Fan Xinfeng, Wang Lei, Liu Hu, Chen Deliang, Song Lei, Wang Yuanwei, Qi Jia, Chai Chenhao, Liu Ruishun, Li Xiuping, Zhou Jing, Guo Xiaoyu, Long Junshui
State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China.
University of Chinese Academy of Sciences, Beijing, 100049, China.
Sci Data. 2024 Jul 13;11(1):773. doi: 10.1038/s41597-024-03623-3.
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.
径流和蒸散发（ET）是水、能量和碳循环的关键组成部分。本研究展示了一个1998 - 2017年的5公里月度网格化径流和ET数据集，涵盖青藏高原七条河流（黄河、长江、湄公河、萨尔温江、雅鲁藏布江、恒河和印度河）的源头（以下简称TPRED）。该数据集是使用先进的冰冻圈 - 水文模型WEB - DHM生成的，与观测流量相比，纳什系数在0.77至0.93之间。研究结果表明，TPRED的月度径流在捕捉水文模式方面明显优于现有数据集，相关系数（CC）（0.944 - 0.995）、偏差（-0.68 - 0.53）和均方根误差（5.50 - 15.59毫米）等稳健指标证明了这一点。此外，TPRED的月度ET估计值与预期的季节性波动密切吻合，与其他ET产品对比时，CC范围为0.94至0.98。此外，TPRED的年度值在多个维度上与业务产品表现出值得称赞的一致性。最终，TPRED将在水文气象学、碳运输、水资源管理、水文建模和水资源可持续发展方面有很大的应用价值。
