ام البنی محمدرضاپور

The use of modern methods of recycling effluent with high treatment efficiency in compare to the traditional methods (the use of sedimentation ponds) is of great importance. One of the modern methods of treating these effluents is the use of filtering presses. A newer method is using hydro cyclones as a result of centrifugal hydrodynamic forces for separating solid particles from the effluent, e.g., stone powder in the current research, (Naderi et al.2019). In this regards, many researches have been done in the field of separation of two different phases of fluid using hydro cyclone in different hydraulic conditions and geometric parameters.

Materials used in research
The materials used in this research were solid particles in the wastewater of the stone cutting factory of Mahmoudabad industrial town of Isfahan. The resulting slurry was collected in the factory and after drying and separation was used for the experiments. In this study, Granite and Marble stone powder with a density of 2750 and 3020 kgm-3 and a particle diameter distribution less than 600µm was used. Also, the effect of hydraulic parameters such as flow division ratio (under flow discharge to inlet flow discharge), wastewater weight concentration and inlet pressure on hydro cyclone performance with a cyclone diameter of 140 mm in the separation of Granite and Marble powder stone from wastewater was investigated.Design of experiments Experiments were designed by Design Expert.10 software with response level method (RSM). In conducting experiments, first, a solution of Granite and Marble powder stone with the desired concentrations (0.64 to 7.36% by weight) in a volume of 20 liters was prepared in a tank, and then this solution was circulated to the hydro cyclone by pressure with a centrifugal pump.In each experiment, inlet perssure and overflow pressure were recorded using pressure guages and the volumetric flow rate from overflow and underflow was measured. Samples of overflow and underflow were taken with a specified volume and then stored and dried in an oven at 105ºC for 24 hours. The residual dry mattter mass was measured from the overflow and underflow samples, and the solid particle separation efficiency was computed from Eq. (1):E=M_u/M×100 (1) In this Equation, Mu is mass per unit volume of Granite and Marble stone powder inside the underflow (grl-1); M is total mass per unit volume of examined Granite and Marble stone powder in hydro cyclone inlet (total overflow and underflow; grl-1) and E is the efficiency of separation of solid particles from the feed.

Influence of operating parameters of weight concentration of the feed (Cw), inlet pressure of the hydro cyclone (Pi), and the Ratio of outlet flow) under flow) from the discharge to inlet flow to the hydro cyclone (Rf) on the efficiency of the examined hydro cyclone is given in the form of Eq. (2) for Granite powder stone and Eq. (3) for Marble powder stone.(2) Efficiency=93.16-1.01R_f-4.36C_w+10.01P_i+0.04R_f C_w-0.04R_f P_i+0.96 C_w P_i+8.12E-003*〖R^2〗_f -0.08*〖C^2〗_w-2.41* P_i ²(3) Efficiency=116.26-2.11R_f-9.13C_w+6.22 P_i+0.11R_f C_w+0.17R_f P_i+1.22 C_w P_i+5.54E-003*〖R^2〗_f+0.12*〖C^2〗_w-2.55* P_i ²In order to validate the obtained model, two normal probability diagram comparing the predicted data of the model with the real values were used. The results showed that with decreasing flow distribution ratio, particle separation efficiency increases, also separation efficiency decreased with increasing inlet pressure, and with increasing effluent concentration.

In this study, the effect of hydraulic parameters including flow separation ratio, inlet pressure and feed concentration was investigated on the performance of a semi industrial hydro cyclone. The analysis of the results using Response Surface Methodology (RSM) showed the effectiveness of the statistical method for obtain the optimum operational condition of the examined hydro cyclone. Based on the RSM method, the highest separation efficiency was obtained 86 and 88%, for Granite and Marble powder stone respectively.

The purpose of this study was to survey the spatial quantities of 22 crop in seven major agricultural crops in 13 major cities of Golestan province and to study its 9-year mean virtual water flow from 2007 to 2015. The priority of crop cultivation was also ranked based on its virtual water values. The results of this study showed that the virtual water of different crops in the cities of the province is different according to the performance. The results of this study showed that rice with virtual water content of 1740 m3 / ton in Ali Abad and Gorgan up to 2840 m3 / ton in Maraveh-Tapeh area had the highest amount of virtual water. Cereals with an average virtual water of 1500 m3 / ton also have high levels of virtual water and Cucurbits and vegetable products with the average virtual water of 100 and 350 m3 / ton have the lowest amounts of virtual water. The results also showed that exports and imports of agricultural products are currently incorrect and Golestan province, despite having a shortage of water, is an average 396 MM3 of virtual water exporter annually, largely driven by exports of cereal and rice products. Ranking the pattern of crop cultivation from the perspective of virtual water also showed that in this province, cucurbits and vegetable crops in all cities are in the top priority and crops such as cereals and rice are last priority.

Drought is one of the most complex natural disasters that causes economic, social and environmental damage and is often described as a creeping phenomenon. Drought monitoring using satellite images can represent the severity of drought in areas with a lack of meteorological precipitation data and compensate for its spatial and temporal deficiency. In this research, the drought of Golestan province has been investigated using SPI, TCI, VCI and VHI indices and with the help of MODIS sensor satellite images. Therefore, first, VHI, VCI and TCI drought index maps were extracted. The findings in the TCI index study showed that in 2000, more than 80% of the studied area experienced severe drought. Similarly, in 2010, 2017 and 2018, a significant part of the studied area was in a severe drought situation. By examining the VCI index, 2008, and 2011. The maps also show that a very severe meteorological drought occurred in 2008. In the study of the VHI index during a period of 21 years in the studied area, it showed that the years 2000, 2001, 2002, 2008, 2010, 2011, 2014, 2015, 2017, 2018 and 2021 have experienced a critical drought situation. Also, in the years 2000, 2008 and 2018, more than 60% of the area of the region was in a very severe drought situation. In general, most of the studied area is in the range of severe and severe drought classes, which requires attention to the optimal management of water resources in these areas.

The aim of this research is to optimize the design parameters of underground drainage systems with an economic approach. The study of the relationship between the depth and distance of drain installation has been the subject of many researchers, each of whom has tried to reduce the costs of drain implementation. In this research, genetic and multi-world algorithm optimization model was used to optimize the main design parameters of the underground drainage system of regional agricultural lands around Gorgan city. The area of the construction area of the drainage system was around 200 hectares. In this research, by using genetic and multi-world algorithm, the design parameters were selected in such a way that they lead to the lowest implementation cost of the underground drainage system. In this regard, the design parameters have been selected by combining Hohhot's permanent equation and optimization algorithms.

The area under study is Aliabad district, one of the functions of Gorgan city. The lands of Ali Abad region are also located in the upper part of the plains. These lands are located in eastern longitude and northern latitude. The study area covers about 200 hectares.
Genetic Algorithm:Genetic algorithm is an optimization method inspired by living nature, which can be referred to as a numerical method, direct and random search in classifications. This algorithm is based on repetition and its basic principles are adapted from genetic science.
Multi verse Algorithm:The big bang theory considers the occurrence of a big explosion as the beginning of the origin of our universe. According to this theory, the big bang is the origin of everything in this universe and nothing existed before it. A population-based algorithm performs the search process in two stages: exploration and exploitation. In this algorithm, the concepts of white hole and black hole are used to explore the search space. In contrast, wormholes help exploit search spaces.

Genetic Algorithm:By applying the genetic algorithm optimization model to the data of the studied lands, the optimal parameters were calculated. Table (4) shows the design parameters obtained from the genetic algorithm optimization model in different drainage coefficients for the allowed depth of drain installation. Considering the entire search area (permissible depth of drainage installation from 1.5 to 3.5 meters from the ground surface), the results obtained from the land input data of the studied area showed that taking into account the drainage coefficient of 2.5 mm per day, the minimum cost the equivalent of 51.3 million Tomans has happened in 8 hectares at a depth of 2.62 meters from the ground surface with an installation distance of 79.9 meters and a diameter of 125 mm.
Multiverse algorithm
The optimal parameters were calculated by applying the multi-world algorithm optimization model. Table (7) shows the design parameters obtained from the optimization model in different drainage coefficients for the allowed depth of drain installation. Considering the entire search area (permissible depth of drain installation from 1.5 to 3.5 meters from the ground surface), the results obtained from the input data of Aliabad lands showed that taking into account the drainage coefficient (discharge intensity) 2.5 mm per the minimum cost equivalent to 51.5 million Tomans has happened in an 8-hectare unit at a depth of 2.61 meters from the ground with an installation distance of 79.5 meters and a diameter of 125 mm.
Comparing the results of genetic and multiverse algorithms
Comparing the performance of genetic and multi-world algorithms shows the high efficiency of both algorithms in solving the problem of optimizing the diameter of drainage pipes and their installation depth. Both algorithms have almost the same performance in solving this optimization problem; So that both algorithms in the distance of the impervious layer to the depth of the drain installation (D) is equal to 2.25 meters, the stabilization depth of the water table (in the middle of the two drains) from the ground level (H) is equal to 1.5 meters and intensity Drainage or drainage from the surface unit (q) is equal to 4 mm per day, and they have calculated the optimal depth of drainage installation to be 13.3 meters

The design of drainage systems consists of choosing three parameters: depth, diameter and distance of drains. Various approaches can be used to choose the best combination of three parameters. One of the approaches can be to reduce the costs of implementing the drainage system. In this research, using the genetic algorithm, these parameters were selected in such a way that they lead to the lowest implementation cost of the drainage system. In this regard, the design parameters have been selected by combining Hohhot's permanent equation and genetic algorithm.

One of the most important crises that most countries are currently ‎facing is the issue of reducing the quality of water resources. Reducing groundwater resources and ‎increasing pollution, reduced the potential for using groundwater for various uses. One of the main ‎reasons for the decline in groundwater quality is the impact of agricultural drainage due to the ‎excessive use of fertilizers and pesticides. Also, industries that in many cases have contaminated ‎groundwater with chemical and hydrocarbon contaminants.‎‏ ‏In addition to these factors, the disposal ‎of sewage in cities and villages through absorbent wells made up of viruses and bacteria also ‎contributes to contaminants‏.‏‎ Groundwater quality monitoring program can ensure the proper quality ‎of water resources for different uses‏.‏‎ Without monitoring, continuous reporting on the quality of ‎the water supply, its evolution, planning for optimal allocation for different uses, assessing the ‎impact of new developments, and designing and implementing management plans is not feasible.‎‏ ‏Identification of homogeneous regions in terms of groundwater quality in Golestan province of ‎northern Iran using Fuzzy Clustering Method combination with genetic algorithm (GA-FCM) was ‎performed on 14 parameters in a 5- year- time step in 2006, 2011 and 2016.‎

To determine the homogeneous regions for each year, the optimal number ‎of clusters was initially obtained. After data clustering in Matlab software, the results of clustering ‎were evaluated qualitatively with Schuler and Wilcox diagrams. For better representation of ‎homogeneous regions, classification maps for the study area were presented.‎

The results showed that the optimum numbers of clusters in 2006, 2011, ‎and 2016 were 6, 5, and 6, respectively. Analysis of groundwater quality classification maps ‎showed that in 2006, cluster no. 6, including 2.7% of the studied wells located within the city of ‎Kalaleh, is poor in terms of drinking and farming groundwater quality. Also, based on the results, it ‎can be seen that 36.8% of the wells across the province were in good condition in terms of quality ‎of drinking and agricultural parameters in 2011. Likewise, 33.33% of the wells are in a moderate ‎condition in terms of drinking quality, and the status of their groundwater has improved in terms of ‎quality since 2006. Also, the results of NSGA- FCM in 2016 showed that most of the parameters ‎‎(5.55% of the wells in the province) in the cluster 3 have a moderate quality.‎

The findings of this study showed that the groundwater quality in the province in ‎‎2016 is lower than in 2011, so appropriate management plans should be adopted. Moreover, it was ‎observed that the fuzzy clustering method is a suitable method for assessing and identification of ‎critical region of the quality of groundwater resources, since it considers the uncertainty conditions ‎in the classes of the classification system.‎

Virtual water in Tony Allen's definition is the amount of water that consumes during agricultural or industrial products and services (Sadek, 2011; Mousavi et al., 2009; Mohammadi, 2012; Agahi et al., 2011; Mehdi Zadeh, 2014; Mokhtari, 2013). The population growth, water crisis, global warming increases the challenges of food security. Therefore, it is essential to consider enhancing water productivity as well as reducing virtual water. Livestock is a kind of activities that consume a considerable amount of water. Some previous studies have been done to the estimation of virtual water in the livestock industry in India (Brindha 2017) and in Saudi Arabia (Shakhawat Chowdhury et al., 2017) in recent years. Moreover, Ibidhi and Salem (2020) reported the water footprint of livestock products strongly related to the water footprint of forage and other kinds of livestock nutrition. Although Iran located in an arid region and the Khorasan Razavi province has an active livestock industry, there were not any surveys in the virtual water trend of live stocks in Khorasan Razavi province. Accordingly, in this study, the virtual water of the purebred, hybrid and native cows has estimated in each city of Khorasan Razavi province.

The virtual water content of livestock products was calculated based on Chapagin and Hokestra (2003). At first, the water requirement of purebred, native and hybrid cows was calculated with CROPWAT software for three consecutive years from 2015 to 2017in 28 cities of Khorasan Razavi province. Then the virtual water content of live cows was calculated. Finally, the virtual water of milk and meat was calculated separately for each city.

The results showed that the highest values of milk’s virtual water, related to hybrid dairy cows with 1590 cubic meters per ton (m3 ton-1) in in Gonabad and Bajestan cities and the lowest one related to native dairy cows with 309 m3 ton-1 in Mashhad. Moreover, the highest amount of virtual water of meat production belonged to hybrid dairy cows with 52350 m3 ton-1 in Gonabad and lowest was for purebred 9232 m3 ton-1 in Mashhad. Therefore, it would be recommended to produce milk from native cows and meat from purebred. Compared to world average values, virtual water of native cow’s milk in Mashhad was 68.8% lower while in Gonabad it was 60.6% higher. Therefore, it could be recommended to produce milk from native cows and meat from purebred.

Livestock feed compositions are one of the most influential factors on the total amount of virtual water in livestock products. In accordance with the previous studies, it could be suggested, the most milk should be produced in industrial conditions as well as should produce in cities which have advantages in producing fodder, based on virtual water aspects. It also might suggest changing the cultivation patterns of the province with less water consumption such as clover, fodder peas, fodder beet and sorghum. Other influential factors in the total amount of virtual water are cattle breeds and the value of milking. Virtual water for milk and meat productions in Gonabad city had the highest values in all three types of livestock and was the lowest for Mashhad and Quchan cities, so it might be better to grow more dairy cattle in Mashhad as well as to decrease the livestock productions and development in Gonabad and similar areas. Calculating the virtual water trends for the whole country also are deeply recommended in order to achieve a better vision for water resource management. Keywords: Virtual water, Khorasan Razavi province, Animal feed, Milk and meat, CROPWAT.

Water stored in the reservoir is one of the main sources of water supply in arid regions. Therefore, optimal operation of it is of utmost importance, especially in drought duration. In this study, optimal operation of Voshmgir dam using continues hedging policy optimized by linear programming (LP) and Partial swarm optimization Algorithm (PSO) that located in Golestan province north of Iran was investigated. The objective function is minimization of the Shortage index. In order to examine the effects of used hedging policy, 3 continuous drought years was considered. To evaluate the results of the models, evaluation criteria such as the percentage of water supply, reliability, vulnerability and stability indicators was used. The threshold volume changes per month was extracted and the base hedging rule curve for reservoir was presented. Evaluating the results of two models showed stability index in linear programming with 41.78 model was much higher than particle swarm algorithm with 6.416. Which indicates the higher performance of this model in the optimization of hedging policy in Voshmgir reservoir.

Virtual water can be considered as a solution for the water crisis in arid countries which they have water scarcity. Meat products utilize far more virtual water than plant products. Therefore, estimating the virtual water of livestock products and revealing its information can play an important role in adopting proper management policies to reduce the pressure on water resources. The aim of this study was to determine the virtual water content of boneless meat and the meat without bones. In order for that, virtual water of livestock products of 28 cities located in Khorasan Razavi province was calculated for years 1394, 1395 and 1396. In this study, by calculating the water need of animal feed with CROPWAT software, the amount of virtual water of livestock products was estimated. Calculations revealed the highest and the lowest "virtual water of cow with bones" among all three types of purebred, native and hybrid cows in Bajestan (30523 ) and Quchan (4956 ), respectively and the highest and the lowest "virtual water content of boneless cow" is among the three types of cows in Gonabad (57917 ) and Quchan (7894 ). The highest and the lowest "virtual water of boneless mutton” are in Gonabad (5643 ) and Mashhad (763 ), respectively, and the highest and the lowest "virtual water content of mutton without bones" are in Sabzevar (6446 ) and Mashhad (864 ).

The investigations show that the increase in greenhouse gasses has led to an increase in the average temperature of the earth’s atmosphere and, consequently the global warming in recent years. Moreover, the rise of greenhouse gasses has also caused changes in other climatic variables such as precipitation. Given the fact that climate change will bring about considerable effects on the water resources, the prediction of the climatic condition and water resources of a region is one of the planning prerequisites for the economic and social development of every country. Therefore, considering the climatic condition and volume of water resources in a country in the future is inevitable. Since the initial effects of climate change are exerted on the meteorological variables of precipitation and temperature, and any change in these variables results in disorder in many hydrological phenomena, it is essential to precisely examine the future changes of these parameters and their simulation methods. Hence, this study was conducted to evaluate the uncertainty of 20 AOGCM models under two emission scenarios of RCP2.6 and RCP8.5 in the two statistical periods (1961-2006) and (2006-2018) in the drainage basin of Karaj River. The changes in the parameters of minimum temperature, maximum temperature, and precipitation in the period of (2020-2040) compared to the baseline period were also investigated.

At first, the downscaling of the parameters of minimum temperature, maximum temperature, and precipitation was carried out using the two statistical periods of (1961-2006) and (2006-2018) and the large-scale NCEP variables as the inputs for the models of Artificial Neural Networks (ANN), LARS-WG, SDSM, and Change Factor method to determine the model’s error and evaluate its performance. For this purpose, the features and functions available in the programming environments of MATLAB, LARS-WG, and SDSM5.5.2 were employed after data normalization. The bootstrap confidence interval method and statistical criteria such as coefficient of determination (R2), Nash–Sutcliffe coefficient (NS), percent bias (PBIAS), and PRS were used to evaluate the performance of the models. Due to the suitable range of each one of statistical evaluation coefficients being within the confidence interval defined by the bootstrap method in the period of (1961-2006), the most appropriate climatic models were chosen for this from the selected AOGCM climatic model of the fifth report. In order to improve the accuracy of the chosen models in the period of (2006-2018) under the scenarios of RCP2.6 and RCP8.5, the most appropriate model for each AOGCM scenario was selected using the statistical indexes and bootstrap confidence interval method. In the next step, the chosen models of each climatic scenario were weighted using the MOTP approach for the final evaluation and selection of the model with the lowest uncertainty. Each one of these weights indicates the capability of each model in simulating the variables of minimum temperature, maximum temperature, and precipitation of the intended month, which was conducted in both scenarios of RCP2.6 and RCP8.5. The weights are presented as percentages, and the highest weight is 100, which is also considered the highest score for each model. The model chosen in this step conducts the downscaling and simulation of statistical parameters with lower uncertainty compared to the other AOGCM models and the downscaling models investigated in this study. In this stage, the confidence interval of the model (MPI-ESM-LR downscaled by the LARS-WG model) was calculated by the bootstrap method to ensure the efficiency of the chosen model. In order to analyze the accuracy of the model in downscaling the climatic elements, the number of station-months within the confidence interval was taken into account. In the last step, the climatic parameters predicted by the chosen optimum model (the model with the lowest uncertainty) in the future period (2020-2040) were compared with those in the baseline period (1999-2018). The changes in the precipitation, minimum temperature, and maximum temperature in the region were also investigated.

In the period of (1961-2006), among 20 AOGCM climatic models of the fifth report, the nine models of MIROC-ESM, CESM1-WACCM, CSIROC-MK3-6-0, EC-EARTH, GISS-E2-H, GISS-E2-R, MIROC-ESM-CHEM, MPI-ESM-LR, and MPI-ESM-MR were selected as the optimum climatic models in the drainage basin of Karaj according to the suitable range of each one of statistical evaluation coefficients for the models being within the confidence interval defined by the bootstrap method. More detailed investigations on the nine selected models in the (2006-2018) period under the RCP2.6 and RCP8.5 emission scenarios showed that the MPI-ESM-LR climatic model simulates and downscales the maximum temperature parameter in the two scenarios of RCP8.5 and RCP2.6 and the precipitation in the RCP8.5 scenario with the lowest uncertainty using the LARS-WG model. The GISS-E2-R2 model has similar performances on the minimum temperature in the RC8.5 scenario. Moreover, the EC-ERTH model simulates and downscales the precipitation with the lowest uncertainty. The three chosen models were weighted using the MOTP approach for the final evaluation and selection of the best model. The results showed that in most of the months, the highest weight percent in the simulation of climatic variables belongs to the MPI-ESM-LR model. This model is more capable of simulating the precipitation, minimum, and maximum temperatures in both scenarios of RCP8.5 and RCP2.6. Eventually, the confidence interval of the MPI-ESM-LR model (downscaled by the LARS-WG model) was calculated by the bootstrap model to ensure the efficiency of the chosen model. According to the results, it was found that among the 72 station-months, the average maximum temperatures in 62 cases were within the confidence interval.Furthermore, the monthly analysis of average and variance of the minimum temperature, maximum temperature, and precipitation showed that in most of the months, these parameters are within the confidence interval. This shows the high accuracy and low uncertainty of the selected model. In the next step, the parameters of minimum temperature, maximum temperature, and precipitation in the period of (2020-2040) were simulated and downscaled by the chosen model. The evaluation of results in this section showed that the minimum temperature would have a growing trend until 2040. The slope of the average minimum temperature curve in the studied statistical period under the RCP2.6 and RCP8.5 scenarios will increase by 0.02% and 0.08%, respectively. The most significant growth of this parameter was estimated to be +0.8ºC and +0.16ºC under the RCP2.6 and RCP8.5 scenarios in September and March, respectively. The precipitation in the RCP2.6 scenario has nor decreasing neither increasing trend. The statistics of Sen Test in the evaluated confidence intervals indicated that the average precipitation had decreased by almost 0.38 mm every year. The annual average in the RCP8.5 scenario has a significant decreasing trend with a slope of -1.31 mm in the low confidence interval (α = 0.1). The most considerable growth and reduction with the values of +0.45 and +0.63 in the slope of precipitation curve in this scenario are seen in July and October, respectively. This parameter has also a decreasing trend in the very high level of (α = 0.001) for the average maximum temperature in both scenarios. Based on the obtained results, this climatic parameter has a significant decreasing trend in the studied confidence intervals in most of the months. The largest reduction of this parameter under the RCP2.6 and RCP8.5 scenarios will happen in March and June by 0.20ºC and 0.14ºC.

ABSTRACT In order to investigate the yield and water use efficiency of wheat (Chamran 2), rapeseed (Hyola 50), potato (Sante) and corn (704) under different levels of irrigation, the present research was carried out in two years 2017-2018 and 2018-2019 as complete randomized block design with four replications at Agricultural Research Center of Jiroft. Irrigation levels were 50, 75 and 100 % of the crop's water requirement. The Yield, biomass, harvest index and water use efficiency were investigated for the proposed crops. The results showed that the effect of irrigation levels was significant during two years on grain yield, biomass and water use efficiency at 1% level and on harvest index at 5% level. By increasing irrigation water, both grain yield and biomass were increased significantly in all crops. Potato and rapeseed had the highest (0.65-0.74) and the lowest (0.20-0.25) water index, respectively. On the other hand, potato and rapeseed showed the highest (10.68-22.76 kg/m3) and the lowest (1.29-1.84 kg/m3) water use efficiency, respectively. The 75% irrigation level is recommended due to lower decrease in yield and higher increase in water use efficiency. In general, according to the results of this study, the highest water use efficiency was observed in potato, wheat, maize and rapeseed plants, respectively. Overall potato and maize rotation is recommended due to higher water use efficiency in Jiroft.

In traditional irrigation systems, inappropriate management of water allocation may lead to poor performance of the irrigation district, an increase in water losses, and a reduction in crop water productivity (CWP). Using optimization methods and nonlinear models along with the geographical information system (GIS) can improve the management of an irrigation district under uncertain condition. The objective of this study is to investigate the optimal water allocation and reasons for the CWP reduction in irrigation distribution district. To do so, in the first stage, those sites of water distribution district with the highest effects on CWP variability were identified. Then, the CWP was increased, later. For this purpose, fuzzy programming models and the possibility theory are used to prepare a water allocation plan for the irrigation system of Sistan Dam. The results show that the highest CWP of irrigation district for wheat fields is 0.45 kg/m3, which exist at the sites by the range of discharge losses in 360 to 400 L/m/hr. The analysis of these critical spots shows that the CWP values do not necessarily depend on crop productivity but they may depend on the management factors of irrigation district and the cultivated areas. Therefore, the spots with an optimized CWP could be considered as suitable patterns for increasing the management efficiency.

To investigate the effect of unconventional water and zeolite on yield and water use efficiency of sorghum, a split plot experiment was conducted based on randomized complete block design with 3 replications, at Gharakhil Agricultural Research Station in Ghaemshahr, Mazandaran Province. In this experiment, the main treatment was irrigation water quality (well water as control (W1); 75% well water and 25% seawater (W2); 25% well water and 75% seawater (W3); 100% treated urban wastewater alternated with 100% seawater (W4); 50% seawater and 50% urban treated wastewater (W5); irrigation with urban treated wastewater (W6)), and sub-treatment included three levels of zeolite as soil amendment (without zeolite Z1, calcic zeolite Z2, and potasic zeolite Z3). The results of data analysis showed that irrigation water quality treatments and zeolite levels had a significant (P<0.05) effect on plant yield. With increasing salinity, the yield of fresh and dry fodder sorghum decreased, but no significant difference was observed between treatments W5 and W4. The fresh and dry fodder yield in treated wastewater with calcic zeolite was higher than other treatments. The highest leaf area index was recorded in W6Z2 treatment (7.62) and the lowest was in W3Z1 treatment (3.80). The highest water use efficiency of fresh forage was observed in W6Z2 treatment (12.7 kg/m3) and the lowest in W3Z1 treatment (4.62 kg/m3).

In order to investigate the qualitative changes in forage products using unconventional waters and zeolites, a split plot experiment was conducted based on randomized complete block design with 3 replications at Gharakhil Agricultural Research Station in Ghaemshahr. In this experiment, the main treatment was irrigation water quality (well water as control (W1) ; 75% well water and 25% seawater (W2); 25% well water and 75% seawater (W3); 100% urban treated wastewater in alternative with 100% seawater (W4); 50% seawater and 50% urban treated wastewater (W5); irrigation with urban treated wastewater (W6)) and sub-treatment including three levels of zeolite as soil modifier (without zeolite Z1, zeolite calcium Z2 and zeolite potasic Z3). The results of data analysis showed that the effect of irrigation water quality treatments and zeolite levels on forage yield had a significant effect at a probability level of 5%. Salinity reduced forage yield but no significant difference was observed between W5 and W4 treatments. The amount of fresh forage yield in treated wastewater with zeolite calcium was 129 t.ha-1, which was more than the rest of the treatments. The protein content of sorghum was decrease with increasing the amount of salinity, but carbohydrate increased. The highest leaf protein content was observed in W6Z2 treatment at 14.83%. The highest carbohydrate content was seen in W3Z3 treatment at 9.75 mg.g-1. The highest rate of adsorption of cadmium and chromium was in W3 treatment, which was higher in root of plant than leaves and stems, and in zeolite-containing treatments, this amount was lower in leaves and stem.

This study was carried out using AquaCrop plant growth model to simulate potato crop yield in irrigation levels of 100, 80 and 65 percent of plant water requirement under climate change conditions in Shahrekord region. The data of two years of 2013 and 2014 were used to calibrate and validate the AquaCrop plant growth model. In order to investigate the effect of climate change on product yield, the output data of the HadCM3 general circulation model under two scenarios A2 and B1 for the periods 2011- 2030 and 2046-2065 are downscaled using LARS-WG model and used as inputs of the growth model. Based on the results, the simulation of potato yields with the AquaCrop plant growth model was carried out with high precision so that the average difference between observed and simulated values in calibration and validation stage was 0.56 and 0.68 ton/ha, respectively. Also, the mean absolute error (MAE) for simulating minimum temperature, maximum temperature, sunshine hours and precipitation with LARS-WG model was 0.05, 0.03, 0.01 and 0.16, respectively which reflects the good performance of the model in producing climate data for the future periods. Simulation results showed that the potato yield for the periods 2011-2030 and 2046-2065 under the A2 scenarios was 15.8 and 24.5 percent, respectively, and under B1 scenario, 11.8 and 22.4 percent increase compared to the base period. Also, for I80 and I65 treatments, the yield value decreases in both the future periods and the two scenarios campared to the base period.

In recent years, overuse of ground waters has led to a significant decrease in water levels and has also reduced groundwater quality. Therefore, qualitative analysis of ground water reservoirs is deemed necessary to manage exploitation of these resources and determine the most optimal and economic cropping patterns. Geostatistical methods are the most widely used and appropriate tools for monitoring qualitative variables. In this regard, the spatial variations of qualitative variables such as Na+, TH, EC, SAR, Cl-, SO42-, Mg2+, PH, TDS and K+driven from 70 wells on aquifers of Ghorveh and Dehgolan Plain located in Kurdistan province were studied. The statistical period of the data used in this study covers the years 1984-2012. After analyzing the variogram by GS+ software, data interpolation was performed using three methods of ordinary kriging, simple kriging, and inverse distance weighing with the powers of 1, 2 and 3, respectively. The results shows that the omni-directional semivariogram for all variables is nearly identical. The results also indicate that using ordinary kriging and simple kriging methodscause fewer errors in estimating most qualitative variables. The values of mean error (ME) statistics in the kriging method are close to zero, indicating the least bias in estimations. Also, water quality was classified in terms of Schuler and Will Cox terms methods, so that the results reveal that most of the wells are within an optimal range, yet a few are in medium and bad ranges. Zoning results demonstrated that groundwater quality in the western, southern, and southeastern zones is better than those of other sectors. Thus, it is necessary for management to reduce consumption and change cropping patterns to improve water quality in areas with poor water quality.

Numerous studies in optimization of water supply networks have been allocated to cost reduction of these infrastructures. In general optimization methods, minimizing the costs is the unique purpose, but applying this view point for the case of water supply systems may lead to reduction of the utility and efficiency of the system. Therefore, some multi-objective optimization models have been used to decrease the large amount of costs in these systems and to increase their operation efficiency. The present study has attempted to illustrate a case study for a town of Kerman in order to decrease the costs of rebuilding pipe network using the Imperialistic Competition Optimization Algorithm. So, the network simulation was performed with Water GEMS software. Firstly, the water supply network of the study area was simulated in the Water GEMS model. Next, the properties of water supply network were inserted. Then, using the standard pressure and speed constraints, the optimal options of the algorithm were obtained. By re-running the results of this optimized model in the Water GEMS model and the limits’ checkup, the total costs were estimated and compared. Analysis of the optimal model results showed that in comparison with the state prior to the network optimization, the Imperialistic Competition Algorithm has significantly reduced the cost function of the network.

One of the most important issues in the field of optimizing water resources management is the optimal utilization of the dam reservoirs. In the recent decades, the optimal operation of dams has been one of the most interesting issues considered by water resources planners in the country. Due to the complexities of the typical optimization methods, employing an evolutionary algorithm is regarded here. One of the most significant algorithms is the ant colony algorithm. So the aim of this study is to optimize the delivery of Golestan and Voshmgir reservoirs to meet the needs of the down lands using the elite ant colony algorithm, maximum – minimum ants, ranked ants, and particle swarm algorithms, and to compare the performance of these algorithms with each other. The considered decision variable was the release of the reservoirs in the above- mentioned dams. In this study, the data over a 5-year period, from 2006-2007 to 2011-2012, was used for modeling. The results showed that all algorithms could optimize the release amount optimally; however, the elite ant algorithm with the objective function value of 0.6407 estimated the release values with great accuracy in both dams. Also, the particle swarm algorithm with 1.275 of the objective function value was well-matched with the release values. The ranked ant algorithm with 18.924 and Max-Min ant with 26.431 of the objective function valuewere, respectively, at the next levels of performance optimization of the release values from Golestan and Voshgar dams.

Obviously, in any planning for qualitative and quantitative management of water resources, ýestimating the water balance and values of the input and output components that will play an ýimportant role. Several studies in the field of evapotranspiration most complex component of ýthe water balance in the world and many models offered and developedþ.þý Remote Sensing due to ýthe superiority of meteorological methods based on measuring point and water balance is more ýin the works. In this study, performance of Surface Energy Balance (SEBS) model to estimate ýactual evapotranspiration in Sistan plain is studied. For this purpose data from Zehak ýmeteorological stations and the technology of remote sensing and MODIS sensor images used. ýSurface flux of energy balance is calculated for each image pixel and actual evapotranspiration ýwere estimated by the remaining amount of the energy balance at the level. The results were ýcompared with results of two point ground-based data consist of the hay grown on the sidelines ýof Zahak synoptic station and water level of reservoir of Chahnime1. Model showed good ýperformance for both land and water based on correlation coefficient value with 0.78 and 0.89 ýrespectively.ý

Accurate estimation as one of the important elements of the hydrological cycle of evaporation play an important role in the development and management of water resources plays countries facing a water crisis. so far methods, and many empirical formulas in estimating the nonlinear process evaporation of the basin, which provide high accuracy and as well as access to all the input parameters problem or measure they need a lot of time and money.The aim of this study was to compare of ability of Gene expression programming and neuro-fuzzy methods for estimation of evaporation in South Khorasan province. For this purpose daily data collected from occurs six synoptic stations during years 1990-2010. Input parameters are daily mean temperature, relative humidity, max and min temperature, wind speed and sun shine. Finally, to evaluate of models and compare them criteria such as coefficient of determination (R2) and Mean Bias Error (MBE) and Root Mean Square Error (RMSE) and MBE is used. Compression of result in test period showed the GEP Model has better performance than the neuro-fuzzy model to estimate the daily evaporation. The best result of GEP is R2=0.79¡ RMSE= 1.44 and MBE=0.35 in Boshroie station and worst is R2=0.7¡ RMSE= 2.6 and MBE=1.2 in Birgand station. Also the results showed the main factor in estimation of evaporation is mean temperature in all station except that mine temperature is impact parameter.

The long history of research on utilization of resources and their allocation to the consuming sectors dates back to the first human efforts in managing his nature in which this exploitation was mostly focused on man (Simonovic, 1992). Now, given the recent droughts in Sistan and due to the fact that the major management of Helmand River occurs in Afghanistan, the Chahnimeh reservoirs in Sistan require special comprehensive management. Therefore, the present study aims to determine the amount of water allocated to the agriculture, potable water, aquaculture, and environmental sectors of quadruplet reservoirs of Chahnimeh.
Chahnimeh reservoirs are located in East and Northeast of Sistan and Baluchistan province between 61° 29' to 61° 44' east longitude and 30° 40' to 30° 54' north. Water management in decision support system (WEAP) deals with proper setting of priorities and preferences in consumption of resources. Factors considered in this study for water resources’ planning include the environmental need, evaporation, potable water, agriculture, and aquaculture. In this study, the environmental water rights are calculated in accordance with the Montana method (Tennant, 2011). Evaporation from the reservoir’s surface is also calculated based on the monthly curve of volume, level, height, and evaporation at different levels. According to the exponential population, the potable water required for 3 regions of Zabol city, Sistan villages and 30% of the water requirement in Zahedan city was calculated as 3% (Statistical Center of Iran, 1390). Parameters required for agriculture were annual cultivation area and the annual rate of water consumption per hectare. In the reference scenario (R), the regional hydrological conditions were considered as the current conditions, and only the irrigation ability of the 1st, 2nd, and 3rd Chahnimeh was used in water resources planning. Scenario (R1) was created based on the reference scenario (R), but the cultivation level of crops according to the appropriate cropping patterns and drought conditions dropped. In scenario (R2), the required water for other sectors (agriculture and portable) was provided and if there is a suitable opening of the Helmand River, the water requirement of Hamoun wetlands will be provided by the Chahnimeh reservoirs. By relying on the natural flow of the river, after implementing the scenario of development (D), the 4th reservoir tank is added to the previous ones and the cultivation level of agricultural products has increased by 13,500 hectares. In scenario (D1), all hydrological conditions and reservoirs are considered in accordance with the scenario of development and the required water provided from these four reservoirs has been studied. Any violation of system performance from a performance threshold or inability of the system in supplying the required water is called system failure. There are several methods to analyze the performance or failure of the system. In this research, the Reliability index is used to compare the scenarios with each other (Hashimoto et al., 1982).
This index is determined by calculating the number of failures per requirements during each simulation period. By comparing the scenarios (R1) with (R), the rate of Reliability index in potable water section rises from 90.6% to 96.9%. In the comparison of the scenarios (R2) with (R), the required rate of environmental need of Hamoun wetland in the scenario (R2) was regarded as 10% of monthly input of the Chahnimeh reservoirs, so the results of the model showed that in comparison with the scenario (R), the Reliability index of the system in other sectors remained constant. In comparing the scenarios (D) and (R), the effect of increasing the area under cultivation from 45,000 hectares in the status quo to 58,500 hectares in the development program and addition of the fourth Chahnimeh reservoir to the utilization system of water resources were reviewed. In the scenario (D), the reduced impact of the Reliability index on agriculture and potable water sectors were ignored, so performing agricultural development program under the status quo with a Reliability index of over 98% would be provided. In comparing the scenarios (D1) and (R), the condition of water rights needed for the sectors of agriculture, The purpose of comparing these two scenarios was to assess and analyze the effect of adding the fourth Chahnimeh on the utilization system of water resources and the agricultural development of the region through taking into account the environmental needs of Hamoun wetland in the region. Storage of surplus water in reservoirs could increase water level subject to evaporation. This case was determined by comparing the scenario (D) with the scenario (D1). The results of the simulation showed that evaporation loss in the scenario (D1) was 50 million m3 less than in the scenario (D) in the 4th Chahnimeh. This result also focused on the amount of water released for meeting the environmental needs of Hamoun wetland. In comparison of the scenarios (R2) with (R), considering the water rights as 10% of the water inlet of the Chahnimeh reservoirs would not be a threat to water allocation to other requirements.Under the scenario (R), which represented the current state of the water resources in the region, in 85% of the years, 57.5% of requirements would be provided in the agriculture sector, whereas in the potable water sector, in 85% of the years 87.3% of the needs were met. Under the scenario (D), representing the management development state of water resources in the region, not only the current land under cultivation would be preserved but also13, 500 hectares of agricultural land would be added to the agricultural lands. In this way, in 85% of the years, it would supply 85% of the requirements. Analysis of these scenarios and the results obtained from the scenario (D1) showed that along with the increased needs of the agricultural sector and the Hamoun wetland, in terms of the Reliability level, the development conditions increased more than other scenarios. Moreover, with the addition of the environmental needs of the Hamoun wetland to the water resources’ planning of the region, the rates of evaporation loss from the 4th reservoir could reduce significantly.

Despite the importance of evapotranspiration in the planning and management of water resources¡ its dependence on climatic factors on the one hand and influence of each of these components on the other hand has made it difficult to estimate evapotranspiration. Therefore¡ in this study¡ attempts to explore the possibility of predicting these important component in Sistan and Baluchestan using meta-heuristic models such as neuro-fuzzy inference system¡ GEP and SVM. In this regard¡ according to the FAO Penman-Monteith equation¡ the monthly potential evapotranspiration in four synoptic stations- Zahedan¡ Zabol¡ Iranshahr¡ and Chabahar- was calculated using the monthly weather data. These values as a reference to compare the results of the Neuro-fuzzy inference models¡ genetic programming¡ and SVM methods were studied. The five models applied in this study were: Model 1 includes input of average air temperature¡ shiny hours and relative humidity in the same month. Model 2 includes average air temperature¡ relative humidity¡ and wind speed in the same month. Model 3 includes average air temperature¡ relative humidity¡ and wind speed in the same month. Model 4 includes average air temperature¡ relative humidity¡ wind speed¡ and average shiny hours in the same month¡ and model 5 includes average air temperature¡ relative humidity¡ wind speed¡ and shiny hours in the same month and the earlier month. The results of different models were compared based on the statistical coefficient of determination and root mean square error. These findings show that in the neuro-fuzzy model¡ the models 2 (r2= 0.945)¡ 3 (r2= 0.982(¡ 4(r2= 0.26)¡ and 5 (r2= 0.423)¡ respectively in Zahedan¡ Zabul and Chabahar¡ and Iranshahr Chabahar stations own greater accuracy. Analysis of results in the gene- expression planning model also indicates that in the test section¡ the model no. 4¡ with the coefficients of 0.974¡ 0.9811¡ 0.982¡ and 0.815¡ respectively for the stations of Zahedan¡ Zabol¡ Iranshahr¡ and Chabahar¡ has higher accuracy. Likewise¡ in the SVM model¡ due to the coefficients of determination¡ 0.997¡ 0.998¡ 0.998¡ and 0.979¡ respectively in the stations of Zahedan¡ Zabol¡ Iranshahr¡ and Chabahar¡ the model 5 had the highest accuracy. Comparison of 3 models in this study also showed that in all stations¡ the Support Vector Machine¡ the programming model of gene expression¡ and the neuro-fuzzy model were paced in the first¡ the second¡ and the third levels of importance for estimating the monthly potential evapotranspiration.

The high cost problem of urban water supply systems, along with the complexity of the design and unsuitable operation problems cause that optimization of the system before applying any changes, has become the basic needs of managers in this area. Due to the complexity of nonlinear and unique design of these networks, in recent years engineers using artificial intelligence and search algorithms to solve this problem. In the present study find solutions for the network in a town of Kerman with help of fast messy Genetic and firefly Algorithms and network simulation software intended WaterGEMS. First the water supply network in the study area simulated in WaterGEMS model and the properties required for optimization algorithms have been extract, then using the standard pressure and speed constraints, these algorithms create optimal choices. By entering these results in WaterGEMS model and re-running for limits check, the cost estimates are discussed and compared. The results show that the optimization of, fast messy Genetic algorithm with 37.7% is able to reduce the cost function of network compare to pre-optimized network. Also Firefly algorithm in the amount of 34.4%, is able to reduce costs. Finally, we can say that both optimization algorithms used in this study have been able to achieve a dramatic reduction in project costs.

Due to its biological nature and high dependence on regional condition, agriculture is the largest consumer of water resources in many countries. Hence, today, agricultural water management plays an important role in the use of water resources of these countries. The present study used Genetic Algorithm to optimize cultivation area, allocate irrigation water, and maximize profits gained from the cultivation of some crops under various weather conditions in Qazvin Plain (located in the north west of the central plateau of Iran), where some of the required water is obtained from Taleghan dam. In this study, different probability levels of rainfall, evaporation, and input flow of optimization were combined under four different weather conditions. The results showed that in normal, wet, dry, and hot - dry weather conditions, the profit earned from the new cultivation pattern introduced by the model was much more than that of the current pattern. Moreover, following this new pattern could mostly result in lower water consumption in this sector, such that the volume of water stored in the dam reservoir at the end of the operation in wet, normal, dry, and hot-dry conditions would increase by, respectively, 262045.2, 2862686.6, 273089 and 955542 m3. The results showed that the cultivation area of sugar beet in every of the four different condition was reduced (over 80%) because of its high water requirement and low yield, therefore, its cultivation is not recommended under any weather conditions in the studied area. Following the new cropping pattern delivered by this model, the farmers’ profit in wet, normal, dry, and hot-dry conditions would increase by, respectively, 2.81%, 2.62%, 1.34%, and 1.53% compared to the prevailing pattern.

In the wake of the damage that man has Sntgrayyash the ground , place the study of climate change and global warming , due to the industrialization of the earth , the day will be added .The radiative effect of greenhouse gases on global warming is a major factor and the factor in global climate change with unprecedented speed . Every kind of climate change on the terrestrial earth is the beginning a chain of reactions whose direct effect on hydrological processes can be observed.
In this study, SDSM model is used to measure the large -scale data of the atmospheric general circulation model (HadCM3) in two local climate change scenarios, A2 and B2, for the meteorological parameters of temperature and precipitation in the basin of Qara Su. Then, considering the data of rainfall, temperature and flow rate and the fine- scale model outputs exponentially in the an artificial neural network is used to calculate the river’s discharge during the future period. Climate model results indicate an increase in temperature and a decrease in rainfall within the desired course relative to the base period. Consequently, this increase in temperature and decrease in rainfall will lessen the discharge rates of Qara Su River.