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Lookup NU author(s): Dr Mohamed Akl, Dr Brian Thomas, Professor Peter ClarkeORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2025 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license. http://creativecommons.org/licenses/by/4.0/. Accurate monitoring of groundwater resources is essential for sustainable water management, especially under escalating pressures from climate variability and intensive human activities. Despite significant advancements provided by the Gravity Recovery and Climate Experiment (GRACE) satellites in monitoring terrestrial water storage anomalies (GRACE-TWSA), isolating representative groundwater signals (GRACE-GWA) remains challenging. This is primarily due to uncertainties in complementary water budget components, which are essential for disaggregating GRACE-TWSA. While multi-model approaches to deriving GRACE-GWA can account for these uncertainties, systematic frameworks to objectively compare and constrain multi-model realizations against observed groundwater data remain scarce. To address this gap, we apply a multi-objective comparative framework employing Nash–Sutcliffe Efficiency (NSE) and Kling-Gupta Efficiency (KGE) metrics to compare multi-model GRACE-GWA realizations against in-situ basin-scale groundwater anomalies. Although these metrics are widely used in the hydrologic community, their combined application for GRACE-GWA evaluation is uncommon. Unlike conventional correlation-based approaches, our framework captures critical aspects of time series similarity, including seasonal amplitude fidelity and magnitude consistency, thus enabling clearer identification of optimal groundwater storage realizations. Our findings reveal significant uncertainty between multi-model groundwater storage trend and seasonal amplitude, emphasizing critical limitations often overlooked in standard GRACE-GWA assessments. By systematically isolating the most hydrologically consistent realizations, our framework significantly enhances the reliability, interpretability, and applicability of GRACE-based groundwater estimates. This methodological framework supports more accurate groundwater monitoring, strengthens data-driven decision-making processes, and ultimately contributes toward ensuring the long-term sustainability and resilience of vital groundwater resources.
Author(s): Akl M, Thomas BF, Clarke PJ
Publication type: Article
Publication status: Published
Journal: Journal of Hydrology
Year: 2026
Volume: 664
Issue: Part A
Print publication date: 01/01/2026
Online publication date: 11/10/2025
Acceptance date: 06/10/2025
Date deposited: 03/11/2025
ISSN (print): 0022-1694
ISSN (electronic): 1879-2707
Publisher: Elsevier BV
URL: https://doi.org/10.1016/j.jhydrol.2025.134403
DOI: 10.1016/j.jhydrol.2025.134403
Data Access Statement: Data will be made available on request.
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