干旱区生态环境知识资源中心(Arid): Soil Erosion Susceptibility Mapping in Kozetopraghi Catchment, Iran: A Mixed Approach Using Rainfall Simulator and Data Mining Techniques

Arid

DOI	10.3390/land9100368
	Soil Erosion Susceptibility Mapping in Kozetopraghi Catchment, Iran: A Mixed Approach Using Rainfall Simulator and Data Mining Techniques
	Esmali Ouri, Abazar; Golshan, Mohammad; Janizadeh, Saeid; Cerda, Artemi; Melesse, Assefa M.
通讯作者	Melesse, AM
来源期刊	LAND
EISSN	2073-445X
出版年	2020
卷号	9 期号:10
英文摘要	Soil erosion determines landforms, soil formation and distribution, soil fertility, and land degradation processes. In arid and semiarid ecosystems, soil erosion is a key process to understand, foresee, and prevent desertification. Addressing soil erosion throughout watersheds scales requires basic information to develop soil erosion control strategies and to reduce land degradation. To assess and remediate the non-sustainable soil erosion rates, restoration programs benefit from the knowledge of the spatial distribution of the soil losses to develop maps of soil erosion. This study presents Support Vector Machine (SVM), Random Forest (RF), and adaptive boosting (AdaBoost) data mining models to map soil erosion susceptibility in Kozetopraghi watershed, Iran. A soil erosion inventory map was prepared from field rainfall simulation experiments on 174 randomly selected points along the Kozetopraghi watershed. In previous studies, this map has been prepared using indirect methods such as the Universal Soil Loss Equation to assess soil erosion. Direct field measurements for mapping soil erosion susceptibility have so far not been carried out in our study site in the past. The soil erosion rate data generated by simulated rainfall in 1 m(2) plots at rainfall rate of 40 mmh(-1) was used to develop the soil erosion map. Of the available data, 70% and 30% were randomly classified to calibrate and validate the models, respectively. As a result, the RF model with the highest area under the curve (AUC) value in a receiver operating characteristics (ROC) curve (0.91), and the lowest mean square error (MSE) value (0.09), has the most concordance and spatial differentiation. Sensitivity analysis by Jackknife and IncNodePurity methods indicates that the slope angle is the most important factor within the soil erosion susceptibility map. The RF susceptibility map showed that the areas located in the center and near the watershed outlet have the most susceptibility to soil erosion. This information can be used to support the development of sustainable restoration plans with more accuracy. Our methodology has been evaluated and can be also applied in other regions.
英文关键词	AdaBoost model hydrological response units (HRUs) rainfall simulator parameter importance Iran soil erosion
类型	Article
语种	英语
开放获取类型	gold
收录类别	SSCI
WOS记录号	WOS:000587451900001
WOS关键词	GULLY HEADCUTS ; RUNOFF ; REGRESSION ; ALGORITHM ; VINEYARDS ; MODELS ; SCALE ; WATER ; PLOT ; CONSERVATION
WOS类目	Environmental Studies
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/327399
作者单位	[Esmali Ouri, Abazar] Univ Mohaghegh Ardabili, Fac Agr & Nat Resources, Dept Watershed Management, Ardebil 5619911367, Iran; [Golshan, Mohammad] Astara, Adm Nat Resources & Watershed Management, Guilan 4391817897, Iran; [Janizadeh, Saeid] Tarbiat Modares Univ, Fac Nat Resources & Marine Sci, Dept Watershed Management Engn & Sci, Tehran 14115111, Iran; [Cerda, Artemi] Univ Valencia, Dept Geog, Soil Eros & Degradat Res Grp, Blasco Ibanez 28, Valencia 46010, Spain; [Melesse, Assefa M.] Florida Int Univ, Dept Earth & Environm, AHC 5-390,11200 SW 8th St, Miami, FL 33199 USA
推荐引用方式 GB/T 7714	Esmali Ouri, Abazar,Golshan, Mohammad,Janizadeh, Saeid,et al. Soil Erosion Susceptibility Mapping in Kozetopraghi Catchment, Iran: A Mixed Approach Using Rainfall Simulator and Data Mining Techniques[J],2020,9(10).
APA	Esmali Ouri, Abazar,Golshan, Mohammad,Janizadeh, Saeid,Cerda, Artemi,&Melesse, Assefa M..(2020).Soil Erosion Susceptibility Mapping in Kozetopraghi Catchment, Iran: A Mixed Approach Using Rainfall Simulator and Data Mining Techniques.LAND,9(10).
MLA	Esmali Ouri, Abazar,et al."Soil Erosion Susceptibility Mapping in Kozetopraghi Catchment, Iran: A Mixed Approach Using Rainfall Simulator and Data Mining Techniques".LAND 9.10(2020).