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Earth Surface Dynamics An interactive open-access journal of the European Geosciences Union
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Volume 2, issue 1
Earth Surf. Dynam., 2, 117-125, 2014
https://doi.org/10.5194/esurf-2-117-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
Earth Surf. Dynam., 2, 117-125, 2014
https://doi.org/10.5194/esurf-2-117-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 04 Mar 2014

Research article | 04 Mar 2014

Seasonal logging, process response, and geomorphic work

C. H. Mohr1, A. Zimmermann1, O. Korup1, A. Iroumé2, T. Francke1, and A. Bronstert1 C. H. Mohr et al.
  • 1Institute of Earth and Environmental Science, University of Potsdam, Potsdam, Germany
  • 2Faculty of Forest Sciences and Natural Resources, Universidad Austral de Chile, Valdivia, Chile

Abstract. Deforestation is a prominent anthropogenic cause of erosive overland flow and slope instability, boosting rates of soil erosion and concomitant sediment flux. Conventional methods of gauging or estimating post-logging sediment flux often focus on annual timescales but overlook potentially important process response on shorter intervals immediately following timber harvest. We resolve such dynamics with non-parametric quantile regression forests (QRF) based on high-frequency (3 min) discharge measurements and sediment concentration data sampled every 30–60 min in similar-sized (∼0.1 km2) forested Chilean catchments that were logged during either the rainy or the dry season. The method of QRF builds on the random forest algorithm, and combines quantile regression with repeated random sub-sampling of both cases and predictors. The algorithm belongs to the family of decision-tree classifiers, which allow quantifying relevant predictors in high-dimensional parameter space. We find that, where no logging occurred, ∼80% of the total sediment load was transported during extremely variable runoff events during only 5% of the monitoring period. In particular, dry-season logging dampened the relative role of these rare, extreme sediment-transport events by increasing load efficiency during more efficient moderate events. We show that QRFs outperform traditional sediment rating curves (SRCs) in terms of accurately simulating short-term dynamics of sediment flux, and conclude that QRF may reliably support forest management recommendations by providing robust simulations of post-logging response of water and sediment fluxes at high temporal resolution.

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