IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v77y2015i1p1-15.html
   My bibliography  Save this article

Reconstruction of long-term earth-flow activity using a hydroclimatological model

Author

Listed:
  • Luigi Guerriero
  • Nazzareno Diodato
  • Francesco Fiorillo
  • Paola Revellino
  • Gerardo Grelle
  • Francesco Guadagno

Abstract

This study presents a new proxy for the reconstruction of the historical activity of large earth flows. A simple relationship between rainfall, temperature and groundwater levels was established using available monthly time series and subsequently utilized to develop the Landslide Hydrological Climatological (LHC) indicator to simulate the effects of hydroclimatic influence on slope stability for the Montaguto earth flow in Southern Italy. In order to identify phases of earth-flow activity, an empirical threshold was assigned. Our result indicates a different response of the earth flow to hydroclimatic stress with both ordinary and extraordinary reactivations over the historic period. Additional information suggests that earth-flow reactivations are clustered in the spring and an extraordinary earth-flow activity follows periods with a LHC below the average. A modeling result shows that the LHC is able to realistically reconstruct the long-term activity of a complex earth flow with only a few false-positives in a very long period of application. Thus, it can be considered as a tool for long-term earth-flow activity reconstruction and assessment. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Luigi Guerriero & Nazzareno Diodato & Francesco Fiorillo & Paola Revellino & Gerardo Grelle & Francesco Guadagno, 2015. "Reconstruction of long-term earth-flow activity using a hydroclimatological model," 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. 77(1), pages 1-15, May.
    • Handle: RePEc:spr:nathaz:v:77:y:2015:i:1:p:1-15
    DOI: 10.1007/s11069-014-1578-5
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11069-014-1578-5
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11069-014-1578-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nazzareno Diodato & Luigi Guerriero & Francesco Fiorillo & Libera Esposito & Paola Revellino & Gerardo Grelle & Francesco Guadagno, 2014. "Predicting Monthly Spring Discharges Using a Simple Statistical Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(4), pages 969-978, March.
    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. Kulwinder Parmar & Rashmi Bhardwaj, 2015. "River Water Prediction Modeling Using Neural Networks, Fuzzy and Wavelet Coupled Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(1), pages 17-33, January.
    2. Yaoze Liu & Sisi Li & Carlington W. Wallace & Indrajeet Chaubey & Dennis C. Flanagan & Lawrence O. Theller & Bernard A. Engel, 2017. "Comparison of Computer Models for Estimating Hydrology and Water Quality in an Agricultural Watershed," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(11), pages 3641-3665, 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:spr:nathaz:v:77:y:2015:i:1:p:1-15. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.