The variation of rainfall runoff after vegetation restoration in upper reaches of the Yellow River by the remote sensing technology

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Abstract
In history, the Yellow River has been suffering from endless floods, which has brought great damage or destruction to agriculture, cities, and people’s lives and property along the river. In this study, the rainfall and runoff characteristics of the Yellow River upstream (Tangnaihai and Lanzhou) after the vegetation restoration were analyzed. With the government implementation of ecological restoration policy since 1999, the vegetation cover in this area has been greatly improved and the normalized difference vegetation index (NDVI) shows a fluctuating increase, with the maximum value of 0.323 (in 2010) and the minimum value of 0.289 (in 2008). The trend of rainfall from 1948 to 2019 was increased, with an average increase of 1.747mm per 10 years. Before the implementation of ecological policy (1948 to 1999), the rainfall decreased by an average of 0.953mm per 10 years, and then increased by an average of 16.519mm per 10 years (2000 to 2019). From 1998 to 2017, the runoff increased by 11.13×108m3 per 10 years (Tangnaihai) and 30.517×108 m3 (Lanzhou) per 10 years, which was due to the increase in rainfall. Annual sediment discharge and annual average sediment concentration decreased by 0.002×108t and 0.103 kg/m3 per 10 years in Tangnaihai, 0.081×108t and 0.395kg/m3 per 10 years in Lanzhou respectively. The decreasing intensity of Lanzhou station was greater. The sediment runoff modulus of Tangnaihai and Lanzhou decreased by 1.4875 km2·year and 4.9439 km2·year respectively. The increase of vegetation has a decreasing effect on sediment discharge. The implementation of ecological restoration policy reduces the amount of sediment into the Yellow River and plays an important role in the protection of ecological environment in the Yellow River Basin.
Funding Information
  • State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University (2018-KF-02)
  • open research fund program of State Key Laboratory of Hydroscience and Engineering, Tsinghua University (sklhse-2021-B-01)
  • National Natural Science Foundation of China (51479179 and 51579230)
  • Science Foundation of Zhejiang Ocean University (21105011713)
  • Innovation and Development of Social Science in Anhui Province (2019CX016)

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