Davide Tiranti

Roberto Cremonini

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EDITORIALpublished: 29 January 2019doi: 10.3389/feart.2019.00003Frontiers in Earth Science | www.frontiersin.org 1 January 2019 | Volume 7 | Article 3Edited and reviewed by:Steven L. Forman,Baylor University, United States*Correspondence:Davide Tirantidavide.tiranti@arpa.piemonte.itSpecialty section:This article was submitted toQuaternary Science, Geomorphologyand Paleoenvironment,a section of the journalFrontiers in Earth ScienceReceived: 07 November 2018Accepted: 07 January 2019Published: 29 January 2019Citation:Tiranti D and Cremonini R (2019)Editorial: Landslide Hazard in aChanging Environment.Front. Earth Sci. 7:3.doi: 10.3389/feart.2019.00003Editorial: Landslide Hazard in aChanging EnvironmentDavide Tiranti* and Roberto CremoniniDepartment of Natural and Environmental Risks, Regional Agency for Environmental Protection of Piemonte, Turin, ItalyKeywords: climate change impacts, landslide early warning system, landslide modeling, landslide hazardassessment, debris flow, flash flood, glacial lake overbust floodEditorial on the Research TopicLandslide Hazard in a Changing EnvironmentLandslides are one of the most common natural disasters in the world causing large economiclosses and casualties. Their impacts are increasing globally due to rapid development, deforestationand urbanization. According to the Emergency Events Database at Université Catholique deLouvain (UCL)—CRED, from 2008 to 2017 (OFDA/CRED, 2018), landslides has been responsiblefor 10,338 deaths worldwide, with more than 3 million citizens affected and more thanUS$ 2.7 billion economic losses. Even in the absence of fatalities, landslides and floods havesignificant socio-economic impacts. These include the severance of access to and from relativelyremote communities for services and markets for goods; employment, health and educationalopportunities; and social activities. Recently, a series of debris flows occurred in southernCalifornia, US, on January 2018 causing 21 deaths and economic losses for more than US$ 207million, and landslides caused by heavy rain killed 32 people in Ethiopia in May 2018.Cruden and Varnes (1996) define landslides as movements of a mass of rock, debris or earthdown the slope. Hungr et al. (2014) classified landslides based on failure mechanisms and involvedmaterial. Other relevant landslide classifications are related to landslide velocity (Cruden andVarnes, 1996) and size (Fell, 1994) as expression of phenomenal magnitude or related to thetriggering factors, like earthquakes or rainfall (Rodríguez et al., 1999; Katsura et al., 2008; Baumand Godt, 2010; Havenith et al., 2016; Calvello, 2017).During the last decades, climate change has affected the stability of natural and engineeredslopes at different temporal and geographical scales (Seneviratne et al., 2012). Several studiesdemonstrated the impact of climate change on landslide occurrence and investigated futurescenarios according to climate model projections (Stoffel et al., 2014, Gariano and Guzzetti, 2016).The type, extent, magnitude and direction of the changes in the stability conditions, and on thelocation, abundance, activity and frequency of landslides as a consequence of the projected climatechanges is under debate (Gariano and Guzzetti, 2016).In this research topic, Zumpano et al. present two case studies in low-density populated areas inthe southern Apennine (Italy) and Romania. In these areas, the main productive activities are basedon agricultural and pastoral resources, evaluating the potential economic loss trends in rural areas,according to future scenarios by 2050. Esposito et al. show an interesting analysis of increasingflash flood frequency linked to climate changes in urbanized coastline in southern Italy, during1970–2014.Developing landslide hazard/risk modeling applications is a complex task that involvesgeomorphology, hydrology, geoengineering and statistics (Hungr et al., 1984; Glade, 2005; Fuchset al., 2008; Bhatt et al., 2013). To properly define hazard/risk scenarios, it is mandatory tocharacterize and to model the triggering causes and the propagational and deposition patternof mobilized material. In this research topic, Gregoretti et al. describe the back analysis of theTiranti and Cremonini Editorial: Landslide Hazard in a Changing Environmentdebris flow that occurred in 2015 at Rio Secco Creek (north-eastern Italy), demonstrating that the proposed rainfall-runoffmodel can reconstruct the triggering factors and the processevolution (propagation and deposition). Boreggio et al. showthat the most relevant input in simulations of debris flowrouting is the Digital Terrain Model (DEM) with appropriateresolution: several interpolation methods to derive DEM incomplex orography are investigated by a GIS framework. Effectsof different gridding techniques are also evaluated on modelingof debris flow routing.Landslide hazard assessment is a relevant step towardlandslide hazard and risk management. Pardeshi et al. (2013)provide a comprehensive overview of current techniques inthis field of research. In this research topic, Tiranti et al.propose an integrated approach in an Alpine environment(north-western Italy), demonstrating that the comprehensivehazard scenario is evaluated by incorporating the source areas’distribution and characteristics, the actual connection to mainchannel, estimated by the Connectivity Index, propagationand deposition modeling operated by a 3D Cellular Automataalgorithm. Frey et al. describe a study on Quillcay catchmentin the Cordillera Blanca, Perú, presenting a scenario-basedmulti-source glacial lake over burst flood. Beside technicalaspects, the study gives special attention to approval anddissemination of hazards information given the complexinstitutional context.In 2009, the United Nations Office for Disaster Risk Reduction(UNISDR, 2009) defined an early warning system (EWS) as“a set of capacities needed to generate and disseminate timelyand meaningful warning information to enable individual,communities and organizations threatened by a hazard to actappropriately and in sufficient time to reduce the possibilityof harm or loss”. There are many operational EWSs currentlyimplemented for various types of natural hazards, includinglandslides. Overview and classification of existing landslideEWSs are presented in Thiebes et al. (2012), Bazin (2012),Stähli et al. (2015), Devoli et al. (2018), and Segoni et al.(2018). In this research topic, a methodology to couple rainfallthresholds and susceptibility maps for hazard assessment at aregional scale is presented by Segoni et al.: this new approachhas been tested in northern Tuscany (central Italy) where anappropriate calibration and validation of the hazard matrixhas been implemented to meet stakeholder requirements. Theavailability of quantitative precipitation estimates (QPEs) basedon weather radars with high spatial and temporal resolutionprovides new chances for automatic EWSs: Cremonini andTiranti illustrate a successful application of an operational EWSin northern Italy. On November 2016, heavy rain hit Piemonte(north-western Italy), causing diffuse landslides and floods: theoperational landslide EWS successfully detected the conditionsfor rainfall-induced landslides.This Research Topic presents some original research paperson scientific studies representing an updated overview ofrecent achievements in slope processes research. The presentedresearches advance our understanding of landslide relatedhazards and the necessary mitigation actions. These papersalso address the possible impacts of climate change on thissignificant natural hazard.AUTHOR CONTRIBUTIONSDT and RC present a sintesys of the state of the art about landslidehazard in the world and introduce the contributions collected inthe Research Topic. Both authors listed have made substantial,direct and intellectual contribution to the work, and approved itfor publication.REFERENCESBaum, R. L., and Godt, J. W. (2010). Early warning of rainfall-inducedshallow landslides and debris flows in the USA. Landslides 7, 259–272.doi: 10.1007/s10346-009-0177-0Bazin, S. (2012). Guidelines for landslide monitoring and early warning systemsin Europe – Design and required technology, Project SafeLand “Living WithLandslide Risk in Europe: Assessment, Effects of Global Change, and RiskManagement Strategies”. Deliverable 4.8, 153 pp. Available online at: https://www.ngi.no/eng/Projects/SafeLand (Accessed May 7, 2018).Bhatt, B. P., Awasthi, K. D., Heyojoo, B. P., Silwal, T., and Kafle, G. (2013).Using geographic information system and analytical hierarchy process inlandslide hazard zonation. Appl. Ecol. Environ. Sci. 1, 14–22. doi: 10.12691/aees-1-2-1Calvello, M. (2017). Early warning strategies to cope with landslide risk. RivistaItal. Geotec. 2, 63–91, doi: 10.19199/2017.2.0557-1405.063Cruden, D. M., and Varnes, D. J. (1996). Landslide types and processes. Landslides:Investigation and Mitigation. Special Report 247, Transportation ResearchBoard, Washington, 36–75.Devoli, G., Tiranti, D., Cremonini, R., Sund, M., and Bøje, S. (2018). Comparisonof landslide forecasting services in Piemonte (Italy) and in Norway, illustratedby events in late spring 2013. Nat. Hazards Earth Syst. Sci. 18, 1351–1372.doi: 10.5194/nhess-18-1351-2018Fell, R. (1994). Landslide risk assessment and acceptable risk. Can. Geotech. J. 31,261–272. doi: 10.1139/t94-031Fuchs, S., Kaitna, R., Scheidl, C., and Hübl, J. (2008). The Application of the RiskConcept to Debris Flow Hazards. Geomechanics and Tunnelling. Vol. 1; Berlin:Ernst & Sohn Verlag für Architektur und technische Wissenschaften GmbH &Co. KG, 120–129.Gariano, S. L., and Guzzetti, F. (2016). Landslides in a changing climate. Earth Sci.Rev. 162, 227–252. doi: 10.1016/j.earscirev.2016.08.011Glade, T. (2005). Linking debris-flow hazard assessment with geomorphology.Geomorphology 66, 189–213. doi: 10.1016/j.geomorph.2004.09.023Havenith, H. B., Torgoev, A., Braun, A., Schlögel, R., and Micu, M. (2016).A new classification of earthquake-induced landslide event sizes basedon seismotectonic, topographic, climatic and geologic factors. Geoenviron.Disasters 3, 1–24. doi: 10.1186/s40677-016-0041-1Hungr, O., Leroueil, S., and Picarelli, L. (2014). The Varnesclassification of landslide types, an update. Landslides 11, 167–194.doi: 10.1007/s10346-013-0436-yHungr, O., Morgan, G. C., and Kellerhals, R. (1984). Quantitative analysis of debristorrent hazard for design of remedial measures. Can. Geotech. J. 21, 663–677.doi: 10.1139/t84-073Katsura, S., Kosugi, K., Mizutani, T., Okunaka, S., and Mizuyama, T. (2008).Effects of bedrock groundwater on spatial and temporal variations in soilmantle groundwater in a steep granitic headwater catchment. Water Resour.Res. 44:W09430. doi: 10.1029/2007WR006610OFDA/CRED (2018). International Disaster Database. Brussels: UniversitéCatholique de Louvain. Available online at: www.emdat.be (Accessed August9, 2018).Frontiers in Earth Science | www.frontiersin.org 2 January 2019 | Volume 7 | Article 3Tiranti and Cremonini Editorial: Landslide Hazard in a Changing EnvironmentPardeshi, S. D., Autade, S. E., and Pardeshi, S. S. (2013). Landslidehazard assessment: recent trends and techniques. Springerplus 2:523.doi: 10.1186/2193-1801-2-523Rodríguez, C. E., Bommer, J. J., and Chandler, R. J. (1999). Earthquakeinduced landslides: 1980–1997. Soil Dyn. Earthq. Eng. 18, 325–346.doi: 10.1016/S0267-7261(99)00012-3Segoni, S., Piciullo, L., and Gariano, S. L. (2018). A review of the recent literatureon rainfall thresholds for landslide occurrence. Landslides 15, 1483–1501.doi: 10.1007/s10346-018-0966-4Seneviratne, S. I., Nicholls, N., Easterling, D., Goodess, C. M., Kanae, S., Kossin,J., et al. (2012). “Changes in climate extremes and their impacts on the naturalphysical environment,” in Managing the Risks of Extreme Events and Disastersto Advance Climate Change Adaptation. A Special Report of Working Groups Iand II of the Intergovernmental Panel on Climate Change (IPCC), eds C. B. Field,V. Barros, T. F. Stocker, D. Qin, D. J. Dokken, K. L. Ebi, M. D. Mastrandrea, K.J. Mach, G.-K. Plattner, S. K. Allen, M. Tignor, and P. M. Midgley (Cambridge;New York, NY: Cambridge University Press), 109–230.Stähli, M., Sättele, M., Huggel, C., McArdell, B. W., Lehmann, P., Van Herwijnen,A., et al. (2015). Monitoring and prediction in early warning systemsfor rapid mass movements. Nat. Hazards Earth Syst. Sci. 15, 905–917.doi: 10.5194/nhess-15-905-2015Stoffel, M., Tiranti, D., and Huggel, C. (2014). Climate change impactson mass movements – case studies from the European Alps.Sci. Total Environ. 493, 1255–1266. doi: 10.1016/j.scitotenv.2014.02.102Thiebes, B., Glade, T., and Bell, R. (2012). “Landslide analysis and integrativeearly warning-local and regional case studies,” in Proceeding 11th InternationalSymposium on Landslides (Banff, AB: CRC Press), 1915–1921.UNISDR (2009). UNISDR – ISDR: Terminology. Available online at: http://www.unisdr.org/eng/library/lib-terminology-enghome.htm (Accessed August8, 2018).Conflict of Interest Statement: The authors declare that the research wasconducted in the absence of any commercial or financial relationships that couldbe construed as a potential conflict of interest.Copyright © 2019 Tiranti and Cremonini. This is an open-access article distributedunder the terms of the Creative Commons Attribution License (CC BY). The use,distribution or reproduction in other forums is permitted, provided the originalauthor(s) and the copyright owner(s) are credited and that the original publicationin this journal is cited, in accordance with accepted academic practice. No use,distribution or reproduction is permitted which does not comply with these terms.Frontiers in Earth Science | www.frontiersin.org 3 January 2019 | Volume 7 | Article 3

Editorial: Landslide Hazard in a Changing Environment

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Editorial: Landslide Hazard in a Changing Environment

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