Literature DB >> 30456707

Spatial gradient and quantitative attribution of karst soil erosion in Southwest China.

Jiangbo Gao1, Huan Wang2,3, Liyuan Zuo2,3.   

Abstract

Soil erosion estimation has attracted considerable attention from the scientific community and governments because of its importance to sustainable regional development. In karst areas, the heterogeneous environment and rocky desertification create difficulties in determining the influencing factors and spatial patterns of soil erosion. A quantitative analysis of karst soil erosion distribution was conducted by applying the revised soil loss equation model and the geographical detector method of attribution identification, which was based on spatial variance analysis. The results show that soil erosion was most severe in areas with an elevation of 1200-1800 m and intense anthropogenic activity. When the vegetation coverage was below 0.5-0.6, soil erosion showed characteristics of a source-limited regime and increased with the increasing vegetation coverage. When the vegetation coverage was higher than 0.5-0.6, soil erosion followed a transport-limited regime and decreased with the increasing vegetation coverage. The factor detector showed land use to be the dominant factor, explaining 51% of soil erosion distribution. Among various land use types, dry land had the greatest vulnerability to soil erosion. Slope served as a controlling factor at large scales, especially when combined with annual precipitation exceeding 1500 mm, and in dry and grassland areas. From the attribution analysis of multiple factors, the combination of land use and slope was the controlling interaction factor explaining 68% of soil erosion distribution. The methods and results of this research could serve as scientific references for decision makers and researchers exploring the characteristics of soil erosion to develop effective measures for its control.

Keywords:  Geographical detectors; RUSLE model; Soil erosion determinants; Spatial consistence; Spatial distribution

Mesh:

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Year:  2018        PMID: 30456707     DOI: 10.1007/s10661-018-7116-2

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  6 in total

1.  [Integrated assessment of eco-environmental vulnerability in Pearl River Delta based on RS and GIS].

Authors:  Qing-Yong Xu; Mei Huang; Hong-Sheng Liu; Hui-Min Yan
Journal:  Ying Yong Sheng Tai Xue Bao       Date:  2011-11

2.  Adapting the RUSLE and GIS to model soil erosion risk in a mountains karst watershed, Guizhou Province, China.

Authors:  Xu Yue-Qing; Shao Xiao-Mei; Kong Xiang-Bin; Peng Jian; Cai Yun-Long
Journal:  Environ Monit Assess       Date:  2007-09-19       Impact factor: 2.513

3.  Soil erosion and sediment fluxes analysis: a watershed study of the Ni Reservoir, Spotsylvania County, VA, USA.

Authors:  Ian C Pope; Ben K Odhiambo
Journal:  Environ Monit Assess       Date:  2013-10-19       Impact factor: 2.513

4.  Soil loss estimation and prioritization of sub-watersheds of Kali River basin, Karnataka, India, using RUSLE and GIS.

Authors:  Vipin Joseph Markose; K S Jayappa
Journal:  Environ Monit Assess       Date:  2016-03-11       Impact factor: 2.513

5.  Impact of tillage erosion on water erosion in a hilly landscape.

Authors:  Y Wang; J H Zhang; Z H Zhang; L Z Jia
Journal:  Sci Total Environ       Date:  2016-02-17       Impact factor: 7.963

6.  Environmental stochasticity controls soil erosion variability.

Authors:  Jongho Kim; Valeriy Y Ivanov; Simone Fatichi
Journal:  Sci Rep       Date:  2016-03-01       Impact factor: 4.379

  6 in total
  1 in total

1.  Spatiotemporal variation and influencing factors of vegetation cover in the ecologically fragile areas of China from 2000 to 2015: a case study in Shaanxi Province.

Authors:  Dingrao Feng; Jinman Wang; Meichen Fu; Guangchao Liu; Min Zhang; Rongbin Tang
Journal:  Environ Sci Pollut Res Int       Date:  2019-08-06       Impact factor: 4.223

  1 in total

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