مدیریت بحران

In the first part of this study, hydraulic modeling of failure of the Tabarakabad and Cahcahe dams in Khorasan Razavi province was analyzed and discussed. In the second part, the consequences of the failure of these two dams will be examined. In order to assess the risk, a method based on descriptive-analytical (quantitative-qualitative) approaches has been proposed and a questionnaire has been prepared in this regard. Risk assessment and analysis of these dams in the proposed method, which is consistent with passive defense approaches, was implemented with the help of experts in this field and with the help of a coded program. Finally, for different scenarios such as overtopping, piping and sudden failures (subversive actions), assets valuation of downstream dams, threats, vulnerabilities, risk zoning maps and drafting of emergency action plan is presented. According to the results, it was indicated that the risk of the Tabarakabad dam is higher than Cahcahe dam and in case of an accident, the villages adjacent to the dam and the city of Quchan will suffer serious damage. However, the correct operation of the Cahcahe dam overtopping can play an important role in stabilizing and preventing the occurrence of crisis.

Storm-inundation models based on hydrology and hydrodynamics require a large amount of input data (detailed terrain, sewer system and land use data). In this paper, in order to determine inundation conditions quickly with only a few usually available input data is proposed an urban storm-inundation simulation method (USISM) based on Geographic Information System (GIS). The USISM is a simplified method of distributed hydrological model based on DEM, in this method depressions in terrain are regarded as the basic inundated area. The amount of water that can be stored in a depression indicates the final inundation distribution. The runoff and maximum storage volume for each depression and the flow direction between these depressions are all considered in the final inundation simulation. The SCS method is used to calculate storm runoff and a water balance equation is used to calculate the water storage in each depression. The result shows that in all four-storm event, the average relative depth errors of depth in all inundation sites are less than 20%, while the average relative errors of area and volume are more than 60% Therefore, the USISM method has a higher ability to simulate the final depth of inundation than the surface and volume of inundation. The result reveals that the USISM method could find the inundation locations in the Damghan Urban Watershed and calculate inundation depth and area quickly and therefore display a significant role in the management of the urban crisis.

Introduction Landslide occurrence is caused by severe ground movement and fault fractures that lead to structural damage, road blockage, human death, and significant damage to other features. Landslide is one of the most destructive natural phenomena that can cause great damage to property and human loss. One of the basic measures to reduce potential damage is to identify landslide-prone areas. Due to the location of most cities in the mountainous and foothill areas and the topographic, geological, and geomorphological features, the natural conditions are vulnerable to a wide range of landslides. Tehran, as the largest city in Iran, has almost 12% of the total population of the country and is partly located in the foothills and mountainous areas. Tehran, has many important infrastructures, including crowded roads, and a large population, therefore, determining areas prone to future landslides is an important management issue. Also, debris flow is one of the main factors that cause serious damage to properties. Thus quantitative assessment and management are required to reduce the possible damages. In addition, technologies are needed to assess disaster prevention facilities and structures in disaster-prone areas. Therefore, using combined methods for landslide susceptibility areas can be very effective in managing the risk of reducing casualties.Materials and MethodsIn this study, the effective factors on landslide occurrence such as rainfall, earthquake, vegetation, land use, geology, river, fault, slope and aspect, and roads are employed using an integrated approach. Then, spatial analysis was performed in ArcGIS using Euclidean distance and Curvature functions. The Haraz and Lavasanat roads were selected as a case study, and each of the criteria was examined and classified using the Euclidean distance method and inverse distance weighted (IDW) technique.Results and Discussion The results showed that the areas facing northeast and southwest parts were ranked 1st and the rest of the area was ranked 0. The areas with slope values higher than 50%, had a higher risk of landslide. The curvature of the selected main and secondary roads was located in convex hillslopes indicating the areas at a high-risk level. These Haraz and Lavasan roads are at risk of slipping during rain, earthquakes, and other hazards. According to the area obtained from the regional statistical properties.Conclusion The mountainous roads of Tehran are vulnerable to landslide and debris flows due to the geographical location, and the existence of faults. The excessive interference in the nature and increase of additional load on the slopes and excessive influence on agricultural and road use are important reasons for instability in the slope and increasing the debris flow in these land uses. The controlling of landslide and debris flow phenomena depends on a comprehensive management plan. Factors such as population growth, land-use change, and climate change are intensifying the landslide and debris flow occurrence. Since rainfall is one of the accelerating the occurrence of natural disasters, the existence of a management system such as an early warning to the endangered population is necessary.

The purpose of this study was to investigate the effective mechanisms of drought crisis management from the viewpoint of the experts of the Ministry of Jihad-e-Agriculture of the province of Alborz. The present research this is a descriptive-correlational research. The statistical population of this research was 316professional agent from the Jihad-e-Agriculture Organization of Alborz Province. The sample size selected based on the Morgan and Morgan table of 183 people, and the sampling method was proportional to the simple random sampling method. The calculated alpha for the research questionnaire is 0.80. .The research data indicate that the variables of managerial factors are about 32.4, the variables of economic factors are about 31%, the variables of educational factors are about 28.5% and the variables of socio-cultural factors account for about 30.5% of the changes in the dependent variable of drought crisis management. The results of Factor Analysis of Drought Crisis Management Solutions in the field of agriculture in Alborz province showed that political-supportive strategies, management solutions, technical solutions, legal solutions, educational strategies and economic solutions are the priorities of the factors that have the highest share in the explanation. Drought crisis management strategies in the field of agriculture in Alborz province have been studied by experts. These factors account for 72.12% of the variance of all variables.

Iran is one of the countries exposed to many natural disasters, of which the flood phenomenon is one of the most serious. According to official statistics, more than 50% of casualties due to natural disasters in Iran are due to floods. Accurate and timely information is needed to plan any flood management measures. Currently, many researchers have examined the methods of obtaining water area information. Among these methods, land use classification and change analysis are the most important applications of remote sensing techniques. One of the most widely practical classifications is the separation of water class from other classes.Also, Landsat images are one of the most common data sources in this field. In this regard researches have been done in the field of identifying water areas, due to its high importance in flood crisis management with the advancement of satellite technology in remote sensing. In this study, an automated method has been developed to prepare flood change maps and use different capabilities of different water and humidity indicators to provide automated training data. This can reduce the challenge of operator interferences. Besides, the efficiency of the high level of automation in the extraction of flooded areas in accelerating and facilitating the management of this crisis is indisputable. Therefore, when manual training data is not available, applying a fully automated approach will be helpful. The integration of indicators can also be effective in improving the accuracy of existing water indicators. Floods are one of the most important natural disasters in the world that occurred due to different factors such as human encroachment on rivers and vegetation damages. The purpose of this study is to develop an automated method for preparing training data for supervised classification of images and using the capabilities of integrated indicators to identify flooded areas. Therefore, several approaches for flood in Golestan province, 2019, were implemented by Landsat-8 data and the results of each were examined. The Kmeans clustering algorithm, Otsu, Multi and Adaptive thresholds were used to generate automated training data based on different water indices (NDWI, AWEI and MNDWI; Then the ANN, SVM, ML, MD and BE classifications) was implemented to monitor flood changes. The results compared with the manual classification method indicated that the proposed approach, in addition to providing a high-level of automation in monitoring changes, also had high efficiency and accuracy. In another development approach, different water and moisture indices were combined with the aim of improving the production process of automated training data. Among the 85 tests performed, the combined approaches had the highest accuracy. Due to the nature of different water indicators, their selection and appropriate combination, in addition to reducing the noise in the water indicator image was also effective in increasing the ability to identify impure water areas. Finally, a comprehensive deductive analysis of automated methods and hybrid indicators was carried out to help to manage flood crisis, facilitate and accelerate the process. It can be said that with the advancement of technology and the emergence of various aerial / satellite images, many opportunities and possibilities have been created for effective and sustainable management. One of the best ways to extract information from digital images is to classify the image. One of the challenges in image classification is to reduce the interference of users using algorithms that have high level of automation. This issue has high importance due to the sensitivity and sudden occurrence of the flood crisis. Therefore, to promote this challenge, in this research, an automated and efficient approach for supervised classifications with emphasis on automatic production of training data to prepare a map of flood changes is presented. In total, 85 different studies were performed to obtain flood change maps, using hybrid and non-hybrid automated methods to prepare automated training data for supervised classifications. It is considered that the obtained results had acceptable accuracy. For example, in all approaches studied, ANN classification offered better accuracy, which could be seen from the diagrams provided. Also, due to the lack of significant difference in the accuracy of the maps, obtained from this classification with different indicators and thresholds, it can be said that this classification is also highly robust. The results indicate that ANN classification in combined approaches with Otsu and Adaptive thresholds has the highest accuracy and maximum robustness. In comparison with methods related to execution speed, ML and MD classifications also provided good performance. However, the difference in the accuracy of these classifications compared to the ANN classification is not significant in some cases and will be possible to replace due to higher execution speed. Finally, by analysis of the results, it can be stated that the automated approaches proposed in this research can be replaced by traditional classification methods.

In the past decades, we have seen drought in several different countries of the world: in developed, developing, and poor countries. Drought is a natural disaster, however, its impact on people and the environment is disastrous. The prediction of the onset, severity, duration, and the end of this phenomenon, is very difficult. Damages caused by drought include economic (decreased production of crops and livestock), environmental (reducing the quality of water resources), and social (mortality and migration) effects. The side effects of the aforementioned impacts are part of the destructive nature of drought on a community. What is clear is that the causes of drought are not in the control of human beings. However, management tools and compatibility with this event are one of the initiatives of major experts and decision-makers of risk management and crisis in a country. In 2014, the World Meteorological Organization (WMO) and the Global Water Partnership (GWP) provided and published a journal entitled “National Guidelines on Drought Policy” or “Continuous Drought Management” that is the result of the efforts of specialists of the two organizations in collecting experiences of successful countries in the management of drought. The conclusion of all of these experiences led to offering a 10-step approach in the National Directorate of drought. What is presented in this paper is a summary of the translation of this publication that deals with strategies of drought management, which our country also faces.

Drought is a one of the most important natural disasters that have high socio-economic and environmental impacts. However، drought is more than a physical phenomenon or natural event. Its impact results from the relation between a natural event and demands on the water supply، and it is often exacerbated by human activities. The traditional approach to drought management has been reactive، relying on crisis management. Due to the drawbacks of crisis management، employing proper risk management techniques has been suggested. In order to move from crisis management to risk management، in this study، risk of drought in Isfahan province was evaluated. Drought hazard index and vulnerability index are components of the drought risk management. Standardized Precipitation Index (SPI) was used as the index of drought hazard. For the calculation of SPI، the monthly rainfall data in 47 meteorological stations during the period of 1975-2007 were collected. The time series of rainfall data were prepared and for calculation of the standardized precipitation index in a 12 month timescale they were imported to SPI program. Percentage of drought occurrence in each severity was calculated and then the drought index map was obtained. Vulnerability index was calculated through socio-economic indicators (population density and percentage of people involved in agriculture)، and physical indicators (available water capacity of soil and land use). Weighted Linear Combination (WLC) technique was applied for combination of vulnerability indicators. To assign weights to the criteria، an Analytical Hierarchy Process (AHP) was used. After providing the maps، fuzzy membership functions for every criterion were used for their standardization. For the weighting of the criteria، a questionnaire was prepared and criteria comparison was done using the participatory approach by a group of experts. Finally، the drought risk index was calculated by multiplying the drought hazard index and vulnerability index. The results showed that hazard of very severe drought is mainly concentrated in the central part of province. The North and North East of Isfahan province could experience condition of severe drought. South West of Isfahan province is under moderate drought condition compared to the other parts of the province. Map of drought vulnerability index showed that the most vulnerability is in the West، South and North-East of province. Map of drought risk index showed that the Northern Province demonstrated high risk. To reduce the drought risk in Isfahan province، improving monitoring، early warning، increasing environmental awareness، and promoting water resource management practices should be considered.

The issue of crisis management in countries and communities is one of the most important challenges in the past and present time for human beings. So far, in countries and communities, there have been many attempts to increase the managerial power especially in the encountering stage, but these attempts have had many advantages and weak points. This research deals with inspecting and studying the existing theories and models and the specific conditions of Golestan province, esp. the natural disasters for flooding and firing, which have been the most frequent problems in this province in the encountering stage particularly in managerial dimensions including conditions of decision making, principles of coordinating and gathering sources and facilities and communications and alarming systems. It also seeks for a definition for the function and conditions of the role of these managerial dimensions to help the managers of this province in encountering natural crises. The objectives and Methods discussed in the present study are applicable and analytical. On the other hand, it should be pointed out that the research pattern and criterion extracted from theoretical bases, have been investigated and approved by using a survey program involving 15 experts. The statistical society of the research involves 300 individuals from managers and experts and Golestan management Coordinating Council and Subsidiaries cities, which on that base the number of calculated statistics is 81. To analyze the data collected, SPSS software and multivariate regression analysis and Friedman test was used. The investigation to calculate face validity of the components dimensions and the relationship between them and also the amount of validity of each component variables, besides, the mutual effects and prioritization of the aspects and components, were calculated quantitatively using SPSS software and multivariate regression analysis and Friedman test. Finally, Golestan natural disaster management model involving aspects of decision making and the alpha coefficient 0.326 (The components of threat, time pressure, surprise) principles of coordination and the alpha coefficient 0.305 (the component of unity of command, Command Line, gamut monitor) mobilize resources and the alpha coefficient 0.292 (Component of the resource, type of resource, resource capacity, quick access resources) and warning systems and information and the alpha coefficient 0.288 (The components of the collection of information, public information and awareness within the organization) were approved.