%0 Journal Article
%J Journal of Hydrology
%D 2024
%T Generative deep learning for probabilistic streamflow forecasting: conditional variational auto-encoder
%A Jahangir, M.S.
%A Quilty, J.
%B Journal of Hydrology
%V 629
%P 130498
%G eng
%U https://www.sciencedirect.com/science/article/pii/S0022169423014403

%0 Journal Article
%J Journal of Hydrology
%D 2023
%T Bayesian extreme learning machines for hydrological prediction uncertainty
%A Quilty, J.
%A Jahangir, M.S.
%A You, J.
%A Hughes, H.
%A Hah, D.
%A Tzoganakis, I.
%B Journal of Hydrology
%V 626
%P 130138
%G eng
%U https://www.sciencedirect.com/science/article/pii/S0022169423010806

%0 Journal Article
%J Journal of Hydrology
%D 2023
%T A quantile-based encoder-decoder framework for multi-step ahead runoff forecasting
%A Jahangir, M.S.
%A You, J.
%A Quilty, J.
%B Journal of Hydrology
%V 619
%P 129269
%G eng
%U https://www.sciencedirect.com/science/article/pii/S0022169423002111

%0 Journal Article
%J Pedosphere
%D 2022
%T Comparing the Soil Conservation Service model with new machine learning algorithms for predicting cumulative infiltration in semi-arid regions
%A Khabat Khosravi
%A TT Phuong
%A Rahim Barzegar
%A John Quilty
%A Mohammad T Alami
%B Pedosphere
%G eng
%U https://www.sciencedirect.com/science/article/pii/S1002016022000157

%0 Journal Article
%J Stochastic Environmental Research and Risk Assessment
%D 2022
%T Investigating the impact of input variable selection on daily solar radiation prediction accuracy using data-driven models: a case study in northern Iran
%A Mohammad Sina Jahangir
%A Seyed Mostafa Biazar
%A David Hah
%A John Quilty
%A Mohammad Isazadeh
%B Stochastic Environmental Research and Risk Assessment
%V 36
%P 225-249
%G eng
%U https://link.springer.com/article/10.1007/s00477-021-02070-5
%N 1

%0 Journal Article
%J Environmental Modelling & Software
%D 2022
%T A stochastic conceptual-data-driven approach for improved hydrological simulations
%A John M Quilty
%A Anna E Sikorska-Senoner
%A David Hah
%B Environmental Modelling & Software
%V 149
%P 105326
%G eng
%U https://www.sciencedirect.com/science/article/pii/S1364815222000329

%0 Generic
%D 2021
%T Improving Deep Learning hydrological time series modeling using Gaussian Filter preprocessing
%A Rahim Barzegar
%A Jan Adamowski
%A John Quilty
%B EGU General Assembly 2021
%P EGU21-1644
%G eng
%U https://meetingorganizer.copernicus.org/EGU21/EGU21-1644.html

%0 Journal Article
%J Journal of Hydrology
%D 2021
%T Improving GALDIT-based groundwater vulnerability predictive mapping using coupled resampling algorithms and machine learning models
%A R Barzegar
%A S Razzagh
%A J Quilty
%A J Adamowski
%A HK Pour
%A MJ Booij
%B Journal of Hydrology
%V 598
%P 126370
%G eng
%U https://www.sciencedirect.com/science/article/abs/pii/S0022169421004170

%0 Generic
%D 2021
%T Improving hydrological forecasts through temporal hierarchal reconciliation
%A Mohammad Sina Jahangir
%A John Quilty
%B EGU General Assembly 2021
%P EGU21-13303
%G eng
%U https://meetingorganizer.copernicus.org/EGU21/EGU21-13303.html

%0 Generic
%D 2021
%T Learning from one’s errors: A data-driven approach for mimicking an ensemble of hydrological model residuals
%A John M Quilty
%A Anna E Sikorska-Senoner
%B EGU General Assembly 2021
%P EGU21-13244
%G eng
%U https://meetingorganizer.copernicus.org/EGU21/EGU21-13244.html

%0 Journal Article
%J Environmental Modelling & Software
%D 2021
%T A maximal overlap discrete wavelet packet transform integrated approach for rainfall forecasting–A case study in the Awash River Basin
%A John Quilty
%A Jan Adamowski
%B Environmental Modelling & Software
%P 105119
%G eng
%U https://www.sciencedirect.com/science/article/abs/pii/S1364815221001626

%0 Journal Article
%J Environmental Modelling & Software
%D 2021
%T A novel ensemble-based conceptual-data-driven approach for improved streamflow simulations
%A Anna E Sikorska-Senoner
%A John M Quilty
%B Environmental Modelling & Software
%P 105094
%G eng
%U https://www.sciencedirect.com/science/article/pii/S1364815221001377

%0 Journal Article
%J Journal of Hydrology
%D 2021
%T Probabilistic urban water demand forecasting using wavelet-based machine learning models
%A Mostafa Rezaali
%A John Quilty
%A Abdolreza Karimi
%B Journal of Hydrology
%P 126358
%G eng
%U https://www.sciencedirect.com/science/article/abs/pii/S0022169421004054

%0 Journal Article
%J Water Resources Research
%D 2020
%T Data assimilation for streamflow forecasting using extreme learning machines
%A Boucher, Marie-Amélie
%A Quilty, John
%A Adamowski, J
%B Water Resources Research
%V 56
%P e2019WR026226
%G eng

%0 Journal Article
%J Advances in Water Resources
%D 2020
%T Multiscale groundwater level forecasting: Coupling new machine learning approaches with wavelet transforms
%A Rahman, A. T. M. S.
%A Hosono, T.
%A Quilty, J.M.
%A Das, J.
%A Basak, A.
%B Advances in Water Resources
%V 141
%P 103595
%G eng

%0 Journal Article
%J Environmental Modelling & Software
%D 2020
%T A stochastic wavelet-based data-driven framework for forecasting uncertain multiscale hydrological and water resources processes
%A Quilty, John
%A Adamowski, Jan
%B Environmental Modelling & Software
%V 130
%P 104718
%G eng

%0 Journal Article
%J EGU General Assembly Conference Abstracts
%D 2020
%T Using a boundary-corrected wavelet transform coupled with machine learning and hybrid deep learning approaches for multi-step water level forecasting in Lakes Michigan and Ontario
%A Rahim Barzegar
%A Jan Adamowski
%A John Quilty
%A Mohammad Taghi Aalami
%B EGU General Assembly Conference Abstracts
%P 4233
%G eng
%U https://scholar.google.ca/scholar?oi=bibs&cluster=8698411343122623888&btnI=1&hl=en

%0 Journal Article
%J Journal of Hydrology
%D 2020
%T Using ensembles of adaptive neuro-fuzzy inference system and optimization algorithms to predict reference evapotranspiration in subtropical climatic zones
%A D. Roy
%A Rahim Barzegar
%A John Quilty
%A Jan Adamowski
%B Journal of Hydrology
%V 591
%P 125509
%G eng
%U https://scholar.google.ca/scholar?oi=bibs&cluster=15103368238207897622&btnI=1&hl=en

%0 Journal Article
%J Agricultural and Forest Meteorology
%D 2019
%T On the applicability of maximum overlap discrete wavelet transform integrated with MARS and M5 model tree for monthly pan evaporation prediction
%A Ghaemi, Alireza
%A Rezaie-Balf, Mohammad
%A Adamowski, Jan
%A Kisi, Ozgur
%A Quilty, John
%B Agricultural and Forest Meteorology
%I Elsevier
%V 278
%P 107647
%G eng

%0 Journal Article
%J Agricultural Water Management
%D 2019
%T Coupling the maximum overlap discrete wavelet transform and long short-term memory networks for irrigation flow forecasting
%A Mouatadid, Soukayna
%A Adamowski, Jan F
%A Tiwari, Mukesh K
%A Quilty, John M
%B Agricultural Water Management
%I Elsevier
%V 219
%P 72–85
%G eng

%0 Journal Article
%J Water Resources Research
%D 2019
%T A stochastic data-driven ensemble forecasting framework for water resources: A case study using ensemble members derived from a database of deterministic wavelet-based models
%A Quilty, John
%A Adamowski, Jan
%A Boucher, Marie-Amélie
%B Water Resources Research
%V 55
%P 175–202
%G eng

%0 Journal Article
%J Journal of Hydrology
%D 2019
%T Using Bootstrap ELM and LSSVM Models to Estimate River Ice Thickness in the Mackenzie River Basin in the Northwest Territories, Canada
%A Barzegar, Rahim
%A Ghasri, Mahsa
%A Qi, Zhiming
%A Quilty, John
%A Adamowski, Jan
%B Journal of Hydrology
%I Elsevier
%G eng

%0 Journal Article
%J Journal of hydrology
%D 2018
%T Addressing the incorrect usage of wavelet-based hydrological and water resources forecasting models for real-world applications with best practices and a new forecasting framework
%A Quilty, John
%A Adamowski, Jan
%B Journal of hydrology
%I Elsevier
%V 563
%P 336–353
%G eng

%0 Thesis
%D 2018
%T An Ensemble Wavelet-based Stochastic Data-driven Framework for Addressing Nonlinearity, Multiscale Change, and Uncertainty in Water Resources Forecasting
%A Quilty, John
%I McGill University Libraries
%G eng
%9 phd

%0 Conference Paper
%B EGU General Assembly Conference Abstracts
%D 2018
%T Information-theoretic-based input variable selection for hydrology and water resources
%A Quilty, John
%A Adamowski, Jan
%A Khalil, Bahaa
%A Rathinasamy, Maheswaran
%B EGU General Assembly Conference Abstracts
%V 20
%P 2379
%G eng

%0 Conference Paper
%B EGU General Assembly Conference Abstracts
%D 2018
%T A stochastic data-driven forecasting framework using wavelets for forecasting uncertain hydrological and water resources processes
%A Quilty, John
%A Adamowski, Jan
%B EGU General Assembly Conference Abstracts
%V 20
%P 2380
%G eng

%0 Journal Article
%J Stochastic environmental research and risk assessment
%D 2017
%T Forecasting effective drought index using a wavelet extreme learning machine (W-ELM) model
%A Deo, Ravinesh C
%A Tiwari, Mukesh K
%A Adamowski, Jan F
%A Quilty, John M
%B Stochastic environmental research and risk assessment
%I Springer Berlin Heidelberg
%V 31
%P 1211–1240
%G eng

%0 Conference Paper
%B EGU General Assembly Conference Abstracts
%D 2017
%T Hydrological data assimilation using Extreme Learning Machines
%A Boucher, Marie-Amélie
%A Quilty, John
%A Adamowski, Jan
%B EGU General Assembly Conference Abstracts
%V 19
%P 5722
%G eng

%0 Journal Article
%J Environmental research
%D 2017
%T Very short-term reactive forecasting of the solar ultraviolet index using an extreme learning machine integrated with the solar zenith angle
%A Deo, Ravinesh C
%A Downs, Nathan
%A Parisi, Alfio V
%A Adamowski, Jan F
%A Quilty, John M
%B Environmental research
%I Academic Press
%V 155
%P 141–166
%G eng

%0 Journal Article
%J Water Resources Research
%D 2016
%T Bootstrap rank-ordered conditional mutual information (broCMI): A nonlinear input variable selection method for water resources modeling
%A Quilty, John
%A Adamowski, Jan
%A Khalil, Bahaa
%A Rathinasamy, Maheswaran
%B Water Resources Research
%V 52
%P 2299–2326
%G eng

%0 Journal Article
%J Atmospheric research
%D 2016
%T Coupling machine learning methods with wavelet transforms and the bootstrap and boosting ensemble approaches for drought prediction
%A Belayneh, A
%A Adamowski, J
%A Khalil, B
%A Quilty, J
%B Atmospheric research
%I Elsevier
%V 172
%P 37–47
%G eng

%0 Journal Article
%J Journal of Hydrology
%D 2016
%T Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq
%A Yaseen, Zaher Mundher
%A Jaafar, Othman
%A Deo, Ravinesh C
%A Kisi, Ozgur
%A Adamowski, Jan
%A Quilty, John
%A El-Shafie, Ahmed
%B Journal of Hydrology
%I Elsevier
%V 542
%P 603–614
%G eng

%0 Journal Article
%J Journal of Hydrology
%D 2015
%T The application of dynamic linear bayesian models in hydrological forecasting: varying coefficient regression and discount weighted regression
%A Ciupak, Maurycy
%A Ozga-Zielinski, Bogdan
%A Adamowski, Jan
%A Quilty, John
%A Khalil, Bahaa
%B Journal of Hydrology
%I Elsevier
%V 530
%P 762–784
%G eng

%0 Conference Paper
%B AGU Fall Meeting Abstracts
%D 2015
%T Stochastic weather inputs for improved urban water demand forecasting: application of nonlinear input variable selection and machine learning methods
%A Quilty, J
%A Adamowski, JF
%B AGU Fall Meeting Abstracts
%G eng

%0 Conference Paper
%B AGU Fall Meeting Abstracts
%D 2014
%T Forecasting Urban Water Demand via Machine Learning Methods Coupled with a Bootstrap Rank-Ordered Conditional Mutual Information Input Variable Selection Method
%A Adamowski, JF
%A Quilty, J
%A Khalil, B
%A Rathinasamy, M
%B AGU Fall Meeting Abstracts
%G eng

%0 Journal Article
%J Expert systems with applications
%D 2014
%T Modeling of daily pan evaporation in sub tropical climates using ANN, LS-SVR, Fuzzy Logic, and ANFIS
%A Goyal, Manish Kumar
%A Bharti, Birendra
%A Quilty, John
%A Adamowski, Jan
%A Pandey, Ashish
%B Expert systems with applications
%I Elsevier
%V 41
%P 5267–5276
%G eng

%0 Conference Paper
%B CSCE 3rd Specialty Conference on Disaster Prevention and Mitigation
%D 2013
%T Forecasting drought via bootstrap and machine learning methods
%A Belayneh, Anteneh
%A Adamowski, J
%A Khalil, Bahaa
%B CSCE 3rd Specialty Conference on Disaster Prevention and Mitigation
%G eng