A Novel Two‐Step Method for Enforcing Water Budget Closure and an Intercomparison of Budget Closure Correction Methods Based on Satellite Hydrological Products

Author:

Luo Zengliang12ORCID,Li Huan345ORCID,Zhang Sihan12,Wang Lunche12ORCID,Wang Shaoqiang12ORCID,Wang Lizhe67ORCID

Affiliation:

1. Key Laboratory of Regional Ecology and Environmental Change School of Geography and Information Engineering China University of Geosciences Wuhan China

2. Hubei Key Laboratory of Yangtze Catchment Environmental Aquatic Science China University of Geosciences Wuhan China

3. Balaton Limnological Research Institute Tihany Hungary

4. School of Earth and Space Sciences Institute of Remote Sensing and GIS Peking University Beijing China

5. Shuhai Information Technology Co. Ltd. Beijing China

6. School of Computer Science China University of Geosciences Wuhan China

7. Hubei Key Laboratory of Intelligent Geo‐Information Processing China University of Geosciences Wuhan China

Abstract

AbstractEnforcing terrestrial water budget closure is critical for obtaining consistent data sets of budget components to understand the changes and availability of water resources over time. However, most existing budget closure correction methods (BCCs) are significantly affected by errors in the budget‐component products. Moreover, these existing BCCs do not fully account for the preselection of high‐precision input data sets before enforcing the water budget closure, resulting in uncertainties in the budget‐corrected data sets. In this study, a two‐step method was proposed to enforce the water budget closure of satellite‐based hydrological products. First, high‐precision budget‐component data sets were selected and second, the water budget closure of the selected high‐precision data sets was then enforced by proposing an improved BCC strategy, that is, the Minimized Series Deviation method (MSD). The performance of the proposed two‐step method was verified in 24 global basins by comparing it to three existing BCCs of varying complexity, that is, Proportional Redistribution (PR), Constrained Kalman Filter (CKF), and Multiple Collocation (MCL). The results showed that compared to the existing BCCs, the proposed two‐step method significantly improved the accuracy of budget‐corrected data sets in the range of 2%–19% (statistical analysis was based root mean square error (RMSE) and mean absolute error (MAE) with estimated observation (EO) as a reference). This study also summarized the main factors influencing the performance of the existing BCCs and their further development prospects based on the results. This provides insight into the expansion of theories and methods related to closing the terrestrial water budget.

Funder

National Natural Science Foundation of China

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

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