Data and scripts supporting Tiwari et al. (2025) "Similarities and divergent patterns in hydrologic fluxes and storages simulated by global water models"
收藏NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Data_and_scripts_supporting_Tiwari_et_al_2025_Similarities_and_divergent_patterns_in_hydrologic_fluxes_and_storages_simulated_by_global_water_models_/28654751
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资源简介:
Global Water Models (GWMs) are critical tools for understanding the Earth's water cycle and water resource management under changing climate and accelerating human interventions. While GWMs have been evaluated for hydrologic fluxes (e.g., river discharge) and the role of representing human activities, there is a persistent gap in understanding models’ ability to simultaneously reproduce fluxes and storages (e.g., terrestrial water storage; TWS). Here, we show that eight state-of-the-art GWMs do not consistently reproduce discharge and TWS with same efficacy across varied geographic and climatic regions. Further, model performance for discharge deteriorates as human impacts intensify. While a general agreement between simulated and observed TWS trends is found in two-third of major global river basins, models tend to underestimate the trends in both directions. Likewise, no single model simulates TWS trends and seasonality accurately and uniformly across major global river basins. While improvements in capturing basin-averaged TWS trends, spatial distributions, and seasonal fluctuations have been achieved compared to previous reports, challenges remain in accurately reproducing both fluxes and storages, owing primarily to inadequate representation of human activities in heavily managed regions. This study underscores critical disparities in GWM performance, emphasizing the need for further model enhancements which is crucial for improved and more robust hydrologic assessments and predictions under climate change.
创建时间:
2025-03-24



