This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
All documents in ORBi are protected by a user license.
[en] In Alpine regions changes in seasonal climatic parameters, such as temperature, rainfall, and snow amount have already been observed. Specifically, in the South Tyrol area, meteorological observations indicate that temperatures are increasing and the number of snow days has generally diminished over time with perennial snow line now observed at higher elevations. Changes in rainfall have also been observed with more events associated with higher temperatures in the summer season. Natural hazards - mainly debris and mud flows, landslides, avalanches, rock falls, and (flash) floods - that affect this area every year, damaging population and infrastructures, are either weather or cryosphere-related. While these events have been recorded sporadically since the beginning of the 20th century, a systematic approach of their inventory has been done by local authorities since the 1990s. So far, Earth observation data has not been exploited to complete or complement existing inventories nor have they been used to investigate the influence of climate perturbation on potentially dangerous natural phenomena. The research presented here thus has three objectives: (i) analyse long time series of climate data and hazard occurrence in South Tyrol to examine if these records exhibit a coherent response of hazards to changes in climate; (ii) measure the spatio-temporal evolution of climatic and natural hazard events recorded, and (iii) explore potential relations between meteorological conditions and the hazard occurrence. In this context, in-situ and satellite-based climate data are exploited to study natural hazard triggers while the potential of Earth observation data is evaluated as a complement to the existing historical records of natural hazards. Specifically, Copernicus Sentinel-1 images are used to detect the spatio-temporal distribution of slow earth surface deformations and the results used for checking the completeness of the actual slow-moving landslide inventories. Hazard-related changes in the South Tyrolian landscape have also been analysed in relation to particular meteorological events at a regional scale, assessing trends and anomalies. Results show that: (i) satellite data are very useful to complement the existing natural hazard inventories; (ii) in-situ and satellite-based climate records show similar patterns but differ due to regional versus local variability; (iii) even in a data-rich region such as the analysed area, the overall response of natural hazard occurrence, magnitude, and frequency to change in climate variables is difficult to decipher due to the presence of multiple triggers and locally driven ground responses. However, an increase in the average annual duration of rainfall events and debris flow occurrence can be observed.
Disciplines :
Earth sciences & physical geography
Author, co-author :
Schlögel, Romy
Kofler, Christian
Gariano, Stefano Luigi
Van Campenhout, Jean ; Université de Liège - ULiège > Département de géographie > Hydrographie et géomorphologie fluviatile
Plummer, Stephen
Language :
English
Title :
Changes in climate patterns and their association to natural hazard distribution in South Tyrol (Eastern Italian Alps)
Beniston, M. & Stoffel, M. Assessing the impacts of climatic change on mountain water resources. Science of The Total Environment 493, 1129–1137, 10.1016/j.scitotenv.2013.11.122 (2014).
Seneviratne, S. I. et al. Changes in Climate Extremes and their Impacts on the Natural Physical Environment, 109–230 (Cambridge University Press, 2012).
Strasser, U. & Kunstmann, H. Tackling complexity in modelling mountain hydrology: where do we stand, where do we go? Cold and Mountain Region Hydrological Systems Under Climate Change: Towards Improved Projections 360, 3–12 (2013).
Beniston, M., Stoffel, M. & Hill, M. Impacts of climatic change on water and natural hazards in the Alps: Can current water governance cope with future challenges? Examples from the European “ACQWA” project. Environmental Science and Policy 14, 734–743, 10.1016/j.envsci.2010.12.009 (2011).
Huggel, C., Clague, J. J. & Korup, O. Is climate change responsible for changing landslide activity in high mountains? Earth Surface Processes and Landforms 37, 77–91, 10.1002/esp.2223 (2012).
McGuire, B. & Maslin, M. Climate forcing of geological hazards (Wiley-Blackwell, Chichester, 2013).
Huggel, C., Salzmann, N. & Allen, S. High-Mountain Slope Failures and Recent and Future Warm Extreme Events, 10.1002/9781118482698.ch9 (2013).
Imaizumi, F., Sidle, R. C., Togari-Ohta, A. & Shimamura, M. Temporal and spatial variation of infilling processes in a landslide scar in a steep mountainous region, Japan. Earth Surface Processes and Landforms 40, 642–653, 10.1002/esp.3659 (2015).
Gariano, S. L. & Guzzetti, F. Landslides in a changing climate. Earth-Science Reviews 162, 227–252, 10.1016/j.earscirev.2016.08.011 (2016).
Allen, S. K., Cox, S. C. & Owens, I. F. Rock avalanches and other landslides in the central Southern Alps of New Zealand: a regional study considering possible climate change impacts. Landslides 8, 33–48, 10.1007/s10346-010-0222-z (2011).
Stoffel, M. & Huggel, C. Effects of climate change on mass movements in mountain environments. Progress in Physical Geography: Earth and Environment 36, 421–439, 10.1177/0309133312441010 (2012).
Stoffel, M., Tiranti, D. & Huggel, C., Climate Change. impacts on mass movements -Ť Case studies from the European Alps. Science of The Total Environment 493, 1255–1266, 10.1016/j.scitotenv.2014.02.102 (2014).
Gobiet, A. et al. 21st century Climate Change in the european alps-a review. Science of the Total Environment 493, 1138–1151, 10.1016/j.scitotenv.2013.07.050 (2014).
Stöffel, M., Mendlik, T., Schneuwly-Bollschweiler, M. & Gobiet, A. Possible impacts of climate change on debris-flow activity in the Swiss Alps. Climatic Change 122, 141–155, 10.1007/s10584-013-0993-z (2013).
Chiarle, M., Iannotti, S., Mortara, G. & Deline, P. Recent debris flow occurrences associated with glaciers in the Alps. Global and Planetary Change 56, 123–136, 10.1016/j.gloplacha.2006.07.003 (2007).
Paranunzio, R., Laio, F., Chiarle, M., Nigrelli, G. & Guzzetti, F. Climate anomalies associated with the occurrence of rockfalls at high-elevation in the Italian Alps. Natural Hazards and Earth System Sciences 16, 2085–2106, 10.5194/nhess-16-2085-2016 (2016).
Paranunzio, R. et al. New insights in the relation between climate and slope failures at high-elevation sites. Theoretical and Applied Climatology 10.1007/s00704-018-2673-4 (2018).
Joyce, K. E., Belliss, S. E., Samsonov, S. V., McNeill, S. J. & Glassey, P. J. A review of the status of satellite remote sensing and image processing techniques for mapping natural hazards and disasters. Progress in Physical Geography: Earth and Environment 33, 183–207, 10.1177/0309133309339563 (2009).
Klemeš, V. The modelling of mountain hydrology: the ultimate challenge Hydrology of Mountainous Areas 29–44, 10.1641/0006-3568(2001)051[0227:HIOEPA]2.0.CO;2 (1990).
Guzzetti, F. et al. Landslide inventory maps: new tools for an old problem. Earth-Science Reviews 112, 42–66, 10.1016/j.earscirev.2012.02.001 (2012).
Schlögel, R., Doubre, C., Malet, J.-P. & Masson, F. Landslide deformation monitoring with ALOS/PALSAR imagery: a D-InSAR geomorphological interpretation method. Geomorphology 231, 314–330, https://doi.org/10.1016/j.geomorph.2014.11.031 (2015).
Aschbacher, J. & Milagro-Pérez, M. P. The European Earth monitoring (GMES) programme: Status and perspectives. Remote Sensing of Environment 120, 3–8, 10.1016/j.rse.2011.08.028 (2012).
Plank, S., Twele, A. & Martinis, S. Landslide mapping in vegetated areas using change detection based on optical and polarimetric sar data. Remote Sensing 8, https://doi.org/10.3390/rs8040307 (2016).
Galve, J. P. et al. Evaluation of the SBAS InSAR service of the European space Agency’s Geohazard Exploitation Platform (GEP) Remote Sensing 9, 10.3390/rs9121291 (2017).
Hollmann, R. et al. The ESA Climate Change Initiative: satellite data records for essential climate variables. Bulletin of the American Meteorological Society 94, 1541–1552, 10.1175/BAMS-D-11-00254.1 (2013).
Plummer, S., Lecomte, P. & Doherty, M. The ESA Climate Change Initiative (CCI): A European contribution to the generation of the Global Climate Observing System. Remote Sensing of Environment 203, 2–8, 10.1016/j.rse.2017.07.014 (2017).
Nagler, T., Rott, H., Ripper, E., Bippus, G. & Hetzenecker, M. Advancements for Snowmelt Monitoring by Means of Sentinel-1 SAR Remote Sensing 8, https://doi.org/10.3390/rs8040348 (2016).
Paul, F. et al. The Glaciers Climate Change Initiative: Algorithms for creating glacier area, elevation change and velocity products. Remote Sensing of Environment 162, 408–426, 10.1016/j.rse.2013.07.043 (2013).
Zemp, M. et al. Global glacier mass changes and their contributions to sea-level rise from 1961 to 2016. Nature 568, 382–386, 10.1038/s41586-019-1071-0 (2019).
Piacentini, D. et al. Statistical analysis for assessing shallow-landslide susceptibility in South Tyrol (south-eastern Alps, Italy). Geomorphology 151-152, 196–206, 10.1016/j.geomorph.2012.02.003 (2012).
Papathoma-Köhle, M. et al. Vulnerability to Heat Waves, Floods, and Landslides in Mountainous Terrain: Test Cases in South Tyrol. In Birkmann, J., Kienberger, S. & Alexander, D. E. (eds.) Assessment of Vulnerability to Natural Hazards, 179-201, https://doi.org/10.1016/B978-0-12-410528-7.00008-4 (Elsevier, 2014).
Destro, E. et al. Spatial estimation of debris flows-triggering rainfall and its dependence on rainfall return period. Geomorphology 278, 269–279, 10.1016/j.geomorph.2016.11.019 (2017).
Renner, K. et al. Spatio-temporal population modelling as improved exposure information for risk assessments tested in the autonomous province of bolzano. International Journal of Disaster Risk Reduction 27, 470–479, 10.1016/j.ijdrr.2017.11.011 (2018).
Mann, H. B. Nonparametric tests against trend. Econometrica 13, 245–259 (1945).
Kendall, M. G. Rank correlation methods. Econometrica 25, 181–183 (1957).
Bollmann, E. et al.Blockgletscherkataster in Südtirol - Erstellung und Analyse, 147–171 (University of Innsbruck, 2012).
Kummert, M. & Delaloye, R. Regional-scale inventory of periglacial moving landforms connected to the torrential network system. Geographica Helvetica 357–371, https://doi.org/10.5194/gh-73-357-2018 (2018).
Haeberli, W., Wegmann, M. & Mühll, D. V. Slope stability problems related to glacier shrinkage and permafrost degradation in the Alps. Eclogae Geologicae Helvetiae 90, 407–414 (1997).
World Meteorological Organization. Guide to Hydrological Practices, Volume I. Hydrology - From Measurement to. Hydrological Information. -No. 168, sixth edition. Tech. Rep., WMO (2008).
LeMoine, N., Hendrickx, F. & Gailhard, J. Rainfall-runoff modelling as a tool for constraining the re-analysis of daily precipitation and temperature fields in mountainous regions. IAHS-AISH Proceedings and Reports 360, 13–18 (2013).
van den Eeckhaut, M. et al. Statistical modelling of Europe-wide landslide susceptibility using limited landslide inventory data. Landslides 9, 357–369, 10.1007/s10346-011-0299-z (2012).
Steger, S., Brenning, A., Bell, R. & Glade, T. The propagation of inventory-based positional errors into statistical landslide susceptibility models. Natural Hazards and Earth System Sciences 16, 2729–2745, 10.5194/nhess-16-2729-2016 (2016).
Pedoth, L. et al. The Role of Risk Perception and Community Networks in Preparing for and Responding to Landslides: A Dolomite Case Study, 197–219 (John Wiley & Sons, Ltd, 2018).
Fisher, R. A. & Tippett, L. H. C. Limiting forms of the frequency distribution of the largest or smallest member of a sample. Proc. Cambridge Philos. Soc 24, 180–190 (1928).
Gumbel, E. J. Floods estimated by probability method Eng. News-Rec 134, 833–837 (1945).
Gumbel, E. J. Statistics of Extremes, 2nd Edition (Columbia University Press, New York, USA, 1960).
Bingham, N. H., Goldie, C. M. & Teugels, J. L. Regular variation (Cambridge University Press, 1987), encyclopedia of mathematics and its applications edn.
Vivekanandan, N. Assessment of extreme rainfall using Gumbel distribution for estimation of peak flood discharge for ungauged catchments. International Journal of Research and Innovation in Social Science (IJRISS) 1, 1–5 (2017).
Melillo, M. et al. A tool for the automatic calculation of rainfall thresholds for landslide occurrence. Environmental Modelling & Software 105, 230–243, 10.1016/j.envsoft.2018.03.024 (2018).
Peruccacci, S. et al. Rainfall thresholds for possible landslide occurrence in Italy. Geomorphology 290, 39–57, 10.1016/j.geomorph.2017.03.031 (2017).
McKee, T. B., Doesken, N. J. & Kleist, J. The relationship of drought frequency and duration to time scales. In Eighth Conference on Applied Climatology, 17-22 January 1993, Anaheim, California, 6 (1993).
Sigdel, M. & Ikeda, M. Spatial and Temporal Analysis of Drought in Nepal using Standardized Precipitation Index and its Relationship with Climate Indices. Journal of Hydrology and Meteorology 7, 59–74, 10.3126/jhm.v7i1.5617 (2010).
Huang, X. et al. Spatiotemporal dynamics of snow cover based on multi-source remote sensing data in china. The Cryosphere 2453-2463, 10.5194/tc-10-2453-2016 (2016).
Schlögel, R., Malet, J.-P., Reichenbach, P., Remaître, A. & Doubre, C. Analysis of a landslide multi-date inventory in a complex mountain landscape: The Ubaye valley case study Natural Hazards and Earth System Sciences 15, https://doi.org/10.5194/nhess-15-2369-2015 (2015).
De Luca, C. et al. Automatic and Systematic Sentinel-1 SBAS-DInSAR Processing Chain for Deformation Time-series Generation. Procedia Computer Science 100, 1176–1180, 10.1016/j.procs.2016.09.275 (2016).
Funk, C. C. et al. A quasi-global precipitation time series for drought monitoring: U.S. Geological Survey Data Series 832 Usgs 4, 10.3133/ds832 (2014).
