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Bayesian modeling of hydrographs
Author(s) -
Merleau James,
Perreault Luc,
Angers JeanFrançois,
Favre AnneCatherine
Publication year - 2007
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2006wr005376
Subject(s) - hydrograph , flood myth , bayesian probability , probabilistic logic , sample (material) , computer science , environmental science , statistics , hydrology (agriculture) , mathematics , geography , geology , geotechnical engineering , chemistry , chromatography , archaeology
This article presents a new approach to model yearly hydrographs with daily or weekly streamflow measurements. The method considers yearly hydrographs as a sample of functions to be modeled nonparametrically in a Bayesian setting. The functional data analysis framework provides great flexibility to reproduce the features of yearly hydrographs, while the Bayesian probabilistic model ensures statistical coherence between the flood variables and the shapes of flood events. The proposed methodology is applied to two samples of hydrographs from two watersheds in the province of Quebec.