干旱区生态环境知识资源中心(Arid): Soil erosion assessment by RUSLE model using remote sensing and GIS in an arid zone

Arid

DOI	10.1080/17538947.2023.2243916
	Soil erosion assessment by RUSLE model using remote sensing and GIS in an arid zone
	Li, Pingheng; Tariq, Aqil; Li, Qingting; Ghaffar, Bushra; Farhan, Muhammad; Jamil, Ahsan; Soufan, Walid; El Sabagh, Ayman; Freeshah, Mohamed
通讯作者	Tariq, A
来源期刊	INTERNATIONAL JOURNAL OF DIGITAL EARTH
ISSN	1753-8947
EISSN	1753-8955
出版年	2023
卷号	16 期号:1 页码:3105-3124
英文摘要	In this research, we used the Revised Universal Soil Loss Equation (RUSLE) and Geographical Information System (GIS) to predict the annual rate of soil loss in the District Chakwal of Pakistan. The parameters of the RUSLE model were estimated using remote sensing data, and the erosion probability zones were determined using GIS. The estimated length slope (LS), crop management (C), rainfall erosivity (R), soil erodibility (K), and support practice (P) range from 0-68,227, 0-66.61%, 0-0.58, 495.99-648.68 MJ/mm.t.ha(-1) .year(-1), 0.15-0.25 MJ/mm.t.ha(-1) .year(-1), and 1 respectively. The results indicate that the estimated total annual potential soil loss of approximately 4,67,064.25 t.ha(-1).year(-1) is comparable with the measured sediment loss of 11,631 t.ha(-1).year(-1) during the water year 2020. The predicted soil erosion rate due to an increase in agricultural area is approximately 164,249.31 t.ha(-1).year(-1). In this study, we also used Landsat imagery to rapidly achieve actual land use classification. Meanwhile, 38.13% of the region was threatened by very high soil erosion, where the quantity of soil erosion ranged from 365487.35 t.ha(-1).year(-1). Integrating GIS and remote sensing with the RUSLE model helped researchers achieve their final objectives. Land-use planners and decision-makers use the result's spatial distribution of soil erosion in District Chakwal for conservation and management planning.
英文关键词	RUSLE Landsat land management DEM soil erosion
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:001047039500001
WOS关键词	SPATIAL-DISTRIBUTION ; LAND-USE ; PREDICTION ; DISTRICT ; CLIMATE ; SYSTEM
WOS类目	Geography, Physical ; Remote Sensing
WOS研究方向	Physical Geography ; Remote Sensing
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/396982
推荐引用方式 GB/T 7714	Li, Pingheng,Tariq, Aqil,Li, Qingting,et al. Soil erosion assessment by RUSLE model using remote sensing and GIS in an arid zone[J],2023,16(1):3105-3124.
APA	Li, Pingheng.,Tariq, Aqil.,Li, Qingting.,Ghaffar, Bushra.,Farhan, Muhammad.,...&Freeshah, Mohamed.(2023).Soil erosion assessment by RUSLE model using remote sensing and GIS in an arid zone.INTERNATIONAL JOURNAL OF DIGITAL EARTH,16(1),3105-3124.
MLA	Li, Pingheng,et al."Soil erosion assessment by RUSLE model using remote sensing and GIS in an arid zone".INTERNATIONAL JOURNAL OF DIGITAL EARTH 16.1(2023):3105-3124.