WATER-QUALITY MODELS - TOOLS FOR THE ANALYSIS OF DATA, KNOWLEDGE, ANDDECISIONS

Due to the rapid development of computational problem solving technolo gies, both in theoretical terms and in applications, the need for meth odological 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 su mmarises 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 em pirical, deterministic, and pragmatic ones. The roles of inductive and deductive components in inference are discussed, and the approaches a re screened with respect to the applied (decision support) and theoret ical (scientific) aspects of the studies. The relative roles of logica l and relational thinking and experience are also considered. The deci sion 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, i ncluding data analysis, knowledge processing, and decision support.