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Prediction of drainage density from surrogate measures
Author(s) -
Richards K. S.
Publication year - 1979
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/wr015i002p00435
Subject(s) - quadrat , watershed , drainage , sampling (signal processing) , drainage density , statistics , drainage basin , line (geometry) , hydrology (agriculture) , scale (ratio) , environmental science , mathematics , geology , geography , computer science , cartography , geotechnical engineering , geometry , filter (signal processing) , ecology , transect , machine learning , oceanography , computer vision , biology
A number of surrogate indices have been proposed as alternatives to, or predictors of, drainage density. These involve quadrat‐ and line‐sampling methods, which avoid the problems of watershed definition and irregular area measurement, and counts of segments, junctions, and sources, which avoid measurement of irregular line lengths. These techniques are evaluated, and the number of Shreve segments within a quadrat‐sampling unit is found to be consistently the best predictor of both quadrat and basin drainage density, although differences occur according to the nature of network definition (blue line or contour crenulated). A number of tests of the suggested prediction relationships are described, and these indicate that the method can successfully predict drainage densities in areas other than the area for which the relationship is derived and on different map editions at the same scale.