ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
Collection
Publisher
Years
  • 1
    Publication Date: 2012-04-15
    Description: ABSTRACT Rain splash erosion is an important soil transport mechanism on steep hillslopes. The rain splash process is highly stochastic; here we seek to constrain the probability distribution of splash transport distances on natural hillslopes as a function of hillslope gradient and total precipitation depth. Field experiments were conducted under natural precipitation events to observe splash travel on varying slope gradients. The downslope fraction of splash transport on 15°, 25° and 33° gradients were 85%, 96% and 96%, respectively. Maximum splash transport ( L max ) was related to the rain splash detachment of soil particles and slope gradient. An empirical relationship of L max to the precipitation depth and gradient was obtained; it is linearly proportional to hillslope gradient and logarithmically related to precipitation depth. Measured splash distances were calibrated to the fully two-dimensional (2D) model of splash transport of Furbish et al . ( Journal of Geophysical Research 112 : F01001, 2007) that is based on the assumption that radial splash distances are exponentially distributed; calibrated values of mean splash transport distances are an order of magnitude greater than those previously determined in a controlled laboratory setting. We also compared measured data with several one-dimensional (1D) probability distributions to asses if splash transport distances could be better explained by a heavy-tailed probability distribution rather than an exponential probability distribution. We find that for hillslopes of 15° and 25°, although a log-normal probability distribution best describes the data, we find its likelihood is nearly indistinguishable from an exponential distribution based on computing maximum likelihood estimators for all 1D distributions (exponential, log-normal and Weibull). At 33°, however, we find stronger evidence that measured travel distances are heavy-tailed. Copyright © 2011 John Wiley & Sons, Ltd.
    Print ISSN: 0197-9337
    Electronic ISSN: 1096-9837
    Topics: Geography , Geosciences
    Published by Wiley
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 2
    Publication Date: 2011-11-01
    Description: Rain splash erosion is an important soil transport mechanism on steep hillslopes. The rain splash process is highly stochastic; here we seek to constrain the probability distribution of splash transport distances on natural hillslopes as a function of hillslope gradient and total precipitation depth. Field experiments were conducted under natural precipitation events to observe splash travel on varying slope gradients. The downslope fraction of splash transport on 15°, 25° and 33° gradients were 85%, 96% and 96% respectively. Maximum splash transport ( L max ) was related to the rain splash detachment of soil particles and slope gradient. An empirical relationship of L max to the precipitation depth and gradient was obtained; it is linearly proportional to hillslope gradient and logarithmically related to precipitation depth. Measured splash distances were calibrated to the fully two dimensional model of splash transport of Furbish et al. (2007) that is based on the assumption that radial splash distances are exponentially distributed; calibrated values of mean splash transport distances are an order of magnitude greater than those previously determined in a controlled laboratory setting. We also compared measured data with several one dimensional probability distributions to asses if splash transport distances could be better explained by a heavy-tailed probability distribution rather than an exponential probability distribution. We find that for hillslopes of 15° and 25°, although a log-normal probability distribution best describes the data, we find its likelihood is nearly indistinguishable from an exponential distribution based on computing maximum likelihood estimators for all 1-D distributions (exponential, log-normal and Weibull). At 33°, however, we find stronger evidence that measured travel distances are heavy-tailed. Copyright © 2011 John Wiley & Sons, Ltd.
    Print ISSN: 0197-9337
    Electronic ISSN: 1096-9837
    Topics: Geography , Geosciences
    Published by Wiley
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...