Bumps in river profiles: uncertainty assessment and smoothing using quantile regression techniques

The analysis of longitudinal river profiles is an important tool for studying landscape evolution. However, characterizing river profiles based on digital elevation models (DEMs) suffers from errors and artifacts that particularly prevail along valley bottoms. The aim of this study is to characteriz...

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Vydáno v:Earth surface dynamics Ročník 5; číslo 4; s. 821 - 839
Hlavní autoři: Schwanghart, Wolfgang, Scherler, Dirk
Médium: Journal Article
Jazyk:angličtina
Vydáno: Gottingen Copernicus GmbH 07.12.2017
Copernicus Publications
Témata:
Accuracy
Algorithms
Analysis
Banks (topography)
Bias
Digital Elevation Models
Elevation
Errors
Geomorphology
Hydrologic models
Hydrology
Landscape evolution
Mathematical models
Methods
Profiles
Quantile regression
Radar systems
Regression analysis
Rivers
Sediments
Slope
Topography
Topography (geology)
Uncertainty
Valleys
ISSN:2196-632X, 2196-6311, 2196-632X
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Shrnutí:The analysis of longitudinal river profiles is an important tool for studying landscape evolution. However, characterizing river profiles based on digital elevation models (DEMs) suffers from errors and artifacts that particularly prevail along valley bottoms. The aim of this study is to characterize uncertainties that arise from the analysis of river profiles derived from different, near-globally available DEMs. We devised new algorithms – quantile carving and the CRS algorithm – that rely on quantile regression to enable hydrological correction and the uncertainty quantification of river profiles. We find that globally available DEMs commonly overestimate river elevations in steep topography. The distributions of elevation errors become increasingly wider and right skewed if adjacent hillslope gradients are steep. Our analysis indicates that the AW3D DEM has the highest precision and lowest bias for the analysis of river profiles in mountainous topography. The new 12 m resolution TanDEM-X DEM has a very low precision, most likely due to the combined effect of steep valley walls and the presence of water surfaces in valley bottoms. Compared to the conventional approaches of carving and filling, we find that our new approach is able to reduce the elevation bias and errors in longitudinal river profiles.
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ISSN:2196-632X
2196-6311
2196-632X
DOI:10.5194/esurf-5-821-2017