Quality assurance in model based water management - review of existing practice and outline of new approaches

  • Authors:

  • Jens Christian Refsgaard;Hans Jørgen Henriksen;William G. Harrar;Huub Scholten;Ayalew Kassahun

  • Affiliations:

  • Geological Survey of Denmark and Greenland (GEUS), Øster Voldgade 10, DK-1350 Copenhagen K, Denmark;Geological Survey of Denmark and Greenland (GEUS), Øster Voldgade 10, DK-1350 Copenhagen K, Denmark;Geological Survey of Denmark and Greenland (GEUS), Øster Voldgade 10, DK-1350 Copenhagen K, Denmark;Wageningen University (WU), Dreijenplein 2, 6703 HB, Wageningen, The Netherlands;Wageningen University (WU), Dreijenplein 2, 6703 HB, Wageningen, The Netherlands

  • Venue:
  • Environmental Modelling & Software
  • Year:
  • 2005

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Abstract

Quality assurance (QA) is defined as protocols and guidelines to support the proper application of models. In the water management context we classify QA guidelines according to how much focus is put on the dialogue between the modeller and the water manager as: (Type 1) Internal technical guidelines developed and used internally by the modeller's organisation; (Type 2) Public technical guidelines developed in a public consensus building process; and (Type 3) Public interactive guidelines developed as public guidelines to promote and regulate the interaction between the modeller and the water manager throughout the modelling process. State-of-the-art QA practices vary considerably between different modelling domains and countries. It is suggested that these differences can be explained by the scientific maturity of the underlying discipline and differences in modelling markets in terms of volume of jobs outsourced and level of competition. The structure and key aspects of new generic guidelines and a set of electronically based supporting tools that are under development within the HarmoniQuA project are presented. Model credibility can be enhanced by a proper modeller-manager dialogue, rigorous validation tests against independent data, uncertainty assessments, and peer reviews of a model at various stages throughout its development.