In the study of climate changes, Prediction of the future climatic parameters is performed by general circulation models (GCMs) and emissions scenarios of greenhouse gases. However, Global Circulation Models have very course spatial resolutions. For this reason, downscaling methods are needed to bridge the gap between the large scale climate scenarios and the fine scale where local stations exist. Downscaling methods are divided into two categories: 1) statistical models and 2) Dynamic models. Among these methods, statistical methods are much more popular which is due to low expenses and less time consuming procedures. Lars-WG and SDSM models are among the most concise methods of statistical tools for downscaling. Herein this research these two models were used in simulating precipitation and temperature changes in Urmia lake basin located in the north west of Iran. Four synoptic stations including Saqez, Tabriz Khoy and Urmia were considered. These four stations had a good and long data especially in base period (1961-1990). In order to assess the models, MSE, RMSE & MAE indexes along with regression and bias were used. Results show that both models were good in simulating temperature but SDSM was better in simulating precipitation according to statistical performance measures and has less uncertainty. But it has more complex and time consuming procedures. While Lars-WG is simpler and faster comparing with SDSM. In general, none of the models has absolute superior in 

This study presents the predicted amount of precipitation, temperature and the climate simulation periods 2099-2070, 2049-2020 and 2008-1979 observation period under A2 and B2 SRES scenarios using the statistical downscaling model (SDSM) in Tehran, Zanjan, Qazvin and Rasht stations on the southern side and Ramsar, Babol and Gorgan in Northern side of the Alborz. Also, future climate was determined using the Domarten method. The main objective was to compare the climate change on two fronts in the north and south of the Alborz. The performance of model to predict the climatic parameters was evaluated based on the coefficient of determination (R² ) and root mean squared estimation error (RMSE). The results of predicting the climate parameters indicate that the model simulated these parameters adequately. The results of the precipitation in all stations in period 2020- 2049 compared with the period 1979-2008 show an increasing trend in all stations and the period 2070-2099 compared to observation periods show an increasing trend in precipitation; while it has a decreasing trend compared to the periods 2020-2049. In 2070-2099 and 2020–2049 periods, the average, minimum and maximum temperature was increased relative to the observation period 1979-2008. The results of the climate determination by the Domarten method show that the climate in the Babolsar, Qazvin, Ramsar and Rasht stations will be change comparing with the observed climate in 1979-2008 in the future periods. In the Gorgan station at period 2070-2099 under the A2 scenario, the climate will change from semi-arid to the arid climate. In the Zanjan station at period 2020-2049 under the A2 scenario, the climate will change from semi-arid to Mediterranean climate and at period 2070-2099 climate from Mediterranean to semi-arid climate. This data can be simulated with high accuracy to better foresight the climatic conditions in future periods to help the future macro-management in providing better productivity of resources, particularly the water resources management.

Climate change impacts are very dependent on regional geographic features and local climate variability. Impact assessment studies on climate change should therefore be performed at local or at most at the regional level for the evaluation of possible consequences. However, climate scenarios are produced by Global Circulation Models with spatial resolutions of several hundreds of kilometers. For this reason, downscaling methods are needed to bridge the gap between the large scale climate scenarios and the fine scale where local impacts happen. A stochastic weather generator, however, can serve as a computationally inexpensive tool to produce multiple-year climate change scenarios at the daily time scale which incorporate changes in both mean climate and in climate variability. In paper, LARS-WG model were used to downscale GCM outputs and then assessment of the performance were done for generated daily data of precipitation, minimum and maximum temperature and sunshine hours. Study area is Ghare-su basin in Gorgan and the station is called Gorgan synoptic station. The first step is running the model for the 1970-1999 period. Then mean of observation and synthetic data were compared. T-test was used in the 95% significance level, and the difference between observation and synthetic data was not significant. Finally monthly mean of observation and synthetic data were compared using Statistical parameters such as NA, RMSE & MAE. As a final result, it is found that performance of model is appropriate for generating daily above listed data in Ghare-su basin. So, it is possible to predict the climatic parameters from GCM output using LARS-WG model. Also minimum and maximum temperatures have highest and sunshine hours have lowest correlation.

Global warming caused by emissions of carbon gases into the atmosphere is a serious threat to sustainable development in developing countries Such as Iran. Carbon sequestration in terrestrial ecosystem is a sustainable approach, with no environmental risks. This research was conducted to evaluate watershed management mechanical operations including water harvesting, terracing, sediment trapping dams, banquette and furrow in different regions of the country (nine provinces) in atmospheric carbon sequestration and to offer optimal options for these regions. For this purpose, field operations were done for soil, biomass and litter sampling, using systematic randomized method in representative sites and control sites. According to research results, regions in the hillsides of the Zagros mountains including Lorestan, Fars, Kermanshah and Kurdestan showed the maximum carbon sequestration potential in about 54 to 112 ton carbon per hectare. In Hirkani regions in Mazandaran province, water harvesting system operation sequestered about 18 ton carbons per hectare. Watershed management operation in center and west part of country with Iranotorani cover type cannot affect in soil organic carbon stock and rangeland biomass, significantly. In study areas, indigenous terracing and water harvesting systems have higher efficiency in carbon sequestration, respectively and different sediment trapping dams did not show significant effect in this case.

Global warming caused by emissions of carbon gases into the atmosphere is a serious threat to sustainable development in developing countries Such as Iran. Carbon sequestration in terrestrial ecosystem is a sustainable approach, with no environmental risks. This research was conducted to assess its impacts on relieving climate change effects. Soils have a good capability in storing carbon. Herein this research, carbon sequestration was assessed in Sorkhehhesar Jajrud. Cupresus arizonica, pinus eldarica and rangeland plants were cut dried and sent to laboratory. Meanwhile soil samples were taken and sent to lab too. Based on random systematic statistical method, 6- 10 sampling plots of 10 x 10 m. size were allocated for each species at planted and unplanted (control) parts, separately. Soil sampling was made in center of each plot at 0-20cm depth after removing the organic layer of the soil surface to measure carbon sequestration, N, P, K, pH, moisture, bulk density, silt, sand, clay and gravel amount. T-test was used and also Levenn test was used for two independent samples. In order to assess the normality, K-S test was used.it is a best fit test. Also in the end, LSD test was used to assess different parts of plants. It was concluded that pinus eldarica, cupressus arizonica and rangeland plants were significantly traps carbon in the soil. This is normally named as carbon sequestration. pinus eldarica and cupressus arizonica are different significantly in carbon sequestration with outside (no plant)but as for the comparison of them with range land plant there is no significant difference though the rate is much more in the first and second species.

In recent decades the rapid growth of industrial activities has caused imbalance in climate of the earth which is so called named climate change. This phenomenon directly affects meteorological parameters such as temperature and precipitation. The objective of this research is investigation of the impacts of climate change on precipitation and maximum and minimum temperatures in Karkheh River Basin during the period of 2010-2039. The representative climate model of the region using AOGCM and observed data period of 1971-2000 was selected. Comparison of performance indicators of few AOGCM models for rainfall and temperature simulation showed that generally HadCM3 model is suitable for the region using synoptic and climatological weather stations of the region. Statistical and   regression downscaling was carried out for the selected AOGCM. Statistical and regression downscaling was performed using statistically dynamic model of SDSM. The final results for near future, 2010-2039, shows 2% reduction in rainfall for both synoptic stations of Kermanshah and Khoramabad in the north of the basin and 4% reduction in Hamidieh climatological weather station in the south of the basin.  The increase in maximum temperature for above stations are estimated as 119 and 3% and increase in minimum temperature are 24,4 and 1% respectively. Using HadCM3 and SDSM for near future, 2010-2039, simulation shows that as we move from north to the south of the basin (colder climate to warmer climate) the effects of climate change on maximum and minimum temperature are less pronounced while the trend for rainfall, although small, is opposite and is 2% for the north and 4% for the south.

Climate change in addition to the direct impact on climate parameter, indirectly on the economy, society, agriculture and ...was impacted and will cause consequences such as floods, drought, migration, poverty and associated. Thus it is necessary to determine the mechanisms and more prepared to reduce the negative consequences of climate change phenomenon is essential to seems to be.Because of the importance of the climate change phenomenon on water resources in rivers, scrutiny of river behavior and specially river dischargein the future periods affected by climate change is essential to water resource management and finding solutions for adaptation and mitigation to climate change.Goal of this reaserch is investigation of climate change impact on watershed runoff of Tuyserkan river and appropriate solutions to reduce the impact of these changes.For this purpose, hydrometric and meteorological data and so soil characteristics and topography of the area, were collected.Using the soil moisture accounting algorithm was implemented to continuous rainfall-runoff model for sub basin of Tuyserkan plain upstream.Then using 15 general circulation model and LARS-WG model and using the beta distribution function were simulated rainfall under A1B and B1 scenarios.Rainfall-runoff model was run using futurerainfall amounts and volume of runoff in each of sub basinwas presented in the future period of 2011-2030.Finally, with 10% increase assuming ofrainfallbycloud seedingtechniquewas estimated toriverrunoff.The results showed thatthedecrease inrainfalldue toclimate changewillreducerunoff volumeof eachsub basin. Asof40.5millioncubic meters in base period will be to34.9 and 35.8 million cubic meters under scenarios A1B and B1. The results showed that the 10% increasein precipitationfromcloudsseeding, about 2millioncubic metersof runoffvolumedeclineddue to climate change will be compensated. The results showed that the 10% increase in precipitation from cloud seeding, about 2 million cubic meters of runoff volume declined due to climate change will be compensated.

            Basins are an open meanwhile a complex system. Most of analysis and behaviour predictions are depend on modeling with different mathematical and statistical methods. Limitations of water resources along with uneven distribution of precipitations have caused, Iran to be very fragile to climate change. As it is not possible to gauge all basins, modeling is necessary. So a model should be selected which needs minimum input data and meanwhile can present a reasonable output. The most important output can be surface ruoff volumes. Among references,IHACRES was selected. Different assessing indexes were used such as NSE, R², RMSE,MAE etc. these indexes show that based on reference period, IHACRES can simulate surface runoff relevantly and also it gives a better estimate in  monthly scale compared to others such as annual one. Runoff were predicted for 2011-2030. It is concluded that surface runoff may change up – 18.65%.

The study is studied forecasts of precipitation and temperature values using general circulation models of the atmosphere in the period 2021-2050. Climate data was taken such as rainfall and average temperature of the Meteorological Organization. To prepare for future climate scenarios was used from general circulation model HadCM3 outputs under the A2 emissions scenario. Due to the low resolution general circulation models of small-scale model of SDSM4.2 use and climate changes in precipitation and temperature parameters were simulated mean for future periods. In this study, the model was calibrated SDSM, the 26 large-scale climatic parameters (NCEP) an average of 3 parameters most correlated with mean temperature and 6 parameters are most correlated with average rainfall Seymare basin. The results showed that the predicted climatic parameters for the simulation of climate parameters with high accuracy, but the average temperature of rainfall is less accurate. This is due to normal lack and unconditional of rainfall data. The results indicate that the average temperature of the area in the period 2050-2021 compared to the observation period (2008-1979) has been facing increasing 1.7 ° C and average rainfall areas showed a decrease of 47%.

Excessive use of fossil fuels, the increasing world population and the ever-increasing of industrial activities accordingly to provide welfare and the needs of humans, thereby has been increased the concentration of greenhouse gases, particularly carbon dioxide in recent decades. This increase in greenhouse gases cause a phenomenon called climate change. The aim of this study was to evaluate the effect of climate change on surface runoff is Caesar's basin (West Iran). The study uses data from a large-scale model HADCM3 under scenario A2, and for small-scale precipitation and average temperature of the climate parameter exponential model was used SDSM. Simulated runoff area for the next period (2021-2050) was IHACRES conceptual model. The results showed an increase in temperature for all stations. The average temperature of the area for the future compared to the observation period increased by 1.7 ° C faces. Simulated rainfall for the next period shows a decrease in precipitation by 24% over the observation period. According to the simulation model IHACRES, the three hydrometric stations used in this study, all stations showed a reduced rate for the area in the future. This reduces discharge for rahimabad, biaton and Cham zaman stations respectively in order to level 29, 19 and 24 percent in the future period was observed compared to base period.

The weather forecast data for future planning is very important in the fields of natural and human. Including could be the prediction of droughts and floods, and so on, in which case systematic planning, reduced probable damages.  In this study, the effects of climate change on drought conditions North Branch of Zab River catchment located in the South West of Western Azerbaijan province, as the most important river plains of Piranshahr, during the period 2065-2046 using the indicators of drought (DI), SIAP and the Standardized Precipitation Index (SPI) has been paid. Initially daily data output of general circulation models of the atmosphere HADCM3 under the scenario A1B, A2 and B1, by statistical model LARS-WG Version 5, small scale and the ability of LARS-WG in the simulation of past climate (2010-1992) studied for the station simulated. So it, using the precipitation data of drought situation to help mentioned indicators is discussed in annual terms, that the results are conform these indicators proves to identify periods of drought. Considering to periods of drought that occurred in the observation data and results for the period is anticipated, we will see station in Piranshahr, increase the severity and duration of drought in the study area in the coming years.

Heavy rainfall is one of the most important climatic events, and if the correct planning is not done, it will have destructive environmental and economic impacts and will be removed without exploitation. This study is trying to forecast changes of the future heavy rainfall  in southern coasts of the Caspian Sea with regard to global climate change in the period of 2011-2030. For this purpose, changes in the pattern of 10, 20 and 25 mm and more rainfall were analyzed based on rainfall data of six synoptic stations (Anzali, Astara, Babolsar, Gorgan, Noshahr, Ramsar and Rasht). Daily rainfall data was simulated in the period 1961-2009, after verification of their accuracy and Correctness, using the Lars-wg model. After comparing the simulated values with the current period data, the daily rainfall values were predicted for the upcoming period (2011-2030). The eleven indexes of the R-Climdex global model were calculated for the current period and the upcoming period. Among these, three heavy rainfall indicators (R10mm, R20mm, R25mm) were analyzed. The results show that at most stations in the area in the upcoming period, the total number of days with rainfall of 10, 20 and 25mm will be added (other than Nowshahr station and Ramsar station). Overall, among all the stations studied, Anzali station will experience the largest number of days with heavy rainfall of 10 mm and heavy rainfall of 20 and 25 millimeters.