Establishment of soil moisture data using satellite information and calculation of hydrological drought index using it

The drought risk in Korea has been gradually increasing, and the southern part of South Korea has experienced prolonged exposure to extremely low precipitation from the summer of 2021 until 2022, leading to the depletion of available water within two months. Droughts can be classified into meteorological, agricultural, and hydrological droughts under different definitions. The drought indices are routinely used to effectively monitor and cope with different drought conditions. In this perspective, various hydrometeorological factors (precipitation, temperature, streamflow, and soil moisture) are required to derive the drought indices according to the classification. Among the factors, the lack of soil moisture data has been an issue in effectively deriving the agricultural drought index compared to precipitation and temperature-based drought indices such as SPI and SPEI. Currently, research on satellite (i.e., C-band SAR) for water resources management is being conducted in South Korea. The agricultural drought index is commonly based on the satellite-based soil moisture and vegetation index, thus, an accurate estimation of soil moisture from the satellite information could be viewed as a main issue in terms of monitoring agricultural drought. In this study, we develop a novel hybrid stochastic simulation model for soil moisture at multiple locations (or grids) with relevant predictors, including hydrometeorological variables and satellite information.

 

Acknowledgement : This work was supported by Korea Environment Industry & Technology Institute(KEITI) through Water Management Program for Drought, funded by Korea Ministry of Environment(MOE)(2022003610001)