Validation of a model appropriateness framework using the Elbe decision support system

YuePing Xu, Martijn J. Booij

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Abstract

This paper describes validation of an appropriateness framework, which has been developed in a former study, to determine appropriate models under uncertainty in a decision support system for river basin management. Models are regarded as ‘appropriate’ if they produce final outputs within adequate uncertainty bands that enable decision-makers to distinguish or rank different river engineering measures. The appropriateness framework has been designed as a tool to stimulate the use of models in decisionmaking under uncertainty and to strengthen the communication between modelers and decision-makers. Through the application to a different river with different objectives in this validation study from the river used in the development stage, this paper investigates whether the appropriateness framework works in a different situation than it was designed for. Recommendations from the development stage are taken into account in this validation case study as well. The final results from the study showed a successful validation of the appropriateness framework and suggested further possibilities for the application in decision support systems for river basin management.
Original languageUndefined
Title of host publicationDecision Support Systems in Agriculture, Food and the Environment: Trends, Applications and Advances
EditorsBasil Manos, Konstantinos Paparrizos, Nikolaos Matsatsinis, Jason Papathanasiou
Place of PublicationHershey, USA
PublisherInformation Science Reference
Pages193-218
Number of pages554
ISBN (Print)978-1-61520-881-4
DOIs
Publication statusPublished - 2010

Publication series

Name
PublisherInformation Science Reference

Keywords

  • IR-78681
  • METIS-271675

Cite this

Xu, Y., & Booij, M. J. (2010). Validation of a model appropriateness framework using the Elbe decision support system. In B. Manos, K. Paparrizos, N. Matsatsinis, & J. Papathanasiou (Eds.), Decision Support Systems in Agriculture, Food and the Environment: Trends, Applications and Advances (pp. 193-218). Hershey, USA: Information Science Reference. https://doi.org/10.4018/978-1-61520-881-4.ch010