The purpose of this study is to predict agricultural reservoir storage rate (RSR) in a month. This algorithm was developed by multiple linear regression model (MLRM) which included the past 3 months RSRs data and the future climate change scenarios. In order to improve use of predicted RSR, this study need the severe criteria in terms of drought. So, the predicted RSR was indexed as the 3 months reservoir drought index (RDI3) and then it was disaggregated into drought duration, severity, and intensity. For the future RSR estimation by climate change scenarios, the 6 RCP 8.5 scenarios of HadGEM2-ES, CESM1-BGC, MPI-ESM-MR, INM-CM4, FGOALS-s2, and HadGEM3-RA were used in three future evaluation periods (S1: 2011~2040, S2: 2041~2070, S3: 2071~2099). The future S3 period of HadGEM2-ES scenario which has the biggest increase in precipitation and temperature showed the largest decrease to 60.2% among the 6 scenarios compared to the historical RSR (1976~2005) 77.3%. In contrast, INM-CM4 scenario which has smallest changes in precipitation and temperature in S3 period showed the smallest decrease to 72.8%. For the CESM1-BGC and MPI-ESM-MR, FGOALS-s2, and HadGEM3-RA, the S3 period RSR showed 72.6%, 72.6%, 67.4%, and 64.5% decrease respectively. The future severe drought condition of RDI3 below –0.25 showed the increase trend for the number and severity up to –2.0 during S3 period.