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Albrecht Weerts
Researcher at Wageningen University and Research Centre
Publications - 161
Citations - 4246
Albrecht Weerts is an academic researcher from Wageningen University and Research Centre. The author has contributed to research in topics: Flood forecasting & Flood myth. The author has an hindex of 31, co-authored 141 publications receiving 3382 citations. Previous affiliations of Albrecht Weerts include University of Duisburg-Essen & University of Amsterdam.
Papers
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Journal ArticleDOI
Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities
Yuqiong Liu,Yuqiong Liu,Albrecht Weerts,Martyn P. Clark,Harrie-Jan Hendricks Franssen,Sujay V. Kumar,Sujay V. Kumar,Hamid Moradkhani,Dong Jun Seo,Dirk Schwanenberg,Paul Smith,A. I. J. M. van Dijk,N. van Velzen,Minxue He,Haksu Lee,Haksu Lee,Seong Jin Noh,Oldrich Rakovec,P. Restrepo +18 more
TL;DR: It is recommended that cost-effective transition of hydrologic DA from research to operations should be helped by developing community-based, generic modeling and DA tools or frameworks, and through fostering collaborative efforts among hydrologics modellers, DA developers, and operational forecasters.
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Particle filtering and ensemble Kalman filtering for state updating with hydrological conceptual rainfall-runoff models
Albrecht Weerts,Ghada El Serafy +1 more
TL;DR: For low flows, EnKF outperforms both particle filters, because it is less sensitive to misspecification of the model and uncertainties, and these methods are feasible and easy to implement in real flood forecasting systems.
Journal ArticleDOI
Continental and global scale flood forecasting systems
Rebecca Emerton,Rebecca Emerton,Elisabeth Stephens,Florian Pappenberger,Thomas C. Pagano,Albrecht Weerts,Andrew W. Wood,Peter Salamon,James D. Brown,Niclas Hjerdt,Chantal Donnelly,Calum Baugh,Hannah Cloke +12 more
TL;DR: In this paper, the current state of operational large scale flood forecasting is discussed, including probabilistic forecasting of floods using ensemble prediction systems, describing similarities and differences in their approaches to forecasting floods at the global and continental scale.
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Estimation of predictive hydrological uncertainty using quantile regression: examples from the national flood forecasting system (England and Wales)
TL;DR: In this paper, a technique is presented for assessing the predictive uncertainty of rainfall runoff and hydraulic forecasts, based on retrospective Quantile Regression of hindcasted water level forecasts and forecast errors.
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Post-processing ECMWF precipitation and temperature ensemble reforecasts for operational hydrologic forecasting at various spatial scales ☆
TL;DR: In this article, the ECMWF temperature and precipitation ensemble reforecasts are evaluated for biases in the mean, spread and forecast probabilities, and how these biases propagate to streamflow ensemble forecasts.