AbstractModeling methodologies capable of coping with changing catchment conditions are becoming more important and are critical to ensure credible model predictions because the hydrologic process of the catchment is inevitably affected by climate change and human activities. A recently developed hydrological modeling framework that treats model parameters to be time-variant by building functions based on identified catchment properties is applied to the Upper Ganjiang River Basin in China experienced soil and water conservation constructions. The efficacy of the time-variant parameter method is investigated, and we further explore the impacts of model structure on hydrological modeling through this method. The approach is tested using two conceptual monthly water balance models, i.e., the ab model derived from the abcd model, and a two-parameter monthly water balance model (TWBM), which have the same model inputs and outputs, number of parameters and state variables. Results of the case study show that through the comparative analysis with the constant parameter models, both time-variant parameter models provide improved runoff simulations, especially for low and high flows. Moreover, the time-variant parameter method brings relatively larger runoff improvements for the TWBM model. For the actual evapotranspiration simulations, the ab model can yield improvements by treating parameter b (i.e., upper soil zone water holding capacity) to be time-variant, whereas the time-variant parameter method shows no efficacy in that for the TWBM model. The results demonstrate that the choice of hydrological model plays an important role in modeling performance of the time-variant parameter framework under a changing environment. Modification of the evapotranspiration calculation module for the TWBM model could be considered as further study to investigate the potential model improvement that compared with only time-variant parameters. This study can provide beneficial reference to comprehensively understand the impacts of changing environment on catchment hydrological modeling and thus improve the regional strategy for future water resource management.