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| DOI：10.13522/j.cnki.ggps. 20190251 |
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| Using NDVI time series data to discern areas irrigated with different water sources: Taking People’s Victory Canal Irrigation District as an Example |
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LI Songjing，FAN Xiangyang，JING Ruoyao，HU Chao，WANG Hezhou，HUANG Zhongdong
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1.Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences, Xinxiang 453002, China;2.Graduate School of Chinese Academy of Agricultural Sciences, Beijing 100081, China; 3. Key Laboratory of High-efficient and Safe Utilization of Agriculture Water Resources, Chinese Academy of Agricultural Sciences, Xinxiang 453002, China; 4.Agricultural Water Soil Environmental Field Research Station of Xinxiang, Chinese Academy of Agricultural Sciences, Xinxiang 453002, China
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| Abstract: |
| 【Objective】This study aimed to provide a basis for the expansion and application of the commensurability theory in the field of drought prediction and early warning.【Method】Based on the historical drought data of Henan province from 1961 to 2016, this paper adopted analytic hierarchy process (AHP), MATLAB and SAS software to predict the year of drought occurrence, which was compared with the prediction results of the predecessors and the prediction results of the Butterfly structure diagram.【Result】Based on the commensurability theory of the ternary, quaternary and quintuple prediction models, it was predicted that the highest frequency of severe drought in Henan Province in 2014 , that is, the probability of occurrence of drought is the highest, which is consistent with the actual situation. Based on the above data, it is predicted that the year of severe drought in Henan Province before 2030 is 2023, which is consistent with the prediction of the Butterfly structure diagram and the results of previous studies. 【Conclusion】The method has strong practicability when predicting the year of occurrence of regional drought. The application of AHP, MATLAB and SAS greatly improves the calculation speed of the model, reduces the artificial influence of subjective factors on the prediction results, and improves the accuracy of the calculation results. |
| Key words: drought prediction; commensurability; analytic hierarchy process; Butterfly structure diagram |
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