Parallelization of a two-dimensional flood inundation model based on domain decomposition

Flood modelling often involves prediction of the inundated extent over large spatial and temporal scales. As the dimensionality of the system and the complexity of the problems increase, the need to obtain quick solutions becomes a priority. However, for large-scale problems or situations where fine resolution data is required, it is often not possible or practical to run the model on a single computer in a reasonable timeframe. This paper presents the development and testing of a parallelized 2D diffusion-based flood inundation model (FloodMap-Parallel) which enables largescale simulations to be run on distributed multi-processors. The model has been applied to three locations in the UK with different flow and topographical boundary conditions. The accuracy of the parallelized model and its computational efficiency have been tested. The predictions obtained from the parallelized model match those obtained from the serialized simulations. The computational performance of the model has been investigated in relation to the granularity of the domain decomposition, the total number of cells and the domain decomposition configuration pattern. Results show that the parallelized model is more effective with simulations of low granularity and a large number of cells. The large communication overhead associated with the potential loadimbalance between sub-domains is a major bottleneck in utilizing this approach with higher domain granularity

From flooding to finance: NHS ambulance‐assisted evacuations of care home residents in Norfolk and Suffolk, UK

Focusing on the counties of Norfolk and Suffolk (UK), this investigation examines the effect of coastal and fluvial flooding on the use of ambulance service vehicles in the assisted evacuation of care home residents and quantifies the cost of this service to the NHS under flood conditions. This was completed using GIS Network Analyst functions to identify the impacts of flood probability (high: 1 in 30, medium: 1 in 30 to 1 in 100, and low: 1 in 100 to 1 in 1000) and target ambulance response-times (7, 18, 120, and 180 min) on ambulance service area, road network accessibility, the number of vulnerable care homes and their accessibility, the appropriateness of pre-identified evacuation routes, and the drive-time based evacuation cost to the National Health Service (NHS). The results indicate that approximately 68 care homes and 2,320 residents in Norfolk and Suffolk are at risk of inundation, and care home accessibility, in addition to ambulance service area, decreases with shorter ambulance response-times and lower flood probabilities. Additionally, the use of pre-identified evacuation routes, by the ambulance service, promotes efficient navigation between ambulance stations, care homes, and rest centres, but can unfavourably cause network clustering if unmanaged. In association with these routes, an estimated cost of evacuation based on ambulance drivetime was calculated at £34,000–£42,000 depending on flood probability. The importance of this research is highlighted by the current lack of identified flood evacuation and accessibility maps for emergency responder use, and the associated lack of evacuation cost estimations to be used by the government and NHS to budget for aid assistance during these natural disasters. Therefore, the application of this approach at a national level in the flood emergency planning process would be beneficial to promote strategic efficiency and financial preparedness of ambulance services for the purpose of ambulance-assisted flood evacuations

Interactions between subgrid-scale resolution, feature representation and grid-scale resolution in flood inundation modelling

Numerical modelling of flood inundation over large and complex floodplains often requires mesh resolutions coarser than the structural features (e.g. buildings) that are known to influence the inundation process. Recent research has shown that this mismatch is not well represented by conventional roughness treatments but that finer scale features can be represented through porositybased sub grid scale treatments. This paper develops this work by testing the interactions between feature representation, sub grid scale resolution and mesh resolution. It uses as the basis for this testing a 2D diffusion-based flood inundation model which is applied to a 2004 flood event in a topologically-complex upland floodplain in northern England. Results showed serious degradation of model predictions without explicit representation of features like walls. Inclusion of such features through raising mesh cell elevations where intersected by a feature resulted in a major improvement in model predictions in terms of reduced inundation extent. To make such treatments physically realistic, and notably so that the full potential for floodplain storage is included, it was shown that a sub grid scale treatment also needed to be included. The effects of this combined treatment was the recovery of more plausible floodplain friction values as well as a sensitivity to friction that allows for more effective representation of floodplain friction effects such as vegetation

Modelling urban rainfall-runoff responses using an experimental, two-tiered physical modelling environment [Abstract]

Modelling urban rainfall-runoff responses using an experimental, two-tiered physical modelling environment [Abstract

Modelling the impact of land subsidence on urban pluvial flooding: a case study of downtown Shanghai, China.

This paper presents a numerical analysis of pluvial flooding to evaluate the impact of land subsidence on flood risks in urban contexts using a hydraulic model (FloodMap-HydroInundation2D). The pluvial flood event of August 2011 in Shanghai, China is used for model calibration and simulation. Evolving patterns of inundation (area and depth) are assessed over four time periods (1991, 1996, 2001 and 2011) for the downtown area, given local changes in topography and rates of land subsidence of up to 27mm/yr. The results show that land subsidence can lead to non-linear response of flood characteristics. However, the impact on flood depths is generally minor (<5cm) and limited to areas with lowest-lying topographies because of relatively uniform patterns of subsidence and micro-topographic variations at the local scale. Nonetheless, the modelling approach tested here may be applied to other cities where there are more marked rates of subsidence and/or greater heterogeneity in the depressed urban surface. In these cases, any identified hot-spots of subsidence and focusing of pluvial flooding may be targeted for adaptation interventions

Validating city-scale surface water flood modelling using crowd-sourced data

Surface water and surface water related flood modelling at the city-scale is challenging due to a range of factors including the availability of subsurface data and difficulty in deriving runoff inputs and surcharge for individual storm sewer inlets. Most of the research undertaken so far has been focusing on local-scale predictions of sewer surcharge induced surface flooding, using a 1D/1D or 1D/2D coupled storm sewer and surface flow model. In this study, we describe the application of an urban hydro-inundation model (FloodMap-HydroInundation2D) to simulate surface water related flooding arising from extreme precipitation at the city-scale. This approach was applied to model an extreme storm event that occurred on 12 August 2011 in the city of Shanghai, China, and the model predictions were compared with a ‘crowd-sourced’ dataset of flood incidents. The results suggest that the model is able to capture the broad patterns of inundated areas at the city-scale. Temporal evaluation also demonstrates a good level of agreement between the reported and predicted flood timing. Due to the mild terrain of the city, the worst-hit areas are predicted to be topographic lows. The spatio-temporal accuracy of the precipitation and micro-topography are the two critical factors that affect the prediction accuracies. Future studies could be directed towards making more accurate and robust predictions of water depth and velocity using higher quality topographic, precipitation and drainage capacity information

Coupled modeling of storm surge and coastal inundation: a case study in New York City during Hurricane Sandy

In this paper we describe a new method of modeling coastal inundation arising from storm surge by coupling a widely used storm surge model (ADCIRC) and an urban flood inundation model (FloodMap). This is the first time the coupling of such models is implemented and tested using real events. The method offers a flexible and efficient procedure for applying detailed ADCIRC storm surge modeling results along the coastal boundary (with typical resolution of ∼100 m) to FloodMap for fine resolution inundation modeling ( 70 m). In further testing, we explored the effects of mesh resolution and roughness specification. Results agree with previous studies that fine resolution is essential for capturing intricate flow paths and connectivity in urban topography. While the specification of roughness is more challenging for urban environments, it may be empirically optimized. The successful coupling of ADCIRC and FloodMap models for fine-resolution coastal inundation modeling unlocks the potential for undertaking large numbers of probabilistically-based synthetic surge events for street-level risk analysis

The motivations, enablers and barriers for voluntary participation in an online crowdsourcing platform

This paper examines the phenomena of online crowdsourcing from the perspectives of both volunteers and the campaign coordinator of Tomnod – an online mapping project that uses crowdsourcing to identify objects and places in satellite images. A mixed-methods approach was used to study the enablers and barriers to participation, taking into consideration the whole spectrum of volunteers. The results show broad diversity in online volunteers, both in their demographics and the factors affecting their voluntary participation. The majority are older than 50 years and many – particularly the most active volunteers – have disabilities or long term health problems. The personal circumstances of participants are highlighted as a major factor affecting involvement in campaigns. Like many other platforms, altruism is a key motivator, yet many participants are more interested in the quality of their data and the impact it has on the ground. For many participants of online crowdsourcing campaigns, their involvement is strongly linked to the level of contact they have with campaign coordinators, both in the design of the platform and in providing feedback on the impact of their contributions

Evaluating the cascading impacts of sea level rise and coastal flooding on emergency response spatial accessibility in Lower Manhattan, New York City

This paper describes a scenario-based approach for evaluating the cascading impacts of sea level rise (SLR) and coastal flooding on emergency responses. The analysis is applied to Lower Manhattan, New York City, considering FEMA’s 100- and 500-year flood scenarios and New York City Panel on Climate Change (NPCC2)’s high-end SLR projections for the 2050s and 2080s, using the current situation as the baseline scenario. Service areas for different response timeframes (3-, 5- and 8-minute) and various traffic conditions are simulated for three major emergency responders (i.e. New York Police Department (NYPD), Fire Department, New York (FDNY) and Emergency Medical Service (EMS)) under normal and flood scenarios. The modelling suggests that coastal flooding together with SLR could result in proportionate but non-linear impacts on emergency services at the city scale, and the performance of operational responses is largely determined by the positioning of emergency facilities and the functioning of traffic networks. Overall, emergency service accessibility to the city is primarily determined by traffic flow speed. However, the situation is expected to be further aggravated during coastal flooding, with is set to increase in frequency and magnitude due to SLR

Evacuation planning with flood inundation as inputs

Recent flooding events happening in our city demonstrate frequency and severity of floods in the UK, highlighting the need to plan and prepare, and efficiently defend. Different from the numerous evacuation model and optimization algorithms, this paper aims to address flood evacuation planning with flood inundation as inputs. A dynamic flooding model and prediction to estimate the development of both surface water and flooding from rivers and watercourses has been fed into evacuation planning at various levels. A three-step approach is proposed. The first step is to identify assembly point designation. The second step is to find the candidate shortest path from each assembly point to all safe areas for all evacuees with consideration of possible inundation. The last step is to determine the optimal safe area for evacuees in the inundation area. The work presented in this paper has emphasized timing issue in evacuation planning. A case study is given to illustrate the use of the approach