فهرست مطالب داریوش یاراحمدی

The phenomenon of precipitation is the final product of several complex atmospheric processes that are different in terms of time and place, and it can be considered one of the climatic characteristics of each region. The diversity of origin, temporal-spatial changes of rainfall systems, ground conditions such as altitude and topography, and distance and proximity to moisture sources cause precipitation behaviors, including continuity, to have temporal-spatial changes. Heavy and continuous rains are significantly effective in supplying water, feeding the underground water table, and storing it in the soil. It can also cause landslides, destruction of vegetation of forests and pastures, severe soil erosion, destruction of water structures, and waste of high volume of surface water resources in arid and semi-arid areas; therefore, it has always interested climate and meteorology researchers. In Iran, heavy and moderate rainfalls have been investigated from different perspectives. Some researchers have investigated heavy rains leading to floods in different regions of the country, and others have zoned rains lasting several days using the clustering method. Despite the various analyses conducted by the researchers, due to the difference in the selection of rainfall amounts and the different behavior of synoptic systems, the factors affecting rainfall lasting several days remain in the veil of ambiguity. This research aims to identify the synoptic patterns of rainfall lasting more than 4 days and to investigate the horizontal flux of specific moisture so that by identifying the behavior of this variable and its related fluctuations, accurate and comprehensive planning can be carried out in the direction of managing the country's water resources. What distinguishes this research from other studies is the method of estimating the limited rainfall of the study stations and the selection of the statistical period leading to 2022.

Methodology (Materials and Methods):

This research used two series of data; the first series was the daily rainfall data of 120 synoptic stations of the country from its establishment until 2022, which was taken from the National Meteorological Organization. First, the total four-day rainfall of weather stations from October to March was calculated. Then, based on the Andersen-Darling index, the best probability distribution function was fitted to the obtained data, and precipitation values above 99% of the fitted curve were obtained, among which the heaviest precipitation was selected. Five distinct clusters were identified using the hierarchical clustering technique based on the height of the middle level of the atmosphere. From each cluster, a precipitation system was chosen for synoptic analysis based on three criteria - intensity, continuity, and comprehensiveness of precipitation.The second series of data used in this research, which was used for the case study of synoptic systems, was taken from the NCEP/NCAR archive. These data in a regular grid are limited to 0 to 80 degrees east longitude and 10 to 60 degrees north latitude with a grid step of two and a half degrees, including an area where synoptic waves can be detected. From this series of data, we can refer to the average sea level pressure, altitude, temperature, and relative humidity of the pressure level of 850 hPa, the wind field and specific humidity of the pressure levels of 925 and 700 hPa, the height and the vertical component of the wind level of 500 hPa and the wind field of the level of 200 hPa.

Five specific patterns were obtained in the hierarchical clustering of the middle level's height. In the four obtained patterns, mid-level troughs with different depths are located in different geographical positions, and in the other pattern, a cut low pressure with a cold core was revealed in the north of the Black Sea. From examining the uncovered troughs, it was seen that in two cases, in the eastern part of the trough, there was a strong pile of height, which prevented the eastward movement of the trough and made it last. In these cases, the stack becomes more profound as the ship's depth increases and the ship's movement becomes slower. In two cases, short and low-amplitude waves caused by the rotating movement of the ship periodically passed through the study area and caused the instability of the atmosphere. In the case of a low-pressure cut, a deep ridge has caused the system to last and continue to rain. Since the water vapor is more in the lower levels above the water sources, the upward movement caused by the eastern circulation of pressure systems has caused the water vapor to be transferred into it and increased the amount of precipitation. Therefore, the persistence and transfer of water vapor have caused the continuation of precipitation in the study area.

Investigations showed that the synoptic systems of mid-latitudes, when passing over the warm waters of the Mediterranean Sea, caused an upward movement due to the gyre circulation and transferred a large amount of moisture on the sea to higher altitudes. In addition, the eastern winds of the high-pressure southern part over the Oman Sea have transferred a large amount of special moisture to the south of the Red Sea, which has been transferred to the south, southwest, and western regions of Iran with the southern winds of the eastern part of the Red Sea pressure trough. As a result of the upward movement, these values have participated in the precipitation process and increased the amount of precipitation and the continuity of rain in the western half of Iran.

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.

This study was aimed at examining the types of inversion and their severity using the thermodynamic indices of the atmosphere such as SI, LI, KI and TT at Bandar Abbas Station for 2010-2020. In this study, Radioosvand data at the Bandar Abbas Station was obtained and used from the University of Wioming for the last 11 years (3.5 local) during the last 11 years (2010 to 2020). The results of the analysis showed that the average number of inversion phenomenon in Bandar Abbas was 501 cases per year, as in some days several types of inversion were observed at different altitude. Of these inversion, about 31.6 % are related to radiation temperature inversion, 4.3 % front, and another 64.1 % for subsidence inversion. Due to the air session underneath, the share of subsidence inversions is more than other types of inversion. In the meantime, the most severe inversion of subsidence was 1354 and the weakest inversions were with 29 cases and fronts. In general, the long -term average intensity coefficient of inversion of Bandar Abbas station with a coefficient of 0.062 indicates that the intensity of the city's inversion is mostly extremely severe, which can be very destructive effects both environmentally and physical health in the city's residents. Bandar Abbas follow. The correlation between the inversion elements also showed that by reducing the thickness of the inversion layer, the intensity of temperature inversion also increased.

Stability in garden products depends on economic, social and environmental factors. The recognition of the stability level of these factors can be effective in developing sustainable horticulture development strategies and its effect on sustainable livelihoods. Therefore, the purpose of this study is to analyze the stability of garden products and its role in the livelihood of household grid operator villages of Bandar-e-Gaz Central District of County. The information required is collected through a questionnaire whose validity is obtained based on the experts of the relevant experts and its reliability by calculating the Cronbach's alpha coefficient. The statistical population of this study consists of the garden operators of three, western Gaz and Val-afra, calculated by the Cochran formula of sample size 250. Random sampling method was used to select sample sample. In order to measure the stability of garden products from 45 indexes for economic, social and environmental dimensions and to measure sustainable livelihoods, the grid operator uses 53 indices to separate the dimensions of financial, social, human, environmental and environmental assets. According to the spearman test, the economic, social and environmental sustainability of the garden products on sustainable livelihoods is effective. The results of the Kruskal test show that the stable livelihoods of operators in the three villages have a significant difference to the confidence level of 99 percent. The results of the analysis of one - way independent variance analysis on the level of culture of three villages also stated that there is significant difference in the three factors in three villages by 99 percent level.

The snows of the Alborz mountain range play an important role in providing underground and surface water for the settlements around it and the densely populated Caspian Plain, and the permanent rivers of the northern and southern slopes of Alborz are fed by the snows of the high places of Alborz. Global warming has caused changes in the atmospheric-climatic parameters of Iran; in such a way that temperature and evaporation have increased and precipitation, especially snow, has decreased. These changes, which are considered as independent variables, will cause changes in the dependent variable, which is the snow cover of the high points of the Alborz Mountains. Its consequences can be accelerating the melting of snow, increasing the process of flooding of rivers in the catchment areas of the study area, and the destruction of habitats and settlements downstream. Therefore, the monitoring of Alborz snow area can be used in formulating water management strategies and sustainable development.

In this study, the temporal-spatial variations of the Central Alborz snow cover on a seasonal scale for the years 1985 to 2020 were monitored using Landsat TM, ETM+ and OLI for 1985, 1995, 2005, 2015 and 2020. For each season of the year, an image was prepared that was a combination of 4 satellite images and radiometric and geometric corrections were made on it. SVM algorithm was used to extract the snow cover. The area of snow cover was obtained by transferring the classified map to the ArcGIS.

The results showed that the kappa coefficient for the classified maps was more than 0.91. The average snow covers for winter, autumn, spring and summer were 1.19, 0.47, 0.14 and 0.004 million hectares, respectively. Snow covers have been declining from 1985 to 2020, reaching 1.98 million hectares in 2020 from 1.68 in 1985 to 1.68 in winter. In the autumn, it increased from 0.84 in 1985 to 0.15 million hectares in 2020. In winter and autumn, snow cover in the eastern part of central Alborz has decreased sharply compared to the western part. In the winter of 1985, snow started at an altitude of 1,500 meters, but by 2020 it reached 2,500 meters. In the summer, snow was more than 3,900 meters high in 1985, but peaks more than 4,200 meters in 2015 and 2020. The area of snow cover in Central Alborz has a decreasing trend, which has the highest rate in winter. In order to increase the spatial accuracy of snow, the present research used Landsat series images with 30 meters pixels, and its results are more favorable than the output of MODIS images.

Therefore, the results of this study showed that the accuracy of the support vector machine algorithm is more than 0.91% in the classification of Landsat images, this method can be used to extract snow patches; in such a way that it separated the shadow snow and cloud from the snow and identified the accumulation of snow in the valleys. It can be concluded that using images with spatial resolution of 30 meters and applying classification algorithms for snow extraction is better than using NDSI index and MODIS images. On the other hand, the process of snow cover in central Alborz has been such that during 25 years, the area of snow has decreased from about 0.7 million hectares and a large amount of fresh water storage in Alborz has been lost.

The height of the boundary layer is one of the most important determining factors, the extent of mixing of pollutants and suspended particles and the quality of air near the surface of the earth. The main goal of this research is to reveal the relationship between land cover changes and boundary layer height changes during the last 3 decades in Lorestan province. In this regard, two sets of data were used, which include the land cover classes of the MODIS sensor and the height of the boundary layer of the ECMWF climate database version ERA5. These data were selected on a monthly scale (January) to check the cold period and (July) to check the warm period and were checked in 7 time periods with 5-year steps during the statistical period of 1990-2020. In this research, the cross-matrix analysis technique was used in the ARC-GIS environment and the average height of the boundary layer on each land use was extracted and compared in 7 time steps of 5 years, separately from the cold and warm periods of the year. The results showed that firstly, the height of the boundary layer during the warm period is significantly higher than the cold period of the year, and secondly, the minimum and maximum spatial pattern of the boundary layer height in the cold and warm periods of the year is different in the province. In the cold period, the maximum height of the boundary layer is in the western parts. and southwest (low-altitude lands with forest cover), while in the warm period of the year, the maximum boundary layer is concentrated in the barren and mountainous lands of the east of the province. In addition, it was observed that in the hot period of the year, agricultural lands with a boundary layer height of 1263 and pasture lands with a boundary layer height of 1243 have the highest boundary layer height among the investigated use classes, while in the cold period of the year, urban and residential lands with a height of 192 meters, It has the highest boundary layer height and the spatial average of the boundary layer height of the province has had an increasing trend

Heavy rains are a risk factor for natural disasters such as floods. Therefore, identifying and predicting their occurrence is one of the measures that can reduce the damage caused by it. This study was with purpose analyze and explain heavy rainfall using statistical-synoptic methods. For this purpose, precipitation data from 14 synoptic and rainfall stations of Karkheh and Dez basins in a period of 60 years (1959-2019) were used. In this regard, first, using the probability distribution function of the final limit of type one (Gamble), the heavy rain threshold was determined. The results obtained from heavy rainfall thresholds showed that the average rainfall of more than 40.7 mm in Karkheh basin and the average rainfall of more than 47 mm in Dez basin are considered as heavy rainfall. The average number of days of heavy rainfall in Karkheh basin is 118 days and Dez basin is 81 days. The flood threshold of Karkheh basin is lower than Dez basin. Therefore, Karkheh rains occur more suddenly and irregularly, while the rains in the Dez basin have more normal time series. As a result, Karkheh basin is more vulnerable to floods than Dez basin in terms of increased heavy rainfall. The results of synoptic analysis showed that in all models, synoptic systems of Sudanese and Sudanese-Mediterranean integration systems have played an effective role in creating heavy rainfall simultaneously in both Karkheh and Dez basins. The deepening of the Mediterranean submarine also activates the humid low-pressure system on Sudan and the Red Sea. The Sudanese system causes heavy rainfall by moving north and northeast of the Mediterranean coast over the study area. The main source of moisture is the Arabian Sea, the Oman Sea, the Red Sea and the Mediterranean.Heavy rains are a risk factor for natural disasters such as floods. Therefore, identifying and predicting their occurrence is one of the measures that can reduce the damage caused by it. This study was with purpose analyze and explain heavy rainfall using statistical-synoptic methods. For this purpose, precipitation data from 14 synoptic and rainfall stations of Karkheh and Dez basins in a period of 60 years (1959-2019) were used. In this regard, first, using the probability distribution function of the final limit of type one (Gamble), the heavy rain threshold was determined. The results obtained from heavy rainfall thresholds showed that the average rainfall of more than 40.7 mm in Karkheh basin and the average rainfall of more than 47 mm in Dez basin are considered as heavy rainfall. The average number of days of heavy rainfall in Karkheh basin is 118 days and Dez basin is 81 days. The flood threshold of Karkheh basin is lower than Dez basin. Therefore, Karkheh rains occur more suddenly and irregularly, while the rains in the Dez basin have more normal time series. As a result, Karkheh basin is more vulnerable to floods than Dez basin in terms of increased heavy rainfall. The results of synoptic analysis showed that in all models, synoptic systems of Sudanese and Sudanese-Mediterranean integration systems have played an effective role in creating heavy rainfall simultaneously in both Karkheh and Dez basins. The deepening of the Mediterranean submarine also activates the humid low-pressure system on Sudan and the Red Sea. The Sudanese system causes heavy rainfall by moving north and northeast of the Mediterranean coast over the study area. The main source of moisture is the Arabian Sea, the Oman Sea, the Red Sea and the Mediterranean.Heavy rains are a risk factor for natural disasters such as floods. Therefore, identifying and predicting their occurrence is one of the measures that can reduce the damage caused by it. This study was with purpose analyze and explain heavy rainfall using statistical-synoptic methods. For this purpose, precipitation data from 14 synoptic and rainfall stations of Karkheh and Dez basins in a period of 60 years (1959-2019) were used. In this regard, first, using the probability distribution function of the final limit of type one (Gamble), the heavy rain threshold was determined. The results obtained from heavy rainfall thresholds showed that the average rainfall of more than 40.7 mm in Karkheh basin and the average rainfall of more than 47 mm in Dez basin are considered as heavy rainfall. The average number of days of heavy rainfall in Karkheh basin is 118 days and Dez basin is 81 days. The flood threshold of Karkheh basin is lower than Dez basin. Therefore, Karkheh rains occur more suddenly and irregularly, while the rains in the Dez basin have more normal time series. As a result, Karkheh basin is more vulnerable to floods than Dez basin in terms of increased heavy rainfall. The results of synoptic analysis showed that in all models, synoptic systems of Sudanese and Sudanese-Mediterranean integration systems have played an effective role in creating heavy rainfall simultaneously in both Karkheh and Dez basins. The deepening of the Mediterranean submarine also activates the humid low-pressure system on Sudan and the Red Sea. The Sudanese system causes heavy rainfall by moving north and northeast of the Mediterranean coast over the study area. The main source of moisture is the Arabian Sea, the Oman Sea, the Red Sea and the Mediterranean.

River flow contain fluctuations with very sharp ups and downs that act as unstable and chaos processes. The complexity of the behavior of such flow can be discovered and identified through the standard Hurst exponent and the generalized Hurst exponent or scale exponent. In this study, in order to identify the multi-fractal characteristics of large-scale and complex dynamics of Kashkan river flow, which has very strong fluctuations, multi-fractal detrended fluctuation analysis (MF-DFA) was used. The results of the detrended fluctuation analysis (DFA) show that there is one crossover with a time scale of 348-405 days in the daily signal of Kashkan river flow, which indicates the existence of fractal structure and different behavior of the time series of the river flow in different time scales. The Hurst exponent (h = 2) of small scales was 1.12, which indicates short-term memory and unstable structure of these time scales, while time series with a scale higher than this scale have a relatively stable structure. The strong dependence and gradual decrease of the generalized Hurst exponent on the degrees of fluctuation (q-order RMS) in the range of -5 to 5, on the one hand, shows the complex multi-fractal nature and dynamics, and on the other hand, the nonlinear memory of the Kashkan river flow signal. In addition, the multi-fractal nature and multiple scales of the river flow were confirmed in terms of the nonlinear relationship between mass exponent (tq) and q-order. The large width and asymmetry of the singularity spectrum, while expressing the intensity of the multi-fractal structure and different dynamics in the river flow signal, indicate the weight imbalance of the effect of large and small fluctuations on the river flow signal. The right tail elongation of this spectrum indicates the predominant effect of local fluctuations with small values on the structure of the Kashkan river flow time series.

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

 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. 

The aim of this study was to investigate the spatio-temporal changes of snow cover and snow water equivalent in Karun, Karkheh and Dez basins and the effect of changes in the discharge of these basins.

In order to extract snow cover and measure snow water equivalent and their correlation with the discharge of Karun, Karkheh and Daz basins, from the thresholding method on reflective and thermal bands, Man Kendal method, Spearman correlation and MODIS measurement data (2000-2020), available images of AMSR-2/AMSR-E sensor (2003-2020) and monthly discharge at the same time with the mentioned satellite images have been used.

The results of time series analysis in all three studied basins show a decreasing trend of snow cover area and volume of the snow water equivalent in most months And The most decreasing changes in snow cover area were observed in Dez basins and March with a value of -3.26 and the most decreasing changes of snow water equivalent were observed in Karun basin and February with a value of -3.86. The highest correlation in all three basins was related to Dez basin in June with a value of 0.775 (p<0.01) and the lowest was related to Karkheh basin in February with a value of 0.183. Examination of the relationship between discharge and snow water equivalent AMSR-E/AMSR-2 images also showed that the highest correlation was related to Karun Basin in January with a value of 0.721 (p<0.01).

Generally, in the observed years, the area of snow cover and snow water equivalent in all months has decreased and is more severe in Karun and Dez basins. In addition, in most months, there is no significant relationship between snow cover area and basin discharge.

Precipitation is important climatic varibles which is directly involved the hydrological cycle. Iran is considered the most arid and semi – arid regions of the world due to lack rainfall and their inappropriate distribution, which has always faced water shortage important limitations of natural resources.Therefore, the present study was conducted with the aim of extracting scale behavior and identifying (long – term and short – term) precipitation memory of two Karkheh and Dez catchment. For this purpose, Precipitation data of two Karkheh and Dez catchment were used over a period of 60 years (1959 – 2019). The results showed that the stations both areas have 2 rainfall regimes. In the study precipitation regimes all stations, two basins were identified. The small – scale precipitation regime has a long – term memory and a stable time series. However the large – scale precipitation regimes has a short – term memory and its time series is static except Doab and Darreh Takht station. both precipitation regimes show completely different scale behavior. the relationship between precipitation scale behavior and topography of the study area was calculated using pearson correlation test. The results show that there is no significant relationship between Karkheh basin both precipitation regimes. but in Dez basin, there is a significant correlation the small – scale precipitation regime, but there is no significant correlation the large – scale precipitation regime. This can be due to the conflicting and heterogeneous topographic situation in different parts of the region in Karkheh

Precipitation is the most important climatic characteristics of any region. This climatic characteristic is one of the most fluctuating climatic variables that seriously affects the water resources the region. This issue is  important in Iran, where the average rainfall is over 250 mm. The purpose this study is to analyze and explain the heavy rainfall  Karkheh and Dez using statistical methods. For this purpose, precipitation data from 14 synoptic stations and rain gauges period 60 years (1959-2019) were used. In order to achieve the objectives  the research using the probabilistic distribution function the final limit  type 1 Gumble, the heavy rain threshold each station was determined. Then to identify the uniform and non- uniform discharges in the time series maximum daily precipitation and total annual precipitation the ITA method and Man – Kendall non-parametric test were used. The results were obtained from heavy rainfall thresholds, The average rainfall of more than 40/7 mm in Karkheh and the average rainfall  more than 47 mm in Daz  are considered as heavy rainfall. The average rainfall in Karkheh is 118 days and the dose  is 81 days. The flood threshold of Karkheh  is less than Dez catchment. Therefore Karkheh rains occur more suddenly and irregularly while Dez  have more normal time series. As a result Karkheh is more vulnerable to floods than Dez in terms increased heavy rainfall. The results of using Man – Kendal and ITA test showed that Man – Kendal test can only detect uniform trends in time series as the advantage ITA method is that in addition to uniform trends. It is able to detect hidden trends and internal in identify time series. For example, although man – Kendal test did not show a specific trend for maximum rainfall at Khorramabad station, The ITA test detected hidden and non-unform trends for this station.

One of the important consequences of climate change is a change in the frequency and intensity of rainfall. In fact, it can be said that as a result of this phenomenon (climate change), in many parts of the world, the frequency and intensity of maximum rainfall have increased. However, the type and severity of these changes vary from region to region (IPCC, 2012: 5). In recent decades, in the framework of climate change, several studies have been conducted on the trend of rainfall in most parts of the world. Most of these studies are based on parametric or non-parametric methods such as linear regression analysis, Spearman's test, age gradient test, and Mann-Kendall test. However, the use of these methods requires some limiting assumptions. In addition, these tests only show the trend of changes in the average time series, while they do not provide any information about the trend of changes in different time series classes. In this regard, Sen (2012: 1044) proposed the ITA method, which addresses the above-mentioned problems in addition to allowing a trend to be identified in a series of "low", "medium" and "high" values.

In this study, in order to achieve the defined goal, the basic method of percentiles was initially used. Since the choice of the threshold value of the base percentile is a matter of taste and does not reflect the intensity-frequency of heavy rainfall, the type 1 equation probabilistic distribution function (Gamble) was used to determine the heavy precipitation threshold to provide a criterion that results in intensity-frequency of occurrence, while it is based on time series distribution of the precipitation data. For this purpose, first the data of rainy days related to 6 synoptic stations in the west of the country from 1961-2019 were obtained from the Meteorological Organization. Then, in order to calculate the maximum amount of daily rainfall during different return periods, the Gamble distribution function was used, based on which the heavy rainfall threshold was defined for the stations in the region and the maximum daily rainfall values during the return periods of 2, 5, 10, 15, 20, 25, 50 and 100 years were calculated. Finally, MK and ITA tests were used to determine the trend of these precipitations. The ITA method was proposed by Sen. Despite its simplicity, it does not require any presuppositions and is more capable than other non-parametric methods because this method is able to identify hidden trends and internal trends in time series in addition to uniform trends. Therefore, in this study, ITA method was used to identify the uniform and non-uniform trends in the maximum daily rainfall and the total annual rainfall in the west of the country.

After determining the thresholds of heavy rainfall using the Gamble distribution function, it became clear that the average rainfall of more than 37 mm in the western region of the country is considered heavy rainfall. The heavy rainfall index of Dezful station was higher than other stations, which indicates the high intensity of daily rainfall in this station. In this study, heavy precipitation threshold was calculated for all stations by applying the percentile method on rainy days with a minimum threshold of 1 mm. Then, ITA method was used to analyze the trend and determine the behavior of total annual rainfall and maximum daily rainfall in the study area. Application of this method on the total annual rainfall of Khorramabad station showed that middle floor precipitation (430-650) of this station is decreasing, while upper and lower floor precipitation was decreasing. In Hamedan station, the precipitation of the middle class (240-240) showed a significant decreasing trend, but no significant trend was observed in the lower class (less than 240) and the upper class (above 440). In Kermanshah, Dezful, Ahvaz and Abadan stations, the trend specified in all classes was decreasing and uniform. The application of Man-Kendall method on the total annual rainfall in the study area showed that the trend of these rains is decreasing in all stations and is significant in Khorramabad, Hamedan, Kermanshah and Dezful at the level of 95%. Regarding the application of ITA method for maximum daily rainfall of Gamble, the results showed that in Khorramabad station, rainfall with a return period of 5, 10, 15, 20 and 25 years of this station increased and precipitation with a return period of 2 years showed no particular trends. At Abadan station, rainfall with a return period of 50 years showed a decreasing trend. In Dezful and Ahvaz stations, the trend marked in all classes was a decreasing trend. In general, no specific trend was observed in Hamedan and Kermanshah stations. Regarding the maximum daily rainfall of Gamble, the results of Mk showed a negative trend in Hamedan, Kermanshah, Ahvaz and Abadan stations and a positive trend in Khorramabad and Hamedan, but only in Ahvaz station, the trend was significant at 95%. In the present study, some conflicting results have been obtained by comparing the ITA and MK methods. This shows the advantage of this method over other process tests. For example, while the Mann-Kendall test on Khorramabad station showed a significant decrease in the total annual rainfall of this station, the Sen method showed a different trend from this method. In fact, according to ITA, it was found that the total rainfall in Khorramabad had an uneven trend, which was divided into three classes, and the precipitation class showed 430 to 650 decreasing trends less than 430 and more than 650 increasing trends in this station.

The results of ITA method showed that on an annual scale, there is a non-uniform trend in rainfall in Khorramabad and Hamedan. But in Kermanshah, Dezful, Ahvaz and Abadan stations, the trend marked in all classes was decreasing and uniform. On a daily scale, the results showed that precipitation with a return period of 5, 10, 15, 20 and 25 years of this station is an increasing trend and precipitation with a return period of 2 years is without a trend. At Abadan station, rainfall with a return period of 50 years showed a decreasing trend. In Dezful and Ahvaz stations, the trend marked in all classes was a decreasing trend. In Hamedan and Kermanshah stations, in general, no specific trend was observed, but in more detail, it can be said that the trend of rainfall on the upper floor of Hamedan station was increasing, whereas the trend was decreasing in Kermanshah station. The results of Mann-Kendall test also showed that on an annual scale, all stations have a decreasing trend and on a daily scale, Hamedan, Kermanshah, Ahvaz and Abadan stations have a negative trend, although Khorramabad and Hamedan stations showed a positive trend in precipitation. In fact, when there is a non-uniform trend in the time series, the MK test shows that the trend is insignificant, but the ITA method detects such non-uniform trends and makes hidden time series information available.

The area of this study, which has covered large parts of the western-southwestern of Iran, has a special topographic and climatic variety. As this area is exposed to geomorphological features such as mountain and plain. In this regard, western and southwestern rainfall systems entering the area, show different reactions to these mid-scale phenomenon (Jahanbakhsh et al; 2020) that such a process has caused the scale behavior and more complex dynamic structure of the rainfall signal in the area. Therefore, on one hand to cover the whole area and on the other hand in order to have long-term daily rainfall statistics, six synotic stations including Khorramabad, Kermanshah, Sanandaj, Dezful, Ahvaz and Abadan stations were selected that have long-term statistics with 1961-2018 as representatives of this area. Also, in order to identify the scale behavior and the dynamics of the structure of the temporal series of rainfall in the western-southwestern of Iran, the fractal and multifractal changed fluctuation analysis method was used (DAF2, MF-DFA2). By using fractal-multifractal analysis of receding fluctuations on daily rainfall signal, it was shown that the rain of all the stations has a scale behavior. In this regard, three different scale periods were identified for records. So that, the fitting of the fluctuation function of DFA2 against different scales show that there are two cross over points that separate three different rainy regimes in the fluctuation function of the stations. These two crossover points are based on a temporal scale of 180 (6 months) and 550 days (approximately 2 years); Therefore, there are three different scale periods including small-scale (less than 6 months), mid-scale (from 6 months to 2 years) and large-scale (more than 2 years) in the rainy temporal series of the stations with different stability and dynamic rainy structure at these three temporal periods. Lovejoy and Mandelbrot, 1985; Matsoukas et al., 2000; Gan et al., 2007; Tan and Gan, (2017) claimed that the existence of cross over points in rainy temporal series, are different mechanisms of raining because temporal scales different. The values of scale exponent in these three periods showed that large-scale rainfalls do not follow a specific spatial pattern and show relatively homogeneous behavior. Although, small-scale raining period has a spatial behavior, in the way that the rain of southwestern stations shows more instability and short-term memory than western stations. Also the results of MF-DFA2 showed that these two cross over points are present in all fluctuations, so that different scale periods are also shown in small to large fluctuations and are not limited to medium period fluctuations. The results of MF-DFA2 showed that the generalized Hurst exponent (hq) has been converged with increasing rainy temporal scale, as the difference between the small fluctuations  and large fluctuations , the small-scale temporal series is larger than the large-scale temporal series; Thus, on a small scale, periods with large fluctuations can be clearly distinguished from periods with small fluctuations. Other multifractal properties, including a decreasing hq with increasing the rank of fluctuation (q), nonlinearity of mass signal  in relation to q indicate the multifractal nature and multiple scale behavior and nonlinear memory of the rainy signal of the studied stations (Adresh et al. 2020; Shimizu et al., 2002 ; Bunde et al., 2012; Tan and Gan, 2017).On one hand, the comparison of the parameters of the singularity spectrum of the stations shows that all the singularity parameters are similar in the area, but have different intensities. In this regard, the singularity spectrum of all stations in the area is asymmetric and has long left tails. Such a tendency in the singularity spectrum indicates the predominant role of large fluctuations in the multifractal structure of the rainy signal (Telesca and Lovallo, 2011). Thus, the shape of the singularity spectrum reveals that the rainy temporal series in the area has such a multifractal structure which is sensitive to local fluctuations with large values (Kalamaras et al., 2017). In this regard, the rainy temporal series in Khorramabad, Kermanshah and Dezful stations were more complex than other temporal series and Abadan and Ahvaz stations showed a very unstable and noisy structure. On the other hand, the extreme rainfall of southwestern stations including Abadan, Ahvaz and Dezful are much more unstable than the western stations and show heavy rainfall. In this regard, although the structure of Sanandaj station rainfall series is highly sensitive to extreme rainfall, but the intensity of its instability rainfall is lower than the limit rainfall of southwestern stations such as Dezful, which are less sensitive to that of Sanandaj. Its scale exponent is equal to 0.67 with the scale exponent of Khorramabad and Kermanshah stations. In general, such results indicate complexities of temporal series s of rainfall that have very strong local fluctuations.

Drought phenomenon as one of the most disastrous natural disasters in the arid and semi-arid regions of the world has caused a lot of problems in these areas. Due to its proximity to large desert areas, Lorestan province is frequently exposed to severe dust. Our goal in this research is to identify areas susceptible to becoming dusty in Lorestan province The method of doing research is analytical and statistical and the method of doing the work based on classification, each of the layers concerned, determining or extracting the criteria of dusty cores, weighing each of the layers using the AHP pair weighing matrix, Finally, the final collapse of the relevant layers is to determine the favorable areas of dusts using GIS, Spss, Expert Choice software. The results showed that about 9% of the area of ​​Lorestan province has a high potential for becoming dusty locally. The spatial distribution of this floor in Lorestan province was presented in the final map of the total weight loss of all layers, which indicated that the largest area of ​​this class is concentrated in the eastern regions, especially the northeast of the province, which includes the Azna and Oligudarz counties. There are also parts of this category in the southern regions of the study area, including the cities of Poldokhtar and Rumshagan. In the central regions of the province as well as in the northwest of the province including the Khorramabad, Delfan, Dynasty and Dorood districts this class is not observed. In the southern parts of the city of Kohdasht, small parts of the floor of the potential centers of dust are also observed. This floor has the most risk of becoming a dusty focus. The power source of many of the provincechr dusty incidents can also be said to be areas where some of them are currently potential sources of dust.

In this study, in order to simulate the monthly flow of the Khorramabad River, the time series of this river was decomposed into three levels using the wavelet of Daubechies-3, during the period of 1955-2014. Based on this, it was found that there is a Non-uniform noise that includes two periods of time in this signal, with the October 2008 border which required that the signal become non-uniform de-noising. Subsequently, by using two models of support vector machine (ɛ and Nu) and random forest algorithm (RF), the main signal and non-uniform de-noising signal of the river flow were simulated separately. The results validation criteria of the model showed that, with the non-uniform de-noising of the river flow signal, the error of the models dropped ɛ from 5.7 to 3.1, Nu from 5.8 to 3.2 and RF from 5 to 2.9 m3/s. Also, the comparison and testing of the computational error ɛ: ɛD; Nu: NuD; RF: RFD were obtained by using the MGN test (-15, -15, -107.6), which indicates a significant improvement in the performance of the models used as a result of the non-uniform de-noising signal. In the following, using optimization simplex algorithm in the of three models ɛD, NuD and RFD, the mean flow of the river was very high in all three models.

Introduction:

 Land use is generally referred to as the use of land in the present state.Land cover and its changes can cause greenhouse gas emissions Which causes climate change.climate change and land use interact with each other.This matter is of great importance in sensitive areas especially in arid and desert areas. These areas are sensitive to climate change and land use. In the case of climate change detection, the drought study has been very much considered in recent years. Iran is one of the countries that has suffered heavy damage from this natural threat because of being in the dry and desert region of the world. Various researchers have pointed to the relationship between land and climate change around the world.The purpose of this study was to investigate the relationship between land use and land use planningin in relation to climate change. This research proposes the new Land Use Planning approach in relation to land use as a management tool for climate change mitigation and carbon footprint reduction. Introduction Land use is generally referred to as the use of land in the present state. Land cover and its changes can cause greenhouse gas emissions Which causes climate change. climate change and land use interact with each other. This matter is of great importance in sensitive areas especially in arid and desert areas. These areas are sensitive to climate change and land use. In the case of climate change detection, the drought study has been very much considered in recent years. Iran is one of the countries that has suffered heavy damage from this natural threat because of being in the dry and desert region of the world. Various researchers have pointed to the relationship between land and climate change around the world( Cuo, Zhang, Gao, Hao, Cairang ,2013; Delgado, Gaspari, Kruse, 2015).The purpose of this study was to investigate the relationship between land use and land use planningin in relation to climate change. This research proposes the new Land Use Planning approach in relation to land use as a management tool for climate change mitigation and carbon footprint reduction. Material and methodes Introducing the study area Kashan watershed covers about 5574 square kilometers and Located in the north of Isfahan province and southwest of Tehran. The climaye of the study area is classified in dry or desert climate In the plain areas and it is classified in the semi-arid climate ,in the mountainous regions according to Domartan method The tools and methods in this research include: A.Land use: In order to study land use changes, Landsat5 MSS images,1985; Landsat-7 ETM+ images,2000 and Landsat 8 OLI,2017 were used. B.Climate change weather data available over the 30 year period from 1988 until 2017 at 7 meteorological stations: Kashan, Isfahan, Golpaiegan, Natanz, Meime, Ardestan, Najafabad(table1). This historical, data were obtained from the Islamic Republic of Iran Meteorological Organization (IRIMO) The model was validated using three

1. Coefficient of Determination(R^2), 2. root-mean-square error (RMSE), 3. Mean Squared Error )MAE) C. Low Carbon Land Use Planning(Green land use planning) Green land use planning(GLUP) is to determine the suitable use of each region based on its potential ,so that a land use with lower carbon levels be selected in place of more carbon levels. C1. Standardization of constraints and limitations C2. Weighing the constraints and limitations C3. Multi-criteria evaluation by weighted linear combination (WLC) Research findings Classification of images The results of the changes shown tha t Agricultural land use area increased by 5.7%, Bare land area by 0.61%, and Residental area by 0.32% of the total study area during the period (1985-2000). Range land, Sanddune,Salt land, Garden have decreased by 5.05, 0.92, 0.57 and 0.1% respectively. The results of Investigating the changes during the time period (2000-2017) show that Salt land, Residental and garden area increased by 12.20, 1.07 and 0.28 percent, respectively, and Range land, agriculture, Bare land and Sanddune area were 5.62, 4.69, 2.52 and 0.73 percent, respectively. Validation of downscaling model The results of the indicators indicate that the SDSM model has a more accuracy than the daily scale in the monthly and seasonal and annual scales for the downscaling of the precipitation parameter in the studied watershed. And in general, this model has a good performance in downscaling region precipitation. The results of Validation of downscaling model Based on the results of the SDSM, RCP4.5 predicts the lowest average rainfall of 0.2 in December and the highest average rainfall of .08 in May. Drought assessment The results of 12month spI index for overall study period during 1950-2050 show that in 1985 there was a drought in the range from 1.5 to 1.99, which indicates the sever drought on the studied area, In 2000 , the drought is located in the 0.99-99 range, which represents a near-normal drought. In 2017, the average 12-month SPI is reduced, and drought is in the 1.99-to-1.5- range, which indicates hard drought. Based on the SPI index for the next years 2030 (2011-2050), under the 4.5 scenario, the drought is reduced compared to the baseline and is located on the range of -2 and less range, which indicates an sever drought, indicating that the monthly precipitation Will decrease in 2030 during the climate change. Evaluation of ecological land capability Ecological capability was evaluated for 8 land uses ( Agriculture, range land , forestry, conservation, Extensive and intensive tourism and urban and rural development. Green Land Use Planning (Low Carbon Land Use Planning) The green land use planning map was created with priority for land uses with less water consumption and less carbon, to reduce the impact on climate change for the Kashan plain watershed. 

Reasults:

 The trend of change in Kashan plain watershed shows that at the same time as the study began, the trend of climate change (1985) has increased the agricultural and residential and industrial land araes. In general, these applications have the greatest impact on the rate of evapotranspiration and reduction of water resources and increased greenhouse gas emissions. With the continuation of the climate change trend and the negative trend of drought , the agricultural land and Range land areas have decreased and increased against the salt land areas. This situation is due to the reduction of agricultural land efficiency due to soil salinity and drying of irrigation wells and the abandonment of these lands, especially in the salt lake and the northern lands of Aran, Bidgol, Abu Zayedabad and Nasr Abad.

The extention of Snow cover and its spatial and temporal changes considered as a basic parameter in climatic and hydrologic studies. Data from satellite images due to the low cost and the large extention of cover are, effectively help the identifying of the snowy basins. Since the satellites are able to imaging a surface at different times, this will allow snow survey studies to investigate the spatial and temporal distribution of snow. In this research, Snow line changes and the surface temperature line in Alborz Mountains using NOAA-AVHRR satellite images since 2006 from 2015 was studied. The results showed that at the study period, maximum area of snow have been observed in April 2015, with the amount of 12051 square kilometers and the minimum area snow have been observed in June 2008, with the amount of 33 square kilometers. The average of the lowest elevation of snow covered areas, have been observed in April 2007, with the amount of 2662 meters and its highest value have been observed in June 2008 with the amount of 3820 meters. Also the most of the snow line change occurred between the years 2007 to 2008. Moreover, in almost of 15 years, the isoterm of zero degrees Celsius, matches with the snow line and its elevation has changed as the snow area is changed.

The plains of flood rivers are among the critical points of the flood. The Kashan Plain Watershed is one of the cases that has been flooded in numerous years. There has been many economic and financial losses in the residents of this watershed. Achieving and resolving environmental management problems in the watershed scale requires an integrated approach in evaluation and management, in which the processes and all the biophysical and socio-economic effects are considered (1). In the last decade, in a comprehensive action with a subtle and flexible combination of empirical models of evaluation of capabilities, the environmental and legal support of some pioneering countries with the approval of the law required the interference of natural disasters in the context of each development program. The new horizon of the Risk land use planning paradigm was opened, and logistic link to the efficiency of the programs and realization of the multilateral goals of sustainable development, and management of its environmental hazards was accelerated drastically (2).
In recent years, several researches in the field of Flood Risk Zoning (3,4), Impact of Land Use Change on Flood Risk Area (5,6,7,8) and Effect of Intensive Use Scenario on Flood Risk Area are presented. In this study, the risk zone of flood in watershed was determined, and the new risk land use planning approach were presented based on the uses of 1985 and 2017 as a management scenario for improving the watershed.

Kashan Plain Watershed has an area equal to 5574 square kilometers. It is located south of Qom Plain, and Salt Lake, and south west of the mountains of Vulture, and east of sand dunes of The High-Rise rig of Kashan. The climate of the study area is classified according to the Domarten method in the lowland areas except the arid or desert climate, and in the highland areas except the semi-arid climate.

There are various factors that can be effective on floods based on available data from the region; 11 effective slope percentage, elevation classes, lithological units, fault distance, distance from waterways, soil type, Stream Power Index (SPI), Topographic Wetness Index (TWI), Ground Curvature, Land Use, and Rainfall, which were selected for 1985 and 2017. Afterward, their raster maps were prepared with 30 * 30 cell dimensions.

The obtained weights were applied to the relevant layers. Then, using the mapping functions, the final map of flood hazard zonation was obtained.

A set of technical validation points (64 points, 30% of the total points) were used to validate the flood risk forecast map. The flood points were overlapped with the final map using a GIS software.

In preparation of the Risk Land Use Planning, the standardization was conducted based on two fuzzy logic (0TH1) for Criteria and Boolean (0 or 1) for limitations. In the next step, the criteria and limitations were weighted according to their importance and their impact on selecting appropriate location using Analytical Hierarchy Process (AHP) method. Further, the procedure was performed by evaluation of power for 8 uses of forestry, rangeland, agriculture, aquaculture, extensive tourism, centralized tourism conservation, and rural development by combining information layers (criteria) with Weighted Linear Combination (WLC) (8).

Finally, to prepare the flood potential map in the study area, eleven maps resulted from the GIS environment were used. The final map was classified in four different areas of potential, including low, medium, high, and very high potential zones. The results showed that from 1985 to 2017, the area of low and middle class decreased by 5.8% and 4.07%, respectively, and increased by 2.22% and 2.543% respectively. The study of Goodarzi and Fatehifar (1398) corresponds to the Azarshahr Tea watershed.

Based on the 1985 and 2017 flood hazard maps, the high and very high floodplains cover most of the catchment area. This indicates the need to prioritize conservation use in the risk management scenario.

In this study, the probability map of flood risk was prepared for both 1985 and 2017 land use. Then, in order to manage the flood risk, the new approach of risk land use planning was introduced. The results show that despite decreasing rainfall from 1985 to 2017, the floods during this period especially increase around Kashan, Aran, Bidgol, and surrounding villages. This concludes that climate change adaptation-based disaster management; containment of illegal land use change in risk land use planning of Kashan Plain Watershed for sustainable development. According to the results, more dire conditions will prevail in the region in the future. Therefore, it is recommended that organizations consider strategic flood prevention plans and prioritize risk planning.

Changing the climatic pattern can lead to major changes in the geographical distribution of infectious diseases. The aim of this study was to investigate the effect of climate change on the favorable bio-climatological zone for leishmaniasis sand-fly living which is a vector of Leishmania in Iran. Data of the climatic factors affecting the biology of sandflies during 1986-2016 were obtained. The climate thresholds for the sand-fly living were prepared on the basis of laboratory studies. Using Boolean algebra in GIS, the favorable bio-climatological sites of sand-fly in Iran were prepared in the basic period of climate (2016-1986). The climatic conditions of 2050 were simulated using the output of the general circulation model HADGEM2-AO under four scenarios RCP2.6, RCP4.5, RCP6, RCP8.5 and the bio-climatological zones of the sand flies were re-created using the Boolean algebra function in GIS, based on simulated climatic factors. The results showed that in the climatic conditions of the base period, about 0.64 of the Iran's area includes the central and southern and southwestern parts of Iran, has the climatic conditions of sandflies. While in the simulated climate of 2050 under RCP2.6, RCP4.5, RCP6, and RCP8.5 scenarios, it will be favorable for living of this vector about 0.63, 0.68, 0.61 and 0.67 of Iran’s area, respectively. Spatial variations of bio-climatological zones of Phlebotomus sandflies in RCP6 scenario had the highest reduction compared to the current climate and the highest increase was observed in RCP4.5.

Nowadays, extreme events, as one of the signs of climate change, have become major climatic hazards. The main objective of this study is to investigate the population exposed hyperthermia in Kermanshah at the time of the heat waves. In this regard, the heat waves of Kermanshah synoptic station were extracted during 2000-2015, and the heat wave in July from 7 to 13 was selected as the case study. The land surface temperature of Kermanshah city was extracted by applying a single channel algorithm on the thermal bands of ،TIRS sensor of the Landsat 8 platform for July 9, 2015. The obtained LST turned into air temperature using 09 UTC air temperature of Kermanshah meteorological Synoptic station. Using spatial statistics analysis of hot spots, critical regions of Kermanshah were identified during heat wave and the population of high risk was obtained from demographic block of 2016 census using tabular matrix analysis. The results showed that 6 districts of Kermanshah with an area of 3072 hectares form a critical heat core. The daily temperature mean of this heat core for 6 heat wave days was not less than 36 degrees Celsius, while the mean of maximum temperature of this part of the city was 47 degrees Celsius. The analysis of the tabular matrix indicates that according to the census of 2016, 0.52 of the total population of the city of Kermanshah, 492285 people, were located in the critical core area, and the population density in this core was 160 people per hectare, which is twice the density of Kermanshah city. 0.44 of the population of two demographic class (99893 people) that have high vulnerability to heat waves, heat stress and hyperthermia, namely, young children (under the age of 10) and the elderly (over the age of 60) are located in the heat core area. Nowadays, the climate change or, more precisely, global warming has had the greatest impact on different aspects of human life as the most serious environmental challenge facing human societies. Urban areas occupy less than 0.1 percent of the earth's surface (Lee and Baik, 2011), but most of the world's population (6.6 billion) is currently living in urban areas (Miller et al, 2013). High population density in urban areas, potentially increase the vulnerability of cities and cause environmental hazards to be more damaging, especially climate hazards. Over the past decades, population growth, rapid growth of industrialization, increased air pollution at low levels of the atmosphere, and the effects of island heat, cause dramatic changes in the  local weather and climate of the big cities. Increasing of climatic hazard frequency, severity and emerging climatic hazards are the most important aspects of climate change. Increasing frequency of extreme event, such as heat waves as one of the critical climatic hazards, has been listed in the World Health Organization since 2005 (Arbuthnott, 2016). The city of Kermanshah with a population of 946,651 people in 2017 is the largest city of Kermanshah province and the second most populous western city of the country after Tabriz and the ninth most populous city of Iran after Tehran, Mashhad, Isfahan, Tabriz, Karaj, Shiraz, Ahvaz and Qom. 0.48 percent of the total populations of the Kermanshah province live in the Kermanshah city (census of 2017). The main objective of this research is to investigate the vulnerability of Kermanshah city in the face of heat waves as one of the emerging climatic hazards. Two types of data were used in this study. The first batch was observed daily air temperature data, and the second batch was Landsat 8 imagery. We calculated daily mean air temperatures obtained from synoptic station of Kermanshah. To distinguish days with extreme air temperature, we used the method of (Fumiaki et al., 2007) that is called normalized temperature deviation or Fumiaki index. Considering the fact that there is only one synoptic station located on the northeastern part of the city, it is not possible to assess the degree of damage caused by heat wave hazard in different parts of Kermanshah city. For this reason, we used data from thermal bands of Landsat 8 (10 and 11 bands) to calculate the land surface temperature of Kermanshah city for the heat wave days. First, land surface temperature was obtained by calculating the brightness temperature, and in the next step, LST was transformed to two-meter air temperature using the development of a function. The hot spots analysis model was used to identify and detect blocks or critical areas of Kermanshah city during the occurrence of heat waves. This analysis, based on Getis-Ord Gi* is used to identify areas or neighborhoods of Kermanshah where during the heat wave event their air temperature was significantly (at a confidence level of 0.95 (P_value = 0.05) higher than the surrounding area. Using tabulate matrix analysis, the relationship between detected critical temperature regions during the heat wave and the population at risk of critical temperatures were identified in different regions of Kermanshah. To assess the potential risk of hyperthermia and the population at risk of it, the heat wave of 7-12 July 2015 was selected as the case study. This heat wave began on 7 July 2015. The warmest day of this heat wave, in terms of daily maximum air temperature, was on the fourth day of the heat wave namely, 11 July. In this day, the mean air temperature of Kermanshah reached 39.3°C, while the maximum air temperature reached 43.2° C. The results of the Getis-Ord Gi hot spot analysis, show that a large part of Kermanshah's area has an instantaneous air temperature that is significantly higher than its surrounding areas. These parts of the city, which have temperatures between 42 to 45°C have a significantly higher temperature than the surrounding areas at a confidence level of 0.95 (P_value = 0.05), forming a significant hot spot. The area of this critical category was 3072 hectares, equal to 0.32 of the total area of the Kermanshah. The daily mean air temperature of this hot core was not lower than 36°C during the 6-day heat wave in 2015, while the mean maximum air temperature of this part of the city was 47°C. The results of the cross tabulate analysis reveals that, 0.522 of the total population of the city of Kermanshah, 492285 people are located in the parts of the city, which its air temperature during the heat wave is in the significant critical area based on the hot spots index. As it can be seen, out of the 40% of the Kermanshah children, 54,436 people were located in this thermal core in which mean air temperature was over 38°C. 0.38 of the elderly population of the total population (33,376 people) was also located in this hot core with a maximum air temperature of 44°C during the heat wave. It was revealed that during the heat wave, a significant part of the area of Kermanshah is exposed to the risk of critical temperatures above 40°C. The area of the city which forms the critical hot core during the heat wave includes a significant part of the population of Kermanshah that is equal to 52% of the total population of the city. Out of 40% of the Kermanshah children, 54,436 people were located in this thermal core in which mean air temperature was over 38°C. 0.38 of the elderly population of the total population (33,376 people) was also located in this hot core with a maximum air temperature of 44°C during the heat wave.

Background Cutaneous Leishmaniasis (CL) is an important infection with a high incidence rate. The
spatiotemporal dynamics of this disease is mainly determined by three main components of parasite,
reservoir and vector. Climatic factors can significantly affect its incidence through their impact on these components.

The present study aimed to assess the effects of climatic changes on the incidence rate of CL in Mashad, Iran. To this end, first different phases of drought were identified through Standard Precipitation Index (SPI). Then the relationship between the incidence of CL and these phases was analyzed with non-parametric Kruskal-Wallis test and Dunn-Bonferroni test at a significance level of 95%.

The results of the non-parametric Kruskal-Wallis test on the incidence of CL in the three phases of drought showed a significant relationship between them. Dunn-Bonferroni test showed that the incidence of CL was significantly higher during the years with severe drought as compared to years with normal rainfall. The significant increase in the mean incidence of CL during severe drought can be attributed to limited food sources available to the vectors, which are mostly rodents.

Scarcity of food sources during drought makes rodents, as the main vector of the disease, to seek food and be more exposed to sandflies. That is how the incidence of CL increases.

Considering the significance of Zagros heights in precipitation distribution, the present study using the RegCM4 model and its simulations, the effect of Zagros heights on convective Cumulative precipitation and vertical velocity of different levels of the atmosphere was investigated. The required data was obtained from NCEP/NCAR with a 2.5 resolution from 22 to 38 latitude and from 38 to 58 longitudes on a grille with a horizontal resolution of 10 KMs and 30 SEC time steps for 2000 to 2005.Comprehensive cumulative convective systems were evaluated in two control run an experimental run and, effects of the Zagros heights in warm and cold seasons of the year was examined on these parameters. Results indicated that cores of rainfall during December-January after crossing system have been weakened, while April systems in East Zagros have continued to operate with the same power. Zagros heights in the months of December-January increased rainfall in West Iran and reduced in the Zagros East. In contrast, in April, there is no significant difference between the two runs in the Zagros East between convective precipitations. And maximum precipitation in both runs, is focused in West Iran and Zagros region and its minimum is focused Zagros East and Iran's central plains; But by eliminating the Zagros heights, the convective rainfall this month has increased on the shores of the Caspian Sea. The Zagros heights has to effect on vertical wind velocity profiles of Low levels and the speed and extent of the jet stream cores of high levels of the atmosphere; So that in April resulted movement atmospheric jet stream from level 200 to 400 hp and increases their speed and extent; So, the flows pattern of the mesoscale convective systems and the convective precipitation resulting from them were influenced by the elevation pattern; and kind and how the Zagros heights effects on convective precipitation and vertical profiles of wind speed in the warm and cold months of year is different; in a way that, the wind slowed down at low levels of the atmosphere in December and increased in January and April.