Feasibility Research on the Auxiliary Variables in Scaling of Soil Moisture Based on the SiB2 Model: A Case Study in Daman

Soil moisture is a core climate variable in land surface processes and has a strong influence on the energy balance and water exchange between the land surface–vegetation–atmosphere columns. However, the low spatial resolution of soil moisture remote sensing products cannot satisfy the requirements of research and applications based on hydro-meteorological and eco-hydrological simulations and the management of water resources at the watershed scale. A feasible solution is to downscale soil moisture products derived from microwave remote sensing, which often requires the support of auxiliary variables. Meanwhile, during the validation process of remote sensing products, the spatial scales between in situ observations and remote sensing pixel retrievals are inconsistent; thus, in situ observations should be translated to ground truths at a pixel scale via reasonable upscaling methods. Many auxiliary variables can serve as proxies in the scaling of soil moisture, although few studies have analyzed their feasibility and application conditions. In this paper, a SiB2 (Simple Biosphere Model-II) simulation for the Daman superstation from 1 May to 30 September 2013, was employed to calculate seven auxiliary variables related to soil moisture: ATIs and ATIc (Apparent Thermal Inertias based on surface soil temperature and canopy temperature), E (Evaporation), E/ETa (Ratio of Evaporation and Actual Evapotranspiration), E/ETp (Ratio of Evaporation and Potential Evapotranspiration), EF (Evaporative Fraction) and AEF (Actual Evaporative Fraction). The applicability of these variables was then evaluated via a correlation analysis between the variables and soil moisture. The results indicated that E is highly sensitive to soil moisture at Phase I (R2 ≥ 0.67), whereas ATIs is the greatest indicator of soil moisture at Phase II (R2 ≥ 0.51). Considering both the correlation and computability of these auxiliary variables, the EF (R2 ≥ 0.56) and AEF (R2 ≥ 0.54) are recommended as proxies for Phase I, while ATIs (R2 ≥ 0.51) is also recommended for Phase II.