Journal of Spatial Analysis

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evapotranspiration is one of the most important components in water balance and management. In this research, to evaluate the effects of climate change on the amount of potential evapotranspiration in the southern part of the Aras River Basin using the downscaled data of the GFDL-ESM2M model in the CORDEX dynamic downscale under the RCP8.5 scenario during the period of 2021-2050 and its comparison. It is treated with the values ​​of the base period (1985-2005). Data with a horizontal resolution of 22 x 22 km from the GFDL-ESM2M model were used in this research. The findings of the research showed that the minimum and maximum temperature and, accordingly, the ETp of the future period will increase compared to the base period in all six studied stations of Aras Basin (Ardebil, Ahar, Jolfa, Khoi, Mako and Pars-Abad). The value of this minimum temperature increase is estimated between 1.4 and 3.8 ºC and for the maximum temperature between 1.7 and 2.2ºC. The range of annual ETp increase varies from 133 mm to 189 mm. In the monthly ETp scale of all stations from January to July with an increase between 3.9 and 1.64 mm and from August to December with a decrease of 0.7 to 38.2 mm. Estimating the increase of ETp in the future period in the basin, especially in the months of spring, which is very important in terms of water demand, requires special attention to the possibility of this estimated increase in the planning of the water and energy sector.
 

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Climate is one of the determining factors in the quantity and quality of agricultural products, therefore, in this study, the relationship between precipitation and temperature (as explanatory variables) with rice yield in 40 cities and wheat yield in 30 cities (as dependent variables) was investigated in the Caspian coastal area during 2000-2017. Spatial statistical analyses were performed with using the Moran autocorrelation test and geographically weighted regression. Based on the results (Moran index, z = 0.4342121 for rice and z = 0.719571 for wheat, respectively), it was revealed that the spatial distribution pattern of rice and wheat yield had a cluster pattern. The results of the geographic weighted regression analysis showed that the temperature increase was more desirable than the precipitation increase so the increasing temperature could lead to yield increases. In the eastern parts of the study area, the positive effect of precipitation on rice yield (with 0.020 to 0.540 regression coefficients) was remarkable; the results also revealed a negative relationship between temperature and rice yield in the southeast and eastern parts and a positive effect on rice yield in other areas. Also, the effect of precipitation on wheat yield was negative in the west and central parts of the study area (with -0.481 to -0.871 regression coefficients). According to the results, a negative relationship was dominant between temperature and wheat yield in the east and southeastern parts of the study area and a positive relationship was detected in other areas. Finally, the results indicated that in the western and central parts, due to heavy rainfall and a low number of sunny hours, an increase in temperature is more favourable than an increase in rainfall. In the eastern and southeastern regions of the region, where the amount of precipitation is lower than the threshold required for rice and wheat, an increase in precipitation is more desirable.

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Introduction
A flood is a natural disaster caused by heavy rainfall, which causes casualties and damage to infrastructure and crops. Trend of floods in the world increasing due to climate change, changing rainfall patterns, rising sea levels in the future, and in addition, population growth and urban development and human settlements near river have caused floods to become a threat to humans. One of the most important and necessary tasks in catchments is to prepare flood risk maps and analyze them. In recent decades, researchers have been using remote sensing techniques and geographic information systems to obtain flood risk maps in an area. Due to the numerous floods that have occurred in the Neka river catchment, it is necessary to conduct a study entitled zoning of flood sensitivity in Neka river catchment for more effective management in this area.

Materials and methods
Study area: Neka river catchment area with an area of ​​1922 Km2 is part of Mazandaran province in terms of political divisions. This basin is between 53º 17´ 54 º44´ east and 36 º 28 ´to 36 º 42´ of north latitude. The highest point of the basin is 3500 m (Shahkuh peak) and the height of the lowest point of the basin in the Ablo station is about 50 m and at the connection to the Caspian Sea is -27 meters. The seven sub-basins of this basin are Laksha, Golord, Burma, Metkazin, Kiasar, Alarez and Sorkh Griyeh. Geologically, the basin is mostly of calcareous and marl formations. In the south and southwest of Neka River, the rock material is mostly clay and calcareous marl, which makes this basin has a high erosion potential
To study the flood zoning of the area using a multi-criteria decision model, 1: 25000 maps of the surveying organization and a digital elevation model with a resolution of 12.5 meters (Alos Palsar) were extracted. In order to study the flood risk in Neka river, 4 criteria of height, distance from the river, land use and slope have been used. In the present study, modeling and preparation of flood risk zoning map in 4 stage including descending valuation, normalization of each class, normalized index weight and integration of criteria has been done by the following linear weighting method. Performing linear weighting operations depends on the weighted average of a number of selected parameters in the opinion of the expert. According to the weight assigned to each criterion based on the expert opinion, each of the criteria was multiplied by the assigned weight and at the end the criteria were added together and the final zoning map was obtained.

Results and Discussion
In this study, using a multi-criteria decision-making system model, a flood risk zoning map in the Neka river catchment was prepared. According to the weight assigned to each criterion based on expert opinion, the final risk probability map has a value between 0.02 to 0.2, which is ultimately divided into 5 classes in terms of flood risk. Value range 0.02 to 0.06 component of very low risk zone, range 0.08 to 0.11 component of low-risk zone, range 0.11 to 0.13 component of medium-risk zone, range 0.13 to 0.16 component of high-risk zone, and finally domain 0.16 to 0.20 components of the area with very high risk potential have been obtained. According to the final divisions in the flood risk zoning map of the catchment area, a safe area means areas where the probability of flooding is very low and close to zero, and in contrast, the area with a high and very high risk potential for flooding has the probability of high-risk floods. According to the final flood risk zoning map, about 982 Km2 (51%) has high and very high vulnerability, as well as about 510 Km2 (26.69%) has medium vulnerability in Neka catchment area.

Conclusion
The results obtained from the model indicates that the highest risk of flooding points are located in the western parts of the Neka catchment area and the end of the catchment area that reach the city of Neka. According to the research findings, the most important factors in increasing the risk of floods were the slope in this area and the distance from the drainage network. According to the results of the model, a large area of ​​the basin is a component of high risk zone, that means the Neka river watershed has a high potential for floods. Evidence and documented reports show that the Neka river Basin has experienced several floods in the last two decades. The major part of the occurrence of floods is due to the natural conditions of the basin, thus it is necessary to reduce flood damage by changing the locations of various land uses based on flood vulnerability maps. Using multi-criteria decision making method can be used to prepare flood risk zoning maps in basins that do not have hydrometric data; It is also a more cost-effective method in terms of time. One of the important issues in the final result of this model is due to the weight of the layers, which should be used by experts, who are familiar with the region and this method and adapt to field evidence.

Keyworlds: Flood, Multi-criteria decision making system(MCDA), Hazard zoning, Nekarod, Natural hazard.



 

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Introduction
Soil erosion is the process by which soil particles and components are separated from their main bed by an erosive agent and transported to another location. In the soil erosion process, there are three distinct phases: 1- separation of soil particles, 2- particle transfer and 3- sedimentation of transported materials. In water erosion, the erosive factors are rainfall and runoff. Erosion and the consequent reduction of soil fertility are among the issues that make it difficult to achieve sustainable agricultural development and environmental protection. It is important to study the quantity and quality of erosion in the country's watersheds and to prevent the loss of one of the richest and most valuable natural resources of the country, namely soil, and to fight against this process. (Tabatabai, 1392). Therefore, to calculate the rate of erosion and sediment production in most watersheds of the country that lack statistics or lack of statistics, the use of experimental models to estimate erosion and sediment is required. According to what has been said, the present study was conducted based on the following two main objectives: 1- Estimation of erosion and sediment in Adineh Masjed watershed, which is one of the main sub-basins of Kamal Saleh Dam, using EPM and MPSIAC experimental models and 2- Investigation and comparing two models and choosing a better model for similar regions and climates.

Materials and methods
Adineh Masjid watershed is one of the sub-basins of Dez and the main sub-basin of Kamal Saleh dam. Temperature, isotherm, geology of the area, slope and available information were performed and finally, by interpreting the photos, types, land units, current land use were determined and updated with field control. For a more detailed study, first, according to the condition of the main waterway and changes in the appearance of the land and vegetation and new land material, the ridges separating the basin were divided into 15 sub-basins. In EPM model, four watershed erosion coefficient (Ψ), land use coefficient (Xa), rock and soil susceptibility coefficient to erosion (Y) and average basin slope (I) and in MPSIAC model, nine geological, soil, climate factor (Climate), runoff, slope, vegetation, land use, current erosion status and waterway erosion are examined. Each model was scored according to data analysis and digital images and then placed in the relevant formula. Finally, the amount of erosion and sediment in the basin was estimated and the sedimentation class of the area was determined.
Results
To determine the score of nine factors affecting soil erosion using MPSIAC method and the four factors of EPM model, each of the factors affecting erosion in units were analyzed. Finally, by weighting, the points of each factor in the models were calculated. The degree of R deposition from the sum of the nine factors of MPSIAC model and the degree of Z erosion was obtained by combining the four EPM factors. Then, the amount of sediment production and erosion in the field of relationships related to each model was calculated and compared and analyzed. In MPSIAC model, the amount of specific sediment (M3 / Km2 / year) was calculated as 112.713 and the specific erosion (M3 / Km2 / year) was calculated as 375.71. In the EPM model, the amount of specific sediment (M3 / Km2 / year) was calculated as 213.95 and Specific erosion (M3 / Km2 / year) was calculated to be 395.86.

Discussion and conclusion
The results of sediment and erosion estimation were estimated separately for each sub-area using two models and it was found that the two models are somewhat relatively compatible with each other. The results of MPSIAC model, have more accuracy and reliability, and therefore the results of the MPSIAC model can be used to estimate the amount of sediment entering the Kamal Saleh Dam. However, due to the small distance between the results of the two models, if we do not have access to MPSIAC model data in similar areas, the EPM model can be used with less data and more easily accessible. It was also observed that in the upper and entrance parts of the basin, where the slope is higher and the vegetation is less, the amount of sediment production and erosion is higher in these areas. So that the upper parts of the basin are in the medium erosion class and the rest of the basin is in the low erosion class.

Keywords: watershed, erosion and sediment, modeling


 

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Changes in the hydrological response due to climatic parameters and human induced activities can be derived from indicators based on the analysis of flow duration curves. The purpose of this research is to determine the flood and the low flow parameters using the flow duration curves. The trend detection technique can be used as a useful tool in deterimining the temporal changes of the different hydro-meteorological parameters. The river gauge stations of the Ardabil province were used for the analysis of high and low flow occurrence in this study. The spatial variations of the flood events can be used as a preliminary guideline for the prioritization of the watershed in the vulnerability assessment and management-oriented measures. Also, the assessment of low flow condition is a useful tool in the allocation of environmental flow allocation and utilization of river surface water resources.
Methodology:
In this research, temporal and spatial changes of Q₁₀, Q₅₀, Q₉₀, Q_90/50 and Lane indices in 31 hydrometric stations of Ardabil province during the period from 1993- 2014 were evaluated. The flow duration curve of each river gauge stations was derived. The flow duration curves also were plotted based on the dimensionless flow divided by the mean discharge and the upstream area of each river gauge station. Also, the temporal variations of the of Q₁₀, Q₅₀, Q₉₀, Q_90/50 and Lane indices were analysed using non-parametric Man Kendall trend test. Then the significant level of upward and downward trend directions were determined. In this study, the results of 5 river gauge stations were presented as example based on the the river flow ranges, which includes low, medium and high river flow discharge (Hajahmadkandi, Nanakaran, Shamsabad, Polesoltani, and Booran).
 
Results:
Based on the results, the trend of Q₁₀ (Flood flow index) was significant at the stations located on the main trunk of the Qarehsou river. Meanwhile the Q₅₀ (average flow index) has a significant decreasing trend in most of the studied river gauge stations. In addition, Q₉₀ and Q_90/50 indices have a significant decreasing trend in most stations. In addition, Q₉₀ and Q_90/50 indices had a significant decrease at (p<0.05) regarding the Lane index as a flood related indicator in the Arbabkandi and Dostbeglo stations, which are affected by the dam construction there is a significant decreasing trend.
Conclusion:
I summary, the values of flood flow index in the upstream rivers of the Ardabil province had a increasing trend.

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Abstract
During the recent decades the discipline of geography has lost its priority and position to some degree in Iran. Most of the graduates could not enter into the work in the universities and other organizations. The human-environment system, the main area of geographical specialty - has experienced many crises and hazards among which the global warming and climate change being the most destructive.  This means that the ongoing curriculum is not working well and needs to experience a fundamental change. To implement this operation some points should be cleared out: The hazardous condition of the world and especially Iran, the education history and state of geography in Iran, and the relation between geography and sustainable development of the world. The discipline of geography has changed its approach according to the circumstances of each period several times. For example, at the beginning of the twenty-century due to the dominance of the environmental determinism, the dominant approach of geography was the relation between man and environment. But since the 1970’s the earth has encountered with different hazards and crises to the extent that it is named as the period of Anthropocene. Accordingly, the dominant approach of geography during this Anthropocene era is to identify and solve the hazards and crises and lead the man- environment system towards the sustainability as once was requested by the secretary general of the United Nation.  In this regard the geography should adopt the sustainable development concepts and goals. For this reason, the geography of Iran should make a switch from its very specialized approach to a relatively wholistic view and pay more attention to the human- environment paradigm. To implement this order, the following assumptions should be considered.

1. The applied objective of the discipline should be defined as “locating the suitable place for the living and activities of man without endangering the sustainability of the natural environment.  This objective is not clear at the present curriculum. Defining this objective will clearly show students what is their job after finishing the career.
2. The main vision of geography education is the creation of the sustainable geographical space or environment.
3. The research approach is problem solving. Because most of the laws and concepts are identified and defined. Due to the hazardous nature of the earth system geographers should identify the problems and research to solve them via geographical thought and knowledge.
4. The terrestrial unit for working is region. This is very important concept in geography. We cannot prescribe one sustainability procedure for all of the world. But we do one for each region. When regions became sustainable, all the world will be sustained.
5. In any region the hazards and crises will be identified and described through the spatial analysis methods and will be conducted towards sustainable human – environment system. This monitoring is composed of the stages of spatial analysis, spatial planning, and spatial managing.
6. All of the geography subjects and materials are necessary for sustainable development goals. The only criteria will be added is the environmental ethics in all of the geography activities and applications.
7. Instructors and students should be familiar with the techniques of integration and multi-dimension modelling.
8. All geography graduates will respect the nature and its resources and should consider the environmental ethics during their academic career. They should be able to identify and solve the environmental problems through the geographical thinking. Geographical thinking means asking geographical question, gathering geographical data, processing the data with geographical (spatial) methods, and presenting the results in the geographical forms, i.e., maps. All the graduates should be creative and critical and should have the power of scientific challenging and discussions.
9. Geography is one independent and overarching discipline and we will offer only one total geography in bachelor level. The master career can be specialized according to the applied objectives of the societies. The doctoral program is also one integrated discipline. The specialty of graduates will be defined according to their dissertation.
10. The subjects include the fundamental courses such as physical geography and sustainable development, regional courses such as the human geography of Iran, technical courses such as remote sensing, GIS, and statistics, the applied courses such as evaluating the natural resources, and so for. The students with any high school background should pass all the courses with high quality so that after graduation they have the potential to analyze the human- environment problems and recommend the required solutions.

Key words: geography curriculum, sustainable development, geography of Iran, twenty first century, environmental ethics, geographical thinking, Geography and sustainable development.

 

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Abstract
Many villages in the country are faced with a series of dangerous factors and elements due to their location and settlement method, the most important of which are natural disasters such as earthquakes, floods, landslides, subsidence, rockfalls, avalanches and snadstorms. A set of biological, environmental, social, economic, and physical factors and processes can also increase the level of risk and vulnerability of villages.. Therefore, it is necessary to take steps to reduce the effects and consequences of accidents by using scientific methods of crisis management based on risk management. Experience shows that the huge costs of reconstruction after disasters can be reduced with prevention, prediction and preparation and according to the sixth development plan, 30% of villages and 20% of the border villages must be secured. The current plan is carried out referring to the sixth development program (clause 8th of article 27th) with the aim of securing villages exposed to the risk of natural disasters in order to identify the villages with the characteristic of being exposed to natural hazards, prioritizing and presenting suggestions regarding how to reduce the risk at the villages are exposed the risk of natural disasters in cooperation with the Islamic Revolution Housing Foundation and the National Disater Management Organization. The priority natural disasters in this plan are: floods, subsidence and sinkholes, earthquakes, sandstorm and slope movements (including landslides, rockfalls, creeping and mudflows) in rural areas. At first, a list of villages at risk of natural disasters was prepared and reviewed through inquiries from provincial disaster management and housing foundations. This project was based on appropriate models and methods and with using of disaster risk zoning maps, screening and selecting the list of villages that are more at risk than others  and by combining risk assessment indicators and criteria with environmental, physical, demographic indicators and risk incident records, the villages with the first priority of risk are extracted separately for each province, and then the results of this stage were checked for accuracy in a collaborative process with related organizations at each province and the project entered the phase of field collection and providing implementation solutions. In this plan, out of 48,857 villages with more than 20 households across the country, about 9,000 villages are at risk with high risk categorized in 5 classes and 1,418 villages across 31 provinces with the first priority visited after verification, in order to local check and providing solutions for risk reduction. These villages were visited by experts from different fields and detailed risk assessment was done. In order to obtain the same and comprehensive information by the referring experts for the field visiting, field evaluation forms were designed with a multi-risk management approach.
 The results of the field visits and the proposed solutions were prepared separately for each village according to the environmental characteristics with the aim of reducing the risk and securing and presented to the Islamic Revolution Housing Foundation, the Disaster Management Organization and the Program and Budget Organization. Also, by designing and establishing a spatial information system for monitoring and evaluating rural settlements at risk, on the web-GIS platform (WEB GIS) at the same time as visiting the mentioned villages, the information collected according to the field collection forms was loaded into the system and according to the characteristics This system, such as designing in the Oracle environment, defining the access level for different stakeholders from national to local levels, the possibility of updating information, having different modules, reporting, spatial analysis of risks and producing thematic and combined maps, it is possible to use this system as a decision support system in all stages of crisis management, before, during and after the disaster, at the country level. Increasing and completing the required information in analyzes related to risk assessments, simultaneously with entering the information collected during field visits, as well as updating the information, will lead to an increase the empowerment of the society regarding the risk management of natural disasters and an increase Speed and accuracy in the analysis of the effects, management decisions and as a result reduce the costs of reconstruction and rehabilitation. It is worth mentioning that in order to create the ability to register information collected online, the mobile application system of rural settlements at risk was also designed and operated.

Key words: villages at risk of natural disasters, immunization,identification, prioritization, webGIS

 

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1- Introduction
Desert dust is formed under the influence of the special weather and environmental conditions of desert areas, enter the atmosphere. Localized hurricanes caused by ground air instability and sweeping dry deserts clear silt and sand particles enter the atmosphere from the surface. Ecologically as well as physically desert dust Effects such as pulmonary heart disease, disruption of plant physiological circulation, and erosion of growing structures include heavy metals deposited on soil surfaces, water surfaces, and canopies Plant surfaces that cause chemical changes and physiological damage to environmental ecosystems. Difficult Metal generally refers to a group of metal elements with a specific gravity of 6g/cm3 or more. Atomic weight greater than 50 g. Heavy metals important from an environmental point of view Cadmium, arsenic, cobalt, vanadium, zinc, mercury, iron, manganese, nickel, lead, chromium, copper, that do not decompose naturally. In addition, the long life of heavy metals is also considered. In the studies that have investigated the effect of dust on citrus fruits, it has been very few and even garden plants have been done on a case-by-case and limited basis. Citrus and especially oranges are one of the important and economic garden products in Iran, which are cultivated in tropical areas with mild and cold winters. Khuzestan plain, especially Dezful, is one of the poles of citrus and orange cultivation. But in Khuzestan, it is under the influence of many environmental stresses, which can be mentioned as drought stress and air pollution in the region. The rising trend of the phenomenon of desert dust in recent years has been shown as a danger and its effect on the environmental health and economy of the region is very severe, and the most damage has been reported to the agricultural sector. Although the damage caused by micro-pollens to the agricultural sector is expressed as an economic figure, the effect on plants, especially citrus fruits, remains unknown. Although researchers have studied the effect of fine dust on sugarcane, grapes, legumes, nectarines and peaches in Iran, India and Pakistan, the effect of fine dust on vegetative traits and orange fruit has not been investigated in Khuzestan. Considering that the first step in controlling the effect of air pollution on plants and horticultural crops is to know how it affects the plant, on this basis, the main goal of the current research is to reveal and evaluate the effect of micro-pollens. Desert is on vegetative and reproductive characteristics of Thomson orange in Dezful.


2- Methodology
In order to evaluate the effect of desert pollen on the quantitative and qualitative yield of orange fruit, Thomson variety, a field experiment in the form of randomized complete block design with four treatments and three replications was carried out in Dezful in 2018-2019. The treatments included 1) road dust and desert fine dust, 2) desert fine dust, 3) washing after the occurrence of fine dust and 4) control away from fine dust. The chemical and functional characteristics of the trees were measured after applying the treatments, which included chlorophylls a and b, relative water content of the leaves, number of fruits, diameter and weight of the fruit, soluble solids of the fruit and the final yield of the tree.

3- Results
The results showed that chlorophyll a decreased by 21% and 11%, respectively, in the road dust and desert fine dust treatments compared to the control. Chlorophyll b also decreased to the same amount compared to the control. The diameter of the fruit also decreased by 20% in the desert dust treatment compared to the control. The number of fruits per tree also decreased by 22 and 20% in the treatments of pollen and fine desert dust compared to the control. In the product yield of each tree, in the treatments of road dust combined with desert fine dust and the second treatment, which was only desert fine dust, it decreased by 22 and 17 percent, respectively, compared to the control. Tukey's mean comparison showed that the difference of all quantitative and qualitative characteristics between the treatments was significant and Desert dust has a negative and decreasing effect on the yield of Thomson orange trees; However, washing the trees after the occurrence of micro-pollen removed the effects of micro-pollen on the performance of trees and it even increased compared to the control; So, washing increased the yield of oranges by 40, 35, and 12 percent compared to the first and second treatments of road dust and fine dust, as well as the control.

4- Discussion & Conclusions
Plant growth cycle and biochemical interactions of plants show different reactions under the influence of environmental stresses. The results of previous studies indicated that fine dust and dust storms have been identified as an environmental stress for plants that have a negative effect on grapes, medicinal plants, sugarcane, nectarines, peaches and legumes. The effect of fine dust on the plant can be investigated in several characteristics and periods of plant phenology. In the first stage, the deposition of desert fine dust on the leaves of the plant causes shading and reducing the light received by the leaf pigments. Fruit formation is the most important phenological period of the plant, and the occurrence of environmental stress can affect the yield and products of the plant. The present research showed that the number of fruits in orange trees showed sensitivity to desert pollen and the settling of soil particles on orange flowers reduced the amount of fruit formation and finally the number of healthy and ripe fruits in the trees treated with road dust and Desert fine dust decreased compared to the control. Finally, the yield of control orange trees decreased by 17% and 22%, respectively, compared to desert dust and road dust treatment with desert dust. The yield of cotton plants in China decreased by about 28% compared to Desert dust. It can be concluded that although desert dust and road dust reduce the yield of Thomson orange fruit, washing it compensates for the damage and will be economical from the economic point of view.

Key words: Citrus, Photosynthetic pigments, Fruit yield, Dust, Dezful

 

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Abstract
Introduction and issue: In today's century when the effects of climate change on different sectors are undeniable, investigating and analyzing the behavior during dry spells is always of special importance and basic priority. On the other hand, the occurrence of extreme events such as precipitation can accelerate the occurrence of climate change. In Iran, rainfall is one of the basic variables for evaluating the potential availability of water resources, but its temporal and spatial distribution is very uneven. The change of dry Spells depending on precipitation always have different fluctuations in different seasons of the year. It seems that this is due to the inherent behavior of precipitation, which generally shows itself as an unstable and unruly variable. This feature causes changes and differences in the temporal and spatial distribution of precipitation in arid and semi-arid regions such as Iran. This inconsistency will face fundamental challenges to regularize dry spells on a seasonal and monthly scale. With a detailed understanding of the behavioral mechanism of dry spells, it is possible to know more precisely the climatic condition of different regions in order to plan in sectors such as; Water resources, agriculture, health, transportation and etc we able to do basic and preventive measures compatible with climate change. It is hoped that this research and related studies will be a positive step towards a more accurate understanding of the climate and its behavior in different seasons of the year.
Data and method: In order to investigate the seasonal behavior of the duration of dry spells, we used daily precipitation data for 44 synoptic stations of Iran and a 30-year statistical period (1988-2018). To reveal the behavior of dry spells, the precipitation data after validation and temporal integration were classified on a seasonal scale.
After the statistical integration of the data, dry spells related to precepitation were extracted and long-term periods lasting more than 20 days were the basis of the study. In the next step, to determine the seasonal weight of courses was used, the step-by-step evaluation method of Swara's fuzzy-numerical logic (SWARA). Thus, in the first step, the longest and most frequent periods are sorted based on relative importance. In the second step, the initial weights of the courses are determined, and in the third and fourth steps, the final and normalized weights of the courses in different seasons are determined, and unrealistic results are removed from the final analysis for proper explanation.
Findings and Results: The effectiveness and weight of each of the criteria with the Swara method in the fuzzy environment showed that in the western and northern regions of the country, winter and spring seasons and criteria such as reversibility and percentage of probability of occurrence have the most initial weight in explaining the periods. In the final explanation, these two season,s had a high weight. These two seasons explain more than 65% of the weight of courses in these regions. In the southern regions and parts of the center (Isfahan, East Fars and West Kerman), winter and autumn explain more than 71% of the weight of periods. Among the criteria explaining the weight of the courses, the reversibility criterion and the probability of occurrence have taken more than 55% of the weight. The northern and humid regions of the country vary in criteria from periods such as; Reversibility, continuity and probability of occurrence are more apparent and this indicates that the border of dry areas in the future of Iran's climate will move towards northern areas. It can be acknowledged that the behavior of long-term dry periods is more a function of two criteria of reversibility and probability of their occurrence. The weighting of the criteria affecting dry periods showed that the return period and the continuation of periods in the cold seasons of the year in dry areas have a more irregular behavior than in wet areas and have more weight in explaining the periods. By determining the weight of seasons in explaining dry periods, we can have better planning and management in related sectors such as water and agriculture.

Key words: dry spells, weighing, precipitation, climate, Swara method, Iran.
 

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Introduction:
The growth rate of urbanization during the recent decades of metropolises has had many destructive effects on the urban environment, among which we can mention the change of temperature of surfaces and local climates. The increase in the urban population, the rapid growth of industrialization and the increase in the concentration of pollutants in the lowest level of the atmosphere have affected the severity of the city's heat islands. Land surface temperature (LST) is a key variable to control the relationship between radiant, latent and sensible heat flux. Analyzing and understanding the dynamics of LST and identifying the relationship between it and changes of human origin is necessary for modeling and predicting environmental changes. The heat of urban surfaces is affected by various characteristics of urban surfaces such as color, surface roughness, humidity level, possibility of chemical compounds, etc. In addition, the changes between LST in a city and its surrounding area are due to surface changes, heat capacity and topography. Since the surface temperature regulates the temperature of the lower layers of the atmosphere, it can be considered as a weather indicator and an important factor in the urban environment. Changes in land use by changing the features of the surface cover such as the shape of the constructed areas, the amount of heat absorption, building materials, surface albedo and the amount of vegetation lead to changes in the temperature of the earth's surface. Barren lands with soil cover, on the contrary, increase the surface temperature of the earth. Climatic characteristics at the time of satellite image imaging also play a role in the extent and intensity of urban cold islands, so that satellite imaging in the middle of hot summer days shows urban cold islands better. The innovation of the research is in the large area of the investigated area, which includes eight urban areas, in order to examine the pattern of temperature changes on a wider level.

Materials and methods
Considering the rapid development of urban and industrial areas in the Ardakan-Yazd plain in recent decades, this study aims to investigate changes in the surface temperature pattern using Landsat 7 and 8 satellite images for both winter and summer seasons. It was done in 2002 and 2019. In addition, the relationship between land use/land cover and surface temperature was also investigated. Geometrical correction of satellite images was done using topographic map 1/25000 of Mapping Organization and atmospheric correction using FLAASH method in ENVI software. Algorithms used to obtain land surface temperature for Landsat 7 images were single-window method and for Landsat 8 images, the Landsat Science Office model was used. Land use/land cover layers related to the years 2002 and 2019 were used, and central statistical profiles and LST distribution were extracted for pasture, agricultural land, blown sands, industrial areas, rock outcrops and cities. In addition to examining temperature changes in different uses, it is also possible to compare over time.

Results and discussion
The results of this study showed that the area of cold islands and thermal islands in winter and summer of 2002 is not much different, so that in winter 10.8 percent and in summer 10.4 percent of the area were cold islands and thermal islands in winter 9.02. It was 8.5% of the region in summer, while this difference is huge in 2019. Thus, 9.4% of the area in winter and 12.1% in summer are covered by cold islands, and thermal islands are 8.3% in winter and 1.6% in summer. Changing land use and increasing the size of urban and industrial areas and reducing agricultural land is one of the main reasons for the increase in cold islands. The survey of land use/land cover changes between these years showed that the extent of urban areas increased from 22,045 to 23,714 hectares, and industrial areas also grew by about two times, from 4,615 in 2002 to 8,187 hectares in 2019. However, during this period, the area of agricultural land has decreased from 1161 hectares in 2002 to 793 hectares in 2019. Also, the results show that the percentage of heat islands is higher in winter than in summer. The main reason for this can be the much less vegetation covers in the winter than in the summer, because the vegetation cover acts as a moderator of the earth's surface temperature. Cold islands are formed in the built-up areas in the winter and summer. From 2002 to 2019, the extent of cold islands decreased in winter and increased in summer, while the extent of thermal islands decreased in winter and summer. Also, the results of the validation section of the single-window method and the model of the Landsat Science Office in calculating LST showed that for both summer and winter seasons, Landsat 8 has a higher accuracy than Landsat 7, and the LST estimation model is based on the exclusive method of this The Landsat series of satellites (Landsat Office of Science model) has a higher efficiency than the single-window method.

Conclusion
The results showed that cities play an important role in changes in the temperature pattern of the earth's surface, and the phenomenon of urban cold islands is not exclusive to big cities in hot, dry and semi-arid regions, but also occurs in medium-sized cities. The temperature variability of eight cities located in the Ardakan-Yazd plain with the land use/cover of the suburbs also showed that the cities are colder than the suburbs in both winter and summer seasons. This study showed the role of vegetation in hot and dry areas in reducing LST and also provided evidence for the change in the degraded state of pastures in this area.

Keywords: Urban climate, Land use, Land surface temperature, surface urban cool island (SUCI), ‎ surface urban ‎heat islands (SUHI)‎


 

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Extended abstract
Landslide risk zoning is one of the basic measures to deal with and reduce the effects of landslides. Vernesara watershed is one of the areas where many landslides have been observed in different parts of it. In this research, in order to zone the risk of landslides using the entropy index, first the ranges of landslides were determined, then the effective factors in the occurrence of range movements were prepared in the ArcGIS software environment, and a landslide susceptibility map of the studied area was prepared. . The prioritization of effective factors using Shannon's entropy index showed that the slope layers, land use, surface curvature, topographic humidity index and topographic position index had the greatest effect on the occurrence of landslides in the region. Also, zoning landslide sensitivity with the mentioned model and evaluating its accuracy using the ROC curve shows the very good accuracy of the model (79.6 percent) with a standard deviation of 0.0228 for the studied area. The zoning map shows that the low-risk areas cover only 13% of the area and more than 56% of the area is in the area with high risk of landslides, which indicates the high potential of the area in the occurrence of landslides. . Construction at a distance from fault lines, waterways and the steep Asmari Formation and safety of communication routes are the most important measures to reduce the amount of damage caused by landslides in Vernesara watershed.
Key words: natural hazards, landslide, entropy, folded Zagros.
 

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Abstract
The aim of this study was to analyze the temporal and spatial nature of dust storms during the period 2016 to 2018 in Kermanshah Using the HYSPLIT routing model and the MCD19A2 product, the Modis sensor was performed in the Google Earth web engine.In order to route the origin of dust particles, the Lagrangian method of HYSPLIT model was used in 48 hours before the occurrence of dust phenomenon in Kermanshah at three altitude levels of 200, 1000 and 1500 meters.Findings from HYSPLIT model tracking maps indicate that the general route for dust transfer to the study area is the north-west-southeast route with the origin of the deserts of Iraq and Syria at three altitudes of 200, 1000 and 1500 meters. On June 17, 2016 and October 27, 2018, as well as the southwest-west route originating in Kuwait, Northern Saudi Arabia and part of Iraq on November 2, 2017.The results of the maps obtained from the MCD19A2 product of the Modis sensor, especially the maps of periodicity, cumulative concentration, spatial variation and the highest AOD map, show a high correlation with the routed maps extracted from the HYSPLIT model. In general, based on the findings of the maps extracted from the product MCD19A2, Modis sensor during the period 2016 to 2018 in Kermanshah, the central and eastern regions have always been more affected by dust storms than in other parts of the city. On average, they were more exposed to dust pollution than other parts of the city. In this regard, the final results show a high correlation between the actual PM10 data and the AOD values derived from the MODIS sensor.

Keyword: Dust, AOD, Modis, HYSPLIT, Kermanshah, Google Earth Engine
 

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Abstract
The continuous and expanding process of global warming, especially in the Asian region, has provided the conditions for increasing drought and the spread of desertification. Many deserts had ecologically balanced soil conservation conditions that until recently have become new sources of dust generation now. Numerous examples have occurred in Iran due to its special geographical location among some of the most important deserts in the world. Temperature anomaly (about 8º C) last winter in the Caspian Sea basin has created new dust sources for the southern coastal of the Caspian Sea. On 30-31 May 1400, dust emission was recorded in meteorological stations of Gilan province in terms of area and concentration. The implementation of HYSPLIT chemical backward models shows the emission of dust from the northwestern region of the Caspian Sea to the southern coastal of the Caspian Sea (Guilan province) for the first time with such intensity. The source and origin of this dust was identified in the Rhine desert in the northwest of the Caspian Sea. Continuous and unprecedented warming in the region and accompanied by strong north-south currents provided the conditions for the emission of this dust. Due to the origin of the emitted dust as well as the geographical and topographical conditions of the Caspian Sea basin, the level of this dust was assessed from the ground level to an altitude of less than 1500 meters. Analysis of synoptic conditions using NCEP / NCAR analysis data with 1 degree horizontal resolution indicates the establishment of high pressure air mass with a center of 1018 hPa on the northwestern parts of the Caspian Sea and the penetration of high pressure to the southern coastal areas of the Caspian Sea. Due to the appropriate pressure gradient and increasing wind speed, dust-producing springs are formed on the desert areas of the Rhine and with the dominance of the northern currents (south-south), the dust mass is sent to Gilan province.

Keywords: Global Warming, Dust emission, Russian Rhine Desert, Gilan.



 

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Investigation of the Temporal and Spatial Variation of Maximum Soil Temperature in Iran

Extended Abstract
Introduction
The study of soil temperature in different depths of soil is important in climatology, hydrology, agrometeorology and water resource management. Different depths has a different temporal and spatial soil temperature variation. It represents the regional ground temperature regime. Furthermore, due to its rapid response to environmental changes, soil temperature is one of the most important indicators of climate change. The increase in soil temperature because of global warming can promotes disasters such as drought by increasing the water demand of agricultural products during the plant growth period. The increase in soil temperature also have a various consequences, include increasing evaporation from the soil surface, soil salinity in susceptible areas, which can lead to a decrease in soil yield and failure in plant growth. Therefore, knowledge of soil temperature changes in different environments is very important in climate studies. The aim of the current research is to analyze the spatial and temporal variations of soil temperature at different depths from five to 30cm of the ground and to investigate the existence of any kind of increasing or decreasing trend at different climates of Iran.
Methodology
Hourly soil temperature data (depths of 5, 10, 20 and 30 cm) were used in this research for the period of 1998-2017. The soil depth temperature is measured three times a day at 6:30 am, 12:30 pm, and 6:30 pm local time (3, 9, and 3 p.m. UTC). These data have been received for 150 synoptic stations of Iran on a daily basis from the Iran Meteorological Organization (IRIMO). IRIMO monitored the quality of soil temperature for data entry, data recording, and data reformatting errors. Data availability, discrepancies, errors, and outliers were identified during the second stage.
At the first step, temporal coefficient of variation were calculated for available soil temperature time series from five to 30 cm depths of each station. For this purpose, the average of three daily measurements of soil temperature was calculated and then the temporal coefficient of variation was obtained. In the next step, trend analysis of soil temperature has been investigated using the non-parametric Mann-Kendal test. The trend slope was calculated using Sen’s slope for each station in seasonal time scale. Trend analysis has been done for all three observations of the day.
Results and Discussion
The studied stations show significant spatial patterns in the temporal variability of soil temperature. In all four investigated depths, from five to 30 cm, the northwest parts of Iran, and some parts of Zagros and Alborz mountain ranges have high temporal coefficient of variation. In contrast, the stations located on the southern coasts and southern islands had the lowest temporal variability. In warm and cold seasons (summer and late autumn to mid-winter), the spatial changes of soil temperature at different depths are lower than spring and early autumn. However, in the warm period of the year, the soil temperature experiences lower spatial variations at different depths. Spring and autumn seasons, as the transition period from cold to warm and warm to cold seasons, show the most spatial temperature variations in Iran. Detected trends do not have significant differences among the three observations of the day. Soil temperature Trend analysis at different depths showed positive values for two seasons of summer and winter over most of the stations throughout Iran. Extreme trends are more frequent in the summertime of Zagros and Alborz mountainous regions, while in the winter season the stations located at the southern latitudes of Iran have experienced the most positive trends. In the summer season, higher trends with 99% confidence are more frequent in the mountainous areas. These positive trends in soil temperature have occurred in all studied depths. The negative trend at different depths is a distinct feature of the autumn season, which is significantly more prevalent than other seasons throughout Iran. The analysis of soil temperature trends in different depths shows that values above 1 degree Celsius often occur in 5 to 20 cm deeps. The increasing trend of soil temperature in winter shows a greater spatial expansion, which is indicate increasing annual minimum soil temperatures and the increasing trend of Iran's soil temperature.
Keywords: Soil Temperature, Spatiotemporal Variations, Man-Kendal Test, Sen's Slope, Iran

 

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Spatial analysis of Iran's climate change from the point of view of sensible heat flux and latent heat flux by Bowen method

Halimeh Shahzaei; Ms.c student of Climatology, Departement of Physical Geography, University of Sistan and Baluchistan, Zahedan, Iran.
Mohsen Hamidianpour[1]; Associate Professor, Departement of Physical Geography, University of Sistan and Baluchistan, Zahedan, Iran.
 Mahsa Farzaneh; Ph.D Graduated. Climatology.



Abstract
Sensible heat flux and latent heat flux are among the variables that are closely related to temperature and humidity and show heat transfer on a surface. So, their changes can be considered related to changes in temperature and humidity. In this regard, the current research aims to analyze and reveal the climatic changes of Iran by examining the course of changes in sensible heat flux and latent heat and the ratio between the two. For this purpose, NCEP/NCAR reanalysis data including sensible and latent heat flux during the period 1948-2020 was used in Iran. Bowen coefficient was calculated from the ratio of these two heat fluxes. Interpolation methods were used for their spatio-temporal analysis. In addition, by using the non-parametric methods of Mann-Kendall and Shibsen, spatial and temporal changes were also investigated.  The first part of the results showed that, spatially, the Bowen coefficient is a function of latitude and roughness. And in terms of time, the lowest value corresponds to the month of January and the highest value corresponds to the month of July. The results of the second part show that the Bowen coefficient has a positive trend over time. Its upward trend indicates an increase in the dryness coefficient of the country. So that this situation can be seen in the positive trend and increase in temperature.
Keywords: climate change, Bowen coefficient, global warming, spatio-temporal analysis.

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Simulation of Zanjan temperature trends based on climate scenarios and artificial neural network method

Abstract
Severe climate changes (and global warming) in recent years have led to changes in weather patterns and the emergence of climate anomalies in most parts of the world. The process of climate change, especially temperature changes, is one of the most important challenges in the field of earth sciences and environmental sciences. Any change in the temperature characteristics, as one of the important climatic elements of any region, causes a change in the climatic structure of that region. The summary of the investigated experimental models on climate change shows that if the concentration of greenhouse gases increases in the same way, the average temperature of the earth will increase dangerously in the near future. More than 70% of the world's CO2 emissions are attributed to cities. It is expected that with the continuation of the urbanization process, the amount of greenhouse gases will increase. According to the fifth report of the International Panel on Climate Change, the average global temperature has increased by 0.85 degrees Celsius during 1880-2012. Therefore, knowing the temperature changes and trends in environmental planning based on the climate knowledge of each point and region seems essential. For this reason, the present study simulates the daily temperature (minimum, maximum and average) of Zanjan until the year 2100.

Research Methods
The method of conducting the research is descriptive-analytical and the method of collecting data is library (documents). To check the temperature of Zanjan city, the minimum, maximum and average daily temperature data from Hamdeed station of Zanjan city during the period of 1961-2021 were used. The data of general atmospheric circulation model was used to simulate climate variables (minimum, average and maximum temperature) using artificial neural network and climate scenarios in future periods. The output variables in this study are minimum, maximum and average daily temperature. Therefore, three neural network models were selected. For model simulation, model inputs (independent variables) need to be selected from among 26 atmospheric variables. Therefore, two methods of progressive and step-by-step elimination were chosen to determine the inputs of the model. In these methods, climate variables that have the highest correlation with minimum, maximum and average daily temperature were selected. By using RCP2.6, RCP4.5 and RCP8.5 scenarios, variables were simulated until the year 2100. Markov chain model was used to check the possibility of occurrence of extreme temperatures of the simulated values.

results
According to the RCP2.6, RCP4.5 and RCP8.5 scenarios and the simulation made by the neural network model, it is possible that on average the minimum temperature will be 3.6 degrees Celsius, the average temperature will be 3.3 degrees Celsius and the maximum temperature will be 2.7 degrees Celsius. Celsius will rise. The monthly review of the simulated data for all scenarios and the observed data of the studied variables shows that the average minimum, average and maximum temperatures in January and February, which are the coldest months of the year, will increase the most and become warmer. While the average minimum temperature in August, the average temperature in April and the maximum temperature in October will have the least increase. According to the simulated seasonal temperature table based on all scenarios, it was found that the average minimum, average and maximum temperature observed with the maximum simulated conditions were 6.9, 5.5 and 5.4 respectively in the winter season, and 3.3 in the spring season. 4, 2.3 and 3, in the summer season it increases by 3.3, 3.4 and 1.4 and in the autumn season it increases by 4.6, 4.5 and zero degrees. The frequency of extreme temperatures observed in all three variables of minimum, average and maximum temperature for the 25th and 75th quartiles is less than the number of occurrences of extreme temperatures simulated in all three scenarios. Based on this, all three variables will increase and there will be fewer cold periods. An increase in night temperature and average temperature in winter season and maximum temperature in summer season will occur more than other seasons. The difference between day and night temperature will be less in autumn and summer. Also, all seasons, especially the summer season, will be hotter and the occurrence of extreme temperatures is increasing for the coming years.

Keywords: climate scenarios, simulation, extreme temperatures, artificial neural network, Zanjan



 

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