In the present time, with the increase of industrial activities and the neglected environmental issues, the effects of climate change have become more evident and poses this phenomenon as a global difficult. Increasing the probability of occurrence of extreme climatic events such as flood and increasing the frequency and intensity of the effects of climate change. The northwest of the country is one of the most vulnerable areas of the country due to its semi-arid and mountainous climates and high rainfall variability. Therefore, zoning due to climate change is essential. Therefore, in this study, in order to investigate the risk of flood in the Azarshahr basin, due to climate change, using the CanESM2 general circulation model under RCP8.5 scenarios negativity according to the assessment report fifth IPCC, rainfall and temperature variables were down scaling by Statistical down scaling model (SDSM). Then, with hydrological model SWAT the daily runoff, the basin map and the lines of the canals are achieved. The results of the evaluation of the SDSM model with a coefficient of determination and Nash-Sutcliff 0.95 on average represent the good performance of the model in the down scaling of large scale data. The results show an increase of 0.23oC and 4.53% rainfall and maximum discharge. The basin is zoned with the combination of the maximum mean discharge map, the coefficient and distance from the river with the AHP approach. Due to the zoning they are 41.55% of the area of the basin, at very low and low risk, 27.23% at average risk and 31.2% at high and very high risk. Also, with the final map, it became clear that the mid-basin had a high risk due to its prerequisite conditions and that it needed to carry out managerial actions.

Water and food security are the key challenges under climate change as both are highly affected by continuously changing climatic patterns. In this study, attempts have been made to investigate the effects of climate change on length of growing season and water use of sugarcane under RCP scenarios in 4 stations of Khuzestan province, southwest of Iran, namely Abadan, Ahvaz, Bostan and Dezful. The outputs of EC-EARTH global climate model data which were dynamically downscaled by Swedish Meteorological and Hydrological Institute (SMHI) under RCP 8.5 and 4.5 scenarios were used as future projections. The climatic observed data of 4 study stations were collected and used to calibrate the model downscaled outputs. The changes of precipitation, crop evapotranspiration and length of growing period of sugarcane were worked out. The results showed that except for Dezful station, growing season rainfall would increase comparing to climatic normal. Besides, the length of growing season under RCP8.5 scenario would decrease significantly in all stations. Future trend of evapotranspiration changes were non-significant and less than 5%.

This study was conducted in order to assess the probable effect of climate change on the trend in the maximum extent of temperature variations in three scales including the point (synoptic stations), zonal (included 10 geographical areas in Iran), and national average scales. This study, the trend in the maximum extent of temperature variations of the baseline climatic period (1986-2005) was investigated against three future climatic projections, and also three future climatic projections, future climatic projections (near, middle, and far) until the end of the 21st century. This study has taken advantage of the downscaled outputs of the CNRM-CM5 global model from the set of CMIP5 models under the RCP scenarios. The results showed, while under the future climatic projections (near, middle, and far), this parameter was 0. 7, 1. 2, 1. 9 oC for the RCP4. 5 scenario and 0. 7, 1. 7, and 3. 9 oC for the RCP8. 5 scenario, respectively, which probably will experience an increase compared with the baseline period. The highest rate of increase in the maximum extent of temperature of the future climatic projections compared with the baseline climatic period occurred in the Zagros region, and the lowest rate of increase was in the Khazar region.

Extended Abstract Introduction 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.   Materials and methods 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.   Results and Discussion 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).   Conclusion 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.

Evapotranspiration after rainfall is the main component of the hydrological cycle that quantifies the amount of water lost. Since climate change directly affects the temperature and rainfall parameters, and the evapotranspiration rate is directly related to the air temperature, it is expected to have significant changes in the future. Therefore, in this research, the possible impacts of climate change on evapotranspiration changes under two RCP2. 6 and RCP8. 5 climate scenarios are investigated using statistical downscaling model (SDSM) and CanESM2 atmospheric general circulation model output for the future period 2030-2059. Reference evapotranspiration rate was compared with Hargreaves-Samani and Thornthwaite methods in monthly and annual periods for the base and future periods. The results showed a mean increase of annual maximum and minimum temperatures in both scenarios from 0. 06 to 0. 26 ° C compared to the base period. The highest increase was in May by 2. 61 ° C under the RCP8. 5 emission scenario. Overall, the trend of evapotranspiration has been increasing throughout the years. The evapotranspiration in the Hargreaves-Samani method in the RCP8. 5 scenario had the highest mean change of 0. 08 mm or 2. 79%. Although annual changes were not perceptible, as evapotranspiration in the basin reaches its maximum in July, the changes increased by 0. 45 mm/day in RCP8. 5 scenario. The results of monthly survey can be used in surface and underground water resources management and watershed projects estimating the water needs of plants plus appropriate timing of useful irrigation.

The Climate change can be a major threat to biodiversity and ecosystem integrity. Therefore, prediction of hydrological behavior of watersheds for conservation and reconstruction of ecosystems is necessary. In this research SWAT semi-distribution hydrological model was used to evaluate water flow and water balance by changing climate in Latyan dam near Tehran during 1988-2014. Also, the output of the CMIP5 series model is under two scenarios RCP 2. 6 and RCP8. 5 for the near future using the model, LARS-WG was introduced into the mode. The result of stimulation for 2021-2050 showed that mean temperature increases by 0. 75 C° for RCP 2. 6 optimistic scenario and 1. 45 C° for RCP 8. 5 pessimistic scenario. In addition, rain was reduced by 2 % in RCP 8. 5 and 5 % in RCP 2. 6. The result for water flow showed that high level of water flow decreases by 2. 4 cubic meter per second in May and increases by 1. 49 in April. The water flow in RCP 8. 5 scenario for May and June was greatly reduced which it can negatively affect level of water in dam until starting rain. Average evapotranspiration was increased by 3 mm in optimistic scenario and 8 mm in pessimistic scenario which it negatively affects the accessible water resource. Reduction of rain was predicted for two scenarios.

Buildings and their subsidiary industries account for a significant portion of world energy consumption and greenhouse gas emissions, making it essential to assess the impact of climate change on them. In this study, the impact of the RCP 2.6 and RCP 8.5 scenarios, as the potential scenarios of the Intergovernmental Panel on Climate Change, has been evaluated on energy consumption of a residential building. A detailed computer model was developed based on local climate data for a villa house to assess the changes in energy use under different climatic impacts. The scenarios are RCP 2.6 which represents the most optimistic scenario, assuming strong mitigation efforts, and RCP 8.5 which reflects the worst-case scenario with minimal climate action. The results showed that a 48% decrease in gas consumption and a 35% increase in electricity will be expected in 2100 according to the RCP 8.5 scenario. Meanwhile, in the RCP 2.6 scenario, gas consumption decreases by 28%, and electricity consumption will increase by only 15%. Iran is struggling with a severe energy deficit crisis exacerbated during the summer due to the government's failure to supply electricity. Providing a realistic estimation of climatic impacts on the energy consumption type and magnitude will help to develop better future strategies to solve this across the country.

The aim of the current study is spatiotemporal analysis of changes in minimum, maximum and mean air temperature over Iran based on Representative Concentration Pathway (RCP) of the fifth report of IPCC. To do this, three datasets have been used: 1) Daily maximum, minimum and mean air temperature data for 42 synoptic stations during 1/1/1979 to 31/12/2005, 2) National Center for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR) data for 26 variables, and 3) Representative Concentration Pathway (RCP) scenarios data during 1/1/2006 to 31/12/2100. The model was calibrated using predictors from the NCEP/NCAR reanalysis datasets over the base period 1979– 2005. The selected downscaling model structure has been done by a recommended method by Mahmood and Babel (2013) which is a combination of the correlation matrix, partial correlation, and P-value was used. Due to the bias, downscaled temperature data forced by CanESM2 model was corrected using a bias correction technique for each station. Finally, changes in the characteristics of temperature were estimated for the future period (2006– 2100) based on the future scenarios RCP2. 6, RCP4. 5 and RCP8 compared to the base period (1979– 2005). The projected changes were assessed with the nonparametric modified Mann-Kendal trend test and Sen Slope estimator at 95% confidence level. The results showed great reliability of SDSM downscaled model structure and screening of variables. The findings illustrated that minimum, maximum and mean air temperature were projected to increase. The projected increases was larger in semi western part of country. Minimum air temperature projected to increase 0. 35, 0. 6 and over 1 ℃ based on the RCP2. 6, RCP4. 5, and RCP8. 5 scenarios, respectively. Maximum air temperature increases rapidly after 2070 decade and projected to increase more than 1℃ rather than base period (1979-2005). The projected changes showed that warming of Iran’ s air temperature more over 0. 5 ℃ after 2040 and reached to 1. 5 ℃ by the end of twenty first century.

The climate of the land has always been changing over time but the current trend in climate change has become important due to the role of humans which has been unprecedented over the past years. In this study, The LARS WG and SDSM models are used to evaluate the climate change at Bojnourd station for downscaling climate and both models evaluate A and B scenarios but also used RCP new scenario in SDSM. The result of the status of the station showed temperature mean station is 13. 52 c but after 2000, the temperature of the station is higher than its long-term average. The results of the LARS WG model show that precipitation will increase at the station in year 2050. In scenario B1, the amount of precipitation increase almost 16 mm more than base precipitation to 2050 and all season’ s precipitation are increasing in this scenario. In scenario A2, the increase in this scenario reaches almost 256mm. In total, the SDSM model downloading to increase precipitation and this increase showed A1 and B2 scenarios more than RCP scenarios, therefore In the scenario A2 value is 289mm, the scenario B2 is 294 mm, the scenario RCP 2. 6 is 264 mm, the scenario 4. 5 RCP this is 273 mm and in the RCP scenario of 264 mm. In the case of temperature in the LARS WG model, the minimum temperature increases in both cases. The maximum winter temperature rise is 0. 8 c in the A2 scenario. In both scenarios, the maximum temperature in March, April and May is the highest increase compared to other months. The SDSM model shows that the maximum and minimum annual temperatures of this model are lower temperatures than the base period. But the monthly increase in the months of March, April and May is the minimum and maximum increase, which indicates the matching of the results of both models.

The present research was conducted to simulate the impact of climate change on irrigated barley in Lorestan and Hamadan provinces. For this purpose, nine regions including Aligudarz, Borujerd, Khorramabad, Kuhdasht, Pol-e Dokhtar, Hamedan, Malayer, Nahavand, and Kabudarahang were selected in the two provinces. The APSIM-barley model was employed to simulate the growth and development of irrigated barley. Firstly, the APSIM-barley model was evaluated using two independent field experiments. The first experiment was conducted in Khorramabad to calibrate the crop model; while the second experiment was done in Hamedan to validate the crop model. The future climate was projected using the AgMIP methodology under two scenarios (RCP4.5 and RCP8.5) for the period 2040-2070. The results of the model validation showed that the crop model was able to simulate barley yield and biomass with nRMSE of 16.4% and 13.3%, respectively. Additionally, the results indicated that on average across the study locations, barley grain yield would decrease by 3.8% and 5.7% under RCP4.5 and RCP8.5, respectively. However, in Pol-e Dokhtar, barley grain yield is projected to increase by 1.3% and 4.8% under RCP4.5 and RCP8.5, respectively. Based on these findings, adaptation strategies should be considered in the future to prevent the reduction of irrigated barley yield in the studied provinces.