Irrigation
E. Rezaei; M. Montaseri; H. Rezaei
Abstract
Introduction: Prioritization of optimal water allocation of surface flow storage dams for different applications (drinking, agriculture, industry, environment, etc.) in arid and semi-arid regions such as Iran due to the range of changes, high flow uncertainty Reservoir inlets, and the occurrence of intermittent ...
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Introduction: Prioritization of optimal water allocation of surface flow storage dams for different applications (drinking, agriculture, industry, environment, etc.) in arid and semi-arid regions such as Iran due to the range of changes, high flow uncertainty Reservoir inlets, and the occurrence of intermittent droughts are of great importance. For this purpose, the Fuzzy Hierarchy Process (FAHP) is proposed and used as a suitable formulation method in prioritizing water allocation in the water resources system. Therefore, in this study, prioritization of water allocation for different purposes of Shahrchai reservoir dam located upstream of Urmia metropolis has been done in a field study using fuzzy hierarchical method.Materials and Methods: A fuzzy hierarchical process based on quantitative and qualitative effective factors has been developed. In the first stage, the problem structure was designed by determining the priority of water allocation of users, criteria, sub-criteria, and other factors. Then the decision-making hierarchy based on the problem structure (purpose, criteria, sub-criteria, factors, and options in the first to fifth levels, respectively) was defined. In the mentioned prioritization structure, the goal was determined at the first level, ie the optimal or appropriate allocation of Shahrchay reservoir dam water for different operators, and at the second level, three economic, social and environmental criteria were considered as the main criteria. At the third level, " cultivation area and gross income" and "employment and population" were considered as sub-criteria of two economic and social criteria, respectively. The main beneficiaries, namely agriculture, urban drinking, recreation and tourism, industry, environmental needs of Lake Urmia and groundwater fourth level (options) have formed the problem structure. At the next step, based on the field data or questionnaires, criteria, sub-criteria, and factors were compared in pairs using the proposed linguistic and fuzzy comparisons, and the priority of water consumption over each criterion or sub-criterion or factor were compared based on fuzzy triangular numbers. The weights were determined and ranked each using the Chang development method. At the third stage of the final ranking, the priority of water allocation was determined based on the final weight of criteria or priorities at the previous stage and the superior option was determined. Finally, a sensitivity analysis of the weight change of the criteria and the decision-making process of the problem has been performed.Results and Discussion: A decision model based on a fuzzy approach is presented to rank the different options using Shahrchay dam water. For this purpose, firstly, using the opinions of experts and researchers, the results of a questionnaire, criteria and sub-criteria and important options in allocating water to Shahrchai Dam were determined. Secondly, using Chang's development analysis, different options were evaluated based on the mentioned criteria, sub-criteria, and factors. From a scientific point of view, because the questionnaires were presented to experts, the economic criterion is a high priority, so it is possible to attach great importance to the general conclusion about the criteria in economic attitudes and related issues. In addition, the allocation of water to the urban drinking sector with a weight of 0.33 was as the top priority, agriculture, Lake Urmia, industry, groundwater, and recreation were in the next priorities, respectively. Therefore, economic criteria and drinking water supply were recognized as the main objectives of planning and managing water resources in the metropolis of Urmia. The drinking sector is a vital factor for the survival of a community and because the drinking water of Urmia city is supplied through Shahrchai dam, so the allocation of water to this sector should be considered as the top priority. The agricultural sector was also given the second priority with less importance. The supply of water to this sector has a significant direct effect on the economy of the agricultural sector and indirectly on the entire economy of the region, which indicates the importance of the agricultural sector in the economy, living conditions of the region and the allocation of water to this sector. Comparing agricultural and industrial activities in Shahrchai catchment area, the most activity in the region is agriculture and industry is in a lower priority, which is also shown by the hierarchical results. Since Shahrchai River is one of the suppliers of water to Lake Urmia, the allocation of water to this section improves the condition of the lake and, consequently, it improves the environmental, economic, and social conditions of the region. The results also indicate the importance of Lake Urmia in relation to industry and its higher status indicates the attention of officials to the drying crisis of the Lake Urmia.
M. Montaseri; B. Amirataee; H. Rezaei
Abstract
Introduction: Drought is a natural phenomenon and was described when precipitation is less than expected. Since the precipitation amounts in terms of spatial and temporal characteristics are different from one region to another, so this phenomenon is known as a multivariate phenomenon. This phenomenon ...
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Introduction: Drought is a natural phenomenon and was described when precipitation is less than expected. Since the precipitation amounts in terms of spatial and temporal characteristics are different from one region to another, so this phenomenon is known as a multivariate phenomenon. This phenomenon often characterized by different variables such as drought duration, severity, intensity and spatial extent. Although site specific analysis can provide useful information on drought occurrences in a limited area, but these results have a fundamental uncertainty to drought risk assessment in a large region. Therefore regional drought analysis, provides a more comprehensive assessment in each region, and is essential for short and long term management of water resources. Meanwhile, the copula functions has been developed as a new advanced technique for modeling the two or multivariate joint probability distribution in different fields such as financial, hydrology, water resources and risk management. So, in this research, regional analysis of drought severity and percent of drought area were performed using the copula functions in Lake Urmia basin, as one of the Iran's drought-prone basin. Such study with emphasis on bivariate analysis of drought severity and drought areal extend were conducted for the first time in the study area. The main objectives of this study are: 1) Modeling drought characteristics in Lake Urmia basin, 2) Evaluation of copula functions in modeling the structure of the region's drought characteristics, and 3) Develop the Severity-Area-Frequency curve using the appropriate copula.
Materials and Methods: Copula is the stochastic model and based on probability. In other words, copulas are function for modeling the two or multivariate random variables. Copulas can be easily coupled the marginal distributions to multiple distributions. There are many parametric copula families available, that seven copula functions such as archimedean (Clayton, Frank, Gumbel and Joe), extreme value (Galambos), elliptical (Normal) and others (Plackett) were used. The SPI-1 was determined at each station and then, the whole area was divided into small grids with cell size of 2000×2000. Distances between the grid centers with all the selected stations were calculated with a programming code. Finally, the SPI values in each grid were calculated using IDW method. The severity and percentage of drought area variables were determined and used for regional drought modeling in the study area based on drought threshold equal to zero. After determining the best statistical distribution of two variables, the appropriate copula function was conducted based on different goodness of fit tests. Finally, the Severity-Area-Frequency curve for the study area was developed based on the appropriate copula function and conditional return periods.
Results and Discussion: The correlation between the two variables of percentage of drought area and severity was assessed using different graphical (Kendall plot and Chi plot) and statistical tests (Spearman rand order correlation and Kendal tau). The results showed a positive correlation between the drought severity and percentage of drought area variables. Based on Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) and graphical test, the Lognormal and Beta probability distributions were select as a best fit distribution of severity and percentage of area under drought, respectively. Finally, the Frank copula among other type of copulas was selected as an appropriate copula for modeling joint drought severity and percentage of area under drought for the study area based on Maximum log likelihood, AIC, BIC and RMSE criteria. The S-A-F curve was developed using conditional return periods based on Frank copula. According to S-A-F curve, it can be seen that increase in the percentage of area under drought in the study area led to increase in drought severity and vice versa. For example, drought severity with return period of 20 years and drought with 20 percent areal extend is obtained equal to 0.37.
Conclusions: Copula functions are of great importance in the analysis of drought, due to preserve correlation between variables and not have any limitation to have a same marginal distribution in long-term prediction of drought events. In this study, using best fit copula (Frank copula) and conditional return periods, the relationships between drought severity and percent of area under drought for the study area named S-A-F curve were developed. These curves can be useful for planning and management of drought in the region. Drought risk assessment based on the results of this study can be high priorities for drought monitoring in large areas.
Alireza Moghaddam; Majid Montaseri; Hossein Rezaei
Abstract
Introduction: The reservoir operation is a multi-objective optimization problem with large-scale which consider reliability and the needs of hydrology, energy, agriculture and the environment. There were not the any algorithms with this ability which consider all the above-mentioned demands until now. ...
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Introduction: The reservoir operation is a multi-objective optimization problem with large-scale which consider reliability and the needs of hydrology, energy, agriculture and the environment. There were not the any algorithms with this ability which consider all the above-mentioned demands until now. Almost the existing algorithms usually solve a simple form of the problem for their limitations. In the recent decay the application of meta-heuristic algorithms were introduced into the water resources problem to overcome on some complexity, such as non-linear, non-convex and description of these problems which limited the mathematical optimization methods. In this paper presented a Simple Modified Particle Swarm Optimization Algorithm (SMPSO) with applying a new factor in Particle Swarm Optimization (PSO) algorithm. Then a new suggested hybrid method which called HGAPSO developed based on combining with Genetic algorithm (GA). In the end, the performance of GA, MPSO and HGAPSO algorithms on the reservoir operation problem is investigated with considering water supplying as objective function in a period of 60 months according to inflow data.
Materials and Methods: The GA is one of the newer programming methods which use of the theory of evolution and survival in biology and genetics principles. GA has been developed as an effective method in optimization problems which doesn’t have the limitation of classical methods. The SMPSO algorithm is the member of swarm intelligence methods that a solution is a population of birds which know as a particle. In this collection, the birds have the individual artificial intelligence and develop the social behavior and their coordinate movement toward a specific destination. The goal of this process is the communication between individual intelligence with social interaction. The new modify factor in SMPSO makes to improve the speed of convergence in optimal answer. The HGAPSO is a suggested combination of GA and SMPSO to remove the limitation of GA and SMPSO. In this paper the initial population which caused randomly in all metha-heuristic algorithms consider fixing for the three mentioned algorithms because the elimination of random effect in initial population may make increase or decrease the convergence speed. The objective function is the minimum sum of the difference between the downstream demand reservoir and system release in the period time. Also the constrains problem is continuity equation, minimum and maximum of reservoir storage and system release.
Results and Discussion: The performance of GA, SMPSO and HGAPSO evaluated based on the objective function for Dez reservoir in the south east of Iran. In this study the programming of GA, SMPSO and HGAPSO was written in Matlab software and then was run for the time period with a maximum of 400 iterations. The minimum of the objective function for GA, SMPSO and HGAPSO was obtained 1.19, 1.05 and 0.9 respectively, and the maximum of objective function was calculated 1.66, 1.26 and 1.10 respectively. The results showed that the minimum of the objective function by HGAPSO was estimated 32 and 16 percent lower than the counts which calculated by GA and SMPSO. The standard deviation of SMPSO and HGAPSO were near to each other and less than GA which shows the diversity between solutions for SMPSO and HGAPSO are much less than GA. Also the HGAPSO had the better performance rather than previous method in terms of minimum, maximum, average and standard deviation. The convergence speed of HGAPSO for finding the optimal solution is much faster of GA and SMPSO. The difference graphs between system release and monthly demand in HGAPSO is much less than GA and SMPSO. Also the storage calculated in HGAPSO and SMPSO is highly close to each other but in GA method the storage calculated more in the first and second years.
Conclusions: The convergence speed in finding the optimal solution in SMPSO in more than GA but in other hand the probability of caughting in local optima for SMPSO is great whereas GA can make the diverse optimal solutions. For this reason, in this paper was trying to improve the performance of the GA and SMPSO and remove their disadvantage based on combining them and presenting a new hybrid method. The results showed the HGAPSO method which presented in this paper to use without any complexity and additional operator to GA and SMPSO has the ability to use for reservoir operation with large-scale. In addition it is suggested which the HGAPSO apply to other water resources engineering problems.
majid montaseri; Negar Rasouli Majd; Javad Behmanesh; Hossein Rezaei
Abstract
Introduction: The water footprint index as a complete indicator represents the actual used water in agriculture based on the climate condition, the amount of crop production, the people consumption pattern, the agriculture practices and water efficiency in any region. The water footprint in agricultural ...
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Introduction: The water footprint index as a complete indicator represents the actual used water in agriculture based on the climate condition, the amount of crop production, the people consumption pattern, the agriculture practices and water efficiency in any region. The water footprint in agricultural products is divided to three components, including green, blue and gray water footprint. Green water footprint is rainwater stored in soil profile and on vegetation. Blue water refers to water in rivers, lakes and aquifers which is used for irrigation purposes. Gray water footprint refers to define as the volume of contaminated water. The water footprint in arid and semiarid regions with high water requirement for plants and limited fresh water resources has considerable importance and key role in the planning and utilization of limited water resources in these regions. On the other hand, increasing the temperature and decreasing the rainfall due to climate change, are two agents which affect arid and semiarid regions. Therefore, in this research the water footprint of agriculturalcrop production in Urmia Lake basin, with application of climate change for planning, stable operating and crop pattern optimizing, was evaluated to reduce agricultural water consumption and help supplying water rights of Urmia Lake.
Materials and Methods:Urmia Lake basin, as one of the main sextet basins in Iran, is located in the North West of Iran and includes large sections of West Azerbaijan, East Azerbaijan and Kurdistan areas. Thirteen major rivers are responsible to drain surface streams in Urmia Lake basin and these rivers after supplying agriculture and drinking water and residential areas in the flow path, are evacuated to the Lake. Today because of non-observance of sustainable development concept, increasing water use in different parts and climate change phenomena in Urmia Lake basin the hydrologic balance was perturbed, and Urmia Lake has been lost 90% of its volume and has a critical condition. Therefore, planning, managing and optimizing utilization of water resources in the basin have a high research priority and this requires the concentration on the consumption of water resources. In this study five major products including, wheat, sugar beet, tomato, alfalfa and corn, were studied. For this purpose, seven synoptic meteorological station data including,Salmas, Urmia, Mahabad, Takab, Tabriz, Maragheh and Sarab were used to calibrate the downscaling atmospheric-ocean general circulation model LARS.WG5 and forecast meteorological data in the future periods time (2011-2030) and (2046-2065) with the A2 scenario.The reason to selectA2 scenario was the most critical situation for the mentioned scenario. Then the obtained data were used to estimate the water requirement and water footprint of mentioned plants separately blue and green water footprint in the future periods.
Results and Discussion:The resultsof themeteorological data prediction showed thatall synoptic stations except for Tabriz station the average annual predicted rainfallvalues had the deviationfromhistoricalvalues.The mentioneddeviation in the south (Tekab, Mahabad) and West (Urmia, Salmas) ofUrmia lake basin will showincreaseanddecrease in theannual rainfallin the future, respectively.Moreover,the average annual of predicted temperature values for all studied stations showed that the temperature will increase about1°Cduring2011-2030 period and 2°C during 2046-2065 period. Potential evapotranspiration, as another important meteorological parameter has essentialrole in the estimation of crop water requirements which will be slightly affected by climate change phenomena and it will increase in the summer. The results of agricultural products water footprint show that the maximum amount of green water footprint in all studied stations was related to wheat and alfalfa, and this water footprint depend on the time and growth period. For corn, tomatoandsugar beetproducts the ratio of blue and green water footprint is greater 9. By comparing the water footprint of products it can be seen that in Urmia, Salmas and Tekab stations water footprint is decreased with decreasing rainfall and this decrease during 2065 – 2045 periods is higher than 2030 – 2011 periods.
Conclusions: According to the results, annual precipitation in southern and western regions of the Lake Urmia basin will be increased and decreased, respectively in the future periods. However, increasing approximately one Celsius degree in temperature is expected for each of the periods all over the basin. In addition,the results showed that the amount of potential evapotranspiration will be increased in the warm months (June to September) in the future periods, and agricultural water consumption pattern will be changed affected by evapotranspiration variations. In the future periods, the blue and green water footprint of most agricultural products will be increased and decreased, respectively.
H. Rezaei; J. Behmanesh; S. Besharat
Abstract
With respect to necessity of the optimum use of water resources and existence of many various optimization methods, in this study 3 kinds of heuristic algorithms have been used including Particle Swarm Optimization, Genetic Algorithm and Simulated Annealing to optimize the operation of Shaharchai dam ...
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With respect to necessity of the optimum use of water resources and existence of many various optimization methods, in this study 3 kinds of heuristic algorithms have been used including Particle Swarm Optimization, Genetic Algorithm and Simulated Annealing to optimize the operation of Shaharchai dam reservoir as an application. The optimization was carried out considering the probability of inflow for a period of 5 years. In order to obtain the best operation of reservoir, monthly release was defined as a second order polynomial according to storage volume and inflow, and different parameters of these algorithms have beenadjusted to minimize the objective function in which supplying the required demand of downstream was defined as the target. The best state of each algorithm is selected through 10 times running of programs (due to intrinsic random behavior of algorithms) and the results comparison leads to realization of which method can perform the best. According to the results, Particle Swarm Optimization method operates more effectively and produces the best results in solving reservoir operation problems. So as an application, control curves of release and storage volume have been extracted for Shaharchai dam reservoir using this method.
