Abstract
Precipitation data from Columbia River Basin was analyzed using different spatial estimation techniques. Kriging, Locally weighted regression (lowess) and Smoothing Spline ANOVA (SS-ANOVA) were used to analyze the data. Log(precipitation) was considered as a function of easting, northing and elevation. Analysis by kriging considered precipitation only as a function of easting and northing. Various quantitative measures of comparisons were considered like maximum absolute deviation, residual sum of squares and scaled variance of deviation. Analyses suggested that SS-ANOVA and lowess performed better than kriging. Residual plots showed that the distribution of residuals was tighter for SS-ANOVA than for lowess and kriging. Precipitation seemed to have an increasing trend with elevation but seemed to stabilize after certain elevation. Analysis was also done for Willamette River Basin data. Similar results were observed.
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© 1994 Springer Science+Business Media Dordrecht
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Satagopan, J., Rajagopalan, B. (1994). Comparing Spatial Estimation Techniques for Precipitation Analysis. In: Hipel, K.W., McLeod, A.I., Panu, U.S., Singh, V.P. (eds) Stochastic and Statistical Methods in Hydrology and Environmental Engineering. Water Science and Technology Library, vol 10/3. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-3083-9_23
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DOI: https://doi.org/10.1007/978-94-017-3083-9_23
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