mina pouresmaeel; ali salajegheh; Arash Malekian; amirreza keshtkar
Abstract
The complexity of the urban environment makes it difficult to consider all the vulnerable components of the urban. Hence, decision-making in urban environments is one of the most important issues in modern management. As a result, the purpose of this study is to investigate the urban vulnerability of ...
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The complexity of the urban environment makes it difficult to consider all the vulnerable components of the urban. Hence, decision-making in urban environments is one of the most important issues in modern management. As a result, the purpose of this study is to investigate the urban vulnerability of Azimiyeh in Karaj to flood based on multi-criteria decision-making method. The statistical population includes specialists who had sufficient knowledge and experience in the field of vulnerability management in urban areas. To this research, first, comprehensive knowledge of the factors affecting the urban vulnerability to floods was obtained using library studies, and then, the results of the Delphi technique, , was shown that among the primary indices, a total of 11 effective indicators were selected and a map of each of them was prepared using ArcGIS software. Then, the urban vulnerability to floods was calculated using the TOPSIS method. The study area was divided into 13 sub-areas based on runoff directional pattern and field observations, and then the decision matrix was made according to 13 sub-areas and 11 indicators. The results showed the vulnerability of this region to floods, which among the studied sub-areas, in sub-areas No. 1 and 2 observed the highest of flood vulnerability and the lowest of it observed in sub-area No. 13. Causes of flood vulnerability in the region include a direct connection to the upstream catchment that has lithology impermeable and geologically impermeable, high-density of building and population, and lack of proportionate open spaces.
Amir Reza Keshtkar; Behnaz Asefjah; Yusef Erfanifard; Ali Afzali
Abstract
The development and implementation of practical natural resources and catchment managementpolicies require a comprehensive knowledge of the system processes (biological, physical, andsocio-economic), their complicated interactions, and how they react to different changes. Thecurrent research assessed ...
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The development and implementation of practical natural resources and catchment managementpolicies require a comprehensive knowledge of the system processes (biological, physical, andsocio-economic), their complicated interactions, and how they react to different changes. Thecurrent research assessed the ecological, physical, and socio-economic consequences ofbiologically-based management scenarios targeting runoff and soil erosion problems in theDarenari catchment. The Darenari catchment with an approximate area of 554 ha is located in Farsprovince, Iran. Three biological activities and 8 management scenarios were considered. Ecologicalconsequences were studied using the weighted land cover area index (WLCAI). Physical effectswere investigated applying the runoff curve number (SCS-CN) hydrologic model. Economic andsocial effects were assessed applying the cost/benefit analysis as well as examining the outcomes ofa social survey. Then, a fuzzy AHP approach was applied to weigh the criteria and ultimately, thebest management option was chosen using FTOPSIS model. The results showed that social criteriawith the highest weight and scenario No 8 was the best scenario and had first priority. The resultsidicated that the multi-criteria decision making techniques included capability of expressingdifferent aspects of the problem and are the perfect tool for watershed resources management.
Arash Malekian; Mahrou Dehbozorgi; Amir Houshang Ehsani; Amir Reza Keshtkar
Abstract
Consecutive droughts in Sistan and Baloochestan province cause water resources restriction and this isa very significant problem for this region. In this study, in order to forecast the drought cycle in 9climatological stations in the province, we used Artificial Neural Networks. The input data wereaverage ...
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Consecutive droughts in Sistan and Baloochestan province cause water resources restriction and this isa very significant problem for this region. In this study, in order to forecast the drought cycle in 9climatological stations in the province, we used Artificial Neural Networks. The input data wereaverage of annual rainfall data in all stations and also deciles precipitation index, which the first 30years from 1971 to 2000 used for training the network and the last 8 years from 2001 to 2008 forsimulating it. The network consists of Multilayer Perceptron (MLP) and Back Propagation Algorithm(BP) and also sigmoid transfer function. Number of Neurons in hidden layer was 10 with 1-10-1structure and was calculated based on the lowest RMSE. Then drought prediction was done in neuralnetwork with the trained algorithm and without using actual and observed data in 2009 to 2012.Results showed that, the network was able to simulate and forecast DPI index with 97% regressionand average RMSE error less than 5%. According to drought indices, results showed that the droughtwill have an increasing trend in all stations in this region in 2009 to 2011. Therefore, by using thismethod, drought can be predicted in later years without any need to have actual meteorological dataand also can be used in water resources management, drought management and climate changes.
