Understanding Irrigation Water Optimization

Irrigation is applied to much of the cropped area of Utah to support crop production. Limited water resources and competing demand for those resources make irrigation water conservation, irrigation water optimization, and efficient use of irrigation water important components of overall water resource management. It is well known in Utah that optimal irrigation use is even more critical during drought conditions. However, optimization practices change the quantity, quality, and timing of water flows. It is important to consider the possible hydrologic impact of irrigation practice changes and the desired outcome of an optimization practice to avoid implementing a practice that has little appreciable effect relative to the desired outcome

Multiobjective Optimization Problem of Multireservoir System in Semiarid Areas

With the increasing scarcity of water resources, the growing importance of the optimization operation of the multireservoir system in water resources development, utilization, and management is increasingly evident. Some of the existing optimization methods are inadequate in applicability and effectiveness. Therefore, we need further research in how to enhance the applicability and effectiveness of the algorithm. On the basis of the research of the multireservoir system’s operating parameters in the Urumqi River basin, we establish a multiobjective optimization problem (MOP) model of water resources development, which meets the requirements of water resources development. In the mathematical model, the domestic water consumption is the biggest, the production of industry and agricultural is the largest, the gross output value of industry and agricultural is the highest, and the investment of the water development is the minimum. We use the weighted variable-step shuffled frog leaping algorithm (SFLA) to resolve it, which satisfies the constraints. Through establishing the test function and performance metrics, we deduce the evolutionary algorithms, which suit for solving MOP of the scheduling, and realize the multiobjective optimization of the multireservoir system. After that, using the fuzzy theory, we convert the competitive multiobjective function into single objective problem of maximum satisfaction, which is the only solution. A feasible solution is provided to resolve the multiobjective scheduling optimization of multireservoir system in the Urumqi River basin. It is the significance of the layout of production, the regional protection of ecological environment, and the sufficient and rational use of natural resources, in Urumqi and the surrounding areas

Ordering Renewables: Groundwater, Recycling, and Desalination

Optimal recycling of minerals can be thought of as an integral part of the theory of the mine. In this paper, we consider the role that wastewater recycling plays in the optimal extraction of groundwater, a renewable resource. We develop a two-sector dynamic optimization model to solve for the optimal trajectories of groundwater extraction and water recycling. For the case of spatially increasing recycling costs, recycled water serves as a supplemental resource in transition to the steady state. For constant unit recycling cost, recycled wastewater is eventually used as a sector-specific backstop for agricultural users, while desalination supplements household groundwater in the steady state. In both cases, recycling water increases welfare by shifting demand away from the aquifer, thus delaying implementation of costly desalination. The model provides guidance on when and how much to develop resource alternatives.Renewable resources, dynamic optimization, groundwater allocation, wastewater reuse, recycling, reclamation, water quality

OPERATIONAL RESEARCH TOOLS IN IRRIGATION - A REVIEW

Operational research optimization is an old method for allocating scarce resources with maximum benefits and efficiency. With increasing global water scarcity, earliness and tiredness in demand base water supply, economical issues, maximizing crop per drop of water, OR is getting popular in irrigation and agriculture sector as well. This paper is intended to review different optimization techniques used so far in the field of irrigation.Key Words: Operation research, optimization, irrigation, water delivery, genetic algorithm, simulated annealing, fuzzy sets, swarm optimization

Optimal irrigation water allocation using a genetic algorithm under various weather conditions

Growing water scarcity, due to growing populations and varying natural conditions, puts pressure on irrigation systems, which often are the main consumptive water users. Therefore, water resources management to improve the allocation of limited water supplies is essential. In this study, a non-linear programming optimization model with an integrated soil/water balance is developed to determine the optimal reservoir release policies and the optimal cropping pattern around Doroudzan Dam in the South-West of Iran. The proposed model was solved using a genetic algorithm (GA). Four weather conditions were identified by combining the probability levels of rainfall, evapotranspiration and inflow. Moreover, two irrigation strategies, full irrigation and deficit irrigation were modeled under each weather condition. The results indicate that for all weather conditions the total farm income and the total cropped area under deficit irrigation were larger than those under full irrigation. In addition, our results show that when the weather conditions and the availability of water changes the optimal area under corn and sugar beet decreases sharply. In contrast, the change in area cropped with wheat is small. It is concluded that the optimization approach has been successfully applied to Doroudzan Dam region. Thus, decision makers and water authorities can use it as an effective tool for such large and complex irrigation planning problems