北方冬小麦干旱风险评估及风险区划研究
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摘要
基于非灌溉与灌溉两种背景,以水分平衡原理求得的冬小麦全生育期自然水分亏缺率为轴线,以风险评估技术方法为核心,分别从实际产量和生产力两种途径研究了北方冬麦区近40年干旱对冬小麦影响的风险水平,利用Mapinfo实现空间的分布规律及灾损区划。
     根据产量对水分的响应,定义了五种干旱年型和减产年型,分别为轻、中、重、严重和极端严重。分析了不同干旱年型和减产年型的时空分布状况及其相关关系,关系表明,干旱年型和减产年型两者没有明显的一致性,而且干旱年型发生的站次多于对应的减产年型,尤其较重的干旱年型出现较多,而较重的减产年型极少。
     采用“逐步订正法”计算光合、光温和气候生产力。从水分平衡角度,采用了新颖的数理模式构建了水分订正函数。结果表明,由于考虑了底墒水,本文计算的气候生产力比以往一些结果高出约20%~30%,这对评估气候生产力有重要意义。降水年际变异较大,区域差异明显,使得气候生产力的时空变化大于光合和光温生产力的时空变化,在中东部,水分由南向北、由东向西减少,中西部由南向北减少,使得各项指标的变化均有与此基本相应的变化趋势。
     建立了实际产量与自然水分亏缺率的相关关系,根据其间不同的敏感性。确定出两类(A、B)不同干旱年型的自然水分亏缺率对应的实际减产率指标。A类不同干旱年型的实际减产率分别为<9%、9%~12%、12%~14%、14%~21%和>21%,该类指标适用于山东东部及中部的部分地区、陕西南部渭河一带、河北中部的部分地区;B类分别为<9%、9%~15%、15%~21%、21%~40%和>40%,该类指标适用于本区的其它地区。
     从风险的角度,建立了冬小麦干旱灾损风险评估的指标体系,包括自然水分亏缺率风险指数、减产率风险指数和抗灾性能趋势向量系数的意义、表征模式和估算技术方法,在此基础上构建了灾损综合风险模型,并对模型参数区域化,结果表明:冬小麦干旱灾损高风险区在陕西中北部山西中部的部分地区和河北沧州的部分地区;较高风险区在山西中部的部分地区、河北的唐山地区和西部的部分地区;中风险区在陕西中部、山西南部、河北沧州的大部分地区;低风险区在陕西中南部、河南中北部、北京市、天津市、河北中南部和山东省。
On the background of irrigation and nonirrigation, making natural moisture deficiency rates calculated basing on the theory of balance of water as axis, and risk assessment techniques and methods as core, the risk levels of effect that drought on yield of winter wheat in semi-humid and semi-drought areas in recent 40 years were studied by two methods from actual yields and productive potentialities respectively. The spatial distribution principles and losses zonation were made by Mapinfo.
    According to the response yield to water, five types of drought and yield reduction were defined, they are light moderate, heavy, serious heavy and ultra-heavy, and the spatio-temporal distribution of which and the correlativity between them in recent 40 years is analysed. The results indicated: the probability distribution of natural moisture deficiency rates of winter wheat during the growing period could be divided into three types because of their regional difference, which were mainly in the north part, the middle part and the south part respectively in producing area of northern China. In north and middle, the frequency of serious drought was higher, but in south, it was the light drought. The probability distribution of yield reduction could be divided into three types also, of all these types, it was the frequency of light yield reduction was higher, which reflected that irrigation was important to lessen the effect drought on yield. The correlativity indicated: there was no clear coherence between
    drought types and yield reduction types, and the frequency of drought was more than that of yield reduction, especially heavier drought occurred more frequently than lighter yield reduction.
    Photosynthesis potential productivity, photo - temperature productivity and climate productive potentialities were calculated using "correcting method step by step". From the balance of water, a new model was used to construct water function. The result indicated that because effective moisture accounts for 20%~30% of the water requirement of winter wheat, and it was important to climatic productive potentialities, the climatic productive potentialities was 20%~30% higher than before accordingly, which would make great sense to evaluate climatic productive potentialities. The high change of preci-pitation made spatio-temporal change of climatic productive potentialities bigger than that of photosynthesis and photo - temperature. The trend of water decreasing from south to north, from east to west in Hebei, Beijing, Tianjin and Shandong, from south to north in Shanxi, Shaanxi and Henan made every index has the same trend almostly.
    Correlations between actual yields of winter wheat and natural moisture deficiency rates in irrigated areas were established, and because of the differences of sensitivity between them, two types(A and B) indices of natural moisture deficiency rates and the corresponding yield reduction rates of actual yield were confirmed. The results indicated: the yield reduction rates of A type are <9 %,9%~12%,12%~14%,14%~21 % and >2\ %, which were suitable for the east and some areas of midst in Shandong,south near Weihe river in Shanxi and some areas of midst in Hebei; and B type were <9 %,9%~15%,15%~21 %,21 %~40%and >40% respectively, which are suitable for other areas?
    From the point of view of risk, a index system of risk assessment of winter wheat losses caused by drought was established, including the meanings, token models and estimate methods of risk index of natural water deficiency rate, risk index of yield reduction rate and trending vector coefficient of disaster resistance capability, then on the base of these indices, the comprehensive risk index model of losses caused by drought was established and regionalized. The results indicated: the high risk region included the middle north of Shanxi, some of middle of Shaanxi and some of Hebei in east; the higher
    
    
    risk region included some of middle of Shaanxi, the Tangshan region and some of west of Hebei; the moderate risk region included the middle of S
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