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Evaluation of sampling frequency impact on the accuracy of water quality status as determined considering different water quality monitoring objectives

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Abstract

Water quality sampling is a key element in tracking water quality monitoring objectives. However, frequencies adapted by different agencies might not be sufficient to provide an accurate indication of water quality status. In this study, data from low- and high-resolution water quality datasets were analyzed to determine the extent to which monitoring objectives could be achieved with different sampling frequencies, with a view to providing recommendations and best practices for water quality monitoring frequency in places with limited resources with which to implement a high-frequency monitoring plan. Water quality data from two watersheds (Maumee River and Raisin River) located in the Western Lake Erie Basin (WLEB) were used since these watersheds have consistent records over substantial periods of time, and the water quality data available have a high resolution (at least daily). The water quality constituents analyzed included suspended solids (SS), total phosphorus (TP), soluble reactive phosphorus (SRP), and nitrate + nitrite (NO2+3). Sources of pollutants for watersheds located in the WLEB include contributions from point sources like discharges from sewage treatment plants and non-point sources such as agricultural and urban storm runoff. Weekly, bi-weekly, monthly, and seasonal datasets were created from the original datasets, following different sampling rules based on the day of the week, week of the month, and month of the year. The resulting datasets were then compared to the original dataset to determine how the sampling frequency would affect the results obtained in a water quality assessment when different monitoring objectives are considered. Results indicated that constituents easily transported by water (such as sediments and nutrients) require more than 50 samples/year to provide a small error (< 10%) with a confidence interval of 95%. Monthly and seasonal sampling were found appropriate to report a stream’s prevailing water quality status and statistical properties. However, these resolutions might not be sufficient to capture long-term trends, in which case bi-weekly samples would be preferable. Limitations of low-resolution sampling frequency could be overcome by including rainfall events and random sampling during specific time windows as part of the monitoring plan.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

The authors are thankful to Maria Camila Fernandez for her work testing and conducting part of the exploratory analysis with the water quality data. Dr. Torres is also grateful to the Fulbright Program and the Colombian Institute of Educational Credit and Technical Studies Abroad (ICETEX) for providing the funding for his doctoral studies under the “Fulbright-Pasaporte a la Ciencia—Foco Alimentos” fellowship program.

Funding

This work was funded in part by USDA National Institute of Food and Agriculture, Hatch Project IND00000752.

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  1. Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN, USA

    Camilo Torres, Margaret W. Gitau & Bernard Engel

  2. Department of Basic Environmental Sciences, Universidad Tecnológica de Pereira, Pereira, Risaralda, Colombia

    Diego Paredes-Cuervo

  3. Department of Civil Engineering, Pontificia Universidad Javeriana, Bogotá, D.C, Colombia

    Camilo Torres

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Torres, C., Gitau, M.W., Paredes-Cuervo, D. et al. Evaluation of sampling frequency impact on the accuracy of water quality status as determined considering different water quality monitoring objectives. Environ Monit Assess 194, 489 (2022). https://doi.org/10.1007/s10661-022-10169-7

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