Landslide Hazard Evaluation and Zonation of Karaj-Chalus Road (North of Iran)

Abstract

Article HistoryMass wasting, one of the major natural disaster, have resulted into significant injury and loss to the human life and damaged Property and infrastructure throughout the world. The studied area is located in the Alborz mountains Range from Karaj to Chalus, central Alborz mountain range, Iran; where is frequently affected by several different mass wasting types and needs to be considered and immediate attention. In this study 9 causative factors, include: drainage density, aspect, slope, vegetation density, lineation density, main fault buffer, landuse, lithology and seismic activity was considered. The studies have shown that the northern part of the rout falls under very low to low risk except near the MarzanAbad city because of the KalarDasht heights. Increasing vegetation density is one of the reasons for reducing the risk in the northern part of the rout. Very high risk zones are mainly concentrated between Aderan and Nesa cities that explained by the presence of steep slopes and the effect of the faults which affected this section of rout. There are significant risk reducing by getting away from the road. In general, most of the areas on this rout are zones that have the medium to high instability.Contribution/Originality: This study uses new estimation methodology in landslide hazard zonation in KarajChalus Road and the results of this study will help to preventing slope instability by enhancing the high risk areas.

How the Currency Crisis Effects the Relationship Between Financial Inflows and Economic Growth in Asean Country

“…An opportunity is created by inflows of remittances for reduction in the foreign exchange gap of reserves. Previously, several studies have empirically signified this through use of cross sectional and panel data to define the relation between remittances and EG (Jawaid & Raza, 2016;Meyer & Shera, 2017;Sorbi, & Farrokhnia, 2018). Moreover, fewer research studies have worked on this empirically using time series analysis.…”