Spatiotemporal Variation of Soil Erosion Characteristics in the Qinghai Lake Basin Based on the InVEST Model

Int J Environ Res Public Health. 2023 Mar 8;20(6):4728. doi: 10.3390/ijerph20064728.

Abstract

The present study aims to quantitatively assess soil erosion intensity (SEI) and amounts in the Qinghai Lake Basin (QLB) over the 1990-2020 period using the Integrated Valuation Ecosystem Services and Tradeoffs (InVEST) model based on multi-source data. In addition, the changing trends and driving factors of soil erosion (SE) in the study area were systematically analyzed. The result showed: (1) An increasing-decreasing trend in the total soil erosion amount (SEA) in the QLB over the 1990-2020 period, with an average SEI of 579.52 t/km2. In addition, very low and low erosion classes covered 94.49% of the total surface area, while areas with high SEI were mainly distributed in alpine areas with low vegetation coverage (VC). (2) The highest average SEI was observed in bare land, while grassland and unused land were the main land use (LU) types where SE mainly occurred, with the ratio of the two being 95.78%. (3) The average value of SEI was positively correlated with altitude values below 4800 m. In addition, areas with altitude ranges of 4000-4400 m, 3600-4000 m, and 4400-4800 m were the main areas where SE occurred, with an average total soil erosion ratio (SER) value of 88.73%. (4) The average SEI was directly proportional to the slope degrees. SE occurred mainly in the areas with slope degree ranges of 15-25°, 25-35°, 8-15°, and >35°, accounting for 93.16% of the average total SER value. (5) The q value of the two-factor interaction was greater than that of the single-factor interaction. In addition, the areas with a high SE risk were mainly those with 1220-2510 m rainfall, <0.104 VC, the land use/land cover (LULC) type bare land, the altitude range 4400-4800 m, and a slope of >35°. The interaction between rainfall, VC, LULC, elevation, and slope had a significant impact on the spatial distribution of SEI.

Keywords: InVEST model; Qinghai Lake Basin; geographic detector; soil erosion; spatiotemporal variation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Conservation of Natural Resources
  • Ecosystem*
  • Environmental Monitoring
  • Lakes
  • Soil
  • Soil Erosion*

Substances

  • Soil

Grants and funding

This work was supported by the Second Tibetan Plateau Scientific Expedition and Research Program (grant no. 2019QZKK0405-02), Integration and Demonstration of In-situ Purification of Rivers Entering Qinghai Lake, and Ecological Management of Estuary Wetlands (grant no. 2022-QY-204).