Enhancing hydrological modeling in large basin with intensive human water use through hierarchical parameterization and bias-integrated calibration

Cai, K., Li, J., Jiang, Q., Hu, L., Fu, J., Zhang, M., Li, Y., Qin, Y., & Liu, Y. (2026). Enhancing hydrological modeling in large basin with intensive human water use through hierarchical parameterization and bias-integrated calibration. Water Cycle 7 219-233. 10.1016/j.watcyc.2025.10.003.

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Abstract

Human management of water resources has profoundly altered the water cycle, creating complex and difficult-to-simulate human-water interactions. Traditional hydrological models, which have commonly focused solely on natural processes, struggle to accurately represent these changes especially in large basins with intensive human water use, highlighting an urgent need for more effective modeling methods to improve this challenge. This study proposed a hierarchical parameterization and bias-integrated calibration method to enhance modeling in those basins, and identified the optimal configuration through a comparative analysis of calibration scenarios based on the hydrological modeling of the Pearl River Basin (PRB) using the Community Water Model (CWatM). The key findings include: (a) Hierarchical calibration significantly improved simulation performance compared to non-regionalized methods, with average modified Kling-Gupta Efficiency (KGE) and NSE (Nash-Sutcliffe Efficiency) values increasing by over 0.5, and the third level of Water Resource Zones (WRZ3) was identified as the optimal calibration scale. (b) Integrating irrigation simulation bias into a single-objective function enabled the simultaneous optimization of both streamflow and irrigation simulations, which reduced irrigation bias from 327 % to 51 % with only a minor decrease in streamflow accuracy (KGE from 0.81 to 0.75), and the effective irrigation weighting coefficient was found to align with the basin's overall irrigation-to-total-runoff ratio. (c) The CWatM was confirmed as suitable for regional applications, although its performance is sensitive to meteorological and inflow boundary data, and it's important to customize the model's parameters to accurately reflect specific regional characteristics. The reproducible technical pathway presented in this paper could facilitate more precise hydrological modeling in similar basins.

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