نشریه جغرافیا و مخاطرات محیطی
پیاپی 29 (بهار 1398)

The Chaos Theory was first used in the meteorology by Edward Lorenz in 1965 that turned it into a science (Kram, 2010). CHAOS means turmoil and disorder, and the synonym is turbulence in mechanics,; the term implies the absence of any structure or order. Usually, in everyday conversations, chaos and turmoil are signs of disorder and ineffectiveness, and have a negative aspect (Sayed Javadin, 2009). Geomorphologists describe the past and present trends as an essential principle and predict the future of processes. They, thus, understand the nature and the speed of change. Chaos means the order of a disorder The presence of new alluvial fans at the base of old alluvial fans, Galli, unbalanced landforms, etc. in the Ghezel Ozan basin indicates a change in the level base and active tectonics in the area. The main reason for the creation of a unbalance is the change in the base level, which they reflected as recession erosion in rivers and canals. Capture and deviation phenomena of glacial lakes discharge are due to variations and imbalances in the basin. The basis of the study of the Ghezel Ozen basin in a chaotic model is linear and surface erosion and a combination of both in different regions. The basin area of Ghezel Ozan is among the Caspian Sea basins, which originates from the heights of the Chehelcheshmeh Cheshmeh Kordestan, and after entering the Bijar Geonrouns, through its tributaries Mahanhan, Rajain, Hashtjin enters Tarom and flows into the lake of Manjil dam, and eventually after joining Shahrud to Sefidrud enter the Caspian Sea. This basin is located in Kurdistan, Zanjan, East Azarbaijan, Ardebil, Hamedan and a small part of the provinces of Qazvin, West Azerbaijan, and Gilan.

This research, which is based on library and field studies, attempts to study the chaotic behavior of geomorphologic processes in the Ghezel Ozan basin. For this purpose, changes in the basal level, captivity and river diversion, the sudden collapse of congestion, intermittent floating cones, hydro-geomorphologic cells, geomorphologic dominoes, salt domes and decreasing erosion coefficients in Ghezel Ozan sub-basins have been studied. To investigate the chaotic dimension of the target area, DEM of 30 * 30m of the region, we extracted our data from SRTEM satellite site. Then we removed the contour layer of the part from the DEM using Arc GIS software. Also, using 1: 50000 topographic maps of the study area, the rivers were extracted and digitize in ArcGIS software, and their pattern was analyzed. The lithology layer was digitized using geology maps of 1: 100,000 and 1: 250,000, and the network of drains was extracted with the help of DEM of the region.

Equilibrium is one of the words that have a special meaning in the chaos perspective. Chaos regards balance as an order in disorder. In the geomorphological equilibrium, external processes affect both the internal and the combination of both. The base of a river and its branches are one of the main parameters without which the analysis of drainage basins is impossible. The unity of the Ghezelan basin at the beginning of the Quaternary meant the existence of different geonerons. , They were an independent gathering place of matter and energy that were formerly local base level.. Such standards are the basis of localization in the current situation through traceable sediment traces. The numerous profiles plotted perpendicular to the Ghezelowzan River indicates a sudden downturn in the valley of rivers. The effects of local changes in Geonroun Bijar and Zanjanrood were detected through aggregate levels and alluvial plains.

The results show that the effects of changes in the baseline levels in Geonroun Bijar and Zanjanrood were reflected as congestion levels. The same changes have led to the capture and diversion of the QalaehChay, Mehrabad and Anguran Chay. The difference in the base levels in Geonroun Tarom on the two sides of the Ghezelowzan has leftover ten overlapping faces. The Geonrountic network of the Ghezel Ozen basin has been affected by several factors; their accumulation referred to as the cell. Distribution of lithological and tectonic cells has caused erosion of the line or line at the river level. The energy of the changes in the base level in the outflow basin transferred from the highest river rank, such as dominoes, to the status of the first rivers. In addition to excavation and excavation of dams, Ghezel Ozan domes, exploring and digging the rivers of the Ghezel Ozan Basin have played a significant role. The fractal dimension between 1 and 2 of most sub-basins is a line-level fractal. The fractal dimension above 2 in the rest of the sub-basins indicated the surface of the fractal. The mean erosion coefficient of recoil at the ranks 1 of the Zanjan and Tarom rivers indicates the discharge of matter and energy of the Tarom geonroun in the line.

Among all natural disasters, floods are the most frequent and affect the highest number of people. Flood risk is particularly severe in urban areas. Improving urban flood risk management has become a high priority at virtually all levels of governance. The proper design and evaluation of measures to enhance urban flood resilience should be based on the analysis of a range of scenarios, in which various hydro meteorological conditions and management options are tested. Human activities in varies forms has increased the flood events probability. These include: location of Iran's villages and cities in Foothills, destruction of vegetation, not respecting river privacy, excessive construction along the rivers, agriculture on the riverside and etc.  Therefore, the risk of flood is very high in urban areas. Urbanization also aggravates floods by increasing the amount of impermeable surfaces and redirect water flow. To describe the watershed hydrologic behavior are used from precipitation and runoff models. The curve number is one of the models for the calculation of runoff volume from rainfall. The curve number in comparison to other factors has the most impact on peak flow during various return periods. However, the rainfall volume has a great effect on peak flow and the intensity of this effect will increase by increasing the curve number.

The study area is located between 31° 51´ N to 31° 58´ N latitudes and 49° 46´ E to 49° 56´ E longitudes. The catchment study area is located in southwest of Izeh city that consists of three sub-basins: Sheykhan, Alahak and Tape- Shohada. Using the digital elevation model (12.5 m resolution), the boundary of watersheds and drainage system were extracted in WMS software environment. Land use map of the region was prepared, using Landsat Satellite Images. Then, field assessment in the region was done to measure cross sections, current velocity, and river slope and to determine the area affected by flooding in the rainy seasons. Furthermore, sediment sampling to identify soil texture was done aiming at characterizing soil hydrologic group. Curved number layer (CN) was prepared using soil characteristics, land use, and soil moisture conditions. Moreover, peak flow values and its duration for various return periods were measured using SCS Flood Calculator software and the data consists of basin extent, average of precipitation and its duration, curve number, river length and slope. To evaluate flooding of urban channels we prepared cross section profile, channel geometry parameters and hydrological features of each sections such as current velocity and discharge. Then, we used from Ghahreman and Abkhezr method (2004) to calculate the amount of rainfall intensity-duration in various return periods.

Based on the data obtained from the sub-basins, the curve number values were calculated and was prepared the curve number map. Based on maps prepared, most sub-basin area especially upstream of the basin have the highest curve number and the least permeability because the Asmari Formation and rock outcropping. Then, there are built-up areas and impenetrable surfaces, such as roads with a curve number of 87. Based on Ghahreman method in varies rainfall intensities, the expected amount of precipitation is calculated and intensities consistent with basin concentration time (30 to 120 minutes) were selected. In the following at the intensity of 30, 60 and 120 minutes, maximum precipitation volume was calculated in 2, 5, 10, 20, 50 and 100 return periods.

The intensity and duration of precipitation during different return periods were used to investigate the flood potential in upstream catchments of Izeh city. The results showed that Shahda Tapeh basin had the highest water withdrawal at the entrance reaches to the city. As a result, it has the most impact on flooding the streets and creating floods in Izeh City.In the second place, Elahak basin has the most effect on the flood in Izeh City, because the topographic slope of the area is high, also the channel was changed regardless of the hydrological parameters. Sheikhan Basin has the most negative impacts from flood damage on agricultural land because it is more distant from the city. The main causes of flooding in Izeh are: Change the natural channel of the river to artificial channels without considering the volume of inlet water, not increasing the width and depth of the channel at the city entrance (from upstream to downstream) and creating inappropriate transverse structures on the channel. Another reason for the increase in flood potential is the loss of the drainage network around the city; because the city has expanded. Also, alluvial fan cones between the city and the mountain were changed and converted into a city. Whereas in the past, alluvial fans have been used for flood spreading.

Protected areas and national parks play an essential role in protecting natural ecosystems and are an effective tool for the conservation of endangered species and the threats posed by human activities. These areas can help protect biodiversity by preserving environmental processes against Turmoil (Orozco et al., 2016). Currently, protected areas are considered as an important component in landscape (Echeverria et al., 2008) and should be evaluated periodically because they are protected for their natural values and can provide many benefits to communities (Pfaff et al., 2009). The risks monitoring in protected areas and national parks is very important in order to understand how they are, their impact on nature, the processes of reconstruction and restoration and to protect them in the long run. Assessing the risk in the ecological resources and ecological conditions of such areas helps managers make the necessary decisions (Jones et al., 2009; Wang et al., 2009). Multi-criteria decision-making techniques are used today for risk assessment in many studies. A review of the history of using multi-criteria decision making methods in risk assessment shows that these methods have been used alone or with other methods for risk assessment in different cases (Makvandi et al., 2013). The most popular multi-criteria decision-making (MCDM) technique is the TOPSIS method (see Hsu et al., 2010; Manouchehri & Shia, 2013). The general objective of the present study is the application of TOPSIS multi-criteria decision-making method for assessing environmental risks of ​​Dez National Park and protected area. In this regard, the most important risks of Dez National Park and protected area ​​are studied in terms of severity, probability and sensitivity of the receiving environment.

Dez Area with an area of 22013 hectares (total national parks and protected areas) in geographical position 22 and 48 to 46 and 48 degrees east longitude and 34, 31 to 12 and 32 degrees north latitude with north-south direction in narrow strip on both sides of the Dez River extends (Khuzestan Department of Environment, 2016(.
In In this study, the existing risks in the area through field visits, interviews with environmental experts and environmentalists present in the area, as well as existing reports and with use of Delphi technique in two parts of natural and environmental disasters were identified.In this research, the assessment and ranking of environmental risks of Dez Protected Area and National Park using TOPSIS method were based on three indicators of intensity of effect, probability of occurrence and sensitivity of the receiving environment. After determining the priority of the regional risks, for, the components of the number of categories and length of the category were determined based on relations 1 and 2 (see Makvandi et al., 2013) in order to determine their degree of risk.
1 + 3.3 log (n) = rank number             n= total number of risks                                     (1)
Category / smallest amount of risk - the largest amount of risk = Length of the category (2)

According to the field surveys, similar reports and experts' views, 33 initial risks were classified into two groups of natural and environmental disasters in this study. Then, using Delphi methodology and scoring the studied factors, 26 risk factors including 5 natural risks, 2 physico-chemical risks, 3 biological risks, 15 socio-economic risks and 3 cultural risks were rated as high as 3 and were accepted. The results showed that the risk of unauthorized hunting with a coefficient of proximity of 0/876811 has the highest risk of the area, while the risk of intentional and unintentional fire with a coefficient of proximity of 0/180761 has the lowest priority. Also, the highest natural risk in the area is drought with a coefficient of proximity of 0/6128228. The risks of Dez Area are affected by five unpredictable, significant, tolerable, modest, and minor categories in which tolerable risks are allocated as the most frequency percentage.

What is considered in sustainable development is the set of conditions leading to a favorable situation, and this goal is pursued in three areas: biological, cultural and economic. The view of environmental management based on natural resource management expresses that human beings need natural resources and the use of these resources still needs many years to come. Using TOPSIS multi-criteria decision-making technique, the hazards were identified and evaluated in Dez Protected Area and National Park. Due to the precise planning and integrated management with regard to the characteristics of the area, it is possible to preserve this particular ecosystem, as well as its sensitive and unique habitats, plant and animal species, and also to guarantee the survival of the human communities in this area. Although the management of each region would have a unique ecosystem, knowing the experiences of the regions and applying the knowledge and methods of international organizations and academic studies in protected areas would enchance the process of sustainable development along with maximum protection of biodiversity.

Water crises and soil erosion are some of the most important challenges threating food security around the world, and Iran is no exception in this case. Watershed management measures are common practices for soil and water conservation. Identifying and prioritizing suitable sites for implementing soil and water conservation measures in a watershed is, in fact, an important decision in watershed management. To this end, the analysis of spatial data and comparison with technical standards of conservation practices is primarily required. Multi Criteria Decision Making (MCDM) analysis methods are a commonly used method of analysis combining data from various criteria. The Analytical Hierarchy Process (AHP) is a MCDM tool widely applied in order to identify the potential sites for flood water spreading, artificial discharge and rainwater harvesting. Terrace and channel terrace are historical measures in soil and water conservation in Iran. Both of these measures are commonly used for upland area to reduce steepness of hill slope. The present research aims to present a GIS-based decision support system for the site selection of terrace and channel terrace in Kakhk Watershed located in the Eastern part of Iran. Finally, the results derived from AHP are compared with the current terrace and channel terrace implemented in the watershed.

The case study of this research is Kakhk Watershed. Kakhk is located between 58° 31′ 22′′–58° 38′ 01′′ E and 34° 02′ 25′′–34° 06′ 14′′ N  in Khorasan Razavi Province in the Southwest of Gonabad. The above mentioned watershed drains an area of 37.8 km2. The major land uses of this watershed include Rangelands and agricultural lands. The mean of annual rainfall in this region is about 279 mm; 58.4% of this rainfall takes place during the winter.
The main criteria for allocating terrace and channel terrace were achieved through the review of past literature in the field. Based on previous studies undertaken in this field, slope, rainfall, runoff, soil depth, soil texture, distance to drainage network and economic issues were the main factors affecting the site selection of terrace and channel terrace. Therefore, spatial data were acquired and processed through Arc GIS 9.2. Software. Rainfall-elevation equation was derived through analyzing eight climatic stations near the watershed used for preparing the annual rainfall map. In order to estimate the direct runoff, the Soil Conservation Service (SCS) Curve Number (CN) method was applied. The weight of each map and classes were derived using AHP and entered in each map and classes. The AHP is a widely used multi-criteria decision-making tool which assists decision makers in planning, selecting the best alternative, and resource allocations. The selected criteria were prioritized based on the decision-making process which, in fact, judges the dominance of one criterion over another. Consistency ratio (CR) was used to assess the consistency in the comparative importance judgment. Final weights derived for each criterion were assigned and calculated in Arc GIS. Then, rasterized maps were used for producing suitability maps. Suitability levels for each map were categorized based on the obtained results from both the field survey and literature review. In order to test the applicability of the approach developed in the study, the locations with existing soil and water conservation measures were compared with locations obtained through AHP.

The results of the AHP analysis reveal that slope and runoff criteria have the highest weight, while the distance to drainage network has the least weight in the allocation of terrace and channel terrace. The results also indicate that 4% and 7% of the watershed are highly suitable highly for terracing. Twenty nine percent and 47% of the watershed area in the West and Southwest have low suitability and are not suitable for terracing, respectively. In addition, the results for channel terrace show that 5% and 14% are suitable and highly suitable for channel terrace. Thirty one percent and 25% of the watershed area with high slope and low depth soil have low suitability and are not suitable for channel terrace, respectively. Highly suitable sites were mainly located near the main outlet due to the existence of deep soils with suitable texture. Upland areas of the studied watershed were mainly located at the unsuitable level although the amount of rainfall was considered to be proper for conservation measures due to the limitations in slope and soil properties.
A comparison between the obtained results and the implemented measures in the watershed reveals that 59% of the area with channel terrace and 21.8% of the area with terraces are located at highly suitable levels. The mismatch between the obtained results using implemented measures may be due to not taking into account the other criteria such as social and economic issues and also people participation during the process of implementation.

The current study aims to apply a combined GIS and MCDM approach to allocate and prioritize sites for the implementation of terrace and channel terrace within the Kakhk Watershed in west of Iran. The obtained results in the present study suggest that decision support system may assist local watershed managers in soil and water conservation. Using further criteria in site selection and using more MCDM methods are also recommended for future studies.

Hillside instabilities, including the separation of rock fragments from heights and their displacement are under the influence of various forces of natural phenomena which occur abundantly in Rocky Mountains every year. The Uremia –Silvana road with approximately 14 kilometers in length passes through Band village, which has lost almost its rural form. Band is a mountainous village and is located in a mountainous region and it has great sights that have turned this promenade to the natural attraction for Uremia city.  In addition to this, the river of Chai city passes through the middle of this village and also the dam of the Chai city which is one of the most beautiful dams in Iran lies in the west of this village and adds to the beauty sights of this area. From the villages around study area, we can mention to the Mir Abad village in the north of it, as well as the villages of Nowshan Sefli and Nowshan Alia in west and the village of Shamlakan in the south of the promenade. We saw major natural hazards, including Hillside instability, such as creep, rock falls, debris and the presence of loose losing alluvium by scrolling along the pathway of Uremia -Silvana; that threat the Uremia- Silvana road and engineering facilities around it in addition to the inhabitants of Band village and Nowshan Sefli.

Various methods have been proposed by scientists and researchers for zoning, each of which has been presented for a specific purpose and for a specific region. In this research, was used of the Anbalagan zoning method that is one of the most common methods for zoning of Natural hazards.  This method helps designers and engineers significantly for implementation of development plans in mountainous areas. The mentioned method depends on the major factors that have effect on Hillside instability, such as geology, gradient, land use and land cover, height difference, and so on. In this research, first data collection was done from the exact position of the hazards, including creep, rock falls, debris, and the presence of loose alluvial deposits in the place of trenches using the (GPS) device by scientific literature, library resources, indigenous knowledge, interviews with residents of the area and extensive scaling in the study area and after field surveys and studying satellite Images, prepared points in field have been provided as a separate layer in (Arc GIS) software and to avoid computational error of software, we reviewed the scope of the study area and identified it with polygon. And in this paper, weighted values that are considered for classification of maps of different factors are from 1 to 10. In this paper, the number 1 has been chosen as the maximum risk for each unit, and the number 10 is our optimal one. The characteristics of the effective parameters in the risk evaluation and how to value them, has been done as follows.

Rocks fall in mountainous areas is a natural phenomenon and their occurrence is a natural event. But when rocks fall threatens human lives (financially and mortally) becomes a natural hazard, and are considered as natural disasters in a situation where there are many mortal and financial losses as a result of their occurrence, however, the collapse of hard and connected to Hillside rocks threats the stability of the area due to the climatic territory and the type of rocks and their characteristics. This instability is for urban and rural housing, recreational and tourist facilities and industrial plants located on subcutaneous or roads that cross mountainous areas. As can be seen in (Fig. 5) and has been shown on the satellite map of the study area with points (3, 4, 7, and 6) (Fig. 6). The fall of rocks has threatened rural buildings and roadway and gas and electricity pumping stations in the region. Severe fluctuations in round the clock temperature, especially at elevations above 1600 meters, lead to intensified chyroclasty activity. In this way, in addition to rural houses and vital facilities, roads were bounded on one side or on either side by a very steep wall of the slopes are continually threatened with the risk of falling large and small rock pieces. In particular, if the earth-forming rocks have several grooves and joints and dialects. Water penetration in the grooves and temperature changes to the point where it is suitable for freezing and melting are led to gradual dismemberment and the provision of coarse fragments and debris. The resulting fragments are collected at the down of the slopes which often have slope cuts or on slopes with gradient less than 35 degrees or 40 degrees.  But if the balance of the gradient of the debris collapses for any reason or the gradient of slope is greater than 40 degrees, the fragments obtained from mother rock fall only under the influence of gravity as soon as they are separated from its wall.1- The fractures of the studied area are the most noticeable tectonic effects, as has been shown at the points (10, 11, and 12) in the satellite image (Fig. 6) jointing along with erosion leads to the crushing of lava on the roadway. Rock falls can attack large structures such as dams and bring damages to their secondary facilities. that of course, rock falls in the 21 point and surrounding areas of the Chai city dam (pebble soil reservoir dam with clay core with a height of 119 meters from the foundation and 84 meters high from the bed and a crown length of 550 meters has been located in the west of the village of Nowshan Alia) has been shown in the satellite image of figure 6. That in this regard, the necessity of using rock falls stabilization methods should be on the agenda to prevent possible damages (Fig. 8). Rocks have become to large and small fragments and as a result of gravity has fallen to the down the hillside. Figure (7), So that they have been formed with steep gradients towards layers that indicate mild flaking in the region and show good correlation with the condition of flaking of the rock units in many cases. Most of these fractures are tectonically young 2- Extreme motility of drift and hidden faults has caused severe crushing of rocks and has created fractures and join on the Uremia- Silvana road. 3- Due to climate change during the year in the study area, the climate along with tectonic factor have caused severe erosion of the outcrops in the area and have increased the volume of debris at down the mountains. 4- Tectonization of the study area is the main reason for rock falls in the region, therefore, as shown in the map of zoning of the risk level in the region, villages and communication routes are affected by faults and hillside falls in high risk areas.
5- According to the zoning the risk level map in the studied area, engineering structures with foundation point such as power distribution stations and very large engineering structures such as Chai city dam are located in areas with medium to very high risk. Therefore, hillside stabilization operation should be done in these areas. 6- In addition to rock falls, the phenomenon of creep has been seen in some parts of the villages in the area and communication paths due to the high groundwater level and the presence of loose alluvials with a height of more than 7 meters in the studied area. That the villages and communication paths should be moved into lower risk areas according to the zoning of hazard levels map.

The Uremia - Silvana road is located in the southwest of the city of Uremia. This road has been started from the beginning of the Band road and has been extended from the promenade and tourist area of Band of Uremia. The purpose of this study is to determine the high risk areas using software (Arc GIS 10) and the Anbalagan zoning method from the point of view of hillside instability in the above axis and villages in the region. for this purpose, 14 layers (fault, height, stream, slope, slope direction, detrial rocks (OMS), alluvial deposits, vegetation, hazard points, village, city, dam, road and rural roads) were prepared. And by weighting to risk factors and using the rock fall hazards zoning map of the study area we divided the results into five groups: According to the desired map, from the total of 7441.07 hectares from the study area, 1509.73 hectares are in a very high risk area, 2330.47 hectares are in a high risk area, 1980.14 hectares are in the medium risk range, 1150.66 hectares are in a low risk area and 470.07 hectares are in a very low range. All villages (Band, Janesloo, Nowshan Alia and Sefli) have been located in high-to-middle risk areas. The highest concentration of high-risk areas is in the west, south-west. Most rural roads are located in low-to-middle risk areas and only 2 kilometers from the main road of 14 kilometers are located in a low-risk and safe range. By adapting the map of the incident points with the zoning map, we conclude that most rock falls and debris are located in a medium to very high risk zone. Chai city dam has been located in a medium-risk range, but the hillsides around the dam are high-risk areas that rock falls in them threatens the Chai city dam.

One of the major issues facing the present-day population of metropolitan settlements, especially in metropolitan areas, with its high population density and physical density, is the natural and man-made hazards that cause serious damage to their structure in various forms. Natural hazards affect every part of the world in a different ways depending on the geomorphology and demography of that place (Nirupama, Adhikari, & Sheybani, 2014). Because natural disasters are unexpected in terms of shape, size, and location, they cannot be prevented. Therefore, the capacity of a system to increase resilience and recovery in the face of natural disasters should increase (Zhou, Wang, Wan, & Jia, 2009).Reducing the disaster risk is an investment at an effective cost in preventing future casualties and managing disaster risk according to sustainable development (UNISDR, 2015). The main solution that various scholars have to admit is to make cities more resilient in dealing with disasters, and assessing the resilience of cities is the first step in this direction.The beginning of the global movement for resilience of communities can be attributed to the Higgo International Conference (2005). The meeting, which aimed to develop a framework for reducing the vulnerability of communities to natural hazards, mentions actions in the context of resilience, stating that the use of knowledge, innovation and education to build a safety and resilience culture at all levels is essential. This important role in the sustainability and reducing the vulnerability of societies in the dangers and in the definition of resilience. The potential capacity of a system, community, or society to face upside risks to adaptation by resistance or change to achieve and maintain an acceptable level of performance and structure depends on the extent to which the social system is able to organize itself in order to increase its capacity and learning from past disasters in the direction of a better future and improving risk reduction measures (United Nations, 2005). The current research aims to identify the current situation of Mashhad metropolis in terms of readiness facing natural hazards using urban resilience approach. Mashhad is the second city of Iran after the capital (Tehran) with population of around 3.3 million based on 1395 census.

Progressive research is conducted quantitatively based on the indicators of the 100 resilient cities, and by using library and documentary studies and completing the questionnaire by experts in the field of natural disasters and natural hazards. The study population was the experts who was aware of the structure of urban system and also urban crisis structure and who were also aware of the degree of vulnerability of the city when facing natural hazards.  The sampling method was used to complete the questionnaires randomly. According to the number of experts in this field, 41 samples were selected based on the Cochran formula. Analysis of the findings was done using tests such as Cronbach's alpha for reliability and T- A single-sample test was performed in SPSS software to measure the degree of readiness of Mashhad in terms of its resiliency and the plotting of the radar chart was performed by Excel software to see if there was a significant and meaningful difference between current and desired status.

To measure the resilience of Mashhad based on the target community's response, one-sample T-test was used for normal data. The results indicate that the research hypothesis is based on the resilience of Mashhad city against natural and earthquake hazards. It can be seen that at the error level of 5% and with test criterion 3, the hypothesis of the test is confirmed with a value less than 0.05; that is, in general, in none of the dimensions of Mashhad city resilience was not found. The research hypothesis is approved in the proponents. Also, there was a difference found between the desired situation of Mashhad and the status in terms of resiliency.

The research confirms the hypothesis of non-resiliency of Mashhad city against natural hazards, including large-scale earthquakes. Despite the novelty of the research in terms of the level and area of measurement, as well as the conceptual model and how it evaluates that, there is a significant difference with other studies in this field. This research investigates theories and findings of other researchers such as Nasr Abadi ,H. & Kharazmi, O. A., & Rahnama, M. R.(2016). and confirm that Mashhad is not resilient in the social, economic, institutional, and physical dimension.The structural weakness of Mashhad city's urban management complex in controlling and managing natural disasters and efforts to rehabilitate and rehabilitate the city and the inability to provide services, livelihoods and employment after a large scale and destructive earthquake is the biggest problem in Mashhad. Managing the situation appropriately and raising awareness among citizens about how to deal with natural disasters is a good solution to adjust and eliminate problems. There is a need to train citizens regarding their readiness over natural hazards and also there is a need to make different regions of Mashhad metropolis consistent with these kind of activities. There are many rural areas very attached and close to metropolitan area of the city and urgent actions are required to reduce the degree of vulnerability of the city in this regard. It is recommended that different stakeholders should be integrated in this issue. Different job descriptions are available for organizations which are sometimes in contradiction and waste resources and time. Therefore, there is a need to make these organizations informed and put them in line with urban resilient integrated policy. This can reduce the degree of overlap and can make their efforts more valuable and effective.

Studies show that in recent years, climate change around the world has been increasing rapidly and has brought about irreparable economic, social and development consequences. Due to the prevailing conditions in different regions, the effects of climate change will vary, and due to the severity and weakness of these symptoms and their effects, significant damages will be caused annually by the increase in temperature. The earth will increase (Alishiri, Khanly. & Bagheri, 2015). Promoting sustainable patterns of energy production and consumption is therefore essential, and the international community is in dire need of a more sustainable lifestyle to reduce energy consumption. Based on predictions, CO2 emissions from energy consumption in developing countries will surpass developed countries in the coming years (Alishiri et al., 2015). The purpose of this study is to identify factors affecting carbon dioxide emission, as one of the key environmental considerations, in the Middle-eastern countries. In this study, first, the definition and concept of environmental quality, the study area and factors affecting environmental quality have been addressed. Then, the research and modeling method is explained and finally the results of modeling and policy suggestions that can lead to an increase in the quality of the environment are presented.

Due to the high share of carbon dioxide in contaminating countries and its distinct data, carbon dioxide emission have always been considered as indicators and environmental quality in research. The same criterion was used in this study.  The study area in this research is Middle-eastern countries. The method used in this study is Panel data and the data is annual. The data ranges from 1990 to 2015. In order to overcome the sample size problem, panel data from the Middle-eastern countries have been used to test the causal relationship between energy consumption growth, economic growth, export growth, population growth and carbon dioxide emission growth.

The purpose of this study was to identify the relationship between carbon dioxide emission and variables such as GDP, GDP2, energy consumption, population density and exports for the Middle East countries during the years 1990 to 2015. In addition, the existence of a Kuznets curve (EKC) for these countries was studied. To analyze the relationships, the panel test data reliability tests, the determination of the panel model test, and finally, the significance analysis of the coefficients were used. The results showed that the relationship between energy consumption variables, GDP, GDP2 and population density with carbon dioxide emission is significant. Also, there is a U-inverse relationship between GDP2 and carbon dioxide emission, so the Kuznets hypothesis applies to these countries. In contrast, the relationship between exports and carbon dioxide emission in this study is not significant. This means that, at the outset, the growth of countries' production is accompanied by the addition of carbon dioxide gas, but after the initial stages of development by a country production increases with the reduction of carbon dioxide gas. The relationship between exports and carbon dioxide emission in this study for the Middle East countries was not confirmed.

The purpose of this study was to identify factors affecting environmental quality. According to the methodology, GDP2, GDP, energy consumption and population density are the main factors affecting CO2 emissions and environmental quality in Middle Eastern countries.A number of policy implications can be made based on the findings of this study. 1) Population policy should move towards decentralization of cities, especially metropolises, in addition to population control. This has led to the spread of population throughout the country, which has reduced the use of contaminants that will reduce pollution. 2) Due to the significant relationship between energy consumption and CO2 emissions, policy should be taken to replace renewable energy with fossil fuels. Failure to reduce energy consumption in the Middle East countries should include funding for scientific and research institutions through projects to increase energy efficiency and reduce the use of fossil fuels. 3) Middle East countries should consider increasing GDP by enhancing the production of goods and services and increasing the productivity of production entities, as in the Kuznets hypothesis (EKC) there is a reverse U-shaped relationship between economic growth and pollution. Increased production and economic growth will reduce carbon dioxide emissions and air pollution. 4) Given that the relationship between export and CO2 emission for the Middle East countries is not statistically significant, production can be further increased by increasing exports, which can lead to economic growth. It is recommended that the Kuznets hypothesis reduce pollution. 5) Middle East countries should use environmentally friendly technologies in the production of goods and services to directly increase pollution production and reduce pollution according to the Kuznets hypothesis as well as directly prevent the spread of pollution. 6) Taxation should be on the agenda of governments to reduce carbon dioxide production technologies as well as domestic pollution generating plants to reduce CO2 emissions.

Assessing the projection of precipitation changes as one of the most important climatic and hydrologic parameters will help to overcome the challenges of water resource managers and planners. The future projection of precipitation is very important for countries whose economies are based on agriculture. On the other hand, by prediction of precipitation, it is possible to cope with the drought and reduce the damage caused by it. Therefore, in this research, the projection of long-term precipitation changes in the northwest of Iran was investigated.

The data of 5 GCMs were under two RCP4.5 and RCP8.5 scenarios downscaled using the LARS-WG6. The precipitation changes were carried out at three different periods (2021-2040, 2051-2070, 2081-2100) and was compared to the base period (1980-1989). LARS-WG6 is a stochastic model using semi-empirical distribution to generate climatic data by statistical downscaling techniques. This model requires less input data than other climatic models because of the repeated calculations and also has more utility for simplicity and efficiency. The LARS-WG model, as a downscaling model, although having less complexity in the simulation process and in relation to input and output data, still has a high ability to predict climate change. The main reason of creating this model was to overcome the weaknesses of the Markov chain. The sixth version of this model (LARS-WG6) has been updated and released in 2018 for Fifth Report Data Mining (CIMP5). To implement the LARS-WG model, daily data on minimum temperature and maximum temperature and daily precipitation in the statistical period (1980–2010) were used as the basis for past climate change and for future climate simulation. To generate synthetic data, the model uses long-term daily station data as input for comparison. If the two data sets are matched, the model will be able to generate time series for future periods. In order to validate and ensure model robustness, the model was run for the baseline statistical period to generate a series of synthetic data in the baseline period. Then, in order to evaluate the performance of the model, the outputs were compared with observational data (meteorological station data) by means of statistical tests (T-test for estimating monthly mean precipitation and F-test for estimating monthly variance of precipitation), were compared. In addition, the performance of the LARS-WG model has been used to determine the coefficients of determination (R2), mean square error (RMSE), mean square error (MSE), and absolute mean error (MAE).

The results of downscaling model performance showed that there is no significant difference between measured and observed values with critical error of 0.05 in most months of the year and this model is a suitable method for simulating rainfall in the study area. Also, future precipitation results showed that according to the predictions of most models, especially EC-EARTH and MIROC5 during the period of 2021 to 2040, precipitation in the study area will decrease by 4.6, 0.9 and 9.4% respectively and the most changes will happen in the southeast and west part of study area especially in the Khalkhal, Khodabandeh and Orumiyeh stations. Based on the results of EC-EARTH and MIROC5 models, rainfall in both scenarios will increase by 2.5% and 12%, respectively, with the most significant changes in the southwestern regions of the study area, especially Mahabad and Sardasht stations. The results of rainfall changes over the period (2051-2070) also showed that according to GFDL-CM3, HadGEM2 and MPI-ESM models, precipitation decreased by 2.5, 0.3 and 11.8%, respectively. The most reduction in scenarios is based on the RCP8.5 scenario and the MPI-ESM model, which decreased from 16 to 130 mm in the study area, the lowest and highest being at Pars Abad and Sardasht stations, respectively. During this period, according to EC-EARTH and MIROC5 models, rainfall will increase in the study area that it's equal with regional rainfall average with 10.1% and 3% respectively. The results of rainfall changes over the period (2081–2100) also indicate that, under GFDL-CM3, MIROC5 and MPI-ESM models, and rainfall rates in the region decrease. The highest RCP8 scenario values 5.5 are 18.8%, 6.2% and 11.3%, respectively. According to the EC-EARTH and HadGEM2 models, rainfall during this period increased by 7.5% and 17.9%, respectively. Results show that the lowest and highest precipitation changes in this period are in the northeast and southwest of the study area. Overall, based on the results of the different models, precipitation will experience a slight increase over the period (2021-2040), with an average of 0.3% of the total model output. The area will be level. In the next two periods (2051-2070 and 2081-2000), the average precipitation is expected to decrease by 0.7% and 1.4%, respectively. According to the results, the most decreasing changes were in the eastern regions of the study area and the most incremental changes were in the southwestern region of the study area. The most decreasing and incremental changes are also more evident under the RCP8.5 scenario than the RCP4.5 scenario. The results show that the model accurately simulates rainfall in the studied stations. Pearson correlation coefficients between observational and simulated data are acceptable at the significant level of 0.01.

Climate change is one of the most important environmental challenges of human society in recent years due to the global warming, the crisis in water resources, the change of ecosystems, and the social and economic problems caused by these changes. It has attracted the attention of many scientific circles worldwide. Temperature and precipitation are among the most prominent climate variables in an area. For this purpose, the present study investigated the prospects of long-term precipitation changes in the northwest of the country by using the outputs of 5 atmospheric general circulation models under two scenarios RCP4.5 and RCP8.5. The LARS-WG6 model was used for microarray outputs. Therefore, the results of performance evaluation of LARS-WG model using different statistical tests and calibration indices showed that this model has good accuracy for simulation of precipitation in most of the studied months and stations. The results of the outputs of different global models showed that precipitation in future periods in the study area based on GFDL-CM3, HadGEM2 and MPI-ESM models will be lower than the base period. So, by using EC-EARTH and Miroc5 models, the rainfall amount will examine more than the value of the base period or close to it, respectively. Various results in the different applied models showed that long-term precipitation prospects will only be investigated using the GCM model, which will lead to many uncertainties too. It can be said that this trend is due to the complexity of the precipitation process and the abilities and characteristics which each of these models exhibits. Overall, according to the results, precipitation will increase in the near future (2021-2040) in the northwest of the country compared to the baseline period. But the prospect of precipitation in the near future shows that there is a decreasing trend among the five GCM models except for HadGEM2. Thus, predicting the probability of precipitation in the northwest of the country in the near future will be a relative increase in precipitation compared to the baseline period and a sharp decrease in precipitation in the near future. The results of this research can be used in the managing and planning of water resources, agriculture, energy and so on.

Urban development and air pollution are among the most important issues related to the climate (Shkakoie, 2006). In spite of statistics comparing Tabriz's pollutants with world standards. The claim is not far from reality. One of the main environmental problems of Tabriz is air pollution. Tabriz, with an area of 135 square kilometers in the northwest of the country, has been located on the topographic surfaces between 1300 and 1750 meters in length. In this research, we have tried to use the ANP model and AHP model, fuzzy logic and compare them. A suitable model for the leveling of different regions of Tabriz should be created and graded in terms of acute and mildness and the effect of each of these factors on damaging Tabriz, will be analyzed by the above models.

In this study, the effective factors in polluting the study area were identified through the study of documentary and library resources (East Azarbaijan Environmental Protection Agency report, air pollution monitoring stations report), digital resources related to the research subject and field studies. These include precipitation, altitude, distance from green space, distance from industrial centers, distance from commercial centers, distance from communication routes, crowding, land use.In the next step, the information layers for each of the factors in the GIS environment were prepared. The use of digital maps is to extract the required data from the map text (including topographic maps, land use, etc.). To evaluate the criteria, the membership function method was used in fuzzy sets. The weighting of the data was also done using the Paired Comparison Method in the framework of Expert selection and CRITIC method. ArcGIS 10, Excel 2007, Super Decision 2.0.8, MATLAB7.11.0 software were used to conduct the research. The results of studying parameters in the studied area is shown in the form of digital maps. With regard to the evaluation models for pollution, the mapping of the parameters of the studied area wasre-classified. Using these maps and descriptive information about the region, a database was developed to analyze sources of pollution.
Analytic Hierarchy Process (AH) Analytic hierarchy process is one of the most comprehensive systems designed for decision making by multiple criteria, first introduced by Thomas (1980). This technique provides the possibility of formulating the problem in a hierarchical manner, and it is also possible to take into account different quantitative and qualitative criteria in problem. This process involves various options in decision making and allows for sensitivity analysis on criteria and sub criteria. In addition to being based on a paired comparison that facilitates judgment and computing as well as the degree of compatibility and incompatibility, it shows the advantages of this technique in multi-criteria decision making (Ghodspour, 2005). With the knowledge of the principles, the AHP method consists of the following steps: Creating a Hierarchy of AHP, 2. Creating a Binary Comparison Matrix, 3. Calculating Standard Weights, 4. Calculating Inconsistency Rate, 5. Spatial Modeling and Layout Composition ANP model The ANP method is a developed form of the AHP method that correlates elements in a decision making process and calculate the internal effects of the components involved in the decision making process. Therefore, due to this feature, this technique is distinct and superior to the previous models. The ANP method has two main parts that integrates these two parts in one process. The first part consists of combinations of control criteria and sub criteria, as well as a group of volunteers.  The second part, a network of vectors and an arc which indicates dependencies and correlations as well as feedback in the decision-making system. The ANP model can be considered as the most comprehensive multi-criteria decision-making method (Razmi, 2008, cited in Mehdizadeh, 2011). ANP has four steps: Determinig the criteria and indicators including rainfall, height, distance from green space, distance from industrial centers, distance from commercial centers, distance from communication paths, crowd, and land use. Determining relationship between elements and cluster. Comparisons between elements and clusters. Super-matrix formation. Super matrix is a matrix of relationships between network components that are derived from the initial vectors of these relationships. Super matrix in ANP, a measure of relative importance values, such as AHP, is performed with paired comparisons with the help of the spectrum from 1 to 9. Number 1 indicates the same importance between the two factors and number 9 indicates the acute importance of one factor relative to the other factor (Kiani et al.,2010). Finally, air pollution potential map was prepared in the framework of the above models. To prepare an air pollution level map, the first step is to create an information layer for the element. In this study, eight criteria or elements were used. Then we ranked, rotated and standardized them using the fuzzy function. Then, using final coefficients of the ANP and AHP models, multiplying  coefficient of each element into the same element map by the Raster Calculator function, and  combining the information layers together, the air pollution potentiality map was prepared in the above form.

In order to provide a risk map, eight criteria were used in this study. First, maps were prepared for each of the criteria. We then ranked, rendered, and standardized them using the fuzzy function.  Using the steps of the AHP model and the final coefficients of the ANP network model, multiplying each elemental map by the Raster Calculator function and combining the information layers together, air pollution of the area was prepared separately on the basis of ANP and AHP outputs. The final modeling was carried out in the Super Decision software. The domain value of the model was calculated for determining the potential air pollution in Tabriz. Final weights were obtained for assessing air pollution. Finally, the studied area was classified into five groups of very high, high, moderate, low and very low risk. Based on the ANP output, areas with very high levels of pollution include the northern and north-western regions, and areas with high levels of pollution include the central regions of the city. Small regions of the south and south-east are low in pollution, while the output of the AHP model shows that areas with a high risk include the entire central region and the northern and western parts, and the area with high pollution is a small region of north and northwest.

The industrialization of societies in the last century has caused many problems, including air pollution, which is due to the inability of the environment to absorb contaminants. In this study, AHP and ANP models were used as multi-criteria decision analysis method in studying the potential of pollutants in Tabriz. The Multi-criteria Evaluation Methodology (MCE) is one of the most principle-based decision-making methods in GIS (Bogdardi et al., 1996), which is used as spatial decision making for land planning. According to the final map of the ANP model the vast majority are in the northern and north-western regions, due to the fact that factories in Tabriz are located in these areas. Highly polluted areas are the central regions of the city. The area that peaked during the day with increasing traffic and exhausts, contaminated air was area 8. The most used were educational, cultural, health, administrative, commercial and communication, and the least use were residential, green spaces which increased pollution. As the map of altitude levels showed, the northern areas of Tabriz have a sharp slope, which is also seen in the south of the city. The central and western parts of the city are smooth, and these factors increase pollution in these areas. Given the map of congestion, despite the fact that a large number of inhabitants live in northern parts of the city, due to the concentration of most services, businesses in the city center, overcrowding has grown throughout the day in the central regions of the city which increases traffic of vehicles and pollution. The results of the AHP model indicate that areas with a high risk include the whole central region and the north-west regions, and the region with high contamination includes a small area from the north and north-west. It should be acknowledged that among the factors influencing the contamination, communication paths with the coefficient of 0.69 is the most valuable and important for contamination.  Population congestion with a coefficient of 539% of land use with 0.460 coefficient are other important factors respectively. Rainfall and altitude factors with respect to weight coefficients have little effect on pollution. In the case of green space agent, it should be noted that parts of the North-West and South-West have a low distribution of green space, the largest distribution of green space in the southern parts, which is less contaminated than the rest of the regions. Therefore, it can be said that the ANP model, in comparison with the AHP model, accurately realizes the relations of the criteria and their coefficient of influence, and the results of the model are closer to the research goal.

Temperature is one of the most important elements in weather and climate forecasting. Therefore studying temperature behavior is important for understanding climate variability that can vary at different spatial and time intervals and local, regional and global scale. The International Climate Change Board (IPCC) has clearly indicated that global temperature trends have increased by about 0.85 ° Cover the period 1880 to 2012. Climate change usually has enormous impacts on people and their temperament, agricultural resources and access to water, especially in areas where their economic activity is dependent on agriculture (as in most parts of Iran). Iran's climate is diverse due to the complexity of the topographic features and the vast geographical extent. Therefore, the effect of major local factors on climate change must be identified.These results can help confirm the studies of climate models that this also helps in planning for agriculture and water supply, especially for the future. In previous decades, most temperature analyzes focused on average values. In recent year's low-temperature analysis has broadly focused on Changes in the occurrence of extreme temperatures with high frequency, Number of days over different temperature limits, Regional trend of minimum and maximum temperatures and diurnal temperature difference events.

This article evaluates the monthly mean and seasonal Minimum and maximum temperature variability in autumn (October-December), winter (January-March) and also the cold period (October-March over a 60-year (1951-2010) statistical period. Stations with 60-year statistics included 26 cases. Before using the data, it is synchronized and any possible errors are removed. Changes in mean and variance were tested by conventional methods. Statistical processing was performed using R software. According to World Meteorological Organization methods, Required statistics include mean, coefficient of variation, probability of up and down 20%, standard deviation, daily and monthly temperature and minimum and maximum temperatures in two 30-year(1951-1980),(1981-2010) and 60-year(1951-2010) periods were calculated. Then, using the Mann-Kendall test, the trend of this minimum and maximum temperature over a 60-year period was determined. The patterns of each statistic are plotted and interpreted using the

The results show that the lowest mean temperatures are in the fall, winter, and cold periods in the northwest and north regions and the lowest is in the south and southeast of the country. The lowest coefficients of change in minimum temperatures for autumn, winter, and cold periods are the northern and southern coasts and the eastern and southeastern parts of the country and the southern and central coasts of the country respectively. The highest coefficient of variation is winter in Hamadan and Gorgan and in cold period in Gorgan and Rasht. In the autumn, the coefficient of variation is generally low. In addition, the lowest maximum temperatures occurred in autumn in the northwest and west and in winter in the north and northwest, which coincided with the pattern of maximum coefficient of variation. The years with a high frequency of 20% at the stations under study are synchronized at both minimum and maximum temperatures. But for the 20% lower limit, this coordination is not seen only in the first 30 years of autumn. Also in the last decade compared to the first decade the minimum temperatures during the autumn, winter and cold periods decreased at 8, 4 and 7 stations and at 18, 22 and 19 stations have increased respectively. In the fall, the maximum temperature only declined at three stations, and in the other two periods, all stations showed an increasing trend and the results in a decrease in the diurnal temperature difference.

Most of the minimum temperature variability is in the northwest and west and northeast of the country that the reason could be the arrival of different air masses, especially through the northwest and west of the country. But on the north and south coasts of the country, this variability is less due to the moderating effect of the sea. Also, the variability in autumn was higher than winter, which it shows the most active air masses in the winter. The occurrence of the highest maximum temperatures in the southern regions with the lowest coefficient of variation indicates a more uniform temperature conditions than elsewhere. Also, in most parts of the country, the diurnal temperature difference has decreased..

Due to the socio-economic consequences, the analysis of the climatic extreme has been studied by many climatologists, environmental scientists and even scholars of humanity and social sciences. Extreme events are said to be rare events far from normal conditions (Bartolini et al., 2008). Time changes in frequency and intensity of high extreme precipitation prevent the floods and itsconsequent risks. High extreme variability of precipitation has widespread effects and  severe consequences on human societies, natural ecosystems and physical structures as these structures are consistent with normal climatic conditions and their adaptation to the extreme conditions is hardly possible. Due to the environmental and human impacts and the importance of high perception, the trends in these events have been widely studied, detected and modeled worldwide. But there are few studies focusing on high and widespread precipitation in the Caspian region; most of these studies have adapted a synoptic approach to do the research. From the perspective of statistical analysis, less attention has been paid to this part. Therefore, concerning the importance of the behavior of precipitation and its changes, the present paper studies the frequency and  the average intensity of high precipitation in the Caspian region  because the increasing and decreasing fluctuations of the extreme precipitation can affect the ecosystem of the area and make management and planning face serious issues.

To determine the frequency and the average of the intensity of widespread and high extreme precipitation events resulted by percentile threshold of 90-95, 95-99 (heavy precipitation) and 99 and more (very heavy precipitation), the daily precipitation data related to synoptic stations, the climatology and the rain gauge in Meteorological Organization and also the Ministry of Energy of Caspian Sea Region have been used from 1966 to 2016 (51 years). Due to different data records regarding the length of station and their non-uniform distribution and the changing of the station data into network data, the Kriging method is used as the optimal method in the interpolation of the observation. The result of the interpolation of daily precipitation is a matrix with 6479  18628 (the rows are cells and the columns are the days of precipitation). Thus, the spatial resolution of the resulted maps from interpolation is 3  To study the extreme precipitation in climatology, various definitions and absolute or relative indexes (the index of curve area of particular precipitation and the index of percentile threshold) are presented (Mofidi, 2007). Accordingly, in the present study the percentile threshold of 90-95 and the percentile threshold of 95-99 were considered as the index of heavy precipitation, and the percentile of 99 and more were regarded as an extreme precipitation index (see Equation 1). Thus, the percentile threshold of precipitation for each cell in each day of the year was calculated in the study area using the MATLAB software. Next, the frequency and the average of the intensity of extreme precipitation were calculated for one up to five days persistence. The frequency of extreme precipitation events refers to the number of the days along with high percentile precipitation in different months. The sum of these frequencies in each month were calculated for the whole statistical period. The average of the intensity of precipitation refers to the amount of precipitation in time unit, mm per day (see Equation 2). Finally, for the purpose of modeling the long-term behavior of the extreme precipitation, linear and nonlinear regression models (35 models) were fitted data using the curve expert software. Regression analysis is a statistical technique for analyzing and modeling the relationship between variables (Bazargan Lary, 2006). Under normal and very simple conditions, the best line is determined by the coordinates of the points obtained from two variables x and y on one page. This kind of regression is known as linear regression. In most cases, the relationship between climate variables (here, extreme precipitation and time indexes) cannot be represented by a line. Therefore, nonlinear regression (logarithmic, exponential, and parabolic) is used to model relations. Non-linear regression is a method for finding a non-linear model to find the relation between dependent and independent variables. After fitting the pattern on the data, the significance of the coefficients of the regression equation was checked. For this purpose, the statistical value of t-student was investigated for the significance of regression coefficients. A model based on coefficients with a significant error of 0.05 was regarded as a fitted pattern. Then, by using the indexes of coefficients of determination ( ), the root mean square error ( ) was considered appropriate among the other fitted models. The coefficient of determination is dimensionless. The sum of squared deviations of the observations around the mean equals the total changes observed in the observations. Also, if we  consider equation 3 as the  squared error or unexplained changes by regression line (or curve), the ratio of these two represents the ratio of the unexplained changes to the regression line  in proportion to the total variation (Asakereh, 2011) In addition, the best value of the coefficient of determination is equal to one. The mean of the squared error represents the error rate of the model, the best value of which is zero and is calculated by Equation (4) (Karamoz. 2006) In the above relations, o and p are respectively the observed and predicted values, and n is the number of data. The threshold of the percentiles examined is 90-95 and 95-99 percentiles for heavy precipitation and  the  percentile  99  and more is for extreme precipitation that have been widespread, the frequency and the average precipitation intensity is considered as independent variable, and time is considered as a dependent variable. At 95% confidence level, the optimal models for each of the high extreme precipitation indexes (i.e. frequency and average intensity) were fitted and evaluated.

This study examines the persistence of frequency and the average intensity of precipitation of extreme precipitation in the Caspian region from 1966 to 2016 based on the thresholds 90-95, 95-99, 99 and more through the linear and non-linear regression model.  The low correlation between dependent and time variables, and consequently the low coefficient of determination among variables, the low variations in these two variables and the high errors of the model based on   indexes show that regression model does not fit the data.

Few studies have been carried out on extreme precipitation in the Caspian Region, these studies have mostly applied synoptic approaches (e.g. Halabian et al., 2011, 2016; Mofidi et al., 2007; Sleigheh, 2016). Here, the frequency and the average of the intensity of extreme precipitation in the Caspian Region have been studied from 1966 to 2016 based on the thresholds 90-95, 95-99, 99 and more. Due to the low correlation between the dependent variables and time, the very there was a low coefficient of determination found between the variables, and the variation of these two variables was found very low.  Despite the significant trend in the observations which has been empirically deducible and tangible within the recent years, the regression patterns have not been able to justify these changes. Therefore, it seems that these patterns do not have the ability to justify the trend of observations in this field or in many others. Thus, two types of evaluation techniques including the analysis of observations based on probability knowledge and random process, as well as the study of observations through artificial intelligence techniques (e.g. artificial neural networks) can be recommended for such observations. Therefore, the probabilistic analysis of observations and the use of artificial neural networks are suggested as methods for evaluating trends in observations.

In this research, the ecological indicators and sustainable development dimensions in the city of Chenaran have been evaluated and the data analysis tool are the Emergy method. Indicators such as renewable, non-renewable, fuel and products have been used, and then Chenaran City has been examined in terms of different dimensions of Emergy (intensity, structure, efficiency and environmental pressure), which is used to examine the severity from Emergy's density and per capita, in Emergy's review of the structure, Emergy flows from renewable sources compared to energy and material imports, as well as self-sufficiency and process efficiency, Emergy fuel and electricity, and ultimately to show environmental pressure and Sustainability Indicators (ESIs) are used to combine all factors and currents that are EYR to ELR (Emergy Performance to Environment Load), as well as Capacity Capacity Tolerance Based on Renewable Emergy.

research

This research is a Quantitative research. The information obtained from various sectors (ecological indicators) includes renewable resources (R), non-renewable resources (N), materials (G) and fuel (F), which are indicators presented by Odum. Using the Emergy method, it was measured and then analyzed and analyzed in four dimensions (Emergy intensity, structure, efficiency and environmental pressure) and its subcategories and related formulas.
Emergy calculation

Calculating Emergy using the thermodynamic basis of all forms of energy, resources, and human services that converts them to the equivalent of a form of energy, usually Emergy Solar. To evaluate a system, and also to organize the assessment and account for all inputs and outputs, a table is to be drawn from all the assessment flows, including actual flows of resources, labor, and energy. And then the final step of the Emergy Assessment is an interpretation of quantitative results. In some cases, an assessment is conducted to determine the status (appropriate or inappropriate) of an environmental development plan, and sometimes evaluation may seek to make the best use of resources to maximize Be a curiosity. Emergy assessment is both quantitative and analytical. Emergy approach evaluates complex systems and ultimately analyzes public policy and environmental management issues (Silvert, 1982). An Emergy flow defined by the current energy of a type that is used directly and indirectly in a service or product and its unit is Sej. As a result of the effective factors, the position variables and other system features can be converted to a normal metric unit, solar emergy. With the definition of Emergy Emk, the flow k obtained from a process is given below:Emk = ∑iTriEi , i= 1,2,….,n   (1)Where Ei is the actual energy content of the independent flow of i into the process and the Tr, corresponding transformation (correspondence) of the input current i, which has already been estimated.
After the table is prepared for the evaluation of all inputs, the Emergy unit value of the product or process is calculated. The output, for the first unit of energy, is evaluated, and then the Emergy input and the energy unit value are calculated by dividing the Emergy by the output units. The unit values that yield the result for any evaluation are also useful for other Emergy evaluations. Therefore, Emergy evaluations generate the values of the new Emergy unit (Skibaba, 2010).

Chenaran city status assessment was carried out at the level of four main indicators (Emergy intensity, Emergy structure, Process efficiency and Environmental pressure). Each of the above is derived from the measurement of the sub-indicators calculated and analyzed by the Emergy method.The calculation and measurement of Emergy are shown in the following four dimensions:Emergy Intensity The total consumption of Emergy in the city of Chennan is 2.81e + 21 (sej) according to the calculations made in the study year. Emergy density and Emergy density were used to evaluate the severity of Emergy. Results were 3.81e + 15 and 5.75e + 16, respectively. Emergy density and capability play important roles in urban system operations.
Emergy structure Emergy structure is critical to the sustainability of the area, given the rapid expansion of urbanization. Emergy is needed to maintain the observed structure of the two main sources of the natural environment and the use and import of fossil fuels and commodities from other economic organizations, and according to information obtained, Emergy flows from renewable sources compared to energy imports. And the material is relatively small. Although the city is not very extensive and industrial, it is a sign of the imbalance of currents in the urban system. The portion of renewable resources is 7.48e + 16, which is lower than non-renewable resources, indicating that living systems in the region are heavily dependent on non-renewable resources and, of course, the diversity of urban performance. It also cannot be ignored. Another indicator related to the Emergy structure is self-sufficiency ratio. According to the calculations carried out by Chenaran, self-sufficiency rate declines. Because high self-sufficiency level indicates good situation and low self-sufficiency level indicates adverse situation and Chenaran city with low self-sufficiency rate is 4.63e-3 or (0.046) and this fact indicates non-renewable and current resource flows. It also shows an increase in Emergy fuel coming into the city and less use of local resources. The use of fossil fuels has a major impact on the structure of Emergy and the city. Process efficiency Two indicators related to process efficiency are the use of Emergy fuel and electricity. To investigate the systematic functioning of the city. Fuel and electricity play a crucial role in urban development, and the intensity of these indicators can affect productivity. As the results show, the fuel and electricity used in the city of Chenaran are generally at a relatively high level, although the factories and industries in the city of Chenaran cannot be denied consumption of energy and consequently the use of fuels. And it has increased electricity in the city of Chennai and could cause problems in the future. And finally, based on the results of the calculations, it can be seen that the city during the process of industrialization and urbanization is seeking more productivity of resources and consequently their demands for resources also increase, thus causing damage to the Provides local resources and overuse of non-native and non-renewable resources. Environmental pressure To illustrate the environmental pressure in an ecosystem, it is important to discuss the pollution and overuse of non-renewable resources and the depletion of local and renewable resources. As mentioned earlier, the city of Chennaran has a high percentage of non-renewable resources and fossil fuels. It has intensified pollution and harmed the environment and ecosystem. The city's dependence on non-renewable resources and mass waste production adds to the environmental pressure. And, in fact, only fully and with respect to all different aspects of urban operations can we have a good overview and perspective of urban development with the concept of long-term sustainability.

It is important to pay attention to the principles of sustainable development, especially implementation and move towards becoming an ecological city. The results show that in four main indicators (Emergy intensity, Emergy structure, process efficiency and environmental pressure) Chenaran City Given that the situation is relatively stable in the present situation, but the orientation in the actions taken, it has been shown that activities in the environmental field were not in line with the idea of an ecological city and that fuel from material emergy flows. , Renewable and non-renewable resources, have been identified. To represent the environmental pressure and sustainability indices (ESIs) in an urban ecosystem, a combination of all factors and streams is used, which is the EYR to ELR ratio (Emergy function to environmental loading), according to the information obtained, The ELR indicates an imbalance between renewable and non-renewable resources used in a process, the low ELR indicating relatively small environmental loading, while the high ELR indicating excessive use and according to calculations performed In the city of Chenaran indicates an imbalance between renewable and non-renewable resources because the amount of non-renewable resources is greater than renewable resources The ratio of renewable to non-renewable sources is 7.48 e + 16 to 1.09e + 19, which, as a result of the available resources and fuels involved, is much higher than that of the available resources. Adds to the imbalance. Using the ESI sustainability index, one can examine the ecological risk assessment in urban ecosystems obtained by combining both socio-economic performance and environmental impacts, calculated from the EYR and ELR ratios. , And measures the output of a system, relative to environmental pressure.The EYRs obtained in the city of Chenaran are 1.05 and ELR3.76e + 04 which indicate the stability (ESI) of the two together, the ESI obtained in the city of Chennar is 2.79e-05 and Emergy performance ratio is lower than environmental loading due to environmental pressure due to the use of non-renewable resources and high fossil fuels, which also have a direct impact on sustainability and lower the level of sustainability in the region. That is, of course, the growth and expansion of the city and the construction that has taken place, making more use of local resources and, consequently, reducing sustainability.
For this reason, policies such as turning a city into an "ecological city" and its related indicators and standards that pay close attention to the environment and environmental issues can provide an environment with high tolerance capacity