Integration of SAR-derived river inundation areas, high-precision topographic data and a river flow model toward near real-time flood management

https://doi.org/10.1016/j.jag.2006.03.003Get rights and content

Abstract

Since several space-borne synthetic aperture radar (SAR) instruments providing high spatial resolutions and multi-polarisation capabilities will be mounted on satellites to be launched from 2006 onwards, radar imagery promises to become an indispensable asset for many environmental monitoring applications. Due to its all weather, day and night capabilities, SAR imagery presents obvious advantages over optical instruments, especially in flood management applications. To date, however, the coarse spatial resolution of available SAR datasets restricts the information that can be reliably extracted and processing techniques tend to be limited to binary floodplain segmentation into ‘flooded’ and ‘non flooded’ areas. It is the purpose of this paper to further improve the exploitation of SAR images in hydraulic modelling and near real-time crisis management by means of developing image processing methodologies that allow for the extraction of water levels at any point of the floodplain. As high-precision digital elevation models (DEM) produced, for instance, from airborne laser scanning become more readily available, methods can be exploited that combine SAR-derived flood extent maps and precise topographic data for retrieving water depth maps. In a case study of a well-documented flood event in January 2003 on the River Alzette, Grand Duchy of Luxembourg, a root mean squared error (R.M.S.E.) of 41 cm was obtained by comparing the SAR-derived water heights with surveyed high water marks that were collected during image acquisition. Water levels that were computed by a previously calibrated hydraulic model also suggest that the water surface profiles provided by the combined use of topographic data and SAR accurately reflect the true water line. The extraction of flooded areas within vegetated areas further demonstrates the usefulness of the proposed methodology.

Section snippets

Introduction and background

Repeated and increasingly frequent (e.g. Drogue et al., 2004) flood inundations occurring in many regions of the world and threatening human life and property enhance the need for effective flood risk management. The integration of various forms of geospatial information within a framework allows for flexible and timely analysis in the areas of flood forecasting, assessment and mitigation. Earth observation technologies and geographical information systems (GIS) are playing a large role in the

Study area and datasets

The SAR data used in this study relate to a flood prone area of the River Alzette, downstream of Luxembourg City (Grand Duchy of Luxembourg, Europe) (Fig. 1). The selected river floodplain with its surrounding villages has been subject to severe flooding in the past. The river reach between the gauging stations at Steinsel and Mersch has a length of approximately 10 km and its alluvial plain has an average width of about 300 m. A well-documented medium-sized flood event that occurred on 2 January

Hydraulic model description

Although believing any model is debatable as any model is subject to uncertainty, this study has assessed remotely sensed data uncertainties by turning the issue of model evaluation with remotely sensed data around. While most modellers in hydrology trust remotely sensed data to reliably evaluate or calibrate their models, in this study, on the contrary, the results of a hydraulic model conditioned on field data have been used as a benchmark test to evaluate SAR remote sensing methods that were

Methodology

Starting with the multi-look ASAR scene that is acquired at peak discharge during the 2 January 2003 flood and two digital elevation models with varying spatial resolution and accuracy, the flood depth mapping method follows the procedure illustrated in Fig. 3.

Results and discussion

This section outlines the application of the previously described methods to the VH-polarised ENVISAT ASAR image acquired during the 2 January 2003 flood in order to derive the water surface profile at peak discharge. The two images resulting from the thresholding and snake procedures were thematically classified into ‘flooded’ and ‘non-flooded’ (i.e. dry) pixels (Fig. 1). With the notable exception of some spurious ponds that were obtained by the thresholding method, the two inundation

Conclusion

This paper has proposed a methodology that acknowledges SAR based flood extent extraction uncertainty and goes beyond a mere descriptive exploitation of radar imagery. Two methods for accurate flood depth extraction are presented and validation with available evidence showed their usefulness for reliable flood stage estimation. With respect to traditional classification methods, substantial improvements were achieved. However, current sources of uncertainty like the coarse spatial resolution of

Acknowledgements

This study is supported by the ‘Ministère Luxembourgeois de la Culture, de l′Enseignement Supérieur et de la Recherche’. The authors would like to thank Jean-Paul Abadie at the French Space Agency (CNES) for supporting the research project and Florian Pappenberger at Lancaster University for helping with the model set-up. The DEM was made available by the ‘Ministère Luxembourgeois de l′Intérieur et de l′Aménagement du Territoire’. Matt Horritt from Bristol University is thanked for providing a

References (41)

  • D.E. Alsdorf et al.

    Amazon floodplain water level changes measured with interferometric SIR-C radar

    IEEE Trans. Geosci. Remote Sens.

    (2001)
  • M. Badji et al.

    Characterization of flood inundated areas and delineation of poor drainage soil using ERS-1 SAR imagery

    Hydrol. Process.

    (1997)
  • D.G. Barber et al.

    The role of earth observation technologies for flood mapping: a Manitoba case study

    Can. J. Remote Sens.

    (1997)
  • R. Barkau

    UNET one-dimensional unsteady flow through a full network of open channels, User's Manual, US Army Corps of Engineers

    (1997)
  • P.D. Bates

    Remote sensing and flood inundation modelling

    Hydrol. Process.

    (2004)
  • P.D. Bates et al.

    Integrating remote sensing observations of flood hydrology and hydraulic modelling

    Hydrol.Process.

    (1997)
  • G.R. Brackenridge et al.

    Orbital SAR remote sensing of a river flood wave

    Int. J. Remote Sens.

    (1998)
  • P.A. Brivio et al.

    Integration of remote sensing data and GIS for accurate mapping of flooded areas

    Int. J. Remote Sens.

    (2002)
  • G. Calabresi

    The use of ERS data for flood monitoring: an overall assessment

  • P. Coppin et al.

    Digital change detection methods in ecosystem monitoring: a review

    Int. J. Remote Sens.

    (2004)
  • Cited by (217)

    • Global and low-cost topographic data to support flood studies

      2023, Hydro-Meteorological Hazards, Risks, and Disasters
    • CARNet: An effective method for SAR image interference suppression

      2022, International Journal of Applied Earth Observation and Geoinformation
      Citation Excerpt :

      Synthetic aperture radar (SAR) is an advanced sensor with all-time, all-weather, high-resolution imaging, and long-range capability, widely applied in environmental mapping (Hashimoto et al., 2019; Wei et al., 2020, 2022b), catastrophe warning (Cai et al., 2022), battlefield detection (Fennell and Wishner, 1998), topographical inspection (Matgen et al., 2007; Li et al., 2022), and remote sensing (Chen et al., 2021; Recla and Schmitt, 2022).

    View all citing articles on Scopus
    View full text