Jean-Luc Martel

Associate Professor

École de technologie supérieure

Canada

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Jean-Luc Martel is an Associate Professor at École de technologie supérieure in Canada. His research focuses on hydrological modeling, climate change impacts, and the application of neural networks in streamflow forecasting. Recent publications emphasize the assessment of traditional hydrological models and the application of long short-term memory (LSTM) networks in improving hydrological predictions and understanding urban drainage systems in the context of climate change.

Articles (18)

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2025

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2021

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2021

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2021

Collaborators (3)

Richard Arsenault

Professor

École de technologie supérieure

CANADA

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Andre St-Hilaire

Professor

CANADA

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Jennifer Drake

University of Toronto

CANADA

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Jean-Luc Martel

Research Interests

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Articles (18)

Value of various elements of the hydrological forecasting chain: Is there a successful pathway for improving the overall performance?

Assessing the adequacy of traditional hydrological models for climate change impact studies: a case for long short-term memory (LSTM) neural networks

Limits of Blue and Green Infrastructures to Adapt Actual Urban Drainage Systems to the Impact of Climate Change

Evaluation of the Impact of Rainfall Increases on Runoff in Urban Watersheds

Using the ERA5 and ERA5-Land reanalysis datasets for river water temperature modelling in a data-scarce region

Improved historical reconstruction of daily flows and annual maxima in gauged and ungauged basins

Continuous streamflow prediction in ungauged basins: long short-term memory neural networks clearly outperform traditional hydrological models

Understanding the influence of “hot” models in climate impact studies: a hydrological perspective

Comparing a long short-term memory (LSTM) neural network with a physically-based hydrological model for streamflow forecasting over a Canadian catchment

Sensitivity analysis of the hyperparameters of an ensemble Kalman filter application on a semi-distributed hydrological model for streamflow forecasting

CMIP5 and CMIP6 Model Projection Comparison for Hydrological Impacts Over North America

CMIP5 and CMIP6 Model Projection Comparison for Hydrological Impacts Over North America

How much water can bioretention retain, and where does it go?

Large-sample study of uncertainty of hydrological model components over North America

Climate Change and Rainfall Intensity–Duration–Frequency Curves: Overview of Science and Guidelines for Adaptation

Climate Change and Rainfall Intensity–Duration–Frequency Curves: Overview of Science and Guidelines for Adaptation

Hydrological ensemble forecasting using a multi-model framework

Daily streamflow prediction in ungauged basins: an analysis of common regionalization methods over the African continent

Collaborators (3)

Richard Arsenault

Andre St-Hilaire

Jennifer Drake

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