Abstract:In arid and semi-arid areas, unsustainable development of irrigated agriculture has reduced the water level of large lakes such as Aral, Urmia, Hamoon, and Bakhtegan. Urmia Lake, as a hyper saline and very shallow lake, located in the northwest of Iran, has water level reductions of about 40 cm each year over the past two decades. In this research, the indices of environmental and agricultural sustainability are evaluated using performance criteria influenced by climate change and water management strategies for the Zarrinehrud and Siminehrud River basins as the largest sub-basin of Urmia Lake basin. Modeling of hydrologic behavior of these basins is performed using WEAP21 model. The model is analyzed for three future emission scenarios (A2, A1B, and B1), for the period of 2015-2040 and five water management scenarios: (1) keeping the existing situation; (2) crop pattern change; (3) improving the conveyance and distribution efficiency; (4) combining the improvement of conveyance and distribution efficiency with improving the application efficiency using modern technology; and (5) the combination of crop pattern change with the improvement of total irrigation efficiency. The results show that the highest values of indices of environmental sustainability and agricultural sustainability are related to the scenario of combining the crop pattern change with improving the total irrigation efficiency under the B1 emission scenario (B1S4).
In this study, a meta-heuristic technique called harmony search (HS) algorithm is developed for reservoir operation optimization with respect to flood control. The HS algorithm is used to minimize the water supply deficit and flood damages downstream of a reservoir. The GIS database is used to determine the flood damage functions. The efficacy of HS algorithm is evaluated in comparison with other techniques by using a benchmark problem for a single reservoir operation optimization problem. HS showed promising results in terms of speed of convergence to an optimal objective function value compared with other techniques such as honey-bee mating optimization (HBMO) and a global optimization model (LINGO 8.0 NLP solver). The HS algorithm is then applied to the Narmab reservoir, north of Iran, as a case study. Narmab reservoir serves multiple purposes including irrigation, flood control, and drinking water requirements. The developed model is applied for monthly operation. The results show that the HS algorithm can be effectively used for operation of reservoir for flood management.
Over the last decades, the increasing water demand has caused a number of problems, to which reservoir operation optimization has been suggested as one of the best solutions. In this research, a model based on mixed integer linear programming (MILP) technique is developed for the systematic operation of multireservoirs that are used to cater for the different needs of the Tehran-Karaj plain. These reservoirs include Laar, Latian, and Karaj dams. The system configuration was accomplished through the nodes and arcs of the network flow model approach and system component implementation including sources, consumption, junctions, and the physical and hydraulic relationship between them. The following were performed via comprehensive developed software: system configuration, objective function and constraints formulation, linearization, determining penalty values, and setting priorities for each node and arc in the system. A comparison between the MILP developed model’s results against the periodic data shows 21.7% less overflow, 11.6% more outflow, and 15.9% more reservoir storage, respectively. The outcome of the MILP-based modeling indicates superior performance to the historical period.
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