期刊
HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES
卷 57, 期 1, 页码 134-143出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/02626667.2011.637494
关键词
paired watershed study; generalized least squares; Prasad-Rao mean-squared error estimator; stream discharge; time series
资金
- Oregon State University Forest Research Laboratory
- Watersheds Research Cooperative
Hydrological data may be temporally autocorrelated requiring autoregressive process parameters to be estimated. Current statistical methods for hydrological change detection in paired watershed studies rely on prediction intervals, but the current form of prediction intervals does not include all appropriate sources of variation. Corrected prediction intervals for the analysis of paired watershed study data that include variation associated with covariance and linear model parameter estimation are presented. We provide an example of their application to data from the Hinkle Creek Paired Watershed Study located in the western Cascade foothills of Southern Oregon, USA. Research implications of using the correct prediction limits and incorporating the estimation uncertainty of autoregressive process parameters are discussed.
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