Modelling uncertainty of flood quantile estimation at ungauged sites by Bayesian networks

Santillan Sanchez, David; Mediero Orduña, Luis y Garrote de Marcos, Luis (2013). Modelling uncertainty of flood quantile estimation at ungauged sites by Bayesian networks. "Journal of hydroinformatics" ; pp. 1-17. ISSN 1464-7141. https://doi.org/10.2166/hydro.2013.065.

Descripción

Título: Modelling uncertainty of flood quantile estimation at ungauged sites by Bayesian networks
Autor/es:
  • Santillan Sanchez, David
  • Mediero Orduña, Luis
  • Garrote de Marcos, Luis
Tipo de Documento: Artículo
Título de Revista/Publicación: Journal of hydroinformatics
Fecha: 30 Noviembre 2013
Materias:
Escuela: E.T.S.I. Caminos, Canales y Puertos (UPM)
Departamento: Ingeniería Civil: Hidráulica y Energética [hasta 2014]
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Prediction at ungauged sites is essential for water resources planning and management. Ungauged sites have no observations about the magnitude of floods, but some site and basin characteristics are known. Regression models relate physiographic and climatic basin characteristics to flood quantiles, which can be estimated from observed data at gauged sites. However, these models assume linear relationships between variables Prediction intervals are estimated by the variance of the residuals in the estimated model. Furthermore, the effect of the uncertainties in the explanatory variables on the dependent variable cannot be assessed. This paper presents a methodology to propagate the uncertainties that arise in the process of predicting flood quantiles at ungauged basins by a regression model. In addition, Bayesian networks were explored as a feasible tool for predicting flood quantiles at ungauged sites. Bayesian networks benefit from taking into account uncertainties thanks to their probabilistic nature. They are able to capture non-linear relationships between variables and they give a probability distribution of discharges as result. The methodology was applied to a case study in the Tagus basin in Spain.

Más información

ID de Registro: 29464
Identificador DC: http://oa.upm.es/29464/
Identificador OAI: oai:oa.upm.es:29464
Identificador DOI: 10.2166/hydro.2013.065
URL Oficial: http://www.iwaponline.com/jh/up/default.htm
Depositado por: Memoria Investigacion
Depositado el: 03 Jul 2014 10:29
Ultima Modificación: 22 Sep 2014 11:45
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