فهرست مطالب اصغر کامیار

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.

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.

Bias correction usually used for the outputs of the climatic model before use as an input of environmental models in the climate change effects studies. In this research, GCM outputs obtained from ESGF dataset with the RcgCM4-4 climate model in the South Asia CORDEX domain with horizontal resolution about 50 km. Precipitation, maximum and minimum temperature data of 41 synoptic stations with the closest distance to model cells in Iran domain obtained from Iran Meteorological Organization. Then the accuracy of the outputs of the cells corresponding compared to the observational data with correlation and normalized standard deviation methods evaluated by Taylor diagram. Then, the model bias with the least error corrected for the precipitation outputs with fitQmapRQUANT method and for the maximum and minimum temperature outputs with the linear scanning bias correction. Results showed that the bias correction methods used for the temperature outputs improved the error of data but for precipitation outputs, it was not effective due to the large difference between observation and model data. The model to estimating the maximum temperature in these regions had less bias than in those at low latitudes. The CCCma model's monthly minimum temperature outputs overestimated this variable, especially in hot seasons, compared to station data in southern Iran. At most stations located at high latitudes, this variable is corrected or underestimated. The bias correction of the model outputs for this variable corrected the biases in the cells corresponding to the observation stations.

  All studies in the field of climate change impact assessment needs climate data with different spatial and temporal scales. The lack of temperature and precipitation data with high spatial resolution is a major limitation to analyzing future climate change. In addition, the output of the models has error that needs to be corrected; otherwise they will make a significant bias for assessing effect of climate change. Therefore, identifying the best regional climate model for downscale the global climate models is essential to better understanding of climate conditions in the local and regional scale. In the last few years, using various regional climate models in order to produce a multi-member set of the downscaled data in the CMIP5 project by World Climate Research Program (WCRP) in action with Coordinated Regional climate Downscaling Experiment (CORDEX) with the aim of producing regional climate change forecasts, was established as an input to researches on the impacts of climate change and ways for adaptation to it. The main objective of this research is accuracy evaluation of different model outputs of the CORDEX project with different domain and resolution in Iran. In the CORDEX project there are two domain that covering Iran. These two domains are North Africa-Middle East (CORDEX-MNA) including latitude of 7° S to 45° N and longitude 27° W to 76° E and South Asia (CORDEX-WAS) that includes latitude 13° S to 44° N and longitude is 27° E to 107° E (Figure 1). To do this research, first daily output of precipitation, maximum and minimum temperatures in the period of 1990-2005 for three regional climate models with a special resolution of 0.22 ° and 0.44 ° that performed by three international meteorology institutes, available at ESGF web site (Table 1). Daily observation data that recorded in 304 synoptic stations in Iran for the three variables were collected from Iran Meteorology Organization and transferred to a matrix with 3044×5844 dimensions. Then, several scripts were written in the MATLAB software for extract the model data in the domain of Iran and compare output model and observational data with two conditions. The first condition is in the output models resolution of 0.44° (spatiotemporal matrix with dimensions of 5844×740), the observation station should have a distance of less than 25 km, and the next condition is in the resolution of 0.22 ° (spatiotemporal matrix with dimensions of 5844×3218) should have a distance of less than 12 km. The difference between observation data and its corresponding estimated cell were investigated with statistical method such as Mean Error (ME), Pearson Correlation Coefficient, Root Mean Square Error (RMSE) and Standard Deviation (SD). Also, we were used Box-Whisker plots and Taylor Diagram to find the best regional climate model.
Result and The precipitation accuracy of regional climate models output presented by different meteorological institutes (Table 1) was evaluated with observational data in two domain, CORDEX-MENA and CORDEX-WAS, in Iran (Fig. 4). The calculation of the outputs mean error of different models showed that none of the models have a suitable estimation of precipitation values in research domain. The HadRM3P model shows the lowest RMSE calculated with comparing to observational data for the maximum temperature across Iran except the central parts. However, for the minimum temperature RegCM4.1 model shows the lowest difference with compare to observation data in most parts of the research domain. For annual precipitation using the Box-Whisker plot, which compares the correlation coefficients between the observed data and the corresponding cells in the northern and southern half of Iran, in general, none of the models have an accurate estimate of precipitation in Iran (Fig. 8a). This plot for different models showed that the outputs of the HadRM3P and RegCM4.1 models, respectively, for maximum and minimum temperatures in most cells, have more than 0.8, correlation coefficient (Fig. 8b and c). The correlation of rainfall data shows that most models in the central and mountainous regions of Iran do not have high correlation coefficient with observational data. Spatial distribution of correlation between maximum temperature model outputs and observational data in Iran shows that the two HadRM3P and RCA4-WAS0.44 models have a strong correlation coefficient, respectively and changes in the correlation coefficient in the HadRM3P model are low in both the northern half and the southern half of Iran. The RegCM4.1 model had the stronger correlation in the northern half in compare to the southern parts of Iran. Also, the mean difference of estimated model output with observation data of this variable in the whole of Iran is less than 1°C and this model is the most appropriate model among the available models for minimum temperature in Iran

Global climate change is relatively depending on human activities which have important impacts on the environment. So the climate change is a very important issue in the recent age. Climate change is the impact on human lives so the climate change increase their temperature and also is very important global problem and monitoring of the climate conditions in early region is a good solution for combating the national housing regarding to climate change large floods and other disasters. There are different climate models and in the CORDEX projects there are regional climate were included in some domains. The main objective of the present work is to evaluate CORDEX-WAS with a spatial resolution of 50 kilometer compared with observational data over Isfahan province. At the end we are evaluating the creation the variation of the minimum and maximum temperature during 2017 -2050 according to model outputs for three models with 2, RCP4.5 and RCP8.5 emissions scenarios.

During the past decades, the human manipulation of the natural environment is increased and influenced the environment destructively. For instance, rising use of fossil fuel and greenhouse gasses emissions accelerated the global climate change. Variation in the amount of precipitation is one of the consequences of this phenomenon that consequently affects the quality of water resources in general, and the quality of surface water resources in particular. Considering the population growth in the country, demands for water resources, for both potable and agricultural purposes, is increasing. Hence, this study attempts to investigate the effect of climate change on the precipitation anomalies and assessment of the relationship between these anomalies and the quality of surface water in the outlet of Gorganrud basin (one of the populous and agricultural basins).