| After rainfall, soil moisture is the most important factor dictating flash flooding, since rainfall infiltration and runoff are based on the saturation of the soil. It is difficult to conduct ground-based measurements of soil moisture consistently and regionally. As such, soil moisture is often derived from models and agencies such as the National Oceanic and Atmospheric Administration's National Weather Service (NOAA/NWS) use proxy estimates of soil moisture at the surface in order support operational flood forecasting. In particular, a daily national map of Flash Flood Guidance is produced that is based on surface soil moisture deficit and threshold runoff estimates. The current FFG system at the ABRFC provides gridded flash flood guidance (GFFG) System using the NWS Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) to translate the upper zone soil moisture to estimates of Soil Conservation Service Curve Numbers.;The remote sensing observations of soil moisture can provide high resolution soil surface information. This study is to evaluate the contribution of remote sensing technology to quantifiable improvements in flash flood applications as well as adding a satellite based soil moisture component to the NWS FFG Algorithm. Soil Moisture and Ocean Salinity (SMOS) measures the microwave radiation emitted from the Earth's surface operating at L-band (1.20-1.41 GHz). Microwave radiation at this wavelength offers relatively deeper penetration and has lower sensitivity to vegetation impacts, which has been proved to be optimal range to observe surface soil moisture. The challenge of the study was employing the direct soil moisture data from SMOS to replace the model-calculated soil moisture state. The study shows the techniques of SMOS soil moisture incorporation to the NWS operational hydrologic model by spatial, vertical, and temporal data assimilations simultaneously.;This study evaluated the value of remote sensing data in constraining the state of the system for main-steam and flash flood forecasting. The results from successfully developed technique implied potential improvement of flash flood forecast with SMOS assimilation through upper zone saturation ratio. Hence, the technique is expected to be practical on various applications including flash flood forecast from SMOS and future SMAP soil moisture data. |
