Two-Objective Simulation-Optimization Model for Cropping Pattern and Water Allocation in Semnan Plain

<p>In this study, we developed a simulation-optimization model for optimum water allocation to meet environmental flow requirements and agricultural demand. The simulation model consists of three modules: a hydrologic module, an agronomic module, and an economic module. The hydrologic module is based on a dynamic coupling of WEAP and MODFLOW, and includes water balances for the crop root zone, the surface water system, and the underlying aquifer. The agronomic module simulates the effect of deficit irrigation on crop yield response in each growth stage, while the economic module calculates the net benefit of crop production. The optimization model contains two objective functions, one related to agricultural production and the other related to environmental flows. These conflicting objective functions are maximized using the Multi-Objective Particle Swarm Optimization algorithm. Decision variables include crop acreages, minimum environmental flow requirements in the river, and the degree of deficit irrigation. We applied the simulation-optimization model to the irrigated Miyandoab plain in the semi-arid northwest of Iran, for the historical period 1984 to 2013. There is competition between irrigation demands in the plain and environmental flow requirements to downstream Lake Urmia, which has been shrinking in recent years due to decreased inflows. Our results quantify what the (Pareto) trade-off looks like between meeting environmental and agricultural water demand in the region. We find that historical water allocations were suboptimal and that both agricultural and environmental benefits can be increased by better management of cropping decisions, deficit irrigation, and environmental flow requirements. We further show that increased groundwater use for irrigation can partly alleviate the trade-off, but that it leads to significant declines in groundwater levels due to the relatively small specific yield of the aquifer.</p>

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Simulation-Optimization for Conjunctive Water Resources Management and Optimal Crop Planning in Kushabhadra-Bhargavi River Delta of Eastern India

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17103521 ◽

2020 ◽

Vol 17 (10) ◽

pp. 3521

Author(s):

Madan K. Jha ◽

Richard C. Peralta ◽

Sasmita Sahoo

Keyword(s):

Water Resources ◽

Simulation Model ◽

Seawater Intrusion ◽

Optimization Model ◽

Crop Yields ◽

Simulation Optimization ◽

Optimization Models ◽

Water Model ◽

Cropping Pattern ◽

Groundwater Exploitation

Water resources sustainability is a worldwide concern because of climate variability, growing population, and excessive groundwater exploitation in order to meet freshwater demand. Addressing these conflicting challenges sometimes can be aided by using both simulation and mathematical optimization tools. This study combines a groundwater-flow simulation model and two optimization models to develop optimal reconnaissance-level water management strategies. For a given set of hydrologic and management constraints, both of the optimization models are applied to part of the Mahanadi River basin groundwater system, which is an important source of water supply in Odisha State, India. The first optimization model employs a calibrated groundwater simulation model (MODFLOW-2005, the U.S. Geological Survey modular ground-water model) within the Simulation-Optimization MOdeling System (SOMOS) module number 1 (SOMO1) to estimate maximum permissible groundwater extraction, subject to suitable constraints that protect the aquifer from seawater intrusion. The second optimization model uses linear programming optimization to: (a) optimize conjunctive allocation of surface water and groundwater and (b) to determine a cropping pattern that maximizes net annual returns from crop yields, without causing seawater intrusion. Together, the optimization models consider the weather seasons, and the suitability and variability of existing cultivable land, crops, and the hydrogeologic system better than the models that do not employ the distributed maximum groundwater pumping rates that will not induce seawater intrusion. The optimization outcomes suggest that minimizing agricultural rice cultivation (especially during the non-monsoon season) and increasing crop diversification would improve farmers’ livelihoods and aid sustainable use of water resources.

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