Recent evidence of the impact of watershed underlying conditions on hydrological processes have made the assumption of stationarity widely questioned. In this study, the temporal variations of frequency distributions of the annual maximum flood were investigated by continuous hydrological simulation considering nonstationarity for Weihe River Basin (WRB) in northwestern China. To this end, two nonstationary versions of the GR4J model were introduced, where the production storage capacity parameter was regarded as a function of time and watershed conditions (e.g., reservoir storage and soil-water conservation land area), respectively. Then the models were used to generate long-term runoff series to derive flood frequency distributions, with synthetic rainfall series generated by a stochastic rainfall model as input. The results show a better performance of the nonstationary GR4J model in runoff simulation than the stationary version, especially for the annual maximum flow series, with the corresponding NSE metric increasing from 0.721 to 0.808. The application of the nonstationary flood frequency analysis indicates the presence of significant nonstationarity in the flood quantiles and magnitudes, where the flood quantiles for an annual exceedance probability of 0.01 range from 4187 m³/s to 8335 m³/s for the past decades. This study can serve as a reference for flood risk management in WRB and possibly for other basins undergoing drastic changes caused by intense human activities.

Accurate simulation and forecast for soil processes has always been a challenge for river management and environmental conservation. However, the sediment modeling technique remains insufficient for catchments characterized by special soil erosion conditions, especially for the steep area of the upper Yangtze River basin. This study presents a framework that incorporates soil erosion and transport calculation modules into a distributed hydrological model, and customized modifications are applied to fit the catchment conditions. In addition, to accurately describe the topography (e.g., slope length and steepness) and to account for its impact on soil process simulation, the sub-basin with high sediment yield is discretized with a higher spatial resolution. The presented is validated in Heishuihe River basin in southwestern China. And the results show that the modified version of the DDRM model (i.e., DDRM-SED) model show a good simulation performance in terms of flow and sediment processes. In addition, the DDRM-SED model with multi-spatial resolution show a better simulation performance than the model with constant spatial resolution.

The pronounced spatial heterogeneity of underlying surface characteristics within the parallel ridge–valley system of eastern Sichuan necessitated hydrological discretization of the watershed into nested subdomains comprising inter-ridge valley units and secondary slope cells. A distributed flood simulation framework specifically adapted to parallel ridge–valley topography was developed, coupled with a sequential intelligent parameter optimization algorithm. Model validation was conducted through the simulation of ninety flood events (2015–2023) in the Lishui watershed, a representative parallel ridge–valley basin. For parameter-calibrated sub-watersheds, mean relative errors of 13.8% (peak discharge) and 12.3% (runoff depth) were achieved, while non-calibrated watersheds exhibited marginally higher inaccuracies at 14.6% and 15.1%, respectively. Spatial parameter estimation was effectively implemented through the assimilation of limited hydrometeorological station data. The integrated modeling framework, incorporating terrain-adaptive parameterization and intelligent calibration protocols, demonstrated high-fidelity flood process simulation capabilities in complex parallel ridge–valley landscapes.