HR: 17:45h
AN: H24E-08    [Abstracts]
TI: A smoothed statistical regionalization approach for modelling monthly precipitation in complex terrain
AU: * González, J
EM: Javier.Gonzalez@uclm.es
AF: University of Castilla-La Mancha, Dept. Civil Engineering Avda. Camilo José Cela, s/n, Ciudad Real, 13071, Spain
AU: Valdés, J B
EM: jvaldes@u.arizona.edu
AF: University of Arizona, Dept. Civil Engineering and Engineering Mechanics, Tucson, AZ 85721-0072, United States
AB: Using rain-gauge station records for the statistical characterization and simulation of spatio-temporal precipitation fields involves many issues and simplifying assumptions. One major issue is related to dealing with uncertainty at-site sample statistical inference, because of the limited length of records. Regional frequency analysis uses substituting space for time in order to reduce uncertainty by assuming equal shapes of the precipitation statistical distributions in a region. However, this assumption limits the area of the analyzed region where this assumption is valid. The extension is dependent on terrain complexity. This work presents a new approach for the statistical regionalization of a large precipitation fields, replacing the constant shape assumption by using a smooth spatial variation. The approach accounts for every uncertainty on site information, using an L-moment method for inference analysis. Additionally, the orographic effect is introduced in the regionalization, which substantially improves the interpolation performance and estimation of areal precipitation. The approach is used for modelling the monthly precipitation field in the Júcar River Basin Authority Demarcation (Spain), incorporating its stochastic structure, and spatial dependency from a geostatistical analysis. Issues related to the estimation of regional precipitation, and mean areal precipitation are also discussed.
DE: 1854 Precipitation (3354)
DE: 1872 Time series analysis (3270, 4277, 4475)
DE: 1880 Water management (6334)
SC: Hydrology [H]
MN: 2007 Fall Meeting