Technical Notes
Mar 27, 2019

Moving-Window Detrending for Grain-Roughness Parameterization

Publication: Journal of Hydraulic Engineering
Volume 145, Issue 6

Abstract

Detrending is required to enable robust parameterization of surface roughness by removing large topographic trends from fluvial data. A range of detrending methods exist in the literature; however, there is limited presentation of the effect of these methods on output roughness statistics. Here, the results of non-detrended data compared with flat-surface detrending (e.g., removal of bed slope and setup misalignment) and moving-window detrending (e.g., removal of nonlinear bed undulations) are presented for a wide suite of roughness statistics. Digital elevation models (DEMs) of gravel surfaces obtained from the field and the laboratory are analyzed. Roughness statistics include the coefficient of variation of the standard deviation of elevations, standard deviation of elevations, skewness, kurtosis, inclination index, and horizontal roughness lengths from second-order structure functions. Similarities exist between non-detrended data and the data detrended using flat-surface detrending. The moving-window detrending method, which removes larger topographic signatures and roughness scales (e.g., the influence of bed forms), results in lower roughness statistics in the coefficient of variation, standard deviation of elevations, and horizontal roughness lengths. In contrast, higher values of skewness and kurtosis are observed with the moving-window detrending method. These observed differences in roughness statistics for studied detrending methods support the use of a moving-window detrending method for robust grain-roughness parameterization. Furthermore, it is highlighted that comparisons between grain-roughness studies need to ensure that the same procedure of detrending has been applied.

Get full access to this article

View all available purchase options and get full access to this article.

Acknowledgments

The study was partly funded by the Marsden Fund (Grant No. UOA1412), administered by the Royal Society of New Zealand.

References

Aberle, J., and V. Nikora. 2006. “Statistical properties of armored gravel bed surfaces.” Water Resour. Res. 42 (11): W11414. https://doi.org/10.1029/2005WR004674.
Aberle, J., V. Nikora, M. Henning, B. Ettmer, and B. Hentschel. 2010. “Statistical characterization of bed roughness due to bed forms: A field study in the Elbe River at Aken, Germany.” Water Resour. Res. 46 (3): W03521. https://doi.org/10.1029/2008WR007406.
Aberle, J., and G. M. Smart. 2003. “The influence of roughness structure on flow resistance on steep slopes.” J. Hydraul. Res. 41 (3): 259–269. https://doi.org/10.1080/00221680309499971.
Baewert, H., M. Bimböse, A. Bryk, E. Rascher, K.-H. Schmidt, and D. Morche. 2014. “Roughness determination of coarse grained alpine river bed surfaces using terrestrial laser scanning data.” Zeitschrift für Geomorphologie, Supplementary Issues 58 (1): 81–95. https://doi.org/10.1127/0372-8854/2013/S-00127.
Bertin, S., and H. Friedrich. 2014. “Measurement of gravel-bed topography: Evaluation study applying statistical roughness analysis.” J. Hydraul. Eng. 140 (3): 269–279. https://doi.org/10.1061/(ASCE)HY.1943-7900.0000823.
Bertin, S., and H. Friedrich. 2016. “Field application of close-range digital photogrammetry (CRDP) for grain-scale fluvial morphology studies.” Earth Surf. Processes Landforms 41 (10): 1358–1369. https://doi.org/10.1002/esp.3906.
Bertin, S., and H. Friedrich. 2018. “Effect of surface texture and structure on the development of stable fluvial armors.” Geomorphology 306: 64–79. https://doi.org/10.1016/j.geomorph.2018.01.013.
Bertin, S., H. Friedrich, P. Delmas, and E. Chan. 2013. “The use of close-range digital stereo-photogrammetry to measure gravel-bed topography in a laboratory environment.” In Proc., 35th IAHR Congress. Beijing: Tsinghua University Press.
Bertin, S., J. Groom, and H. Friedrich. 2017. “Isolating roughness scales of gravel-bed patches.” Water Resour. Res. 53 (8): 6841–6856. https://doi.org/10.1002/2016WR020205.
Brasington, J., D. Vericat, and I. Rychkov. 2012. “Modeling river bed morphology, roughness, and surface sedimentology using high resolution terrestrial laser scanning.” Water Resour. Res. 48 (11): 1–18. https://doi.org/10.1029/2012WR012223.
Butler, J. B., S. N. Lane, and J. H. Chandler. 2001. “Characterization of the structure of river-bed gravels using two-dimensional fractal analysis.” Math. Geol. 33 (3): 301–330. https://doi.org/10.1023/A:1007686206695.
Coleman, S. E., V. I. Nikora, and J. Aberle. 2011. “Interpretation of alluvial beds through bed-elevation distribution moments.” Water Resour. Res. 47 (11): W11505. https://doi.org/10.1029/2011WR010672.
Cooper, J. R., and S. J. Tait. 2009. “Water-worked gravel beds in laboratory flumes-A natural analogue?” Earth Surf. Processes Landforms 34 (3): 384–397. https://doi.org/10.1002/esp.1743.
Curran, J. C., and K. A. Waters. 2014. “The importance of bed sediment sand content for the structure of a static armor layer in a gravel bed river.” J. Geophys. Res. Earth Surf. 119 (7): 1484–1497. https://doi.org/10.1002/2014JF003143.
Detert, M., and V. Weitbrecht. 2012. “User guide to gravelometric image analysis by BASEGRAIN.” In Advances in science and research, 1789–1795. London: Taylor & Francis Group.
Diaz, J. C. F., J. Judge, K. C. Slatton, R. Shrestha, W. E. Carter, and D. Bloomquist. 2010. “Characterization of full surface roughness in agricultural soils using groundbased LiDAR.” In Proc., 2010 IEEE Int. Geoscience and Remote Sensing Symp., 4442–4445. New York: IEEE.
Gimel’farb, G. 2002. “Probabilistic regularisation and symmetry in binocular dynamic programming stereo.” Pattern Recognit. Lett. 23 (4): 431–442. https://doi.org/10.1016/S0167-8655(01)00175-1.
Goring, D., V. Nikora, and I. McEwan. 1999. Analysis of the texture of gravel beds using 2-D structure functions, 111–120. New York: Springer.
Graham, D. J., A. J. Rollet, H. Piégay, and S. P. Rice. 2010. “Maximizing the accuracy of image-based surface sediment sampling techniques.” Water Resour. Res. 46 (2): W02508. https://doi.org/10.1029/2008WR006940.
Groom, J., S. Bertin, and H. Friedrich. 2018a. “Assessing intra-bar variations in grain roughness using close-range photogrammetry.” J. Sediment. Res. 88 (5): 555–567. https://doi.org/10.2110/jsr.2018.30.
Groom, J., S. Bertin, and H. Friedrich. 2018b. “Evaluation of DEM size and grid spacing for fluvial patch-scale roughness parameterisation.” Geomorphology 320: 98–110. https://doi.org/10.1016/j.geomorph.2018.08.017.
Hodge, R., J. Brasington, and K. Richards. 2009a. “Analysing laser-scanned digital terrain models of gravel bed surfaces: Linking morphology to sediment transport processes and hydraulics.” Sedimentology 56 (7): 2024–2043. https://doi.org/10.1111/j.1365-3091.2009.01068.x.
Hodge, R., J. Brasington, and K. Richards. 2009b. “In situ characterization of grain-scale fluvial morphology using terrestrial laser scanning.” Earth Surf. Processes Landforms 34 (7): 954–968. https://doi.org/10.1002/esp.1780.
James, T. D., P. E. Carbonneau, and S. N. Lane. 2007. “Investigating the effects of DEM error in scaling analysis.” Photogramm. Eng. Remote Sens. 73 (1): 67–78. https://doi.org/10.14358/PERS.73.1.67.
Lamarre, H., and A. G. Roy. 2005. “Reach scale variability of turbulent flow characteristics in a gravel-bed river.” Geomorphology 68 (1): 95–113. https://doi.org/10.1016/j.geomorph.2004.09.033.
Lane, S. N. 2005. “Roughness-Time for a re-evaluation?” Earth Surf. Processes Landforms 30 (2): 251–253. https://doi.org/10.1002/esp.1208.
Legleiter, C. J., T. L. Phelps, and E. E. Wohl. 2007. “Geostatistical analysis of the effects of stage and roughness on reach-scale spatial patterns of velocity and turbulence intensity.” Geomorphology 83 (3): 322–345. https://doi.org/10.1016/j.geomorph.2006.02.022.
Mao, L., J. R. Cooper, and L. E. Frostick. 2011. “Grain size and topographical differences between static and mobile armour layers.” Earth Surf. Processes Landforms 36 (10): 1321–1334. https://doi.org/10.1002/esp.2156.
Millane, R. P., M. I. Weir, and G. M. Smart. 2006. “Automated analysis of imbrication and flow direction in alluvial sediments using laser-scan data.” J. Sediment. Res. 76 (8): 1049–1055. https://doi.org/10.2110/jsr.2006.098.
Morvan, H., D. Knight, N. Wright, X. Tang, and A. Crossley. 2008. “The concept of roughness in fluvial hydraulics and its formulation in 1D, 2D and 3D numerical simulation models.” J. Hydraul. Res. 46 (2): 191–208. https://doi.org/10.1080/00221686.2008.9521855.
Nelson, P. A., D. Bellugi, and W. E. Dietrich. 2014. “Delineation of river bed-surface patches by clustering high-resolution spatial grain size data.” Geomorphology 205: 102–119. https://doi.org/10.1016/j.geomorph.2012.06.008.
Nestler, J., and V. K. Sutton. 2000. “Describing scales of features in river channels using fractal geometry concepts.” Regulated Rivers Res. Manage. 16 (1): 1–22. https://doi.org/10.1002/(SICI)1099-1646(200001/02)16:1%3C1::AID-RRR566%3E3.0.CO;2-F.
Nikora, V. I., D. G. Goring, and B. J. F. Biggs. 1998. “On gravel-bed roughness characterization.” Water Resour. Res. 34 (3): 517–527. https://doi.org/10.1029/97WR02886.
Noss, C., and A. Lorke. 2016. “Roughness, resistance, and dispersion: Relationships in small streams.” Water Resour. Res. 52 (4): 2802–2821. https://doi.org/10.1002/2015WR017449.
Ockelford, A. M., and H. Haynes. 2013. “The impact of stress history on bed structure.” Earth Surf. Processes Landforms 38 (7): 717–727. https://doi.org/10.1002/esp.3348.
Pearson, E., M. W. Smith, M. J. Klaar, and L. E. Brown. 2017. “Can high resolution 3D topographic surveys provide reliable grain size estimates in gravel bed rivers?” Geomorphology 293: 143–155. https://doi.org/10.1016/j.geomorph.2017.05.015.
Powell, D. M., A. Ockelford, S. P. Rice, J. K. Hillier, T. Nguyen, I. Reid, N. J. Tate, and D. Ackerley. 2016. “Structural properties of mobile armors formed at different flow strengths in gravel-bed rivers.” J. Geophys. Res. Earth Surf. 121 (8): 1494–1515. https://doi.org/10.1002/2015JF003794.
Qin, J., and S. Ng. 2012. “Estimation of effective roughness for water-worked gravel surfaces.” J. Hydraul. Eng. 138 (11): 923–934. https://doi.org/10.1061/(ASCE)HY.1943-7900.0000610.
Qin, J., D. Zhong, G. Wang, and S. L. Ng. 2012. “On characterization of the imbrication of armored gravel surfaces.” Geomorphology 159: 116–124. https://doi.org/10.1016/j.geomorph.2012.03.012.
Robert, A. 1990. “Boundary roughness in coarse-grained channels.” Prog. Phys. Geogr. 14 (1): 42–70. https://doi.org/10.1177/030913339001400103.
Robert, A., A. Roy, and B. De Serres. 1996. “Turbulence at a roughness transition in a depth limited flow over a gravel bed.” Geomorphology 16 (2): 175–187. https://doi.org/10.1016/0169-555X(95)00143-S.
Schneider, J. M., D. Rickenmann, J. M. Turowski, and J. W. Kirchner. 2015. “Self-adjustment of stream bed roughness and flow velocity in a steep mountain channel.” Water Resour. Res. 51 (10): 7838–7859. https://doi.org/10.1002/2015WR016934.
Smart, G., J. Aberle, M. Duncan, and J. Walsh. 2004. “Measurement and analysis of alluvial bed roughness.” J. Hydraul. Res. 42 (3): 227–237. https://doi.org/10.1080/00221686.2004.9728388.
Smart, G. M., M. J. Duncan, and J. M. Walsh. 2002. “Relatively rough flow resistance equations.” J. Hydraul. Eng. 128 (6): 568–578. https://doi.org/10.1061/(ASCE)0733-9429(2002)128:6(568).
Smith, M. W. 2014. “Roughness in the earth sciences.” Earth-Sci. Rev. 136: 202–225. https://doi.org/10.1016/j.earscirev.2014.05.016.
Trevisani, S., and M. Cavalli. 2016. “Topography-based flow-directional roughness: Potential and challenges.” Earth Surf. Dyn. 4 (2): 343–358. https://doi.org/10.5194/esurf-4-343-2016.
Tuijnder, A. P., and J. S. Ribberink. 2012. “Experimental observation and modelling of roughness variation due to supply-limited sediment transport in uni-directional flow.” J. Hydraul. Res. 50 (5): 506–520. https://doi.org/10.1080/00221686.2012.719201.
Verhoest, N., H. Lievens, W. Wagner, J. Alvarez-Mozos, M. Moran, and F. Mattia. 2008. “On the soil roughness parameterization problem in soil moisture retrieval of bare surfaces from synthetic aperture radar.” Sensors 8 (7): 4213–4248. https://doi.org/10.3390/s8074213.
Zhang, Z. 2000. “A flexible new technique for camera calibration.” IEEE Trans. Pattern Anal. Mach. Intell. 22 (11): 1330–1334. https://doi.org/10.1109/34.888718.

Information & Authors

Information

Published In

Go to Journal of Hydraulic Engineering
Journal of Hydraulic Engineering
Volume 145Issue 6June 2019

History

Received: Aug 16, 2018
Accepted: Dec 27, 2018
Published online: Mar 27, 2019
Published in print: Jun 1, 2019
Discussion open until: Aug 27, 2019

Permissions

Request permissions for this article.

Authors

Affiliations

Ph.D. Student, Dept. of Civil and Environmental Engineering, Univ. of Auckland, Private Bag 92019, Auckland 1142, New Zealand (corresponding author). Email: [email protected]
Stephane Bertin [email protected]
Postdoctoral Researcher, Dept. of Civil and Environmental Engineering, Univ. of Auckland, Private Bag 92019, Auckland 1142, New Zealand. Email: [email protected]
Heide Friedrich [email protected]
Senior Lecturer, Dept. of Civil and Environmental Engineering, Univ. of Auckland, Private Bag 92019, Auckland 1142, New Zealand. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share