On the use of SRTM and altimetry data for flood modeling in data‐sparse regions

Domeneghetti, Alessio

doi:10.1002/2015wr017967

Cited by 59 publications

(38 citation statements)

References 53 publications

(124 reference statements)

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“…It was a LiDAR technology that, in our case, used an infrared laser beam [40]. Similar poor results could be expected from other remote-sensing methods [8][9][10][11]. The error produced by these models depends on the size of the neglected flow area of the river channel [18,42].…”

Section: Thalweg Comparisonsupporting

confidence: 57%

“…DEMs obtained from satellites are commonly used on a global scale, but the spatial resolution of these models often does not meet the requirements of precise hydrodynamic modelling. The most commonly cited DEMs used for hydrodynamic modelling are the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and the Shuttle Radar Topography Mission (SRTM) [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

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River Bathymetry Model Based on Floodplain Topography

Bureš

Sychová

Máca

et al. 2019

Water

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An appropriate digital elevation model (DEM) is required for purposes of hydrodynamic modelling of floods. Such a DEM describes a river's bathymetry (bed topography) as well as its surrounding area. Extensive measurements for creating accurate bathymetry are time-consuming and expensive. Mathematical modelling can provide an alternative way for representing river bathymetry. This study explores new possibilities in mathematical depiction of river bathymetry. A new bathymetric model (Bathy-supp) is proposed, and the model's ability to represent actual bathymetry is assessed. Three statistical methods for the determination of model parameters were evaluated. The best results were achieved by the random forest (RF) method. A two-dimensional (2D) hydrodynamic model was used to evaluate the influence of the Bathy-supp model on the hydrodynamic modelling results. Also presented is a comparison of the proposed model with another state-of-the-art bathymetric model. The study was carried out on a reach of the Otava River in the Czech Republic. The results show that the proposed model's ability to represent river bathymetry exceeds that of his current competitor. Use of the bathymetric model may have a significant impact on improving the hydrodynamic model results.

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Section: Thalweg Comparisonsupporting

confidence: 57%

Section: Introductionmentioning

confidence: 99%

River Bathymetry Model Based on Floodplain Topography

Bureš

Sychová

Máca

et al. 2019

Water

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“…Monthly maximum values of floodplain inundation volumes and extent predicted by LISFLOODFP-HBV (i.e., using modeled streamflow; thereafter indicated with fv,HBV i and fe,HBV i as explained in Table 1) and LISFLOODFP-MEAS (i.e., using gauged streamflow; thereafter indicated with fv,G i and fe,G i as explained in Table 1) were compared by counting the number of flooded cells in the floodplain (i.e., river cells were omitted). A cell in the floodplain was flagged as flooded if the computed water depth was higher than 5 cm; a sensitivity analysis not shown in this paper demonstrated that the use of a different threshold value (1, 10, and 50 cm) did not affect the outcomes of the analysis presented thereafter, attributed to the inherently large vertical error variations in the SRTM topography (a discussion of these errors can be found in Domeneghetti, 2016). Discrepancies between simulated and measured cumulative input volumes (equations 1 and 2 in Table 1) over a lapse of time could lead to discrepancies in the prediction of floodplain dynamics.…”

Section: Definitions Symbolsmentioning

confidence: 91%

Challenges, Opportunities, and Pitfalls for Global Coupled Hydrologic‐Hydraulic Modeling of Floods

Grimaldi

Schumann

Shokri

et al. 2019

Water Resources Research

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Flood modeling at the regional to global scale is a key requirement for equitable emergency and land management. Coupled hydrological‐hydraulic models are at the core of flood forecasting and risk assessment models. Nevertheless, each model is subject to uncertainties from different sources (e.g., model structure, parameters, and inputs). Understanding how uncertainties propagate through the modeling cascade is essential to invest in data collection, increase flood modeling accuracy, and comprehensively communicate modeling results to end users. This study used a numerical experiment to quantify the propagation of errors when coupling hydrological and hydraulic models for multiyear flood event modeling in a large basin, with large morphological and hydrological variability. A coupled modeling chain consisting of the hydrological model Hydrologiska Byråns Vattenbalansavdelning and the hydraulic model LISFLOOD‐FP was used for the prediction of floodplain inundation in the Murray Darling Basin (Australia), from 2006 to 2012. The impacts of discrepancies between simulated and measured flow hydrographs on the predicted inundation patterns were analyzed by moving from small upstream catchments to large lowland catchments. The numerical experiment was able to identify areas requiring tailored modeling solutions or data collection. Moreover, this study highlighted the high sensitivity of inundation volume and extent prediction to uncertainties in flood peak values and explored challenges in time‐continuous modeling. Accurate flood peak predictions, knowledge of critical morphological features, and an event‐based modeling approach were outlined as pragmatic solutions for more accurate prediction of large‐scale spatiotemporal patterns of flood dynamics, particularly in the presence of low‐accuracy elevation data.

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“…Results show that naturally surveyed cross sections can be replaced by synthetic geometry cross sections of rectangular shape maintaining a correct representation of channel slope (i.e., thalweg profile) and channel conveyance (i.e., channel flow area). This result links this research with large scale flood hazard modeling based on the use of geomorphic laws or literature values for providing valid estimation of morphologic parameters (river/floodplain width, depth and flow area) associated to varying climatic, geomorphic and hydrologic regimes [20][21][22].…”

Section: Discussionmentioning

confidence: 54%

“…At larger scales, we posit that the use of geomorphological laws, depicting the hydraulic geometry of stream channels [17], may provide solid means for surrogating to the lack of surveyed river cross sections and bathymetric information. Geomorphic laws to support large scale hydraulic modeling are investigated as a mean for improving flood routing model performances [18][19][20][21][22]. Nevertheless, DTM-based terrain analysis for implementing the use of geomorphic laws for large scale hydraulic models is still a challenging and active research issue.This research investigated a floodplain DTM data processing procedure aiming to produce a coarse resolution bidimensional (2D) hydraulic model for fast inundation mapping.…”

mentioning

confidence: 99%

Floodplain Terrain Analysis for Coarse Resolution 2D Flood Modeling

Peña

Nardi

2018

Hydrology

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Hydraulic modeling is a fundamental tool for managing and mitigating flood risk. Developing low resolution hydraulic models, providing consistent inundation simulations with shorter running time, as compared to high-resolution modeling, has a variety of potential applications. Rapid coarse resolution flood models can support emergency management operations as well as the coupling of hydrodynamic modeling with climate, landscape and environmental models running at the continental scale. This work sought to investigate the uncertainties of input parameters and bidimensional (2D) flood wave routing simulation results when simplifying the terrain mesh size. A procedure for fluvial channel bathymetry interpolation and floodplain terrain data resampling was investigated for developing upscaled 2D inundation models. The proposed terrain processing methodology was tested on the Tiber River basin evaluating coarse (150 m) to very coarse (up to 700 m) flood hazard modeling results. The use of synthetic rectangular cross sections, replacing surveyed fluvial channel sections, was also tested with the goal of evaluating the potential use of geomorphic laws providing channel depth, top width and flow area when surveyed data are not available. Findings from this research demonstrate that fluvial bathymetry simplification and DTM resampling is feasible when the terrain data resampling and fluvial cross section interpolation are constrained to provide consistent representation of floodplain morphology, river thalweg profile and channel flow area. Results show the performances of low-resolution inundation simulations running in seconds while maintaining a consistent representation of inundation extents and depths.Hydrology 2018, 5, 52 2 of 16 to continental domains. Nonetheless, several challenges and uncertainties impact high-resolution numerical models of flood events [10,11]. The quest for always more accurate and detailed flood models prompts the need for investigations identifying an optimal balance between hydraulic model output details and topographic input data resolution [8].We argue that the downscaling of the flood model resolution-i.e., decreasing the size of the mesh elements that characterize the Digital Terrain Model (DTM) of the inundation domain-has to be properly developed considering the scale and properties of the flood event of interest. As a result, hyper-resolution flood models are not always strictly needed, especially when the size of the flood wave and associated dynamics (i.e., inundation depths and floodplain flow velocities) can be consistently analyzed by coarse resolution (i.e., from tens to hundreds of meters) numerical models. The upscaling of flood models represents a viable solution for flood risk assessment in several applications, especially when high resolution distributed topographic data and super-performing computers are not available or when a very fast inundation simulation is needed.Additionally, large scale flood models are still suffering the lack of effective EO-based fluvial bathymet...

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On the use of SRTM and altimetry data for flood modeling in data‐sparse regions

Cited by 59 publications

References 53 publications

River Bathymetry Model Based on Floodplain Topography

River Bathymetry Model Based on Floodplain Topography

Challenges, Opportunities, and Pitfalls for Global Coupled Hydrologic‐Hydraulic Modeling of Floods

Floodplain Terrain Analysis for Coarse Resolution 2D Flood Modeling

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