Near-Real-Time Assimilation of SAR-Derived Flood Maps for Improving Flood Forecasts
Hostache, R., Chini, M., Giustarini, L., Neal, J., Kavetski, D., Wood, M., ... Matgen, P. (2018). Near-Real-Time Assimilation of SAR-Derived Flood Maps for Improving Flood Forecasts. Water Resources Research, 54(8), 5516-5535. https://doi.org/10.1029/2017WR022205 Publisher's PDF, also known as Version of record License (if available): CC BY Link to published version (if available): 10.1029/2017WR022205 Link to publication record in Explore Bristol Research PDF-document This is the final published version of the article (version of record). It first appeared online via AGU at https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2017WR022205 . Please refer to any applicable terms of use of the publisher. University of Bristol - Explore Bristol Research General rights This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms Water Resources Research RESEARCH ARTICLE Near-Real-Time Assimilation of SAR-Derived Flood Maps 10.1029/2017WR022205 for Improving Flood Forecasts Key Points: • Probabilistic flood maps are derived Renaud Hostache1 , Marco Chini1, Laura Giustarini1, Jeffrey Neal2 , Dmitri Kavetski3 , from SAR images Melissa Wood1,2,4, Giovanni Corato1, Ramona-Maria Pelich1, and Patrick Matgen1 • Probabilistic flood maps are assimilated into a flood forecasting 1 model cascade Department of Environmental Research and Innovation, Luxembourg Institute of Science and Technology, Esch sur • Water level forecast quality improves Alzette, Luxembourg, 2School of Geographical Sciences, University of Bristol, Bristol, UK, 3School of Civil, Environmental substantially in the assimilation time and Mining Engineering, University of Adelaide, Adelaide, South Australia, Australia, 4Faculty of Geosciences, Utrecht steps, and benefits persist for hours University, Utrecht, Netherlands to days Correspondence to: Abstract Short- to medium-range flood forecasts are central to predicting and mitigating the impact R.
[Show full text]