IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v88y2017i3d10.1007_s11069-017-2921-4.html
   My bibliography  Save this article

Modeling debris flow initiation and run-out in recently burned areas using data-driven methods

Author

Listed:
  • Raquel Melo

    (Universidade de Lisboa)

  • José Luís Zêzere

    (Universidade de Lisboa)

Abstract

In the framework of the landslide susceptibility assessment, the maps produced should include not only the landslide initiation areas, but also those areas potentially affected by the traveling mobilized material. To achieve this purpose, the susceptibility analysis must be separated in two distinct components: (1) The first one, which is also the most discussed in the literature, deals with the susceptibility to failure, and (2) the second component refers to the run-out modeling using the initiation areas as an input. Therefore, in this research we present a debris flow susceptibility assessment in a recently burned area in a mountain zone in central Portugal. The modeling of debris flow initiation areas is performed using two statistical methods: a bivariate (information value) and a multivariate (logistic regression). The independent validation of the results generated areas under the receiver operating characteristic curves between 0.91 and 0.98. The slope angle, plan curvature, soil thickness and lithology proved to be the most relevant predisposing factors for the debris flow initiation in recently burned areas. The run-out is simulated by applying two different methods: the empirical model Flow Path Assessment of Gravitational Hazards at a Regional Scale (Flow-R) and the hydrological algorithm D-infinity downslope influence (DI). The run-out modeling of the 36 initiation areas included in the debris flow inventory delivered a true positive rate of 83.5% for Flow-R and 80.5% for DI, reflecting a good performance of both models. Finally, the susceptibility map for the entire basin including both the initiation and the run-out areas in a scenario of a recent wildfire was produced by combining the four models mentioned above.

Suggested Citation

  • Raquel Melo & José Luís Zêzere, 2017. "Modeling debris flow initiation and run-out in recently burned areas using data-driven methods," 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. 88(3), pages 1373-1407, September.
  • Handle: RePEc:spr:nathaz:v:88:y:2017:i:3:d:10.1007_s11069-017-2921-4
    DOI: 10.1007/s11069-017-2921-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-017-2921-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11069-017-2921-4?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. Dieter Rickenmann, 1999. "Empirical Relationships for Debris Flows," 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. 19(1), pages 47-77, January.
    2. Susan Cannon & Eric Boldt & Jayme Laber & Jason Kean & Dennis Staley, 2011. "Rainfall intensity–duration thresholds for postfire debris-flow emergency-response planning," 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. 59(1), pages 209-236, October.
    3. Dieu Bui & Owe Lofman & Inge Revhaug & Oystein Dick, 2011. "Landslide susceptibility analysis in the Hoa Binh province of Vietnam using statistical index and logistic regression," 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. 59(3), pages 1413-1444, December.
    4. Th. Asch & C. Tang & D. Alkema & J. Zhu & W. Zhou, 2014. "An integrated model to assess critical rainfall thresholds for run-out distances of debris flows," 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. 70(1), pages 299-311, January.
    5. Samuele Segoni & Guglielmo Rossi & Filippo Catani, 2012. "Improving basin scale shallow landslide modelling using reliable soil thickness maps," 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. 61(1), pages 85-101, March.
    6. Jordi Corominas & Ramon Copons & Joan Vilaplana & Joan Altimir & Jordi Amigó, 2003. "Integrated Landslide Susceptibility Analysis and Hazard Assessment in the Principality of Andorra," 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. 30(3), pages 421-435, November.
    7. A. Clerici & S. Perego & C. Tellini & P. Vescovi, 2010. "Landslide failure and runout susceptibility in the upper T. Ceno valley (Northern Apennines, Italy)," 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. 52(1), pages 1-29, January.
    8. Chang-Jo Chung & Andrea Fabbri, 2003. "Validation of Spatial Prediction Models for Landslide Hazard Mapping," 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. 30(3), pages 451-472, November.
    9. M. Parise & S. Cannon, 2012. "Wildfire impacts on the processes that generate debris flows in burned watersheds," 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. 61(1), pages 217-227, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    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. Netra Bhandary & Ranjan Dahal & Manita Timilsina & Ryuichi Yatabe, 2013. "Rainfall event-based landslide susceptibility zonation mapping," 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. 69(1), pages 365-388, October.
    2. Massimo Conforti & Gaetano Robustelli & Francesco Muto & Salvatore Critelli, 2012. "Application and validation of bivariate GIS-based landslide susceptibility assessment for the Vitravo river catchment (Calabria, south Italy)," 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. 61(1), pages 127-141, March.
    3. Halil Akinci & Mustafa Zeybek, 2021. "Comparing classical statistic and machine learning models in landslide susceptibility mapping in Ardanuc (Artvin), Turkey," 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(2), pages 1515-1543, September.
    4. L. Lombardo & M. Cama & C. Conoscenti & M. Märker & E. Rotigliano, 2015. "Binary logistic regression versus stochastic gradient boosted decision trees in assessing landslide susceptibility for multiple-occurring landslide events: application to the 2009 storm event in Messi," 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. 79(3), pages 1621-1648, December.
    5. A. Clerici & S. Perego & C. Tellini & P. Vescovi, 2010. "Landslide failure and runout susceptibility in the upper T. Ceno valley (Northern Apennines, Italy)," 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. 52(1), pages 1-29, January.
    6. Khabat Khosravi & Ebrahim Nohani & Edris Maroufinia & Hamid Reza Pourghasemi, 2016. "A GIS-based flood susceptibility assessment and its mapping in Iran: a comparison between frequency ratio and weights-of-evidence bivariate statistical models with multi-criteria decision-making techn," 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. 83(2), pages 947-987, September.
    7. G. Chevalier & V. Medina & M. Hürlimann & A. Bateman, 2013. "Debris-flow susceptibility analysis using fluvio-morphological parameters and data mining: application to the Central-Eastern Pyrenees," 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. 67(2), pages 213-238, June.
    8. Martin Mergili & Wolfgang Fellin & Stella Moreiras & Johann Stötter, 2012. "Simulation of debris flows in the Central Andes based on Open Source GIS: possibilities, limitations, and parameter sensitivity," 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. 61(3), pages 1051-1081, April.
    9. Ruoshen Lin & Gang Mei & Ziyang Liu & Ning Xi & Xiaona Zhang, 2021. "Susceptibility Analysis of Glacier Debris Flow by Investigating the Changes in Glaciers Based on Remote Sensing: A Case Study," Sustainability, MDPI, vol. 13(13), pages 1-23, June.
    10. Quang-Khanh Nguyen & Dieu Tien Bui & Nhat-Duc Hoang & Phan Trong Trinh & Viet-Ha Nguyen & Isık Yilmaz, 2017. "A Novel Hybrid Approach Based on Instance Based Learning Classifier and Rotation Forest Ensemble for Spatial Prediction of Rainfall-Induced Shallow Landslides using GIS," Sustainability, MDPI, vol. 9(5), pages 1-24, May.
    11. Yumin Tan & Dong Guo & Bo Xu, 2015. "A geospatial information quantity model for regional landslide risk assessment," 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. 79(2), pages 1385-1398, November.
    12. Luca Maria Falconi & Lorenzo Moretti & Claudio Puglisi & Gaia Righini, 2023. "Debris and mud flows runout assessment: a comparison among empirical geometric equations in the Giampilieri and Briga basins (east Sicily, Italy) affected by the event of October 1, 2009," 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. 117(3), pages 2347-2373, July.
    13. Taskin Kavzoglu & Emrehan Kutlug Sahin & Ismail Colkesen, 2015. "An assessment of multivariate and bivariate approaches in landslide susceptibility mapping: a case study of Duzkoy district," 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. 76(1), pages 471-496, March.
    14. Alexander N. Gorr & Luke A. McGuire & Rebecca Beers & Olivia J. Hoch, 2023. "Triggering conditions, runout, and downstream impacts of debris flows following the 2021 Flag Fire, Arizona, USA," 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. 117(3), pages 2473-2504, July.
    15. Francesca Vergari, 2015. "Assessing soil erosion hazard in a key badland area of Central Italy," 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. 79(1), pages 71-95, November.
    16. Chun-Kuo Yeh & Shyue-Cherng Liaw, 2016. "Trajectories, drivers, and probabilities of land cover change in a disturbed forested watershed in eastern Taiwan," 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. 82(2), pages 1099-1122, June.
    17. D. Costanzo & C. Cappadonia & C. Conoscenti & E. Rotigliano, 2012. "Exporting a Google Earth ™ aided earth-flow susceptibility model: a test in central Sicily," 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. 61(1), pages 103-114, March.
    18. E. Rotigliano & C. Cappadonia & C. Conoscenti & D. Costanzo & V. Agnesi, 2012. "Slope units-based flow susceptibility model: using validation tests to select controlling factors," 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. 61(1), pages 143-153, March.
    19. Kourosh Shirani & Mehrdad Pasandi & Alireza Arabameri, 2018. "Landslide susceptibility assessment by Dempster–Shafer and Index of Entropy models, Sarkhoun basin, Southwestern Iran," 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. 93(3), pages 1379-1418, September.
    20. Nisar Ali Shah & Muhammad Shafique & Muhammad Ishfaq & Kamil Faisal & Mark Van der Meijde, 2023. "Integrated Approach for Landslide Risk Assessment Using Geoinformation Tools and Field Data in Hindukush Mountain Ranges, Northern Pakistan," Sustainability, MDPI, vol. 15(4), pages 1-21, February.

    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:88:y:2017:i:3:d:10.1007_s11069-017-2921-4. 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.