Eleven indicators of water quality in two areas of the Caohai Lake (Yangguanshan and the middle part) in Guizhou Province were measured seasonally in 2016. Trophic state index (TLI) and Surface Water Quality Standard (GB 3838—2002) were used to evaluate the trophic status of water quality, and principal component analysis (PCA) was conducted to assess the pollution level and main influential factors. Results demonstrated that: (1) The eleven indicators in both areas displayed significant seasonal variations, among which transparency and dissolved oxygen (DO) were highest in winter; while suspended solids (SPM) was highest in autumn. Except that in autumn, pH remained at about 8. TN, TP, NH4+-N and CODMn were in 0.58-2.27, 0.032-0.072, 0.059-0.364 and 4.28-6.79 mg/L, respectively and Chl.a ranged from 5.62 to 9.95 mg/m3, with the highest TN in autumn, the highest TP in autumn and winter, and highest CODMn and Chl.a in summer and autumn. (2) The TLI of both areas were slightly higher than 50 in autumn, indicating slight pollution, while in other seasons, the TLI ranged between 30 and 50, implying medium trophic state. Evaluation results from GB 3838—2002 show that the water quality in Yangguanshan belonged to class Ⅱ and Ⅲ, except for a few occasions; whereas in the middle part, the water quality was mainly class Ⅱ and Ⅳ. TN and CODMn were major influential factors, while TP and NH4+-N were at level Ⅱ throughout the year. (3) Principle component analysis revealed that the most important influencing factors of water quality in Yangguanshan were ions, nitrogen, organic matter, DO and Chl.a, while in the middle part were Chl.a, NH4+-N, SD, EC, TP, DO, WT and SPM. In conclusion, nitrogen and organic matters are the most important influencing factors and the fundamental causes of water quality in Yangguanshan and the middle part of Caohu Lake. Controlling the inputs of external nitrogen and organic matters would be the key to improving the water quality in Caohai Lake.
Key words
water quality assessment /
Caohai Lake /
seasonal variation /
trophic state index (TLI) /
principal component analysis (PCA)
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