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

Abstract

The abundance of global, remotely sensed surface water observations has accelerated efforts 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 recipe-predicted flow directions agreed with expert judgement for 97 % of all tested links, and most disagreementsmore » were attributed to unusual channel network topologies that can easily be accounted for by pre-seeding critical links with known flow directions. Our results highlight the (non)universality of process–form relationships across deltas and braided rivers.« less

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); USDOE Laboratory Directed Research and Development (LDRD) Program
OSTI Identifier:
1603987
Report Number(s):
LA-UR-19-22689
Journal ID: ISSN 2196-632X
Grant/Contract Number:  
89233218CNA000001; 20170668PRD1
Resource Type:
Accepted Manuscript
Journal Name:
Earth Surface Dynamics
Additional Journal Information:
Journal Volume: 8; Journal Issue: 1; Journal ID: ISSN 2196-632X
Country of Publication:
United States
Language:
English
Subject:
Earth sciences; river channel networks; topology; flow direction; graphs; delta; braided river

Citation Formats

Schwenk, Jon Pauk, Piliouras, Anastasia, and Rowland, Joel C. Determining flow directions in river channel networks using planform morphology and topology. United States: N. p., 2020. Web. doi:10.5194/esurf-8-87-2020.
Schwenk, Jon Pauk, Piliouras, Anastasia, & Rowland, Joel C. Determining flow directions in river channel networks using planform morphology and topology. United States. doi:10.5194/esurf-8-87-2020.
Schwenk, Jon Pauk, Piliouras, Anastasia, and Rowland, Joel C. Wed . "Determining flow directions in river channel networks using planform morphology and topology". United States. doi:10.5194/esurf-8-87-2020. https://www.osti.gov/servlets/purl/1603987.
@article{osti_1603987,
title = {Determining flow directions in river channel networks using planform morphology and topology},
author = {Schwenk, Jon Pauk and Piliouras, Anastasia and Rowland, Joel C.},
abstractNote = {The abundance of global, remotely sensed surface water observations has accelerated efforts 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 recipe-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. Our results highlight the (non)universality of process–form relationships across deltas and braided rivers.},
doi = {10.5194/esurf-8-87-2020},
journal = {Earth Surface Dynamics},
number = 1,
volume = 8,
place = {United States},
year = {2020},
month = {2}
}

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