THE USE OF MULTIPLE REGRESSION MODELS IN PREDICTING SEDIMENT YIELD1

ABSTRACT. Four commonly used models for predicting sediment yield are analyzed and compared using previously published data. Three of these models involve logarithmic transformations. Some of the problems involved in transforming data are discussed in the context of logarithmic transformations. These problems are illustrated using the results of standard regression analyses and economic loss function analyses. For the data analyzed, the linear model is preferable to each of the logarithmic models on the basis of each analysis, and the usual multiple objective nature of the model choice problem is thus modified. The extent to which these results can be generalized is discussed in the context of model choice.     

OPTIMAL CAPACITIES OF WATER SUPPLY RESERVOIRS IN SERIES AND PARALLEL1

ABSTRACT: The planning of water supply reservoirs has traditionally been based on the Rippl or sequent peak analysis which applies to the design of a single reservoir. This paper incorporates the sequent peak method as the central feature in establishing a procedure for determining the sizes of several potential reservoirs located in a system of one or more rivers. Separate algorithms are developed for sites on parallel streams and for sites on the same stream. In both cases the approach is to find the combination of reservoirs which can satisfy a given constant monthly demand at a minimum total construction cost. It is shown that both problems can be cast in the form of a dynamic programming problem. A more complex system is then a combination of reservoirs in parallel and in series. An extension is given if the monthly demand is not constant but each reservoir satisfies a constant fraction of the monthly demand.     

Characterizing the Spatial Pattern of Soil Carbon and Nitrogen Pools in the Turkey Lakes Watershed: A Comparison of Regression Techniques

There is considerable spatial heterogeneity in organic carbon (C), total nitrogen (N), and potentially mineralizable nitrogen (PMN) pools in the soils of the Turkey Lakes Watershed. We hypothesized that topography regulates the spatial pattern of these pools through a combination of static factors (slope, aspect and elevation), which influence radiation, temperature andmoisture conditions, and dynamic factors (catenary position,profile and planar curvature), which influence the transport ofmaterials downslope. We used multiple linear regression (MLR)and tree regression (TR) models as exploratory techniques todetermine if there was a topographic basis for the spatialpattern of the C, N and PMN pools. The MLR and TR modelspredicted similar integrated totals (i.e., within 5% of eachother) but dissimilar spatial patterns of the pools. For thecombined litter, fibric and hemic layer, the MLR models explaineda significant portion of the variance (R² = 0.38, 0.23 and0.28 for C, N and PMN, respectively), however, the residuals werelarge and biased (the smallest contents were over-predicted andthe largest contents were under-predicted). The TR models (9-branch), in contrast, explained a greater portion of the variance (R² = 0.75, 0.67 and 0.62 for C, N and PMN, respectively) and the residuals were smaller and unbiased. Based on our sampling strategy, the models suggested that static factors were most important in predicting the spatial pattern of the nutrient pools. However, a nested sampling strategy that included scales where both static (among hillslopes) and dynamic (within hillslope) factors result in a systematic variation in soil nutrient pools may have improvedthe predictive ability of the models.     

SPATIAL VARIABILITY IN WATER‐BALANCE MODEL PERFORMANCE IN THE CONTERMINOUS UNITED STATES1

ABSTRACT: A monthly water‐balance (WB) model was tested in 44 river basins from diverse physiographic and climatic regions across the conterminous United States (U.S.). The WB model includes the concepts of climatic water supply and climatic water demand, seasonality in climatic water supply and demand, and soil‐moisture storage. Exhaustive search techniques were employed to determine the optimal set of precipitation and temperature stations, and the optimal set of WB model parameters to use for each basin. It was found that the WB model worked best for basins with: (1) a mean elevation less than 450 meters or greater than 2000 meters, and/or (2) monthly runoff that is greater than 5 millimeters (mm) more than 80 percent of the time. In a separate analysis, a multiple linear regression (MLR) was computed using the adjusted R‐square values obtained by comparing measured and estimated monthly runoff of the original 44 river basins as the dependent variable, and combinations of various independent variables [streamflow gauge latitude, longitude, and elevation; basin area, the long‐term mean and standard deviation of annual precipitation; temperature and runoff; and low‐flow statistics (i.e., the percentage of months with monthly runoff that is less than 5 mm)]. Results from the MLR study showed that the reliability of a WB model for application in a specific region can be estimated from mean basin elevation and the percentage of months with gauged runoff less than 5 mm. The MLR equations were subsequently used to estimate adjusted R‐square values for 1,646 gauging stations across the conterminous U.S. Results of this study indicate that WB models can be used reliably to estimate monthly runoff in the eastern U.S., mountainous areas of the western U.S., and the Pacific Northwest. Applications of monthly WB models in the central U.S. can lead to uncertain estimates of runoff.     

宜兴市殷村港叶绿素a与影响因子的多元分析

根据2011年1月—2015年12月殷村港水体中叶绿素a(Chl-a)及溶解氧、氨氮、总磷、总氮和水温等环境因子的监测数据,通过Pearson相关分析分析了叶绿素a浓度与水质指标、环境因子之间的相关性,并确定了影响因子;通过多元回归分析模型,建立了叶绿素a浓度和影响因子之间的相关性,实现叶绿素a浓度的预测,多元回归方程的复相关系数R都较高,均在0.8以上。多元回归模型能够较好地预测叶绿素a的浓度和走向趋势,对蓝藻水华的爆发提供参考。     

Rewriting the Plot: Sustaining allotments in the UK and Japan

In the search for a model form of allotment garden in the late 1980s, capable of absorbing surplus farmland while sustaining the capacity of the land to support agriculture, Japanese experts rejected the UK allotment, which was perceived to be of low status and in decline, in favour of the German Kleingarten. This paper suggests that it may be time to reconsider the UK experience, in the light of subsequent moves to rewrite the image and practice of allotment gardening in the UK within the local sustainable development agenda, and the problems which the Japanese version of the Kleingarten model has encountered in the changed economic circumstances of the 1990s.     

多输入多输出系统的相干性的问题分析

从相干性的来源入手,依次介绍了常相干性、偏相干性、重相干性的物理意义和运算关系,并研究了在实际试验中对相干性的估计和误差方面的问题。此外,还列出了一些对相关性理解和利用方面的一些命题,并依次进行了论证。     

由两起事故谈多能源设备的能源隔离措施

分析了两起因能量意外释放导致的伤害事故,制定了具备多能源设备的锁定和挂牌的安全作业流程,并提出预防事故的措施.     

米诺效应中的多事故点协同作用后果研究

为了研究多米诺效应中多事故点协同作用的后果,将并联系统概率模型运用到贝叶斯概率计算过程中,体现出多事故点协同作用对多米 诺效应传播的概率影响;后果分析部分从人、物、环境3个方面出发,对事故的后果影响以及事故预防提出建议措施。最后运用模型对实例进行 了应用分析,结果表明:多事故点协同作用下储罐的多米诺失效概率增大,罐区危险性增强,可以通过对储罐设置安全屏障等措施,有效的切 断导致事故最大概率的链条。     

环境污染应急处置技术的CBR-MADM两步筛选法模型

突发环境污染事件进行应急处置时,需要在历史案例库和处置技术库的基础上通过筛选模型筛选出最适宜的应急处置技术.其中筛选的效率和准确性是构建技术筛选模型的首要因素,目前尚无较为满意的解决方案.本文结合案例推理技术(CBR)和模糊多属性群决策模型(MADM)的优势,建立了环境污染应急处置技术的CBR-MADM两步筛选法模型:第1步,先利用基于熵权G1法的CBR推理从案例库中匹配案例,再从相似度最高的几个案例中提取应急处置技术作为备选技术;第2步,利用MADM对备选技术进行筛选和决策.CBR-MADM两步筛选法既充分利用了历史处置经验,又极大地提高了应急处置技术的筛选速度和效率.将该方法应用于2012年底山西长治浊漳河苯胺泄漏污染事件中,成功筛选出“投加混凝剂-活性炭坝拦截”技术,同实际情况吻合,验证了其适用性和可行性.