Water quality models: Tools for the analysis of data, knowledge, and decisions

Varis, O. (1994). Water quality models: Tools for the analysis of data, knowledge, and decisions. Water Science & Technology 30 (2) 13-19.

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Due to the rapid development of computational problem solving technologies, both in theoretical terms and in applications, the need for methodological diffusion across borders between traditional disciplines is increasingly important. Moreover, we should be able to use rationally approaches from very different methodological families. This study summarises 27 case studies on water quality and fisheries management, in which a variety of computational techniques have been used. Regarding philosophical orientation of the approaches, they are clustered to empirical, deterministic, and pragmatic ones. The roles of inductive and deductive components in inference are discussed, and the approaches are screened with respect to the applied (decision support) and theoretical (scientific) aspects of the studies. The relative roles of logical and relational thinking and experience are also considered. The decision support feature is discussed starting from the needs of directive, strategic, tactical, and operational management. Conclusions include a strong emphasis on the need to utilize a variety of problem solving tools to cope with the multiple tasks set for water quality models, including data analysis, knowledge processing, and decision support.

Item Type: Article
Uncontrolled Keywords: Case studies; Data interpretation; Decision making; Economic analysis; Environmental impact; Fish management; Fisheries; Fishery management; Mathematical models; Model studies; Pollution control; Pollution effects; Simulation; Statistical analysis; Statistics; Water pollution; Water quality
Research Programs: Regional Water Policies (RWP)
Bibliographic Reference: Water Science and Technology; 30(2):13-19 (1994)
Related URLs:
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 02:03
Last Modified: 27 Aug 2021 17:35
URI: https://pure.iiasa.ac.at/3819

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