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Analysis on the spatiotemporal characteristics of water quality and trophic states in Tiegang Reservoir: A public drinking water supply reservoir in South China

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Published under licence by IOP Publishing Ltd
, , Citation Yun-long Song et al 2017 IOP Conf. Ser.: Earth Environ. Sci. 81 012085 DOI 10.1088/1755-1315/81/1/012085

1755-1315/81/1/012085

Abstract

Shenzhen is the most densely populated city in China and with a severe shortage of water. The per capita water resource is less than 200 m3, which is approximately 1/12 of the national average level. In 2016, nearly 90% of Shenzhen's drinking water needed to be imported from the Pearl River. After arrived at Shenzhen, overseas water was firstly stockpiled in local reservoirs and then was supplied to nearby water works. Tiegang Reservoir is the largest drinking water supply reservoir and its water quality has played an important role to the city's drinking water security. A fifteen-month's field observation was conducted from April 2013 to June 2014 in Tiegang Reservoir, in order to analyze the temporal and spatial distribution of water quality factors and seasonal variation of trophic states. One-way ANOVA showed that significant difference was found in water quality factors on month (p<0.005). The spatial heterogeneity of water quality was obvious (p<0.05). The distribution pattern of WT, TOC, Silicate, NO3 --N, TN and Fe was pre-rainy period > latter rainy period > high temperature and rain free period > temperature jump period > winter drought period, while SD showed the contrary. Two-way ANOVA showed that months rather than locations were the key influencing factors of water quality factors succession. Tiegang reservoir was seriously polluted by TN, as a result WQI were at IV∼V level. If TN was not taken into account, WQI were atI∼III level. TLI (Σ) were about 35∼60, suggesting Tiegang reservoir was in mesotrophic and light-eutrophic trophic states. The WQI and TLI (Σ) in sampling sites 9 and 10 were poorer than that of other sites. The 14 water quality factors were divided into 5 groups by factor analysis (FA). The total interpretation rate was 73.54%. F1 represents the climatic change represented by water temperature. F2 and F4 represent the concentration of nutrients. F3 and F5 represent the sensory indexes of water body, such as turbidity, transparency. The FA results indicated that water quality potential risk factors was total nitrogen (TN), and potential risk factors also include chlorophyll-a and nitrate nitrogen (NO3 --N).

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10.1088/1755-1315/81/1/012085