Elisa Ragno

Assistant Professor (tenure-track)

Delft University of Technology

Netherlands

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Elisa Ragno is an Assistant Professor (tenure-track) at Delft University of Technology in the Netherlands. Her research focuses on probabilistic modeling and hydrodynamics, with recent articles addressing ship-induced wave heights, compound flood hazards, and meteorological transitions in river basins. Dr. Ragno actively contributes to advancements in understanding flood risks and water management strategies in delta regions.

Articles (15)

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2025

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2024

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2024

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2024

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2024

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2023

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2023

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2023

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2022

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2022

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2021

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2021

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2020

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2020

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2020

Collaborators (8)

Jeremy Bricker

Delft University of Technology

NETHERLANDS

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Andreia F. S. Ribeiro

PORTUGAL

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Qian Ke

NETHERLANDS

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Markus Hrachowitz

Prof.

Delft University of Technology

NETHERLANDS

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Miguel Angel Mendoza Lugo

Delft University of Technology

NETHERLANDS

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Oswaldo Morales Nápoles

Associate professor probabilistic design

Delft University of Technology

NETHERLANDS

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Alessandro Antonini

Assistant Professor of Coastal Structures

Delft University of Technology

NETHERLANDS

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Fabrizio Durante

Full Professor

Università del Salento

ITALY

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Elisa Ragno

Research Interests

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Articles (15)

Probabilistic Estimation of Primary Ship-Induced Wave Heights at Estuary Groins Using a Nonparametric Bayesian Network

Combining statistical and hydrodynamic models to assess compound flood hazards from rainfall and storm surge: a case study of Shanghai

Investigating meteorological wet and dry transitions in the Dutch Meuse River basin

Probabilistic characterizations of flood hazards in deltas

The legacy of STAHY

Perspectives on Compound Flooding in Chinese Estuary Regions

Investigating extreme sea level components and their interactions in the Adriatic and Tyrrhenian Seas

PyBanshee version (1.0): A Python implementation of the MATLAB toolbox BANSHEE for Non-Parametric Bayesian Networks with updated features

Compound flood impact of water level and rainfall during tropical cyclone periods in a coastal city

Applying non-parametric Bayesian networks to estimate maximum daily river discharge: potential and challenges

Statistical modelling and climate variability of compound surge and precipitation events in a managed water system: a case study in the Netherlands

Guidelines for Studying Diverse Types of Compound Weather and Climate Events

BANSHEE–A MATLAB toolbox for Non-Parametric Bayesian Networks

BANSHEE–A MATLAB toolbox for Non-Parametric Bayesian Networks

Quantifying increased fire risk in California in response to different levels of warming and drying

Collaborators (8)

Jeremy Bricker

Andreia F. S. Ribeiro

Qian Ke

Markus Hrachowitz

Miguel Angel Mendoza Lugo

Oswaldo Morales Nápoles

Alessandro Antonini

Fabrizio Durante

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