A Global Flood Risk Modeling Framework Built With Climate Models and Machine Learning-Reference-Cited by-同舟云学术

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A Global Flood Risk Modeling Framework Built With Climate Models and Machine Learning

Published:2021-04 Issue:4 Volume:13 Page:
ISSN:1942-2466
Container-title:Journal of Advances in Modeling Earth Systems
language:en
Short-container-title:J. Adv. Model. Earth Syst.

Author:

Carozza David A.¹^ORCID,Boudreault Mathieu¹^ORCID

Affiliation:

1. Département de Mathématiques Université du Québec à Montréal Montréal QC Canada

Funder

Mitacs

Fonds de recherche du Québec – Nature et technologies

Natural Sciences and Engineering Research Council of Canada

Marine Environmental Observation Prediction and Response Network

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Environmental Chemistry,Global and Planetary Change

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2020MS002221

Reference81 articles.

1. Normalised flood losses in Europe: 1970–2006

2. A trend analysis of normalized insured damage from natural disasters

3. Neural Networks inRUsing the Stuttgart Neural Network Simulator:RSNNS

4. Down to Basics: Runoff Processes and the Modelling Process

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1. Flood occurrence and impact models for socioeconomic applications over Canada and the United States;Natural Hazards and Earth System Sciences;2024-07-26

2. Flooding exposure accelerated biological aging: a population-based study in the UK;Environmental Research Letters;2024-07-01

3. Projected seasonal flooding in Canada under climate change with statistical and machine learning;Journal of Hydrology: Regional Studies;2024-06

4. A data science approach to climate change risk assessment applied to pluvial flood occurrences for the United States and Canada;ASTIN Bulletin;2024-05-21

5. Floods and cause-specific mortality in the UK: a nested case-control study;BMC Medicine;2024-05-07

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