Originally published on August 14, 2012 at The Spout
Making a decision on the best way to operate a reservoir during a flooding or high inflow event is a multi-objective and challenging task; and depending on the size of the reservoir, the level of success is usually highly affected by water level in the reservoir before the event occurs. Therefore, decision making before and during these events is too complicated to be handled only by reservoir operation planners’ judgement. A Risk-Informed Decision Making (RIDM) framework to acquire all the necessary information from multiple sources and providing planners with the collected information and a pre-designed and solid guideline to follow in order to make recommendations to decision makers seems to be the best approach to deal with this task.
The framework, as a guideline, requires gathering information on possible inflow scenarios for the probable high inflow or flooding period. These scenarios are inputted into simulation and/or optimization models developed for the task of reservoir operation. The outputs of these models are probability density functions for the value of the objectives function(s) and variables of the model(s). The outputs are generated separately for each different operational alternative. In order to analyze the performance of operational alternatives on each objective, a number of streamflow impact curves are coupled with the outputs of simulation and/or optimization models to translate the variables values into meaningful data to evaluate the alternatives performance and generate a performance matrix for each alternative.
Finally, the performance matrices, decision makers’ desirable risk-taking level on each objective, and relative importance of the objectives are inputted into a Multi-Criteria Decision Making (MCDM) software package. The outcome is a ranking of the operational alternatives for the task of reservoir operation during the flooding or high inflow period. If the recommended alternative is acceptable to decision makers, the corresponding operational plan might be implemented. Otherwise, the decision makers might order developing new operational alternatives and reiterating the process.
M. H. (Ali) Alipour is a Ph.D. candidate and recipient of Trustees Doctoral Fellowship at the University of Central Florida (Orlando). His research includes water resources planning and management, hydrology, and ecohydraulics.