Water Quality Modelling for Nitrate Nitrogen Control Using HEC-RAS: Case Study of Nakdong River in South Korea

Abstract

The World Health Organization (WHO) and the U.S. Environmental Protection Agency (EPA) provide guidelines on the maximum levels of nitrate nitrogen (NO3-N) contained in drinking water since excess nitrate ingestion may harm human health. Thus, monitoring and controlling the NO3-N concentration is of paramount importance, especially in sources of drinking water such as the Nakdong River in South Korea. This study addresses NO3-N pollution in the Nakdong River in South Korea, where such pollution mostly comes from diffuse sources in the catchment due to the agricultural use of fertilizers. The objective of this study is to suggest guidelines for designing strategies to control NO3-N in this river using a process-based model developed with HEC-RAS. The model was built based on water quality parameters (water temperature, dissolved oxygen, ammonia nitrogen, etc.) related to NO3-N dynamics incorporating hydraulic and meteorological data. This model simulated NO3-N dynamics downstream under 55 scenarios while focusing on a section near locations of drinking water intakes. The scenarios were constructed based on variations in water quantity and quality upstream. The simulation results showed that the peak concentration of NO3-N downstream could be directly controlled by limiting the NO3-N concentration upstream. Additionally, control of the flow rate upstream could also lead to a reduction in the overall average concentration of NO3-N downstream, but this predominantly occurred when the NO3-N concentration was decreasing. In conclusion, the design and implementation of strategies for the control of NO3-N downstream should be carried out after performing a quantitative analysis of the impact of different control measures for different downstream conditions using a water quality model.

Decision Support Framework for Optimal Reservoir Operation to Mitigate Cyanobacterial Blooms in Rivers

“…In our earlier study [48], we developed a river water quality model using HEC-RAS version 5.0.7 to simulate the NO3-N dynamics at Chilgok Weir, given upstream boundary In the optimization model, we employed NSGA-II, a widely applied genetic algorithm using a fast nondominated sorting procedure [46]. The Python library pymoo (version 0.6.0) was used [47].…”

“…In our earlier study [48], we developed a river water quality model using HEC-RAS version 5.0.7 to simulate the NO 3 -N dynamics at Chilgok Weir, given upstream boundary conditions. This model, evaluated to have a high performance of 0.76 or higher with both R 2 (Coefficient of Determination) and NSE (Nash Sutcliffe Efficiency) [48], was applied in Step 4 of the framework, since the model covered the same area as in this study.…”

“…Such surrogate models, based on machine learning, when trained, are much more computationally efficient compared with process-based models [50]. The model was built based on Equation ( 6) [2][3][4] by using the hydraulic, water quality, and meteorological data obtained for developing the HEC-RAS model in our previous study [48]. The dataset for training and testing the surrogate model consisted of 508,923 instances, which were generated using the HEC-RAS model by varying the upstream boundary conditions, such as flow rate and NO 3 -N concentration.…”

“…When values of water level for unsteady flow in each cross-section are calculated using HEC-RAS, a dry condition for a cross-section makes an error [49]. To avoid this error, a minimum flow rate is required, and the value of 17.5 m 3 s −1 was used as the minimum flow rate for the HEC-RAS model in our previous study [48].…”

Assessing the Effects of Environmental Flows on Water Quality for Urban Supply

“…The assessment of the water resources quality is a major concern in the realm of environmental protection policy. The significance of this endeavor cannot be overstated, as it has a direct impact not only on the health and well-being of human populations but also on the overall ecological balance [8,9].…”