mohammad baaghideh

The performance of broiler chickens is directly influenced by temperature changes and the occurrence of heat stress, whether it is cold or hot. The present study aims to assess the cooling and heating degree days in different stages of broiler chicken production in Khorasan Razavi province. To achieve this objective, daily average temperature data were collected from 13 synoptic stations during the statistical period of 1988-2018. Cooling and heating degree days were calculated for each week of production using specific thresholds, and their spatial distribution was analyzed. Furthermore, the relationship between cooling and heating degree days and geographical features was evaluated. The findings indicate a decrease in cooling degree days and an increase in heating degree days as latitude increases. The northern and western regions of the province exhibited a greater need for heating throughout all stages of broiler chicken production, whereas the eastern and southern regions had higher cooling requirements at different production stages. Overall, the northeastern, southern, and western marginal areas of the province, including Khaf, Gonabad, Kashmar, Sarakhs, and Sabzevar, exhibited the lowest cooling and heating needs during the 6-week period of broiler chicken production, making them suitable climates for this economic activity.

Heat waves are one of the natural climate phenomena in different regions of the world, which have increased as a result of global climate fluctuations in recent years; which has negative effects on agriculture, fires of forests and pastures, water resources, energy consumption and human health.There is no comprehensive and clear definition of heat wave globally, so that even the World Meteorological Organization has not been able to provide a comprehensive definition of heat waves. Heat wave is variable in different situations and no specific criterion has been defined for it. On the other hand, the characteristics and intensity of heat waves are also variable in each place. But in general, heat waves can be considered as positive fluctuations above the average maximum daily temperatures, which have continuity over days and sometimes weeks.It seems that in each geographical region, based on its environmental and climatic characteristics, certain temperature thresholds can be considered to define the heat wave.Generally, a heat wave refers to intense periods of heat that last more than 5 days and the temperature is 5 degrees higher than normal and also creates a crisis for the environment and human health. In other words, intense heating of the air or the rule and invasion of very hot air in a wide area is called a heat wave.

In this research, the daily maximum temperature data of Isfahan synoptic station were used to identify heat waves in Isfahan. Identification of heat waves based on the 90th percentile was done in such a way that by considering the thresholds for each season and month, the periods in which the maximum temperature was higher than the desired threshold for at least three consecutive days (90th percentile) were considered as heat waves. . In the next step, the frequency of heat waves for different seasons and months was checked, and taking into account the difference between the 90th percentile threshold and the average temperature of the heat wave, the intensity of each heat wave was also calculated, and the trend of its changes in the scale of months and seasons was checked. In the next step, the continuity of each of the identified waves was checked for different months and seasons; in this way, the average continuity and the highest continuity of heat waves and the trend of their changes during the statistical period were evaluated. In this research, the daily heat wave magnitude index (HWMI) has been used. Extraction of heat waves in each season has been done based on a separate percentage threshold of that season. Annual values are also obtained from seasonal values. In this way, the sum of the number of waves of the seasons determines the number of annual waves and the average magnitude of all the waves of the seasons determines the average magnitude of the annual waves of each station. The magnitude of each heat wave is the sum of the magnitude figures of all the days of that wave. Also, the biggest wave of each year is considered as the indicator wave of that year and the biggest wave of each season is considered as the indicator wave of that season.

In the spring and summer seasons, in the first decades of the statistical period, durations of less than 5 days prevailed, but since the mid-90s, heat wave events have occurred in higher durations, with the highest duration in the spring season with 18 days for 2017 and the highest heat wave event. The summer season in 2003 was recorded with duration of 17 days. Spring, summer and autumn have not had much difference in the average duration of heat waves; in such a way that for these three seasons, heat waves continued for an average of 6 days; But for the autumn season, the lowest average duration was recorded with 4.35 days. In line with the trend of changes in continuities, a significant increase has occurred for a large index in the late 90s compared to the beginning of the statistical period. Its clear examples are in the spring season, the magnitude of 29.54 in 2017, in the summer season, the magnitude of 28.05 in 1977, and the highest average magnitude value, which is recorded in these seasons. Examining the changes in the heat wave intensity index, all seasons during the statistical period, from 1970 to 2021, shows that the most intense heat wave is related to the spring with an intensity of 3.88 in 2020, the summer season in 2012 with an intensity of 1.65, and the autumn season It occurred with a magnitude of 2.93 in 2017. The most severe heat waves related to the winter season occurred in three consecutive years between 2016 and 2018, and the intensity of these three waves was 3.31, 3.35 and 3.36, respectively.

There has been a significant increasing trend with a rate of more than 0.5 degree increase for each decade. By examining the frequency of occurrence of waves, we found that the occurrence of heat waves in all seasons of the year in the entire statistical period under study had an increasing trend. The highest frequency related to the spring season with 61 cases and the autumn season with 43 waves during the statistical period, have the lowest frequency of heat waves among other seasons. Examining the frequency of occurrence of heat waves on a monthly scale showed that the months of May and June had the highest frequency of heat waves with 21 and 20 occurrences, respectively, and July had the lowest frequency of heat waves with 13 occurrences in the statistical period studied. Examining the intensity of the waves showed that this index had an increasing trend in all seasons, and based on the results of the Mann-Kendall test, this increasing trend was significant for all seasons except summer. The changes in the highest duration of heat waves show that, in the first decades of the statistical period, durations of less than 5 days prevailed, but since the mid-90s, heat wave events have occurred in higher durations. The longest recorded duration of heat waves for spring and summer was 18 and 17 days, respectively. Since 1990, at the same time as the trend of global warming, the penetration of heat waves in Isfahan city has increased significantly, and the most heat waves were recorded in 2003 and 1999. On a monthly scale, the highest average persistence was in March and August. The highest duration recorded for heat waves in the months studied in the statistical period (1970-2021) was for April and July with 13 days and the smallest for January with 6 days. Along with the trend of changes in continuities, a significant increase has occurred for a large index in the late 90s compared to the beginning of the statistical period.

The aim of this research is to evaluate the capabilities and limitations of climate parameters in Shiraz’s urban design and architecture with a focus on energy management. For this purpose, Climate Consultant software was used; this software can display and graphically examine climatic features and uses a strong and documented database called EPW in the time step of long-term hourly averages for radiation data, dry temperature, soil temperature at different depths, relative humidity, and wind speed and direction. Determining the level of comfort and providing energy-saving strategies in different climate zones are among the important capabilities of this tool. The results showed that the months of January, February, and December are completely outside the range of thermal comfort, and the most comfortable conditions are in the radiation range of 800 to 900 W/m2 with a temperature range of 20 to 25 degrees Celsius. According to the psychometric chart, 10.1% of the hours of the year are in complete comfort conditions, and reaching comfort conditions in other hours and days of the year requires the use of different strategies. The ideal thickness for the mass of the walls is estimated to be 4 to 5 inches with optimal materials (brick, concrete, and stone), and it is better for the mass of the inner wall to be denser than the outer wall. It is very convenient to use massive structures with small holes that perform night ventilation. Ceiling fans can reduce indoor temperature by at least 2.8 degrees Celsius. Flat roofs with light colors are the most suitable option, and in designs with courtyards, the presence of small ponds is very effective in cooling the adjacent rooms. Interior spaces and doors can be used to promote natural cross-ventilation. Also, to protect privacy, the design of air-flow jump channels can be used. By shading the windows in line with the direction of the prevailing wind, natural ventilation can reduce or even eliminate the need for cooling facilities

The activities of humanity on Earth have significantly changed over the past hundred years. The increase in greenhouse gas concentrations has led to global warming and, as a result, has caused changes in climate indices. Assessing extreme temperature and precipitation values is of great importance in agricultural planning and water resource management policies. In this study, using daily temperature and precipitation data from 18 synoptic stations located on the periphery of the central desert of Iran, 12 extreme indices, including 6 temperature indices and 6 precipitation indices defined by ETCCDMI, were evaluated for the time period from 1991 to 2020. For trend and magnitude determination of the indices, the Mann-Kendall test and Sen's slope estimator were used. The research results indicate an increasing trend in warm extreme indices and a decreasing trend in cold extreme indices in the study area. The Alborz Mountains factor has some influence on these indices, with the decreasing trend in cold extreme indices being less pronounced in the northern part of the region, which is closer to the Alborz Mountains, compared to the southern part. For instance, the Shahroud station and warm extreme indices in the southern part of the region show a significant increasing trend compared to the north. Furthermore, the diurnal temperature range index in the northern part of the region, which is close to the southern slopes of the Alborz Mountains, exhibits the highest increasing trend, while in the southern part, this index shows a decreasing trend. Regarding the 6 precipitation indices, no significant trend was observed in most of the stations.

The aim of the present study is to dynamically model the spatial-temporal characteristics of dust in the south and southeast of Iran with REG-CM4 model using monthly dust data and RegCM4 data. For this purpose, the dust distribution of the IDW method along with the dust diagrams were plotted. The RegCM4 model was implemented with the paired Lambert image imaging system for 40 km horizontal separation with the paired chemistry model. The location of monthly and annual dust distribution shows the highest amounts of dust for the cities of Zabol, Bandar Abbas, Zahedan and Jask compared to Sirjan, Kahnooj and Lar stations. The highest frequency of dust in Sistan and Baluchestan (48%), Hormozgan (27%) and Fars provinces with 16% and the lowest frequency for Kerman province (9%). In general, the summer seasons (at Sistan station) and the winter (Kerman station) have the highest and minimum dust events, respectively. The time survey also has the highest amount of dust for the warm months of the year and the lowest for the cold months of the year. July at Zabol station and November and December at Sirjan station have the highest and lowest dust levels, respectively. The RegCM4 climate model also shows maximum dust on the southeast, south and south coasts for different variables.

Worries about how to plan and exploit water resources in confronting new conditions have increased as evidence of climate change becomes more apparent. This issue has led a significant portion of recent meteorological research to examine climate change's consequences on water resources. One of the most important developments is the change in the inflows to the dam's reservoirs. The Dez Dam was built over the Dez river and is located in southwestern Iran, within 23 kilometers of distance from Andimeshk. Its maximum capacity is 3.3 billion m3. As one of the most important water supply sources in the agricultural and electric energy sector of Khuzestan province, this dam has faced severe droughts in recent years, and the flow to the reservoir has been decreasing. The purpose of this study is to evaluate the amount of inflow and reservoir volume of the dam under the conditions of climate change.

To simulate basin temperature and precipitation, the accuracy of 17 Regional Climate Models of the CORDEX - WAS project (South Asia) was evaluated based on the skill score (SS). Then, a combination of ten with the lowest skill score was used to simulate the climatic parameters of temperature and precipitation for future periods. Also, the bias correction of simulated monthly precipitation and temperature data in the historical period and then the future period was done in each station and for each parameter using the change factor method. Simulations of these parameters were conducted for three 20-year periods 2020s (2020-2039), 2050s (2050-2069), and 2080s (2080-2099) under the RCP4.5 and RCP8.5 scenarios for selected stations. In this research, the SWAT semi-distributed hydrological and MODSIM models was used to simulate the inflow and reservoir volume, respectively.

The results of the downscale of the selected models and climatic scenarios indicate an increase in minimum and maximum temperatures in all months of the year and decreased average rainfall in the future. Predictions considered the range of minimum and maximum temperature increase under selected models in the RCP4.5 scenario from 1.5 - 4.2 ° C and 1.5 - 3 ° C, respectively, and in the RCP8.5 scenario from 2.7 - 5.3 ° C, and 1.6 - 5.8 ° C probable. The models also predicted the range of precipitation change to be 11 up 17% under the RCP4.5 scenario and 8 to 18% under the RCP8.5 scenario. After ensuring the hydrological model's accuracy and the general circulation models (RCM) output, the SWAT model was implemented under different scenarios. The outflows indicate a significant reduction in the flow of the Dez River in the future. The reduction rate can be between 49 and 52% in the RCP4.5 scenario and the RCP8.5 scenario was more, especially in the last decade of the 21st century, about 44 to 64%. The highest decrease will occur in the colder months of the year. In other words, the inflow decreases in December and even further decreases in April and March. One of the main reasons for the decrease in the volume of flow in the region in these months (March, April, and May) is changes in the precipitation pattern, in addition to the decrease in precipitation. In other words, in these months, the water of snow melting is associated with an increase in the river's discharge in the current climate, but such conditions will change in the future. The decrease in the flow rate entering the dam has caused a decrease in the reservoir volume of the dam, and its volume has decreased under RCP4.5 and RCP8.5 release scenarios. In the RCP4.5 scenario, the average annual volume of the reservoir will reach 1184.4, 1179.8, and 1138.8 billion m3 for the three decades of 2020-2039, 2050-2069, and 2080-2099, respectively. In the RCP8.5 scenario, this average value equals 1293.8, 1070.4, and 1008.9 billion m3, respectively. Therefore, under the two selected scenarios, the reservoir volume was reduced between 47 to 50% for the future decades. This significant decrease in volume in the future decades, which has affected the volume of water discharge of the dam, that is indicate Dez Dam will face significant challenges in come cross  with downstream needs (environmental needs, agriculture, drinking, industry, and electric energy).

This study evaluated the effect of climate change on the amount of inflow and the reservoir volume of Dez Dam under two climate scenarios. Using the semi-distributed SWAT model, the water flow simulation to the dam is done. After evaluating the model and calibrating and validating the parameters of the hydrological model, by entering the future precipitation and temperature data into the calibrated SWAT model, the flow was simulated for the three future periods under the above scenarios. The results of the climate models illustrated that the average minimum and maximum annual temperature would have increased by 3 and 3.5 degrees Celsius, respectively, for the future decades. The average annual precipitation for the study area will have decreased by 14%. The prediction of the inflow to the dam by the SWAT model under two scenarios indicate a significant decrease in the discharge of the Dez River in the future; The amount of this decrease in the RCP4.5 scenario will be between 49 to 52%, and in the RCP8.5 scenario and especially in the last decade of the 21st century, it will be more and around 44 to 64%. The decrease in the flow rate entering the dam has caused a decrease in the volume of the reservoir of the dam, and its volume will have decreased between 47 and 54 percent under the two selected scenarios for the future decades. In general, the results obtained from this study indicate that this region will move towards a climate with lower humidity and higher temperature in the future decades. This situation will increase the shortage of water resources in the basin and will intensify the water crisis in the downstream areas. Therefore, it seems that the water resources management in this basin requires a review for its sustainable development and exploitation. Since, the flow rate of Dez in the future decades will significantly decrease due to, the expected of the climate changes, the Dez dam's primary goals to meet the needs of agriculture, electricity, drinking, etc. will have face significant shortages. It is recommended to implement the policy of reducing demand, changing the cultivation pattern, recommending and developing the cultivation of low water-demanding plants, using new irrigation methods, and using unconventional waters.

 The choice of land use has always been a part of the evolution of human societies. This means that with the gradual evolution of human societies, there has been a change in the type of their needs and as a result, different societies have realized the need for a change in the use of land. The purpose of this study is to determine the suitability of lands in terms of soil characteristics including soil texture, soil electrical conductivity and soil lime for barberry in Iran.

 Using ArcGIS software and kriging method interpolation, generalization of point-to-area data and combination of maps, suitable places for barberry cultivation in Iran during the statistical period of 20 years (1997-1997).

 After identifying the soil factors affecting barberry cultivation based on kriging method, spatial data were analyzed using GIS and the location map of barberry cultivating areas in three classes of suitable, relatively suitable and unsuitable areas was determined.

 From this research, agro-climatic information is provided for planners and officials to use this information to carry out agricultural development activities in Iran.

Human comfort is significantly affected by climatic parameters and geographical features. There are few studies that have focused on the role of these two factors together in human comfort. Considering this, this research tried to evaluate different levels of human comfort using the Somatosensory Temperature (ST) index based on the golden ratio theory in 13 Iranian metropolitan cities. The parameters of minimum and maximum temperature, minimum and maximum humidity, precipitation and average wind speed were obtained from the Iran Meteorological Organization for (1991-2020) period. The ST index was designed based on the Golden Ratio theory and the Actual Optimum Comfort Temperature (AOCT) and its important features are significant flexibility to changes in latitude, altitude, and season. The results showed that there is a significant (α<0.01) inverse correlation (-0.867) between latitude and optimal comfort temperature, and this relationship for the height parameter is also with the correlation (-0.607) was significant at the 0.05 level. Bandar Abbas and Ahvaz had the highest frequency of hot thermal sensation and Tabriz had the highest frequency of very cold days. The highest monthly distribution of thermal comfort conditions is estimated for Rasht. For the summer, Tabriz with a total of 21% comfortable conditions has the best situation among other cities, while Ahvaz, Bandar Abbas, Kerman and Yazd have not experienced any of the comfort levels in this season. The highest percentage of the frequency of complete comfort conditions belongs to the autumn, so that in this season, complete comfort prevailed in 9 cities. The use of all the main climate parameters and the possibility of applying various corrections have provided the ST index with the ability to be used in a significant range of latitudes and regions with different altitudes.

Global warming has intensified the corals bleaching in some areas. In this study, the effect of climatic parameters on the health of branching corals in Chabahar Bay was investigated. For this purpose, climatic data of ECMWF center and Chabahar meteorological station were used. Coral health data were obtained from the Coral watch site and also by diving operations by the author. Statistical analyzes were performed using Pearson correlation, multiple regression, Mann-Kendall trend and analysis of variance. To estimate the temperature and health level of the coral ecosystem in the coming decades, the combined data of GCM models of CORDEX database were used under two scenarios of radiation induction RCP8.5 and RCP4.5. The results showed that despite the significant increase in air temperature and a significant decrease in coral health index in the past, the health status of branching corals at the end of 2019 is classified as "good". According to forecasts, although there are differences in the level of branching coral health index between the observation period and the coming decades, these differences are only statistically significant for the distant future and only under the pessimistic scenario of RCP8.5. In other words, under the conditions of climate change from the perspective of both scenarios, the health index of branching corals for the coming decades in the "good" classification with an average annual color grade of about 4 out of 6 Score for the RCP8.5 scenario and 4.3 for the scenario RCP4.5 will be maintained.

Coral ecosystems, like other natural habitats, are under the influence of global warming. Every year we see the bleaching of corals in different parts of the world. Since the physical parameters of seawater are affected by meteorological phenomena, so in this study using ten-year data of oceanographic buoys, the effect of physical parameters of seawater including water surface temperature, salinity, acidity and electrical conductivity on the phenomenon of bleaching of branching corals in Chabahar Bay was investigated.

For this purpose, the trend of multi-year data of marine parameters was determined by non-parametric Mann-Kendall test. In the next step, the Pearson correlation test showed the correlation between seawater parameters and choreographed Zooxanthellae algae color score data as a coral health index produced by the authors during long-term diving operations using the Coral Watch method.

The results of this study showed that among the four parameters: water surface temperature, electrical conductivity, acidity and salinity, the highest correlation and the most effective independent variable in multivariate regression between coral health and seawater parameters is concern to EC.

Due to the insignificance of the increasing trend of water surface temperature in previous years and the existence of a significant negative correlation at the level of 0.01 between the health status of corals and water surface temperature, fortunately, the branching corals of Chabahar Bay have been in good condition. As human and sea pollutants are controlled in the coming years. We will see the survival of this valuable ecosystem.

Nowadays, corals are exposed to bleaching due to climate change and rising water temperatures. On the other hand, the physical parameters of seawater are per-se affected by climate fluctuations. In this study, we aimed to investigate the effect of physical water parameters such as water temperature, salinity, acidity, electrical conductivity as well as climatic parameters such as air temperature and maximum wind speed on the health of massive corals in the Chabahar Bay. For this purpose, the data recorded at Chabahar Bay Hydrographic Field Station, the ECMWF Center Database, and Chabahar Meteorological Station were used. Ten-year monthly color data of the algae coexisting with massive corals have been extracted as a coral health indicator during diving operations using the Coral Watch method. The relationship between variables was also investigated through the Pearson correlation test, multivariate linear regression, and Mann-Kendall trend analysis using SPSS and Minitab software. According to the results, salinity and electrical conductivity showed a significant decreasing trend, while water acidity and air temperature showed a significant increasing trend. Meanwhile, water temperature and wind speed maximum showed insignificant increasing and decreasing trends, respectively. As for the health status of massive corals, there was a significant decreasing trend ending in 2019 (with a color score of 3.54 out of 6) set is in the category of "moderate". In addition, the health of mass corals showed the highest positive correlation with salinity and EC while indicating a negative correlation with maximum wind speed with a level of 0.01. On the contrary, there was no significant correlation between bulk corals' health and water temperature.

In order to develop Shahid Beheshti port of Chabahar, about 20,000 coral colonies were moved from the port development plan to a new site located in the north of Shahid Kalantari port. A decade after the corals were transferred, it is essential to know their health in order to make future decisions in similar cases. In this study, while examining the trend of air temperature and water temperature of Chabahar Bay, by diving operations and using Line Intercept Transect and Coral Watch methods, the health status and coverage of corals was monitored monthly from 2011 to 2017. Climatic data required for this study were obtained from Chabahar Meteorological Station and the satellite database of ECMWF Center. The relationship between the variables was examined through Pearson correlation test and Man Kendall trend analysis and the capability of SPSS and Minitab software. According to the results, the health status and development of the mentioned corals has a decreasing trend to the extent that the percentage of live coral coverage has increased from 98% in 1390 to 71.5% in 1398. On the other hand, the color degree of the health index of branched corals with a score of 4.31 out of 6 was in the "good" condition and mass corals with a score of 3.59 points were in the "average" condition. Despite the negative correlation between temperature and health of corals and the existence of a significant upward trend in the parameter of air temperature, due to the insignificance of the upward trend of water temperature, it seems that other factors besides water temperature fluctuations in the downward trend of health of corals have been involved.

Iran is a country with an average rainfall of about one third of the world's average rainfall, and is severely under water due to water resources. Therefore, improvement of water use efficiency based on production in agricultural sector is very important. In this regard, the simulation of plant growth stages and, as a result of the need for forecasting, will result in better planning and more efficient management in the production process.Nowadays, tools are needed to help irrigation system designers to optimize irrigation water management in agriculture; Therefore, the FAO, with the development of the Aqua Crop model, provides these essential management tools for the various agricultural sectors necessary; In this research, Aqua Crop plant model was used for water requirement of barberry cultivars. For this purpose, inputs to the model include meteorological, vegetation data, irrigation management, farm management, soil characteristics, simulation time period, and initial conditions in the field. The survey of water requirement zonation map indicates that, considering the climatic conditions, the climate of the northern regions of the country, despite the fact that it is not recommended for the cultivation of barberry, is the least water requirement in comparison with other regions of the country. The provinces of Khorasan Razavi, North and South, which are the best places to grow barberry at the moment, and the major production of barberry in these areas, are higher than other areas in need of water. The northern parts of the country also have a moderate water requirement.

Surface temperature is one of the main indices of Earth's energy balance and has an impact on human life because all human activities, direct and indirect, are related to the temperature of the air, which is affected by the temperature of the earth's surface. Therefore, in this study, using Landsat satellite images dating from 19/05/1394, the relationship between vegetation and surface temperature in the northern part of Ardebil province was studied. To this purpose, vegetation indices (NDVI, SAVI, and LAI) and LST index using the Mono Window method were used in ENVI 4.8 software. The results showed that there is a direct correlation between vegetation indices and surface temperature, and in urban areas and Wasteland, the highest LST is evident, with the expansion of urbanization and the increase of desertification over the years, it will be added. Therefore, the northern and southeastern regions of the study area (including Moghan plain and Fandoghlo forests), which are rich in vegetation, have LST less (LST values in this region are around 290 to 300 Kelvin), and the central regions of the study area Which is poor in terms of vegetation and includes Wasteland with a higher LST (LST in this area is between 312 and 324 degrees Kelvin). The results of this study are very useful in environmental and natural resource conservation studies and could be the basis for environmental protection planning.

Understanding the main components of the watershed water basin and analyzing their hydrologic behavior are among the key components of any planning and management procedures in the field of water resources engineering. Today, the need to use modern technologies in hydrological modeling of watersheds has been discussed more than before. The purpose of this study is the simulation of hydrological components in various land use categories in the catchment area of the Dez river basin. Since the tool used in the research is the SWAT model and the SUFI-2 algorithm, the database used include a range of input data. In order to determine the level of sensitivity of the model to the input parameters, global sensitivity analysis was performed. Then, by adjusting the selected parameters and using the observation current, the model was calibrated and validated for the periods 2007 - 1994 and 2013 - 2008, respectively. The coefficients of NS, R2, P-factor and R-factor confirmed the modelchr('39')s ability to simulate river flow in the studied basin. The results of the model showed that the areas with forest use share the highest contribution to aquifer nutrition, and the barren lands have the highest surface runoff. Surface runoff has the leading role in creating the main stream of the river and after that the main flow has been effective in this area. The forest use change to Agricultural lands and pasture will change the hydrological parameters of the basin, and the result of these changes will lead to the increase in the surface runoff, the reduction of nutrition of groundwater resources and the reduction of river basin water. The SWAT model can be used as a precursor model in watershed management studies.

The application of the RegCM4 dynamic model has enabled the study of mesoscale and regional scale atmospheric phenomena in different regions. Heavy precipitation is one of the essential atmospheric phenomena critical for agriculture in arid regions. Optimal use of rainwater increases water resources in the arid region. One of the solutions for optimal use of water in arid climate is to utilize crop pattern. The crop pattern means the share of cropping and selection of crops in an area, employing the optimal cropping pattern as one of the important solutions to water efficiency in agriculture. In this research, various data including rainfall data, NCEP/NCAR, TRMM satellite model, RegCM4 regional climate model, Aphrodite, and finally, agricultural data were used to change the cropping pattern for optimum use of water. Then, 5% precipitation threshold method was used to investigate heavy rainfall and selected as a representative of heavy rainfall in the study area on March 14th. The seasonal rainfall percentile chart, heavy rainfall maps and rainfall zones and performance of crops were then prepared and analyzed. The results indicate that the percentage of seasonal precipitation is in ascending and descending order in spring and winter, respectively. According to the regression model, Birjand, Nehbandan, and Ghayen stations are suitable in spring, and Ferdows and Boshrouyeh stations in winter. Moreover, the intensity of atmospheric streams in NCEP/NCAR and TRMM model maps gradually in northeast and east areas especially south Khorasan has led to heavy rainfall that RegCM4 model has been able to significantly simulate it and this rainfall has considerable values. Humidity values have increased on CAPE and thermodynamic graphs. Furthermore, in the zoning maps in the output of the observation map on Birjand station, Birjand, Ghayen, and Nehabandan, with the highest rainfall show better agricultural performance, while Boshrouyeh and Ferdows stations have the lowest performance. Therefore, since crop performance is directly related to rainfall, heavy rainfall can improve in agricultural in South Khorasan as a dry climate province. One way to deal with low-water resources in arid climates is to use crops such as Jujube, Barberry, and Saffron that are less water-intensive in agriculture and more adaptable to climate and regional conditions than other crops. Therefore, with proper use of rainwater during heavy rainfall in low-lying areas, the performance of agricultural products will greatly improve in South Khorasan province.

Drought is one of the recurring phenomena in all parts of the world with high-rainfall and low-rainfall climates and it is consider as a natural disaster. Iran is also one of the countries which involved in this phenomenon in different places. Its characteristics, such as the severity, duration, and extent of the drought, are vary from place to place and its damages is depending on the country's planning. In this regard, the necessity of knowing the correct weather conditions and climatic characteristics of different regions have become clear to planners through environmental, economic, agricultural and industrial potentials and their optimal use, as well as predicting the occurrence of natural disasters such as floods and droughts. In this study, for evaluating and comparing drought and wetness events, the precipitation data for the period (1987- 2017), as well as the evaporation and transpiration data and the number of rainy days during a statistical period of 10 years (2008-2017) were obtained from 9 stations in Fars province. The standardized precipitation index (SPI) was used, and the Arc GIS software, the drought zoning, evaporation and transpiration maps, and the number of rainy days in the province were plotted. In the studied years, Fars province has faced a near-normal state for 24 years in and drought for 5 years and wetness for one year. The drought situation was studied and analyzed in Shiraz city in the continuation. According to the obtained results, the drought in Shiraz city is more severe than the other parts of the province and it will continue in the future. The SPI index has the highest correlation with the parameters of the number of rainy days with a rate of (0.46) and evaporation and transpiration with a rate of (0.26) in 2012 and 2008.

Climate is one of the most important factors affecting life and distribution of plants and animals in every geographical setting. This research was an attempt to identify climatic sub-regions of Kermanshah Province using factor analysis. After data analysis, six factors were distinguished based on correlation. Combination of these six factors (temperature, precipitation, humidity, cloud, thunder, wind and dust) explained about 90% of the climatic behavior of the study area. Using cluster analysis and integration method, the studied stations were divided into three climatic clusters. In De Martonne classification of Kermanshah Province, two types of semi-arid and humid climates were distinguished whereas applying Emberger classification, two types of cold semi-arid and cold semi-humid climates were found.

Heat-humidity stress is one of the most important environmental factors affecting the development of the fetus and the health of pregnant maternal., Studies in this area have been limited. The aim of this study was to investigate the effects of short-term exposure to heat-humidity stress in the form of THI on fetal growth and development. For this purpose, animal models were used...  pregnant NMRI mice that were exposed to heat-humidity stress in the chamber during the second period of pregnancy (3, 5, 8, 10 and 15 minutes) daily for short periods Placement courses (GD 14.5-17) is designed in accordance with the growth and development of the human embryo. Exposure to thermal-humidity stresses in the second period (GD6.5-14) during of pregnancy shows an increase in maternal mortality and fetal weight loss, crown-to-rump length (CLR) and placental weight in comparison with the control group. Also, with increasing thresholds of stress at different thresholds of the index, embryonic abnormality (Exohatics, Facial Deformity, C-Shaped Body, Ear structure defects, Hemangioma and Limbic Adhesion) have increased. T-test of two independent samples and ANOVA confirmed the above-mentioned results at the level (p-value<0.01). The results of this study can be effective in the development of care programs, treatment and education of pregnant mothers, and to monitor the thermal stresses and design of warning systems.

Evapotranspiration monitoring has important implications for climate modeling and water resource management at the global and regional levels. Considering that the semi-northern half of Ardabil province is one of the important agricultural poles of the country, evapotranspiration was, therefore, estimated in this research using the Landsat 8 images (dated 2018/7/1) and the SEBAL and mountain SEBAL methods were applied and compared with the Penman-Monteith method. Then, different levels of land use were extracted in the region using the object-oriented image classification with a kappa coefficient of 0.945 and a general accuracy of 0.956. Based on the obtained results, the water levels (9.61 and 9.5 mm/day) had the highest evapotranspiration and urban and bare lands with mean values of 2.845 and 2.08 mm/day in the SEBAL and Mountain SEBAL methods, respectively, had the lowest 24-hour evapotranspiration. Moreover, amounts of 7.14 and 6.70 mm/day were estimated for water requirement of pea crop for SEBAL and mountain SEBAL methods, respectively. These values were compared with that of Penman-Monteith method (6.32 mm/day) with a mean absolute difference (MAD) of 0.60. Subsequently, the extracted area of each land revealed the lowest amount (an area of 1202.62 hectares) of cultivated pea land, which was about 4.6 percent different from the area  (1147.25 hectares) previously declared by the Agricultural Jihad in Ardabil province; though, it seems to be acceptable. In addition to precipitation and runoff, evapotranspiration is one of the main components of the hydrological cycle, which is affected by two biophysical and environmental processes among the soil, plant, and atmosphere. Monitoring evapotranspiration has important implications for both global and regional climate modeling; it is also helpful in the understanding of the hydrological cycle and assessment of the environmental stresses affecting the forests and agricultural ecosystems. This is because evapotranspiration is one of the processes influenced by the climatic elements such as precipitation, cloudiness, humidity, distribution of wind, and concentration of atmospheric gases. Constant precipitation and reduced rainfall in some cases, and, in contrast, increased evapotranspiration have faced most of human, agricultural, and natural needs with available water shortages. As a result, hydrologic equilibrium methods, such as evapotranspiration modeling, are widely used to assess the impacts of climate change on the water requirements of crops and plants. For this purpose, many studies have been carried out around the world and Iran to estimate the amounts of evapotranspiration.

Areas under study in this research were the semi-northern half of Ardabil province, including Ardabil, Bilesvar, Germi, Meshkinshahr, Namin, and Parsabad, with an area of 12571.33 square kilometers located in the northwest of Iran. The province is geographically located between 37° 45׳ to 39° 42׳ N, and 47° and 30׳ to 48° and 55׳ E latitudes. Maximum and minimum altitudes in this area are 4732 and 36 m above sea level.  Ardabil is the most important city in this area. In this study, Landsat 8 image of 2018/7/1 and meteorological data of the same day were used to compare the evapotranspiration of different land uses by SEBAL and mountain SEBAL with Penman-Monteith methods. ENVI 4.8, ERDAS and RefET were used to process images and implement the algorithms of SEBAL, Mountain SEBAL, and Penman-Monteith. The eCognition software was also employed for object-based land use classification. The SEBAL algorithm (Surface Energy Balance Algorithm for Land) and the mountain SEBAL algorithm are both determined based on the energy balance at the surface. In other words, the energy used for evapotranspiration is calculated as the remaining equation of the flux of the surface flow energy.

To estimate the actual evapotranspiration of different land uses and the pea crop, the required images were prepared and processed, followed by calculations related to the SEBAL and mountain SEBAL algorithms. Then, the land use map was classified into nine classes (agriculture, bare lands, grade 1 range, grade 2 range, grade 3 range, forest, pea, residential areas, and water levels) using the object-based image classification method with a Kappa coefficient of 0.945 and an overall accuracy of 0.956 for the studied area. Then the area of each application was calculated in hectare, indicating the bare and pea-cultivated lands as the largest (847985.10 ha) and the smallest (1202.62 ha) ones among the studied locations. Also, the area of pea-cultivated land was compared with that (1147.25 ha) declared by the Agricultural Jihad in Ardabil Province, which were 4.6% different that seems to be acceptable.

The SEBAL model has high accuracy in estimating the evapotranspiration of flat agricultural areas. However, due to the influence of some factors such as slope, elevation, and direction of gradient on evapotranspiration, a new model, called mountain SEBAL, was presented in order to correct these factors while interfering with the factors mentioned in the calculation process. In this research, therefore, the SEBAL and mountain SEBAL methods were used to estimate the evapotranspiration of different lands. Also, amounts of 7.14 and 6.70 were estimated for water requirement of the cultivated pea crop using the SEBAL and mountain SEBAL, respectively. These values were compared with the Penman-Monteith FAO method (6.32 mm/day) due to non-availability of a lysimeter and the wide range of the study area. Accordingly, the Penman-Monteith method used to estimate the water demand of chickpea had an absolute difference (AD) of 0.82 and 0.38, and a mean absolute difference (MAD) of 0.66, respectively.

This study was fulfilled aiming at the identification of spatial and temporal changes of temperature islands in Isfahan province First, a data basis of the highest and lowest net-based temperature and a committee were founded in Isfahan. Using the data of the basis, a statistical period of 35 years from 1980 to 2014 was chosen as the basis of the study and a geo with dimensions of 18 by 18 kilometers was spread on the area understudy. In order to access the during-year changes of the temperature islands of Isfahan, modern methods of spatial statistics such as Moran's I autocorrelation and hotspots in GIS environment were used. The results of the study showed that the changes of spatial and temporal in temperature islands of Isfahan possess a high cluster pattern. Based on the local Moran’s indicator and hotspot, the temperature islands of the east and north of the province have a positive spatial autocorrelation while the west and southwest areas have negative spatial correlation. During the study 41.45 of the province has not had any meaningful pattern or spatial autocorrelation. It was also shown that the temperature islands are controlled and affected by the local factors which control the space as well as the outside factors which control the time.

Although nature has the ability to deal with change, it cannot tolerate the growth of industries, deforestation and degradation of the environment. These huge and abrupt changes have caused to increasing the destruction of nature in recent decades, and increasing greenhouse gases. Ground water plays an important role in sustaining ecosystems and enabling human adaptation to climate variability and climate change. Groundwater resources are the largest store of fresh water in arid and semi-arid regions. In the areas where surface water resources are limited and inaccessible for people, groundwater can be considered as a secure resource. Climate change caused fluctuations in the ground water. Many wells dried up and some of them have lost their advantage due to the lack of available water. Climate change through changing climatic variables (including temperature, precipitation and evapotranspiration) directly affects surface water resources in many parts of the country. Besides, there have been many related problems such as drying up wells, reducing river flow, decreasing water quality, subsiding in lands, diminishing fresh water supplies and increasing salts in water. Climate change and its associated problems appear to be a serious challenge in the regions as Khorasan Razavi that 32 of 34 desert plains were declared prohibited. Due to cold and dry weather conditions and use of aquifers and wells as the main sources of water, Mashhad relies on groundwater as well as underground resources. The water resources of this plain are affected and threatened by changes in groundwater levels, temperature, rainfall, and frequent droughts. This research aims to study the groundwater level decline in Mashhad plain which is located in Khorasan Razavi province, northeastern of Iran. The study tries to conduct a comprehensive study through the analysis of monthly precipitations data acquired from 34 synoptic, climatology and rain-gauge stations, monthly discharge of 13 hydrometric stations, and 60 groundwater piezometric wells. It confirmed the normality of climatic data, using the Kolmogorov-Smirnov test. The research also used multivariable regression methods as well as HadCM3 climate model scenarios to model groundwater perspective of Mashhad’s plains and to predict future climate variables, respectively. To compare the output scale of the mentioned model with the required scale of climate change studies, the data of temperature and precipitation were downscaled for the two periods of 2015-2030 and 2046-2065, under three scenarios of A1B, A2 and B1 using the LARS-WG5.5 model. It later employs geographical weighted regression (GWR) to model the ground water level (as the dependent variable) with climatic parameters of temperature, precipitation, and evapotranspiration (as independent variables). Mashhad’s prospect of precipitation and temperature revealed a rainfall reduction for the cold season, its increase in the warm season, and at least one-degree increase compared to the base year. Modelling of groundwater level changes (using the parameters of rainfall, temperature and evapotranspiration) showed decline in groundwater levels in the range of at least 0.2 meters and maximum 0.7 meters. The research provides an intelligent simulation for fluctuations of groundwater using multiple regression models and the historical data of rainfall, temperature and evapotranspiration, which helps to estimate underground water level in the coming years. The results indicate a drop in the water level of all studied piezometric wells, under three climate change scenarios for future periods. The study concluded that the most important reason of water loss in Mashhad’s plains is the human overuse of groundwater. Fluctuations in groundwater assessment have shown that the highest annual fluctuations of groundwater were occurred in the southern part of Mashhad plain. Fluctuation assessments of surface water showed negative fluctuation in upstream and positive in downstream. These issues reflect the role of human factors in increasing the groundwater level in downstream and reducing the level in upstream. Modeling of groundwater level fluctuations with climate parameters (temperature, precipitation and evapotranspiration), using GWR and OLS models, represents superior of geographical weighted regression model compared with ordinary least squares models. Fitting weighting matrices to GWR model showed high accuracy of Gauss method than the other studied methods. The important issue that was obtained from simulations of Mashhad station is reducing the variance of rainfall in A1B emission scenario, indicating the absence of stable conditions in the future. The results of this research showed that the most important reason for the drop in Mashhad plain is overuse of groundwater.

Climate change and its impacts stand as the most important challenge to the world. One of the fundamental issues that have emerged in recent decades is the limited water resources. Because of the high dependence on precipitation, water resources are heavily susceptible to damage from climate change. Projection the effects associated with climate change is a major part of strategic planning in the current century. Cold climate regions are the main reservoir and feeding source for surface and underground water and a vital supplier of hydroelectric power in Iran. Any change in the seasonal precipitation situation will have severe outcomes for the status of water resources in cold regions. The purpose of this study is to investigate the impacts of climate change on seasonal precipitation in cold regions of Iran based on the outputs of new CMIP5 models and radiative forcing (RCP) scenarios. Alongside this, changes were first observed for the period 1980-2005. Afterwards, the data for the upcoming period up to the 2090 horizon were processed using the models BCC-CSM1.1, HadGEM2-ES, GFDL-CM3, MIROC-ESM and GISS-E2-R from the series of CMIP5 models of the MarksimGCM database based on the radiative forcing scenarios RCP8.5 and RCP4.5. The data were subsequently validated based on weighing method and RMSE, MAE, MBE and R2 evaluation criteria. The results of the processing were drawn on the digital elevation layer (DEM) of cold climate regions of Iran in the form of temporal-spatial seasonal precipitation distribution. Is The results showed that based on the weighing method and applying statistical indices on the output of CMIP5 models, the output of the HadGEM2.ES general circulation model is accompanied by fewer simulation errors in illustrating the climate change of the future period than the observation or baseline period. In fact, based on the evaluation criteria or errors, this model showed a higher compliance with observational data. In the monthly pattern in cold regions of Iran during the cold months, especially in the autumn and winter months, the precipitation parameter indicates a slight increase from 10-20 mm relative to the baseline period. This small increase in precipitation over the coming decades, based on the structure of the models, cannot be stable because of increasing temperature and evapotranspiration. However, in the annual and normal long-term pattern, the precipitation level will be less than the preceding period such that in the 2020-2055 period in the annual pattern, precipitation decreases by 54 mm, equivalent to 20.1% decrease. Seasonal precipitation will decrease in winter, autumn, and summer of the upcoming period up to the 2090 horizon, according to radiative forcing scenarios. Precipitation reduction in the summer will be more severe than in other seasons. Only in spring season will the amount of precipitation in the coming period increase slightly compared to the baseline period. Most of the spatial variations in precipitation distribution will occur in the cold climate regions of Iran in the high-altitude areas of the middle Alborz and especially in high Zagros regions. The center of areas with maximum precipitation in cold regions will mainly move to higher latitudes. In fact, the regions with substantial precipitation will become smaller, whereas areas with low rainfall will be extended. Therefore, climate change will have an impact on the temporal-spatial distribution of precipitation in the cold climate regions of Iran and will face with a future with less and variable precipitations.

Climate is considered as one of the most important factors affect the tourism industry. The present study is a field study that aims to investigate the role of climate in tourism and validate the performance of bioclimatic indices. This research has been carried out in Gondman lagoon area in Chahar Mahal and Bakhtiari province on the Nowruz holiday of 1396. The field data are collected through a questionnaire with axial topics including thermal sensation, thermal preference, aesthetics, adaptive behavior, and individual characteristics. Another part of the data is climate parameters such as temperature, relative humidity, cloudiness and wind, which is measured at the same time as completing the questionnaire by the lutron-lm-9000 data logger calibrated to CE standard. Bioclimatic indices (Predicted mean vote and Physiological Equivalent Temperature) are used to measure the thermal comfort conditions. Besides, Pearson correlation and multiple regression model are used to analyze the data. The results show that there is no significant correlation between the actual data obtained from the questionnaire and the data estimates by the indicators. Biochemical indicators show more warming conditions, while actual data often indicate a feeling of thermal cooling. In contrast, the thermal sensation of individuals reveals a significant and meaningful impact on independent climate parameters, the highest for clouds (R = -0.82) and humidity (R = -0.88). In other words, the visual conditions of the environment have a significant role in the type of person's sense of warmth. Due to the negative of these coefficients, cloudy sky with high humidity has significantly affected the type of heat feeling stated in the questionnaires. The use of bioclimatic indices in the evaluation of thermal comfort conditions requires the validation of these indicators and, if necessary, corrected.