Abstract

The Cau river basin in northern Vietnam is experiencing increasing pressures on water resources due to rapid urbanization, industrial development, agricultural expansion, and inadequate wastewater management. Understanding the interactions between surface water, groundwater, and water quality is essential for developing effective and sustainable water management strategies. This study developed and applied a coupled MIKE SHE–MIKE 11 framework to simulate surface–groundwater connectivity and its influence on water quality dynamics in the Cau river basin. Hydrometeorological and water quality datasets collected during 2023–2024 were used to calibrate and test the integrated model at key monitoring locations, including Cha, Phuc Loc Phuong, and Dap Cau stations. The hydrological component demonstrated satisfactory performance, with Nash–Sutcliffe Efficiency (NSE) values ranging from 0.55 to 0.79 for water level simulations, indicating a reliable representation of surface and subsurface flow processes. Simulated river–aquifer exchange fluxes revealed pronounced spatial variability across the basin. Upstream reaches predominantly functioned as groundwater recharge zones, whereas the middle and downstream sections exhibited dynamic bidirectional exchanges governed by river stage fluctuations, hydraulic gradients, and local hydrogeological conditions. Water quality simulations for BOD5, COD, NH4+, total nitrogen (TN), and total phosphorus (TP) showed good agreement with observations, with calibration and testing errors generally remaining below 25%. Incorporating surface–groundwater interactions improved the representation of pollutant transport, residence time, and nutrient accumulation processes compared with conventional river-only simulations. The results demonstrate that river–aquifer connectivity plays a critical role in regulating both hydrological processes and water quality conditions in the basin. The coupled modeling framework provides a robust scientific basis for identifying critical interaction zones, assessing pollution risks, optimizing monitoring programs, and supporting integrated water resource planning. By explicitly linking hydrological connectivity with water quality dynamics, the proposed framework serves as a practical decision-support tool for sustainable water resource management in the Cau river basin and other river–aquifer systems facing increasing environmental pressures and progressive water quality degradation.

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