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Multivariate Interpolation of Precipitation Using Regularized Spline with Tension
Author(s) -
Hofierka Jaroslav,
Parajka Juraj,
Mitasova Helena,
Mitas Lubos
Publication year - 2002
Publication title -
transactions in gis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.721
H-Index - 63
eISSN - 1467-9671
pISSN - 1361-1682
DOI - 10.1111/1467-9671.00101
Subject(s) - interpolation (computer graphics) , smoothing , spline (mechanical) , smoothing spline , terrain , univariate , multivariate statistics , multivariate interpolation , spline interpolation , surface runoff , thin plate spline , mathematics , precipitation , algorithm , statistics , computer science , meteorology , artificial intelligence , bilinear interpolation , geography , engineering , cartography , structural engineering , motion (physics) , ecology , biology
Regularized Spline with Tension (RST) is an accurate, flexible and efficient method for multivariate interpolation of scattered data. This study evaluates its capabilities to interpolate daily and annual mean precipitation in regions with complex terrain. Tension, smoothing and anisotropy parameters are optimized using the cross‐validation technique. In addition, smoothing and rescaling of the third variable (elevation) is used to minimize the predictive error. The approach is applied to data sets from Switzerland and Slovakia and interpolation accuracy is compared to the results obtained by several other methods, expert‐drawn maps and measured runoff. The results demonstrate that RST performs as well or better than the methods tested in the literature. The incorporation of terrain improves the spatial model of precipitation in terms of its predictive error, spatial pattern and water balance.