نشریه تحلیل فضایی مخاطرات محیطی
سال پنجم شماره 3 (پاییز 1397)

Global temperatures have increased in the past 100 years by an average of 0.74°C (IPCC, 2013), with minimum temperatures increasing faster than maximum temperatures and winter temperatures increasing faster than summer temperatures (IPCC, 2013). Total annual rainfall tends to increase at the higher latitudes and near the equator, while rainfall in the sub-tropics is likely to decline and become more variable (Asseng et al., 2016). Considering probability of occurrence climate change and its hazardous impacts, it seems essential to clarify future climate. General Circulation Models is widely used to assess future climate and its probable changes. Although the outputs of these models are not appropriate for small-scale regions because of its coarse resolution. Thus, statistical or dynamical techniques are used to downscaling the outputs of these models using observed data in weather stations. Despite the fact that frequent researches has done in relation with climate and climate change, but it is unclear yet future climate, especially climate change, in Iran. The goal of this study was to present the results of climate change predictions which has been done so far in Iran, in order to help prospective studies in this field. This step can be important to consider new questions and challenges. In this study, we assessed future climate change in Iran using results of statistical downscaling studies of atmospheric-oceanic General Circulation Model’s outputs. To do this, studies on prediction of precipitation and temperature parameters in Iran by different emission scenarios, atmospheric-oceanic General Circulation Model’s outputs and statistical downscaling techniques were gathered. Then a comprehensive view about Iran's future climate and specifically the climate changes presented by descriptive-content based analysis and comparison of their results. Used downscaling techniques in these researches were included: LARS-WG, SDSM, ASD, Clim-Gen and used General Circulation Models were: HADCM3, BCM2, IPCM4, MIHR, CGCM3, CCSM4 and finally used emission scenarios were A1B, A1, A2, B1, B2, RCP4.5. Based on climatically geographical differences in Iran, the results discussed separately in six different regions across Iran. The results of various regions are different because of usage of different models and different climatological and geographical conditions. These models simulate temperature more accurate than precipitation, because of more variability and temporal discontinuity of the precipitation relative to temperature. Assessment of results in 30-year periods from 2011 to 2099 showed that in North West of Iran (Ardebil, Azarbayejan- Sharqi and Azarbayejan- Qarbi provinces), precipitation will be decreasing, decreasing- oscillating, decreasing- transitional and temperature will be increasing. Decreasing- transitional trend, in other words decrease precipitation in cold seasons and increase of it in warm seasons, lead to a decrease in the snow occurrence and an increase in the rainfall occurrence. Thus, it can affect the frequency of floods occurrence. In west and southwest region of Iran precipitation has been predicted to have different changes in various sections of it. It will be decreasing-oscillating in Kermanshah and Kordestan provinces and oscillating in Hamedan province. Precipitation will increase in Lorestan and finally it expected to decrease in Khoozestan, Chaharmahal-va-Bakhtiari, and Ilam. However Temperature will rise across this region. In south and south east region of Iran (Fars, Hormozgan, Kerman and sistan-va-Baloochestan provinces), precipitation will be decreasing, decreasing-oscillating, oscillating and increasing-oscillating. Also in this region, temperature expected to increase similar to other regions. In east and north east of Iran (Khorasan Shomali, Khorasan Razavi and Khorasan Jonobi provinces), temperature predicted to be increasing-oscillating, that it is different with other regions. Changes in precipitation will be oscillating and decreasing-oscillating. In the northern coasts of Iran (Gilan, Mazandaran and Golestan provinces), precipitation changes will be decreasing and increasing-oscillating and temperature changes expected to be increasing and increasing-oscillating. Thus, it expected to increase heat wave, drought, and aridness condition as the results of these changes. Precipitation changes in south of Alborz region and center of Iran (Semnan, Tehran, Qazvin, Markazi, Esfahan and Yazd provinces), will be decreasing, oscillating, increasing-oscillating. Also temperature will be increasing in this region. Considering the decreasing trend of precipitation and the increasing trend of temperature in the most of Iran, it is probable to increase the occurrence of climatic and environmental hazards such as flood, drought and heat waves in the future. These events can have serious effects on water resources, agriculture and tourism, especially in regions such as Iran where have sensitive environment.

Environment, development and sustainability are the three significant issues of worldwide concern. Environmental vulnerability and assessment of natural and anthropogenic activities impacts represent a comprehensive evaluation approach. The main purpose of this study is to present a comprehensive and novel framework in order to environmental vulnerability assessment using by spatial data and techniques. The method of this research is analytical-descriptive. The basic premise is that the finding of this study can be applied in the local planning system and policy making process of environmental conservation particularly to cope with rapid environmental change. The environmental vulnerability is defined and governed by four factors: hydro-meteorology signatures, environmental attributes, human activities and natural hazard. Based on data availability and vulnerability status of different areas, there is no general rule for selecting how many variables are required to assess the environmental vulnerability. In this study, 18 variables were taken into account and organized into four aforementioned groups. The process of environmental vulnerability index is proposed to integrate AHP approach, remote sensing indices and GIS techniques. The environmental vulnerability showed distinct spatial distribution in the study area. Furthermore, the distribution of heavy and very heavy vulnerability patterns mainly occur in low and medium lands where the human activities have been developing rapidly and is the nearest region to Urmia lake in the west region.

Sea surface temperature is one of the most effective physical parameters that affects the health of coral reefs communities.High frequency of the bleaching phenomenon has extensively occurred in the Persian Gulf in the recent years due to the increase in temperature and increased changes in the sea surface temperature (SST) resulting in great mortality in the coral communities. The aim of this research is to determinate a temperature threshold which may function as a warning for the incidence anticipation of this phenomenon. Data on the variation of the SST that has been taken from National Oceanic and Atmospheric Administration (NOAA). Information related to bleaching in the regions of the southern Persian Gulf was extracted from the published papers and reports. Each of these sources also has been extracted for a 35-year statistical course (1980-2015) and by the index of degree heating weeks (DHWs) determined for the same statistical course in this research for the assessment and anticipation of bleaching phenomenon. For reviewing of the work accuracy, Peirce Skill Score (PSS) technique was used to quantify the accuracy of previous and subsequent anticipations. According to the derived results, DHWs threshold for the study region was determined to be 7.13. the threshold 7.13 for DHW is suggested as a caution threshold for bleaching incidence in southern regions of the Persian Gulf that is whenever the values of weekly positive temperature DHW show number 7.13 and higher, there is an expectation of bleaching phenomenon incidence of corals for these regions. And the score of PSS= 0.72 derived from the amounts of H= 7/8= 0.87 for the Hit rate and F= 4/26= 0.15 for the False alarm rate of the bleaching was obtained for the southern regions of Persian Gulf and study region. In northern regions of the Persian Gulf the threshold 5.3 for DHW is suggested as a caution threshold for bleaching incidence. The rate of pss = 0.62 derived from the amounts of (3/4 = 0.75) for the Hit rate and ( 3/23 = 0.13) for the False alarm rate of the bleaching was obtained for the northern regions of Persian Gulf and study region. Difference in DHWs values of the south and north of Persian Gulf shows more resistance of the corals of south Persian Gulf against DHW changes and SST anomalies. Also the amounts of DHW alongside SST can help more completely to the anticipation of bleaching phenomenon.

Atmospheric boundary layer (ABL), is the lowest part of the atmosphere. Its behavior is directly influenced by its contact with earth surface. On earth it usually responds to changes in surface radiative forcing in an hour or less. In this layer physical quantities such as flow velocity, temperature, moisture, etc., display rapid fluctuations (turbulence) and vertical mixing is strong. Above the ABL is the "free atmosphere" where the wind is approximately geostrophic while within the ABL the wind is affected by surface drag and turns across the isobars. The land use/cover changes affecting the surface radiative forces lead to ABL spatio-temporal variation. The main object of this study is to analysis the association among ABL height and built-up spatial growth in Kermanshah city. Data and methods: Multi-temporal satellite images from Landsat imagery data for 1990 to 2015 series of sensors TM, and OLI (Landsat 5 and 8) were taken from USGS database. Data of the Atmospheric Boundary layer height (ABL height) for the city of Kermanshah also were taken during 1990- 2015 from ECMWF – Eran-Intrim website at 0.0125 ° spatial resolution. Firstly, we analysis the temporal trends of ABL height of Kermanshah in summer and winter using linear regression in 0.95 confidence level (P_value = 0.05). The built up area of Kermanshah has been extracted from TM and OLI images using supervised classification method and maximum likelihood classification(MLC) algorithm in GIS image analysis. The Pearson correlation analysis has been used to reveal the relationship between annual ABL height variation and built-up growth of Kermanshah. The results of long term trend of Built up growth of Kermanshah that extracted using MLC algorithm as can be seen in figure 1 indicated that the built up area in Kermanshah has been growth by 1.02 square kilometer annually.According the figure 2, The results of annual trend of ABL height in summer and winter also reveals that in summer there is no significant trends in ABL height while in winter the significant increasing long term trend has been observed in ABL height.

Introduction: Trend of increasing natural resource degradation in many parts of the world, is a serious threat to humanity. Desertification is one of the manifestations of the damage that has already suffered as a scourge of many countries, including developing countries are. At present, remote sensing is one of technologies with timeliness data and accuracy suitable for monitoring land use changes in the areas of natural resources. Desertification monitoring and tracking changes, which seeks to desertification that the change could be for any reason and also collect and analyze data from activities, projects, plans and programs that may desertification range condition assessment and reporting to provide them. The purpose of this study was to evaluate changes in land use on desertification monitoring using remote sensing techniques to the agricultural lands around zayandeh rood in the East region of Isfahan. materials and methods: In this study, the image sensor of TM to date 1987, 1998, ETM+ to date 2002 and OLI to date 2014 related to the Landsat 5,7 and 8 to obtain the land use map used and then was performed radiometric and geometric correction.Then was used the color combination, the main component analysis, vegetation index and supervised classification method for detection of complications and the maximum likelihood algorithm as the most appropriate method for supervised classification in classes 9 of land cover. After production the land use map correctness evaluating operations with calculation error matrix and then was performed detection operations for these maps. Finally, for desertification of monitoring, land use years 27 changes around zayandeh rood using the comparison method is paid changes to identify and was obtained the area of each use. Results and discussion: For investigate the the process of desertification, land use changes in the period of 27 years. In order to select the appropriate bands in supplying the best color composite satellite images and operations classified in order to reconstruct the images, index optimization factor was applied. The results of accuracy assessment shows that For all the images above the 80% overall accuracy and Kappa statistics indicate that almost 80 percent. Generally good agreement between the classification and classes of users on the ground there. By comparing bit images specified land use changes in the period of 27 years, riverbank has the greatest changes during this period. So during these 27 years the river high Zayandehrood degradation, which could be due to the expansion of agricultural activities in rivers. This degradation is generally represents gradual drying of the river and go surrounding cultivated by farmers. This degradation process in the margins of the river and the gradual drying of the river towards the desertification situation in the region shows. Conclusion: In year 27 time period, Zayandeh Rood neighboring rivers has changed dramatically, so 86.43% of neighboring rivers was destroyed due to the expansion of agricultural activities vicinity of the river and drying river. Another significant changes, loss of agricultural land is notable such that 64% of this land has been reduced compared to 1987. Of reasons for the loss of agricultural land will be noted the region drought and Zayandeh Rood river drying up and Low rainfall, land use change and the proximity of the region desert. Also, has become about hectares 324.99 Of salt marsh lands to agricultural land. Moreover, the developed urban areas to its development contributed agricultural land and rangeland. Bayer lands around Zayandeh Rood Increase and also in region of rangeland lands Low and has increased Bayer lands and somewhat until agricultural land which inappropriate use of this land shows in order to the agricultural. That this is the desertification progress in the region. Generally desertification process in this period years 27 has been a growing trend.Therefore multi-temporal and multi-spectral satellite data for enhancement, especially for desertification monitoring was large capability and classification after comparison method is helpful for determine the type and direction of changes occurred. Since the development of desertification, limited to a small area and is not recommended range is therefore more effective, in addition to work sheets, other sheets around the area also evaluate the process of desertification is to allow for planning and management in the field of combating desertification exist.

Problem statement: The occurrence of terrible floods due to climate change has caused much damages in different parts of the world in recent decades, and the effect of these changes is more pronounced in dry areas. Floods are the most common environmental damage. On average, 60 floods occur annually in Iran, with an average annual flood loss of 141 people, meaning more than 2 deaths per year per flood event. Research Methodology: The study area consists of six stations located in Hormozgan, Kerman, Yazd, Kohgiluyeh, and Fars provinces. In this study, two types of ground and high data are used as follows:A) - Using daily rainfall data of the 44 years (1967-2014) statistical stations of the region obtained from the country's Meteorological Organization B) Use of high-level data. Includes revised data for geopotential heights, sea level pressure, wind direction, meridian wind, omega, and humidity, from the National Center for Environmental Excellence at Colorado. To conduct synoptic analysis, the circular environmental method was used; after observing the daily rainfall during the statistical period of all rainfall over 50 mm in selected stations of Yazd, Jiroft, Shiraz, Bandar Abbas, and Yasuj, 118 heavy rainfall events were investigated. After identifying and separating days, 105 observation systems were identified and analyzed.
After the evaluation and control of the pressure maps of the sea of the systems of landing, 4 patterns were selected and identified. Explain and interpret the results: The results showed that heavy precipitation occurred in the months of December, December, February, February, and November, respectively. Since November, with the retreat of high-performance dynamic systems to the southern latitudes and the influx of western winds from high latitudes on the area, conditions for the occurrence of heavy rainfall are provided. Most centers with 9 heavy rainwater systems of Sudan's lowland, 6 the moderate Sudanese-Mediterranean component of the Middle East has been on Iraq, and the four satellite systems have been the Mediterranean-Sudan-Mediterranean integration. The most frequent Sudanese pattern in 2-day continuity with 17 cases was Sudan-Mediterranean integration pattern with 7 cases in 3-day continuation, Sudanese-Mediterranean integration pattern in the Eastern Mediterranean, 4-day continuity with 7 events, and equidistant Mediterranean pattern The continuity of 2 to 4 days has been due to the increased load of Mediterranean systems ranging from 70 to 90 mm.

Dust is one of the environmental hazards and atmospheric phenomena familiar to residents of the southern and southeastern parts of the country. Which each year causes a lot of damages to various sectors such as environment, agriculture, health, transportation, facilities, and so on. Therefore, in this research, we investigated and identified the sources of dust in the area, the intensity and frequency of dust, its governing patterns and dust-free areas during the 30-year statistical period (1984-1984). The research method is a combination of statistical, synoptic and remote sensing analysis. The data used include the hourly data of 22 synoptic stations (8 times per 24 hours), CDC1 data up to 2006, and then GDAS data, temperature, wind direction and wind speed, geopotential height at different levels. In selecting the studied days, it was tried to select the selected samples with a duration of three days and more, the spatial expansion of at least 4 stations with horizontal vision less than 1000 meters. For this purpose, were used the characteristics of the 11.3 and 12-micrometric wavelengths of the wavelengths were used to visualize the dust on the MODIS images from the ENVI 5.2 software environment, to track the wind direction from the GDAS data in the HYSPLIT software environment and to study the maps of various atmospheric levels from Temperature, wind speed, wind speed and geopotential heights were used from GRADS software and weather data stations. The annual frequency of the occurrence of days with dusty phenomena in the study area showed that during the statistical period of 1984-2013, a total of 11616 days with dust was recorded with the 06 code for south and southeast of Iran at the stations study. Most days with the dust event at Zabol Station with 1136 days and the lowest occurrence occurred at Bandar Abbas Station with 171 days during the studied period. In general, the annual survey of the data shows that the phenomenon of dust in the stations study in the past has been high and very high; however, in recent years, it has been expanding more and more than the past, and has been growing. The results of the monthly and seasonal surveys showed that the summer and the months of June, July, August and May are the most frequent and most frequent, with a peak of 1000 meters, respectively, and December have the lowest dust incidence and Zabul and Zahedan station