فهرست مطالب حمید نظری پور

Today, the adverse effects of climate change and the resulting damages have become an environmental, social and economic problem. Evaluating the resilience of local communities against climate change and its limitations and obstacles is an important step for identifying effective mechanisms and prioritizing management that promotes flexibility and increases adaptation capacity. Due to the importance of this issue, the current research aims to identify the limitations of coping. and resilience against the risks caused by climate change was carried out in Zahedan city. The current research is applied in terms of purpose and its method is descriptive-analytical. The tool for collecting data and information was a researcher-made questionnaire from the study area. The statistical population was the rural households of Zahedan city, which due to the dispersion of villages and their large number, 12 villages (2 villages from each village) were randomly selected as sample villages. According to 832 households of the studied society and using Cochran's formula, the sample size of 263 households was obtained, which was increased to 265 households. In order to analyze the data, ISDM method was used in SPSS software and structural equation method in LISREL software. The results showed that 12.83% of residents have weak perception, 23.02% have moderate perception, 35.85% have strong perception and 28.30% have very strong perception of climate change. Also, the physical factor (factor load 0.941), social factor (factor load 0.922) and economic factor (factor load 0.895) are the most important limitations of resilience against the risks caused by climate change in Zahedan city.

A lack of adaptive capacities for climate change prevents poor farmers from diversifying agricultural production. Climate change adaptation strategies can reduce the production risk relating to unforeseen climatic shocks and increase farmers’ food, income, and livelihood security. This paper investigates date palm farmers’ adaptive capacities to adapt climate change strategies to reduce the date production risk. The study collected 300 farm-level micro-data of date palm farmers with the direct cooperation. The survey was conducted during periods between July and September of 2022. Date palm farmers’ adaptive capacities were estimated quantitatively by categorizing the farmers as high, moderate, and low-level adapters to climate change adaptation strategies. In this study, a Cobb–Douglas production function was used to measure the effects of farmers’ adaptive capacities on date production. The obtained results show that farmers are moderately adaptive in terms of adaptation strategies on climate change and the degree of adaptation capacities. Agronomic practices such as the quantity of fertilizer used, the amount of labor, the farm’s size, and extension contacts have a substantial impact on date production. This study recommends that a farmer more significantly adjusts to adaptation strategies on climate change to reduce date production. These strategies will help farmers to reduce the risk and produce higher quality date fruit. Consequently, date palm farmers should facilitate better extension services and change the present agronomic practice to attain a higher adaptation status. It can be very clearly seen that low adaptability results in lower date yields

Precipitation is a parameter related to climate and research on it is facing problems due to the lack of continuous data. Accurate planning and management of water resources depends on the availability of continuous and accurate precipitation data at meteorological stations. Hence, estimation of missing rainfall data is important in order to obtain more reliable results. Various imputation methods have been proposed and developed by researchers to estimate missing values in daily and monthly rainfall data. In most situations, spatial interpolation techniques such as normal ratio and inverse distance methods are used for estimating missing rainfall values at a particular target station based on the available rainfall values recorded at the neighboring stations. Moreover, these two methods are found to be very useful in the case where the neighboring stations are very close and highly correlated with the target stations. In this study, several modifications and improvements have been proposed to these methods in order to estimate the missing rainfall values at the target station using the information from the nearby stations. The methods have been tested with different percentages of missing rainfall values and also with a radius range of 75 km to 150 km in the catchment area of South Balochestan. The result indicate that the performance of these modified methods improved the estimation of missing rainfall values at the target station based on the similarity index (S-index), mean absolute error (MAE) and coefficient of correlation (R).

Drought, as one of the major natural hazards, affects the environment, society, agriculture and economy. Several indices have been developed for drought quantification based on ground data and remote sensing. Traditional drought quantification methods are based on meteorological data and conventional criteria and are usually not available in near real- time. On the other hand, data based on remote sensing are continuously available and can be used to detect several aspects and characteristics of drought. The purpose of this research is to investigate and compare different indices derived from remote sensing and meteorological data for local scale drought monitoring (eastern part of Kurdistan Province).

Seven drought indices were compared, including Vegetation Condition Index (VCI), Vegetation Drought Index (VDI), Vegetation Health Index (VHI), Vegetation Supply Water Index (VSWI), Normalized Difference Vegetation Index (NDVI), Temperature Condition Index (TCI) and Standardized Precipitation Index (SPI). Remote sensing indicators are derived from MODIS data. The meteorological index SPI is obtained by combining the data of rain gauge stations and gridded precipitation data. The digital maps of the seven drought indicators have been prepared for the period of 2002-2021 with the same time interval (16-days). To analyze the characteristics of each drought index, a comparative method including the selection of specific periods of drought and spatial drought identification characteristics has been used. The comparison of drought indicators was done May, which is the growing season. Finally, Pearson's correlation analysis was used to evaluate the behavioral similarity of the indicators.

The spatial comparative analysis between the drought indicators showed that all the indicators had certain adaptations in the distribution of the regional scale of drought, especially those derived from similar data sets. Meanwhile, the difference in local scale distribution was found among different groups of indicators. The results showed that the general trend of the VSWI had a better compliance with the standardized precipitation index. Based on the correlation analysis, it was proved that the VSWI  can be a better reflection of the amount of rainfall and the severity of drought due to the lack of rainfall. In addition, the land surface temperature (LST) contributes more to the VSWI results than the reflectance information. A two-period (32-day) delay of the indicators indicating the state of vegetation is a good indicator of the meteorological drought conditions in the study area. The absence and lack of rainfall in at least five periods (80 days) earlier can had a serious effect on the state of vegetation in the existing conditions. Plain and mountainside areas located in the central, eastern and south-eastern parts of the study area were more sensitive to drought conditions than other parts due to the dominance of grain farming, especially rainfed farming.

While remote sensing drought indicators have many advantages in the analysis of drought in real-time, meteorological drought indicators are still the priority for drought monitoring. This is due to the dependence of hydrological and agricultural systems on meteorological conditions. Mainly, these hydrological and agricultural systems in different regions respond to meteorological fluctuations with different time delays. Understanding these complex relationships between meteorological, hydrological and agricultural systems can be useful in early preparation programs against drought and its management.

By assessing the trend of air temperature changes, it is possible to explore traces of climatic changes in the area of Iran. Climate change and temperature increase are important human-environmental issues. Based on the change point method, it is possible to identify the onset time of changes in basic variables such as minimum and maximum temperature. Therefore, the present research aims to analyze the change point of temperature thresholds of heat and cold waves in Iran. The temperature threshold means the 95th percentile for maximum temperature values and the 5th percentile for minimum values. For this purpose, the temperature data (minimum and maximum) of 43 synoptic stations in Iran, which have a long statistical period (1966-2018) and suitable distribution, were used. To identify the temperature threshold change time, three change point methods - Pettitt, SNHT, and Buishand's Range Test were used. The results showed that the temperature threshold of heat and cold waves has been increasing over the past few decades. The rising growth rate is equal to 0.019 and 0.052 degrees Celsius per year, respectively. Therefore, in the current study, it was found that the increasing trend of the temperature threshold led to an increase in the frequency of maximum temperatures, and on the other hand, it will lead to an increase in hot days and a decrease in cold nights, in addition to the higher frequency of events, it can be stated that the frequencies will move towards higher values. Based on the results of the spatial-temporal analysis of the thresholds, the increasing trend of the minimum temperature in the northwest, Zagros, and southeast regions of Iran is quite evident. And from the other results of this study, we can emphasize the time of the change point or jump of the temperature threshold of cold and heat waves around 1991. The mentioned year is in line with global studies

Flood risk maps and Flood zoning techniques are useful tools to manage this hazard in the catchment and mitigation of flood impacts. In South Baluchestan and Kahir Basin, due to the existence of winter and summer precipitation regimes, the occurrence of flash floods is inevitable due to the establishment of rural communities and settlements in flood-prone areas, the flooding has caused many damages to the region's vulnerable population. In order to zone flood risk and prepare flood risk maps, climatic data, hydrological, land cover, and topography of the basin were prepared from reliable sources and according to scientific studies, 12 variables affecting flood risk in the form of five main components (Hydrology, vegetation, land cover, climate, and topography) were prepared. According to the regional conditions of the basin, using the opinions of experts based on scientific methods, the weight of each variable and component was determined by Analytical Hierarchy Process(AHP). Using two methods of fuzzy overlay, Weighted Overlay, and the Geographical Information System facilities, a map of variables and components was prepared after reclassification and fuzzy membership function with appropriate operators. The results showed that the fuzzy overlay method concerning its dominant logic has a better distinction of flood-prone areas and can help determine flood hazard micro-zonation in the drainage basins like the Kahir basin. By comparing the results from the real data of the January 2020 flood obtained from satellite images. Due to poor infrastructure and high economic, the risk of flooding may be more harmful and widespread in the future.

Date palm (Phoenix dactylifera L.) is an important commercial crop in many countries, including Iran. Understanding the possible future climate conditions will enable environmental managers to prepare appropriate strategies to manage the changes. In the current study, climatic conditions and water requirement of date palm in arid regions of southeastern Iran have been simulated under possible future climatic conditions. For this purpose, the stochastic weather generator model (LARS-WG) has been used to generate local-scale climate scenarios based on global climate models (GCM) to assess the effects of future climate change. Forecasts have been made for the near future period (2040-2021) and the distant future (2080-2061) based on observational data of Saravan and Iranshahr weather stations in the base period of 1987-2010. The water requirement of date palm has also been determined through CROPWAT 8.0 computer program for the intended courses based on simulated climatic data. The results showed that a relative decrease in climatic suitability for date palm cultivation in the study district by 2100. This means that the predicted increase in precipitation will be not able to compensate for the evapotranspiration deficit due to the predicted increase in temperature, and these conditions will increase the water requirement of the crop. But on the other hand, changes in rainfall regime (time of receipt) and extreme climate events will have negative effects on date palm cultivation in southeastern Iran. The results of this research can play a significant role in adopting forward-looking policies to address the impacts and challenges of climate change on the agriculture section of Iran.

In this study, the decade variability of frequency and severity of drought in Iran has been investigated. The one-month scale data from the standardized precipitation-evapotranspiration index (SPEI 01) in the period 1956 - 2015 have been used. Based on the common numerical thresholds, the characteristics of the frequency and severity of drought for each pixel have been calculated and they are the basis for the analysis of the drought situation. Then, the frequency of drought severity classes was calculated and its trend was investigated using the non-parametric Mann-Kendall test. The findings indicated the spatio-temporal variability of drought frequency and intensity patterns in Iran. The frequency of mild droughts has decreased from south to north and from east to west; while the frequency of more severe droughts has increased from north to south and from west to east. The frequency of mild droughts in the southeast, northwest, and northeast has increased by 5 to 40 percent. While the frequency of more severe droughts in most parts of Iran has increased between 10 and 20 percent. Variability in the frequency of more severe droughts is more pronounced in the Central Plateau catchment area as well as in the Persian Gulf-Oman Sea. The trend of drought intensity is decreasing (drought intensification) at the same time as the prevailing rainfall regime in Iran. A significant increase in drought intensity (wet season intensification) is observed only in southeastern Iran at the same time as the monsoon regime. However, extra-arid and arid regions of southeastern Iran are affected by the frequency and severity of drought and have a high degree of vulnerability.

In arid environments, extreme wet and dry periods are considered a serious threat to human societies. These periods affect the agricultural sector, transportation networks, vegetation, the environment, water resources, and the sustainability of human societies. Extra-arid and arid regions of southeastern Iran are good examples of an area affected by extreme climate events hazards, such as, floods and droughts. This study, to better understanding the causes and processes leading to extremely dry and wet episodes in southeastern Iran, investigates the space and time variability of winter dry/wet events and their associated large-scale atmospheric driving circulations. The data of this research are of two categories. Monthly gridded data from 1-month standardized precipitation-evapotranspiration index (SPEI01) and daily average geopotential field data of 500 hPa (HGT500) retrieved from NCEP/NCAR Reanalysis data over a period of 55 years (1960-2015) have been used to evaluate the dry and wet spells and circulation types (CTs) of winter atmosphere, respectively. December to March (DJFM) are selected as winter months and data for 55 winters are extracted through MATLAB programming facilities in the southeastern part of Iran. 168 gridpoints cover the southeastern part of Iran. The western and northern boundaries of the study area are bounded by the meridian 55 degrees east and 32 degrees north. Finally, a new database with the arrangement  was formed and became the basis for further processing. Of course, the database of the variable height of geopotential is different and has a matrix with dimensions . Extreme wet and dry periods have been identified based on SPEI01 values outside the range [+1.5, -1.5], respectively. By applying the Principal Component Analysis (PCA) with Varimax rotation on S-mode analysis and correlation matrix of the SPEI01 field, three sub-regions of independent climatic variability are identified. Large-scale daily atmospheric circulation patterns are then classified into twelve circulation types (CTs) by applying PCA to the 500 hPa geopotential height fields and non-iterative K-means clustering technique to the retained PCA scores, followed by Esteban et al. (2005). The linkage between daily CTs and winter, dry/wet spells in the region are investigated by applying the performance index (PI) to the daily precipitation data of three representative stations of the identified sub-regions. Results show a significant relationship between the frequencies of occurrence of the identified CTs and of dry/wet spells at the three representative stations, in extra-arid and arid regions of southeastern Iran. 6 circulation patterns (CT) were identified for the study area, each of which has a negative phase and a positive phase, and a total of 12 patterns were identified. According to the results of the performance index, CT1+ pattern with deep Trough and ridge pattern on the Mediterranean Sea and the Caspian Sea, respectively, has a large share in providing above-average rainfall (P1> 1) in the east and southeast (Zahedan station). But this phase is related to the dry periods of the study area. Unlike the second type (CT2), its positive phase (+CT2) is associated with dry periods and its negative phase (-CT2) is associated with wet periods.

Blizzards are severe forms of snowstorms that occur in the middle and upper latitudes of the northern hemisphere in winter season. The devastating disaster of a snowstorm with dangerous blizzard conditions on February 3 to 9, 1972, with more than 4,000 dead in Iran, is one of the most destructive snowstorms in the world. In this study, aspects of the synoptic scale at the time of occurrence of this phenomenon have been investigated using the reanalysis data of NCEP/NCAR and ECMWF databases. The variables used include geopotential height, sea level pressure, air temperature, specific humidity, relative humidity and zonal and meridional velocity of wind. In addition, the parameters of omega, relative vorticity, and zonal jet index have been calculated to explain the performance of the atmospheric system. The results indicate the dominance of atmospheric block (Rex) system in two separate phases from 3 to 6 February and from 7 to 9 February. The role of the artic polar vortex in injecting cold air into low latitudes and a noticeable decrease in temperature before a snowstorm and blizzard in saturating the atmosphere and providing the moisture needed for snowfall is quite evident. The zonal index of Jetstream showed the significant jump of the core of subtropical jet stream at the time of the occurrence of this extreme phenomenon.The zonal index of Jetstream showed the significant jump of the core of subtropical jet stream at the time of the occurrence of this extreme phenomenon.The zonal index of Jetstream showed the significant jump of the core of subtropical jet stream at the time of the occurrence of this extreme phenomenon.

The main objective of the study was to investigate spatial and statistical and spectral characteristics of Iranshahr weather station wind speed in the marge of jazmourian wetland in southeastern Iran. Daily wind data from Iranshahr weather station located in eastern marge of wetland, operated from 1991 to 2020, used in the analysis. Simple linear regression (SLR) method is used to analyze the trend and spectral analysis and standard normal homogeneity (SNHT) test are used to analyze cycles and wind speed jumps. Preliminary analyzes revealed that the maximum daily wind speed occurs in July, June and August, and the minimum occurs in November and December. Results of Simple linear regression test showed that the wind speed during the study period in the monthly scale decreased. However, the standard normal homogeneity does not confirm a significant jump in the average wind speed. In order to investigate possible changes in the average wind speed in the frequency domain, spectral analysis method has been applied to monthly and annual data. Significant cycles extracted for the annual and monthly data of the average wind speed of Iranshahr station indicate the existence of short-term and medium-term cycles in the data of the average wind speed of the station.. In order to investigate possible changes in the average wind speed in the frequency domain, spectral analysis method has been applied to monthly and annual data. Significant cycles extracted for the annual and monthly data of the average wind speed of Iranshahr station indicate the existence of short-term and medium-term cycles in the data of the average wind speed of the station.. In order to investigate possible changes in the average wind speed in the frequency domain, spectral analysis method has been applied to monthly and annual data. Significant cycles extracted for the annual and monthly data of the average wind speed of Iranshahr station indicate the existence of short-term and medium-term cycles in the data of the average wind speed of the station.

Public open spaces in residential areas of cities are one of the fields for the social interactions. Hence, the climatic and geometric characteristics of urban open spaces must be harmonious and facilitate social relations. This is doubly important, especially in hot and arid environments. The purpose of this study is to investigate the thermal comfort of urban open space and its influential components in strengthening social relations in the old neighborhood of Quds neighborhood in Zahedan.

The present paper is applied in terms of purpose and experimental-correlation in terms of method. To evaluate the thermal comfort of the outdoor spaces, physiologically equivalent temperature (PET) and predicted mean votes (PMV) based RayMan model and universal thermal comfort index (UTCI) based on BioKlima model have been used. A new mathematical model is then proposed based on the correlation relations between environmental variables and individual subjective responses. Field studies including measuring meteorological parameters, thermal environment perception, and geometry of urban open space are the final part of this research.

Findings showed that the time range of urban outdoor thermal comfort in Quds neighborhood is abundant in the afternoon in summer. The afternoon microclimate is dependent on the fabric of the neighborhood and has the potential to enhance social interactions. The proposed mathematical model for estimating thermal comfort in hot and arid environments based on the correlation of environmental variables and actual sensation vote (ASV) is well able to express an actual thermal sensation of outdoor spaces.

Therefore, in order to take the necessary measures to develop and promote the social interactions of the neighborhood, physical infrastructure such as outdoor furniture development and neighborhood social institutions should be strengthened. The results of these measures can reduce the urban social harms.

The main objective of the study was to investigate spatial and statistical and spectral characteristics of Iranshahr weather station wind speed in the marge of jazmourian wetland in southeastern Iran. Daily wind data from Iranshahr weather station located in eastern marge of wetland, operated from 1991 to 2020, used in the analysis. Simple linear regression (SLR) method is used to analyze the trend and spectral analysis and standard normal homogeneity (SNHT) test are used to analyze cycles and wind speed jumps. Preliminary analyzes revealed that the maximum daily wind speed occurs in July, June and August, and the minimum occurs in November and December. Results of Simple linear regression test showed that the wind speed during the study period in the monthly scale decreased. However, the standard normal homogeneity does not confirm a significant jump in the average wind speed. In order to investigate possible changes in the average wind speed in the frequency domain, spectral analysis method has been applied to monthly and annual data. Significant cycles extracted for the annual and monthly data of the average wind speed of Iranshahr station indicate the existence of short-term and medium-term cycles in the data of the average wind speed of the station.. In order to investigate possible changes in the average wind speed in the frequency domain, spectral analysis method has been applied to monthly and annual data. Significant cycles extracted for the annual and monthly data of the average wind speed of Iranshahr station indicate the existence of short-term and medium-term cycles in the data of the average wind speed of the station.. In order to investigate possible changes in the average wind speed in the frequency domain, spectral analysis method has been applied to monthly and annual data. Significant cycles extracted for the annual and monthly data of the average wind speed of Iranshahr station indicate the existence of short-term and medium-term cycles in the data of the average wind speed of the station.

Drought is known as one of the main natural hazards especially in arid and semi-arid regions where there are considerable issues in regard to water resources management. The focus of the present study is mainly on hydrological aspects of drought. For hydrological drought analysis, streamflow data is used as the key variable to identify drought events with reference to a demand specific threshold level, termed as truncation level. Thus, the objective of the present study is to (a) investigate the hydrological drought characteristics in Nesa River using streamflow data; (b) determine independent drought events, their duration, and severity using the variable truncation level approach; and (c) derive streamflow drought severity index. Based on expedience probabilities, the monthly flow duration curves for Nesa River were derived. These were utilized to estimate different dependable flows, and the values of variable truncation levels were obtained for a 75% probability level for each month. These values were used to distinguish the deficit and surplus flow periods independent drought events identified using the pooling procedure. Since 10 daily flow data were utilized, the minimum deficit flow duration was 10 days. In the following, have been identified some short duration (one or two 10-daily time step) surplus and deficit events. To decide on independent drought despite the short duration inter-event surplus has been used for a pooling procedure known as inter-event time and volume criterion (IC). Eventually, identified independent drought events and also describe their duration, severity, intensity, and DSI. Analysis of independent drought Characteristics in Nesa River indicated that are prolonged dry period in the hydrological regime of this river. In addition, based on DSI, Nesa droughts mostly are in sever category. Hence, it is suggested more realistic reload occurs in management programs of this river including storage, distribution and assign to various resources.

 Soil moisture is considered to be a key parameter in meteorology, hydrology, and agriculture, and the estimation of its temporal-spatial distribution contributes to understanding the relations between precipitation, evaporation, water cycle, and etc. Soil moisture reduction results in the creation of centers susceptible to dust storms. With socio-economic impacts ranging from urban to intercontinental and from a few minutes to several decades, this can challenge regional development. The first estimate of potential dust sources is derived from the soil properties. With the reduction of surface soil moisture and the wind speedcrossing a certain threshold level, wind erosion process can cause the formation of dust storms. Field studies have proved that increasing the moisture content in soil from zero to about 3%, reduces the dust concentrationsignificantly. To understand the climatology of dust and develop related numerical predictive methods, continuous recording of dust storms is essential, which requires effective and continuous monitoring of the variations in surface soil moisture. Remote sensing technology is an effective method for calculating soil moisture. This technology was first used for the estimation of energy flux and surface soil moisture in the 1970s. To extract the surface soil moisture content, some remote sensing methods use surface radiation temperature and some others apply water transfer (soil/vegetation/air) (SVAT) model. Various indices have been developed for soil moisture monitoring, such as soil moisture (SM), soil water index (SWI), Temperature-Vegetation-Dryness Index (TVDI), Soil Moisture Index (SMI) and Perpendicular Soil Moisture Index (PSMI), all of which combine vegetation and surface temperature variables.

Soil moisture is considered to be a significant parameter in the exchange of mass and energy between the Earth surface and the atmosphere. Lack of soil moisture or decreased moisture in soil is considered to be a factoraccelerating the process of dust storm formation. During the previous decades, water stresses on the ecosystem of Hour-al-Azim have transformed this wetland into one of the main dust centers in the southwest Iran. Hour-al-Azim is one of the largest wetlands in southwestern Iran. This wetland is shared between in Iran and Iraq. It is located between N 30° 58´- N31° 50´ and E 47° 20´- 47° 55´. The Iranian part of this wetland encompassed an area of 64,100 ha in the 1970s, while in the 2000s, the area has decreased to only 29,000 ha. The present study aims to monitor the spatial-temporal variability of soil moisture in Hour-al-Azim wetland and to investigate the relation between these changes and dust storms in the southwest Iran. To reach this end, we used 8-day images obtained from the Aqua satellite in the period of 2003 to 2017 and also annual frequency of dust storms with a visibility of less than 1000 m in the period of1987–2017. A database consisting of 189 images of the red band, near-infrared band, and ground surface temperature (LST) was created, which contained 4 images per year (one image per season). The resolution of the red / near-infrared band data and daily LST values were 231.65 and 926.62 meters, respectively. Then, soil adjusted vegetation indices (SAVI) and perpendicular soil moisture index (PSMI) were extracted. SAVI index is used to reduce the effect of background soil on vegetation cover in semi-arid and arid environments with less than 30% vegetation cover.Compared to NDVI, SAVIwith L = 0.5reduces the effect of soil changes on green plants. In the next step, a trapezoidal method was used to calculate the PSMI index. In order to investigate changes in the soil moisture content of the Hour-al-Azim wetland, three time series obtained from regional mean of SAVI, LST and PSMI remote sensing indices and a time series consisting of the number of days with dust storms observed in the 9 stations were evaluated using simple linear regression test. 

Extracting Soil Adjusted Vegetation Index indicated that in the study period, the highest values of this index was observed with a regional mean of 0.15 on 4/7/2014 and the lowest values was observed with a regional mean of 0.08 on 1/1/2005. Land Surface Temperature survey showed that during the study period, the highest values of this index was observed with a regional mean of 54.42 ° C on 7/4/2010 and the lowest values was observed with a regional mean of 17.28 ° C on 1/1/2007. The regional mean of Perpendicular Soil Moisture Index indicates that despite winter is considered to bethe wettest season of the region, PSMI index with a regional mean of 0.2 has experienced the driest soil moisture conditionsat the beginning of winter (1/1/2016),while it had experienced the wettest soil moisture conditionsin the same season on 1/1/2009 with a regionalaverage of 0.13. 

Finding of the present study indicate an increasing trend in the range of remote sensing indicators. The range of SAVI index is increasing, which means that the density of vegetation in the Wetland is decreasing. Perpendicular Soil Moisture Index values also show an increasing trend, indicating a decrease in soil moisture content. As a result of the decrease in soil moisture, the vegetation density also has decreased and the land surface temperature has increased. Results of statistical tests indicate the role of changes in environmental conditions of Hour-al-Azim wetland in the frequency of dust storms. Using findings of the present study, or studies such as Kim et al. (2017), it is possible to take advantage of soil moisture variations for the prediction of dust generation, its emission, and spread level.

Climate classification systems(CCSs) are important tools for understanding the specific characteristics of a region's climate. The main purpose of these classifications is to determine the climate types and to find their similarities, differences and variability. Climate zones are threatened by global warming and climate change. The purpose of this study is to evaluate the possible shifts of climate zones over the Balochistan plateau of Pakistan and its potential challenges to Iran based on the improved Koppen-Geiger CCSs. The data includes average monthly precipitation and temperature of the Delaware university dataset for the 1990-2017 periods. The results show the main climate with two subgroups in the study area. These climates include a hot desert climate(BWh) and a cold desert climate(BWk). The hot desert climate is dominated in southern and western and the cold desert climate in northern and western regions.In recent decades, the increasing range of hot desert climate limited the cold desert climate. The range of the cold desert climate has declined sharply, reaching from about 55-65 to about 50-55 percent. In contrast, the range of hot desert climate increased in response to these conditions, reaching from about 35-45 to about 45-50 percent.Therefore, it is expected that the zones of the hot desert climate will increase rapidly in the future. These conditions will add to environmental quality and resource depletion problems especially in border areas with Iran and can pose important challenges such as climate migration, border security, and health. The results of this research can play a significant role in adopting forward-looking policies to address the impacts and challenges of climate change on the border regions of Iran.

The climate of the summer season, dry and low rainfall region of the Middle East, has not been considered by atmosphere scientists for unclear reasons. The claim for the need to update the definition of seasons is due to the fact that the weather conditions are not considered in the meteorological and astronomical definitions. Almost all of the definitions given to identify the characteristics of the summer season follow three physical, dynamic and synthetic approaches. The physical index considers days with an average temperature above threshold as a summer day. Dynamically, more heat transfer in the summer leads to an increase in altitude and a reduction in the pressure of the tropopause. Synoptically, scholars have outlined the beginning of the summer to overcome the Persian trough over the region. In addition, with the sudden disappearance of the Persian trough in the middle of September, the summer season ends. With the assumption that global warming has accelerated the course of the summer period and significantly increased its intensity over the past decades, researchers have been reviewing the summer atmosphere in the Middle East, and especially in Iran, by designing new indicators. Materials and methods: In this study, using the reanalyzed data of temperature, tropopause pressure and geopotential height of the NCEP/NCAR database during 1948-2016, the characteristics of the summer season, including its start, peak, durability and ending in Iran has been evaluated. By using the script written in the GRADS software, the daily values of the data were extracted in the desired ranges. Then, in order to estimate the summer period based on the threshold of each indicator, the daily average of the data was calculated. The thresholds for physical, dynamical and synoptic indicators for estimating the start and end of the summer season and the number of summer days, respectively, were daily temperatures higher than 25 degrees, tropopause pressure less than 120, and geopotential heights less than 50 meters. The transit of daily data values from the threshold and their 10-day continuity indicates the beginning and end of the summer period. Finally, the summer weather variations in Iran were also studied based on the Kendal’s tau tests and the graphically Man-Kendal test. Results and discussion: the results of temperature-based index (physical index) with a threshold of 25 degrees Celsius and a 10-day durability shown that the beginning of the summer season in Iran is 1 June and its end is 27 September. Based on the variations of the tropopause level pressure (dynamic index) with a pressure threshold of less than 120hp and ten day duration, the beginning of the summer season is 4 June and the its end 1 October. The results of the assessment based on the index of geopotential height changes in 1000hp level (Synoptic index; Persian Trough Formation) with a threshold of 50 meters and ten days duration showed the beginning and end of the summer season in the Iranian region, 20 May and 15 September, respectively. The average annual summer season based on physical, dynamic and synoptic indexes was estimated, respectively, 134, 120 and 119 days. The results of trend analysis indicate that the frequency of summer days on the Iran based on the physical index has a significant upward trend. Accordingly, the summer atmosphere has a tendency towards early starters and late end-time. Dynamic and especially Synoptic indices the opposite of the physical index show the declining trend of summer atmosphere. Conclusion: The time series process of the temperature-based physical index indicates the upward trend in the number of summer days during the study period. The correlation coefficient of τ=0.39 and a significant trend in the time series of the mean time average of the summer temperatures of the 69-year period, also proving the hypothesis that climate change was happened. In terms of the physical index (temperature) over the last seven decades, the summer tended to start earlier and more sustained, while the synoptic index was opposite. In contrast, the time series of the synoptically index based on the period of the Persian trough formation over the Persian Gulf region indicates a decline in the number of annual summer days. Because of the differences in the results of the physical index and the similarity of the dynamical and synoptic indexes with previous studies, the authors emphasize the need for further research in this regard.

Whereas climatic parameters find importance due to their impacts on water resources, therefore this research was done carried out for investigating of meteorological drought and its impacts on Kerman groundwater resources in the eighteen- year’s period (1997-2014). In this regard Standardized Precipitation Index (SPI) values in Kerman meteorological station and Groundwater Resource Index (GRI) of plain in different time scales (1, 3, 6, 9, 12, 18, 24 and 48 months) was calculated. The results of correlation test between GRI index in different time scales and SPI index in the time period under research without any delay and with a time lag of one to twelve months showed that 6 and 18 months GRI index have significantly related to 48 month SPI index with 0.628 and 0.631 Pearson coefficients, respectively and also 48 months GRI index was correlated to 48 months SPI index with 6 month lag time and its Pearson coefficient was 0.686. The results of regression model showed that up to 57 percent of variations in GRI index explained and justified by SPI index. This is due to other factors such as uncontrolled exploitation of groundwater resources on the loss of groundwater and groundwater index linked. Iso-decline maps showed that the decline in groundwater levels across the plain, an average of 20 meters and rising in ground water levels in the range of Kerman city by 14 meters.

Precipitation is one of the vital climatic parameter, that plays a major role in human life.thereforethe impact of Precipitation in occurrence or non-occurrence of droughts and dry spells have been very effective.Identification and extraction length of dry spells in arid and semi-arid regions is very important. According to the most recent climate classification that has done, about 90 percent area of Iran is located in arid and semi-arid climate and more than 40 percent area of Iran is facing a severe water crisis.Therefore, understanding the behavioral mechanisms of dry spells have a great significance in arid and semi-arid Area, like country of Iran. Especially with the pose of the phenomenon of climate change that caused the worsening dryness and desertification in some of the region.Many research simulated dry spells with climate change approach and use of the output of AOGCM models. Researches in this category is less number, but the most recent research has been done by the authors(hashmy titles et al., 2015), investegation and modeling length dry spells in the southwest area of Iran.The aim of this research is examined,Validation of AOGCMs Capabilities for Simulation Length of Dry Spells under the Climate Change and Uncertainty in Iran
According to aim this research we used two database in this study: The first database involves collecting and analyzing information data base all (minimum temperature, maximum temperature, rainfall and sunshine) per dayly scale in 234 synoptic stations (with different statistical period), but the format for the data station and point during the period of statistical modeling was needed for more than 30 years, which has a large statistical defects were excluded, and finally 45 synoptic stations that have favorable conditions (the maximum area coverage and data continuous and reliable) who were selected for the final processing of the data first base. According that during the period is not uniform; therefore the period 1981-2010 was used as the base period. The second database contains data provided by version 5 models (LARS-WG) and on emissions scenarios (B1, A1B, A2) from AOGCM models for the decade 2050 to be downscaled. In fact, this data is the first data base (minimum temperature, maximum, precipitation and sunshine) prepare based on the format models for analysis and predict climate change, after downscale it.
Because this study was based on study and extraction length of dry spells in the range of long-term with approach of climate change, so the methodology based on several stages: In the first verification (validation) of LARS-WG, to ensure efficiency in the process model simulation will be discussed. Then assessment performance and capabilities 15 AOGCM models that in the new version Lars-wg. At the end of the precipitation threshold is defined and extract longest of length dry spells and compare it with the maximum length of the dry spells will be simulated.
After calibrating the model of statistical properties (comparison tests T, F and Pvalue (decision criteria), all stations were used to confirmed the validity of the model. The results of this calibration indicates that in more than 96% of stations for the minimum and maximum temperature, and sunshine model show high accuracy (in Dezful stations and Gorgan results of error was greater). In all of these stations were like Abadan station variables significant (P-value) at /05. It is acceptable that the data generated is random. Considering the bias error more than 95 percent of stations were very good agreement between the observed and modelling data (for every 4 variables).
Based on the the principles of (1 to 3), and using statistical methods and indicators, the AOGCM models to simulate and extraction during dry spells were examined and it was found that two models (Hadcm3 and GFDL-CM2.1) maximum performance (correlation) and the lowest error in estimating for simulation data precipitation. The model (INM-CM3 and NCPCM) have least amount of correlation and efficiency.
To estimate the maximum length of dry spells used Hadcm3 results under scenario (A2 and B1) for the decade 2050 and was skipped use the results of other models in this research.
Maximum dry spells in Iran, compliance with drynes condation in central and eastern areas. So that the country could be on the threshold of ./1 mm divided into 6 orbital region of the northern circuit during the period of 37 days (in the Rasht station) minimum and 351-day observation period southeastern Chabahar stations. The values show that the threshold of ./1 mm at more than 65 percent of the area’s dry spells over 7 months there was no rain on them yet. With a threshold of 5 mm needs maximum length of dry spells that lasted about a year with 364 days in Yazd station. That is roughly the size of 5 mm precipitation a year not registered at this station.
Modeling dry periods with calculate scenarios of climate change and the Considering Uncertainty resources of output models (AOGCM), showed that the worst-case scenario (A2), and critical status (2080), the average temperature of the country 2.7 degree (ºC) and Despite increased precipitation in some Stations, but 33% reduction in the all area of Iran. According to The most optimistic (B1) scenarios, increased the average of temperature 1.4 (ºC) and precipitation is Reduced 14% compared with the observation. The results of the uncertainty for dry Spells in 2050 and 2080 decades showed that in the two decades based on three scenarios (B1, A1B, A2), Length of Dry spells increased in all Area of Iran.Most of the changes in Length of Dry spells is, belongs the northwest Area of Iran (Oromeyeh, Khoy, Kermanshah, Hamedan and Lorestan).

Tourism and recreation are important economic factors which are directly connected to weather and climate of a specific destination. Climate is an important resource for tourism and an equally important element that needs to be included in tourism purposes. Tourism, especially coastal or maritime tourism is an important source for economic growth in the countries such as Iran. This study reveals potential impacts of climate change on tourism in south beaches of Iran. These conditions were identified by using Climate Tourism Information Scheme (CTIS) over 1989-2008 period in the 24 meteorological stations and analyzing the different thermal perceptions values that emerged. At first, by using of Ray Man and CTIS software models, thermal, physical and aesthetical aspects of Climate Tourism Information Scheme were calculated. Then, Mann-Kendal method was also used to detect possible trends in the data time series. The results revealed that from December to February is the optimum period (comfortable) in the Oman Sea shores and March and November in Persian Gulf shores. The parameters of thermal and physical aspects have changed in the studied area. The results also indicated, in Oman, sea shores that sultry days and heat stress are absolutely consistent with increasing and thermal comfortable with decreasing trend. These conditions cause a decrease in the desirable times for tourism in the future. In the Persian Gulf shores, the situation is different. In the March and November, a significant decrease in cold, heat stress and sultry trends was evident. Therefore, it is predicated that desirable times for tourism will increase in the future.

Hydrological drought is defined as a significant decrease in the availability of water in all its forms appearing in the land phase of the hydrological cycle. These forms are reflected in various hydrological variables such as stream flow (including snowmelt and spring flow), lake and reservoir level, and groundwater level. A variety of indices and methods for characterizing hydrological drought have been devised. In this study, an index called Streamflow Drought Index (SDI) have been used for characterizing the severity of hydrological droughts. Investigation of the forecasting possibility of hydrological droughts has been carried out by two approaches. First, when the appropriate historical data are available, Markov chain method have been used. The main output of the methodology is the matrix of state transition frequency for a selected pair of reference periods under the hypothesis of a Markov chain for the underlying state process. In other words, the output is a single value of drought state while the probabilities of remaining in the same state or passing to other states in the next reference period are withdrawn from tables which have been obtained off-line. Since, in general, streamflow data are difficult to obtain in real-time, the possibility of using a meteorological drought index was investigated. More specifically, a linear function of SPI was found to predict SDI to an accuracy level which is sufficient for characterizing drought severity. This involves prior calibration of a simple regression equation with modified SPI as the explanatory variable and SDI as the explained variable. The methodology is validated using reliable data from the Nesa and Fashkoh rivers basin in the southwestern margin of Kavir-e Lut (Iran). The results indicate that calibration of rainfall and streamflow relations provides a good opportunity to forecasting of hydrological droughts states in the lack of river flow data. A key consideration is that in this basin, a high degree of successful prediction is observed for the wet period of October to March. In addition, due to lack of storage snow in this basin, which can compensate the deficit rainfall in dry period, drought states predicting for other periods is also possible by using Markov chain methodology.

Drought is a climatic anomaly that associates with a significant decrease (lack) of precipitation and water resources availability, which spreads on vast temporal and spatial scales, and significantly affects various aspects of life and environment. One of the most common methods of drought assessing and monitoring is calculating drought indices (DIs). Drought areal and temporal extent and its severity are determined by these indices. In this study, an aggregate drought index (Hydro-Meteorological) has been developed for the assessment of hydrological and meteorological droughts in Sarbaz river basin located in southeastern of Iran. The Aggregate Drought Index (ADI) comprehensively considers all physical forms of drought (meteorological, hydrological, and agricultural) through selection of variables that are related to each drought type. In this case, monthly values of Stream flow Drought Index (SDI) and Standardized Precipitation Index (SPI) indicators were used for four similar reference periods with principle component analysis and aggregate hydro-meteorological index was defined based on its first component. The study time span was set between 1981-82 to 2010-11, which begins of October in Iran. Results based on the aggregate drought index (ADI) revealed that a long period of hydro-meteorological drought occurred from 1999-2000 to 2005/06 in southeast of Iran, in which, 2003/04 water year has been extremely a drought year. The ADI methodology provides a clear, objective approach for describing the intensity of drought. This index is appropriately able to represent the behavior of Hydro-Meteorological droughts and recommended as an integrated index for assessing and monitoring of regional droughts. Finally, different states of hydro-meteorological drought have been extracted based on conventional regional thresholds, and have been modeled by Markov chain. This made the estimation of drought state transition frequency possible, and made the prediction of next drought state time more real. State transition frequency matrices, are the main instruments for predicting drought states in real time. Results of validation tests and conforming the predicted results with real data indicate that predicting hydrological drought state transitions in the study area using Markov chain method is valid.

Drought is a climatic anomaly that associates with a significant decrease (lack) of precipitation and water resources availability, which spreads on vast temporal and spatial scales, and significantly affects various aspects of life and environment. One of the most common methods of drought assessing and monitoring is calculating drought indices (DIs). Drought areal and temporal extent and its severity are determined by these indices. In this study, an aggregate drought index (Hydro-Meteorological) has been developed for the assessment of hydrological and meteorological droughts in Sarbaz river basin located in southeastern of Iran. The Aggregate Drought Index (ADI) comprehensively considers all physical forms of drought (meteorological, hydrological, and agricultural) through selection of variables that are related to each drought type. In this case, monthly values of Stream flow Drought Index (SDI) and Standardized Precipitation Index (SPI) indicators were used for four similar reference periods with principle component analysis and aggregate hydro-meteorological index was defined based on its first component. The study time span was set between 1981-82 to 2010-11, which begins of October in Iran. Results based on the aggregate drought index (ADI) revealed that a long period of hydro-meteorological drought occurred from 1999-2000 to 2005/06 in southeast of Iran, in which, 2003/04 water year has been extremely a drought year. The ADI methodology provides a clear, objective approach for describing the intensity of drought. This index is appropriately able to represent the behavior of Hydro-Meteorological droughts and recommended as an integrated index for assessing and monitoring of regional droughts. Finally, different states of hydro-meteorological drought have been extracted based on conventional regional thresholds, and have been modeled by Markov chain. This made the estimation of drought state transition frequency possible, and made the prediction of next drought state time more real. State transition frequency matrices, are the main instruments for predicting drought states in real time. Results of validation tests and conforming the predicted results with real data indicate that predicting hydrological drought state transitions in the study area using Markov chain method is valid.

This study was made following the re-recognition of the cause of occurrences of severe, widespread and persistent frost event in 2003 in Iran. Based on previous studies, the cause of the creation and persistent of this sever frost is the dominancy of Siberian high pressure system. For this purpose, the gridded daily minimum temperature, northern hemisphere teleconnection indices and sea level pressure data have been used. Based on the indices of frost wave onset index (FWOI),ending and persistent of cold wave and by considering the spread, the location and time patterns, the frost wave of December 2004 was recognized. On this basis, its starting date was recognized 11 December 2011 and its ending as 16 December 2003, which was persisted for 6 days in Iran's area. Also the location pattern of cold wave has had an east ward arrangement and was dominant in more than 75% of Iran's area in its maximum intense.The highest continuation of cold wave was recorded in the Iranian plateau, while the northern shores of the Persian Gulf and Oman Sea on the southern slopes of the Zagros ruggedness have not received the cold wave. Increase and decrease pattern of spatial range of cold wave is a signal for accompany of some recognized systems of sea level pressure with Siberian high pressure system in its occurrence. For this purpose, long term time series (1950-2010) of tele-connection patterns of northern hemisphere were studied from October up to December. For example,co-phase coherence between the patterns of North Sea- Caspian sea, Arctic Oscillation and North Atlantic Oscillation and no phase coherence of the pattern of east of Atlas Ocean- West Russia and the North Pacific Ocean with the standardized index of intensity of Siberian high pressure are the reasons of other pressure systems at the sea level of high pressure system of Siberian in the event of the said frost wave. Assessment of spatial-temporal variability of sea level pressure systems in the before occurrence (08 to 10 December 2003) to occurrence (11 to 16 December 2003) showed that December frost wave has occurred in as a result of an interaction of High Pressure System (AHPS) include Europe, North West Iran and Siberian high pressure systems with Scandinavian low pressure system. Spatial-temporal array type of Scandinavian Low Pressure system has a great important role in the formation, persistent, intensity and rupture of aggregate high pressure system.

A drought is a prolonged period of water deficit and usually occurs when an area does not receive significant precipitation for a sustained period of time, say several months (Chen, Kuo, & Yu, 2009; Linsely, Kohlerm, & Paulhus, 1959). The effects of drought often accumulate slowly over a considerable period of time that may linger for several years even after the termination of drought. Therefore, some authors have called it a creeping phenomenon (Wilhite, 2000). It is difficult to precisely determine the onset and end of a drought event. A drought can be short, lasting for a just a few months, or it may persist for years before climatic conditions return to normal. Drought considered as the most complex, but the least understandable phenomenon of all the natural hazards affecting more people than any other hazards (Mishra & Desai, 2005). Droughts can be classified into four categories as meteorological, hydrological, agricultural and socioeconomic (American Meteorological Society, 1997; Palmer, 1965; White & Walcott, 2009). The preparedness and planning for a drought depend on the information about its areal extent, severity and duration (Mishra & Singh, 2011). This information can be obtained through drought monitoring that is usually done with the use of drought indices (DIs) which provide information to decision makers about drought characteristics. Thus, these indices can be used to initiate drought action plans. Prediction of droughts is useful for early warning that may reduce the response time and consequently the impact of a drought. For many regions, especially semi-arid regions, limited knowledge is available about the diurnal and seasonal cycles of land surface interactions. Semi-arid areas pose a challenge due to large contrasts between dry and wet conditions within a temporal cycle (Schuttemeyer, 2005). Meteorological drought is generally an indicator of other drought types with below normal precipitation, and usually occurs first before other drought types do. The seasonality and climatological conditions vary by location. Drought severity may differ from site to site under different climatic conditions, hence, as many as applications of DIs and their comparisons are beneficial for specific regions in the world. The objective of this study is to develop an aggregate drought index (ADI) based on principal component analysis (PCA) to assess the severity of Hydro-Meteorological drought in the southeast of Iran. Therefore, Stream flow drought index (SDI) and effective drought index (EDI) is determined for several different monthly time steps. The ADI is calculated after a principal component analysis to determine aggregated index value.
Study Area : Southeast area of Iran is confined to Sistan and Baluchestan province and located southeast of the intersection of between 29ºN and 57ºE. In this area, precipitation mostly falls in winter and summer seasons. Summer rainfall related to the monsoon mass effect, which comes from Indian Ocean. Climate is arid and semi-arid. Bahouklat is the most important river in area. The origin of this river is the Pir Abad Mountains in the southeastern of Iranshahr city and the passing of Sarbaz, Bahoukalat, Pishin and Dashtyari regions eventually lead to Govare Bay. This river has various names in different regions and called Sarbaz River from Sarbaz to Rask and passes of Pishin dam. Discharge of this river (Sarbaz) is very important in this area.
Material and Hydrological and meteorological drought values are necessary for ADI computation over a long period. Therefore, streamflow drought (SDI) and effective drought (EDI) Indicators were used to estimate the hydrological and meteorological droughts. The input variables include the daily values of stream flow of Sarbaz River in the Pirdan hydrometric station and rainfall during the 21 March 1985 to 20 March 2011 common period. Variables were arranged according to water year (also water year, flow year or discharge year), which begins in October in Iran. Daily timestep of SDI and EDI were estimated respectively according to Nalbantis (2008) and Byun and Wilhite (1999) and then ADI were calculated based on principal component analysis according to Keyantash and Dracup (2004).
Drought is a very common phenomenon in Iran and particularly in the south east and it has become a recurrent phenomenon in this area in the last few decades .The hydrometeorological drought index was applied for the identification of drought severity in south east of Iran and drought occurrences were monitored during the experimental years of 1985/86 to 2010/11. Results based on the aggregate drought index (ADI) revealed that a long period of hydro-meteorological drought occurred from 1994/95 to 1998/99. Also, a prolonged wet period has started immediately after the end of drought and has continued to June 2005. In addition, according to drought severity, 1997/98 and 2003/04 water years respectively are extreme drought and extreme wet years. Finally, we have compared the performance of EDI (Meteorological drought index) and SDI (Hydrological drought index) with aggregate drought index. Based on this comparison, aggregate drought index (ADI) could be better highlighting the drought conditions and its characteristics.
Aggregate drought index (ADI) is methodology presented for replacing the unidimensional analysis of drought phenomena which can assist authorities and stakeholders to take rational decisions for combating droughts. Using this approach, a more effective way for assessing the severity of drought is obtained. On the other hand, ADI shows capability to detect dry and wet years. Moreover, it has capability to detect historical drought. Overall, by considering the results, the ADI is more reliable than EDI and SDI for drought monitoring in the study area. In this study, ADI time series were compared against the EDI and SDI to describe an important and long drought event in south east of Iran, the 2003-2004 event from a hydro-meteorological perspective. The ADI methodology provides a clear, objective approach for describing the intensity of drought and can be readily adapted to characterize drought on each area.