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http://dx.doi.org/10.5389/KSAE.2019.61.1.031

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

Ryu, JaeHyun (Department of Soil and Water Systems, College of Agricultural and Life Sciences, University of Idaho)
Kim, JungJin (Texas A&M AgriLife Research, Texas A&M University)
Lee, KyungDo (National Institute of Agricultural Science, Rural Development Administration)
Publication Information
Journal of The Korean Society of Agricultural Engineers / v.61, no.1, 2019 , pp. 31-44 More about this Journal
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.
Keywords
HCDI; drought; drought indices; skill score;
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