Precipitation estimation in mountainous terrain using multivariate geostatistics. Part I: structural analysis

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Abstract

To estimate average annual precipitation (AAP) over the entire watershed, historical precipitation data and station elevations were obtained from a network of 62 stations in southern Nevada and southeastern California. Multivariate geostatistics (cokriging) was selected as an estimation method because of a significant (p=0.05) correlation of r=.75 between the natural log of AAP and station elevation. A sample direct variogram for the transformed variable, TAAP-ln[(AAP)1000], was fitted with an isotropic, spherical model defined by a small nugget value of 5000, a range of 190 000 ft, and a sill value equal to the sample variance of 163 151. Elevations for 1531 additional locations were obtained from topographic maps to improve the accuracy of cokriged estimates. A sample direct variogram for elevation was fitted with an isotropic model consisting of a nugget value of 5500 and three nested transition structures: a Gaussian structure with a range of 61 000 ft, a spherical structure with a range of 70 000 ft, and a quasi-stationary, linear structure. The use of an isotropic, stationary model for elevation was considered valid within a sliding-neighbourhood radius of 120 000 ft. -from Authors

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Hevesi, J. A., Istok, J. D., & Flint, A. L. (1992). Precipitation estimation in mountainous terrain using multivariate geostatistics. Part I: structural analysis. Journal of Applied Meteorology, 31(7), 661–676. https://doi.org/10.1175/1520-0450(1992)031<0661:PEIMTU>2.0.CO;2

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