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

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 proposes 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 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. • Water Source Zones of level 3 (WRZ3) was optimal scale for hierarchical calibration • Bias-integrated weighted method balanced streamflow and irrigation effectively • Irrigation weighting, close to water-to-runoff ratio, optimizes coupled simulation • Hierarchical calibration highly sensitive to meteorological and inflow data quality • CWatM is suitable for regional modelling, requiring a detailed basin-specific setup

Authors

Institutions

Publication Details

Journal
Water Cycle
Published
2025-10-18
DOI
https://doi.org/10.1016/j.watcyc.2025.10.003
Primary Topic
Hydrology and Watershed Management Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Kaikui Cai, Qingsong Jiang, Jiaxing Fu, Lian Hu et al.
Water Cycle
Hydrology and Watershed Management Studies
article

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

Kaikui Cai, Qingsong Jiang, Jiaxing Fu, Lian Hu, Man Zhang, Yifan Li, Jincheng Li, Yong Liu, Yue Qin
article en

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 proposes 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 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. • Water Source Zones of level 3 (WRZ3) was optimal scale for hierarchical calibration • Bias-integrated weighted method balanced streamflow and irrigation effectively • Irrigation weighting, close to water-to-runoff ratio, optimizes coupled simulation • Hierarchical calibration highly sensitive to meteorological and inflow data quality • CWatM is suitable for regional modelling, requiring a detailed basin-specific setup

Water CycleVol. 7
International Institute for Applied Systems Analysis (AT), Peking University (CN), Institute of Tibetan Plateau Research (CN)
Openalex Percentile: Top 73%
Hydrology and Watershed Management Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.