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 ground water 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 utilize state-of-the-art remotely sensed (RS) 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. 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/stream flow, ET, and soil moisture) and their uncertainties.