Journal
GEOMORPHOLOGY
Volume 354, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.geomorph.2020.107043
Keywords
Loess Plateau; River networks; Morphometric; Dominant process
Funding
- National Key Research and Development Program of China [2016YFC0402406]
- National Natural Science Foundation of China [51525901, 51639005]
- China Scholarship Council [201806210119]
- Natural Sciences and Engineering Research Council of Canada
- Canada Foundation for Innovation
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The Loess Plateau in China is the largest and deepest loess deposit in the world. The surficial geology is dominated by Quaternary loess deposits of varying thicknesses, which exhibit some of the fastest erosion rates in the world. Although the plateau has been traditionally thought of as morphologically homogenous, river network morphometrics in this area are spatially variable, suggesting that landscape evolution processes across the plateau are sensitive to variability in local conditions. We divided the plateau into sub-basins and examined six DEM-derived morphometric parameters: Aspect Ratio, Anisotropic Coefficient Variation (ACV), Bifurcation Ratio, Concavity, Steepness, and Mean Junction Angle. The sub-basins exhibited low aspect ratios, high bifurcation ratios and large junction angles relative to landscapes around the world, however they varied intra-regionally relative to each other. Through the use of Principal Component Analysis and Cluster Analysis, we observed specific spatial variation inmorphometrics attributable to differences in climate, lithology and tectonics along a NW-SE transect through the plateau. Sub-basins in the elevated plateau regions are more oval with higher aspect ratios and lower ACV values while those located in down-dropped valley regions have smaller junction angles, lower concavity and steepness index. Sub-basins in the transition area between down-dropped and elevated parts of the plateau are distinguished by their high bifurcation ratios and elongated shape. We propose a conceptual model to explain the relationship between these morphometrics and the local environmental conditions. (C) 2020 Elsevier B.V. All rights reserved.
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