Landslide hazard mapping of oghan watershed basin in Golestan province using Analytic Network Process (ANP) model

Document Type : Complete scientific research article

Authors

1 Consultant of Red Crescent

2 Professor- azad nive.science and research branch

3 Assistant. Professor

Abstract

Extended abstract​
Background and objectives
Landslide is one of the most destructive natural events in steep areas. Due to its geographical position, climatic and geomorphological conditions, population increase, pressure on natural resources and land use change, Iran is exposed to natural hazards. Therefore, preparation of landslide hazards mapping is very important. So according to landslide events reports of Oghan watershed basin in Golestan province, The aim for this research is landslide hazards mapping using Analytic Network Process model.
Materials and methods
For landslide hazard mapping in Oghan watershed basin, At first step, maps of effective factors were prepared by using of information sources, 1:50000 topographic and 1:100000 geological maps, rain statistics, aerial photos and satellite images. Then, these information were completed by field surveying in mentioned region that its geographical position is between37° 9´ to 37° 15´ northern latitude and 55° 5´ to 55° 43´eastern longitude with area and average altitude of 40352 ha. After that, maps of the effective factors were organized, such as: slope, aspect, elevation, rain, distance from streams, roads and fault, land use, lithology and landslide dispersion layer at ArcGIS. In the second step, the weight of effective factors was calculated by ANP model and applied to the information layers in the GIS environment. By overlapping them, a map of zonation of landslide occurrence was prepared. In the third step, the accuracy of the map of zonation was evaluated using the degree of proportionality and index Density ratio.
Results
Result of identification of 88 landslide zones with area of 181ha and investigation of their relationship with effective factors showed that most of landslides are located in lithological units of shale, marl, bedded limestone, sandstone and quaternary deposits (Table1). Furthermore, results of elevation and slope layers assessment show that most landslides were happened in slope of 15-30% . In rain classes assessment, landslide occurrence has direct relationship with rain increase and classes of 500-700 and more than 700mm of annual rain have considerable percent of landslide. Results of distance from road and stream showed that most of occurred landslides are in distance less than 100m from these features and it demonstrates the role of mass taking from downhill via human or natural factors. Finally, assessment of distance from fault showed that most of landslides are located in distance classes of more than 400m (Table1).
Conclusion
The results of zonation with the ANP model in the Oghan watershed basin showed that 29 percent of the basin in the four classes is in high and very high hazard areas. Among the eight information layers, the slop factor (0.215), lithology (0.182) and distance from the road with score weighted (0.173) had the highest weight and gradient direction with the score weight (0.018), the lowest Points in the zonation. Evaluation of different classes of effective factors also showed that the class is 100 m distance from the distance from streams with score weight (0.08), slope class of 15-15% with a rate weight (0,788) and a class of 100-0 (m) distance from the road With a score weight of 0.068, they earned the highest rating weighted. The results of this model finally showed that the convergence of factors such as slope, lithology, distance from the river as natural factors along with the human factor, such as road construction, has a great influence on the hazard of landslide. Finally, by studying the density rate of 88 landslide occurrence in the basin and its upward curve and the adaptation of the sliding zones with the application of the degree of proportionality of 69.7% on the high and very high classes in the final map

Keywords


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