Articles | Volume 29, issue 3
https://doi.org/10.5194/hess-29-627-2025
https://doi.org/10.5194/hess-29-627-2025
Research article
 | 
04 Feb 2025
Research article |  | 04 Feb 2025

Achieving water budget closure through physical hydrological process modelling: insights from a large-sample study

Xudong Zheng, Dengfeng Liu, Shengzhi Huang, Hao Wang, and Xianmeng Meng

Data sets

TRMM (TMPA) Precipitation L3 1 day 0.25 degree x 0.25 degree V7 G. J. Huffman et al. https://doi.org/10.5067/TRMM/TMPA/DAY/7

GlobSnow v3.0 Northern Hemisphere snow water equivalent dataset (https://www.globsnow.info/swe/) K. Luojus et al. https://doi.org/10.1038/s41597-021-00939-2

The CAMELS data set: catchment attributes and meteorology for large-sample studies (https://ncar.github.io/hydrology/datasets/CAMELS_attributes) N. Addor et al. https://doi.org/10.5194/hess-21-5293-2017

ERA5-Land: a state-of-the-art global reanalysis dataset for land applications (https://doi.org/10.24381/cds.e2161bac) J. Muñoz-Sabater et al. https://doi.org/10.5194/essd-13-4349-2021

Download
Short summary
Water budget non-closure is a widespread phenomenon among multisource datasets which undermines the robustness of hydrological inferences. This study proposes a Multisource Dataset Correction Framework grounded in Physical Hydrological Process Modelling to enhance water budget closure, termed PHPM-MDCF. We examined the efficiency and robustness of the framework using the CAMELS dataset and achieved an average reduction of 49 % in total water budget residuals across 475 CONUS basins.