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Geosciences
Special Issues
Local and Territorial Landslide Early Warning Systems
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Local and Territorial Landslide Early Warning Systems

A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Natural Hazards".

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 15858

Special Issue Editors

Dr. Luca Piciullo

E-Mail Website
Guest Editor
Norwegian Geotechnical Institute (NGI), Sognsvn. 72, 0855 Oslo, Norway
Interests: early warning systems; slope stability and monitoring; landslide modeling and correlations; machine learning applied in natural hazard risk assessment; rainfall thresholds; risk management of dam tailings
Dr. James Michael Strout

E-Mail Website
Guest Editor
Norwegian Geotechnical Institute (NGI), Sognsvn. 72, 0855 Oslo, Norway
Interests: sensors and sensor systems; remote sensing methodologies and applications; climate change adaption; nature-based solutions and sustainability
Dr. Samuele Segoni

E-Mail Website
Guest Editor
Department of Earth Sciences, University of Firenze, Firenze, Italy
Interests: prediction and mapping of landslide hazards; physically based models for the triggering of shallow landslides; landslide susceptibility maps; rainfall thresholds for landslide triggering; regional-scale landslide early warning systems; civil protection; land planning; landslide risk assessment
Special Issues, Collections and Topics in MDPI journals
Dr. Emanuele Intrieri

E-Mail Website
Guest Editor
Department of Earth Sciences, Università degli Studi di Firenze, via G. La Pira 4, 50121 Firenze, Italy
Interests: cultural heritage; early warning systems; remote sensing; landslides; forecasting methods; SAR interferometry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Among the many mitigation measures available for reducing the risk to life related to landslides, early warning systems certainly constitute a significant option available to the authorities in charge of risk management and governance. Landslide early warning systems (LEWS) are non-structural risk mitigation measures applicable at different scales of analysis: slope and regional. Systems addressing single landslides at slope scale can be called local LEWS (Lo-LEWS), while systems operating over wide areas at regional scale are referred to as territorial systems (Te-LEWSs). An initial key difference between Lo-LEWSs and Te-LEWSs is the knowledge a priori of the areas affected by future landsliding. When the location of future landslides is unknown, and the area of interest extends beyond a single slope, only Te-LEWS can be employed. Conversely, Lo-LEWSs are typically adopted to cope with the risk related to one or more known well-identified landslides.

This Special Issue focuses on landslide early warning systems (LEWSs) at both regional and local scales. The Special Issue wishes to gather high-quality contributions on different operational approaches, original monitoring techniques, and methods useful to operate reliable (efficient and effective) Lo-LEWS and Te-LEWS. Contributions addressing the following topics are welcome:

  • Improvement of landslide and rainfall databases;
  • Innovative monitoring systems;
  • Real-time monitoring and stability analysis with the Internet of Things (IoT);
  • Rainfall thresholds definition;
  • Warning models for warning levels issuing;
  • Performance analysis of landslide warning models;
  • Communication strategies;
  • Emergency phase management;
  • Landslide risk communication.

Dr. Luca Piciullo
Dr. James Michael Strout
Dr. Samuele Segoni
Dr. Emanuele Intrieri
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Geosciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Landslide
  • Landslide monitoring
  • Remote sensing
  • Internet of Things (IoT)
  • Landslide and rainfall databases
  • Rainfall thresholds
  • Short-term localized forecast
  • Performance
  • Risk management
  • Communication strategy

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Published Papers (3 papers)

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Research

16 pages, 5827 KB  
Article
Wadenow: A Matlab Toolbox for Early Forecasting of the Velocity Trend of a Rainfall-Triggered Landslide by Means of Continuous Wavelet Transform and Deep Learning
by Giordano Teza, Simonetta Cola, Lorenzo Brezzi and Antonio Galgaro
Geosciences 2022, 12(5), 205; https://doi.org/10.3390/geosciences12050205 - 12 May 2022
Cited by 9 | Viewed by 5666
Abstract
A procedure aimed at forecasting the velocity trend of a landslide for a period of some hours to one or two days is proposed here together with its MATLAB implementation. The method is based on continuous wavelet transform (CWT) and convolutional neural network [...] Read more.
A procedure aimed at forecasting the velocity trend of a landslide for a period of some hours to one or two days is proposed here together with its MATLAB implementation. The method is based on continuous wavelet transform (CWT) and convolutional neural network (CNN) applied to rainfall and velocity time series provided by a real-time monitoring system. It is aimed at recognizing the conditions that induce a strong increase, or even a significant decrease, in the average velocity of the unstable slope. For each evaluation time, the rainfall and velocity scalograms related to the previous days (e.g., two weeks) are computed by means of CWT. A CNN recognizes the velocity trend defined in the training stage corresponds to these scalograms. In this way, forecasts about the start, persistence, and end of a critical event can be provided to the decision makers. An application of the toolbox to a landslide (Perarolo di Cadore landslide, Eastern Alps, Italy) is also briefly described to show how the parameters can be chosen in a real case and the corresponding performance. Full article
(This article belongs to the Special Issue Local and Territorial Landslide Early Warning Systems)
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19 pages, 9224 KB  
Article
Robotic Total Station Monitoring in High Alpine Paraglacial Environments: Challenges and Solutions from the Great Aletsch Region (Valais, Switzerland)
by Franziska Glueer, Simon Loew, Reto Seifert, Jordan Aaron, Lorenz Grämiger, Stefan Conzett, Philippe Limpach, Andreas Wieser and Andrea Manconi
Geosciences 2021, 11(11), 471; https://doi.org/10.3390/geosciences11110471 - 16 Nov 2021
Cited by 7 | Viewed by 4281
Abstract
Investigating surface displacements in high alpine environments is often subject to challenges due to the difficult accessibility or harsh climatic conditions. Measurement systems have improved greatly in recent years regarding accuracy, range, or energy consumption. Continuously receiving high-precision, real-time monitoring data from a [...] Read more.
Investigating surface displacements in high alpine environments is often subject to challenges due to the difficult accessibility or harsh climatic conditions. Measurement systems have improved greatly in recent years regarding accuracy, range, or energy consumption. Continuously receiving high-precision, real-time monitoring data from a remote location can still support a better understanding of slope dynamics and risk. We present the design, construction, operation, and performance of a complex surface displacement monitoring system installed in the surroundings of the Great Aletsch Glacier in the Swiss Alps, based on two robotic total stations to continuously measure 3D displacements with high accuracies. In addition, GNSS stations are also considered in order to pass from a local to a geographic reference system, as well as to improve the measurement accuracy. The monitoring network is aimed at studying several types of deformation processes, i.e., (i) gravitationally driven and irreversible rockslide movements around the tongue of the Great Aletsch Glacier, (ii) reversible rock slope deformations caused by annual cycles of groundwater recharge and depletion, and (iii) small irreversible deformations of stable rock slopes resulting from progressive rock damage driven by glacier retreat and cyclic hydraulic and thermal loading. We describe the technical details of the monitoring system, which has been in operation successfully for 6 years, and discuss the system performance in terms of its robustness and accuracy. Full article
(This article belongs to the Special Issue Local and Territorial Landslide Early Warning Systems)
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24 pages, 9516 KB  
Article
Wildfires Effect on Debris Flow Occurrence in Italian Western Alps: Preliminary Considerations to Refine Debris Flow Early Warnings System Criteria
by Davide Tiranti, Roberto Cremonini and Daniele Sanmartino
Geosciences 2021, 11(10), 422; https://doi.org/10.3390/geosciences11100422 - 10 Oct 2021
Cited by 12 | Viewed by 4028
Abstract
Rarely, a close correlation between wildfires and the occurrence of channelized debris flows has been observed in the Western Italian Alps. Only two cases in history have been reported, after brief and localized rainfall events of moderate intensity in Italy’s Piemonte region (NW [...] Read more.
Rarely, a close correlation between wildfires and the occurrence of channelized debris flows has been observed in the Western Italian Alps. Only two cases in history have been reported, after brief and localized rainfall events of moderate intensity in Italy’s Piemonte region (NW Italy) caused debris flows, on 18 July 2005, in Verbania province (Pallanzeno municipality), and on June 2018 in Turin province (Bussoleno municipality). These phenomena occurred after a large portion of the catchments were affected by wide wildfires in the preceding months. Debris flow deposits showed an unusually large number of fine-grained particles, forming dark-brown mud-rich deposits associated with burnt wood deposits. Rainfall analysis related to the period between the wildfires’ occurrence and the debris flow events, using both raingauge and weather radar data, pointed out that the debris flows triggered in July 2005 and June 2018 were characterized by greater magnitude but associated with less precipitation intensity rates as compared with previous mud flows occurring just after wildfires. These behaviors can be explained by the presence of burned organic material and fine-grained sediment, generated from the soil’s thermal reworking, which formed a thick layer, centimeters deep, covering a large percentage of catchments and slopes. Most of this layer, generated by wildfires’ action were winnowed by rainfall events that had occurred in the months before the debris flow events, of significant magnitude, exhuming a discontinuous hydrophobic soil surface that changed the slopes’ permeability characteristics. In such conditions, runoff increased, corrivation time shortened, and, consequently, discharge along the two catchments’ channels-network increased as well. Consequently, the rainfall effects associated with rainfall events in July 2005 and June 2019 were more effective in mobilizing coarse sediments in channel beds than was typical for those catchments. Full article
(This article belongs to the Special Issue Local and Territorial Landslide Early Warning Systems)
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