Optimal conjunctive use of surface water and groundwater resources : a systematic state-of-the-art review with potential application in arid and semi-arid regions
Kayhomayoon, Zahra ; Milan, Sami Ghordoyee ; Rashidi, Sajjad ; Arya Azar, Naser ; Kerachian, Reza and Berndtsson, Ronny LU
(2025)
In Hydrology Research
56(8).
p.698-722
- Abstract
We reviewed papers on optimal conjunctive use of surface and groundwater (GW) with application in dry regions. Selected papers from the last 25-year period were reviewed using the PRISMA method. We show that with increasing scarcity of water, objectives of models developed for optimal conjunctive use have become more environmentally and socially oriented. About two-thirds of the studies are dedicated to single-objective problems, while the rest are dedicated to multi-objective problems. More than 45% of the single-objective optimization models employed metaheuristic algorithms. Genetic algorithm and particle swarm optimization were the most popular algorithms. There are still many challenges in the optimal conjunctive use of surface... (More)
We reviewed papers on optimal conjunctive use of surface and groundwater (GW) with application in dry regions. Selected papers from the last 25-year period were reviewed using the PRISMA method. We show that with increasing scarcity of water, objectives of models developed for optimal conjunctive use have become more environmentally and socially oriented. About two-thirds of the studies are dedicated to single-objective problems, while the rest are dedicated to multi-objective problems. More than 45% of the single-objective optimization models employed metaheuristic algorithms. Genetic algorithm and particle swarm optimization were the most popular algorithms. There are still many challenges in the optimal conjunctive use of surface water and GW resources. GW quality, which affects human health and the environment, is often not considered in optimization studies. Climate change and drought, as serious threats to the water supply, need to be more adequately addressed. Uncertainty in data and results is often not considered in such studies. Most importantly, there is usually no proper collaboration between various stakeholders, and thus, the level of satisfaction and benefit due to optimization approaches is still unclear. Water resources managers and decision makers need to be made aware of this approach, in which researchers can play more effective roles.
(Less)
- author
- Kayhomayoon, Zahra
; Milan, Sami Ghordoyee
; Rashidi, Sajjad
; Arya Azar, Naser
; Kerachian, Reza
and Berndtsson, Ronny
LU
- organization
- publishing date
- 2025-08
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- conjunctive use, groundwater, machine learning, optimization, surface water, sustainability
- in
- Hydrology Research
- volume
- 56
- issue
- 8
- pages
- 25 pages
- publisher
- IWA Publishing
- external identifiers
-
- scopus:105018723316
- ISSN
- 1998-9563
- DOI
- 10.2166/nh.2025.191
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2025 The Authors.
- id
- fe05383a-86e0-4557-bddc-e80a31b16145
- date added to LUP
- 2025-10-25 22:07:00
- date last changed
- 2025-10-27 14:24:26
@article{fe05383a-86e0-4557-bddc-e80a31b16145,
abstract = {{<p>We reviewed papers on optimal conjunctive use of surface and groundwater (GW) with application in dry regions. Selected papers from the last 25-year period were reviewed using the PRISMA method. We show that with increasing scarcity of water, objectives of models developed for optimal conjunctive use have become more environmentally and socially oriented. About two-thirds of the studies are dedicated to single-objective problems, while the rest are dedicated to multi-objective problems. More than 45% of the single-objective optimization models employed metaheuristic algorithms. Genetic algorithm and particle swarm optimization were the most popular algorithms. There are still many challenges in the optimal conjunctive use of surface water and GW resources. GW quality, which affects human health and the environment, is often not considered in optimization studies. Climate change and drought, as serious threats to the water supply, need to be more adequately addressed. Uncertainty in data and results is often not considered in such studies. Most importantly, there is usually no proper collaboration between various stakeholders, and thus, the level of satisfaction and benefit due to optimization approaches is still unclear. Water resources managers and decision makers need to be made aware of this approach, in which researchers can play more effective roles.</p>}},
author = {{Kayhomayoon, Zahra and Milan, Sami Ghordoyee and Rashidi, Sajjad and Arya Azar, Naser and Kerachian, Reza and Berndtsson, Ronny}},
issn = {{1998-9563}},
keywords = {{conjunctive use; groundwater; machine learning; optimization; surface water; sustainability}},
language = {{eng}},
number = {{8}},
pages = {{698--722}},
publisher = {{IWA Publishing}},
series = {{Hydrology Research}},
title = {{Optimal conjunctive use of surface water and groundwater resources : a systematic state-of-the-art review with potential application in arid and semi-arid regions}},
url = {{http://dx.doi.org/10.2166/nh.2025.191}},
doi = {{10.2166/nh.2025.191}},
volume = {{56}},
year = {{2025}},
}