Bedforms-ATM, an open source software to analyze the scale-based hierarchies and dimensionality of natural bed forms

Gutiérrez, Ronald R.; Mallma, Jose Antonio; Núñez‐González, Francisco; Link, Oscar; Abad, J. D.

doi:10.1016/j.softx.2018.06.001

Cited by 25 publications

(36 citation statements)

References 13 publications

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“…The general reliability of the outlined methodology was validated using a freely available MBES data set from Rio Paraná, Argentina, which was originally investigated by Parsons et al ., (2005). After detecting prevailing bedforms along a total of 150 longitudinal transects from a single (snapshot) bathymetry, dune dimensions and abundances were compared to results obtained from an analysis in accordance with the wavelet analysis tool developed by Gutierrez et al ., (2018) and those published in Cisneros et al ., (2020). Especially regarding the results of the former, the examination of this independent study area reveals good resemblance between the proposed and at least one established approach, except for the occurrence of outlying ‘high small dunes’ and ‘low large or very large dunes’, respectively, which are deemed critical by the authors.…”

Section: Methodsmentioning

confidence: 65%

“…Unlike other dune tracking tools (e.g. Gutierrez et al ., 2018; van der Mark and Blom, 2007), the algorithm employed in this study does not evaluate BEPs that are detrended or filtered in any way. In order to make allowance for the underlying, complex character of compound dunes in the focus area, it is instead based on an iterative identification of local extremes spaced in accordance with a widely accepted classification scheme proposed by (Ashley et al ., 1990).…”

Section: Methodsmentioning

confidence: 99%

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Robust methods for the decomposition and interpretation of compound dunes applied to a complex hydromorphological setting

Scheiber

Lojek

Götschenberg³

et al. 2021

Earth Surf Processes Landf

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Underwater dunes are a morphological feature that are explored by marine scientists and coastal engineers alike. This study presents new methodologies in order to simplify bedform identification and morphodynamic analyses. Specifically, subaqueous compound dunes are decomposed with a simple yet extensive tracking algorithm, which relies on a repeated evaluation of unfiltered bed elevation profiles according to five predefined length classes. In a second step, morphological trends are assessed in the form of bed migration rates, bed slope asymmetries and net sediment changes, in which all parameters are referred to equidistant sections of the examined fairway stretch. This integrated approach not only avoids the challenges in weighting the varying size and abundance of dunes of different scales but also ensures comparability between dune‐specific and areal parameters, which significantly improves the interpretation of the morphological setting as a whole. The developed methods are applied to the Outer Jade fairway, an anthropogenically influenced and regularly maintained waterway in the German Bight, and allow scrutiny of spatio‐temporal trends in this region. Based on a unique data set of 100 sequential high‐quality echo‐sounding surveys, various types of bedforms are identified, comprising large‐scale primary as well as superimposing secondary dunes that are assumed to interfere with each other. Temporal trends show a long‐term rise of the troughs of major bedforms and constant maximum crest elevations near the official maintenance depth, which matches the observed long‐term aggradation of sediments. The spatial distribution of integrated morphodynamic parameters reflects a previously described zone of primary dune convergence and facilitates the precise localization of this geophysical singularity. The presented findings both confirm the robustness of the proposed methodologies and, in return, enhance the understanding of morphological processes in the Outer Jade. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.

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Section: Methodsmentioning

confidence: 65%

Section: Methodsmentioning

confidence: 99%

Robust methods for the decomposition and interpretation of compound dunes applied to a complex hydromorphological setting

Scheiber

Lojek

Götschenberg³

et al. 2021

Earth Surf Processes Landf

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“…We believe that the Bedforms‐ATM platform of Gutierrez et al . (2018) could potentially be used to build such code. Bedforms‐ATM is currently written in Matlab.…”

Section: Towards Bed Form Data Analysis Standardizationmentioning

confidence: 99%

“…Recently, some progress has been made in this respect: some researchers are starting to share their data, encouraged by the requirements from some funding agencies and scientific journals to make data openly available; many data publishers and repositories are being established; and freely available software for bed form analysis is being developed. For example, Bradley and Venditti (2017) have compiled flow and dune dimension data for bed forms in unidirectional flows, and have made the data available as supplementary material; researchers have published nearly 400 000 datasets to date through the data publisher PANGAEA, including 125 related to bed forms; Gutierrez et al (2018) provided technical details of the free access software named Bedforms-ATM (Bedforms Analysis Toolkit for Multiscale Modeling), which proposes standardizing the scale-based discrimination and dimensionality quantification of natural bed forms in a single platform and whose structure encourages its expandability via collaboration from the community of users. The use of Bedforms-ATM to conduct scientific research has been reported by Lefebvre (2019).…”

Section: Introductionmentioning

confidence: 99%

Towards adopting open and data‐driven science practices in bed form dynamics research, and some steps to this end

Gutiérrez

Lefebvre

Núñez‐González

et al. 2020

Earth Surf Processes Landf

Self Cite

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In recent years, open and data‐driven science has fostered very important scientific breakthroughs. This study describes the challenges and opportunities for the scientific community devoted to bed form dynamics research in adopting such scientific paradigms through, for example, engineered data sharing, formal recognition of scientists who collect the data, and collaborative development of free accessible software. It highlights that once these actions are completed, the potential application of deep learning techniques could substantially improve bed form models and the scientific understanding of bed form dynamics. Likewise, it discusses the potential of Bedforms‐ATM, a free available software, to standardize some bed form data analysis techniques. We propose that the technical challenges be tackled by following scholarly accepted/proposed standards (e.g. FAIR Guiding Principles, Geoscience Papers of the Future), using the body of knowledge being built on the matter by some institutions (e.g. Federation of Earth Science Information Partners), and through technical discussions at scientific meetings such as MARID. © 2020 John Wiley & Sons, Ltd.

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“…The crest and trough positions of the large bedforms are determined semiautomatically. First, the 400 transects from the 0.5‐m resolution bathymetry are analyzed using the Bedforms‐ATM toolbox (Gutierrez et al, ). The results of this analysis showed that the dominant wavelength of the large bedforms is 60 m. Subsequently, a zero‐crossing technique similar to the dune tracking method of Van der Mark and Blom () is used on the filtered morphology of the large bedforms, targeting the dominant bedform length of 60 m (Figure a).…”

Section: Río Paraná Bedformsmentioning

confidence: 99%

Three‐Dimensional Flow Above River Bedforms: Insights From Numerical Modeling of a Natural Dune Field (Río Paraná, Argentina)

Lefebvre

2019

JGR Earth Surface

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Bedforms are ubiquitous features in rivers and shallow seas, as mobile sediment is transported by flowing water. The mutual interaction of hydrodynamics and bedform has been widely studied in the laboratory over two‐dimensional bedforms having an angle‐of‐repose (30°) lee side and a relatively simple shape. However, the influence of bedform natural morphology and three‐dimensionality on the flow is still poorly constrained. The present work looks at how a natural three‐dimensional (3‐D) bedform field influences flow properties through high‐resolution numerical modeling. A 3‐D numerical model is set up with Delft3D and verified against lab experiments of idealized 3‐D bedforms. The model is used to simulate water velocities, turbulence, water levels, and bed shear stress above a natural bedform field from the Río Paraná (Argentina). The presence and size of the flow separation zone and turbulent wake depend on the presence and properties of the slip face (defined here as the portion of the lee side with angles >15°) and not on those of the crest. When present, the flow separation and wake lengths are, for the tested settings, respectively, around 5 and 13 times the slip face height. A slip face orientation of 25° or more compared to the flow increases cross‐stream flow and suppresses flow reversal over the slip face. To understand and predict flow and bedform properties, the slip face rather than the crest position should be identified and analyzed.

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Bedforms-ATM, an open source software to analyze the scale-based hierarchies and dimensionality of natural bed forms

Cited by 25 publications

References 13 publications

Robust methods for the decomposition and interpretation of compound dunes applied to a complex hydromorphological setting

Robust methods for the decomposition and interpretation of compound dunes applied to a complex hydromorphological setting

Towards adopting open and data‐driven science practices in bed form dynamics research, and some steps to this end

Three‐Dimensional Flow Above River Bedforms: Insights From Numerical Modeling of a Natural Dune Field (Río Paraná, Argentina)

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