values over the years, showing significant differences as effect of the cut and fill operations.

  16. Spatial variability of organic layer thickness and carbon stocks in mature boreal forest stands--implications and suggestions for sampling designs.

    PubMed

    Kristensen, Terje; Ohlson, Mikael; Bolstad, Paul; Nagy, Zoltan

    2015-08-01

    Accurate field measurements from inventories across fine spatial scales are critical to improve sampling designs and to increase the precision of forest C cycling modeling. By studying soils undisturbed from active forest management, this paper gives a unique insight in the naturally occurring variability of organic layer C and provides valuable references against which subsequent and future sampling schemes can be evaluated. We found that the organic layer C stocks displayed great short-range variability with spatial autocorrelation distances ranging from 0.86 up to 2.85 m. When spatial autocorrelations are known, we show that a minimum of 20 inventory samples separated by ∼5 m is needed to determine the organic layer C stock with a precision of ±0.5 kg C m(-2). Our data also demonstrates a strong relationship between the organic layer C stock and horizon thickness (R (2) ranging from 0.58 to 0.82). This relationship suggests that relatively inexpensive measurements of horizon thickness can supplement soil C sampling, by reducing the number of soil samples collected, or to enhance the spatial resolution of organic layer C mapping.

  17. Individual Movement Variability Magnitudes Are Explained by Cortical Neural Variability.

    PubMed

    Haar, Shlomi; Donchin, Opher; Dinstein, Ilan

    2017-09-13

    Humans exhibit considerable motor variability even across trivial reaching movements. This variability can be separated into specific kinematic components such as extent and direction that are thought to be governed by distinct neural processes. Here, we report that individual subjects (males and females) exhibit different magnitudes of kinematic variability, which are consistent (within individual) across movements to different targets and regardless of which arm (right or left) was used to perform the movements. Simultaneous fMRI recordings revealed that the same subjects also exhibited different magnitudes of fMRI variability across movements in a variety of motor system areas. These fMRI variability magnitudes were also consistent across movements to different targets when performed with either arm. Cortical fMRI variability in the posterior-parietal cortex of individual subjects explained their movement-extent variability. This relationship was apparent only in posterior-parietal cortex and not in other motor system areas, thereby suggesting that individuals with more variable movement preparation exhibit larger kinematic variability. We therefore propose that neural and kinematic variability are reliable and interrelated individual characteristics that may predispose individual subjects to exhibit distinct motor capabilities. SIGNIFICANCE STATEMENT Neural activity and movement kinematics are remarkably variable. Although intertrial variability is rarely studied, here, we demonstrate that individual human subjects exhibit distinct magnitudes of neural and kinematic variability that are reproducible across movements to different targets and when performing these movements with either arm. Furthermore, when examining the relationship between cortical variability and movement variability, we find that cortical fMRI variability in parietal cortex of individual subjects explained their movement extent variability. This enabled us to explain why some subjects

  18. Monitoring meteorological spatial variability in viticulture using a low-cost Wireless Sensor Network

    NASA Astrophysics Data System (ADS)

    Matese, Alessandro; Crisci, Alfonso; Di Gennaro, Filippo; Primicerio, Jacopo; Tomasi, Diego; Guidoni, Silvia

    2014-05-01

    In a long-term perspective, the current global agricultural scenario will be characterize by critical issues in terms of water resource management and environmental protection. The concept of sustainable agriculture would become crucial at reducing waste, optimizing the use of pesticides and fertilizers to crops real needs. This can be achieved through a minimum-scale monitoring of the crop physiologic status and the environmental parameters that characterize the microclimate. Viticulture is often subject to high variability within the same vineyard, thus becomes important to monitor this heterogeneity to allow a site-specific management and maximize the sustainability and quality of production. Meteorological variability expressed both at vineyard scale (mesoclimate) and at single plant level (microclimate) plays an important role during the grape ripening process. The aim of this work was to compare temperature, humidity and solar radiation measurements at different spatial scales. The measurements were assessed for two seasons (2011, 2012) in two vineyards of the Veneto region (North-East Italy), planted with Pinot gris and Cabernet Sauvignon using a specially designed and developed Wireless Sensor Network (WSN). The WSN consists of various levels: the Master/Gateway level coordinates the WSN and performs data aggregation; the Farm/Server level takes care of storing data on a server, data processing and graphic rendering. Nodes level is based on a network of peripheral nodes consisting of a sensor board equipped with sensors and wireless module. The system was able to monitor the agrometeorological parameters in the vineyard: solar radiation, air temperature and air humidity. Different sources of spatial variation were studied, from meso-scale to micro-scale. A widespread investigation was conducted, building a factorial design able to evidence the role played by any factor influencing the physical environment in the vineyard, such as the surrounding climate

  19. Spatial variability of coastal wetland resilience to sea-level rise using Bayesian inference

    NASA Astrophysics Data System (ADS)

    Hardy, T.; Wu, W.

    2017-12-01

    The coastal wetlands in the Northern Gulf of Mexico (NGOM) account for 40% of coastal wetland area in the United States and provide various ecosystem services to the region and broader areas. Increasing rates of relative sea-level rise (RSLR), and reduced sediment input have increased coastal wetland loss in the NGOM, accounting for 80% of coastal wetland loss in the nation. Traditional models for predicting the impact of RSLR on coastal wetlands in the NGOM have focused on coastal erosion driven by geophysical variables only, and/or at small spatial extents. Here we developed a model in Bayesian inference to make probabilistic prediction of wetland loss in the entire NGOM as a function of vegetation productivity and geophysical attributes. We also studied how restoration efforts help maintain the area of coastal wetlands. Vegetation productivity contributes organic matter to wetland sedimentation and was approximated using the remotely sensed normalized difference moisture index (NDMI). The geophysical variables include RSLR, tidal range, river discharge, coastal slope, and wave height. We found a significantly positive relation between wetland loss and RSLR, which varied significantly at different river discharge regimes. There also existed a significantly negative relation between wetland loss and NDMI, indicating that in-situ vegetation productivity contributed to wetland resilience to RSLR. This relation did not vary significantly between river discharge regimes. The spatial relation revealed three areas of high RSLR but relatively low wetland loss; these areas were associated with wetland restoration projects in coastal Louisiana. Two projects were breakwater projects, where hard materials were placed off-shore to reduce wave action and promote sedimentation. And one project was a vegetation planting project used to promote sedimentation and wetland stabilization. We further developed an interactive web tool that allows stakeholders to develop similar wetland

  20. Spatial and temporal variability in sediment deposition and seabed character on the Waipaoa River margin, New Zealand

    NASA Astrophysics Data System (ADS)

    Walsh, J. P.; Corbett, D. R.; Kiker, J. M.; Orpin, A. R.; Hale, R. P.; Ogston, A. S.

    2014-09-01

    The stratigraphic record is the manifestation of a wide range of processes, interactions and responses to environmental drivers. Understanding the functioning of river sediment dispersal systems is necessary to determine the fate of sediment and associated material in the marine environment and differentiate key influences in the development of the stratigraphic record. To that end, this study uses sediment cores collected on four successive cruises (January, May and September 2010 and February 2011) on the Waipaoa River margin, New Zealand, to provide insight into spatial and temporal variability in sediment deposition and seabed character. The Waipaoa River discharges a large sediment load into an energetic coast that has a complex margin morphology. Several flood and wave events occurred during the study, and sedimentation varied spatially and temporally. X-radiographs and short-lived radioisotopes indicate emplacement of new event layers prior to all cruises. Notable variation in surficial seabed character (grain-size composition, loss-on-ignition percentage) was apparent on the inner shelf (water depths <40 m), but mid-shelf areas and seaward had more homogeneous sediment properties. 7Be inventories indicate variable patterns of deposition related to fluvial and oceanographic conditions prior to cruises. Ephemeral sediment storage occurs on the inner-shelf of Poverty Bay, into which the Waipaoa River discharges directly, and subsequent export and dispersal patterns are linked to the relative timing and size of flood and wave events. Surficial deposits with characteristics of fluid muds and wave-enhanced sediment gravity flows were noted at some (<25 sites total) mid-shelf and shallower sites from all cruises. During the last cruise considerable inter- and intra-site seabed variability occurred in the interbedded river-proximal inner-shelf deposits over spatial scales of less than a few kilometers. Evidence from earlier sidescan data infer that this could be

  1. Towards a More Biologically-meaningful Climate Characterization: Variability in Space and Time at Multiple Scales

    NASA Astrophysics Data System (ADS)

    Christianson, D. S.; Kaufman, C. G.; Kueppers, L. M.; Harte, J.

    2013-12-01

    Sampling limitations and current modeling capacity justify the common use of mean temperature values in summaries of historical climate and future projections. However, a monthly mean temperature representing a 1-km2 area on the landscape is often unable to capture the climate complexity driving organismal and ecological processes. Estimates of variability in addition to mean values are more biologically meaningful and have been shown to improve projections of range shifts for certain species. Historical analyses of variance and extreme events at coarse spatial scales, as well as coarse-scale projections, show increasing temporal variability in temperature with warmer means. Few studies have considered how spatial variance changes with warming, and analysis for both temporal and spatial variability across scales is lacking. It is unclear how the spatial variability of fine-scale conditions relevant to plant and animal individuals may change given warmer coarse-scale mean values. A change in spatial variability will affect the availability of suitable habitat on the landscape and thus, will influence future species ranges. By characterizing variability across both temporal and spatial scales, we can account for potential bias in species range projections that use coarse climate data and enable improvements to current models. In this study, we use temperature data at multiple spatial and temporal scales to characterize spatial and temporal variability under a warmer climate, i.e., increased mean temperatures. Observational data from the Sierra Nevada (California, USA), experimental climate manipulation data from the eastern and western slopes of the Rocky Mountains (Colorado, USA), projected CMIP5 data for California (USA) and observed PRISM data (USA) allow us to compare characteristics of a mean-variance relationship across spatial scales ranging from sub-meter2 to 10,000 km2 and across temporal scales ranging from hours to decades. Preliminary spatial analysis at

  2. Spatial and temporal variability of urban fluxes of methane, carbon monoxide and carbon dioxide above London, UK

    NASA Astrophysics Data System (ADS)

    Helfter, Carole; Tremper, Anja H.; Halios, Christoforos H.; Kotthaus, Simone; Bjorkegren, Alex; Grimmond, C. Sue B.; Barlow, Janet F.; Nemitz, Eiko

    2016-08-01

    We report on more than 3 years of measurements of fluxes of methane (CH4), carbon monoxide (CO) and carbon dioxide (CO2) taken by eddy-covariance in central London, UK. Mean annual emissions of CO2 in the period 2012-2014 (39.1 ± 2.4 ktons km-2 yr-1) and CO (89 ± 16 tons km-2 yr-1) were consistent (within 1 and 5 % respectively) with values from the London Atmospheric Emissions Inventory, but measured CH4 emissions (72 ± 3 tons km-2 yr-1) were over two-fold larger than the inventory value. Seasonal variability was large for CO with a winter to summer reduction of 69 %, and monthly fluxes were strongly anti-correlated with mean air temperature. The winter increment in CO emissions was attributed mainly to vehicle cold starts and reduced fuel combustion efficiency. CO2 fluxes were 33 % higher in winter than in summer and anti-correlated with mean air temperature, albeit to a lesser extent than for CO. This was attributed to an increased demand for natural gas for heating during the winter. CH4 fluxes exhibited moderate seasonality (21 % larger in winter), and a spatially variable linear anti-correlation with air temperature. Differences in resident population within the flux footprint explained up to 90 % of the spatial variability of the annual CO2 fluxes and up to 99 % for CH4. Furthermore, we suggest that biogenic sources of CH4, such as wastewater, which is unaccounted for by the atmospheric emissions inventories, make a substantial contribution to the overall budget and that commuting dynamics in and out of central business districts could explain some of the spatial and temporal variability of CO2 and CH4 emissions. To our knowledge, this study is unique given the length of the data sets presented, especially for CO and CH4 fluxes. This study offers an independent assessment of "bottom-up" emissions inventories and demonstrates that the urban sources of CO and CO2 are well characterized in London. This is however not the case for CH4 emissions which are

  3. Experimental assessment of the spatial variability of porosity, permeability and sorption isotherms in an ordinary building concrete

    NASA Astrophysics Data System (ADS)

    Issaadi, N.; Hamami, A. A.; Belarbi, R.; Aït-Mokhtar, A.

    2017-10-01

    In this paper, spatial variabilities of some transfer and storage properties of a concrete wall were assessed. The studied parameters deal with water porosity, water vapor permeability, intrinsic permeability and water vapor sorption isotherms. For this purpose, a concrete wall was built in the laboratory and specimens were periodically taken and tested. The obtained results allow highlighting a statistical estimation of the mean value, the standard deviation and the spatial correlation length of the studied fields for each parameter. These results were discussed and a statistical analysis was performed in order to assess for each of these parameters the appropriate probability density function.

  4. Wet-season spatial variability of N2O emissions from a tea field in subtropical central China

    NASA Astrophysics Data System (ADS)

    Fu, X.; Liu, X.; Li, Y.; Shen, J.; Wang, Y.; Zou, G.; Li, H.; Song, L.; Wu, J.

    2015-01-01

    Tea fields emit large amounts of nitrous oxide (N2O) to the atmosphere. Obtaining accurate estimations of N2O emissions from tea-planted soils is challenging due to strong spatial variability. We examined the spatial variability of N2O emissions from a red-soil tea field in Hunan province, China, on 22 April 2012 (in a wet season) using 147 static mini chambers approximately regular gridded in a 4.0 ha tea field. The N2O fluxes for a 30 min snapshot (10-10.30 a.m.) ranged from -1.73 to 1659.11 g N ha-1 d-1 and were positively skewed with an average flux of 102.24 g N ha-1 d-1. The N2O flux data were transformed to a normal distribution by using a logit function. The geostatistical analyses of our data indicated that the logit-transformed N2O fluxes (FLUX30t) exhibited strong spatial autocorrelation, which was characterized by an exponential semivariogram model with an effective range of 25.2 m. As observed in the wet season, the logit-transformed soil ammonium-N (NH4Nt), soil nitrate-N (NO3Nt), soil organic carbon (SOCt), total soil nitrogen (TSNt) were all found to be significantly correlated with FLUX30t (r=0.57-0.71, p<0.001). Three spatial interpolation methods (ordinary kriging, regression kriging and cokriging) were applied to estimate the spatial distribution of N2O emissions over the study area. Cokriging with NH4Nt and NO3Nt as covariables (r= 0.74 and RMSE =1.18) outperformed ordinary kriging (r= 0.18 and RMSE =1.74), regression kriging with the sample position as a predictor (r= 0.49 and RMSE =1.55) and cokriging with SOCt as a covariable (r= 0.58 and RMSE =1.44). The predictions of the three kriging interpolation methods for the total N2O emissions of the 4.0 ha tea field ranged from 148.2 to 208.1 g N d-1, based on the 30 min snapshots obtained during the wet season. Our findings suggested that to accurately estimate the total N2O emissions over a region, the environmental variables (e.g., soil properties) and the current land use pattern (e.g., tea

  5. Wet-season spatial variability in N2O emissions from a tea field in subtropical central China

    NASA Astrophysics Data System (ADS)

    Fu, X.; Liu, X.; Li, Y.; Shen, J.; Wang, Y.; Zou, G.; Li, H.; Song, L.; Wu, J.

    2015-06-01

    Tea fields emit large amounts of nitrous oxide (N2O) to the atmosphere. Obtaining accurate estimations of N2O emissions from tea-planted soils is challenging due to strong spatial variability. We examined the spatial variability in N2O emissions from a red-soil tea field in Hunan Province, China, on 22 April 2012 (in a wet season) using 147 static mini chambers approximately regular gridded in a 4.0 ha tea field. The N2O fluxes for a 30 min snapshot (10:00-10:30 a.m.) ranged from -1.73 to 1659.11 g N ha-1 d-1 and were positively skewed with an average flux of 102.24 g N ha-1 d-1. The N2O flux data were transformed to a normal distribution by using a logit function. The geostatistical analyses of our data indicated that the logit-transformed N2O fluxes (FLUX30t) exhibited strong spatial autocorrelation, which was characterized by an exponential semivariogram model with an effective range of 25.2 m. As observed in the wet season, the logit-transformed soil ammonium-N (NH4Nt), soil nitrate-N (NO3Nt), soil organic carbon (SOCt) and total soil nitrogen (TSNt) were all found to be significantly correlated with FLUX30t (r = 0.57-0.71, p < 0.001). Three spatial interpolation methods (ordinary kriging, regression kriging and cokriging) were applied to estimate the spatial distribution of N2O emissions over the study area. Cokriging with NH4Nt and NO3Nt as covariables (r = 0.74 and RMSE = 1.18) outperformed ordinary kriging (r = 0.18 and RMSE = 1.74), regression kriging with the sample position as a predictor (r = 0.49 and RMSE = 1.55) and cokriging with SOCt as a covariable (r = 0.58 and RMSE = 1.44). The predictions of the three kriging interpolation methods for the total N2O emissions of 4.0 ha tea field ranged from 148.2 to 208.1 g N d-1, based on the 30 min snapshots obtained during the wet season. Our findings suggested that to accurately estimate the total N2O emissions over a region, the environmental variables (e.g., soil properties) and the current land use pattern

  6. Spatial and Temporal Variability of Surface Energy Fluxes During Autumn Ice Advance: Observations and Model Validation

    NASA Astrophysics Data System (ADS)

    Persson, O. P. G.; Blomquist, B.; Grachev, A. A.; Guest, P. S.; Stammerjohn, S. E.; Solomon, A.; Cox, C. J.; Capotondi, A.; Fairall, C. W.; Intrieri, J. M.

    2016-12-01

    From Oct 4 to Nov 5, 2015, the Office of Naval Research - sponsored Sea State cruise in the Beaufort Sea with the new National Science Foundation R/V Sikuliaq obtained extensive in-situ and remote sensing observations of the lower troposphere, the advancing sea ice, wave state, and upper ocean conditions. In addition, a coupled atmosphere, sea ice, upper-ocean model, based on the RASM model, was run at NOAA/PSD in a hindcast mode for this same time period, providing a 10-day simulation of the atmosphere/ice/ocean evolution. Surface energy fluxes quantitatively represent the air-ice, air-ocean, and ice-ocean interaction processes, determining the cooling (warming) rate of the upper ocean and the growth (melting) rate of sea ice. These fluxes also impact the stratification of the lower troposphere and the upper ocean. In this presentation, both direct and indirect measurements of the energy fluxes during Sea State will be used to explore the spatial and temporal variability of these fluxes and the impacts of this variability on the upper ocean, ice, and lower atmosphere during the autumn ice advance. Analyses have suggested that these fluxes are impacted by atmospheric synoptic evolution, proximity to existing ice, ice-relative wind direction, ice thickness and snow depth. In turn, these fluxes impact upper-ocean heat loss and timing of ice formation, as well as stability in the lower troposphere and upper ocean, and hence heat transport to the free troposphere and ocean mixed-layer. Therefore, the atmospheric structure over the advancing first-year ice differs from that over the nearby open water. Finally, these observational analyses will be used to provide a preliminary validation of the spatial and temporal variability of the surface energy fluxes and the associated lower-tropospheric and upper-ocean structures in the simulations.

  7. Assimilation of temperature and hydraulic gradients for quantifying the spatial variability of streambed hydraulics

    NASA Astrophysics Data System (ADS)

    Huang, Xiang; Andrews, Charles B.; Liu, Jie; Yao, Yingying; Liu, Chuankun; Tyler, Scott W.; Selker, John S.; Zheng, Chunmiao

    2016-08-01

    Understanding the spatial and temporal characteristics of water flux into or out of shallow aquifers is imperative for water resources management and eco-environmental conservation. In this study, the spatial variability in the vertical specific fluxes and hydraulic conductivities in a streambed were evaluated by integrating distributed temperature sensing (DTS) data and vertical hydraulic gradients into an ensemble Kalman filter (EnKF) and smoother (EnKS) and an empirical thermal-mixing model. The formulation of the EnKF/EnKS assimilation scheme is based on a discretized 1D advection-conduction equation of heat transfer in the streambed. We first systematically tested a synthetic case and performed quantitative and statistical analyses to evaluate the performance of the assimilation schemes. Then a real-world case was evaluated to calculate assimilated specific flux. An initial estimate of the spatial distributions of the vertical hydraulic gradients was obtained from an empirical thermal-mixing model under steady-state conditions using a constant vertical hydraulic conductivity. Then, this initial estimate was updated by repeatedly dividing the assimilated specific flux by estimates of the vertical hydraulic gradients to obtain a refined spatial distribution of vertical hydraulic gradients and vertical hydraulic conductivities. Our results indicate that optimal parameters can be derived with fewer iterations but greater simulation effort using the EnKS compared with the EnKF. For the field application in a stream segment of the Heihe River Basin in northwest China, the average vertical hydraulic conductivities in the streambed varied over three orders of magnitude (5 × 10-1 to 5 × 102 m/d). The specific fluxes ranged from near zero (qz < ±0.05 m/d) to ±1.0 m/d, while the vertical hydraulic gradients were within the range of -0.2 to 0.15 m/m. The highest and most variable fluxes occurred adjacent to a debris-dam and bridge pier. This phenomenon is very likely

  8. Energy density and variability in abundance of pigeon guillemot prey: Support for the quality-variability trade-off hypothesis

    USGS Publications Warehouse

    Litzow, Michael A.; Piatt, John F.; Abookire, Alisa A.; Robards, Martin D.

    2004-01-01

    1. The quality-variability trade-off hypothesis predicts that (i) energy density (kJ g-1) and spatial-temporal variability in abundance are positively correlated in nearshore marine fishes; and (ii) prey selection by a nearshore piscivore, the pigeon guillemot (Cepphus columba Pallas), is negatively affected by variability in abundance. 2. We tested these predictions with data from a 4-year study that measured fish abundance with beach seines and pigeon guillemot prey utilization with visual identification of chick meals. 3. The first prediction was supported. Pearson's correlation showed that fishes with higher energy density were more variable on seasonal (r = 0.71) and annual (r = 0.66) time scales. Higher energy density fishes were also more abundant overall (r = 0.85) and more patchy at a scale of 10s of km (r = 0.77). 4. Prey utilization by pigeon guillemots was strongly non-random. Relative preference, defined as the difference between log-ratio transformed proportions of individual prey taxa in chick diets and beach seine catches, was significantly different from zero for seven of the eight main prey categories. 5. The second prediction was also supported. We used principal component analysis (PCA) to summarize variability in correlated prey characteristics (energy density, availability and variability in abundance). Two PCA scores explained 32% of observed variability in pigeon guillemot prey utilization. Seasonal variability in abundance was negatively weighted by these PCA scores, providing evidence of risk-averse selection. Prey availability, energy density and km-scale variability in abundance were positively weighted. 6. Trophic interactions are known to create variability in resource distribution in other systems. We propose that links between resource quality and the strength of trophic interactions may produce resource quality-variability trade-offs.

  9. Electrical resistivity tomography to delineate greenhouse soil variability

    NASA Astrophysics Data System (ADS)

    Rossi, R.; Amato, M.; Bitella, G.; Bochicchio, R.

    2013-03-01

    Appropriate management of soil spatial variability is an important tool for optimizing farming inputs, with the result of yield increase and reduction of the environmental impact in field crops. Under greenhouses, several factors such as non-uniform irrigation and localized soil compaction can severely affect yield and quality. Additionally, if soil spatial variability is not taken into account, yield deficiencies are often compensated by extra-volumes of crop inputs; as a result, over-irrigation and overfertilization in some parts of the field may occur. Technology for spatially sound management of greenhouse crops is therefore needed to increase yield and quality and to address sustainability. In this experiment, 2D-electrical resistivity tomography was used as an exploratory tool to characterize greenhouse soil variability and its relations to wild rocket yield. Soil resistivity well matched biomass variation (R2=0.70), and was linked to differences in soil bulk density (R2=0.90), and clay content (R2=0.77). Electrical resistivity tomography shows a great potential in horticulture where there is a growing demand of sustainability coupled with the necessity of stabilizing yield and product quality.

  10. Temporal and spatial variability of frost-free seasons in the Great Lakes region of the United States

    Treesearch

    Lejiang Yu; Shiyuan Zhong; Xindi Bian; Warren E. Heilman; Jeffrey A. Andresen

    2014-01-01

    The frequency and timing of frost events and the length of the growing season are critical limiting factors in many human and natural ecosystems. This study investigates the temporal and spatial variability of the date of last spring frost (LSF), the date of first fall frost (FFF), and the length of the frost-free season (FFS) in the Great Lakes region of the United...

  11. Short-Term Effects of Climatic Variables on Hand, Foot, and Mouth Disease in Mainland China, 2008-2013: A Multilevel Spatial Poisson Regression Model Accounting for Overdispersion.

    PubMed

    Liao, Jiaqiang; Yu, Shicheng; Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying

    2016-01-01

    Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008-2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse "V" shape and "V" shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic variables spatial heterogeneity distributed across

  12. Variability of winds and temperature in the Bergen area

    NASA Astrophysics Data System (ADS)

    Schönbein, Daniel; Ólafsson, Haraldur; Asle Olseth, Jan; Furevik, Birgitte

    2017-04-01

    In recent years, observations have been made by a dense network of automatic weather stations in the Bergen area in W-Norway (Bergen School of Meteorology). Here, cases are presented that feature large spatial variability in winds and temperature and the ability of a numerical model to reproduce this variability is assessed.

  13. Spatial Variability of Cyanobacteria and Heterotrophic Bacteria in Lake Taihu (China).

    PubMed

    Qian, Haifeng; Lu, Tao; Song, Hao; Lavoie, Michel; Xu, Jiahui; Fan, Xiaoji; Pan, Xiangliang

    2017-09-01

    Cyanobacterial blooms frequently occur in Lake Taihu (China), but the intertwined relationships between biotic and abiotic factors modulating the frequency and duration of the blooms remain enigmatic. To better understand the relationships between the key abiotic and biotic factors and cyanobacterial blooms, we measured the abundance and diversity of prokaryotic organisms by high-throughput sequencing, the abundance of key genes involved in microcystin production and nitrogen fixation or loss as well as several physicochemical parameters at several stations in Lake Taihu during a cyanobacterial bloom of Microcystis sp.. Measurements of the copy number of denitrification-related genes and 16S rRNA analyses show that denitrification potential and denitrifying bacteria abundance increased in concert with non-diazotrophic cyanobacteria (Microcystis sp.), suggesting limited competition between cyanobacteria and heterotrophic denitrifiers for nutrients, although potential bacteria-mediated N loss may hamper Microcystis growth. The present study provides insight into the importance of different abiotic and biotic factors in controlling cyanobacteria and heterotrophic bacteria spatial variability in Lake Taihu.

  14. Application of geostatistics with Indicator Kriging for analyzing spatial variability of groundwater arsenic concentrations in Southwest Bangladesh.

    PubMed

    Hassan, M Manzurul; Atkins, Peter J

    2011-01-01

    This article seeks to explore the spatial variability of groundwater arsenic (As) concentrations in Southwestern Bangladesh. Facts about spatial pattern of As are important to understand the complex processes of As concentrations and its spatial predictions in the unsampled areas of the study site. The relevant As data for this study were collected from Southwest Bangladesh and were analyzed with Flow Injection Hydride Generation Atomic Absorption Spectrometry (FI-HG-AAS). A geostatistical analysis with Indicator Kriging (IK) was employed to investigate the regionalized variation of As concentration. The IK prediction map shows a highly uneven spatial pattern of arsenic concentrations. The safe zones are mainly concentrated in the north, central and south part of the study area in a scattered manner, while the contamination zones are found to be concentrated in the west and northeast parts of the study area. The southwest part of the study area is contaminated with a highly irregular pattern. A Generalized Linear Model (GLM) was also used to investigate the relationship between As concentrations and aquifer depths. A negligible negative correlation between aquifer depth and arsenic concentrations was found in the study area. The fitted value with 95 % confidence interval shows a decreasing tendency of arsenic concentrations with the increase of aquifer depth. The adjusted mean smoothed lowess curve with a bandwidth of 0.8 shows an increasing trend of arsenic concentration up to a depth of 75 m, with some erratic fluctuations and regional variations at the depth between 30 m and 60 m. The borehole lithology was considered to analyze and map the pattern of As variability with aquifer depths. The study has performed an investigation of spatial pattern and variation of As concentrations.

  15. Albedo Spatial Variability and Causes on the Western Greenland Ice Sheet Percolation Zone

    NASA Astrophysics Data System (ADS)

    Lewis, G.; Osterberg, E. C.; Hawley, R. L.; Koffman, B. G.; Marshall, H. P.; Birkel, S. D.; Dibb, J. E.

    2016-12-01

    Many recent studies have concluded that Greenland Ice Sheet (GIS) mass loss has been accelerating over recent decades, but spatial and temporal variations in GIS mass balance remain poorly understood due to a complex relationship among precipitation and temperature changes, increasing melt and runoff, ice discharge, and surface albedo. Satellite measurements from MODerate resolution Imaging Spectroradiometer (MODIS) indicate that albedo has been declining over the past decade, but the cause and extent of GIS albedo change remains poorly constrained by field data. As fresh snow (albedo > 0.85) warms and melts, its albedo decreases due to snow grain growth, promoting solar absorption, higher snowpack temperatures and further melt. However, dark impurities like soot and dust can also significantly reduce snow albedo, even in the dry snow zone. While many regional climate models (e.g. the Regional Atmospheric Climate MOdel - RACMO2) calculate albedo spatial resolutions on the order of 10-30 km, and MODIS averages albedo over 500 m, surface features like sastrugi can affect albedo on much smaller scales. Here we assess the relative importance of grain size and shape vs. impurity concentrations on albedo in the western GIS percolation zone. We collected broadband albedo measurements (300-2500 nm at 3-8 nm resolution) at 35 locations using an ASD FieldSpec4 spectroradiometer to simultaneously quantify radiative fluxes and spectral reflectance. Measurements were collected on 10 x 10 m, 1 x 1 km, 5 x 5 km, and 10 x 10 km grids to determine the spatial variability of albedo as part of the 850-km Greenland Traverse for Accumulation and Climate Studies (GreenTrACS) traverse from Raven/Dye 2 to Summit. Additionally, we collected shallow (0-50 cm) snow pit samples every 5 cm at ASD measurement sites to quantify black carbon and mineral dust concentrations and size distributions using a Single Particle Soot Photometer and Coulter Counter, respectively. Preliminary results

  16. Spatial and Temporal Variability in Biogenic Gas Accumulation and Release in The Greater Everglades at Multiple Scales of Measurement

    NASA Astrophysics Data System (ADS)

    McClellan, M. D.; Cornett, C.; Schaffer, L.; Comas, X.

    2017-12-01

    Wetlands play a critical role in the carbon (C) cycle by producing and releasing significant amounts of greenhouse biogenic gasses (CO2, CH4) into the atmosphere. Wetlands in tropical and subtropical climates (such as the Florida Everglades) have become of great interest in the past two decades as they account for more than 20% of the global peatland C stock and are located in climates that favor year-round C emissions. Despite the increase in research involving C emission from these types of wetlands, the spatial and temporal variability involving C production, accumulation and release is still highly uncertain, and is the focus of this research at multiple scales of measurement (i.e. lab, field and landscape). Spatial variability in biogenic gas content, build up and release, at both the lab and field scales, was estimated using a series of ground penetrating radar (GPR) surveys constrained with gas traps fitted with time-lapse cameras. Variability in gas content was estimated at the sub-meter scale (lab scale) within two extracted monoliths from different wetland ecosystems at the Disney wilderness Preserve (DWP) and the Blue Cypress Preserve (BCP) using high frequency GPR (1.2 GHz) transects across the monoliths. At the field scale (> 10m) changes in biogenic gas content were estimated using 160 MHz GPR surveys collected within 4 different emergent wetlands at the DWP. Additionally, biogenic gas content from the extracted monoliths was used to developed a landscape comparison of C accumulation and emissions for each different wetland ecosystem. Changes in gas content over time were estimated at the lab scale at high temporal resolution (i.e. sub-hourly) in monoliths from the BCP and Water Conservation Area 1-A. An autonomous rail system was constructed to estimate biogenic gas content variability within the wetland soil matrix using a series of continuous, uninterrupted 1.2 GHz GPR transects along the samples. Measurements were again constrained with an array

  17. Climate variation explains a third of global crop yield variability

    PubMed Central

    Ray, Deepak K.; Gerber, James S.; MacDonald, Graham K.; West, Paul C.

    2015-01-01

    Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32–39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability. PMID:25609225

  18. Measuring Spatial Variability of Vapor Flux to Characterize Vadose-zone VOC Sources: Flow-cell Experiments

    DOE PAGES

    Mainhagu, Jon; Morrison, C.; Truex, Michael J.; ...

    2014-08-05

    A method termed vapor-phase tomography has recently been proposed to characterize the distribution of volatile organic contaminant mass in vadose-zone source areas, and to measure associated three-dimensional distributions of local contaminant mass discharge. The method is based on measuring the spatial variability of vapor flux, and thus inherent to its effectiveness is the premise that the magnitudes and temporal variability of vapor concentrations measured at different monitoring points within the interrogated area will be a function of the geospatial positions of the points relative to the source location. A series of flow-cell experiments was conducted to evaluate this premise. Amore » well-defined source zone was created by injection and extraction of a non-reactive gas (SF6). Spatial and temporal concentration distributions obtained from the tests were compared to simulations produced with a mathematical model describing advective and diffusive transport. Tests were conducted to characterize both areal and vertical components of the application. Decreases in concentration over time were observed for monitoring points located on the opposite side of the source zone from the local–extraction point, whereas increases were observed for monitoring points located between the local–extraction point and the source zone. We found that the results illustrate that comparison of temporal concentration profiles obtained at various monitoring points gives a general indication of the source location with respect to the extraction and monitoring points.« less

  19. Bayesian data fusion for spatial prediction of categorical variables in environmental sciences

    NASA Astrophysics Data System (ADS)

    Gengler, Sarah; Bogaert, Patrick

    2014-12-01

    First developed to predict continuous variables, Bayesian Maximum Entropy (BME) has become a complete framework in the context of space-time prediction since it has been extended to predict categorical variables and mixed random fields. This method proposes solutions to combine several sources of data whatever the nature of the information. However, the various attempts that were made for adapting the BME methodology to categorical variables and mixed random fields faced some limitations, as a high computational burden. The main objective of this paper is to overcome this limitation by generalizing the Bayesian Data Fusion (BDF) theoretical framework to categorical variables, which is somehow a simplification of the BME method through the convenient conditional independence hypothesis. The BDF methodology for categorical variables is first described and then applied to a practical case study: the estimation of soil drainage classes using a soil map and point observations in the sandy area of Flanders around the city of Mechelen (Belgium). The BDF approach is compared to BME along with more classical approaches, as Indicator CoKringing (ICK) and logistic regression. Estimators are compared using various indicators, namely the Percentage of Correctly Classified locations (PCC) and the Average Highest Probability (AHP). Although BDF methodology for categorical variables is somehow a simplification of BME approach, both methods lead to similar results and have strong advantages compared to ICK and logistic regression.

  20. Using hydrophones as a surrogate monitoring technique to detect temporal and spatial variability in bedload transport

    USGS Publications Warehouse

    Marineau, Mathieu D.; Minear, J. Toby; Wright, Scott A.

    2015-01-01

    Collecting physical bedload measurements is an expensive and time-consuming endeavor that rarely captures the spatial and temporal variability of sediment transport. Technological advances can improve monitoring of sediment transport by filling in temporal gaps between physical sampling periods. We have developed a low-cost hydrophone recording system designed to record the sediment-generated noise (SGN) resulting from collisions of coarse particles (generally larger than 4 mm) in gravel-bedded rivers. The sound level of the signal recorded by the hydrophone is assumed to be proportional to the magnitude of bedload transport as long as the acoustic frequency of the SGN is known, the grain-size distribution of the bedload is assumed constant, and the frequency band of the ambient noise is known and can be excluded from the analysis. Each system has two hydrophone heads and samples at half-hour intervals. Ten systems were deployed on the San Joaquin River, California, and its tributaries for ten months during water year 2014, and two systems were deployed during a flood event on the Gunnison River, Colorado in 2014. A mobile hydrophone system was also tested at both locations to collect longitudinal profiles of SGN. Physical samples of bedload were not collected in this study. In lieu of physical measurements, several audio recordings from each site were aurally reviewed to confirm the presence or absence of SGN, and hydraulic data were compared to historical measurements of bedload transport or transport capacity estimates to verify if hydraulic conditions during the study would likely produce bedload transport. At one site on the San Joaquin River, the threshold of movement was estimated to have occurred around 30 m 3 /s based on SGN data. During the Gunnison River flood event, continuous data showed clockwise hysteresis, indicating that bedload transport was generally less at any given streamflow discharge during the recession limb of the hydrograph. Spatial

  1. Spatial variability of total carbon and soil organic carbon in agricultural soils in Baranja region, Croatia

    NASA Astrophysics Data System (ADS)

    Bogunović, Igor; Trevisani, Sebastiano; Pereira, Paulo; Šeput, Miranda

    2017-04-01

    Climate change is expected to have an important influence on the crop production in agricultural regions. Soil carbon represents an important soil property that contributes to mitigate the negative influence of climate change on intensive cropped areas. Based on 5063 soil samples sampled from soil top layer (0-30 cm) we studied the spatial distribution of total carbon (TC) and soil organic carbon (SOC) content in various soil types (Anthrosols, Cambisols, Chernozems, Fluvisols, Gleysols, Luvisols) in Baranja region, Croatia. TC concentrations ranged from 2.10 to 66.15 mg/kg (with a mean of 16.31 mg/kg). SOC concentrations ranged from 1.86 to 58.00 mg/kg (with a mean of 13.35 mg/kg). TC and SOC showed moderate heterogeneity with coefficient of variation (CV) of 51.3% and 33.8%, respectively. Average concentrations of soil TC vary in function of soil types in the following decreasing order: Anthrosols (20.9 mg/kg) > Gleysols (19.3 mg/kg) > Fluvisols (15.6 mg/kg) > Chernozems (14.2 mg/kg) > Luvisols (12.6 mg/kg) > Cambisols (11.1 mg/kg), while SOC concentrations follow next order: Gleysols (15.4 mg/kg) > Fluvisols (13.2 mg/kg) = Anthrosols (13.2 mg/kg) > Chernozems (12.6 mg/kg) > Luvisols (11.4 mg/kg) > Cambisols (10.5 mg/kg). Performed geostatistical analysis of TC and SOC; both the experimental variograms as well as the interpolated maps reveal quite different spatial patterns of the two studied soil properties. The analysis of the spatial variability and of the spatial patterns of the produced maps show that SOC is likely influenced by antrophic processes. Spatial variability of SOC indicates soil health deterioration on an important significant portion of the studied area; this suggests the need for future adoption of environmentally friendly soil management in the Baranja region. Regional maps of TC and SOC provide quantitative information for regional planning and environmental monitoring and protection purposes.

  2. The spatial variable glacier mass loss over the southeast Tibet Plateau and the climate cause analyses

    NASA Astrophysics Data System (ADS)

    Ke, L.; Ding, X.; Song, C.; Sheng, Y.

    2016-12-01

    Temperate glaciers can be highly sensitive to global climate change due to relatively humid and warm local climate. Numerous temperate glaciers are distributed in the southeastern Tibet Plateau (SETP) and their changes are still poorly represented. Based on a latest glacier inventory and ICESat altimetry measurements, we examine the spatial heterogeneity of glacier change in the SETP (including the central and eastern Nyainqêntanglha ranges) and further analyze its relation with climate change by using station-based and gridded meteorological data. Our results show that SETP glaciers experienced drastic surface lowering at about -0.84±0.26 m a-1 on average over 2003-2008. Debris-covered ice thinned at an average rate of -1.13±0.32 m a-1, in comparison with -0.92±0.17 m a-1 over the debris-free ice areas. The thinning rate is the strongest in the southeastern sub-region (up to -1.24 m a-1 ) and moderate ( -0.45 m a-1 ) in the central and northwestern parts, which is in general agreement with the pattern of surface mass changes based on the GRACE gravimetry observation. Long-term climate data at weather stations show that, in comparison with the period of 1992-2002, mean temperature increased by 0.46 °C - 0.59 °C in the recent decade (2003-2013); while the change of summer precipitation exhibited remarkably spatial variability, following a southeast-northwest contrasting pattern (decreasing by over 10% in the southeast, to stable level in the central region, and increment up to 10% in the northwest). This spatially variable precipitation change is consistent with results from CN05 grid data and ERA re-analysis data, and agrees well with the spatial pattern of glacier surface elevation changes. The results suggest that overall negative glacier mass balances in SETP are governed by temperature rising, while the different precipitation change could contribute to inconsistent glacier thinning rates. The spatial pattern of precipitation decrease and mass loss might

  3. Influence of management of variables, sampling zones and land units on LR analysis for landslide spatial prevision

    NASA Astrophysics Data System (ADS)

    Greco, R.; Sorriso-Valvo, M.

    2013-09-01

    Several authors, according to different methodological approaches, have employed logistic Regression (LR), a multivariate statistical analysis adopted to assess the spatial probability of landslide, even though its fundamental principles have remained unaltered. This study aims at assessing the influence of some of these methodological approaches on the performance of LR, through a series of sensitivity analyses developed over a test area of about 300 km2 in Calabria (southern Italy). In particular, four types of sampling (1 - the whole study area; 2 - transects running parallel to the general slope direction of the study area with a total surface of about 1/3 of the whole study area; 3 - buffers surrounding the phenomena with a 1/1 ratio between the stable and the unstable area; 4 - buffers surrounding the phenomena with a 1/2 ratio between the stable and the unstable area), two variable coding modes (1 - grouped variables; 2 - binary variables), and two types of elementary land (1 - cells units; 2 - slope units) units have been tested. The obtained results must be considered as statistically relevant in all cases (Aroc values > 70%), thus confirming the soundness of the LR analysis which maintains high predictive capacities notwithstanding the features of input data. As for the area under investigation, the best performing methodological choices are the following: (i) transects produced the best results (0 < P(y) ≤ 93.4%; Aroc = 79.5%); (ii) as for sampling modalities, binary variables (0 < P(y) ≤ 98.3%; Aroc = 80.7%) provide better performance than ordinated variables; (iii) as for the choice of elementary land units, slope units (0 < P(y) ≤ 100%; Aroc = 84.2%) have obtained better results than cells matrix.

  4. Interresponse Time Structures in Variable-Ratio and Variable-Interval Schedules

    ERIC Educational Resources Information Center

    Bowers, Matthew T.; Hill, Jade; Palya, William L.

    2008-01-01

    The interresponse-time structures of pigeon key pecking were examined under variable-ratio, variable-interval, and variable-interval plus linear feedback schedules. Whereas the variable-ratio and variable-interval plus linear feedback schedules generally resulted in a distinct group of short interresponse times and a broad distribution of longer…

  5. Spatial multi-scale variability of soil nutrients in relation to environmental factors in a typical agricultural region, eastern China.

    PubMed

    Liu, Yang; Lv, Jianshu; Zhang, Bing; Bi, Jun

    2013-04-15

    Identifying the sources of spatial variability and deficiency risk of soil nutrients is a crucial issue for soil and agriculture management. A total of 1247 topsoil samples (0-20 cm) were collected at the nodes of a 2×2 km grid in Rizhao City and the contents of soil organic carbon (OC), total nitrogen (TN), and total phosphorus (TP) were determined. Factorial kriging analysis (FKA), stepwise multiple regression, and indicator kriging (IK) were appled to investigate the scale dependent correlations among soil nutrients, identify the sources of spatial variability at each spatial scale, and delineate the potential risk of soil nutrient deficiency. Linear model of co-regionalization (LMC) fitting indicated that the presence of multi-scale variation was comprised of nugget effect, an exponential structure with a range of 12 km (local scale), and a spherical structure with a range of 84 km (regional scale). The short-range variation of OC and TN was mainly dominated by land use types, and TP was controlled by terrain. At long-range scale, spatial variation of OC, TN, and TP was dominated by parent material. Indicator kriging maps depicted the probability of soil nutrient deficiency compared with the background values in eastern Shandong province. The high deficiency risk area of all nutrient integration was mainly located in eastern and northwestern parts. Copyright © 2013 Elsevier B.V. All rights reserved.

  6. Efficient Variable Selection Method for Exposure Variables on Binary Data

    NASA Astrophysics Data System (ADS)

    Ohno, Manabu; Tarumi, Tomoyuki

    In this paper, we propose a new variable selection method for "robust" exposure variables. We define "robust" as property that the same variable can select among original data and perturbed data. There are few studies of effective for the selection method. The problem that selects exposure variables is almost the same as a problem that extracts correlation rules without robustness. [Brin 97] is suggested that correlation rules are possible to extract efficiently using chi-squared statistic of contingency table having monotone property on binary data. But the chi-squared value does not have monotone property, so it's is easy to judge the method to be not independent with an increase in the dimension though the variable set is completely independent, and the method is not usable in variable selection for robust exposure variables. We assume anti-monotone property for independent variables to select robust independent variables and use the apriori algorithm for it. The apriori algorithm is one of the algorithms which find association rules from the market basket data. The algorithm use anti-monotone property on the support which is defined by association rules. But independent property does not completely have anti-monotone property on the AIC of independent probability model, but the tendency to have anti-monotone property is strong. Therefore, selected variables with anti-monotone property on the AIC have robustness. Our method judges whether a certain variable is exposure variable for the independent variable using previous comparison of the AIC. Our numerical experiments show that our method can select robust exposure variables efficiently and precisely.

  7. Spatial variability of biotic and abiotic tree establishment constraints across a treeline ecotone in the Alaska Range

    USGS Publications Warehouse

    Stueve, K.M.; Isaacs, R.E.; Tyrrell, L.E.; Densmore, R.V.

    2011-01-01

    Throughout interior Alaska (USA), a gradual warming trend in mean monthly temperatures occurred over the last few decades (;2-48C). The accompanying increases in woody vegetation at many alpine treeline (hereafter treeline) locations provided an opportunity to examine how biotic and abiotic local site conditions interact to control tree establishment patterns during warming. We devised a landscape ecological approach to investigate these relationships at an undisturbed treeline in the Alaska Range. We identified treeline changes between 1953 (aerial photography) and 2005 (satellite imagery) in a geographic information system (GIS) and linked them with corresponding local site conditions derived from digital terrain data, ancillary climate data, and distance to 1953 trees. Logistic regressions enabled us to rank the importance of local site conditions in controlling tree establishment. We discovered a spatial transition in the importance of tree establishment controls. The biotic variable (proximity to 1953 trees) was the most important tree establishment predictor below the upper tree limit, providing evidence of response lags with the abiotic setting and suggesting that tree establishment is rarely in equilibrium with the physical environment or responding directly to warming. Elevation and winter sun exposure were important predictors of tree establishment at the upper tree limit, but proximity to trees persisted as an important tertiary predictor, indicating that tree establishment may achieve equilibrium with the physical environment. However, even here, influences from the biotic variable may obscure unequivocal correlations with the abiotic setting (including temperature). Future treeline expansion will likely be patchy and challenging to predict without considering the spatial variability of influences from biotic and abiotic local site conditions. ?? 2011 by the Ecological Society of America.

  8. Spatial and seasonal characterization of net primary productivity and climate variables in southeastern China using MODIS data*

    PubMed Central

    Peng, Dai-liang; Huang, Jing-feng; Huete, Alfredo R.; Yang, Tai-ming; Gao, Ping; Chen, Yan-chun; Chen, Hui; Li, Jun; Liu, Zhan-yu

    2010-01-01

    We developed a sophisticated method to depict the spatial and seasonal characterization of net primary productivity (NPP) and climate variables. The role of climate variability in the seasonal variation of NPP exerts delayed and continuous effects. This study expands on this by mapping the seasonal characterization of NPP and climate variables from space using geographic information system (GIS) technology at the pixel level. Our approach was developed in southeastern China using moderate-resolution imaging spectroradiometer (MODIS) data. The results showed that air temperature, precipitation and sunshine percentage contributed significantly to seasonal variation of NPP. In the northern portion of the study area, a significant positive 32-d lagged correlation was observed between seasonal variation of NPP and climate (P<0.01), and the influences of changing climate on NPP lasted for 48 d or 64 d. In central southeastern China, NPP showed 16-d, 48-d, and 96-d lagged correlation with air temperature, precipitation, and sunshine percentage, respectively (P<0.01); the influences of air temperature and precipitation on NPP lasted for 48 d or 64 d, while sunshine influence on NPP only persisted for 16 d. Due to complex topography and vegetation distribution in the southern part of the study region, the spatial patterns of vegetation-climate relationship became complicated and diversiform, especially for precipitation influences on NPP. In the northern part of the study area, all vegetation NPP had an almost similar response to seasonal variation of air temperature except for broad crops. The impacts of seasonal variation of precipitation and sunshine on broad and cereal crop NPP were slightly different from other vegetation NPP. PMID:20349524

  9. Modelling spatial and temporal variability of hydrologic impacts under climate changes over the Nenjiang River Basin, China

    NASA Astrophysics Data System (ADS)

    Chen, Hao; Zhang, Wanchang

    2017-10-01

    The Variable Infiltration Capacity (VIC) hydrologic model was adopted for investigating spatial and temporal variability of hydrologic impacts of climate change over the Nenjiang River Basin (NRB) based on a set of gridded forcing dataset at 1/12th degree resolution from 1970 to 2013. Basin-scale changes in the input forcing data and the simulated hydrological variables of the NRB, as well as station-scale changes in discharges for three major hydrometric stations were examined, which suggested that the model was performed fairly satisfactory in reproducing the observed discharges, meanwhile, the snow cover and evapotranspiration in temporal and spatial patterns were simulated reasonably corresponded to the remotely sensed ones. Wetland maps produced by multi-sources satellite images covering the entire basin between 1978 and 2008 were also utilized for investigating the responses and feedbacks of hydrological regimes on wetland dynamics. Results revealed that significant decreasing trends appeared in annual, spring and autumn streamflow demonstrated strong affection of precipitation and temperature changes over the study watershed, and the effects of climate change on the runoff reduction varied in the sub-basin area over different time scales. The proportion of evapotranspiration to precipitation characterized several severe fluctuations in droughts and floods took place in the region, which implied the enhanced sensitiveness and vulnerability of hydrologic regimes to changing environment of the region. Furthermore, it was found that the different types of wetlands undergone quite unique variation features with the varied hydro-meteorological conditions over the region, such as precipitation, evapotranspiration and soil moisture. This study provided effective scientific basis for water resource managers to develop effective eco-environment management plans and strategies that address the consequences of climate changes.

  10. Spatial variability of biotic and abiotic tree establishment constraints across a treeline ecotone in the Alaska range.

    PubMed

    Stueve, Kirk M; Isaacs, Rachel E; Tyrrell, Lucy E; Densmore, Roseann V

    2011-02-01

    Throughout interior Alaska (U.S.A.), a gradual warming trend in mean monthly temperatures occurred over the last few decades (approximatlely 2-4 degrees C). The accompanying increases in woody vegetation at many alpine treeline (hereafter treeline) locations provided an opportunity to examine how biotic and abiotic local site conditions interact to control tree establishment patterns during warming. We devised a landscape ecological approach to investigate these relationships at an undisturbed treeline in the Alaska Range. We identified treeline changes between 1953 (aerial photography) and 2005 (satellite imagery) in a geographic information system (GIS) and linked them with corresponding local site conditions derived from digital terrain data, ancillary climate data, and distance to 1953 trees. Logistic regressions enabled us to rank the importance of local site conditions in controlling tree establishment. We discovered a spatial transition in the importance of tree establishment controls. The biotic variable (proximity to 1953 trees) was the most important tree establishment predictor below the upper tree limit, providing evidence of response lags with the abiotic setting and suggesting that tree establishment is rarely in equilibrium with the physical environment or responding directly to warming. Elevation and winter sun exposure were important predictors of tree establishment at the upper tree limit, but proximity to trees persisted as an important tertiary predictor, indicating that tree establishment may achieve equilibrium with the physical environment. However, even here, influences from the biotic variable may obscure unequivocal correlations with the abiotic setting (including temperature). Future treeline expansion will likely be patchy and challenging to predict without considering the spatial variability of influences from biotic and abiotic local site conditions.

  11. Spatially uniform but temporally variable bacterioplankton in a semi-enclosed coastal area.

    PubMed

    Meziti, Alexandra; Kormas, Konstantinos A; Moustaka-Gouni, Maria; Karayanni, Hera

    2015-07-01

    Studies focusing on the temporal and spatial dynamics of bacterioplankton communities within littoral areas undergoing direct influences from the coast are quite limited. In addition, they are more complicated to resolve compared to communities in the open ocean. In order to elucidate the effects of spatial vs. temporal variability on bacterial communities in a highly land-influenced semi-enclosed gulf, surface bacterioplankton communities from five coastal sites in Igoumenitsa Gulf (Ionian Sea, Greece) were analyzed over a nine-month period using 16S rDNA 454-pyrosequencing. Temporal differences were more pronounced than spatial ones, with lower diversity indices observed during the summer months. During winter and early spring, bacterial communities were dominated by SAR11 representatives, while this pattern changed in May when they were abruptly replaced by members of Flavobacteriales, Pseudomonadales, and Alteromonadales. Additionally, correlation analysis showed high negative correlations between the presence of SAR11 OTUs in relation to temperature and sunlight that might have driven, directly or indirectly, the disappearance of these OTUs in the summer months. The dominance of SAR11 during the winter months further supported the global distribution of the clade, not only in the open-sea, but also in coastal systems. This study revealed that specific bacteria exhibited distinct succession patterns in an anthropogenic-impacted coastal system. The major bacterioplankton component was represented by commonly found marine bacteria exhibiting seasonal dynamics, while freshwater and terrestrial-related phylotypes were absent. Copyright © 2015 Elsevier GmbH. All rights reserved.

  12. Deriving Surface NO2 Mixing Ratios from DISCOVER-AQ ACAM Observations: A Method to Assess Surface NO2 Spatial Variability

    NASA Astrophysics Data System (ADS)

    Silverman, M. L.; Szykman, J.; Chen, G.; Crawford, J. H.; Janz, S. J.; Kowalewski, M. G.; Lamsal, L. N.; Long, R.

    2015-12-01

    Studies have shown that satellite NO2 columns are closely related to ground level NO2 concentrations, particularly over polluted areas. This provides a means to assess surface level NO2 spatial variability over a broader area than what can be monitored from ground stations. The characterization of surface level NO2 variability is important to understand air quality in urban areas, emissions, health impacts, photochemistry, and to evaluate the performance of chemical transport models. Using data from the NASA DISCOVER-AQ campaign in Baltimore/Washington we calculate NO2 mixing ratios from the Airborne Compact Atmospheric Mapper (ACAM), through four different methods to derive surface concentration from column measurements. High spectral resolution lidar (HSRL) mixed layer heights, vertical P3B profiles, and CMAQ vertical profiles are used to scale ACAM vertical column densities. The derived NO2 mixing ratios are compared to EPA ground measurements taken at Padonia and Edgewood. We find similar results from scaling with HSRL mixed layer heights and normalized P3B vertical profiles. The HSRL mixed layer heights are then used to scale ACAM vertical column densities across the DISCOVER-AQ flight pattern to assess spatial variability of NO2 over the area. This work will help define the measurement requirements for future satellite instruments.

  13. Spatial Variability of Perchlorate along a Traverse Route from Zhongshan Station to Dome A, East Antarctica

    NASA Astrophysics Data System (ADS)

    Jiang, S.; Cole-Dai, J.; Li, Y.; An, C.

    2016-12-01

    Snow deposition and accumulation on the Antarctic ice sheet preserve records of climatic change, as well as those of chemical characteristics of the environment. Chemical composition of snow and ice cores can be used to track the sources of important substances including pollutants and to investigate relationships between atmospheric chemistry and climatic conditions. Recent development in analytical methodology has enabled the determination of ultra-trace levels of perchlorate in polar snow. We have measured perchlorate concentrations in surface snow samples collected along a traverse route from Zhongshan Station to Dome A in East Antarctica to determine the level of atmospheric perchlorate in East Antarctica and to assess the spatial variability of perchlorate along the traverse route. Results show that the perchlorate concentrations vary between 32 and 200 ng kg-1, with an average of 104.3 ng kg-1. And perchlorate concentration profile presents regional variation patterns along the traverse route. In the coastal region, perchlorate concentration displays an apparent decreasing relationship with increasing distance inland; it exhibits no apparent trend in the intermediate region from 200 to 1000 km. The inland region from 1000 to 1244 km presents a generally increasing trend of perchlorate concentration approaching the dome. Different rates of atmospheric production, dilution by snow accumulation and re-deposition of snow-emitted perchlorate (post-depositional change) are the three possible factors influencing the spatial variability of perchlorate over Antarctica.

  14. Quantifying interindividual variability and asymmetry of face-selective regions: a probabilistic functional atlas.

    PubMed

    Zhen, Zonglei; Yang, Zetian; Huang, Lijie; Kong, Xiang-Zhen; Wang, Xu; Dang, Xiaobin; Huang, Yangyue; Song, Yiying; Liu, Jia

    2015-06-01

    Face-selective regions (FSRs) are among the most widely studied functional regions in the human brain. However, individual variability of the FSRs has not been well quantified. Here we use functional magnetic resonance imaging (fMRI) to localize the FSRs and quantify their spatial and functional variabilities in 202 healthy adults. The occipital face area (OFA), posterior and anterior fusiform face areas (pFFA and aFFA), posterior continuation of the superior temporal sulcus (pcSTS), and posterior and anterior STS (pSTS and aSTS) were delineated for each individual with a semi-automated procedure. A probabilistic atlas was constructed to characterize their interindividual variability, revealing that the FSRs were highly variable in location and extent across subjects. The variability of FSRs was further quantified on both functional (i.e., face selectivity) and spatial (i.e., volume, location of peak activation, and anatomical location) features. Considerable interindividual variability and rightward asymmetry were found in all FSRs on these features. Taken together, our work presents the first effort to characterize comprehensively the variability of FSRs in a large sample of healthy subjects, and invites future work on the origin of the variability and its relation to individual differences in behavioral performance. Moreover, the probabilistic functional atlas will provide an adequate spatial reference for mapping the face network. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Large-Scale Circulation and Climate Variability. Chapter 5

    NASA Technical Reports Server (NTRS)

    Perlwitz, J.; Knutson, T.; Kossin, J. P.; LeGrande, A. N.

    2017-01-01

    The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

  16. The macro-structural variability of the human neocortex.

    PubMed

    Kruggel, Frithjof

    2018-05-15

    The human neocortex shows a considerable individual structural variability. While primary gyri and sulci are found in all normally developed brains and bear clear-cut gross structural descriptions, secondary structures are highly variable and not present in all brains. The blend of common and individual structures poses challenges when comparing structural and functional results from quantitative neuroimaging studies across individuals, and sets limits on the precision of location information much above the spatial resolution of current neuroimaging methods. This work aimed at quantifying structural variability on the neocortex, and at assessing the spatial relationship between regions common to all brains and their individual structural variants. Based on structural MRI data provided as the "900 Subjects Release" of the Human Connectome Project, a data-driven analytic approach was employed here from which the definition of seven cortical "communities" emerged. Apparently, these communities comprise common regions of structural features, while the individual variability is confined within a community. Similarities between the community structure and the state of the brain development at gestation week 32 lead suggest that communities are segregated early. Subdividing the neocortex into communities is suggested as anatomically more meaningful than the traditional lobar structure. Copyright © 2018 Elsevier Inc. All rights reserved.

  17. All varieties of encoding variability are not created equal: Separating variable processing from variable tasks

    PubMed Central

    Huff, Mark J.; Bodner, Glen E.

    2014-01-01

    Whether encoding variability facilitates memory is shown to depend on whether item-specific and relational processing are both performed across study blocks, and whether study items are weakly versus strongly related. Variable-processing groups studied a word list once using an item-specific task and once using a relational task. Variable-task groups’ two different study tasks recruited the same type of processing each block. Repeated-task groups performed the same study task each block. Recall and recognition were greatest in the variable-processing group, but only with weakly related lists. A variable-processing benefit was also found when task-based processing and list-type processing were complementary (e.g., item-specific processing of a related list) rather than redundant (e.g., relational processing of a related list). That performing both item-specific and relational processing across trials, or within a trial, yields encoding-variability benefits may help reconcile decades of contradictory findings in this area. PMID:25018583

  18. An examination of the spatial variability of the United States surface water balance using the Budyko relationship for current and projected climates

    NASA Astrophysics Data System (ADS)

    Ficklin, D. L.; Abatzoglou, J. T.

    2017-12-01

    The spatial variability in the balance between surface runoff (Q) and evapotranspiration (ET) is critical for understanding water availability. The Budyko framework suggests that this balance is solely a function of aridity. Observed deviations from this framework for individual watersheds, however, can vary significantly, resulting in uncertainty in using the Budyko framework in ungauged catchments and under future climate and land use scenarios. Here, we model the spatial variability in the partitioning of precipitation into Q and ET using a set of climatic, physiographic, and vegetation metrics for 211 near-natural watersheds across the contiguous United States (CONUS) within Budyko's framework through the free parameter ω. Using a generalized additive model, we found that precipitation seasonality, the ratio of soil water holding capacity to precipitation, topographic slope, and the fraction of precipitation falling as snow explained 81.2% of the variability in ω. This ω model applied to the Budyko framework explained 97% of the spatial variability in long-term Q for an independent set of near-natural watersheds. The developed ω model was also used to estimate the entire CONUS surface water balance for both contemporary and mid-21st century conditions. The contemporary CONUS surface water balance compared favorably to more sophisticated land-surface modeling efforts. For mid-21st century conditions, the model simulated an increase in the fraction of precipitation used by ET across the CONUS with declines in Q for much of the eastern CONUS and mountainous watersheds across the western US. The Budyko framework using the modeled ω lends itself to an alternative approach for assessing the potential response of catchment water balance to climate change to complement other approaches.

  19. Spatial and Temporal Variability of Southern Auroral Emissions in the IR from JIRAM/Juno Data

    NASA Astrophysics Data System (ADS)

    Mura, A.; Altieri, F.; Moriconi, M. L.; Adriani, A.; Grassi, D.; Migliorini, A.; Gerard, J. C. M. C.; Dinelli, B. M.; Fabiano, F.; Filacchione, G.; Sindoni, G.; Tosi, F.; Piccioni, G.; Noschese, R.; Cicchetti, A.; Sordini, R.; Bolton, S. J.; Connerney, J. E. P.; Atreya, S. K.; Levin, S.; Lunine, J. I.; Turrini, D.; Stefani, S.; Olivieri, A.; Plainaki, C.

    2017-12-01

    JIRAM (Jupiter Infrared Auroral Mapper) is the infrared imaging spectrometer on board the NASA Juno mission. The data collected since August 2016 on both Northern and Southern polar aurora at Jupiter have an unprecedented spatial. Moreover, the JIRAM scanning mirror allows observations of the same area at serveral adjacent time frames.In this work, we focus on the spatial and temporal variability of the Southern aurora. The JIRAM data of the L imager channel (3.3-3.6 µm) have been averaged in bins of 2.5°Lat × 2°Lon and variations of the signal have been investigated for 17:50 < time < 19:45, 27 August 2016. The time frames have been carefully selected in order to avoid possible instrumental residuals in the signal (Mura et al., 2017). We find that near the South Pole, for -87.5°

  20. Middle Pliocene sea surface temperature variability

    USGS Publications Warehouse

    Dowsett, H.J.; Chandler, M.A.; Cronin, T. M.; Dwyer, Gary S.

    2005-01-01

    Estimates of sea surface temperature (SST) based upon foraminifer, diatom, and ostracod assemblages from ocean cores reveal a warm phase of the Pliocene between about 3.3 and 3.0 Ma. Pollen records and plant megafossils, although not as well dated, show evidence for a warmer climate at about the same time. Increased greenhouse forcing and altered ocean heat transport are the leading candidates for the underlying cause of Pliocene global warmth. Despite being a period of global warmth, this interval encompasses considerable variability. Two new SST reconstructions are presented that are designed to provide a climatological error bar for warm peak phases of the Pliocene and to document the spatial distribution and magnitude of SST variability within the mid-Pliocene warm period. These data suggest long-term stability of low-latitude SST and document greater variability in regions of maximum warming. Copyright 2005 by the American Geophysical Union.

  1. Advances in satellite remote sensing of environmental variables for epidemiological applications.

    PubMed

    Goetz, S J; Prince, S D; Small, J

    2000-01-01

    Earth-observing satellites have provided an unprecedented view of the land surface but have been exploited relatively little for the measurement of environmental variables of particular relevance to epidemiology. Recent advances in techniques to recover continuous fields of air temperature, humidity, and vapour pressure deficit from remotely sensed observations have significant potential for disease vector monitoring and related epidemiological applications. We report on the development of techniques to map environmental variables with relevance to the prediction of the relative abundance of disease vectors and intermediate hosts. Improvements to current methods of obtaining information on vegetation properties, canopy and surface temperature and soil moisture over large areas are also discussed. Algorithms used to measure these variables incorporate visible, near-infrared and thermal infrared radiation observations derived from time series of satellite-based sensors, focused here primarily but not exclusively on the Advanced Very High Resolution Radiometer (AVHRR) instruments. The variables compare favourably with surface measurements over a broad array of conditions at several study sites, and maps of retrieved variables captured patterns of spatial variability comparable to, and locally more accurate than, spatially interpolated meteorological observations. Application of multi-temporal maps of these variables are discussed in relation to current epidemiological research on the distribution and abundance of some common disease vectors.

  2. Basin-scale heterogeneity in Antarctic precipitation and its impact on surface mass variability

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

    Fyke, Jeremy; Lenaerts, Jan T. M.; Wang, Hailong

    Annually averaged precipitation in the form of snow, the dominant term of the Antarctic Ice Sheet surface mass balance, displays large spatial and temporal variability. Here we present an analysis of spatial patterns of regional Antarctic precipitation variability and their impact on integrated Antarctic surface mass balance variability simulated as part of a preindustrial 1800-year global, fully coupled Community Earth System Model simulation. Correlation and composite analyses based on this output allow for a robust exploration of Antarctic precipitation variability. We identify statistically significant relationships between precipitation patterns across Antarctica that are corroborated by climate reanalyses, regional modeling and icemore » core records. These patterns are driven by variability in large-scale atmospheric moisture transport, which itself is characterized by decadal- to centennial-scale oscillations around the long-term mean. We suggest that this heterogeneity in Antarctic precipitation variability has a dampening effect on overall Antarctic surface mass balance variability, with implications for regulation of Antarctic-sourced sea level variability, detection of an emergent anthropogenic signal in Antarctic mass trends and identification of Antarctic mass loss accelerations.« less

  3. Basin-scale heterogeneity in Antarctic precipitation and its impact on surface mass variability

    DOE PAGES

    Fyke, Jeremy; Lenaerts, Jan T. M.; Wang, Hailong

    2017-11-15

    Annually averaged precipitation in the form of snow, the dominant term of the Antarctic Ice Sheet surface mass balance, displays large spatial and temporal variability. Here we present an analysis of spatial patterns of regional Antarctic precipitation variability and their impact on integrated Antarctic surface mass balance variability simulated as part of a preindustrial 1800-year global, fully coupled Community Earth System Model simulation. Correlation and composite analyses based on this output allow for a robust exploration of Antarctic precipitation variability. We identify statistically significant relationships between precipitation patterns across Antarctica that are corroborated by climate reanalyses, regional modeling and icemore » core records. These patterns are driven by variability in large-scale atmospheric moisture transport, which itself is characterized by decadal- to centennial-scale oscillations around the long-term mean. We suggest that this heterogeneity in Antarctic precipitation variability has a dampening effect on overall Antarctic surface mass balance variability, with implications for regulation of Antarctic-sourced sea level variability, detection of an emergent anthropogenic signal in Antarctic mass trends and identification of Antarctic mass loss accelerations.« less

  4. Spatial Variability of Trace Gases During DISCOVER-AQ: Planning for Geostationary Observations of Atmospheric Composition

    NASA Technical Reports Server (NTRS)

    Follette-Cook, Melanie B.; Pickering, K.; Crawford, J.; Appel, W.; Diskin, G.; Fried, A.; Loughner, C.; Pfister, G.; Weinheimer, A.

    2015-01-01

    Results from an in-depth analysis of trace gas variability in MD indicated that the variability in this region was large enough to be observable by a TEMPO-like instrument. The variability observed in MD is relatively similar to the other three campaigns with a few exceptions: CO variability in CA was much higher than in the other regions; HCHO variability in CA and CO was much lower; MD showed the lowest variability in NO2All model simulations do a reasonable job simulating O3 variability. For CO, the CACO simulations largely under over estimate the variability in the observations. The variability in HCHO is underestimated for every campaign. NO2 variability is slightly overestimated in MD, more so in CO. The TX simulation underestimates the variability in each trace gas. This is most likely due to missing emissions sources (C. Loughner, manuscript in preparation).Future Work: Where reasonable, we will use these model outputs to further explore the resolvability from space of these key trace gases using analyses of tropospheric column amounts relative to satellite precision requirements, similar to Follette-Cook et al. (2015).

  5. Mapping Variables.

    ERIC Educational Resources Information Center

    Stone, Mark H.; Wright, Benjamin D.; Stenner, A. Jackson

    1999-01-01

    Describes mapping variables, the principal technique for planning and constructing a test or rating instrument. A variable map is also useful for interpreting results. Provides several maps to show the importance and value of mapping a variable by person and item data. (Author/SLD)

  6. Applicability of API ZYM to capture seasonal and spatial variabilities in lake and river sediments.

    PubMed

    Patel, Drashti; Gismondi, Renee; Alsaffar, Ali; Tiquia-Arashiro, Sonia M

    2018-05-02

    Waters draining into a lake carry with them much of the suspended sediment that is transported by rivers and streams from the local drainage basin. The organic matter processing in the sediments is executed by heterotrophic microbial communities, whose activities may vary spatially and temporally. Thus, to capture and evaluate some of these variabilities in the sediments, we sampled six sites: three from the St. Clair River and three from Lake St. Clair in spring, summer, fall, and winter of 2016. At all sites and dates, we investigated the spatial and temporal variations in 19 extracellular enzyme activities using API ZYM. Our results indicated that a broad range of enzymes were found to be active in the sediments. Phosphatases, lipases, and esterases were synthesized most intensively by the sediment microbial communities. No consistent difference was found between the lake and sediment samples. Differences were more obvious between sites and seasons. Sites with the highest metabolic (enzyme) diversity reflected the capacity of the sediment microbial communities to breakdown a broader range of substrates and may be linked to differences in river and lake water quality. The seasonal variability of the enzymes activities was governed by the variations of environmental factors caused by anthropogenic and terrestrial inputs, and provides information for a better understanding of the dynamics of sediment organic matter of the river and lake ecosystems. The experimental results suggest that API ZYM is a simple and rapid enzyme assay procedure to evaluate natural processes in ecosystems and their changes.

  7. Spatial variability of the Black Sea surface temperature from high resolution modeling and satellite measurements

    NASA Astrophysics Data System (ADS)

    Mizyuk, Artem; Senderov, Maxim; Korotaev, Gennady

    2016-04-01

    Large number of numerical ocean models were implemented for the Black Sea basin during last two decades. They reproduce rather similar structure of synoptical variability of the circulation. Since 00-s numerical studies of the mesoscale structure are carried out using high performance computing (HPC). With the growing capacity of computing resources it is now possible to reconstruct the Black Sea currents with spatial resolution of several hundreds meters. However, how realistic these results can be? In the proposed study an attempt is made to understand which spatial scales are reproduced by ocean model in the Black Sea. Simulations are made using parallel version of NEMO (Nucleus for European Modelling of the Ocean). A two regional configurations with spatial resolutions 5 km and 2.5 km are described. Comparison of the SST from simulations with two spatial resolutions shows rather qualitative difference of the spatial structures. Results of high resolution simulation are compared also with satellite observations and observation-based products from Copernicus using spatial correlation and spectral analysis. Spatial scales of correlations functions for simulated and observed SST are rather close and differs much from satellite SST reanalysis. Evolution of spectral density for modelled SST and reanalysis showed agreed time periods of small scales intensification. Using of the spectral analysis for satellite measurements is complicated due to gaps. The research leading to this results has received funding from Russian Science Foundation (project № 15-17-20020)

  8. Spatial Variability of the Background Diurnal Cycle of Deep Convection around the GoAmazon2014/5 Field Campaign Sites

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

    Burleyson, Casey D.; Feng, Zhe; Hagos, Samson M.

    The Amazon rainforest is one of a few regions of the world where continental tropical deep convection occurs. The Amazon’s isolation makes it challenging to observe, but also creates a unique natural laboratory to study anthropogenic impacts on clouds and precipitation in an otherwise pristine environment. Extensive measurements were made upwind and downwind of the large city of Manaus, Brazil during the Observations and Modeling of the Green Ocean Amazon 2014-2015 (GoAmazon2014/5) field campaign. In this study, 15 years of high-resolution satellite data are analyzed to examine the spatial and diurnal variability of convection occurring around the GoAmazon2014/5 sites. Interpretationmore » of anthropogenic differences between the upwind (T0) and downwind (T1-T3) sites is complicated by naturally-occurring spatial variability between the sites. During the rainy season, the inland propagation of the previous day’s sea-breeze front happens to be in phase with the background diurnal cycle near Manaus, but is out of phase elsewhere. Enhanced convergence between the river-breezes and the easterly trade winds generates up to 10% more frequent deep convection at the GoAmazon2014/5 sites east of the river (T0a, T0t/k, and T1) compared to the T3 site which was located near the western bank. In general, the annual and diurnal cycles during 2014 were representative of the 2000-2013 distributions. The only exceptions were in March when the monthly mean rainrate was above the 95th percentile and September when both rain frequency and intensity were suppressed. The natural spatial variability must be accounted for before interpreting anthropogenically-induced differences among the GoAmazon2014/5 sites.« less

  9. The Impact of Soil Sampling Errors on Variable Rate Fertilization

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

    R. L. Hoskinson; R C. Rope; L G. Blackwood

    2004-07-01

    Variable rate fertilization of an agricultural field is done taking into account spatial variability in the soil’s characteristics. Most often, spatial variability in the soil’s fertility is the primary characteristic used to determine the differences in fertilizers applied from one point to the next. For several years the Idaho National Engineering and Environmental Laboratory (INEEL) has been developing a Decision Support System for Agriculture (DSS4Ag) to determine the economically optimum recipe of various fertilizers to apply at each site in a field, based on existing soil fertility at the site, predicted yield of the crop that would result (and amore » predicted harvest-time market price), and the current costs and compositions of the fertilizers to be applied. Typically, soil is sampled at selected points within a field, the soil samples are analyzed in a lab, and the lab-measured soil fertility of the point samples is used for spatial interpolation, in some statistical manner, to determine the soil fertility at all other points in the field. Then a decision tool determines the fertilizers to apply at each point. Our research was conducted to measure the impact on the variable rate fertilization recipe caused by variability in the measurement of the soil’s fertility at the sampling points. The variability could be laboratory analytical errors or errors from variation in the sample collection method. The results show that for many of the fertility parameters, laboratory measurement error variance exceeds the estimated variability of the fertility measure across grid locations. These errors resulted in DSS4Ag fertilizer recipe recommended application rates that differed by up to 138 pounds of urea per acre, with half the field differing by more than 57 pounds of urea per acre. For potash the difference in application rate was up to 895 pounds per acre and over half the field differed by more than 242 pounds of potash per acre. Urea and potash

  10. MOnthly TEmperature DAtabase of Spain 1951-2010: MOTEDAS (2): The Correlation Decay Distance (CDD) and the spatial variability of maximum and minimum monthly temperature in Spain during (1981-2010).

    NASA Astrophysics Data System (ADS)

    Cortesi, Nicola; Peña-Angulo, Dhais; Simolo, Claudia; Stepanek, Peter; Brunetti, Michele; Gonzalez-Hidalgo, José Carlos

    2014-05-01

    One of the key point in the develop of the MOTEDAS dataset (see Poster 1 MOTEDAS) in the framework of the HIDROCAES Project (Impactos Hidrológicos del Calentamiento Global en España, Spanish Ministery of Research CGL2011-27574-C02-01) is the reference series for which no generalized metadata exist. In this poster we present an analysis of spatial variability of monthly minimum and maximum temperatures in the conterminous land of Spain (Iberian Peninsula, IP), by using the Correlation Decay Distance function (CDD), with the aim of evaluating, at sub-regional level, the optimal threshold distance between neighbouring stations for producing the set of reference series used in the quality control (see MOTEDAS Poster 1) and the reconstruction (see MOREDAS Poster 3). The CDD analysis for Tmax and Tmin was performed calculating a correlation matrix at monthly scale between 1981-2010 among monthly mean values of maximum (Tmax) and minimum (Tmin) temperature series (with at least 90% of data), free of anomalous data and homogenized (see MOTEDAS Poster 1), obtained from AEMEt archives (National Spanish Meteorological Agency). Monthly anomalies (difference between data and mean 1981-2010) were used to prevent the dominant effect of annual cycle in the CDD annual estimation. For each station, and time scale, the common variance r2 (using the square of Pearson's correlation coefficient) was calculated between all neighbouring temperature series and the relation between r2 and distance was modelled according to the following equation (1): Log (r2ij) = b*°dij (1) being Log(rij2) the common variance between target (i) and neighbouring series (j), dij the distance between them and b the slope of the ordinary least-squares linear regression model applied taking into account only the surrounding stations within a starting radius of 50 km and with a minimum of 5 stations required. Finally, monthly, seasonal and annual CDD values were interpolated using the Ordinary Kriging with a

  11. Evolution of dispersal in spatially and temporally variable environments: The importance of life cycles.

    PubMed

    Massol, François; Débarre, Florence

    2015-07-01

    Spatiotemporal variability of the environment is bound to affect the evolution of dispersal, and yet model predictions strongly differ on this particular effect. Recent studies on the evolution of local adaptation have shown that the life cycle chosen to model the selective effects of spatiotemporal variability of the environment is a critical factor determining evolutionary outcomes. Here, we investigate the effect of the order of events in the life cycle on the evolution of unconditional dispersal in a spatially heterogeneous, temporally varying landscape. Our results show that the occurrence of intermediate singular strategies and disruptive selection are conditioned by the temporal autocorrelation of the environment and by the life cycle. Life cycles with dispersal of adults versus dispersal of juveniles, local versus global density regulation, give radically different evolutionary outcomes that include selection for total philopatry, evolutionary bistability, selection for intermediate stable states, and evolutionary branching points. Our results highlight the importance of accounting for life-cycle specifics when predicting the effects of the environment on evolutionarily selected trait values, such as dispersal, as well as the need to check the robustness of model conclusions against modifications of the life cycle. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

  12. Relating Solar Resource Variability to Cloud Type

    NASA Astrophysics Data System (ADS)

    Hinkelman, L. M.; Sengupta, M.

    2012-12-01

    Power production from renewable energy (RE) resources is rapidly increasing. Generation of renewable energy is quite variable since the solar and wind resources that form the inputs are, themselves, inherently variable. There is thus a need to understand the impact of renewable generation on the transmission grid. Such studies require estimates of high temporal and spatial resolution power output under various scenarios, which can be created from corresponding solar resource data. Satellite-based solar resource estimates are the best source of long-term solar irradiance data for the typically large areas covered by transmission studies. As satellite-based resource datasets are generally available at lower temporal and spatial resolution than required, there is, in turn, a need to downscale these resource data. Downscaling in both space and time requires information about solar irradiance variability, which is primarily a function of cloud types and properties. In this study, we analyze the relationship between solar resource variability and satellite-based cloud properties. One-minute resolution surface irradiance data were obtained from a number of stations operated by the National Oceanic and Atmospheric Administration (NOAA) under the Surface Radiation (SURFRAD) and Integrated Surface Irradiance Study (ISIS) networks as well as from NREL's Solar Radiation Research Laboratory (SRRL) in Golden, Colorado. Individual sites were selected so that a range of meteorological conditions would be represented. Cloud information at a nominal 4 km resolution and half hour intervals was derived from NOAA's Geostationary Operation Environmental Satellite (GOES) series of satellites. Cloud class information from the GOES data set was then used to select and composite irradiance data from the measurement sites. The irradiance variability for each cloud classification was characterized using general statistics of the fluxes themselves and their variability in time, as represented

  13. Observed Decrease of North American Winter Temperature Variability

    NASA Astrophysics Data System (ADS)

    Rhines, A. N.; Tingley, M.; McKinnon, K. A.; Huybers, P. J.

    2015-12-01

    There is considerable interest in determining whether temperature variability has changed in recent decades. Model ensembles project that extratropical land temperature variance will detectably decrease by 2070. We use quantile regression of station observations to show that decreasing variability is already robustly detectable for North American winter during 1979--2014. Pointwise trends from GHCND stations are mapped into a continuous spatial field using thin-plate spline regression, resolving small-scales while providing uncertainties accounting for spatial covariance and varying station density. We find that variability of daily temperatures, as measured by the difference between the 95th and 5th percentiles, has decreased markedly in winter for both daily minima and maxima. Composites indicate that the reduced spread of winter temperatures primarily results from Arctic amplification decreasing the meridional temperature gradient. Greater observed warming in the 5th relative to the 95th percentile stems from asymmetric effects of advection during cold versus warm days; cold air advection is generally from northerly regions that have experienced greater warming than western or southwestern regions that are generally sourced during warm days.

  14. Satellite Analysis of Ocean Biogeochemistry and Mesoscale Variability in the Sargasso Sea

    NASA Technical Reports Server (NTRS)

    Siegel, D. A.; Micheals, A. F.; Nelson, N. B.

    1997-01-01

    The objective of this study was to analyze the impact of spatial variability on the time-series of biogeochemical measurements made at the U.S. JGOFS Bermuda Atlantic Time-series Study (BATS) site. Originally the study was planned to use SeaWiFS as well as AVHRR high-resolution data. Despite the SeaWiFS delays we were able to make progress on the following fronts: (1) Operational acquisition, processing, and archive of HRPT data from a ground station located in Bermuda; (2) Validation of AVHRR SST data using BATS time-series and spatial validation cruise CTD data; (3) Use of AVHRR sea surface temperature imagery and ancillary data to assess the impact of mesoscale spatial variability on P(CO2) and carbon flux in the Sargasso Sea; (4) Spatial and temporal extent of tropical cyclone induced surface modifications; and (5) Assessment of eddy variability using TOPEX/Poseidon data.

  15. Spatiotemporal Variability of Hillslope Soil Moisture Across Steep, Highly Dissected Topography

    NASA Astrophysics Data System (ADS)

    Jarecke, K. M.; Wondzell, S. M.; Bladon, K. D.

    2016-12-01

    Hillslope ecohydrological processes, including subsurface water flow and plant water uptake, are strongly influenced by soil moisture. However, the factors controlling spatial and temporal variability of soil moisture in steep, mountainous terrain are poorly understood. We asked: How do topography and soils interact to control the spatial and temporal variability of soil moisture in steep, Douglas-fir dominated hillslopes in the western Cascades? We will present a preliminary analysis of bimonthly soil moisture variability from July-November 2016 at 0-30 and 0-60 cm depth across spatially extensive convergent and divergent topographic positions in Watershed 1 of the H.J. Andrews Experimental Forest in central Oregon. Soil moisture monitoring locations were selected following a 5 m LIDAR analysis of topographic position, aspect, and slope. Topographic position index (TPI) was calculated as the difference in elevation to the mean elevation within a 30 m radius. Convergent (negative TPI values) and divergent (positive TPI values) monitoring locations were established along northwest to northeast-facing aspects and within 25-55 degree slopes. We hypothesized that topographic position (convergent vs. divergent), as well as soil physical properties (e.g., texture, bulk density), control variation in hillslope soil moisture at the sub-watershed scale. In addition, we expected the relative importance of hillslope topography to the spatial variability in soil moisture to differ seasonally. By comparing the spatiotemporal variability of hillslope soil moisture across topographic positions, our research provides a foundation for additional understanding of subsurface flow processes and plant-available soil-water in forests with steep, highly dissected terrain.

  16. Assessing the accuracy and stability of variable selection ...

    EPA Pesticide Factsheets

    Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used, or stepwise procedures are employed which iteratively add/remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating dataset consists of the good/poor condition of n=1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p=212) of landscape features from the StreamCat dataset. Two types of RF models are compared: a full variable set model with all 212 predictors, and a reduced variable set model selected using a backwards elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors, and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substanti

  17. LTP saturation and spatial learning disruption: effects of task variables and saturation levels.

    PubMed

    Barnes, C A; Jung, M W; McNaughton, B L; Korol, D L; Andreasson, K; Worley, P F

    1994-10-01

    The prediction that "saturation" of LTP/LTE at hippocampal synapses should impair spatial learning was reinvestigated in the light of a more specific consideration of the theory of Hebbian associative networks, which predicts a nonlinear relationship between LTP "saturation" and memory impairment. This nonlinearity may explain the variable results of studies that have addressed the effects of LTP "saturation" on behavior. The extent of LTP "saturation" in fascia dentata produced by the standard chronic LTP stimulation protocol was assessed both electrophysiologically and through the use of an anatomical marker (activation of the immediate-early gene zif268). Both methods point to the conclusion that the standard protocols used to induce LTP do not "saturate" the process at any dorsoventral level, and leave the ventral half of the hippocampus virtually unaffected. LTP-inducing, bilateral perforant path stimulation led to a significant deficit in the reversal of a well-learned spatial response on the Barnes circular platform task as reported previously, yet in the same animals produced no deficit in learning the Morris water task (for which previous results have been conflicting). The behavioral deficit was not a consequence of any after-discharge in the hippocampal EEG. In contrast, administration of maximal electroconvulsive shock led to robust zif268 activation throughout the hippocampus, enhancement of synaptic responses, occlusion of LTP produced by discrete high-frequency stimulation, and spatial learning deficits in the water task. These data provide further support for the involvement of LTP-like synaptic enhancement in spatial learning.

  18. Spatial and Temporal Variabilities of Solar and Longwave Radiation Fluxes below a Coniferous Forest in the French Alps

    NASA Astrophysics Data System (ADS)

    Sicart, J. E.; Ramseyer, V.; Lejeune, Y.; Essery, R.; Webster, C.; Rutter, N.

    2017-12-01

    At high altitudes and latitudes, snow has a large influence on hydrological processes. Large fractions of these regions are covered by forests, which have a strong influence on snow accumulation and melting processes. Trees absorb a large part of the incoming shortwave radiation and this heat load is mostly dissipated as longwave radiation. Trees shelter the snow surface from wind, so sub-canopy snowmelt depends mainly on the radiative fluxes: vegetation attenuates the transmission of shortwave radiation but enhances longwave irradiance to the surface. An array of 13 pyranometers and 11 pyrgeometers was deployed on the snow surface below a coniferous forest at the CEN-MeteoFrance Col de Porte station in the French Alps (1325 m asl) during the 2017 winter in order to investigate spatial and temporal variabilities of solar and infrared irradiances in different meteorological conditions. Sky view factors measured with hemispherical photographs at each radiometer location were in a narrow range from 0.2 to 0.3. The temperature of the vegetation was measured with IR thermocouples and an IR camera. In clear sky conditions, the attenuation of solar radiation by the canopy reached 96% and its spatial variability exceeded 100 W m-2. Longwave irradiance varied by 30 W m-2 from dense canopy to gap areas. In overcast conditions, the spatial variabilities of solar and infrared irradiances were reduced and remained closely related to the sky view factor. A simple radiative model taking into account the penetration through the canopy of the direct and diffuse solar radiation, and isotropic infrared emission of the vegetation as a blackbody emitter, accurately reproduced the dynamics of the radiation fluxes at the snow surface. Model results show that solar transmissivity of the canopy in overcast conditions is an excellent proxy of the sky view factor and the emitting temperature of the vegetation remained close to the air temperature in this typically dense Alpine forest.

  19. Performance analysis of improved methodology for incorporation of spatial/spectral variability in synthetic hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Scanlan, Neil W.; Schott, John R.; Brown, Scott D.

    2004-01-01

    Synthetic imagery has traditionally been used to support sensor design by enabling design engineers to pre-evaluate image products during the design and development stages. Increasingly exploitation analysts are looking to synthetic imagery as a way to develop and test exploitation algorithms before image data are available from new sensors. Even when sensors are available, synthetic imagery can significantly aid in algorithm development by providing a wide range of "ground truthed" images with varying illumination, atmospheric, viewing and scene conditions. One limitation of synthetic data is that the background variability is often too bland. It does not exhibit the spatial and spectral variability present in real data. In this work, four fundamentally different texture modeling algorithms will first be implemented as necessary into the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model environment. Two of the models to be tested are variants of a statistical Z-Score selection model, while the remaining two involve a texture synthesis and a spectral end-member fractional abundance map approach, respectively. A detailed comparative performance analysis of each model will then be carried out on several texturally significant regions of the resultant synthetic hyperspectral imagery. The quantitative assessment of each model will utilize a set of three peformance metrics that have been derived from spatial Gray Level Co-Occurrence Matrix (GLCM) analysis, hyperspectral Signal-to-Clutter Ratio (SCR) measures, and a new concept termed the Spectral Co-Occurrence Matrix (SCM) metric which permits the simultaneous measurement of spatial and spectral texture. Previous research efforts on the validation and performance analysis of texture characterization models have been largely qualitative in nature based on conducting visual inspections of synthetic textures in order to judge the degree of similarity to the original sample texture imagery. The quantitative

  20. Performance analysis of improved methodology for incorporation of spatial/spectral variability in synthetic hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Scanlan, Neil W.; Schott, John R.; Brown, Scott D.

    2003-12-01

    Synthetic imagery has traditionally been used to support sensor design by enabling design engineers to pre-evaluate image products during the design and development stages. Increasingly exploitation analysts are looking to synthetic imagery as a way to develop and test exploitation algorithms before image data are available from new sensors. Even when sensors are available, synthetic imagery can significantly aid in algorithm development by providing a wide range of "ground truthed" images with varying illumination, atmospheric, viewing and scene conditions. One limitation of synthetic data is that the background variability is often too bland. It does not exhibit the spatial and spectral variability present in real data. In this work, four fundamentally different texture modeling algorithms will first be implemented as necessary into the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model environment. Two of the models to be tested are variants of a statistical Z-Score selection model, while the remaining two involve a texture synthesis and a spectral end-member fractional abundance map approach, respectively. A detailed comparative performance analysis of each model will then be carried out on several texturally significant regions of the resultant synthetic hyperspectral imagery. The quantitative assessment of each model will utilize a set of three peformance metrics that have been derived from spatial Gray Level Co-Occurrence Matrix (GLCM) analysis, hyperspectral Signal-to-Clutter Ratio (SCR) measures, and a new concept termed the Spectral Co-Occurrence Matrix (SCM) metric which permits the simultaneous measurement of spatial and spectral texture. Previous research efforts on the validation and performance analysis of texture characterization models have been largely qualitative in nature based on conducting visual inspections of synthetic textures in order to judge the degree of similarity to the original sample texture imagery. The quantitative

  1. Spatial variability of drinking water iodine in Denmark: implications for future policy making

    NASA Astrophysics Data System (ADS)

    Voutchkova, Denitza; Ernstsen, Vibeke; Kristiansen, Søren; Hansen, Birgitte

    2014-05-01

    The iodine-an essential component of human thyroid hormones-is provided to our organisms naturally from the food and water and/or is added artificially to the diet. One of the major natural contributors to the dietary iodine intake in Denmark is the drinking water. Both insufficient or excessive iodine intake can cause health problems however the attention falls mainly on the iodine deficiency (ID). Denmark is classified to have mild ID, which is based on sub-national data only. On a bigger scale, in Europe, about 40% of the general population is estimated to suffer from insufficient iodine intake (based on recent update on the iodine status worldwide). A mandatory addition of iodine to the salt was introduced in 2001 in Denmark to address the population's mild deficiency. One of the components of the Danish monitoring program investigating the effect of the salt iodizing (DanThyr) was based on the geographical variation of drinking water iodine levels. More specifically, the location of the two DanThyr cohort studies was chosen to reflect the low concentrations in the western part of Denmark and higher concentration in the eastern part. However, the knowledge about the spatial variability of iodine in Danish ground- and drinking water at that time was quite limited and misrepresentation of the natural variability is suspected. The presented sampling campaign was completed in 2013, and includes 144 waterworks with annual abstraction of about 175 mio m3 groundwater (~45% of the total groundwater abstraction by all active public and private Danish waterworks). The results show a surprisingly complex spatial pattern concerning both the iodine concentrations and speciation. By estimating the dietary iodine intake from water and comparing it to the WHO recommendations, it becomes possible to recognize potentially deficient/excessive geographical areas. Moreover, it is demonstrated that drinking water iodine levels (major dietary iodine contributor in Denmark) can be

  2. Passive microwave derived snowmelt timing: significance, spatial and temporal variability, and potential applications

    NASA Astrophysics Data System (ADS)

    Semmens, Kathryn Alese

    Snow accumulation and melt are dynamic features of the cryosphere indicative of a changing climate. Spring melt and refreeze timing are of particular importance due to the influence on subsequent hydrological and ecological processes, including peak runoff and green-up. To investigate the spatial and temporal variability of melt timing across a sub-arctic region (the Yukon River Basin (YRB), Alaska/Canada) dominated by snow and lacking substantial ground instrumentation, passive microwave remote sensing was utilized to provide daily brightness temperatures (Tb) regardless of clouds and darkness. Algorithms to derive the timing of melt onset and the end of melt-refreeze, a critical transition period where the snowpack melts during the day and refreezes at night, were based on thresholds for Tb and diurnal amplitude variations (day and night difference). Tb data from the Special Sensor Microwave Imager (1988 to 2011) was used for analyzing YRB terrestrial snowmelt timing and for characterizing melt regime patterns for icefields in Alaska and Patagonia. Tb data from the Advanced Microwave Scanning Radiometer for EOS (2003 to 2010) was used for determining the occurrence of early melt events (before melt onset) associated with fog or rain on snow, for investigating the correlation between melt timing and forest fires, and for driving a flux-based snowmelt runoff model. From the SSM/I analysis: the melt-refreeze period lengthened for the majority of the YRB with later end of melt-refreeze and earlier melt onset; and positive Tb anomalies were found in recent years from glacier melt dynamics. From the AMSR-E analysis: early melt events throughout the YRB were most often associated with warm air intrusions and reflect a consistent spatial distribution; years and areas of earlier melt onset and refreeze had more forest fire occurrences suggesting melt timing's effects extend to later seasons; and satellite derived melt timing served as an effective input for model

  3. Geomorphic and substrate controls on spatial variability in river solute transport and biogeochemical cycling

    NASA Astrophysics Data System (ADS)

    Blaen, Phillip; Kurz, Marie; Knapp, Julia; Mendoza-Lera, Clara; Lee-Cullin, Joe; Klaar, Megan; Drummond, Jen; Jaeger, Anna; Zarnetske, Jay; Lewandowski, Joerg; Marti, Eugenia; Ward, Adam; Fleckenstein, Jan; Datry, Thibault; Larned, Scott; Krause, Stefan

    2016-04-01

    Nutrient concentrations in surface waters and groundwaters are increasing in many agricultural catchments worldwide as a result of anthropogenic activities. Increasing geomorphological heterogeneity in river channels may help to attenuate nutrient pollution by facilitating water exchange fluxes with the hyporheic zone; a site of intense microbial activity where biogeochemical transformation rates (e.g. denitrification) can be high. However, the controls on spatial variability in biogeochemical cycling, particularly at scales relevant for river managers, are not well understood. Here, we aimed to assess: 1) how differences in geomorphological heterogeneity control river solute transport and rates of biogeochemical cycling at sub-reach scales (102 m); and 2) the relative magnitude of these differences versus those relating to reach scale substrate variability (103 m). We used the reactive 'smart' tracer resazurin (Raz), a weakly fluorescent dye that transforms to highly fluorescent resorufin (Rru) under mildly reducing conditions, as a proxy to assess rates of biogeochemical cycling in a lowland river in southern England. Solute tracer tests were conducted in two reaches with contrasting substrates: one sand-dominated and the other gravel-dominated. Each reach was divided into sub-reaches that varied in geomorphic complexity (e.g. by the presence of pool-riffle sequences or the abundance of large woody debris). Slug injections of Raz and the conservative tracer fluorescein were conducted in each reach during baseflow conditions (Q ≈ 80 L/s) and breakthrough curves monitored using in-situ fluorometers. Preliminary results indicate overall Raz:Rru transformation rates in the gravel-dominated reach were more than 50% higher than those in the sand-dominated reach. However, high sub-reach variability in Raz:Rru transformation rates and conservative solute transport parameters suggests small-scale targeted management interventions to alter geomorphic heterogeneity may be

  4. Improving understanding of controls on spatial variability in methane fluxes in Arctic tundra

    NASA Astrophysics Data System (ADS)

    Davidson, Scott J.; Sloan, Victoria; Phoenix, Gareth; Wagner, Robert; Oechel, Walter; Zona, Donatella

    2015-04-01

    The Arctic is experiencing rapid climate change relative to the rest of the globe, and this increase in temperature has feedback effects across hydrological and thermal regimes, plant community distribution and carbon stocks within tundra soils. Arctic wetlands account for a significant amount of methane emissions from natural ecosystems to the atmosphere and with further permafrost degradation under a warming climate, these emissions are expected to increase. Methane (CH4) is an extremely important component of the global carbon cycle with a global warming potential 28.5 times greater than carbon dioxide over a 100 year time scale (IPCC, 2013). In order to validate carbon cycle models, modelling methane at broader landscape scales is needed. To date direct measurements of methane have been sporadic in time and space which, while capturing some key controls on the spatial heterogeneity, make it difficult to accurately upscale methane emissions to the landscape and regional scales. This study investigates what is controlling the spatial heterogeneity of methane fluxes across Arctic tundra. We combined over 300 portable chamber observations from 13 micro-topographic positions (with multiple vegetation types) across three locations spanning a 300km latitudinal gradient in Northern Alaska from Barrow to Ivotuk with synchronous measurements of environmental (soil temperature, soil moisture, water table, active layer thaw depth, pH) and vegetation (plant community composition, height, sedge tiller counts) variables to evaluate key controls on methane fluxes. To assess the diurnal variation in CH4 fluxes, we also performed automated chamber measurements in one study site (Barrow) location. Multiple statistical approaches (regression tree and multiple linear regression) were used to identify key controlling variables and their interactions. Methane emissions across all sites ranged from -0.08 to 15.3 mg C-CH4 m-2 hr-1. As expected, soil moisture was the main control

  5. Aspect-related Vegetation Differences Amplify Soil Moisture Variability in Semiarid Landscapes

    NASA Astrophysics Data System (ADS)

    Yetemen, O.; Srivastava, A.; Kumari, N.; Saco, P. M.

    2017-12-01

    Soil moisture variability (SMV) in semiarid landscapes is affected by vegetation, soil texture, climate, aspect, and topography. The heterogeneity in vegetation cover that results from the effects of microclimate, terrain attributes (slope gradient, aspect, drainage area etc.), soil properties, and spatial variability in precipitation have been reported to act as the dominant factors modulating SMV in semiarid ecosystems. However, the role of hillslope aspect in SMV, though reported in many field studies, has not received the same degree of attention probably due to the lack of extensive large datasets. Numerical simulations can then be used to elucidate the contribution of aspect-driven vegetation patterns to this variability. In this work, we perform a sensitivity analysis to study on variables driving SMV using the CHILD landscape evolution model equipped with a spatially-distributed solar-radiation component that couples vegetation dynamics and surface hydrology. To explore how aspect-driven vegetation heterogeneity contributes to the SMV, CHILD was run using a range of parameters selected to reflect different scenarios (from uniform to heterogeneous vegetation cover). Throughout the simulations, the spatial distribution of soil moisture and vegetation cover are computed to estimate the corresponding coefficients of variation. Under the uniform spatial precipitation forcing and uniform soil properties, the factors affecting the spatial distribution of solar insolation are found to play a key role in the SMV through the emergence of aspect-driven vegetation patterns. Hence, factors such as catchment gradient, aspect, and latitude, define water stress and vegetation growth, and in turn affect the available soil moisture content. Interestingly, changes in soil properties (porosity, root depth, and pore-size distribution) over the domain are not as effective as the other factors. These findings show that the factors associated to aspect-related vegetation

  6. The test-retest reliability and minimal detectable change of spatial and temporal gait variability during usual over-ground walking for younger and older adults.

    PubMed

    Almarwani, Maha; Perera, Subashan; VanSwearingen, Jessie M; Sparto, Patrick J; Brach, Jennifer S

    2016-02-01

    Gait variability is a marker of gait performance and future mobility status in older adults. Reliability of gait variability has been examined mainly in community dwelling older adults who are likely to fluctuate over time. The purpose of this study was to compare test-retest reliability and determine minimal detectable change (MDC) of spatial and temporal gait variability in younger and older adults. Forty younger (mean age=26.6 ± 6.0 years) and 46 older adults (mean age=78.1 ± 6.2 years) were included in the study. Gait characteristics were measured twice, approximately 1 week apart, using a computerized walkway (GaitMat II). Participants completed 4 passes on the GaitMat II at their self-selected walking speed. Test-retest reliability was calculated using Intra-class correlation coefficients (ICCs(2,1)), 95% limits of agreement (95% LoA) in conjunction with Bland-Altman plots, relative limits of agreement (LoA%) and standard error of measurement (SEM). The MDC at 90% and 95% level were also calculated. ICCs of gait variability ranged 0.26-0.65 in younger and 0.28-0.74 in older adults. The LoA% and SEM were consistently higher (i.e. less reliable) for all gait variables in older compared to younger adults except SEM for step width. The MDC was consistently larger for all gait variables in older compared to younger adults except step width. ICCs were of limited utility due to restricted ranges in younger adults. Based on absolute reliability measures and MDC, younger had greater test-retest reliability and smaller MDC of spatial and temporal gait variability compared to older adults. Copyright © 2015 Elsevier B.V. All rights reserved.

  7. Capability of Hyperspectral data in Spatial Variability Distribution of Chlorophyll and Water Stress in Rice Agriculture System

    NASA Astrophysics Data System (ADS)

    Moharana, S.; Dutta, S.

    2016-12-01

    Abstract : The mapping and analysis of spatial variability within the field is a challenging task. However, field variability of a single vegetation cover does not give satisfactory results mainly due to low spectral resolution and non-availability of remote sensing data. From the NASA Earth Observing-1 (EO-1) satellite data, spatial distribution of biophysical parameters like chlorophyll and relative water content in a rice agriculture system is carried out in the present study. Hyperion L1R product composed of 242 spectral bands with 30m spatial resolution was acquired for Assam, India. This high dimensional data is allowed for pre-processing to get an atmospherically corrected imagery. Moreover, ground based hyperspectral measurements are collected from experimental rice fields from the study site using hand held ASD spectroradiometer (350-1050 nm). Published indices specifically designed for chlorophyll (OASVI, mSR, and MTCI indices) and water content (WI and WBI indices) are selected based on stastical performance of the in-situ hyperspectral data. Index models are established for the respective biophysical parameters and observed that the aforementioned indices followed different linear and nonlinear relationships which are completely different from the published indices. By employing the presently developed relationships, spatial variation of total chlorophyll and water stress are mapped for a rice agriculture system from Hyperion imagery. The findings showed that, the variation of chlorophyll and water content ranged from 1.77-10.61mg/g and 40-90% respectively for the studied rice agriculture system. The spatial distribution of these parameters resulted from presently developed index models are well captured from Hyperion imagery and they have good agreement with observed field based chlorophyll (1.14-7.26 mg/g) and water content (60-95%) of paddy crop. This study can be useful in providing essential information to assess the paddy field heterogeneity in an

  8. Spatial variability of soil water content in the covered catchment at Gårdsjön, Sweden

    NASA Astrophysics Data System (ADS)

    Nyberg, Lars

    1996-01-01

    The spatial variability of soil water content was investigated for a 6300 m2 covered catchment on the Swedish west coast. The catchment podzol soil is developed in a sandy - silty till with a mean depth of 43 cm and the dominant vegetation is Norway spruce. The acid precipitation is removed by a plastic roof and replaced with lake water irrigated under the tree canopies. On two occasions, in April and May 1993, TDR measurements were made at 57-73 points in the catchment using 15 and 30 cm long vertically installed probes. The water content pattern at the two dates, which occurred during a relatively dry period, were similar. The range of water content was large, from 5 to 60%. In May 1993 measurements also were made in areas of 10 × 10 m, 1 × 1 m and 0·2 × 0·2 m. The range and standard deviation for the 10 × 10 m area, which apart from a small-scale variability in soil hydraulic properties and fine root distribution also had a heterogeneous micro- and macro-topography, was similar to the range and standard deviation for the catchment. The 1 × 1 m and 0·2 × 0·2 m areas had considerably lower variability. Semi-variogram models for the water content had a range of influence of about 20 m. If data were paired in the east--west direction the semi-variance reflected the topography of the central valley and had a maximum for data pairs with internal distances of 20-40 m. The correlation between soil water content and topographic index, especially when averaged for the eight topographically homogeneous subareas, indicated the macro-topography as the cause of a large part of the water content variability.

  9. Impact of Hydrologic and Micro-topographic Variabilities on Spatial Distribution of Mean Soil-Nitrogen Age

    NASA Astrophysics Data System (ADS)

    Woo, D.; Kumar, P.

    2015-12-01

    Excess reactive nitrogen in soils of intensively managed agricultural fields causes adverse environmental impact, and continues to remain a global concern. Many novel strategies have been developed to provide better management practices and, yet, the problem remains unresolved. The objective of this study is to develop a 3-dimensional model to characterize the spatially distributed ``age" of soil-nitrogen (nitrate and ammonia-ammonium) across a watershed. We use the general theory of age, which provides an assessment of the elapsed time since nitrogen is introduced into the soil system. Micro-topographic variability incorporates heterogeneity of nutrient transformations and transport associated with topographic depressions that form temporary ponds and produce prolonged periods of anoxic conditions, and roadside agricultural ditches that support rapid surface movement. This modeling effort utilizes 1-m Light Detection and Ranging (LiDAR) data. We find a significant correlation between hydrologic variability and mean nitrate age that enables assessment of preferential flow paths of nitrate leaching. The estimation of the mean nitrogen age can thus serve as a tool to disentangle complex nitrogen dynamics by providing the analysis of the time scales of soil-nitrogen transformation and transport processes without introducing additional parameters.

  10. Dynamics and spatio-temporal variability of environmental factors in Eastern Australia using functional principal component analysis

    USGS Publications Warehouse

    Szabo, J.K.; Fedriani, E.M.; Segovia-Gonzalez, M. M.; Astheimer, L.B.; Hooper, M.J.

    2010-01-01

    This paper introduces a new technique in ecology to analyze spatial and temporal variability in environmental variables. By using simple statistics, we explore the relations between abiotic and biotic variables that influence animal distributions. However, spatial and temporal variability in rainfall, a key variable in ecological studies, can cause difficulties to any basic model including time evolution. The study was of a landscape scale (three million square kilometers in eastern Australia), mainly over the period of 19982004. We simultaneously considered qualitative spatial (soil and habitat types) and quantitative temporal (rainfall) variables in a Geographical Information System environment. In addition to some techniques commonly used in ecology, we applied a new method, Functional Principal Component Analysis, which proved to be very suitable for this case, as it explained more than 97% of the total variance of the rainfall data, providing us with substitute variables that are easier to manage and are even able to explain rainfall patterns. The main variable came from a habitat classification that showed strong correlations with rainfall values and soil types. ?? 2010 World Scientific Publishing Company.

  11. Spatial variability in levels of benzene, formaldehyde, and total benzene, toluene, ethylbenzene and xylenes in New York City: a land-use regression study.

    PubMed

    Kheirbek, Iyad; Johnson, Sarah; Ross, Zev; Pezeshki, Grant; Ito, Kazuhiko; Eisl, Holger; Matte, Thomas

    2012-07-31

    Hazardous air pollutant exposures are common in urban areas contributing to increased risk of cancer and other adverse health outcomes. While recent analyses indicate that New York City residents experience significantly higher cancer risks attributable to hazardous air pollutant exposures than the United States as a whole, limited data exist to assess intra-urban variability in air toxics exposures. To assess intra-urban spatial variability in exposures to common hazardous air pollutants, street-level air sampling for volatile organic compounds and aldehydes was conducted at 70 sites throughout New York City during the spring of 2011. Land-use regression models were developed using a subset of 59 sites and validated against the remaining 11 sites to describe the relationship between concentrations of benzene, total BTEX (benzene, toluene, ethylbenzene, xylenes) and formaldehyde to indicators of local sources, adjusting for temporal variation. Total BTEX levels exhibited the most spatial variability, followed by benzene and formaldehyde (coefficient of variation of temporally adjusted measurements of 0.57, 0.35, 0.22, respectively). Total roadway length within 100 m, traffic signal density within 400 m of monitoring sites, and an indicator of temporal variation explained 65% of the total variability in benzene while 70% of the total variability in BTEX was accounted for by traffic signal density within 450 m, density of permitted solvent-use industries within 500 m, and an indicator of temporal variation. Measures of temporal variation, traffic signal density within 400 m, road length within 100 m, and interior building area within 100 m (indicator of heating fuel combustion) predicted 83% of the total variability of formaldehyde. The models built with the modeling subset were found to predict concentrations well, predicting 62% to 68% of monitored values at validation sites. Traffic and point source emissions cause substantial variation in street-level exposures

  12. 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

  13. Unsupervised Unmixing of Hyperspectral Images Accounting for Endmember Variability.

    PubMed

    Halimi, Abderrahim; Dobigeon, Nicolas; Tourneret, Jean-Yves

    2015-12-01

    This paper presents an unsupervised Bayesian algorithm for hyperspectral image unmixing, accounting for endmember variability. The pixels are modeled by a linear combination of endmembers weighted by their corresponding abundances. However, the endmembers are assumed random to consider their variability in the image. An additive noise is also considered in the proposed model, generalizing the normal compositional model. The proposed algorithm exploits the whole image to benefit from both spectral and spatial information. It estimates both the mean and the covariance matrix of each endmember in the image. This allows the behavior of each material to be analyzed and its variability to be quantified in the scene. A spatial segmentation is also obtained based on the estimated abundances. In order to estimate the parameters associated with the proposed Bayesian model, we propose to use a Hamiltonian Monte Carlo algorithm. The performance of the resulting unmixing strategy is evaluated through simulations conducted on both synthetic and real data.

  14. African hydroclimatic variability during the last 2000 years

    NASA Astrophysics Data System (ADS)

    Nash, David J.; De Cort, Gijs; Chase, Brian M.; Verschuren, Dirk; Nicholson, Sharon E.; Shanahan, Timothy M.; Asrat, Asfawossen; Lézine, Anne-Marie; Grab, Stefan W.

    2016-12-01

    The African continent is characterised by a wide range of hydroclimate regimes, ranging from humid equatorial West Africa to the arid deserts in the northern and southern subtropics. The livelihoods of much of its population are also vulnerable to future climate change, mainly through variability in rainfall affecting water resource availability. A growing number of data sources indicate that such hydroclimatic variability is an intrinsic component of Africa's natural environment. This paper, co-authored by members of the PAGES Africa 2k Working Group, presents an extensive assessment and discussion of proxy, historical and instrumental evidence for hydroclimatic variability across the African continent, spanning the last two millennia. While the African palaeoenvironmental record is characterised by spatially disjunctive datasets, with often less-than-optimal temporal resolution and chronological control, the available evidence allows the assessment of prominent spatial patterns of palaeomoisture variability through time. In this study, we focus sequentially on data for six major time windows: the first millennium CE, the Medieval Climate Anomaly (900-1250 CE), the Little Ice Age (1250-1750 CE), the end of the LIA (1750-1850 CE), the Early Modern Period (1850-1950), and the period of recent warming (1950 onwards). This results in a continent-wide synthesis of regional moisture-balance trends through history, allowing consideration of possible driving mechanisms, and suggestions for future research.

  15. The geovisualisation window of the temporal and spatial variability for Volunteered Geographic Information activities

    NASA Astrophysics Data System (ADS)

    Medynska-Gulij, Beata; Myszczuk, Miłosz

    2012-11-01

    This study presents an attempt to design geographical visualisation tools that allow to tackle the immensity of spatial data provided by Volunteered Geographic Information (VGI), both in terms of temporal and spatial aspects. In accordance with the assumptions made at the conceptual stage, the final action was the implementation of the window entitled ‘Geovisualisation of the Panoramio.com Activities in District of Poznan 2011’ into the web browser. The concept has been based on a division of the geovisualisation window into three panels, of which the most important - in order to capture spatial variability - have statistical maps at the general level (dot map and choropleth map), while at the detailed level - a dot map on a topographic reference map or tourist map. For two ranges, temporal variability is presented by graphs, while a review of attributes of individual activities of the social website in question is set forward in the table panel. The element that visually interlinks all of the panels is the emphasised individual activity. Problemem podjetym w tych badaniach stało sie wykorzystanie metod z nurtu geograficznej wizualizacji do wskazania cech fenomenu VGI w zakresie zmiennosci czasowo-przestrzennej. Zgodnie z załozeniami poczynionymi w etapie koncepcyjnym finalnym działaniem stało sie zaimplementowanie do przegladarki internetowej okna pod tytułem: ”Geowizualizacja aktywnosci społecznosci Panoramio.com w powiecie poznanskim w 2011 roku”. Koncepcja została oparta na podziale okna geowizualizacji na trzy panele, z których najwazniejsze znaczenie dla uchwycenia zmiennosci przestrzennej na poziomie ogólnym ma kartogram, natomiast na poziomie szczegółowym mapa kropkowa wyswietlana na podkładzie mapy topograficznej lub turystycznej. Zmiennosc czasowa w dwóch zakresach prezentuja wykresy, a przeglad atrybutów poszczególnych aktywnosci prezentowanego portalu społecznosciowego zapewnia tabela. Elementem spajajacym wizualnie wszystkie

  16. Tidal and spatial variability of nitrous oxide (N2O) in Sado estuary (Portugal)

    NASA Astrophysics Data System (ADS)

    Gonçalves, Célia; Brogueira, Maria José; Nogueira, Marta

    2015-12-01

    The estimate of the nitrous oxide (N2O) fluxes is fundamental to assess its impact on global warming. The tidal and spatial variability of N2O and the air-sea fluxes in the Sado estuary in July/August 2007 are examined. Measurements of N2O and other relevant environmental parameters (temperature, salinity, dissolved oxygen and dissolved inorganic nitrogen - nitrate plus nitrite and ammonium) were recorded during two diurnal tidal cycles performed in the Bay and Marateca region and along the estuary during ebb, at spring tide. N2O presented tidal and spatial variability and varied spatially from 5.0 nmol L-1 in Marateca region to 12.5 nmol L-1 in Sado river input. Although the Sado river may constitute a considerable N2O source to the estuary, the respective chemical signal discharge was rapidly lost in the main body of the estuary due to the low river flow during the sampling period. N2O varied with tide similarly between 5.2 nmol L-1 (Marateca) and 10.0 nmol L-1 (Sado Bay), with the maximum value reached two hours after flooding period. The influence of N2O enriched upwelled seawater (˜10.0 nmol L-1) was well visible in the estuary mouth and apparently represented an important contribution of N2O in the main body of Sado estuary. Despite the high water column oxygen saturation in most of Sado estuary, nitrification did not seem a relevant process for N2O production, probably as the concentration of the substrate, NH4+, was not adequate for this process to occur. Most of the estuary functioned as a N2O source, and only Marateca zone has acted as N2O sink. The N2O emission from Sado estuary was estimated to be 3.7 Mg N-N2O yr-1 (FC96) (4.4 Mg N-N2O yr-1, FRC01). These results have implications for future sampling and scaling strategies for estimating greenhouse gases (GHGs) fluxes in tidal ecosystems.

  17. Groundwater level responses to precipitation variability in Mediterranean insular aquifers

    NASA Astrophysics Data System (ADS)

    Lorenzo-Lacruz, Jorge; Garcia, Celso; Morán-Tejeda, Enrique

    2017-09-01

    Groundwater is one of the largest and most important sources of fresh water on many regions under Mediterranean climate conditions, which are exposed to large precipitation variability that includes frequent meteorological drought episodes, and present high evapotranspiration rates and water demand during the dry season. The dependence on groundwater increases in those areas with predominant permeable lithologies, contributing to aquifer recharge and the abundance of ephemeral streams. The increasing pressure of tourism on water resources in many Mediterranean coastal areas, and uncertainty related to future precipitation and water availability, make it urgent to understand the spatio-temporal response of groundwater bodies to precipitation variability, if sustainable use of the resource is to be achieved. We present an assessment of the response of aquifers to precipitation variability based on correlations between the Standardized Precipitation Index (SPI) at various time scales and the Standardized Groundwater Index (SGI) across a Mediterranean island. We detected three main responses of aquifers to accumulated precipitation anomalies: (i) at short time scales of the SPI (<6 months); (ii) at medium time scales (6-24 months); and at long time scales (>24 months). The differing responses were mainly explained by differences in lithology and the percentage of highly permeable rock strata in the aquifer recharge areas. We also identified differences in the months and seasons when aquifer storages are more dependent on precipitation; these were related to climate seasonality and the degree of aquifer exploitation or underground water extraction. The recharge of some aquifers, especially in mountainous areas, is related to precipitation variability within a limited spatial extent, whereas for aquifers located in the plains, precipitation variability influence much larger areas; the topography and geological structure of the island explain these differences. Results

  18. Characterization of the Spatial Variability of Methane, Ozone, and Carbon Dioxide in Two Oil and Gas Production Basins Via a Spatial Grid of Continuous Measurements

    NASA Astrophysics Data System (ADS)

    Casey, J. G.; Collier, A. M.; Hannigan, M.; Piedrahita, R.; Vaughn, B. H.; Sherwood, O.

    2015-12-01

    In recent years, aided by the advent of horizontal drilling used in conjunction with hydraulic fracturing, oil and gas production in basins around the United States has increased significantly. A study was conducted in two oil and gas basins during the spring and summer of 2015 to investigate the spatial and temporal variability of several atmospheric trace gases that can be influenced by oil and gas extraction including methane, ozone, and carbon dioxide. Fifteen air quality monitors were distributed across the Denver Julesburg Basin in Northeast Colorado, and the San Juan Basin, which stretches from Southwest Colorado into Northwest New Mexico in Four Corners Region. Spatial variability in ozone was observed across each basin. The presence of dynamic short-term trends observed in the mole fraction of methane and carbon dioxide indicate the extent to which each site is uniquely impacted by local emission sources. Diurnal trends of these two constituents lead toward a better understanding of local pooling of emissions that can be influenced by topography, the planetary boundary layer height, atmospheric stability, as well as the composition and flux of local and regional emissions sources.

  19. Integrating spatial and temporal variability into the analysis of fish food web linkages in Tijuana Estuary.

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

    West, Janelle M.; Williams, Greg D.; Madon, Sharook P.

    2003-05-14

    Our understanding of fish feeding interactions at Tijuana Estuary was improved by incorporating estimates of spatial and temporal variability into diet analyses. We examined the stomach contents of 7 dominant species (n=579 total fish) collected between 1994 and 1999. General feeding patterns pooled over time produced a basic food web consisting of 3 major trophic levels: (1) primary consumers (Atherinops affinis, Mugil cephalus) that ingested substantial amounts of plant material and detritus; (2) benthic carnivores (Clevelandia ios, Hypsopsetta guttulata, Gillichthys mirabilis, and Fundulus parvipinnis) that ingested high numbers of calanoid copepods and exotic amphipods (Grandidierella japonica); and (3) piscivores (Paralichthysmore » californicus and Leptocottus armatus) that often preyed on smaller gobiids. Similarity-based groupings of individual species' diets were identified using nonmetric multidimensional scaling to characterize their variability within and between species, and in s pace and time. This allowed us to identify major shifts and recognize events (i.e., modified prey abundance during 1997-98 El Nino floods) that likely caused these shifts.« less

  20. Characterization of spatial and temporal variability in hydrochemistry of Johor Straits, Malaysia.

    PubMed

    Abdullah, Pauzi; Abdullah, Sharifah Mastura Syed; Jaafar, Othman; Mahmud, Mastura; Khalik, Wan Mohd Afiq Wan Mohd

    2015-12-15

    Characterization of hydrochemistry changes in Johor Straits within 5 years of monitoring works was successfully carried out. Water quality data sets (27 stations and 19 parameters) collected in this area were interpreted subject to multivariate statistical analysis. Cluster analysis grouped all the stations into four clusters ((Dlink/Dmax) × 100<90) and two clusters ((Dlink/Dmax) × 100<80) for site and period similarities. Principal component analysis rendered six significant components (eigenvalue>1) that explained 82.6% of the total variance of the data set. Classification matrix of discriminant analysis assigned 88.9-92.6% and 83.3-100% correctness in spatial and temporal variability, respectively. Times series analysis then confirmed that only four parameters were not significant over time change. Therefore, it is imperative that the environmental impact of reclamation and dredging works, municipal or industrial discharge, marine aquaculture and shipping activities in this area be effectively controlled and managed. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Natural trophic variability in a large, oligotrophic, near-pristine lake

    USGS Publications Warehouse

    Young, Talia; Jensen, Olaf P.; Weidel, Brian C.; Chandra, Sudeep

    2015-01-01

    Conclusions drawn from stable isotope data can be limited by an incomplete understanding of natural isotopic variability over time and space. We quantified spatial and temporal variability in fish carbon and nitrogen stable isotopes in Lake Hövsgöl, Mongolia, a large, remote, oligotrophic lake with an unusually species-poor fish community. The fish community demonstrated a high degree of trophic level overlap. Variability in δ13C was inversely related to littoral-benthic dependence, with pelagic species demonstrating more δ13C variability than littoral-benthic species. A mixed effects model suggested that space (sampling location) had a greater impact than time (collection year) on both δ13C and δ15N variability. The observed variability in Lake Hövsgöl was generally greater than isotopic variability documented in other large, oligotrophic lakes, similar to isotopic shifts attributed to introduced species, and less than isotopic shifts attributed to anthropogenic chemical changes such as eutrophication. This work complements studies on isotopic variability and changes in other lakes around the world.

  2. Quantifying Variability of Avian Colours: Are Signalling Traits More Variable?

    PubMed Central

    Delhey, Kaspar; Peters, Anne

    2008-01-01

    Background Increased variability in sexually selected ornaments, a key assumption of evolutionary theory, is thought to be maintained through condition-dependence. Condition-dependent handicap models of sexual selection predict that (a) sexually selected traits show amplified variability compared to equivalent non-sexually selected traits, and since males are usually the sexually selected sex, that (b) males are more variable than females, and (c) sexually dimorphic traits more variable than monomorphic ones. So far these predictions have only been tested for metric traits. Surprisingly, they have not been examined for bright coloration, one of the most prominent sexual traits. This omission stems from computational difficulties: different types of colours are quantified on different scales precluding the use of coefficients of variation. Methodology/Principal Findings Based on physiological models of avian colour vision we develop an index to quantify the degree of discriminable colour variation as it can be perceived by conspecifics. A comparison of variability in ornamental and non-ornamental colours in six bird species confirmed (a) that those coloured patches that are sexually selected or act as indicators of quality show increased chromatic variability. However, we found no support for (b) that males generally show higher levels of variability than females, or (c) that sexual dichromatism per se is associated with increased variability. Conclusions/Significance We show that it is currently possible to realistically estimate variability of animal colours as perceived by them, something difficult to achieve with other traits. Increased variability of known sexually-selected/quality-indicating colours in the studied species, provides support to the predictions borne from sexual selection theory but the lack of increased overall variability in males or dimorphic colours in general indicates that sexual differences might not always be shaped by similar selective

  3. Spatial and temporal variability of runoff and streamflow generation within and among headwater catchments: a combined hydrometric and stable isotope approach

    NASA Astrophysics Data System (ADS)

    Singh, N. K.; Emanuel, R. E.; McGlynn, B. L.

    2012-12-01

    The combined influence of topography and vegetation on runoff generation and streamflow in headwater catchments remains unclear. We aim to understand how spatial, hydrological and climate variables affect runoff generation and streamflow at hillslope and watershed scales at the Coweeta Hydrologic Laboratory (CHL) in the southern Appalachian Mountains by analyzing stable isotopes of hydrogen (2H) and oxygen (18O) coupled with measurements of hydrological variables (stream discharge, soil moisture, shallow groundwater) and landscape variables (upslope accumulated area, vegetation density slope, and aspect). We investigated four small catchments, two of which contained broadleaf deciduous vegetation and two of which contained evergreen coniferous vegetation. Beginning in June 2011, we collected monthly water samples at 25 m intervals along each stream, monthly samples from 24 shallow groundwater wells, and weekly to monthly samples from 10 rain gauges distributed across CHL. Water samples were analyzed for 2H and 18O using cavity ring-down spectroscopy. During the same time period we recorded shallow groundwater stage at 30 min intervals from each well, and beginning in fall 2011 we collected volumetric soil moisture data at 30 min intervals from multiple depths at 16 landscape positions. Results show high spatial and temporal variability in δ2H and δ18O within and among streams, but in general we found isotopic enrichment with increasing contributing area along each stream. We used a combination of hydrometric observations and geospatial analyses to understand why stream isotope patterns varied during the year and among watersheds, and we used complementary measurements of δ2H and δ18O from other pools within the watersheds to understand the movement and mixing of precipitation that precedes runoff formation. This combination of high resolution stable isotope data and hydrometric observations facilitates a clearer understanding of spatial controls on streamflow

  4. The near-infrared counterpart of a variable galactic plane radio source

    NASA Technical Reports Server (NTRS)

    Margon, Bruce; Phillips, Andrew C.; Ciardullo, Robin; Jacoby, George H.

    1992-01-01

    A near-infrared counterpart to the highly variable, unresolved galactic plane radio source GT 0116 + 622 is identified. This source is of particular interest, as it has been previously suggested to be the counterpart of the gamma-ray source Cas gamma-l. The present NIR and red images detect a faint, spatially extended (3 arcsec FWHM), very red object coincident with the radio position. There is complex spatial structure which may be due in part to an unrelated superposed foreground object. Observations on multiple nights show no evidence for flux variability, despite the high amplitude variability on a time-scale of days reported for the radio source. The data are consistent with an interpretation of GT 0116 + 622 as an unusually variable, obscured active galaxy at a distance of several hundred megaparsecs, although more exotic, and in particular galactic, interpretations cannot yet be ruled out. If the object is extragalactic, the previously suggested identification with the gamma-ray source would seem unlikely.

  5. Crown fuel spatial variability and predictability of fire spread

    Treesearch

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

    2010-01-01

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

  6. Spatial variability of throughfall in a stand of Scots pine (Pinus sylvestris L.) with deciduous admixture as influenced by canopy cover and stem distance

    NASA Astrophysics Data System (ADS)

    Kowalska, Anna; Boczoń, Andrzej; Hildebrand, Robert; Polkowska, Żaneta

    2016-07-01

    Vegetation cover affects the amount of precipitation, its chemical composition and its spatial distribution, and this may have implications for the distribution of water, nutrients and contaminants in the subsurface soil layer. The aim of this study was a detailed diagnosis of the spatio-temporal variability in the amount of throughfall (TF) and its chemical components in a 72-year-old pine stand with an admixture of oak and birch. The spatio-temporal variability in the amount of TF water and the concentrations and deposition of the TF components were studied. The components that are exchanged in canopy (H+, K, Mg, Mn, DOC, NH4+) were more variable than the components whose TF deposition is the sum of wet and dry (including gas) deposition and which undergo little exchange in the canopy (Na, Cl, NO3-, SO42-). The spatial distribution was temporally stable, especially during the leafed period. This study also investigated the effect of the selected pine stand characteristics on the spatial distribution of throughfall and its chemical components; the characteristics included leaf area index (LAI), the proportion of the canopy covered by deciduous species and pine crowns, and the distance from the nearest tree trunk. The LAI measured during the leafed and leafless periods had the greatest effect on the spatial distribution of TF deposition. No relationship was found between the spatial distribution of the amount of TF water and (i) the LAI; (ii) the canopy cover of broadleaf species or pines; or (iii) the distance from the trunks.

  7. Short-Term Effects of Climatic Variables on Hand, Foot, and Mouth Disease in Mainland China, 2008–2013: A Multilevel Spatial Poisson Regression Model Accounting for Overdispersion

    PubMed Central

    Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying

    2016-01-01

    Background Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. Methods The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008–2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. Results The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse “V” shape and “V” shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. Conclusion We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic

  8. Characterizing spatial and temporal variability in methane gas-flux dynamics of subtropical wetlands in the Big Cypress National Preserve, Florida

    NASA Astrophysics Data System (ADS)

    Sirianni, M.; Comas, X.; Shoemaker, B.

    2017-12-01

    Wetland methane emissions are highly variable both in space and time, and are controlled by changes in certain biogeochemical controls (i.e. organic matter availability; redox potential) and/or other environmental factors (i.e. soil temperature; water level). Consequently, hot spots (areas with disproportionally high emissions) may develop where biogeochemical and environmental conditions are especially conducive for enhancing certain microbial processes such as methanogenesis. The Big Cypress National Preserve is a collection of subtropical wetlands in southwestern Florida, including extensive forested (cypress, pine, hardwood) and sawgrass ecosystems that dry and flood annually in response to rainfall. In addition to rainfall, hydroperiod, fire regime, elevation above mean sea level, dominant vegetation type and underlying geological controls contribute to the development and evolution of organic and calcitic soils found throughout the Preserve. Currently, the U.S. Geological Survey employs eddy covariance methods within the Preserve to quantify carbon and methane exchanges over several spatially extensive vegetation communities. While eddy covariance towers are a convenient tool for measuring gas exchanges at the ecosystem scale, their spatially extensive footprint (hundreds of meters) may mask smaller scale spatial variabilities that may be conducive to the development of hot spots. Similarly, temporal resolution (i.e. sampling effort) at scales smaller that the eddy covariance measurement footprint is important since low resolution data may overlook rapid emission events and the temporal variability of discrete hot spots. In this work, we intend to estimate small-scale contributions of organic and calcitic soils to gas exchanges measured by the eddy covariance towers using a unique combination of ground penetrating radar (GPR), capacitance probes, gas traps, and time-lapse photography. By using an array of methods that vary in spatio-temporal resolution, we

  9. Thermal infrared imagery as a tool for analysing the variability of surface saturated areas at various temporal and spatial scales

    NASA Astrophysics Data System (ADS)

    Glaser, Barbara; Antonelli, Marta; Pfister, Laurent; Klaus, Julian

    2017-04-01

    Surface saturated areas are important for the on- and offset of hydrological connectivity within the hillslope-riparian-stream continuum. This is reflected in concepts such as variable contributing areas or critical source areas. However, we still lack a standardized method for areal mapping of surface saturation and for observing its spatiotemporal variability. Proof-of-concept studies in recent years have shown the potential of thermal infrared (TIR) imagery to record surface saturation dynamics at various temporal and spatial scales. Thermal infrared imagery is thus a promising alternative to conventional approaches, such as the squishy boot method or the mapping of vegetation. In this study we use TIR images to investigate the variability of surface saturated areas at different temporal and spatial scales in the forested Weierbach catchment (0.45 km2) in western Luxembourg. We took TIR images of the riparian zone with a hand-held FLIR infrared camera at fortnightly intervals over 18 months at nine different locations distributed over the catchment. Not all of the acquired images were suitable for a derivation of the surface saturated areas, as various factors influence the usability of the TIR images (e.g. temperature contrasts, shadows, fog). Nonetheless, we obtained a large number of usable images that provided a good insight into the dynamic behaviour of surface saturated areas at different scales. The images revealed how diverse the evolution of surface saturated areas can be throughout the hydrologic year. For some locations with similar morphology or topography we identified diverging saturation dynamics, while other locations with different morphology / topography showed more similar behaviour. Moreover, we were able to assess the variability of the dynamics of expansion / contraction of saturated areas within the single locations, which can help to better understand the mechanisms behind surface saturation development.

  10. Spatial variability of the response to climate change in regional groundwater systems -- examples from simulations in the Deschutes Basin, Oregon

    USGS Publications Warehouse

    Waibel, Michael S.; Gannett, Marshall W.; Chang, Heejun; Hulbe, Christina L.

    2013-01-01

    We examine the spatial variability of the response of aquifer systems to climate change in and adjacent to the Cascade Range volcanic arc in the Deschutes Basin, Oregon using downscaled global climate model projections to drive surface hydrologic process and groundwater flow models. Projected warming over the 21st century is anticipated to shift the phase of precipitation toward more rain and less snow in mountainous areas in the Pacific Northwest, resulting in smaller winter snowpack and in a shift in the timing of runoff to earlier in the year. This will be accompanied by spatially variable changes in the timing of groundwater recharge. Analysis of historic climate and hydrologic data and modeling studies show that groundwater plays a key role in determining the response of stream systems to climate change. The spatial variability in the response of groundwater systems to climate change, particularly with regard to flow-system scale, however, has generally not been addressed in the literature. Here we simulate the hydrologic response to projected future climate to show that the response of groundwater systems can vary depending on the location and spatial scale of the flow systems and their aquifer characteristics. Mean annual recharge averaged over the basin does not change significantly between the 1980s and 2080s climate periods given the ensemble of global climate models and emission scenarios evaluated. There are, however, changes in the seasonality of groundwater recharge within the basin. Simulation results show that short-flow-path groundwater systems, such as those providing baseflow to many headwater streams, will likely have substantial changes in the timing of discharge in response changes in seasonality of recharge. Regional-scale aquifer systems with flow paths on the order of many tens of kilometers, in contrast, are much less affected by changes in seasonality of recharge. Flow systems at all spatial scales, however, are likely to reflect

  11. Photometric variability in earthshine observations.

    PubMed

    Langford, Sally V; Wyithe, J Stuart B; Turner, Edwin L

    2009-04-01

    The identification of an extrasolar planet as Earth-like will depend on the detection of atmospheric signatures or surface non-uniformities. In this paper we present spatially unresolved flux light curves of Earth for the purpose of studying a prototype extrasolar terrestrial planet. Our monitoring of the photometric variability of earthshine revealed changes of up to 23% per hour in the brightness of Earth's scattered light at around 600 nm, due to the removal of specular reflection from the view of the Moon. This variability is accompanied by reddening of the spectrum and results from a change in surface properties across the continental boundary between the Indian Ocean and Africa's east coast. Our results based on earthshine monitoring indicate that specular reflection should provide a useful tool in determining the presence of liquid water on extrasolar planets via photometric observations.

  12. Spatial and temporal variability of fine particle composition and source types in five cities of Connecticut and Massachusetts

    PubMed Central

    Lee, Hyung Joo; Gent, Janneane F.; Leaderer, Brian P.; Koutrakis, Petros

    2011-01-01

    To protect public health from PM2.5 air pollution, it is critical to identify the source types of PM2.5 mass and chemical components associated with higher risks of adverse health outcomes. Source apportionment modeling using Positive Matrix Factorization (PMF), was used to identify PM2.5 source types and quantify the source contributions to PM2.5 in five cities of Connecticut and Massachusetts. Spatial and temporal variability of PM2.5 mass, components and source contributions were investigated. PMF analysis identified five source types: regional pollution as traced by sulfur, motor vehicle, road dust, oil combustion and sea salt. The sulfur-related regional pollution and traffic source type were major contributors to PM2.5. Due to sparse ground-level PM2.5 monitoring sites, current epidemiological studies are susceptible to exposure measurement errors. The higher correlations in concentrations and source contributions between different locations suggest less spatial variability, resulting in less exposure measurement errors. When concentrations and/or contributions were compared to regional averages, correlations were generally higher than between-site correlations. This suggests that for assigning exposures for health effects studies, using regional average concentrations or contributions from several PM2.5 monitors is more reliable than using data from the nearest central monitor. PMID:21429560

  13. Fish Assemblage Structure Under Variable Environmental Conditions in the Ouachita Mountains

    Treesearch

    Christopher M. Taylor; Lance R. Williams; Riccardo A. Fiorillo; R. Brent Thomas; Melvin L. Warren

    2004-01-01

    Abstract - Spatial and temporal variability of fish assemblages in Ouachita Mountain streams, Arkansas, were examined for association with stream size and flow variability. Fishes and habitat were sampled quarterly for four years at 12 sites (144 samples) in the Ouachita Mountains Ecosystem Management Research Project, Phase III watersheds. Detrended...

  14. Method and system for spatially variable rate application of agricultural chemicals based on remotely sensed vegetation data

    NASA Technical Reports Server (NTRS)

    Lewis, Mark David (Inventor); Seal, Michael R. (Inventor); Hood, Kenneth Brown (Inventor); Johnson, James William (Inventor)

    2007-01-01

    Remotely sensed spectral image data are used to develop a Vegetation Index file which represents spatial variations of actual crop vigor throughout a field that is under cultivation. The latter information is processed to place it in a format that can be used by farm personnel to correlate and calibrate it with actually observed crop conditions existing at control points within the field. Based on the results, farm personnel formulate a prescription request, which is forwarded via email or FTP to a central processing site, where the prescription is prepared. The latter is returned via email or FTP to on-side farm personnel, who can load it into a controller on a spray rig that directly applies inputs to the field at a spatially variable rate.

  15. Method and apparatus for spatially variable rate application of agricultural chemicals based on remotely sensed vegetation data

    NASA Technical Reports Server (NTRS)

    Hood, Kenneth Brown (Inventor); Johnson, James William (Inventor); Seal, Michael R. (Inventor); Lewis, Mark David (Inventor)

    2004-01-01

    Remotely sensed spectral image data are used to develop a Vegetation Index file which represents spatial variations of actual crop vigor throughout a field that is under cultivation. The latter information is processed to place it in a format that can be used by farm personnel to correlate and calibrate it with actually observed crop conditions existing at control points within the field. Based on the results, farm personnel formulate a prescription request, which is forwarded via email or FTP to a central processing site, where the prescription is prepared. The latter is returned via email or FTP to on-side farm personnel, who can load it into a controller on a spray rig that directly applies inputs to the field at a spatially variable rate.

  16. Characterizing local variability in long‐period horizontal tilt noise

    USGS Publications Warehouse

    Rohde, M.D.; Ringler, Adam; Hutt, Charles R.; Wilson, David; Holland, Austin; Sandoval, L.D; Storm, Tyler

    2017-01-01

    Horizontal seismic data are dominated by atmospherically induced tilt noise at long periods (i.e., 30 s and greater). Tilt noise limits our ability to use horizontal data for sensitive seismological studies such as observing free earth modes. To better understand the local spatial variability of long‐period horizontal noise, we observe horizontal noise during quiet time periods in the Albuquerque Seismological Laboratory (ASL) underground vault using four small‐aperture array configurations. Each array comprises eight Streckeisen STS‐2 broadband seismometers. We analyze the spectral content of the data using power spectral density and magnitude‐squared coherence (γ2‐coherence). Our results show a high degree of spatial variability and frequency dependence in the long‐period horizontal wavefield. The variable nature of long‐period horizontal noise in the ASL vault suggests that it might be highly local in nature and not easily characterized by simple physical models when overall noise levels are low, making it difficult to identify locations in the vault with lower horizontal noise. This variability could be limiting our ability to apply coherence analysis for estimating horizontal sensor self‐noise and could also complicate various indirect methods for removing long‐period horizontal noise (e.g., collocated rotational sensor or microbarograph).

  17. The Variability of the Horizontal Circulation in the Troposphere and Stratosphere: A Comparison

    NASA Technical Reports Server (NTRS)

    Perlwitz, Judith; Graf, Hans-F.; Hansem, James E. (Technical Monitor)

    2001-01-01

    The variability of the horizontal circulation in the stratosphere and troposphere of the Northern Hemisphere (NH) is compared by using various approaches. Spatial degrees of freedom (dof) on different time scales were derived. Modes of variability were computed in geopotential height fields at the tropospheric and stratospheric pressure levels by applying multivariate statistical approaches. Features of the spatial and temporal variability of the winterly zonal wind were studied with the help of recurrence and persistence analyses. The geopotential height and zonally-averaged zonal wind at the 50-, 500- and 1000-hPa level are used to investigate the behavior of the horizontal circulation in the lower stratosphere, mid-troposphere and at the near surface level, respectively. It is illustrated that the features of the variability of the horizontal circulation are very similar in the mid-troposphere and at the near surface level. Due to the filtering of tropospheric disturbances by the stratospheric and upper tropospheric zonal mean flow, the variability of the stratospheric circulation exhibits less spatial complexity than the circulation at tropospheric pressure levels. There exist enormous differences in the number of degrees of freedom (or free variability modes) between both atmospheric layers. Results of the analyses clearly show that the concept of a zonally symmetric AO with a simple structure in the troposphere similar to the one in the stratosphere is not valid. It is concluded that the spatially filtered climate change signal can be detected earlier in the stratosphere than in the mid-troposphere or at the near surface level.

  18. The contribution of hydroxylamine content to spatial variability of N2O formation in soil of a Norway spruce forest

    NASA Astrophysics Data System (ADS)

    Liu, Shurong; Herbst, Michael; Bol, Roland; Gottselig, Nina; Pütz, Thomas; Weymann, Daniel; Wiekenkamp, Inge; Vereecken, Harry; Brüggemann, Nicolas

    2016-04-01

    Hydroxylamine (NH2OH), a reactive intermediate of several microbial nitrogen turnover processes, is a potential precursor of nitrous oxide (N2O) formation in the soil. However, the contribution of soil NH2OH to soil N2O emission rates in natural ecosystems is unclear. Here, we determined the spatial variability of NH2OH content and potential N2O emission rates of organic (Oh) and mineral (Ah) soil layers of a Norway spruce forest, using a recently developed analytical method for the determination of soil NH2OH content, combined with a geostatistical Kriging approach. Potential soil N2O emission rates were determined by laboratory incubations under oxic conditions, followed by gas chromatographic analysis and complemented by ancillary measurements of soil characteristics. Stepwise multiple regressions demonstrated that the potential N2O emission rates, NH2OH and nitrate (NO3-) content were spatially highly correlated, with hotspots for all three parameters observed in the headwater of a small creek flowing through the sampling area. In contrast, soil ammonium (NH4+) was only weakly correlated with potential N2O emission rates, and was excluded from the multiple regression models. While soil NH2OH content explained the potential soil N2O emission rates best for both layers, also NO3- and Mn content turned out to be significant parameters explaining N2O formation in both soil layers. The Kriging approach was improved markedly by the addition of the co-variable information of soil NH2OH and NO3- content. The results indicate that determination of soil NH2OH content could provide crucial information for the prediction of the spatial variability of soil N2O emissions.

  19. Artificial Neural Network to Predict Vine Water Status Spatial Variability Using Multispectral Information Obtained from an Unmanned Aerial Vehicle (UAV).

    PubMed

    Poblete, Tomas; Ortega-Farías, Samuel; Moreno, Miguel Angel; Bardeen, Matthew

    2017-10-30

    Water stress, which affects yield and wine quality, is often evaluated using the midday stem water potential (Ψ stem ). However, this measurement is acquired on a per plant basis and does not account for the assessment of vine water status spatial variability. The use of multispectral cameras mounted on unmanned aerial vehicle (UAV) is capable to capture the variability of vine water stress in a whole field scenario. It has been reported that conventional multispectral indices (CMI) that use information between 500-800 nm, do not accurately predict plant water status since they are not sensitive to water content. The objective of this study was to develop artificial neural network (ANN) models derived from multispectral images to predict the Ψ stem spatial variability of a drip-irrigated Carménère vineyard in Talca, Maule Region, Chile. The coefficient of determination (R²) obtained between ANN outputs and ground-truth measurements of Ψ stem were between 0.56-0.87, with the best performance observed for the model that included the bands 550, 570, 670, 700 and 800 nm. Validation analysis indicated that the ANN model could estimate Ψ stem with a mean absolute error (MAE) of 0.1 MPa, root mean square error (RMSE) of 0.12 MPa, and relative error (RE) of -9.1%. For the validation of the CMI, the MAE, RMSE and RE values were between 0.26-0.27 MPa, 0.32-0.34 MPa and -24.2-25.6%, respectively.

  20. Water availability as a driver of spatial and temporal variability in vegetation in the La Mancha plain (Spain): Implications for the land-surface energy, water and carbon budget

    NASA Astrophysics Data System (ADS)

    Los, Sietse

    2017-04-01

    Vegetation is water limited in large areas of Spain and therefore a close link exists between vegetation greenness observed from satellite and moisture availability. Here we exploit this link to infer spatial and temporal variability in moisture from MODIS NDVI data and thermal data. Discrepancies in the precipitation - vegetation relationship indicate areas with an alternative supply of water (i.e. not rainfall), this can be natural where moisture is supplied by upwelling groundwater, or can be artificial where crops are irrigated. As a result spatial and temporal variability in vegetation in the La Mancha Plain appears closely linked to topography, geology, rainfall and land use. Crop land shows large variability in year-to-year vegetation greenness; for some areas this variability is linked to variability in rainfall but in other cases this variability is linked to irrigation. The differences in irrigation treatment within one plant functional type, in this case crops, will lead to errors in land surface models when ignored. The magnitude of these effects on the energy, carbon and water balance are assessed at the scale of 250 m to 200 km. Estimating the water balance correctly is of particular important since in some areas in Spain more water is used for irrigation than is supplemented by rainfall.

  1. Spatial and temporal variability of greenhouse gas emissions from a small and shallow temperate lake

    NASA Astrophysics Data System (ADS)

    Praetzel, Leandra; Schmiedeskamp, Marcel; Broder, Tanja; Hüttemann, Caroline; Jansen, Laura; Metzelder, Ulrike; Wallis, Ronya; Knorr, Klaus-Holger; Blodau, Christian

    2017-04-01

    Small inland waters (< 1 km2) have recently been discovered as significant sources and sinks in the global carbon cycle because they cover larger areas than previously assumed and exhibit a higher metabolic activity than larger lakes. They are further expected to be susceptible to changing climate conditions. So far, little is known about the spatial and temporal variability of carbon dioxide (CO2) and methane (CH4) emissions and in-lake dynamics of CH4 production and oxidation in small, epilimnetic lakes in the temperate zone. Of particular interest is the potential occurrence of "hot spots" and "hot moments" that could contribute significantly to total emissions. To address this knowledge gap, we determined CO2 and CH4 emissions and dynamics to identify their controlling environmental factors in a polymictic small (1.4 ha) and shallow (max. depth approx. 1.5 m) crater lake ("Windsborn") in the Eifel uplands in south-west Germany. As Lake Windsborn has a small catchment area (8 ha) and no surficial inflows, it serves well as a model system for the identification of factors and processes controlling emissions. In 2015, 2016 and 2017 we measured CO2 and CH4 gas fluxes with different techniques across the sediment/water and water/atmosphere interface. Atmospheric exchange was measured using mini-chambers equipped with CO2 sensors and with an infra-red greenhouse gas analyzer for high temporal resolution flux measurements. Ebullition of CH4 was quantified with funnel traps. Sediment properties were examined using pore-water peepers. All measurements were carried out along a transect covering both littoral and central parts of the lake. Moreover, a weather station on a floating platform in the center of the lake recorded meteorological data as well as CO2 concentration in different depths of the water column. So far, Lake Windsborn seems to be a source for both CO2 and CH4 on an annual scale. CO2 emissions generally increased from spring to summer. Even though CO2

  2. A Model of the Spatial Structure and Productivity of Phytoplankton Populations during Variable Upwelling Off the Coast of Oregon

    DTIC Science & Technology

    1976-09-01

    Univ., Corvallis, 71 p. barber, R. T. and J. H. Ryther, 1969. Organic chelators: factors affecting primary production in the Cromwell1 current upwelling...Mesoscale Air-Sea Interaction Group Technical Report I A MODEL OF THE SPATIAL STRUCTURE AND PRODUCTIVITY OF PHYTOPLANKTON POPULATIONS DURING...Variability in the wind stress affects the rate of ufpwelling and ultimtely the local biological productivity . To investigate the relationship between wind

  3. How Variables Uncorrelated with the Dependent Variable Can Actually Make Excellent Predictors: The Important Suppressor Variable Case.

    ERIC Educational Resources Information Center

    Woolley, Kristin K.

    Many researchers are unfamiliar with suppressor variables and how they operate in multiple regression analyses. This paper describes the role suppressor variables play in a multiple regression model and provides practical examples that explain how they can change research results. A variable that when added as another predictor increases the total…

  4. Variable Pitch Propellers

    NASA Technical Reports Server (NTRS)

    1920-01-01

    In this report are described four different types of propellers which appeared at widely separated dates, but which were exhibited together at the last Salon de l'Aeronautique. The four propellers are the Chaviere variable pitch propeller, the variable pitch propeller used on the Clement Bayard dirigible, the variable pitch propeller used on Italian dirigibles, and the Levasseur variable pitch propeller.

  5. Gravity dependence of subjective visual vertical variability.

    PubMed

    Tarnutzer, A A; Bockisch, C; Straumann, D; Olasagasti, I

    2009-09-01

    The brain integrates sensory input from the otolith organs, the semicircular canals, and the somatosensory and visual systems to determine self-orientation relative to gravity. Only the otoliths directly sense the gravito-inertial force vector and therefore provide the major input for perceiving static head-roll relative to gravity, as measured by the subjective visual vertical (SVV). Intraindividual SVV variability increases with head roll, which suggests that the effectiveness of the otolith signal is roll-angle dependent. We asked whether SVV variability reflects the spatial distribution of the otolithic sensors and the otolith-derived acceleration estimate. Subjects were placed in different roll orientations (0-360 degrees, 15 degrees steps) and asked to align an arrow with perceived vertical. Variability was minimal in upright, increased with head-roll peaking around 120-135 degrees, and decreased to intermediate values at 180 degrees. Otolith-dependent variability was modeled by taking into consideration the nonuniform distribution of the otolith afferents and their nonlinear firing rate. The otolith-derived estimate was combined with an internal bias shifting the estimated gravity-vector toward the body-longitudinal. Assuming an efficient otolith estimator at all roll angles, peak variability of the model matched our data; however, modeled variability in upside-down and upright positions was very similar, which is at odds with our findings. By decreasing the effectiveness of the otolith estimator with increasing roll, simulated variability matched our experimental findings better. We suggest that modulations of SVV precision in the roll plane are related to the properties of the otolith sensors and to central computational mechanisms that are not optimally tuned for roll-angles distant from upright.

  6. Variable mechanical ventilation

    PubMed Central

    Fontela, Paula Caitano; Prestes, Renata Bernardy; Forgiarini Jr., Luiz Alberto; Friedman, Gilberto

    2017-01-01

    Objective To review the literature on the use of variable mechanical ventilation and the main outcomes of this technique. Methods Search, selection, and analysis of all original articles on variable ventilation, without restriction on the period of publication and language, available in the electronic databases LILACS, MEDLINE®, and PubMed, by searching the terms "variable ventilation" OR "noisy ventilation" OR "biologically variable ventilation". Results A total of 36 studies were selected. Of these, 24 were original studies, including 21 experimental studies and three clinical studies. Conclusion Several experimental studies reported the beneficial effects of distinct variable ventilation strategies on lung function using different models of lung injury and healthy lungs. Variable ventilation seems to be a viable strategy for improving gas exchange and respiratory mechanics and preventing lung injury associated with mechanical ventilation. However, further clinical studies are necessary to assess the potential of variable ventilation strategies for the clinical improvement of patients undergoing mechanical ventilation. PMID:28444076

  7. 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.

  8. 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

  9. Estimation of Traffic Variables Using Point Processing Techniques

    DOT National Transportation Integrated Search

    1978-05-01

    An alternative approach to estimating aggregate traffic variables on freeways--spatial mean velocity and density--is presented. Vehicle arrival times at a given location on a roadway, typically a presence detector, are regarded as a point or counting...

  10. Spatial and Temporal Variability of Trace Gas Columns Derived from WRF/Chem Regional Model Output: Planning for Geostationary Observations of Atmospheric Composition

    NASA Technical Reports Server (NTRS)

    Follette-Cook, M. B.; Pickering, K.; Crawford, J.; Duncan, B.; Loughner, C.; Diskin, G.; Fried, A.; Weinheimer, A.

    2015-01-01

    We quantify both the spatial and temporal variability of column integrated O3, NO2, CO, SO2, and HCHO over the Baltimore / Washington, DC area using output from the Weather Research and Forecasting model with on-line chemistry (WRF/Chem) for the entire month of July 2011, coinciding with the first deployment of the NASA Earth Venture program mission Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ). Using structure function analyses, we find that the model reproduces the spatial variability observed during the campaign reasonably well, especially for O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument will be the first NASA mission to make atmospheric composition observations from geostationary orbit and partially fulfills the goals of the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission. We relate the simulated variability to the precision requirements defined by the science traceability matrices of these space-borne missions. Results for O3 from 0- 2 km altitude indicate that the TEMPO instrument would be able to observe O3 air quality events over the Mid-Atlantic area, even on days when the violations of the air quality standard are not widespread. The results further indicated that horizontal gradients in CO from 0-2 km would be observable over moderate distances (= 20 km). The spatial and temporal results for tropospheric column NO2 indicate that TEMPO would be able to observe not only the large urban plumes at times of peak production, but also the weaker gradients between rush hours. This suggests that the proposed spatial and temporal resolutions for these satellites as well as their prospective precision requirements are sufficient to answer the science questions they are tasked to address.

  11. Hydrographic Variability off the Coast of Oman

    NASA Astrophysics Data System (ADS)

    Belabbassi, L.; Dimarco, S. F.; Jochens, A. E.; Al Gheilani, H.; Wang, Z.

    2010-12-01

    Data from hydrographic transects made in 2001 and 2002 and between 2007 and 2009 were obtained from the Oman Ministry of Fisheries Wealth. Property-depth plots of temperature, salinity, and dissolved oxygen were produced for all transects and in all months for which data were available. These were analyzed for temporal and spatial variability. For all transects, there exist large variability on various timescales, with strong spatial variability. Two common features that are seen in the hydrographic data sets are the Persian Gulf Water (PGW) and a layer of continuous low oxygen concentrations in the lower part of the water column. Plots of salinity produced for transects located in the northern part of the Gulf of Oman show a one-unit increase in salinity of the water at the bottom of deepest station during the months of August and September as compared to the other months. Similarly, cross-shelf contour plots of temperature shows an increase in water temperature near the bottom station during the months of August and September. These indicate the presence of the PGW outflow in the northern part of the Gulf of Oman. For dissolved oxygen distributions, hydrographic transects that did not extend far offshore show monthly differences in the presence of water with low oxygen concentrations. For transects that do extend far offshore and also show a layer of low oxygen water throughout the year, there is generally a monthly difference on whether this water is found close to the surface or deeper in the water column. The variability seen in the data could only be explained by comparing these data to data collected from the real time cable ocean observing system installed by Lighthouse R &D Enterprise in the Oman Sea and the Arabian Sea in 2005. The analysis of these data reveal that the variability observed is related to processes such as ocean conditions, monsoonal cycle, and extreme weather events.

  12. The Importance of Freshwater to Spatial Variability of Aragonite Saturation State in the Gulf of Alaska

    NASA Astrophysics Data System (ADS)

    Siedlecki, Samantha A.; Pilcher, Darren J.; Hermann, Albert J.; Coyle, Ken; Mathis, Jeremy

    2017-11-01

    High-latitude and subpolar regions like the Gulf of Alaska (GOA) are more vulnerable than equatorial regions to rising carbon dioxide (CO2) levels, in part due to local processes that amplify the global signal. Recent field observations have shown that the shelf of the GOA is currently experiencing seasonal corrosive events (carbonate mineral saturation states Ω, Ω < 1), including suppressed Ω in response to ocean acidification as well as local processes like increased low-alkalinity glacial meltwater discharge. While the glacial discharge mainly influences the inner shelf, on the outer shelf, upwelling brings corrosive waters from the deep GOA. In this work, we develop a high-resolution model for carbon dynamics in the GOA, identify regions of high variability of Ω, and test the sensitivity of those regions to changes in the chemistry of glacial meltwater discharge. Results indicate the importance of this climatically sensitive and relatively unconstrained regional freshwater forcing for Ω variability in the nearshore. The increase was nearly linear at 0.002 Ω per 100 µmol/kg increase in alkalinity in the freshwater runoff. We find that the local winds, biological processes, and freshwater forcing all contribute to the spatial distribution of Ω and identify which of these three is highly correlated to the variability in Ω. Given that the timing and magnitude of these processes will likely change during the next few decades, it is critical to elucidate the effect of local processes on the background ocean acidification signal using robust models, such as the one described here.

  13. Spatial Variability of Sources and Mixing State of Atmospheric Particles in a Metropolitan Area.

    PubMed

    Ye, Qing; Gu, Peishi; Li, Hugh Z; Robinson, Ellis S; Lipsky, Eric; Kaltsonoudis, Christos; Lee, Alex K Y; Apte, Joshua S; Robinson, Allen L; Sullivan, Ryan C; Presto, Albert A; Donahue, Neil M

    2018-05-30

    Characterizing intracity variations of atmospheric particulate matter has mostly relied on fixed-site monitoring and quantifying variability in terms of different bulk aerosol species. In this study, we performed ground-based mobile measurements using a single-particle mass spectrometer to study spatial patterns of source-specific particles and the evolution of particle mixing state in 21 areas in the metropolitan area of Pittsburgh, PA. We selected sampling areas based on traffic density and restaurant density with each area ranging from 0.2 to 2 km 2 . Organics dominate particle composition in all of the areas we sampled while the sources of organics differ. The contribution of particles from traffic and restaurant cooking varies greatly on the neighborhood scale. We also investigate how primary and aged components in particles mix across the urban scale. Lastly we quantify and map the particle mixing state for all areas we sampled and discuss the overall pattern of mixing state evolution and its implications. We find that in the upwind and downwind of the urban areas, particles are more internally mixed while in the city center, particle mixing state shows large spatial heterogeneity that is mostly driven by emissions. This study is to our knowledge, the first study to perform fine spatial scale mapping of particle mixing state using ground-based mobile measurement and single-particle mass spectrometry.

  14. Effectiveness of Drafting Models for Engineering Technology Students and Impacts on Spatial Visualization Ability: An Analysis and Consideration of Critical Variables

    ERIC Educational Resources Information Center

    Katsioloudis, Petros J.; Stefaniak, Jill E.

    2018-01-01

    Results from a number of studies indicate that the use of drafting models can positively influence the spatial visualization ability for engineering technology students. However, additional variables such as light, temperature, motion and color can play an important role but research provides inconsistent results. Considering this, a set of 5…

  15. Accuracy and Spatial Variability in GPS Surveying for Landslide Mapping on Road Inventories at a Semi-Detailed Scale: the Case in Colombia

    NASA Astrophysics Data System (ADS)

    Murillo Feo, C. A.; Martnez Martinez, L. J.; Correa Muñoz, N. A.

    2016-06-01

    The accuracy of locating attributes on topographic surfaces when, using GPS in mountainous areas, is affected by obstacles to wave propagation. As part of this research on the semi-automatic detection of landslides, we evaluate the accuracy and spatial distribution of the horizontal error in GPS positioning in the tertiary road network of six municipalities located in mountainous areas in the department of Cauca, Colombia, using geo-referencing with GPS mapping equipment and static-fast and pseudo-kinematic methods. We obtained quality parameters for the GPS surveys with differential correction, using a post-processing method. The consolidated database underwent exploratory analyses to determine the statistical distribution, a multivariate analysis to establish relationships and partnerships between the variables, and an analysis of the spatial variability and calculus of accuracy, considering the effect of non-Gaussian distribution errors. The evaluation of the internal validity of the data provide metrics with a confidence level of 95% between 1.24 and 2.45 m in the static-fast mode and between 0.86 and 4.2 m in the pseudo-kinematic mode. The external validity had an absolute error of 4.69 m, indicating that this descriptor is more critical than precision. Based on the ASPRS standard, the scale obtained with the evaluated equipment was in the order of 1:20000, a level of detail expected in the landslide-mapping project. Modelling the spatial variability of the horizontal errors from the empirical semi-variogram analysis showed predictions errors close to the external validity of the devices.

  16. 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.

  17. 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

  18. Modelling spatial and temporal vegetation variability with the Climate Constrained Vegetation Index: evidence of CO2 fertilisation and of water stress in continental interiors

    NASA Astrophysics Data System (ADS)

    Los, S. O.

    2015-06-01

    A model was developed to simulate spatial, seasonal and interannual variations in vegetation in response to temperature, precipitation and atmospheric CO2 concentrations; the model addresses shortcomings in current implementations. The model uses the minimum of 12 temperature and precipitation constraint functions to simulate NDVI. Functions vary based on the Köppen-Trewartha climate classification to take adaptations of vegetation to climate into account. The simulated NDVI, referred to as the climate constrained vegetation index (CCVI), captured the spatial variability (0.82 < r <0.87), seasonal variability (median r = 0.83) and interannual variability (median global r = 0.24) in NDVI. The CCVI simulated the effects of adverse climate on vegetation during the 1984 drought in the Sahel and during dust bowls of the 1930s and 1950s in the Great Plains in North America. A global CO2 fertilisation effect was found in NDVI data, similar in magnitude to that of earlier estimates (8 % for the 20th century). This effect increased linearly with simple ratio, a transformation of the NDVI. Three CCVI scenarios, based on climate simulations using the representative concentration pathway RCP4.5, showed a greater sensitivity of vegetation towards precipitation in Northern Hemisphere mid latitudes than is currently implemented in climate models. This higher sensitivity is of importance to assess the impact of climate variability on vegetation, in particular on agricultural productivity.

  19. 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.

  20. Time-Lapse Geophysical Measurements targeting Spatial and Temporal Variability in Biogenic Gas Production from Peat Soils in a Hydrologically Controlled Wetland in the Florida Everglades

    NASA Astrophysics Data System (ADS)

    Wright, W. J.; Shahan, T.; Sharp, N.; Comas, X.

    2015-12-01

    Peat soils are known to release globally significant amounts of methane (CH4) and carbon dioxide (CO2) to the atmosphere. However, uncertainties still remain regarding the spatio-temporal distribution of gas accumulations and triggering mechanisms of gas releasing events. Furthermore, most research on peatland gas dynamics has traditionally been focused on high latitude peatlands. Therefore, understanding gas dynamics in low-latitude peatlands (e.g. the Florida Everglades) is key to global climate research. Recent studies in the Everglades have demonstrated that biogenic gas flux values may vary when considering different temporal and spatial scales of measurements. The work presented here targets spatial variability in gas production and release at the plot scale in an approximately 85 m2 area, and targets temporal variability with data collected during the spring months of two different years. This study is located in the Loxahatchee Impoundment Landscape Assessment (LILA), a hydrologically controlled, landscape scale (30 Ha) model of the Florida Everglades. Ground penetrating radar (GPR) has been used in the past to investigate biogenic gas dynamics in peat soils, and is used in this study to monitor changes of in situ gas storage. Each year, a grid of GPR profiles was collected to image changes in gas distribution in 2d on a weekly basis, and several flux chambers outfitted with time-lapse cameras captured high resolution (hourly) gas flux measurements inside the GPR grid. Combining these methods allows us to use a mass balance approach to estimate spatial variability in gas production rates, and capture temporal variability in gas flux rates.

  1. Spatial Variability of Benthic-Pelagic Coupling in an Estuary Ecosystem: Consequences for Microphytobenthos Resuspension Phenomenon

    PubMed Central

    Ubertini, Martin; Lefebvre, Sébastien; Gangnery, Aline; Grangeré, Karine; Le Gendre, Romain; Orvain, Francis

    2012-01-01

    The high degree of physical factors in intertidal estuarine ecosystem increases material processing between benthic and pelagic compartments. In these ecosystems, microphytobenthos resuspension is a major phenomenon since its contribution to higher trophic levels can be highly significant. Understanding the sediment and associated microphytobenthos resuspension and its fate in the water column is indispensable for measuring the food available to benthic and pelagic food webs. To identify and hierarchize the physical/biological factors potentially involved in MPB resuspension, the entire intertidal area and surrounding water column of an estuarine ecosystem, the Bay des Veys, was sampled during ebb tide. A wide range of physical parameters (hydrodynamic regime, grain size of the sediment, and suspended matter) and biological parameters (flora and fauna assemblages, chlorophyll) were analyzed to characterize benthic-pelagic coupling at the bay scale. Samples were collected in two contrasted periods, spring and late summer, to assess the impact of forcing variables on benthic-pelagic coupling. A mapping approach using kriging interpolation enabled us to overlay benthic and pelagic maps of physical and biological variables, for both hydrological conditions and trophic indicators. Pelagic Chl a concentration was the best predictor explaining the suspension-feeders spatial distribution. Our results also suggest a perennial spatio-temporal structure of both benthic and pelagic compartments in the ecosystem, at least when the system is not imposed to intense wind, with MPB distribution controlled by both grain size and bathymetry. The benthic component appeared to control the pelagic one via resuspension phenomena at the scale of the bay. Co-inertia analysis showed closer benthic-pelagic coupling between the variables in spring. The higher MPB biomass observed in summer suggests a higher contribution to filter-feeders diets, indicating a higher resuspension effect in

  2. Intra-urban spatial variability of surface ozone in Riverside, CA: viability and validation of low-cost sensors

    NASA Astrophysics Data System (ADS)

    Sadighi, Kira; Coffey, Evan; Polidori, Andrea; Feenstra, Brandon; Lv, Qin; Henze, Daven K.; Hannigan, Michael

    2018-03-01

    Sensor networks are being more widely used to characterize and understand compounds in the atmosphere like ozone (O3). This study employs a measurement tool, called the U-Pod, constructed at the University of Colorado Boulder, to investigate spatial and temporal variability of O3 in a 200 km2 area of Riverside County near Los Angeles, California. This tool contains low-cost sensors to collect ambient data at non-permanent locations. The U-Pods were calibrated using a pre-deployment field calibration technique; all the U-Pods were collocated with regulatory monitors. After collocation, the U-Pods were deployed in the area mentioned. A subset of pods was deployed at two local regulatory air quality monitoring stations providing validation for the collocation calibration method. Field validation of sensor O3 measurements to minute-resolution reference observations resulted in R2 and root mean squared errors (RMSEs) of 0.95-0.97 and 4.4-5.9 ppbv, respectively. Using the deployment data, ozone concentrations were observed to vary on this small spatial scale. In the analysis based on hourly binned data, the median R2 values between all possible U-Pod pairs varied from 0.52 to 0.86 for ozone during the deployment. The medians of absolute differences were calculated between all possible pod pairs, 21 pairs total. The median values of those median absolute differences for each hour of the day varied between 2.2 and 9.3 ppbv for the ozone deployment. Since median differences between U-Pod concentrations during deployment are larger than the respective root mean square error values, we can conclude that there is spatial variability in this criteria pollutant across the study area. This is important because it means that citizens may be exposed to more, or less, ozone than they would assume based on current regulatory monitoring.

  3. Long-term Variability of Beach Cusps

    NASA Astrophysics Data System (ADS)

    Pianca, C.; Holman, R. A.; Siegle, E.

    2016-02-01

    The most curious morphological features observed on beaches are the cusps. Due to their rhythmic spacing, beach cusps have attracted many observers and many, often contradictory, theories as to their form. Moreover, most of the research about beach cusps has focused on their formation. Few had available long time series to study such things as the variability of alongshore and cross-shore position and spacing on the cusp field, the presence, longevity and interactions between higher and lower sets of cusps, and the processes by which cusp fields extend, shrink or change length scale. The purpose of this work is to use long-term data sets of video images from two study sites, an intermediate (Duck, USA, 26 years) and a reflective beach (Massaguaçu, Brazil, 3 years), to investigate the temporal and spatial changes of cusps conditions. Time-evolving shoreline data were first extracted using an algorithm called ASLIM (Pianca et al 2015). Cusps were then identified based on the band-passed variability of time exposure image data about this shoreline as a function of elevation relative to MSL. The identified beaches cusps will be analyzed for cusp spacing, positions (upper or lower cusps), alongshore variability, merging events, percentage of cusp events, patterns of the events and time scales of variability. Finally, the relationship of these characteristics to environmental conditions (wave, tides, beach conditions) will be studied.

  4. Spatial prediction of water quality variables along a main river channel, in presence of pollution hotspots.

    PubMed

    Rizo-Decelis, L D; Pardo-Igúzquiza, E; Andreo, B

    2017-12-15

    In order to treat and evaluate the available data of water quality and fully exploit monitoring results (e.g. characterize regional patterns, optimize monitoring networks, infer conditions at unmonitored locations, etc.), it is crucial to develop improved and efficient methodologies. Accordingly, estimation of water quality along fluvial ecosystems is a frequent task in environment studies. In this work, a particular case of this problem is examined, namely, the estimation of water quality along a main stem of a large basin (where most anthropic activity takes place), from observational data measured along this river channel. We adapted topological kriging to this case, where each watershed contains all the watersheds of the upstream observed data ("nested support effect"). Data analysis was additionally extended by taking into account the upstream distance to the closest contamination hotspot as an external drift. We propose choosing the best estimation method by cross-validation. The methodological approach in spatial variability modeling may be used for optimizing the water quality monitoring of a given watercourse. The methodology presented is applied to 28 water quality variables measured along the Santiago River in Western Mexico. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. The influence of spatial variability of lithological and morphometric characters on drainage network arrangement

    NASA Astrophysics Data System (ADS)

    Coco, Laura; Buccolini, Marcello

    2015-04-01

    Several factors control the spatial setting and temporal development of the drainage systems: climate, sea level changes, lithology, tectonics, morphometry, land use and land cover. The present work deals with the role of spatial variability of lithology and morphometry on drainage networks arrangement and presents some preliminary evaluations. The test area was the Periadriatic belt of central Italy, composed of Plio-Pleistocene foredeep succession (clay, sands and conglomerate) arranged in a northeastern vergence monocline. We analyzed 37 small basins directly flowing in the Adriatic Sea (18 in Abruzzi and 19 in Marche Region) that have homogenous climatic, eustatic, tectonic, land use and land cover features. For this reason, we could focus our research on lithology and morphometry. We used 10 m cell-size Italian DEM (TINITALY) supplying by INGV (National Institute of Geophysics and Volcanology) [from http://tinitaly.pi.ingv.it/] as source of morphometric data, and extracted watersheds and stream networks through an automatic procedure included in TauDEM toolbox within ArcGIS 9.3 [freely downloaded from http://hydrology.usu.edu/taudem/taudem5/index.html]. For each drainage basin, we reconstructed the topography prior to the inception of fluvial incision through the Topo-to-Raster interpolation tool, considering the heights of the watershed divide as elevation points and obtaining the pre-incision DEM in which the fluvial valleys resulted filled. On this DEM, we calculated the Morphometric Slope Index (MSI), developed by Buccolini et al. (2012), using the formula M SI = Rc -L -Ar/A2D in which Rc is circularity ratio, L is slope length, A2D and Ar are plane and surface area, respectively. In particular, Ar represents the three-dimensional area calculated on the pre-incision DEM. This index is a unique reference index for basin morphometry including both areal and linear features, such as size, shape, inclination, length and width. As drainage network parameter we

  6. A new numerical benchmark for variably saturated variable-density flow and transport in porous media

    NASA Astrophysics Data System (ADS)

    Guevara, Carlos; Graf, Thomas

    2016-04-01

    In subsurface hydrological systems, spatial and temporal variations in solute concentration and/or temperature may affect fluid density and viscosity. These variations could lead to potentially unstable situations, in which a dense fluid overlies a less dense fluid. These situations could produce instabilities that appear as dense plume fingers migrating downwards counteracted by vertical upwards flow of freshwater (Simmons et al., Transp. Porous Medium, 2002). As a result of unstable variable-density flow, solute transport rates are increased over large distances and times as compared to constant-density flow. The numerical simulation of variable-density flow in saturated and unsaturated media requires corresponding benchmark problems against which a computer model is validated (Diersch and Kolditz, Adv. Water Resour, 2002). Recorded data from a laboratory-scale experiment of variable-density flow and solute transport in saturated and unsaturated porous media (Simmons et al., Transp. Porous Medium, 2002) is used to define a new numerical benchmark. The HydroGeoSphere code (Therrien et al., 2004) coupled with PEST (www.pesthomepage.org) are used to obtain an optimized parameter set capable of adequately representing the data set by Simmons et al., (2002). Fingering in the numerical model is triggered using random hydraulic conductivity fields. Due to the inherent randomness, a large number of simulations were conducted in this study. The optimized benchmark model adequately predicts the plume behavior and the fate of solutes. This benchmark is useful for model verification of variable-density flow problems in saturated and/or unsaturated media.

  7. Spatial variability in secondary metabolites of the indo-pacific sponge Stylissa massa.

    PubMed

    Rohde, Sven; Gochfeld, Deborah J; Ankisetty, Sridevi; Avula, Bharathi; Schupp, Peter J; Slattery, Marc

    2012-05-01

    Chemical diversity represents a measure of selective pressures acting on genotypic variability. In order to understand patterns of chemical ecology and biodiversity in the environment, it is necessary to enhance our knowledge of chemical diversity within and among species. Many sponges produce variable levels of secondary metabolites in response to diverse biotic and abiotic environmental factors. This study evaluated intra-specific variability in secondary metabolites in the common Indo-Pacific sponge Stylissa massa over various geographic scales, from local to ocean basin. Several major metabolites were quantified in extracts from sponges collected in American Samoa, Pohnpei, Saipan, and at several sites and depths in Guam. Concentrations of several of these metabolites varied geographically across the Pacific basin, with American Samoa and Pohnpei exhibiting the greatest differences, and Guam and Saipan more similar to each other. There were also significant differences in concentrations among different sites and depths within Guam. The crude extract of S. massa exhibited feeding deterrence against the omnivorous pufferfish Canthigaster solandri at natural concentrations, however, none of the isolated compounds was deterrent at the maximum natural concentrations observed, nor were mixtures of these compounds, thus emphasizing the need for bioassay-guided isolation to characterize specific chemical defenses. Antibacterial activity against a panel of ecologically relevant pathogens was minimal. Depth transplants, predator exclusion, and UV protection experiments were performed, but although temporal variability in compound concentrations was observed, there was no evidence that secondary metabolite concentration in S. massa was induced by any of these factors. Although the reasons behind the variability observed in the chemical constituents of S. massa are still in question, all sponges are not created equal from a chemical standpoint, and these studies provide

  8. Optimization of Variable-Depth Liner Configurations for Increased Broadband Noise Reduction

    NASA Technical Reports Server (NTRS)

    Jones, M. G.; Watson, W. R.; Nark, D. M.; Schiller, N. H.; Born, J. C.

    2016-01-01

    This paper employs three acoustic propagation codes to explore variable-depth liner configurations for the NASA Langley Grazing Flow Impedance Tube (GFIT). The initial study demonstrates that a variable impedance can acceptably be treated as a uniform impedance if the spatial extent over which this variable impedance occurs is less than one-third of a wavelength of the incident sound. A constrained optimization study is used to design a variable-depth liner and to select an optimization metric. It also provides insight regarding how much attenuation can be achieved with variable-depth liners. Another optimization study is used to design a liner with much finer chamber depth resolution for the Mach 0.0 and 0.3 test conditions. Two liners are designed based on spatial rearrangement of chambers from this liner to determine whether the order is critical. Propagation code predictions suggest this is not the case. Both liners are fabricated via additive manufacturing and tested in the GFIT for the Mach 0.0 condition. Predicted and measured attenuations compare favorably across the full frequency range. These results clearly suggest that the chambers can be arranged in any order, thus offering the potential for innovative liner designs to minimize depth and weight.

  9. Low-Frequency Temporal Variability in Mira and Semiregular Variables

    NASA Astrophysics Data System (ADS)

    Templeton, Matthew R.; Karovska, M.; Waagen, E. O.

    2012-01-01

    We investigate low-frequency variability in a large sample of Mira and semiregular variables with long-term visual light curves from the AAVSO International Database. Our aim is to determine whether we can detect and measure long-timescale variable phenomena in these stars, for example photometric variations that might be associated with supergranular convection. We analyzed the long-term light curves of 522 variable stars of the Mira and SRa, b, c, and d classes. We calculated their low-frequency time-series spectra to characterize rednoise with the power density spectrum index, and then correlate this index with other observable characteristics such as spectral type and primary pulsation period. In our initial analysis of the sample, we see that the semiregular variables have a much broader range of spectral index than the Mira types, with the SRb subtype having the broadest range. Among Mira variables we see that the M- and S-type Miras have similarly wide ranges of index, while the C-types have the narrowest with generally shallower slopes. There is also a trend of steeper slope with larger amplitude, but at a given amplitude, a wide range of slopes are seen. The ultimate goal of the project is to identify stars with strong intrinsic red noise components as possible targets for resolved surface imaging with interferometry.

  10. Variable magnification variable dispersion glancing incidence imaging x-ray spectroscopic telescope

    NASA Technical Reports Server (NTRS)

    Hoover, Richard B. (Inventor)

    1991-01-01

    A variable magnification variable dispersion glancing incidence x-ray spectroscopic telescope capable of multiple high spatial revolution imaging at precise spectral lines of solar and stellar x-ray and extreme ultraviolet radiation sources includes a pirmary optical system which focuses the incoming radiation to a primary focus. Two or more rotatable carries each providing a different magnification are positioned behind the primary focus at an inclination to the optical axis, each carrier carrying a series of ellipsoidal diffraction grating mirrors each having a concave surface on which the gratings are ruled and coated with a mutlilayer coating to reflect by diffraction a different desired wavelength. The diffraction grating mirrors of both carriers are segments of ellipsoids having a common first focus coincident with the primary focus. A contoured detector such as an x-ray sensitive photogrpahic film is positioned at the second respective focus of each diffraction grating so that each grating may reflect the image at the first focus to the detector at the second focus. The carriers are selectively rotated to position a selected mirror for receiving radiation from the primary optical system, and at least the first carrier may be withdrawn from the path of the radiation to permit a selected grating on the second carrier to receive radiation.

  11. Variable magnification variable dispersion glancing incidence imaging x ray spectroscopic telescope

    NASA Technical Reports Server (NTRS)

    Hoover, Richard (Inventor)

    1990-01-01

    A variable magnification variable dispersion glancing incidence x ray spectroscopic telescope capable of multiple high spatial revolution imaging at precise spectral lines of solar and stellar x ray and extreme ultraviolet radiation sources includes a primary optical system which focuses the incoming radiation to a primary focus. Two or more rotatable carriers each providing a different magnification are positioned behind the primary focus at an inclination to the optical axis, each carrier carrying a series of ellipsoidal diffraction grating mirrors each having a concave surface on which the gratings are ruled and coated with a multilayer coating to reflect by diffraction a different desired wavelength. The diffraction grating mirrors of both carriers are segments of ellipsoids having a common first focus coincident with the primary focus. A contoured detector such as an x ray sensitive photographic film is positioned at the second respective focus of each diffraction grating so that each grating may reflect the image at the first focus to the detector at the second focus. The carriers are selectively rotated to position a selected mirror for receiving radiation from the primary optical system, and at least the first carrier may be withdrawn from the path of the radiation to permit a selected grating on the second carrier to receive radiation.

  12. Effects of spatially variable resolution on field-scale estimates of tracer concentration from electrical inversions using Archie's law

    USGS Publications Warehouse

    Singha, Kamini; Gorelick, Steven M.

    2006-01-01

    Two important mechanisms affect our ability to estimate solute concentrations quantitatively from the inversion of field-scale electrical resistivity tomography (ERT) data: (1) the spatially variable physical processes that govern the flow of current as well as the variation of physical properties in space and (2) the overparameterization of inverse models, which requires the imposition of a smoothing constraint (regularization) to facilitate convergence of the inverse solution. Based on analyses of field and synthetic data, we find that the ability of ERT to recover the 3D shape and magnitudes of a migrating conductive target is spatially variable. Additionally, the application of Archie's law to tomograms from field ERT data produced solute concentrations that are consistently less than 10% of point measurements collected in the field and estimated from transport modeling. Estimates of concentration from ERT using Archie's law only fit measured solute concentrations if the apparent formation factor is varied with space and time and allowed to take on unreasonably high values. Our analysis suggests that the inability to find a single petrophysical relation in space and time between concentration and electrical resistivity is largely an effect of two properties of ERT surveys: (1) decreased sensitivity of ERT to detect the target plume with increasing distance from the electrodes and (2) the smoothing imprint of regularization used in inversion.

  13. Spatial and temporal variability of fine particle composition and source types in five cities of Connecticut and Massachusetts.

    PubMed

    Lee, Hyung Joo; Gent, Janneane F; Leaderer, Brian P; Koutrakis, Petros

    2011-05-01

    To protect public health from PM(2.5) air pollution, it is critical to identify the source types of PM(2.5) mass and chemical components associated with higher risks of adverse health outcomes. Source apportionment modeling using Positive Matrix Factorization (PMF), was used to identify PM(2.5) source types and quantify the source contributions to PM(2.5) in five cities of Connecticut and Massachusetts. Spatial and temporal variability of PM(2.5) mass, components and source contributions were investigated. PMF analysis identified five source types: regional pollution as traced by sulfur, motor vehicle, road dust, oil combustion and sea salt. The sulfur-related regional pollution and traffic source type were major contributors to PM(2.5). Due to sparse ground-level PM(2.5) monitoring sites, current epidemiological studies are susceptible to exposure measurement errors. The higher correlations in concentrations and source contributions between different locations suggest less spatial variability, resulting in less exposure measurement errors. When concentrations and/or contributions were compared to regional averages, correlations were generally higher than between-site correlations. This suggests that for assigning exposures for health effects studies, using regional average concentrations or contributions from several PM(2.5) monitors is more reliable than using data from the nearest central monitor. Copyright © 2011 Elsevier B.V. All rights reserved.

  14. Spatial structure of monthly rainfall measurements average over 25 years and trends of the hourly variability of a current rainy day in Rwanda.

    NASA Astrophysics Data System (ADS)

    Nduwayezu, Emmanuel; Kanevski, Mikhail; Jaboyedoff, Michel

    2013-04-01

    Climate plays a vital role in a wide range of socio-economic activities of most nations particularly of developing countries. Climate (rainfall) plays a central role in agriculture which is the main stay of the Rwandan economy and community livelihood and activities. The majority of the Rwandan population (81,1% in 2010) relies on rain fed agriculture for their livelihoods, and the impacts of variability in climate patterns are already being felt. Climate-related events like heavy rainfall or too little rainfall are becoming more frequent and are impacting on human wellbeing.The torrential rainfall that occurs every year in Rwanda could disturb the circulation for many days, damages houses, infrastructures and causes heavy economic losses and deaths. Four rainfall seasons have been identified, corresponding to the four thermal Earth ones in the south hemisphere: the normal season (summer), the rainy season (autumn), the dry season (winter) and the normo-rainy season (spring). Globally, the spatial rainfall decreasing from West to East, especially in October (spring) and February (summer) suggests an «Atlantic monsoon influence» while the homogeneous spatial rainfall distribution suggests an «Inter-tropical front» mechanism. What is the hourly variability in this mountainous area? Is there any correlation with the identified zones of the monthly average series (from 1965 to 1990 established by the Rwandan meteorological services)? Where could we have hazards with several consecutive rainy days (using forecasted datas from the Norwegian Meteorological Institute)? Spatio-temporal analysis allows for identifying and explaining large-scale anomalies which are useful for understanding hydrological characteristics and subsequently predicting these hydrological events. The objective of our current research (Rainfall variability) is to proceed to an evaluation of the potential rainfall risk by applying advanced geospatial modelling tools in Rwanda: geostatistical

  15. Artificial Neural Network to Predict Vine Water Status Spatial Variability Using Multispectral Information Obtained from an Unmanned Aerial Vehicle (UAV)

    PubMed Central

    Bardeen, Matthew

    2017-01-01

    Water stress, which affects yield and wine quality, is often evaluated using the midday stem water potential (Ψstem). However, this measurement is acquired on a per plant basis and does not account for the assessment of vine water status spatial variability. The use of multispectral cameras mounted on unmanned aerial vehicle (UAV) is capable to capture the variability of vine water stress in a whole field scenario. It has been reported that conventional multispectral indices (CMI) that use information between 500–800 nm, do not accurately predict plant water status since they are not sensitive to water content. The objective of this study was to develop artificial neural network (ANN) models derived from multispectral images to predict the Ψstem spatial variability of a drip-irrigated Carménère vineyard in Talca, Maule Region, Chile. The coefficient of determination (R2) obtained between ANN outputs and ground-truth measurements of Ψstem were between 0.56–0.87, with the best performance observed for the model that included the bands 550, 570, 670, 700 and 800 nm. Validation analysis indicated that the ANN model could estimate Ψstem with a mean absolute error (MAE) of 0.1 MPa, root mean square error (RMSE) of 0.12 MPa, and relative error (RE) of −9.1%. For the validation of the CMI, the MAE, RMSE and RE values were between 0.26–0.27 MPa, 0.32–0.34 MPa and −24.2–25.6%, respectively. PMID:29084169

  16. Cataclysmic Variable Stars

    NASA Astrophysics Data System (ADS)

    Hellier, Coel

    2001-01-01

    Cataclysmic variable stars are the most variable stars in the night sky, fluctuating in brightness continually on timescales from seconds to hours to weeks to years. The changes can be recorded using amateur telescopes, yet are also the subject of intensive study by professional astronomers. That study has led to an understanding of cataclysmic variables as binary stars, orbiting so closely that material transfers from one star to the other. The resulting process of accretion is one of the most important in astrophysics. This book presents the first account of cataclysmic variables at an introductory level. Assuming no previous knowledge of the field, it explains the basic principles underlying the variability, while providing an extensive compilation of cataclysmic variable light curves. Aimed at amateur astronomers, undergraduates, and researchers, the main text is accessible to those with no mathematical background, while supplementary boxes present technical details and equations.

  17. Spatial variability of polycyclic aromatic hydrocarbon load of urban wet weather pollution in combined sewers.

    PubMed

    Gasperi, J; Moilleron, R; Chebbo, G

    2006-01-01

    In Paris, the OPUR research programme created an experimental on-site observatory of urban pollutant loads in combined sewer systems in order to characterise the dry and wet weather flows at different spatial scales. This article presents the first results on the spatial variability of the polycyclic aromatic hydrocarbon (PAH) load during wet weather flow (WWF). At the scale of a rain event, investigations revealed that (i) PAH concentrations were relatively homogenous whatever the spatial scale and were greater than those of the dry weather flow (DWF), (ii) PAH distributions between dissolved and particulate phases were constant, and (iii) PAH fingerprints exhibited a similar pattern for all catchments. Moreover, an evaluation of the contribution of DWF, runoff and erosion of sewer deposits to WWF load was established. According to the hypothesis on the runoff concentration, the contributions were evaluated at 14, 8 and 78%, respectively, at the scale of the Marais catchment. For all the catchments, the runoff contribution was found quite constant and evaluated at approximately 10%. The DWF contribution seems to increase with the catchment area, contrary to the sewer erosion contribution, which seems to decrease. However, this latter still remains an important source of pollution. These first trends should be confirmed and completed by more investigations of rain events.

  18. Long-term Observations of Intense Precipitation Small-scale Spatial Variability in a Semi-arid Catchment

    NASA Astrophysics Data System (ADS)

    Cropp, E. L.; Hazenberg, P.; Castro, C. L.; Demaria, E. M.

    2017-12-01

    In the southwestern US, the summertime North American Monsoon (NAM) provides about 60% of the region's annual precipitation. Recent research using high-resolution atmospheric model simulations and retrospective predictions has shown that since the 1950's, and more specifically in the last few decades, the mean daily precipitation in the southwestern U.S. during the NAM has followed a decreasing trend. Furthermore, days with more extreme precipitation have intensified. The current work focuses the impact of these long-term changes on the observed small-scale spatial variability of intense precipitation. Since limited long-term high-resolution observational data exist to support such climatological-induced spatial changes in precipitation frequency and intensity, the current work utilizes observations from the USDA-ARS Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona. Within this 150 km^2 catchment over 90 rain gauges have been installed since the 1950s, measuring at sub-hourly resolution. We have applied geospatial analyses and the kriging interpolation technique to identify long-term changes in the spatial and temporal correlation and anisotropy of intense precipitation. The observed results will be compared with the previously model simulated results, as well as related to large-scale variations in climate patterns, such as the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO).

  19. Impact of Subsurface Temperature Variability on Meteorological Variability: An AGCM Study

    NASA Astrophysics Data System (ADS)

    Mahanama, S. P.; Koster, R. D.; Liu, P.

    2006-05-01

    Anomalous atmospheric conditions can lead to surface temperature anomalies, which in turn can lead to temperature anomalies deep in the soil. The deep soil temperature (and the associated ground heat content) has significant memory -- the dissipation of a temperature anomaly may take weeks to months -- and thus deep soil temperature may contribute to the low frequency variability of energy and water variables elsewhere in the system. The memory may even provide some skill to subseasonal and seasonal forecasts. This study uses two long-term AGCM experiments to isolate the contribution of deep soil temperature variability to variability elsewhere in the climate system. The first experiment consists of a standard ensemble of AMIP-type simulations, simulations in which the deep soil temperature variable is allowed to interact with the rest of the system. In the second experiment, the coupling of the deep soil temperature to the rest of the climate system is disabled -- at each grid cell, the local climatological seasonal cycle of deep soil temperature (as determined from the first experiment) is prescribed. By comparing the variability of various atmospheric quantities as generated in the two experiments, we isolate the contribution of interactive deep soil temperature to that variability. The results show that interactive deep soil temperature contributes significantly to surface temperature variability. Interactive deep soil temperature, however, reduces the variability of the hydrological cycle (evaporation and precipitation), largely because it allows for a negative feedback between evaporation and temperature.

  20. Variability in results from negative binomial models for Lyme disease measured at different spatial scales.

    PubMed

    Tran, Phoebe; Waller, Lance

    2015-01-01

    Lyme disease has been the subject of many studies due to increasing incidence rates year after year and the severe complications that can arise in later stages of the disease. Negative binomial models have been used to model Lyme disease in the past with some success. However, there has been little focus on the reliability and consistency of these models when they are used to study Lyme disease at multiple spatial scales. This study seeks to explore how sensitive/consistent negative binomial models are when they are used to study Lyme disease at different spatial scales (at the regional and sub-regional levels). The study area includes the thirteen states in the Northeastern United States with the highest Lyme disease incidence during the 2002-2006 period. Lyme disease incidence at county level for the period of 2002-2006 was linked with several previously identified key landscape and climatic variables in a negative binomial regression model for the Northeastern region and two smaller sub-regions (the New England sub-region and the Mid-Atlantic sub-region). This study found that negative binomial models, indeed, were sensitive/inconsistent when used at different spatial scales. We discuss various plausible explanations for such behavior of negative binomial models. Further investigation of the inconsistency and sensitivity of negative binomial models when used at different spatial scales is important for not only future Lyme disease studies and Lyme disease risk assessment/management but any study that requires use of this model type in a spatial context. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. Factors Influencing Spatial and Annual Variability in Eelgrass (Zostera marina L.) Meadows in Willapa Bay, Washington, and Coos Bay, Oregon, Estuaries

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

    Thom, Ronald M.; Borde, Amy B.; Rumrill, Steven

    2003-08-01

    Environmental factors that influence annual variability and spatial differences in eelgrass meadows (Zostera marina L.) were examined within Willapa Bay, WA, and Coos Bay, OR, over a period of 4 years (1998-2001). A suite of eelgrass metrics were recorded annually at field sites that spanned the estuarine gradient from the marine-dominated to mesohaline regions. Growth of eelgrass plants was also monitored on a monthly basis within Sequim Bay, WA. Both the spatial cover and density of Z. marina were positively correlated with estuarine salinity and inversely correlated with temperature of the tideflat sediment. Experimental evidence verified that optimal eelgrass growthmore » occurred at highest salinities and relatively low temperatures. Eelgrass density, biomass, and the incident of flowering plants all increased substantially in Willapa Bay, and less so in Coos Bay, over the duration of the study. Warmer winters and cooler summers associated with the transition from El Ni?o to La Ni?a ocean conditions during the study period were correlated with the increase in eelgrass abundance and flowering. Anthropogenic factors (e.g., disturbance and erosion by vessel wakes and recreational shellfishing activities) may have contributed to spatial variability. Our findings indicate that large-scale changes in climate and nearshore ocean conditions can exert a strong regional influence on eelgrass abundance, which can vary annually by as much as 700% in Willapa Bay. Lower levels of variability observed in Coos Bay may be due to the stronger and more direct influence of the nearshore Pacific Ocean. We conclude that climate variation may have profound effects on the abundance and distribution of eelgrass meadows throughout the Pacific Northwest, and we anticipate that ocean conditions will emerge as a primary driving force for living estuarine resources and ecological processes that are associated with Z. marina beds within the landscape of these estuarine tidal basins.« less

  2. Relationships between pediatric asthma and socioeconomic/urban variables in Baltimore, Maryland

    NASA Technical Reports Server (NTRS)

    Kimes, Daniel; Ullah, Asad; Levine, Elissa; Nelson, Ross; Timmins, Sidey; Weiss, Sheila; Bollinger, Mary E.; Blaisdell, Carol

    2004-01-01

    Spatial relationships between clinical data for pediatric asthmatics (hospital and emergency department utilization rates), and socioeconomic and urban characteristics in Baltimore City were analyzed with the aim of identifying factors that contribute to increased asthma rates. Socioeconomic variables and urban characteristics derived from satellite data explained 95% of the spatial variation in hospital rates. The proportion of families headed by a single female was the most important variable accounting for 89% of the spatial variation. Evidence suggests that the high rates of hospital admissions and emergency department (ED) visits may partially be due to the difficulty of single parents with limited resources managing their child's asthma condition properly. This knowledge can be used for education towards mitigating ED and hospital events in Baltimore City.

  3. Multiscale analysis of the spatial variability of heavy metals and organic matter in soils and groundwater across Spain

    NASA Astrophysics Data System (ADS)

    Luque-Espinar, J. A.; Pardo-Igúzquiza, E.; Grima-Olmedo, J.; Grima-Olmedo, C.

    2018-06-01

    During the last years there has been an increasing interest in assessing health risks caused by exposure to contaminants found in soil, air, and water, like heavy metals or emerging contaminants. This work presents a study on the spatial patterns and interaction effects among relevant heavy metals (Sb, As and Pb) that may occur together in different minerals. Total organic carbon (TOC) have been analyzed too because it is an essential component in the regulatory mechanisms that control the amount of metal in soils. Even more, exposure to these elements is associated with a number of diseases and environmental problems. These metals can have both natural and anthropogenic origins. A key component of any exposure study is a reliable model of the spatial distribution the elements studied. A geostatistical analysis have been performed in order to show that selected metals are auto-correlated and cross-correlated and type and magnitude of such cross-correlation varies depending on the spatial scale under consideration. After identifying general trends, we analyzed the residues left after subtracting the trend from the raw variables. Three scales of variability were identified (compounds or factors) with scales of 5, 35 and 135 km. The first factor (F1) basically identifies anomalies of natural origin but, in some places, of anthropogenics origin as well. The other two are related to geology (F2 and F3) although F3 represents more clearly geochemical background related to large lithological groups. Likewise, mapping of two major structures indicates that significant faults have influence on the distribution of the studied elements. Finally, influence of soil and lithology on groundwater by means of contingency analysis was assessed.

  4. Remote sensing of the Canadian Arctic: Modelling biophysical variables

    NASA Astrophysics Data System (ADS)

    Liu, Nanfeng

    It is anticipated that Arctic vegetation will respond in a variety of ways to altered temperature and precipitation patterns expected with climate change, including changes in phenology, productivity, biomass, cover and net ecosystem exchange. Remote sensing provides data and data processing methodologies for monitoring and assessing Arctic vegetation over large areas. The goal of this research was to explore the potential of hyperspectral and high spatial resolution multispectral remote sensing data for modelling two important Arctic biophysical variables: Percent Vegetation Cover (PVC) and the fraction of Absorbed Photosynthetically Active Radiation (fAPAR). A series of field experiments were conducted to collect PVC and fAPAR at three Canadian Arctic sites: (1) Sabine Peninsula, Melville Island, NU; (2) Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU; and (3) Apex River Watershed (ARW), Baffin Island, NU. Linear relationships between biophysical variables and Vegetation Indices (VIs) were examined at different spatial scales using field spectra (for the Sabine Peninsula site) and high spatial resolution satellite data (for the CBAWO and ARW sites). At the Sabine Peninsula site, hyperspectral VIs exhibited a better performance for modelling PVC than multispectral VIs due to their capacity for sampling fine spectral features. The optimal hyperspectral bands were located at important spectral features observed in Arctic vegetation spectra, including leaf pigment absorption in the red wavelengths and at the red-edge, leaf water absorption in the near infrared, and leaf cellulose and lignin absorption in the shortwave infrared. At the CBAWO and ARW sites, field PVC and fAPAR exhibited strong correlations (R2 > 0.70) with the NDVI (Normalized Difference Vegetation Index) derived from high-resolution WorldView-2 data. Similarly, high spatial resolution satellite-derived fAPAR was correlated to MODIS fAPAR (R2 = 0.68), with a systematic

  5. A global perspective on Glacial- to Interglacial variability change

    NASA Astrophysics Data System (ADS)

    Rehfeld, Kira; Münch, Thomas; Ho, Sze Ling; Laepple, Thomas

    2017-04-01

    Changes in climate variability are more important for society than changes in the mean state alone. While we will be facing a large-scale shift of the mean climate in the future, its implications for climate variability are not well constrained. Here we quantify changes in temperature variability as climate shifted from the Last Glacial cold to the Holocene warm period. Greenland ice core oxygen isotope records provide evidence of this climatic shift, and are used as reference datasets in many palaeoclimate studies worldwide. A striking feature in these records is pronounced millennial variability in the Glacial, and a distinct reduction in variance in the Holocene. We present quantitative estimates of the change in variability on 500- to 1500-year timescales based on a global compilation of high-resolution proxy records for temperature which span both the Glacial and the Holocene. The estimates are derived based on power spectral analysis, and corrected using estimates of the proxy signal-to-noise ratios. We show that, on a global scale, variability at the Glacial maximum is five times higher than during the Holocene, with a possible range of 3-10 times. The spatial pattern of the variability change is latitude-dependent. While the tropics show no changes in variability, mid-latitude changes are higher. A slight overall reduction in variability in the centennial to millennial range is found in Antarctica. The variability decrease in the Greenland ice core oxygen isotope records is larger than in any other proxy dataset. These results therefore contradict the view of a globally quiescent Holocene following the instable Glacial, and imply that, in terms of centennial to millennial temperature variability, the two states may be more similar than previously thought.

  6. Efficient Reformulation of HOTFGM: Heat Conduction with Variable Thermal Conductivity

    NASA Technical Reports Server (NTRS)

    Zhong, Yi; Pindera, Marek-Jerzy; Arnold, Steven M. (Technical Monitor)

    2002-01-01

    Functionally graded materials (FGMs) have become one of the major research topics in the mechanics of materials community during the past fifteen years. FGMs are heterogeneous materials, characterized by spatially variable microstructure, and thus spatially variable macroscopic properties, introduced to enhance material or structural performance. The spatially variable material properties make FGMs challenging to analyze. The review of the various techniques employed to analyze the thermodynamical response of FGMs reveals two distinct and fundamentally different computational strategies, called uncoupled macromechanical and coupled micromechanical approaches by some investigators. The uncoupled macromechanical approaches ignore the effect of microstructural gradation by employing specific spatial variations of material properties, which are either assumed or obtained by local homogenization, thereby resulting in erroneous results under certain circumstances. In contrast, the coupled approaches explicitly account for the micro-macrostructural interaction, albeit at a significantly higher computational cost. The higher-order theory for functionally graded materials (HOTFGM) developed by Aboudi et al. is representative of the coupled approach. However, despite its demonstrated utility in applications where micro-macrostructural coupling effects are important, the theory's full potential is yet to be realized because the original formulation of HOTFGM is computationally intensive. This, in turn, limits the size of problems that can be solved due to the large number of equations required to mimic realistic material microstructures. Therefore, a basis for an efficient reformulation of HOTFGM, referred to as user-friendly formulation, is developed herein, and subsequently employed in the construction of the efficient reformulation using the local/global conductivity matrix approach. In order to extend HOTFGM's range of applicability, spatially variable thermal

  7. Spatial Dimension as a Variable in Quantum Mechanics

    NASA Astrophysics Data System (ADS)

    Doren, Douglas James

    Several approximation methods potentially useful in electronic structure calculations are developed. These methods all treat the spatial dimension, D, as a variable. In an Introduction, the motivations for these methods are described, with special attention to the semiclassical 1/D expansion. Several terms in this expansion have been calculated for two-electron atoms. The results have qualitative appeal but poor convergence properties when D = 3. Chapter 1 shows that this convergence problem is due to singularities in the energy at D = 1 and a method of removing their effects is demonstrated. Chapter 2 treats several model problems, showing how to identify special dimensions at which the energy becomes singular or the Hamiltonian simplifies. Expansions are developed about these special finite values of D which are quite accurate at low order, regardless of the physical parameters of the Hamiltonian. In Chapter 3, expansions about singular points in the energy at finite values of D are used to resum the 1/D series in cases where its leading orders are not sufficient. This leads to a hybrid expansion which typically improves on both the 1/D and the finite D series. These methods are applied in Chapter 4 to two -electron atoms. The ground state energy of few-electron systems is dominated by the presence of a pole when D = 1. The residue of this pole is determined by the eigenvalue of a simple limiting Schrodinger equation. The limit and first order correction are determined for both unapproximated nonrelativistic two-electron atoms and the Hartree-Fock approximation to them. The hybrid expansion using only the first few terms in the 1/D series determines the energy at arbitrary D, providing estimates accurate to four or five figures when D = 3. Degeneracies between D = 3 states and those in nonphysical dimensions are developed in Chapter 5 which provide additional applications for this series. Chapter 6 illustrates these methods in an application to the H(' -) ion, an

  8. Thermodynamic and Differential Entropy under a Change of Variables

    PubMed Central

    Hnizdo, Vladimir; Gilson, Michael K.

    2013-01-01

    The differential Shannon entropy of information theory can change under a change of variables (coordinates), but the thermodynamic entropy of a physical system must be invariant under such a change. This difference is puzzling, because the Shannon and Gibbs entropies have the same functional form. We show that a canonical change of variables can, indeed, alter the spatial component of the thermodynamic entropy just as it alters the differential Shannon entropy. However, there is also a momentum part of the entropy, which turns out to undergo an equal and opposite change when the coordinates are transformed, so that the total thermodynamic entropy remains invariant. We furthermore show how one may correctly write the change in total entropy for an isothermal physical process in any set of spatial coordinates. PMID:24436633

  9. Climate-mediated spatiotemporal variability in the terrestrial productivity across Europe

    NASA Astrophysics Data System (ADS)

    Wu, X.; Mahecha, M. D.; Reichstein, M.; Ciais, P.; Wattenbach, M.; Babst, F.; Frank, D.; Zang, C.

    2013-11-01

    Quantifying the interannual variability (IAV) of the terrestrial productivity and its sensitivity to climate is crucial for improving carbon budget predictions. However, the influence of climate and other mechanisms underlying the spatiotemporal patterns of IAV of productivity are not well understood. In this study we investigated the spatiotemporal patterns of IAV of historical observations of crop yields, tree ring width, remote sensing retrievals of FAPAR and NDVI, and other variables relevant to the terrestrial productivity in Europe in tandem with a set of climate variables. Our results reveal distinct spatial patterns in the IAV of most variables linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions. Our results further indicate that variations in the water balance during active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity related variables in temperate Europe. We also observe a~temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe, which is likely attributable to the recently increased IAV of water availability in these regions. These findings suggest nonlinear responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become more sensitive and more vulnerable to changes in water availability in the dry regions in Europe. The changing climate sensitivity of terrestrial productivity accompanied by the changing IAV of climate could impact carbon stocks and the net carbon balance of European ecosystems.

  10. Effects of soil spatial variability at the hillslope and catchment scales on characteristics of rainfall-induced landslides

    NASA Astrophysics Data System (ADS)

    Fan, Linfeng; Lehmann, Peter; Or, Dani

    2016-03-01

    Spatial variations in soil properties affect key hydrological processes, yet their role in soil mechanical response to hydro-mechanical loading is rarely considered. This study aims to fill this gap by systematically quantifying effects of spatial variations in soil type and initial water content on rapid rainfall-induced shallow landslide predictions at the hillslope- and catchment-scales. We employed a physically-based landslide triggering model that considers mechanical interactions among soil columns governed by strength thresholds. At the hillslope scale, we found that the emergence of weak regions induced by spatial variations of soil type and initial water content resulted in early triggering of landslides with smaller volumes of released mass relative to a homogeneous slope. At the catchment scale, initial water content was linked to a topographic wetness index, whereas soil type varied deterministically with soil depth considering spatially correlated stochastic components. Results indicate that a strong spatial organization of initial water content delays landslide triggering, whereas spatially linked soil type with soil depth promoted landslide initiation. Increasing the standard deviation and correlation length of the stochastic component of soil type increases landslide volume and hastens onset of landslides. The study illustrates that for similar external boundary conditions and mean soil properties, landslide characteristics vary significantly with soil variability, hence it must be considered for improved landslide model predictions.

  11. Impulse-variability theory: implications for ballistic, multijoint motor skill performance.

    PubMed

    Urbin, M A; Stodden, David F; Fischman, Mark G; Weimar, Wendi H

    2011-01-01

    Impulse-variability theory (R. A. Schmidt, H. N. Zelaznik, B. Hawkins, J. S. Frank, & J. T. Quinn, 1979) accounts for the curvilinear relationship between the magnitude and resulting variability of the muscular forces that influence the success of goal-directed limb movements. The historical roots of impulse-variability theory are reviewed in the 1st part of this article, including the relationship between movement speed and spatial error. The authors then address the relevance of impulse-variability theory for the control of ballistic, multijoint skills, such as throwing, striking, and kicking. These types of skills provide a stark contrast to the relatively simple, minimal degrees of freedom movements that characterized early research. However, the inherent demand for ballistic force generation is a strong parallel between these simple laboratory tasks and multijoint motor skills. Therefore, the authors conclude by recommending experimental procedures for evaluating the adequacy of impulse variability as a theoretical model within the context of ballistic, multijoint motor skill performance. Copyright © Taylor & Francis Group, LLC

  12. STOCHASTIC DESCRIPTION OF SUBGRID POLLUTANT VARIABILITY IN CMAQ

    EPA Science Inventory

    This paper describes a tool for investigating and describing fine scale spatial variability in model concentration fields with the goal of improving the use of air quality models for driving exposure modeling to assess human risk to hazardous air pollutants or air toxics. Region...

  13. The Ocean's Role in Outlet Glacier Variability: A Case Study from Uummannaq, Greenland

    NASA Astrophysics Data System (ADS)

    Sutherland, D.; Catania, G. A.; Bartholomaus, T. C.; Nash, J. D.; Shroyer, E.; Walker, R. T.; Stearns, L. A.

    2014-12-01

    The dynamics controlling the coupling between fjord circulation and outlet glacier movement are poorly understood. Here, we use oceanographic data collected from 2013-2014 from two west Greenland fjords, Rink Isbrae and Kangerdlugssup Sermerssua, to constrain the spatial and temporal variability observed in fjord circulation. We aim to quantify the ocean's role, if any, in explaining the marked differences in glacier behavior from two systems that are in close proximity to one another. Combining time series data from a set of subsurface moorings with repeat transects in each fjord allows an unprecedented look at the temporal and spatial variability in circulation. We find significant differences in the variability in each fjord and discuss the implications for the glaciers.

  14. Spatial variability of shelf sediments in the STRATAFORM natural laboratory, Northern California

    USGS Publications Warehouse

    Goff, J.A.; Wheatcroft, R.A.; Lee, H.; Drake, D.E.; Swift, D.J.P.; Fan, S.

    2002-01-01

    The "Correlation Length Experiment", an intensive box coring effort on the Eel River shelf (Northern California) in the summer of 1997, endeavored to characterize the lateral variability of near-surface shelf sediments over scales of meters to kilometers. Coring focused on two sites, K60 and S60, separated by ??? 15 km along the 60 m isobath. The sites are near the sand-to-mud transition, although K60 is sandier owing to its proximity to the Eel River mouth. Nearly 140 cores were collected on dip and strike lines with core intervals from < 10m to 1 km. Measurements on each core included bulk density computed from gamma-ray attenuation, porosity converted from resistivity measurements, and surficial grain size. Grain size was also measured over the full depth range within a select subset of cores. X-radiograph images were also examined. Semi-variograms were computed for strike, dip, and down-hole directions at each site. The sand-to-mud transition exerts a strong influence on all measurements: on average, bulk density increases and porosity decreases with regional increases in mean grain size. Analysis of bulk density measurements indicates very strong contrasts in the sediment variability at K60 and S60. No coherent bedding is seen at K60; in the strike direction, horizontal variability is "white" (fully uncorrelated) from the smallest scales examined (a few meters) to the largest (8 km), with a variance equal to that seen within the cores. In contrast, coherent bedding exists at S60 related to the preservation of the 1995 flood deposit. A correlatable structure is found in the strike direction with a decorrelation distance of ??? 800 m, and can be related to long-wavelength undulations in the topography and/or thickness of the flood layer or overburden. We hypothesize that the high degree of bulk density variability at K60 is a result of more intense physical reworking of the seabed in the sandier environment. Without significant averaging, the resistivity

  15. Spatial and temporal variability of cv. Tempranillo phenology and grape quality within the Ribera del Duero DO (Spain) and relationships with climate.

    PubMed

    Ramos, M C; Jones, G V; Yuste, J

    2015-12-01

    The aim of this work was to analyze spatial phenology and grape quality variability related to the climatic characteristics within the Ribera del Duero Designation of Origin (DO). Twenty plots planted with cv. Tempranillo and distributed within the DO were analyzed for phenology from 2004 to 2013. Grape quality parameters at ripening (berry weight, sugar content, acidity and pH, and anthocyanins) were analyzed in 26 plots for the period 2003-2013. The relationships between phenology and grape parameters with different climatic variables were confirmed with a multivariate analysis. On average, bud break was April 27(th), bloom June 17(th), and veraison August 12th. However, phenology during the time period showed high variability, with differences between years of up to 21 days for a phenology stage. The earliest dates were observed in dry years (2005, 2006, and to a lesser degree in 2009) while the later phenology dates occurred in the wettest year of the period (2008). High correlations were found between veraison date and temperature variables as well as with precipitation-evapotranspiration recorded during the bloom-veraison period. These effects tended to be higher in the central part of the DO. Grape quality parameters also showed high variability among the dry and the wet years, and the influence of extreme temperatures on color development as well as the effect of available water on acidity were observed.

  16. Spatial and temporal variability of cv. Tempranillo phenology and grape quality within the Ribera del Duero DO (Spain) and relationships with climate

    NASA Astrophysics Data System (ADS)

    Ramos, M. C.; Jones, G. V.; Yuste, J.

    2015-12-01

    The aim of this work was to analyze spatial phenology and grape quality variability related to the climatic characteristics within the Ribera del Duero Designation of Origin (DO). Twenty plots planted with cv. Tempranillo and distributed within the DO were analyzed for phenology from 2004 to 2013. Grape quality parameters at ripening (berry weight, sugar content, acidity and pH, and anthocyanins) were analyzed in 26 plots for the period 2003-2013. The relationships between phenology and grape parameters with different climatic variables were confirmed with a multivariate analysis. On average, bud break was April 27th, bloom June 17th, and veraison August 12th. However, phenology during the time period showed high variability, with differences between years of up to 21 days for a phenology stage. The earliest dates were observed in dry years (2005, 2006, and to a lesser degree in 2009) while the later phenology dates occurred in the wettest year of the period (2008). High correlations were found between veraison date and temperature variables as well as with precipitation-evapotranspiration recorded during the bloom-veraison period. These effects tended to be higher in the central part of the DO. Grape quality parameters also showed high variability among the dry and the wet years, and the influence of extreme temperatures on color development as well as the effect of available water on acidity were observed.

  17. Intraspecific variability in functional traits matters: case study of Scots pine.

    PubMed

    Laforest-Lapointe, Isabelle; Martínez-Vilalta, Jordi; Retana, Javier

    2014-08-01

    Although intraspecific trait variability is an important component of species ecological plasticity and niche breadth, its implications for community and functional ecology have not been thoroughly explored. We characterized the intraspecific functional trait variability of Scots pine (Pinus sylvestris) in Catalonia (NE Spain) in order to (1) compare it to the interspecific trait variability of trees in the same region, (2) explore the relationships among functional traits and the relationships between them and stand and climatic variables, and (3) study the role of functional trait variability as a determinant of radial growth. We considered five traits: wood density (WD), maximum tree height (H max), leaf nitrogen content (Nmass), specific leaf area (SLA), and leaf biomass-to-sapwood area ratio (B L:A S). A unique dataset was obtained from the Ecological and Forest Inventory of Catalonia (IEFC), including data from 406 plots. Intraspecific trait variation was substantial for all traits, with coefficients of variation ranging between 8% for WD and 24% for B L:A S. In some cases, correlations among functional traits differed from those reported across species (e.g., H max and WD were positively related, whereas SLA and Nmass were uncorrelated). Overall, our model accounted for 47% of the spatial variability in Scots pine radial growth. Our study emphasizes the hierarchy of factors that determine intraspecific variations in functional traits in Scots pine and their strong association with spatial variability in radial growth. We claim that intraspecific trait variation is an important determinant of responses of plants to changes in climate and other environmental factors, and should be included in predictive models of vegetation dynamics.

  18. Using a chemistry transport model to account for the spatial variability of exposure concentrations in epidemiologic air pollution studies.

    PubMed

    Valari, Myrto; Menut, Laurent; Chatignoux, Edouard

    2011-02-01

    Environmental epidemiology and more specifically time-series analysis have traditionally used area-averaged pollutant concentrations measured at central monitors as exposure surrogates to associate health outcomes with air pollution. However, spatial aggregation has been shown to contribute to the overall bias in the estimation of the exposure-response functions. This paper presents the benefit of adding features of the spatial variability of exposure by using concentration fields modeled with a chemistry transport model instead of monitor data and accounting for human activity patterns. On the basis of county-level census data for the city of Paris, France, and a Monte Carlo simulation, a simple activity model was developed accounting for the temporal variability between working and evening hours as well as during transit. By combining activity data with modeled concentrations, the downtown, suburban, and rural spatial patterns in exposure to nitrogen dioxide, ozone, and PM2.5 (particulate matter [PM] < or = 10 microm in aerodynamic diameter) were captured and parametrized. Exposures predicted with this model were used in a time-series study of the short-term effect of air pollution on total nonaccidental mortality for the 4-yr period from 2001 to 2004. It was shown that the time series of the exposure surrogates developed here are less correlated across co-pollutants than in the case of the area-averaged monitor data. This led to less biased exposure-response functions when all three co-pollutants were inserted simultaneously in the same regression model. This finding yields insight into pollutant-specific health effects that are otherwise masked by the high correlation among co-pollutants.

  19. North Polar Radiative Flux Variability from 2002 Through 2014

    NASA Technical Reports Server (NTRS)

    Rutan, David; Rose, Fred; Doelling, David; Kato, Seiji; Smith, Bill, Jr.

    2017-01-01

    NASA's Clouds and the Earth's Radiant Energy System (CERES) project produces the SYN1Deg data product. SYN1deg provides global, 1deg gridded, hourly estimates of Top of Atmosphere (TOA) (CERES observations and calculations) and atmospheric and surface radiative flux (calculations). Examples of 12 year North Polar averages of some variables are shown to the right. Given recent interest in polar science we focus here on TOA and Surface validation of calculated irradiant fluxes. TOA upward longwave irradiance calculations match the CERES observations well both spatially and temporally with correlations remaining strong through PC 6. Compare SYN1Deg Calculations & Meteorological Teleconnections. TOA reflected shortwave irradiance calculations match the CERES observations well both spatially and temporally with correlations remaining string through PC 7. Comparing SYN1Deg calculations to teleconnection patterns requires expanding the area to 30N for EOF analyses. Correlating the Principal Components of various variables to teleconnection time series indicates which variable is most highly correlated with which teleconnection signal. The tables indicate the Pacific North American Oscillation is most correlated to the OLR EOF 1, and the North American Oscillation is correlated most closely to surface LW flux down EOF 1.

  20. Seasonal and spatial variability of rainfall redistribution under Scots pine and Downy oak forests in Mediterranean conditions

    NASA Astrophysics Data System (ADS)

    Garcia-Estringana, Pablo; Latron, Jérôme; Molina, Antonio J.; Llorens, Pilar

    2013-04-01

    The large degree of temporal and spatial variability of throughfall input patterns may lead to significant changes in the volume of water that reach the soil in each location, and beyond in the hydrological response of forested hillslopes. To explore the role of vegetation in the temporal and spatial redistribution of rainfall in Mediterranean climatic conditions two contrasted stands were monitored. One is a Downy oak forest (Quercus pubescens) and the other is a Scots pine forest (Pinus sylvestris), both are located in the Vallcebre research catchments (NE Spain, 42° 12'N, 1° 49'E). These plots are representative of Mediterranean mountain areas with spontaneous afforestation by Scots pine as a consequence of the abandonment of agricultural terraces, formerly covered by Downy oaks. The monitoring design of each plot consists of a set of 20 automatic rain recorders and 40 automatic soil moisture probes located below the canopy. 100 hemispheric photographs of the canopy were used to place the instruments at representative locations (in terms of canopy cover) within the plot. Bulk rainfall, stemflow and meteorological conditions above the forest cover are also automatically recorded. Canopy cover as well as biometric characteristics of the plots are also regularly measured. This work presents the first results describing the variability of throughfall beneath each forest stand and compares the persistence of temporal patterns among stands, and for the oaks stand among the leafed and the leafless period. Furthermore, canopy structure, rainfall characteristics and meteorological conditions of rainfall events are evaluated as main drivers of throughfall redistribution.

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