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

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?...

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Main Authors: Yonghua Zhao, Li Liu, Shuaizhi Kang, Yong Ao, Lei Han, Chaoqun Ma
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Land
Subjects:
Online Access:https://www.mdpi.com/2073-445X/10/6/604
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spelling doaj-b92083aeaf104e34acae05369ff6f4552021-06-30T23:27:24ZengMDPI AGLand2073-445X2021-06-011060460410.3390/land10060604Quantitative Analysis of Factors Influencing Spatial Distribution of Soil Erosion Based on Geo-Detector Model under Diverse Geomorphological TypesYonghua Zhao0Li Liu1Shuaizhi Kang2Yong Ao3Lei Han4Chaoqun Ma5The 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, ChinaThe 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, ChinaThe 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, ChinaThe 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, ChinaThe 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, ChinaThe 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, ChinaThe 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<sup>2</sup>·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.https://www.mdpi.com/2073-445X/10/6/604soil erosionRUSLE modelGeo-detector modelmodel applicabilityYan’an City
collection DOAJ
language English
format Article
sources DOAJ
author Yonghua Zhao
Li Liu
Shuaizhi Kang
Yong Ao
Lei Han
Chaoqun Ma
spellingShingle Yonghua Zhao
Li Liu
Shuaizhi Kang
Yong Ao
Lei Han
Chaoqun Ma
Quantitative Analysis of Factors Influencing Spatial Distribution of Soil Erosion Based on Geo-Detector Model under Diverse Geomorphological Types
Land
soil erosion
RUSLE model
Geo-detector model
model applicability
Yan’an City
author_facet Yonghua Zhao
Li Liu
Shuaizhi Kang
Yong Ao
Lei Han
Chaoqun Ma
author_sort Yonghua Zhao
title Quantitative Analysis of Factors Influencing Spatial Distribution of Soil Erosion Based on Geo-Detector Model under Diverse Geomorphological Types
title_short Quantitative Analysis of Factors Influencing Spatial Distribution of Soil Erosion Based on Geo-Detector Model under Diverse Geomorphological Types
title_full Quantitative Analysis of Factors Influencing Spatial Distribution of Soil Erosion Based on Geo-Detector Model under Diverse Geomorphological Types
title_fullStr Quantitative Analysis of Factors Influencing Spatial Distribution of Soil Erosion Based on Geo-Detector Model under Diverse Geomorphological Types
title_full_unstemmed Quantitative Analysis of Factors Influencing Spatial Distribution of Soil Erosion Based on Geo-Detector Model under Diverse Geomorphological Types
title_sort quantitative analysis of factors influencing spatial distribution of soil erosion based on geo-detector model under diverse geomorphological types
publisher MDPI AG
series Land
issn 2073-445X
publishDate 2021-06-01
description 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<sup>2</sup>·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.
topic soil erosion
RUSLE model
Geo-detector model
model applicability
Yan’an City
url https://www.mdpi.com/2073-445X/10/6/604
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