News from members

New article on wildfire effects on debris flows and LEWS

NEWS received from
Davide Tiranti, Regional Agency for Environmental Protection of Piedmont region, Italy

New article “Wildfires Effect on Debris Flow Occurrence in Italian Western Alps: Preliminary Considerations to Refine Debris Flow Early Warnings System Criteria” published in the special issue of Geosciences journal on “Local and Territorial Landslide Early Warning Systems

In this paper, two case studies in the Italian western Alps on the relationship between wildfires and debris flows occurrence have been analyzed to understand how to integrate this factor in the regional debris flow early warning system (DFEWS). To define these correlations, the authors conducted analyses to characterize changes in the conditions and behavior of catchments after wildfires. The Curve Number (CN) method was adopted to estimate hydrological variations before and after wildfires and identify the differences in catchments response to rainfall events, due to its simple applicability over a large number of catchments. Rainfall analyses, using both data from raingauges and weather radars to identify the actual distribution of precipitation intensity fields, were addressed. The case studies described have led to some interesting results, both regarding the understanding of the wildfires effects on debris flows triggering in small Alpine catchments and on the necessary technical and operational adjustments to improve the DFEWS performance in case of wildfire occurrence.

Reference: Tiranti D., Cremonini R., Sanmartino D. (2021) Wildfires Effect on Debris Flow Occurrence in Italian Western Alps: Preliminary Considerations to Refine Debris Flow Early Warnings System Criteria. Geosciences 11, 422.

News from members

New article: Landslide risk assessment considering socionatural factors

NEWS received from
Paulo Hader – São Paulo State University (UNESP)

New article: Risk cross-referencing for landslide risk assessment at a municipal scale, by Paulo Hader and co-authors from São Paulo State University, Brazil

This recently published paper proposes a model for landslide risk assessment at the municipal scale, useful for early waninrg purposes.
Three products, being rainfall thresholds, landslide susceptibility map and social vulnerability map were produced statistically. To couple them, the authors used a two-matrix approach, where in the first matrix the susceptibility map and the vulnerability map were crossed, constituting the socio-natural criterion; and in the second matrix, the rainfall thresholds were coupled to the socionatural criterion, allowing a real-time assessment.
The authors found that the model offers easy adaptation and calibration once new data emerges, as well as being able to be integrated into a landslide early warning system to make explicit the areas of highest degree of loss, where interventions can be made in advance to reduce the risk in specific areas.

Reference: Hader, P.R.P., Reis, F.A.G.V. & Peixoto, A.S.P. (2021) Landslide risk assessment considering socionatural factors: methodology and application to Cubatão municipality, São Paulo, Brazil. Natural Hazards

News from members

New article: Wicki et al. (2021)

NEWS received from
Adrian Wicki
PhD StudentSwiss Federal Research Institute WSL
Mountain Hydrology and Mass Movements Research Unit
Zürcherstrasse 111
CH-8903 Birmensdorf

In a recently published article we assess the potential of simulated soil moisture for regional landslide early warning. For this study, soil moisture variation was simulated with a physically-based 1D soil water transfer model and forecasst goodness for landslides was assessed using a statistical landslide forecast model. In direct comparison with in-situ measured soil moisture we found that the overall representativeness for regional landslide occurence is high, however that it is particularly challenging to well characterize critical antecedent wetness conditions.

Wicki, A., Jansson, P.-E., Lehmann, P., Hauck, C., and Stähli, M.: Simulated or measured soil moisture: which one is adding more value to regional landslide early warning?, Hydrol. Earth Syst. Sci., 25, 4585–4610,, 2021.

LandAware network

LandAware in the journal “Landslides”

A News/Kyoto Commitment article has been published today (online first) on the scientific journal “Landslides” to present the LandAware network to the many readers of the journal.

Calvello M, Devoli G, Freeborough K, Gariano SL; Guzzetti F, Kirschbaum D, Nakaya H, Robbins J, Stähli M (2020). LandAware: a new international network on Landslide Early Warning Systems. Landslides, online first.

Extracts from the article

Many recent international initiatives have been highlighting the importance of EWSs for disaster risk reduction purposes. [..] In response to these global initiatives, natural hazard experts working with EWSs around the world have recently founded programs and networks to promote international collaboration among members engaged in both surveillance of natural hazards and issuance of warnings to key stakeholders (authorities and public). Among them we can mention multi-hazard initiatives, such as the multi-stakeholder International Network for Multi-Hazard Early Warning Systems promoted by the World Meteorological Organization, as well as initiatives focusing on single natural hazards, such as the Intergovernmental Oceanographic Commission Tsunami Programme, the World Organization of Volcanic Observatories, the Global Seismographic Network of the IRIS consortium in the USA, and the European Avalanche Warning Services. Filling a gap in this global scenario, and in response to the abovementioned requests from the landslide risk scientific community, in July 2020 a multi-disciplinary international network of experts in LEWS was founded. The network is named “LandAware – the international network on Landslide Early Warning Systems”.

[..] upcoming activities of LandAware will always be, given the stated purposes of the network, in line with Kyoto Landslide Commitment 2020 priority action no. 1, which aims at promoting “the development of people-centered early warning technology for landslides with increased precision and reliable prediction both in time and location, especially in a changing climate context.”