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AbstractSediment deposition and intensified eutrophication of the Miyun Reservoir are directly affecting the water quality in Beijing, China, owing to water pollution issues in the Chaohe River Basin, which contains the main inflow river of the reservoir. This study analysed the runoff, sediment, total nitrogen and total phosphorus load simulation results from three observation stations using the Hydrological Simulation Program–FORTRAN model (Nash efficiency coefficient [NSE] = 0.65–0.8, R2 = 0.62–0.92) and a statistical regression model (R2 = 0.55–0.79). Results indicate that applying these models in combination to basins from which pollution source data are difficult to obtain can fully utilize the advantages of both models. The parameter uncertainty analysis of the model's runoff and pollution‐related parameters is discussed from the basis of the generalized likelihood uncertainty estimation analysis method. Further, using the Mann–Kendall test and the double cumulative curve method, an attribute analysis of climate change and human activities in the basin was carried out. Results show that in the context of global climate change, fundamental ways to achieve the goal of adaptive catchment management include adjusting the land use structure, optimizing the land use mode and carrying out comprehensive management of soil and water loss with vegetation restoration as the main body.