干旱区生态环境知识资源中心(Arid): Assessment of the gully erosion susceptibility using three hybrid models in one small watershed on the Loess Plateau

Arid

DOI	10.1016/j.still.2022.105481
	Assessment of the gully erosion susceptibility using three hybrid models in one small watershed on the Loess Plateau
	Wang, Ziguan; Zhang, Guanghui; Wang, Chengshu; Xing, Shukun
通讯作者	Zhang, GH
来源期刊	SOIL & TILLAGE RESEARCH
ISSN	0167-1987
EISSN	1879-3444
出版年	2022
卷号	223
英文摘要	Gully erosion is globally considered a severe environmental problem that causes great damage to arable lands, roads, and forests; therefore, it is crucial to evaluate the gully erosion susceptibility. The objective of this study was to establish three hybrid models based on VlseKriterijumska optimizacija I Kompromisno Resenje (VIKOR), frequency ratio (FR), random forest (RF), gradient boosting decision tree (GBDT), and randomized tree (ET) data to assess the susceptibility of gully erosion in a small watershed of the Loess Plateau of China. We extracted 540 gullies with 24, 919 gully pixels and 11 conditioning factors were extracted and utilized to establish a gully inventory database. Subsequently, FR was applied to determine the relationships between the conditioning factors and gully pixels, and machine learning methods were used to quantify the relative importance of these conditioning factors. Three hybrid gully erosion susceptibility models, that is, VIKOR-FR-RF, VIKOR-FR-GBDT, and VIKOR-FR-ET, were established for gully erosion susceptibility mapping (GESM). The receiver operating characteristic curve (ROC) and area under the curve (AUC) were utilized to evaluate the performance of these models. The results showed that elevation, distance to road, and the normalized difference vegetation index significantly contributed to the gully occurrences. VIKOR-FR-ET had the highest performance, with an AUC of 0.83, followed by VIKOR-FR-RF (AUC = 0.81) and VIKOR-FR-GBDT (AUC = 0.70). Therefore, we concluded that VIKOR-FR-ET was the most efficient approach for predicting gully erosion susceptibility in a semi-arid region, such as the Loess Plateau. Our results will help design soil and water conservation measures for gully erosion control at small watershed scales.
英文关键词	Gully erosion susceptibility mapping Hybrid model VIKOR Machine learning The Loess Plateau
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000883425700009
WOS关键词	REGION ; PERFORMANCE ; PARAMETERS ; REGRESSION ; RESOLUTION ; VIKOR
WOS类目	Soil Science
WOS研究方向	Agriculture
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/394506
推荐引用方式 GB/T 7714	Wang, Ziguan,Zhang, Guanghui,Wang, Chengshu,et al. Assessment of the gully erosion susceptibility using three hybrid models in one small watershed on the Loess Plateau[J],2022,223.
APA	Wang, Ziguan,Zhang, Guanghui,Wang, Chengshu,&Xing, Shukun.(2022).Assessment of the gully erosion susceptibility using three hybrid models in one small watershed on the Loess Plateau.SOIL & TILLAGE RESEARCH,223.
MLA	Wang, Ziguan,et al."Assessment of the gully erosion susceptibility using three hybrid models in one small watershed on the Loess Plateau".SOIL & TILLAGE RESEARCH 223(2022).