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Showing 2 results for Analytical Hierarchy Process

Dr Amir Saberinasr, Dr Majid Dashti Barmaki,
Volume 18, Issue 2 (9-2024)
Abstract

One of the strategies for water storage in arid and semi-arid areas such as Iran is the construction of underground dams; however, identifying suitable sites for the construction of these structures remains a major challenge. The aim of this paper is to identify the optimal locations for the construction of underground dams using a geographic information system and multi-criteria decision making techniques. Firstly, thematic maps were prepared in ArcGIS environment including geological condition, land use, landslide potential, topography, water stress, aquifer area and distance from dam, village, qanat, stream, fault, airport and road. Hierarchical analysis and fuzzy logic methods were used to weight the prepared maps. By removing unsuitable and restricted areas for the construction of underground dams, a final potential map for this structure was prepared. The results show that the provinces of Razavi and South Khorasan, Kerman, Yazd, Sistan and Baluchistan, Hamedan, Qazvin, Zanjan, Markazi and Qom have greater potential for the construction of underground dams than other provinces in the country. Finally, to validate the results, a comparison was made between the results presented in this study and several successful underground dam projects in the country, showing a relatively close match between the potential map and the implemented structures.

Nafiseh Shokri, Dr Aliakbar Momeni,
Volume 19, Issue 4 (12-2024)
Abstract

The purpose of this study is to create a map of landslide hazard potential along the Tuskestan road using Analytical Hierarchy Process (AHP) model. The effective parameters on landslides that were used in this study are lithology, slope, slope aspect, vegetation, distance from the road, distance from the stream, and distance from the fault. At the first, a map of each of these parameters is prepared and divided into three or four subgroups based on their changes. Then, using hierarchical analysis, for each of these subgroups based on the degree of superiority , a weight was assigned to compare them together, so that qualitative maps are converted into quantitative maps. The result of this weighting showed that lithology and slope had the greatest effect, while the distance from the fault had the least effect in landslide hazard zoning. The final weight of each layer was obtained by multiplying the weight of each parameter by the weight of its sub-group. Finally, these quantitative maps were integrated into the Geographic Information System (GIS) environment to obtain the final landslide hazard zonation map. Assessment of the location of the previous landslides showed that among the 7 old landslides, 6 landslides were in the range of high hazard potential and 1 landslide was in the relatively high hazard category, which indicates the accuracy of the landslide hazard map. The obtained hazard zoning map showed that 9.3% of this area with an area of 355 hectares is located in the category of high hazard potential of landslides.


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