Detection of Nonstationarity in Hydrologic Time Series
A. Ramachandra Rao and
G. H. Yu
Additional contact information
A. Ramachandra Rao: School of Civil Engineering, Purdue University, West Lafayette, Indiana 47907
G. H. Yu: School of Civil Engineering, Purdue University, West Lafayette, Indiana 47907
Management Science, 1986, vol. 32, issue 9, 1206-1217
Abstract:
Detection of changes in hydrologic time series due to intervention by man or natural causes is an important problem. Although intervention analysis has been used in the recent past to analyze nonstationary hydrologic time series, the necessity to specify a model of change and an initial time at which the time series has started to change are obvious disadvantages of intervention analysis. An alternative to intervention analysis is a method which is based on spectral characteristics and an exponential moving average model. The basic objective of the research discussed in the present paper is to test this alternative method. The model is tested by using synthetic uncorrelated and correlated data with step and gradual changes as well as by using real hydrologic time series. The sensitivity of the model to different parameters is also explored. The alternative model is found to be quite accurate in detecting changes in hydrologic time series.
Keywords: nonstationarity; hydrology; stochastic models; time series (search for similar items in EconPapers)
Date: 1986
References: Add references at CitEc
Citations:
Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.32.9.1206 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:32:y:1986:i:9:p:1206-1217
Access Statistics for this article
More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().