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Céline Cattoën

affiliation not provided to SSRN

  • affiliation not provided to SSRN

SCHOLARLY PAPERS

3

DOWNLOADS

152

TOTAL CITATIONS

3

Scholarly Papers (3)

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1.

Geofabrics 1.0.0: An Open-Source Python Package for Automatic Hydrological Conditioning of Digital Elevation Models for Flood Modelling

Number of pages: 27 Posted: 30 May 2023
Rose Pearson, Alice Harang, Céline Cattoën, Cyprien Bosserelle, Richard Measures, Matt Wilkins, Graeme Smart and Emily M. Lane
National Institute of Water and Atmospheric Research, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN and National Institute of Water and Atmospheric Research
Downloads 80 (823,616)
Citation 3

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Hydrological conditioning, LiDAR, Open-source software, Automated framework, DEM generation

2.

‘That Still Haunts Me a Little Bit’: Decision-Makers and Information Providers’ Experiences of Recurring Flood Events

Number of pages: 29 Posted: 17 Oct 2024
Danielle Johnson, Sarah Harrison, Céline Cattoën, Jordan Luttrell and Paula Blackett
National Institute of Water and Atmospheric Research (NIWA), affiliation not provided to SSRN, affiliation not provided to SSRN, National Institute of Water and Atmospheric Research (NIWA) and affiliation not provided to SSRN
Downloads 43 (1,145,425)

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Mental health, Wellbeing, Emergency Response, Flooding, natural hazards, climate change

3.

Benchmarking the Computational Efficiency of Deep Learning-based Surrogate Inundation Models

Number of pages: 74 Posted: 11 Feb 2026
Malintha Ranasinghe, Emma E.H. Doyle, Marion Tan, Céline Cattoën and Raj Prasanna
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN and affiliation not provided to SSRN
Downloads 29 (1,372,601)

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Fluvial flood, Flood mapping, Deep learning, machine learning, surrogate model, computational efficiency benchmark, flood early warning