Upscaling the shallow water model with a novel roughness formulation

Özgen, Ilhan; Teuber, Katharina; Simons, Franz; Liang, Dongfang; Hinkelmann, Reinhard

doi:10.1007/s12665-015-4726-7

Cited by 20 publications

(16 citation statements)

References 43 publications

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“…Acknowledging the salient importance of the inundation ratio Λ, upscaled roughness formulations have been proposed with inundation ratio-dependent Manning coecients [36].…”

Section: Momentum Source Termsmentioning

confidence: 99%

Flux closures and source term models for shallow water models with depth-dependent integral porosity

Guinot

Delenne

Rousseau

et al. 2018

Advances in Water Resources

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A two-dimensional shallow water model with depth-dependent porosity is presented. The purpose is the coarse grid simulation of shallow ows over complex topographies and geometries. Two ux closures are examined: the Integral Porosity (IP) and Dual Integral Porosity (DIP) closures. Energy losses are described using a subgrid scale model that accounts for bottom and wall friction, transient momentum dissipation and energy losses induced by obstacle submersion. A complete wave propagation property analysis is provided for the IP and DIP closures, yielding more accurate numerical stability constraints than published previously. Five computational examples are presented, including transients in compound and meandering channels, urban dambreak problems with building submersion and runo over variable microtopography. The ability of the model to deal with subgrid-scale features is conrmed. The DIP ux is shown to be superior to the IP closure. The transient dissipation term is essential in reproducing the eect of obstacles and microtopography. Distinguishing between the building wall-and building roof-induced friction is seen to be essential. The model is validated successfully against a scale model experimental dataset for the submersion of a coastal urban area by a tsunami wave.

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“…Acknowledging the salient importance of the inundation ratio Λ, upscaled roughness formulations have been proposed with inundation ratio-dependent Manning coecients [36].…”

Section: Momentum Source Termsmentioning

confidence: 99%

Flux closures and source term models for shallow water models with depth-dependent integral porosity

Guinot

Delenne

Rousseau

et al. 2018

Advances in Water Resources

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“…In shallow water modeling of river hydraulics (Özgen et al, 2013;Kesserwani and Liang, 2015), urban flooding (Liang, 2010;Mignot et al, 2006), urban runoff (Cea et al, 2010;Liang et al, 2007;Liang et al, 2015) and rainfall-runoff on natural environments (Mügler et al, 2011;Özgen et al, 2015;Simons et al, 2014;Viero et al 2014), the topographical features have a large influence on the numerical results. The availability of digital elevation data has increased significantly due to recent improvements in surveying technology, notably laser scanning and light detection and ranging (LIDAR) technologies, which provide high-resolution data sets at relatively low cost (Gessner et al, 2014;Gourbesville, 2009).…”

Section: Introductionmentioning

confidence: 99%

Urban flood modeling using shallow water equations with depth-dependent anisotropic porosity

Özgen

Zhao

Liang

et al. 2016

Journal of Hydrology

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Hinkelmann, R. (2016). Urban flood modeling using shallow water equations with depth-dependent anisotropic porosity. Journal of Hydrology, 541, 1165Hydrology, 541, -1184Hydrology, 541, . https://doi.org/10.1016Hydrology, 541, /j.jhydrol.2016 Özgen, I.; Zhao, J.; Liang, D.; Hinkelmann, R.Urban flood modeling using shallow water equations with depth-dependent anisotropic porosity The shallow water model with anisotropic porosity conceptually takes into account the unresolved subgrid-scale features, e.g. microtopography or buildings. This enables computationally efficient simulations that can be run on coarser grids, whereas reasonable accuracy is maintained via the introduction of porosity. This article presents a novel numerical model for the depth-averaged equations with anisotropic porosity. The porosity is calculated using the probability mass function of the subgrid-scale features in each cell and updated in each time step. The model is tested in a one-dimensional theoretical benchmark before being evaluated against measurements and high-resolution predictions in three case studies: a dam-break over a triangular bottom sill, a dam-break through an idealized city and a rainfall-runoff event in an idealized urban catchment. The physical processes could be approximated relatively well with the anisotropic porosity shallow water model. The computational resolution influences the porosities calculated at the cell edges and therefore has a large influence on the quality of the solution. The computational time decreased significantly, on average three orders of magnitude, in comparison to the classical high-resolution shallow water model simulation.

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“…It should also be noticed that while many studies have pointed out the importance of a hydrological network [19], vegetation resistance [18,20,21,42], and infiltration [23] in flow modeling, these factors were not considered here, and could explain some errors in our simulation. However, the integration of these factors in hydrological modeling remains challenging for three reasons.…”

Section: Model Performance and Limitationsmentioning

confidence: 99%

“…Conversely, LiDAR-based digital terrain models (DTM) provide high-resolution spatial information, and have been found to be suitable for the characterization of subtle ground altimetry variations in wetlands [15]. As a result, many studies have pointed out the strong influence of microtopography that has been derived from LiDAR DTMs and shallow patterns in overland flow simulations [16][17][18][19][20][21]. As an example, a LiDAR-based DTM was used to successfully assess the maximum water storage capacity in wetlands [22], model a storm event at the watershed scale [23], and simulate the discontinuous puddle-to-puddle overland flow dynamics for infiltrating surfaces [24].…”

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confidence: 99%

Daily Monitoring of Shallow and Fine-Grained Water Patterns in Wet Grasslands Combining Aerial LiDAR Data and In Situ Piezometric Measurements

et al. 2018

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The real-time monitoring of hydrodynamics in wetlands at fine spatial and temporal scales is crucial for understanding ecological and hydrological processes. The key interest of light detection and ranging (LiDAR) data is its ability to accurately detect microtopography. However, how such data may account for subtle wetland flooding changes in both space and time still needs to be tested, even though the degree to which these changes impact biodiversity patterns is of upmost importance. This study assesses the use of 1 m × 1 m resolution aerial LiDAR data in combination with in situ piezometric measurements in order to predict the flooded areas at a daily scale along a one-year hydrological period. The simulation was applied over 663 ha of wet grasslands distributed on six sites across the Marais Poitevin (France). A set of seven remote sensing images was used as the reference data in order to validate the simulation and provide a high overall accuracy (76-94%). The best results were observed in areas where the ditch density was low, whereas the highly drained sites showed a discrepancy with the predicted flooded areas. The landscape proportion index was calculated for the daily steps. The results highlighted the spatiotemporal dynamics of the shallow flooded areas. We showed that the differences in the flooding durations among the years were mainly related to a narrow contrast in topography (40 cm), and occurred over a short period of time (two months).Sustainability 2018, 10, 708 2 of 16 address these challenges, data with both spatial fine-scale and intensive temporal resolutions for the flooding proxies are required.There have been recent advances in Earth observation technology, including improved spatial, temporal, spectral, and radiometric resolutions [7]; however, the monitoring of shallow and fine-grained water pattern dynamics is still limited by the trade-off between either high-resolution images or images with intensive repetition over time [8]. As an example, some studies have shown an interest in SAR (Synthetic Aperture Radar) time series for monitoring flooded areas in wetlands at a regional scale [9,10], while other studies have underlined an interest in single-date light detection and ranging (LiDAR) intensity [11] or multispectral data [12] for detecting fine-scale spatial patterns in the flooding of shallow waters.Earth observation data can be used to calibrate and develop flood models [13]. Topographic data are crucial for hydraulic modeling, particularly in wetlands where the topography affects water runoff [1]. Topographic data are also the most significant source of uncertainty [14]; consequently, the broad digital elevation model (DEM) derived from SAR data such as SRTM (Shuttle Radar Topography Mission), or, more recently, TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurement) are only appropriate for large-scale flood studies [8]. Conversely, LiDAR-based digital terrain models (DTM) provide high-resolution spatial information, and have been found to be suitable for the characteri...

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Upscaling the shallow water model with a novel roughness formulation

Cited by 20 publications

References 43 publications

Flux closures and source term models for shallow water models with depth-dependent integral porosity

Flux closures and source term models for shallow water models with depth-dependent integral porosity

Urban flood modeling using shallow water equations with depth-dependent anisotropic porosity

Daily Monitoring of Shallow and Fine-Grained Water Patterns in Wet Grasslands Combining Aerial LiDAR Data and In Situ Piezometric Measurements

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