钢铅组合防屈曲支撑的滞回性能与参数研究

为简化防屈曲支撑的加工工艺,提高防屈曲支撑的初始刚度和在小变形下的耗能能力,基于现有防屈曲支撑在截面形式与构造方式上的特点,提出了一种新型钢铅组合防屈曲支撑并进行了构造设计。通过有限元数值模拟,分析了钢铅组合防屈曲支撑的耗能特性与效果,建立了恢复力简化模型,并根据理想弹塑性材料本构关系推导出滞回规则。通过对不同设计参数的理论分析和数值模拟,分析了钢铅屈服力比、铅剪切面长宽比、核心段宽厚比和耗能段长度等参数对防屈曲支撑滞回性能的影响。研究结果表明,钢铅组合防屈曲支撑能够提供较大的抗侧刚度,耗能效果良好,加工工艺简单,适合工程应用。     

1980年以来中国大宗作物空间格局变化分析

利用1980～2014年间的大宗作物(玉米、水稻、小麦、棉花、油菜)面积数据,以省级行政区为研究单元,采用多种数理统计和GIS空间分析技术,结合同期作物之间的竞争性用地关系,对全国上述五类大宗作物的空间分布格局及其变化特征进行分析.研究结果表明:玉米的空间分布相对较均衡;小麦的空间格局总的变化不明显但是省际分布最不均衡;棉花近30 a来空间格局变化极其显著,其面积重心从河南境内不断地向西北地区移动,目前位于甘肃省境内;油菜的面积重心自湖北境内不断地向南推移到湖南境内,水稻的面积重心则自江西境内逐渐向北移动到湖北境内.另外,部分区域的同期作物(如油菜与小麦、棉花与春玉米)空间格局变化存在明显的“消-长”关系,特别是在甘肃和内蒙,油菜小麦的面积变化有着极强的负相关性,其pearson系数低于-0.8.作物种植的成本收益变化是造成这些大宗作物空间格局变化的主要原因,城市化发展的程度、农民非农就业机会的高低、同期作物之间的比较效益差距等也是这些大宗作物时空格局产生变化的重要原因.     

硝酸盐氮,亚硝酸盐氮总量紫外吸收快速测定

水体中尤其是海水中硝酸盐氮的测定较繁琐,干扰物质多,分析时间长,重现性差,准确性不高。文章通过实验介绍一种省时、省力、简便可行不消耗化学试剂且抗氯化物干扰、精度和准确度较高的硝酸盐氮、亚硝酸盐氮总量测定方法。     

负荷历时曲线法在梁子湖流域污染容量总量控制中的应用

采用负荷历时曲线法(LDC),基于水质保护目标,研究水体纳污能力,确定最大日负荷总量(TMDL)是当前流域污染总量控制的主要方法之一。根据梁子湖高桥河流域控制断面2008~2011年的水文、水质数据,以主要污染物COD为指标,将负荷历史曲线法运用到梁子湖高桥河等子流域污染容量总量控制中,对该流域的最大日负荷(TMDL)变化规律进行分析,提出流域不同水文条件下的污染负荷消减量。研究结果表明:梁子湖水环境受面源污染影响较大。高桥河、徐家港、张家桥港、山坡港、宁港流域,在高流量期实际负荷值均已超出了允许负荷,其削减量分别为61.36、4.33、12.98、3.84、7.13 t/d;徐家港和宁港流域在丰水期实际负荷值也超出了允许负荷,削减量分别为0.16、0.17 t/d。该研究为流域相关管理部门对湖泊水环境的污染控制提供可靠的决策依据。     

SCS URBAN CURVE NUMBERS FROM A LANDSAT DATA BASE1

Estimating the Curve Numbers used in the Soil Conservation Service hydrologic models is a tedious and costly task. Recent advances in remote sensing and data processing have led to the development of readily available land cover data bases for many areas of the United States. This study evaluated the potential of using a Landsat data base to make the Curve Number estimation process more cost-effective and less tedious. Ten watersheds in the Washington, D.C., area were evaluated using a Landsat land cover data base developed by the U.S. Geological Survey. Results showed that these data can be useful. Predictions can be improved if ancillary data on residential lot size are included. It was concluded that this type of data base must be examined carefully before implementation.     

EVALUATION OF CURVE NUMBER PROCEDURES TO PREDICT RUNOFF IN GLEAMS1

ABSTRACT: Proper selection of curve number values will improve the capability of the SCS-Curve Number procedure in predicting runoff. Both CREAMS and GLEAMS models use the Smith and Williams (1980) approach of converting CNII (curve number value for average antecedent moisture conditions) into CNI (curve number value for dry antecedent moisture conditions) in calculating the soil retention parameter (S). CREAMS and GLEAMS have been found to under predict runoff because of the internal conversion of CNII to CNI. This study shows modifications of the GLEAMS model using CMI without converting it to CM and it also shows the seasonal curve number approaches with and without converting CNII to CNI. Results indicate that using CNII without internal conversion to CNI provides better runoff and erosion predictions than the original version of GLEAMS and versions with seasonal curve numbers when tested with four years of field data in the Coastal Plain physiographic region of Maryland.     

Nonparametric Monte Carlo Simulation for Flood Frequency Curve Derivation: An Application to a Korean Watershed1

Abstract: A mix of causative mechanisms may be responsible for flood at a site. Floods may be caused because of extreme rainfall or rain on other rainfall events. The statistical attributes of these events differ according to the watershed characteristics and the causes. Traditional methods of flood frequency analysis are only adequate for specific situations. Also, to address the uncertainty of flood frequency estimates for hydraulic structures, a series of probabilistic analyses of rainfall‐runoff and flow routing models, and their associated inputs, are used. This is a complex problem in that the probability distributions of multiple independent and derived random variables need to be estimated to evaluate the probability of floods. Therefore, the objectives of this study were to develop a flood frequency curve derivation method driven by multiple random variables and to develop a tool that can consider the uncertainties of design floods. This study focuses on developing a flood frequency curve based on nonparametric statistical methods for the estimation of probabilities of rare floods that are more appropriate in Korea. To derive the frequency curve, rainfall generation using the nonparametric kernel density estimation approach is proposed. Many flood events are simulated by nonparametric Monte Carlo simulations coupled with the center Latin hypercube sampling method to estimate the associated uncertainty. This study applies the methods described to a Korean watershed. The results provide higher physical appropriateness and reasonable estimates of design flood.     

CURVE NUMBER HYDROLOGY IN WATER QUALITY MODELING: USES,ABUSES, AND FUTURE DIRECTIONS1

ABSTRACT: Although the curve number method of the Natural Resources Conservation Service has been used as the foundation of the hydrology algorithms in many nonpoint source water quality models, there are significant problematic issues with the way it has been implemented and interpreted that are not generally recognized. This usage is based on misconceptions about the meaning of the runoff value that the method computes, which is a likely fundamental cause of uncertainty in subsequent erosion and pollutant loading predictions dependent on this value. As a result, there are some major limitations on the conclusions and decisions about the effects of management practices on water quality that can be supported with current nonpoint source water quality models. They also cannot supply the detailed quantitative and spatial information needed to address emerging issues. A key prerequisite for improving model predictions is to improve the hydrologic algorithms contained within them. The use of the curve number method is still appropriate for flood hydrograph engineering applications, but more physically based algorithms that simulate all streamflow generating processes are needed for nonpoint source water quality modeling. Spatially distributed hydrologic modeling has tremendous potential in achieving this goal.     

Nitrogen accumulation and plant species replacement in three salt marsh systems in the Wadden Sea

Salt marsh development on the coastal barrier island of Schiermonnikoog (The Netherlands) was compared with two other salt marsh systems in the Wadden Sea. Accretion rate, nitrogen accumulation and changes in plant species composition were investigated using chronosequences. The age of the marsh was estimated from aerial photographs and old maps. In 7230 plots, the elevation of the marsh surface, the thickness of the sediment layer (clay) and the presence of plant species was recorded. In addition, the nitrogen pool was measured at each successional stage. Accretion rates were similar in the three salt marshes. Higher accretion rates were found at younger marshes. A strong linear relationship between nitrogen pool size and thickness of the clay layer was found for the three marshes. The accumulation rate of nitrogen is therefore strongly related to the accretion rate. Thus, more nitrogen is present in the sediment of later successional stages where more clay has accumulated. On the high salt marsh (55 cm+MHT),Ameria maritima disappeared andArtemisia maritima, Juncus gerardi andElymus athericus established at sites with a thicker clay layer. On the low salt marsh (25 cm+MHT),Plantago maritima, Puccinellia maritima andLimonium vulgare disappeared andAtriplex (Halimione) portulacoides established. Apparently, with the accumulation of clay and therefore of nitrogen, tall growing species take over in salt marshes not grazed by livestock.     

Scaling down the “Netherlands Fallacy”: a local-level quantitative study of the effect of affluence on the carbon footprint across the United States

Much quantitative research examining the determinants of the ecological footprint has been conducted cross-nationally, where data on cross-boundary flows have been readily available. While local-level studies of the footprint do exist for specific localities, most quantitative research at this scale has examined direct environmental impacts attributed to the internal activities of the locality, for instance, carbon emissions. Our analysis builds on this previous work by exploiting a local-level carbon footprint dataset with coverage for 28,321 zip codes across the United States. Following prior research, we focus on the effect of local affluence, measured in terms of median household income. In spatial regression models, we regress the per capita carbon footprint on local affluence, controlling for a variety of other factors. Consistent with previous work, we find that affluence is positively correlated the carbon footprint and there is no evidence of an environmental Kuznets curve. In the conclusion, we review the results of the study and discuss their implications for policy, specifically in terms of cross-boundary environmental problems.