Journal of Spatial Analysis

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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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Predicting the average annual maximum wind speed in Sistan region using spatio-temporal regression method
: Abstract                              
The wind is a quantitative vector that moves from high-pressure centers to low-pressure centers and is measured by two factors, the direction of the wind, which originates from the north and increases in degrees clockwise, and the wind speed, which is the horizontal flow. Air is measured in units of time. The wind speed can move colloidal particles, including clay and silt, from the site of destruction to a distance of hundreds of kilometers. Studies show that most dust days occur in the eastern regions of the country so that in the range of 120-day winds in Sistan, the frequency of dust per year reaches more than 150 days. Moreover, the prediction of numerical values ​​of maximum annual wind speed using the Spatio-temporal regression method was considered in this study. Error variance and alignment analysis using variance inflation index showed that numerical models of the Spatio-temporal regression of data could predict the Average maximum wind speed in the coming years. The results also show that regression Spatio-temporal until 2022 can predict wind speed.
The numerical model indicates that the lowest annual average wind speed from 2019 to 2022 is related to the Ghaen station. Its forecast trend shows that by 2022, the average annual wind speed will decrease. The highest annual average wind speed is related to Zabol station, in which the forecast trend of this station shows that the average annual wind speed will decrease by 2022.

Keywords: Spatio-temporal regression, Wind speed prediction, Sistan region
 

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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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New Social Movements: A Case Study of Emerging Environmental Movements

Abstract
The term modern social movements is used to describe movements that were active in France in the late 1960s through collective action in the social sphere. The most important new social movements are the civil rights movement, the women's movement, the peace movement and the environmental movement. The rapid growth of industrial and capitalist societies, regardless of environmental degradation, has created many problems. The most important problems are soil erosion, resource reduction, ozone depletion, greenhouse effects, extinction of animal and plant species and various types of soil and climate pollution. The combination of these factors has provided the basis for the formation and activation of environmental movements. The present paper tries to answer the question of how emerging environmental movements can be analyzed in the form of new social movements? And what are their effects on new social movements? Therefore, with the qualitative interpretive method, and the method of case studies, it examines the nature and why of emerging environmental movements. The research findings show that environmental crises and the need to solve environmental problems that have become a pervasive and global crisis, have provided the basis for the formation, activity and impact of emerging environmental movements. Therefore, in order to deal with the existing crises, emerging environmental movements first informed and increased public awareness, and then created pro-environmental organizations and groups, and finally, by entering In the field of politics, and using new tools and methods, they have expressed their demands and protests in a peaceful and non-violent way, in order to force governments to respond and finally enter directly into The field of politics as influential groups and political parties in the field of public policy. As a result, the volume and scope of social power and the political influence of emerging environmental movements have led to the revitalization and enrichment of new social movements; in a way that today they can be identified and analyzed as powerful social forces and influential actors in the field of political sociology.

Keywords: New Social Movements, Emerging Environmental Movements, Social Forces, Methods of Action, Political Nature.

 

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Revealing surface reflection forcings of land cover in Lorestan province using MODIS sensor products

Introduction
Human interventions in natural areas as a change in land use have led to a domino effect of anomalies and then environmental hazards. These extensive and cumulative changes in land cover and land use have manifested themselves in the form of anomalies such as the formation of severe runoff, soil erosion, the spread of desertification, and salinization of the soil. The main purpose of this study is to reveal the temperature inductions of the land cover structure of Lorestan province and to analyze the effect of land use changes on the temperature structure of the province. In this regard, the data of land cover classes of MCD12Q2 composite product and ground temperature of MOD11A2 product of MODIS sensor were used. Also, in order to detect the temperature inductions of each land cover during the hot and cold seasons, cross-analysis matrix (CTM) technique was used. The results showed that in general in Lorestan province 5 cover classes including: forest lands, pastures, agricultural lands, constructed lands and barren lands could be detected. The results of cross-matrix analysis showed that in hot and cold seasons, forest cover (IGBP code 5) with a temperature of 48 ° C and urban and residential land cover (IGBP code 13) with a temperature of 16 ° C as the hottest land use, respectively. They count. In addition, it was observed that the thermal inductions of land cover in the warm season are minimized and there is no significant difference between the temperature structure of land cover classes; But in the cold season, the thermal impulses of land cover are more pronounced. The results of analysis of variance test showed that in the cold period of the year, unlike the warm period of the year, different land cover classes; Significantly (Sig = 0.026) has created different thermal impressions in the province. Scheffe's post hoc analysis indicated that this was the difference between rangeland cover classes and billet up cover.   
                                                                                                                  
materials and Method                                                                                                                
 In this study, to reveal the relationship between land cover levels and different land use classes, cross-information matrix analysis was used in the ARC-GIS software platform. Since one of the main objectives of the study was to investigate and reveal the albedo inductions of land cover classes in Lorestan province, so the relationship between these two factors was investigated by cross-matrix analysis technique. In this regard, two sets of data were used. The first set of data was related to land cover classes of MODIS sensor composite product with a spatial resolution of 1 km and hierarchical data format (MCD      
   12(Q2 (MCD product) which was obtained from the database of this sensor

Conclusion
 Land cover classes or perhaps it can be said that land use is one of the most important shapers and determinants of climate near the earth. In this study, it was observed that in general, 5 major land cover classes in the province are separable, among which rangeland and forest lands account for 85% of the total land cover of the province. On the other hand, it was seen in this study that the average spatial albedo of the province in spring, autumn and winter is about 0.2, which is very close to the global value of this component, but in winter the average value of this index in the province reaches 0.3, which can be increased Shows attention. The five land cover classes in the province had their own unique albido induction in winter, which was separable and distinct from each other, but in spring, summer and autumn, no significant distinction of albido induction of these land cover was revealed.                                                                                                                                       

Keywords: Land cover changes, Land surface temperature, Cross-information analysis matrix, Lorestan province












 

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Evaluation of occurrence, tracing and origin of dust phenomenon in Zagros forest degradation monitoring sites of Chaharmahal and Bakhtiari province
Abstract
Decay and drought of oak has occurred in more than 40 countries, including Iran. Numerous factors have contributed to the drought and oak decay. Among the natural causes of climate change is common in all countries, but dust has played an important role as a contributing factor to the decline of the Zagros forests, which are adjacent to and the passage of dust currents. In this study, with the aim of investigating the occurrence of dust and its direction in Zagros deterioration monitoring sites in Chaharmahal and Bakhtiari province, meteorological statistics and data of the nearest synoptic station were used. Dust event codes were extracted from 100 phenomenon codes (0-99) and the frequency of dust events with different horizontal field of view was investigated. In order to identify the direction of dust entry, the graph diagram was used and to draw the dust, WR-PLOT software was used. Data related to wind direction and speed were extracted and wind direction and speed corresponding to dust days were extracted to enter the dust drawing software and converted to a special format of this software. HYSPLIT simulation model was used to identify the source of incoming dust sources in the area of deterioration monitoring sites. The results showed that the occurrence of dust in decay monitoring sites has an increasing trend and the path of dust entering the decay sites from the west and southwest and northwest have been important, respectively. And being in the path of incoming atmospheric currents has been affected by dust mites inside and outside the country. Tracing the origin of dust particles at three altitudes of 1000, 500 and 1500 meters showed that the most important sources of dust entering the region are from Iraq and Saudi Arabia, which has been strengthened by passing through the centers of domestic dust in Khuzestan province. Considering that the occurrence of dust and its entry path can be one of the factors contributing to the decline of Zagros oak trees and the extent of its effects is different in the south-north and west-east slopes, help decision makers and planners of forest ecosystems. At the macro level, with the control programs of domestic centers and international cooperation with neighboring countries to make fruitful and fruitful efforts to preserve and rehabilitate forests.

Keywords: Oak decay, Internal and External dust, Golghobar, WR-PLOT software, HYSPLIT model

 

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The sedimentation, sediment transport, erosion and sedimentation problems are important discussions in the planning of wisdom and macro watershed strategies and management of watershed basins. The sediment collection in lower areas causes regional damage, the destruction of the pathway of the waterways, the flow of water pollution, the accumulation of streams of sediment and reducing the capacity of reservoirs of dams and environmental bottlenecks. The sediment resulting from the watersheds erosion, in addition to soil loss and its degradation results in a decrease in water quality and endangers the useful life of dams due to the accumulation of deposits in their reservoirs. In this research, Spatiotemporal variations of suspended sediment load were investigated at three hydrometric stations of Sefidchah, Gelevard and Ablou located on the main channel of the Nakaroud Basin using sediment rating curves and linear regression model through applying MINITAB and EXCEL softwares. In order to determine the best model, determination coefficient (R2) was used. The results of this study showed that in seasonal variations of spring season in all three stations with a determination coefficient of at least 82% and a maximum of 89% as the most suitable model for estimating suspended sediment load among the models studied. In spatial studies, the Ablou station located at the outlet of the watershed has the highest determination coefficient (0.934) between sediment discharge and streamflow discharge.
 

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Glaciers are one of the most important water resources in the world, which are heavily affected by global warming and climate change. This paper investigates the effects of global warming on the changes in the snow cover level of the Takht Suleiman region located in Mazandaran province during the warm months of the year through the past three decades using remote sensing. For this purpose, the images from June to August of the Landsat-5 and 8 satellites in the period of 1990 to 2021, as well as the data of the air temperature product of the ERA5 sensor were processed on the Google Earth Engine. In this research, NDSI index (Normalized Snow Cover Surface Index) was used to detect snow covered surfaces and the Mann-Kendall test was used to evaluate the trend of the data. The results of the overall accuracy and Kappa coefficient in the Google Earth Engine system show an overall accuracy of 94% and a Kappa coefficient of 89% in 2021, which shows the high compatibility of this method with real data.
The results obtained during the investigated period show an increase of about 1.5 degrees in temperature during the last three decades at a significant level of 95%. The snow and ice cover of the Takht Suleiman region in June month decreased from 127 square kilometers( in 1990) with a decrease of 82% to 22 square kilometers( in 2021). The trend of changes in the level of snow cover in June was analyzed with the Mann-Kendall test, which shows a decreasing trend at a significance level between 80 and 90%. In general, these results indicate an increase in temperature and a decrease in the level of this glacier during the statistical period studied, and the continuation of the gradual depletion of the glaciers of this region in the future is a serious threat to the downstream water source and the surrounding environment.

 

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Space-based quantification of anthropogenic CO₂ emissions in an urban area using “bottom-up” method
(Case study: Isfahan Metropolitan)
Abstract
Increasing consumption of fossil fuels in urban areas emits enormous amounts of greenhouse gases into the atmosphere. Therefore, the study of carbon dioxide (CO₂) emissions from urban areas has become an important research topic. The main purpose of this study is space-based quantification of carbon dioxide emissions driving from fossil fuel combustion in different source sectors in Isfahan. To achieve it, in the present study, the "bottom-up" method was used to quantify the carbon dioxide gas emission based on its production sources sectors. In this method, the amount of emission was measured distinctly for different sources of energy consumption and consequently the spatial distribution map the CO₂ emission was generated. The results of this study revealed that the total amount of carbon dioxide emissions driving from fossil fuels is 13855525 tons per year in Isfahan. Separately stationary sectors of power plant, housing and commercial and mobile sources including road and railroad and existing agricultural machinery were responsible for emitting 50.61, 21.78, 17.18, 4.92, 4.37, and 1.14% of CO₂, respectively. In conclusion, through applying the bottom-up method and CO₂ emission distribution mapping based on different source sectors, mitigation measures can be applied more efficiently in urban planning.
Key words: Greenhouse gas (GHG), Fossil fuel combustion, Mobile and stationary source of energy consumption, climate change, Mitigation strategies

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 A comparative study of quantitative mapping methods for bias correction of ERA5 reanalysis precipitation data

Kaveh Bapirzadeh¹, Hesam Seyed kaboli^*2, Leila Najafi^3
1 MSc student, Department of Civil Engineering, Jundi-Shapur University of Technology, Dezful, Iran.
^*2 Associate Professor, Department of Civil Engineering, Jundi-Shapur University of Technology, Dezful, Iran. Corresponding Author: Email: hkaboli@jsu.ac.ir
³ Instructor, Department of Civil Engineering, Jundi-Shapur University of Technology, Dezful, Iran.
Abstract
This study evaluates the ability of different quantitative mapping (QM) methods as a bias correction technique for ERA5 reanalysis precipitation data. Climate type and geographical location can affect the performance of the bias correction method due to differences in precipitation characteristics. For this purpose, ERA5 reanalysis precipitation data for the years 1989-2019 for 10 selected synoptic stations in climates with different topographic characteristics were received daily from the European Centre for Medium-Range Weather Forecasts (ECMWF) website. Bias correction of these data was performed using 5 quantitative mapping methods based on observational data in R software environment. Two-part evaluation and Taylor diagram were used to compare the performance of different methods. The results showed that the performance of the quantification mapping method depends on the performance functions, set of parameters and climatic conditions. In general, non-parametric methods of multiple mapping have better performance than parametric methods, so that the best performance is related to QUANT and RQUANT methods, among which DIST method has the weakest performance.

Keywords: Quantitative mapping, Bias correction, ERA5, ECMWF
 

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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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Risk assessment of Maroun gas and oil pipelines due to land sliding hazard

based on D-InSAR technique

Mohammad Sharifikia, @ Associate professor, Tarbiat Modares University, Department of Remote Sensing-

Iran

Meral Poorhamzah, postgraduate in Remote Sensing, Tarbiat Modares University

Abstract
It is importance to note that Iranian oil company have to transfer this valuable enrage from one side to other side of
country passing form several ridge and valley prone with several natural hazard. This is because the natural sources
of oil and gas generally lied in south west part of Iran locally calling Manathegh Nafte Khize Jonoub (south oil field
area). This area is closed to one of most active geological zone of Iran (Zakrose) covering thousands of kilometer
from south east to north west. Supplying natural enrages to central port of country need to crossing from this zone
which is suffering with several difficulties as well as neutral hazard. Out of neutral hazards can found to excite in
this area, the landslide hazard is a main restriction for pipeline crossing over.
The present research is dale with radar interferometry techniques applying for risk assessment and mapping over the
oil and gas pipelines suffering to landslides hazard in the part of Central Zagros (Maroun-Esfahan). For this purpose,
two individual radar dataset in C (ASAR) and L (PALSAR) band with deferent time were collected. Furthermore,
the D-InSAR technique was applied for land surface movement and land displacement detection. The outcome map
was showed the maximum rate of land displacement in this region is about 7.4 cm uplifted and 3.9 cm subsidence
with duration of almost one year. this is due to shape of landslide over the area’s slop. Overlying the landslide map
with the pipeline crossing route shown at lies three active landslides over the Maroun-Esfahan gas and oil pipelines.
For investigation about this three landslide and damage estimation over the pipeline the field study has been done
for accuracy assessment and land movement rat measuring and evaluation. Which, successfully identified and
mapped 3 landslides were located across the pipeline and damage it. Furthermore, map surveying by DGPS in RTK
method over the one of landslide shown that sliding transfer 20 m with falling 10 m over the length of 45 m of gas
pipeline. moreover, the press of landslide made curvatures on straight pip hogging pipe 43 cm. continued this
landslide activation and more pressing in close further can make a fracture and pessimistic pipe expulsion. With can
a kind of disaster if the event be close to settlements are.
The outcome landslide map shown the active landslide points (small area) very well, but the main think need to
suffusion information about interred area. For this exigency have to convert points data map to area as prediction
hazard. For this proses and to understanding the amplitude of landslide hazard in area the information value model
was applied for hazard zonation and mapping. The landslide hazard map resulting from D-InSAR technique as
inventory map along with 8 data set maps namely, lito-logy, soil, land cover, lineaments, faults, roads, derange
pattern and slop, has been interred to model for zonation and hazard estimation over the area. Furthermore, this map
was reclass in 5 individual hazard and risk class from low to high risk. The hazard map analyses and calculation was
show about 20 percent of area study was marked as high and very high risk zone. This is mainly because of
morphological and lito-logical exclusivity of area resulting by active tectonics. Crooning and overlaying the
landslide hazard map with pipeline track has been shown 28.5 percent of line length crossing over the high and very
high risk zone, where the 52 percent was prone with low and very low risk zone. This mine that near 1/3 of mention
pipeline length suffering from hazardous area which can classified as high risk part of pipeline.
Interpreting the hazardous classes on the prediction map is an important concern in landslide prediction models. For
this purpose, the prediction-rate curve was generated using validation group of landslide locations to validate the
prediction map obtained. This rate curve explains how well the model and factors predict the landslide. Results from
the success-rate curve are very promising, since the 3% area predicted as the most hazardous, includes 42.35% of
the total area affected by landslides, and this value grows to 90%, when about 25% area of highest susceptibility is
considered. The prediction accuracy can be assessed qualitatively by calculation the area under cover. The total area

equal to one means perfect prediction accuracy. In this model ratio area was 0.633 that means the prediction
accuracy was 63.3%.
Keywords: Differential SAR Interferometry, PALSAR, ASAR, Landslide, Oil and Gas Pipeline risk

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Synoptic analysis of the changes trend of the share of systems due to the Sudan low
In the cold period of the Persian Gulf coast during 1976-2017


 Introduction
In the Ethiopian-Sudan range forms the low pressure system without front in the cold and transition seasons that is affecting the climate of the adjacent regions by crossing the Red sea. Based on the evidence in the context of Iran, studying Sudan low was first begun by Olfat in 1968. Olfat refers to low pressures which are formed in northeastern Africa and the Red Sea and then pass Saudi Arabia and the Persian Gulf, enter Iran, and finally, cause rainfall. The most comprehensive research specifically examining Sudan low, was the work carried out by the Lashkari in 1996. While he studying the floods that occurred in southwestern of Iran, he was identified Sudan low by the most important cause of such flooding and he explained how they are formed, and how these low-pressure systems were deployed on the southwest of Iran.

 Materials and methods
The study period with long-term variations was considered from 9.5 to 11 years based on solar cycles. Precipitation data for 13 synoptic stations are considered above 5 mm in south and southwestern Iran. With three criteria were determined for the days of rainfall caused by each type of atmospheric system. The visual analysis of high and low altitude cores and geopotential height at 1000 hPa pressure level (El-Fandy, 1950a; Lashkari, 1996; 2002) were considered based on the aim of the study. Accordingly, the approximate locations of activity centers, as well as the range of the formation and displacement of the Sudan system were initially identified based on the location of the formation of low and high-pressure cores. Then, the rainy days due to the Sudan system in January were separated from the precipitation of the other atmospheric system.

 Results and discussion
According to the selected criteria in the forty-year statistical period, 507 precipitation systems were identified with different continuities that led to precipitation in the northern coast of the Persian Gulf. The pattern of independent Sudan low rainfall was responsible for 77% of the precipitation in the Persian Gulf. Decade frequency share of Sudan low was lower in the first decade (16%) compared to the next three decades. This system of rainfall was more activated during the second and third decades compared to the first decade. However, rainfall changes were not evident in the mid-decade. Independent Sudan low precipitation provide 25% and 27% of the cold season precipitation of the Persian Gulf during the second and third decades respectively. In accordance with the 24th solar cycle, at the end of the study period, the Sudan low was more effective on the Gulf coast than ever before. During this decade, 125 cases of Sudan low rainfall was recorded for the Persian Gulf. Thus, the frequency of Sudan low during the fourth decade was about 31%, which was higher than in the rest of the decade. Overall, the Sudan low rainfall was repeated 151 times for 2 days rainfall, during the statistical period studied. This Precipitation has increased over the last decades compared to other periods.

 Conclusion
The severe variability of rainfall along the timing and location of the permanent Persian Gulf coasts can have a significant impact on the economic and agricultural behavior of the Gulf population in the three provinces of Ahwaz, Bushehr and Hormozgan.The purpose of this study was to evaluate the precipitation changes due to Sudan low in the Persian Gulf coastal region during the cold period. The results of this study showed that the role of integration patterns in influencing the precipitation of the Persian Gulf coast has decreased with the strengthening and further activation of the Sudan low system during the last two decades. That way, about 77percent of the region's rainfall is provided by independent Sudan low. At the end of the course (in accordance with 24th solar cycle activity) the Sudan low system was more active than before. Although the Sudan low activity was different at each station during the period studied, but in the historical passage incremental and decade's positive behavior of Sudan low was common to all stations. Evaluation of changes in rainfall duration shows that the pattern of precipitation with 2days duration is more frequent than the patterns of one to several days.

Keywords: Sudan low- Solar cycle- Persian Gulf.





 

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Factors affecting the adaptation of rural settlements to the water crisis of Lake Urmia Case study: Miandoab County

Problem statement
In recent years, Lake Urmia, the largest lake in Iran, has faced severe water shortages, which has raised concerns in terms of economic, social and environmental consequences in the surrounding communities, especially in rural areas. Livelihood dependence of rural community stakeholders, to the natural resources and agricultural products have caused the harmful effects of drying Urmia Lake to be more visible. The drying up of Lake Urmia is not limited to this lake, but human communities have also suffered a lot from their sphere of influence. Due to the human effects of the drying of Lake Urmia,  it is necessary to analyze the effects of this phenomenon from a human perspective in research. Identifying the adaptive capacity of rural community stakeholders makes it possible to adopt appropriate management strategies to reduce the damage caused by lake drying. Therefore, despite the importance of the subject of this research, it seeks to study the factors and forces affecting the adaptation capacity of rural settlements in the face of the drying crisis of Lake Urmia in the city of Miandoab and so on.

Research Methodology
In terms of methodology, strategy and design, the present study is a combination of (mixed), sequential and explanatory exploratory, respectively. In this study, for a detailed study of community mentalities, a discourse on effective factors to increase the adaptive capacity of rural settlements in the face of drying or water retreat of Lake Urmia, the combined method of (Q) was selected. The research discourse community included local managers (governorate experts, heads and employees of government departments, districts, rural districts and Islamic councils) as well as local experts in the sample villages of Miandoab city. Targeted sampling method (snowball) was used to select the statistical sample. Q statements were also compiled using first-hand sources (expert opinions, local managers, field observations, etc.) and codified sources (books, articles, publications, etc.) using the library and field methods. The Q questionnaire was also used to assess the attitude of experts. In order to analyze the data of the Q (Q) method matrices, heuristic factor analysis based on the individual method (Stanfson method) was used.

Description and interpretation of results
 In reviewing the findings of the exploratory factor analysis model with KMO criterion, Bartlett test confirmed the sufficient number of samples and its appropriateness for the research. To investigate the most important influencing factors, the specific value and percentage of variance were calculated and the number of factors was determined by pebble diagram and Kaiser Guttman criterion. The results showed that the most important factors and forces affecting the increase of adaptation capacity to the drying of Lake Urmia in the sample villages of Miandoab are: 1) Increasing economic capital and the use of natural resources, 2) Increasing social capital and investment, 3) Developing infrastructure facilities and improving the skills of villagers, 4) Economic diversification and improving rural management .. Among these factors, the first factor with a specific value of 5.40 and a percentage of variance of 24.55 was recognized as the most important factor and effective force in increasing the adaptation capacity of the studied villages against the drying of Lake Urmia. Thus, economic and natural factors, as the most important assets of the villagers, are endangered at any time by the drying up and retreat of the water of Lake Urmia and have a direct impact on the livelihood of the villagers.

Keywords: Adaptation capacity, Lake Harumiyeh, Miandoab County.

 

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Synoptic analysis of the torrential on Day 21, 1398 (Case study: Zahedan and Qeshm)

Abstract
Rainfall is the most important phenomenon or feature of the environment and so far many studies have been done about its causes. In any place, rainfall occurs when humid air and climbing cause are provided. Both of these conditions are provided by the circulation pattern. The study area is affected by some severe and sudden weather phenomena such as low annual rainfall, short rainfall period and rainfall in the form of heavy showers. Thus, it is possible that the limited and pervasive precipitation of the area is due to a different synoptic pattern. Because the relationship between circulation patterns and precipitation is significant, achieving acceptable results in the field of the relationship between these patterns with the limit and total rainfall of the studying area requires the analysis of synoptic maps. Therefore, the most important purpose of the present study is the synoptic analysis of heavy cloud rainfall of the studying area on Day 1398.
Two sets of data were required for this study: A: Daily precipitation data of study stations on the day of heavy cloud rainfall on 21 Day (January 11, 2020) along with daily precipitation data in the days before the flood (96 hours before the flood) which was received from the main Meteorological Organization of the country.
B: atmosphere data levels including: sea level (SLP), 850 and 500 hPa levels, vertical atmospheric velocity and wind flow levels of 1000, 850 and 500 hPa, specific humidity of 1000 and 700 hPa levels and 250 hPa surface flow winds for study days from the US National Center for Environmental Forecasting / National Atmospheric Research Center (NCEP/NCAR) were provided in the range of 0 to 60 degrees at north latitude and 0 to 80 degrees at east longitude, and finally, maps were drawn and prepared in Gardes software to provide the ability to interpret.
The synoptic analysis of sea level showed that: on the day of the heavy cloud, a low-height closed center with a central core of 1,010 hPa in the northeast-southwest direction covered the entire study area. Then, the high-height with a central core equal to 1030 hPa is located at northwest of Iran, northwest of Europe and on Tibet. According to the location of high-pressure dams around Iran and the location of low-pressure centers on the study area and water resources in the south, a strong pressure has been created. Subsequently, with height increasing, low-height with central core equal to 1440 geopotential meters is located at northeast-southwest direction of entire study area. And the low height of northern Russia extends to the Persian Gulf and provides the conditions for severe ascent and instability in a very large area. The rear dams of Nave transferred the cold air of the high latitudes into the bottom of the Nave located on the study area and have intensified the instability. Also, the geopotential height of 500 hPa level of deep descent is located at the northeast-southwest direction of Iran and core of the Nave covers the Persian Gulf completely, that is the study area in the best condition and in front of the Nave, which is diverged by hot and humid weather. This deepening of the rotation and the penetration of the Nave to the lower latitudes caused the cold air to fall. 
The analysis of the 250-hectopascal-level flow-wind shows that the flow-wind with a core speed of 65 meters per second has covered the entire study area by crossing above the Persian Gulf, and compared to the previous days, the flow-wind is completely meridional.
Synoptic analysis of the vertical velocity at the level of 1000 hPa shows that the maximum negative omega -0.2 to -0.15 Pascal per second in the northwest-southeast direction has covered the study area. The presence of negative omega index values ​​indicates the role of convection in intensifying precipitation in mentioned area and the dynamic ascent of air. The study map shows that compared to other countries in the study map, the maximum of negative omega is located on Iran, which is reduced along to the west of Iran. With increasing altitude, the maximum negative omega has increased to -0.3 Pascal per second and the core of the maximum negative omega is completely located on the study stations (Zahedan and Qeshm). Then, at the level of 500 hPa, the maximum negative omega has reached -0.6 Pascal per second and its value has doubled compared to the level of 850 hPa, which covers the northeast-southwest direction from Zahedan to the Strait of Hormuz. Cold air fall has increased with increasing of omega levels in the middle levels of the atmosphere.In other words, in the middle levels of the atmosphere, with increasing temperature difference between the earth's surface and the level of 500 hPa, the amount of precipitation has increased.
Synoptic analysis of specific moisture level of 1000 hPa shows that the most moisture deposition was from south water sources to the study area, and the amount of moisture equal to 14 grams per kilogram has entered the study area from the Oman Sea and then its amount has been reduced crossing to other regions of Iran. Furthermore, at the level of 700 hPa, the maximum advection of hot and humid air is in front of the upper atmosphere of Nave from the Red Sea over the study area. There is a moisture strip from the southeast to the whole area under analysis. These suitable humidity conditions with the depth of the western wave have been able to cause heavy cloud rainfall. The maximum amount of moisture in the study area is equal to 7 grams per kilogram, which is a large amount compared to heavy rainfalls.

Keywords: heavy rainfall, flood, synoptic, Zahedan, Qeshm

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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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Determination of flood-prone areas using Sentinel-1 Radar images
(Case study: Flood on March 2019, Kashkan River, Lorestan Province)

Introduction
Although natural hazards occur in all parts of the world, their incidence is higher in Asia than in any other part of the world. Natural phenomena are considered as natural hazards when they cause damage or financial losses to human beings. Iran is also one of the high-risk countries in terms of floods. Until 2002, about 467 floods have been recorded by the country's hydrometric stations. In addition to natural factors such as rainfall, researchers consider human impacts such as destruction of vegetation cover, soil destruction, inefficient management, destruction of pastures and forests, and encroachment on the river are the most important factors for the occurrence and damage of floods in the country. One of the most efficient and emerging tools in flood surveys is the use of radar images. SAR images and flood maps produced by radar images provide researchers valuable and reliable information. Moreover, maps obtained from SAR images help officials to manage the crisis and take preventive measures against floods. The Sentinel-1 satellite is part of the Copernicus program, launched by the European Space Agency, and is widely used in mapping flood-prone areas. The contribution of Sentinel-1 to the application of flood mapping arises from the sensitivity of the backscatter signal to open water. This study aims to determine high-risk and flood-prone areas along the Kashkan River using Sentinel-1 radar images.
Data and Methods
 The study area includes a part of the Kashkan river from Mamolan city to the connection point of this river to Seymareh river, after Pol-dokhtar city. The average annual discharge of the Kashkan river is 33.2 cubic meters per second based on the data of the Pole-Kashkan Station. The length of the river in the study area is about 100 km. To investigate flood-prone areas, we applied pre-processing and image-processing steps to each flood event including SAR images belonging to March 25^th, 2019, March 31^st 2019, and April 2^nd, 2019. SAR images were acquired from ESA Copernicus Open Access Hub. climatic data was downloaded from power.larc.nasa.gov. To create meander cross-sections, the Digital Elevation Model of the studied area was utilized. Cross-sections were created using QGIS software. Pre-processing steps include: applying orbit data, removing SAR thermal noise, calibration of SAR images, de-speckling and topographic correction. In image processing, we applied the Otsu thresholding method to distinguish water pixels from land pixels. In thresholding methods, the histogram of each image is divided into two parts according to the amount of gray composition. The higher the amount of gray (i.e., the pixel tends to be darker), the more pixels represent water, and conversely, the lighter-toned pixels (i.e., pixels that tend to whiten) represent land. The Otsu thresholding method is a commonly used method for water detection in SAR images. It uses an image histogram to determine the correct threshold. The most important feature of the Otsu method is that it is capable of determining the threshold automatically. The Otsu algorithm was applied to all images using MATLAB.
Results
According to the flood maps, on March 25th, 6.51 percent of the study area was flooded, while on March 31th, only 3.96 percent was flooded. This is mainly due to less precipitation on the 31st. On March 25^th the average daily precipitation was 47.46 mm while on 31^st of March the average daily precipitation was 31.64 mm. On April 2nd, however, there was no rainfall, on the day before more than 63 mm of precipitation has occurred. This massive amount of precipitation on the previous day has led to more than 25km2 being flooded in the studied area.
Conclusion
Results showed that meanders and their surrounding areas are the most dangerous sections in terms of flooding. The meander's dynamic and the river's hydrologic processes are essential factors affecting flooding in those sections. Generally, various factors affect flooding and the damage caused by it. This study aimed to determine flooded and flood-prone areas (according to flooded areas in previous events) using new methods in a short time and with high accuracy to use this tool for more accurate zoning and efficient planning in the future. The results showed that radar images are practical, robust, and reliable tools for determining flooded areas, especially for rapid and near-real-time studies of flood events.
Keywords: Floods, Radar images, Sentinel-1Satelitte, Kashkan river



 

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The statistical and spatial analysis of extreme rainfall is considered as one of the components of the management tool to prevent or control the risks caused by this phenomenon. The purpose of this research is to statistically investigate and spatially analyze the extreme precipitations in the Kashan Plain.The extreme rainfall of Kashan synoptic station were statistically analyzed in the period of 1971-2022 AD and the water year of 1350-1351 to 1401-1400 for a total of 18618 days.Then six cases of widespread extreme rainfall were selected and analyzed with the rainfall data of 13 synoptic stations and 11 rain gauge stations using geostatistics and spatial analysis methods.The extreme rainfall zonation maps of Kashan plain were prepared using by variogram models and kriging method.The results showed that the frequency of heavy and super heavy rains in winter and very heavy rains in spring is more than other seasons.The very high correlation of annual rainfall with the total and frequency of extreme rainfall shows that the volume of annual rainfall is more affected by the concentration of rainfall in short periods of a few days than by the distribution of rainfall throughout the year.Therefore, it was found that extreme precipitation plays an important role in the total precipitation and surface runoff, and as a result, the water balance of the region.The zoning maps showed that the rainfall of April 8, 2020, which is concentrated on the western belt and the heights of the basin, causes the erosion of the heights and causes floods in the foothills and low-lying areas of the plain. Also, rains such as the rains of March 8, 2019, which are most concentrated in the central areas, have a high potential to cause flooding.

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Investigation of the effects of Covid-19 pandemic on UHI in residential, industrial and green spaces of Tehran

 Abstract
Rapid urbanization in recent decades has been a major driver of ecosystems and environmental degradation, including changes in agricultural land use and forests. Urbanization is rapidly transforming ecosystems into buildings that increase heat storage capacity. Loss of vegetation and increase in built-up areas may ultimately affect climate variability and lead to the creation of urban heat islands. The occurrence of natural disasters such as flood, earthquake … is one of the most effecting factors on the changes in intensity of urban heat islands. So far, a lot of research has been done on how it is affected by various types of natural disasters such as floods, earthquakes, droughts and tsunamis.
Two major environmental challenges for many cities are preventing flooding after heavy rains and minimizing urban temperature rise due to the effects of heat islands. There is a close relationship between these two phenomena, because with increasing air temperature, the intensity of precipitation increases. Drought is also a phenomenon that is affected by rainfall, temperature, evapotranspiration, water and soil conditions. One of the major differences between drought and other natural disasters is that they occur over a longer period of time and gradually than others that occur suddenly. Another natural disaster is the tsunami, which increases the area of water by turning wetlands into lakes, thereby increasing the index of normal water differences, which has a strong negative relationship with surface temperature. Ecosystems in urban areas play a role in reducing the impact of urban heat islands. This is because plants and trees regulate the temperature of their foliage by evaporation and transpiration, which leads to a decrease in air temperature.
Applying the locked down of the Covid-19 pandemic since the spring of 2020 has led to the global restoration of climatic elements such as air quality and temperature. In this study, the effects of Covid-19 locked down on the intensity of urban heat islands due to the limitations in industrial activities such as factories and power plants and the application of new laws to reduce traffic in Tehran were investigated. In this regard, the Landsat-8 satellite taken from a part of Tehran city has been used.

Materials and Methods
In order to investigate the effects of locked down in the spring of 2020 on the intensity of urban heat islands; the status of UHI maps in Tehran during the same period of locked down in three years before and one year after has been studied. The proposed method in this paper consists of two main steps. The first step is to generate UHI maps using land surface temperature (LST), normalized difference vegetation index (NDVI) and land use / land cover map analysis. In the second step, in order to analyze the behavioral changes in the intensity of urban heat islands during locked down and compare it with previous and subsequent years, changes in the intensity of UHIs are monitored.
UHI maps consist of three classes of high, medium and low intensities urban heat islands, which are based on performing the rule based analysis on land surface temperature characteristics and normal vegetation difference index derived from Landsat-8 satellite images as well as land use / land cover map. LULC maps are produced by support vector machine classification method consisting of three classes of soil, building and vegetation. In order to calculate the spectral features used in the rule based analysis, atmospheric and radiometric corrections must first be made on the red, near-infrared, and thermal spectral bands of the image captured by the Landsat-8 satellite. Then, vegetation spectral indices including NDVI and PV indices are generated.

Disscussion of Results
The capability of the proposed algorithm in this paper is first evaluated in the whole area covered by satellite images taken from the city of Tehran, and then in three areas including residential, industrial and green spaces. The data used in this article are images taken by the OLI sensor of Landsat-8 satellite in the spring of 2017-2021.
In the first step of the proposed method, maps of urban heat islands are generated based on multi-temporal satellite images of Landsat-8 taken in the years 2017to 2021 in the MATLAB programming software. Then, by comparing pairs of UHI maps in each of the residential, industrial and green space study areas, the trend of changes in the intensity of UHI is analyzed and the effects of locked down application in 2020 are evaluated.
The results of changes detection in urban heat islands in the period under consideration in this study showed that the percentage of areas that are in the class of high UHI in 2020 due to locked down of pandemic Covid-19 compared to the average of three years before that is 55.71%, has a decrease of 17.61%. The percentage of areas in the class of medium UHI intensity in 2020 due to locked down compared to the average of three years ago, which is 39%, increased by 4.8%, and in 2021 this amount again has decreased to less than the average. Also, the percentage of low intensity UHI class in 1399 compared to the average of three years ago, which is 5.3%, has increased by 12.8%.

Conclusion
In this study, the effect of locked down application due to the Covid-19 virus pandemic, which was applied in Iran in the spring of 2020 is investigated on the intensity of  urban heat islands in a part of Tehran city and three selected areas with residential, industrial and green space. Detection of changes in the intensity of urban heat islands was done based on the post-classification method and on the UHI classification maps related to the years 2017 to 2021. In order to produce UHI maps, in addition to the land surface temperature, the amount of vegetation index and the type of land use / land cover class were also used in the form of a set of classification rules.
Comparing the results of the study areas of residential, industrial and green spaces, it is important to note that the rate of reduction of the area of UHI with high intensity in the residential area is 5.25% more than the industrial area and 6.1% more than the green space. However, the reduction of locked down restrictions in 2021 had the greatest effect on the return of the area of ​​the high UHI class and caused the area of ​​this class to increase by 23% compared to 2020. These results indicate the fact that restrictions on the activities of industrial units such as factories and power plants and the application of new laws to reduce traffic, despite the same weather conditions in an area have been able to significantly reduce the severity of urban heat islands.

 Keywords: Urban Heat Islands, Land Surface Temperature, Vegetation Index, Change Detection, Covid-19

 

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Estimation of methane gas leakage from Mashhad urban landfills and evaluation of economic and environmental effects
Abstract
This study, which was conducted in 8 urban gas areas of Mashhad; At first, descriptive statistics of the state of Mashhad urban gas regulators and different leakage modes were presented; In order to analyze the collected data and investigate the causes of leakage, the relationship between 5 variables and the amount of leakage from gas regulators was tested with the Statistical Package for the Social Sciences (SPSS) V.26 software; These 5 variables are: regulator equipment/connections, regulator operation age, regulator service type (domestic, industrial and commercial), urban area and different seasons of the year.
The results of the analysis showed that there was a significant difference between the type of equipment/connections and leakage. (P-Value = 0.0001). Also, a significant difference was observed among other variables of the research (the operation age of the regulator, the type of regulator service (domestic, industrial and commercial), the urban area and different seasons of the year) with the leakage rate (P-Value=0.0001); The pressure drop due to the greater demand of gas consumption in the winter season has reduced the amount of leakage compared to other seasons; The influence of the age of distribution network equipment/connections due to wear and tear and longer life will aggravate the amount of methane gas leakage; Also, the amount of leakage in commercial places had a significant difference with other types of uses; Being in an urban area has also increased the amount of methane gas leakage compared to other areas; The type and quality of equipment and connections as the main and influential factor in methane gas leakage should be considered by managers and officials in this field of work.
Keyword: Methane, Riser, Urban area, Environmental effects, Economy Effects, Gas, Emission