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利用纵向岭谷及对比区58个典型站点1971~2000年逐月气象资料及逐日降水量,分析各站ET0年值、月ET0最大值(5月份)、月ET0最小值(12月份)、水稻灌溉需水及农业综合灌溉需水定额(年值及4~6月主灌溉期),以地统计学方法分析了6者的空间变化特性.研究表明:在小范围内,6个灌溉需水变量随距离都有正的自相关性,且绝大多数都在S-N方向的Moran’sⅠ系数最大,空间自相关性最强;受不同季风气候、纬度、海拔及土壤因素影响,水稻灌溉需水的空间自相关性较其他变量更复杂;所有变量都是结构性因素引起的空间变异起主导作用,结构性变异达到60.2%~87.9%,随机成分引起的空间变异只占12.1%~39.8%;受夏季来自印度洋和太平洋两股水汽交汇区的移动轨迹、冬季来自大陆干暖的南支西风作用,ET0年值、5月份及12月份的ET0值都是在NW-SE和NE-SW两个方向的分形维数最小、变异性最大;水稻灌溉需水和农业综合灌溉需水定额(年值及4~6月主灌溉期)在S-N的变异性最大,主要受纵向岭谷走向的影响,水气和能量在南北向的河流通道作用下形成扩散的梯度效应;所有6个需水变量在E-W的空间自相关性都最小,证实纵向岭谷区各个灌溉需水变量在空间分布上受到“通道-阻隔”作用的影响.
Using monthly meteorological data from 1971 to 2000 and monthly precipitation of 58 typical stations in the vertical and horizontal valleys and contrasting areas, the annual ET0 values, monthly ET0 maximum values (May), monthly ET0 minimum values (December), rice Irrigation water demand and agricultural irrigation water quota (annual value and main irrigation period from April to June), the geostatistics method was used to analyze the spatial variation characteristics of the six species.The results showed that in a small area, six irrigation water The variables have positive autocorrelation with distance, and most of them have the largest Moran’sⅠ coefficient in SN direction and have the strongest spatial autocorrelation. Under the influence of different monsoon climate, latitude, altitude and soil factors, Spatial autocorrelation is more complicated than other variables. All the variables are the leading factors of spatial variability caused by structural factors, the structural variability reaches 60.2% ~ 87.9%, and the spatial variability caused by random components only accounts for 12.1% ~ 39.8%. In the summer, the moving trajectories from the intersection of the Indian Ocean and the Pacific Ocean are converging. The winter comes from the dry and warm south-westerly westerlies in the mainland. ET0 values, ET0 values in May and December are both in the NW-SE and NE-SW directions The smallest fractal dimension, the largest variability; rice Irrigation water demand and agricultural irrigation water quota (annual value and April to June main irrigation period) in the SN variability is the largest, mainly due to the longitudinal direction of the valley effect, water and energy in the north-south river channel under the action of And all the six water-demand variables have the smallest spatial autocorrelation in the EW, confirming that the spatial distribution of each irrigation water demand variable in the longitudinal gully region is affected by the “channel-barrier” effect.