Appropriatie spatial scales to achieve model output uncertainty goals

Martijn J. Booij, Charles S. Melching

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Appropriate spatial scales of hydrological variables were determined using an existing methodology based on a balance in uncertainties from model inputs and parameters extended with a criterion based on a maximum model output uncertainty. The original methodology uses different relationships between scales and variable statistics. It is extended with two different uncertainty propagation methods, the mean-value first-order second-moment (MFOSM) method and Monte Carlo analysis, and backward uncertainty propagation to obtain appropriate scales based on two uncertainty criteria. The methodology is applied to three flood estimation methods. The application to the River Meuse basin in western Europe revealed that the methodology can be used for the considered flood estimation methods under similar climatological and geographical conditions. The results showed different relative input and parameter uncertainties for the different flood estimation methods (3–6%) for a specific maximum output uncertainty (25%) and different appropriate spatial scales for the dominant variables
Original languageUndefined
Title of host publicationHydrological Sciences for Managing Water Resources in the Asian Developing World, Guangzhou China, June 2006
EditorsXiaohong Chen, Yongqin Chen, Jun Xia, Hailun Zhang
Place of PublicationGuangzhou
PublisherIAHS Press
ISBN (Print)9781901502442
Publication statusPublished - 2008
EventHydrological Sciences for Managing Water Resources in the Asian Developing World - Guangzhou, China
Duration: 1 Jun 20061 Jun 2006

Publication series

NameIAHS publication
PublisherIAHS Press
ISSN (Print)0144-7815


ConferenceHydrological Sciences for Managing Water Resources in the Asian Developing World
OtherJune 2006


  • IR-78695
  • appropriate scale
  • METIS-249620
  • backward uncertainty propagation
  • unit hydrograph
  • SCS method
  • flood estimation
  • Monte Carlo analysis
  • HBV model
  • MFOSM method

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