Abstract
Quantifying flood hazard is an essential component of resilience planning, emergency response, and mitigation, including insurance. Traditionally undertaken at catchment and national scales, recently, efforts have intensified to estimate flood risk globally to better allow consistent and equitable decision making. Global flood hazard models are now a practical reality, thanks to improvements in numerical algorithms, global datasets, computing power, and coupled modelling frameworks. Outputs of these models are vital for consistent quantification of global flood risk and in projecting the impacts of climate change. However, the urgency of these tasks means that outputs are being used as soon as they are made available and before such methods have been adequately tested. To address this, we compare multi-probability flood hazard maps for Africa from six global models and show wide variation in their flood hazard, economic loss and exposed population estimates, which has serious implications for model credibility. While there is around 30-40% agreement in flood extent, our results show that even at continental scales, there are significant differences in hazard magnitude and spatial pattern between models, notably in deltas, arid/semi-arid zones and wetlands. This study is an important step towards a better understanding of modelling global flood hazard, which is urgently required for both current risk and climate change projections.
| Original language | English |
|---|---|
| Article number | 094014 |
| Number of pages | 10 |
| Journal | Environmental Research Letters |
| Volume | 11 |
| Issue number | 9 |
| Early online date | 14 Sept 2016 |
| DOIs | |
| Publication status | Published - Sept 2016 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 13 Climate Action
Keywords
- flood hazard
- flood risk
- global flood models
Fingerprint
Dive into the research topics of 'The credibility challenge for global fluvial flood risk analysis'. Together they form a unique fingerprint.Datasets
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Aggregated fluvial flood hazard output for six Global Flood Models for the African Continent.
Trigg, M. A. (Creator), Birch, C. E. (Creator), Neal, J. C. (Creator), Bates, P. D. (Creator), Smith, A. (Creator), Sampson, C. C. (Creator), Yamazaki, D. (Creator), Hirabayashi, Y. (Creator), Pappenberger, F. (Creator), Dutra, E. (Creator), Ward, P. J. (Creator), Winsemius, H. C. (Creator), Salamon, P. (Creator), Dottori, F. (Creator), Rudari, R. (Creator), Kappes, M. S. (Creator), Simpson, A. L. (Creator), Hadzilacos, G. (Creator) & Fewtrell, T. J. (Creator), University of Leeds, 2016
DOI: 10.5518/96, http://archive.researchdata.leeds.ac.uk/79/
Dataset
Profiles
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Professor Jeff Neal
- School of Geographical Sciences - Professor of Hydrology
- Cabot Institute for the Environment
- Hydrology
Person: Academic , Member
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