Expert-based Bayesian Network modeling for environmental management

  • Bayesian Networks are computer-based environmental models that are frequently used to support decision-making under uncertainty. Under data scarce conditions, Bayesian Networks can be developed, parameterized, and run based on expert knowledge only. However, the efficiency of expert-based Bayesian Network modeling is limited by the difficulty in deriving model inputs in the time available during expert workshops. This thesis therefore aimed at developing a simple and robust method for deriving conditional probability tables from expert estimates in a time-efficient way. The design and application of this new elicitation and conversion method is demonstrated using a case study in Xinjiang, Northwest China. The key characteristics of this method are its time-efficiency and the approach to use different conversion tables based on varying levels of confidence. Although the method has its limitations, e.g. it can only be applied for variables with one conditioning variable; it provides the opportunity to support the parameterization of Bayesian Networks which would otherwise remain half-finished due to time constraints. In addition, a case study in the Murray-Darling Basin, Australia, is used to compare Bayesian Network types and software to improve the presentation clarity of large Bayesian Networks. Both case studies aimed at gaining insights on how to improve the applicability of Bayesian Networks to support environmental management.

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Author:Sina Kai Frank
Parent Title (German):Frankfurt hydrology paper ; 11
Series (Serial Number):Frankfurt Hydrology Paper (11)
Publisher:Univ., Inst. of Physical Geography
Place of publication:Frankfurt (Main)
Referee:Petra DöllORCiDGND, Martin Welp
Document Type:Doctoral Thesis
Year of Completion:2015
Year of first Publication:2015
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Granting Institution:Johann Wolfgang Goethe-Universität
Date of final exam:2015/03/09
Release Date:2015/05/15
Tag:Bayesian Network; environmental management; expert knowledge; participatory modeling
Page Number:215
Last Page:179
Institutes:Geowissenschaften / Geographie / Geowissenschaften
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Licence (German):License LogoDeutsches Urheberrecht