Validation of flood risk models: Current practice and possible improvements

Molinari, Daniela; Bruijn, K de; Castillo-Rodríguez, Jesica T.; Aronica, Giuseppe Tito; Bouwer, Laurens M.

doi:10.1016/j.ijdrr.2018.10.022

Cited by 107 publications

(85 citation statements)

References 59 publications

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“…Still, as for other damage models, the variability of parameters required by AGRIDE-c together with the limited availability of data for its validation (see Section 2) suggest the use of the model not in absolute terms (i.e. to evaluate the effectiveness of a specific measure), but as a tool to compare among several alternatives (Molinari et al 2019). 25…”

Section: Discussionmentioning

confidence: 99%

AGRIDE-c, a conceptual model for the estimation of flood damage to crops: development and implementation

Molinari¹,

Scorzini²,

Gallazzi³

et al. 2019

Preprint

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This paper presents AGRIDE-c, a conceptual model for the assessment of flood damage to crops. All available knowledge on damage mechanisms triggered by inundation phenomena is systematised in a usable and consistent tool, with 10 the main strength represented by the integration of physical damage assessment with the evaluation of its economic consequences on farmers' gross product. This allows AGRIDE-c to be used to guide the flood damage assessment process in different geographical and economic contexts, as demonstrated by the example provided in this study for the Po Plain (North of Italy). The development and implementation of the model highlighted that a thorough understanding and modelling of damage mechanisms to crops allows for comprehensive cost-benefit analyses of risk mitigation actions, and is a powerful tool 15 to orient farmers' behaviour towards more resilient damage alleviation practices.

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Section: Discussionmentioning

confidence: 99%

AGRIDE-c, a conceptual model for the estimation of flood damage to crops: development and implementation

Molinari¹,

Scorzini²,

Gallazzi³

et al. 2019

Preprint

Self Cite

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“…We argue that a sound flood risk assessment should be based on a high-resolution-individual building-based-building asset value map because of the high spatial heterogeneity of flood hazards.Röthlisberger and colleagues [13] compared five building value models for flood risk analysis, and proposed that estimating exposed-building values should be based on individual buildings rather than on areas of land-use types. Higher quality exposure data is needed to perform validations of flood risk models [14].However, for flood risk analysis, quite often a spatial mismatch exists between hazard intensity data (e.g., inundation depth), which are frequently modelled on a high-resolution raster level, and exposure data, which are usually only available at coarse census units (e.g., counties) or aggregated land-use/land cover classes [14][15][16][17]. Flood risk assessments often invest much more in hazard modelling of water depths or inundation areas at a spatially explicit raster level [18,19], while only a limited number of studies have explicitly focused on the estimations of assets and their disaggregation to overcome the spatial mismatch between the quality of hazard and exposure data [20][21][22][23].…”

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confidence: 99%

“…Röthlisberger and colleagues [13] compared five building value models for flood risk analysis, and proposed that estimating exposed-building values should be based on individual buildings rather than on areas of land-use types. Higher quality exposure data is needed to perform validations of flood risk models [14].…”

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confidence: 99%

Building Asset Value Mapping in Support of Flood Risk Assessments: A Case Study of Shanghai, China

Wang

et al. 2019

Sustainability

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Exposure is an integral part of any natural disaster risk assessment, and damage to buildings is one of the most important consequence of flood disasters. As such, estimates of the building stock and the values at risk can assist in flood risk management, including determining the damage extent and severity. Unfortunately, little information about building asset value, and especially its spatial distributions, is readily available in most countries. This is certainly true in China, given that the statistical data on building floor area (BFA) is collected by administrative entities (i.e. census level). To bridge the gap between census-level BFA data and geo-coded building asset value data, this article introduces a method for building asset value mapping, using Shanghai as an example. This method consists of a census-level BFA disaggregation (downscaling) by means of a building footprint map extracted from high-resolution remote sensing data, combined with LandScan population density grid data and a financial appraisal of building asset values. Validation with statistical data and field survey data confirms that the method can produce good results, but largely constrained by the resolution of the population density grid used. However, compared with other models with no disaggregation in flood exposure assessment that involves Shanghai, the building asset value mapping method used in this study has a comparative advantage, and it will provide a quick way to produce a building asset value map for regional flood risk assessments. We argue that a sound flood risk assessment should be based on a high-resolution-individual building-based-building asset value map because of the high spatial heterogeneity of flood hazards.Röthlisberger and colleagues [13] compared five building value models for flood risk analysis, and proposed that estimating exposed-building values should be based on individual buildings rather than on areas of land-use types. Higher quality exposure data is needed to perform validations of flood risk models [14].However, for flood risk analysis, quite often a spatial mismatch exists between hazard intensity data (e.g., inundation depth), which are frequently modelled on a high-resolution raster level, and exposure data, which are usually only available at coarse census units (e.g., counties) or aggregated land-use/land cover classes [14][15][16][17]. Flood risk assessments often invest much more in hazard modelling of water depths or inundation areas at a spatially explicit raster level [18,19], while only a limited number of studies have explicitly focused on the estimations of assets and their disaggregation to overcome the spatial mismatch between the quality of hazard and exposure data [20][21][22][23]. Meanwhile, the quality of the exposure data is one of the most important uncertainties in flood risk assessments [24][25][26][27]. Because of the high spatial resolution of water inundation depth estimation, which is mainly a function of topography [28,29], flood risk assessments are much more sensi...

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“…The energy dissipation rate is enhanced by effective operation rules to stabilize the downstream flow regimes.Rapidly varied flow having large streamline curvatures exerts non-hydrostatic pressure distribution over the dam discharge structure surface. The enormous three-dimensional (3D) effect of dam discharge flow reveals that two-dimensional (2D) assumptions in solving such problems are inadequate [13][14][15]. 3D numerical simulation comes into sight gradually because it can yield a high-resolution outcome and vividly display the variation of physical parameters in the flow field [16].…”

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confidence: 99%

Three-Dimensional Numerical Simulation of Dam Discharge and Flood Routing in Wudu Reservoir

Rong

Zhang

Peng

et al. 2019

Water

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The main objectives of the present work are to investigate the hydraulic characteristics of the dam discharge flow and its impact downstream. Building information modeling technology is adopted to generate the terrain entity and hydraulic structures. The calculation of the dam discharge and flood routing simulation is achieved by employing Reynolds-Averaged Navier-Stokes equations with the RNG k-ε eddy viscosity model for its turbulence closure, as well as the Volume of Fluid method. An urban flood experiment and the field measurement records are utilized and validated the model accuracy. The flow field is obtained to assess the dam working conditions under different water levels. The results show that the maximum downstream flow depth, the maximum discharge capacity and the hydraulic jump length under normal water level is 18.6 m, 13,800 m 3 /s, and 108 m, respectively. The dam satisfies the safety demand under different water levels but close attention should be paid to the dam foundation, especially around the incident points of the discharge flow. Complex turbulent flow patterns, including collision, reflection, and vortices, are captured by three-dimensional simulation. The numerical simulation can assist the reservoir management vividly, so as to guarantee the stability of the dam operation. 2 of 20 experiments and confinements of empirical equations, researchers have attempted to adopt numerical simulation to check the working conditions of hydraulic structures [9-11]. Li et al. [12] simulated the joint flood discharge with the surface outlet and bottom outlet of a dam. The energy dissipation rate is enhanced by effective operation rules to stabilize the downstream flow regimes.Rapidly varied flow having large streamline curvatures exerts non-hydrostatic pressure distribution over the dam discharge structure surface. The enormous three-dimensional (3D) effect of dam discharge flow reveals that two-dimensional (2D) assumptions in solving such problems are inadequate [13][14][15]. 3D numerical simulation comes into sight gradually because it can yield a high-resolution outcome and vividly display the variation of physical parameters in the flow field [16]. In fact, 3D flood numerical simulation can be used to judge disaster losses in terms of visual experience. More concretely, it can qualitatively and quantitatively assess flood hazards and render visual reference for the development of flood control schemes, providing an important foundation for flood forecasting, dam design, and flood control system application [17]. The 3D simulation is approximately equivalent to the reality in terms of landform and boundary conditions. Therefore, the results are more accurate and convincing, and it is widely available in practical engineering [18][19][20][21].Dam discharge simulation requires an integrated tool that can handle both terrain entities and hydraulic structures. The building information modeling (BIM) method renders an effective approach for the generation of these models. It can provide detailed structure ...

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Validation of flood risk models: Current practice and possible improvements

Cited by 107 publications

References 59 publications

AGRIDE-c, a conceptual model for the estimation of flood damage to crops: development and implementation

AGRIDE-c, a conceptual model for the estimation of flood damage to crops: development and implementation

Building Asset Value Mapping in Support of Flood Risk Assessments: A Case Study of Shanghai, China

Three-Dimensional Numerical Simulation of Dam Discharge and Flood Routing in Wudu Reservoir

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