Assessment of river health based on a novel multidimensional similarity cloud model in the Lhasa River, Qinghai-Tibet Plateau

Rivers provide the basis for sustainable socio-economic development, but increasingly intense human activities poses a threat to river health. To comprehensively investigate the river health in the Qinghai-Tibet Plateau, China, the Lhasa River is selected as study area, and a comprehensive indicator system incorporating ecosystem integrity (physical habitat, water quantity and quality, aquatic life) and non-ecological performance (social services) is constructed. The random impacts of sampling methods and environmental factors on the accuracy of monitoring data are effectively reduced by the wavelet noise reduction. Combined weights of river health indicators are calculated using the minimum deviation principle. A novel multidimensional similarity cloud model (MSCM) is then developed for assessing river health with fuzzy monitoring data. Results show that the upper reaches of Lhasa River is healthy in terms of ecosystem integrity and non-ecological performance. And the health level exhibits significant spatial variability influenced by urban construction and water conservancy projects, with decreasing health level from upper to lower reaches. 52% of the sampling sites are at excellent or healthy levels, 40% are subhealthy, and 8% are unhealthy in the Lhasa River. Accordingly, recommendations and measures are proposed to improve river health level and explore sustainable water-management policies in the Qinghai-Tibet Plateau, China.