HR: 0800h
AN: H21G-0817    [Abstracts]
TI: Yearly Streamflow Discharge Analysis Using Functional Regression Models
AU: * Greenwood, M C
EM: greenwood@math.montana.edu
AF: Dept. of Mathematical Sciences, Montana State University - Bozeman, PO BOX 172400, Bozeman, MT 59717-2400, United States
AU: Harper, J T
EM: joel@mso.mt.edu
AF: Dept. of Geosciences, University of Montana, 32 Campus Drive, Missoula, MT 59812, United States
AU: Moore, J N
EM: johnnie.moore@umontana.edu
AF: Dept. of Geosciences, University of Montana, 32 Campus Drive, Missoula, MT 59812, United States
AB: Earlier spring runoff from snow melt in western North America has been suggested from analysis of both river discharge and snowpack data. This work takes a different approach to detecting evidence of earlier spring onset using a new semi-metric based on yearly streamflow discharge records. New methods of time series analysis for functional data (Ramsay and Silverman, 2005) are presented to analyze the inverse yearly cumulative discharge functions. An algorithm is developed for estimation of a functional regression model that incorporates autocorrelated errors. A framework for choosing the model structure is provided using a functional extension of a model selection criterion. Further, a diagnostic for assessing autocorrelation in the errors is provided. Results based on the analysis of streamflow records for Water Years 1951-2005 from the South Fork of the Boise River are used to illustrate the new techniques.
DE: 1616 Climate variability (1635, 3305, 3309, 4215, 4513)
DE: 1803 Anthropogenic effects (4802, 4902)
DE: 1807 Climate impacts
DE: 1833 Hydroclimatology
DE: 1879 Watershed
SC: Hydrology [H]
MN: 2007 Fall Meeting