Value of seasonal flow forecasts for enhancing reservoir operation and drought management in South Korea

Abstract. Drought poses significant challenges across various sectors such as agriculture, water resources, environment, and energy. In the past few decades, numerous devastating droughts have been reported worldwide including in South Korea. A recent drought in South Korea, which lasted from 2013 to 2016, led to significant consequences including water restrictions and nationwide crop failures. Historically, reservoirs have played a crucial role in mitigating hydrological droughts by ensuring water supply stability. With exacerbating intensity and frequency of droughts attributed to climate change, enhancing the operational efficiency of existing reservoirs for drought management becomes increasingly important. This study examines the value of Seasonal Flow Forecasts (SFFs) in informing reservoir operations, focusing on two critical reservoir systems in South Korea. We assess and compare the value derived from using two deterministic scenarios (worst and 20-year return period drought) and two ensemble forecasts products (SFFs and Ensemble Streamflow Prediction, ESP). Our study proposes an innovative method for assessing forecast value, providing a more intuitive and practical understanding by directly relating it to the likelihood of achieving better operational outcomes compared to historical operation. Furthermore, we analyse the sensitivity of forecast value to key choices in the set-up of the simulation experiments. Our findings indicate that while deterministic scenarios show higher accuracy, forecast-informed operations with ensemble forecasts tend to yield greater value. This highlights the importance of considering the uncertainty of flow forecasts in operating reservoirs. Although SFFs generally show higher accuracy than ESP, the difference in value between these two ensemble forecasts is found to be negligible. Last, the sensitivity analysis shows that the method used to select a compromise release schedule between competing operational objectives is a key determinant of forecast value, implying that the benefits of using seasonal forecasts may vary widely depending on how priorities between objectives are established.