Ali Heshmatpour; Seyed Javad Sajjadi; Yusuf Mohammadian
Abstract
Low rainfall with improper temporal and spatial distribution is a significant problem in arid and semi-arid areas. Due to the lack of water resources and the increasing water demand, access to new water resources is necessary. Rainwater collection is one of the most prominent methods of rainwater exploitation ...
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Low rainfall with improper temporal and spatial distribution is a significant problem in arid and semi-arid areas. Due to the lack of water resources and the increasing water demand, access to new water resources is necessary. Rainwater collection is one of the most prominent methods of rainwater exploitation management to deal with water shortage which is developing rapidly in many areas. Considering the diversity and breadth of rainwater collection methods, serious attention should be paid in choosing the influencing factors and the type of criteria combination method. In this article, in order to determine the places prone to the construction of rain catchment surfaces for livestock drinking, first the effective factors were determined with the studies conducted and the characteristics of the area.Seven factors were considered, including slope, land use, soil depth, distance from fault and waterway, proximity to livestock farming, and prevailing wind direction.The factors were ranked using the fuzzy logic technique.This involved dividing them into nine separate parts. A geographic information system was then used to overlap these layers. The results of this overlap were classified into five classes: poor, average, relatively good, good, and very good.The rainwater collection areas for each class were 44.01, 53.94, 30.31, 30.48 and 12.51 km², respectively. Also,Based on the results of fuzzy logic, the south and southeast part of the region had the first priority for the construction of rain catchment surfaces.Therefore, it can be used to collect rainwater and store it for future use.The findings of this research work will help policy makers and decision makers to implement different rainwater collection structures in the study area to overcome water shortage problems
Somayeh Movahedi; aboalhasan fathabadi; null null; Ali Heshmatpour
Abstract
In this study using Frequency Ratio (FR), Statistical Index (SI), Weights Of Evidence(WOF), Logistic Regression (LR), Random Forest (RF) models the probability of gully formation was calculated in Aytamar watershed and susceptibility maps was prepared. First the thematic maps of 13 gully conditioning ...
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In this study using Frequency Ratio (FR), Statistical Index (SI), Weights Of Evidence(WOF), Logistic Regression (LR), Random Forest (RF) models the probability of gully formation was calculated in Aytamar watershed and susceptibility maps was prepared. First the thematic maps of 13 gully conditioning factors including lithological formations, distance to faults, faults density, altitude, slope-length, slope angle, slope aspect, plan curvature, profile curvature, distance to roads, land use, distance to rivers, stream power index and topographic wetness index was prepared. Then landslide inventory map was combined with each gully conditioning factor and all models weights and parameters were calculated. Area under curve for test data was calculated as 0.74, 0.78, 0.75, 0.86 and 0.96 for Frequency Ratio (FR), Statistical Index (SI), Weights Of Evidence(WOF), Logistic Regression (LR), Random Forest (RF) models, respectively. Random forest, Frequency Ratio and Logistic Regression have the least the area of high susceptibility zone, respectively. With respect three validation criteria multivariate methods including Random Forest and Logistic Regression had the best performance among all models.
