| Cite this article: | 张敏讷,赵伟霞,李久生,等.基于冠层温度的水分亏缺指标空间分布图插值方法研究[J].灌溉排水学报,0,():-. |
| ZHANG Minne,ZHAO Weixia,LI Jiusheng,et al.基于冠层温度的水分亏缺指标空间分布图插值方法研究[J].灌溉排水学报,0,():-. |
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| DOI： |
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| Research on interpolation method of spatial distribution map of water deficit index based on canopy temperature |
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ZHANG Minne, ZHAO Weixia, LI Jiusheng, LI Yanfeng
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State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin,China Institute of Water Resources and Hydropower Research
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| Abstract: |
| 【Objective】 Canopy temperature is an important index to reflect crop water deficit, and its spatial distribution map is the basis for dynamic management of variable rate irrigation. To select a reasonable interpolation method, 【Method】 this study discussed the interpolation accuracy and zoning effect of canopy temperature and normalized relative canopy temperature (NRCT) under 10 interpolation methods based on the interpolation module of ArcGIS software at two experimental sites. The characteristic values, normalized root mean square error(nRMSE) and Pearson correlation coefficient between predicted and measured values, and spatial distribution maps of canopy temperature and NRCT were used to evaluate the interpolation effect. 【Result】 The results indicated that the canopy temperature distribution of winter wheat and summer maize had strong spatial autocorrelation. When using the local polynomial method and universal Kriging method to interpolate, the canopy temperature would have abnormal values. When using the global polynomial interpolation, the nRMSE between measured and predicted values of canopy temperature(5.9%) and NRCT(28.6%) were highest, and thire Pearson correlation coefficient between the predicted and measured values was 0.33. The maximum interpolation accuracy was obtained withordinary Kriging method, in which the difference between the average value of predicted and measured canopy temperature was less than 0.5℃, the nRMSE of canopy temperature(3.6%) and NRCT(17.5%) were the lowest, and the Pearson correlation coefficient was 0.8. The spatial distribution maps generated bysimple Kriging method, disjunctive Kriging method and empirical bayesian Kriging method were similar to ordinary Kriging method，and their overlapping percentage was greater than 90%. 【Conclusion】 Considering the interpolation accuracy and the spatial distribution map of canopy temperature and NRCT, the order of interpolation method was ordinary Kriging method> simple Kriging method= disjunctive Kriging method> empirical bayesian Kriging method> radial basis function method(tension spline function)> radial basis function method(regular spline function)> inverse distance weight method. The ordinary Kriging method was recommendedfor dynamic management of variable rate irrigation based on canopy temperature. |
| Key words: Canopy temperature; normalized relative canopy temperature; variable rate irrigation; dynamic zoning; spatial interpolation |
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