مقالات رزومه کامران داوری

Clustering is an instrument that divides existing data into different groups. Generally, the number of clusters is determined based on the least changes within the group and the most changes outside the group. The study area is country of Iran. Coordinates of longitude, latitude, altitude, average temperature, relative humidity and total monthly rainfall of 420 synoptic stations from its establishment until 2018 have been used in this study. After reviewing, screening and repairing the data, only 375 stations remained to continue the research. Due to the length of the statistical period is an important factor influencing clustering, the stations are statistically divided into three periods: less than 5 years with 42 stations; 1-6 years with 33 stations and more than 10 years with 300 stations, were classified. Seven methods of hierarchical clustering (3 subsets), separation (2 subsets) and ward (2 subsets) have been used in this study. Cophenetic correlation coefficient, Silhouette width test are two indicators of clustering and selection. The coding was performed in R statistical software. Based on the Cophenetic and Silhouette coefficient indices, the best number and method of clustering for 1-5-year data are 4 clusters with the middle axis separation method, for the data of 6-10 years are 5 clusters with the mean-centered hierarchical method and for stations with a statistical period of more than 10 years are 4 clusters with the separation average axis method. The zoning of the clusters is plotted on the geographical map of Iran using ARCGIS software for all three categories. Keywords: Clustering, Geographical coordinates, Synoptic, Iran.Clustering is an instrument that divides existing data into different groups. Generally, the number of clusters is determined based on the least changes within the group and the most changes outside the group. The study area is country of Iran. Coordinates of longitude, latitude, altitude, average temperature, relative humidity and total monthly rainfall of 420 synoptic stations from its establishment until 2018 have been used in this study. After reviewing, screening and repairing the data, only 375 stations remained to continue the research. Due to the length of the statistical period is an important factor influencing clustering, the stations are statistically divided into three periods: less than 5 years with 42 stations; 1-6 years with 33 stations and more than 10 years with 300 stations, were classified. Seven methods of hierarchical clustering (3 subsets), separation (2 subsets) and ward (2 subsets) have been used in this study. Cophenetic correlation coefficient, Silhouette width test are two indicators of clustering and selection. The coding was performed in R statistical software. Based on the Cophenetic and Silhouette coefficient indices, the best number and method of clustering for 1-5-year data are 4 clusters with the middle axis separation method, for the data of 6-10 years are 5 clusters with the mean-centered hierarchical method and for stations with a statistical period of more than 10 years are 4 clusters with the separation average axis method. The zoning of the clusters is plotted on the geographical map of Iran using ARCGIS software for all three categories. Keywords: Clustering, Geographical coordinates, Synoptic, Iran.Clustering is an instrument that divides existing data into different groups. Generally, the number of clusters is determined based on the least changes within the group and the most changes outside the group. The study area is country of Iran. Coordinates of longitude, latitude, altitude, average temperature, relative humidity and total monthly rainfall of 420 synoptic stations from its establishment until 2018 have been used in this study. After reviewing, screening and repairing the data, only 375 stations remained to continue the research. Due to the length of the statistical period is an important factor influencing clustering, the stations are statistically divided into three periods: less than 5 years with 42 stations; 1-6 years with 33 stations and more than 10 years with 300 stations, were classified. Seven methods of hierarchical clustering (3 subsets), separation (2 subsets) and ward (2 subsets) have been used in this study. Cophenetic correlation coefficient, Silhouette width test are two indicators of clustering and selection. The coding was performed in R statistical software. Based on the Cophenetic and Silhouette coefficient indices, the best number and method of clustering for 1-5-year data are 4 clusters with the middle axis separation method, for the data of 6-10 years are 5 clusters with the mean-centered hierarchical method and for stations with a statistical period of more than 10 years are 4 clusters with the separation average axis method. The zoning of the clusters is plotted on the geographical map of Iran using ARCGIS software for all three categories. Keywords: Clustering, Geographical coordinates, Synoptic, Iran.

Evapotranspiration (ET) is one of the most important components of the hydrological cycle and an important factor in determining water demand, its spatial distribution and accurate estimation for many studies such as water balance, crop production simulation, program Irrigation planning and water resources management are very important. Also, using of geostatistical methods is one of the ways to estimate evapotranspiration in places without stations. In this study, SWAT hydrological model was used to simulate evapotranspiration of Samalghan watershed . To evaluate the simulation results, indices R2 , bR2 , NS was used. In the calibration stage, the coefficients of R2, bR2 and NS were equal to 0.74, 0.71 and 0.68, respectively, and in the validation stage, they was equal to 0.69, 0.62 and 0.59. .Then, using the results of spatial analysis of data in this study, the exponantial model was selected as the most appropriate model for zoning due to the lower RMSe value and higher correlation.

The Earth’s climate has been changing since began drastically. Global warming and change in precipitation pattern are consequence of climate change. Climate change and over-withdrawal of water for industrial purposes has increase water stresses around the world. Long-term water stresses may cause disasters. Hence it is necessary to control water stress. This paper proposes a model to manage water stress of different catchments by proper locating of large industries considering climate change.

Global warming in recent decades has caused significant changes in precipitation and temperature, including changes in the mean and standard deviation of these variables and changes in the intensity and frequency of climatic extremes (floods and droughts). Given the importance of these changes in water resources management, it is crucial to study the trends in these variables. In this study, in 12 selected stations in different climatic regions in Iran, the changes in monthly and annual precipitation and mean temperature during 1961-1990 and 1991-2020 were examined. The results of Mann-Kendall test showed in most stations precipitation had an increasing trend in the first period, and a decreasing trend in the second period; although in both periods the trend was not significant (Z<1.645). The mean temperature has increased in both periods, which in the second period has increased with a higher level of confidence (Z>2,576) and greater slope than in the first period. The average annual rainfall has decreased in most stations, and the average annual temperature has increased in all stations. The distribution of precipitation and temperature showed that in some stations, the probability of occurrence of extreme events and hot and cold periods in the second period has increased compared to the first period. In some other stations, droughts/floods are more/less likely to occur. This indicates that the activity of air masses affecting each station can be intensified or weakened due to climate change.

In order to predict the behavior of soil-related phenomena, it is necessary to have knowledge about unsaturated flow and using models that provide optimal estimates of the retention curve and hydraulic conductivity of soils. Despite the widespread use of the classic van Genuchten-Mualem model (VGM), this model usually performs poorly in predicting hydraulic conductivity and modification of some of its parameters seems necessary. In this research, a number of 283 soils from different texture of the UNSODA bank were selected and divided into two sections of calibration and validation sections and their soil parameters were extracted and categorized. Then, by defining the modified unsaturated hydraulic conductivity (Ksc) instead of the saturated hydraulic conductivity (Ks) and determining the limits for l and n parameters, the hydraulic conductivity-moisture function of this model were solved using 24600 pairs of points li and nj for each soil of the three main soil texture classes. In the following, the optimal l value (l̂) of each texture class was selected based on the minimum value of the hydraulic conductivity estimation error using the root mean square error (RMSE) index and the n values that create the minimum errors were selected as the optimal pore size distribution coefficients of the hydraulic conductivity-moisture function (n̂opt). In order to create pedotransfer functions for estimating n̂opt, we ran stepwise regression in MATLAB software considering the condition of statistical significance (P-value=0.05) for independent variables and functions for each soil texture class. After creating pedotransfer functions, the results of the proposed method of this research (MVGM) were compared with the VGM model results using RMSE and Nash-Sutcliffe (NSE) indices. The results showed that in both sections of creating and validation functions, the MVGM performed better in estimating hydraulic conductivity and had a higher efficiency index for all classes of soil texture.

Irrigation plays an important role in increasing crop yield especially in arid and semi-arid regions, where optimizing irrigation depth and leaching is crucial. Using simulation models such as AquaCrop help to analyze different irrigation scenarios and also help farmers to optimize water resources management in such conditions. In this study, calibrated and validated AquaCrop model was used for two wheat varieties in Birjand region and one wheat variety in Mashhad region. A Matlab program has been developed to link to the AquaCrop in order to achieve the optimized values of irrigation and leaching in the water constraint conditions. The optimization results showed that net profit for the best irrigation and leaching management at all salinity levels and different wheat varieties, except for salinity levels of 8.6 and 10 dS m-1 in the Mashhad variety and level of 9.6 dS m-1 in the Roshan variety, was more than the current management researches of Shahidi and Haghverdi. While the aim is to achieve maximum profit and minimal drainage water, the model by changing the type of irrigation management and reduce leaching, especially in the last two irrigations only, reduced the amount of water consumed and the amount of drainage water to zero. The results also showed the reduction of gross irrigation water in the salinity levels more than tolerance threshold of wheat was less than the other salinity levels and the difference was completely negligible. Because in high salinity levels, yield reduction in deficit irrigation was more in comparison with low salinity levels, therefore deficit irrigation in salinity levels of more than the wheat tolerance threshold is not economic. Generally, the optimization results showed that in the area of Birjand and Mashhad, using the best irrigation and leaching management at different salinity levels can increase the benefit of wheat cultivation.

Water is one of the most important physical factors to provide the food security of the world’s growing population. The limitation of Iran’s water resources, as well as the increasing competition of different sectors for the use of water make the optimal management of water resources necessary. Different strategies are used in irrigation networks for water resources management. One of these strategies is optimal allocation of water and land. In this research, an optimization model for water and land allocation with the aim of maximizing economic benefit is presented based on genetic algorithm and using the AquaCrop plug-in model. For this purpose, #C coding was done in Visual Studio. In order to measure the model performance, the lands covered by one of the Moghan irrigation network channels were investigated. In this model, the agricultural year was divided into 36 periods of ten days. The irrigation water depth in each period and the cultivated area were considered as decision variables. The results show that the highest increase in percentage of economic benefit is related to the first-cultivation maize, alfalfa and wheat by 9, 7.3 and 7 percent respectively. Although the lowest increase in economic benefit is related to the second-cultivation seed maize and soybeans. The optimal allocated water volume was decreased by 14.7 percent, meanwhile the economic benefit was increased by 5.7 percent. Therefore, the optimal water allocation in this region encourages saving water consumption more than increasing economic benefit.

There are several reasons to answer the question of why hydrological processes should be modeled. The main answer to this question is the limitation of measurement methods in hydrology. In this study, SWAT model, which is a conceptual and semi-distributive model in the watershed scale, was used for hydrological simulation of Samalghan watershed. After preparing the data according to the desired format, the model was implemented. After sensitivity analysis and determination of important parameters, the model was calibrated and validated. In order to reduce uncertainty, different components of water balance were considered in calibration and observational data of several measuring stations were used simultaneously. Then, SUFI 2 algorithm was used to evaluate and validate the model. The calibration process was performed for the period 2007 to 2013 and the validation process was performed for the period 2014 to 2017. To evaluate the simulation results, indices R2, bR2 (weight correlation coefficient), NS (Nash-Sutcliffe) were used. In the validation stage, the coefficients of R2, bR2 and NS coefficients were 0.74, 0.71 and 0.68, respectively, and in the validation stage, 0.69, 0.62 and 0.95 were obtained. The indicators and graphs obtained in the calibration and validation phase of the model to simulate the monthly runoff flow show that the model has been more successful in the calibration phase. Also, the model has been able to determine the peak time of the Dubai peak. This research provides useful information about the water balance of the Samolghan River basin and helps to more accurately plan water resources in this basin.

This study sets out to assess flood susceptibility in the Zoshk watershed, Razavi Khorasan, using the coupled fuzzy-AHP method, which incorporated different stages including rate assignment to criteria and sub-criteria based on expertise, fuzzification of rates, fuzzified weight assignment, and ultimately superimposing the layers. To this end, fifteen thematic maps of different characteristics were generated and used as inputs to the modeling process, including morphometric (DEM, slope, aspect, planar and profile curvatures, RSP, TRI), topo-hydrologic (flow accumulation, proximity to streams, HAND, TWI, SPI), edaphic (curve number), vegetation (NDVI), and climatic (precipitation) factors. Results revealed that among the adopted flood controlling factors, the factor of proximity to streams as the mainstream and a key driver to flood events plays the most critical role in the study area, followed by flow accumulation, curve number, and normalized difference vegetation index (NDVI) (topo-hydrologic, edaphic, and botanic, accordingly) with the respective fuzzified weights of 0.072, 0.071, 0.07, 0.068, and 0.067. The results of flood susceptibility zonation attest that 27.5% (1873 ha) of the entire study area falls within the very high and high susceptibility classes. The spatial distribution of high flood susceptibility classes in upstream and downstream sectors indicates that soft engineering techniques (biologic and biomechanical measures) in upstream and hard mechanical engineering measures in downstream areas should be concurrently considered. Additionally, educating the local communities about the concepts of flood hazard and risk should be considered across the entire area, from the lowest to the highest susceptible parts of the study area.

To choose the right cropping pattern with the aim of maximizing farmer income, stability and stability in production, can not be satisfied only with one-year economic issues, but also issues such as weed control, pest and disease control and soil fertility in the long run should be considered. The method that farmers traditionally use and still is applicabe today, is crop rotation. However, crop rotation is not usually considered in crop pattern optimization. In this study, the effect of crop rotation on crop yield and the amount of profit (as an effective management practice) obtained from the crop unit has been investigated by an evaluation equation. In order to calculate crop rotation as a factor in the optimization equation, an innovative method is presented in this study. In this method, the matrix of crop rotation impact coefficient matrix was completed through the knowledge-base of an expert farmer. The values ​​of this matrix show the coefficients of impact of cultivation of each crop after another crop. Also, to evaluate the effect of rotation, according to farmers, seven different rotations with wheat, potato, corn, barley and fallow crops were studied. The study area is Shavoor irrigation and drainage network in Khuzestan province. The results of the rotation effect showed that in different rotations, the yield of wheat increased by 9.6%, corn by 3.3% and barley by 11.4%, which increases the profit per crop. Also, reviewing superior rotation with other rotations, the results showed that the presence of fallow in rotation and the use of appropriate rotation with selected plants, can increase the profitability of the crop unit.

Currently, most parts of the world face a serious water supply challenge, with limited access to freshwater resources of good quality. In addition to reducing the damage caused by the discharge of raw wastewater in the environment, wastewater treatment and re-use can help in providing one part of the water need. The use of wastewater for various purposes can have many social, economic, and environmental impacts if not managed properly, even though it is a tool against water shortage. This research by using a multi-criteria decision-making process is a comprehensive study of the effective criteria for the possibility of using wastewater for various purposes. Criteria include environmental, social, economic, and sub-criteria including water storage, reduction of pollutants discharged into the environment, health risks, cooperation between institutions and government, food security, public acceptance, wastewater quality, investment opportunities, revenue generation, feasibility. Combined with the Analytical Hierarchy Process (AHP) technique and pairwise comparisons and relies on the judgments our study shows that the best use of wastewater can be found in the agricultural, industrial, environmental, urban, impoundments, groundwater recharge sectors for non-drinkable usages and indirect usages for drinkable items. and non-volatile uses and indirect use for potable.

Proper soil hydraulic functions that accurately predict soil water characteristic curve and hydraulic conductivity are essential for studies of unsaturated flow in soils. In this study, 8 soils from different texture classes of UNSODA soil bank were selected and the optimal validity of shape factor (n) of the RETC software (using retention curve function of van Genuchten-Mualem (VGM) model) was investigated for predicting the value of unsaturated hydraulic conductivity at different moisture contents. Since the predicted results of this model were poor, we attempted to investigate a separate shape factor such as  for the hydraulic conductivity-moisture (K-θ) function of VGM Model. To this end, 24 soil samples from different texture classes of UNSODA were selected and their measured parameters were analyzed by regression analysis to find a suitable pedotransfer function for estimating . The developed function confirmed the relationship of  with both saturated moisture (θs) and organic matter contents with a correlation coefficient of r = 0.745 at significant level of P = 0.0005. Also, to validate the developed pedotransfer function, the hydraulic conductivity values ​​corresponding to the measured moistures for the 8 selected soils in the validation section were calculated based on the two shape factors obtained from the pedotransfer function ( ) and the RETC (n) and the results were compared with the measured values. The statistical indices of root mean square error of model (RMSEM) and Nash-Sutcliff model efficiency coefficient  (NSE) showed that the shape factor of the developed pedotransfer function compared to the RETC, had a better performance in predicting unsaturated hydraulic conductivity values.

One of the main causes of the water crisis in Iran is the lack of a well-organized framework for providing information about water balance components and water uses. Therefore, the use of a water accounting framework is a necessity. The purpose of this study is to show the capacity of the WA + framework for the preparation of water accounts in Rokh-Neishaboor basin, which is presented in four main sections: Organizing information, reporting, planning and assessing. The Organizing information section includes the collection of data from various sources, including of satellite measurements and modelling. The planning section include scenario development that in this study, two scenarios of reducing aquifer withdrawals were considered which were in line with the approvals of the Supreme Water Council. Reporting was done by completing various WA + sheets for three years inculding wet, normal and dry under real and scenario conditions. The assessing section was presented by the indicators for each sheet and for real and scenarios conditions.The results of the water situation in the basin showed that in Rokh-Neishaboor basin, a sharp drop in aquifer storage occurs every year. Also, about 80% of rainfall in the basin evaporates and becomes unavailable. Finally, the findings of using scenarios to reduce aquifer withdrawals (according to aquifer restoration plan( showed that if the aquifer withdraw was equal to renewable water, the annual aquifer deficit would reach zero and its reserve would increase.

Actual evapotranspiration (ET) is one of the most important and complex components of the water balance. In recent years, various remote sensing techniques and algorithms have been developed which provide a cost‐effective and reliable estimate of actual ET. In this research, the spatial distribution of actual ET at the basin scale was estimated based on SEBS algorithm and world-known information data sources which are rarely used in Iran. The estimated actual ET values were compared to the results of well-known SEBAL algorithm and the SWAT hydrological model. The study shows that the SEBS algorithm has overestimated actual ET in comparison with SEBAL algorithm. The primary cause of differences between two models is in their algorithms for calculating sensible heat. Moreover, SEBS algorithm is highly sensitive to the air temperature. SEBAL is a more complex and reliable method, but it needs reliable ground-based weather data. On the other hand, SEBS does not depend on ground-based data and its results could be acceptable under limited data condition.

For estimating evapotranspiration of landscape, in addition to vegetation coefficient, coefficients related to microclimate, plant density adjustment and specific plant species adjustment must also be calculated. In this study, using Landsat 7 satellite images and Mashhad Synoptic Station data, the actual evapotranspiration of landscape was calculated then, using climatic and environmental parameters obtained from satellite images and Seabl model, a relationship between microclimate coefficient and air temperature as well as relationship between density coefficient and normalized difference index of vegetation was established. Finally, the obtained relationships were evaluated by field monitoring of soil moisture in Ghadir Park of Mashhad. By determining the locations of field locations on the satellite image the relationship between NDVI index and the landscape density coefficient was investigated. The results showed that the best model presented using linear regression as Kd = 0.9941 * NDVI + 0.5058 with a correlation coefficient of 0.98 that the maximum percentage of error between calculated evapotranspiration for landscape using extracted relationships and measured values from moisture weight monitoring is less than 24%. due to severe water deficit in the forest landscape and insufficient water availability of the plant, evapotranspiration calculation using the Sabal model is inappropriate and has many errors. Therefore, instead of using the Sebal model, the extracted relationships can be used to determine the vegetation coefficients and the water requirement of urban landscape.

Iran's water situation has reached a critical level due to frequent droughts and over-abstraction of water resources. Therefore, dealing with the optimal allocation of water resources in these conditions is an important and vital issue. In the present study, the model of water resources allocation in critical conditions has been developed and the proposed model has been implemented in Mashhad. The innovation of the proposed model of the present study is to consider the sustainability of water resources and simultaneously pay attention to the quantity and quality of water resources. In this study, considering the stochastic value of available water parameter, two-stage stochastic allocation model is presented and solved by the method of Goal Attainment, and implemented in MATLAB software. This model has been developed with the aim of maximizing the profits of different users, minimizing the allocation of saline water from the underground source and minimizing the shortage of water. The results of the study indicate that even in the wet scenario, available water resources cannot meet the demand of different sectors. If the stability index is maintained at 75%, the amount of water shortage in the drought scenario is equivalent to 501.75 MCM, in the normal scenario is equal to 358.75 MCM, and the in the wet scenario is equal to 78.75 MCM. In addition, the sensitivity analysis of the model with different data indicates that if in the drought scenario, the amount of available water from both surface and treated water sources is equivalent to 300 and 200 MCM, respectively, then the optimal allocation pattern has changed and the amount of water shortage that can lead to overdraft is 103.75 MCM.

Deteriorated quality and scarcity of water are two serious problems and the water resources management corresponding to these problems is often accompanied by conflict between consumers. The purpose of this study is to analyze the behaviors and interactions of stakeholders in the Karaj basin in order to provide optimal strategy in sustainable policy-making of water resources in this basin with respect to environmental protection. In this study, definitions of stability were used to analyze the results of the Graph model in non-cooperative game theory. Players include the Ministry of Agriculture, the Regional Water Company, the Farmers and the Department of Environment. The results of the Graph model showed that among the definitions of stability used in this study, Non-Myopic stability analysis is reliable for the analysis of this game and the output of this stability is more likely to occur in the behavior of players. One of the most desirable equilibrium states is the basic situation and the other equilibrium state is the situation in which farmers perform unauthorized withdrawals of irrigation canals, in which case an undesirable situation will occur in the future. Therefore, the water resources management in the basin can be improved by determining incentives from the regional water company for the cooperation of farmers and their training, as well as identifying and punishing violators. Finally, the results showed that using appropriate stability definitions can provide valuable insights for policy-making to analyze specific conflict, when there is uncertainty about player behavior.

Surface water resource planning requires estimatiof of water balance components at different spatial and temporal scales. Moreover, due to the inadequacy of the stations in terms of number, dispersion and temporal data recording, numerical modeling of land surface is necessary. In this study, the Noah-MP model was used to compare the simulated runoff by SIMTOP and BATS schemes and to evaluate the dynamic vegetation scheme for estimating actual evapotranspiration in Neishaboor watershed at monthly scale in 2000-2009. Due to low accuracy and dispersion of hydrometric stations, the SWAT model output was used for evaluation. In order to develop the model, first, the sensitivity analysis of the modeled runoff to parameters of model was performed. The model showed the highest and least sensitivity respectively to the soil parameter in the Clapp-Hornberger relation (b) and runoff decay factor (f), respectively. the best and first performance of simulated runoff by BATS scheme were in mountainous areas and the evaluation criteria including R2, NSE and RMSE were respectively 0.81, 0.64 and 1.91. The second grade of performance was for the plain and The lowest values for simulated runoff were in foothills regions. Results indicate that BATS scheme shows better results in the plain and foothills areas and the results of SIMTOP scheme in the mountainous regions were similar to BATS results. The dynamic vegetation scheme has been able to simulate evapotranspiration changes along with the stages of plant growth. the mean of annual evapotranspiration estimated by Noah-MP model was 305 mm.

In this study, MODFLOW and MT3DMS codes were used to evaluate changes in groundwater quality in Neyshabour plain under different scenarios. During developing the conceptual model, it was found that the aquifer salinity increased due to the presence of fine alluvium and evaporite minerals in the margins of the plain and agricultural return flow. Groundwater models was calibrated under transient condition for 10 years from October 2001 to September 2011 and validated for a 4-year period (October 2011 to September 2015). Quantitative comparison of the head and Cl data in all the observation points indicated a reasonable match between the observed and the calculated values. The root mean squared error (RMSE) was 1.92 m and 1.65 m for the calibration and validation periods in the flow model, and the RMSE was 2 mg/l for the mass transport model in Neyshabour aquifer. The MODFLOW and MT3DMS models were used to simulate the effect of the two scenarios: (1) continue the current trend in groundwater withdrawals and (2) 40% reduction in groundwater withdrawals has been examined by the model. In the first scenario, the average groundwater level showed annual loss of 0.79 m and increasing in the groundwater salinity. Under the second scenario, which aimed to achieve equilibrium status in the groundwater balance, pumping rate for all wells were reduced by 40%. The results showed that although the average water level in the aquifer does not decrease, the groundwater salinity is still increasing, with a rate of 50% lower than in comparison to the first scenario. This reflects the fact that reduced groundwater withdrawals at the same rate for all wells may not meet water resource management goals and groundwater management requires distributed information about the aquifer

Sophisticated social- ecology systems, such as those in water management in a basin, are usually dynamic, multidimensional, or multidimensional, requiring serious engagement by multiple actors, and decision making in such systems is always faced with serious problems Kashafrood basin in Khorasan Razavi province is one of the most critical aquifers in the country due to the high population growth, high economic development, water scarcity and non-integrated allocation of water resources. In this regard, the best way to manage water is to create constructive interaction between actors involved in the basin. To this end, the present study has been conducted with a collaborative approach to provide a framework for identifying, analyzing and participating key actors in the decision-making process of this catchment area. This collaborative framework has two parts. The first part is the analysis of over 60 activists using the snowball method and the power-interest matrix, and the second part involves the involvement of key actors using the Circle of Influence Models (CI) and IAP2. The results of this study have led to the development of a common perspective on horizon 1420, in which the basin will have a sustainable balance in resources and water consumption. Under this vision, 19 strategies, 63 macro policies and 232 micro policy (executive), 41% of these policies have a social nature. The evaluation of the policy questionnaire, the implementation and effectiveness of the policies has shown that the majority of key actors in the basin have agreed on a high consensus on the implementation and effectiveness of those policies to achieve a common vision. According to the results of this research, the coherent framework presented can serve as a basis for identification, prioritization, analysis and collaboration of actors in order to increase their level of collaboration in the process of water management decision making in the basin of the country.

The growing population of the world, particularly in the developing world, on the one hand, and the need to provide food for this over expanding population on the other, has had nothing but an overwhelming harvest of resources. To chase the United Nations' sustainable development goals, researchers have developed a variety of interdisciplinary approaches to achieve some kind of dynamic balance in the production and consumption of resources. The most important of those goals are Water, Energy, and Food (WEF) Nexus. WEF nexus management with the aim of water and energy security requires integrated approaches to analysis to be able to plan appropriately and cost-effectively. Iran, with its arid and semi-arid climate and limited water resources, nowadays needs more water, food and energy security than ever before. Considering the importance of the issue, one of the most critical plains of Iran, the Mashhad study area, is discussed. This study area attracts the attention of many executives and policymakers due to metropolitan Mashhad city with a significant population (fixed and variable). In this study, the WEAP software was used for water and food resources management and LEAP software for energy sector management. Two scenarios were considered to assess the WEF Nexus approach. The first scenario defined the interaction of resources and consumption without considering the WEF Nexus approach and the second scenario with the WEF Nexus approach. After reviewing and comparing both scenarios results, it is concluded that the condition of the study area is much more critical by considering the WEF Nexus approach than the Non-WEF nexus approach.

Fuzzy methods in simulating water flow in to the soil has attracted the attention of researchers because of the possibility of considering the uncertainty and variability of the parameters in this methods. The sensitivity of the fuzzy model is to find the balance between the accuracy of the fuzzy model and its speed of execution, which depends on the number of fuzzy rules. Therefore, our goal in this research is to investigate the effect of the number of fuzzy rules on the accuracy of the model. In order to achieve this, the fuzzy model for predicting water movement in unsaturated soil was evaluated by considering fuzzy sets with different supports and consequently different rule numbers. The rules of the fuzzy model were derived from the large training sets obtained by numerical solution of Richards equation by using HYDRUS-1D model. The results showed that increasing the number of fuzzy rules initially increased the accuracy of the model (NRMSE value decreased from 4.3 to 3.1 and maximum error value from 0.128 to 0.09 for fuzzy model with 9 and 49 rules, respectively but by increasing the number of input fuzzy sets and increasing the rules to 81, the accuracy of the fuzzy model was reduced. The reason for the reduced efficiency of the fuzzy model is rules overlap.