Estimating uncertainty in hydrologic model predictions

Kathryn Goodwin, Carlos Rentas, Kevin Lansey, Bisher Imam, Soroosh Sorooshian

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Parameters for physically based hydrologic models are typically developed based upon user judgement and look up tables. Parameter estimates inherently contain a certain amount of error that affect the reliability of hydrologic models. By considering these estimates to be random variables, the output of the models in which they are used must also be considered as uncertain. While sensitivity analysis provides information about how much the output changes with small changes in a particular input parameter, uncertainty analysis goes further. It provides the statistical properties and an estimate of the statistical distribution of the output from the statistics or distribution of the input. Thus, the error introduced into model results by uncertain model input parameters can be assessed quantitatively.

Original languageEnglish (US)
Title of host publicationWRPMD 1999
Subtitle of host publicationPreparing for the 21st Century
PublisherAmerican Society of Civil Engineers (ASCE)
ISBN (Print)0784404305, 9780784404300
DOIs
StatePublished - Jan 1 1999
Event29th Annual Water Resources Planning and Management Conference, WRPMD 1999 - Tempe, AZ, United States
Duration: Jun 6 1999Jun 9 1999

Publication series

NameWRPMD 1999: Preparing for the 21st Century

Other

Other29th Annual Water Resources Planning and Management Conference, WRPMD 1999
CountryUnited States
CityTempe, AZ
Period6/6/996/9/99

ASJC Scopus subject areas

  • Computer Networks and Communications

Fingerprint Dive into the research topics of 'Estimating uncertainty in hydrologic model predictions'. Together they form a unique fingerprint.

Cite this