Monitoring stormwater road runoff quality with sensors: assessing seasonal effects on sensor performance

Today, the quality of stormwater runoff can be monitored with sensors. However, the effects of complex analytical conditions of stormwater on their performance have not yet been formally investigated. This study, therefore, focuses on evaluating the performance of turbidity, pH, and electrical conductivity sensors. The evaluation is based on a cross-examination using continuous field data and discrete data from laboratory analysis of 153 samples. The study site is situated in northern Sweden. Its geography enables and defines a specific focus of this study - investigating factors inherent in cold climates and urban environments that might influence monitoring strategies. Results indicate that field pH readings typically deviated less than 10% from laboratory values, while conductivity field and laboratory measurements showed a strong linear correlation (<i>R</i><sup>2</sup> = 0.99); their relative deviations varied within a range. In contrast, turbidity measurements faced significant challenges during the cold season, likely due to smaller particle sizes during studded tire use and winter road maintenance practices, showing no alignment with laboratory measurements (<i>R</i><sup>2</sup> = 0.12). The findings reveal, for the first time, that nephelometric ISO 7027-compliant turbidity instruments (90° near-IR scattering) may face limitations under cold-climate conditions. Seasonal changes in temperature, salinity, and flow did not affect turbidity accuracy.

Authors

Institutions

Publication Details

Journal
Water Science & Technology
Published
2025-08-15
DOI
https://doi.org/10.2166/wst.2025.125
Primary Topic
Urban Stormwater Management Solutions
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Monitoring stormwater road runoff quality with sensors: assessing seasonal effects on sensor performance

Kelsey Flanagan, Maria Viklander, Tone Merete Muthanna, Nikita Razguliaev
Water Science & Technology
Urban Stormwater Management Solutions
article

Monitoring stormwater road runoff quality with sensors: assessing seasonal effects on sensor performance

Kelsey Flanagan, Maria Viklander, Tone Merete Muthanna, Nikita Razguliaev
article en

Abstract

Today, the quality of stormwater runoff can be monitored with sensors. However, the effects of complex analytical conditions of stormwater on their performance have not yet been formally investigated. This study, therefore, focuses on evaluating the performance of turbidity, pH, and electrical conductivity sensors. The evaluation is based on a cross-examination using continuous field data and discrete data from laboratory analysis of 153 samples. The study site is situated in northern Sweden. Its geography enables and defines a specific focus of this study - investigating factors inherent in cold climates and urban environments that might influence monitoring strategies. Results indicate that field pH readings typically deviated less than 10% from laboratory values, while conductivity field and laboratory measurements showed a strong linear correlation (<i>R</i><sup>2</sup> = 0.99); their relative deviations varied within a range. In contrast, turbidity measurements faced significant challenges during the cold season, likely due to smaller particle sizes during studded tire use and winter road maintenance practices, showing no alignment with laboratory measurements (<i>R</i><sup>2</sup> = 0.12). The findings reveal, for the first time, that nephelometric ISO 7027-compliant turbidity instruments (90° near-IR scattering) may face limitations under cold-climate conditions. Seasonal changes in temperature, salinity, and flow did not affect turbidity accuracy.

Water Science & TechnologyVol. 92(4)
Luleå University of Technology (SE), Norwegian University of Science and Technology (NO)
VINNOVA
Openalex Percentile: Top 81%
Urban Stormwater Management Solutions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.