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Assessing the characteristics of recent drought events in South Korea using WRF-Hydro
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NSTL
Elsevier
Drought is a complex and slow-moving disaster that is difficult to monitor and define. This study, therefore, aims to demonstrate the characteristics of recent droughts occurring from 2008 to 2015 over South Korea using a process-based land and hydrologic model, Weather Research and Forecasting-Hydro modeling system (WRFHydro). To drive the standalone WRF-Hydro, gridded meteorological data (5 km) were generated using stationbased observations and the Parameter-elevation Regressions on Independent Slopes Model (PRISM). The model was calibrated and evaluated using inflow observations at four locations with dams; for 2008-2010 (calibration) and 2011-2015 (evaluation), it demonstrated average R2 values of 0.80 and 0.75, respectively. While Standardized Precipitation Index is used for calculating meteorological drought using precipitation from PRISM, Standardized Soil Moisture Index and Standardized Streamflow Index, at different timescales, are used to calculate agricultural and hydrological droughts, respectively, with WRF-Hydro simulations. The correlation coefficients between SPI and both SSFI and SSMI were calculated to detect their response times. The hydrological and agricultural droughts showed response times 0.5-1 month later than meteorological drought. In 2008-2015, agricultural and hydrological drought events occurred 1.6 times per year on average in South Korea, whereas meteorological droughts occurred 4.3 times per year on average. Agricultural and hydrological droughts lagged behind meteorological droughts by up to 53, 65, and 83 days, when using 1-, 3-, and 6-month SPI, respectively. Moreover, hydrological droughts were less severe than meteorological droughts due to the propagation of drought by attenuation. This study demonstrates that WRF-Hydro can be used to quantitatively determine the different types of drought events and their propagation, which could help policy makers manage drought risks.
NSTL
Elsevier
