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The aim of this research is landslide hazard assessment in a part of Haraz watershed using fuzzy multi

criteria decision making. At first, landslide locations were identified using aerial photos and field study,

then landslide distribution map was produced. Effective factors on landslide occurrence such as: slope,

aspect, elevation, lithology, land use, distance to fault, distance to road and distance to drainage network

were digitized in GIS environment as shape digital layers and then used for analysis of fuzzy sets theory.

Fuzzy analysis was accomplished after determining membership function for each effective parameter in

landslide occurred using Matlab 7.1 software. Then the results representing hazard degree for each pixel

in case study map was transported in ILWIS software and landslide hazard zonation was produced. The

results showed that identified landslides were located in the class very high (29.42%), high (32.19%), moderate

(30.36%) and low (8.04%) in susceptibility zones.

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Dam underground structures that block the natural flow of ground water and underground water resources are causing. The purpose of this study was to determine the suitable location for the construction of an underground dam method of fuzzy and boolean logic and the AHP. The parameters which are used to locate underground dam slope, geology, permeability, curve numbers, land use, EC, distance from roads, distance from the village, residential water demand and the thickness of the alluvium. Layers corresponding to each parameter is weighted by the theory of fuzzy logic and analyse hierarchy process and the operator product algebra multiplication factors were combined.Also because of the underground dam constructed on the bed of the stream and the slope is less than 5%, These two layers are considered as a filter, The underground dam was set to 17 fertile region of the 11 points in the underground dam was right And 6 points in the area of underground dams were relatively favorable

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Increasing population in one side and water demands in other sides, the importance of groundwater resources as one of the most important fresh water resources, be more and more apparent. In this study, stream density, distance from drainage, slope, elevation, thickness of the aquifer, water table, rainfall, topography wetness index and the rate of permeability criteria were used to identify areas with potential of groundwater in Varamin plain.  The Map of these criteria prepared and weighted using Analytical Hierarchy Process method, and with determination of the effective rate for each class and using fuzzy logic, prediction map of groundwater potential with two methods of AHP and fuzzy AHP were prepared and accuracy of the method was evaluated using wells with high discharge. The results showed that, due to hydro-geological complexity of the area, accuracy of fuzzy AHP and AHP was respectively 61 and 54 percent. Also, the areas with high potential were located in the northern half of the plains which covered with coarse sediment during the Quaternary. The results showed that application of fuzzy AHP method, besides saving time and money, had a good ability to predict the groundwater potential

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The main aim of this study is to estimate the Curves Number based on remote sensing and fuzzy methods for use in precipitation-runoff modelling. For this purpose, Landsat-7 satellite images were used for the second degree basin of Gorgan River, northern Iran. By making the corrections and satellite images processing using ENVI, the NDVI index of vegetation and the type of vegetation were extracted. Then, using soil map, obtained from the National's Resources Comprehensive Plan, and land slope map the type of vegetation, the CN of the sub-basins with fuzzy logic and non-fuzzy approaches calculated. To evaluate the calculated CN, a rainfall-runoff event was selected and by simulating the rainfall-runoff using HEC-HMS model, the runoff simulation was performed. The results showed that the calculated CN involving Landsat-7, using fuzzy logic simulated the runoff more accurately than non-fuzzy. So that the coefficients of determination between the observed and simulated hydrographs, obtained from non-fuzzy, fuzzy Gaussian and fuzzy trapezoidal functions were obtained equal 0.76, 0.94 and 0.84, respectively. Also, the maximum flow rate of the simulated hydrograph compared to the observed hydrograph in the fuzzy state has a difference of less than 2 m3/s compared to the non-fuzzy with a difference of 5 m3/s.