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Recently, the frequency of drought occurrence and the resulting damage has increased due to climate change. Frequent severe droughts induce water shortages in agricultural reservoirs. The role of drought monitoring and prediction is critical for mitigating the effects of severe drought in agricultural areas. In this study, a compound standardized storage and precipitation index (CSSPI) was developed that adapted the existing drought index-the standardized precipitation index (SPI)-by adding hydrological data on storage rate. Furthermore, the future storage rate was simulated using autoregressive models (AR) to estimate the future CSSPI. A dataset containing records of reservoirs and precipitation at the three areas of Jungbu, Youngnam, and Honam was applied to estimate the current and future status of the CSSPI. The results indicate that the CSSPIs generated accurately present the past pattern of the observed data and that they can be considered as inputs for predicting future drought conditions.

Reliability Assessment of Agricultural Reservoirs for Water Supply under Climate Change