Volume 17 Issue 1
Mar.  2024
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Qin Qian, Mengjie He, Frank Sun, Xinyu Liu. 2024: Monitoring and evaluation of the water quality of the Lower Neches River, Texas, USA. Water Science and Engineering, 17(1): 21-32. doi: 10.1016/j.wse.2023.10.002
Citation: Qin Qian, Mengjie He, Frank Sun, Xinyu Liu. 2024: Monitoring and evaluation of the water quality of the Lower Neches River, Texas, USA. Water Science and Engineering, 17(1): 21-32. doi: 10.1016/j.wse.2023.10.002

Monitoring and evaluation of the water quality of the Lower Neches River, Texas, USA

doi: 10.1016/j.wse.2023.10.002
Funds:

This work was supported by Center for Resiliency (CfR) at Lamar University (Grant No. 22PSS01).

  • Received Date: 2022-11-20
  • Accepted Date: 2023-09-23
  • Available Online: 2024-03-05
  • Increasing bacteria levels in the Lower Neches River caused by Hurricane Harvey has been of a serious concern. This study is to analyze the historical water sampling measurements and real-time water quality data collected with wireless sensors to monitor and evaluate water quality under different hydrological and hydraulic conditions. The statistical and Pearson correlation analysis on historical water samples determines that alkalinity, chloride, hardness, conductivity, and pH are highly correlated, and they decrease with increasing flow rate due to dilution. The flow rate has positive correlations with Escherichia coli, total suspended solids, and turbidity, which demonstrates that runoff is one of the causes of the elevated bacteria and sediment loadings in the river. The correlation between E. coli and turbidity indicates that turbidity greater than 45 nephelometric turbidity units in the Neches River can serve as a proxy for E. coli to indicate the bacterial outbreak. A series of statistical tools and an innovative two-layer data smoothing filter are developed to detect outliers, fill missing values, and filter spikes of the sensor measurements. The correlation analysis on the sensor data illustrates that the elevated sediment/bacteria/algae in the river is either caused by the first flush rain and heavy rain events in December to March or practices of land use and land cover. Therefore, utilizing sensor measurements along with rainfall and discharge data is recommended to monitor and evaluate water quality, then in turn to provide early alerts on water resources management decisions.

     

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