Bayesian change-point analysis in hydrometeorological time series. Part 1.The normal model revisited

A Bayesian method is presented for the analysis of two types of sudden chan ge at an unknown time-point in a sequence of energy inflows modeled by inde pendent normal random variables. First, the case of a single shift in the m ean level is revisited to show how such a problem can be straightforwardly addressed through the Bayesian framework. Second, a change in variability i s investigated. In hydrology, to our knowledge, this problem has not been s tudied from a Bayesian perspective. Even if this model is quite simple, no analytic solutions for parameter inference are available, and recourse to a pproximations is needed. It is shown that the Gibbs sampler is particularly suitable for change-point analysis, and this Markovian updating scheme is used. Finally, a case study involving annual energy inflows of two large hy dropower systems managed by Hydro-Quebec is presented in which informative prior distributions are specified from regional information. (C) 2000 Elsev ier Science B.V. All rights reserved.