A Framework for Optimal Reservoir Operation to Improve Downstream Aquatic Environment: Application to Nakdong River Basin in South Korea

In the water sector, issues concerning the aquatic environment have been extensively discussed due to climate change. In particular, water quality problems such as harmful cyanobacterial blooms (CyanoHABs) in rivers have arisen in South Korea since 2012. The Korean government constructed 16 weirs in the rivers during the Four Major Rivers Restoration Project. These weirs were built to more effectively use water resources in the rivers. Many environmental activists, however, have claimed that the weirs have caused water quality problems of CyanoHABs in the rivers. These CyanoHABs can be threats to the water environment while harming human health and aquatic ecosystems since CyanoHABs produce toxic substances such as microcystins.
To address the problems of these CyanoHABs, many researchers have conducted studies on predictive models for CyanoHABs. A predictive model using a data-driven approach can be useful in exploring the main factors affecting CyanoHABs at a specific location. However, these studies have not focused on preventing the occurrence of CyanoHABs but only on predicting their occurrence. If these studies are designed to link with a practical method for reducing the frequency of CyanoHABs, viable strategies can be proposed to effectively control CyanoHABs. Therefore, detailed considerations are required concerning the prevention or mitigation of CyanoHABs.
Reservoir operation can be a solution for reducing the problem of CyanoHABs in a downstream river. For example, discharging more water from upstream reservoirs can flush CyanoHABs downstream. However, the risk of water shortage can be increased in a reservoir if it is operated for improving water quality downstream. This is because reservoirs were typically designed for management of water quantity such as water supply. To use limited water resources in a reservoir to reduce the frequency of CyanoHABs downstream, optimal reservoir operations are necessary that simultaneously consider both the quantity and the quality of water.
This study focused on establishing a practical framework for the optimal operation of upstream reservoirs to address the problem of CyanoHABs in a downstream river. Furthermore, the applicability of this framework was demonstrated using observational data related to the quantity and quality of the upstream reservoirs in the study area, the Nakdong River basin of South Korea. The framework was established by incorporating three models: a machine learning model, a river water quality model, and an optimization model for reservoir operation.