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DOI:
:2014,(1):236-239
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基于条件植被温度指数的冬小麦主要生育时期干旱监测效果评价——Ⅱ.改进的层次分析法和变异系数法组合赋权
李 艳,王鹏新,刘峻明,张树誉,李 俐1,2,3
(1.(1.中国农业大学信息与电气工程学院, 北京 100083;2.河北科技师范学院城市建设学院, 河北 秦皇岛 066004;3.陕西省气象局, 陕西 西安 710014))
Evaluation of drought monitoring effects in the main growing stages of winter wheat by using the vegetation temperature condition index——Ⅱ.Improved analytic hierarchy process and variation coeffici
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中文摘要: 运用改进的层次分析法、变异系数法及主客观组合赋权法确定关中平原冬小麦越冬后主要生育时期干旱对产量的影响权重,建立关中平原五市2002—2009年每年的加权条件植被温度指数(VTCI)与冬小麦单产的一元线性回归模型,分析VTCI与产量间的线性关系。结果表明,变异系数法确定的加权VTCI与小麦单产的线性相关性不显著,渭南、咸阳及铜川的决定系数R2值均低于0.5;改进的层次分析法和组合赋权法确定的加权VTCI与小麦单产的线性相关性显著,除铜川外其余四市的R2值接近0.5,或者高于0.6,且组合赋权法的结果中西安的R2值达到0.7。基于改进的层次分析法和变异系数法的归一组合赋权法的结果优于其它 主客观组合赋权法的结果,为最优赋权方法,可用于评价冬小麦主要生育时期的干旱监测效果。
Abstract:Using the improved analytic hierarchy process, variation coefficient method and combination weighted methods, the impact weights of drought to the yield of winter wheat in main growng stage after winter was determined. During 2002 to 2009 in Five Cities of Guanzhong Plain, a linear regression model of annual weighted VTCI to the yield of winter wheat was established and analyzed the linear relation of VTCI with yield. The results showed that the linear relativity of weighted VTCI to yield of winter wheat determined by the variation coefficient method was not remarkable, the dicision coefficient R2 value was total less than 0.5 in Weinan, Xianyang and Tongchuan. But the linear relativity of weighted VTCI to yield of winter wheat determined by the improved analytic hierarchy process and combination weighted method was remarkable, and the R2 values of the Four Cities except Tongchuan was close to 0.5 or larger than 0.6, and the R2 values in Xian by the combination weighted method was larger than 0.7. The results of improved analytic hierarchy process and variation coefficient method was better than the combination weighted method, so they were the good methods and can be used to evaluate the drought monitoring effects in the main growing period of winter wheat.
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基金项目:“十二五”国家科技支撑计划资助项目(2012BAD20B0103);国家自然科学基金资助项目(41371390,41071235);高等学校博士学科点专项科研基金项目(20100008110031)
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