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An innovative hydrological model for the sparsely-gauged Essequibo River basin, northern Amazonia

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DataCite Commons2025-05-12 更新2024-08-18 收录
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https://tandf.figshare.com/articles/dataset/An_innovative_hydrological_model_for_the_sparsely-gauged_Essequibo_River_basin_northern_Amazonia/24562653
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Tropical river basins – crucial components of global water and carbon cycles – are threatened by logging, mining, agricultural conversion, and climate change. Thus, decision-makers require hydrological impact assessments to sustainably manage threatened basins, such as the ∼68,000 km<sup>2</sup> Essequibo River basin in Guyana. Emerging global data products offer the potential to better understand sparsely-gauged basins. We combined new global meteorological and soils data with established <i>in situ</i> observations to build the first physically-based spatially-distributed hydrological model of the Essequibo. We developed new, open source, methods to translate global data (ERA5-Land, WFDE5, MSWEP, and IMERG) into a grid-based SHETRAN model. Comparing the performance of several global and local precipitation and evaporation datasets showed that WFDE5 precipitation, combined with ERA5-Land evaporation, yielded the best daily discharge simulations from 2000 to 2009, with close water balances (PBIAS = −3%) and good discharge peaks (NSE = 0.65). Finally, we tested model sensitivity to key parameters to show the importance of actual to potential evapotranspiration ratios, Strickler runoff coefficients, and subsurface saturated hydraulic conductivities. Our data translation methods can now be used to drive hydrological models nearly anywhere in the world, fostering the sustainable management of the Earth’s sparsely-gauged river basins.

热带河流流域作为全球水文与碳循环的关键组成部分,正面临伐木、采矿、农业开垦以及气候变化的多重威胁。为此,决策者需开展水文影响评估,以对受威胁流域实现可持续管理,例如圭亚那境内面积约6.8万平方千米的埃塞奎博河流域。新兴全球数据产品为深入理解观测稀疏(sparsely-gauged)流域提供了新的可能。本研究将新型全球气象与土壤数据与已有的原位(in situ)观测数据相结合,构建了首个针对埃塞奎博河流域的物理机制空间分布式水文模型。本研究开发了全新的开源方法,可将ERA5-Land、WFDE5、MSWEP及IMERG等全球数据转换为基于网格的SHETRAN模型。通过对比多套全球与局地降水、蒸发数据集的模拟表现,本研究发现结合使用WFDE5降水数据与ERA5-Land蒸发数据,可在2000年至2009年间实现最优的日径流模拟效果,其水量平衡偏差极小(百分比偏差PBIAS = -3%),且径流峰值模拟表现良好(纳什效率系数NSE = 0.65)。最后,本研究通过测试模型对关键参数的敏感性,阐明了实际与潜在蒸散比、斯特里克勒径流系数以及地下饱和导水率的重要性。目前,本研究开发的数据转换方法可用于驱动全球几乎任意区域的水文模型,为全球观测稀疏河流流域的可持续管理提供助力。
提供机构:
Taylor & Francis
创建时间:
2023-11-14
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