FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2155487242> ?p ?o ?g. }

• W2155487242 endingPage "286" @default.
• W2155487242 startingPage "275" @default.
• W2155487242 abstract "Abstract. Flood forecasts are essential to issue reliable flood warnings and to initiate flood control measures on time. The accuracy and the lead time of the predictions for head waters primarily depend on the meteorological forecasts. Ensemble forecasts are a means of framing the uncertainty of the potential future development of the hydro-meteorological situation. This contribution presents a flood management strategy based on probabilistic hydrological forecasts driven by operational meteorological ensemble prediction systems. The meteorological ensemble forecasts are transformed into discharge ensemble forecasts by a rainfall-runoff model. Exceedance probabilities for critical discharge values and probabilistic maps of inundation areas can be computed and presented to decision makers. These results can support decision makers in issuing flood alerts. The flood management system integrates ensemble forecasts with different spatial resolution and different lead times. The hydrological models are controlled in an adaptive way, mainly depending on the lead time of the forecast, the expected magnitude of the flood event and the availability of measured data. The aforementioned flood forecast techniques have been applied to a case study. The Mulde River Basin (South-Eastern Germany, Czech Republic) has often been affected by severe flood events including local flash floods. Hindcasts for the large scale extreme flood in August 2002 have been computed using meteorological predictions from both the COSMO-LEPS ensemble prediction system and the deterministic COSMO-DE local model. The temporal evolution of a) the meteorological forecast uncertainty and b) the probability of exceeding flood alert levels is discussed. Results from the hindcast simulations demonstrate, that the systems would have predicted a high probability of an extreme flood event, if they would already have been operational in 2002. COSMO-LEPS showed a reasonably good performance within a lead time of 2 to 3 days. Some of the deterministic very short-range forecast initializations were able to predict the dynamics of the event, but others underpredicted rainfall. Thus a lagged average ensemble approach is suggested. The findings from the case study support the often proposed added value of ensemble forecasts and their probabilistic evaluation for flood management decisions." @default.
• W2155487242 created "2016-06-24" @default.
• W2155487242 creator A5006171538 @default.
• W2155487242 creator A5018447036 @default.
• W2155487242 creator A5065049373 @default.
• W2155487242 creator A5069261081 @default.
• W2155487242 creator A5070085126 @default.
• W2155487242 creator A5074768458 @default.
• W2155487242 creator A5079304223 @default.
• W2155487242 date "2008-03-19" @default.
• W2155487242 modified "2023-10-16" @default.
• W2155487242 title "Combination of different types of ensembles for the adaptive simulation of probabilistic flood forecasts: hindcasts for the Mulde 2002 extreme event" @default.
• W2155487242 cites W1439583882 @default.
• W2155487242 cites W1505423953 @default.
• W2155487242 cites W1527594523 @default.
• W2155487242 cites W1603903339 @default.
• W2155487242 cites W1971398942 @default.
• W2155487242 cites W1971553499 @default.
• W2155487242 cites W1984350169 @default.
• W2155487242 cites W1988218448 @default.
• W2155487242 cites W2010686465 @default.
• W2155487242 cites W2012316213 @default.
• W2155487242 cites W2013765062 @default.
• W2155487242 cites W2027130724 @default.
• W2155487242 cites W2030134440 @default.
• W2155487242 cites W2035733695 @default.
• W2155487242 cites W2060742029 @default.
• W2155487242 cites W2065265184 @default.
• W2155487242 cites W2069049955 @default.
• W2155487242 cites W2070133622 @default.
• W2155487242 cites W2070683189 @default.
• W2155487242 cites W2073799710 @default.
• W2155487242 cites W2087883388 @default.
• W2155487242 cites W2124738823 @default.
• W2155487242 cites W2133144322 @default.
• W2155487242 cites W2141394518 @default.
• W2155487242 cites W2147108096 @default.
• W2155487242 cites W2151545251 @default.
• W2155487242 cites W2157098139 @default.
• W2155487242 cites W2158840489 @default.
• W2155487242 cites W2160288696 @default.
• W2155487242 cites W2163710018 @default.
• W2155487242 cites W2171174555 @default.
• W2155487242 cites W2280457841 @default.
• W2155487242 doi "https://doi.org/10.5194/npg-15-275-2008" @default.
• W2155487242 hasPublicationYear "2008" @default.
• W2155487242 type Work @default.
• W2155487242 sameAs 2155487242 @default.
• W2155487242 citedByCount "28" @default.
• W2155487242 countsByYear W21554872422012 @default.
• W2155487242 countsByYear W21554872422013 @default.
• W2155487242 countsByYear W21554872422014 @default.
• W2155487242 countsByYear W21554872422016 @default.
• W2155487242 countsByYear W21554872422017 @default.
• W2155487242 countsByYear W21554872422020 @default.
• W2155487242 countsByYear W21554872422021 @default.
• W2155487242 countsByYear W21554872422022 @default.
• W2155487242 crossrefType "journal-article" @default.
• W2155487242 hasAuthorship W2155487242A5006171538 @default.
• W2155487242 hasAuthorship W2155487242A5018447036 @default.
• W2155487242 hasAuthorship W2155487242A5065049373 @default.
• W2155487242 hasAuthorship W2155487242A5069261081 @default.
• W2155487242 hasAuthorship W2155487242A5070085126 @default.
• W2155487242 hasAuthorship W2155487242A5074768458 @default.
• W2155487242 hasAuthorship W2155487242A5079304223 @default.
• W2155487242 hasBestOaLocation W21554872421 @default.
• W2155487242 hasConcept C119898033 @default.
• W2155487242 hasConcept C120417685 @default.
• W2155487242 hasConcept C127313418 @default.
• W2155487242 hasConcept C144133560 @default.
• W2155487242 hasConcept C153294291 @default.
• W2155487242 hasConcept C154945302 @default.
• W2155487242 hasConcept C162853370 @default.
• W2155487242 hasConcept C166957645 @default.
• W2155487242 hasConcept C183195422 @default.
• W2155487242 hasConcept C205649164 @default.
• W2155487242 hasConcept C2781468064 @default.
• W2155487242 hasConcept C39432304 @default.
• W2155487242 hasConcept C41008148 @default.
• W2155487242 hasConcept C49204034 @default.
• W2155487242 hasConcept C49937458 @default.
• W2155487242 hasConcept C74256435 @default.
• W2155487242 hasConcept C83002819 @default.
• W2155487242 hasConceptScore W2155487242C119898033 @default.
• W2155487242 hasConceptScore W2155487242C120417685 @default.
• W2155487242 hasConceptScore W2155487242C127313418 @default.
• W2155487242 hasConceptScore W2155487242C144133560 @default.
• W2155487242 hasConceptScore W2155487242C153294291 @default.
• W2155487242 hasConceptScore W2155487242C154945302 @default.
• W2155487242 hasConceptScore W2155487242C162853370 @default.
• W2155487242 hasConceptScore W2155487242C166957645 @default.
• W2155487242 hasConceptScore W2155487242C183195422 @default.
• W2155487242 hasConceptScore W2155487242C205649164 @default.
• W2155487242 hasConceptScore W2155487242C2781468064 @default.
• W2155487242 hasConceptScore W2155487242C39432304 @default.
• W2155487242 hasConceptScore W2155487242C41008148 @default.
• W2155487242 hasConceptScore W2155487242C49204034 @default.
• W2155487242 hasConceptScore W2155487242C49937458 @default.

• next