Imperial College London
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ProfessorWouterBuytaert

Faculty of Engineering, Department of Civil and Environmental Engineering

Professor in Hydrology and Water Resources
 
 
 
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Contact

 

+44 (0)20 7594 1329w.buytaert Website

 
 
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Assistant

 

Miss Judith Barritt +44 (0)20 7594 5967

 
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Location

 

403ASkempton BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Ocio:2017:10.1002/2016WR020225,
author = {Ocio, D and Le, Vine N and Westerberg, I and Pappenberger, F and Buytaert, W},
doi = {10.1002/2016WR020225},
journal = {Water Resources Research},
pages = {4197--4213},
title = {The role of rating curve uncertainty in real-time flood forecasting},
url = {http://dx.doi.org/10.1002/2016WR020225},
volume = {53},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Data assimilation has been widely tested for flood forecasting, although its use in operational systems is mainly limited to a simple statistical error correction. This can be due to the complexity involved in making more advanced formal assumptions about the nature of the model and measurement errors. Recent advances in the definition of rating curve uncertainty allow estimating a flow measurement error that includes both aleatory and epistemic uncertainties more explicitly and rigorously than in the current practice. The aim of this study is to understand the effect such a more rigorous definition of the flow measurement error has on real-time data assimilation and forecasting. This study, therefore, develops a comprehensive probabilistic framework that considers the uncertainty in model forcing data, model structure, and flow observations. Three common data assimilation techniques are evaluated: (1) Autoregressive error correction, (2) Ensemble Kalman Filter, and (3) Regularized Particle Filter, and applied to two locations in the flood-prone Oria catchment in the Basque Country, northern Spain. The results show that, although there is a better match between the uncertain forecasted and uncertain true flows, there is a low sensitivity for the threshold exceedances used to issue flood warnings. This suggests that a standard flow measurement error model, with a spread set to a fixed flow fraction, represents a reasonable trade-off between complexity and realism. Standard models are therefore recommended for operational flood forecasting for sites with well-defined stage-discharge curves that are based on a large range of flow observations.
AU  - Ocio,D
AU  - Le,Vine N
AU  - Westerberg,I
AU  - Pappenberger,F
AU  - Buytaert,W
DO  - 10.1002/2016WR020225
EP  - 4213
PY  - 2017///
SN  - 0043-1397
SP  - 4197
TI  - The role of rating curve uncertainty in real-time flood forecasting
T2  - Water Resources Research
UR  - http://dx.doi.org/10.1002/2016WR020225
UR  - http://hdl.handle.net/10044/1/51281
VL  - 53
ER  -
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