Ground-based investigation of soil moisture variability within remote sensing footprints during the Southern Great Plains 1997 (SGP97) Hydrology Experiment

Surface soil moisture content is highly variable in both space and time. While remote sensing provides an effective methodology for mapping surface moisture content over large areas, it averages within-pixel variability thereby masking the underlying heterogeneity observed at the land surface. This variability must be better understood in order to rigorously evaluate sensor performance and to enhance the utility of the larger-scale remotely sensed averages by quantifying the underlying variability that remote sensing cannot record explicitly. In support of the Southern Great Plains 1997 (SGP97) Hydrology Experiment (a surface soil moisture mapping mission conducted between June 18 and July 17, 1997, in central Oklahoma) an investigation was conducted to characterize soil moisture variability within remote sensing footprints (approximately 0.64 km2) with more certainty than would be afforded with conventional gravimetric moisture content sampling. Nearly every day during the experiment period, portable impedance probes were used to intensively monitor volumetric moisture content in the 0- to 6-cm surface soil layer at six footprint-sized fields scattered over the SGP97 study area. A minimum of 49 daily moisture content measurements were made on most fields. Higher-resolution grid and transect data were also collected periodically. In total, more than 11,000 impedance probe measurements of volumetric moisture content were made at the six sites by over 35 SGP97 participants. The wide spatial distribution of the sites, combined with the intensive, near-daily monitoring, provided a unique opportunity (relative to previous smaller-scale and shorter-duration soil moisture studies) to characterize variations in surface moisture content over a range of wetness conditions. In this paper the range and temporal dynamics of the variability in moisture content within each of the six fields are described, as are general relationships between the variability and footprint-mean moisture content. Results indicate that distinct differences in mean moisture content between the six sites are consistent with variations in soil type, vegetation cover, and rainfall gradients. Within fields the standard deviation, coefficient of variation, skewness, and kurtosis increased with decreasing moisture content; the distribution of surface moisture content evolved from negatively skewed/nonnormal under very wet conditions, to normal in the midrange of mean moisture content, to positively skewed/nonnormal under dry conditions; and agricultural practices of row tilling and terracing were shown to exert a major control on observed moisture content variations. Results presented here can be utilized to better evaluate sensor performance, to extrapolate estimates of subgrid-scale variations in moisture content across the entire SGP97 region, and in the parameterization of soil moisture dynamics in hydrological and land surface models. | Surface soil moisture content is highly variable in both space and time. While remote sensing provides an effective methodology for mapping surface moisture content over large areas, it averages within-pixel variability thereby masking the underlying heterogeneity observed at the land surface. This variability must be better understood in order to rigorously evaluate sensor performance and to enhance the utility of the larger-scale remotely sensed averages by quantifying the underlying variability that remote sensing cannot record explicitly. In support of the Southern Great Plains 1997 (SGP97) Hydrology Experiment (a surface soil moisture mapping mission conducted between June 18 and July 17, 1997, in central Oklahoma) an investigation was conducted to characterize soil moisture variability within remote sensing footprints (approximately 0.64 km2) with more certainty than would be afforded with conventional gravimetric moisture content sampling. Nearly every day during the experiment period, portable impedance probes were used to intensively monitor volumetric moisture content in the 0- to 6-cm surface soil layer at six footprint-sized fields scattered over the SGP97 study area. A minimum of 49 daily moisture content measurements were made on most fields. Higher-resolution grid and transect data were also collected periodically. In total, more than 11,000 impedance probe measurements of volumetric moisture content were made at the six sites by over 35 SGP97 participants. The wide spatial distribution of the sites, combined with the intensive, near-daily monitoring, provided a unique opportunity (relative to previous smaller-scale and shorter-duration soil moisture studies) to characterize variations in surface moisture content over a range of wetness conditions. In this paper the range and temporal dynamics of the variability in moisture content within each of the six fields are described, as are general relationships between the variability and footprint-mean moisture content. Results indicate that distinct differences in mean moisture content between the six sites are consistent with variations in soil type, vegetation cover, and rainfall gradients. Within fields the standard deviation, coefficient of variation, skewness, and kurtosis increased with decreasing moisture content; the distribution of surface moisture content evolved from negatively skewed/nonnormal under very wet conditions, to normal in the midrange of mean moisture content, to positively skewed/nonnormal under dry conditions; and agricultural practices of row tilling and terracing were shown to exert a major control on observed moisture content variations. Results presented here can be utilized to better evaluate sensor performance, to extrapolate estimates of subgrid-scale variations in moisture content across the entire SGP97 region, and in the parameterization of soil moisture dynamics in hydrological and land surface models

An Innovative Approach for Locating and Evaluating Subsurface Pathways for Nitrogen Loss

Fundamental watershed-scale processes governing chemical flux to neighboring ecosystems are so poorly understood that effective strategies for mitigating chemical contamination cannot be formulated. Characterization of evapotranspiration, surface runoff, plant uptake, subsurface preferential flow, behavior of the chemicals in neighboring ecosystems, and an understanding of how crop management practices influence these processes are needed. Adequate characterization of subsurface flow has been especially difficult because conventional sampling methods are ineffective for measuring preferential flow of water and solutes. A sampling strategy based on ground-penetrating radar (GPR) mapping of subsurface structures coupled with near real-time soil moisture data, surface topography, remotely sensed imagery, and a geographic information system (GIS) appears to offer a means of accurately identifying subsurface preferential flow pathways. Four small adjacent watersheds draining into a riparian wetland and first-order stream at the USDA-ARS Beltsville Agricultural Research Center, Beltsville, MD are being studied with this protocol. The spatial location of some preferential flow pathways for chemicals exiting these agricultural watersheds to the neighboring ecosystems have been identified. Confirmation of the pathways is via examination of patterns in yield monitor data and remote sensing imagery