JWSS - Journal of Water and Soil Science

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Chezgi J, Asiyaei M. Determination of Erosion-Prone Areas using GIS and Multi-Criteria Decision-Making Models: A Case Study: Bagheran Birjand Region. jwss 2021; 25 (1) :279-293
URL: http://jstnar.iut.ac.ir/article-1-3972-en.html

Erosion causes the reduction and degradation and the soil fertility; one of its most important consequences, endangering the food security of the inhabitants of the area. Therefore, to reduce erosion, it needs to be controlled and managed using good soil conservation methods. It is only necessary to manage and control the full impact of the factors affecting the soil first. If there is a critical state of erosion in the four watersheds, identifying the precise location of erosion will be done quickly and with less cost; thus, further erosion control and counter-operation will be feasible. In this study, geographic information system and decision making models of AHP and ANP in Bagheran region of Birjand were used to determine the erosion prone areas. First, 10 effective criteria including rain, slope, slope direction, soil, geology, permeability, vegetation, land use, distance from road and village, were determined on the erosion in the area based on the expert opinion and library studies. Next, the questionnaires were sent to experts to explore g the impact of the criteria on erosion; after completing the questionnaires based on Expert Choice and Supper Decision software, the relative importance of the criteria was obtained. The maps were then compiled and integrated according to the relative importance of the criteria. Rainfall factor had the greatest impact on the erodibility of the area in the AHP method with the relative importance of 0.21 and the   vegetation criterion with the weight of 0.158 in the ANP method had the most impact on the determination of erosion prone areas. Finally, the erodibility map of the area was obtained based on the presented models. Subsequently, the region was classified into five classes of erosion susceptibility, with areas of moderate sensitivity having the most area in both models. In the lower and upper classes, the ANP method performed better; in the middle classes the AHP method performed better.