Categoria: LandAware network

The recording of the webinar “From Landslide Hazard Assessment to Early Warning: Integrating Geomechanical, Environmental, and Remote Sensing Approaches in Data-Scarce Mountain Regions”, by Danny Love Wamba Djukem (University of Liège, Belgium), held on 25 June 2026, is available on the LandAware YouTube channel.

The fourth webinar of the LandAware 2026 webinar series “What Makes Landslide Forecasts Actionable? Lessons from Users of Aotearoa New Zealand’s Trial Products”, by Sara Harrison (Earth Sciences New Zealand) is scheduled for 30 April 2026, 05:00 UTC.

Dr Sara Harrison is a Hazard and Risk Social Scientist at Earth Sciences New Zealand, specialising in the design and use of people‑centred early warning systems for natural hazards.

Her work focuses on how hazard forecasts, warnings, and decision‑support tools are developed, communicated, and used in real‑world risk management, with a strong emphasis on ensuring science is actionable for those who need it most. In her current role, Sara contributes to national and international projects exploring how trial forecasting products—such as landslide, severe weather, and tsunami hazard and impact forecasts—can be made more usable, trusted, and decision‑relevant. Her work bridges social science and operational hazard modelling, helping ensure that forecast products support effective action rather than simply providing more information.

In this webinar, Sara draws on lessons from users of Aotearoa New Zealand’s trial landslide forecasting products to explore what makes forecasts truly actionable—and how understanding user contexts, decision thresholds, and institutional settings is just as critical as improving technical accuracy.

The third webinar of the LandAware 2026 webinar series “Atmospheric River Controls on Extreme Rainfall and Landslide Hazard in Southeast Alaska”, by Deanna Nash (Center for Western Weather and Water Extremes) is scheduled for 26 March 2026, 15:00 UTC.

Abstract:
Landslides triggered by extreme precipitation during atmospheric rivers (ARs) pose significant hazards to rural and Indigenous communities in Southeast Alaska. Recent research has demonstrated a strong relationship between AR strength and extreme precipitation in the region; however, forecasted AR magnitude and duration alone do not fully explain when impacts occur or provide sufficient context for emergency managers and the public. To address this gap, ongoing collaborative work with the National Weather Service (NWS) in Juneau is focused on developing a forecasting tool that leverages the relationship between AR characteristics and extreme precipitation while also incorporating additional key factors such as freezing level, low-level wind speed and direction, AR orientation, and forecasted precipitation.
Using NOAA’s Global Ensemble Forecast System version 12 (GEFSv12) reforecast dataset, we developed a Model Climate (M-Climate) framework for integrated water vapor transport (IVT), freezing level, low-level winds, and quantitative precipitation forecasts (QPF). M-Climate places these forecast variables within the context of historical reforecasts with the same lead time and time of year. For example, a 95th percentile M-Climate IVT indicates that the ensemble-mean IVT is greater than 95% of reforecast values at that location, lead time, and time of year. By comparing forecasts to analogous forecasts rather than to observations, M-Climate preserves the magnitude of ensemble-mean anomalies that might otherwise be dampened when compared to observed climatology.
Using a catalog of impactful landslides compiled by NWS Juneau, we applied the M-Climate framework to develop the Southeast Alaska Atmospheric River Impact Tool, which highlights when forecasted AR conditions are most likely to lead to impacts such as landslides. The tool is now available operationally to support NWS Juneau forecasters by improving situational awareness and enhancing Impact Decision Support Services (IDSS) messaging before and during high-impact weather events. By linking forecasted AR characteristics to potential impacts, the tool also helps forecasters communicate risk more effectively to weather partners, community leaders, and the public.

Bio:
Deanna Nash, Ph.D., is a Precipitation and Geohazards Scientist at the Center for Western Weather and Water Extremes at the Scripps Institution of Oceanography at the University of California San Diego. Her research focuses on improving understanding and forecasting of meteorological conditions during atmospheric rivers that produce extreme precipitation and increase the risk of flooding and landslides, particularly in mountainous regions of the world. In Southeast Alaska, she contributed to an NSF-funded project through the Coastlines and Peoples Initiative called KUTÍ (one of the Tlingit words for weather), which collaborated closely with forecasters at the National Weather Service Weather Forecast Office in Juneau to develop forecasting tools for extreme atmospheric rivers that are now incorporated into their operational workflows.

The second webinar of the LandAware 2026 webinar series “Landslide Monitoring at the Slope Scale: From Challenges to Early Warning Solutions“, by Andrea Carri (ASE – Advanced Slope Engineering S.r.l.) is scheduled for February 26, 2026 at 06:00 UTC (07:00 CET – 11:30 IST – Feb 25, 23:00 MST).

Abstract:
Slope-scale landslide monitoring represents a critical yet complex component of effective early warning systems. Unlike regional-scale approaches, slope-scale monitoring requires site-specific design choices and long-term operational strategies that directly affect the reliability and credibility of the warning process. This webinar provides a comprehensive overview of the technical and operational challenges associated with the planning, design, implementation, and management of slope-scale monitoring systems.
Key topics include the definition of monitoring objectives, sensor selection and spatial configuration, power supply and communication constraints, data continuity, system maintenance, and robustness under real-world environmental conditions. Particular emphasis is placed on the integration of heterogeneous monitoring technologies and on the transition from raw data acquisition to interpretation and decision support.
The execution phase is explored through real case studies, illustrating how monitoring data are processed, validated, and interpreted over time. Specific attention is given to threshold definition, alert logic, and the management of uncertainties, including the identification and filtering of false positives. Examples of operational early warning actions triggered by monitoring systems are presented to highlight the practical implications of monitoring results.
The webinar aims to contribute to the LandAware community by fostering a shared understanding of best practices, limitations, and lessons learned, and by strengthening the link between slope-scale monitoring, operational decision-making, and landslide early warning.

Biography:
PhD, Eng. Andrea Carri (born 1990) is a civil and environmental engineer specialized in landslide monitoring systems and early warning applications. He obtained his Bachelor’s degree in Civil and Environmental Engineering from the University of Parma in 2012 and his Master’s degree in Environmental Engineering in 2015, with a thesis focused on automatic slope monitoring systems, software development, and data processing.
In 2019, he was awarded a PhD in Engineering and Architecture (31st cycle) at the University of Parma. His doctoral research, supervised by Prof. Andrea Segalini, was entitled “Innovative monitoring instrumentation and methods for landslide risk management and mitigation” and focused on advanced sensing technologies, data interpretation, and operational monitoring strategies.
Since 2015, he has been working at ASE – Advanced Slope Engineering S.r.l., initially within the R&D department. He has served as Technical Director since 2021 and is a member of the company’s Board. His professional activity focuses on the design and implementation of slope-scale monitoring systems, software architecture, data processing algorithms, and calculation methodologies for geotechnical monitoring and early warning.
Andrea Carri is the author and co-author of numerous scientific publications in national and international journals and has been involved in the co-supervision of PhD and Master’s theses in Engineering and Geology. He is an active member of the LandAware Network and of the SIG – Società Italiana Gallerie (Italian Tunnelling Society).