A Stochastic Conflict Resolution Optimization Model for Flood Management in Detention Basins: Application of Fuzzy Graph Model

Banafsheh Nematollahi, Parnian Hashempour Bakhtiari, Nasser Talebbeydokhti*, Gholam Reza Rakhshandehroo, Mohammad Reza Nikoo, Amir H. Gandomi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Floods are a natural disaster of significant concern because of their considerable damages to people’s livelihood. To this extent, there is a critical need to enhance flood management techniques by establishing proper infrastructure, such as detention basins. Although intelligent models may be adopted for flood management by detention basins, there is a literature gap on the optimum design of such structures while facing flood risks. The presented study filled this research gap by introducing a methodology to obtain the optimum design of detention basins using a stochastic conflict resolution optimization model considering inflow hydrographs uncertainties. This optimization model was developed by minimizing the conditional value-at-risk (CvaR) of flood overtopping, downstream flood damage, and deficit risk of water demand, as well as the deviation of flood overtopping and downstream damage based on non-linear interval number programming (NINP), for four different outlets types via a robust optimization tool, namely the non-dominated sorting genetic algorithm-III (NSGA-III). Conflict resolution was performed using the graph model for conflict resolution (GMCR) technique, enhanced by fuzzy preferences, to comply with the authorities’ priorities. Results indicated that the proposed framework could effectively design optimum detention basins consistent with the regional and hydrological standards.

Original languageEnglish
Article number774
JournalWater (Switzerland)
Volume14
Issue number5
DOIs
Publication statusPublished - Mar 1 2022

Keywords

  • Conditional value-at-risk (CVaR) method
  • Flood management
  • Fuzzy preferences
  • Graph model for conflict resolution (GMCR)
  • Non-dominated sorting genetic algorithm-III (NSGA-III)
  • Non-linear interval number programming (NINP)

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Biochemistry
  • Aquatic Science
  • Water Science and Technology

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