科研成果

Various multivariate statistical methods including cluster analysis (CA), discriminant analysis (DA), factor analysis (FA), and principal component analysis (PCA) were used to explain the spatial and temporal patterns of surface water pollution in Lake Dianchi. The dataset, obtained during the period 2003-2007 from the Kunming Environmental Monitoring Center, consisted of 12 variables surveyed monthly at eight sites. The CA grouped the 12 months into two groups, August-September and the remainder, and divided the lake into two regions based on their different physicochemical properties and pollution levels. The DA showed the best results for data reduction and pattern recognition in both temporal and spatial analysis. It calculated four parameters (TEMP, pH, COD(Mn), and Chl-a) to 85.4% correct assignment in the temporal analysis and three parameters (BOD, NHNH(4)(+)-N, and TN) to almost 71.7% correct assignment in spatial analysis of the two clusters. The FA/PCA applied to datasets of two special clusters of the lake calculated four factors for each region, capturing 72.5% and 62.5% of the total variance, respectively. Strong loadings included DO, BOD, TN, COD(Cr), COD(Mn), NH(4)(+)-N, TP, and EC. In addition, box-whisker plots and GIS further facilitated and supported the multivariate analysis results.

Recent studies of Chesapeake Bay hypoxia suggest higher susceptibility to hypoxia in years after the 1980s. We used two simple mechanistic models and Bayesian estimation of their parameters and prediction uncertainty to explore the nature of this regime shift. Model estimates show increasing nutrient conversion efficiency since the 1980s, with lower DO concentrations and large hypoxic volumes as a result. In earlier work, we suggested a 35% reduction from the average 1980-1990 total nitrogen load would restore the Bay to hypoxic volumes of the 1950s-1970s. With Bayesian inference, our model indicates that, if the physical and biogeochemical processes prior to the 1980s resume, the 35% reduction would result in hypoxic volume averaging 2.7 km(3) in a typical year, below the average hypoxic volume of 1950s-1970s. However, if the post-1980 processes persist the 35% reduction would result in much higher hypoxic volume averaging 6.0 km(3). Load reductions recommended in the 2003 agreement will likely meet dissolved oxygen attainment goals if the Bay functions as it did prior to the 1980s; however, it may not reach those goals if current processes prevail.

Comprehensive evaluation of the water environment for effective water quality management is complicated by a considerable number of factors and uncertainties. It is difficult to combine micro-evaluation with the macro-evaluation process. To effectively eliminate the subjective errors of the traditional analytic hierarchy process (AHP), a new modeling approach—the analytic hierarchy process and grey target theory (AHP-GTT) systematic model—is presented in this study to evaluate water quality in a certain watershed. A case study of applying the AHP-GTT systematic model to the evaluation and analysis of the water environment was conducted in the Yibin section of the Yangtze River, China. The micro-evaluation is based on defining the weights of indices of the water quality (IWQ) of each water cross-section, while the macro-evaluation is based on calculating the comprehensive indices of water environmental quality and analyzing the tendency of the water environment of each cross-section. The results indicated that the Baixi and Shuidongmen sections are seriously polluted areas, with the tendencies of becoming worse. Also, the key IWQs of these two cross-sections are 5-day biochemical oxygen demand and chemical oxygen demand of permanganate, respectively.