Maria Katherina Dal Barco

In our previous study, we identified that extreme sea levels, heavy precipitation, and strong winds were the main drivers of past impacts along the coastal municipalities of the Veneto region (Italy). Here, we introduce a two-tier approach that determine a daily risk score and estimates the annual frequency of impacts. By integrating climate change scenarios for these key drivers (sea level, precipitation, and wind) into our AI-based model, we project a gradual increase in impacts under all scenarios. Our findings highlight that sea level rise drives the long-term upward trend, while precipitation influences seasonal variability.

From rising seas to extreme weather: what’s coming for the Veneto coasts?
In our latest study we estimated the annual frequency of impacts, revealing a gradual increase across all scenarios: SLR drives the rising trend, while precipitation influences seasonal variability.

📌 doi.org/10.1016/j.sc...

03.03.2025 18:34 — 👍 2    🔁 0    💬 0    📌 0

Explore emerging innovations in multi-hazard systemic risk assessment. Share insights on #AI, #multi-risk, resilience-building to advance disaster risk management and climate #adaptation. Submit your research at #EGU2025 and join session NH10.6: meetingorganizer.copernicus.org/EGU25/sessio...

29.11.2024 14:19 — 👍 3    🔁 0    💬 0    📌 0

Last week our team presented to the Veneto SHs #AcquaGuard, a brand new EU-funded project aimed at developing the capabilities of local and regional governments to systematically plan, integrate, and implement #NBS to face climate-related risks and hazards.

🌍 www.italy-croatia.eu/web/acquaguard

19.11.2024 22:54 — 👍 3    🔁 0    💬 0    📌 0

Which are the main drivers of risks in the Veneto coast that can be identified by applying #ML algorithms? 🌊☔🌀

In our latest publication we tested three Machine Learning tools to estimate daily #risk in coastal areas and identify climate hazards triggering coastal risks.

📌 doi.org/10.1016/j.ij...

19.11.2024 22:35 — 👍 3    🔁 0    💬 0    📌 0

Bayesian Network Analysis for Shoreline Dynamics, Coastal Water Quality, and Their Related Risks in the Venice Littoral Zone, Italy The coastal environment is vulnerable to natural hazards and human-induced stressors. The assessment and management of coastal risks have become a challenging task, due to many environmental and socio...

This study assesses the combined impact of climate stressors on coastal change and water quality in low-lying coastal areas, employing a Bayesian Network model for multi-risk scenario analysis along the Venetian coast.

📌 doi.org/10.3390/jmse...

19.11.2024 22:19 — 👍 2    🔁 0    💬 0    📌 0

📢Is 𝕘𝕣𝕖𝕖𝕟🌿the new 🅑🅛🅐🅒🅚?
In this publication we focused on the assessment of coastal erosion #risk in the Apulian shoreline also considering both climate change scenarios and the potential risk reduction effects induced by #NBS

📌 doi.org/10.1016/j.en...

19.11.2024 22:13 — 👍 0    🔁 0    💬 0    📌 0

Our team developed a multi-model chain approach (combining ocean hydrodynamics, wave fields, and shoreline extraction models) to build a Bayesian Network-based model to assess coastal risk related to shoreline evolution and seawater quality.

📌 doi.org/10.1016/j.en...

19.11.2024 22:11 — 👍 0    🔁 0    💬 0    📌 0

Combining remote sensing analysis with machine learning to evaluate short-term coastal evolution trend in the shoreline of Venice With increasing storminess and incessant sea-level rise, coastal erosion is becoming a primary issue along many littorals in the world. To cope with p…

A fast way to evaluate coastal evolution trends? 🐚🌊🏝️
#satelliteimages #machinelearning #GIS

In this paper, we present findings and insights on shoreline change detection along the Venice littoral, utilizing remote sensing analysis combined with machine learning techniques
📌 doi.org/10.1016/j.sc...

19.11.2024 22:00 — 👍 4    🔁 1    💬 0    📌 0

Hello! 👋
I am a researcher at the CMCC Foundation specializing in multi-hazard and multi-risk assessment and management of coastal areas. I would appreciate it if you could include me on the list. Thank you!

19.11.2024 21:44 — 👍 2    🔁 0    💬 1    📌 0