Surface temperature variability patterns within irrigated fields |
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| Authors: | JL Hatfield M Vauclin SR Vieira R Bernard |
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| Institution: | 1. Department of Land, Air, and Water Resources, University of California, Davis, CA 95616 U.S.A.;2. Institut de Mecanique, Grenoble France;3. Instituto Agronomico de Campinas, Campinas Brazil;4. CRPE, Issy-les-Moulineux France |
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| Abstract: | During 1981, an experiment was conducted to examine the spatial variability of surface temperature within differentially irrigated grain sorghum fields. The measurements were performed at the University of California-Davis in 85 m long transects measured with an infrared thermometer reading at 1.0 m intervals. These measurements were made repeatedly throughout the season. When the data were analyzed to evaluate the spatial variability along each transect, it was found that along the transects the readings at 1 m intervals were not correlated. This lack of structure or spatial dependence within a given field suggests that a random sampling in a field would be adequate for infrared thermometer measurements. During a drying cycle from one irrigation to the next, the variance of surface temperature along a transect increased. However, there was not a statistically significant relationship between the amount of water extracted from the upper 150 cm of the profile when more than 40% of the available water remained. When more than 60% of the available water had been removed, the variance increased above 0.5°C2 but below this amount the variances did not exhibit any significant pattern. These data suggest that the variance of surface temperature within a field may not be a sensitive indicator of the soil water status. Utilizing the fact that the surface temperatures along the transects were random and normally distributed, we calculated that the number of samples needed to achieve a confidence limit of 1.0°C about the mean was 10 samples for a field with more than 40% available soil water and increased to 20 samples as the field dried below the 60% extraction level. These data suggest that the spatial variability techniques could be utilized to evaluate agricultural fields for their distribution efficiencies and problems. In application the samples required per field are a manageable number and could be analyzed with classical statistical methods. |
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