Improved SM2RAIN Algorithm to Estimate Rainfall by Incorporating Soil Physical Properties

Spatial and temporal imbalances in rainfall are accelerating due to the increase in extreme weather events caused by climate change. The Korean Peninsula, characterized by a monsoon climate, experiences prolonged periods of summer rainfall. However, in recent years, it has increasingly shifted towards localized heavy rainfall, resulting in frequent saturation of soil moisture and regional imbalances of rainfall. A recent study has demonstrated a correlation between changes in rainfall characteristics and an increase in rainfall imbalance, which has resulted in an escalation in disaster occurrences. To address this challenge, a multifaceted approach to rainfall monitoring has been adopted in Korea, such as a combination of in-situ observations, radar, modeling approaches, and remote sensing data. However, the diversification of rainfall data remains a crucial challenge for effective disaster risk management. In this study, soil physical properties were incorporated into the SM2RAIN algorithm, a simple model that estimates rainfall based on soil moisture content. Soil Moisture Active Passive Level 4 (SMAP L4) data was utilized as the input to SM2RAIN, and the generated rainfall was then subjected to correlation analysis with SM2RAIN-ASCAT and Global Precipitation Measurement Integrated Multi-satellitE Retrievals for GPM (GPM IMERG). Rainfall data incorporating soil physical properties exhibited a comparable trend to that of GPM IMERG. The results of this study are anticipated to ensure the diversification of rainfall datasets by providing a relatively simple method for estimating rainfall in ungauged regions.

 

Keywords: Soil Moisture, Rainfall, SM2RAIN, Soil Physical Properties

 

Acknowledgment: This research was supported by the BK21 FOUR (Fostering Outstanding Universities for Research) funded by the Ministry of Education (MOE, Korea) and National Research Foundation of Korea (NRF). This work is financially supported by Korea Ministry of Land, Infrastructure and Transport (MOLIT) as 「Innovative Talent Education Program for Smart City」. This work was supported by Korea Environment Industry & Technology Institute (KEITI) through Research and Development on the Technology for Securing the Water Resources Stability in Response to Future Change Project, funded by Korea Ministry of Environment (MOE)(RS-2024-00332300). This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (RS-2024-00416443). This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2022R1A2C2010266). This work was supported by Korea Environment Industry & Technology Institute (KEITI) through Water Management Program for Drought Project, funded by Korea Ministry of Environment (MOE) (RS-2023-00230286).