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Adding Gaussian noise to inaccurate digital elevation models improves spatial fidelity of derived drainage networks
Author(s) -
Gatziolis Demetrios,
Fried Jeremy S.
Publication year - 2004
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2002wr001735
Subject(s) - digital elevation model , ephemeral key , elevation (ballistics) , terrain , drainage , global positioning system , computer science , hydrology (agriculture) , noise (video) , fidelity , geology , remote sensing , cartography , artificial intelligence , algorithm , geography , geotechnical engineering , mathematics , telecommunications , ecology , geometry , biology , image (mathematics)
An economical approach to improving predictions of hydrological models produced highly accurate representations of ephemeral and perennial stream networks. Traditional drainage network extraction from digital elevation models (DEMs) often yields inaccurate and inconsistent results because of elevation errors. Topographic wetness index maps calculated from alternative terrain representations, produced by adding random errors to a DEM of a subwatershed with low relief, were combined to delineate a stream network that matches one produced by more time‐intensive (and costly) differential Global Positioning System (GPS) field methods, particularly with respect to the ephemeral component of the drainage network.