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Journal of Iberian Geology

, Volume 44, Issue 3, pp 355–373 | Cite as

Monitoring ephemeral river changes during floods with SfM photogrammetry

  • Mikel Calle
  • Petteri Alho
  • Gerardo Benito
Research Paper
  • 54 Downloads

Abstract

Monitoring detailed topographic changes in rivers is an essential tool for understanding the morpho-sedimentary behavior of rivers. However, as the resolution of topographic reconstruction techniques improves, survey costs and the time consumed increase. In this paper, the emerging Structure from Motion Multi-View Stereo (SfM-MVS), a high resolution but low cost technique, is scrutinized to assess whether it constitutes a viable option for ‘change detection’ in ephemeral rivers. To that end, three photogrammetric flights were carried out to reconstruct the subsequent digital elevation models (DEMs) and quantify fluvial change caused by two floods in 2015 along a 6.5 km reach in an ephemeral gravel-bed river (Rambla de la Viuda; eastern Spain). The application of SfM-MVS resulted in a maximum point cloud density of 1295.4 pts/m2 and a DEM resolution of 3.11 cm/pix. Individual flights registered errors of 0.101, 0.171 and 0.083 m. Level of detection (LoD) of DEMs of difference (DoDs), i.e. topographic change detection, resulted in 0.198 and 0.190 between the first and second, and second and third flights respectively. Orthomosaics were also successfully created at a maximum resolution of 2.50 cm/pix. Analysis of the best configuration of SfM-MVS for ephemeral river monitoring indicated that a high overlap of photographs and, therefore, a large number of projections were critical for an efficient workflow and a high-quality model. To ensure model quality and survey efficiency, the following configuration is recommended: (1) overlap index of more than 20 projections, (2) flight distribution at two heights, and (3) the use of ground control points. SfM-MVS topographies and DoDs showed a discontinuous pattern represented by a succession of erosive-depositional sequences. Evolution of one of these sequences has been studied in detail and the legacy of a past mining pit was pointed out to be the principal driver for this morphosedimentary pattern. Change detection quantified a net erosion of (−)3118 m3 for Flood #1 and a net deposition of (+)787 m3 for Flood #2, at a 95% confidence. Knickpoint retreat, riverbed lowering and bank erosion were identified as the principal sources of sediment. Analyzing separately each flood highlighted that the mobilization of sediments was not proportional to peak discharges (98 and 80 m3/s, respectively). Interpretation of this behavior was hypothesized to be produced by the difference in total water volume (32.5 and 7.1 hm3), longer discharge period (24 and 11 days), different entrainment thresholds of each flood, or a clockwise hysteresis effect in the sediment transport, probably due to varying sediment availability. Thus, it was concluded that SfM-MVS worked especially well for change detection in ephemeral rivers and served as a basis for understanding morphological river patterns associated to floods and human impacts.

Keywords

Gravel-bed Change detection SfM-MVS Ephemeral river Level of detection 

Resumen

Para llegar a comprender el comportamiento morfosedimentario de los ríos es necesario realizar un seguimiento detallado de los cambios topográficos que tienen lugar en sus cauces. Sin embargo, cuanto mayor es la resolución de la técnica utilizada para la reconstrucción topográfia, el coste y el tiempo necesario para cubrir una cierta superficie se incrementa. En este trabajo se ha utilizado y comprobado la utilidad de la fotogrametría digital automática (Structure from Motion Multi-View Stereo: SfM-MVS), una técnica que puede alcanzar gran resolución a un bajo coste. Para ello se han llevado a cabo tres vuelos fotográficos para reconstruir el modelo digital de elevaciones (MDE) de un tramo de 6.5 km de la Rambla de la Viuda, un río efímero situado en el Levante español. Estos MDE fueron comparados entre sí para cuantificar las modificaciones producidas por dos inundaciones ocurridas en 2015. Se obtuvo una nube de puntos con una densidad máxima de 1295.4 pts/m2 y una resolución para el MDE de 3.11 cm/pixel. Los errores asociados a las tres topografías fueron de 0.101, 0.171 y 0.083 m, respectivamente. El nivel de detección de cambios (LoD) fue de ±0.198 y ±0.190 para los modelos digitales de las diferencias entre las superficies (DoDs), obtenidos entre el primero y el segundo, y el segundo y el tercer vuelo respectivamente. Como subproducto del procesamiento de las topografías se obtuvieron ortofotos con una resolución máxima de 2.50 cm/pix. En relación a la metodología se observó que para un flujo de trabajo eficiente y una reproducción topográfica fidedigna es crucial seguir estas recomendaciones: (1) mantener un alto grado de superposición entre fotografías, manteniendo un valor de número de proyecciones superior a 20, (2) distribuir el plan de vuelo en dos pasadas a dos alturas distintas, para ganar resolución a la par que superposición y (3) el uso de puntos de control fijos al sustrato rocoso, para evitar la gran inversión de tiempo que supone desplegar los puntos de control en el campo. Desde un punto de vista geomorfológico, el resultado de los DoDs reveló la presencia de un patrón discontinuo compuesto por una sucesión de secuencias de erosión-deposito. Una de estas secuencias fue estudiada en detalle desvelando que la aparición, evolución de estas secuencias y su distribución a lo largo del cauce está íntimamente relacionada con la extracción de gravas. Los volúmenes netos de sedimentos movilizados por cada uno de los eventos revelaron un comportamiento muy distinto entre los eventos. La primera inundación (Flood #1) produjo una erosión neta de (−)3118 m3 mientras que el segundo evento de inundación (Flood #2) produjo una acumulación de (+)787 m3 ambos calculados dentro del margen de confianza del 95%. Según los DoDs y las ortofotos, las principales fuentes de removilización de sedimento estuvieron asociadas a la erosión del lecho y los márgenes. Hecho que fue aparentemente desencadenado por la migración aguas arriba del knickpoint generado por la extracción de gravas. Analizando por separado cada uno de los eventos de inundación (con picos de 98 y 80 m3/s, respectivamente) se vio que la respuesta sedimentaria no fue proporcional a su magnitud. Este comportamiento puede estar relacionado con los diferentes volúmenes de agua aportados (32.5 y 7.1 hm3), diferencias en la duración del hidrograma (24 y 11 días), diferentes umbrales de transporte de cada inundación o a fenómenos de histéresis en sentido horario del transporte asociado a la disponibilidad sedimentaria. Este trabajo concluye que la fotogrametría digital automática (SfM-MVS) funciona especialmente bien para la detección de cambios en ríos efímeros dada su escasa vegetación y ausencia de agua. De esta manera, puede ser una herramienta propicia para comprender los patrones morfológicos asociados a las inundaciones y a los impactos humanos sobre los cauces.

Palabras clave

Lecho de gravas Detección de cambios geomorfológicos SFM-MVS Río efímero Nivel de detección 

Notes

Acknowledgements

This paper has been funded by the Spanish Ministry of Economy and Competitiveness through the projects PALEOMED (CGL2014-58127-C3-1-R) and EPHIMED (CGL2017-86839-C3-1-R). MC funded by the Spanish FPI scholarship (BES-2012-056723), PA has received funding from the Academy of Finland, the Strategic Research Council (COMBAT project, Grant 293389). Special thanks to Alicia Castán for field support during flights and Laura Barrios for statistical support. Also to Patricia Mañana-Borrazas, Alejandro Güimil-Fariña, César Parcero-Oubiña and Pastor Fábrega-Álvarez for the course TDDG2016 and their help with PhotoScan software. I also thank the editor, Pedro Alfaro, and two unknown reviewers for kindly providing constructive comments and selflessly improve this paper.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.National Museum of Natural SciencesSpanish Research Council (CSIC)MadridSpain
  2. 2.Department of Geography and GeologyUniversity of Turku/Turun YliopistoTurkuFinland

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