Abstract
The comprehensive water quality index (CWQI) reflects the comprehensive pollution status of rivers through mathematical statistics of several water quality indicators. Using computational mathematical simulations, high-confidence CWQI predictions can be obtained based on limited water quality monitoring samples. At present, most of the CWQI reported in the literature are based on conventional indicators such as nitrogen and phosphorus levels, and do not include the petroleum hydrocarbons levels. This article takes a typical river in eastern China as an example, based on the 1-year monitoring at 20 sampling sets, a CWQI containing five factors, TN, NH4+-N, TP, ∑n-Alks, and ∑PAHs was established, and further predicted by a Monte-Carlo model. The predicted CWQI for each monitoring section is above 0.7, indicating that most of the monitoring sections are moderately polluted, and some sections are seriously polluted. The Spearman rank correlation coefficient analysis results show that TN, ∑PAHs, and ∑n-Alks are the main factors influencing the water quality, especially the petroleum hydrocarbons have a significant impact on the middle and lower reaches due to shipping. In the future, more attention should be paid to petroleum hydrocarbon organic pollutants in the water quality evaluation of similar rivers.
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