Evaluation of predicted patterns of erosional processes using GIS techniques can be problematic in areas where few field data are available. Yet it is in such areas where the ability to extrapolate using GIS could be most useful in practical applications. We compare patterns of low and high intensity erosion predicted by topographically driven, process-based models to geomorphological mapping in a mountainous 350 km 2 sub-catchment of the Iruya Basin in northern Argentina. Following Dietrich et al. (Channelization thresholds and land surface morphology. Geology 1992, 29, 675–679), areas most susceptible to different erosion processes were identified by plotting thresholds for soil saturation, erosion by overland flow and landsliding on a graph of drainage area versus slope. Within areas potentially subject to shallow landsliding, relative hazard was further stratified using a simple slope stability model. For areas dominated by overland flow, relative erosional intensity was modeled based on Hortonian overland flow. We compared model predictions to the distribution of areas identified from thematic mapping as subject to weak or strong erosion. Each of the process models predicted that large drainage areas and steep slopes produce energetic erosion associated with features that appear in classic geomorphological mapping. However, fine-scale differences in the patterns of predicted and mapped erosional intensity reflect fundamental differences between the generalized polygons generated by thematic mapping and pixel-by-pixel analysis generated by process models. Our analysis illustrates how DEM-driven process models and thematic mapping provide complementary tools for predicting landscape-scale patterns of erosional processes.
Journal of Hydrology – Elsevier
Published: Apr 2, 2001
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
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.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera