The Xin’anjiang model is a conceptual hydrological model, which has an essential application in humid and semi-humid regions. In the model, the parameters estimation of runoff routing has always been a significant problem in hydrology. The quantitative relationship between parameters of the lag-and-route method and catchment characteristics has not been well studied. In addition, channels in Muskingum method of the Xin’anjiang model are assumed to be virtual channels. Therefore, its parameters need to be estimated by observed flow data. In this paper, a new routing scheme for the Xin’anjiang model is proposed, adopting isochrones method for overland flow and the grid-to-grid Muskingum–Cunge–Todini (MCT) method for channel routing, so that the routing parameters can be estimated according to the geographic information. For the new routing scheme the average overland flow velocity can be determined through the land cover and overland slope, and the channel routing parameters can be determined through channel geometric characteristic, stream order and channel gradient. The improved model was applied at a 90 m grid scale to a nested watershed located in Anhui province, China. The parent Tunxi watershed, with a drainage area of 2692 km², contains four internal points with available observed streamflow data, allowing us to evaluate the model’s ability to simulate the hydrologic processes within the watershed. Calibration and verification of the improved model were carried out for hourly time scales using hourly streamflow data from 1982 to 2005. Model performance was assessed by comparing simulated and observed flows at the watershed outlet and interior gauging stations. The performance of both original and new runoff routing schemes were tested and compared at hourly scale. Similar and satisfactory performances were achieved at the outlet both in the new runoff routing scheme using the estimated routing parameters and in the original runoff routing scheme using the calibrated routing parameters, with averaged Nash-Sutcliffe efficiency (NSE) of 0.92 and 0.93, respectively. Moreover, the new runoff routing scheme is also able to reproduce promising hydrographs at internal gauges in study catchment with the mean NSE ranging from 0.84 to 0.88. These results indicate that the parameter estimation approach is efficient and the developed model can satisfactorily simulate not only the streamflow at the parent watershed outlet, but also the flood hydrograph at the interior gauging points without model recalibration. This study can provide some guidance for the application of the Xin’anjiang model in ungauged areas.

Flood simulation in small and medium-sized catchments across China is constrained by limited hydrometeorological data and pronounced hydroclimatic heterogeneity. The wflow_sbm model offers promising potential, as seamless parameter fields can be estimated from global datasets via pedotransfer functions (PTFs), enabling explicit representation of the spatial and temporal variability of catchment characteristics. However, the extent to which parameter sensitivity differs between humid and semi-humid regions with distinct runoff-generation mechanisms remains insufficiently understood. Moreover, it is unclear whether parameters derived by PTFs are directly applicable to small and medium-sized catchments or require regional adjustment.In this study, the wflow_sbm model is applied to two representative Chinese catchments: the humid Tunxi basin and the semi-humid Chenhe basin. Distributed parameters are derived from global datasets using HydroMT model setup and preprocessing framework. We (1) systematically analyze the sensitivity of three key parameters about soil water dynamics (KsatHorFrac, InfiltCapSoil and SoilThickness) in humid and semi-humid basins, (2) assess the applicability of seamless parameter maps derived by PTFs and evaluate the necessity of regional adjustment, and (3) benchmark the performance of wflow_sbm against the well-established Xin’anjiang (XAJ) model in China, including multi-site validation to assess spatial robustness.Results reveal clear regional differences in parameter sensitivity: KsatHorFrac and InfiltCapSoil dominate runoff responses in the humid Tunxi basin, whereas KsatHorFrac and SoilThickness exert the strongest control in the semi-humid Chenhe basin. The PTF-derived SoilThickness (~2 m) in Chenhe leads to systematic underestimation of flood volume and peaks. Reducing it to ~0.2 m substantially improves model performance and is consistent with vadose-zone depth estimates from the XAJ model, highlighting SoilThickness as a key control in semi-humid basins. The results also show that the wflow_sbm model achieves performance comparable to XAJ in both catchments, with an average NSE of 0.85 in Tunxi and generally NSE >0.7 in Chenhe. The good performance at the internal stations in Tunxi (average NSE > 0.70) further demonstrates that the parameter maps derived by PTFs are applicable and reliable for small and medium-sized basins.Overall, wflow_sbm is applicable for flood simulation in small and medium-sized catchments in humid and semi-humid regions and is particularly advantageous in data-scarce basins. However, if its application in semi-humid regions requires appropriate adjustment of SoilThickness, which can be guided by parameter ranges inferred from the XAJ model.

Flood simulation in small- and medium-sized catchments is hindered by data scarcity and strong hydroclimatic heterogeneity. Distributed models with pedotransfer functions offer new opportunities, yet their parameter sensitivity and regional applicability remain insufficiently understood. In this study, the wflow_sbm model was applied to two catchments: the humid Tunxi basin and the semi-humid Chenhe basin, China. Model seamless parameters, defined as spatially continuous fields derived directly from global datasets using pedotransfer functions without local calibration, were generated using the HydroMT system. The parameter sensitivity, applicability of pedotransfer function derived parameters, and model performance were systematically evaluated and benchmarked against the well-established Xin’anjiang (XAJ) model, which is a conceptual lumped hydrological model widely used for flood simulation in humid and semi-humid regions of China. Sensitivity analysis identified KsatHorFrac and InfiltCapSoil as dominant in Tunxi, and KsatHorFrac and SoilThickness in Chenhe. SoilThickness derived by HydroMT underestimated flood volumes in the Chenhe basin but was substantially improved after applying a uniform scaling factor of 0.1, resulting in an effective SoilThickness of approximately 0.2 m. The wflow_sbm model achieved performance comparable to the XAJ model. Optimal calibration achieved N_SE = 0.85 in Tunxi with good performance at internal sub-catchments (Yuetan and Chengcun, N_SE > 0.70), and generally above 0.7 in Chenhe. These findings highlight the region-dependent validity of parameterization and provide guidance for distributed flood modeling in data-scarce basins.