@article {34878,
	title = {Generative deep learning for probabilistic streamflow forecasting: conditional variational auto-encoder},
	journal = {Journal of Hydrology},
	volume = {629},
	year = {2024},
	pages = {130498},
	url = {https://www.sciencedirect.com/science/article/pii/S0022169423014403},
	author = {Jahangir, M.S. and Quilty, J.}
}
@article {34879,
	title = {Bayesian extreme learning machines for hydrological prediction uncertainty},
	journal = {Journal of Hydrology},
	volume = {626},
	year = {2023},
	pages = {130138},
	url = {https://www.sciencedirect.com/science/article/pii/S0022169423010806},
	author = {Quilty, J. and Jahangir, M.S. and You, J. and Hughes, H. and Hah, D. and Tzoganakis, I.}
}
@article {34880,
	title = {A quantile-based encoder-decoder framework for multi-step ahead runoff forecasting},
	journal = {Journal of Hydrology},
	volume = {619},
	year = {2023},
	pages = {129269},
	url = {https://www.sciencedirect.com/science/article/pii/S0022169423002111},
	author = {Jahangir, M.S. and You, J. and Quilty, J.}
}
@article {31163,
	title = {Comparing the Soil Conservation Service model with new machine learning algorithms for predicting cumulative infiltration in semi-arid regions},
	journal = {Pedosphere},
	year = {2022},
	url = {https://www.sciencedirect.com/science/article/pii/S1002016022000157},
	author = {Khabat Khosravi and TT Phuong and Rahim Barzegar and John Quilty and Mohammad T Alami}
}
@article {31162,
	title = {Investigating the impact of input variable selection on daily solar radiation prediction accuracy using data-driven models: a case study in northern Iran},
	journal = {Stochastic Environmental Research and Risk Assessment},
	volume = {36},
	year = {2022},
	pages = {225-249},
	url = {https://link.springer.com/article/10.1007/s00477-021-02070-5},
	author = {Mohammad Sina Jahangir and Seyed Mostafa Biazar and David Hah and John Quilty and Mohammad Isazadeh}
}
@article {31161,
	title = {A stochastic conceptual-data-driven approach for improved hydrological simulations},
	journal = {Environmental Modelling \& Software},
	volume = {149},
	year = {2022},
	pages = {105326},
	url = {https://www.sciencedirect.com/science/article/pii/S1364815222000329},
	author = {John M Quilty and Anna E Sikorska-Senoner and David Hah}
}
@presentation {29027,
	title = {Improving Deep Learning hydrological time series modeling using Gaussian Filter preprocessing},
	journal = {EGU General Assembly 2021},
	year = {2021},
	pages = {EGU21-1644},
	url = {https://meetingorganizer.copernicus.org/EGU21/EGU21-1644.html},
	author = {Rahim Barzegar and Jan Adamowski and John Quilty}
}
@article {29024,
	title = {Improving GALDIT-based groundwater vulnerability predictive mapping using coupled resampling algorithms and machine learning models},
	journal = {Journal of Hydrology},
	volume = {598},
	year = {2021},
	pages = {126370},
	url = {https://www.sciencedirect.com/science/article/abs/pii/S0022169421004170},
	author = {R Barzegar and S Razzagh and J Quilty and J Adamowski and HK Pour and MJ Booij}
}
@presentation {29029,
	title = {Improving hydrological forecasts through temporal hierarchal reconciliation},
	journal = {EGU General Assembly 2021},
	year = {2021},
	pages = {EGU21-13303},
	url = {https://meetingorganizer.copernicus.org/EGU21/EGU21-13303.html},
	author = {Mohammad Sina Jahangir and John Quilty}
}
@presentation {29028,
	title = {Learning from one\&rsquo;s errors: A data-driven approach for mimicking an ensemble of hydrological model residuals},
	journal = {EGU General Assembly 2021},
	year = {2021},
	pages = {EGU21-13244},
	url = {https://meetingorganizer.copernicus.org/EGU21/EGU21-13244.html},
	author = {John M Quilty and Anna E Sikorska-Senoner}
}
@article {29023,
	title = {A maximal overlap discrete wavelet packet transform integrated approach for rainfall forecasting\&ndash;A case study in the Awash River Basin},
	journal = {Environmental Modelling \& Software},
	year = {2021},
	pages = {105119},
	url = {https://www.sciencedirect.com/science/article/abs/pii/S1364815221001626},
	author = {John Quilty and Jan Adamowski}
}
@article {29025,
	title = {A novel ensemble-based conceptual-data-driven approach for improved streamflow simulations},
	journal = {Environmental Modelling \& Software},
	year = {2021},
	pages = {105094},
	url = {https://www.sciencedirect.com/science/article/pii/S1364815221001377},
	author = {Anna E Sikorska-Senoner and John M Quilty}
}
@article {29026,
	title = {Probabilistic urban water demand forecasting using wavelet-based machine learning models},
	journal = {Journal of Hydrology},
	year = {2021},
	pages = {126358},
	url = {https://www.sciencedirect.com/science/article/abs/pii/S0022169421004054},
	author = {Mostafa Rezaali and John Quilty and Abdolreza Karimi}
}
@article {25973,
	title = {Data assimilation for streamflow forecasting using extreme learning machines},
	journal = {Water Resources Research},
	volume = {56},
	year = {2020},
	pages = {e2019WR026226},
	author = {Boucher, Marie-Am{\'e}lie and Quilty, John and Adamowski, J}
}
@article {25974,
	title = {Multiscale groundwater level forecasting: Coupling new machine learning approaches with wavelet transforms},
	journal = {Advances in Water Resources},
	volume = {141},
	year = {2020},
	pages = {103595},
	author = {Rahman, A. T. M. S. and Hosono, T. and Quilty, J.M. and Das, J. and Basak, A.}
}
@article {25975,
	title = {A stochastic wavelet-based data-driven framework for forecasting uncertain multiscale hydrological and water resources processes},
	journal = {Environmental Modelling \& Software},
	volume = {130},
	year = {2020},
	pages = {104718},
	author = {Quilty, John and Adamowski, Jan}
}
@article {27220,
	title = {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},
	journal = {EGU General Assembly Conference Abstracts},
	year = {2020},
	pages = {4233},
	url = {https://scholar.google.ca/scholar?oi=bibs\&cluster=8698411343122623888\&btnI=1\&hl=en},
	author = {Rahim Barzegar and Jan Adamowski and John Quilty and Mohammad Taghi Aalami}
}
@article {27219,
	title = {Using ensembles of adaptive neuro-fuzzy inference system and optimization algorithms to predict reference evapotranspiration in subtropical climatic zones},
	journal = {Journal of Hydrology},
	volume = {591},
	year = {2020},
	pages = {125509},
	url = {https://scholar.google.ca/scholar?oi=bibs\&cluster=15103368238207897622\&btnI=1\&hl=en},
	author = {D. Roy and Rahim Barzegar and John Quilty and Jan Adamowski}
}
@article {ghaemi2019applicability,
	title = {On the applicability of maximum overlap discrete wavelet transform integrated with MARS and M5 model tree for monthly pan evaporation prediction},
	journal = {Agricultural and Forest Meteorology},
	volume = {278},
	year = {2019},
	pages = {107647},
	publisher = {Elsevier},
	author = {Ghaemi, Alireza and Rezaie-Balf, Mohammad and Adamowski, Jan and Kisi, Ozgur and Quilty, John}
}
@article {mouatadid2019coupling,
	title = {Coupling the maximum overlap discrete wavelet transform and long short-term memory networks for irrigation flow forecasting},
	journal = {Agricultural Water Management},
	volume = {219},
	year = {2019},
	pages = {72{\textendash}85},
	publisher = {Elsevier},
	author = {Mouatadid, Soukayna and Adamowski, Jan F and Tiwari, Mukesh K and Quilty, John M}
}
@article {quilty2019stochastic,
	title = {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},
	journal = {Water Resources Research},
	volume = {55},
	number = {1},
	year = {2019},
	pages = {175{\textendash}202},
	author = {Quilty, John and Adamowski, Jan and Boucher, Marie-Am{\'e}lie}
}
@article {barzegar2019using,
	title = {Using Bootstrap ELM and LSSVM Models to Estimate River Ice Thickness in the Mackenzie River Basin in the Northwest Territories, Canada},
	journal = {Journal of Hydrology},
	year = {2019},
	publisher = {Elsevier},
	author = {Barzegar, Rahim and Ghasri, Mahsa and Qi, Zhiming and Quilty, John and Adamowski, Jan}
}
@article {quilty2018addressing,
	title = {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},
	journal = {Journal of hydrology},
	volume = {563},
	year = {2018},
	pages = {336{\textendash}353},
	publisher = {Elsevier},
	author = {Quilty, John and Adamowski, Jan}
}
@mastersthesis {quilty2018ensemble,
	title = {An Ensemble Wavelet-based Stochastic Data-driven Framework for Addressing Nonlinearity, Multiscale Change, and Uncertainty in Water Resources Forecasting},
	year = {2018},
	school = {McGill University Libraries},
	type = {phd},
	author = {Quilty, John}
}
@conference {quilty2018information,
	title = {Information-theoretic-based input variable selection for hydrology and water resources},
	booktitle = {EGU General Assembly Conference Abstracts},
	volume = {20},
	year = {2018},
	pages = {2379},
	author = {Quilty, John and Adamowski, Jan and Khalil, Bahaa and Rathinasamy, Maheswaran}
}
@conference {quilty2018stochastic,
	title = {A stochastic data-driven forecasting framework using wavelets for forecasting uncertain hydrological and water resources processes},
	booktitle = {EGU General Assembly Conference Abstracts},
	volume = {20},
	year = {2018},
	pages = {2380},
	author = {Quilty, John and Adamowski, Jan}
}
@article {deo2017forecasting,
	title = {Forecasting effective drought index using a wavelet extreme learning machine (W-ELM) model},
	journal = {Stochastic environmental research and risk assessment},
	volume = {31},
	number = {5},
	year = {2017},
	pages = {1211{\textendash}1240},
	publisher = {Springer Berlin Heidelberg},
	author = {Deo, Ravinesh C and Tiwari, Mukesh K and Adamowski, Jan F and Quilty, John M}
}
@conference {boucher2017hydrological,
	title = {Hydrological data assimilation using Extreme Learning Machines},
	booktitle = {EGU General Assembly Conference Abstracts},
	volume = {19},
	year = {2017},
	pages = {5722},
	author = {Boucher, Marie-Am{\'e}lie and Quilty, John and Adamowski, Jan}
}
@article {deo2017very,
	title = {Very short-term reactive forecasting of the solar ultraviolet index using an extreme learning machine integrated with the solar zenith angle},
	journal = {Environmental research},
	volume = {155},
	year = {2017},
	pages = {141{\textendash}166},
	publisher = {Academic Press},
	author = {Deo, Ravinesh C and Downs, Nathan and Parisi, Alfio V and Adamowski, Jan F and Quilty, John M}
}
@article {quilty2016bootstrap,
	title = {Bootstrap rank-ordered conditional mutual information (broCMI): A nonlinear input variable selection method for water resources modeling},
	journal = {Water Resources Research},
	volume = {52},
	number = {3},
	year = {2016},
	pages = {2299{\textendash}2326},
	author = {Quilty, John and Adamowski, Jan and Khalil, Bahaa and Rathinasamy, Maheswaran}
}
@article {belayneh2016coupling,
	title = {Coupling machine learning methods with wavelet transforms and the bootstrap and boosting ensemble approaches for drought prediction},
	journal = {Atmospheric research},
	volume = {172},
	year = {2016},
	pages = {37{\textendash}47},
	publisher = {Elsevier},
	author = {Belayneh, A and Adamowski, J and Khalil, B and Quilty, J}
}
@article {yaseen2016stream,
	title = {Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq},
	journal = {Journal of Hydrology},
	volume = {542},
	year = {2016},
	pages = {603{\textendash}614},
	publisher = {Elsevier},
	author = {Yaseen, Zaher Mundher and Jaafar, Othman and Deo, Ravinesh C and Kisi, Ozgur and Adamowski, Jan and Quilty, John and El-Shafie, Ahmed}
}
@article {ciupak2015application,
	title = {The application of dynamic linear bayesian models in hydrological forecasting: varying coefficient regression and discount weighted regression},
	journal = {Journal of Hydrology},
	volume = {530},
	year = {2015},
	pages = {762{\textendash}784},
	publisher = {Elsevier},
	author = {Ciupak, Maurycy and Ozga-Zielinski, Bogdan and Adamowski, Jan and Quilty, John and Khalil, Bahaa}
}
@conference {quilty2015stochastic,
	title = {Stochastic weather inputs for improved urban water demand forecasting: application of nonlinear input variable selection and machine learning methods},
	booktitle = {AGU Fall Meeting Abstracts},
	year = {2015},
	author = {Quilty, J and Adamowski, JF}
}
@conference {adamowski2014forecasting,
	title = {Forecasting Urban Water Demand via Machine Learning Methods Coupled with a Bootstrap Rank-Ordered Conditional Mutual Information Input Variable Selection Method},
	booktitle = {AGU Fall Meeting Abstracts},
	year = {2014},
	author = {Adamowski, JF and Quilty, J and Khalil, B and Rathinasamy, M}
}
@article {goyal2014modeling,
	title = {Modeling of daily pan evaporation in sub tropical climates using ANN, LS-SVR, Fuzzy Logic, and ANFIS},
	journal = {Expert systems with applications},
	volume = {41},
	number = {11},
	year = {2014},
	pages = {5267{\textendash}5276},
	publisher = {Elsevier},
	author = {Goyal, Manish Kumar and Bharti, Birendra and Quilty, John and Adamowski, Jan and Pandey, Ashish}
}
@conference {belayneh2013forecasting,
	title = {Forecasting drought via bootstrap and machine learning methods},
	booktitle = {CSCE 3rd Specialty Conference on Disaster Prevention and Mitigation},
	year = {2013},
	author = {Belayneh, Anteneh and Adamowski, J and Khalil, Bahaa}
}
