Usefulness and limitations of global flood risk models

Ward, Philip J.; Jongman, Brenden; Salamon, Peter; Simpson, Alanna Leigh; Bates, Paul; Groeve, Tom De; Muis, Sanne; Pérez, Erin Coughlan de; Rudari, Roberto; Trigg, Mark A.; Winsemius, Hessel

doi:10.1038/nclimate2742

Cited by 240 publications

(189 citation statements)

References 19 publications

(17 reference statements)

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“…At this point, GFDS and MODIS (see Section 2.1) are the only sources of satellite water detection which are publicly available with a daily time step. One separate development that may be a promising alternative is the progress in global flood forecasting models [39], such as GloFAS (Global Flood Awareness System) [40] and GFMS (Global Flood Monitoring System) [28]. The performance of these systems for taking DRM actions prior to flood events is currently being tested by the Uganda Red Cross, together with the German Red Cross and the Red Cross/Red Crescent Climate Centre [41].…”

Section: Gfds Satellite Informationmentioning

confidence: 99%

Early Flood Detection for Rapid Humanitarian Response: Harnessing Near Real-Time Satellite and Twitter Signals

Jongman

Wagemaker²,

Revilla-Romero

et al. 2015

IJGI

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115

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Humanitarian organizations have a crucial role in response and relief efforts after floods. The effectiveness of disaster response is contingent on accurate and timely information regarding the location, timing and impacts of the event. Here we show how two near-real-time data sources, satellite observations of water coverage and flood-related social media activity from Twitter, can be used to support rapid disaster response, using case-studies in the Philippines and Pakistan. For these countries we analyze information from disaster response organizations, the Global Flood Detection System (GFDS) satellite flood signal, and flood-related Twitter activity analysis. The results demonstrate that these sources of near-real-time information can be used to gain a quicker understanding of the location, the timing, as well as the causes and impacts of floods. In terms of location, we produce daily impact maps based on both satellite information and social media, which can dynamically and rapidly outline the affected area during a disaster. In terms of timing, the results show that GFDS and/or Twitter signals flagging ongoing or upcoming flooding are regularly available one to several days before the event was reported to humanitarian organizations. 2247In terms of event understanding, we show that both GFDS and social media can be used to detect and understand unexpected or controversial flood events, for example due to the sudden opening of hydropower dams or the breaching of flood protection. The performance of the GFDS and Twitter data for early detection and location mapping is mixed, depending on specific hydrological circumstances (GFDS) and social media penetration (Twitter). Further research is needed to improve the interpretation of the GFDS signal in different situations, and to improve the pre-processing of social media data for operational use.

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Section: Gfds Satellite Informationmentioning

confidence: 99%

Early Flood Detection for Rapid Humanitarian Response: Harnessing Near Real-Time Satellite and Twitter Signals

Jongman

Wagemaker²,

Revilla-Romero

et al. 2015

IJGI

Self Cite

115

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“…Since recent research showed that flood inundation can easily affect large areas, in particular neighbouring river basins (Jongman et al, 2014), it is vital that flood hazard models can simulate the relevant processes over large domains. Applying such large-scale models has the additional advantage of facilitating the identification of risk hotspots and providing critical insight into data-scarce areas (Ward et al, 2015). In fact, there are already a number of global-scale inundation models available Pappenberger et al, 2012;Sampson et al, 2015;Winsemius et al, 2013;Yamazaki et al, 2011), differing in their process descriptions and computational engine.…”

Section: Introductionmentioning

confidence: 99%

GLOFRIM v1.0 – A globally applicable computational framework for integrated hydrological–hydrodynamic modelling

et al. 2017

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Abstract. We here present GLOFRIM, a globally applicable computational framework for integrated hydrologicalhydrodynamic modelling. GLOFRIM facilitates spatially explicit coupling of hydrodynamic and hydrologic models and caters for an ensemble of models to be coupled. It currently encompasses the global hydrological model PCR-GLOBWB as well as the hydrodynamic models Delft3D Flexible Mesh (DFM; solving the full shallow-water equations and allowing for spatially flexible meshing) and LISFLOOD-FP (LFP; solving the local inertia equations and running on regular grids). The main advantages of the framework are its open and free access, its global applicability, its versatility, and its extensibility with other hydrological or hydrodynamic models. Before applying GLOFRIM to an actual test case, we benchmarked both DFM and LFP for a synthetic test case. Results show that for sub-critical flow conditions, discharge response to the same input signal is near-identical for both models, which agrees with previous studies. We subsequently applied the framework to the Amazon River basin to not only test the framework thoroughly, but also to perform a first-ever benchmark of flexible and regular grids on a large-scale. Both DFM and LFP produce comparable results in terms of simulated discharge with LFP exhibiting slightly higher accuracy as expressed by a Kling-Gupta efficiency of 0.82 compared to 0.76 for DFM. However, benchmarking inundation extent between DFM and LFP over the entire study area, a critical success index of 0.46 was obtained, indicating that the models disagree as often as they agree. Differences between models in both simulated discharge and inundation extent are to a large extent attributable to the gridding techniques employed. In fact, the results show that both the numerical scheme of the inundation model and the gridding technique can contribute to deviations in simulated inundation extent as we control for model forcing and boundary conditions. This study shows that the presented computational framework is robust and widely applicable. GLOFRIM is designed as open access and easily extendable, and thus we hope that other large-scale hydrological and hydrodynamic models will be added. Eventually, more locally relevant processes would be captured and more robust model inter-comparison, benchmarking, and ensemble simulations of flood hazard on a large scale would be allowed for.

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“…The availability of real-time operational systems for assessing potential consequences of forecasted events would be a substantial advance in helping emergency response (Molinari et al, 2013), and indeed flood risk forecasts are increasingly being requested by end users of early warning systems (Emerton et al, 2016;Ward et al, 2015). At a local scale, the joint evaluation of flood probabilities and consequences may not only increase preparedness of emergency services but also allow cost-benefit considerations for planning and prioritizing response measures (e.g.…”

Section: Introductionmentioning

confidence: 99%

An operational procedure for rapid flood risk assessment in Europe

Dottori

Kalaš

Salamon

et al. 2017

Nat. Hazards Earth Syst. Sci.

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Abstract. The development of methods for rapid flood mapping and risk assessment is a key step to increase the usefulness of flood early warning systems and is crucial for effective emergency response and flood impact mitigation. Currently, flood early warning systems rarely include realtime components to assess potential impacts generated by forecasted flood events. To overcome this limitation, this study describes the benchmarking of an operational procedure for rapid flood risk assessment based on predictions issued by the European Flood Awareness System (EFAS). Daily streamflow forecasts produced for major European river networks are translated into event-based flood hazard maps using a large map catalogue derived from highresolution hydrodynamic simulations. Flood hazard maps are then combined with exposure and vulnerability information, and the impacts of the forecasted flood events are evaluated in terms of flood-prone areas, economic damage and affected population, infrastructures and cities.An extensive testing of the operational procedure has been carried out by analysing the catastrophic floods of May 2014 in Bosnia-Herzegovina, Croatia and Serbia. The reliability of the flood mapping methodology is tested against satellite-based and report-based flood extent data, while modelled estimates of economic damage and affected population are compared against ground-based estimations. Finally, we evaluate the skill of risk estimates derived from EFAS flood forecasts with different lead times and combinations of probabilistic forecasts. Results highlight the potential of the real-time operational procedure in helping emergency response and management.

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Usefulness and limitations of global flood risk models

Abstract: Global flood risk models were developed to identify risk hotspots in a world with increasing flood occurrence. Here we assess the ability and limitations of the current models and suggest what is needed moving forward. Table 1 | Links to models, tools, and programmes discussed in the text.

Cited by 240 publications

References 19 publications

Early Flood Detection for Rapid Humanitarian Response: Harnessing Near Real-Time Satellite and Twitter Signals

Early Flood Detection for Rapid Humanitarian Response: Harnessing Near Real-Time Satellite and Twitter Signals

GLOFRIM v1.0 – A globally applicable computational framework for integrated hydrological–hydrodynamic modelling

An operational procedure for rapid flood risk assessment in Europe

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