Using the multidimensional synthesis methods with non-parameter test, multiple time scales analysis to assess water quality trend and its characteristics over the past 25 years in the Fuxian Lake, China

Fuxian Lake is one of the most important conservation areas in the southwest of China. Understanding the water-quality trend and characteristics is the basis of area protection for Fuxian Lake. This study combines of the Mann-Kendall, Mann-Kendall-Sneyers, water pollution index (WPI), the trophic state index and time series analysis to detect and characterize the water quality with a set of indicators: transparency (SD), permanganate index (IMn), total phosphorus (TP), total nitrogen (TN), biochemical oxygen demand (BOD5), ammonia nitrogen (NH3-N) and chlorophyll-a (Chl.a). Then, the characteristics are discussed on the scales of long-period, sections divided by the change point, and monthly data. Results show that the water quality of Fuxian Lake is at a good level but decreases consistently. Especially, the increasing trends of IMn, BOD5, and Chl.a pass the confidence limit of the Z value of 2.56. The year of 2007 was designated as the change point. The characteristics of pollution and typical components vary in the long-period series, between the two sections divided by the change point, and in the monthly data. In the long period, the TN and TP are typical pollution components. However, the IMn, BOD5, and Chl.a are typical components as the large changes of a 99.1% and 89.5% increase after the change point with respect to the former values, respectively. On the scale of monthly data of a typical year, the pollution grade and components varies within the years. The multidimensional synthesis methodology established by employing evaluation index systems from the aspects of pollution level, multi-attributes and the trophic state status could also be applied to detect and characterize the water quality of other water bodies. The results of the Fuxian Lake study can provide the base information and decision-making support for water quality management and area protection. (C) 2018 Elsevier B.V. All rights reserved.