Download or read book Simulation of Spatial and Temporal Variability of Soil Moisture Using Swatre Model and Geostatistical Procedures written by Suria Darma Tarigan and published by . This book was released on 1991 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Analysis of Large Scale Spatial Variability of Soil Moisture Using a Geostatistical Method written by and published by . This book was released on 2010 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial and temporal soil moisture dynamics are critically needed to improve the parameterization for hydrological and meteorological modeling processes. This study evaluates the statistical spatial structure of large-scale observed and simulated estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial in calibration and validation of large-scale satellite based data assimilation systems. Spatial analysis using geostatistical approaches was used to validate modeled soil moisture by the Agriculture Meteorological (AGRMET) model using in situ measurements of soil moisture from a state-wide environmental monitoring network (Oklahoma Mesonet). The results show that AGRMET data produces larger spatial decorrelation compared to in situ based soil moisture data. The precipitation storms drive the soil moisture spatial structures at large scale, found smaller decorrelation length after precipitation. This study also evaluates the geostatistical approach for mitigation for quality control issues within in situ soil moisture network to estimates at soil moisture at unsampled stations.

Download or read book Precision Agriculture written by John V. Lake and published by John Wiley & Sons. This book was released on 2008-04-30 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book investigates new agricultural systems such as organic and green manuring, as well as integrated pest management practices, and looks at how they can improve farm productivity against the enhancements for the environment. Much of the information presented focuses on microinvestigation of the soil, and on the effects of soil variability within fields on yields and nutrient flows.

Download or read book Spatial and Temporal Modeling of Soil Moisture Using Remote Sensing written by Scott D. Lindsey and published by . This book was released on 1991 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Modeling the Spatial and Temporal Distribution of Soil Moisture at Watershed Scales Using Remote Sensing and GIS written by PJ. Starks and published by . This book was released on 2003 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soil water content (2v) is of fundamental importance in meteorology, agriculture, and hydrology, among other scientific disciplines. In hydrology, 2v partitions rainfall into runoff and infiltration, thus impacting surface and groundwater recharge, flood forecasting, and flow routing modeling. Measurement of 2v at a point is straightforward, but point measurements are inadequate for watershed hydrology due to variability of soil properties, land cover, and meteorological inputs over space. Passive microwave remote sensing systems have been successfully used to provide regional estimates of surface 2v (0-5 cm surface layer) at the spatial resolution of the sensor. To extend these data to other depths and scales, a two-layer soil water budget model was used to combine remotely sensed estimates of 2v and spatial information on land cover, soil type and meteorological inputs to predict root zone 2v over a 611 km2 watershed. A GIS was used to pre-process and geo-register spatial data sets for input into the soil water budget model, and analyze the results.

Download or read book Understanding Spatio Temporal Variability and Associated Physical Controls of Near Surface Soil Moisture in Different Hydro Climates written by Champa Joshi and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Near-surface soil moisture is a key state variable of the hydrologic cycle and plays a significant role in the global water and energy balance by affecting several hydrological, ecological, meteorological, geomorphologic, and other natural processes in the land-atmosphere continuum. Presence of soil moisture in the root zone is vital for the crop and plant life cycle. Soil moisture distribution is highly non-linear across time and space. Various geophysical factors (e.g., soil properties, topography, vegetation, and weather/climate) and their interactions control the spatio-temporal evolution of soil moisture at various scales. Understanding these interactions is crucial for the characterization of soil moisture dynamics occurring in the vadose zone. This dissertation focuses on understanding the spatio-temporal variability of near-surface soil moisture and the associated physical control(s) across varying measurement support (point-scale and passive microwave airborne/satellite remote sensing footprint-scale), spatial extents (field-, watershed-, and regional-scale), and changing hydro-climates. Various analysis techniques (e.g., time stability, geostatistics, Empirical Orthogonal Function, and Singular Value Decomposition) have been employed to characterize near-surface soil moisture variability and the role of contributing physical control(s) across space and time. Findings of this study can be helpful in several hydrological research/applications, such as, validation/calibration and downscaling of remote sensing data products, planning and designing effective soil moisture monitoring networks and field campaigns, improving performance of soil moisture retrieval algorithm, flood/drought prediction, climate forecast modeling, and agricultural management practices. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/149547

Download or read book Analysis and Modeling of Space time Organization of Remotely Sensed Soil Moisture written by and published by . This book was released on 2001 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The characterization and modeling of the spatial variability of soil moisture is an important problem for various hydrological, ecological, and atmospheric processes. This dissertation proposes a compact representation of interdependencies among soil moisture distribution and environmental factors using two complimentary approaches. In the first approach, a stochastic framework is developed for characterizing the soil moisture distribution. The resulting model provides closed form analytical solutions for (a) the variance of soil moisture distribution; (b) the covariance between soil moisture distribution and soil properties; and (c) the covariance between soil moisture distribution and topography as a function of soil heterogeneity, topography and soil moisture. Series of simulations are performed using various combinations of parameters. Comparisons between simulated results and a number of field observations show qualitative agreement. Application of the proposed stochastic framework requires statistical information of soil characteristics. In the second approach, possibility of inferring soil physical properties from remotely sensed brightness temperature maps is explored. Remotely sensed brightness temperature data from a single drying cycle from Washita '92 Experiment and two different ANN architectures (Feed-Forward Neural Network (FFNN), Self Organizing Map (SOM)) are used to classify soil types into three categories. Results show that FFNN yield better classification accuracy (about 80% accuracy) than SOM (about 70% accuracy). The SOM, however, has an advantage because it requires very little information regarding soil properties. To classify soil into more than three categories, this study suggests the use of multiple-drying-cycle brightness temperature data. Use of multiple-drying-cycle brightness temperature data from the Southern Great Plains suggests that it is possible to classify soil into more than three groups. It appears that the requirement of rapidly changing decision boundary, in the case of space-time evolution of brightness temperature data, will restrict the FFNN model to yield better accuracy. Motivated by these observations, a simple prototype-based classifier, known as 1-NN model, is used which yield 86% classification accuracy for six textural groups. A comparison of classification error regions for both models suggests that, for the given input representation, further improvement in classification accuracy is feasible with different ANN structure.

Download or read book Geostatistical Simulation written by Christian Lantuejoul and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with the estimation of natural resources using the Monte Carlo methodology. It includes a set of tools to describe the morphological, statistical and stereological properties of spatial random models. Furthermore, the author presents a wide range of spatial models, including random sets and functions, point processes and object populations applicable to the geosciences. The text is based on a series of courses given in the USA and Latin America to civil, mining and petroleum engineers as well as graduate students in statistics. It is the first book to discuss the geostatistical simulation techniques in such a specific way.

Download or read book Modeling and Application of Soil Moisture at Varying Spatial Scales with Parameter Scaling written by Narendra Narayan Das and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The dissertation focuses on characterization of subpixel variability within a satellite-based remotely sensed coarse-scale soil moisture footprint. The underlying heterogeneity of coarse-scale soil moisture footprint is masked by the area-integrated properties within the sensor footprint. Therefore, the soil moisture values derived from these measurements are an area average. The variability in soil moisture within the footprint is introduced by inherent spatial variability present in rainfall, and geophysical parameters (vegetation, topography, and soil). The geophysical parameters/variables typically interact in a complex fashion to make soil moisture evolution and dependent processes highly variable, and also, introduce nonlinearity across spatio-temporal scales. To study the variability and scaling characteristics of soil moisture, a quasi-distributed Soil-Vegetation-Atmosphere-Transfer (SVAT) modeling framework is developed to simulate the hydrological dynamics, i.e., the fluxes and the state variables within the satellite-based soil moisture footprint. The modeling framework is successfully tested and implemented in different hydroclimatic regions during the research. New multiscale data assimilation and Markov Chain Monte Carlo (MCMC) techniques in conjunction with the SVAT modeling framework are developed to quantify subpixel variability and assess multiscale soil moisture fields within the coarse-scale satellite footprint. Reasonable results demonstrate the potential to use these techniques to validate multiscale soil moisture data from future satellite mission e.g., Soil Moisture Active Passive (SMAP) mission of NASA. The results also highlight the physical controls of geophysical parameters on the soil moisture fields for various hydroclimatic regions. New algorithm that uses SVAT modeling framework is also proposed and its application demonstrated, to derive the stochastic soil hydraulic properties (i.e., saturated hydraulic conductivity) and surface features (i.e., surface roughness and volume scattering) related to radar remote sensing of soil moisture.

Download or read book Spatial Variability Models and Prediction Analysis of Soil Properties Using Geostatistics written by Tejo Vikash Bheemasetti and published by . This book was released on 2015 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soils are composed of solid, water and air phases whose characteristics are highly variable. The interactions of these phases in the soil matrix can lead to different types of topographical formations and characteristics. Due to the uncertainty and complex interactions among these phases, studies on soils have always been a challenging problem for engineers. These variations and uncertainties make it necessary for engineers to adopt new techniques and methods to analyze soil properties in order to determine or interpret their generalized behaviors and patterns. Existing research in variability analysis tends to focus on the distribution of the soil properties, reliability-based design, and simulation of random fields. Despite an increase in the probabilistic and statistical analysis, many challenges remain in incorporating the spatial variability present in the soil properties into prediction analysis. In this research study, a framework was developed using univariate statistics and randomized random variable theory for analyzing the spatially-varied soil properties. The spatial variability present in the soil properties was modeled using the geostatistical tool, Variograms. The variability models were utilized to interpret the soil properties in three different studies in geotechnical engineering, encompassing natural soils, man-made soils, and natural soils rich with chemicals such as sulfates. This research highlights the adaptability of the framework for analyzing the soil properties varying from low-to-high variability.

Download or read book Soil Moisture Dynamics and Soil Moisture Controlled Runoff Processes at Different Spatial Scales written by Thomas Gräff and published by . This book was released on 2011 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soil moisture is a key state variable that controls runoff formation, infiltration and partitioning of radiation into latent and sensible heat. However, the experimental characterisation of near surface soil moisture patterns and their controls on runoff formation remains a challenge. This subject was one aspect of the BMBF-funded OPAQUE project (operational discharge and flooding predictions in head catchments). As part of that project the focus of this dissertation is on: (1) testing the methodology and feasibility of the Spatial TDR technology in producing soil moisture profiles along TDR probes, including an inversion technique of the recorded signal in heterogeneous field soils, (2) the analysis of spatial variability and temporal dynamics of soil moisture at the field scale including field experiments and hydrological modelling, (3) the application of models of different complexity for understanding soil moisture dynamics and its importance for runoff generation as well as for improving the prediction of runoff volumes. To fulfil objective 1, several laboratory experiments were conducted to understand the influence of probe rod geometry and heterogeneities in the sampling volume under different wetness conditions. This includes a detailed analysis on how these error sources affect retrieval of soil moisture profiles in soils. Concerning objective 2 a sampling strategy of two TDR clusters installed in the head water of the Wilde Weißeritz catchment (Eastern Ore Mountains, Germany) was used to investigate how well the catchment stateʺ can be characterised by means of distributed soil moisture data observed at the field scale. A grassland site and a forested site both located on gentle slopes were instrumented with two Spatial TDR clusters that consist of up to 39 TDR probes. Process understanding was gained by modelling the interaction of evapotranspiration and soil moisture with the hydrological process model CATFLOW. A field scale irrigation experiment was carried out to investigate near subsurface processes at the hillslope scale. The interactions of soil moisture and runoff formation were analysed using discharge data from three nested catchments: the Becherbach with a size of 2 kmø, the Rehefeld catchment (17 kmø) and the superordinate Ammelsdorf catchment (49 kmø).Statistical analyses including observations of pre-event runoff, soil moisture and different rainfall characteristics were employed to predict stream flow volume. On the different scales a strong correlation between the average soil moisture and the runoff coefficients of rainfall-runoff events could be found, which almost explains equivalent variability as the pre-event runoff. Furthermore, there was a strong correlation between surface soil moisture and subsurface wetness with a hysteretic behaviour between runoff soil moisture. To fulfil objective 3 these findings were used in a generalised linear model (GLM) analysis which combines state variables describing the catchments antecedent wetness and variables describing the meteorological forcing in order to predict event runoff coefficients. GLM results were compared to simulations with the catchment model WaSiM ETH. Hereby were the model results of the GLMs always better than the simulations with WaSiM ETH. The GLM analysis indicated that the proposed sampling strategy of clustering TDR probes in typical functional units is a promising technique to explore soil moisture controls on runoff generation and can be an important link between the scales. Long term monitoring of such sites could yield valuable information for flood warning and forecasting by identifying critical soil moisture conditions for the former and providing a better representation of the initial moisture conditions for the latter.

Download or read book Scale Issues in Hydrological Modelling written by J. D. Kalma and published by John Wiley & Sons. This book was released on 1995-09-11 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a growing need for appropriate models which address the management of land and water resources and ecosystems at large space and time scales. Theories of non-linear hydrological processes must be extrapolated to large-scale, three-dimensional natural systems such as drainage basins, flood plains and wetlands. This book reports on recent progress in research on scale issues in hydrological modelling. It brings together 27 papers from two special issues of the journal Hydrological Processes. The book makes a significant contribution towards developing research strategies for linking model parameterisations across a range of temporal and spatial scales. The papers selected for this book reflect the tremendous advances which have been made in research into scale issues in hydrological modelling during the last ten years.

Download or read book Spatial Variation of Soil Type and Soil Moisture in the Regional Atmospheric Modeling System written by and published by . This book was released on 2001 with total page 5 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soil characteristics (texture and moisture) are typically assumed to be initially constant when performing simulations with the Regional Atmospheric Modeling System (RAMS). Soil texture is spatially homogeneous and time-independent, while soil moisture is often spatially homogeneous initially, but time-dependent. This report discusses the conversion of a global data set of Food and Agriculture Organization (FAO) soil types to RAMS soil texture and the subsequent modifications required in RAMS to ingest this information. Spatial variations in initial soil moisture obtained from the National Center for Environmental Predictions (NCEP) large-scale models are also introduced. Comparisons involving simulations over the southeastern United States for two different time periods, one during warmer, more humid summer conditions, and one during cooler, dryer winter conditions, reveals differences in surface conditions related to increases or decreases in near-surface atmospheric moisture con tent as a result of different soil properties. Three separate simulation types were considered. The base case assumed spatially homogeneous soil texture and initial soil moisture. The second case assumed variable soil texture and constant initial soil moisture, while the third case allowed for both variable soil texture and initial soil moisture. The simulation domain was further divided into four geographically distinct regions. It is concluded there is a more dramatic impact on thermodynamic variables (surface temperature and dewpoint) than on surface winds, and a more pronounced variability in results during the summer period. While no obvious trends in surface winds or dewpoint temperature were found relative to observations covering all regions and times, improvement in surface temperatures in most regions and time periods was generally seen with the incorporation of variable soil texture and initial soil moisture.

Download or read book A Framework for the Prediction of Soil Moisture written by and published by . This book was released on 2004 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: Through its influence on the mobility of troops and materiel, the interaction between weather and landscape is of primary importance to the effectiveness and timeliness of Army operations. More specifically. knowledge of the spatial and temporal variability in soil moisture over large areas, at the scale of tactical operations (^100 m), has the potential to dramatically improve trafficability assessments. The majority of Army operations are conducted in regions where field observations of soil moisture are sparse in space and/or time or completely unavailable. However, remotely sensed information about the factors that affect the spatial variability in soil moisture over a range of spatial scales are available. We present here a framework by which we can fuse these remotely sensed data representing the various factors affecting soil moisture through the existing tRIBS hydrologic model to produce forecasts of the spatial distribution of soil moisture. Using data assimilation techniques these forecasts can be dynamically updated when remotely sensed observations of soil moisture using become available. When used in conjunction with tactical decision aids. such as IWEDA. the proposed fusion of data through tRIBS has the potential to improve trafficability assessments and other soil moisture dependent Army operations.

Download or read book Spatial Modeling in GIS and R for Earth and Environmental Sciences written by Hamid Reza Pourghasemi and published by Elsevier. This book was released on 2019-01-18 with total page 800 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial Modeling in GIS and R for Earth and Environmental Sciences offers an integrated approach to spatial modelling using both GIS and R. Given the importance of Geographical Information Systems and geostatistics across a variety of applications in Earth and Environmental Science, a clear link between GIS and open source software is essential for the study of spatial objects or phenomena that occur in the real world and facilitate problem-solving. Organized into clear sections on applications and using case studies, the book helps researchers to more quickly understand GIS data and formulate more complex conclusions. The book is the first reference to provide methods and applications for combining the use of R and GIS in modeling spatial processes. It is an essential tool for students and researchers in earth and environmental science, especially those looking to better utilize GIS and spatial modeling. - Offers a clear, interdisciplinary guide to serve researchers in a variety of fields, including hazards, land surveying, remote sensing, cartography, geophysics, geology, natural resources, environment and geography - Provides an overview, methods and case studies for each application - Expresses concepts and methods at an appropriate level for both students and new users to learn by example

Download or read book Modeling Spatial Variability Using Geostatistical Simulation written by AJ. Desbarats and published by . This book was released on 1996 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper, the last in a four part introduction to geostatistics, describes the application of simulation to site investigation problems. Geostatistical simulation is a method for generating digital representations or "maps" of a variable that are consistent with its values at sampled locations and with its in situ spatial variability, as characterized by histogram and variogram models. Continuing the synthetic case study of the three previous papers, the reader is lead through the steps of a geostatistical simulation. The simulated fields are then compared with the exhaustive data sets describing the synthetic site. Finally, it is shown how simulated fields can be used to answer questions concerning alternative site remediation strategies.

Download or read book Footprint scale Soil Moisture Spatial temporal Variability and Implications for Satellite Validation written by Dongryeol Ryu and published by . This book was released on 2006 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: