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Volume 1, Issue 3 (10-2014)
Various community groups can play important role in disaster management. Countries with different segments of people directly participate in activities to reduce the risk. Therefore, regarding the role of women's participation in disaster management process and as a part of human society will have an important role in this process, identify and analyze the factors affecting women's presence is essential. However, the central role of women in families and communities remains unknown in most parts of the world specially in planning and managing the disaster. The purpose of this study is to identify and understand the different capabilities of women to participate actively in the cycle of disaster management and providing strategies for increasing women's participation in the prevention, preparedness, response and recovery of probable disasters. This study is an original and practical research. According to the theoretical research, a questionnaire was designed in four parts and it was completed through sampling. The sample population is women living in 22 districts of Tehran. This study implies that there is the low participation rate of women in disaster management among citizens of Tehran. To complete the data, proportional sampling was used and data were analyzed using factor analysis. Using this method, the data and the variables were summarized and the most effective factors were set in the partnership. These factors include disaster management, cultural factors and gender, fatalism, a feeling of power and confidence that the results of the factor analysis was performed using four dimensions. Based on tradition of social research and the findings of previous empirical research on women's participation in disaster management and the factors influencing voluntary participation, contextual condition of social variables (including socio-economic condition, occupation, marital status, number of children and age), as well as religious and fatalistic attitude would studied and evaluated the factors influencing the motivation and willingness to participate as a volunteer in the field of disaster management. The findings show that KMO value was equivalent to 0.74 in four factors of disaster management and the total values of the sector were defined 67.42% of total variance of the variables. KMO value in the sense of power and confidence variables was 0.72 and 65.27% of this segment can be explained by four factors the variability of the variables. In fatalism variable the KMO value was 0.599 and 59.56% of the four factors could explain the variability of variables. Finally, the KMO of socio-cultural norms was 0.71 and 70.52% of the variability of the variables was explained by five factors in this sector. Women cooperation alongside men play a major role in the use and implementation of policies and programs related to accidents. Thus, participation as one of the arguments in crisis management requires people involved in all processes related to the crisis management cycle. Since public participation opportunities and fields are different in societies and in different groups, so, to attract the participation in each group, identifying effective components is essential. Finally, after using factor analysis and extracting four factors, including knowledge of effective crisis management, cultural factors and gender, fatalism, a sense of power and self-confidence were classified. In general, most people do not do any activities in disaster management and their awareness and knowledge does not lead to disaster management needs. Thus, organizational barriers, structural, administrative and educational activities to promote social and cultural constraints are considering strategies promoting women's participation in disaster management cycle.
Volume 4, Issue 2 (7-2017)
The issue of drought has recently been the major concern all over the country and particularly in Urmia Basin. This is considered as a key factor in Urmia Lake crisis. Urmia's rural settlements are also affected by the management factor in a variety of spatial dimensions. The crisis of the dramatic decrease in Urmia Lake water and its management (decisions making) has posed a serious challenge to rural areas. This article to pursue to base management as a foreign factor on the basis of a good governance approach to the analysis and analysis of the role It focuses on the transformation of rural settlements in Urmia.
This research is applied in terms of its purpose and based on descriptive-analytical method. The statistical population of the study was the experts in the institutions related to the county crisis management. Experts from sample target communities were 70 people who were identified by a sample size determination method with an unknown community. A sample sampling method was used to select the samples. Data and information was collected using library and information technology. The questionnaire was used to assess the role of the management system in the framework of the components of a good governance approach and Referring to related research backgrounds, they were identified. To measure the normal distribution of data and appropriate regression selection, Kolmogorov-Smirnov and Dorbin Watson's tests were used. Also, for measuring the direct and indirect effects and the correlation between the components, Pearson's path analysis and Pearson correlation tests were used in SPSS software.
The findings of the research shows that the villages affected by the disaster management system in facing the risk of drying the Lake Urmia have encountered inappropriate environmental, social, economic and physical changes. These changes are influenced by the military mechanism that It is not due to being state-owned, focused, and open-minded; they are not accountable, legitimate, and efficient. In the meantime, the weakness of the legitimacy of failure in effective performance has had a direct impact on the disaster management inefficiency. Of course, other components such as weakness of pivotal justice, weakness of accountability, weakness of orientation affect the components of the weakness of legitimacy and weakness of the role Effectiveness has doubled disaster management inefficiencies.
The assessment of the disaster management system of Lake Urmia, based on the governance framework, indicates that the management system has not been efficient. This ineffectiveness, however, is heavily influenced by the weakness of legitimacy. But, indirectly influenced by other factors, including weakness of orientation, weakness of justice, and weakness of accountability. The important thing in this regard is the impact of the indirect factors on the legitimacy factor. By considering the nature of their direct and indirect factors, it is clear that the weak role of the villagers and the means to participate in disaster management, the cause of all problems In the countryside. Restoring Lake Urmia without paying attention to the villagers living around the Lake Urmia will be difficult. Therefore, giving villagers the role of the main beneficiaries of Lake Urmia Basin can help restore Lake Urmia.infact,Communities are the first responders in case of a disaster. Therefore, community-based disaster risk management should be the core of any risk reduction approach. community based Disaster risk management focuses more on community participation and reducing underlying risk, encouraging preventive action before a disaster. and focuses on participation on design, decision and performance for better management of disasters.
Volume 8, Issue 3 (12-2021)
Investigation of Temperature and Precipitation Changes in the Seymarreh Basin by Using CMIP5 Series Climate Models
Abstract
Panel reports on climate change suggest that climate change around the world is most likely due to human factors. Temperature and precipitation are two important parameters in the climate of a region whose variations and fluctuations affect different areas such as agriculture, energy, tourism and so on. Seymareh basin is one of the most significant sub-basins of Karkheh. The purpose of this study is to predict the impact of climate change on precipitation and temperature of the Seymareh Basin in 2021-2040 period. These effects were analyzed at selected stations with uncertainties related to atmospheric general circulation models (GCMs) of CMIP5 models under two scenarios of RCP45 and RCP85 through LARS-WG statistical model. Then the uncertainties of the models and scenarios were investigated by comparing the monthly outputs of the models by the coefficients of determination coefficient (R2) in the forthcoming period (2021-2040) with the base period (1980–2010). The root mean square error (RMSE) calculations presented the best model and scenarios for generating future temperature and precipitation data.
The Seymareh catchment is the largest and the main Karkheh sub-basin that covers parts of Kermanshah, Lorestan and Ilam provinces. The length of the largest river at the basin level to the site of the Seymareh Reservoir Dam is approximately 475 km, and the area of the basin is 26,700 km2. Geographic coordinates of the basin are from 33° 16 ́ 03 ̋to 34°59 ́ 29 ̋north latitudes and 46°6 ́9 ̋to ̋ 5 ́ 0 ° 49 Eastern longitudes, minimum basin height 698 m at the dam outlet and its maximum height 3,638 m. It is on the western highlands of Borujerd.
The information used in this study was obtained from the Meteorological Organization of the country. For this study, three synoptic stations of Kermanshah, Hamadan and Khorramabad, which had the highest statistical records and had appropriate distribution at basin level, were used. These data included daily and monthly temperature and precipitation information, and sunshine hours.
The LARS-WG fine-scale exponential model was proposed by Rasko et al., Semnoff and Barrow (1981). We used daily data at stations under current and future weather conditions. In order to select the best GCM model from the models mentioned above, minimum temperature, maximum temperature, precipitation and sunshine data were entered daily in the base period (1980–2010) and data were generated for five models under two scenarios of RCP45 and RCP85 for the period 2040–2021. The data were generated in 100 random series and the mean of required variables (minimum temperature, maximum temperature and rainfall) were extracted monthly in the period 2021-2040. Then, root mean square error (RMSE) and determination coefficient (R2) were used to evaluate the performance of the models and compare the results.
To ensure the models' ability to generate data in the coming period, computational data from the model and observational data at the stations under study should have been compared. The capability of the LARS-WG model in modeling the minimum temperature, maximum temperature, and radiation at the stations under study was completely consistent with the observed data. The model's ability to exemplify rainfall was also acceptable, however the highest modeling error was related to March rainfall.
By comparing the observed and produced data including monthly average precipitation, minimum and maximum temperatures through five mentioned models with their indices, the best model and scenario for future fabrication were determined. The results of this comparison showed that among the available models, HADGEM2-ES model under RCP 4.5 scenario had the best result for precipitation and HADGEM2-ES under RCP 8.5 scenario predicted the best result for maximum temperature. Determining the best model, precipitation data, minimum temperature and maximum temperature produced in the selected models and scenarios were analyzed to investigate the climate change temperature and precipitation for the future period.
The results of this study indicated that due to the wide range of output variations of different models and scenarios, by not taking into account the uncertainties of the models and scenarios can have a great impact on the results of the studies. It was also found in this study that the LARS-WG exponential model was capable of modeling precipitation data and baseline temperature in the study area, so that the radiation data, minimum and maximum temperatures were completely consistent with the data.
The observations are consistent and the models' ability to predict rainfall is very good and acceptable manner. In investigating the uncertainties caused by atmospheric general circulation models and existing scenarios, the best model to predict precipitation in the study area is HADGEM2-ES model under RCP 8.5 scenario, the best model for temperature estimation model HADGEM2-ES under RCP scenario No. 4.5.
The overall results of this study revealed that the average precipitation in the basin will decrease by 4.5% on average, while the minimum temperature will be 1.5° C and the maximum temperature will be 2.17° C. The highest increase will be due to the warmer months of the year. Notable are the disruptions of rainfall distribution and the high temperatures will have significantly negative consequences than rainfall reduction.
- : Climate Change, Climate Scenarios, Uncertainty, LARS-WG, Seymareh.
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