Time series analysis of retrieved soil moisture and vegetation water content using QuikSCAT data

Future water resources are a critical societal impact of climate change and hydrological cycles. Current climate models uncertainties result in disagreement on the amount of water. Soil moisture and vegetation water content are key environmental variables on evaporation and transpiration at the land-atmosphere boundary. Radar remote sensing helps to improve our estimate of water resources spatially and temporally. SMAP (Soil Moisture Active Passive) and SWOT (Surface Water Ocean Topography) are the two future NASA missions to monitor water resources and their variations at L-band and Ka-band, respectively. In this study, we show the potential of using already available QuikSCAT Ku-band backscattered power data over the land to quantify vegetation water content and soil moisture. Li et al. developed a physically based six-channel algorithm, which uses dual-polarization Windsat passive microwave data to retrieve soil moisture and vegetation water content. We use the retrieved soil moisture and vegetation water content using Windsat descending pass (around 6AM), and also simultaneous collocated QuikSCAT dual-polarization backscattered power to estimate different parameters of land surface using a proposed backscattered power formulation.