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To plug‐in or not to plug‐in? Geomorphic analysis of rivers using the River Styles Framework in an era of big data acquisition and automation

Focus Article

Kirstie A. Fryirs, Joseph M. Wheaton, Simone Bizzi, Richard Williams, Gary J. Brierley

Published Online: Jul 22 2019

DOI: 10.1002/wat2.1372

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Abstract In an era of big‐data acquisition and semiautomation of geomorphic river surveys, it is timely to consider how to better integrate this into existing and widely used conceptual frameworks and approaches to analysis. We demonstrate how Stage 1 of the River Styles Framework, which entails identification and interpretation of river character and behavior, patterns and controls, can be used as a “powerboard” into which available, developing and future semiautomated tools and workflows can be plugged (or unplugged). Prospectively, such approaches will increase the efficiency and scope of analyses, providing unprecedented insights into the diversity of rivers and their morphodynamics. We appraise the role of human decision‐making in conducting expert‐manual analyses and interpretations. Genuine integration of big‐data analytics, remote‐sensing based tools for semiautomated river analysis with expert‐manual interpretations including field insights, will be an essential ingredient to fully exploit emerging computational and remote sensing technologies to advance our understanding of river systems, to translate information into knowledge, and raise the standards of practice in river science and management. This article is categorized under: Water and Life > Conservation, Management, and Awareness Water and Life >Methods Engineering Water > Planning Water Engineering Water > Sustainable Engineering of Water

Examples of geomorphic river diversity. Valley bottom margin noted as white lines. For definitions and methods see Fryirs, Wheaton, and Brierley (), Fryirs and Brierley (), and O'Brien et al. (). (a) Franklin River, Australia; (b) Rhein River, Germany; (c) Pages River, Australia; (d) Williams River, Australia; I Humboldt River, USA; (f) Squamish River, Canada; (g) Brahmaputra River, Bangladesh; (h) Nowitna River, Alaska; (i) Macquarie River, Australia; (j) Cooper Creek, Australia; (k) Wingecaribee River, Australia; (l) Mulwaree ponds, Australia. Basemaps produced with ArcGIS software by Esri. Sources: Esri, DigitalGlobe, GeoEye, earthstar Geographics, CNES/Airbus DS, USDA, USGS, AeroGRID, IGN, and the GIS user community. For approaches to identification and naming of these examples see Fryirs and Brierley ()

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(a) Plug‐in options available to aid production of (b) stacked‐longitudinal profile plots for analysis of downstream patterns and controls on river character and behavior. The example used is the middle fork John Day, USA. (Reprinted with permission from O'Brien et al., . Copyright 2017 Taylor and Francis Online)

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Example of geomorphic change detection (GCD) output overlayed with expert‐manual interpretation of processes and types of adjustment. (a) Wheaton et al. () and (b) Williams, Rennie, Brasington, Hicks, and Vericat ()

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(a) Plug‐in options available to aid production of (b) example outputs that can be used to characterize river types. Table provides links to, and key readings for, these available tools

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Stage 1, Step 1 of the River Styles Framework as a powerboard into which semiautomated tools for analysis can be plugged or unplugged (denoted by the yellow shading with three‐point power socket) where data and technology are available for tool development (blue shading), and where an expert‐manual approach is still needed (green shading). Note: relative proportions of color in each box are not significant. (a) From Brierley and Fryirs () and Fryirs and Brierley (). (b) V‐BET, valley‐bottom extraction tool; VBCT, valley bottom confinement tool; FCT, fluvial corridor toolkit; API, aerial photograph interpretation; GE, Google earth; SVMc, support vector machine classifier; GUT, geomorphic unit tool; GUS, geomorphic unit survey. The category “H‐res DEM” (high‐resolution digital elevation model) includes use of LiDAR and structure from motion (SfM) as two available geomatics technologies. The category “satellite” refers to both planimetric imagery and derived DEMs. Table provides links to, and key readings for, these available tools

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Further Reading

Czuba,, J. A. (2018). A Lagrangian framework for exploring complexities of mixed‐size sediment transport in gravel‐bedded river networks. Geomorphology, 321, 146–152. https://doi.org/10.1016/j.geomorph.2018.08.031
Fryirs,, K. A. (2017). River sensitivity: A lost foundation concept in fluvial geomorphology. Earth Surface Processes and Landforms, 42(1), 55–70. https://doi.org/10.1002/esp.3940
Williams,, R., Moir,, H., & Wheaton,, J. (2018). Geomorphic unit diversity in restored rivers: How important is riparian woodland? AGU Fall Meeting, Washington DC, 10–14 December 2018.

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