Multi-Objective Planning for Conjunctive Use of Surface and Ground Water Resources Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@Article{Sepahvand:2019:WRM,

• author = "Reza Sepahvand and Hamid R. Safavi and Farshad Rezaei",
• title = "Multi-Objective Planning for Conjunctive Use of Surface and Ground Water Resources Using Genetic Programming",
• publisher = "springer",
• year = "2019",
• volume = "33",
• pages = "2123--2137",
• journal = "Water Resources Management",
• keywords = "genetic algorithms, genetic programming, conjunctive use, multi-crop pattern planning, simulation-optimisation, multi-objective optimisation, compromise programming",
• DOI = "doi:10.1007_s11269-019-02229-4",
• URL = "http://link.springer.com/10.1007/s11269-019-02229-4",
• abstract = "In arid and semi-arid regions, climate change causes a drastic decline in the volume of water resources as water demands increase. Thus, the present study is aimed at using a simulation-optimisation model to perform conjunctive management of surface-ground water use to achieve two main objectives: (1) minimising shortages in meeting irrigation water demands and (2) maximising the total agricultural net benefit for the main crops of an agricultural sector. To meet these main goals, first, the genetic programming (GP) method is used to simulate surface water-groundwater interactions. Then, the simulation model is linked to a multi-objective genetic algorithm (MOGA) as the optimisation model, yielding a simulation-optimisation model. In order to investigate the impact of different climatic conditions on the optimised surface and ground water allocation and propose an optimal crop pattern for each climatic period, three planning periods (wet, normal and dry) were addressed in modelling the conjunctive water use management problem. Finally, the economic results of this study suggested a maximum increase in the net benefit by 38.19percent, 59.37percent and 45percent, as compared to those obtained in the actual operation in wet, normal and dry years, respectively, for one study sub-area. The net benefit was also increased by at most 84.79percent, 83.3percent and 120.77percent in wet, normal and dry years, respectively, for another study sub-area, demonstrating the competence of the optimal conjunctive use model to enhance net benefits with the least negative socio-environmental impacts resulting from any development and management scheme in the field of water resources.",
• bibsource = "OAI-PMH server at oai.repec.org",
• identifier = "RePEc:spr:waterr:v:33:y:2019:i:6:d:10.1007_s11269-019-02229-4",

}

Genetic Programming entries for Reza Sepahvand Hamid R Safavi Farshad Rezaei

Citations