Prediction of total organic carbon and E. coli in rivers within the Milwaukee River basin using machine learning methods

Author:

Nafsin Nabila1ORCID,Li Jin1

Affiliation:

1. Department of Civil and Environmental Engineering, University of Wisconsin-Milwaukee, WI 53211, USA

Abstract

Ensemble-hybrid ML models can explain and predict the variability in water quality parameters and living microorganism behavior in natural streams with satisfactory prediction accuracies based on specific physicochemical parameters.

Publisher

Royal Society of Chemistry (RSC)

Reference41 articles.

1. Foreshore Sand as a Source of Escherichia coli in Nearshore Water of a Lake Michigan Beach

2. Milwaukee Riverkeeper , Milwaukee River Basin Report Card , Milwaukee Riverkeeper , 2018 , https://milwaukeeriverkeeper.org/wp-content/uploads/2019/11/2018MKERiverBasinReportCard.pdf

3. M.Burzynski , The State of the Milwaukee River Basin. A Report by the Wisconsin Department of Natural Resources , 2001 August , PUBL WT 704 2001, https://dnr.wi.gov/water/basin/milw/milwaukee_801.pdf

4. Monitoring and predicting the fecal indicator bacteria concentrations from agricultural, mixed land use and urban stormwater runoff

5. Using CANARY event detection software for water quality analysis in the Milwaukee River

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