Assessing the Resilience of Agricultural Reservoirs in Ungauged Catchments under Climate Change Using a Ratio Correction Factors-Based Calibration and Run Theory

Abstract

This study applied ratio correction factor (RCF) optimization to calibrate the daily storage of agricultural reservoirs located in ungauged catchments that lack stream flow data. Using Run theory, we then assessed the impacts of climate change on the resilience of agricultural reservoir operations during reservoir drought conditions. First, we optimized the RCFs of inflow and outflow in three agricultural reservoirs in Korea using limited measurement data from 2008 to 2017; the results showed high performance regarding the simulation of daily reservoir storage. Second, we simulated daily storage volume in reservoirs from 2018 to 2099, using future climate change data, and analyzed the duration and intensity of reservoir drought conditions, which indicated that the storage capacity is under the critical value. Without calibration, the correlation between the simulated and measured reservoir water volumes was very low, but the correlation increased after calibration of the simulated water volumes. A linear relationship between the simulated and measured volumes was observed with a correlation coefficient value of 0.9, indicating that the simulated reservoir values after calibration closely match the measured values. In addition, the maximum intensity of reservoir drought in the Kicheon reservoir was determined to be 486,000 m3 before calibration but 506,000 m3 after calibration. The duration results showed that long-term reservoir drought conditions will be observed more often in the future owing to climate change, and this could be a negative factor affecting the resilience of reservoir operations.

Keywords

• agricultural reservoir
• calibration
• ratio correction factor
• resilience
• climate change