Soil Erosion Susceptibility Mapping Using GIS and AHP Case Study Kalat-e-Naderi, Northeast Iran

Soil erosion is one of the most important natural hazards which negatively affect crop production inagriculture by losing the nutrient components of soil (Jebur et al., ۲۰۱۴). Several factors could be responsibleto increase soil erosion rate. This study aims to determine soil erosion susceptibility zones using GIS andspatial analyst tools in conjunction with Analytical Hierarchy Process (AHP) in Kalat-e-Naderi, northeastIran. The combination of the AHP method and GIS (Saaty, ۱۹۸۰) is one of the most powerful tools whichdemonstrated its valence in different assessments like soil erosion hazard mapping (Alexakis et al., ۲۰۱۳).The study area is partly covered by loess. The majority of agricultural lands in the study area are locatedon loess-covered sections due to their fertility (Chesworth, ۱۹۸۲; Smalley, ۱۹۶۸). Since loess is highlyerodible by water and mass movements, finding out the high-risk zones is necessary for sustainableagricultural activities. Eight indicators affecting soil erosion were selected to create the soil erosionsusceptibility map. Hypsometric and slope maps were driven out from ALOS-PALSAR (with ۱۲.۵-meterpixel size) digital elevation model (DEM). Elevation by affecting soil organic matter (Halefom & Teshome,۲۰۱۹) and slope by providing suitable conditions for surficial flows in steeper slopes (Tahmassebipoor etal., ۲۰۱۶) influence soil erosion. Landuse, NDWI, and NDVI were extracted from Landsat-۸ OLI (۳۰ mresolution). The image used in this study belongs to August ۲۰۱۸. Different types of landuses could impactsoil erosion rates. Greater values of NDWI can cause more soil erosion by the wetness of the soil andinstability. In terms of NDVI, poor vegetation areas (values near zero) like bare lands are more susceptibleto soil erosion. The lithology raster layer was prepared based on the ۱:۱۰۰۰۰۰ geologic map of the studyarea. Every geologic formation can change the erosion rate based on its erosion resistance. The more theformation is resistant, the erosion rate decreases. Distance from road and streams were calculated inArcMap. To determine the road, Google Earth was used. By deforming the profiles and vegetation cover,roads can cause soil erosion (Seutloali & Beckedahl, ۲۰۱۵). Streames were extracted from the digitalelevation model. The dense stream network could increase the soil erosion. Weighting has been done foreach factor using the Analytical Hierarchy Process (AHP) by a pairwise comparison matrix. The final maphas been generated by combining all factors in Geographic Information System (GIS). The final map showsfive different soil erosional susceptibility zones, ranging from low to very high (Fig. ۱). Based on the results,more than ۴۵% of the study area is in the high and very high-risk zones (Table۱). Based on the pairwisecomparison (table ۲), Lithology, landuse, distance from streams, elevation, and slope are respectively themain factors in the soil erosion in the study area.

کلیدواژه ها:

soil erosion ، AHP ، GIS ، Loess ، susceptibility mapping