Some focused applications of our current work include understanding movement of septic effluent in leach fields and identifying causes of leach field failure, high resolution soil texture mapping in the deeper vadose zone to understand water and contaminant movement, quantifying surface and sub-surface heterogeneity for hydrological applications, spatial upscaling of soil moisture from the Representative Elementary Volume (REV) to field scale for agricultural applications, soil hydraulic parameterization at the REV scale and beyond. We use a combination of advanced sensing techniques, statistical and process-based modeling in our lab.
Developing An ArcGIS toolbox for Automating Digitization of Septic Systems: While septic systems are often cited as a potential source of contamination of water bodies, counties seldom have digitized information on septic system location and ages. Since money is limited to generate such resources, we are developing an automated system based on GIS and Remote sensing to populate such a database for Jackson county, GA. Funded by Environmental Protection Division, Georgia.
Nutrient transport at the hillslope scale: Lateral transport of nutrients to open water bodies through groundwater can be highly impacted by preferential flowpaths. These preferential flowpaths are difficult to identify by using conventional field based soil monitoring methods. We are exploring the use of geophysics techniques like Electrical Resistance Tomography (ERT) to identify preferential flowpaths in the Piedmont geological system.
Assessing the effects of machinery traffic on alfalfa yield and nutritive value via remote sensing techniques: Vehicular traffic on agricultural fields can cause soil compaction and undesired effects on soil permeability. The problem is compounded for perennial crops like alfalfa which undergo multiple harvests. In collaboration with University of Wisconsin, we are studying the impact of machinery traffic on alfalfa yield and nutritive value in a green house setting. Funded by United States Department of Agriculture – National Institute of Food and Agriculture (Alfalfa and Forage Research Program)
Space-time scaling of remotely sensed soil moisture: An understanding of the variability in soil moisture and evapotranspiration is critical to management of water resources in agriculture, flood prediction, drought estimation and watershed management. However, both these variables vary considerably in space and time which makes it challenging to estimate them globally using only ground based measurements that provide only localized estimates. Remote sensing of soil moisture has emerged as one of the most powerful techniques to provide soil moisture globally despite being subject to limitations of coarse space-time resolutions. In our lab, we focus on developing downscaling techniques for soil moisture under varying heterogeneous conditions. These techniques are aimed at generating soil moisture data products that enable the use of remotely sensed soil moisture in applied hydrological modeling and water management. This work has mainly been done in humid, sub-humid and arid hydro-climates. Partially funded by NASA Earth and Space Science Fellowship (NNX13AN64H)
• Using remote sensing to estimate evapo-transpiration: Since remotely sensed soil moisture data cannot typically measure below the top 5 cm of soil, we use remotely sensed evapotranspiration estimates to evaluate variability in the root zone moisture. These estimates can be made at varying spatial scales depending upon the type of platform used to collect data (airborne and satellite). This work has mainly been done in semi-arid row cropped orchard environment and has implications for precision agriculture.