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• W2943283346 abstract "The structure and organization of river networks has been used for decades to investigate the influence of climate and tectonics on landscapes. The majority of these studies either analyze rivers in profile view by extracting channel steepness or calculate planform metrics such as drainage density. However, these techniques rely on the assumption of homogeneity: that intrinsic and external factors are spatially or temporally invariant over the measured profile. This assumption is violated for the majority of Earth's landscapes, where variations in uplift rate, rock strength, climate, and geomorphic process are almost ubiquitous. We propose a method for classifying river profiles to identify landscape regions with similar characteristics by adapting hierarchical clustering algorithms developed for time series data. We first test our clustering on two landscape evolution scenarios and find that we can successfully cluster regions with different erodibility and detect the transient response to sudden base level fall. We then test our method in two real landscapes: first in Bitterroot National Forest, Idaho, where we demonstrate that our method can detect transient incision waves and the topographic signature of fluvial and debris flow process regimes; and second, on Santa Cruz Island, California, where our technique identifies spatial patterns in lithology not detectable through normalized channel steepness analysis. By calculating channel steepness separately for each cluster, our method allows the extraction of more reliable steepness metrics than if calculated for the landscape as a whole. These examples demonstrate the method's ability to disentangle fluvial morphology in complex lithological and tectonic settings." @default.
• W2943283346 created "2019-05-09" @default.
• W2943283346 creator A5007492971 @default.
• W2943283346 creator A5062287980 @default.
• W2943283346 creator A5076017313 @default.
• W2943283346 date "2019-06-01" @default.
• W2943283346 modified "2023-09-23" @default.
• W2943283346 title "Clustering River Profiles to Classify Geomorphic Domains" @default.
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• W2943283346 doi "https://doi.org/10.1029/2019jf005025" @default.
• W2943283346 hasPublicationYear "2019" @default.
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