Temporal and spatial variation characteristics of surface water area in the Yellow River Basin from 1986 to 2021

Ying Yong Sheng Tai Xue Bao. 2023 Mar;34(3):761-769. doi: 10.13287/j.1001-9332.202303.021.

Abstract

The Yellow River Basin is short of water resources. The dynamic monitoring of surface water area is helpful to clarify the distribution and change trend of water resources in this area. It is of great scientific significance to deeply understand the impacts of climate change and human activities on water resources and ensure the ecological security of the basin. Based on the Google Earth Engine (GEE) cloud platform, we analyzed the spatial variations of surface water area in the Yellow River Basin from 1986 to 2021 by using the mixed index algorithm, and revealed the driving factors of surface water area change in the Yellow River Basin. The results showed that the overall recognition accuracy of the water extraction algorithm based on mixing index was 97.5%. Compared with available water data products, the proposed algorithm can guarantee the integrity of the whole water area to a certain extent. The surface water area in the upper, middle, and lower reaches of the Yellow River Basin was 71.7%, 18.4%, and 9.9% of the total surface water area, respectively. From 1986 to 2021, the surface water area of the basin showed an overall upward trend, with a total increase of 3163.6 km2. The surface water area of the upper, middle, and downstream regions increased by 72.0%, 22.4%, and 5.6%, respectively. The increase of precipitation was the main reason for the increase of water area, with a contribution of 55%. Vegetation restoration and construction of water conservancy projects had increased the water area of the basin. The intensification of human water extraction activity reduced the water area of the basin.

黄河流域水资源短缺,开展地表水体面积的动态监测,有助于明晰流域水资源的分布状况与变化趋势,对深入理解气候变化和人类活动对水资源的影响、保障流域生态安全具有重要的科学意义。本研究基于Google Earth Engine(GEE)云平台,利用混合指数算法,分析1986—2021年黄河流域地表水体面积的空间格局与变化特征,并揭示了流域地表水体面积变化的驱动因素。结果表明: 基于混合指数的水体提取算法总体识别精度为97.5%;相比现有部分水体数据产品,本算法在一定程度上能保证水域整体的完整性。黄河流域上、中、下游地区的地表水体面积分别占流域地表水体总面积的71.7%、18.4%、9.9%。1986—2021年间,流域地表水体面积总体呈上升趋势,共增加3163.6 km2,上、中、下游地区流域地表水体面积分别增加72.0%、22.4%、5.6%。降水量的增多是流域水体面积增加的主要原因,其贡献率为55%;植被恢复、兴建水利工程等对流域水体面积起增加作用;人类取水活动的加剧对流域水体面积起减少作用。.

Keywords: Google Earth Engine (GEE); Yellow River Basin; influencing factor; surface water area; temporal and spatial pattern.

MeSH terms

  • Algorithms
  • China
  • Climate Change
  • Environmental Monitoring*
  • Humans
  • Rivers
  • Water*

Substances

  • Water