What can hydrological modelling gain from spatially explicit parameterization and multi-gauge calibration?

Zheng, Xudong; Liu, Dengfeng; Wang, Hao; Ma, Chuanhui; Liu, Hui; Ming, Guanghui; Li, Qiang; Khan, Mohd Yawar Ali; Hussain, Fiaz

doi:10.5194/hess-30-2493-2026

Articles | Volume 30, issue 8

https://doi.org/10.5194/hess-30-2493-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-30-2493-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 30, issue 8

Research article

|

29 Apr 2026

Research article |

| 29 Apr 2026

What can hydrological modelling gain from spatially explicit parameterization and multi-gauge calibration?

Xudong Zheng, Dengfeng Liu, Hao Wang, Chuanhui Ma, Hui Liu, Guanghui Ming, Qiang Li, Mohd Yawar Ali Khan, and Fiaz Hussain

Supplement

https://doi.org/10.5194/hess-30-2493-2026-supplement

Data sets

MODIS/Terra+Aqua BRDF/Albedo Black Sky Albedo Shortwave Daily L3 Global 30ArcSec CMG V061 C. Schaaf and Z. Wang https://doi.org/10.5067/MODIS/MCD43D51.061

MODIS/Terra Vegetation Indices Monthly L3 Global 1km SIN Grid V061 K. Didan https://doi.org/10.5067/MODIS/MOD13A3.061

MODIS/Terra Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid V061 R. Myneni et al. https://doi.org/10.5067/MODIS/MOD15A2H.061

ERA5-Land monthly averaged data from 1950 to present J. Muñoz Sabater https://doi.org/10.24381/cds.68d2bb30

China multi-period land use remote sensing monitoring dataset (CNLUCC) X. Xu et al. https://doi.org/10.12078/2018070201

Model code and software

Code for the paper "What can Hydrological Modelling gain from Spatially Explicit Parameterization and Multi-gauge Calibration?" Xudong Zheng https://doi.org/10.5281/zenodo.18076164

Short summary

This study presents an experimental framework (EF-SPM) to disentangle and evaluate the benefits of spatially explicit parameterization and multi-gauge calibration in distributed hydrological modelling. Experiments in a nested catchment show that both strategies consistently improve streamflow simulations across sub-basins, jointly alleviating multi-objective competition and the trade-off between spatial complexity and parameter identifiability.