Abstract. Integrated water system modeling is a reasonable approach to provide scientific understanding of severe water crisis faced all over the world and to promote the implementation of integrated river basin management. Time Variant Gain Model (TVGM), which is a classic hydrological model, is based on the complex Volterra nonlinear formulation and has gotten good performance of runoff simulation in numerous basins. However, TVGM is disadvantageous to predict other water-related components. In this study, TVGM was extended to an integrated water system model by coupling multiple water-related processes in hydrology, biogeochemistry, water quality and ecology, and considering the interference of human activities. The parameter sensitivity and autocalibration modules were also developed to improve the simulation efficiency. The Shaying River Catchment, which is the largest, highly regulated and heavily polluted tributary in the Huai River Basin of China, was selected as the study area. The key water related components (e.g., runoff, water quality, nonpoint source pollutant load and crop yield) were simulated. The results showed that the extended model produced good simulation performance of most components. The simulated daily runoff series at most regulated and less-regulated stations matched well with the observations. The average values of correlation coefficient and coefficient of efficiency between the simulated and observed runoffs were 0.85 and 0.70, respectively. The simulations of both low and high flow events were improved when the dam regulation was considered except the low flow simulation at Zhoukou and Huaidian stations. The daily ammonia-nitrogen (NH4-N) concentration, as a key index to assess water quality in China, was well captured with the average correlation coefficient of 0.67. Furthermore, the nonpoint source NH4-N load and corn yield were simulated for each administrative region and the results were reasonable in comparison with the data from the official report and the statistical yearbooks, respectively. This study is expected to provide a scientific support for the implementation of such a modeling practice for integrated river basin management.