نشریه جغرافیا و مخاطرات محیطی
پیاپی 28 (زمستان 1397)

Landslide is one of the catastrophic hazards which occurs in many parts of the world, causing hundreds of billions of dollars of economic damage and hundreds of thousands of deaths and injuries each year (Aleotti & Chowdhur, 1999). Landslide susceptibility assessment can be tricky, because the evaluation of both the spatial and temporal distribution of past events for large areas is difficult mainly due to the limitations and gaps of historical records and geographic information (Leonardia et al., 2016). Therefore, the identification of susceptible areas plays an important role in the assessment of environmental hazards and management of the catchment area (Sakar et al., 1995). Latian Dam is located in the northeastern of Tehran; this basin is naturally susceptible to landslide due to topographic topography, tectonic activity and seismicity, various geological, and climatic conditions. On the other hand, the dangers caused by landslide and the filling of the dam caused by sliding movements make it clear that it is necessary to study the landslide in this area. Therefore, this area was selected as the study area, and damage zoning was determined through the entropy and the fuzzy model.

The study area is located in the northeastern of Tehran, the capital of Iran. It is 192.52. The coordinates are '29 ° 51 'to 51 ° 51' eastern longitude and '47 ° 35 'to 56 ° 35' north latitude (see pic. 1). Latian Dam lies in the southern end of the basin. Latian basin is placed in the southern slopes of Central Alborz which its main river is Jayrud. It matches with Mosha-Fasham which is located in the zone of earthquake risk in a severely degraded area. Geologically, it belongs to the first, the second and the third era. The petrographic composition of this area is mainly shale-sandstone-basalt-tuff-marl and alluvial deposits. Geomorphologically, it is mainly in the form of rock mass - stone outcrop. The rainfall is more than 500 mm per year in the study area. That is more than half of the precipitations in the form of snow.
Figure 1. Case study: Latian basin in in the upstream of the Latian Dam.

To begin with, the landslide area was prepared through the map of geomorphologic faces, Google earth images, and geological map. Next, the factors affecting the slip were identified according to the region conditions, and the expert scores were given to the classes of each level, which indicated its importance in creating a slide. Then, each map was analyzed using the ARC GIS 10 software. Finally, the entropy and fuzzy methods were used to assess the risk of slid in the area, It (risk area map obtaining from fuzzy and entropy model) was overlaid with landslides occurred. Fuzzy logic was first introduced by Lotfi Zadeh (1965), an Iranian scientist at the University of California in 1965 (as cited in Amini Feshoody, 2005).

The regional model of erosion occurrence in the Latian basin is depicted in the following:

The abbreviations used here include: T: texture, Df: distance from fault, V: vegetation, DR: distance from river, LU: land use, S: slope, I: lithology, A: Aspect, E: Elevation, and R: rainfall.
High-risk regions include the following features: texture as an effective factor in the landslide occurrence in the region under study shares 17.65 %, distance from fault shares 14.42 %, vegetation 13.35 %, distance from river11.73 %, land use 11.53 %, and etc. The aspect, elevation and rainfall are the lowest impact percentage and their scores are equal. That is, most of the slides are in the same aspect, elevation, and rainfall. Base on entropy model, about 107 square kilometers, which is equivalent to 53.87 percent of the study area is situated at a higher than average risk. Only one landslide in the medium-range range has occurred. Based on the fuzzy model, landslides are distributed throughout the entire range of danger zones from very little to very large. The distribution of landslides in relation to hazard limits is not logical and It has not been concentrated in a particular area.

Landslide is one of the catastrophic hazards occurring in many parts of the world and causing hundreds of billions of dollars of economic damages and hundreds of thousands of deaths and injuries each year. Latian Dam lies in the southern end of the Latian basin. And more than ten landslides with a total area of 2.53 square kilometers were identified on top of Latian Dam. They could be considered as threatening factor for Latian Dam by increasing sediment load entering the dam. In this research, ten factors affecting landslides were identified. They were prioritized with the entropy model after the matrix was prepared. Then, using this model and the fuzzy method, high risk areas were identified. The map of landslide distribution overlapped with the hazard map and the contribution of each of the risk areas was evaluated for the occurrence of landslide. The results indicated that texture as an effective factor in landslide occurrence in the investigated region shares 17.65 %, distance from fault shares 14.42 %, vegetation 13.35 %, distance from river11.73 %, land use 11.53 %, and etc. Furthermore, in the entropy model the number of landslide incidents is more reasonable than the risk zones as compared with the fuzzy model.

Humans have affected 83 percent of the land surface till now (Sanderson et al., 2002). Habitat fragmentation is the process of subdividing a contiguous habitat into smaller pieces (Kolbert, 2014). There is a major concern that land use change and habitat fragmentation have direct and indirect effects on biodiversity, which can lead to the extinction of many species (McInerny et al., 2007). To all intents, the major cause of species extinction is habitat loss (Keenleyside et al., 2012). Although roads are a major cause of habitat fragmentation (the process during which a large expanse of habitat is transformed into a number of smaller isolated patches) and usually negatively affect many mammal populations, different mammal species can be highly variable in their tolerance to the fragmentation and other human developments (Schuster et al., 2013). Landscape fragmentation seriously affects the survival of meta-populations. Patch size can affect the resilience of ecosystems and population structure. In larger patches, the populations are more stable and population viability could increase under the conditions. Rodents are mammals belong to the order Rodentia. About 40% of all mammal species are in this order and they play a considerable role in ecosystems (Amori & Gippoliti, 2000), but they are rarely taking into account by the legislation and only very few small mammal species are currently protected according to national and international laws (Bertolino et al., 2015).

This research is a filed study which focuses on the habitat fragmentation caused by civilization development. In order to study the impact of habitat fragmentation on the population dynamics of common voles (Microtus arvalies), three small habitat patches (0/3 – 2 ha) that are surrounded by roads and highways were selected. These patches with the grassland cover type are located in Louvain-la-Neuve city in Belgium. This city is an almost newly born town (created in 1969) that is situated in the French-speaking part of Belgium, in the Wallon Brabant province. In this study, the common voles’ colonies of each patch were considered as a single meta-population.
The study used Capture-Mark-Recapture which is one of the most widely used techniques for demographic studies. This technique mostly can be used to assess population status (such as abundance fluctuations) or to investigate population dynamics. To capture the common voles, 65 ugglan small mammal live capture traps that have high efficiency were used. This study was conducted in a period of 1/5 year (during four seasons). Trapping was done in 13 sessions. During each session, traps were opened over 2 nights and were closed during the day. In order to differentiate between the captured animals, each animal was tagged by two 11.2 mm “Michele clips” (ear tags). Captured animals were released back to their habitats after some information such as tag number, sex, age class, body mass and reproductive status were noted. Population dynamics and population structure were analyzed using CMR specialized package and Microsoft office 2007, respectively.

A total of 283 specimens were captured and tagged; 176 specimens were new and they were being caught for the first time. In general, all the studied patches showed the highest population size in June and July. Persistence curves of successive cohorts (have been caught during the same session) in studied plots revealed abundance fluctuations in each plot and the differences in population survival between the studied plots. Plot B was considerably different from the two others. The common voles in this plot showed an instability or low persistence and strong downward trends of population size.
In plot C, with larger size in comparison to other patches, more stability in the population structure and abundance were observed. This study showed how habitat fragmentation has negatively affected meta-populations of common voles and showed that the risk of local extinction is high in the studied meta-populations.
The results clearly indicated that patch size and habitats isolations have an important role in animal population survival and its structural stability. Moreover, this study demonstrated that the remained small isolated meta-populations of common voles after huge landscape fragmentation and civilization of Louvain-la-Neuve city, generally failed to find adaptive mechanisms to their new man-made conditions.

The study proposes considerable differences among studied meta-populations in the survival and sex ration resilience. The results demonstrated that the meta-population of patch B was not able to recover itself. Consequently, common voles in this patch are facing a local extinction. The preventive efforts for maintaining the integrity of the ecosystems can have an effective protection against environmental disturbances. Development and construction projects must be done with full attention to landscape structure and regional biodiversity. Nevertheless, re-establishment of populations would be very costly, time-consuming and mostly impossible for the government and biodiversity conservationists.

Given to the geographical circumstances, Iran has been considered as one of the driest regions of the world and is always subject to severe droughts. Khorasan Razavi province, which is located in the northeastern part of the country is subject to the drought phenomenon due to the subtropical high pressure. Regarding the conditions of the province, the city of Chenaran also faces drought phenomenon, so that based on the Standardized Precipitation Index (SPI), during a seven-year period, 68% of the area of Chenaran County had suffered from moderate drought and 32% from severe drought. On the other hand, 45/08% of rural workers are active in the agricultural sector. In recent years, droughts have led to excessive exploitation of underground aquifers, so that 77.8% of underground water has been evacuated by wells in the city. In spite of these restrictions, the city of Chenaran is known as the second largest producer of orchard crops and the fifth place in the province's crops production. Findings showed that the city’s rural settlements have been facing various inconstancies in recent years, and abandoning the villages has been increasing. From 2006 to 2011, the number of vacant villages in Chenaran increased from 59 to 106 villages. Development theorists have proposed a “diversification approach” in the framework of a sustainable rural development model to enhance adaptation to external crises. As the diverse economic activities in the rural community create such a degree of security that the rural economy could withstand the main constraints of the environment (drought, frostbite, etc.) and socio-economic instability especially the market volatility and the price of manufactured goods and ...), it seems that the variety of the means of livelihood can be an influencing factor in reducing the natural hazards, especially drought in rural areas.

The research methodology is descriptive-analytical. The statistical population of the study consists of 133 villages over 20 households in Chenaran county. In this study, 15 villages with 271 households were selected as sample. “Resilience” and “variety of economic activities” in rural households have been considered as dependent and independent variables, respectively. Resilience was investigated by means of 34 indicators in 5 components in Likert scale, including economic capacity with 7 indicators, policies and government support with 6 indicators, knowledge capacity with 11 indicators, social capacity with 7 indicators, and finally, environmental capacities with 3 indicators. Variety of economic activities was investigated in two sections: a) crop and agricultural activities and b) non-crop and non- agricultural activities. Cronbach's alpha coefficient 0.77 represents an internal correlation between questions and the desired reliability of the research tool.

The results showed that most of rural households have a dysfunctional economy, so that only 2.95% of households have a variety of income sources in non-agricultural sectors, 22.41% in agricultural activities and 4.9% have diversified income sources (crop and non-crop). Based on the one way analysis of variance (Sig = 0/002), it was indicated that the diversity of economic activities has been effective on the resilience of rural households in the city of Chenaran. The average resiliency of drought-affected households among households with non-productive income sources, semi diverse, and various sources of income has been estimated 2.40, 2.48 and 2.48, respectively. According to the obtained findings, the diversity of income sources has led to the increased resilience among the surveyed households. In addition, the non-crop economic activities have been effective on the resilience of rural households in the city of Chenaran. Among those households without non-crop various income sources, non-crop semi diverse income sources and non-crop various income sources have been reported 2.43, 2.42 and 2.80 respectively. In fact, the diversity of non-agricultural income sources has increased the resilience of the surveyed households. But the diversity of economic–agronomic activities did not have a significant effect on the resilience of rural households in Chenaran. It has been concluded that the variables of income diversification, diversity of crop income resources and non-crop income resources directly influence the resilient structure (Sig. ≤0 / 05). The variable of the diversity of income sources with beta of 0.19 had the greatest impact on the resilience of rural households. It is worth mentioning that the variability of non-crop income sources has a direct effect on increasing the resilience of rural households.

This study showed that the economic dependence of rural areas of the country on the agricultural sector and its lack of dynamism and diversity have led to an increase in vulnerability to external shocks (drought, frostbite, global price fluctuations of agricultural products, etc.). In this regard, by creating job opportunities in non-agricultural sectors, we can make a new source of income for the villagers and reduce the vulnerability of rural households to drought.

The environment is the place we live, work, and play; it supplies the most basic human needs, as it is a thing that is becoming increasingly important every day. However, during his dominance over the earth, human beings have consumed the resources indiscriminately and in an unplanned manner. Many of the threats made against human society are merely associated with environmental issues. Although these threats have a non-security nature, in fact, they affect the national security of the countries. As human societies are facing with the growing trend of environmental degradation, it is essential to set some measures for environmental management and other critical resources. Therefore, to prevent irreversible damage to renewable sources, long-term management is a necessity. As rural areas play an important role in production, employment, within the geographical borders and population, they should have a special place in the development of the country. Climate changes and global warming, desertification and lack of fresh water are among the issues the study seeks to investigate. Proper management is essential for the protection of rural areas, but there are some challenges that the current study have tried to examine. The main question is: what are the main challenges in managing environmental resources in the study area?

Binaloud County (Torghabeh Shandiz) with an area of 1185.26 km2 is located in the center of Khorasan Razavi province, northeastern Iran and has a population of 69,640 people. Based on the latest administrative divisions of Iran, this county consists of two districts (Torghabeh and Shandiz) and four Dehestans (rural districts) including Jaghraq, Torghabeh, Abardeh and Shandiz. The county has 52 villages with a total population of 34,653 people in 10,905 rural households.

The study is an applied one, conducted using a descriptive-analytical method. To answer the research questions, we reviewed the literature and comments made by experts, and accordingly formulated the standards and features of effective environmental resources management. After setting the boundaries of the study area, the data was collected. The next step in the research process was to identify and verify the classification of the factors, and to explore the interrelationship between the indicators based on their effects on each other. Data analysis was conducted by Analytic Network Process (ANP), in which after discovering the inter-relations between indicators, similar to AHP method, the weight of the indicators must be determined compared to the target group, and the weight of each sub-indicator is determined compared to the relevant indicators. This was performed by designing questionnaires that were completed by 22 certified experts. According to their responses, the appropriate weight of each criteria and sub-criteria were determined.

The Analytic Network Process (ANP) is a multi-criteria decision making technique. Given the complexity of various environmental issues, ANP may produce better results. Looking at the related literature, the criteria and indicators were organized into 10 clusters. Within each cluster, relevant elements and criteria were divided. While elements of each cluster are interconnected, some of them may also be associated with elements of other clusters. According to the diagrams and table of the final weight of clusters, it was concluded that challenges in the cluster of laws and regulations with an impact factor of 0.237, is the biggest challenge to the management of environmental resources. Monitoring cluster was the second challenge affecting the management of environmental resources in the study area. The findings showed that issues such as lack of legal mechanism for the protection of environmental resources, weak laws and regulations on investment, lack of transparency of investment rules on environmental resources, and access to resources, services and facilities in rural areas and environmental degradation, a subset of performance cluster, is the least significant challenge to the management of environmental resources which has the impact factor of 0.037. The challenges related to economic issues and personal skills have the second and third least impact factors, respectively.

In this study, using ANP the authors analyzed the challenges for managing environmental resources and identified indicators which are among the most important challenges in managing environmental resources. Challenges, including the lack of screening in accessing the effects of environmental resources, lack of deterrence and executive guarantees of environmental regulations in evaluation of natural resources, lack of expert instructions for environmental assessment of the projects, lack of reform in making use of natural resources and curbing the unstable factors, lack of clarity about environmental resources on land use planning and its legal status are the most important challenges. On the other hand, lack of legal mechanisms for protecting the environmental resources, weak laws and regulations on investment, lack of transparency in investment rules about environmental resources, access to resources, services and facilities in rural areas and environmental degradation are the least important challenges to the management of environmental resources. Accordingly, in this study, it is recommended that the Environmental Protection Agency in collaboration with other stakeholders, evaluate the efficiency of environmental laws and regulations, and report the performance, efficiency and achievement of legislations based on the indicators of environmental quality, and present it with suggestions for updating and promoting their efficiency.

The following could be among the responsibilities of the government towards the deployment of an environmental resources management system: to achieve consensus and coordination in various sectors of industry and production;
to set priorities in development, completion, and promoting the regulations;
to impose limitations or bans on the indiscriminate and irresponsible consumption of natural resources;
to define research projects to develop standards and guidelines;
to formulate and implement comprehensive programs of quality management and environmental resources;
to review the laws and regulations on protecting the environment and quality of resources;
to make managers sensitive to issues of environmental resources and their improper use;
to employ academic and practical methods to manage resource consumption;
to develop a risk management plan for resources against natural disasters;
to assess the environmental impact of projects.

The growth of industries, and consequently, the excessive consumption of fossil fuels on the one hand, and the increase in the world's population and extensive land-use changes on the other hand, has led to the gradual transformation of the global climate after the industrial revolution. In recent decades, the air temperature has suddenly increased with significant changes in the frequency of cold and hot extremes. This study examines the future extreme minimum air temperature across Iran.

The average daily temperature from EH5OM database was used for assessment of global warming effects on daily minimum air temperature over Iran. EH5OM is one of the CMIP5’s AOGCM models, which uses ECHAM dynamic core with 31 vertical levels (up to near 10 hPa), developed in Max Planck Physics Institute. The simulation results for EH5OM are available from 1960 to 2100 for different IPCC’s emission scenarios. For this study, A1B scenario was chosen, because its fundamental assumption of balanced emphasis on all energy sources (fossil and non-fossil). Previous study shows that the result of this scenario is applicable for analysis of climate change in near future.

The trend of normalized temperature deviation index time series for Iran in the next decades shows a large number of abnormalities. The number of extreme cold days shows a decreasing trend during the study period. In April, most of the country's regions have decreasing trend of frozen events. This downward trend in the western part of the country is more pronounced than the eastern regions, with the highest decreasing trend in the Zagros Mountains. In May, as in April, the negative trend of frozen days covers most regions of Iran, except that in the mentioned period, the decreasing trend of frozen days shows higher values in eastern parts of the country.

The analysis of spatio-temporal patterns of the normalized temperature deviation index (NTD) for Iran during the study period (2015-2050) shows a major abnormality. Frozen days show a significant downward trend in the first half of the year. In winter (except for March) and spring, there is a dominant decreasing trend. Specifically in north-western regions of the country and Zagros Mountains, a significant decreasing trend will be expected in the next decades. Positive trend in the number of frozen days was also projected in some regions of the country, especially for October, November and February in north-western strip and south of Zagros Mountains. This increase in the frozen days during the cold season, may be unexpected at first glance, but with the warming of the ground and climbing the air towards the air, the shape of the polar vortex forms the airflow at high altitudes, resulting in This intense airflow (wind) is created around polar regions, which causes the air to release the cold weather of the polar regions towards the central regions of the planet, which is one of the most important reasons for the shape of cold faults in the decades to come.

Although climate change is a global challenge, its effects occur locally and differ from region to region (Filho et al., 2016; Leonard et al., 2014). Over the past few years, the large positive departures of temperatures from their mean values have become commonplace in many parts of the world. Surface temperature over land regions have warmed at a faster rate than over the oceans in both hemispheres (IPCC, 2007). Each of the last three decades has been successively warmer at the Earth’s surface than any preceding decades since 1850. The warmth of the period from 1983 to 2012 is very likely higher than any 30-year period in last 1,400 years in the Northern Hemisphere. The globally averaged temperature that results from combined land and ocean surface data shows a warming of 0.85 °C during the period 1880 to 2012, (IPCC, 2013). Indices for climate variability and extremes have been used for a long time, often by assessing daily temperature or precipitation observation above or below specific thresholds (Zhang et al., 2011). The dependence and thermodynamic relations between the precipitation and temperature have been addressed in numerous studies (Liu et al., 2012). Changes in extreme weather and climate events have significant impacts and are among the most serious challenges to society in coping with a changing climate (CCSP, 2008). The warming global climate has increased the concurrent climatic extremes and the intensity of extreme weather events over different regions of the Earth, such as drought, heat waves, tropical cyclones, floods, and fires (AghaKouchak et al., 2014; Alexander et al., 2005; Leonard et al., 2014). The projections of extreme weather phenomena on the basis of temperature and precipitation indices in AR5 show a probable increase in the number and intensity of dry and hot periods in the summer time (Filho et al., 2016; Hao et al., 2013). Many practical problems require the knowledge of the behavior of extreme values. In particular, the infrastructures we depend upon for food, water, energy, shelter and transportation are sensitive to the high or low values of meteorological variables (WMO, 2009). The impact of these events can be due to a single variable in an extreme state, but more often it is the result of a combination of variables which are not all necessarily extreme (Leonard et al., 2014). The combination of variables leading to an extreme impact is referred to a compound event (Beniston, 2011). Recent studies of joint quantities of precipitation and temperature are often described in terms of warm/wet, warm/dry, cool/wet and cool/dry climate combinations (e.g., Arsenovic et al., 2013; Beniston et al., 2009; Estralla & Menzel, 2012; Hao et al., 2013; Lopez-Moreno et al., 2011) and/or based on copula theory (see Miao et al., 2016). The combination of warm/wet, warm/dry, cool/wet and cool/dry modes reveals a systematic change at all the locations investigated with significant declines in the frequency of occurrence of the cool modes and a sharp rise in that of the warm modes. This article investigates the trends of combined temperature, precipitation, humidity, wind speed and sunshine statistic in spatial domain in Iran. Our investigation aims to use the joint quantities of temperature and precipitation and other variables of weather to offer some insights into the behavior of particular modes of heat and moisture which cannot be achieved by the analysis of the statistics of each individual variable. Over the last years, several extreme precipitation and temperature indices have been explained and analyzed in the literature (e.g., Parak et al., 2015; Rahimzadeh et al., 2009; Tabari et al., 2011); however, the climate change has not been concerned with the use of joint extremes indices.

The study area in Iran lies approximately between 25oN and 40oN in latitude and between44oE and 64oE in longitude (see Fig. 1). Based on the Koppen climate classification, most parts of Iran are categorized under arid (BW) and semi-arid (BS) climates. Alborz and Zagros are the important mountains of Iran which play an important role in non-uniform spatiotemporal distribution of temperature and precipitation in Iran (Dinpashoh, 2006).
The examination of climate changes needs long and high quality records of climatic variables. In the present study, the dataset of daily maximum, the minimum and mean air temperatures and precipitation (P) for the period 1981-2015 from 47 synoptic stations from different geographic locations of Iran (Fig. 1) were collected from the Islamic Republic of Iran Meteorological Organization (IRIMO) and were then analyzed. The homogeneity of the dataset was also assessed and approved by IRIMO. Most of the regions were covered by the corresponding data and the geographical location of the stations.

One solution for the better detection of climate change is the use of compound indices; therefore, a set of compound indices derived using daily resolution climatic time series data with a major focus on extreme events were computed and analyzed to assess climate changes in Iran. The compound indices consisted of cool/dry, cool/wet, warm/dry, warm/wet, TCI and UTCI which were examined for a 47 synoptic meteorological stations during 1981-2015. The main results of the research showed a substantial change in the behavior of the joint extremes of temperature and precipitation quantities associated with warming has occurred in the past three decades. More than 80 percent of Iran has experienced a decrease in the annual occurrence of the cold modes and an increase in the annual occurrence of the warm modes. Universal thermal climate index (UTCI) change showed a widespread and significant increase in the annual occurrence of the strong heat stress (32–38 °C) and a significant decrease in the annual occurrence of the no thermal stress class (9-26 °C); in fact, the changes are also spatially coherent as compared with joint extremes of temperature and precipitation changes. Trends in tourism climatic index (TCI), including the number of days with TCI≥60, and the number of days with TCI≥80 showed similar changes but with weak spatial coherence. The results of this study also allow researchers to preview the condition that may occur with greater frequency in the future throughout Iran.

This paper attempts to present a suite of compound extreme indices with a primary focus on extreme events. These indices were calculated and analyzed for a number of sites between the years of 1981-2015 to provide a general overview of climate change in Iran. The results from non-parametric test showed statistically significant and spatially coherent trends in the compound extreme indices. It was found that in more than 80 percent of Iran the frequency of the warm modes has increased, while the frequency of cold modes has decreased but with smaller magnitudes. More than 97% of the country exhibited a positive trend for the annual WD index. The significant increasing trends of the annual WD varied from (+) 3.7 to (+) 14.5 days per decade respectively in Chabahar and Kish Island stations. Based on the results of the analysis, apart from a few stations and more specifically in Shahrekord station, joint quantities of temperature and precipitation indicates almost the same trend and responding to these differences definitely requires further investigation. At the same time, the occurrence of TCI and UTCI in the range strong heat stress (32-38 °C) events has increased almost over the whole country, which is consistent with the increase of the frequency of warm modes. The distribution of the annual compound indices trends indicated that the negative and positive significant trends have mainly occurred in the northwest of Iran. The results also suggested the need for further investigation on local factors intervention in the environment, which could be one of the major causes of climate change.

With the growth of urbanization and the construction of high-rise buildings, attention to the behavior of individuals during the evacuation is an important issue in the design of such buildings. The concerns in this regard are the lack of proper behavior patterns during evacuation from high-rise buildings and lack of attention to the risk perception of individuals in the fire, which is one of the key factors influencing individual's decision-making, especially in the pre-evacuation phase in Iran. This issue is especially important in high-rise buildings due to the height and number of people. Human behavior is one of the key factors, and how to behave in crisis and emergency situations has become one of the concerns of researchers in recent decades, especially after the terrorist attacks of September 11, 2001, in the United States (Kuligowski, 2008, 2009, 2013, 2016; Kuligowski & Hoskins, 2010, 2011; Nilsson & Johansson, 2009; Norazahar et al., 2014; Proulx, 1993; X. Zhang, 2017; Zhu & Shi, 2016 , which can be considered as the most important factor in the necessity of risk analysis that changes the risk pattern (Moghimi, 2015). There are various models and patterns to determine behavior when humans are at risk and how they perceive the danger of many models and patterns (Hackman & Knowlden, 2014; Heath et al., 2017; Ryu & Kim, 2015). Among these, Protective Action Decision Model-PADM is a model that can be found to determine the behavior and perceptions of the perceived individuals in the fire compared to other models for the type of termination, the duration of the implementation and the simultaneous transmission of information to individuals (Lindell & Perry, 2012) more influential. The purpose of this study was to explore the behaviors of individuals who are caught in fire in the pre-flight phase. Subsequently, by placing these behaviors in Protective Action Decision Model, the risk perception of individuals in the fire will be measured and ultimately the activities that take time to evacuation this time will be identified. Several studies have been conducted on conceptual frameworks and different types of pre-evacuation activities, but the studies have been limited; Firstly, discuss the relationship of this activity with risk perception of individuals, secondly: activities that spend more time in the evacuation phase have not been identified. Using the results of this research one can first identify activities before evacuation of individuals, as well as activities that spend more time in high-rise office buildings, secondly, with the placement of the given activities in Protective Action Decision Model, we can measure their risk perception and prioritize those activities; and thirdly, the results of the present study, which are a new way of using Protective Action Decision Model based on the factors of each question - instead of answering "yes" or "no" in each direction - can be useful in determining more accurate individual's behaviors trapped in a fire. In this regard, the present research can be an innovative one.

The research method in this study is of mixed Method and its scope includes high-rise office buildings in Tehran during 2011-2017. The sample is consisted of 8 high-rise office buildings based on the Cochran formula, in which the sample size includes 245 people who are either trapped in fire or evacuation. Impact components on the model core of decision making were based on specific studies and the questionnaire was designed in two sections. The first part is an open-ended question: what was your first action after realizing the fire? And for analysis the data Colaizzi Method was used. In the second part, the decision-making questions of five-step spectrum maimed the views of individuals caught in the fire, and the scores earned were calculated for each indicator. Finally, using the SPSS 22, linear regression coefficient (R2), and path coefficient (Beta), the role of components of the decision model in relation to pre-evacuation activities was determined.

The results showed that, the behaviors formed in the pre-evacuation phase were divided into two functional tasks (for examples: moving to the window and terrace and opening them to ask for help, collecting properties ect.) and information tasks (for examples: Contacting the fire department, building management and services ect.). It also showed that, these behaviors were examined based on Protective Action Decision Model and extracted four models. It was found that the behavior of “unlocking the unit door due to the smoke in lobby and corridor”, “collecting assets”, and “finding the staircase according to the familiarity with the path”, have the highest relationship with risk perception and spending lesser time.

In the study, using Colaizzi Method, first, ten behaviors were identified in the first protective action and then by placing the behaviors in the Protective Action Decision Model, four models were extracted. According to the results of the first model, it is suggested that in each high-rise building, exit patterns at the beginning of the entrance of elevators and stairs should be installed in order to increase the level of familiarity with the location. According to the results of the second model, it is suggested that the panel “The elevator is off during hazardous situations” and also emergency numbers written on it be installed. According to the results of the third model, it is recommended to make voice announcements in high-rise buildings and report exit status for individuals. Also, according to the results of the fourth model, it is suggested that in order to reduce the Normalcy bias and optimistic bias on exit, the intensity and validity of signs and warnings (for example, with flashing lights) be increased. In this way, the risk perception of individual's evacuation will increase and the time of evacuation from fire hazards will decrease

In all air maps, without exception, belts or wind straps are seen at high speeds that extend over very long distances. According to the World Meteorological Organization, if the velocities of these velocities are more than 30 meters per second, the flow of the Jet stream is created (Alijani & Kaviani, 2000). However, jet stream is referred to the extreme horizontal winds at speeds exceeding 50 knots or about 26 m/s above the planet's winds. Since the geographical distribution of rainfall intensity on a planetary scale, in addition to system pressure patterns, seating tropical convergence belt, ocean currents affect the make-up jet stream, position and expand them as well. In this paper, an attempt has been made to identify a process of effective factors in the occurrence of storms in order to optimize the use of these rainfall in the study area. In other words, the purpose of this article is to determine the position and frequency of the storms and their average velocity during the storm events of Armand basin.

Essentially, in every ongoing study, there is a need for two databases; one for the environmental event database (surface), and another for the atmospheric database that identifies how atmospheric flows are. First, the daily precipitation data of the synoptic stations of Chaharmahal and Bakhtiari province from 1973 to 2004 were selected and prepared as environmental event database. The second group of variables consisted of wind and orbital component data that was used to plot the basins at 250 and 300 hpa. The first and second groups of variables were obtained from the Iranian Meteorological Organization and website www.cdc.noaa.gov.

3.1. The Role of Jet Stream Instability
The core of the jet stream in the context of long and short wave move. the entrance area on the left and the exit area on the right. In fact, based on the circle model, the core of the velocity is drawn into four sections: the right and left inputs of the divergence and the left and right inputs are convergent.
Frequency and average velocity analysis of the Jet Stream at 300 hectares
The large Jet Stream drawings at 300 hectares indicate that in the hours of 00:00 the highest frequency of inflows is observed on Saudi Arabia. There are two abundant small rivers, one on Uzbekistan and another on the north of the Caspian Sea and on Kazakhstan.
Frequency analysis and average velocity flow of 250 hPa
Frequency analysis of jet stream at the level of 250 hpa shows that in the hours of 00:00, the highest frequency of river flows extends from the Red Sea to the Persian Gulf, and south and west of the country. The analysis of average speed of the storms in the synoptic hours in this alignment shows that the average speeds of the storms are more than 40 m/s. The maximum velocity in the territory under question is at 6:00 pm, with its central core at 55 m/s on the Persian Gulf, Saudi Arabia and the southwest of the country, which also includes the study area. The mean velocity map for the above hour, which corresponds to the maximum occurrence of coincidences and coincidence with their maximum velocity occurrences in the study area, indicates that the fourth quarter (which is associated with positive precipitation increase as well as upper surface divergence and convergence of low atmospheric levels) is located on the study area. This can lead to high-level air mass expansion or upward movement. This seems to provide the necessary basis for the occurrence of instability at the time of flood and basin storms in the area under discussion.

The abundance analysis of the riverbeds at the 250-hp level revealed that over the hours of 00:00, 06:00, 12:00 and 18:00, the abundance of the riverbeds has spread over Saudi Arabia to the Persian Gulf, the center and west of the country In other words, in this area more than 50% of the formation and establishment of the jet stream.. During the four hours of the occurrence of synoptic atmospheric jet streams this level only based on the maximum frequency of the jet stream jet stream At 06:00, the range expanded under the influence of jet streams and jet streams while a wide range of western and southern half of Iran are obvious especially in the southwestern and southern parts of Iran. The most frequent occurrence of the river is the same hour, with the western zone of the country which is more than 60% consistent. The study of riverbed frequencies at 300 hPa level also indicated that the inflow of the Jet Stream in the four-hour significantly reduced compared to the higher levels.

One of the basic concepts of sustainable livelihood is resilience against injury. This concept, which refers to the complexities and conditions that affect people's life, is a way to improve the understanding of rural people’s livelihood in the context of ​​vulnerability to the incidents they are exposed to (Udaykumara & Shrestha, 2011). Reducing the vulnerability of villagers by increasing the level of resilience and improving flexibility against natural disasters like drought can characterize management, planning and development efforts, which is made possible by improving resilience. Therefore, the purpose of this research is to measure the indicators of livelihood and resilience and explain their relationship. The research is an attempt the question as to whether there is a significant relationship between different types of livelihood and resilience capitals of rural areas in the study area.
Finally, the research contributes to coping with this natural hazard and promoting sustainable livelihood in the study area by suggesting some approaches.

This research was applied in terms of purpose and descriptive-analytical in nature, which was carried out quantitatively. The study area encompasses 64 rural districts in the central district of Ardabil County. Among these 64 villages, 46 villages are administrated by their own rural administration and the rest by the rural administrations of surrounding villages. Thirty-six villages with a total population of 8,151 households were sampled by the stratified randomization. The sample size was estimated to be 367 by the Cochran formula. The dispersion of the sample across the villages was proportional to the number of households in each village. The sample was taken by the systematic randomization method. Data were collected by documentary and field studies. Livelihood was analyzed by five indicators within 46 items and resilience was analyzed by five indicators within 30 items, derived from the review of the literature. The face validity of the questionnaire was examined by a panel of experts who confirmed it after making some modifications. To estimate the reliability of the questionnaire, 30 questionnaires were administered in the study site as a pre-test, and the total reliability was estimated to be 0.89. Data were analyzed by the Kolmogorov-Smirnov test to measure the normality of research variables, a single-sample t-test to examine the villagers' view about the indicators of livelihood capital, Pearson’s correlation coefficient to check the relationship between livelihood capital variables and resilience against drought, and the Topsis technique to find out the resilience of the rural people.

In this study, Pearson correlation coefficient was used to study the relationship between livelihood capital and resilient against drought. The results showed a positive and significant relationship between livelihoods and resilience with a correlation coefficient of 0.33 and a confidence level of 0.99. Also, the strongest correlation was observed between human capital and resilience (0.41) and the weakest correlation (0.27) between physical capital and resilience. In order to study the villagers' viewpoint about livelihood, a single sample t-test was used. The average natural capital index was 2.63, economic capital was 2.87, human capital was 3.16, physical capital was 2.69 and social capital was 4.14. The significance level of all indices was less than the test error level (5%). The rural people perceive that the human capital is in a more optimal condition than the other indicators, but they assess the capital, economic and physical capitals to be non-optimal. This, according to them, is a reason for lower resilience against drought. In order to determine the resilience of the studied villages, the Topsis decision technique was used. The results showed that Sham Asbi, Anzab Ali, and Gurjan villages were more resilient than the other villages. The resilience of all villages was estimated to be 0.341. So, according to its distance from the ideal value, we can say that this level is not at an optimal level.

The findings indicated that the livelihood of the studied communities is not in a good condition and this is influential on their resilience in dealing with drought so that most studied villages are also far from the ideal in terms of resilience. This requires adopting a livelihood diversity approach as a desirable approach to promote the resilience of villagers against drought. By its holistic view on rural development and the use of a specific methodology for the development of rural livelihoods by empowering rural communities, this approach can contribute to planning and management for the improvement of resilience in rural areas. In other words, any enhancement of the studied capitals in the studied villages will increase resilience against drought. So, it can be said that livelihood is the basis of and a requirement for resilience. One of the most influential aspects of livelihood and resilience of villagers is their access to financial capitals, which affect the life of villagers depending on their type, amount, and nature. The lack of the economic and financial capitals will degrade the livelihood of rural people, resulting in their vulnerability and poverty and, consequentlyسرمایه های معیشتی, the loss of resilience to natural and environmental hazards. Therefore, to improve this situation and promote the studied variables and indicators, it is necessary to adopt such approaches as increasing non-agricultural incomes, diversifying agricultural activities, creating employment, and job diversity in rural area by identifying their potentials, and considering natural resources and attempting to maintain and empower their environmental and natural capabilities

One of the most important goals of spatial statistics is the study of spatial relationships of environmental data for the analysis of patterns and spatial dependencies. From behavioral aspects of precipitation as environmental data are extreme amounts of precipitation. Extreme event is the occurrence of a value of a weather or climate variable above (or below) a threshold value near the upper (or lower) ends of the range of observed values of the variable, that are associated with negative and environmental-human consequences (such as flood, drought, landslide, soil erosion, and physical damage to infrastructure (roads-dams), impact on human activities (settlement-agriculture-industry-services). In this regard, exploratory analysis of spatial data provides methods for distinguishing between random and non-random patterns. Precipitation extremes follow a geographical pattern like all other climate elements. Recognition of such patterns, specifically in those areas where people’s lives depend on precipitations can determine the success in environmental management as well as certainty in resources planning. The geographical position of Iran’s coastal region of Caspian Sea,(Adjacent to the Caspian sea, and the Alborz mountains), and the adjacent various geographic units (sea, plain and mountains),as well as their interactions with each other, provide appropriate conditions for extreme precipitation occurrences in this area. As researchers believe that the extreme precipitations in Caspian region is part of the intrinsic properties (Mofidi,2008). Regarding extreme precipitation in Iran’s coastal region of Caspian Sea, especially in eastern parts, is one of the natural hazards.the recognition of spatial auto-correlation of such a phenomenon can facilitate environmental planning and the reduction of vulnerability and also increasing adaptability capacities with such a disaster.

In order to analyze the auto-correlation of the sum frequency of monthly heavy precipitations of the study area, the 90-95, 95-99 percentile of precipitation for each pixel of the map is considered in both groups for cool seasons. Accordingly, 385 stations (synoptic, climatology, and rain gauge of Islamic Republic Organization of Meteorology, and rain gauge of the Ministry of Power) were studied during the time period covering 1966 to 2016. At first, the frequency of monthly extreme precipitation was plotted in the Surfer software. Then, spatial statistics techniques (global Moran index (function 1), local Moran (function 2), and Gettis-ord-J index (function 3) were used to analyze spatial auto-correlation features.

Function (1)

Function (2)

Function (3)

In the last step, the relationship between the spatial factors with the extreme precipitation frequency for each month was calculated using general Moran multivariate statistics (function 4).

Function(4)

One of the optimal methods for identifying the spatial distribution of climate events is to analyze the spatial relationships. The study aimed at determining the spatial pattern of the sum monthly precipitation frequency patterns in two groups (90-95, 95-99 percentile), using the spatial statistics techniques (global Moran index, local Moran, and Gi* index). The findings indicated that the global Moran index is statistically at 99% significant level. Results of the present showed that the dominant behavior in sum frequency of monthly extreme precipitation of the study area followed a cluster pattern in each group. The areas with positive auto-correlated clusters were in western and central regions and negative auto-correlated clusters were in the eastern parts. Gi* test approved the frequency of clusters with high and low values. The two-variable Moran's statistics between extreme precipitation and geographic factors showed that the effect of geographic factors on the spatial frequency pattern of extreme precipitation occurrence is weaker than the performance and influence of synoptic systems.

In general, it can be said that the Caspian region is more affected by the precipitation of the first group (90-95 percentile), which covers a vast area of the region. Results of the study showed that the dominant behavior in sum frequency of monthly extreme precipitation of study area followed a cluster pattern. The areas with positive auto-correlated clusters wاere in western and central regions and negative auto-correlated clusters were in the eastern parts. The comparison of the findings with those of previous studies showed that the geographical location of the study area, features of Alborz mountains, and also synoptic systems have affected the spatial auto-correlation frequency pattern of extreme precipitation occurrence. Finally, considering that heavy precipitation in the Caspian Sea region causes one of the natural hazards (flood), especially in the eastern parts with heavily-populated regions, recognizing the spatial patterns of this phenomenon can be very useful for planning environmental hazards and reducing vulnerability and increasing the compatibility