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

Yonghua Zhao, Li Liu, Shuaizhi Kang, Yong Ao, Lei Han and Chaoqun Ma
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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

Land, 2021, vol. 10, issue 6, 1-17

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.

Keywords: soil erosion; RUSLE model; Geo-detector model; model applicability; Yan’an City (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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