جستجوی مقالات مرتبط با کلیدواژه « climate change » در نشریات گروه « محیط زیست »

Climate change is the biggest ecological and social challenge of the current century, which is worth sociological investigation. The purpose of this article is to present general perspectives and highlights regarding sociological approaches concerning adaptation to climate change. The study investigated social approaches based on adaptation with perspectives of sociological research on the drivers of climate change and its consequences. The results were classified in the form of sociological approaches in three scales: macro, medium, and micro. The results showed that structural, institutional, and social adaptation measures are three important options for reducing vulnerability and increasing adaptation capacity. In addition, measures associated with adaptation to climate change to reduce present and future vulnerabilities are under three elements; Exposure, Sensitivity, and Adaptive Capacity. Government solutions to correct climate injustices are still unclear from the perspective of social justice, and there are still many questions that require further study.

Iran stands out as one of the world's biodiversity hotspots. Simultaneously, river fish species within the country face imminent threats from various human activities. Climate change, among other challenges, poses a significant risk to the biodiversity of Iran. Consequently, there is a critical need to anticipate potential habitat changes for freshwater fish species in response to climate change. This study focuses on evaluating the impact of climate change on the habitats of the Song fish, a species with economic value and conservation significance. The Song fish is currently classified as Vulnerable (VU) by the International Union for Conservation of Nature (IUCN), making the examination of climate change effects crucial for the future population of this species.

This study employs the MaxEnt model to predict the spatial distribution of the Song fish at two different time scales (2050 and 2080 AD) under both optimistic (RCP2.6) and pessimistic (RCP8.5) climate scenarios. The R software environment was used for the analysis. Environmental variables, including slope, annual temperature range, flow accumulation, annual precipitation, annual mean temperature, and upstream drainage area, were considered. The data related to the observations of this species have been collected from sampling and various library sources. Modeling performance in predicting species distribution has also been evaluated by the AUC (Area Under the Curve) criterion.

The model demonstrated excellent performance in predicting species distribution, as indicated by the high AUC (Area Under the Curve) criterion value of 0.989. Among the environmental variables, annual average temperature and slope emerge were the most influential factors in determining the distribution of the Song fish. Furthermore, the study revealed a projected decrease in the distribution range of this species under both optimistic and pessimistic scenarios for 2050 and 2080.

To safeguard the Song fish, it is imperative for managers to identify and implement appropriate measures. These measures should aim to mitigate the effects of climate change and alleviate threats associated with these changes.

Dust is a common phenomenon in arid and semi-arid regions. One of the factorsthat play a role in the occurrence of this phenomenon is the change in weather conditions, whichleads to drought, and the drying of lakes and rivers has caused crises such as sandstorms. Thisphenomenon leads to negative effects on agriculture, water and soil pollution, and respiratorydiseases, as well as environmental and social challenges such as reduced visibility and roadaccidents. The purpose of this research is to investigate the relationship between the DSI dustindex and SPI standardized precipitation drought index in Semnan Province.

The studied area of Semnan Province is located in the southern regionof the Alborz Mountain range. To investigate the effect of drought on the amount of dust, thedaily data of dust, monthly rainfall, temperature, relative humidity and evapotranspiration offive synoptic stations of Semnan Province within a period of 15 years (2003-2017) were usedon an annual scale. During a 15-year period, the drought storm index (DSI) was determined forthe synoptic stations using the dust storm index, and then the cumulative DSI index wascalculated. Afterwards, statistical and experimental evaluations was done on annualfluctuations to identify potential trends. Also, experiment and linear regression analysis wereused to evaluate the correlation of standard precipitation index and dust storms, and Arc GISsoftware was used for zoning.

The results showed that the average annual temperature in the regionhas increased from 2003 to 2017. This rapid warming has caused drought and as a result,temperature, evaporation and transpiration have also increased and led to a decrease in rainfall.A month-by-month survey of wind speed in different stations showed that there is a possibilityof dust in the province in the months of June and July when the maximum wind speed prevails.On the contrary, the months of December and January experienced the least occurrence of dust.The annual changes of DSI (2003 to 2017) showed an irregular shape and do not have a trend.Thus, in 2011, the intensity of dust was high and decreased in the following year, and the samewas observed in 2016. According to the SPI index, Semnan Province was in the normal droughtcategory with a score of 0.59. The in-depth analysis of the correlation chart between thestandardized rainfall indices and DSI showed that the DSI has increased along with the severityof drought during the study period and there is a good correlation between the DSI index andthe meteorological drought in the region, so that when there was a drought period, the value ofDSI decreased and when it was a drought period, the value of the dust index increased.However, there is no significant relationship between these two indicators (p =0.07 andR2=0.22) during the 15-year research period.

Our findings indicated an increase in dust from the west to the east of the provincedue to the increase in average dust storm days. Correlation results between SPI and DSI indexshowed that although DSI index increased during the analyzed period along with the severityof drought, the correlation between the two was not significant. However, the DSI index trendpattern was consistent with the drought pattern trend. Finally, the correlation between droughtand DSI has always fluctuated according to droughts.

Climate change and global warming, caused by the increase in the concentrationof greenhouse gases, have garnered significant attention across various national and internationalsectors. The emission of greenhouse gases has long been recognized as one of the most pressingenvironmental issues, sparking widespread concern. Since the Industrial Revolution, the demandfor energy and the consumption of fossil fuels have escalated, leading to increased greenhouse gasemissions. While the input and output of atmospheric carbon dioxide have traditionally remainedin balance with nature, human activities and carbon dioxide emissions have disrupted thisequilibrium in recent decades, giving rise to climate change and global warming.

There are various methods for measuring atmospheric carbon dioxide.Remote sensing technology, in particular, has emerged as a solution, overcoming the limitationsof ground-based measurement methods by offering continuous monitoring and global coverageof greenhouse gases. Despite the absence of ground stations for monitoring greenhouse gases inthe Middle East region, spanning 7,207,570 square kilometers, this study investigates the monthly,seasonal, and annual atmospheric concentrations of carbon dioxide using data from satellites suchas SCIAMACHY, GOSAT, and OCO. The study period spans from 2003 to 2020.

The findings indicate a significant increase in atmospheric carbondioxide concentration over the 18 years examined by all three satellites. In addition toexamining annual changes, this study also investigated seasonal and monthly variations inatmospheric CO2 concentration. The lowest concentrations of this greenhouse gas occurredduring the summer months, particularly in August and September, while the highestconcentrations were observed during the spring months, specifically in April and May.Furthermore, the analysis of differences in atmospheric CO2 between seasons revealed the mostsignificant changes from spring to summer, with an average decrease of 6 ppm. Conversely,the highest increases in atmospheric CO2 between seasons were observed from summer toautumn, with a recorded average increase of approximately 4 ppm.

This research indicates a notable increase in atmospheric CO2 concentration in theMiddle East region from 2003 to 2020, accompanied by seasonal and monthly fluctuationsconsistent with global trends of this greenhouse gas. This long-term rise in greenhouse gaslevels can lead to various detrimental effects in the region, including temperature escalation,alterations in rainfall patterns, heightened drought severity, and damage to natural ecosystems.Consequently, the socio-economic stability of the region could be jeopardized, impactingagriculture, water resources, human health, and biodiversity. To effectively manage andmitigate greenhouse gas emissions, immediate action is imperative at both national andinternational levels. Such measures may involve promoting renewable energy sources,enhancing energy efficiency, curbing industrial pollution, advancing emission reductiontechnologies, and fostering regional and international collaboration in greenhouse gas reductionefforts. Moreover, public awareness campaigns and policy interventions are essential tomobilize stakeholders and facilitate the transition to a low-carbon economy in the Middle East,ensuring sustainable development and climate resilience for future generations.

One of the consequences of the climate change in Khuzestan Province is thedrying up of a large part of the wetlands of this province, including Miangaran and Hoor al-Azim, which has caused dust storms in recent years. In this regard, this research aims to predictclimate changes in the area of Miangaran and Hoor al-Azim wetlands by using the SDSMstatistical microscale model based on HadCM3 B2 and A2 climate scenarios. Considering thespecific conditions of the region and the fact that few studies have been done regardingtemperature change in these areas, knowing the state of temperature change can help bettermanagement of resources, especially water resources management.

These parameters include the average sea level pressure, thegeopotential height of the surface of 850 hectopascals and the average temperature at a heightof two meters. For this purpose, by using the daily data of average temperature, minimum andmaximum temperature in the synoptic stations of Izeh and Bostan as the closest stations to Hooral-Azim and Miangaran wetlands in the periods of 2010-2039, 2040-2069 and 2070-2099,predictions were made and then a comparison was made with the base period (1961-1990). Theselected predictors in climate parameters were chosen using NCEP observational large-scaleparameters and SDSM software. These parameters included average sea level pressure, surfacegeopotential height of 850 hectopascals, and average temperature of two meters above thesurface. Also, with scenarios A2 and B2 until the year 2099, the prediction of the return periodof extreme climatic events in the HadCM3 model was done.

The results of the simulation of the HadCM3 model along withobservational data from the Izeh station, modeled annual average temperature data was 18.47°Cand for the Bostan station, modeled annual data average temperature was 19.10°C. Both stationshad a higher average temperature in the base period, and the maximum temperature in theMiangaran wetland was much higher than Hoor al-Azim wetland in the base period. The resultsshowed that in both stations in scenario A2, the average temperature had significant cycles withreturn periods of 1.2 years and the lowest significant cycles for the two stations were in returnperiods of 2.3 and 1.3 years, respectively. In scenario B2, the average temperature in twostations has significant cycles with return periods of 7.5 years and the lowest significant cyclewith a return period of 1.2 years. The results of examining the cycles in the studied areasindicate that in the A2 scenario, certain climatic conditions in the area have short-term returnperiods. One year was obtained in both scenarios, which indicates a wider range of the returnperiod and a higher probability of extreme temperature events in the B2 scenario. In thecomparison of the two stations, it can be seen that in scenario A2, the average temperature ofthe Miangaran wetland is 1.02 °C and the Hoor al-Azim wetland is 1.08 °C.

The results of the data analysis in the future observation and simulation periodswith scenarios B2 and A2 showed an increase in the mean, minimum, and maximum averagetemperature in the future simulation periods compared to the base period in Izeh and Bostanstations. In Bostan station, the average minimum and maximum annual temperature alsoincreased in the third period compared to the base period. In both scenarios, due to the increasein temperature, the drying process of both wetlands will continue.

The impact of climate change and global warming on Earth's climate and other systems such as water sources, agriculture, environment, industry, health and the economy as a known the threats to sustainable development. So the effects of climate change on different systems and adaptive solutions to deal with the negative consequences of this phenomenon in future periods is essential. So according to importance of the issue, the purpose of this study was to evaluate the effects of climate change on temperature, precipitation, runoff and finally hydrological drought in the “Roude Zard” watershed in the future. For this purpose, data from the years 2000-1971 as a base data to small-scale model of LARS-WG introduction and calibration data for the years 1997-1990 and 1989-1974 years data were used to validate models of rainfall-runoff IHACRES. In order to evaluate hydrologic drought index SDI was used. Results show that increase in mean annual temperature in the study area 1.02 degrees Celsius as well as the expected changes in mean annual precipitation to the study area 11/91 percent and 73/78 millimeters. Results IHACRES model to simulate rainfall-runoff study area show that this model is suitable. The simulation results runoff also indicated an increase in the average runoff affected by climate change in some of the months of January, February and March and a decrease in average monthly runoff out of the area in September, October. Also results of the SDI index show increase in intensity of drought in the future compared to the base period. The results of this study will be to adapt to climate change studies in order to provide suitable management strategies used in the study area.

Environmental problems in the world are a manifestation of unsustainable and inconsistent development with the capacities of the earth. Climate change is among all the problems, due to the global impact on the scale of the earth and effects such as floods, storms, unusual rain showers, increasing intensity, duration and volume of droughts, heat waves, melting of polar ice, rising sea water levels and going under water, loss of coastal lands, increase in minimum and maximum temperature in most areas, increase in evaporation and transpiration and water requirement of crops and Baghi, more evaporation of surface water and reduction of available fresh water sources, reduction of precipitation, increase of erosion and dust storms have attracted the attention of countries more than before. Iran, as one of the countries influencing the increase of greenhouse gases, is trying to increase adaptation and reduce the risk of climate change risks in order to manage surface and underground water resources, agriculture and improve the level of food security, natural resources and biodiversity (biological resources) and health of the country. In this regard, it is necessary to establish the governance of climate change in the policies and executive measures of the country at different national, regional, provincial and local levels in such a way that adaptation to it is implemented as a part of the country's daily life and development environment and as a result of increasing the level of environmental resilience, social, economic and cultural, all classes will benefit from its results. Climate change is one of the important factors that will affect different parts of human life on the planet and will have harmful effects on environmental, economic, social and especially water resources. For a long time, the change in meteorological characteristics of different regions of the world has been proven for researchers. The reduction of precipitation, reduction of surface currents and changes in the production and performance of agricultural products can be felt in many regions of the world. Our country is also facing many issues in this regard. Climate change has a significant impact on water resources and environment, which in turn is reflected in agriculture, society and economy.The increase in the concentration of greenhouse gases in the last few decades and the resulting increased temperature have led to significant changes in meteorological elements. Global warming, climate change and changes in temperature and precipitation parameters have now become one of the most important environmental challenges in the world. The reason for this is that these changes will cause droughts or severe, short and long term floods in the future. Therefore, one of the ways to reduce the effects of climate change is to evaluate its effects on rainfall and temperature in each region.

In order to simulate the climatic data, at first, the observational data of Arak synoptic station including minimum temperature, maximum temperature, precipitation and daily sunshine hours in the statistical period of 1980-2005 were obtained from the country's meteorological organization. Also, CanESM2 global model data under RCP2.6, RCP4.5 and RCP8.5 scenarios along with observational data related to National Center for Environmental Variables Prediction (NCEP) were downloaded from this center's website. In order to scale the output data of CanESM2 and HadGEM2-ES models, LARS-WG model was used. LARS-WG model is also one of the statistical exponential microscale models. This model is one of the most famous meteorological data generation models, which is used to generate daily data of maximum and minimum temperature, precipitation and sunny hours in a station under current and future climate conditions (Alizadeh et al., 2013). In this research, the 6th version of this model was used to scale the output of the HadGEM2-ES model. In the LARS-WG model, after receiving the daily observation data (minimum temperature, maximum temperature, precipitation and sunny hours), the statistical characteristics of the data were extracted. Then, in order to ensure the ability of the model, a series of artificial data was produced in the base period (1980-2005) and compared with the observational data. In order to calibrate and ensure the accuracy of LARS-WG model performance, simulated variables and real data were evaluated. The results show that the LARS-WG model has a good accuracy (R2=0.99) in simulating the minimum and maximum temperature. Also, the accuracy of the model in simulating precipitation (R2=0.98) is acceptable.

Based on the results of the model under the RCP8.5 scenario, the LARS-WG model shows a decrease in rainfall in all three periods, which is consistent with the assumption that the continuation of global warming will lead to a decrease in rainfall. Based on the results, LARS-WG model has predicted minimum temperature increase in all three scenarios and all three periods. Regarding the annual maximum temperature, the results of the LARS-WG model have increased in all three scenarios and all three periods compared to the base period. The minimum temperature and the maximum temperature simulated by the LARS-WG model increase under all three scenarios to reach the maximum value in the RCP8.5 scenario, which indicates the effect of the intensity of carbon dioxide emission concentration in the atmosphere as well as other It is a greenhouse gas. Also, the results showed that the most changes in the maximum temperature related to the RCP 8.5 scenario (from 23.12 in the first period to 26.51 degrees Celsius in the third period), the most changes in the minimum temperature related to the RCP 8.5 scenario (from 8.71 in the first period to 60/11 in the third period) and the most precipitation changes are related to the RCP 8.5 scenario. The period studied in this research was 2021-2040 (first period), 2041-2060 (second period) and 2061-2080 (third period). The modeling results show a decrease in rainfall in all three periods, which is consistent with the assumption that the continuation of global warming will lead to a decrease in rainfall. The minimum and maximum temperature changes showed that in most cases, the minimum and maximum temperature will increase in the future. The maximum temperature increase was more than the minimum temperature, so that the highest temperature increase occurs in the month of February by 1.89 degrees Celsius compared to the base period. Examining the changes in the amount of rainfall also showed that the lowest amount of rainfall in the coming period will be observed in the month of June in the amount of 07.07 mm. A decrease in rainfall on the one hand and an increase in temperature on the other hand can indicate that the increase in evaporation and transpiration and the decrease in snow cover can move the water balance towards land and reduce water reserves.

Climate change has a direct impact on hydrological components and water resources and plays an important role in aggravating possible risks such as drought and floods. Therefore, it is necessary to investigate the effects of climate change on water components such as runoff. This study evaluates the effect of climate change on climatic parameters (temperature and precipitation) and the amount of runoff in Kiwi Chai basin from an environmental point of view. The hydrological model of the Soil and Water Assessment Tool (SWAT) was used to analyze the effects of climate change on the water resources of the Kiwi Chai basin, which is one of the Sefidroud sub-basins. Runoff simulation by applying climate change conditions for models (EC-EARTH, HadGEM2-ES, MIROC5, MPI-ESM) under two scenarios (RCP 4.5 and RCP 8.5) in three periods (2040-2021), (2041-2060), ( 2061-2080) and statistical analysis was performed to identify which climate model is more consistent with the changes in the mean and standard deviation of the historical series. An increasing trend in precipitation and a significant increase in average annual temperature were predicted in the early, middle, and late 21st century. The results of simulation of basin runoff with SWAT model also showed a significant decrease in basin runoff in future periods compared to the base period. These findings provide local water management authorities with useful information to aid decision-making in the face of climate change.

Climate change is known as one of the main reasons biodiversity loss and natural ecosystems destruction. Carnivores are strongly affected by habitat changes, due to their large home range and low population density, and they are often forced to change their distribution to unsuitable habitats. One of the important carnivores is Asiatic cheetah, which there are probably only less than 40 left in Iran. The purpose of this research is to predict and evaluate climate change on the Asiatic cheetah habitat in Touran protecting complex using presence points, environmental factors (such as elevation, slope, vegetation type, distribution of prey (Indian Gazelle, Persian Gazelle, Wild Goat, Wild Sheep), water sources (springs), roads, etc ), climatic variables and species distribution models such as CTA, RF, MARS and SRE in R software. For forecasting, GISS-E2-1-H climate model and 4 scenarios SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5 were used and the habitat suitability map of Asiatic cheetah under current and future climate conditions was prepared. The results showed that the area of suitable habitats is currently about 300000 hectares, which in 2050 under the optimistic scenario will be 240000 hectares and under the pessimistic scenario will be 165000 hectares. In 2050, the suitable habitat of Asiatic cheetah in Touran protecting complex will be separated from the current suitable areas and will be moved to the borders and outside the study area. There are some strategies for managing the likely climate change impacts on Asiatic cheetah’s habitat in order to conserve the species and its habitat more effectively, including, increasing conserving proceedings to recover grasslands and prey population in suitable habitats, designing new Protected Areas and extending the border of current Protected Areas and creating corridors between the current and potential habitats of cheetah.

Energy use in agriculture has grown faster than other sectors of the global economy. In developing countries, most agricultural systems consume significant amounts of energy to increase production and food security. Energy consumption leads to the emission of greenhouse gases and environmental pollutions in the agriculture sector. Besides, the use of fossil fuels in the production process and transfer of inputs emits greenhouse gases, which in turn cause global warming and climate change. Analyzing and good understanding of energy flow and Greenhouse Gas (GHG) emissions in agricultural production systems can help to optimize crop management practices thereby reducing environmental problems.Qazvin Plain is one of the most important agricultural plains in Iran, which along with the use of groundwater, has the largest irrigation canal network in the country. Differences in agricultural water supply sources can lead to differences in energy consumption and GHG emissions as electricity and other inputs may be affected. Alfalfa and maize silage are major forage crops in Qazvin Plain. Alfalfa and maize silage need a relatively high irrigation water requirement. This paper evaluates the energy flow and Global Warming Potential (GWP) of alfalfa and maize silage farms with two different water supply sources (well and canal) in Qazvin Plain.

The data were collected through face-to-face interviews with farmers in the years 2018-2019. Energy indices were estimated based on the analysis of farm inputs and outputs. GWP was calculated using the Life Cycle Assessment (LCA) method and SimaPro 8.2 software. GHGs were calculated using the conversion coefficients presented by the IPCC GWP 100 method. 

The output energy values of maize silage and alfalfa were calculated as 232726, 191812 MJ ha-1 for well water irrigation system and 234167 and 248060 MJ ha-1 for the canal water irrigation, respectively. Results showed higher net energy values for alfalfa (176218 MJ ha-1) and maize silage (169192 MJ ha-1) in canal water irrigation system compared to well water irrigation (63115 MJ ha-1 and 132956 MJ ha-1 for alfalfa and maize silage, respectively) mainly because of the relatively lower input energy. The results showed that the highest and lowest values of input energy were related to alfalfa production with well water irrigation (128697 MJ ha-1) and maize silage with canal water irrigation (64975 MJ ha-1), respectively. Also, the energy use efficiency of maize silage (3.6) and alfalfa (3.4) were higher in canal water irrigation systems compared to well water irrigation systems (2.3 for maize silage and 1.49 for alfalfa). In the well water irrigation systems, GWP was calculated to be 7466.9 kg CO2-eq ha−1 and 7995.7 kg CO2-eq ha−1 for maize silage and alfalfa, respectively. These values were 5533.3 kg CO2-eq ha−1 and 4947.6 kg CO2-eq ha−1 for maize silage and alfalfa in the canal water irrigation systems, respectively. Electricity and direct emission showed the highest share of total energy consumption and GHG emission.

Generally, our results showed that energy consumption and GWP were lower in the canal irrigation systems than well irrigation systems mainly as a result of electricity used for water pumping in well irrigation operations. It can be inferred from the present study that for efficient use of resources and decreasing environmental problems in the study area, practices such as optimal management of irrigation water, conservation tillage, and optimal management of chemical fertilizers can help to achieve these goals.

Preventing nuclear war and avoiding catastrophic climate changes are two of the most fundamental challenges facing human civilization in this century. The purpose of this research is to investigate the effects of nuclear disarmament on climate change from the perspective of international law. This research focuses on the potential links between nuclear energy as an option to reduce climate change and nuclear disarmament and, respectively, discusses topics such as current nuclear risks, the scale of the nuclear-climate challenge, nuclear security and Its relationship with nuclear energy, non-proliferation and disarmament, management of nuclear disarmament and basic steps to address the challenges of proliferation and disarmament and the political links between maintaining and strengthening the global non-proliferation regime, nuclear disarmament and the growth of nuclear energy It has been done on a large scale. The use of nuclear energy places unprecedented demands on global systems for the verification, control and security of weapons-usable nuclear material. Reducing or abandoning or emptying many nuclear weapons and equipment and their final ban also requires new approaches to manage the huge global stockpile of weapons-usable nuclear materials. The international community should take measures so that nuclear energy can help reduce climate change in the long term. As a result of such actions, nuclear disarmament becomes more practical, desirable, and unattainable, and lays the foundations for a world in which nuclear technology contributes to sustainable development while nuclear weapons begin to fade from the scene.

Climate change and its consequences have become a threat to the planet, the natural and man-made environment, and it leads to an increase in greenhouse gas emissions, global warming. In recent decades, the amount of carbon dioxide in the atmosphere has increased, and this factor of climate change, such as temperature, has decreased. One of the effective factors in the management of agricultural and industrial projects is that changing the pattern of distribution and its amount, especially its decreasing trend, can play important role in determining the time of crop cultivation and water resources planning. Temperature as one of the important climatic factors, causes changes in the temporal and mechanical pattern of climatic phenomena and droughts, floods, storms and heat waves. Destructive climate change is due to a great increase or intensity of extreme weather phenomena and climatic events. In fact, extreme events rarely occur, but they have a direct impact on communities and vulnerable areas. Studies have proved that climate change is driven by simultaneous increases in evapotranspiration and changes, contributing to water cycle processes. Social and environmental impacts of extreme events are locally significant as a result and can severely affect specific sectors and locations. From a statistical point of view, climatic events, changes in the average limit and deviation of climatic indicators alters the occurrence probability of number of frost days, cold and hot days and nights, and the length of the growing season. Climate change intensify the hydrological cycle and change the amount of evaporation and transpiration and the pattern of precipitation. Climate change and global warming increase droughts and their continuation, and this change also causes uneven distribution and affects water resources. The purpose of this study was to evaluate the temporal and spatial variations of climatic rainfall indices in the central part of Ardabil province.

In this study, 11 climatic extreme indices were selected and evaluated in a 40-year period (1973-2014) to evaluate changes. At first, the required data were prepared and after processing, the values of the indices were calculated using Excel software, then the temporal trend of the indices was analyzed by ProUCL software. Evaluating the existence of a trend in the time series data is one of the important aspects of time series. In this regard, non-parametric methods are usually used due to the lack of statistical assumptions. In this research, the Man-Kendal method was used to investigate the changing process of climatic extreme indices. The non-parametric Mann-Kendall test has the ability to adopt with non-normal time series that does not follow a specific distribution. Also, this test has a small influence of the outlier values in the time series. Regarding the spatial interpolations, there are several methods to estimate the spatial changes of variables. The difference between these methods is the way of calculating the weight that is given to the observed points around the unknown point. In this research, the inverse distance weighting method was used, which estimates the values of unknown points through the weighted average of observational data with identical points.

In general, the changes in rainfall extreme indices have a decreasing trend in all stations, but it is significant in Hir station. Based on the results of interpolation maps, the indicators of maximum 1-day monthly rainfall, maximum 5-day monthly rainfall and total annual rainfall on rainy days in the central and western parts show the least and most values, respectively. Raw rainfall intensity indicators, total annual rainfall in 95% of rainy days in the northern, southern and western parts of Ardabil province show the most values and in the eastern part of the region the least values. The indicators of the number of days with rainfall of 10 mm or more, the number of days with rainfall of 20 mm or more and the total annual rainfall in 99 percent of rainy days showed the least and most changes in the east and north-west of the region, respectively. The indicators of wet period length and Rnnmm indices show the most values in the western and eastern parts and the least values in the central part of the province. The high values of number of rainy days index with more than 20 mm precipitation are related to Sablan slopes. It should be noted that the maximum length of the dry season is longer in the middle parts than in the areas of Musharraf and the north, as well as in the slopes of Sablan. The spatial distribution pattern of the maximum wet period index is also such that the maximum length of the wet period is in the stations located on the path of rainfall caused by the incoming moisture from the Caspian Sea and Gilan province, and this effect of the increase of the wet period is also clearly visible in the stations of Sablan slopes.

According to the findings of the study, the least changes in precipitation extreme indices occurred in central stations and the highest values in precipitation extreme indices occurred in stations located in western part of the study area. Overall, it can be said that assessing changes in extreme indices can be a guide in assessing climate change and its negative effects on soil and water conditions. It should be noted that the changes in extreme indicators in different regions will be different based on climatic conditions, but in most areas, the changes in extreme indicators are such that extreme events are intensified. One of the important effects of climate change is changing the rainfall regime and the pattern in the future. In many cases, changes in precipitation characteristics and extreme events may not follow the general trend of precipitation reduction. Spatial evaluations of changes in the occurrence and trend of extreme climatic indicators can help in identifying the signs of climate change. The dominant trend of increasing changes in rainfall extremes can have a significant contribution in intensifying the flood occurrence. The extreme rainfall events have undergone many changes in recent years under the influence of many factors. Considering the occurrence of severe floods under the effect of extreme rainfall events, examining the changes in the trend of these events in the past years and predicting them in the future will be effective in planning and managing water resources and natural disasters caused by these events. Forecasting changes in climatic extreme events is necessary to take effective considerations to deal with the harmful effects of climate change. In general, it can be said that the analysis of indicators related to extreme events can complement the results of evaluating the annual average values of climatic variables.