paired watershed study

Corrected Prediction Intervals for Change Detection in Paired Watershed Studies
Som, N.A., N.P. Zegre, L.M. Ganio, A.E. Skaugset

Autoregressive process pHydrological 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 aarameters are discussed.

DISCIPLINE: Hydrology & Water Quality    STUDY: Hinkle Creek    TYPE: Journal Articles    TAGS: paired watershed study, generalized least squares, Prasad-Rao mean-squared error estimator, stream discharge, time series
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