贝诺特工法在香港大澳岛避风塘码头超深桩工程中的应用

介绍了贝诺特工法在香港大澳岛避风塘码头的超深灌注桩工程中的施工情况，并对其优越性及在国内的发展前景作了简要分析。     

泥石流运动衰减动力学初步研究

我国公路泥石流病害严重，泥石流淤埋公路构建筑物是一类常见的公路泥石流病害类型。泥石流衰减动力学是防治泥石流淤埋病害的重要关键技术，也是泥石流运动学、动力学研究的核心问题之一。本文作者运用泥沙运动力学及流体力学原理，初步建立了泥石流固相颗粒和液相浆体的能量衰减条件，把泥石流衰减模式概化为两类，即能量抑制衰减和能量自由衰减；通过泥石流沉积模型试验，得到了不同粘度泥石流体的沉积扇变化形态，随着泥石流体粘度的增大，沉积扇边缘变陡、扩展范围变小、纵轴线长度减小等结论与实际情况吻合；初步建立了泥石流能量衰减速率计算方法。研究成果为防治公路泥石流病害奠定了基础。     

经济欠发达地区县级城镇居民休闲时间利用特征分析--以云南蒙自县为例

随着县级城镇社会经济的迅速发展,城镇居民的休闲时间日渐增多,休闲时间的利用成为人们关注的焦点。以蒙自为案例地的中国经济欠发达地区县级城镇居民的休闲时间利用结构已经日趋多样化,但主要还是集中于看电视、散步、书报业务学习、家庭娱乐、做家务等几项传统休闲方式,家庭内休闲在城镇居民的休闲活动中占了很大比重,这反映出休闲时间利用低水平的问题。县级城镇休闲设施和休闲产业都比较落后,影响了城镇居民休闲质量的提高和休闲消费、休闲经济的发展。因此,政府及有关部门应努力改善城镇的休闲设施,大力发展休闲产业,从多方面引导居民科学、有效、合理地利用休闲时间,最终促进休闲经济的发展,提高城镇居民的生活质量。     

中国陆地净初级生产力的季节变化研究

了解不同季节陆地净初级生产力(NPP)的变化及与气候的相互关系以及在不同地类的差异对深刻理解我国陆地生态系统对全球气候变化的响应和陆地碳循环研究具有重要意义。本文使用1981～2000年间GLO-PEM模型模拟的我国陆地NPP数据和同期气温、降水以及土地利用数据, 研究不同季节我国陆地植被NPP的变化。结果表明,在1981～2000年期间,四个季节的NPP都呈显著增加趋势,春季是NPP增加速率最快的季节,夏季是NPP增加量最大的季节。耕地在春、夏和秋季NPP增长和增长率最高,林地冬季NPP增长最多而水域冬季NPP增长率最高。夏季NPP增长最高的区域分布于我国东部的多数地区、内蒙古东部、四川盆地、贵州东部、藏南和新疆西部;夏季NPP降低最多的区域分布于在呼伦贝尔高原、鄂尔多斯高原、黄土高原、青藏高原东部和新疆西北部。     

矢量元胞自动机中的邻域影响力度量——以深圳市为例

基于矢量元胞自动机(cellular automata,CA),对深圳市城市土地利用变更模拟中的邻域影响力进行了讨论,选取矢量密度因子及矢量邻域索引构建邻域影响力函数.根据深圳市路网数据及相关参数权重,计算地块通达度及发展为居住或生产用地的适宜度,同时结合政府规划的土地利用分区状态进行土地利用变更的模拟.使用Kappa...     

北秦岭二郎坪群抱树坪组沉积时代与构造环境

二郎坪群抱树坪组作为北秦岭早古生代重要的沉积记录,其研究程度较低。本文通过对抱树坪组内火山岩夹层和花岗斑岩脉进行岩石学、地球化学和锆石U- Pb测年研究,旨在进一步确定其沉积时代与构造环境。研究结果表明：豫西夏馆地区抱树坪组火山岩夹层已变质为（黑云）阳起钠长片岩,常与黑云石英片岩呈“互层状”产出;岩石原岩为安山质凝灰岩,具有相对低的SiO2（52. 56%~62. 04%）、较高的Al2O3（10. 70%~18. 55%）、低的MgO（4. 06%~6. 21%）和FeOT/MgO（1. 23~1. 81）,富集轻稀土元素和大离子亲石元素Rb、Th、U、K,相对亏损高场强元素Nb、Ta、P、Ti,具镁安山质岩石的特点;结合地球化学特征及前人研究认为,抱树坪组可能形成于活动陆缘弧后盆地。获得黑云阳起钠长片岩原岩的结晶锆石U- Pb年龄为446. 0±1. 7 Ma,以及侵入其中花岗斑岩脉的成岩年龄为430. 0±3. 0 Ma,首次将抱树坪组的形成时代准确地限定为晚奥陶世至早志留世。综合区域研究成果认为,小寨组和抱树坪组在地层层序和地层时代上符合广义二郎坪群的划分方案,但大庙组、火神庙组及由小寨组和抱树坪组构成的整体三者在形成时代上表现为近于同时性,在空间上主体呈现近平行关系,可能主体属时代大体相当的不同沉积环境的产物;在大地构造属性方面,认为二郎坪群是在约470 Ma之前由于商丹洋向北俯冲而形成的火山岛弧,在470~436 Ma转化为弧后盆地,至约430 Ma之前最终完成消减闭合。     

东北太平洋一次强爆发性气旋发展的机制分析

使用FNL Analysis全球格点资料,对东北太平洋一次强爆发性气旋的特殊性进行了分析,发现气旋对其西北部低压系统的吸收合并是其爆发性发展过程中的典型特征,斜压强迫对其快速发展的作用较弱,与西北太平洋爆发性气旋的发展过程存在显著差异。同时,使用Zwack-Okossi诊断方程,从影响爆发性发展的动力和热力因子方面,对其发展机制作了深入的探讨。研究表明,正涡度平流、暖平流和非绝热加热的共同作用使气旋开始爆发性发展,由潜热释放导致的非绝热加热的贡献最大,非绝热加热是其快速发展的主导因子,其中正涡度平流贡献主要来自于中高层,暖平流的贡献主要来自于中低层和高层,而非绝热加热主要发生在中低层,这为东北太平洋爆发性气旋的发展机制提供了一个新的认识。     

中国地区三种地表反照率产品比较

利用2007—2011年MODIS、GlobAlbedo和ERA-Interim的3种地表反照率产品,借助地理信息系统(Geographic Information System, GIS)空间化技术,对中国地区3种地表反照率产品进行了对比分析。结果表明：3种产品与气象站观测值的时间分布趋势一致,冬季高夏季低,且相关性较高。3种产品中,MODIS与GlobAlbedo的绝对差异值最小,ERA-Interim与MODIS、GlobAlbedo的绝对差异值较大。3种产品在青藏高原和西北山地区域表现出较大的差异,且差异表现为冬半年高,夏半年低。3种产品之间相关性最高的是MODIS与GlobAlbedo,最低的是MODIS与ERA-Interim, 3种产品在40°N以北具有较好的相关性。且在夏季和冬季地表反照率均值的表现说明,ERA-Interim相比MODIS、GlobAlbedo难以反映地表反照率受地形和土地覆被的影响。     

Influence of Near Real-Time Green Vegetation Fraction Data on Numerical Weather Prediction by WRF over North China

The green vegetation fraction(GVF) can greatly influence the partitioning of surface sensible and latent heat fluxes in numerical weather prediction(NWP) models. However, the multiyear averaged monthly GVF climatology—the most commonly used representation of the vegetation state in models—cannot capture the real-time vegetation state well. In this study, a near real-time(NRT) GVF dataset generated from an 8-day composite of the normalized difference vegetation index is compared with the 10-yr averaged monthly GVF provided by the WRF model. The annual variability of the GVF over North China is examined in detail. Many differences between the two GVF datasets are found over dryland, grassland, and cropland/grassland mosaic areas. Two experiments using different GVF datasets are performed to assess the impacts of GVF on forecasts of screen-level temperature and humidity. The results show that using NRT GVF can lead to a widespread reduction of 2-m temperature forecast errors from April to October.Evaluation against in-situ observations shows that the positive impact on 2-m temperature forecasts in the morning is more distinct than that in the afternoon. Our study demonstrates that NRT GVF can provide a more realistic representation of the vegetation state, which in turn helps to improve short-range forecasts in arid and semiarid regions of North China. Moreover, our study shows that the negative effect of using NRT GVF is closely related to the initial soil moisture.     

Evaluation of Global Gridded Precipitation and Temperature Datasets against Gauged Observations over the Upper Tekeze River Basin,Ethiopia

The availability of satellite and reanalysis climate datasets and their applicability have been greatly promoted in hydro-climatic studies. However, such climatic products are still subject to considerable uncertainties and an evaluation of the products is necessary for applications in specific regions. This study aims to evaluate the reliability of nine gridded precipitation and temperature datasets against ground-based observations in the upper Tekeze River basin(UTB) of Ethiopia from 1982 to 2016. Precipitation, maximum temperature(T_(max)), minimum temperature(T_(min)), and mean temperature(T_(mean)) were evaluated at daily and monthly timescales. The results show that the best estimates of precipitation are from the Eart H2 Observe, WFDEI, and ERA-Interim reanalysis data Merged and Bias-corrected for the Inter-Sectoral Impact Model Intercomparison Project(EWEMBI), and the Climate Hazards Group Infra Red Precipitation with Station data(CHIRPS) datasets. The percentage biases and correlation coefficients(CCs) are within ±15% and 0.5, respectively, for both EWEMBI and CHIRPS at the two timescales. All products underestimate the drought conditions indicated by the standardized precipitation index(SPI), while the EWEMBI and CHIRPS datasets show higher agreement with the observations than other datasets. The Tmean estimates produced by the ECMWF ReAnalysis version 5(ERA5) and the Climate Hazards Group Infra Red Temperature with Station data(CHIRTS) are the closest to the observations, with CCs of 0.65 and 0.55, respectively, at the daily timescale. The CHIRTS and EWEMBI datasets show better representations of Tmax(T_(min)), with CCs of 0.69(0.72) and 0.62(0.68), respectively,at the monthly timescale. The temperature extremes are better captured by the ERA5(T_(mean)), CHIRTS(T_(max)), and EWEMBI(T_(min)) datasets. The findings of this study provide useful information to select the most appropriate dataset for hydrometeorological studies in the UTB and could help to improve the regional representation of global datasets.