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Article

Neural Structures to Predict River Stages in Heavily Urbanized Catchments

1
Department of Electronics, Informatiom, and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
2
Agenzia Interregionale per il Fiume Po, 43121 Parma, Italy
3
Ufficio dei Corsi D’acqua, 6501 Bellinzona, Switzerland
*
Author to whom correspondence should be addressed.
Academic Editors: Celestine Iwendi and Thippa Reddy Gadekallu
Water 2022, 14(15), 2330; https://doi.org/10.3390/w14152330
Received: 19 June 2022 / Revised: 22 July 2022 / Accepted: 24 July 2022 / Published: 27 July 2022
(This article belongs to the Special Issue AI and Deep Learning Applications for Water Management)
Accurate flow forecasting may support responsible institutions in managing river systems and limiting damages due to high water levels. Machine-learning models are known to describe many nonlinear hydrological phenomena, but up to now, they have mainly provided a single future value with a fixed information structure. This study trains and tests multi-step deep neural networks with different inputs to forecast the water stage of two sub-alpine urbanized catchments. They prove effective for one hour ahead flood stage values and occurrences. Convolutional neural networks (CNNs) perform better when only past information on the water stage is used. Long short-term memory nets (LSTMs) are more suited to exploit the data coming from the rain gauges. Predicting a set of water stages over the following hour rather than just a single future value may help concerned agencies take the most urgent actions. The paper also shows that the architecture developed for one catchment can be adapted to similar ones maintaining high accuracy. View Full-Text
Keywords: machine learning; neural networks; multi-step ahead; flood forecasting; sub-alpine catchments; Lura and Laveggio rivers machine learning; neural networks; multi-step ahead; flood forecasting; sub-alpine catchments; Lura and Laveggio rivers
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MDPI and ACS Style

Chiacchiera, A.; Sai, F.; Salvetti, A.; Guariso, G. Neural Structures to Predict River Stages in Heavily Urbanized Catchments. Water 2022, 14, 2330. https://doi.org/10.3390/w14152330

AMA Style

Chiacchiera A, Sai F, Salvetti A, Guariso G. Neural Structures to Predict River Stages in Heavily Urbanized Catchments. Water. 2022; 14(15):2330. https://doi.org/10.3390/w14152330

Chicago/Turabian Style

Chiacchiera, Annunziata, Fabio Sai, Andrea Salvetti, and Giorgio Guariso. 2022. "Neural Structures to Predict River Stages in Heavily Urbanized Catchments" Water 14, no. 15: 2330. https://doi.org/10.3390/w14152330

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