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HS5.7

Computational methods for management and optimization of water resources systems
Convener: Niels Schuetze  | Co-Conveners: Claudius Bürger , Peter Bayer , Michael de Paly , Thomas Wöhling 
Poster Programme
 / Attendance Tue, 05 Apr, 17:30–19:00  / Display Tue, 05 Apr, 08:00–19:30  / Hall A
Features inherent to problems of natural water management in river basins or aquifer systems provide challenging tasks for planners. Commonly, operations have to be designed over long periods of time, in a heterogeneous and uncertain environment. Each case is unique and typically involves multiple decision criteria and constraints over a wide range of levels in time and space. Moreover, robust results at the larger scale depend on assumptions about the performance of smaller scale systems in operation. Another crucial issue is the assessment of the expected value of information when field investigation campaigns are planned. An integrative approach can be used to simultaneously optimize both field data collection and operation design, independent of the type of data and the nature of decision objectives. Strategic planning of a sequence of actions does not only require optimal scheduling. Considering imperfect predictions and the increase of environmental extremes, there is a need for assigning “values” to flexibility. The session proposed here aims to exploit innovative methods from the fields of classic optimization concepts, Bayesian decision theory, artificial intelligence and operations research to tackle complex problems in water resources management. We invite papers that investigate techniques, which are still uncommon in current planning practice, bear the theoretical potential to advance the state-of-the art, particularly towards improved integral and strategic problem solving models. The session will serve as an open forum for researchers and engineers to demonstrate the potential of innovative methods through a broad range of working cases, which represent model-based virtual realities or are oriented at field cases of different scale.