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https://doi.org/10.5194/nhess-2020-85
https://doi.org/10.5194/nhess-2020-85
20 Apr 2020
 | 20 Apr 2020
Status: this preprint has been withdrawn by the authors.

Erosion risk assessment and identification of susceptibility lands using the ICONA model and RS and GIS techniques

Hossein Esmaeili Gholzom, Hassan Ahmadi, Abolfazl Moeini, and Baharak Motamed Vaziri

Abstract. Soil erosion in Iran due to the destruction of natural resources has intensified in recent years and land use changes have played a significant role in this process. On the other hand, the lack of data in most watersheds to evaluate erosion and sedimentation for finding quick and timely solutions for watershed management has made the use of models inevitable. The purpose of this study was to use the ICONA model and RS and GIS techniques to assess the risk of erosion and to identify areas sensitive to water erosion in the kasilian watershed in northern Iran. The results of this study showed that with very high slope class percentage (20 %–35 %) and sensitivity of shemshak formation to weathering which covers a large part of the watershed, soil erodibility class is high. But there is adequate land cover along with high percentage of natural forest cover, it has mitigated erosion. For this reason, the kasilian watershed is generally classified as low to moderate of erosion risk. Based on the erosion risk map, results show that the moderate class had the highest percentage of erosion risk (26.26 %) at the watershed. On the other hand, the low erosion risk class comprises a significant portion (25.44 %) of the catchment area. Also, 10.92 % of the catchment area contains a very high erosion risk class, with most of it in rangeland and Rock outcrops second. However, the erodibility of the kasilian watershed is currently controlled by appropriate land cover, but the potential susceptibility to erosion is high. If land cover is redused due to inadequate land management, the risk of erosion is easily increased.

This preprint has been withdrawn.

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Hossein Esmaeili Gholzom, Hassan Ahmadi, Abolfazl Moeini, and Baharak Motamed Vaziri
Hossein Esmaeili Gholzom, Hassan Ahmadi, Abolfazl Moeini, and Baharak Motamed Vaziri
Hossein Esmaeili Gholzom, Hassan Ahmadi, Abolfazl Moeini, and Baharak Motamed Vaziri

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