Comprehensive evaluation of water quality grades based on improved CRITIC and multidimensional connection cloud combination

Abstract This study proposes a comprehensive water quality assessment method for nine major plateau lakes in Yunnan Province, based on an improved CRITIC method combined with a multidimensional connectivity cloud model. Key water quality monitoring indicators (NH3‐N, COD, TP, TN, permanganate index, DO, pH) were selected, and the weights were determined using the improved CRITIC method, highlighting the impact of NH3‐N, COD, and TP. These weights were then integrated with a multidimensional connectivity cloud model to classify lake water quality levels. The results indicated the following water quality grades for the lakes: Dianchi (III), Fuxian Lake (I), Erhai (II), Xingyun Lake (I), Qilu Lake (II), Yilong Lake (II), Lugu Lake (I), Yangzonghai (II), and Chenghai (II). Compared to five conventional methods, the proposed approach better addresses the issues of fuzziness, randomness, and discreteness in water quality indicators, avoiding the boundary selection problems inherent in traditional methods. By combining the improved CRITIC method with a multidimensional connectivity cloud model, the study achieves more precise and reliable evaluations through objective weighting and comprehensive consideration of multiple indicators. This method offers a more accurate reflection of lake water quality conditions and provides a scientific basis for water quality management and decision‐making, demonstrating significant potential for application in the field of environmental science.