Effects of digital elevation model resolution on derived stream network positions

Effects of digital elevation model resolution on derived stream network positions This study examines the effect of digital elevation model (DEM) resolution on the positional accuracy of derived hydrologic networks and quantitatively confirms that DEM resolution should be greater than the average hillslope length when used for hydrologic modeling. Seven hundred kilometers of mapped stream networks are compared to stream networks derived from 17 DEMs with resolutions ranging from 30 m to 3 km. Comparison between predicted and mapped streams reveals that accuracy of predicted stream locations decays quickly beyond a DEM resolution of 180 m. A new application of 's (1995) DEM resolution suitability test based on average slope and vertical resolution indicates an average hillslope length of between 150 and 180 m. 's (1991) method of determining average hillslope length based on slope and accumulation areas reconfirms the length to be 150 m and verifies the link between network accuracy and hillslope scale. Two algorithms are used to derive stream networks: the D∞ algorithm (, 1997), which allows for flow dispersion, and the D8 algorithm (, 1984), which does not. A comparison between the D8 and D∞ algorithms shows that modeling flow dispersion is not necessary in steep terrain, as both algorithms performed equally well. However, the D∞ algorithm is found to be less susceptible to modeling erroneous hillside flow convergence, making it preferable to the D8 algorithm when used by 's (1991) method of determining the average hillslope lengths. Finally, field observation indicates that predicted first‐ and second‐order streams tend to exist when predicted; however, mapped streams have a higher positional accuracy. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Water Resources Research Wiley

Effects of digital elevation model resolution on derived stream network positions

Water Resources Research, Volume 38 (4) – Apr 1, 2002

Loading next page...
 
/lp/wiley/effects-of-digital-elevation-model-resolution-on-derived-stream-pfVnypPyV4
Publisher
Wiley
Copyright
Copyright © 2002 by the American Geophysical Union.
ISSN
0043-1397
eISSN
1944-7973
D.O.I.
10.1029/2000WR000150
Publisher site
See Article on Publisher Site

Abstract

This study examines the effect of digital elevation model (DEM) resolution on the positional accuracy of derived hydrologic networks and quantitatively confirms that DEM resolution should be greater than the average hillslope length when used for hydrologic modeling. Seven hundred kilometers of mapped stream networks are compared to stream networks derived from 17 DEMs with resolutions ranging from 30 m to 3 km. Comparison between predicted and mapped streams reveals that accuracy of predicted stream locations decays quickly beyond a DEM resolution of 180 m. A new application of 's (1995) DEM resolution suitability test based on average slope and vertical resolution indicates an average hillslope length of between 150 and 180 m. 's (1991) method of determining average hillslope length based on slope and accumulation areas reconfirms the length to be 150 m and verifies the link between network accuracy and hillslope scale. Two algorithms are used to derive stream networks: the D∞ algorithm (, 1997), which allows for flow dispersion, and the D8 algorithm (, 1984), which does not. A comparison between the D8 and D∞ algorithms shows that modeling flow dispersion is not necessary in steep terrain, as both algorithms performed equally well. However, the D∞ algorithm is found to be less susceptible to modeling erroneous hillside flow convergence, making it preferable to the D8 algorithm when used by 's (1991) method of determining the average hillslope lengths. Finally, field observation indicates that predicted first‐ and second‐order streams tend to exist when predicted; however, mapped streams have a higher positional accuracy.

Journal

Water Resources ResearchWiley

Published: Apr 1, 2002

References

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 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

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

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create folders to
organize your research

Export folders, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off