Preprints
https://doi.org/10.5194/egusphere-2023-217
https://doi.org/10.5194/egusphere-2023-217
01 Mar 2023
 | 01 Mar 2023

Forecasting estuarine salt intrusion in the Rhine-Meuse delta using an LSTM model

Bas Johan Marinus Wullems, Claudia Catharina Brauer, Fedor Baart, and Albrecht Henricus Weerts

Abstract. Estuarine salt intrusion causes problems with freshwater availability in many deltas. Water managers require timely and accurate forecasts to be able to mitigate and adapt to salt intrusion. Data-driven models derived with machine learning are ideally suited for this, as they can mimic complex non-linear systems and are computationally efficient. We set up a Long Short Term Memory (LSTM) model to forecast salt intrusion in the Rhine-Meuse delta. It forecasts chloride concentrations up to 7 days ahead at Krimpen aan den IJssel, an important location for freshwater provision. The model forecasts baseline concentrations and peak timing well, but peak height is underestimated, a problem that becomes worse with increasing lead time. Between lead times of 1 and 7 days, forecast precision declines from 0.9 to 0.7 and forecast recall declines from 0.7 to 0.5 on average. Given these results, we aim to extend the model to other locations in the delta. We expect that a similar setup can work in other deltas, especially those with a similar or simpler channel network.

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Journal article(s) based on this preprint

27 Oct 2023
Forecasting estuarine salt intrusion in the Rhine–Meuse delta using an LSTM model
Bas J. M. Wullems, Claudia C. Brauer, Fedor Baart, and Albrecht H. Weerts
Hydrol. Earth Syst. Sci., 27, 3823–3850, https://doi.org/10.5194/hess-27-3823-2023,https://doi.org/10.5194/hess-27-3823-2023, 2023
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

Short summary
In deltas, salt water sometimes intrudes far inland and causes problems with freshwater...
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