Marie-Amélie Boucher

Professor

Université de Sherbrooke

Canada

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Research Interests

Climatology

30%

Meteorology

50%

Forecasting

50%

Circulation Modeling

50%

Data Assimilation

40%

Water Resource Management

40%

Hydrometeorology

40%

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Articles13

Hybrid forecasting: blending climate predictions with AI models

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Year:

2023

Fully integrating probabilistic flood forecasts into the decision-making process across southern Quebec, Canada: some factors to consider

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Year:

2023

Observed and projected trends in spring flood discharges for the Upper Harricana River, eastern boreal Canada

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Year:

2023

Comparing numerical modelling, traditional machine learning and theory-guided machine learning in inverse modeling of groundwater dynamics: A first study case application

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Year:

2022

Exploring hydrologic post-processing of ensemble streamflow forecasts based on affine kernel dressing and non-dominated sorting genetic algorithm II

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Year:

2022

Large-scale snow data assimilation using a spatialized particle filter: recovering the spatial structure of the particles

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Year:

2022

Spatio-temporal discretization uncertainty of distributed hydrological models

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Year:

2022

Investigating ANN architectures and training to estimate snow water equivalent from snow depth

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Year:

2021

Review: Theory-guided machine learning applied to hydrogeology—state of the art, opportunities and future challenges,应用于水文地质的具有理论的机器学习综述:最新技术、机遇和未来挑战,Revue: Apprentissage automatique guidée par la théorie appliqué à l’hydrogéologie—état de l’art, opportunités et défis,Revisão: Aprendizagem de máquina orientada pela teoria aplicada à hidrogeologia—estado da arte, oportunidades e futuros desafios,Revisión: La teoría del aprendizaje automático aplicada a la hidrogeología—estado del arte, oportunidades y desafíos futuros

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Year:

2021

Data Assimilation for Streamflow Forecasting Using Extreme Learning Machines and Multilayer Perceptrons

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Year:

2020

Ensemble hydrological forecasts for reservoir management of the Shipshaw River catchment using limited data

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Year:

2020

Using artificial neural networks to estimate snow water equivalent from snow depth

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Year:

2020

Water-table fluctuation method for assessing aquifer recharge: application to Canadian aquifers and comparison with other methods,评价含水层补给量的地下水位波动方法:在加拿大含水层的应用及与其他方法的比较,Méthode des variations du niveau piézométrique pour évaluer la recharge d’un aquifère: application à des aquifères canadiens et comparaison avec d’autres méthodes,Método da flutuação do nível freático para avaliar a recarga de aquíferos: aplicação em aquíferos canadenses e comparação com outros métodos,Método de la fluctuación de los niveles freáticos para evaluar la recarga de acuíferos: aplicación a los acuíferos canadienses y comparación con otros métodos

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Year:

2020

Collaborators6

Andrew Wood

Research Professor

Colorado School of Mines

UNITED STATES

Linda Speight

University of Oxford

UNITED KINGDOM

Chaopeng Shen

Assistant Professor

Pennsylvania State University

UNITED STATES

François Anctil

CANADA

Robert Wilby

Loughborough University

UNITED KINGDOM

Louise Slater

University of Oxford

UNITED KINGDOM

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