ArticleScientific data2024
Tibetan Plateau Runoff and Evapotranspiration Dataset by an observation-constrained cryosphere-hydrology model.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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13 authors.
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Abstract
Runoff and evapotranspiration (ET) are pivotal constituents of the water, energy, and carbon cycles. This research presents a 5-km monthly gridded runoff and ET dataset for 1998-2017, encompassing seven headwaters of Tibetan Plateau rivers (Yellow, Yangtze, Mekong, Salween, Brahmaputra, Ganges, and Indus) (hereinafter TPRED). The dataset was generated using the advanced cryosphere-hydrology model WEB-DHM, yielding a Nash coefficient ranging from 0.77 to 0.93 when compared to the observed discharges. The findings indicate that TPRED's monthly runoff notably outperforms existing datasets in capturing hydrological patterns, as evidenced by robust metrics such as the correlation coefficient (CC) (0.944-0.995), Bias (-0.68-0.53), and Root Mean Square Error (5.50-15.59 mm). Additionally, TPRED's monthly ET estimates closely align with expected seasonal fluctuations, as reflected by a CC ranging from 0.94 to 0.98 when contrasted with alternative ET products. Furthermore, TPRED's annual values exhibit commendable concordance with operational products across multiple dimensions. Ultimately, the TPRED will have great application on hydrometeorology, carbon transport, water management, hydrological modeling, and sustainable development of water resources.
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