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Quantitative Analysis of Factors Influencing Spatial Distribution of Soil Erosion Based on Geo-Detector Model under Diverse Geomorphological Types

Author

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  • Yonghua Zhao

    (The School of Land Engineering, Shaanxi Key Laboratory of Land Consolidation, Key Laboratory of Degraded and Unused Land Consolidation Engineering, the Ministry of Natural and Resources, Chang’an University, Xi’an 710054, China)

  • Li Liu

    (The School of Land Engineering, Shaanxi Key Laboratory of Land Consolidation, Key Laboratory of Degraded and Unused Land Consolidation Engineering, the Ministry of Natural and Resources, Chang’an University, Xi’an 710054, China)

  • Shuaizhi Kang

    (The School of Land Engineering, Shaanxi Key Laboratory of Land Consolidation, Key Laboratory of Degraded and Unused Land Consolidation Engineering, the Ministry of Natural and Resources, Chang’an University, Xi’an 710054, China)

  • Yong Ao

    (The School of Land Engineering, Shaanxi Key Laboratory of Land Consolidation, Key Laboratory of Degraded and Unused Land Consolidation Engineering, the Ministry of Natural and Resources, Chang’an University, Xi’an 710054, China)

  • Lei Han

    (The School of Land Engineering, Shaanxi Key Laboratory of Land Consolidation, Key Laboratory of Degraded and Unused Land Consolidation Engineering, the Ministry of Natural and Resources, Chang’an University, Xi’an 710054, China)

  • Chaoqun Ma

    (The School of Land Engineering, Shaanxi Key Laboratory of Land Consolidation, Key Laboratory of Degraded and Unused Land Consolidation Engineering, the Ministry of Natural and Resources, Chang’an University, Xi’an 710054, China)

Abstract

The Loess Plateau of China suffers from severe erosion, which results in a great variety of economic and ecological problems. For scientific control of soil erosion, the key questions urgently to be addressed in this paper are: (1) Which are the driving factors under diverse geomorphological types? (2) Do these driving factors operate independently or by interacting? (3) Which zones under diverse geomorphological types suffer from severe erosion and need more attention? In this paper, the RUSLE model was applied here to demonstrate the spatio-temporal variations in soil erosion from 2010 to 2017 in Yan’an City, and the Geo-detector model proved to be a useful tool to solve the questions mentioned above. The results showed that the average erosion modulus in Yan’an City decreased by 1927.36 t/km 2 ·a from 2010 to 2017. The intensity of soil erosion in the northern Baota District, central Ganquan County, Luochuan County, Ansai County, and Zhidan County decreased to varying degrees. The effect size of driving factors affecting soil erosion varied significantly in diverse geomorphological types. The effect size of interaction between land-use types and vegetation coverage, land-use types and slope, slope and precipitation was higher than that of a single factor. High-risk zones with severe erosion were closer to cultivated land and forest land with steep slopes (>25°) in the mid-elevation hills of Yan’an City. Additionally, based on the specificity of the study area, the Geo-detector model performed better in a relatively flat region, and factors with macroscopic spatial distributions weaken its explanatory power on soil erosion on a regional scale. Based on data selection, data of different accuracy sparked the issue of “data coupling”, which led to the enormous deviation of model results in mid-elevation plains. Results from our analysis provide insights for a more ecologically sound development of Yan’an City and provide references for the scientific use of the Geo-detector model.

Suggested Citation

  • Yonghua Zhao & Li Liu & Shuaizhi Kang & Yong Ao & Lei Han & Chaoqun Ma, 2021. "Quantitative Analysis of Factors Influencing Spatial Distribution of Soil Erosion Based on Geo-Detector Model under Diverse Geomorphological Types," Land, MDPI, vol. 10(6), pages 1-17, June.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:6:p:604-:d:569892
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    References listed on IDEAS

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    1. Liu, Yansui, 2018. "Introduction to land use and rural sustainability in China," Land Use Policy, Elsevier, vol. 74(C), pages 1-4.
    2. Yao, Xiaolei & Yu, Jingshan & Jiang, Hong & Sun, Wenchao & Li, Zhanjie, 2016. "Roles of soil erodibility, rainfall erosivity and land use in affecting soil erosion at the basin scale," Agricultural Water Management, Elsevier, vol. 174(C), pages 82-92.
    3. Dlamini, P. & Orchard, C. & Jewitt, G. & Lorentz, S. & Titshall, L. & Chaplot, V., 2011. "Controlling factors of sheet erosion under degraded grasslands in the sloping lands of KwaZulu-Natal, South Africa," Agricultural Water Management, Elsevier, vol. 98(11), pages 1711-1718, September.
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    Citations

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    Cited by:

    1. Xu Yang & Xuan Zou & Xueqi Liu & Qixuan Li & Siqian Zou & Ming Li, 2023. "The Spatiotemporal Pattern and Driving Mechanism of Urban Sprawl in China’s Counties," Land, MDPI, vol. 12(3), pages 1-16, March.
    2. Chao Yang & Jianrong Fan & Jiali Liu & Fubao Xu & Xiyu Zhang, 2021. "Evaluating the Dominant Controls of Water Erosion in Three Dry Valley Types Using the RUSLE and Geodetector Method," Land, MDPI, vol. 10(12), pages 1-16, November.
    3. Maomao Zhang & Abdulla-Al Kafy & Bing Ren & Yanwei Zhang & Shukui Tan & Jianxing Li, 2022. "Application of the Optimal Parameter Geographic Detector Model in the Identification of Influencing Factors of Ecological Quality in Guangzhou, China," Land, MDPI, vol. 11(8), pages 1-20, August.
    4. Jingya Tang & Lichun Sui, 2022. "Geodetector-Based Livability Analysis of Potential Resettlement Locations for Villages in Coal Mining Areas on the Loess Plateau of China," Sustainability, MDPI, vol. 14(14), pages 1-19, July.
    5. Shixian Xu & Xinjun Wang & Xiaofei Ma & Shenghan Gao, 2023. "Risk Assessment and Prediction of Soil Water Erosion on the Middle Northern Slope of Tianshan Mountain," Sustainability, MDPI, vol. 15(6), pages 1-14, March.
    6. Guoyi Cui & Yan Zhang & Feihang Shi & Wenxia Jia & Bohua Pan & Changkun Han & Zhengze Liu & Min Li & Haohao Zhou, 2022. "Study of Spatiotemporal Changes and Driving Factors of Habitat Quality: A Case Study of the Agro-Pastoral Ecotone in Northern Shaanxi, China," Sustainability, MDPI, vol. 14(9), pages 1-23, April.
    7. Yuankai Ge & Longlong Zhao & Jinsong Chen & Xiaoli Li & Hongzhong Li & Zhengxin Wang & Yanni Ren, 2023. "Study on Soil Erosion Driving Forces by Using (R)USLE Framework and Machine Learning: A Case Study in Southwest China," Land, MDPI, vol. 12(3), pages 1-20, March.

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