Sustainable decision making under uncertainty: A case study in dredged material management

Background: The port of Lübeck is one of Germany's most important harbours for goods traffic to and from the Baltic Sea Region. Sedimentation from the River Trave requires regularly maintenance dredging as well as capital dredging operations in order to maintain the operational capability of the port. A range of solutions for sustainable dredged material handling exist and an assessment of these options often proves to be challenging for decision makers. Multi-criteria decision analysis (MCDA) provides decision support by processing different data sets and evaluating suitable options in a rational way. Using the stochastic multi-criteria acceptability analysis (SMAA)-TRI method with a modification of a previously developed computerised model for decision support in dredged material management, this study was performed to test decision support under uncertainty. Results: The analysis endorsed that relocation to a dredged discharge pool and capping of an ammunition disposal site are viable options for Lübeck port. On the other hand, the use of dredged material from port expansion and its disposal on land are considered to be of very low sustainability under the given circumstances. Conclusions: The case study demonstrates capabilities as well as boundaries of computer-aided decision making under the premise of incomplete information. Despite uncertainties, sustainable decision making is possible with appropriate MCDA methodologies although minimum requirements concerning both data quality and data quantity must be fulfilled. Consequently, one possible alternative could not be integrated into the case study due to incomplete information. © 2014 Scheffler et al.

Subjects

Decision support

Dredged material management

MCDA

Risk analysis

Sustainability

Uncertainty

DDC Class

620: Ingenieurwissenschaften

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https://creativecommons.org/licenses/by/2.0/

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2190-4715-26-7.pdf

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633.67 KB

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Adobe PDF

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Sustainable decision making under uncertainty: A case study in dredged material management