Articles | Volume 26, issue 10
https://doi.org/10.5194/nhess-26-4861-2026
© Author(s) 2026. 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-26-4861-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Invited perspectives
| Highlight paper
| 
07 Oct 2026
Invited perspectives | Highlight paper |
| 07 Oct 2026
| 07 Oct 2026
Invited perspective: Uncertainties in natural systems may be uncomfortable, but ignoring them would be absurd
Warner Marzocchi
CORRESPONDING AUTHOR
Department of Earth, Environmental, and Resources Sciences, University of Naples Federico II, Naples, Italy
Interdisciplinary science-technology department, Scuola Superiore Meridionale, Naples, Italy
Alberto Montanari
Department of Civil, Chemical, Environmental, and Materials engineering, University of Bologna, Italy
A full list of authors appears at the end of the paper.
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Flavia Ferriero, Fausto Guzzetti, and Warner Marzocchi
Nat. Hazards Earth Syst. Sci., 26, 4457–4477, https://doi.org/10.5194/nhess-26-4457-2026, https://doi.org/10.5194/nhess-26-4457-2026, 2026
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Landslides cause thousands of deaths and billions in damages yearly, yet predicting them remains a major challenge. We developed a Bayesian method that estimates landslide probability as a function of rainfall, explicitly accounting for uncertainty. Applied in southern Italy, landslide probability increases gradually with rainfall, with no sharp thresholds in the triggering conditions. This approach supports a more uncertainty-aware landslide risk management.
Salvatore Ferrara, Jacopo Selva, Jacopo Natale, and Warner Marzocchi
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This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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We develop a probabilistic framework for modeling volcanic eruption sizes. Assuming a power-law distribution on erupted volumes, we analyze how measurement error can cause the observed trend to deviate from such a distribution. We apply this framework to Campi Flegrei, Italy, and Taupo, New Zealand, and observe that when the error is properly accounted for, the data distribution is compatible with a power-law, supporting the use of such a distribution in size forecasting.
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We propose a scoring strategy to rank multiple models/branches of a probabilistic seismic hazard analysis (PSHA) model that could be useful to consider specific requests from stakeholders responsible for seismic risk reduction actions. In fact, applications of PSHA often require sampling a few hazard curves from the model. The procedure is introduced through an application aimed to score and rank the branches of a recent Italian PSHA model according to their fit with macroseismic intensity data.
John Douglas, Helen Crowley, Vitor Silva, Warner Marzocchi, Laurentiu Danciu, and Rui Pinho
EGUsphere, https://doi.org/10.5194/egusphere-2023-991, https://doi.org/10.5194/egusphere-2023-991, 2023
Preprint withdrawn
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Estimates of the earthquake ground motions expected during the lifetime of a building or the length of an insurance policy are frequently calculated for locations around the world. Estimates for the same location from different studies can show large differences. These differences affect engineering, financial and risk management decisions. We apply various approaches to understand when such differences have an impact on such decisions and when they are expected because data are limited.
Domenico Giaquinto, Warner Marzocchi, and Jürgen Kurths
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Despite being among the most severe climate extremes, it is still challenging to assess droughts’ features for specific regions. In this paper we study meteorological droughts in Europe using concepts derived from climate network theory. By exploring the synchronization in droughts occurrences across the continent we unveil regional clusters which are individually examined to identify droughts’ geographical propagation and source–sink systems, which could potentially support droughts’ forecast.
Warner Marzocchi, Jacopo Selva, and Thomas H. Jordan
Nat. Hazards Earth Syst. Sci., 21, 3509–3517, https://doi.org/10.5194/nhess-21-3509-2021, https://doi.org/10.5194/nhess-21-3509-2021, 2021
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Eruption forecasting and volcanic hazard analysis are pervaded by uncertainty of different kinds, such as the natural randomness, our lack of knowledge, and the so-called unknown unknowns. After discussing the limits of how classical probabilistic frameworks handle these uncertainties, we put forward a unified probabilistic framework which unambiguously defines uncertainty of different kinds, and it allows scientific validation of the hazard model against independent observations.
Yue Lai, Rui Guo, and Alberto Montanari
EGUsphere, https://doi.org/10.5194/egusphere-2026-5518, https://doi.org/10.5194/egusphere-2026-5518, 2026
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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Predicting how extreme precipitation will change is vital for flood protection, yet remains difficult. Using one of the longest daily precipitation records, from Bologna, Italy, since 1813, we tested many climate models and combined them into more reliable projections. Extreme precipitation intensity will likely keep rising this century, especially under high emission scenarios. This can provide a solid foundation for regional flood risk management and adaptation planning.
Flavia Ferriero, Fausto Guzzetti, and Warner Marzocchi
Nat. Hazards Earth Syst. Sci., 26, 4457–4477, https://doi.org/10.5194/nhess-26-4457-2026, https://doi.org/10.5194/nhess-26-4457-2026, 2026
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Landslides cause thousands of deaths and billions in damages yearly, yet predicting them remains a major challenge. We developed a Bayesian method that estimates landslide probability as a function of rainfall, explicitly accounting for uncertainty. Applied in southern Italy, landslide probability increases gradually with rainfall, with no sharp thresholds in the triggering conditions. This approach supports a more uncertainty-aware landslide risk management.
Salvatore Ferrara, Jacopo Selva, Jacopo Natale, and Warner Marzocchi
EGUsphere, https://doi.org/10.5194/egusphere-2026-1415, https://doi.org/10.5194/egusphere-2026-1415, 2026
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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We develop a probabilistic framework for modeling volcanic eruption sizes. Assuming a power-law distribution on erupted volumes, we analyze how measurement error can cause the observed trend to deviate from such a distribution. We apply this framework to Campi Flegrei, Italy, and Taupo, New Zealand, and observe that when the error is properly accounted for, the data distribution is compatible with a power-law, supporting the use of such a distribution in size forecasting.
Alonso Pizarro, Demetris Koutsoyiannis, and Alberto Montanari
Hydrol. Earth Syst. Sci., 29, 4913–4928, https://doi.org/10.5194/hess-29-4913-2025, https://doi.org/10.5194/hess-29-4913-2025, 2025
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We introduce the ratio of uncertainty to mutual information (RUMI), a new metric to improve rainfall-runoff simulations. RUMI better captures the link between observed and simulated stream flows by considering uncertainty at a core computation step. Tested on 99 catchments and with the GR4J model, it outperforms traditional metrics by providing more reliable and consistent results. RUMI paves the way for more accurate hydrological predictions.
Alberto Montanari, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 28, 2603–2615, https://doi.org/10.5194/hess-28-2603-2024, https://doi.org/10.5194/hess-28-2603-2024, 2024
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Floods often take communities by surprise, as they are often considered virtually
impossibleyet are an ever-present threat similar to the sword suspended over the head of Damocles in the classical Greek anecdote. We discuss four reasons why extremely large floods carry a risk that is often larger than expected. We provide suggestions for managing the risk of megafloods by calling for a creative exploration of hazard scenarios and communicating the unknown corners of the reality of floods.
Vera D'Amico, Francesco Visini, Andrea Rovida, Warner Marzocchi, and Carlo Meletti
Nat. Hazards Earth Syst. Sci., 24, 1401–1413, https://doi.org/10.5194/nhess-24-1401-2024, https://doi.org/10.5194/nhess-24-1401-2024, 2024
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We propose a scoring strategy to rank multiple models/branches of a probabilistic seismic hazard analysis (PSHA) model that could be useful to consider specific requests from stakeholders responsible for seismic risk reduction actions. In fact, applications of PSHA often require sampling a few hazard curves from the model. The procedure is introduced through an application aimed to score and rank the branches of a recent Italian PSHA model according to their fit with macroseismic intensity data.
Rui Guo and Alberto Montanari
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The present study refers to the region of Bologna, where the availability of a 209-year-long daily rainfall series allows us to make a unique assessment of global climate models' reliability and their predicted changes in rainfall and multiyear droughts. Our results suggest carefully considering the impact of uncertainty when designing climate change adaptation policies for droughts. Rigorous use and comprehensive interpretation of the available information are needed to avoid mismanagement.
John Douglas, Helen Crowley, Vitor Silva, Warner Marzocchi, Laurentiu Danciu, and Rui Pinho
EGUsphere, https://doi.org/10.5194/egusphere-2023-991, https://doi.org/10.5194/egusphere-2023-991, 2023
Preprint withdrawn
Short summary
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Estimates of the earthquake ground motions expected during the lifetime of a building or the length of an insurance policy are frequently calculated for locations around the world. Estimates for the same location from different studies can show large differences. These differences affect engineering, financial and risk management decisions. We apply various approaches to understand when such differences have an impact on such decisions and when they are expected because data are limited.
Domenico Giaquinto, Warner Marzocchi, and Jürgen Kurths
Nonlin. Processes Geophys., 30, 167–181, https://doi.org/10.5194/npg-30-167-2023, https://doi.org/10.5194/npg-30-167-2023, 2023
Short summary
Short summary
Despite being among the most severe climate extremes, it is still challenging to assess droughts’ features for specific regions. In this paper we study meteorological droughts in Europe using concepts derived from climate network theory. By exploring the synchronization in droughts occurrences across the continent we unveil regional clusters which are individually examined to identify droughts’ geographical propagation and source–sink systems, which could potentially support droughts’ forecast.
Warner Marzocchi, Jacopo Selva, and Thomas H. Jordan
Nat. Hazards Earth Syst. Sci., 21, 3509–3517, https://doi.org/10.5194/nhess-21-3509-2021, https://doi.org/10.5194/nhess-21-3509-2021, 2021
Short summary
Short summary
Eruption forecasting and volcanic hazard analysis are pervaded by uncertainty of different kinds, such as the natural randomness, our lack of knowledge, and the so-called unknown unknowns. After discussing the limits of how classical probabilistic frameworks handle these uncertainties, we put forward a unified probabilistic framework which unambiguously defines uncertainty of different kinds, and it allows scientific validation of the hazard model against independent observations.
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Editorial statement
The paper advances hazard and risk science by developing a cross-hazard framework for systematically identifying, separating, quantifying, and communicating multiple sources of uncertainty, centred on the novel concept of a “complete forecast.” The paper can be a highlight paper because it bridges traditionally fragmented disciplinary approaches to uncertainty and offers a broadly applicable foundation for more transparent model evaluation, risk communication, and uncertainty-informed decision-making.
The paper advances hazard and risk science by developing a cross-hazard framework for...
Short summary
Natural systems are complex and uncertain, making probabilistic forecasts essential. Representing and communicating all uncertainties is challenging but vital for risk management. A multidisciplinary review identified common challenges across hazards and proposes a shared framework based on a clear hierarchy of uncertainties, complete forecasts, rigorous model evaluation, and effective communication to support decision-making.
Natural systems are complex and uncertain, making probabilistic forecasts essential....
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