Sustainable Basin-Scale Water Allocation with Hydrologic State-Dependent Multi-Reservoir Operation Rules

Shima Nabinejad, S. Jamshid Mousavi, Joong Hoon Kim

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)


This study extends the PSO-MODSIM model, integrating particle swarm optimization (PSO) algorithm and MODISM river basin decision support system (DSS) to determine optimal basin-scale water allocation, in two aspects. The first is deriving hydrologic state-dependent (conditional) operating rules to better account for drought and high-flow periods, and the second is direct, explicit consideration of sustainability criteria in the model’s formulation to have a better efficiency in basin-scale water allocation. Under conditional operating rules, the operational parameters of reservoir target storage levels and their priority rankings were conditioned on the hydrologic state of the system in a priority-based water allocation scheme. The role of conditional operating rules and policies were evaluated by comparing water shortages associated with objective function values under unconditional and conditional operating rules. Optimal basin-scale water allocation was then evaluated by incorporating reliability, vulnerability, reversibility and equity sustainability indices into the PSO objective function. The extended model was applied for water allocation in the Atrak River Basin, Iran. Results indicated improved distribution of water shortages by about 7.5% using conditional operating rules distinguishing dry, normal and wet hydrologic states. Alternative solutions with nearly identical objective function values were found with sustainability indices included in the model.

Original languageEnglish
Pages (from-to)1-20
Number of pages20
JournalWater Resources Management
Publication statusAccepted/In press - 2017 May 10


  • Basin-scale water allocation
  • Conditional operating rules
  • Optimization
  • Sustainability indices

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Water Science and Technology


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