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基于水文模型的印度次大陆河流流域 1951-2021 年的径流重建。

Hydrological model-based streamflow reconstruction for Indian sub-continental river basins, 1951-2021.

机构信息

Civil Engineering, Indian Institute of Technology (IIT) Gandhinagar, Gandhinagar, India.

Earth Sciences, Indian Institute of Technology (IIT) Gandhinagar, Gandhinagar, India.

出版信息

Sci Data. 2023 Oct 18;10(1):717. doi: 10.1038/s41597-023-02618-w.

Abstract

Streamflow is a vital component of the global water cycle. Long-term streamflow observations are required for water resources planning and management, hydroclimatic extremes analysis, and ecological assessment. However, long-term streamflow observations for the Indian-Subcontinental (ISC) river basins are lacking. Using meteorological observations, state-of-the-art hydrological model, and river routing model, we developed hydrological model-simulated monthly streamflow from 1951-2021 for the ISC river basins. We used high-resolution vector-based routing model (mizuRoute) to generate streamflow at 9579 stream reaches in the sub-continental river basins. The model-simulated streamflow showed good performance against the observed flow with coefficient of determination (R) and Nash-Sutcliffe efficiency (NSE) above 0.70 for more than 60% of the gauge stations. The dataset was used to examine the variability in low, average, and high flow across the streams. Long-term changes in streamflow showed a significant decline in flow in the Ganga basin while an increase in the semi-arid western India and Indus basin. Long-term streamflow can be used for planning water management and climate change adaptation in the Indian sub-continent.

摘要

河流径流量是全球水循环的重要组成部分。水资源规划和管理、水文极端事件分析以及生态评估都需要长期的河流径流量观测数据。然而,印度次大陆(ISC)流域的长期河流径流量观测数据却很匮乏。我们利用气象观测数据、最先进的水文模型和河道水流模型,为 ISC 流域的 1951 年至 2021 年的河流径流量建立了水文模型模拟数据。我们利用高分辨率基于矢量的河道水流模型(mizuRoute),在次大陆流域的 9579 个河道上生成了流量数据。模型模拟的径流量与观测到的流量具有很好的吻合度,超过 60%的测站的决定系数(R)和纳什-苏特克里夫效率(NSE)都在 0.70 以上。该数据集被用于研究河流径流量在低流量、平均流量和高流量之间的变化情况。长期的河流径流量变化显示,恒河流域的流量明显减少,而半干旱的印度西部和印度河流域的流量则有所增加。长期的河流径流量数据可用于规划印度次大陆的水资源管理和适应气候变化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d15/10584895/c6c207cc5963/41597_2023_2618_Fig1_HTML.jpg

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