Details
| Original language | English |
|---|---|
| Pages (from-to) | 1529-1540 |
| Number of pages | 12 |
| Journal | Natural Hazards and Earth System Science |
| Volume | 9 |
| Issue number | 4 |
| Publication status | Published - 31 Aug 2009 |
| Externally published | Yes |
Abstract
Ensemble forecasts aim at framing the uncertainties of the potential future development of the hydrometeorological situation. A probabilistic evaluation can be used to communicate forecast uncertainty to decision makers. Here an operational system for ensemble based flood forecasting is presented, which combines forecasts from the European COSMO-LEPS, SRNWP-PEPS and COSMO-DE prediction systems. A multi-model lagged average superensemble is generated by recombining members from different runs of these meteorological forecast systems. A subset of the super-ensemble is selected based on a priori model weights, which are obtained from ensemble calibration. Flood forecasts are simulated by the conceptual rainfall-runoff-model ArcEGMO. Parameter uncertainty of the model is represented by a parameter ensemble, which is a priori generated from a comprehensive uncertainty analysis during model calibration. The use of a computationally efficient hydrological model within a flood management system allows us to compute the hydro-meteorological model chain for all members of the sub-ensemble. The model chain is not re-computed before new ensemble forecasts are available, but the probabilistic assessment of the output is updated when new information from deterministic short range forecasts or from assimilation of measured data becomes available. For hydraulic modelling, with the desired result of a probabilistic inundation map with high spatial resolution, a replacement model can help to overcome computational limitations. A prototype of the developed framework has been applied for a case study in the Mulde river basin. However these techniques, in particular the probabilistic assessment and the derivation of decision rules are still in their infancy. Further research is necessary and promising.
ASJC Scopus subject areas
- Earth and Planetary Sciences(all)
- General Earth and Planetary Sciences
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In: Natural Hazards and Earth System Science, Vol. 9, No. 4, 31.08.2009, p. 1529-1540.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Assessing uncertainties in flood forecasts for decision making
T2 - Prototype of an operational flood management system integrating ensemble predictions
AU - Dietrich, J.
AU - Schumann, A. H.
AU - Redetzky, M.
AU - Walther, J.
AU - Denhard, M.
AU - Wang, Y.
AU - Pfützner, B.
AU - Büttner, U.
PY - 2009/8/31
Y1 - 2009/8/31
N2 - Ensemble forecasts aim at framing the uncertainties of the potential future development of the hydrometeorological situation. A probabilistic evaluation can be used to communicate forecast uncertainty to decision makers. Here an operational system for ensemble based flood forecasting is presented, which combines forecasts from the European COSMO-LEPS, SRNWP-PEPS and COSMO-DE prediction systems. A multi-model lagged average superensemble is generated by recombining members from different runs of these meteorological forecast systems. A subset of the super-ensemble is selected based on a priori model weights, which are obtained from ensemble calibration. Flood forecasts are simulated by the conceptual rainfall-runoff-model ArcEGMO. Parameter uncertainty of the model is represented by a parameter ensemble, which is a priori generated from a comprehensive uncertainty analysis during model calibration. The use of a computationally efficient hydrological model within a flood management system allows us to compute the hydro-meteorological model chain for all members of the sub-ensemble. The model chain is not re-computed before new ensemble forecasts are available, but the probabilistic assessment of the output is updated when new information from deterministic short range forecasts or from assimilation of measured data becomes available. For hydraulic modelling, with the desired result of a probabilistic inundation map with high spatial resolution, a replacement model can help to overcome computational limitations. A prototype of the developed framework has been applied for a case study in the Mulde river basin. However these techniques, in particular the probabilistic assessment and the derivation of decision rules are still in their infancy. Further research is necessary and promising.
AB - Ensemble forecasts aim at framing the uncertainties of the potential future development of the hydrometeorological situation. A probabilistic evaluation can be used to communicate forecast uncertainty to decision makers. Here an operational system for ensemble based flood forecasting is presented, which combines forecasts from the European COSMO-LEPS, SRNWP-PEPS and COSMO-DE prediction systems. A multi-model lagged average superensemble is generated by recombining members from different runs of these meteorological forecast systems. A subset of the super-ensemble is selected based on a priori model weights, which are obtained from ensemble calibration. Flood forecasts are simulated by the conceptual rainfall-runoff-model ArcEGMO. Parameter uncertainty of the model is represented by a parameter ensemble, which is a priori generated from a comprehensive uncertainty analysis during model calibration. The use of a computationally efficient hydrological model within a flood management system allows us to compute the hydro-meteorological model chain for all members of the sub-ensemble. The model chain is not re-computed before new ensemble forecasts are available, but the probabilistic assessment of the output is updated when new information from deterministic short range forecasts or from assimilation of measured data becomes available. For hydraulic modelling, with the desired result of a probabilistic inundation map with high spatial resolution, a replacement model can help to overcome computational limitations. A prototype of the developed framework has been applied for a case study in the Mulde river basin. However these techniques, in particular the probabilistic assessment and the derivation of decision rules are still in their infancy. Further research is necessary and promising.
UR - http://www.scopus.com/inward/record.url?scp=76149088451&partnerID=8YFLogxK
U2 - 10.5194/nhess-9-1529-2009
DO - 10.5194/nhess-9-1529-2009
M3 - Article
AN - SCOPUS:76149088451
VL - 9
SP - 1529
EP - 1540
JO - Natural Hazards and Earth System Science
JF - Natural Hazards and Earth System Science
SN - 1561-8633
IS - 4
ER -