Journal of Environmental Management (2001) 63, 293–305 doi:10.1006/jema.2001.0483, available online at http://www.idealibrary.com on Identification of river water quality using the Fuzzy Synthetic Evaluation approach Ni-Bin Chang * , H. W. Chen and S. K Ning Department of Environmental Engineering National Cheng-Kung University Tainan, Taiwan, R.O.C. Received 21 November 1999; accepted 8 June 2001 Proper identification of water quality conditions in a river system based on limited observations is an essential task for meeting the goals of environmental management. Various classification methods have been used for estimating the changing status and usability of surface water in river basins. However, a discrepancy frequently arises from the lack of a clear distinction between each water utilisation mode, the uncertainty in the quality criteria employed and the vagueness or fuzziness embedded in the decision-making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies when describing integrated water quality conditions with respect to various chemical constituents, biological aspects, nutrients, and aesthetic qualities. This paper presents a comparative study using three fuzzy synthetic evaluation techniques to assess water quality conditions in comparison to the outputs generated by conventional procedures such as the Water Quality Index (WQI). Based on a set of data collected at seven sampling stations, a case study for the Tseng-Wen River system in Taiwan was used to demonstrate their application potential. The findings clearly indicate that the techniques may successfully harmonise inherent discrepancies and interpret complex conditions. A further, newly developed fuzzy synthetic evaluation approach described in this paper might also be useful for verifying water quality conditions for the Total Maximum Daily Load (TMDL) program and be helpful for constructing an effective water quality management strategy.  2001 Academic Press Keywords: water quality index, water quality management, fuzzy logic, fuzzy synthetic evaluation, environmental monitoring, fuzzy clustering, fuzzy pattern recognition. Introduction Many countries have introduced a scheme for river water quality monitoring and assessment, exam- ining separate stretches of freshwater in terms of their chemical, biological and nutrient constituents and overall aesthetic condition (Horton, 1965; Sii, 1993; Heinonen and Herve, 1994; and Dojlido et al., 1994). General indices are used as comprehensive evaluation instruments to help assess conditions at the earliest stage to clarify monitoring priorities for regulatory agencies dealing with pollution control problems. Numerous interpretations of water quality have been addressed in the literature. Horton (1965) made a pioneering attempt to study the general Ł Corresponding author. Email: a1211@mail.acku.edu.tw indices, selecting and weighting parameters. One well-known assessment methodology is the Water Quality Index (WQI), developed by the National Sanitation Foundation (NSF) using the Delphi technique as a tool in a formal assessment pro- cedure (Ott, 1978). WQI was originally designed to include nine constituents designed for making an integrated assessment of water quality conditions in order to meet utilisation goals. This was consid- ered a promising approach in the 1980s and 1990s. Considerable advances have since been made based on WQI using slightly modified concepts (Chou, 1990; Heinonen and Herve, 1994; Dojlido et al., 1994; Suvarna and Somashekar, 1997). However, discrepancies frequently arise from the lack of clear distinctions between each mode, the uncertainty in the quality criteria employed and the imprecision, vagueness, or fuzziness in the decision-making out- put values. Sometimes, it is difficult to judge water 0301–4797/01/110293C13 $35.00/0  2001 Academic Press