Journal of Spatial Analysis

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Evaluation of the effect of particulate matter and vegetation on the formation of heat and cold islands in Tehran
Seyed Kamyar Mortazavi Asl: PhD Student in Urban Planning, Islamic Azad University, UAE
Dr. Navid Saeedi Rezvani: Assistant Professor, Department of Urban Planning, Faculty of Architecture and Urban Planning, Islamic Azad University, Qazvin, Iran
Dr. Mahmud Rezaei:  Associate Professor, Department of Urban Planning, Faculty of Architecture and Urban Planning, Islamic Azad University, Tehran, Iran

Abstract:
Global warming and the heat islands of cities are one of the biggest challenges in the world today. Cold islands is a word that stands in front of heat islands and refers to areas of the city that have lower temperatures than the surrounding areas. In this study, in order to investigate the factors affecting the formation of cool and heat islands of the city, it was first obtained by using Landsat image processing and using the single-channel surface temperature algorithm. Then to investigate the parameters affecting the land surface temperature changes; Criteria for changes in particulate matter and changes in vegetation were considered. The NDVI index was used for vegetation and the algorithm proposed by Saraswat et al. was used for the amount of particulate matter. According to the results, the highest-ranking neighborhood for heat islands were in Bustan, Shahid Bagheri township and the airport, respectively, and the lowest amount of cool islands were in Baharan, Niavaran and Darband, respectively. Pearson coefficient obtained from the relationship between surface temperature and vegetation was -21.29%, which indicates the inverse relationship between temperature and vegetation, as well as the amount of vegetation index in hot and cold regions. Regarding the relationship between land surface temperature and air pollution, the correlation between these two parameters was equal to 19.31% and comparing the pollution index in areas with cold and warm islands showed that there is a significant relationship between reducing air pollutants and cold islands but the opposite is not true.

Keywords: Cool Islands, Tehran, LST, Air Pollution

 

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The effect of climatic parameters on vegetation distribution in central Iran
Introduction
Climate or climate reflects the daily weather conditions in a particular place for a long time. Most climatic elements are closely related to ecological factors, which is why the analysis of the relationship between climate and plant distribution patterns has been discussed in scientific and research circles for many years. And in recent years, scientists have been using a combination of climatic characteristics with other environmental factors to describe vegetation around the world. Climate change and atmosphere condition will change the content and composition of many plant communities.

The Study Area
The geographic coordinates of the studied area are between latitudes 29°32’ to 33°59’ and 51°27’ to 55°5’. The position of the selected provinces of central Iran compared to the neighboring provinces are shown in Figure 1 The annual data of 8 stations have been analyzed during the stations period determined by the National Meteorological Organization. The stations characteristics including latitude, longitude, elevation and specific statistical period are shown in Table 3.

Data and research methods
In this study, the role of temperature changes and relative humidity on vegetation in Central Iran has been investigated using statistical models of analysis of the main components and hierarchical clustering. This research is applied and its method is slightly analytical. In order to investigate the climatic fluctuations of the center of Iran with respect to urban green space, statistical data related to average temperature and relative humidity during the 32-year period (1986 to 2018) selected central stations of Iran to come and statistical deficiencies such as Data loss was performed by reconstructing differential equations using SPSS software. The criterion for selecting stations is the availability of long-term statistics. Using statistical methods and Geographic Information System (GIS), vegetation classification was performed for Central Iran. ArcGIS, Minitab, SPSS and EXCEL software are used in this research. After identifying the stations, climatic variables including temperature and relative humidity were selected from the data of 8 meteorological stations and were analyzed using the techniques mentioned above. Then, using statistical regression analysis, the impact (topography, average temperature and average relative humidity) on how to distribute and distribute vegetation was investigated. Kendall-man non parametric test was used to investigate changes in the vegetation index trend.

Results and discussion
Analysis of temporal changes in climatic parameters and NDVI index
The results show that the distribution of relative humidity in Abadeh and Kerman stations has decreased by 3% and the temperature distribution in these stations has increased by more than one percent. Relative humidity changes in Kashan and Sirjan stations have a weak decreasing trend, while the relative humidity distribution in Isfahan station has decreased by about 2%.The temperature distribution of Shiraz and Yazd stations increased by 3%, Abadeh station increased by 2% and also Isfahan and Kerman stations increased by 1%. The distribution of vegetation in Yazd and Khor Biyabank stations has decreased by one percent, while the growth of vegetation in Isfahan, Abadeh and Sirjan stations is increasing by less than one percent.

Distribution of NDVI vegetation index in Central Iran using cluster analysis
The stations are located in three distinct areas in terms of distribution of vegetation, each group having the same climatic characteristics in the distribution of similar vegetation. Based on this, three climatic zones in the study area can be identified.

Conclusion
The aim of this study was to investigate the effect of climatic parameters (average temperature and relative humidity) on the distribution of vegetation in Central Iran using comparison of statistical models; by examining the distribution and density of vegetation, eight factors were identified. Among the factors, the first and second factors, with 81.57% of the total vegetation variance, have played the most important role in determining the climatic diversity of Central Iran. In total, these eight factors have justified about 100% of the vegetation behavior in the area Also, according to the analysis of images of Modis satellite measuring satellites from the vegetation situation in the last 5 years, Central Iran, the value of NDVI index in Central Iran varies between 0.2 to 0.64, the northwestern parts of Fars province have the highest vegetation density and The central parts of Isfahan, especially Yazd, lack vegetation. Based on the results, altitude has a direct and significant relationship with temperature distribution in plants, especially in the study area. However, the height of Iran's central regions has affected the distribution of vegetation.

Keywords:  climatic parameters, vegetation distribution, central Iran

 

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 Determining Strategies for Improving Environmental Resilience in Gharehshiran Watershed in Ardabil using SOAR Analysis Technique
Ebrahim Asgari - PhD Student of Watershed Science & Engineering, Yazd University, Yazd, Iran. Email: ebrahim.asgari90@yahoo.com
Mahboobeh Noori - PhD Student of Geography & Urban Planning, Yazd University, Yazd, Iran. Email: mnori@stu.yazd.ac.ir
MohammadReza Rezaei - Associate Professor of Geography and Urban Planning, Yazd University, Yazd, Iran. Email: mrezaei@yazd.ac.ir
Raoof Mostafazadeh - Associate Professor Department of Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran. Email: raoofmostafazadeh@uma.ac.ir (Corresponding author)

Extended Abstract
Introduction: New approaches of crisis management have changed from the concepts of vulnerability to resilience and emphasize on strengthening the system's ability to deal with the risks of natural disasters. Therfore, the aim of this study was identifying the watershed capabilities of Qarahshiran and crisis management planning with emphasis on environmental resilience.
Methodology: The SOAR analytical technique and expert opinions of 52 experts were used to formulate the strategy, determine the strengths, opportunities, ideals and measurable results. The results of SOAR technique and crisis management prevention and preparedness strategies were compared with the environmental resilience of the field.
Results: Based on the results, reducing direct and indirect flood damage with 51.9% and low amount of soil erosion and water loss with 42.3%, were the most important results of the SOAR model. Out of 15 components of environmental resilience, the performance of 5 components was accepted as significant (α<0.05 confidence level). The evaluation of environmental resilience using one-sample t-test showed that the environmental dimension of resilience (2.67) with a significant level (α=0.003) has a significant that indicates high vulnerability and low resilience.
Conclusion: Considering site selection of watershed management structures, creating more opportunities and using the private sector potentials, and local NGOs will be useful in crisis management. Analysis of watershed resilience components in achieving integrated watershed management, proper knowledge of watershed function, possibility of self-regulation and recovery of balance and acceptance of adaptation to natural hazards, co-design of watershed residents, preparedness and coping with crisis can be more effective over the study area.
Key words: SOAR Model, Strategic Planning, Prevention and Preparedness, Resilience, Gharehshiran Watershed

 

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Considering the increase in housing construction in developing societies such as Iran, it is necessary to address the issue of reducing construction accidents, especially in metropolises, and related safety measures with the help of emerging technologies. Therefore, the main goal of the current research is to investigate the use of Internet of Things to monitor and control high-risk points in order to reduce accidents and improve safety in the spaces of construction site in Tehran.
In this applied research, first, a library study was conducted regarding the concept and application of Internet of Things in the safety field of the construction industry. Then, high risk points and activities were identified. After that, in the field study phase, this list was corrected and completed by 52 competent building safety consultants. After that, ten semi-structured interviews were conducted with safety experts and knowledgebale in the field of IoT. Therefore, effective solutions based on Internet of Things were extracted to control and monitor high risk points. Also, in this regard, the current situation and required platforms were explained from the aspects of technology, organization, cost and outsourcing.
In fact, the main findings of this research, in the form of a conceptual model, show that paying attention to the stages of choosing the incident, choosing the desired point and activity, determining the appropriate solution for the determined situation (monitoring the amount of movement and health of the structure, monitoring the proximity of flammable materials with other materials, monitoring the proximity of people and machines and preventing the continuation of movement and determining the limits around the openings) and checking the required platforms (infrastructure, support, accreditation, culture, budget, employers and law), respectively, in order to design and implement IoT-based safety systems in the spaces of construction sites is vital.

 

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Onset and End of Natural Seasons in Iran

Introduction:
 Season is the natural pattern of change in nature, which is related to the movement of the sun, the temperature cycle, the life cycle of the earth (phenology) and human culture. In astronomical and climatic seasons, a year divided into four seasons, spring, and summer, autumn and winter (Alsop, 2005), (Trenberth, 1983). Season is a period of the year with a homogeneous climate (Alsop, 1989), that is difficult to determine exactly when to start and end. The methods of determining of the seasons are: change in the face of the earth (Cayan et al, 2001), (Wang et al., 2021), constant temperature threshold, (Jaagus et al, 2003; Kitowski et al, 2019; Ruosteenoja et al, 2019; Alijani,1998), Air Masses, (Lamb, 1950; Cheng et al, 1997; Pielke et al, 1987; Kalinicky,1987; Alpert et al, 2004). What is a natural constant sign is the key to determining change and starting a new season. Organisms react to the onset and end of natural seasons by changing their behavior. Naturally, plants and animals adjust and adapt their phonological stages to temperature changes and jumps (Sparks et al, 2002), Plants germinate and flower in spring,fruit in summer, reduced activity and leaf in autumn and in winter fall asleep (Menzel et al, 1999 Animals are also adapted to reproduction, nesting and childbirth, And their phonological period is also related to vegetation conditions. In other words, the life stages of living organisms are adapted and dependent on these natural changes (Schwartz et al, 2000). Some organisms also migrate in order to adapt (Smith et al, 2012). The genetic response of organisms to rapid climate change and seasons associated with winter warming across the north, the early onset of spring and a long growing season is a factor in impairing the physiological response (reproduction, dormancy or migration time) of species(Bradshaw et al, 2008). On the other hand, the sensible temperature of organisms is affected by radiation, wind, air temperature and humidity. As appearance temperature is an important heat factor (heat and cold) in nature, to which animals, plants and humans react. Ruosteenoja et al (2019), showed the length and onset seasons of European with thresholds of 0 and 10 ° C focusing on the scenario of a 2 ° increase in temperature, an increase in summer length and a decrease in winter compared to pre-industrialization. The length of summer increases by 1 degree, increases by 10 days, and the length of winters decreases by 10 to 24 days. Kitowski et al, (2019), showed the onset of summer earlier, the shorter autumn, the longer summer and the shorter winter in Poland with zero-, 5- and 15-degree temperature thresholds. Wang et al, (2021) change the onset time and length of natural and summer seasons from 78 days to 95 days, and spring, autumn and winter, 124 to 115, 87 to 82, and 76 to 73 days, respectively. Also, summer is halfway through the year and winter is less than two months to 2100 in the middle of the Northern Hemisphere. Dong (2009) showed that in most parts of China since 1950, summers have been longer and winters shorter, with the onset of summer 5.8 days earlier and the length of the season 9 days longer and the winter 5.6 days later and the length of the season 11 days. Changes in transition seasons are less. Season start, end and season length changes studied in Oregon and Washington (Alsop, 1989), in the United States (Barry and Perry, 1973), Europe (Jaagus et al, 2003), Estonia (Jaagus et al, 2000), South Korea (Choi et al, 2006), China (Ma et al, 2020), Xinjiang in northwestern China (Jiang et al, 2011; Cheng et al, 1997), Eastern Mediterranean (Alpert et al, 2004), Iran (Alijani ,1377). Therefore, with the increasing trend of temperature in different regions of Iran (Alijani et al, 2012), study of change of the start and end dates of natural seasons in connection with life in nature is necessary (Penuelas et al, 2002). The aim of this study is determine the time of onset, end and length of natural and significant seasons and its difference with astronomical and climatic seasons in Iran with highlands, inland and coastal lowlands in the north and south with a new approach based on biological physiology.
Material and methods:
To determine the onset and end of natural seasons, daily data of relative humidity, water vapor pressure, and wind speed and air temperature over a 60-year period for 32 synoptic stations in Iran from 1959 to 2018 were used. Selected stations cover all areas of Iran (coastal, low and highlands). In the first step, the apparent daily temperature of each station was calculated (Formula 1). In the second stage, with the knowledge of the direct effect of atmospheric circulation factors in the occurrence of natural phenomena (Alijani, 2011) And rapid changes in temperature (season), the 4-day moving averages of apparent temperature (average life of cyclone and anticyclone) at each station were calculated and was the basis of study. The onset and end of the season are with a natural and biological approach related to the stages of bio phenology and the natural part's reaction to temperature changes. Therefore, the apparent temperature of zero and below zero with the reduction or cessation of biological activity in nature, is the onset of winter. On the other hand, the time required by nature to adapt to new temperature conditions, is at least 10 days (Joy, 2017). Therefore, the temperature of zero degrees and non-return to zero Up to at least the next 10 days, is the basis for the onset of winter. In fact, with the continuation of sub-zero temperatures for 10 days, the living part of nature receives the signal of change. If after that, for a period of less than 10 days, the temperature goes above zero, the situation will not return to the previous state (nature did not react and adaptation occurred). On the other hand, the best temperature for the growth period is from at least zero degrees to a maximum of 30 degrees in nature (Abrami, 1972). The second key indicator is the temperature of the onset of summer and the warm period. For the onset of the summer season, the temperature of 20 degrees was base with the previous conditions. Because at this temperature, the reproductive period in plants and animals has started, most animals and plants have children and humans also feel warm. As plants begin to fill grain at this temperature, including wheat (Jenner, 1991 and Dupont et al, 2003) as the world's oldest grain. Here, the same condiction as before, don’t return to 20 degrees for at least the next 10 days was the basis. So at the onset of both seasons, if the temperature returns to zero and 20 in the 10-day period, the season has not begun, and in that year the station does not have winter and summer, respectively. Then, the temperature of 19 degrees and less with the above conditions, the onset of autumn and the temperature of 1 degree and more with the above conditions, are the basis for the onset of spring.
Formula 1: Calculate the apparent temperature                      AT = T + 0.33 PV - 0.7 WS – 4
T = air temperature in Celsius, PV = water vapor pressure in hPa, WS = wind speed in meters per second, AT = apparent temperature in Celsius

Results and discussion:
 The onset and end of natural seasons are different in the geographical and topographical location of Iran. Southern regions and the northern coasts are two seasons with a warm summer season and a transitional season (cool). Other parts of Iran, like the temperate regions of the globe, have four seasons, but the start, end and length varies. The longest winter in the northwest and the western heights and the length of winter to the east and south is short and vice versa, the longest summer in the south and center of Iran. Spring season in below 29 degrees orbit, Khuzestan and the shores of the Caspian Sea is not a separate season, but with the absence of winter, it merges with autumn. In other regions, spring begins in the south and northwest, respectively, from 31 January to 8 March. In most parts of Iran, the onset of spring coincides with the traditional date of Nowruz, after small chelleh of winter. This month coincides with the rise in temperature and the revival of nature and the introduction of the New Year. The end of spring in the central regions, 10 May and in the northwest, 18 June, and its length varies from 103 to 96 days in the northwest and northeast, respectively. In the temperate regions of Iran, it is about three months with a 10-day spatial fluctuation (Table 1). The onset of summer is with a new stage of phenology in nature. The onset of summer is from 15 April on the southern coasts with high tropical arrival and the latest onset of summer in the northwestern part is 19 June (Table 1). In the south of the orbit of 29 degrees and the region of Khuzestan, until 8 May, in the central and northeastern regions of Iran from 22 May to 29 May and the west and northwest region, from mid-June to the end of June. The end of summer, as opposed to the onset, is the earliest time of 17 September in the northwest, and in the southern regions of Iran, the end of 8 October is in the 29 degree orbit. The southern regions of Iran, the longest summer that shows the role of latitude and slower exit of the tropical system (Alijani, 1390). The length of the summer season in temperate regions varies from 90 to 139 days, approximately three to five months, respectively in the northwest and the 29-degree geographical orbit, respectively. Therefore, the spatial trend of summer length from east and south of Iran to north and northwest is decreasing and there are the shortest summers in northwest of Iran. Naturally, this spatial trend is related to the high-altitude inbound and outbound routes of the subcontinent and the western systems from the south and northwest, respectively. The month of October and November is the onset of autumn in Iran, in the northwest and northeast, with the arrival of cold atmospheric circulation from above, the angle of radiation and altitude, is 18 September. The latest start of autumn in Hormozgan is 12 November (Table 1). The end of autumn is the first of April to the first of June in the south and north coasts, respectively. In the northeast of Iran, 24 to 28 December, and in the central regions, 28 to 31 December, is the end of the autumn season. The earliest end in the northwestern regions of Iran at the end of December is 10-17 December. The length of the autumn season in temperate regions is 83 to 97 days, respectively, in the northwest and northeast, that’s an average of nearly three months. With the onset of winter, decreases in temperature (frost) and winter during the year below the 29 degree orbit are rare, but on the northern coast, with the influence of atmospheric systems, it is a coincidence. In other regions of Iran, northwest, west and east of Zagros and south of Alborz, above 29 degree orbit, from 11 December to 1 January, is the time of winter. Respectively, the earliest onset of winter is in the northwest, and the latest onset in the central regions (Table 1). As the westerly winds of the extraterrestrial latitudes with cyclones and anticyclones dominate the Iranian atmosphere, also, the angle of radiation and the amount of radiation received at the earth's surface at this time, reaches a minimum during the year. The end of winter in temperate regions is from 30 January in the 29 degree orbit to 7 March in the northwestern regions. Winter length reaches 86 days in northwestern Iran, 29 days in central regions (above 29 degree orbit) and 58 days in northeastern Iran, Therefore, there are only three winter months in northwestern Iran and in other parts of Iran, it is the shortest season during the year. Spatial trend of winter length from northwest of Iran to east and south is decreasing.
Figure1: Date of onset, end and duration of natural seasons in different regions of Iran

Fall

Summer

Spring

Winter

Season

Length

End

onset

Length

End

onset

Length

End

onset

Length

End

onset

83

10 Dec

18 Sep

227

17 Sep

15 Apr

100

10 may

31 Jan

86

30 Jan

11 Dec

Earlier

160

21 Apr

13 Nov

90

12 Nov

19 Jun

103

18 Jun

8 Mar

29

7 Mar

1 Jan

Later

77

133

56

137

55

65

3

39

36

57

36

21

Fluctuation

Conclusion:
The time of the onset, end and length of natural seasons in Iran are different from astronomical and calendar seasons. The slow decreasing and increasing trend of temperature at the onset and end of the seasons is initially a function of the angle of radiation and the length of day and night, but the real onset of a season with temperature jumps associated with the migratory atmospheric system (cyclone and anticyclone), Siberian hypertension, It is from the north and high in the subtropics from the south. Areas below 29 degree orbit in the south of Iran and Khuzestan and the northern coasts, have only two seasons of autumn (cool) and summer (warm) and the temperature decreases to zero and less (occurrence of winter), in the southern regions, rare and on the northern coasts is accidental and short. The apparent temperature in these areas has been decreasing since late summer and in the middle of the cold period, it is decreasing to the maximum (lowest temperature during the year) and increasing again until the onset of summer. Therefore, the above areas are two periods, with a cool season and a hot and hot season. The southern coasts of Iran and Khuzestan have short cooling seasons and long hot and hot summers, and the northern coasts, on the contrary, have shorter summers and longer and cooler autumns, that The influence of water temperature, latitude, topography and atmospheric systems are effective in these differences. In other regions of Iran, except the mentioned regions, four natural seasons occur (spring, summer, autumn and winter). In connection with the role of latitude, altitude, the arrival of migratory and high pressure Siberian atmospheric systems, the time of onset, end and length of the season has a change of location. As the length of summer is more in the southern, eastern and central regions of Iran and decreases in the northwest and west of Iran, and the length of winter is the opposite. The length of the transitional seasons (autumn and spring) in the temperate regions of Iran is not different and the three months in the season are similar to the astronomical and calendar seasons. The most important spatial difference is during winter and summer. Winter decreases from three months in the northwest of Iran to the south and east of Iran and reaches a month in the 29 degree orbit. On the other hand, the length of summer, on the contrary, varies from five and three months from east and south of Iran to northwest of Iran. Therefore, in temperate regions of Iran, the length of natural seasons from the south and east of Iran to the west and northwest of Iran is more regular and approaches to three months in each season. This spatial trend indicates the climatic similarity of western and northwestern Iran with temperate regions of the globe in higher latitudes and but to the center, south and east of Iran, this similarity decreases and to hot and cold dry desert climate in the Middle East and central Asia region is similar, respectively. This indicates regularity and order in nature, which is related to the geographical principle of Tobler’s law, the spatial correlation of climates and the onset, end and length of their seasons. Therefore, if we consider three months in a season as a natural feature of the temperate regions of the earth and two seasons (climatic period) as a feature of the subtropical regions, Iran is in the transition zone of these two climates. As from three months, the length of each season in the northwest to less than a month in the range of orbit 29 degrees, and then the subtropical conditions with two seasons (warm and cool) appear. Therefore, from northwest to east and south of Iran, the climatic moderation decreases and its tropical sub-characteristic (longer summer and shorter winter) heat and dryness to heat and humidity in southern Iran is added. Naturally, in this spatial process, primarily large-scale atmospheric rotations and secondly, geographical phenomena (their shape and position) play a pivotal role. The Caspian Sea coast is an exception to this rule due to its higher latitude and complexity of geographical phenomena and the role of water, because the climate systems related to the Caspian climate are different from other regions of Iran.

Key words: Natural Seasons, Apparent Temperature, Plant and Animal Phenology, Iran.


 

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In the present study, the data of the ECMWF for a period of 1979 to 2018 was adopted to analyze the long term changes (trends) of the number of cyclones centers of the Mediterranean Sea.There are many methods (e.g. parametric and non- parametric)  for examining changes and trends in a given dataset. The linear regression method is of parametric category and the most common nonparametric method is Mann-Kendall test. By fitting the Mann-kendall model and the linear regression model, the frequency of the cyclone centers of the Mediterranean basin was evaluated in seasonal and annual time scales. Analyzing the trend of changes of the number of cyclone centers on a seasonal scale showed that the five-day duration have had a significant trend in spring, autumn and summer. Whilest on an annual scale, there was no significant trend in any of the duration. By fitting the regression model on seasonal and annual scale, one- and two-day duration have a positive regression line slop.

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Explaining the spatial patterns of drought intensities in Iran

Abstract
Recognition of spatial patterns of drought plays an important role in monitoring, predicting, confronting, reducing vulnerability, and increasing adaptation to this hazard. This study aims to identify the spatial distribution and analyze the spatial patterns of annual, seasonal, and monthly drought intensities in Iran. For this purpose, the European center Medium-Range Weather Forecast (ECMWF) data for the period 1979-2021 and the ZSI index were used to extract the drought intensities. To achieve the research goal and explain the spatial pattern of the frequency of drought intensities (Extreme, severe, moderate, and weak), spatial statistical methods such as global Moran’s I, Anselin local Moran’s Index, and hot spots were used. The results of the global Moran’s I showed that with increasing intensity, the spatial distribution of drought events has become clustered. The spatial distribution of the local Moran’s Index and hot spots also confirms this. Very clear contrast was observed in the local clusters of high (low) occurrence as well as hot (cold) spots of severe (Extreme) yearly droughts in the south, southeast, and east. In autumn, weak to Extreme droughts show a southeast-northwest pattern. But in spring and winter, the spatial pattern of drought is very strong as opposed to severe and moderate drought. Despite the relatively high variability of maximum positive spatial Autocorrelation of severe and Extreme monthly droughts, their spatial pattern is almost similar. The spatial clusters of severe and very severe droughts in the northwest, northeast, and especially on the Caspian coast, are a serious warning for the management of water resources, especially for precipitation-based activities, such as agriculture.
Introduction
Drought or lack of precipitation over some time is the most widespread natural hazard on the earth compared to its long-term average. This risk negatively affects various sectors such as hydropower generation, health, industry, tourism, agriculture, livestock, environment, and economy. To reduce these negative or destructive effects, it must be determined how often drought occurs during the period and in which areas it is most severe. Doing so requires determining the characteristics of the drought. These characteristics include area, intensity, duration, and frequency of drought. Discovering the geographical focus, recognizing the pattern governing the frequency of occurrence and temporal-spatial distribution as well as changes in the dynamics of this hazard facilitate an important role in drought monitoring, early warning, forecasting, and dealing with these potential hazards; this information can be used to create a drought plan by providing analysts and decision-makers with ideas about drought, helping to reduce the negative and vulnerable effects and ultimately make it easier to protect or replace for greater adaptation. Many researchers have been led by these approaches to the use of statistical analysis. Numerous studies have been conducted in the study of climatic phenomena such as drought with space statistics techniques in various regions, including China, India, South Korea, and even Iran. Part of the domestic research on spatial patterns of drought is without the use of spatial statistics and a limited number of others who have used these analyzes have only studied the overall intensity of drought and have not studied the spatial patterns of different drought intensities. The main purpose of this study is to identify the distribution and spatial patterns of drought intensities in Iran using spatial analysis functions of spatial statistics based on the frequency of drought intensities (Extreme, severe, moderate, and weak) with yearly, seasonal and monthly multi-scale approach. Therefore, this study will answer the questions: a) What is the spatial distribution of drought intensity data in Iran? And b) What is the variability of spatial patterns of Iranian droughts at different time scales?
Material &Method
ERA5 monthly precipitation data for a period of 43 years from 1979 to 2021 were used for this study. an array of dimensions of 78×59×504 of data were formed in MATLAB software in which 78×59 is the number of nodes with a spatial resolution of 0.25 degrees and 504 represents the month. After creating the database, the ZSI index was used to calculate the severity of drought in annual, seasonal, and monthly comparisons. Finally, to achieve the research goal and explain the spatial pattern governing the frequency of drought intensities (Extreme, severe, moderate, and weak), spatial statistical methods such as global Moran’s I, Anselin local Moran I and hot spots was used.
Discussion of Results
Due to its ecological conditions, geographical location, and location in an arid and semi-arid region of the world, Iran is among the most vulnerable countries due to natural hazards, including drought. It has experienced many severe droughts in the last century. The occurrence of drought and its effects is one of the major challenges of water resources management in this century. The results of the Global Moran’s Index for all three annual, seasonal, and monthly scales showed a highly clustered pattern of drought events in the country. Spatial clustering of the occurrence of severe and Extreme yearly droughts in the eastern, southeastern, and southern regions is also an interesting result. These conditions are due to low precipitation and high spatial variation coefficient in these areas. This contrast of spatial clusters of drought intensities indicates the relationship between drought and temporal-spatial anomalies of precipitation so that with increasing precipitation, spatial variability of precipitation decreases, and consequently spatial homogeneity of precipitation increases. severe and moderate-intensity spots in the south-southeast in autumn and spring can be affected by fluctuations in the beginning and end of the monsoon season in South Asia due to the high variability of atmospheric circulation at the beginning and end of precipitation in these areas. Some studies have also shown the relationship between precipitation in these areas and the monsoon behavior of South Asia. Extreme drought events in winter and spring have had a positive spatial correlation pattern in the southwest, west, and northwest. However, precipitation at this time of year is concentrated in these areas. Warm clusters or concentrations of very severe drought events in the northern strip of the country, especially in the Caspian region, can be due to the high variability of precipitation at the beginning of the annual precipitation season (late summer and early autumn).  Observations of these conditions in the northern strip indicate that an event with a high frequency of severe droughts, even in rainy areas, should not be unexpected. Spatial clusters of Extreme, severe, moderate, and weak drought every month using both local Moran and hot spots statistics show the fact that in Iran, the most severe droughts have occurred in the western, northwestern, and coastal areas of the Caspian Sea. However, the absence of severe droughts or spatial clusters has been the occurrence of low drought in the southeast and to some extent in the south. On a yearly scale, the south, southeast, and east have played a significant role in the spatial cluster of severe and extreme droughts. So that these areas of the country have had positive spatial solidarity. However, in these areas, negative spatial correlation prevailed in the autumn for severe drought. This may indicate an anomaly and a tendency to concentrate more precipitation in Iran, as well as many changes in seasonal and local precipitation regimes. According to the research results, a high incidence of severe and extreme drought on all three scales (monthly, seasonal and annual) even in the wettest climate of the country (northern Iran, especially the southern shores of the Caspian Sea) shows that High-intensity droughts can occur in all parts of the country, regardless of the weather conditions.
Keywords: Natural hazards, spatial patterns, Moran statistics, spatial autocorrelation, hot spots


 

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One of the most important issues that has always affected the Iranian climate and has left many socio-economic consequences and financial losses climate change is. On the other hand  Sea level pressure is one of the most important climatic elements that can affect other climatic elements such as temperature, humidity and wind. The study aimed to evaluate CMIP5 models based on CORDEX and Verdai dynamics Seasonal pressure anomalies in Iran among CMIP5 models based on CORDEX project dynamic models BCC-CSM, HadGEM2-ES, GFDL and MIROC model HADGEM2-ES had a higher level of correlation and efficiency than other models.
The data of 36 synoptic milestones during the statistical period (1960-2005), the data of the HadGEM2-ES model were applied by using the CORDEX model and the RCPs scenarios for the two historical periods (1960-2005) and predicted during Three periods of near future (2040-2011), middle future (2070-2041) and distant future (2099-2071) were used. Six methods R2, MAE, MBE RMSE, t-Jacovides and t-Jacovides / R2 ratio were used to evaluate the model performance. The results showed that the model has good performance in low altitude areas. Seasonal anomalies in all seasons, scenarios and time periods studied are positive and winter shows the maximum pressure anomalies between seasons.
The maximum seasonal pressure anomaly of Iran in all seasons, scenarios and periods studied corresponds to the altitudes, including its epicenter in the Alborz and Zagros heights and high geographical offerings and the minimum pressure anomaly corresponding to low and low areas such as Khuzestan plain and The southern coast of the country.

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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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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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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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