Articles | Volume 24, issue 10
https://doi.org/10.5194/nhess-24-3381-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-24-3381-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Preface: Advances in pluvial and fluvial flood forecasting and assessment and flood risk management
IHCantabria – Instituto de Hidráulica Ambiental de la Universidad de Cantabria, Santander, Spain
Dhruvesh Patel
Pandit Deendayal Energy University (PDEU) – formerly PDPU, School of Technology, Civil Engineering Department, Gujarat, India
Dawei Han
Department of Civil Engineering, University of Bristol, Bristol, UK
Benjamin Dewals
Research unit Urban & Environmental Engineering (UEE), Hydraulics in Environmental & Civil Engineering (HECE), University of Liège, Liège, Belgium
Michaela Bray
School of Engineering, Cardiff University, Cardiff, UK
Daniela Molinari
Department of Civil and Environmental Engineering, Politecnico di Milano, Milan, Italy
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Sara Rrokaj, Chiara Arrighi, Marta Ballocci, Gabriele Bertoli, Francesca da Porto, Claudia De Lucia, Mario Di Bacco, Paola Di Fluri, Alessio Domeneghetti, Marco Donà, Alice Gallazzi, Andrea Gennaro, Gianluca Lelli, Sara Mozzon, Natasha Petruccelli, Elisa Saler, Anna Rita Scorzini, Simone Sterlacchini, Gaia Treglia, Debora Voltolina, Marco Zazzeri, and Daniela Molinari
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-358, https://doi.org/10.5194/essd-2025-358, 2025
Preprint under review for ESSD
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Flood damage data are key to understanding territorial risks and supporting the design of mitigation measures. However, such data are scarce, and the available ones often lack a high level of detail. We conducted a field survey of residential, commercial, and industrial buildings affected by the record-breaking flood event that hit Italy’s Marche region in 2022. The resulting datasets cover 256 assets and include detailed information on damage, building features, and mitigation measures.
Pradeep Acharya, Mario Di Bacco, Daniela Molinari, and Anna Rita Scorzini
EGUsphere, https://doi.org/10.5194/egusphere-2025-1413, https://doi.org/10.5194/egusphere-2025-1413, 2025
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INSYDE-content is a novel probabilistic model designed to estimate flood damage to household items with a component-based approach. By incorporating multiple variables and addressing uncertainties, the model enables more comprehensive and insightful damage assessments by accounting for an often-overlooked asset
Tim Busker, Daniela Rodriguez Castro, Sergiy Vorogushyn, Jaap Kwadijk, Davide Zoccatelli, Rafaella Loureiro, Heather J. Murdock, Laurent Pfister, Benjamin Dewals, Kymo Slager, Annegret H. Thieken, Jan Verkade, Patrick Willems, and Jeroen C. J. H. Aerts
EGUsphere, https://doi.org/10.5194/egusphere-2025-828, https://doi.org/10.5194/egusphere-2025-828, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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In July 2021, the Netherlands, Luxembourg, Germany, and Belgium were hit by an extreme flood event with over 200 fatalities. Our study provides, for the first time, critical insights into the operational flood early-warning systems in this entire region. Based on 13 expert interviews, we conclude that the systems strongly improved in all countries. Interviewees stressed the need for operational impact-based forecasts, but emphasized that its operational implementation is challenging.
Marta Ballocci, Daniela Molinari, Giovanni Marin, Marta Galliani, Alessio Domeneghetti, Giovanni Menduni, Simone Sterlacchini, and Francesco Ballio
EGUsphere, https://doi.org/10.5194/egusphere-2024-3017, https://doi.org/10.5194/egusphere-2024-3017, 2024
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This study estimates flood direct damage to businesses in Italy using 812 damage records from five riverine flood case studies. A multiple regression model predicts economic damage based on business size, water depth, and economic sectors. The results show that damage increases non-proportionally with firm size, while water depth mainly affects stock damage. Healthcare, commercial, and manufacturing sectors are most vulnerable to building, stock, and equipment damage, respectively.
Mario Di Bacco, Daniela Molinari, and Anna Rita Scorzini
Nat. Hazards Earth Syst. Sci., 24, 1681–1696, https://doi.org/10.5194/nhess-24-1681-2024, https://doi.org/10.5194/nhess-24-1681-2024, 2024
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INSYDE 2.0 is a tool for modelling flood damage to residential buildings. By incorporating ultra-detailed survey and desk-based data, it improves the reliability and informativeness of damage assessments while addressing input data uncertainties.
Natasha Petruccelli, Luca Mantecchini, Alice Gallazzi, Daniela Molinari, Mohammed Hammouti, Marco Zazzeri, Simone Sterlacchini, Francesco Ballio, Armando Brath, and Alessio Domeneghetti
Proc. IAHS, 385, 407–413, https://doi.org/10.5194/piahs-385-407-2024, https://doi.org/10.5194/piahs-385-407-2024, 2024
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The study illustrates the methodology developed for flood risk assessment for road and railway infrastructures. Through the creation of a detailed database, using different data sources, and the definition of a risk matrix, a risk level (High, Medium, Low and Null) is assigned to each section, considering the physical and functional characteristics of the infrastructure, as well as its relevance and the magnitude of the expected event.
Panagiotis Asaridis and Daniela Molinari
Adv. Geosci., 61, 1–21, https://doi.org/10.5194/adgeo-61-1-2023, https://doi.org/10.5194/adgeo-61-1-2023, 2023
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This paper presents a conceptual model for the estimation of flood damage to power grids and reviews the available methodologies, to better understand current modelling approaches, challenges, and limitations. The model adopts an interdisciplinary and multi-scale evaluation approach to handle the complex damage mechanisms and capture the cascading effects. In doing so, it adapts to different geographical and economic contexts, allowing stakeholders to implement comprehensive damage assessments.
Hsi-Kai Chou, Ana Maria Heuminski de Avila, and Michaela Bray
Geosci. Model Dev., 15, 5233–5240, https://doi.org/10.5194/gmd-15-5233-2022, https://doi.org/10.5194/gmd-15-5233-2022, 2022
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Land surface models allow us to understand and investigate the cause and effect of environmental process changes. Therefore, this type of model is increasingly used for hydrological assessments. Here we explore the possibility of this approach using a case study in the Atibaia River basin, which serves as a major water supply for the metropolitan regions of Campinas and São Paulo, Brazil. We evaluated the model performance and use the model to simulate the basin hydrology.
Tommaso Simonelli, Laura Zoppi, Daniela Molinari, and Francesco Ballio
Nat. Hazards Earth Syst. Sci., 22, 1819–1823, https://doi.org/10.5194/nhess-22-1819-2022, https://doi.org/10.5194/nhess-22-1819-2022, 2022
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The paper discusses challenges (and solutions) emerged during a collaboration among practitioners, stakeholders, and scientists in the definition of flood damage maps in the Po River District. Social aspects were proven to be fundamental components of the risk assessment; variety of competences in the working group was key in finding solutions and revealing weaknesses of intermediate proposals. This paper finally highlights the need of duplicating such an experience at a broader European level.
Anna Rita Scorzini, Benjamin Dewals, Daniela Rodriguez Castro, Pierre Archambeau, and Daniela Molinari
Nat. Hazards Earth Syst. Sci., 22, 1743–1761, https://doi.org/10.5194/nhess-22-1743-2022, https://doi.org/10.5194/nhess-22-1743-2022, 2022
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This study presents a replicable procedure for the adaptation of synthetic, multi-variable flood damage models among countries that may have different hazard and vulnerability features. The procedure is exemplified here for the case of adaptation to the Belgian context of a flood damage model, INSYDE, for the residential sector, originally developed for Italy. The study describes necessary changes in model assumptions and input parameters to properly represent the new context of implementation.
Animesh K. Gain, Yves Bühler, Pascal Haegeli, Daniela Molinari, Mario Parise, David J. Peres, Joaquim G. Pinto, Kai Schröter, Ricardo M. Trigo, María Carmen Llasat, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 22, 985–993, https://doi.org/10.5194/nhess-22-985-2022, https://doi.org/10.5194/nhess-22-985-2022, 2022
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To mark the 20th anniversary of Natural Hazards and Earth System Sciences (NHESS), an interdisciplinary and international journal dedicated to the public discussion and open-access publication of high-quality studies and original research on natural hazards and their consequences, we highlight 11 key publications covering major subject areas of NHESS that stood out within the past 20 years.
Xichao Gao, Zhiyong Yang, Dawei Han, Kai Gao, and Qian Zhu
Hydrol. Earth Syst. Sci., 25, 6023–6039, https://doi.org/10.5194/hess-25-6023-2021, https://doi.org/10.5194/hess-25-6023-2021, 2021
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We proposed a theoretical framework and conducted a laboratory experiment to understand the relationship between wind and the rainfall–runoff process in urban high-rise building areas. The runoff coefficient (relating the amount of runoff to the amount of precipitation received) found in the theoretical framework was close to that found in the laboratory experiment.
Laurène J. E. Bouaziz, Fabrizio Fenicia, Guillaume Thirel, Tanja de Boer-Euser, Joost Buitink, Claudia C. Brauer, Jan De Niel, Benjamin J. Dewals, Gilles Drogue, Benjamin Grelier, Lieke A. Melsen, Sotirios Moustakas, Jiri Nossent, Fernando Pereira, Eric Sprokkereef, Jasper Stam, Albrecht H. Weerts, Patrick Willems, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 25, 1069–1095, https://doi.org/10.5194/hess-25-1069-2021, https://doi.org/10.5194/hess-25-1069-2021, 2021
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We quantify the differences in internal states and fluxes of 12 process-based models with similar streamflow performance and assess their plausibility using remotely sensed estimates of evaporation, snow cover, soil moisture and total storage anomalies. The dissimilarities in internal process representation imply that these models cannot all simultaneously be close to reality. Therefore, we invite modelers to evaluate their models using multiple variables and to rely on multi-model studies.
Qiang Dai, Jingxuan Zhu, Shuliang Zhang, Shaonan Zhu, Dawei Han, and Guonian Lv
Hydrol. Earth Syst. Sci., 24, 5407–5422, https://doi.org/10.5194/hess-24-5407-2020, https://doi.org/10.5194/hess-24-5407-2020, 2020
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Rainfall is a driving force that accounts for a large proportion of soil loss around the world. Most previous studies used a fixed rainfall–energy relationship to estimate rainfall energy, ignoring the spatial and temporal changes of raindrop microphysical processes. This study proposes a novel method for large-scale and long-term rainfall energy and rainfall erosivity investigations based on rainfall microphysical parameterization schemes in the Weather Research and Forecasting (WRF) model.
Daniela Molinari, Anna Rita Scorzini, Chiara Arrighi, Francesca Carisi, Fabio Castelli, Alessio Domeneghetti, Alice Gallazzi, Marta Galliani, Frédéric Grelot, Patric Kellermann, Heidi Kreibich, Guilherme S. Mohor, Markus Mosimann, Stephanie Natho, Claire Richert, Kai Schroeter, Annegret H. Thieken, Andreas Paul Zischg, and Francesco Ballio
Nat. Hazards Earth Syst. Sci., 20, 2997–3017, https://doi.org/10.5194/nhess-20-2997-2020, https://doi.org/10.5194/nhess-20-2997-2020, 2020
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Flood risk management requires a realistic estimation of flood losses. However, the capacity of available flood damage models to depict real damages is questionable. With a joint effort of eight research groups, the objective of this study was to compare the performances of nine models for the estimation of flood damage to buildings. The comparison provided more objective insights on the transferability of the models and on the reliability of their estimations.
Marta Galliani, Daniela Molinari, and Francesco Ballio
Nat. Hazards Earth Syst. Sci., 20, 2937–2941, https://doi.org/10.5194/nhess-20-2937-2020, https://doi.org/10.5194/nhess-20-2937-2020, 2020
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INSYDE is a multivariable synthetic model for flood damage assessment of dwellings. The analysis and use of this model highlighted some weaknesses, linked to its complexity, that can undermine its usability and correct implementation. This study proposes a simplified version of INSYDE which maintains its multivariable and synthetic nature but has simpler mathematical formulations permitting an easier use and a direct analysis of the relation between damage and its explanatory variables.
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