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Earth Surface Dynamics An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/esurf-2019-19
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esurf-2019-19
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 23 May 2019

Submitted as: research article | 23 May 2019

Review status
This discussion paper is a preprint. A revision of the manuscript was accepted for the journal Earth Surface Dynamics (ESurf).

Determining flow directions in river channel networks using planform morphology and topology

Jon Schwenk, Anastasia Piliouras, and Joel C. Rowland Jon Schwenk et al.
  • Los Alamos National Laboratory, Earth and Environmental Sciences Division

Abstract. The abundance of global, remotely-sensed surface water observations has paved the way toward characterizing and modeling how water moves across the Earth's surface through complex channel networks. In particular, deltas and braided river channel networks may contain thousands of links that route water, sediment, and nutrients across landscapes. In order to model flows through channel networks and characterize network structure, the direction of flow for each link within the network must be known. In this work, we propose a rapid, automatic, and objective method to identify flow directions for all links of a channel network using only remotely-sensed imagery and knowledge of the network's inlet and outlet locations. We designed a suite of direction-predicting algorithms (DPAs), each of which exploits a particular morphologic characteristic of the channel network to provide a prediction of a link's flow direction. DPAs were chained together to create “recipes”, or algorithms that set all the flow directions of a channel network. Separate recipes were built for deltas and braided rivers and applied to seven delta and two braided river channel networks. Across all nine channel networks, the recipes' predicted flow directions agreed with expert judgement for 97 % of all tested links, and most disagreements were attributed to unusual channel network topologies that can easily be accounted for by pre-seeding critical links with known flow directions.

Jon Schwenk et al.
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Status: final response (author comments only)
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Jon Schwenk et al.
Jon Schwenk et al.
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Latest update: 13 Dec 2019
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Short summary
Standing on a riverbank, it is usually obvious which direction the river flows. However, when observing a river from space, we cannot see the flowing water and must use context to determine flow directions. For complicated river channel networks such as those of deltas and braided rivers, determining the flow direction of each channel within the network is not trivial. We present and demonstrate a method to automatically determine flow directions within aerially-viewed river channel networks.
Standing on a riverbank, it is usually obvious which direction the river flows. However, when...
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