Sediment and nutrient pollution in water bodies is threatening human health and the ecosystem, due to rapid land use changes and improper agricultural practices. The impact of the nonpoint source pollution needs to be evaluated for the sustainable use of water resources. An ideal tool like the soil and water assessment tool (SWAT) can assess the impact of pollutant loads on the drainage area, which could be beneficial for developing a water quality management model. This study aims to evaluate the SWAT model’s multi-objective and multivariable calibration, validation, and uncertainty analysis at three different sites of the Yarra River drainage area in Victoria, Australia. The drainage area is split into 51 subdrainage areas in the SWAT model. The model is calibrated and validated for streamflow from 1990 to 2008 and sediment and nutrients from 1998 to 2008. The results show that most of the monthly and annual calibration and validation for streamflow, nutrients, and sediment at the three selected sites are found with Nash–Sutcliffe efficiency values greater than 0.50. Furthermore, the uncertainty analysis of the model shows satisfactory results where the p-factor value is reliable by considering 95% prediction uncertainty and the d-factor value is close to zero. The model's results indicate that the model performs well in the river's watershed, which helps construct a water quality management model. Finally, the model application in the cost-effective management of water quality might reduce pollution in water bodies due to land use and agricultural activities, which would be beneficial to water management managers.

由于土地利用的快速变化和不当的农业实践，水体中的沉积物和营养物污染正在威胁人类健康和生态系统。为了水资源的可持续利用，需要评估面源污染的影响。土壤和水评估工具（SWAT）等理想工具可以评估污染物负荷对流域的影响，这可能有利于开发水质管理模型。本研究旨在评估 SWAT 模型在澳大利亚维多利亚州亚拉河流域三个不同地点的多目标和多变量校准、验证和不确定性分析。 SWAT模型将流域划分为51个子流域。该模型针对 1990 年至 2008 年的水流以及 1998 年至 2008 年的沉积物和营养物进行了校准和验证。结果表明，三个选定地点的大部分月度和年度校准和验证的水流、营养物和沉积物都是通过纳什发现的–Sutcliffe 效率值大于 0.50。此外，模型的不确定性分析显示出令人满意的结果，其中考虑到 95% 的预测不确定性，p 因子值是可靠的，并且 d 因子值接近于零。模型结果表明该模型在河流流域表现良好，有助于构建水质管理模型。最后，该模型在具有成本效益的水质管理中的应用可能会减少由于土地使用和农业活动而造成的水体污染，这将有利于水管理管理者。