Marie-Amélie Boucher at Université de Sherbrooke - Research Interests, Publications & Academic Profile

Marie-Amélie Boucher

Professor

Université de Sherbrooke

Canada

This profile is automatically generated from trusted academic sources.

Google Scholar

ORCID

How do Chinese students reach out?

Meet Kite AI

Contact this professor

ORCID

Google Scholar

Academic Page

Research Interests

Climatology

30%

Meteorology

50%

Forecasting

50%

Circulation Modeling

50%

Data Assimilation

40%

Water Resource Management

40%

Hydrometeorology

40%

Ask ApplyKite AI

Start chatting

How can you help me contact this professor?

What are this professor's research interests?

How should I write an email to this professor?

Articles13

Hybrid forecasting: blending climate predictions with AI models

Article Link

Year:

2023

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

Article Link

Year:

2023

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

Article Link

Year:

2023

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

Article Link

Year:

2022

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

Article Link

Year:

2022

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

Article Link

Year:

2022

Spatio-temporal discretization uncertainty of distributed hydrological models

Article Link

Year:

2022

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

Article Link

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

Article Link

Year:

2021

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

Article Link

Year:

2020

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

Article Link

Year:

2020

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

Article Link

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

Article Link

Year:

2020

Collaborators5

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

How do Chinese students reach out?

Meet Kite AI