Multi-Objective Planning for Conjunctive Use of Surface and Ground Water Resources Using Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @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