Impute Water Temperature in the Swiss River Network Using LSTMs

Benjamin Fankhauser, Vidushi Bigler, Kaspar Riesen

2024

Abstract

Switzerland is home to the sources of major European rivers. As the thermal regime of rivers is crucial for the environment, the Federal Office for the Environment has been collecting discharge and water temperature data at 81 river water stations for several decades. However, despite diligent collection 30% of the water temperature data is missing due to various reasons. These missing data are problematic in many ways – for instance, in predicting water temperatures based on different models. To tackle this problem, we propose to use LSTMs for water temperature imputing. In particular, we introduce three different scenarios – depending on the available input data – to impute possible data gaps. Then, we propose several methods for each scenario. For our empirical evaluation, we engineer a novel dataset (with ground truth) by artificially introducing gaps of sizes 2, 10, 30 and 60 days in the middle of 90-day sequences. A rather simple interpolation baseline achieves a competitive RMSE on gaps of two days. For larger gaps, however, this simple method clearly fails, and the novel, far more sophisticated models significantly outperform both interpolation and the current state of the art in this application.

Paper Citation

in Harvard Style

Fankhauser B., Bigler V. and Riesen K. (2024). Impute Water Temperature in the Swiss River Network Using LSTMs. In Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM; ISBN 978-989-758-684-2, SciTePress, pages 732-738. DOI: 10.5220/0012358100003654

in Bibtex Style

@conference{icpram24,
author={Benjamin Fankhauser and Vidushi Bigler and Kaspar Riesen},
title={Impute Water Temperature in the Swiss River Network Using LSTMs},
booktitle={Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM},
year={2024},
pages={732-738},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012358100003654},
isbn={978-989-758-684-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM
TI - Impute Water Temperature in the Swiss River Network Using LSTMs
SN - 978-989-758-684-2
AU - Fankhauser B.
AU - Bigler V.
AU - Riesen K.
PY - 2024
SP - 732
EP - 738
DO - 10.5220/0012358100003654
PB - SciTePress