Multistage scenario-based interval-stochastic programming for planning water resources allocation |
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| Authors: | Y P Li G H Huang X Chen |
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| Institution: | (1) College of Urban and Environmental Sciences, Peking University, 100871 Beijing, China;(2) Environmental Systems Engineering Program, University of Regina, Regina, SK, S4S 0A2, Canada;(3) Chinese Research Academy of Environmental Science, Beijing Normal University, 100012-100875 Beijing, China;(4) Key Laboratory of Oasis Ecology and Desert Environment, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 830011 Urumqi, Xinjiang, China |
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| Abstract: | In this study, a multistage scenario-based interval-stochastic programming (MSISP) method is developed for water-resources
allocation under uncertainty. MSISP improves upon the existing multistage optimization methods with advantages in uncertainty
reflection, dynamics facilitation, and risk analysis. It can directly handle uncertainties presented as both interval numbers
and probability distributions, and can support the assessment of the reliability of satisfying (or the risk of violating)
system constraints within a multistage context. It can also reflect the dynamics of system uncertainties and decision processes
under a representative set of scenarios. The developed MSISP method is then applied to a case of water resources management
planning within a multi-reservoir system associated with joint probabilities. A range of violation levels for capacity and
environment constraints are analyzed under uncertainty. Solutions associated different risk levels of constraint violation
have been obtained. They can be used for generating decision alternatives and thus help water managers to identify desired
policies under various economic, environmental and system-reliability conditions. Besides, sensitivity analyses demonstrate
that the violation of the environmental constraint has a significant effect on the system benefit. |
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| Keywords: | Dynamics Interval Optimization Risk analysis Scenario-based Stochastic Uncertainty Water resources |
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