Ghodspour M, Sarai Tabrizi M, Saremi A, Kardan Moghadam H, Akbari M. Two-Objective Simulation-Optimization Model for Cropping Pattern and Water Allocation in Semnan Plain. jwss 2021; 25 (3) :177-189
URL:
http://jstnar.iut.ac.ir/article-1-4067-en.html
Islamic Azad University, Tehran scince and Research Branch, Tehran, Iran , mahdisarai@yahoo.com
Abstract: (2281 Views)
The application of simulation-optimization models is a valuable tool for selecting the appropriate cropping pattern. The main objective of this research is to develop a two-objective simulation-optimization model to determine the pattern of cultivation and water allocation. The model performs the optimization with the multi-objective metamorphic algorithm (MOALO) after simulating different states of the cultivation pattern. The decision variables including land and water allocated to ten-day periods of plant growth were designed in a way that the minimum utilization of water resources and economic maximization were identified as target functions. The developed model was used to simulate and optimize the cultivation pattern with an area of 5500 hectares and water allocation of Semnan plain with renewable water at the rate of 60.8 million cubic meters. Harvesting scenarios of 80 (GW80) and 100 (GW100) percent of renewable groundwater and scenarios of change in existing cropping pattern of 30 (AC30) and 60 (AC60) percent were considered and each scenario was simulated with the MOALO algorithm. Optimization using the proposed model in four scenarios improved the water and economic objective functions compared to the initial simulation performance. The results showed that the four proposed scenarios were obtained by minimizing the water objective function and maximizing the economic objective function relative to the current situation (simulation). In general, the proposed model had a good performance despite its simplicity, which is a specialized tool to optimize the crop pattern with water allocation.
Type of Study:
Research |
Subject:
Ggeneral Received: 2020/09/1 | Accepted: 2021/01/13 | Published: 2021/12/1