Interval number fuzzy linear programming for climate change impact assessments of reservoir active storage

Ching Pin Tung, Nien Ming Hong, Ming hsu Li

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


The major uncertainty in the climate change impact study inherits from applying the predictions of General Circulation Models (GCMs). Different results might be obtained by using various GCMs' predictions, which causes difficulties on the decision making of water resources management. This study proposed an integrated hydrological simulations and optimization framework, consisting of a fuzzy linear programming model with interval numbers, a streamflow simulation model, and agricultural water demand projections, to evaluate the impacts of climate change on reservoir active storage. The reservoir inflows are simulated by the WatBal model, while agricultural water demands are predicted based on the projected change of potential evapotranspiration. Inflows and water demands are used to formulate an interval number fuzzy linear programming model. Fuzzy relationships are used to describe tolerable deficits of water resources, and the interval number is employed to indicate ranges of possible inflows and water demands. This systematic framework is applied to study the Tsengwen reservoir watershed to provide an optimal interval of active storage. The results further indicate the higher tolerable deficit, the smaller difference between superior and inferior active storage.

Original languageEnglish
Pages (from-to)349-356
Number of pages8
JournalPaddy and Water Environment
Issue number4
StatePublished - Dec 2009


  • Climatic change
  • Global warming
  • Uncertainty
  • Water resources


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