Improving the accuracy of an integrated watershed-reservoir water quality modeling approach (SWAT and CE-QUAL-W2) in data scarce watersheds

Watershed-reservoir modeling is an essential tool in lake and reservoir management. Despite its importance, accurately modeling these systems remains challenging due to their inherent complexity and the scarcity of reliable forcing data. This study focuses on a watershed and reservoir located in northern Portugal, where data scarcity presents significant challenges for accurate modeling. Therefore, the primary goal of this study was to improve the prediction capability of an integrated watershed-reservoir water quality modeling solution and to establish a robust methodology that can be effectively applied to other cases. The modelling solution proposed in this study computes a daily ratio (per water quality variable) between the watershed reference and load reduction modeling scenarios, obtained with the SWAT model, which is then applied to the observed forcing water quality data of a reservoir water quality model (CE-QUAL-W2). The load reduction scenario increases the watershed municipal wastewater treatment plant's efficiency from secondary to tertiary and applies a haul-off scenario to the livestock manure, reducing the reservoir input load of Total P, Total N, and BOD5 in the reservoir by 87%,86%, and 83%, respectively. The results obtained with the classical model solution provided an inaccurate conclusion regarding the load reduction scenario output that was corrected with the proposed modeling approach. Overall, after the correction, the load reduction scenario served to considerably improve the reservoir water quality by reducing the Total P and the phytoplankton biomass by 39% and 72%, respectively, while increasing the DO concentration by 27%. The results of this study show that the proposed modeling approach improves the performance of integrated watershed-reservoir modeling systems in data scarce settings and can serve as a useful tool to support decision-making with regard to water resource management and planning at regional and national level.