Estimating Effective Soil Hydraulic Properties Using Spatially Distributed Soil Moisture and Evapotranspiration

摘要: With the development of many earth-observing remote sensing (RS) platforms, spatially distributed products are becoming critical inputs to hydrologic and meteorological models. Remotely sensed soil moisture (SM) evapotranspiration (ET) including ground-based data have potential be used for estimating pixel-scale hydraulic parameters. However, only a few studies been conducted better understand impact assimilating both SM ET in properties root zone. In this study, we inverse modeling based on Noisy Monte Carlo Genetic Algorithm by linking RS derived from Surface Energy Balance Land effective properties. Walnut Creek (Iowa), Brown (Illinois), Lubbock (Texas) test sites were selected assess performance approach point satellite scales using synthetic validation experiments. For comparison purposes, results analyzed under three scenarios (ET only, + optimization criteria). These showed that considering components improved estimations reduced their uncertainties than or only. Overall, although uncertainty exists, our proposed scheme performed well at multiple spatial (point, airborne, footprints) various hydroclimatic conditions.