Abstract
Landslides and slope instabilities are major risks for human activities which often lead to economic losses and human fatalities all over the world. The main purpose of this study is to evaluate and compare the results of Landslide Nominal Risk Factor (LNRF), Frequency Ratio (FR), and Analytical Hierarchy Process (AHP) models in mapping Landslide Susceptibility Index (LSI). The study case, Nojian watershed with an area of 344.91 km2, is located in Lorestan province of Iran. The procedure was as follows: first, the effective factors of the landslide basin were prepared for each layer in the GIS software. Then, the layers and the landslides of the basin were also prepared using aerial photographs, satellite images, and fieldwork. Next, the effective factors of the layers were overlapped with the map of landslide distribution to specify the role of units in such distribution. Finally, nine factors including lithology, slope, aspect, altitude, distance from the fault, distance from river, fault land use, rainfall, and altitude were found to be effective elements in landslide occurrence of the basin. The final maps of LSI were prepared based on seven factors using LNRF, FR, and AHP models in GIS. The index of the quality sum (Qs) was also used to assess the accuracy of the LSI maps. The results of the three models with LNRF (40%), FR (39%), and AHP (44%) indicated that the whole study area was located in the classes of high to very high hazard. The Qs values for the three models above were also found to be 0.51, 0.70 and 0.70, respectively. In comparison, according to the amount of Qs, the results of AHP and FR models have slightly better performed than the LNRF model in determining the LSI maps in the study area. Finally, the study watershed was classified into five classes based on LSI as very low, low, moderate, high, and very high. The landslide susceptibility maps can be helpful to select sites and mitigate landslide hazards in the study area and the regions with similar conditions.
Highlights
Landslides cause great damages in residential areas, roads, facilities, agricultural fields, gardens, grasslands, etc
Based on the relative weight, the factor of lithology (0.242), slope (0.197), land use (0.183), distance from the fault (0.174), rainfall (0.103), altitude (0.043), aspect (0.026), distance from the road (0.018), and distance from the main drainage (0.014) in the order of priority were identified as the effective factors contributing to landslide occurrence in the Nojian watershed
We attempted to compare the results of landslide susceptibility mapping using three different models, namely Landslide Nominal Risk Factor (LNRF), 1 3
Summary
Landslides cause great damages in residential areas, roads, facilities, agricultural fields, gardens, grasslands, etc. Recognizing the mechanism and zoning of prone areas to landslide occurrence play a crucial role in disaster management. It can be employed as a standard tool to support decision-making in different areas (Bui et al 2016). Potentially there are suitable conditions for slope instability related to the alternating layers of limestone and thin layers of the marl and deeply weathered formation on the slopes. Due to geomorphological properties such as lithology, tectonics activity, altitude, seismicity, slope, climatic conditions, deeply weathered formation and human impact, the study watershed was potentially highly prone to landslide occurrence. Conditions of topography and geomorphology, climatology and human impact of the study area have provided the best position for sliding small or large masses of materials of the slopes
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