南方三省(区)南洋楹气候区划的研究

选择纬度、经度以及16个与水热状况有关的气象因子进行R型主成分分析,用前5个主成分坐标值进行模糊ISODATA聚类分析,将研究区划分为3类;用逐步判别分析建立了各类的判别函数式,回判准确率为91.81%;结合模糊相似优先比的结果,将研究区区划为南洋楹适宜发展区、南洋次适宜发展和南洋楹控制发展区3个气候区.     

动物杂种优势利用及其预测方法

杂种优势因具有提高两个不同亲本的遗传组成杂交所产后代的生产性能、生活力和抗逆性等特点,被广泛地运用在动植物杂交育种中.杂种优势利用率越高,种畜产生的价值越高,其后代产生的额外利润就越大.因此,杂种优势的利用率是广大育种工作者所关注的一项重要内容.杂种优势利用率的评估则依赖于对种畜杂种优势大小的预测.本文主要从杂种优势利...     

Error assessment in decision-tree models applied to vegetation analysis

Methods were developed to evaluate the performance of a decision-tree model used to predict landscape-level patterns of potential forest vegetation in central New York State. The model integrated environmental databases and knowledge on distribution of vegetation. Soil and terrain decision-tree variables were derived by processing state-wide soil geographic databases and digital terrain data. Variables used as model inputs were soil parent material, soil drainage, soil acidity, slope position, slope gradient, and slope azimuth. Landscapescale maps of potential vegetation were derived through sequential map overlay operations using a geographic information system (GIS). A verification sample of 276 field plots was analyzed to determine: (1) agreement between GIS-derived estimates of decision-tree variables and direct field measurements, (2) agreement between vegetation distributions predicted using GIS-derived estimates and using field observations, (3) effect of misclassification costs on prediction agreement, (4) influence of particular environmental variables on model predictions, and (5) misclassification rates of the decision-tree model. Results indicate that the prediction model was most sensitive to drainage and slope gradient, and that the imprecision of the input data led to a high frequency of incorrect predictions of vegetation. However, in many cases of misclassification the predicted vegetation was similar to that of the field plots so that the cost of errors was less than expected from the misclassification rate alone. Moreover, since common vegetation types were more accurately predicted than rare types, the model appears to be reasonably good at predicting vegetation for a randomly selected plot in the landscape. The error assessment methodology developed for this study provides a useful approach for determining the accuracy and sensitivity of landscape-scale environmental models, and indicates the need to develop appropriate field sampling procedures for verifying the predictions of such models.     

基于GA-BP网络的西藏高海拔地区ET0预报

选择那曲县(海拔4 450 m)、改则县(海拔4 700 m)作为西藏高原气候典型地区,通过遗传-神经(GA-BP)网络训练,应用1983—2012年30年的数据建立GA-BP网络模型,采用前一年的气象资料预报当年的参考作物腾发量,当2010—2012年连续3年的预报值均满足设定的阈值下限时,输出预测结果,这样使得模型在保证了预报精确度的同时兼具预报稳定性。结果发现:经GA-BP网络确定的2010—2012年3年模型预报值与真实值间的线性关系明显,决定系数R~2分别达到0.8805、0.9363、0.9167,斜率接近于1;多年的模拟预报值与实际值之间的相对误差均处于0.1以下,小于设定的阈值下限。对于易获得气象资料的地区,研究成果可对高海拔地区未来月际间作物需水量的变化进行预判,进而为将来灌溉制度的制定提供依据;对于缺测气象资料的地区,通过本文建立的网络模型,结合气象条件类似的站点,可在大时间尺度下对该地区ET_0变化趋势进行模拟,同时对下年度灌溉制度的拟定提供指导。     

基于RAGA-Shepard模型的滦河大河口站年径流预测

应用基于RAGA的Shepard相似模型,在实测径流统计特性分析的基础上对内蒙古滦河上游主要测站大河口站的年径流进行了预测.为科学调度水资源,最大限度地满足各方面的用水需求,提供有效依据.     

灰色系统理论和可公度性理论在大连市涝灾预测中的应用

采用大连市1951-2006年的降水资料,应用Z指标法得出大连市1951-2006年的涝灾年份.在这些数据分析的基础上,应用了三元、四元、五元可公度法分别预测了大连市的下一次可能发生的涝灾的年份.同时根据灰色系统理论建立灰色GM(1,1)模型对大连市未来的涝灾年份做出预测.结果表明:两种方法都能较好的应用于大连市涝灾研...