Article

How climate change erodes short-term lake-temperature predictability: informing climate resilient lake forecasting

Details

Citation

Beckmann DA, Werther M, Shatwell T, Spyrakos E, Hunter P & Jones ID (2026) How climate change erodes short-term lake-temperature predictability: informing climate resilient lake forecasting. Water Research X, 30, Art. No.: 100457. https://doi.org/10.1016/j.wroa.2025.100457

Abstract
Climate warming threatens short-term environmental forecast skill, yet its effect on water quality predictability is largely unquantified. Here, we demonstrate a new approach for assessing climate change effects on lake forecasts. Random forest (RF) and gated recurrent unit network models were trained on data from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) Local Lakes Sector (five central-European lakes, four hydrodynamic models) and then used to forecast daily lake surface temperature 14 days ahead for 2060 - 2100 under four climate scenarios. We then varied (i) sensor-sampling interval (3, 7, 14 days) and (ii) training-set length (1 - 30 years). Under the strongest forcing (SSP585), the summer mean absolute error (MAE) of worst-affected lake, Esthwaite, rose by 0.14 °C (from 1.75 to 1.89 °C), driven by higher day-to-day temperature volatility (R² = 0.78). For this lake, extending the training set from 5 to 20 years or shortening sampling from 14 to 3 days reduced summer MAE by 0.11 and 0.17 °C, effectively offsetting the volatility caused by climate change. In winter, forecast error declined for four lakes because warmer, more stratified conditions simplified surface-layer dynamics. Thus, modest investments in monitoring cadence or historical record length can preserve forecast skill, even under extreme climate change. More broadly, this highlights a largely unexplored potential use for climate scenario projections: informing the design of climate resilient lake monitoring systems.

Keywords
Forecasting; Machine learning; Water quality; Climate change

Journal
Water Research X: Volume 30

StatusPublished
FundersUniversity of Stirling
Publication date31/01/2026
Date accepted by journal22/11/2025
URLhttp://hdl.handle.net/1893/37633
PublisherElsevier BV
ISSN2589-9147

People (5)

Mr Daniel Atton Beckmann

Mr Daniel Atton Beckmann

PhD Researcher, Biological and Environmental Sciences

Professor Peter Hunter

Professor Peter Hunter

Professor, Biological and Environmental Sciences

Dr Ian Jones

Dr Ian Jones

Lecturer in Environmental Sensing, Biological and Environmental Sciences

Professor Evangelos Spyrakos

Professor Evangelos Spyrakos

Professor, Biological and Environmental Sciences

Dr Mortimer Werther

Dr Mortimer Werther

Honorary Research Fellow, Biological and Environmental Sciences

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