River water quality management considering agricultural return flows: application of a nonlinear two-stage stochastic fuzzy programming

Ali Tavakoli, Mohammad Reza Nikoo, Reza Kerachian*, Maryam Soltani

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)

Abstract

In this paper, a new fuzzy methodology is developed to optimize water and waste load allocation (WWLA) in rivers under uncertainty. An interactive two-stage stochastic fuzzy programming (ITSFP) method is utilized to handle parameter uncertainties, which are expressed as fuzzy boundary intervals. An iterative linear programming (ILP) is also used for solving the nonlinear optimization model. To accurately consider the impacts of the water and waste load allocation strategies on the river water quality, a calibrated QUAL2Kw model is linked with the WWLA optimization model. The soil, water, atmosphere, and plant (SWAP) simulation model is utilized to determine the quantity and quality of each agricultural return flow. To control pollution loads of agricultural networks, it is assumed that a part of each agricultural return flow can be diverted to an evaporation pond and also another part of it can be stored in a detention pond. In detention ponds, contaminated water is exposed to solar radiation for disinfecting pathogens. Results of applying the proposed methodology to the Dez River system in the southwestern region of Iran illustrate its effectiveness and applicability for water and waste load allocation in rivers. In the planning phase, this methodology can be used for estimating the capacities of return flow diversion system and evaporation and detention ponds.

Original languageEnglish
Article number158
JournalEnvironmental Monitoring and Assessment
Volume187
Issue number4
DOIs
Publication statusPublished - Apr 2015

Keywords

  • QUAL2Kw
  • SWAP
  • Uncertainty analysis
  • Water and waste load allocation
  • Water quality

ASJC Scopus subject areas

  • Environmental Science(all)
  • Pollution
  • Management, Monitoring, Policy and Law

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