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Title: COMPARISON OF GRID-BASED ALGORITHMS FOR COMPUTING UPSLOPE CONTRIBUTING AREA

Author
item Erskine, Robert - Rob
item Green, Timothy
item RAMIREZ, JORGE - COLORADO STATE UNIVERSITY
item MACDONALD, LEE - COLORADO STATE UNIVERSITY

Submitted to: Water Resources Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/19/2006
Publication Date: 9/28/2006
Citation: Erskine, R.H., Green, T.R., Ramirez, J.A., Macdonald, L.H. Comparison of grid-based algorithms for computing upslope contributing area. Water Resources Research. Vol. 42, W09416, doi:10.1029/2005WR004648, 2006.

Interpretive Summary: Five algorithms (D8, '8, MFD, DEMON, and D') for computing contributing area, A, were compared on two agricultural fields (63 and 109 ha) in northeastern Colorado. Global positioning system (GPS) data (0.02 m accuracy) were used to generate grid digital elevation models (DEMs) at 5, 10, and 30-m cell sizes. Quantitative relative differences between single- and multiple-direction algorithms increased with decreasing grid cell size. Relative differences were greatest in divergent upslope areas, and differences decreased where the terrain became more convergent. Thus, flow divergence is a critical component for spatial estimation of A.

Technical Abstract: Five algorithms (D8, '8, MFD, DEMON, and D') for computing contributing area, A, were compared on two agricultural fields (63 and 109 ha) in northeastern Colorado. Global positioning system (GPS) data (0.02 m accuracy) were used to generate grid digital elevation models (DEMs) at 5, 10, and 30-m cell sizes. Quantitative relative differences between single- and multiple-direction algorithms increased with decreasing grid cell size. Relative differences were greatest in divergent upslope areas, and differences decreased where the terrain became more convergent. Thus, flow divergence is a critical component for spatial estimation of A.