A Markov chain Monte Carlo (MCMC) based algorithm was developed to derive upscaled land surface p... more A Markov chain Monte Carlo (MCMC) based algorithm was developed to derive upscaled land surface parameters for a soil‐vegetation‐atmosphere‐transfer (SVAT) model using time series data of satellite‐measured atmospheric forcings (e.g., precipitation), and land surface states (e.g., soil moisture and vegetation). This study focuses especially on the evaluation of soil moisture measurements of the Aqua satellite based Advanced Microwave Scanning Radiometer (AMSR‐E) instrument using the new MCMC‐based scaling algorithm. Soil moisture evolution was modeled at a spatial scale comparable to the AMSR‐E soil moisture product, with the hypothesis that the characterization of soil microwave emissions and their variations with space and time on soil surface within the AMSR‐E footprint can be represented by an ensemble of upscaled soil hydraulic parameters. We demonstrated the features of the MCMC‐based parameter upscaling algorithm (from field to satellite footprint scale) within a SVAT model f...
Estimation of effective/average soil hydraulic properties for large land areas is an outstanding ... more Estimation of effective/average soil hydraulic properties for large land areas is an outstanding issue in hydrologic modeling. The goal of this study is to provide flow‐specific rules and guidelines for upscaling soil hydraulic properties in an areally heterogeneous field. In this study, we examined the impact of areal heterogeneity of soil hydraulic parameters on soil ensemble behavior for steady state evaporation and infiltration. The specific objectives of this study are (1) to address the impact of averaging methods of shape parameters and parameter correlation on ensemble behavior of steady state flow in an areally heterogeneous field and (2) to investigate the effectiveness of the “average parameters” in terms of the degree of correlation between hydraulic property parameters for the steady state evaporation and infiltration in unsaturated soil. Using an analytical solution of Richards' equation, the ensemble characteristics and flow dynamics based on average hydraulic pro...
Process‐based soil hydrologic models require input of saturated hydraulic conductivity (Ksat). Ho... more Process‐based soil hydrologic models require input of saturated hydraulic conductivity (Ksat). However, model users often have limited access to measured data and thus use published or estimated values for many site‐specific hydrologic and environmental applications. We proposed an algorithm that uses the Karhunen‐Loève expansion (KLE) in conjunction with the Markov chain Monte Carlo (MCMC) technique, which employs measured soil moisture values to characterize the saturated hydraulic conductivity of an agricultural field at a 30 m resolution. The study domain is situated in the Walnut Creek watershed, Iowa, with soybean crop (in 2005) and well‐defined top (atmospheric) and bottom (groundwater) boundary conditions. The KLE algorithm parameterizes and generates Ksat fields with random correlation lengths that are used in the SWMS_3D model for predicting the soil moisture dynamics for two different scenarios: (1) the van Genuchten soil hydraulic parameters (except Ksat) are constant an...
Soil moisture is an important hydrologic state variable critical to successful hydroclimatic and ... more Soil moisture is an important hydrologic state variable critical to successful hydroclimatic and environmental predictions. Soil moisture varies both in space and time because of spatio‐temporal variations in precipitation, soil properties, topographic features, and vegetation characteristics. In recent years, air‐ and space‐borne remote sensing campaigns have successfully demonstrated the use of passive microwave remote sensing to map soil moisture status near the soil surface (≈0–0.05 m below the ground) at various spatial scales. In this study root zone (e.g., ≈0–0.6 m below the ground) soil moisture distributions were estimated across the Little Washita watershed (Oklahoma) by assimilating near‐surface soil moisture data from remote sensing measurements using the Electronically Scanned Thinned Array Radiometer (ESTAR) with an ensemble Kalman filter (EnKF) technique coupled with a numerical one‐dimensional vadose zone flow model (HYDRUS‐ET). The resulting distributed root zone so...
In this study, the authors investigate effective soil hydraulic parameter averaging schemes for s... more In this study, the authors investigate effective soil hydraulic parameter averaging schemes for steady-state flow in heterogeneous shallow subsurfaces useful to land–atmosphere interaction modeling. “Effective” soil hydraulic parameters of the heterogeneous shallow subsurface are obtained by conceptualizing the soil as an equivalent homogeneous medium. It requires that the effective homogeneous soil discharges the same mean surface moisture flux (evaporation or infiltration) as the heterogeneous media. Using the simple Gardner unsaturated hydraulic conductivity function, the authors derive the effective value for the saturated hydraulic conductivity Ks or the shape factor α under various hydrologic scenarios and input hydraulic parameter statistics. Assuming one-dimensional vertical moisture movement in the shallow unsaturated soils, both scenarios of horizontal (across the surface landscape) and vertical (across the soil profile) heterogeneities are investigated. The effects of hyd...
Sinkholes and the Engineering and Environmental Impacts of Karst, Sep 22, 2005
An experimental rainfall simulation plot (7 x 14 m) in the Edwards Aquifer region of Texas was es... more An experimental rainfall simulation plot (7 x 14 m) in the Edwards Aquifer region of Texas was established in dense juniper land cover to measure the effects of brush clearing on runoff. This project includes the monitoring of lateral subsurface flow using a trench (2.5 m deep x 8 m ...
Over the last hundred years, the semi-arid region of Southwestern United States has undergone a c... more Over the last hundred years, the semi-arid region of Southwestern United States has undergone a considerable change in landscape. The region that was once primarily covered by native grass has been invaded with brushy species, such as ash juniper (cedar) and mesquite. This brush encroachment has resulted in a major effect on the hydrologic cycle. With new brush species dominating
ABSTRACT Temporal and spatial variability of water content in soil results from a complex interac... more ABSTRACT Temporal and spatial variability of water content in soil results from a complex interaction of different factors such as duration and frequency of rainfall, soil layering, vegetation, and topography. The objectives of this study were (i) to use a resistant median-polishing scheme to quantify the temporal variability of a depth and a horizontal location factor in an additive model, and (ii) to investigate the time stability of those two factors at a detailed temporal scale during different infiltration and redistributions cycles. Time series of water content were measured at 5 depths and 12 locations along a transect of 6 m using Time Domain Reflectometry (TDR). Measurements were repeated every 2-hours for 168 days under natural boundary conditions. At each time step, the mean water content of the soil profile, 5 depth factors and 12 location factors were estimated. The time series of these factors were qualitatively interpreted and related to the atmospheric and prevailing soil conditions. It was found that micro-heterogeneity plays an important role, even at this small plot-scale. The relative contributions of the factors were dependent on the antecedent soil moisture conditions. Also, the ratio of the deterministic variance, i.e., variance explained by the deterministic factors, of water content to the observed variance is variable in time.
The goal of this project is to gain further understanding of soil moisture/temperature dynamics a... more The goal of this project is to gain further understanding of soil moisture/temperature dynamics at different spatio-temporal scales and physical controls/parameters.We created a comprehensive GIS database, which has been accessed extensively by NASA Land Surface Hydrology investigators (and others), is located at the following URL: http://www.essc.psu.edu/nasalsh. For soil moisture field experiments such as SGP97, SGP99, SMEX02, and SMEX03, cartographic products were designed for multiple applications, both pre- and post-mission. Premission applications included flight line planning and field operations logistics, as well as general insight into the extent and distribution of soil, vegetation, and topographic properties for the study areas. The cartographic products were created from original spatial information resources that were imported into Adobe Illustrator, where the maps were created and PDF versions were made for distribution and download.
ABSTRACT Pedo Transfer Functions (PTFs) based on Artificial Neural Networks (ANNs) have been used... more ABSTRACT Pedo Transfer Functions (PTFs) based on Artificial Neural Networks (ANNs) have been used in the field of hydrology for some time. However, while most previous studies derive and adopt these parameters at matching spatial scales (1:1) of input and output data, here we present two methodologies to derive the soil water retention function at the point or local scale using PTFs trained with coarser scale input data. In the first study, a conventional ANN was trained using soil texture and bulk density data from the SSURGO database (scale 1:24,000) and then used for predicting the soil water contents at different pressure heads with point scale data (1:1) inputs. Suitable bias correction was applied to the resulting output and used to construct the van Genuchten soil water characteristic curve. The results show good agreement between the soil water retention curves constructed from the ANN-based PTFs and the field observations at the local scale. In the second study we employed a Markov Chain Monte Carlo (MCMC) based Bayesian Neural Network to derive the soil water content values. While conventional ANN training attempts to describe the target variable as a function of the input vector and the training weights, Bayesian training attempts to update the weight vector with information available in the data. Comparisons of the outputs from the two methodologies are presented and their respective advantages and disadvantages are highlighted. These methods have potential as suitable tools to tackle the dual problems of parameter estimation and their scaling in one simple package.
... Authors: Jana, RB; Mohanty, BP. ... Further, the theoretical basis is validated with data fro... more ... Authors: Jana, RB; Mohanty, BP. ... Further, the theoretical basis is validated with data from two different sites - one at the Panola Mountain Research Watershed in Georgia, and the other in the Little Washita watershed in Oklahoma. ...
ABSTRACT Soil moisture and soil hydrologic fluxes (infiltration, ET, runoff) are affected at diff... more ABSTRACT Soil moisture and soil hydrologic fluxes (infiltration, ET, runoff) are affected at different scales by the spatial variability of influencing factors such as soil, topography, vegetation, and climatic forcings such as precipitation and temperature patterns. Understanding the nature of the linkage between these physical controls and the soil hydraulic parameters is critical in developing efficient scaling schemes for effective hydrologic modeling at large domains. We present results from a multi-location, multi-scale study designed to tease out the dominant physical control of soil hydraulic parameter variability at each scale of interest, and the evolution of the dominance with scale. Mathematical techniques such as Wavelet analysis and Karhunen-Loeve expansion are applied to bring out the extent of influence of the physical controls on the distribution signatures of the hydraulic parameters at the various scales. Data from diverse hydro-climatic locations across the globe, at various scales, derived from multiple platforms/sensors such as in-situ sensors, airborne remote sensors, and various satellite-borne remote sensors are used in this study to improve our understanding of the processes governing the hydraulic variability of soils. The study also considers the correlations among the soil hydraulic parameters, and their progression with change in scale. Further, we test the efficacy of certain existing soil hydraulic parameter scaling algorithms with regard to preserving these relationships (both among the hydraulic parameters, and with the physical controls) and provide guidelines for their usage at specific scales.
A Markov chain Monte Carlo (MCMC) based algorithm was developed to derive upscaled land surface p... more A Markov chain Monte Carlo (MCMC) based algorithm was developed to derive upscaled land surface parameters for a soil‐vegetation‐atmosphere‐transfer (SVAT) model using time series data of satellite‐measured atmospheric forcings (e.g., precipitation), and land surface states (e.g., soil moisture and vegetation). This study focuses especially on the evaluation of soil moisture measurements of the Aqua satellite based Advanced Microwave Scanning Radiometer (AMSR‐E) instrument using the new MCMC‐based scaling algorithm. Soil moisture evolution was modeled at a spatial scale comparable to the AMSR‐E soil moisture product, with the hypothesis that the characterization of soil microwave emissions and their variations with space and time on soil surface within the AMSR‐E footprint can be represented by an ensemble of upscaled soil hydraulic parameters. We demonstrated the features of the MCMC‐based parameter upscaling algorithm (from field to satellite footprint scale) within a SVAT model f...
Estimation of effective/average soil hydraulic properties for large land areas is an outstanding ... more Estimation of effective/average soil hydraulic properties for large land areas is an outstanding issue in hydrologic modeling. The goal of this study is to provide flow‐specific rules and guidelines for upscaling soil hydraulic properties in an areally heterogeneous field. In this study, we examined the impact of areal heterogeneity of soil hydraulic parameters on soil ensemble behavior for steady state evaporation and infiltration. The specific objectives of this study are (1) to address the impact of averaging methods of shape parameters and parameter correlation on ensemble behavior of steady state flow in an areally heterogeneous field and (2) to investigate the effectiveness of the “average parameters” in terms of the degree of correlation between hydraulic property parameters for the steady state evaporation and infiltration in unsaturated soil. Using an analytical solution of Richards' equation, the ensemble characteristics and flow dynamics based on average hydraulic pro...
Process‐based soil hydrologic models require input of saturated hydraulic conductivity (Ksat). Ho... more Process‐based soil hydrologic models require input of saturated hydraulic conductivity (Ksat). However, model users often have limited access to measured data and thus use published or estimated values for many site‐specific hydrologic and environmental applications. We proposed an algorithm that uses the Karhunen‐Loève expansion (KLE) in conjunction with the Markov chain Monte Carlo (MCMC) technique, which employs measured soil moisture values to characterize the saturated hydraulic conductivity of an agricultural field at a 30 m resolution. The study domain is situated in the Walnut Creek watershed, Iowa, with soybean crop (in 2005) and well‐defined top (atmospheric) and bottom (groundwater) boundary conditions. The KLE algorithm parameterizes and generates Ksat fields with random correlation lengths that are used in the SWMS_3D model for predicting the soil moisture dynamics for two different scenarios: (1) the van Genuchten soil hydraulic parameters (except Ksat) are constant an...
Soil moisture is an important hydrologic state variable critical to successful hydroclimatic and ... more Soil moisture is an important hydrologic state variable critical to successful hydroclimatic and environmental predictions. Soil moisture varies both in space and time because of spatio‐temporal variations in precipitation, soil properties, topographic features, and vegetation characteristics. In recent years, air‐ and space‐borne remote sensing campaigns have successfully demonstrated the use of passive microwave remote sensing to map soil moisture status near the soil surface (≈0–0.05 m below the ground) at various spatial scales. In this study root zone (e.g., ≈0–0.6 m below the ground) soil moisture distributions were estimated across the Little Washita watershed (Oklahoma) by assimilating near‐surface soil moisture data from remote sensing measurements using the Electronically Scanned Thinned Array Radiometer (ESTAR) with an ensemble Kalman filter (EnKF) technique coupled with a numerical one‐dimensional vadose zone flow model (HYDRUS‐ET). The resulting distributed root zone so...
In this study, the authors investigate effective soil hydraulic parameter averaging schemes for s... more In this study, the authors investigate effective soil hydraulic parameter averaging schemes for steady-state flow in heterogeneous shallow subsurfaces useful to land–atmosphere interaction modeling. “Effective” soil hydraulic parameters of the heterogeneous shallow subsurface are obtained by conceptualizing the soil as an equivalent homogeneous medium. It requires that the effective homogeneous soil discharges the same mean surface moisture flux (evaporation or infiltration) as the heterogeneous media. Using the simple Gardner unsaturated hydraulic conductivity function, the authors derive the effective value for the saturated hydraulic conductivity Ks or the shape factor α under various hydrologic scenarios and input hydraulic parameter statistics. Assuming one-dimensional vertical moisture movement in the shallow unsaturated soils, both scenarios of horizontal (across the surface landscape) and vertical (across the soil profile) heterogeneities are investigated. The effects of hyd...
Sinkholes and the Engineering and Environmental Impacts of Karst, Sep 22, 2005
An experimental rainfall simulation plot (7 x 14 m) in the Edwards Aquifer region of Texas was es... more An experimental rainfall simulation plot (7 x 14 m) in the Edwards Aquifer region of Texas was established in dense juniper land cover to measure the effects of brush clearing on runoff. This project includes the monitoring of lateral subsurface flow using a trench (2.5 m deep x 8 m ...
Over the last hundred years, the semi-arid region of Southwestern United States has undergone a c... more Over the last hundred years, the semi-arid region of Southwestern United States has undergone a considerable change in landscape. The region that was once primarily covered by native grass has been invaded with brushy species, such as ash juniper (cedar) and mesquite. This brush encroachment has resulted in a major effect on the hydrologic cycle. With new brush species dominating
ABSTRACT Temporal and spatial variability of water content in soil results from a complex interac... more ABSTRACT Temporal and spatial variability of water content in soil results from a complex interaction of different factors such as duration and frequency of rainfall, soil layering, vegetation, and topography. The objectives of this study were (i) to use a resistant median-polishing scheme to quantify the temporal variability of a depth and a horizontal location factor in an additive model, and (ii) to investigate the time stability of those two factors at a detailed temporal scale during different infiltration and redistributions cycles. Time series of water content were measured at 5 depths and 12 locations along a transect of 6 m using Time Domain Reflectometry (TDR). Measurements were repeated every 2-hours for 168 days under natural boundary conditions. At each time step, the mean water content of the soil profile, 5 depth factors and 12 location factors were estimated. The time series of these factors were qualitatively interpreted and related to the atmospheric and prevailing soil conditions. It was found that micro-heterogeneity plays an important role, even at this small plot-scale. The relative contributions of the factors were dependent on the antecedent soil moisture conditions. Also, the ratio of the deterministic variance, i.e., variance explained by the deterministic factors, of water content to the observed variance is variable in time.
The goal of this project is to gain further understanding of soil moisture/temperature dynamics a... more The goal of this project is to gain further understanding of soil moisture/temperature dynamics at different spatio-temporal scales and physical controls/parameters.We created a comprehensive GIS database, which has been accessed extensively by NASA Land Surface Hydrology investigators (and others), is located at the following URL: http://www.essc.psu.edu/nasalsh. For soil moisture field experiments such as SGP97, SGP99, SMEX02, and SMEX03, cartographic products were designed for multiple applications, both pre- and post-mission. Premission applications included flight line planning and field operations logistics, as well as general insight into the extent and distribution of soil, vegetation, and topographic properties for the study areas. The cartographic products were created from original spatial information resources that were imported into Adobe Illustrator, where the maps were created and PDF versions were made for distribution and download.
ABSTRACT Pedo Transfer Functions (PTFs) based on Artificial Neural Networks (ANNs) have been used... more ABSTRACT Pedo Transfer Functions (PTFs) based on Artificial Neural Networks (ANNs) have been used in the field of hydrology for some time. However, while most previous studies derive and adopt these parameters at matching spatial scales (1:1) of input and output data, here we present two methodologies to derive the soil water retention function at the point or local scale using PTFs trained with coarser scale input data. In the first study, a conventional ANN was trained using soil texture and bulk density data from the SSURGO database (scale 1:24,000) and then used for predicting the soil water contents at different pressure heads with point scale data (1:1) inputs. Suitable bias correction was applied to the resulting output and used to construct the van Genuchten soil water characteristic curve. The results show good agreement between the soil water retention curves constructed from the ANN-based PTFs and the field observations at the local scale. In the second study we employed a Markov Chain Monte Carlo (MCMC) based Bayesian Neural Network to derive the soil water content values. While conventional ANN training attempts to describe the target variable as a function of the input vector and the training weights, Bayesian training attempts to update the weight vector with information available in the data. Comparisons of the outputs from the two methodologies are presented and their respective advantages and disadvantages are highlighted. These methods have potential as suitable tools to tackle the dual problems of parameter estimation and their scaling in one simple package.
... Authors: Jana, RB; Mohanty, BP. ... Further, the theoretical basis is validated with data fro... more ... Authors: Jana, RB; Mohanty, BP. ... Further, the theoretical basis is validated with data from two different sites - one at the Panola Mountain Research Watershed in Georgia, and the other in the Little Washita watershed in Oklahoma. ...
ABSTRACT Soil moisture and soil hydrologic fluxes (infiltration, ET, runoff) are affected at diff... more ABSTRACT Soil moisture and soil hydrologic fluxes (infiltration, ET, runoff) are affected at different scales by the spatial variability of influencing factors such as soil, topography, vegetation, and climatic forcings such as precipitation and temperature patterns. Understanding the nature of the linkage between these physical controls and the soil hydraulic parameters is critical in developing efficient scaling schemes for effective hydrologic modeling at large domains. We present results from a multi-location, multi-scale study designed to tease out the dominant physical control of soil hydraulic parameter variability at each scale of interest, and the evolution of the dominance with scale. Mathematical techniques such as Wavelet analysis and Karhunen-Loeve expansion are applied to bring out the extent of influence of the physical controls on the distribution signatures of the hydraulic parameters at the various scales. Data from diverse hydro-climatic locations across the globe, at various scales, derived from multiple platforms/sensors such as in-situ sensors, airborne remote sensors, and various satellite-borne remote sensors are used in this study to improve our understanding of the processes governing the hydraulic variability of soils. The study also considers the correlations among the soil hydraulic parameters, and their progression with change in scale. Further, we test the efficacy of certain existing soil hydraulic parameter scaling algorithms with regard to preserving these relationships (both among the hydraulic parameters, and with the physical controls) and provide guidelines for their usage at specific scales.
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Papers by Binayak Mohanty