Inter-basin hydropolitics for optimal water resources allocation.

Allocation policies Artificial neural network (ANN) Conflict Gini coefficient Justice Multi-objective optimization Sefidrud Sustainability

Journal

Environmental monitoring and assessment
ISSN: 1573-2959
Titre abrégé: Environ Monit Assess
Pays: Netherlands
ID NLM: 8508350

Informations de publication

Date de publication:
01 Jul 2020
Historique:
received: 06 02 2020
accepted: 21 06 2020
entrez: 3 7 2020
pubmed: 3 7 2020
medline: 11 7 2020
Statut: epublish

Résumé

Efficient, just, and sustainable water resources' allocation is difficult to achieve in multi-stakeholder basins. This study presents a multi-objective optimization model for water resources allocation and reports its application to the Sefidrud basin in Iran. Available water resources are predicted until 2041with the artificial neural network algorithm (ANN). This is followed by multi-objective optimization of water resource allocation. The first objective function of the optimization model is maximization of revenue, and the second objective function is the achievement of equity in water resources allocation in the basin. This study considers two scenarios in the optimization scheme. The first scenario concerns the water allocation with existing dams and dams under construction. The second scenario tackles water allocation adding dams currently in the study stage to those considered in Scenario 1. The Gini coefficient is about 0.1 under the first scenario, indicating the preponderance of economic justice in the basin. The Gini coefficient is about 0.4 under the second scenario, which signals an increase of injustice in water allocation when considering the future operation of dams currently under study.

Identifiants

pubmed: 32613462
doi: 10.1007/s10661-020-08439-3
pii: 10.1007/s10661-020-08439-3
doi:

Substances chimiques

Water 059QF0KO0R

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

478

Auteurs

Mehdi Kazemi (M)

Department of Irrigation & Reclamation Engineering, Faculty of Agricultural Engineering & Technology, College of Agriculture & Natural Resources, University of Tehran, Karaj, Tehran, 3158777871, Iran.

Omid Bozorg-Haddad (O)

Department of Irrigation & Reclamation Engineering, Faculty of Agricultural Engineering & Technology, College of Agriculture & Natural Resources, University of Tehran, Karaj, Tehran, 3158777871, Iran. OBHaddad@ut.ac.ir.

Elahe Fallah-Mehdipour (E)

Department of Water and Energy, Moshanir Consultant Co., Tehran, Iran.

Hugo A Loáiciga (HA)

Department of Geography, University of California, Santa Barbara, CA, 93016-4060, USA.

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Classifications MeSH