Development & Evaluation of Real-time Ensemble Drought Prediction System

Abstract

The objective of this study is to develop and evaluate the system to produce the realtime ensemble drought prediction data. Ensemble drought prediction consists of 3 processes (meteorological outlook using the multi-initial conditions, hydrological analysis and drought index calculation) therefore, more processing time and data is required than that of single member. For ensemble drought prediction, data process time is optimized and hardware of existing system is upgraded. Ensemble drought data is estimated for year 2012 and to evaluate the accuracy of drought prediction data by using ROC (Relative Operating Characteristics) analysis. We obtained 5 ensembles as optimal number and predicted drought condition for every tenth day i.e. 5th, 15th and 25th of each month. The drought indices used are SPI (Standard Precipitation Index), SRI (Standard Runoff Index), SSI (Standard Soil moisture Index). Drought conditions were determined based on results obtained for each ensemble member. Overall the results showed higher accuracy using ensemble members as compared to single. The ROC score of SRI and SSI showed significant improvement in drought period however SPI was higher in the demise period. The proposed ensemble drought prediction system can be contributed to drought forecasting techniques in Korea.

Standar Dization and Evaluation of PDSI Calculation Method for Korean Drought Management Agencies

“…따라서 가뭄을 감지하더라도 구체적인 발생 시기, 장소, 원인을 규명하는 것이 어 렵고 피해규모 및 영향력도 막대하다 (Lee et al, 2006). 국내에서는 이러한 가뭄은 짧게는 2~3년, 길게는 5~7 년 주기로 빈번하게 발생한다고 알려져 있으며 (KMA, 2012;Bae et al, 2013) PDSI는 크게 수분수지 해석과 가뭄지수 산정으로 분류되며, 주요 입력자료는 월별 강수량, 기온 및 위 도별 일조시간 보정계수, 상부 및 하부토층의 토양유 효용량(Available Water Capacity of the soil, AWC)이 있다. PDSI에 관한 이론은 그 동안 국내에서도 여러 차례 기술된바 있으며 (Yoon et al, 1996;Lee et al, 2006;KMA, 2007)…”