• Journal of Korea Water Resources Association
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• v.55 no.6
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• pp.393-404
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• 2022

Reliable terrestrial rainfall observations from satellites at finer spatial resolution are essential for urban hydrological and microscale agricultural demands. Although various traditional "top-down" approach-based satellite rainfall products were widely used, they are limited in spatial resolution. This study aims to assess the potential of a novel "bottom-up" approach for rainfall estimation, the parameterized SM2RAIN model, applied to the C-band SAR Sentinel-1 satellite data (SM2RAIN-S1), to generate high-spatial-resolution terrestrial rainfall estimates (0.01° grid/6-day) over Central South Korea. Its performance was evaluated for both spatial and temporal variability using the respective rainfall data from a conventional reanalysis product and rain gauge network for a 1-year period over two different sub-regions in Central South Korea-the mixed forest-dominated, middle sub-region and cropland-dominated, west coast sub-region. Evaluation results indicated that the SM2RAIN-S1 product can capture general rainfall patterns in Central South Korea, and hold potential for high-spatial-resolution rainfall measurement over the local scale with different land covers, while less biased rainfall estimates against rain gauge observations were provided. Moreover, the SM2RAIN-S1 rainfall product was better in mixed forests considering the Pearson's correlation coefficient (R = 0.69), implying the suitability of 6-day SM2RAIN-S1 data in capturing the temporal dynamics of soil moisture and rainfall in mixed forests. However, in terms of RMSE and Bias, better performance was obtained with the SM2RAIN-S1 rainfall product over croplands rather than mixed forests, indicating that larger errors induced by high evapotranspiration losses (especially in mixed forests) need to be included in further improvement of the SM2RAIN.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.2
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• pp.127-139
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• 2024

Climate change has increased extreme weather events likewise heatwaves, heavy rain, and drought. Unlike other natural disaster, drought is a slowly developing phenomenon and thus drought damage increases as the drought continues. Therefore, it is necessary to understand the characteristics and mechanism of drought occurrence. Agricultural drought occurs when the water supply needed by crops becomes insufficient due to lack of soil water. Therefore, soil water is used as a key variable affecting agricultural drought. In this study, we examined the spatio-temporal distribution and trends of drought across the Korean Peninsula by determining the soil available water content (SAWC) through a model that integrated soil, meteorological, and crop data. Moreover, an investigation into the correlation between meteorological variables and the SAWC was conducted to assess how meteorological characteristics influence the nature of drought occurrences. During the soybean cultivation period, the average SAWC was lowest in 2018 at 88.6% and highest in 2021 at 103.2%. Analysis of the spatial distribution of SAWC by growth stage revealed that the lowest SAWC occurred during the flowering stage (S3) in 2018, during the leaf extension stage (S2) in 2019, during the seedling stage (S1) in 2020, again during the flowering stage (S3) in 2021, and during the seedling stage (S1) in 2022. Based on the average SAWC across different growth stages, the frequency of upland drought was the highest at 22 times during the S3 in 2018. The lowest SAWC was primarily influenced by a significant negative correlation with rainfall and evapotranspiration, whereas the highest SAWC showed a significant positive correlation with rainfall and relative humidity, and a significant negative correlation with reference evapotranspiration.