Efficient incorporation of channel cross-section geometry uncertainty into regional and global scale flood inundation models

Neal, Jeffrey; Odoni, N. A.; Trigg, Mark A.; Freer, J. E.; García-Pintado, Javier; Mason, David C.; Wood, Melissa; Bates, Paul

doi:10.1016/j.jhydrol.2015.07.026

Cited by 92 publications

(81 citation statements)

References 39 publications

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“…It is logical therefore to see changes in r producing a marked change in flood extent. Channel roughness changes by contrast have an impact more on flow velocities, consequently impacting on the timing of flood wave propagation through the channel (as discussed in Neal et al, 2015). This would have a more spatially diffuse impact on flood extent that is barely perceptible here.…”

Section: Csi Scoresmentioning

confidence: 77%

Calibration of channel depth and friction parameters in the LISFLOOD-FP hydraulic model using medium-resolution SAR data and identifiability techniques

Wood

Hostache

Neal

et al. 2016

Hydrol. Earth Syst. Sci.

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Abstract. Single satellite synthetic aperture radar (SAR) data are now regularly used to estimate hydraulic model parameters such as channel roughness, depth and water slope. However, despite channel geometry being critical to the application of hydraulic models and poorly known a priori, it is not frequently the object of calibration. This paper presents a unique method to simultaneously calibrate the bankfull channel depth and channel roughness parameters within a 2-D LISFLOOD-FP hydraulic model using an archive of moderate-resolution (150 m) ENVISAT satellite SAR-derived flood extent maps and a binary performance measure for a 30 × 50 km domain covering the confluence of the rivers Severn and Avon in the UK. The unknown channel parameters are located by a novel technique utilising the information content and dynamic identifiability analysis (DY-NIA) (Wagener et al., 2003) of single and combinations of SAR flood extent maps to find the optimum satellite images for model calibration. Highest information content is found in those SAR flood maps acquired near the peak of the flood hydrograph, and improves when more images are combined. We found that model sensitivity to variation in channel depth is greater than for channel roughness and a successful calibration for depth could only be obtained when channel roughness values were confined to a plausible range. The calibrated reach-average channel depth was within 0.9 m (16 % error) of the equivalent value determined from river crosssection survey data, demonstrating that a series of moderateresolution SAR data can be used to successfully calibrate the depth parameters of a 2-D hydraulic model.

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Section: Csi Scoresmentioning

confidence: 77%

Calibration of channel depth and friction parameters in the LISFLOOD-FP hydraulic model using medium-resolution SAR data and identifiability techniques

Wood

Hostache

Neal

et al. 2016

Hydrol. Earth Syst. Sci.

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“…However, for some rivers, it might be impossible to model the observed discharge-water-level relationships with such simplistic cross sections. The approach can be adapted for a slightly more complex representation of cross-section geometry, as for example suggested by Neal et al (2015).…”

Section: Cross-section Calibrationmentioning

confidence: 99%

Application of CryoSat-2 altimetry data for river analysis and modelling

Schneider

Godiksen

Villadsen

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. Availability of in situ river monitoring data, especially of data shared across boundaries, is decreasing, despite growing challenges for water resource management across the entire globe. This is especially valid for the case study of this work, the Brahmaputra Basin in South Asia. Commonly, satellite altimeters are used in various ways to provide information about such river basins. Most missions provide virtual station time series of water levels at locations where their repeat orbits cross rivers. CryoSat-2 is equipped with a new type of altimeter, providing estimates of the actual ground location seen in the reflected signal. It also uses a drifting orbit, challenging conventional ways of processing altimetry data to river water levels and their incorporation in hydrologic-hydrodynamic models. However, CryoSat-2 altimetry data provides an unprecedentedly high spatial resolution. This paper suggests a procedure to (i) filter CryoSat-2 observations over rivers to extract water-level profiles along the river, and (ii) use this information in combination with a hydrologic-hydrodynamic model to fit the simulated water levels with an accuracy that cannot be reached using information from globally available digital elevation models (DEMs) such as from the Shuttle Radar Topography Mission (SRTM) only. The filtering was done based on dynamic river masks extracted from Landsat imagery, providing spatial and temporal resolutions high enough to map the braided river channels and their dynamic morphology. This allowed extraction of river water levels over previously unmonitored narrow stretches of the river. In the Assam Valley section of the Brahmaputra River, CryoSat-2 data and Envisat virtual station data were combined to calibrate cross sections in a 1-D hydrodynamic model of the river. The hydrologichydrodynamic model setup and calibration are almost exclusively based on openly available remote sensing data and other global data sources, ensuring transferability of the developed methods. They provide an opportunity to achieve forecasts of both discharge and water levels in a poorly gauged river system.

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“…Thus, for different subregions of the basin, channel cross-sectional dimensions derived from the same formulae and parameters contained biases of various magnitudes. Hydrologic modeling results were demonstrated to be sensitive to channel cross-sectional dimensions and shapes (Getirana et al, 2013;Neal et al, 2015;Paiva et al, 2013a;Yamazaki et al, 2011), so improving the representation of channel morphology could be important. In this study, the basin-wide parameters for the channel geometry formulae were refined for various subregions of the Amazon Basin based on local channel morphology information to better represent the spatial variability in channel morphology.…”

mentioning

confidence: 99%

Modeling surface water dynamics in the Amazon Basin using MOSART-Inundation v1.0: impacts of geomorphological parameters and river flow representation

Luo

Leung

et al. 2017

Geosci. Model Dev.

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Abstract. In the Amazon Basin, floodplain inundation is a key component of surface water dynamics and plays an important role in water, energy and carbon cycles. The Model for Scale Adaptive River Transport (MOSART) was extended with a macroscale inundation scheme for representing floodplain inundation. The extended model, named MOSART-Inundation, was used to simulate surface hydrology of the entire Amazon Basin. Previous hydrologic modeling studies in the Amazon Basin identified and addressed a few challenges in simulating surface hydrology of this basin, including uncertainties of floodplain topography and channel geometry, and the representation of river flow in reaches with mild slopes. This study further addressed four aspects of these challenges. First, the spatial variability of vegetationcaused biases embedded in the HydroSHEDS digital elevation model (DEM) data was explicitly addressed. A vegetation height map of about 1 km resolution and a land cover dataset of about 90 m resolution were used in a DEM correction procedure that resulted in an average elevation reduction of 13.2 m for the entire basin and led to evident changes in the floodplain topography. Second, basin-wide empirical formulae for channel cross-sectional dimensions were refined for various subregions to improve the representation of spatial variability in channel geometry. Third, the channel Manning roughness coefficient was allowed to vary with the channel depth, as the effect of riverbed resistance on river flow generally declines with increasing river size. Lastly, backwater effects were accounted for to better represent river flow in mild-slope reaches. The model was evaluated against in situ streamflow records and remotely sensed Envisat altimetry data and Global Inundation Extent from Multi-Satellites (GIEMS) inundation data. In a sensitivity study, seven simulations were compared to evaluate the impacts of the five modeling aspects addressed in this study. The comparisons showed that representing floodplain inundation could significantly improve the simulated streamflow and river stages. Refining floodplain topography, channel geometry and Manning roughness coefficients, as well as accounting for backwater effects had notable impacts on the simulated surface water dynamics in the Amazon Basin. The understanding obtained in this study could be helpful in improving modeling of surface hydrology in basins with evident inundation, especially at regional to continental scales.

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Efficient incorporation of channel cross-section geometry uncertainty into regional and global scale flood inundation models

Cited by 92 publications

References 39 publications

Calibration of channel depth and friction parameters in the LISFLOOD-FP hydraulic model using medium-resolution SAR data and identifiability techniques

Calibration of channel depth and friction parameters in the LISFLOOD-FP hydraulic model using medium-resolution SAR data and identifiability techniques

Application of CryoSat-2 altimetry data for river analysis and modelling

Modeling surface water dynamics in the Amazon Basin using MOSART-Inundation v1.0: impacts of geomorphological parameters and river flow representation

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