수문기상가뭄지수 (HCDI) 개발 및 가뭄 예측 효율성 평가

Development of Hydroclimate Drought Index (HCDI) and Evaluation of Drought Prediction in South Korea

Abstract

The main objective of this research is to develop a hydroclimate drought index (HCDI) using the gridded climate data inputs in a Variable Infiltration Capacity (VIC) modeling platform. Typical drought indices, including, Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and Self-calibrated Palmer Drought Severity Index (SC-PDSI) in South Korea are also used and compared. Inverse Distance Weighting (IDW) method is applied to create the gridded climate data from 56 ground weather stations using topographic information between weather stations and the respective grid cell ($12km{\times}12km$). R statistical software packages are used to visualize HCDI in Google Earth. Skill score (SS) are computed to evaluate the drought predictability based on water information derived from the observed reservoir storage and the ground weather stations. The study indicates that the proposed HCDI with the gridded climate data input is promising in the sense that it can help us to predict potential drought extents and to mitigate its impacts in a changing climate. The longer term drought prediction (e.g., 9 and 12 month) capability, in particular, shows higher SS so that it can be used for climate-driven future droughts.

Fig. 1 Study area

Fig. 2 Spatial interpolation method to create the gridded meterological dataset from the selected weather stations

Fig. 3 Box plot comparisons of total skill scores computed by drought indices (SPI, SEPI, and SC-PDSI) between the gridded dataset (GS) and the observed weather dataset (WS)

Fig. 4 Skill score comparison between SPI, SPEI, sc-PDSI and HCDI

Fig. 5 SPI (a), SPEI (b), (c) SC-PDSI, and (d) HCDI drought maps for 1, 3, and 12 month time window in Google Earth

Table 1 The selected multipurpose dam watersheds from the major four river watersheds in Korea

Table 2 Drought response phase based on the storage rates in the selected multipurpose dams

Table 3 The classified drought condition of SPI, SPEI, HCDI, and SC-PDSI

Table 4 The Reclassified drought indices

Table 5 The matrix table to apply skill scores methods

Table 6 Average skill score (SS) for each drought index for the observed weather station and the gridded climate data in the selected basins

Table 7 Average skill score of SPI, SPEI, SC-PDSI, and HCDI (1, 3, 6, 9, 12 month time windows) for KSS and HSS in the selected multipurpose dam watersheds