Articles | Volume 25, issue 11
https://doi.org/10.5194/nhess-25-4317-2025
© Author(s) 2025. 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-25-4317-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
INSYDE-content: a synthetic, multi-variable flood damage model for household contents
Pradeep Acharya
Department of Civil, Environmental and Architectural Engineering, University of L'Aquila, 67100 L'Aquila, Italy
Department of Civil and Environmental Engineering, Politecnico di Milano, 20133 Milano, Italy
Mario Di Bacco
Department of Civil and Environmental Engineering, University of Florence, 50139 Firenze, Italy
Daniela Molinari
Department of Civil and Environmental Engineering, Politecnico di Milano, 20133 Milano, Italy
Anna Rita Scorzini
CORRESPONDING AUTHOR
Department of Civil, Environmental and Architectural Engineering, University of L'Aquila, 67100 L'Aquila, 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
Revised manuscript accepted 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.
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.
Cristina Prieto, Dhruvesh Patel, Dawei Han, Benjamin Dewals, Michaela Bray, and Daniela Molinari
Nat. Hazards Earth Syst. Sci., 24, 3381–3386, https://doi.org/10.5194/nhess-24-3381-2024, https://doi.org/10.5194/nhess-24-3381-2024, 2024
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.
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.
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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Short summary
INSYDE-content is a novel probabilistic model designed to estimate flood damage to household contents. Based on a synthetic “what-if” approach, it integrates multiple input variables describing both exposed items and damage mechanisms, while accounting for uncertainty. The model expands the range of available tools for flood damage assessment by including an often overlooked asset in current literature.
INSYDE-content is a novel probabilistic model designed to estimate flood damage to household...
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