Assessment of seasonal forecasts for reservoir operation in South Korea

Increased intensity and frequency of extreme weather events predicted in a warmer climate can cause damages to human life, properties and the natural environment. Also, these changes pose significant challenges to water resources management. For example, in South-Korea, there were prolonged droughts lasting more than 3 years from 2013 to 2015 whereas, record-breaking monsoon caused severe flood damages in 2020.  Nowadays the construction of new water infrastructure such as large reservoirs is almost impossible in many developed countries due to social and environmental objections and therefore the operation of existing reservoirs is extremely important. In order to improve the performance of reservoir operations, we need to make better use of reliable weather forecasting information.

There have been noteworthy advances in seasonal climate forecasts over the last decade. Seasonal forecasts are long-term meteorological forecasts (1 to 7 months) that could be a game changer in reservoir operation and adaptation to climate change once it is demonstrated that they provide reliable information in the water sector. However, so far seasonal forecasts have never been used in practice and simulation experiments similar to those reported in the scientific literature for other regions, such as Europe or the US, have not been conducted for South Korea.

Therefore, assessing the value of seasonal forecasts in reservoir operation is highly significant matter. In this study, we will try to demonstrate their value by comparing, via model simulation, the use of forecasts with the use of diverse scenarios, including deterministic low inflow scenarios (or worst cases), Ensemble Streamflow Prediction (ESP) and perfect forecast conditions (where observations are used in place of forecasts). The analysis will be carried out for 6 different reservoirs having different catchment sizes  from 95.4km² to 1,584km² to determine any link between forecasts value and catchment characteristics and draw general guidelines for future forecasts use. The results from each scenario will be compared in terms of ‘skill’, representing the forecast accuracy, and ‘value’, representing the final effect on reservoir operation such as water resources availability and flood prediction. This study aims at understanding how valuable the seasonal forecasts can be and how to apply them to have better performance in practice.