IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v11y2022i8p1125-d869076.html
   My bibliography  Save this article

The Role of Soil Type in Triggering Shallow Landslides in the Alps (Lombardy, Northern Italy)

Author

Listed:
  • Fabio Luino

    (Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Strada delle Cacce 73, 10135 Torino (TO), Italy)

  • Jerome De Graff

    (Department of Earth & Environmental Science, California State University, M/S ST24, Fresno, CA 93740, USA)

  • Marcella Biddoccu

    (Istituto di Scienze e Tecnologie per l’Energia e la Mobilità Sostenibili, Consiglio Nazionale delle Ricerche, Strada delle Cacce 73, 10135 Torino (TO), Italy)

  • Francesco Faccini

    (Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Strada delle Cacce 73, 10135 Torino (TO), Italy
    Dipartimento di Scienze della Terra, dell’Ambiente e della Vita, Università di Genova, Corso Europa 26, 16132 Genova (GE), Italy)

  • Michele Freppaz

    (Dipartimento di Scienze Agrarie, Forestali e Alimentari, Università di Torino, Largo Paolo Braccini 2, 10095 Grugliasco (TO), Italy)

  • Anna Roccati

    (Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Strada delle Cacce 73, 10135 Torino (TO), Italy)

  • Fabrizio Ungaro

    (Istituto per la BioEconomia, Consiglio Nazionale delle Ricerche, Via Madonna del Piano 10, 50018 Sesto Fiorentino (FI), Italy)

  • Michele D’Amico

    (Dipartimento di Scienze Agrarie e Ambientali—Produzione, Territorio, Agroenergia, Università degli Studi di Milano, Via Celoria 2, 20133 Milano (MI), Italy)

  • Laura Turconi

    (Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Strada delle Cacce 73, 10135 Torino (TO), Italy)

Abstract

Shallow landslides due to the soil saturation induced by intense rainfall events are very common in northern Italy, particularly in the Alps and Prealps. They are usually triggered during heavy rainstorms, causing severe damage to property, and sometimes causing casualties. A historical study and analysis of shallow landslides and mud-debris flows triggered by rainfall events in Lombardy was carried out for the period of 1911–2010, over an area of 14,019 km 2 . In this study, intensity–duration rainfall thresholds have been defined using the frequentist approach, considering some pedological characteristics available in regional soil-related databases, such as the soil region, the textural class, and the dominant soil typological units (STU). The soil-based empirical rainfall thresholds obtained considering the soil regions of the study area were significantly different, with a lower threshold for landslide occurrence in the soil region M1 (Alps), where soils developed over siliceous parent material, with respect to the whole study area and the soil region M2 (Prealps), where soils developed over calcareous bedrocks. Furthermore, by considering textural classes, the curves were differentiated, with coarse-textured soils found more likely to triggerlandslides than fine soils. Finally, considering both texture and main soil groups, given the same rainfall duration, the rainfall amount and intensity needed to initiate a landslide increased in the following order: “coarse-skeletal” Cambisols < Umbrisols < Podzols < “fine” Cambisols. The results of this study highlighted the relevant role of pedological conditioning factors in differentiating the activation of rainfall-induced shallow landslides in a definite region. The information on soils can be used to define more precise rainfall–pedological thresholds than empirical thresholds based solely on meteorological conditions, even when they are locally defined. This knowledge is crucial for forecasting and preventing geo-hydrological processes and in developing better warning strategies to mitigate risks and to reduce socio-economic damage.

Suggested Citation

  • Fabio Luino & Jerome De Graff & Marcella Biddoccu & Francesco Faccini & Michele Freppaz & Anna Roccati & Fabrizio Ungaro & Michele D’Amico & Laura Turconi, 2022. "The Role of Soil Type in Triggering Shallow Landslides in the Alps (Lombardy, Northern Italy)," Land, MDPI, vol. 11(8), pages 1-26, July.
  • Handle: RePEc:gam:jlands:v:11:y:2022:i:8:p:1125-:d:869076
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/11/8/1125/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/11/8/1125/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. K. S. Sajinkumar & S. Rinu & T. Oommen & C. L. Vishnu & K. R. Praveen & V. R. Rani & C. Muraleedharan, 2020. "Improved rainfall threshold for landslides in data sparse and diverse geomorphic milieu: a cluster analysis based approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(1), pages 639-657, August.
    2. Rajkumar Andrewwinner & Sembulichampalayam Sennimalai Chandrasekaran, 2021. "Investigation on the Failure Mechanism of Rainfall-Induced Long-Runout Landslide at Upputhode, Kerala State of India," Land, MDPI, vol. 10(11), pages 1-25, November.
    3. Shirin Moradi & Thomas Heinze & Jasmin Budler & Thanushika Gunatilake & Andreas Kemna & Johan Alexander Huisman, 2021. "Combining Site Characterization, Monitoring and Hydromechanical Modeling for Assessing Slope Stability," Land, MDPI, vol. 10(4), pages 1-23, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Somnath Bera & Vaibhav Kumar Upadhyay & Balamurugan Guru & Thomas Oommen, 2021. "Landslide inventory and susceptibility models considering the landslide typology using deep learning: Himalayas, India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(1), pages 1257-1289, August.
    2. Philipp Marr & Yenny Alejandra Jiménez Donato & Edoardo Carraro & Robert Kanta & Thomas Glade, 2023. "The Role of Historical Data to Investigate Slow-Moving Landslides by Long-Term Monitoring Systems in Lower Austria," Land, MDPI, vol. 12(3), pages 1-22, March.
    3. Adrián G. Bruzón & Patricia Arrogante-Funes & Fátima Arrogante-Funes & Fidel Martín-González & Carlos J. Novillo & Rubén R. Fernández & René Vázquez-Jiménez & Antonio Alarcón-Paredes & Gustavo A. Alon, 2021. "Landslide Susceptibility Assessment Using an AutoML Framework," IJERPH, MDPI, vol. 18(20), pages 1-20, October.
    4. Enrico Miccadei & Cristiano Carabella & Giorgio Paglia, 2022. "Landslide Hazard and Environment Risk Assessment," Land, MDPI, vol. 11(3), pages 1-5, March.
    5. Jasmin Grifka & Maximilian Weigand & Andreas Kemna & Thomas Heinze, 2022. "Impact of an Uncertain Structural Constraint on Electrical Resistivity Tomography for Water Content Estimation in Landslides," Land, MDPI, vol. 11(8), pages 1-13, July.
    6. Dhanya Madhu & G. K. Nithya & S. Sreekala & Maneesha Vinodini Ramesh, 2024. "Regional-scale landslide modeling using machine learning and GIS: a case study for Idukki district, Kerala, India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(11), pages 9935-9956, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:11:y:2022:i:8:p:1125-:d:869076. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.