期刊
INTERNATIONAL JOURNAL OF CLIMATOLOGY
卷 25, 期 3, 页码 351-363出版社
WILEY
DOI: 10.1002/joc.1131
关键词
Benevento; southern Italy; multivariate geostatistics; GIS; precipitation; elevation; vegetation cover factor
Precipitation variability results from atmospheric circulation and complex site-specific bio-geoclimatic characteristics; therefore, climatic variables are expected to be correlated in a scale-dependent way. This paper studies the influence of topographic co-variables on the spatial variability of precipitation over small regions of complex terrain. For this purpose, the mutual benefits of an integrated geographic information system (GIS) and a geostatistics approach was used for spatial precipitation interpolation from rainfall observations measured at 51 climatic stations in a mountainous region of southern Italy (Benevento province). As no single method is optimal for all regions, it is important to compare the results obtained using alternative methods applied to the same data set. Therefore, besides ordinary kriging examination, two auxiliary variables were added for ordinary co-kriging of annual and seasonal precipitation: terrain elevation data and a topographic index. Cross-validation indicated that the ordinary kriging yielded the largest prediction errors. The smallest prediction errors were produced by a multivariate geostatistical method. However, the results favour the ordinary co-kriging with inclusion of information on the topographic index. The application of co-kriging is particularly justified in areas where there are nearby stations and where landform is very complex. We conclude that ordinary co-kriging is a very flexible and robust interpolation method because it may take into account several properties (soft and hard data) of the landscape. Copyright (c) 2005 Royal Meteorological Society.
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