Comparison of Dam Inflow Generation Techniques for Assessing Drought Coping Capacity

Abstract

Heavy rainfall during flood seasons has become more concentrated, whereas rainfall during dry seasons has decreased, owing to the impacts of climate change. Despite similar average annual precipitation, this phenomenon has led to the occurrence of stronger and more localized droughts. To address this issue, the Korea Water Resources Corporation (K-water) adopted the K-water disaggregation method (KDM) to manage dam operations efficiently by considering regional characteristics. KDM calculates the monthly inflow for the upcoming year using the correlation between the annual and monthly inflow frequency analysis results. However, the current implementation of KDM, which provides a single scenario, often exhibits significant discrepancies from the observed inflow. To overcome this limitation, this study proposes incorporating uncertainty through a disaggregation model to enhance the accuracy of inflow estimation. Thus, a wider range of inflow scenarios can be considered, thereby enhancing the strategy for dam operations. This study compared the inflow scenarios generated by two different methods and assessed the corresponding drought coping capacities expected from operating dams under these scenarios. The drought coping capacity assessment included calculating the Supply-day (S-day) and dam storage performance measures. The results indicated that KDM generally showed a lower S-day during the water supply seasons and exhibited a lower dam storage performance than the disaggregation method inflow scenarios. Consequently, the single scenario provided by KDM may distort the potential inflow scenarios for the target dam. Considering a range of monthly scenarios for an annual drought quantile proved advantageous for assessing drought coping capacity. This study issues a broader warning, not only for Korea but also for other countries, about the risks of relying on a single scenario for determining next-year drought inflows, which may increase the likelihood of encountering more severe droughts than anticipated.