Systematic analysis of uncertainty in 2D flood inundation models

Willis, Thomas; Wright, Nigel; Sleigh, Andrew

doi:10.1016/j.envsoft.2019.104520

Cited by 31 publications

(27 citation statements)

References 41 publications

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“…The qualitative level of topographical parameters derived from Digital Terrain Model (DTM)/DEM and subsequently entered into hydrodynamic models results in the associated uncertainties of these models (DEM), as confirmed in the work of S. P. Wechsler [45] and M. Podhorányi [46]. In connection with the examining of uncertainties in topographic data and their impact on the modeling of flood scenarios in built-up areas, is in work Willis et al [47] an important aspect of model selection and its parameters specific to the problem and input data.…”

Section: Overview Of Spatial Data Quality Aspectsmentioning

confidence: 76%

Evaluation of Selected Sub-Elements of Spatial Data Quality on 3D Flood Event Modeling: Case Study of Prešov City, Slovakia

et al. 2020

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Weather-related disasters represent a major threat to the sustainable development of society. This study focuses directly on the assessment of the state of spatial information quality for the needs of hydrodynamic modeling. Based on the selected procedures and methods designed for the collection and processing of spatial information, the aim of this study was to assess their qualitative level of suitability for 3D flood event modeling in accordance with the Infrastructure for Spatial Information in the European Community (INSPIRE) Directive. In the evaluation process we entered geodetic measurements and the digital relief model 3.5 (DMR 3.5) available for the territory of the Slovak Republic. The result of this study is an assessment of the qualitative analysis on three levels: (i) main channel and surrounding topography data from geodetic measurements; (ii) digital relief model; and (iii) hydrodynamic/hydraulic modeling. The qualitative aspect of the input data shows the sensitivity of a given model to changes in the input data quality condition. The average spatial error in the determination of a point’s position was calculated as 0.017 m of all measured points along a watercourse and its slope foot and slope edge. Although the declared accuracy of DMR 3.5 is assumed to be ±2.50 m, in some of the sections in the selected area there were differences in elevation up to 4.79 m. For this reason, we needed a combination of DMR 3.5 and geodetic measurements to refine the input model for the process of hydrodynamic modeling. The quality of the hydrological data for the monitored N annual flow levels was of fourth-class reliability for the selected area.

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Section: Overview Of Spatial Data Quality Aspectsmentioning

confidence: 76%

Evaluation of Selected Sub-Elements of Spatial Data Quality on 3D Flood Event Modeling: Case Study of Prešov City, Slovakia

et al. 2020

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“…Estimating a flood HR usually involves measuring a product quantity of a water depth h to a velocity magnitude V (Costabile, Costanzo, de Lorenzo, & Macchione, 2020). As in Kvočka, Falconer, and Bray (2016) and Willis, Wright, and Sleigh (2019), the degree of flood HR is estimated as HR = ( V + 0.5) × h , with V = max (| u |, | v |), following the risk to people method developed for the UK Environment Agency (2006). Pedestrian agents therefore consider a flood risk state and a walking speed state based on the information of the flood HR they receive at their local and temporal location.…”

Section: Methodsmentioning

confidence: 99%

Agent‐based simulator of dynamic flood‐people interactions

Shirvani

Kesserwani

Richmond

2021

J Flood Risk Management

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This article presents a simulator for the modelling of the two‐way interactions between flooding and people. The simulator links a hydrodynamic model to a pedestrian model in a single agent‐based modelling platform, Flexible Large‐scale Agent Modelling Environment for the Graphical Processing Unit (FLAMEGPU). Dynamic coupling is achieved by the simultaneous update and exchange of information across multiple agent types. Behavioural rules and states for the pedestrian agents are proposed to account for the pedestrians' presence/actions in/to floodwater. These are based on a commonly used hazard rate (HR) metric to evaluate the risk states of people in floodwater, and by considering two roles for the pedestrians: evacuees or responders for action during or before the flood event, respectively. The potential of the simulator is demonstrated in a case study of a flooded and busy shopping centre for two scenarios: (a) during a flood evacuation and (b) pre‐flood intervention to deploy a sandbag barrier. The evacuation scenario points to changes in floodwater hydrodynamics around congested areas, which either worsen (by 5–8%) or lessen (by 25%) the HR. The intervention scenario demonstrates the utility of the simulator to select an optimal barrier height and number of responders for safe and effective deployment. Accompanying details for software accessibility are provided.

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Section: Model Behavior Sensitivity Analysis and Model Uncertaintymentioning

confidence: 99%

“…Uncertainty analysis is often applied for flood hazard models to give a quantitative statement about the accuracy of the modeling results [46]. In Willis et al ( 2019) [46] there can be found an example of the application of an uncertainty analysis for different sources of uncertainty. He gives the classification by [47] of four different types of uncertainty from 1. input data, 2. parameter, 3. model structure and 4. model assessment.…”

Section: Model Behavior Sensitivity Analysis and Model Uncertaintymentioning

confidence: 99%

A Systematic Analysis of the Interaction between Rain-on-Grid-Simulations and Spatial Resolution in 2D Hydrodynamic Modeling

David

Schmalz

2021

Water

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A large number of 2D models were originally developed as 1a models for the calculation of water levels along the main course of a river. Due to their development as 2D distributed models, the majority have added precipitation as a source term. The models can now be used as quasi-2D hydrodynamic rainfall–runoff models (‘HDRRM’). Within the direct rainfall method (‘DRM’), there is an approach, referred to as ‘rain-on-grid’, in which input precipitation is applied to the entire catchment area. The study contains a systematic analysis of the model behavior of HEC-RAS (‘Hydrologic Engineering Center—River Analysis System’) with a special focus on spatial resolution. The rain-on-grid approach is applied in a small, ungauged, low-mountain-range study area (Messbach catchment, 2.13 km2) in Central Germany. Suitable model settings and recommendations on model discretization and parametrization are derived therefrom. The sensitivity analysis focuses on the influence of the mesh resolution’s interaction with the spatial resolution of the underlying terrain model (‘subgrid’). Furthermore, the sensitivity of the parameters interplaying with spatial resolution, like the height of the laminar depth, surface roughness, model specific filter-settings and the precipitation input-data temporal distribution, is analyzed. The results are evaluated against a high-resolution benchmark run, and further criteria, such as 1. Nash–Sutcliffe efficiency, 2. water-surface elevation, 3. flooded area, 4. volume deficit, 5. volume balance and 6. computational time. The investigation showed that, based on the chosen criteria for this size and type of catchment, a mesh resolution between 3 m to 5 m, in combination with a DEM resolution from 0.25 m to 1 m, are recommendable. Furthermore, we show considerable scale effects on flooded areas for coarser meshing, due to low water levels in relation to topographic height.

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Systematic analysis of uncertainty in 2D flood inundation models

Cited by 31 publications

References 41 publications

Evaluation of Selected Sub-Elements of Spatial Data Quality on 3D Flood Event Modeling: Case Study of Prešov City, Slovakia

Evaluation of Selected Sub-Elements of Spatial Data Quality on 3D Flood Event Modeling: Case Study of Prešov City, Slovakia

Agent‐based simulator of dynamic flood‐people interactions

A Systematic Analysis of the Interaction between Rain-on-Grid-Simulations and Spatial Resolution in 2D Hydrodynamic Modeling

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