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Upscaling river networks for use in climate models
Author(s) -
Arora Vivek K.,
Harrison Stephen
Publication year - 2007
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2007gl031865
Subject(s) - grid , computer science , resolution (logic) , measure (data warehouse) , flow (mathematics) , fraction (chemistry) , process (computing) , grid cell , algorithm , data mining , hydrology (agriculture) , remote sensing , geology , artificial intelligence , mathematics , geodesy , geometry , chemistry , geotechnical engineering , operating system , organic chemistry
Upscaling fine resolution river networks in a realistic manner is a cumbersome process and manual corrections are difficult to avoid. A modified algorithm is presented that offers improvement over the existing approaches and requires comparatively fewer manual corrections. The algorithm uses fine resolution flow directions to find the adjacent coarse resolution grid cell in which the majority of water drains and then corrects for increased occurrences of river flow through the sides of the grid cells. Visual comparison remains an acceptable way to assess the success of various upscaling algorithms given the complex nature of rivers and in the absence of a method for comprehensive quantitative comparison. Here, the fraction of ordinal river flow directions (a measure of side‐to‐corner preference) and the fraction of grid cells that only drain themselves (a measure of connectivity of low order river segments) are used to provide information about the nature of upscaled coarse resolution river networks in comparison to the fine resolution networks. For both visual evaluation and these more quantitative measures, the modified algorithm presented here yields the best comparison with the 0.5° resolution river networks on which the upscaled coarse resolution networks are based.