A probabilistic approach to post-wildfire debris-flow volume modeling

A probabilistic approach to post-wildfire debris-flow volume modeling As populations continue to move into more mountainous terrain, a greater understanding of the processes controlling debris flows has become important for the protection of human life and property. The potential volume of an expected debris flow must be known to effectively mitigate any hazard it may pose, yet an accurate estimate of this parameter has to this point been difficult to model. To this end, a probabilistic method for the prediction of debris flow volumes using a database of 1351 yield rate measurements from 33 post-wildfire, runoff-generated debris flows in the Western USA is presented herein. A number of geomorphological, climatic, and geotechnical basin characteristics were considered for inclusion in the model, and correlation analysis was conducted to identify those with the greatest influence on debris flow yield rates. Groupings within the database were then clustered based on their similarity levels; a total of six clusters were identified with similar slope angle and burn intensity characteristics. For each of these six clusters, a probability density function detailing the distribution of yield rates within the cluster was developed. The model uses a Monte Carlo simulation to combine each of these distributions into a single probabilistic model for any basin in which a debris flow is expected to occur. This approach was validated by applying the model to ten basins that experienced debris flows of known volumes throughout the Western USA. The model predicted nine of the ten debris flow volumes to within the 95% confidence interval of the final distribution; a regression analysis for the ten volumes resulted in an R 2 of 0.816. These results compared favorably with those generated by an existing volume model. This approach provides accurate results based on easily obtainable data, encouraging widespread use in land planning and development. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Landslides Springer Journals

A probabilistic approach to post-wildfire debris-flow volume modeling

Loading next page...
Springer Berlin Heidelberg
Copyright © 2017 by Springer-Verlag Berlin Heidelberg
Earth Sciences; Natural Hazards; Geography, general; Agriculture; Civil Engineering
Publisher site
See Article on Publisher Site


You’re reading a free preview. Subscribe to read the entire article.

DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

Monthly Plan

  • Read unlimited articles
  • Personalized recommendations
  • No expiration
  • Print 20 pages per month
  • 20% off on PDF purchases
  • Organize your research
  • Get updates on your journals and topic searches


Start Free Trial

14-day Free Trial

Best Deal — 39% off

Annual Plan

  • All the features of the Professional Plan, but for 39% off!
  • Billed annually
  • No expiration
  • For the normal price of 10 articles elsewhere, you get one full year of unlimited access to articles.



billed annually
Start Free Trial

14-day Free Trial