جستجوی مقالات مرتبط با کلیدواژه « برنامه ریزی خطی » در نشریات گروه « آب و خاک »

In recent years, the conflict between environmental interests and farmers' livelihoods has emerged as one of the most crucial issues in the environmental and agricultural governance of the Zayandeh-Rood watershed. Hence, achieving a balance between economic profitability through the use of an optimal cropping pattern and preventing the excessive extraction of groundwater resources holds great importance for policymakers in this field. In this study, the environmental function was modeled by considering water resources limitation, while the economic function was modeled based on the economic profit derived from the cultivated crops in Kohpayeh-Segzi Plain in 1996-2011. The Nash function was optimized by using constrained nonlinear optimization by taking into account the limitation of water resources in each year. After optimizing the Nash function, the cropping pattern was determined using both game theory (GT) method and linear programming (LP) method. Results indicated 30% reduction in water consumption with the GT and 17% reduction with the LP method. Additionally, the profit reductions for these two methods were 16% and 3%, respectively, compared to the base case. Furthermore, the results revealed that the groundwater level in the representative hydrograph of the plain decreased by 3.94 and 2.23 m in the GT and LP methods, respectively. Conversely, in the optimized GT method with an economic function weight of 0.5, the groundwater level of the plain increased by 8.67 m. Considering the reduction of water consumption, profit reduction, and the increase in groundwater level, the optimized GT method with a weight of 0.5 was superior to the LP method.

This study is conducted with the aim of determining the optimal cultivation pattern based on the concept of virtual water and considering the objectives of minimizing virtual water consumption and maximizing economic profit of the products in Omrani plain of Gonabad as a case study. At first, the optimization problems are defined by defining appropriate objective equations, and limitations based on different constrains such as available water or local and regional policies. Then, by using linear and multi-objective programming in MATLAB software, the appropriate cultivation pattern was determined. Next, using GIS, the optimal crops were allocated to different farmland in the region. Results showed that the best policy was a combination of the two-objective including minimizing virtual water and maximizing economic profits. In this case, the amount of virtual water consumption in the region was reduced by more than 57% which is considerable. Also, even with this consumption of virtual water, the higher economic benefit is achievable if the pattern of cultivation is changed.

Optimal operation of dam reservoirs is one of the important issues in the field of water resources management. In this study, optimal operation of dam has been investigated in a deterministic and probabilistic manner in order to supply maximum water demands of the dam downstream. The optimal allocation conditions of the system are examined by considering the probabilistic inflow and investigating the effect of cumulative distribution function on meeting the water demands. The chance constrained linear programming method has been used in the uncertainty approach for reservoir inflow. The study area is considered in Gheshlagh Dam located on Maryam-Negar River in Kermanshah province. Water supply optimization of water demands on downstream has been presented by using coding in LINGO software environment in two different modes. The results of optimization by deterministic approach show that the supply in the agricultural, domestic, and environmental water demands are 92%, 95% and 95%., respectively. In the probabilistic approach, considering the uncertainty in the inflow to the reservoir in two different ways, the results showed that not only is it not necessary to choose the best statistical distribution model of the inflow to the reservoir and the experimental distribution of Weibull is sufficient for this purpose, but also due to the reduction of the inflow volume to the reservoir, the optimal volume of the dam reservoir with a confidence level of 60% was estimated to be equal to 27.3 MCM. In this volume, the dam reservoir is fully able to supply the downstream demands of Gheshlagh Dam. Therefore, due to the uncertainty of the precipitation phenomenon, consequently the inflow to the dam reservoir and the obtained results, this approach is essential in the design and optimal use of dam reservoirs.

Suitable planning for the use of limited water resources can increase the production of agricultural crops effectively. In this research, optimal cultivation areas were determined based on reservoir volume and available water scarcity conditions in Arasbaran plain. At first, the net benefit from cultivation in the period (2002-2011) obtained using the Stewart model and the region economic values. Optimal water allocation program was run using the linear programming for each time period of year for maximizing the net benefit objective function considering the restrictions. Optimization performed for five scenarios of available irrigation water (NIV) and for each of them, optimal annual cultivated areas for the proposed plants were obtained. By optimizing the annual cultivated areas, a constant optimal form was also obtained for the region. The results showed that the net benefit changes per unit volume of water, decreased with the increase of available water in both cases as a second degree curve and in all NIVs the benefit of the variable cultivated area was 7% higher. Also, the total net benefit of the annual optimal cultivated area for available water of 8 million cubic meters was 8% more than the fixed cultivated area, and for 10 to 16 million cubic meters, this value increases linearly from 11% to 18%, that shows the relative superiority of the variable optimal cultivated area without considering the management benefits of the fixed mode such as design, irrigation and mechanization.

The groundwater level of Silakhor plain has decreased significantly with the occurrence of successive droughts, industrial growth and increasing water needs. In addition, the cultivation pattern of the region in recent years has tended to cultivate water crops, and the combination of these events raises the need for efficient management in the allocation of limited water resources in the region. In this study, in order to sustainable management of groundwater resources, the optimal cultivation pattern of major crops in Silakhor plain has been determined, with the aim of maximizing farmers' net income and available water and land constraints. In this regard, two approaches to using Linear Programming (LP) and using Multi-Objective Meta Heuristic Algorithms in different exploitation scenarios have been investigated and the performance of different penalty functions in algorithms has been evaluated. Also, how to change the optimal cultivation pattern by increasing groundwater exploitation has been studied.

In the first step, after modeling the rainfall of the last 10 years using Artificial Neural Network (ANN) and Genetic Programming (GP) and selecting a better model in terms of accuracy, rainfall for the next three years was forecasted and groundwater recharge was estimated. Then, for each crop year, 100 different exploitation scenarios were considered according to the groundwater recharge and water exploitation in previous years. In the second step, using LP with the aim of maximizing farmers' incomes and available water and land constraints, the optimal cultivation pattern was obtained in the determined exploitation scenarios. Finally, in order to unbound the problem, the mentioned constraints were implemented as static, dynamic and classified dynamic penalty functions in MATLAB software. Then, the performance of three algorithms NSGA-Ⅱ, SPEA-Ⅱ and PESA-Ⅱ with the objective functions of maximizing farmers' incomes and minimizing penalty functions, to achieve the optimal cultivation pattern obtained from LP was examined.

The results of this study indicate that although with the increase of groundwater exploitation, farmers' incomes increase in the optimal cultivation pattern; However, in the exploitation of more than 223.5, 222.2 and 225.1 million m3 for the cropping years 2020-2021, 2021-2022 and 2022-2023, respectively, the limitation of the total arable land in Silakhor plain prevents the increase of crop cultivation and the area under cultivation of crops remains constant and consequently the income of farmers does not change. The results of the study of algorithms and penalty functions also show that in this problem, the best performance among the algorithms belongs to SPEA-Ⅱ, PESA-Ⅱ and NSGA-Ⅱ algorithms, respectively, with an average number of iterations of 12.1, 14.5 And is 17.8. Among the penalty functions in all three algorithms, the best performance belongs to the classified dynamic, dynamic and static penalty functions with an average number of repetitions of 13.1, 13.7 and 17.5, respectively.

In general, it can be seen that the optimization of the cultivation pattern in different exploitation scenarios provides a comprehensive view to the authorities for the sustainable management of valuable and limited water resources and its optimal allocation. In this regard, the use of SPEA-Ⅱ algorithm with classified dynamic penalty function in determining the optimal cultivation pattern leads to desirable results.

The occurrence of successive droughts, along with increasing water needs and lack of proper management of water resources has caused a water crisis that has various environmental and economic consequences. In addition to the drought, the change in the cropping pattern towards water crops has also made the water crisis the first critical phenomenon in recent years in the community, which has a direct impact on the agricultural sector as the largest consumer of water. Therefore, optimizing the cropping pattern is one of the most important factors in managing water resources and coping with water shortages. In this study, to determine the optimal cropping pattern of major crops in Silakhor plain in the next three years using two approaches using Linear Programming and Meta-Heuristic Algorithms.

In the first step, in order to determine the optimal cropping pattern with the aim of maximizing farmers' incomes in the next three years and the limited water and land available, the amount of rainfall recharge is used as a criterion to determine the water exploitation interval and determine the minimum and maximum exploitation each year. In order to forecast rainfall, SARIMA time series models and Genetic Programming were used considering the data of the last 10 years in both seasonal and monthly modes, and according to RMSE and D.C. criteria, a better model was selected. Then, for each crop year, 100 exploitation scenarios were determined according to the amount of groundwater recharge caused by rainfall and the amount of exploitation in previous years. In the second step, Linear Programming was used to determine the optimal cropping pattern with the aim of maximizing farmers' incomes and limitations of exploitable water in each scenario and arable land. The price of each product is projected according to the average long-term inflation of the country, i.e., 20%, and the profit from the cultivation of each product was calculated as a proportion of the price of the product in each year by examining the previous years. Finally, the performance of three types of Static, Dynamic, and Classified Dynamics Penalty Functions into two algorithms, Differential Evolution and PSO was investigated to achieve the results obtained from Linear Programming. Static penalty functions use a constant value during the optimization process, whereas in dynamic penalty functions, the fines are modified during the process and depend on the number of generations. In the classified dynamics penalty, groups of violations are also determined, and the penalty of each response is determined according to the amount of violation of the restrictions and the generation number.

The results show that with increasing groundwater exploitation, farmers' incomes also increase; However, in the exploitation of more than 223.5, 222.2, and 225.1 million cubic meters for the cropping years 2020-2021, 2021-2022, and 2022-2023, respectively, the limitation of the total arable land has prevented the increase of the area under cultivation, and by increasing exploitation, farmers' incomes remain stable. Also, in order to cultivate four crops of wheat, barley, rice, and corn with the current area under cultivation in Silakhor plain, 142 million cubic meters of water is harvested annually from underground sources. By optimizing the cropping pattern for the four crops studied, with the current water exploitation, the income of farmers in the region will increase by 18%. In general, the PSO algorithm answers this problem much faster. The average number of iterations of the PSO algorithm to solve each scenario in this problem is 38% of the number of iterations of the Differential Evolution algorithm. Overall, in solving this problem, the PSO algorithm has performed better in 84% of the scenarios. In penalty functions, the best performance in both algorithms belongs to the classified dynamics, dynamic, and static penalty functions, respectively. By changing the penalty function from static to classified dynamics penalty function, the number of iterations of the Differential Evolution algorithm to achieve the Linear Programming solution is reduced by an average of 11%; In contrast, the PSO algorithm did not react significantly to the change in the penalty function, and its repetitions decreased by an average of only 3%.

The results show that the cropping pattern of the region is not optimal, and with the increase of water exploitation, it will move towards the cultivation of water products. Also, by optimizing the cultivation pattern of the region, farmers' incomes can be increased. Examination of Differential Evolution and PSO algorithms with three types of penalty functions also show that using the classified dynamics penalty function in the PSO algorithm can have good results.

Increasing water demand has become inevitable due to population growth, industrial development and agriculture. On the contrary, water resources limitation and observing sustainability have restricted water allocation. Therefore, supply of water for all demands is impossible. Overuse of groundwater and surface resources, rainfall reduction, drought in most parts of the world, as well as pollution of ground and surface water have severely lessened available water resources. So, using these vital resources, with sustainable manner, requires proper management. Demand management and water production are two effective approaches. But, water production projects are time-consuming and high-cost. So, water management models are appropriate tools for decision making to predict the future situation, with low time and cost. Mathematical techniques are useful tools for keeping the balance between environmental requirements and human demands, specifically for optimal utilization of water resources in complex applications such as watershed or aquifer management. Aiming to more comprehensive decision making, a combination of two powerful operational and research techniques, including simulation and optimization could lead to a possible sustainable and optimal economic management. This study was aimed to the simulate water policy in the Arazkuse watershed, Golestan province, Iran. In this regard, both system dynamics model and water balance relationships were applied. VENSIM as a system dynamics software was used to capture causal and consultative relationship among controlling factors, while water balance was applied to estimate availability of surface and subsurface water. As four sectors of water consumption (urban, industrial, environmental and agricultural) were considered in the current study, the data about landuse, cultivated crops in the watershed, hydrological information and drinking water consumption were gathered. Then, the water consumption was optimized in the agricultural sector, using linear programming technique with the two objectives of maximizing economic benefits and minimizing water consumption, by Lingo software. Finally, the effect of water optimization in the agricultural sector on the groundwater sustainability index of Arazkuse basin was investigated. The groundwater sustainability index represents the portion withdrawn water from the whole of aquifer reservoir.The infiltrated water volume and deep storage coefficient variables were used to evaluate available groundwater from the total groundwater and the total discharge of the basin during the simulation period. Accounting for as much as 75% of the water consumption in the basin is supplied from groundwater while for surface water this portion was 25%. In general, the total volume of annual available groundwater in the Arazkuse basin was about 75 million cubic meters whereas the total volume of available surface water equaled 155 million cubic meters. These values indicated that a large volume of surface water flows out of reach, which puts extra pressure on groundwater to meet the needs and may endanger the stability of the aquifer. Due to the amount of water supply and requirements by various sectors (including the drinking water, environment, agriculture and industry) the available water to each sector was calculated. A linear programming technique was used to optimize the allocation of water resources with an objective function of maximizing economic profit while minimizing water consumption in the agricultural sector. Flood irrigation is a common strategy for rice cultivation. Hence, irrigation efficiency in the studied watershed is lower than other watersheds which applied the irrigation methods such as drip and sprinkler systems. Considering the fact that about 32% of agricultural lands in Arazkuse watershed are dedicated for rice cultivation, to some extent could be concluded that it would be possible to increase irrigation efficiency, by improving conveyance and distribution coefficients. The results showed that although the available surface water was approximately double, provided water by groundwater supplied about 75% of the required water, especially for the case of agricultural needs. Despite the fact that runoff may be the source for a part of recharged water, a considerable amount of the available water exits in the form of runoff. Therefore, the supplied water for various sectors was linked to the excessive use of groundwater resources. Hence, the agricultural sector was the main water consumption that needed to be optimized. The assessment of the effect of optimization of agricultural water use on groundwater sustainability index showed under optimal condition of water required for agriculture the index shifted from 14.4 in the present condition to 1.9 for the new scenario.

Water scarcity is one of the major problems for farmers in arid and semi-arid areas, and theexcessive groundwater resources harvesting cause a decrease in groundwater level in aquifers. Therefore, planning for the optimal use of water resources by introducing appropriate cropping patterns, taking into account the maximum profit and minimum water consumption, is necessary. In this study, two methods of conventional linear and goal programming for the ideal planning of appropriate cropping pattern and the optimal harvesting of groundwater resources is presented in Gogan and Kordkuy cites located in Golestan province.

The cities of Gorgan and Kordkuy located in Golestan province, which are important agricultural sites, are considered as a study area in this research. After providing information on the area of cultivation, the cost of production and the price of sales of major agricultural products, net irrigation demand was calculated considering irrigation efficiency using NETWAT software. The mentioned data besides information on the potential of groundwater harvesting in both linear and goal programming were compared considering market constraints and the goals of increasing profits and reducing water use to optimize the cropping pattern and groundwater harvesting values.

The results showed that by using linear programming, water consumption in Gorgan and Kordkuycould be reduced by 19.6 and 8.8 percent, respectively, and the profit from agricultural production in Gorgan and Kordkuy cities will experience increase equal to 12.6 and 10.4 percent. Linear planning suggests that the products such as wheat, rice, potatoes and forage corn in Gorgan city and wheat, rice, rainfed spring soybean and summer cotton in Kordkuy while the goal programming suggests the optimized cropping pattern with an increase of 5 percent in profit and with a 45 percent reduction in water consumption. The results of goal programming showed that the cropping pattern in Gorgan city should be wheat, rice, tomato, and rapeseed while it should be wheat, rice and rainfed spring soybean in Kordkuy.

The outcomes of linear and goal programming hn this study for determination of optimal cropping pattern in Gorgan and Kordkuy cities show there is no optimal cropping pattern in the current condition. The results of this study indicate the possibility of a reduction in water consumption, as a valuable item in the study area, equal to 46 and 47 percent in Gorgan and Kordluy cities respectively with 5 percent increase in of profit in both cities.

Designing and implementing suitable cropping patterns are necessary to control the limiting factors and optimal utilization of available water resources. In the present study, cropping pattern optimization in Qazvin irrigation and drainage district has conducted considering the five levels of irrigation including I1, I2, I3, I4, and I5 (representing water allocation of 100, 90, 80, 70, and 65 percents of the crop evapotranspiration) and three different levels of cultivated areas including S1, S2, and S3 (representing, current cultivated area, 10 percents increase and 10 percents decrease in the crop cultivated area compared to the current conditions). Crops cultivation areas and water allocation were optimized using a linear programming method and the objective function was to maximize the benefit. The results indicated that the model in condition S2 allocated the most cultivation area to strategic crops and in condition S3 allocated the most cultivation area to economic crops. The condition S3I1 had the highest income (315 million rials) among the all scenarios. Water allocation alternative named I2, increased the economic productivity by average 0.82 million rials per cubic meter of water at all the cultivation area alternatives while maintaining income. Therefore, it was possible to allocate less cultivation area and a lower amount of water while earning more income. Also,  water allocation alternatives named I4 and I5 were not recommended due to reduced income and yield. Model had a limited cultivation area of water-consuming crops such as tomato, sugar beet, and the alfalfa under water shortage condition.

Existence periods of drought in the past decade, increasing growth of population, limitation surface water resources, cause the proper management of the reservoirs of dams. Operation of reservoirs is influenced by a lot of goals and generally many of these goals are incompatible with each other. The inflows to the reservoir and the storage volumes are uncertain which increases the operation of the complexity of the reservoir. The main challenge is to find the best release of the reservoir and hydrosystems optimization. Various optimization methods have been introduced for the operation of the reservoir. But some of these methods have disadvantages that use of them are not possible for all issues. Bozorg Haddad (2005) used Honey Bees Mating optimization for solving design problems and o The ant colony algorithm was also used to exploit a four-reservoir system in a discrete space that was able to optimize the problem with greater accuracy and less computing time than the genetic algorithm (Jalali et al 2007). Mousavi et al (2017) used the Harmony Search Algorithm to the optimization of water powerhouse storage projects and reported satisfactory results. Harmony search algorithm was presented by Geem et al for the first time in 2000. In this research Harmony Search Algorithm (HSA) is evaluated to determine the optimal operation of multi-reservoir systems. Then in order to evaluate the ability of the algorithm to solve real problems, the optimal operation of Dez Dam reservoir in Khuzestan province has been considered for a period of 10 years (1990-1992) with 120 months. In the single- reservoir issue of Dez Dam, the goal is to provide of agricultural demand of downstream or to determine the optimal monthly release for 10 years operation. The optimum value was obtained by using a linear programming model (Lingo). Lingo model has the ability to solve nonlinear models and provides the global optimum in some cases such as the intended problem where the objective function is convex. Therefore, the solutions obtained from the HSA model were compared with the solutions obtained from Lingo software program. A new heuristic algorithm derived from an artificial phenomenon found in musical performance namely the process of searching for better harmony can be introduced. Music harmony is a combination of sounds considered pleasing from an aesthetic point of view. Harmony in nature is a special relationship between several sound waves that have different frequencies. Musical performances seek the best state (fantastic harmony) determined by aesthetic estimation, as the optimization algorithms seek the best state (global optimum-minimum cost or maximum benefit or efficiency) determined by objective function evaluation. Aesthetic estimation find by the set of the sounds played by joined instruments, just as objective function evaluation find by the set of the values produced by component variables; the sounds for better aesthetic estimation can be improved through practice after practice, just as the values for better objective function evaluation can be improved iteration by iteration. The new algorithm is named Harmony Search (HS) and the steps in the procedure of HS are as follows: Step 1) Initialize a Harmony Memory (HM). Step 2) Improvise a new harmony from HM. Step 3) If the new harmony is better than least harmony in HM, include the new harmony in HM, and exclude the minimum harmony from HM. Step 4) If stopping criteria are not satisfied, go to Step 2. Harmony Memory Considering Rate (HMCR), which ranges from 0 to 1. If a uniformly generated value between 0 -1 occurs above the current value of the HMCR, then HS finds notes randomly within the possible playable range without considering HM. An HMCR of 0.85 means that at the next step, the algorithm chooses a variable value from HM with an 85% probability. For improving solutions and escaping local optima, yet another option may be introduced. This option mimics the pitch adjustment of each instrument for tuning the ensemble. For computation, the pitch adjustment mechanism is devised as shifting to neighboring values within a range of possible values. A Pitch Adjusting Rate (PAR) of 0.10 means that the algorithm chooses a neighboring value with 10% probability (an upper value with 5% or lower value with 5%. In the present study, first HSA was used to the optimization of a four-reservoir system. The objective function was calculated to equal to 308.2915 by using Lingo software, and this amount was calculated to equal to 308.2900 by using HSA that had a different of 0.0005 percent with the global optimum. After the success of HSA in solving the four-reservoir system, a ten-reservoir system was considered. The Objective function was calculated to equal to 1194.4 by using Lingo software, and this value was calculated to equal to 1193.1 by using HSA that had a different of 0.1 percent with the global optimum. In the single- reservoir issue of Dez Dam, the value of global optimum of the objective function was calculated by using software Lingo 1.9188 and by using HSA 1.944 that had a different of 1.31% with the global optimum. So it can be concluded that this algorithm has the ability to solve optimization problems of the real system

Dam rule curves should be derived using operation models and considering reservoir storage as well as input flows, which results in better management of reservoir water. In this paper rule curves of Doroudzan dam in Fars province, has been derived, using standard operating policy (SOP), hedging rules and linear programming. The objective function is water deficit minimization during 88-92. Standard operating policies result in severe water shortage. To mitigate the severe water shortage in SOP; the hedging policy has been used, which accept some present delivery deficit to reduce greater shortage in the future. The Genetic algorithm has been used to find the hedging optimal factors. Finally, the results of SOP and hedging-GA are compared with a model linear programming based on hedging rules model. Total shortage in hedging-GA is 84.19 MCM, hedging-LP is 219.5 MCM and in SOP is 216.57 MCM. The GA-hedging model by supplying 88.33% of demands control the amount of shortage as well as the shortage severity. In addition, the average reservoir storage is the biggest amount among the three methods. Comparison of the mentioned models using assessment criteria including time reliability, volume reliability and vulnerability shows the hedging-GA model is less vulnerable and more reliable; therefor this model performance is better than the two other models.

The aims of current study are maximization of annual gross margin and allocation of surface water and groundwater in farms under Mollasadra dam; containing Kamfiruz and Korbal plains. For this purpose, deterministic linear programming (DLP) and chanced constrained linear programming (CCLP) to representation an optimal cropping pattern with uncertainty were used. To investigate the effect of increasing irrigation efficiency on annual gross margin, four irrigation efficiency hypothetical scenarios include 50, 60, 70 and 80 percent in certainty and uncertainty conditions (in three levels of 90, 95 and 99 confidence percent) were used. Main crops of the study area, in the form of dry and irrigated agriculture and for the spring (dry) and fall (rainy), were considered. Required data for cultivated area and the type of crops has been derived from database of Fars Agriculture Jahad Organization in 2013, and requirment data for amount of rainfall, surface water and groundwater has been derived from Fars regional water Organization in 2006 to 2013. The results indicated that by applying long run planning for a 30 percent increase in farm irrigation efficiency, annual gross margin of farmers increases from 390 billion Rials to 602 billion Rials and 1 million cubic meters groundwater would be saved. Therefore, a research about water saving technologies and investment in new irrigation systems, which leads to improvement of irrigation efficiency, is recommended.

Nowadays, Soil erosion is one of the largest problems of the world, particularly in Iran. side effects and dangers of this phenomenon within the watershed field is the main problem that affected the overall ecological balance of the basin. The main objective of this study was to determine the optimal level land use for reducing erosion and enhance stakeholders income at Saghezchi watershed is located in the Ardebil. For this aim, linear programming model for three different options include current situation land uses, standard land use and standard conditions with biological measures land use in accordance with scientific principles and criteria were used. The results showed that the current land use level to reduce erosion and increase the income of residents is not suitable and in optimal conditions must be changed. in optimal conditions the garden lands level from 132.29 hectare to 1902.83 hectare (1438.4 % increased), rangeland level without change, irrigated land surface from 319.94 hectare to 57.6 (81.99% decrease) and rainfed cultivation is also from 1549 hectare to 40.8 hectare (97.36% decrease) was changed. In addition, the results showed that land use optimization in the current situation, The ratio of soil erosion and total profitability, 0.07% decrease and 7.7% increase respectively, at the standard conditions land use 3.72% decrease, 7.7% increase respectively and at the standard conditions with biological measures land use, The ratio of ​​soil erosion and total profitability, 5.48% decrease and 30.65% is increased respectively.

Considering the complexity of water resource systems, nowadays managers have widely applied optimization models as efficient tools to reach useful decisions on this issue. The existing optimization models provide new opportunities for better decision making in field of water resources development and planning. Using optimization methods allows decision makers to make the most appropriate decisions among the solutions available for water and soil resources. Optimization is a method by which the best possible answer for a problem is determined according to the target and the existing conjugations, which are specified by functions and mathematical relations. The optimal problem has a target function and several constraints. Math planning is suggested as a useful and efficient way to solve resource allocation problems especially when decision variables, constraints and various parameters are examined. Linear programming is one of the simplest and most practical optimization models. This type of planning can be used for issues with simple relationships such as direct resource allocation to complex operational and management issues. Since all the mathematical relations contained in this model are of the first order type, it is called the linear model.
Hamedan-Bahar plain has faced many problems such as lack of surface water resources, decline of underground water resources and the negative balance of groundwater in the recent years, one part of agricultural land in Hamadan-Bahar Basin is located in Bahar city and the other part in Hamedan city. The water needed for agricultural sector in Bahar city is completely extracted from underground resources while in Hamedan city, about 80% is extracted from underground resources and the rest is supplied by the surface resources. In this region, the first priority is the allocation of water resources for drinking and the second priority belongs to the industrial sector, and agricultural sector is in the third priority. Due to this allocation priority as well as lack of water resources in the region, the water need of crops is not fully ensured according to irrigation scheduling and pattern of cultivation. This research has been tried to compare the different methods of planning, with considering the priorities of water resources allocation and percentage of water supply needs in agricultural sector. Therefore, a linear programming model was created with the goal of 1- determining the optimal cultivation pattern, 2- determining the optimal allocation of surface water and underground water sources, and 3- maximizing the benefit from crop production. This model, based on available water resources and also with considering limitations, determines the cultivation pattern of crops and the amount of water allocated, so the most benefit from crop production will be obtained. Studying the cultivation pattern on this plain and water resources management scenarios, linear program and LINGO software were used. Objective of this model was maximizing of benefit and optimizing allocation of water and cultivation pattern. Evaluating three Scenarios of optimization of cultivation pattern in current situation, optimization of cultivation pattern in changing irrigation method and optimization of cultivation pattern by limiting of groundwater utilization, showed that, the optimization of cultivation pattern in changing irrigation method is better than two others and have more benefits. In this scenario, water consumption of cultivation pattern showed 23.8 % decrease; also, production, area of cultivation and advantage showed 13.1%, 12.7% and 15.8% increase, receptively. The results of this research revealed the necessity of changing the pattern of water consumption in agriculture as an optimal solution to overcome the problems of dehydration and shrinkage of aquifers. Meanwhile, providing social and cultural backgrounds for modifying the pattern of crops by replacing less-water-based products with more economic costs, instead of high-water requirements products, can reduce water use and improve conditions to sustainable use of water resources in the region. Due to the proper allocation of water, demand management and water consumption patterns, especially in the agricultural sector, can create a better and more stable economic situation. Finally, it can be claimed that with the help of planning and optimization models, examining and comparing different methods, making the best decision in the field of water resources management is possible. Eventually, examining other models such as nonlinear planning and applying more limitations and scenarios, especially changes in cultivation pattern, and comparing with the results of this study is suggested.

Based on water deficits and the severe limitation of water in the country, one of the basic steps for the management, planning and water supply in available and developed projects of catchments, is estimation the maximum yield values. As flow regime in catchments is usually regular and affected by the series and parallel dams, use of appropriate and applicable methods are necessary. In this research, a yield model based on linear programming, for three reservoirs- Zohre catchment in south-west of Iran, has developed. The base of this model is including reservoir storage continuity equations, stream flow expressions in each reservoir, water allocation equations, and storage capacity limitation. The objective function is the maximization of total monthly yield for a long-term period of inflow that can be released from reservoir dams to supply demands in water resource systems. After implementing of the yield model, the modified shortage index in the water resource system has improved in comparison to Standard Operating Policy (SOP) and it has been effective in adjusting severe deficit.The results showed that the reliability for satisfying demands in developed future condition of zohre water resource system is about 83% and the yield is about 65% of demands.

Iran with the average of annual precipitation about 230 mm is one of the countries in the world which is located in the semi-arid and arid regions. Improper spatial and temporal distribution of rainfall regarding to the time of required water for agriculture is another problem for agricultural sector. Using crop growth simulation models is a strategy which can be used to assess water balance, to simulate the growth process and to study different managerial scenarios.
In this regard, the combination of crop growth simulation models with geographic information system (GIS) and optimization models is also necessary. Calibration of crop parameters is one of the limiting factors of the use of crop growth simulation models. Results of previous researches have shown that the use of simulation models out of range, often leading to disappointing results. Some of these parameters are crop (variety) specific, so to use of these models, they must first be calibrated according to the local varieties. In the past decades several models have been developed for agricultural land use planning in different scales. The aim of the present study was to determine the cropping area of major agricultural crops based on the combined results of the Crop growth simulation model and is linear programming in the Mahidasht plain, Kermanshah province. In this study, WOFOST model is used to simulate crop growth and GAMS software is used for linear programming.
Material and Field experiments was carried out in the cropping year 2010-2011 for calibration and validation of crop parameters of WOFOST model for major crops (wheat, barley and maize) under deficit irrigation managements. Experiments were implemented as randomized complete block design with three irrigation regimes (Full irrigation, 20 and 40 percent deficit irrigation) and four replications. Agricultural lands in the plain were classified into 440 equal units according to soil characteristics and administrative divisions. Maximization of farmer's income was considered as the objective function in the linear programming model. The constraints of monthly water, seasonal water, labor, land and agricultural machinery were considered at the study area. Considering the available water in the study area the best cropping pattern in 8 studied scenarios of water supply and irrigation system were determined using developed model.
The value of most sensitive parameters of WOFOST model for major crops in the Mahidasht plain was determined by model calibration. Yield and water requirement of mentioned crops in the potential and water-limited situations were estimated in the region regarding to long-term average climatic parameters. Analysis of the scenarios showed that the scenario 6 (doubled water price and sprinkler irrigation system) with the total farmer's income of 140 billion IRR has the highest income among studied scenarios. The area under cultivation in this scenario would be 75,262 hectares which shows increasing compared to the base scenario.
The combination of crop growth simulation models and linear programming can be used for determination of the appropriate cropping patterns under different conditions of water resources.
The maximum farmer's income in this study would be occurred in the scenario 6 which water price will be doubled and irrigation system is sprinkler.

Over the past decades, solving operation problems has been a challenge for water resource planners and managers. Holistic standpoint and integrated management have been applied as a replacement for traditional and partial insight in water resource development projects in recent years. Hence, one of the operator's key questions in multi-reservoirs systems is that which reservoirs should be depleted earlier for satisfying shared downstream demands. In addition, to refill the reservoirs, which ones should be filled earlier? Accordingly, multi-reservoir operation in water resource systems should be done to maximize the total water extracted. In this case, one of the important parameters affecting the system performance is ranking and prioritizing the reservoirs storages for supplying the shared downstream demands. In fact, refill and deplete order of cascade or parallel reservoirs are effective on the reservoir storage distribution. This approach can make also direct effects on the total losses including spill and evaporation of the reservoirs, reforming the total regulated water obtained of reservoir dams.
In this paper, a simulation model with a linear programming optimizing engine is utilized for operational ranking of the reservoirs during a long-term monthly inflow period. Simulation has been implemented for monthly time interval using inflow historical data. In this study, Acres Reservoir Simulation Program (ARSP) has been utilized including a linear programming for optimal water allocation and reservoir storage within each time interval. The main advantage of the ARSP is its inherent flexibility in defining the operating policies through a penalty structure. The model uses network flow optimization techniques in which total components of the system are made through nodes and arcs. Nodes are including reservoir dams, withdrawal and return flow locations, irrigation and water supply networks, and junction points for river reaches or streams. Arcs include different kinds of stream, canals, river reaches and different zone of reservoir dams. Nodes and arcs totally fulfill a closed network that characterizes final structure river system. There are arcs connecting reservoirs and demand nodes to the source and sink node. The source node supplies water to nodes within the network to simulate local inflow and the sink node receive flow from nodes within the network to represent consumptive use. In this state, certain number of arcs defines each stream and storage zone in reservoir. In fact, each arc represents an operating purpose, for which a comparative penalty representing relative priority of desired purpose can be assigned by the user. Based on this penalty for unit flow violation, ARSP imposes the operational strategy by allocating the available water in a manner that minimizes the total system penalties. In selecting these penalty values, three specific aspects should be considered: inter-reservoir zonal operation, relation between storage and flow violation, and inter-reservoir policies. In this process, the reservoirs are ranked according to priority relationships. The model first violates the storage in the lowest priority corresponding to the lowest zonal penalty, and then it proceeds to the other priorities.
As a case study, the seven reservoirs system of Zohreh water resource in southwest of Iran has been studied. A future planning horizon was selected for the study including seven reservoir dams, eleven irrigation networks, four public demands, two minimum flow channels, eleven junctions node, and some general channels. Target values for demands are also set based on the planned water demand for future horizon distributed as 71% for agriculture demands, 16% for the minimum flow, and 13% for public demands. To evaluate the long-term performance of reservoir operation, 48 years of monthly inflow is used, resulting in a total of 576 months. The other input data are reservoir properties, penalty values, evaporation from reservoir, and return flows. Here, different scenarios have been defined for the ranking of the reservoirs. This approach has been effective about 6% on decreasing the water losses including spillway and evaporation of reservoir. The comparison among different scenarios showed that reservoirs ranking affects in all modern indicators for the operation performance. Based on flexibility index, storage ranking in parallel reservoirs is more effective than cascade reservoirs. In this process, reliability and vulnerability indexes were improved for the selective scenario, however, resiliency index was reduced a little. Moreover, reservoirs refill order from upstream to downstream of the catchment, in comparison with opposite state, accomplished better performance as in this state the possibility for spill control in the next reservoir is better provided.

Land use optimization is one of the appropriate methods for soil conservation which helps decision makers and watershed planners in order to make the optimum decision among different land uses. The main objective of this research was to find the optimum area of each land use to reduce soil erosion rate as well as to increase the income of stakeholders in Golroudbar watershed located in Semnan province of Iran. The linear programming model was used in three different scenarios including current land use condition without any land management plan, current land use condition with land management plan and the standard land use level. The results showed that in the optimized condition, the orchard land 28.85 percent, rangelands 74.12 percent and irrigated lands 283.78 percent were increased. Additionally, by optimization of the land in standard condition, soil erosion decreased 16.28 percent and the profitability increased 94.58 percent.

One of the practical and classic problems in the water resource studies is estimation of the optimal reservoir capacity to satisfy demands. However, full supplying demands for total periods need a very high dam to supply demands during severe drought conditions. That means a major part of reservoir capacity and costs is only usable for a short period of the reservoir lifetime, which would be unjustified in economic analysis. Thus, in the proposed method and model, the full meeting demand is only possible for a percent time of the statistical period that is according to reliability constraint. In the general methods, although this concept apparently seems simple, there is a necessity to add binary variables for meeting or not meeting demands in the linear programming model structures. Thus, with many binary variables, solving the problem will be time consuming and difficult. Another way to solve the problem is the application of the yield model. This model includes some simpler assumptions and that is so difficult to consider details of the water resource system. The applicationof evolutionary algorithms, for the problems have many constraints, is also very complicated. Therefore, this study pursues another solution.
In this study, for development and improvement the usual methods, instead of mix integer linear programming (MILP) and the above methods, a simulation model including flow network linear programming is used coupled with an interface manual code in Matlab to account the reliability based on output file of the simulation model. The acre reservoir simulation program (ARSP) has been utilized as a simulation model. A major advantage of the ARSP is its inherent flexibility in defining the operating policies through a penalty structure specified by the user. The ARSP utilizes network flow optimization techniques to handle a subset of general linear programming (LP) problems for individual time intervals. The objective of the LP application is to minimize a cost function, which reflects relative benefits derived from a particular operating policy. In this model, the priority for supplying different demands is defined based on a penalty structure. In this approach, the original system elements are delineated by nodes and arcs. Accordingly, nodes are junction points and arcs are the basic elements used to represent channels, and reservoir storages for each time interval. There are arcs connecting reservoir and demand nodes to the source and sink node. The source node supplies water to nodes within the network to simulate local inflow and the sink node receives flow from nodes within the network to represent consumptive use. Application of the simulation model causes that the configuration of the water resource system with more details is investigated. In this research, tree alternative for reliability including 80, 85 and 90 percent were considered, which are usual reliability for satisfying demands in water resource management in Iran. Then, for the each reliability, optimal reservoir volume was calculated along with optimal flow in each arc. The inflow to the model is established based on a long-term period of historical data (48 years) with monthly time interval.
Results Evaluation of the alternative, defined for reliability, demonstrated if the reliability increases from 85 to 90 %, the incremental volume of the reservoir will be considerable. In fact, for a higher reliability the model must supply water for a more severe drought. However, for the reliability from 80 to 85% the required incremental volume is negligible. Thus, selecting the reliability of 85% is more justified, by which the optimal reservoir volume will be 4.6 million cubic meters. Additionally, increasing of the reliability resulted in decreasing in average deficit and modified shortage index (MSI). However, these two deficit indexes have no same descending trend. The MSI has a less variations versus the reliability that is due to use square deficit in its formulation.
The model used in this research, in comparison to the MILP that is a common method for solving the above problem, make a reform in the traditional mass balance and flow routing in the network. The results show the reservoir capacity sensitivity versus the reliability, in which the sensitivity amount is affected by the intensity and duration drought periods. In fact, with considering higher reliability for supplying demands, a variation of the required reservoir volume has an ascending trend. Thus, application of predefined reliability, that is a common method in designing reservoir volume in Iran, is not appropriate for all drought conditions. In this regard, a sensitivity analysis of reservoir volume versus the reliability accompanying an economical analysis is recommended.

Nowadays, the need for countries to design water distribution networks and abundant costs of water transfer projects, lead us to the use of new and effective methods for designing and optimizing water distribution networks. Practically, engineers, based on engineering judgment, traditionally use methods of trial and error in order to find a suitable solution. Many research have been conducted in the field of optimizing methods because traditional practices do not guaranty an approach to optimized, or even close to optimized, answer. Choosing the appropriate system would be done using different approaches. One of these approaches, which has been used in present study, is the Method of Linear Programming. In the practical method of this study, in compliance with the technical limitations, a water supply system will be optimized to prevent hydraulic patrimonial flows. Using this method, we can optimize all costs of structures including purchasing, Implementation and maintenance, by making them Linear. Therefore, an objective function which represent the minimizing of the costs and Linear equations that represent the technical limitations were defined. Each Linear programming equation contains three basic steps including Objective Function, Limitations (for example Suitable pressure range, Standard speed range and pipe diameter) and Decision Variables which, in this study, are defined for water supply systems. In present study, this process was configured for a real water supply project. The design, which is studied in this research, is the water supply project to the rural area of “Behbahan Qala Madrese” that covers about 720 hectares of the district. With regard to the existence of rivers, and also roads and farms in the area, the net cultivated area was estimated about 625 hectares. The distance this land from the nearest river (Kheirabad River) is about six kilometers. Then, by defining Objectives Functions, Constraints of issue and Variables in LINGO, were optimized and results were compared with various practical conditions. In order to define various practical conditions, ten scenarios were defined using traditional and trial and error based methods. These scenarios, before and after the installation of protective structures, were hydraulically implemented in WATER HAMMER and the results of costs of each scenario, separated into purchase, implementation and operation, were extracted. In the next step, similar to practical condition, optimizing results of LINGO model including pumping system, pipe diameter, type and size of the protective structures were implemented in WATER HAMMER under tow conditions, before and after implementation of protective structures. After that, the results of optimizing by LINGO were compared with the results of practical method. According to the results, Programming Method is capable of optimizing all major parts of the implementation of the branch networks. This method incorporates an approach with high potential for optimizing; in a way that best pumping system will be extracted using pressure limits (between 20 to 100 meters of water column) and water speed in pipes (maximum 1.5 meter per second), optimum diameter and with compliance with price limits of pumps, electricity and required system pressure (according to the topography of the land). In other hand, best protective structures will be chosen in order to prevent patrimonial hydraulic flows including Water Hammer and/or Negative Pressure in water supply system. Eventually, hydraulic simulation was conducted by implementing the results of LINGO into WATERHAMMER. In this research, all three parts were simultaneously defined in the Objective Function and all restrictions were taken under consideration in order to optimizing the entire system because of the effect of pumping system, piping network and also protective structures on patrimonial flows. Using Linear Designing Method will prevent wastage of national resources in addition to improving design speed and economic efficiency. Defined practical scenarios, by changing pipe diameter, pumps and protective devices, were configured as a combination; practical scenario number 10 had the lowest implementation cost compared with other scenarios. However, Linear Programming results indicated that more costs can be reduced; in a way that, comparing the costs of implementation of the transfer line in this scenario with the costs of optimizing method by Linear Programming reviles that a reduction of 3.39 in piping sector, 17.34 in buying and planting pumps, 2.74 in protective structures and finally 3.69 in total costs of the project would occur.