Optimal water and waste load allocation in reservoir-river systems: A case study

Mohammad Reza Nikoo, Reza Kerachian, Akbar Karimi, Ali Asghar Azadnia, Keighobad Jafarzadegan

Research output: Contribution to journalArticlepeer-review

45 Citations (Scopus)


In this paper, a new methodology is developed for optimization of water and waste load allocation in reservoir-river systems considering the existing uncertainties in reservoir inflow, waste loads and water demands. A stochastic dynamic programming (SDP) model is used to optimize reservoir operation considering the inflow uncertainty, and another model called PSO-SA is developed and linked with the SDP model for optimizing water and waste load allocation in downstream river. In the PSO-SA model, a particle swarm optimization technique with a dynamic penalty function for handling the constraints is used to optimize water and waste load allocation policies. Also, a simulated annealing technique is utilized for determining the upper and lower bounds of constraints and objective function considering the existing uncertainties. As the proposed water and waste load allocation model has a considerable run-time, some powerful soft computing techniques, namely, Regression tree Induction (named M5P), fuzzy K-nearest neighbor, Bayesian network, support vector regression and an adaptive neuro-fuzzy inference system, are trained and validated using the results of the proposed methodology to develop real-time water and waste load allocation rules. To examine the efficiency and applicability of the methodology, it is applied to the Dez reservoir-river system in the south-western part of Iran.

Original languageEnglish
Pages (from-to)4127-4142
Number of pages16
JournalEnvironmental Earth Sciences
Issue number9
Publication statusPublished - May 2014


  • Nonlinear interval optimization
  • Operating rules
  • Particle swarm optimization (PSO)
  • Reservoir-river systems
  • Simulated annealing (SA)
  • Water and waste load allocation

ASJC Scopus subject areas

  • Global and Planetary Change
  • Environmental Chemistry
  • Water Science and Technology
  • Soil Science
  • Pollution
  • Geology
  • Earth-Surface Processes


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