Maryam Asadi; Arash Malekian; Ali Salajegheh
Abstract
GCM models are widely used to assess climate change on a global scale, but outputs of these models are not sufficient and accurate to assess climate change at local and regional levels. Therefore, in this study, SDSM model was used for micro-scaling of CanESM2 model data and climate conditions of Semirom ...
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GCM models are widely used to assess climate change on a global scale, but outputs of these models are not sufficient and accurate to assess climate change at local and regional levels. Therefore, in this study, SDSM model was used for micro-scaling of CanESM2 model data and climate conditions of Semirom region based on three scenarios of RCP2.6, RCP4.5 and RCP8.5 in the period 2020 to 2100. The results of model evaluation based on NCEP database showed that the model was more accurate in estimating and predicting temperature data especially mean temperature. Comparison of observation and simulated data of temperature and precipitation of GCMs in the baseline period (1980 to 2005) based on NCEP predictor variables showed the mean correlation of precipitation data of 0.52, mean temperature of 0.88, maximum temperature of 0.80 and minimum temperature of 0.70 for validation and verification periods. The results of the estimation of precipitation variations in different scenarios also predicted a decrease of at least 7.24% and a maximum of 18.55% for the time period of 2020 to 2100 compared to the baseline period (1980-2005). The results of precipitation prediction also show the changes of precipitation pattern. The comparison of the scenarios also shows that the RCP2.6 scenario as the most optimistic scenario has the least rainfall while the RCP8.5 scenario predicts the highest rainfall reduction. Examination of the predicted changes in temperature also shows an increase for the mean, minimum and maximum temperatures,
saeid khosrobeigi bozchelui; Arash Malekian; Alireza Moghaddam Nia; Shahra,m Khalighi
Abstract
Flood is one of the most devastating natural disasters, causing financial and human losses each year. At the same time, many rivers in Iran's watersheds lack complete and accurate statistics and information. On the other hand, estimating the flow of floods is one of the most important factors for the ...
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Flood is one of the most devastating natural disasters, causing financial and human losses each year. At the same time, many rivers in Iran's watersheds lack complete and accurate statistics and information. On the other hand, estimating the flow of floods is one of the most important factors for the design and implementation of water structures. In such cases, one of the appropriate solutions to estimate the maximum flow rate with different return periods is flood analysis. In order to conduct the present study, 55 hydrometric stations with a common statistical period of 20 years were considered to perform the work after the statistical deficiencies were eliminated. Then, based on the distribution of the third type of Pearson logo with the lowest error rate and the highest number of first rank as the most suitable fit function, the amount of discharge in different return periods was estimated. The following information was collected on the types of physiography, land use, climate and geology variables. After collecting information about all independent variables using Gamma test, the most important variables affecting the maximum instantaneous flow, including area, drainage density, maximum 24-hour rainfall and watershed environment, were selected and modeled using methods. Random forest modeling and support vector modeling were performed and their efficiency was determined based on statistical indicators With an efficiency coefficient of 74 to 83%, the error of 3.05 to 32.11 m3 and the coefficient of explanation of 76 to 91 are more accurate than the random forest model.
Javad Motamedi; Ali Mohebi; Kambiz Alizadeh
Abstract
Background: Coping with climate change (CC) is part of the way to face this phenomenon. This depends on the understanding of CC and the degree of adaptability to it.Objective: The research was conducted with the aim of measuring the level of nomads' understanding (NU) of CCe and their adaptation strategies ...
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Background: Coping with climate change (CC) is part of the way to face this phenomenon. This depends on the understanding of CC and the degree of adaptability to it.Objective: The research was conducted with the aim of measuring the level of nomads' understanding (NU) of CCe and their adaptation strategies (AS) in the face of CC.Research method: The research was descriptive and the data collection tool was a questionnaire whose items were obtained based on interviews.Findings: NU of the effects of CC is not the same. According to them, CC has had the most obvious impact on vegetation. The priority of AS is also different in the face of CC. A positive relationship was observed between understanding the effects of CC and the degree of adaptability in facing CC. Nomads who had a better understanding of the effects of CC have used livestock management strategies to adapt to it. Age and history of animal husbandry had a positive relationship with the level of understanding of the effects of CC. A negative and significant relationship was also observed between the number of animals and the degree of compatibility.Conclusion: The NU of CC and its effects on the ecology of the environment is an important starting point in dealing with the negative effects of CC and choosing appropriate strategies to adapt or deal with it. So that the selection of suitable adaptation methods by the nomads reduces the vulnerability of CC on the condition of livestock and rangeland.
