基于GIS的土壤质量评价研究

介绍了基于GIS土壤质量等级评价的实现过程。探讨了土壤等级评价因子的选择和因子权重的确定方法。在分析了几种常用方法在土壤质量评价中的应用特点并指出几种方法的局限性之后，提出了顾及因子稳定性的多元线性回归分析法，并以南方某地为例进行了实例分析。     

地图投影的最小二乘二元多项式拟合的误差估计

探讨了在地图投影的最小二乘二元多项式拟合中参考点的分布对拟合误差的影响,提出了一种基于矩阵的秩亏的方法来判断参考点是否在指定次数的二元多项式空间的代数曲线上,并导出在极小范数最小二乘意义下的拟合多项式的误差估计式,公式表明拟合误差和参考点的最小二乘误差无关。     

河北省粮食生产发展趋势及其地区差异

河北省2002年粮食作物播种面积为6484.4千hm2,其中小麦占37.8%,玉米39.7%;粮食、棉花、油料的种植比例为15.9:1.0:1.6。北部四地市粮食播面占全省的23.3%,南部七地市76.7%。2002年粮食总产2435.8万t,为1949年的5.2倍;粮食单产3756kg/hm2,为1949年的5.8倍;人均粮食362kg,为1949年的2.4倍。北部地区粮食总产占全省的17.2%,南部地区82.8%。据回归分析与双向差分建模分析,2010年粮食总产可达3087.5万t,粮食单产4478kg/hm2,人均粮食460kg。据灰关联分析,影响粮食总产的主要因子有:粮食单产、农副产品收购价格总指数(1978年=100)、农业机械总动力、农村用电量、农田化肥施用量与有效灌溉面积等。根据笔者预测,若2010年农业机械总动力达8989万kw,农村用电量240.8亿kwh,农田化肥施用量356.1万t,有效灌面4549.2千hm2,则其粮食单产可达4664kg/hm2;若2010年仍保持2000年小麦播面所占比例(0.387),玉米播面所占比例达0.439,则其单产可达4387kg/hm2。     

地震动输入能量衰减规律的研究

对所收集到的266条强震记录，将其按场地条件分类，计算了不同场地条件、不同延性系数下的“绝对”和“相对”输入能量反应谱，然后利用两步回归法，得出了不同场地条件下地震动“绝对”和“相对”两种输入能量的衰减规律，分析了场地条件、延性系数、震级及距离等参数对地震动能量谱的影响，并对两种输入能量衰减规律进行了比较。     

影响上海市地价空间分布的区位因子分析

本文采用ＧＩＳ技术和多元线性回归分析方法，以土地批租地块为样本，分析上海市地价与城市区位因子的线性关系。回归分析结果表明；南京路，市中心和淮海路是影响上海市寺价空间差异的主要区位因子，外滩，次级商业中心和交通结节点对地价的影响很小，表明上海市地价的空间分布具有很高的向心性。     

岩质边坡设计坡角和锚固方案的确定

本文运用赤平极射投影、块体理论和岩体力学的基本原理, 试探求一种可供边坡工程设计采用的确定人工岩质边坡最大安全设计坡角和锚固方案的简易方法。     

Regionalization of unit hydrograph parameters: 1. Comparison of regression analysis techniques

Hydrologic regionalization is a useful tool that allows for the transfer of hydrological information from gaged sites to ungaged sites. This study developed regional regression equations that relate the two parameters in Nash's IUH model to the basin characteristics for 42 major watersheds in Taiwan. In the process of developing the regional equations, different regression procedures including the conventional univariate regression, multivariate regression, and seemingly unrelated regression were used. Multivariate regression and seeming unrelated regression were applied because there exists a rather strong correlation between the Nash's IUH parameters. Furthermore, a validation study was conducted to examine the predictability of regional equations derived by different regression procedures. The study indicates that hydrologic regionalization involving several dependent variables should consider their correlations in the process of establishing the regional equations. The consideration of such correlation will enhance the predictability of resulting regional equations as compared with the ones from the conventional univariate regression procedure.     

The separation of the influence of nutrients and climate on the varve time-series of baldeggersee, Switzerland

The varve data-set from a freeze-core taken in the deepest part of Baldeggersee was subjected to different multivariate statistical analyses in order to estimate the amount of variance in the varve thickness measures explicable by past climate and by the trophic state of the lake. A comparison of two different time-periods (1902 to1992 versus 1920 to 1980) revealed that the lake restoration programme since 1982 has had a significant impact on the formation of the seasonal layers. Results of the partitioning of the variance in the varve thickness measures showed that about two thirds of the variance are unexplained by a climate and trophic state model and that trophic state explains 6%, whereas climate accounts for about 28% of the variance before the effect of lake restoration had a strong impact on the varves. Among the climate parameters the amount of annual precipitation is a strong predictor for explaining the thickness of both dark layer and total couplet thickness, whereas summer precipitation is important for the thickness of the light layer.     

Regionalization of unit hydrograph Parameters: 2. Uncertainty analysis

Hydrologic model parameters obtained from regional regression equations are subject to uncertainty. Consequently, hydrologic model outputs based on the stochastic parameters are random. This paper presents a systematic analysis of uncertainty associated with the two parameters, N and K, in Nash's IUH model from different regional regression equations. The uncertainty features associated with N and K are further incorporated to assess the uncertainty of the resulting IUH. Numerical results indicate that uncertainty of N and K from the regional regression equations are too significant to be ignored.     

Regionalization of unit hydrograph Parameters: 2. Uncertainty analysis

Hydrologic model parameters obtained from regional regression equations are subject to uncertainty. Consequently, hydrologic model outputs based on the stochastic parameters are random. This paper presents a systematic analysis of uncertainty associated with the two parameters, N and K, in Nash's IUH model from different regional regression equations. The uncertainty features associated with N and K are further incorporated to assess the uncertainty of the resulting IUH. Numerical results indicate that uncertainty of N and K from the regional regression equations are too significant to be ignored.