Funding Agency:
NASA

Soil moisture and hydrologic fluxes in the root zone (land surface to the shallow groundwater table) are known to significantly influence atmospheric boundary layer, groundwater recharge, and surface and subsurface runoff production. Results of most previous studies indicate soil moisture spatio-temporal pattern reflects a conjoint variability of soil, topography, vegetation, and precipitation, and is “dominated” by soil properties at the field scale, topographic features at the catchment/watershed scale, vegetation characteristics and precipitation patterns at the regional scale and beyond. Ensemble hydrologic fluxes (including evapotranspiration, infiltration, shallow groundwater recharge) within and across the vadose zone reflect the evolution of soil moisture at a particular spatial scale (field, watershed, or region) and can be “effectively” represented by one or more linear/nonlinear hydrologic scale parameters. Overarching the above concepts, we hypothesized that effective soil hydraulic property in the root zone at the footprint-scale is an effective indicator for combined soil, topography, and vegetation heterogeneities in land-atmosphere interaction models at different spatial scales.

To test this overarching scientific hypothesis, we will utilize state-of-the-art remotely sensed (RS) near-surface soil moisture data at multiple resolutions with a newly developed inverse model including a soil-water-atmosphere-plant model and advanced parameter estimation techniques. Effective root zone soil hydraulic parameters estimated using deterministic or stochastic inverse modeling approach (top-down) will be tested and compared for relative performance against numerical-cum-measurement upscaling schemes (bottom-up) for steady and transient conditions inclusive of various soil textures and structures, small- and large-scale topographic features, and a range of land covers and root distributions. We will evaluate our proposed inverse modeling (top-down) approach at three hydro-climatic regions of humid Iowa, semi-humid Oklahoma, and semiarid Arizona by using thematically-measured root zone soil hydraulics followed by appropriate upscaling (bottom-up) treatment.

Predictive watershed-scale modeling will test our hypothesis that “effective” hydraulic properties with larger RS footprint-scale measurement support are better predictors than “upscaled” hydraulic properties using local-scale measurements and scaling rules, based on estimated hydrologic fluxes (runoff/streamflow, ET, and soil moisture) and their uncertainties. Once validated, effective soil hydraulic property database for the continental USA will be generated using SMAP soil moisture products at 36 kmX 36 km resolution. Determining “effective root zone soil hydraulic properties” in complex landscapes from remote sensing data will open up a new paradigm and will have tremendous impacts on our ability to predict terrestrial hydrology, weather, climate, and global circulation of water, energy, and chemicals in the environment.