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https://doi.org/10.5194/egusph...
Article . 2025 . Peer-reviewed
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How does future seasonal variability in rainfall affect landslide-prone areas?

Authors: Mateja Jemec Auflič; Nejc Bezak; Ela Šegina; Peter Frantar; Stefano Luigi Gariano; Anže Medved; Tina Peternel;

How does future seasonal variability in rainfall affect landslide-prone areas?

Abstract

During the next few decades, changes in rainfall frequency and magnitude are expected to have major impacts on landscape evolution, social, and economic aspects of human society.We focus on seasonal rainfall variations by the end of the 21st century to define affected landslide-prone areas, future landslide alerts and the impact of shllow and deep-seated landslides on landscape development in the juncture of the Alpine, Pannonian, and Mediterranean region. For this work, we selected the six regional climate models (RCMs) from the EURO-CORDEX project, with the global climate simulations from CMIP5 (Coupled Model Intercomparison Project phase) driven by the six global circulation models (GCMs).  Of the two available spatial resolutions, i.e., 0.11° (12.5 km) and 0.44° (50 km), we considered the 0.11° spatial resolution with a regular 12.5 km grid with spacing between computational points. Six models were selected from 14 combinations of GCMs and RCMs that differ as much as possible from each other while reflecting as closely as possible the measured values of past climate variables. For this study, we considered climate scenarios variable: the daily rainfall datasets of two Representative Concentration Pathways (RCP), namely RCP4.5 (mid-way) and RCP8.5 (worst-case) for the time window from 1981 to 2100. Daily rainfall data were downscaled from 12.5 km resolution to 1 km. The downscaling of the data was performed daily for all six RCMs. To analyse future climate impact on landslides, the calculated models were divided into three 30-year projection periods: 1st period (near-term) between 2011-2040, 2nd period (mid-century) between 2041-2070, 3rd period (end of the century) between 2071-2100. To show the characteristics of seasonal variations, shorter periods within a year were considered, namely four meteorological seasons: winter (December, January, February), spring (March, April, May), summer (June, July, August), and autumn (September, October, November). Future projections represent a 30-year maximum rainfall from the 30-year baseline period in the past (1981-2010).The observed changes in the occurrence of shallow landslides are significant, especially in the winter months, where we can expect more landslide-prone areas compared to the baseline period. Shallow landslides will have a greater impact on the landscape in spring and summer than deep-seated landslides, especially in vineyards.FundingThis work was supported by the by the Slovenian Research and Innovation Agency (the research project J1-3024). Additional financial support was provided by the project “Development of research infrastructure for the international competitiveness of the Slovenian RRI space – RI-SI-EPOS” (co-financed by the Republic of Slovenia, Ministry of Education, Science and Sport and the European Union from the European Regional Development Fund).ReferenceJemec Auflič, M., Bezak, N., Šegina, E. et al. Climate change increases the number of landslides at the juncture of the Alpine, Pannonian and Mediterranean regions. Sci Rep 13, 23085 (2023). https://doi.org/10.1038/s41598-023-50314-x

Country
Italy
Keywords

landslides, climate change

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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