FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2893276853> ?p ?o ?g. }

• W2893276853 endingPage "123" @default.
• W2893276853 startingPage "114" @default.
• W2893276853 abstract "Accurate flood hazard assessments are crucial for adequate flood hazard mapping and hydraulic infrastructure design. The choice of an acceptable and cost-effective solution for such assessments depends upon the estimation of quantiles for different characteristics of floods, usually maximum discharges. However, gauge series usually have a limited time length and, thereby, quantile estimates associated to high return periods are subject to large uncertainties. To overcome this limitation, reconstructed flood series from historical, botanical or geological archives can be incorporated. In this study, we propose a novel approach that i) combines classic series of observations with paleodischarges (of the Rhône River) reconstructed from open lake sediments (Lake Bourget, Northwestern Alps, France) and ii) propagates uncertainties related to the reconstruction method during the estimation of extreme quantiles. A Bayesian approach is adopted in order to properly treat the non-systematic nature of the reconstructed flow data, as well as the uncertainties related to the reconstruction method. While this methodology has already been applied to reconstruct maximum discharges from historical documents, tree rings or fluvial sediments, similar applications need to be tested today on open lake sediments as they are one of the only archives that provide long and continuous paleoflood series. Reconstructed sediment volumes being subject to measurement errors, we evaluate and account for this uncertainty, along with the uncertainty related to the reconstruction method, the parametric uncertainty, and the rating-curve errors for systematic gauged flows by propagating these uncertainties through the modeling chain. Reconstructed maximum discharges appear to largely overcome values of observations, reaching values of approximately 2,600, 4,200, 2,450 and 2,500 m3/s in 1689, 1711, 1733 and 1737 respectively, which correspond to historically-known catastrophic floods. Extreme quantiles are estimated using direct measurements of maximum discharges (1853-2004) only and then combined to the sedimentary information (1650-2013). The comparison of the resulting estimates demonstrates the added value of the sedimentary information. In particular, the four historical catastrophic floods are very unlikely if only direct observations are considered for quantile estimations." @default.
• W2893276853 created "2018-10-05" @default.
• W2893276853 creator A5004556876 @default.
• W2893276853 creator A5017842655 @default.
• W2893276853 creator A5031545362 @default.
• W2893276853 date "2019-01-01" @default.
• W2893276853 modified "2023-09-25" @default.
• W2893276853 title "Flood hazard assessment of the Rhône River revisited with reconstructed discharges from lake sediments" @default.
• W2893276853 cites W1560205290 @default.
• W2893276853 cites W1586313814 @default.
• W2893276853 cites W1972183204 @default.
• W2893276853 cites W1986390233 @default.
• W2893276853 cites W1995778358 @default.
• W2893276853 cites W1996071089 @default.
• W2893276853 cites W2006605186 @default.
• W2893276853 cites W2056760934 @default.
• W2893276853 cites W2060094617 @default.
• W2893276853 cites W2062234223 @default.
• W2893276853 cites W2065955587 @default.
• W2893276853 cites W2075008680 @default.
• W2893276853 cites W2079628820 @default.
• W2893276853 cites W2087406343 @default.
• W2893276853 cites W2090435705 @default.
• W2893276853 cites W2101963528 @default.
• W2893276853 cites W2111183161 @default.
• W2893276853 cites W2120347659 @default.
• W2893276853 cites W2315151319 @default.
• W2893276853 cites W2479216701 @default.
• W2893276853 cites W2525109780 @default.
• W2893276853 cites W2568752782 @default.
• W2893276853 cites W2591782938 @default.
• W2893276853 cites W2750624391 @default.
• W2893276853 cites W2889081361 @default.
• W2893276853 doi "https://doi.org/10.1016/j.gloplacha.2018.09.010" @default.
• W2893276853 hasPublicationYear "2019" @default.
• W2893276853 type Work @default.
• W2893276853 sameAs 2893276853 @default.
• W2893276853 citedByCount "17" @default.
• W2893276853 countsByYear W28932768532019 @default.
• W2893276853 countsByYear W28932768532020 @default.
• W2893276853 countsByYear W28932768532021 @default.
• W2893276853 countsByYear W28932768532022 @default.
• W2893276853 crossrefType "journal-article" @default.
• W2893276853 hasAuthorship W2893276853A5004556876 @default.
• W2893276853 hasAuthorship W2893276853A5017842655 @default.
• W2893276853 hasAuthorship W2893276853A5031545362 @default.
• W2893276853 hasConcept C105795698 @default.
• W2893276853 hasConcept C109007969 @default.
• W2893276853 hasConcept C112959462 @default.
• W2893276853 hasConcept C114793014 @default.
• W2893276853 hasConcept C118671147 @default.
• W2893276853 hasConcept C127313418 @default.
• W2893276853 hasConcept C143724316 @default.
• W2893276853 hasConcept C151730666 @default.
• W2893276853 hasConcept C162324750 @default.
• W2893276853 hasConcept C166957645 @default.
• W2893276853 hasConcept C178790620 @default.
• W2893276853 hasConcept C185592680 @default.
• W2893276853 hasConcept C187320778 @default.
• W2893276853 hasConcept C187736073 @default.
• W2893276853 hasConcept C205649164 @default.
• W2893276853 hasConcept C2816523 @default.
• W2893276853 hasConcept C33923547 @default.
• W2893276853 hasConcept C39432304 @default.
• W2893276853 hasConcept C41008148 @default.
• W2893276853 hasConcept C49261128 @default.
• W2893276853 hasConcept C74256435 @default.
• W2893276853 hasConcept C76886044 @default.
• W2893276853 hasConcept C87027312 @default.
• W2893276853 hasConcept C96250715 @default.
• W2893276853 hasConceptScore W2893276853C105795698 @default.
• W2893276853 hasConceptScore W2893276853C109007969 @default.
• W2893276853 hasConceptScore W2893276853C112959462 @default.
• W2893276853 hasConceptScore W2893276853C114793014 @default.
• W2893276853 hasConceptScore W2893276853C118671147 @default.
• W2893276853 hasConceptScore W2893276853C127313418 @default.
• W2893276853 hasConceptScore W2893276853C143724316 @default.
• W2893276853 hasConceptScore W2893276853C151730666 @default.
• W2893276853 hasConceptScore W2893276853C162324750 @default.
• W2893276853 hasConceptScore W2893276853C166957645 @default.
• W2893276853 hasConceptScore W2893276853C178790620 @default.
• W2893276853 hasConceptScore W2893276853C185592680 @default.
• W2893276853 hasConceptScore W2893276853C187320778 @default.
• W2893276853 hasConceptScore W2893276853C187736073 @default.
• W2893276853 hasConceptScore W2893276853C205649164 @default.
• W2893276853 hasConceptScore W2893276853C2816523 @default.
• W2893276853 hasConceptScore W2893276853C33923547 @default.
• W2893276853 hasConceptScore W2893276853C39432304 @default.
• W2893276853 hasConceptScore W2893276853C41008148 @default.
• W2893276853 hasConceptScore W2893276853C49261128 @default.
• W2893276853 hasConceptScore W2893276853C74256435 @default.
• W2893276853 hasConceptScore W2893276853C76886044 @default.
• W2893276853 hasConceptScore W2893276853C87027312 @default.
• W2893276853 hasConceptScore W2893276853C96250715 @default.
• W2893276853 hasLocation W28932768531 @default.
• W2893276853 hasLocation W28932768532 @default.
• W2893276853 hasLocation W28932768533 @default.
• W2893276853 hasOpenAccess W2893276853 @default.

• next