Frontiers in Water | Water and Artificial Intelligence

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

2,374 views
2 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

4,014 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

4,639 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

4,787 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

3,477 views
6 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

7,077 views
28 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

2,913 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

3,754 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

8,492 views
24 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

3,315 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

2,730 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

3,217 views
2 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

4,276 views
19 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

2,789 views
4 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

4,712 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

6,023 views
16 citations

40 articles

articles

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