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 Taheri; Hasan Ahmadi; Jamal Ghodousi; ُSadat Feiznia; Shahram Khalighi Sigaroudi; Mohamad Hossein Ramesht
Abstract
subsidence in urban areas poses significant risks to infrastructure, including buildings, roads, railways, pipelines, sewage systems, and wells. Therefore, assessing its potential is crucial. This study models the subsidence risk in Karaj city using Geographic Information Systems (GIS) and the Weight ...
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subsidence in urban areas poses significant risks to infrastructure, including buildings, roads, railways, pipelines, sewage systems, and wells. Therefore, assessing its potential is crucial. This study models the subsidence risk in Karaj city using Geographic Information Systems (GIS) and the Weight of Evidence (WoE) model. To achieve this, we created maps of factors influencing subsidence, such as slope, alluvial thickness, groundwater fluctuations, aquifer layering, particle size, and permeability. These maps were then compared with recorded subsidence data to determine the weight of each factor's influence. By integrating the effects of these factors, a Subsidence Index (SI) map was generated and categorized using the Success Rate Curve (SRC), identifying five sensitivity zones from very sensitive to very low sensitivity. The effectiveness of the WoE model was evaluated, revealing that the subsidence sensitivity prediction map covers 93.64% of actual occurrences. Results indicated that aquifer layering positively influences subsidence development, with the highest impact arising from alluvial deposits with good permeability and fine particles. This factor, with a weight of 3.72, demonstrates significant influence among all evaluated parameters. In terms of thickness, the most significant subsidence occurred in alluvial deposits exceeding 200 meters. Areas experiencing groundwater level declines of over half a meter annually markedly contributed to subsidence. Additionally, slopes of less than two degrees were identified as the most susceptible to subsidence. Thus, while many areas in Karaj are relatively safe, the threat is notably higher in the southern and southwestern parts, requiring special attention in urban management.
tayebeh sohrabi; Abbas Ali Vali; Abolfazl Ranjbar Fordoei; sayed Hojat Mousavi
Abstract
Dust event is one of the secondary complications of ecosystem in arid and semi-arid areas. This phenomenon results from system feedback against multiple factors of pressure and destruction. One of the most important foundations of ecosystems is vegetation. Because the vegetation factor reflects many ...
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Dust event is one of the secondary complications of ecosystem in arid and semi-arid areas. This phenomenon results from system feedback against multiple factors of pressure and destruction. One of the most important foundations of ecosystems is vegetation. Because the vegetation factor reflects many factors in the ecosystem, therefore, the interaction of factors can be understood by studying the relationship between its changes and other factors such as dust phenomena. The aim of this study was to investigate the effect of vegetation and relationship with dust events in Esfahan province during 2000-2016 using Geographic information system and Normalized difference vegetation index. The data of dusty days in the region synoptic stations were provided from Meteorological Organization and the frequency of dusty days in different years were determined. Using the method of Normal Kriging in GIS; dusty days were zoned. Vegetation map was prepared based on NDVI in July for each year using MODIS image. The regression analysis of annual dust and vegetation index were also performed to quantitatively analyze the effect of vegetation cover on the occurrence of dust.The results showed. Vegetation cover has been the lowest during the study period in the east and center of the province. The NDVI was also the lowest in 2011-2012 and 2015, with a change from 0.69 to -0.19. The results showed significant correlation between the number of dust event and vegetation distribution
Mahsa Ghazimoradi; Mostafa Tarkesh; Hossein Bashari; Mohammad Reza Vahabi
Abstract
In this study, the ability of Generalized Additive Model (GAM) for mapping potential distribution of Ferula ovina Boiss, and the description of species response curves to environmental variables were examined in Fereidonshar region with area of 1000 square kilometers located in West of Isfahan province. ...
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In this study, the ability of Generalized Additive Model (GAM) for mapping potential distribution of Ferula ovina Boiss, and the description of species response curves to environmental variables were examined in Fereidonshar region with area of 1000 square kilometers located in West of Isfahan province. The presence and absence data of the species were collected from 278 sites (including 138 presence sites and 140 absence sites) by random systematic method, and 9 soil variables, 22 climate variables and 3 physiographic variables were mapped with pixel size of 72*72 square meters by using interpolation techniques (krigging, Inverse Distance Weighting) for the entire studied area. Then, the relationships between presence and absence of the species with the environmental variables were examined by GAM method. According to the results, the presence of Ferula ovina was inversely correlated with some environmental variables including soil silt and clay contents and also its distribution was directly correlated with slope, distance from sea level, organic matter content, soil saturation percentage and average annual temperature. The model evaluation conducted by the separate data gave Kappa coefficient equal to 0.64 and ROC area under curve equal to 0.86. According to the produced potential habitat map and the response curves of the species, the presence of Ferula ovina is more likely in the habitats with mean annual temperature: 9-11 degree centigrade, slop: 25-50%, elevation: 1950-3000 meter (Above sea level), CaCO3 content of soil: 10-30%, organic matter: 4-6%, silt: 10-30% and soil saturation percentage: 45-60%. The GAM enables managers to identify appropriate areas for rangelands rehabilitation and protection programs. The produced model has a suitable performance in identifying regions with high growth potential and rangelands rehabilitation and protection programs.
