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Estimation of daily space–time precipitation series for macroscale hydrological modelling
Author(s) -
Haberlandt U.,
Kite G. W.
Publication year - 1998
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/(sici)1099-1085(199807)12:9<1419::aid-hyp645>3.0.co;2-a
Subject(s) - precipitation , interpolation (computer graphics) , environmental science , hydrological modelling , series (stratigraphy) , drainage basin , meteorology , data assimilation , structural basin , multivariate interpolation , hydrology (agriculture) , climatology , geology , computer science , mathematics , statistics , geography , geomorphology , animation , paleontology , computer graphics (images) , cartography , geotechnical engineering , bilinear interpolation
An important problem in modelling macroscale basins, especially for sparsely observed regions, is the lack of precipitation information. Alternatives to using straightforward interpolated surface observations include the utilization of more advanced interpolation techniques and the use of additional precipitation information from atmospheric models. Conventional and geostatistical methods are applied for optimal interpolation and assimilation of observed and model precipitation. Various time‐series of daily areal precipitation distributions are produced and compared using not only an internal precipitation validation, but also an objective verification based on stream flow simulations. The Mackenzie River Basin in north‐western Canada is used as the study area and hydrological simulations are carried out with the model SLURP. It was found that better interpolation techniques and the use of combined precipitation data can improve the hydrological simulations and that the enhancements are related to the relative size of the simulation units used. © 1998 John Wiley & Sons, Ltd.