Water Quality Assessment and Pollution Source Identification of the Eastern Poyang Lake Basin Using Multivariate Statistical Methods

Abstract

Multivariate statistical methods including cluster analysis (CA), discriminant analysis (DA) and component analysis/factor analysis (PCA/FA), were applied to explore the surface water quality datasets including 14 parameters at 28 sites of the Eastern Poyang Lake Basin, Jiangxi Province of China, from January 2012 to April 2015, characterize spatiotemporal variation in pollution and identify potential pollution sources. The 28 sampling stations were divided into two periods (wet season and dry season) and two regions (low pollution and high pollution), respectively, using hierarchical CA method. Four parameters (temperature, pH, ammonia-nitrogen (NH 4 -N), and total nitrogen (TN)) were identified using DA to distinguish temporal groups with close to 97.86% correct assignations. Again using DA, five parameters (pH, chemical oxygen demand (COD), TN, Fluoride (F), and Sulphide (S)) led to 93.75% correct assignations for distinguishing spatial groups. Five potential pollution sources including nutrients pollution, oxygen consuming organic pollution, fluorine chemical pollution, heavy metals pollution and natural pollution, were identified using PCA/FA techniques for both the low pollution region and the high pollution region. Heavy metals (Cuprum (Cu), chromium (Cr) and Zinc (Zn)), fluoride and sulfide are of particular concern in the study region because of many open-pit copper mines such as Dexing Copper Mine. Results obtained from this study offer a reasonable classification scheme for low-cost monitoring networks. The results also inform understanding of spatio-temporal variation in water quality as these topics relate to water resources management.

Spatiotemporal Variability in the Water Quality of Poyang Lake and Its Associated Responses to Hydrological Conditions

“…As a typical flushing lake, Poyang Lake has a relatively shorter water retention time (7 days to 30 days) during different water regimes [28], in comparison with Tai Lake (270 days) and Chao Lake (136 days) [29,30]. Spatially, site 1 has the highest RSs,p for TN, TP, and NH4-N, which may be attributed that the Rao River was characterized with highest pollutants concentration [31] (Figure S1), with average fluxes of 0.54 kg/s and 0.05 kg/s for NH4-N and TP in 2009-2011, which were approximately 7 and 2 times higher than the Xiu River. The field survey also reveals that the year-round dredging activities near site 1 may remarkably change the topography of the lakebed and dredge up substantial sediment.…”

“…This can be explained by the fact that although the velocities were lower in lake phase, the five tributaries produce more freshwater discharge in the lake phase than in the river phase (Figure 9), thereby effectively diluting the contaminants in each site. In addition, there are more aquatic organisms in lake phase than in the river phase, which consuming more nutrients [31]. The impoundment of the Three Gorges Reservoir also causes a large flow gradient from Hukou to the Yangtze River in the river phase, thereby weakening the self-purification capability of Poyang Lake [35].…”

Identification and Quantification of Physicochemical Parameters Influencing Chlorophyll-a Concentrations through Combined Principal Component Analysis and Factor Analysis: A Case Study of the Yuqiao Reservoir in China

“…Conversely, PCA can identify the influencing parameters but cannot explain their meaning [30,32,42]. Duan et al [53] applied PCA/FA to study Poyang Lake; however, this study only extracted the main influencing physicochemical parameters, and did not built a quantitative model. In this study, the combination of FA and PCA overcame the above shortfalls.…”

The Water Pollution Policy Regime Shift and Boundary Pollution: Evidence from the Change of Water Pollution Levels in China

“…Six ministries jointly formulated and issued the specific assessment approach in April 2009, which did not form a rigid constraint until the first assessment came out in June 2011. Failures to meet water quality targets have affected the promotion of local officials since then [30].…”