Methodology to Combine Topography and Bathymetry Data Sets for Hydrodynamic Simulations: Case of Tagus River
Publication: Journal of Surveying Engineering
Volume 142, Issue 4
Abstract
Recent techniques for acquiring elevation, such as the advanced synthetic aperture radar (SAR) interferometric techniques, enable the creation of very detailed models in a short time. However, because of its incapacity to penetrate the water, the collection of bathymetric information in water-covered areas must be performed with other techniques. Thus, data compatibility is a key factor for two-dimensional (2D) hydrodynamic simulations because a single elevation model is required in general. Such operation is often challenging, because it is not simply obtainable by merging the data sets or replacing the main river channel information with the bathymetry. This study presents a geographic information system (GIS)–based methodology to merge the bathymetry and topography of a river and validates it with 2D flood event simulations. Therefore, the floodplain topography data sets, including emerged fluvial features and profile-shaped bathymetric surveys covering only limited sections of the river channel, were combined to produce a single elevation model. The methodology is based on the extraction of the riverbanks on a digital elevation model (DEM) to locate the thalweg and two ancillary lines, which support an interpolation of cross-section data. The case study is the middle section of the Tagus River in Portugal, for which distinct data sets of bathymetry (namely, cross sections) and a DEM obtained by the advanced interferometric techniques were available. A segment of flooded/unflooded areas obtained from a SAR image of a previous flood event was used as a basis to compare the flooded area resulting from two hydrodynamic simulations. The disagreement in flooded area extension was reduced from 12% difference to 1% using the proposed combined DEM. Water levels, measured at a hydrometric station, were also used for assessment. A significant improvement was also found using the combined DEM: the maximum water level differences decreased from 218.7 to 24.4 cm.
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Acknowledgments
This work was supported by Fundação para a Ciência e a Tecnologia through projects RIVERSAR 350 (PTDC/CTE-GIX/099085/2008) and SEICHE (EXCL/GEO-FIQ/0411/2012). The used image was obtained through ESA Category 1, Project 9,441. The authors express gratitude to Teresa Alvares, Emília Van Zeller, and Victor Rodrigues of the Portuguese Environment Agency for providing all bathymetric and sand-extraction location data sets, and for their work in the 2012 cross-section surveying. The authors are indebted to the anonymous reviewers for their thorough reading of the article and for providing insightful comments.
References
Araújo, M. A. V. C., Mazzolari, A., and Trigo-Teixeira, A. (2013). “An object oriented mesh generator: Application to flooding in the Douro estuary.” J. Coastal Res., 1(65), 642–647.
ArcGIS 10.1 [Computer software]. Esri, Redlands, CA.
Bangen, S. G., Wheaton, J. M., Bouwes, N., Bouwes, B., and Jordan, C. (2014). “A methodological intercomparison of topographic survey techniques for characterizing wadeable streams and rivers.” Geomorphology, 206, 343–361.
BKG (Bundesamt für Kartographie und Geodäsie). (2015). “Height datum relations—European national height reference systems.” 〈http://www.bkg.bund.de〉 (in German).
Buttner, O. (2007). “The influence of topographic and mesh resolution in 2D hydrodynamic modelling for floodplains and urban areas.” Geophys. Res. Abstr., 9, 08232.
Costa, B. M., Battista, T. A., and Pittman, S. J. (2009). “Comparative evaluation of airborne LiDAR and ship-based multibeam SoNAR bathymetry and intensity for mapping coral reef ecosystems.” Remote Sens. Environ., 113(5), 1082–1100.
Coveney, S., and Fotheringham, A. S. (2011). “The impact of DEM data source on prediction of flooding and erosion risk due to sea-level rise.” Int. J. Geog. Inf. Sci., 25(7), 1191–1211.
Di Baldassarre, G., Schumann, G., Brandimarte, L., and Bates, P. (2011). “Timely low resolution SAR imagery to support floodplain modelling: a case study review.” Surv. Geophys., 32(3), 255–269.
DiGruttolo, N., and Mohamed, A. (2011). “Emerging unmanned aerial remote sending system for intertidal zone modelling: A low-cost method of collecting remote sensing data for modelling short-term effects of sea level rise, part II: Close-range airborne remote sensing.” Surv. Land Inf. Sci., 70(3), 119–129.
European Union. (2007). Directive 2007/60/EC of the European Parliament and of the Council of 23 October 2007 on the assessment and management of flood risks 〈http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=CELEX:32007L0060:EN:NOT〉.
EVRS (European Vertical Reference System). (2007) “European national height reference systems.” 〈http://www.bkg.bund.de/nn_164776/geodIS/EVRS/EN/Projects/03HeightDatumRel/height-datum-rel__node.html〉
Falcão, A. P., Mazzolari, A., Gonçalves, A. B., Araújo, M. A. V. C., and Trigo-Teixeira, A. (2013). “Influence of elevation modelling on hydrodynamic simulations of a tidally-dominated estuary.” J. Hydrol., 497, 152–164.
Hailemariam, F. M., Brandimarte, L., and Dottori, F. (2014). “Investigating the influence of minor hydraulic structures on modeling flood events in lowland areas.” Hydrol. Processes, 28(4), 1742–1755.
Hardy, R. J., Bates, P. D., and Anderson, M. G. (1999). “The importance of spatial resolution in hydraulic models for floodplain environments.” J. Hydrol., 216(1–2), 124–136.
Horritt, M. S., Bates, P. D., and Mattinson, M. J. (2006). “Effects of mesh resolution and topographic representation in 2D finite volume models of shallow water fluvial flow.” J. Hydrol., 329(1–2), 306–314.
Manjusree, P., Kumar, L. P., Bhatt, C. M., Rao, G. S., and Bhanumurthy, V. (2012). “Optimization of threshold ranges for rapid flood inundation mapping by evaluating backscatter profiles of high incidence angle SAR images.” Int. J. Disaster Risk Sci., 3(2), 113–122.
Mason, D. C., Horritt, M. S., Speck, R., and Bates, P. D. (2009). “Improving flood inundation models using remotely sensed data.” Int. Conf. on Space Technology, IEEE Geoscience and Remote Sensing Society, New York.
Merwade, V. (2009). “Effect of spatial trends on interpolation of river bathymetry.” J. Hydrol., 371(1–4), 169–181.
Merwade, V., Cook, A., and Coonrod, J. (2008). “GIS techniques for creating river terrain models for hydrodynamic modeling and flood inundation mapping.” Environ. Modell. Software, 23(10–11), 1300–1311.
Neal, J., Schumann, G., and Bates, P. (2012). “A subgrid channel model for simulating river hydraulics and floodplain inundation over large and data sparse areas.” Water Resour. Res., 48(11), W11506.
NEXTMap [Computer software]. Intermap Technologies, Denver.
Omer, C. R., Nelson, E. J., and Zundel, A. K. (2003). “Impact of varied data resolution on hydraulic modeling and floodplain delineation.” J. Am. Water Resour. Assoc., 39(2), 467–475.
Pe'eri, S., and Long, B. (2011). “LIDAR technology applied in coastal studies and management.” J. Coastal Res., 62, 1–5.
Pestana, R., et al. (2013). “Calibration of 2D hydraulic inundation models in the floodplain region of the lower Tagus River.” ESA Living Planet Conf. 2013, European Space Agency, Paris.
Roque, D., Afonso, N., Fonseca, A. M., and Heleno, S. (2013). “Building a database of flood extension maps using satellite imagery.” ESA Living Planet Conf. 2013, European Space Agency, Paris.
Salgueiro, A. R., Machado, M. J., Barriendos, M., Garcia Pereira, H., and Benito, G. (2013). “Flood magnitudes in the Tagus River (Iberian Peninsula) and its stochastic relationship with daily North Atlantic oscillation since mid-19th Century.” J. Hydrol., 502, 191–201.
Sánchez-Carnero, N., Aceña, S., Rodríguez-Pérez, D., Couñago, E., Fraile, P., and Freire, J. (2012). “Fast and low-cost method for VBES bathymetry generation in coastal areas.” Estuarine Coastal Shelf Sci., 114, 175–182.
Schäppi, B., Perona, P., Schneider, P., and Burlando, P. (2010). “Integrating river cross section measurements with digital terrain models for improved flow modelling applications.” Comput. Geosci., 36(6), 707–716.
Straatsma, M., and Huthoff, F. (2011). “Uncertainty in 2D hydrodynamic models from errors in roughness parameterization based on aerial images.” Phys. Chem. Earth Parts A/B/C, 36(7–8), 324–334.
Tarpanelli, A., Brocca, L., Melone, F., and Moramarco, T. (2013). “Hydraulic modelling calibration in small rivers by using coarse resolution synthetic aperture radar imagery.” Hydrol. Processes, 27(9), 1321–1330.
TUFLOW Classic [Computer software]. BMT Group Ltd., Teddington, U.K.
Wegmüller, U., Santoro, M., Werner, C., Strozzi, T., Wiesmann, A., and Lengert, W. (2009). “DEM generation using ERS–ENVISAT interferometry.” J. Appl. Geophys., 69(1), 51–58.
Woodget, A. S., Carbonneau, P. E., Visser, F., and Maddock, I. P. (2015). “Quantifying submerged fluvial topography using hyperspatial resolution UAS imagery and structure from motion photogrammetry.” Earth Surf. Processes Landforms, 40(1), 47–64.
Yoon, Y., Durand, M., Merry, C. J., Clark, E. A., Andreadis, K. M., and Alsdorf, D. E. (2012). “Estimating river bathymetry from data assimilation of synthetic SWOT measurements.” J. Hydrol., 464-465, 363–375.
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© 2016 American Society of Civil Engineers.
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Received: May 19, 2015
Accepted: Mar 2, 2016
Published online: May 4, 2016
Discussion open until: Oct 4, 2016
Published in print: Nov 1, 2016
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