The Influence of Equipment Bias on Reported Temperature Trends: Implications for River Temperature Monitoring Networks
Year: 2025
Type: article
Abstract: ABSTRACT River temperature is an important control on ecosystem health. Concerns around climate change impacts and availability of lower cost sensors have led to an increase in temperature monitoring of aquatic environments. While equipment biases are typically small compared to daily, seasonal, and spatial temperature variability at catchment scales, they can be large in the context of long‐term temporal trends. Failure to address issues of quality control and calibration can thus affect the detection, direction, and magnitude of reported temperature trends. This study uses a 35‐year river temperature time series, collected in the Girnock Burn, Scotland, to illustrate the potential influence of equipment (datalogger/sensor) bias on reported trends. Non‐linear, seasonally varying trends were observed, with summer months showing the greatest positive trends. Calibration experiments comparing historical and contemporary equipment with a calibrated internal reference logger revealed that older dataloggers (pre‐2007) exhibited coarse reporting resolutions and measurement rounding resulting in positive and negative biases depending on the equipment make and model. Recent dataloggers collected data at a higher reporting resolution, where operational rounding issues were not relevant, and exhibit only relatively minor biases, even before calibration. Comparison of raw and bias‐corrected temperature trends showed that uncorrected time series exhibited moderated temporal trends due to positive biases prior to 1998 and negative biases between 1998 and 2007. This study illustrates the importance of metadata in interpreting long‐term time series and the need for appropriate calibration and quality control procedures for temperature monitoring networks, especially where long‐term trends are of interest.
Source: River Research and Applications
DOI: 10.1002/rra.70012
Authors: Faye L. Jackson, Robert J. Fryer, Denise Stirling, Iain A. Malcolm
Institutions: Scottish Government, University of Aberdeen
Language: English
Subfield: Management, Monitoring, Policy and Law
Field: Environmental Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4412196789