Determining the drivers and rates of soil erosion on the Loess Plateau since 1901

Pengfei Li, Jiannan Chen, Guangju Zhao, Joseph Holden, Bintao Liu, Faith Ka Shun Chan, Jinfei Hu, Peili Wu, Xingmin Mu

Research output: Journal PublicationArticlepeer-review

1 Citation (Scopus)

Abstract

Attributing soil erosion to land management and climatic drivers is important for global policy development to protect soils. The Chinese Loess Plateau is one of the most eroded areas in the world. However, there has been limited assessment of historic spatial changes in erosion rates on the Loess Plateau and the major contributors driving these spatial changes. In this study, the Revised Universal Soil Loss Equation was empirically validated and employed to assess spatially distributed historical erosion rates on the Loess Plateau from 1901 to 2016. A double mass curve attribution technique was then used to investigate the impact of land management and climatic drivers on the Loess Plateau. Decadal average erosion rates and the total area with intensive erosion (>5000 t km−2 yr−1) experienced a sharp increase from the 1930s to 1970s, followed by a decline to an historic low between the 1980s and 2000s. Mean erosion rates for the 2000s were 54.3% less than those of the 1970s. However, a recent increase in erosion rates was observed between 2010 and 2016. Land management change was the dominant driver of historical erosion rate changes before 2010. Extensive deforestation and farming, driven by population increase, were responsible for intensifying erosion between the 1930s and 1970s, while policy-driven conservation schemes and revegetation led to reduction thereafter. However, the recent increase in erosion between 2010 and 2016 was mainly driven by extreme rainfall events, a major concern given climate change projections. Advanced erosion control strategies are therefore required as part of integrated catchment management that both maintain water supplies for human use during dry periods while reducing erosion during storm events.

Original languageEnglish
Article number153674
JournalScience of the Total Environment
Volume823
DOIs
Publication statusPublished - 1 Jun 2022

Keywords

  • Attribution analysis
  • Conservation
  • Land degradation
  • Modelling
  • Spatiotemporal patterns

ASJC Scopus subject areas

  • Environmental Engineering
  • Environmental Chemistry
  • Waste Management and Disposal
  • Pollution

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