Dynamic properties of green water event in the overtopping of extreme waves on a fixed dock

A statistical model is developed to predict wave overtopping volume and rate of extreme waves on a fixed deck. The probability density function for the volume and rate of overtopping water are formulated based on the truncated Weibull distribution with the assumption of local sinusoidal profile for small amplitude waves. Sensitivity to the wave nonlinearity parameter and deck clearance is discussed. The statistical model is compared to laboratory data of the instantaneous free surface elevation measured in front of a fixed deck, and overtopping volume and overtopping rate measured at the leading edge of the deck. The statistical theory compared well with the measured exceedance probability seaward of the deck. The model prediction of the exceedance probability of deck overtopping gave qualitatively good agreement for large overtopping values.     

Distribution of nonlinear wave crests

The distribution of nonlinear wave crests is examined on the basis of a theoretical probability density previously given elsewhere (J. Eng. Mech. 120 (1994) 1009). Certain errors contained in the original theoretical density are corrected, and the corresponding exceedance distribution is derived. The resulting theoretical forms of the probability density and exceedance distribution are then slightly simplified and compared with nonlinear wave data gathered under hurricane conditions. The results indicate that the proposed theoretical forms describe the observed distributions of large wave crests better than the Rayleigh law. However, the quantitative accuracy of the predictions is somewhat poor, as is typical of approximate theories based on Gram–Charlier-type expansions.     

UNB多波束数据格式解析

采用VB进行程序设计,实现了对数据文件的解析,提取出了各种不同类型的数据,介绍了数据的处理与应用.     

基于生态足迹模型的山区生态经济协调发展定量评估--以贵州镇远县为例

采用国际上逐渐引起重视的衡量可持续发展的生物物理方法——生态足迹(Ecological Footprint),在简要介绍该理论方法的基础上,针对当前我国西部山地型生态经济类型区发展现状和面临的生态问题,以我国西南山区镇远县为例,采用该地区生态经济发展的截面资料,对其生态经济协调发展的状态进行了定量评估,并对其发展趋势做了保守估计。结果表明:目前地区的生态足迹需求小于生态供给能力,生态盈余为0.0677hm~2;生态空间供需结构存在明显的不对称性;自然资源利用率低于整个西部和东部沿海省份。以目前的趋势来看,生态盈余状态最多能维持5～15a。     

西北四省(区)2000年的水资源足迹

水资源足迹是如实反映人类对水资源消费利用的新概念,能深刻揭示社会经济系统对水资源的消费,为干旱缺水地区水资源科学管理提供了一个新视角.提出了水资源足迹的概念和衡量方法,引进了虚拟水概念,简要介绍了产品虚拟水计算方法,并以新疆、青海、甘肃和陕西为例,计算分析了2000年各省水资源足迹.结果表明,2000年西北四省(区)总的水足迹是为613.3×108m3,人均水足迹为712.3m3·人-1·a-1和1952L·人-1·d-1,高于统计的水资源利用量.以虚拟水概念为基础的水资源足迹更真实地衡量了社会经济系统对水资源的消费利用状况,为解决区域水资源短缺和创新水资源管理体制提供了新思路,产品形式的虚拟水贸易是平衡水资源赤字、维持区域水安全的有效工具.     

A Simple Parameterisation for Flux Footprint Predictions

Flux footprint functions estimate the location and relative importance of passive scalar sources influencing flux measurements at a given receptor height. These footprint estimates strongly vary in size, depending on receptor height, atmospheric stability, and surface roughness. Reliable footprint calculations from, e.g., Lagrangian stochastic models or large-eddy simulations are computationally expensive and cannot readily be computed for long-term observational programs. To facilitate more accessible footprint estimates, a scaling procedure is introduced for flux footprint functions over a range of stratifications from convective to stable, and receptor heights ranging from near the surface to the middle of the boundary layer. It is shown that, when applying this scaling procedure, footprint estimates collapse to an ensemble of similar curves. A simple parameterisation for the scaled footprint estimates is presented. This parameterisation accounts for the influence of the roughness length on the footprint and allows for a quick but precise algebraic footprint estimation.     

Geographical distribution of ecological footprint and sustainability analysis for Liaoning Province

This paper presents the detailed results and analyses on the ecological footprints and bio-capacities of the individual cities and the province as a whole for the year 2001, providing a clear picture of sustainability for the province. Results show that the ecological footprints of most cities in Liaoning exceeded their respective bio-capacities, incurring high ecological deficits. The ecological deficit of the province as a whole was 1.31 ha/cap. Those cities with resources extraction and/or primary material-making as their major industries constitute the "ecologically black band", whose ecological deficits ranged from 2.45 to 5.23 ha/cap, the highest of all cities in the province. Fossil energy consumption was the major source of footprint amounting to 1.63 ha/cap at the provincial level, taking up 67.3% of the total. For cropland, modest ecological surpluses occurred in Jinzhou, Tieling, Huludao, and Panjin while modest ecological deficits in Dalian, Benxi, Fushun, and Dandong, resulting in an overall surplus for the province. Liaoning had a certain level of surplus in fishing ground (water area), mainly distributed in the coastal cities of Dalian, Panjin, Huludao, Yingkou, Jinzhou, and Dandong. Most cities had a small ecological deficit in pasture and all had a small ecological surplus in forest. The eco-efficiency, expressed as GDP value per hectare of footprint, exhibits high variations among the cities, with the highest (Shenyang) more than 10 times the lowest (Fuxin). Cities with manufacture, high-tech, and better developed service industries had high eco-efficiency, while those with resources extraction, primary material-making, and less developed service industries had low eco-efficiency. Based on the components and geographical distribution of ecological footprint, strategic policy implications are outlined for Liaoning's development toward a sustainable future.     

Vertical structures of PM10 and PM 2.5 and their dynamical character in low atmosphere in Beijing urban areas

The vertical structures and their dynamical character of PM2.5 and PM10 over Beijing urban areas are revealed using the 1 min mean continuous mass concentration data of PM2.5 and PM10 at 8, 100, and 320 m heights of the meteorological observation tower of 325 m at Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP CAS tower hereafter) on 10―26 August, 2003, as well as the daily mean mass concentration data of PM2.5 and PM10 and the continuous data of CO and NO2 at 8, 100 (low layer), 200 (middle layer), and 320 m (high layer) heights, in combination with the same period meteorological field observation data of the meteorological tower. The vertical distributions of aerosols observed on IAP CAS tower in Beijing can be roughly divided into two patterns: gradually and rapidly decreasing patterns, I.e. The vertical distribution of aerosols in calm weather or on pollution day belongs to the gradually decreasing pattern, while one on clean day or weak cold air day belongs to the rapidly decreasing pattern. The vertical distributive characters of aerosols were closely related with the dynamical/thermal structure and turbulence character of the atmosphere boundary layer. On the clean day, the low layer PM2.5 and PM10 concentrations were close to those at 8 m height, while the concentrations rapidly decreased at the high layer, and their values were only one half of those at 8 m, especially, the concentration of PM2.5 dropped even more. On the clean day, there existed stronger turbulence below 150 m, aerosols were well mixed, but blocked by the more stronger inversion layer aloft, and meanwhile, at various heights, especially in the high layer, the horizontal wind speed was larger, resulting in the rapid decrease of aerosol concentration, I.e. Resulting in the obvious vertical difference of aerosol concentrations between the low and high layers. On the pollution day, the concentrations of PM2.5 and PM10 at the low, middle, and high layers dropped successively by, on average, about 10% for each layer in comparison with those at 8 m height. On pollution days, in company with the low wind speed, there existed two shallow inversion layers in the boundary layer, but aerosols might be, to some extent, mixed below the inversion layer, therefore, on the pollution day the concentrations of PM2.5 and PM10 dropped with height slowly; and the observational results also show that the concentrations at 320 m height were obviously high under SW and SE winds, but at other heights, the concentrations were not correlated with wind directions. The computational results of footprint analysis suggest that this was due to the fact that the 320 m height was impacted by the pollutants transfer of southerly flow from the southern peripheral heavier polluted areas, such as Baoding, and Shijiazhuang of Hebei Province, Tianjin, and Shandong Province, etc., while the low layer was only affected by Beijing's local pollution source. The computational results of power spectra and periods preliminarily reveal that under the condition of calm weather, the periods of PM10 concentration at various heights of the tower were on the order of minutes, while in cases of larger wind speed, the concentrations of PM2.5 and PM10 at 320 m height not only had the short periods of minute-order, but also the longer periods of hour order. Consistent with the conclusion previously drawn by Ding et al., that air pollutants at different heights and at different sites in Beijing had the character of "in-phase" variation, was also observed for the diurnal variation and mean diurnal variation of PM2.5 and PM10 at various heights of the tower in this experiment, again confirming the "in-phase" temporal/spatial distributive character of air pollutants in the urban canopy of Beijing. The gentle double-peak character of the mean diurnal variation of PM2.5 and PM10 was closely related with the evident/similar diurnal variation of turbulent momentum fluxes, sensible heat fluxes, and turbulent kinetic energy at various heights in the urban canopy. Besides, under the condition of calm weather, the concentration of PM2.5 and PM10 declined with height slowly, it was 90% of 8 m concentration at the low layer, a little lesser than 90% at the middle layer, and 80% at the high layer, respectively. Under the condition of weak cold air weather, the concentration remarkably dropped with height, it was 70% of 8 m concentration at the low layer, and 20%―30% at the middle and high layers, especially the concentration of PM2.5 was even lower.     

兰州大学(盘旋路校区)2003年生态足迹调查分析

人均消费产品的数量是计算区域人均生态足迹关键和基础的一步。通过实地问卷调查，运用自下而上法收集资料，计算小尺度生态足迹。兰州大学(盘旋路校区)2003年的生态足迹计算结果为：人均生态足迹0．892hm^2，男、女生的人均生态足迹分别为0．976hm^2和0．788hm^2。这些数据与全国或者西部的人均生态足迹相比明显偏低，但总生态足迹为4119．3hm^2，是校园面积的73．7倍。因此，应合理利用自然资源，减少学生的生态足迹，真正做到可持续发展。     

生态足迹模型在山区生态可持续评价中的初步应用--以1999年北京西部山区为例

在剖析生态足迹分析法的理论基础上，进一步考虑不同消费水平对生态足迹时空变异的影响，划分农村居民和城镇居民两类不同的消费群体，分别计算各自的生态足迹，其次进一步细化模型中人均水资源足迹，从而构建生态足迹与生态容量平衡模型。根据平衡模型计算出生态盈亏，得出区域生态持续性评价结果。并以1999年北京西部山区门头沟区为例，进行模型计算和生态可持续评价，结果表明1999年门头沟区处于生态赤字状态，说明该区生态系统处于不可持续状态。在对门头沟区的初步研究基础上，指出生态足迹作为山区生态可持续评价指标的优点及当前存在的缺点。