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当前位置: 首页 > 文章 > 作物系数影响因素分析 节水灌溉 2016 (8) 149-152+156
Position: Home > Articles > Analysis of Influencing Factors of Crop Coefficient Water Saving Irrigation 2016 (8) 149-152+156

作物系数影响因素分析

作  者：
吴慧蓉;崔远来;高明利
单  位：
武汉大学水资源与水电工程科学国家重点实验室;湖北省漳河工程管理局
关键词：
水稻;作物系数;参考作物蒸发蒸腾量;时间变化;空间变化
摘  要：
作物系数Kc的合理取值对作物需水量分析计算精度十分关键。以水稻为例,基于江西省灌溉试验中心站及浙江永康灌溉试验站的实测数据,分析了Kc与降雨量及ET0的关系,以及灌溉模式对Kc的影响,以江西及云南省为例,探讨了Kc在省域尺度上的空间变化规律。结果表明,Kc年内变化呈现先增大后减小的趋势,在抽穗开花期达到最大;Kc年际变化存在差异,早晚稻Kc与ET0呈负相关,晚稻Kc与降雨呈弱正相关,但关系均不明显,采用连续3年Kc实测平均值代替各年Kc满足精度要求;节水型灌溉模式下作物系数明显小于淹灌模式;采用FAO修订办法计算了江西省19个站点的Kc并进行了比较,Kcini均为1.05,Kcmid和Kcend的标准差与变异系数均在0.01左右,Kcmid、Kcend最大值与最小值相差3%左右,而云南36个站点的比较表明,Kcini标准差与变异系数在0.03~0.04,Kcmid,Kcend标准差和变异系数在0.02左右,Kcini最大值与最小值相差10%,Kcmid、Kcend最大值与最小值相差在5%左右。因此,对于省域尺度,如果省内气象要素变异不大,某个站点的作物系数可以扩展到整个省内使用,否则需进行修订。
译  名：
Analysis of Influencing Factors of Crop Coefficient
作  者：
WU Hui-rong;CUI Yuan-lai;GAO Ming-li;State Key Laboratory of Water Resources and Hydropower Engineering Science,Wuhan University;Zhanghe Engineering Management Bureau;
关键词：
rice;;crop coefficient;;reference evapotranspiration;;time variation;;spatial variation
摘  要：
It is very important for the accuracy of crop water requirement calculation to make reasonable value of Crop coefficient(Kc).Taking rice for example,the Kc was calculated based on the observed data from the Jiangxi irrigation experiment station and the Yongkang irrigation experiment station,and the correlation of Kcto rainfall and reference evapotranspiration(ET0)was analyzed.Meanwhile,the effect of the irrigation mode on the Kc was analyzed.Furthermore,the spatial variation characteristics of Kc on a provincial scale were discussed based on the calculated values of that in Jiangxi and Yunnan provinces.The results show that,in ayear,the Kcincreases first to an maximum in the heading and flowering stage,then it decreases;there are differences among the annual values of Kc,and the value of that is negatively correlated with ET0 for both early and late rice,whereas the Kcof late rice is weakly positively correlated with rainfall.Moreover,we found that the average value of Kccalculated with observed data in 3years instead of annual value can meet the requirements of accuracy.Additionally,the value of Kcin water-saving irrigation mode is significantly smaller than that in flooding irrigation mode.The values of Kcin 19 stations in Jiangxi province was revised according to the method proposed by FAO,and the results indicate that the Kciniof 19 stations are all 1.05,and the standard deviation and the coefficient of variation of Kcmidand Kcendare about 0.01,meanwhile,the percentage of maximum and minimum of Kcmid and Kcendis about 3%.Whereas,the result of the 36 stations in Yunnan shows that:the standard deviation and the coefficient of variation ofKcinivaries from 0.03 to 0.04,and standard deviation and variation coefficient of Kcmidand Kcendare about 0.02.In addition,the percentage difference of maximum and minimum of Kciniis 10%,and the percentage difference of maximum and minimum of Kcmid and Kcendis about 5%.Therefore,on a provincial scale,if the variation of meteorological elements is not obvious,the Kcof a station can be extended to the entire province,otherwise the crop coefficient needed to be revised.

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