Articles | Volume 21, issue 12
https://doi.org/10.5194/bg-21-2937-2024
© 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/bg-21-2937-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Jun 2024
Research article |
| 18 Jun 2024
| 18 Jun 2024
Spatial patterns of organic matter content in the surface soil of the salt marshes of the Venice Lagoon (Italy)
Department of Land, Environment, Agriculture And Forestry, University of Padua, Padua, 35131, Italy
Department of Geosciences, University of Padua, Padua, 35131, Italy
Davide Tognin
Department of Civil, Environmental and Architectural Engineering, University of Padua, Padua, 35131, Italy
Massimiliano Ghinassi
Department of Geosciences, University of Padua, Padua, 35131, Italy
Erica Franceschinis
Department of Pharmaceutical and Pharmacological Sciences, University of Padua, Padua, 35131, Italy
Nicola Realdon
Department of Pharmaceutical and Pharmacological Sciences, University of Padua, Padua, 35131, Italy
Marco Marani
Department of Civil, Environmental and Architectural Engineering, University of Padua, Padua, 35131, Italy
Andrea D'Alpaos
Department of Geosciences, University of Padua, Padua, 35131, Italy
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EGUsphere, https://doi.org/10.5194/egusphere-2026-1243, https://doi.org/10.5194/egusphere-2026-1243, 2026
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
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Sea level records are often too short. The traditional asymptotic extreme value analysis fails to produce accurate results with short records. By leveraging the non-asymptotic Metastatistical Extreme Value Distribution via the integration of two novel independent event selection methodologies, along with a robust cross-validation procedure, we found that our methodology can accurately estimate the likelihood of long return period extreme sea level events in data-scarce settings.
Andrea D'Alpaos, Davide Tognin, Laura Tommasini, Luigi D'Alpaos, Andrea Rinaldo, and Luca Carniello
Earth Surf. Dynam., 12, 181–199, https://doi.org/10.5194/esurf-12-181-2024, https://doi.org/10.5194/esurf-12-181-2024, 2024
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Sediment erosion induced by wind waves is one of the main drivers of the morphological evolution of shallow tidal environments. However, a reliable description of erosion events for the long-term morphodynamic modelling of tidal systems is still lacking. By statistically characterizing sediment erosion dynamics in the Venice Lagoon over the last 4 centuries, we set up a novel framework for a synthetic, yet reliable, description of erosion events in tidal systems.
Davide Tognin, Andrea D'Alpaos, Luigi D'Alpaos, Andrea Rinaldo, and Luca Carniello
Earth Surf. Dynam., 12, 201–218, https://doi.org/10.5194/esurf-12-201-2024, https://doi.org/10.5194/esurf-12-201-2024, 2024
Short summary
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Reliable quantification of sediment transport processes is necessary to understand the fate of shallow tidal environments. Here we present a framework for the description of suspended sediment dynamics to quantify deposition in the long-term modelling of shallow tidal systems. This characterization, together with that of erosion events, allows one to set up synthetic, yet reliable, models for the long-term evolution of tidal landscapes.
Guillaume Goodwin, Marco Marani, Sonia Silvestri, Luca Carniello, and Andrea D'Alpaos
Biogeosciences, 20, 4551–4576, https://doi.org/10.5194/bg-20-4551-2023, https://doi.org/10.5194/bg-20-4551-2023, 2023
Short summary
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Seagrass meadows are an emblematic coastal habitat. Their sensitivity to environmental change means that it is essential to monitor their evolution closely. However, high costs make this endeavor a technical challenge. Here, we used machine learning to map seagrass meadows in 148 satellite images in the Venice Lagoon, Italy. We found that adding information such as depth of the seabed and known seagrass location improved our capacity to map temporal change in seagrass habitat.
T. Blount, S. Silvestri, M. Marani, and A. D’Alpaos
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W1-2023, 57–62, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-57-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W1-2023-57-2023, 2023
Eleonora Dallan, Francesco Marra, Giorgia Fosser, Marco Marani, Giuseppe Formetta, Christoph Schär, and Marco Borga
Hydrol. Earth Syst. Sci., 27, 1133–1149, https://doi.org/10.5194/hess-27-1133-2023, https://doi.org/10.5194/hess-27-1133-2023, 2023
Short summary
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Convection-permitting climate models could represent future changes in extreme short-duration precipitation, which is critical for risk management. We use a non-asymptotic statistical method to estimate extremes from 10 years of simulations in an orographically complex area. Despite overall good agreement with rain gauges, the observed decrease of hourly extremes with elevation is not fully represented by the model. Climate model adjustment methods should consider the role of orography.
Maria Francesca Caruso and Marco Marani
Nat. Hazards Earth Syst. Sci., 22, 1109–1128, https://doi.org/10.5194/nhess-22-1109-2022, https://doi.org/10.5194/nhess-22-1109-2022, 2022
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We comparatively evaluate the predictive performance of traditional and new approaches to estimate the probability distributions of extreme coastal water levels. The metastatistical approach maximizes the use of observational information and provides reliable estimates of high quantiles with respect to traditional methods. Leveraging the increased estimation accuracy afforded by this approach, we investigate future changes in the frequency of extreme total water levels.
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Short summary
This study aims at inspecting organic matter dynamics affecting the survival and carbon sink potential of salt marshes, which are valuable yet endangered wetland environments. Measuring the organic matter content in marsh soils and its relationship with environmental variables, we observed that the organic matter accumulation varies at different scales, and it is driven by the interplay between sediment supply and vegetation, which are affected, in turn, by marine and fluvial influences.
This study aims at inspecting organic matter dynamics affecting the survival and carbon sink...
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