Water quality assessment for Ulansuhai Lake using fuzzy clustering and pattern recognition

• Published in: Chinese journal of oceanology and limnology Vol. 26; no. 3; pp. 339 - 344
• Main Authors: Ren, Chuntao, Li, Changyou, Jia, Keli, Zhang, Sheng, Li, Weiping, Cao, Youling
• Format: Journal Article
• Language: English
• Published: Heidelberg SP Science Press 01.08.2008; Springer Nature B.V; Inner Mongolia Survey & Design Institute of Water Conservancy & Hydropower, Huhhot 010020, China
• Subjects: Algorithms; Arid climates; Aridity; Clustering; Earth and Environmental Science; Earth Sciences; Fuzzy logic; Lakes; Limnology; Marine; Oceanography; Pattern recognition; Physics; Quality assessment; Quality control; Water quality; Water quality assessments; Water use; China, People's Rep., Inner Mongolia; China, People's Rep; transitive closure method; partitioning of water quality; ISODATA clustering algorithm; fuzzy pattern recognition method
• ISSN: 0254-4059; 2096-5508; 1993-5005; 2523-3521
• DOI: 10.1007/s00343-008-0339-2

Water quality assessment of lakes is important to determine functional zones of water use. Considering the fuzziness during the partitioning process for lake water quality in an arid area, a multiplex model of fuzzy clustering with pattern recognition was developed by integrating transitive closure method, ISODATA algorithm in fuzzy clustering and fuzzy pattern recognition. The model was applied to partition the Ulansuhai Lake, a typical shallow lake in arid climate zone in the west part of Inner Mongolia, China and grade the condition of water quality divisions. The results showed that the partition well matched the real conditions of the lake, and the method has been proved accurate in the application.