Frontiers in Water | Water and Artificial Intelligence

Original Research

Published on 26 Jan 2024

Fuzzy C-Means clustering for physical model calibration and 7-day, 10-year low flow estimation in ungaged basins: comparisons to traditional, statistical estimates

in Water and Artificial Intelligence

Andrew DelSanto
Richard N. Palmer
Konstantinos Andreadis

Frontiers in Water

doi 10.3389/frwa.2024.1332888

2,518 views
2 citations

Original Research

Published on 17 Jan 2024

Operational low-flow forecasting using LSTMs

in Water and Artificial Intelligence

Jing Deng
Anaïs Couasnon
Ruben Dahm
Markus Hrachowitz
Klaas-Jan van Heeringen
Hans Korving
Albrecht Weerts
Riccardo Taormina

Frontiers in Water

doi 10.3389/frwa.2023.1332678

4,918 views
4 citations

Original Research

Published on 13 Dec 2023

Investigating machine learning and ensemble learning models in groundwater potential mapping in arid region: case study from Tan-Tan water-scarce region, Morocco

in Water and Artificial Intelligence

Abdessamad Jari
El Mostafa Bachaoui
Soufiane Hajaj
Achraf Khaddari
Younes Khandouch
Abderrazak El Harti
Amine Jellouli
Mustapha Namous

Frontiers in Water

doi 10.3389/frwa.2023.1305998

5,187 views
14 citations

Original Research

Published on 06 Dec 2023

Advancing deep learning-based detection of floating litter using a novel open dataset

in Water and Artificial Intelligence

Tianlong Jia
Andre Jehan Vallendar
Rinze de Vries
Zoran Kapelan
Riccardo Taormina

Frontiers in Water

doi 10.3389/frwa.2023.1298465

5,069 views
18 citations

Original Research

Published on 27 Oct 2023

NeuralFlood: an AI-driven flood susceptibility index

in Water and Artificial Intelligence

Justice Lin
Chhayly Sreng
Emma Oare
Feras A. Batarseh

Frontiers in Water

doi 10.3389/frwa.2023.1291305

10,841 views
11 citations

Original Research

Published on 17 Oct 2023

An active learning convolutional neural network for predicting river flow in a human impacted system

in Water and Artificial Intelligence

Scott M. Reed

Frontiers in Water

doi 10.3389/frwa.2023.1271780

2,505 views
6 citations

Original Research

Published on 14 Sep 2023

The contribution of remote sensing and input feature selection for groundwater level prediction using LSTM neural networks in the Oum Er-Rbia Basin, Morocco

in Water and Artificial Intelligence

Tarik Bouramtane
Marc Leblanc
Ilias Kacimi
Hamza Ouatiki
Abdelghani Boudhar

Frontiers in Water

doi 10.3389/frwa.2023.1241451

4,351 views
12 citations

Original Research

Published on 13 Jul 2023

Application of machine learning and deep neural networks for spatial prediction of groundwater nitrate concentration to improve land use management practices

in Water and Artificial Intelligence

Divas Karimanzira
Jonas Weis
Andreas Wunsch
Linda Ritzau
Tanja Liesch
Marc Ohmer

Frontiers in Water

doi 10.3389/frwa.2023.1193142

4,966 views
13 citations

Original Research

Published on 30 Jun 2023

Forecasting bacteriological presence in treated drinking water using machine learning

in Water and Artificial Intelligence

Grigorios Kyritsakas
Joby Boxall
Vanessa Speight

Frontiers in Water

doi 10.3389/frwa.2023.1199632

5,027 views
10 citations

Original Research

Published on 23 Jun 2023

Evaluating deep learning architecture and data assimilation for improving water temperature forecasts at unmonitored locations

in Water and Artificial Intelligence

Jacob A. Zwart
Jeremy Diaz
Scott Hamshaw
Samantha Oliver
Jesse C. Ross
Margaux Sleckman
Alison P. Appling
Hayley Corson-Dosch
Xiaowei Jia
Jordan Read

Frontiers in Water

doi 10.3389/frwa.2023.1184992

3,841 views
8 citations

Original Research

Published on 05 Jun 2023

Predicting streamflow with LSTM networks using global datasets

in Water and Artificial Intelligence

Katharina Wilbrand
Riccardo Taormina
Marie-Claire ten Veldhuis
Martijn Visser
Markus Hrachowitz
Jonathan Nuttall
Ruben Dahm

Frontiers in Water

doi 10.3389/frwa.2023.1166124

7,585 views
34 citations

Editorial

Published on 01 Jun 2023

Editorial: Data-driven machine learning for advancing hydrological and hydraulic predictability

in Water and Artificial Intelligence

Dan Lu
Tiantian Yang
Xiaofeng Liu

Frontiers in Water

doi 10.3389/frwa.2023.1215966

3,067 views
2 citations

Original Research

Published on 24 May 2023

Deep learning of model- and reanalysis-based precipitation and pressure mismatches over Europe

in Water and Artificial Intelligence

Kaveh Patakchi Yousefi
Stefan Kollet

Frontiers in Water

doi 10.3389/frwa.2023.1178114

4,072 views
6 citations

Original Research

Published on 21 Apr 2023

Uncertainty quantification of machine learning models to improve streamflow prediction under changing climate and environmental conditions

in Water and Artificial Intelligence

Siyan Liu
Dan Lu
Scott L. Painter
Natalie A. Griffiths
Eric M. Pierce

Frontiers in Water

doi 10.3389/frwa.2023.1150126

9,198 views
26 citations

Original Research

Published on 17 Apr 2023

Short-term runoff forecasting in an alpine catchment with a long short-term memory neural network

in Water and Artificial Intelligence

Corinna Frank
Marc Rußwurm
Javier Fluixa-Sanmartin
Devis Tuia

Frontiers in Water

doi 10.3389/frwa.2023.1126310

3,532 views
5 citations

Original Research

Published on 22 Mar 2023

Hydraulic head change predictions in groundwater models using a probabilistic neural network

in Water and Artificial Intelligence

Mathias Busk Dahl
Troels Norvin Vilhelmsen
Torben Bach
Thomas Mejer Hansen

Frontiers in Water

doi 10.3389/frwa.2023.1028922

2,928 views
2 citations

Original Research

Published on 21 Mar 2023

Simulating hydrological extremes for different warming levels–combining large scale climate ensembles with local observation based machine learning models

in Water and Artificial Intelligence

Sandra M. Hauswirth
Karin van der Wiel
Marc F. P. Bierkens
Vincent Beijk
Niko Wanders

Frontiers in Water

doi 10.3389/frwa.2023.1108108

3,422 views
3 citations

Original Research

Published on 14 Mar 2023

Investigation of hydrometeorological influences on reservoir releases using explainable machine learning methods

in Water and Artificial Intelligence

Ming Fan
Lujun Zhang
Siyan Liu
Tiantian Yang
Dan Lu

Frontiers in Water

doi 10.3389/frwa.2023.1112970

4,662 views
22 citations

Original Research

Published on 14 Mar 2023

Super-resolution and uncertainty estimation from sparse sensors of dynamical physical systems

in Water and Artificial Intelligence

Adam M. Collins
Peter Rivera-Casillas
Sourav Dutta
Orie M. Cecil
Andrew C. Trautz
Matthew W. Farthing

Frontiers in Water

doi 10.3389/frwa.2023.1137110

3,005 views
5 citations

Original Research

Published on 08 Dec 2022

Seasonal prediction of Horn of Africa long rains using machine learning: The pitfalls of preselecting correlated predictors

in Water and Artificial Intelligence

Victoria M. H. Deman
Akash Koppa
Willem Waegeman
David A. MacLeod
Michael Bliss Singer
Diego G. Miralles

Frontiers in Water

doi 10.3389/frwa.2022.1053020

4,980 views
13 citations

Original Research

Published on 27 Jun 2022

Interpreting Deep Machine Learning for Streamflow Modeling Across Glacial, Nival, and Pluvial Regimes in Southwestern Canada

in Water and Artificial Intelligence

Sam Anderson
Valentina Radić

Frontiers in Water

doi 10.3389/frwa.2022.934709

6,314 views
18 citations

45 articles

articles

Fuzzy C-Means clustering for physical model calibration and 7-day, 10-year low flow estimation in ungaged basins: comparisons to traditional, statistical estimates

Operational low-flow forecasting using LSTMs

Investigating machine learning and ensemble learning models in groundwater potential mapping in arid region: case study from Tan-Tan water-scarce region, Morocco

Advancing deep learning-based detection of floating litter using a novel open dataset

NeuralFlood: an AI-driven flood susceptibility index

An active learning convolutional neural network for predicting river flow in a human impacted system

The contribution of remote sensing and input feature selection for groundwater level prediction using LSTM neural networks in the Oum Er-Rbia Basin, Morocco

Application of machine learning and deep neural networks for spatial prediction of groundwater nitrate concentration to improve land use management practices

Forecasting bacteriological presence in treated drinking water using machine learning

Evaluating deep learning architecture and data assimilation for improving water temperature forecasts at unmonitored locations

Predicting streamflow with LSTM networks using global datasets

Editorial: Data-driven machine learning for advancing hydrological and hydraulic predictability

Deep learning of model- and reanalysis-based precipitation and pressure mismatches over Europe

Uncertainty quantification of machine learning models to improve streamflow prediction under changing climate and environmental conditions

Short-term runoff forecasting in an alpine catchment with a long short-term memory neural network

Hydraulic head change predictions in groundwater models using a probabilistic neural network

Simulating hydrological extremes for different warming levels–combining large scale climate ensembles with local observation based machine learning models

Investigation of hydrometeorological influences on reservoir releases using explainable machine learning methods

Super-resolution and uncertainty estimation from sparse sensors of dynamical physical systems

Seasonal prediction of Horn of Africa long rains using machine learning: The pitfalls of preselecting correlated predictors

Interpreting Deep Machine Learning for Streamflow Modeling Across Glacial, Nival, and Pluvial Regimes in Southwestern Canada