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Mapping the Areal Precipitation over Arizona - Using Kriging Technique
| dc.contributor.author | Karnieli, Arnon,1952- | |
| dc.date.accessioned | 2013-07-18T18:59:51Z | |
| dc.date.available | 2013-07-18T18:59:51Z | |
| dc.date.issued | 1988-04-16 | |
| dc.identifier.issn | 0272-6106 | |
| dc.identifier.uri | http://hdl.handle.net/10150/296409 | |
| dc.description | From the Proceedings of the 1988 Meetings of the Arizona Section - American Water Resources Association and the Hydrology Section - Arizona-Nevada Academy of Science - April 16, 1988, University of Arizona, Tucson, Arizona | en_US |
| dc.description.abstract | The classical methods for interpolating and spatial averaging of precipitation fields fail to quantify the accuracy of the estimate. On the other hand, kriging is an interpolation method for predicting values of regionalized variables at points (punctual kriging) or average values over an area (block kriging). This paper demonstrates the use of the kriging method for mapping and evaluating precipitation data for the state of Arizona. Using 158 rain gage stations with 30 years or more of record, the precipitation over the state has been modeled as a realization of a two dimensional random field taking into consideration the spatial variability conditions. Three data sets have been used: (1) the mean annual precipitation over the state; (2) the mean summer rainy season; and (3) the mean winter rainy season. Validation of the empirical semi-variogram for a constant drift case indicated that the exponential model was appropriate for all the data sets. In addition to a global kriging analysis, the data have been examined under an anisotropic assumption which reflects the topographic structure of the state. | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Arizona-Nevada Academy of Science | en_US |
| dc.rights | Copyright ©, where appropriate, is held by the author. | |
| dc.subject | Hydrology -- Arizona. | en_US |
| dc.subject | Water resources development -- Arizona. | en_US |
| dc.subject | Hydrology -- Southwestern states. | en_US |
| dc.subject | Water resources development -- Southwestern states. | en_US |
| dc.title | Mapping the Areal Precipitation over Arizona - Using Kriging Technique | en_US |
| dc.type | text | en_US |
| dc.type | Proceedings | en_US |
| dc.contributor.department | U.S. Department of Agriculture, Agricultural Research Service, Tucson, Arizona 85719 | en_US |
| dc.contributor.department | University of Arizona, Water Resources Research Center | en_US |
| dc.identifier.journal | Hydrology and Water Resources in Arizona and the Southwest | en_US |
| dc.description.collectioninformation | This article is part of the Hydrology and Water Resources in Arizona and the Southwest collections. Digital access to this material is made possible by the Arizona-Nevada Academy of Science and the University of Arizona Libraries. For more information about items in this collection, contact anashydrology@gmail.com. | en_US |
| refterms.dateFOA | 2018-07-14T02:38:16Z | |
| html.description.abstract | The classical methods for interpolating and spatial averaging of precipitation fields fail to quantify the accuracy of the estimate. On the other hand, kriging is an interpolation method for predicting values of regionalized variables at points (punctual kriging) or average values over an area (block kriging). This paper demonstrates the use of the kriging method for mapping and evaluating precipitation data for the state of Arizona. Using 158 rain gage stations with 30 years or more of record, the precipitation over the state has been modeled as a realization of a two dimensional random field taking into consideration the spatial variability conditions. Three data sets have been used: (1) the mean annual precipitation over the state; (2) the mean summer rainy season; and (3) the mean winter rainy season. Validation of the empirical semi-variogram for a constant drift case indicated that the exponential model was appropriate for all the data sets. In addition to a global kriging analysis, the data have been examined under an anisotropic assumption which reflects the topographic structure of the state. |
