سید جواد ساداتی نژاد

Climate change is one of the most important challenges of this century. The consequences of these changes and how to adapt to them as well as reducing the causes of climate change are important points of this phenomenon. Currently, there is scientific and definite evidence about the warming of the earth and the unprecedented increase in temperature on the surface of the earth and the atmosphere caused by it is a human activity, it is a proof of this. The most important parameters affecting the phenomenon of climate change are precipitation and temperature.

The CanESM2 model was used to predict the climatic parameters of temperature, precipitation and wind speed under the RCP to predict the climate change in Karaj station.

The results showed that the average rainfall in the Karaj station was 96 mm in the historical period which is according to the scenarios RCP2.6, RCP4.5 and RCP 8.5 will decrease in the near future (2060 - 2030) and 62 % in the near future (2060 - 2030) and 81 % in the future (2070 - 2099) than the observed period (1985 - 2017). The results of the simulation of the average temperature according to RCP2.6, RCP4.5 and RCP8.5 scenarios showed that the average temperature in the future period is close to 0.53, 0.17 and 0.19% compared to the observation period (15.81 degrees Celsius) will decrease, while in the future period (2070-2100) under the RCP2.6 scenario, it will decrease by 1.11 percent and according to the RCP4.5 and RCP8.5 scenarios, it will increase by 0.39 and 2.13 percent. The average simulated wind speed showed that the wind speed was 27.89, 25.03 and 24.55% in the period from 2030 to 2060 and 34.16, 25.37 and 23.84% in the period from 207 to 2100 under the RCP scenarios compared to the value observed (2.41 m/s) will increase.

The evaluation results of CanESM2 model in this study can be considered as an acceptable statistical result to investigate the changes of climatic parameters. Observing the pattern of consumption and optimal use of water resources as well as preventing the increase of greenhouse gases can control the trend of increasing temperature and decreasing rainfall.

This study focuses on the Kashan Plain Aquifer (KPA), an emblematic case in Iran, where over-pumping groundwater intensifies salinity. Employing advanced isotopic techniques, specifically analyzing stable water molecule isotopes (δ18O and δ2H) through the Gasbench+DeltaPlusXP method, the current study addresses the intricate nature of saline waters by analyzing geochemistry and isotopes of 15 groundwater samples. It should be noted that the electric conductivity (EC) of the water samples varied from 2210 to 212000, with their mean value being 65499 μS/cm. The study also investigates the impact of salinity on isotopic values, considering ion hydration and salt effects that are crucial for accurate measurements. The results of the study revealed that δ18O values ranged between -8.4 to 6 and -8.38 to 6.48 % before and after salt effect correction, respectively. Moreover, it was found that the average δ18O values varied from -4.58 to -4.49 % before and after salt effect correction. In addition, the disparity between measured and corrected δ18O revealed the impact of MgCl2, and CaCl2 salts on δ18O in all collected samples. However, no difference was found between measured and corrected δ2H. Therefore, while the findings indicate the necessity of salinity correction for δ18O, it appears that salinity correction bears less significance for δ2H.

Today, the importance of modern science and technology, especially the use of environmental isotopes in various studies, including hydrology and geohydrology, is obvious for anyone. Given the quantitative and qualitative crisis status of groundwater resources in Iran, having accurate isotopic data on the quantitative and qualitative status of water resources can lead to good planning and, consequently, proper management of water resources. Due to the lack of sufficient studies on the environmental isotopes in Iran, which, of course, is due to the lack of technologies, high costs of sample transfer to overseas and sanctions, while reviewing the sampling of Groundwater resources, sample preparation methods for stable isotopes of 2H, 18O, 34S and 13C, and the standards for each isotope; related devices such as Gasbench+ DeltaPlusXP, Elemental Analyzer-Isotope Ratio Mass Spectrometer (EA-IRMS), and Total Inorganic Carbon-Total Organic Carbon (TIC-TOC), as well as measurement methods are presented.

Estimating the amount of evaporation from water resources is one of the important and key factors in calculating the water balance and managing water resources in each region. In order to calculate the average evaporation from water resources in Kashan plain and to check the amount of enrichment, the information of stable isotopes of water molecules was used. In this study, 42 water samples were collected from groundwater, Playa Lake and Serajeh salt pan in order to analyze the hydrogeochemical and isotopic characteristics. The amount of 18O isotopic enrichment factor was determined based on and the amount of deuterium based on . According to the results, the overall enrichment value due to evaporation, under the specified conditions and an average annual temperature of 30°C, was determined to be -16.4‰ and -82.25‰ for oxygen-18 and deuterium, respectively. Additionally, based on the Rayleigh distillation, the amount of water losses due to evaporation was calculated based on the differences between the initial sample and the 18O value of the Playa using the simplified Rayleigh equation. Since the remaining water fraction was found to be 0.40, hence the water loss rate in the northeastern part of the aquifer was estimated to be 60 percent.

The water resources of the earth have currently been reduced due to various factors such as rising population, and an increase in human activities, including the growth of urbanization and industries, and increasing agricultural and economic activities. Therefore, water shortage seems to be one of the most important crises that threaten the future life of living creatures. In this regard, arid and semi-arid regions are subject to more risks due to reasons such as climate change, drought, and excessive extraction of groundwater resources for industrial, agricultural, and drinking purposes. On the other hand, in addition to the increase in temperature, climate change will also cause changes in precipitation and evaporation rates, leading to the loss of large amounts of water by decreasing precipitation and increasing evaporation rates, respectively. In such a situation, the groundwater resources are highly pressurized, considering the continuous drop in the water level, the fact that the amount of harvest is always more than that of the recharge, and the irreparable damages that may follow. Therefore, this study sought to investigate the influence of climate change on the groundwater level of the Ravansar-Sanjabi basin and to analyze its results. To this end, first, the groundwater simulation was carried out by Mudflow code. Then, the effect of climate change on groundwater resources was investigated during the future period (2021-2040), taking into account different climate scenarios.

Known as a relatively rectangular plain with north-south extension, the Ravansar-Sanjabi plain is located in the northwest of Kermanshah city (the center of Kermanshah province) between 18'26°46'' to 00'50°46'' eastern longitudes and 00'25°34'' to 34’50’48’’ latitude''. According to the latest nationally published statistics, there are 881 wells in the Ravansar-Sanjabi basin with a discharge of 27 million cubic meters per year (Figure (3). Moreover, the main sources of the basin’s recharge are precipitation and the amount of water returned from exploitation wells, with approximately 17% of the precipitation in the area being considered as recharge.

As for the groundwater modeling, there was an acceptable correlation between the simulation and observation data under both stable and unstable states, indicating the appropriate performance of the MODFLOW simulation model in the Ravansar-Sanjabi basin. Moreover, the error-index value was found to be 0.95 for groundwater modeling with RMSE, suggesting an appropriate accuracy of the model in an unstable state. In addition, the values of the explanation coefficient and MAE were reported as 0.98 m and 0.87 m, respectively, falling in a suitable error range. On the other hand, the calibrated hydraulic conductivity values showed that the hydraulic conductivity values varied from 52 and 30 meters per day in the north of the basin. However, the greatest hydraulic conductivity values were found in the southeastern part of the basin, ranging from 16.5 to 29 meters per day. Also, the average values of hydraulic conductivity belonged to the central area of the basin, ranging from 8 to 12 meters per day. According to the results obtained for the selection of an appropriate climate model, it was found that out of 20 existing models, the HadGEM2-ES, CanESM2, and CSIRO-MK3-6-0 had the greatest values (15.5, 15.5, and 17.25, respectively), being selected as the best models in this research. Moreover, the results of climate change indicated that the precipitation rate did not change much throughout the study period (2021-2040). On the other hand, while changes in the precipitation rate were found to be small under the RCP2.5 scenarios, they were significant under the RCP8.5 scenarios, especially the reduction of precipitation in some months. As regards the temperature changes throughout the study period (2021-2040) under all three climate scenarios, the results indicated a decrease in temperature rates, with the lowest and highest decrease occurring under the RCP2.6 and RCP8.5 scenarios, respectively. Accordingly, the temperature is predicted to decrease by approximately 0.5 degrees Celsius in the worst case. It was also found that the groundwater level varied from 20 cm to 60 cm in all months, with the lowest balance reduction having occurred in January, and the highest balance reduction having occurred in April, May, and June. Moreover, according to the results of changes in temperature and precipitation under the three climate scenarios, it could be argued that the greatest and slightest decrease in the groundwater level will occur under the RCP 85 and RCP 26 scenarios, respectively.

Groundwater is the main component of sustainable development in Iran. Due to population growth, over-exploitation, reduced precipitation, and inappropriate cultivation practices, water storage has significantly declined. Therefore, it is imperative to model groundwater and predict the future state of the aquifer for effective management. In this study, we have modeled the qualitative and quantitative changes of the Kashan aquifer. Based on the hydrological and hydrogeological conditions of the Kashan plain aquifer, we developed a groundwater quantity and quality model (2009-2015) under stable and unstable conditions using the MODFLOW and SEAWAT models in the GMS software. The models were validated through statistical evaluation, demonstrating their accuracy in modeling. Once the models were validated, we assessed the status and quality of the aquifer for the next period (2016-2023) by considering various practical scenarios. Applying the current trend scenarios revealed a projected decrease in aquifer volume to 1.556 Mm3 and an average increase in salt density of quality wells to 160.33 ppm in the next period. Conversely, when simulating the scenario of shutting off wells for a month, the aquifer volume was projected to increase to 0.0147 Mm3, and the salt density of quality wells would decrease to an average of 42.27 ppm during that one-month period. These results highlight the model's capability to accurately recognize and predict observed and calculated outcomes. The expansion of saline water in the northeastern part of the aquifer has resulted in a decline in both quantity and quality in that region. Finally, implementing multiple management and scientific scenarios concurrently is crucial to prevent further deterioration of the quantitative and qualitative status of water resources in this region.

As one of the greatest natural disasters, meteorological drought has traditionally affected human life. Considering the fact that the consequences of drought and its socio-economic damages increase with increasing population, it is necessary to have an effective monitoring system to analyze the drought process and reduce its adverse effects, thereby taking effective measures to manage the crisis.

The study area and data: This study was conducted in Isfahan province, located at latitudes of 30° 43' to 34° 27'N and longitudes of 49° 38' to 55° 32' E with an area of ​​107145 km2 (equivalent to 3.6 percent of the total area of ​​Iran), whose annual precipitation rate is 130 mm which is less than half the country's average rainfall rate and one sixth of the average global rate. This study used 30-year precipitation data collected from 10 meteorological stations and neighboring areas with appropriate statistical quality to investigate the drought indices of the Isfahan province.

Trend analysis of precipitation and drought data plays a significant role in the future development and management of water resources. Therefore, this study sought to analyze the trends of meteorological droughts and monthly precipitation rate for the period of 1990-2020 extracted from 10 synoptic stations in Isfahan province, including Ardestan, East Isfahan, Golpaygan, Isfahan, KabootarAbad, Kashan, Khorobianbanak, Naein, Natanz, Shahreza. Moreover, to investigate the variability of the Z-Score Index (ZSI) for different time intervals, the ZSI values of all these stations were calculated at multiple scales of 1, 3, 6, 9, 12, 24 and 48 monthly scales, whose trends were analyzed for all stations by applying the non-parametric Mann–Kendall at 5% significance level. The magnitudes of the trends were also computed and tested using the Sen’s slope estimator method.

It should be noted that the purpose of the Mann-Kendall test is to statistically assess the existence of monotonic upward or downward trend of the intended variable over time. A monotonic upward (downward) trend means that while the variable consistently increases (decreases) over time, the trend may be eighter linear or non-linear.To identify a linear trend, the slope is usually estimated by computing the least squares estimates using linear regression. However, this is only valid when there is no serial correlation. Moreover, the least squares method is very sensitive to outliers. Therefore, as a robust method against those two least square assumptions, non-parametric Sen’s slope estimator was used to analyze ZSI Indices and detect the possible trend. Further trend analysis was also applied to detect possible single change-point using Pettitt’s test, which helped investigate significant abrupt changes in the level of time series at 5% significance level for all stations and different ZSI monthly scales. All statistical analyses were carried out via R statistical software and the facilities of its packages.

The results of applying Mann–Kendall and Sen’s slope tests based on ZSI Index for 9, 12, 18, 24, and 48-month scales indicated that the drought trend was significantly increasing for all stations out of Esfahan and Shahreza stations. In Isfahan station, the drought trend was significantly decreasing in the 48-month scale, and in Shahreza station, the drought trend was significantly increasing in all time periods. Moreover, the results of Mann–Kendall and Sen’s slope tests for a one-month period revealed a is significantly increasing trend in terms of ZSI Index in Naein and KabootarAbad stations only. Furthermore, applying Mann–Kendall test on monthly precipitation rates of all stations showed an insignificant downward trend.Finally, the results of the Pettitt’s change point test for 9, 12, 18, 24, and 48-month scales indicated the existence of a significant change point in terms of the ZSI Index. However, no change point was observed for all stations' monthly precipitation rates throughout the same periods.In short, considering the ZSI drought index, it could be said about 58% of all stations showed significant downward trend according to the results of the Mann-Kendall test, 56% of all stations showed a significant slope trend according to the Sen's slope test, and 81% of all stations showed a significant change point according to the results of the Pettitt's test. In general, it could be argued that drought trends are better analyzed and displayed in terms of the ZSI index for over six-month periods, and that under six-month scale are unable to produce significant results.Considering what discussed above, it should be reiterated that Isfahan province is facing a water crisis, requiring very urgent water demand management.

Meteorological drought is a complex natural disaster that occurs everywhere in the world. Predicting the occurrence and severity of drought can be effective in managing water crises and their impacts. The purpose of the current study is to select the most appropriate model from statistical models and artificial intelligence (artificial neural networks) to predict drought in Isfahan synoptic station during the span period of 1990-1920 using the Z-Score index (ZSI). In this study, the capability and efficiency of the SARIMA stochastic linear model and three advanced learning machine models of the Feedforward Neural Networks (FNNs), Multi-layer Perceptron (MLP), and Extreme Learning Machines (ELM) were evaluated based on Root Mean Squared Error (RMSE), Mean Absolute Square Error (MASE) and Mean Absolute Error (MAE). The results showed that among the many models made, the Feedforward Neural Networks (FNNs) model with RMSE of 0.33, MASE of 0.02, and MAE of 0.22 were selected as the best model. Using the superior model, precipitation for the period of 2025-2021 of Isfahan synoptic station was predicted, then based on the ZSI drought index, drought intensity of forecast precipitation data in 3, 6, 9, 12-month time scales, 18, and 24 months was calculated. The results of drought severity predicting showed that severe drought in 3 and 6 month time scales in 2021 and 2023 and in 9 and 18 month time scales in 2024, moderate drought in all time scales in 2024, and weak droughts occurred at the 3, 6, and 24-month time scales in 2024 and 2025, respectively. Overall, the results showed that the use of feed neural network model was more efficient. Since predicting drought at all time scales can reveals drought more accurately, this predicting in turn to facilitate the development of water resources management strategies for management of drought is effective.

This study was aimed to investigate Precipitation Extremes variability in Bakhtegan Basin. Climate data corresponding to Bakhtegan basin was extracted from AgMERRA dataset for the study time period (1980-2010) using R software. Daily precipitation data was also extracted from the meteorological stations data arhive in the basin during the study period. Rx1day, Rx5day, PRCPTOT, CDD, R10mm, R20mm, R95p and R99p indices were selected and calculated to study climate change in the region. RX1day results with the changes trend of -1.186 to 0.217, RX5day, -0.624 to 0.82, R10, -0.179 to 0.025, R20, -0.06 to 0.046 and PRCPTOT, -3.675 to 2.028 showed a decreasing trend in catchment’s most parts and jointly in the catchment’s southern and western parts. Decreasing precipitation, the consecutive dry days (CDD) increased and generally showed an increase throughout the basin (except for a small section in the catchment’s centeral and eastern parts). The most consecutive dry days were observed 259 days in 2008, 245 in 1983 and 264 in 1999 in Shiraz, Doroudzan Dam and Aliabad Kamin stations, respectively. Both R95p and R99p indices illustrated increasing and decreasing trends in different parts of the basin.

In recent decades, environmental problems caused by population growth and energy consumption have raised concerns about global warming. Therefore, this article has calculated the environmental cost with the aim of evaluating the environmental problems caused by the operation of power plants. This study aimed to calculate the environmental costs of generating electricity from different technologies. In this research, 5 thermal power plants in Tehran province were investigated. According to the emission factor of pollutants and also the specific production of each power plant in 1396, the amount of pollutants emitted from Tehran thermal power plants was calculated. Then, according to the emission factor of each polluting gas, heat rate of each power plant and the value of the damaged environment, the environmental cost of electricity generation from thermal power plants in Tehran province was calculated. The results showed that during one year of operation of thermal power plants in Tehran province, about 14 million tons of various pollutants go into the air and CO2 and C are the main pollutants. On average, the total external cost of electricity production from thermal power plants in Tehran province is equal to 8.82 cents per kilowatt hour, which should be included in the final cost of electricity production from these power plants.

Unsteady flow analysis is performed using hydraulic and hydrological routing methods. Hydrological routing methods, while accurate, are much simpler and less expensive than hydraulic routing methods, and for flood routing calculations, only data related to hydrographs (flow changes over time) recorded at upstream and downstream hydrometric stations of the study area are needed. In the present study, the effect of the basic flood on the accuracy of flood routing in the Karun River was investigated using hydrological routing methods including linear Muskingum method, Working Values, Convex, and modified Att-Kin method. In other words, using the Particle Swarm Optimization (PSO) Algorithm and the 4 observational floods data recorded at the Mollasani (upstream) and Ahwaz (downstream) hydrometric stations of the Karun River, for each flood, separately, the linear Muskingum method parameters (X, K, ∆t) Optimized and used to calculate the outflow hydrograph of all floods. The results show that due to the effect of rivers flooding extent on the mentioned parameters if the range of inflow of basic flood changes is closer to the inflow of calculated flood, the accuracy of hydrological routing methods in outflow hydrograph estimation increases.

Estimation of evapotranspiration at a regional level is an important element in efficient management of water resources. Evapotranspiration includes the evaporation from the surface of soil and water and also, the transpiration by the plant that is very important in arid and semi-arid areas. There are many empirical methods for evapotranspiration estimation of reference plants, but these methods donchr('39')t produce the same results for all areas. Lysimeter studies are carried out to determine the most suitable method in each area.

The study area in this research is located in Kashan University, based in the center of Kashan plain with geographical coordinates of ° 45 ′21 ° 51 east longitude and ″ 18 ′00 ° 34 northern latitudes. Then, to measure the evapotranspiration of the reference grass plant, three drained lysimeters of the grass plant and one control lysimeter were made and used in the research site for 6 months within the statistical year of 2012-2013. Moreover, empirical methods of evapotranspiration estimation and evaporation pan were compared based on lysimeter data.

Using lysimeter in the project area, the estimation results for monthly evapotranspiration were reported as being 24.49, 38.39, 51.52, 73.87, 119.77, and 180 mm in January, February, March, April, May, and June, respectively. Moreover, from among the methods investigated, Thornthwaite turned out to be the most accurate ones with R2 = 0.95, R=0.97, NSC= 0.986, RMSE=4.29, and MBE= -1.15, being considered as the most suitable method for evapotranspiration estimation in the study area. After that, modified Jensen Hayes, Blaney –Criddle, Jensen-Hayes, Hargreaves-Samani, evaporation pan, and FA0-Penman-Monteith were considered as other useful methods in that regard though with lower accuracy. Finally, the Penman method with R2 = 0.58 was found to have the least accuracy from among the relevant methods considered.

Kashan is one of Iran’s arid regions which faced a severe shortage of water resources. Therefore, careful planning and efficient management of water resources is required to avoid any serious problem in providing water for different purposes. The evapotranspiration parameter is considered as an important criterion in determining the extent of drought in different areas. Experimental methods for estimating evapotranspiration including the Penman and FAO-Penman-Monteith require many meteorological parameters. Penman method has been introduced for humid climates of England and is not suitable for the arid and semi-arid conditions of Kashan. As it considers a large number of climatic parameters in its calculation of evapotranspiration, this method has acceptable accuracy, but as all the required information is not calculated, it cannot provide a good estimate. In this study, the appropriate evapotranspiration method for the Kashan region was obtained, using the data gathered over six months in the statistical year of 2012-2013. Therefore, to ensure the accuracy of the results obtained, it is recommended that this research continues for at least the next two or three years. On the other hand, due to a possible error in the drainage lysimeter when calculating the actual evapotranspiration, it is recommended that the research get conducted in the region via accurate weight lysimeters so that it could identify the most appropriate method of estimating evapotranspiration in Kashan more accurately.

In this study the recharge and discharge of Isfahan-borkhar aquifer was investigated. This leads to long-term management of the aquifer and will make appropriate decisions by planners. The results of this study showed that the water table was constantly decreasing over the selected statistical period. The water table level was reduced by 0.46m per year, which reflects the fact that the aquifer is in critical conditions. In the present study, the recharge rate was determined by three factors including leakage from the river, rainfall infiltration and agricultural wastewater by using MODFLOW and then the correlation coefficient above 0.97% indicated high accuracy of the simulation. According to the results, it was found that recharge by agricultural wastewater is more than recharge by rainfall (about 32% of total irrigation water), which is due to the type of irrigation in the area (check-basin irrigation) and after that the influence of rainfall (about 10% of the total rainfall), which is a low contribution to this area due to high evaporation rates in the region. Thus, it can be concluded that the most important source of aquifer recharge is agricultural wastewater, which is necessary to be accurately calculated according to the type of product, irrigation, soil characteristics and climatic conditions of the study area in hydrological modeling studies. In case study of Isfahan-Borkhar, there is no possibility of exploitation of the aquifer due to the continuous decrease of the water table of groundwater that is clearly evident in the aquifer hydrograph, as well as the negative balance of groundwater resources.

Radioisotopes, as a new achievement in the environmental sciences, have found significant development in water resources management, especially in dating, aquifer recharge management, and the role of contaminants in water resources pollution. Due to the quantitative and qualitative critical condition of groundwater resources in Kashan plain, having accurate isotopic data from water resources can be effective in proper management of water resources in this region. In this paper, while present the groundwater sampling, preparation and analysis methods for measuring 3H and 14C, we have investigated the age of groundwater resources in Kashan plain. For this aim, 11 groundwater samples for tritium by enrichment method and 3 samples for carbon-14 were analyzed. The results showed that the amount of tritium in the groundwater resources of Kashan plain is less than 0.08 TU which indicates that the water resources are old. Also, carbon-14 results showed that the age of groundwater resources in Kashan plain varies between 10,000 and 21,000 years. The results showed that by moving toward the northeast of the aquifer (aquifer’s outlet), the age of the water resources decreased, which indicating that the paleo deep-waters were mixed with the freshwater waters. In general, by mowing toward the southwest and west of the aquifer to northeast of the aquifer, groundwater age decreases.

   Drought, as a natural disaster, has a major impact on agriculture and ecosystem of the affected region. Droughts occur mainly in areas like Iran being located in the world dry belt, with below normal levels of rainfall.  There is a need to study and predict the drought situation because, according to statistics, Iran is among the most water-stressed countries, with serious problems in occurring floods, supplying drinking water and generation of electricity, so assessing the drought situation in order to reduce damage, comprehensive drought plans are essential for the country and the studied province.In this study drought situation in Isfahan province, has been evaluated using a relatively long (> 27 years) monthly precipitation data, with simultaneous considering of six drought indies including MCZI, CZI, ZIS, SPI, DI and PNPI.  Study area and data:   Isfahan province has geographical coordinates of 30 degrees 43 minutes to 34 degrees and 27 minutes north latitude and 49 degrees and 38 minutes to 55 degrees 32 minutes east length and area of ​​107145 square kilometers (equivalent to 3.6 percent of the total area of ​​Iran). The annual rainfall in the study area is 130 mm which is less than half the country's average rainfall and one sixth of the global average.   In this study, in order to study the drought indices of Isfahan province, 27 year precipitation data of 12 stations in the province and neighboring areas were used with appropriate statistical quality. Case Study Indicators: In this study, six drought indexes based on rainfall were selected to evaluate drought indices of Isfahan province. The basis of drought indicators is often based on the estimation of precipitation deviation from the long-term average over a given period. General features and formulas used to calculate each of the drought indicators are: , , , , and each of the indicators has different classes of drought. Evaluating the Efficiency of Drought Indicators:  The meteorological drought is based on the assumption that the minimum rainfall during the long term of the weather represents a very severe or severe meteorological drought that occurred in the studied area. In order to investigate this hypothesis, rainfall at each station was determined using drought indices and the indicators that were most consistent with the climate conditions were identified.Finally, using inverse distance method in ArcGIS tools, the most accurate index maps were developed.Findings and In the first stage of this research, in order to better evaluate the spatial variations of rainfall in the selected stations, in addition to the quantity and quality of data, latitude and longitude, and altitude from the sea level, the 27-year time base (from 1990-2017) as the common statistical basis for the study of time variation Precipitation was taken into consideration. Then, the accuracy and homogeneity of the data and the incomplete statistics of precipitation of the stations were reconstructed using correlation method and normal ratio method.In the second stage, using the moving average method, dry and wet periods were measured by long-term rainfall data with continuity periods and drought severity using different drought indices. Then, to determine the hypothesis, the minimum rainfall was determined at each station and then evaluated using drought indices. Using inverse interpolation method and using the GIS and based on available spatial distribution data, an interpolation map was prepared and using the superior climatic index (CZI, DI, SPI and PNPI) during the 27 year statistical period (1990- 2017), drought zoning maps were prepared monthly, quarterly, and five-monthly and annual.Discussion and The results showed that the ability of the SPI, DI, PNPI, ZSI, CZI and MCZI indices is based on the relationships defined in the climatic drought conditions. Drought indicators at different stations have different results that can be seen even at nearby stations. The reason for this is the high rainfall variation in the study area.Among the indices, the DI ranked first, the second highest SPI, the third highest CZI, and the PNPI index, the ZSI index, and the MCZI index in the next ranking. Therefore, in order to zoning the drought, the first three indicators are used.Although the results of the hypothesis test showed that the SPI index and Decile precipitation (DI) index were consistent with the minimum rainfall year, but showed a severe and severe drought occurrence in all stations, and, in terms of other indicators, had more performance. Display Severe drought, but the range of monthly and annual Deciles of Index (DI) is slightly higher than other indicators in the charts. Especially in the graphs shown by the decimal index (DI), it seems a small increase in the rate of drought and tropical manifestations. It can be said that according to this study, precipitation index fluctuations (DI), although according to other indicators, are more marked in monthly and annual rainfall graphs.Based on the calculations, six climatic indicators at annual time scale showed that SPI, ZSI and CZI indices are consistent with drought persistence and drought severity. The results of selected criteria show that in the years 1994 to 1995, 2001 to 2005 and 2008 severe drought occurred in most parts of the province.From the station's point of view, the highest drought frequency in the studied area for DI, SPI, ZSI and CZI indicators from Natanz and Kebootar Abad stations and the longest drought resistance in different time scales in the study area; DI: Kabottarabad station from 2007 to 2009 and Naine station from 1993 to 1995 on a seasonal scale is the longest drought. According to the SPI index, the Neen station spent the longest drought from late 1999 to the beginning of 2007 on a 24-month scale from 2001 to early 2007 at Reza Station.In the preparation of annual drought maps using the indicators, it was found that annual time indices cannot accurately represent drought zoning and estimate the severity of drought at the lower end. So, for these indicators, drought plans should be prepared monthly to month. This result shows that droughts are heavily dependent on the time of occurrence and vary locally and locally according to short-term time. Therefore, providing annual drought map using monthly indicators cannot provide a realistic picture of spatial development and drought severity.In the droughts map, the most severe droughts during the studied period show severe droughts in the center and south-east of the area around the stations of Naein, Kabootar Abad, KhoroBiabanak, Ardestan and Shah Reza compared to other areas of the area. From the point of view of the longest continuity in the region, the central and south-east and north parts of the area are more susceptible to potential, and the western and southwest sections are less susceptible. This feature is especially important in the southeast and the center of the area surrounding the Naein, Kabootar Abad, Shah Reza and Ardestan stations

the required information from the Mehrabad synoptic station in the Tehran-Karaj area of Tehran and Alborz provinces was prepared and then the parameters of rainfall, maximum temperature and minimum temperature were calculated by the SDSM scale scaling model under the new meteorological scenarios (AR5) and the CanESM2 general circulation model.Then, according to the outputs of the model, intensity, duration and frequency curves were extracted in different return periods for observation periods (1986-2018) and future (2051-2020 and 2051-2080).The results showed that although the winter and summer rainfall in the periods (2051-2021) and (2051-2020) in all three scenarios increased, the total annual precipitation would decrease for all three scenarios and in both periods (6.17 %, 8.02% and 8.48% respectively for scenarios of 2.6, 4.5 and 8.5, for the period 2021-2020 and 9.43, 7.98 and 8.56% during the period 2080-2080).Despite the fact that the average annual temperature does not show any significant changes compared to the observation period, the study of temperature data trends in different scenarios suggests an upward trend of the average annual temperature in predicted periods.Also, rainfall intensity in the periods 2021-2020 and 2080-2080 will decrease in all three scenarios: 2.6, 4.5 and 8.5 compared to the observation period (1986-2018). So that In the statistical period 2021-2050scenario 2.6 and In the statistical period 2051-2080, scenario 4.5, will have the highest reduction in rainfall compared to the observation period.

In this study, the EPA-SWMM model was used to simulate the flood-induced rainfall 6 hour showers with a return period of 2, 5 and 10 years and for 12 hours.The results indicate that some of the network parts that contain a number of nodes and ducts leading to critical paths showed that due to the large volume of flow in some areas there is no ability to run runoff in existing conditions , Which is the main cause of flooding, the smallness of the cross section of the ducts, as well as the low slope in some of the gorges. In this study, in order to validate the model, 5 rainfall events were used and runoff speed was calculated. The model's performance indicators in this research include Nash-Sutcliff, error square root and bias. The results of calibration of the model showed that there is a good agreement between simulated and observational data and indicates the high accuracy of the model for this area, so that the amount of NS (NS) for precipitation events is 0.88, 0.71, 0.89, 0.74 and 0.77, and it has been determined that the cause of flooding in some channels and channels is due to lack of sufficient capacity of the channels. Based on the above results, in general, this model can be used in appropriate design and evaluation of the system Municipalities used urban drainage networks.

Evaporation as a natural parameter due to the release of water from the upper part of mankind has always been of interest to scholars and researchers. In this study, we try to apply the artificial neural network model to estimate evaporation from the Amir Kabir dam and to evaluate the model accuracy. In this context, 18 years data from 1997 to 2014 were used and after consecutive try and error, the best structure for computing the amount of evaporation from the surface of the dam was selected. This structure has five neurons in the first, fourth and second layers that showed the best result in 1000 replications. Also, statistical coefficients obtained from the analysis using artificial neural network was considered in choosing the best structure with the amount of 0.9365 which was the highest amount among other tests and the amount of test and training data error were 0.0321 and 0.0311, respectively. In addition, general trend of effective data on evaporation was determined, using Mann-Kendall test on 15 years daily data. In Mann-Kendall method, temperature changes, wind speed and precipitation graphs had no significand trend and showed -1.69< U

Long-term groundwater monitoring networks can provide essential information for planning and management water resources. Budget constraints in water resource management agencies often mean a reduction in the number of observation wells included in a monitoring network. Due to economic considerations and reducing monitoring costs, the optimization approach in this study is to reduce the monitoring stations. In the present study, genetic algorithm was used to designing optimal water level monitoring network. The aim of optimization to determine an optimal combination (reduced) from the main network was well observed, so that the possibility of measurement error smallest and least loss of data and provide the best distribution of wells. Using the genetic algorithm, the groundwater monitoring network of the region was optimized. Using the genetic algorithm, the groundwater monitoring network of the region was optimized. In Koohdasht Plain, among of 15 observation wells, 13 wells observations had data. in order to do this research, the data for 36 consecutive months, namely, data from 1392 to 1394 were used. Using the genetic algorithm, the groundwater monitoring network was redesigned and selected wells were selected from potential points. finally, 28 wells had the lowest RMSE of 0.113 and had the best distribution. Location of wells obtained by a number of existing wells was near. The results obtained with the criteria of the quantity of groundwater monitoring network design, which corresponded to show the effectiveness of this approach.