On the prediction of channel heads in a complex alpine terrain using gridded elevation data
Abstract
Threshold conditions for channel initiation are evaluated by using gridded elevation
data derived from a lidar survey, a reliable algorithm for the determination of surface
flow paths, and field observations of channel heads for a study area located in the
eastern Italian Alps. These threshold conditions are determined by considering the
channel heads observed across a portion of the study area and computing the related
values of (1) drainage area A, (2) area-slope function AS2, with S being the local
slope, and (3) Strahler order ω* of surface flow paths extracted from gridded elevation
data. Attention is focused on the dependence of the obtained threshold values on the
size of grid cells involved and on the ability of the identified threshold conditions
to provide reliable predictions of channel heads across the entire study area. The
results indicate that the threshold values of A, AS2, and ω* are all significantly
dependent on grid cell size, and the uncertainty in the determination of threshold
values of ω* is significantly smaller than that affecting the determination of threshold
values of A and AS2. The comparison between predicted and observed channel heads indicates
that the considered methods display variable reliability and sensitivity over different
drainage basins and grid cell sizes, with a general tendency to predict more channel
heads than can be observed in the field. Acceptable predictions are normally obtained
where channel heads are formed essentially by surface runoff. More comprehensive methods
seem, however, to be needed to predict channel heads affected by groundwater seeping
upward. Copyright 2011 by the American Geophysical Union.
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https://hdl.handle.net/10161/11628Published Version (Please cite this version)
10.1029/2010WR009648Publication Info
Orlandini, S; Tarolli, P; Moretti, G; & Dalla Fontana, G (2011). On the prediction of channel heads in a complex alpine terrain using gridded elevation
data. Water Resources Research, 47(2). 10.1029/2010WR009648. Retrieved from https://hdl.handle.net/10161/11628.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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STEFANO ORLANDINI
Adjunct Associate Professor in the Department of Civil and Environmental Engineering

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