基于剪切波速的深层砂土地震液化研究     

王薇  李恒  徐利军 《大地测量与地球动力学》2019,39(1):93-97

阐述了剪切波速法判别饱和砂土液化的原理，结合武汉地区某工程实例，对场地内埋深超越“规范法”适用范围的砂层进行液化判别，确定场地的临界液化深度。通过与室内动三轴试验的对比得出，2种方法的液化判别结果及确定的临界液化深度均吻合较好，验证了以剪切波速为指标的液化评估方法的可行性。  相似文献   

利用GLAS激光测高数据评估DSM产品质量及精度优化   总被引：2，自引：0，他引：2  

胡柳茹  唐新明  李国元  付冬暇  窦显辉  赵世湖 《测绘通报》2019,(11):39-43

提出了一种利用卫星激光测高数据直接优化提升数字表面模型（DSM）产品精度的方法。选取境外中亚地区的资源三号DSM开展试验，通过采用多准则约束方法提取激光高程控制点，分别利用偏度、中值、线性、二次多项式等进行DSM误差修正，发现4种模型均能有效消除DSM系统误差，其中基于二次多项式的方法更适用于平地和丘陵地貌，线性模型更适用于高山地貌。试验验证了采用卫星激光测高数据优化境外DSM技术流程的可行性，最终可提高DSM的绝对高程精度。  相似文献   

Influence of a coarse interlayer on seawater intrusion and contaminant migration in coastal aquifers          下载免费PDF全文

Yi Liu  Xiaomin Mao  Jian Chen  D. A. Barry 《水文研究》2014,28(20):5162-5175

Vertical 2D slice laboratory experiments were carried out in homogenous and layered sand tanks to elucidate the effects of a highly permeable (coarse‐grained sand) interlayer on seawater intrusion and transport of contaminants to a coastal sea. Tidal fluctuations produced oscillations in the seawater–freshwater transition zone, fluctuations of the contaminant infiltration rate and a zigzag contaminant plume outline. The seawater wedge became discontinuous at the (vertical) edges of the interlayer because of increased lateral movement of the seawater–freshwater interface within the interlayer. The contaminant plume formed a tail within the interlayer depending on the tidal stage, and similar to the wedge, its movement was accentuated. A simple analytical model that neglected vertical flow reliably predicted steady‐state seawater intrusion into the coastal aquifer. Numerical modeling was used to gain insight into the groundwater hydrodynamics and contaminant migration. The numerical results confirmed the experimental findings, i.e. that a highly permeable interlayer can provide a rapid transit path for contaminants to reach the seaward boundary and that the interlayer amplifies the effects of tidal fluctuations, resulting in wider transition zones for the seawater wedge and contaminant plume. Numerical simulations further showed that, with increasing interlayer hydraulic conductivity, the maximum seawater intrusion distance inside the interlayer increases approximately linearly. For the fixed‐head contaminant injection condition used, the model showed that contaminant infiltration increases approximately logarithmically with increasing interlayer hydraulic conductivity (other factors held fixed). Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

Inference and uncertainty of snow depth spatial distribution at the kilometre scale in the Colorado Rocky Mountains: the effects of sample size,random sampling,predictor quality,and validation procedures          下载免费PDF全文

J. L. McCreight  A. G. Slater  H. P. Marshall  B. Rajagopalan 《水文研究》2014,28(3):933-957

Historically, observing snow depth over large areas has been difficult. When snow depth observations are sparse, regression models can be used to infer the snow depth over a given area. Data sparsity has also left many important questions about such inference unexamined. Improved inference, or estimation, of snow depth and its spatial distribution from a given set of observations can benefit a wide range of applications from water resource management, to ecological studies, to validation of satellite estimates of snow pack. The development of Light Detection and Ranging (LiDAR) technology has provided non‐sparse snow depth measurements, which we use in this study, to address fundamental questions about snow depth inference using both sparse and non‐sparse observations. For example, when are more data needed and when are data redundant? Results apply to both traditional and manual snow depth measurements and to LiDAR observations. Through sampling experiments on high‐resolution LiDAR snow depth observations at six separate 1.17‐km² sites in the Colorado Rocky Mountains, we provide novel perspectives on a variety of issues affecting the regression estimation of snow depth from sparse observations. We measure the effects of observation count, random selection of observations, quality of predictor variables, and cross‐validation procedures using three skill metrics: percent error in total snow volume, root mean squared error (RMSE), and R². Extremes of predictor quality are used to understand the range of its effect; how do predictors downloaded from internet perform against more accurate predictors measured by LiDAR? Whereas cross validation remains the only option for validating inference from sparse observations, in our experiments, the full set of LiDAR‐measured snow depths can be considered the ‘true’ spatial distribution and used to understand cross‐validation bias at the spatial scale of inference. We model at the 30‐m resolution of readily available predictors, which is a popular spatial resolution in the literature. Three regression models are also compared, and we briefly examine how sampling design affects model skill. Results quantify the primary dependence of each skill metric on observation count that ranges over three orders of magnitude, doubling at each step from 25 up to 3200. Whereas uncertainty (resulting from random selection of observations) in percent error of true total snow volume is typically well constrained by 100–200 observations, there is considerable uncertainty in the inferred spatial distribution (R²) even at medium observation counts (200–800). We show that percent error in total snow volume is not sensitive to predictor quality, although RMSE and R² (measures of spatial distribution) often depend critically on it. Inaccuracies of downloaded predictors (most often the vegetation predictors) can easily require a quadrupling of observation count to match RMSE and R² scores obtained by LiDAR‐measured predictors. Under cross validation, the RMSE and R² skill measures are consistently biased towards poorer results than their true validations. This is primarily a result of greater variance at the spatial scales of point observations used for cross validation than at the 30‐m resolution of the model. The magnitude of this bias depends on individual site characteristics, observation count (for our experimental design), and sampling design. Sampling designs that maximize independent information maximize cross‐validation bias but also maximize true R². The bagging tree model is found to generally outperform the other regression models in the study on several criteria. Finally, we discuss and recommend use of LiDAR in conjunction with regression modelling to advance understanding of snow depth spatial distribution at spatial scales of thousands of square kilometres. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

牡蛎对浮游植物群落下行控制作用的围隔实验研究     

王兆慧  张光涛 《海洋科学》2020,44(9):47-53

牡蛎的滤食作用不但能控制浮游植物丰度，还能通过摄食选择性影响群落结构。通过在较高营养水体的围隔实验表明，牡蛎养殖在持续磷限制条件下，促使浮游植物群落由甲藻向小型硅藻优势转变。实验结束时对照组中浮游植物群落由扁压原甲藻主导，占总丰度的77%；而牡蛎养殖组新月柱鞘藻丰度占比达到93%。牡蛎养殖组中，甲藻去除速率随养殖密度增长，但是硅藻最终丰度在高密度牡蛎组最高。研究结果说明大量的贝类养殖能够提升小型链状硅藻的优势度，增加此类赤潮发生风险。  相似文献   

Global Statistical Assessment and Cross-Calibration with Jason-2 for Reprocessed HY-2 A Altimeter Data     

Maofei Jiang  Ke Xu  Yalong Liu 《Marine Geodesy》2018,41(3):289-312

HY-2 A (Haiyang-2 A) satellite was launched on August 16, 2011 and radar altimeter is one of its main payloads. We reprocessed two years of HY-2 A altimeter sensor geophysical dataset records (SGDR) data. This paper presents the main results in terms of reprocessed HY-2 A altimeter data quality: verification of data availability and validity, monitoring several relevant altimeter parameters, and assessment of the HY-2 A altimeter system performances. A cross-calibration analysis of reprocessed HY-2 A altimeter data with Jason-2 was conducted. The reprocessed HY-2 A altimeter data show good quality and have a low level of noise with respect to Jason-2. The same geophysical correction methods were used to calculate the sea surface height (SSH) for the two missions. The mean standard deviations of the crossover differences for HY-2 A and Jason-2 are 5.24 cm and 5.34 cm, respectively. The mean standard deviation of the crossover differences between HY-2 A and Jason-2 is 5.37 cm. These show that HY-2 A can provide SSH measurements at almost the same level of accuracy as Jason-2. The relative SSH bias between HY-2 A and Jason-2 due to the Ultra Stable Oscillator (USO) drift is obviously observed, and it can affect the calculation of mean sea level and should be further studied and corrected.  相似文献   

SMAP卫星海表盐度产品的检验与校正     

秦思思  王辉  朱江  万莉颖  张宇  王昊运 《海洋学报(英文版)》2020,39(3):148-158

In this study, sea surface salinity(SSS) Level 3(L3) daily product derived from soil moisture active passive(SMAP)during the year 2016, was validated and compared with SSS daily products derived from soil Moisture and ocean salinity(SMOS) and in-situ measurements. Generally, the root mean square error(RMSE) of the daily SSS products is larger along the coastal areas and at high latitudes and is smaller in the tropical regions and open oceans. Comparisons between the two types of daily satellite SSS product revealed that the RMSE was higher in the daily SMOS product than in the SMAP, whereas the bias of the daily SMOS was observed to be less than that of the SMAP when compared with Argo floats data. In addition, the latitude-dependent bias and RMSE of the SMAP SSS were found to be primarily influenced by the precipitation and the sea surface temperature(SST). Then, a regression analysis method which has adopted the precipitation and SST data was used to correct the larger bias of the daily SMAP product. It was confirmed that the corrected daily SMAP product could be used for assimilation in high-resolution forecast models, due to the fact that it was demonstrated to be unbiased and much closer to the in-situ measurements than the original uncorrected SMAP product.  相似文献   

圆紫菜(Pyropia suborbiculata)减数分裂时期的遗传分析与叶状体形态建成     

杨秀文  丁洪昌  严兴洪  刘长军 《海洋与湖沼》2019,50(1):173-180

本文以圆紫菜的绿色突变体(LT)和红色突变体(HT)进行杂交实验,证实了圆紫菜减数分裂发生的时期,并观察了圆紫菜的早期发育和形态建成过程。杂交F1叶状体中,出现了2种亲本色和2种重组色,它们分别为绿色(G,母本色)、红色(R,父本色)、野生色(W)和黄褐色(Y)。4种颜色在F1叶状体中形成了大量由2—4个色块组成的颜色嵌合体,色块出现了分离并呈线性排列。F1叶状体中嵌合体所占比例为82.9%,其中两嵌合最多,三嵌合次之,四嵌合最少。4种颜色在嵌合体的分离比为1G:0.97R:0.88W:0.69Y。上述结果证实圆紫菜的减数分裂发生在壳孢子萌发初期。减数分裂产生的四分子呈线形排列,随后继续发育成叶状体,叶状体发育至7—9个细胞时进行第一次纵向分裂,叶状体形态变宽。随后,圆紫菜梢部开始大量形成和放散单孢子,最终导致圆紫菜的形状为圆形或肾脏形。  相似文献   

海表面温度时空变异特征及对验证误差影响     

蒋锦刚  徐曜  聂晨晖  潘骁骏  周斌 《遥感学报》2019,23(2):336-348

海洋要素的变化存在明显的区域性和季节性的变化特性,本文选择海洋要素中最为突出的海表面温度(SST)要素作为主要分析参数,设计时空变异参数的计算指标,分析时空变异对验证误差影响的关系,通过研究及试验的数据精度验证,证明了时空变异是造成误差的直接原因之一。强烈的时空属性变异,在验证过程中会引入很大的验证误差,处于不同变异等级区划的数据,其验证结果相对误差可达13.08%,变异越剧烈的区域,精度验证效果越差,验证误差就越大,这些误差并非完全是遥感产品的误差,验证结果不具有代表性,不能真实的反映遥感产品的误差特征。对于SST等海洋遥感产品验证时,需要考虑时空变异对验证误差的影响和贡献,合理选择验证试验区域、代表性的评价数据集和科学的评价方法。  相似文献   

中国区域MuSyQ叶面积指数产品验证与分析     

马培培  李静  柳钦火  何彬彬  赵静 《遥感学报》2019,23(6):1232-1252

对多源遥感数据协同生产的2010年—2015年中国区域1 km空间分辨率5天合成的MuSyQ（Multi-source data Synergized Quantitative remote sensing production system）叶面积指数LAI产品进行验证。参考现有的LAI产品（MODIS c5，GLASS LAI）和中国生态系统研究网络部分农田和森林站点可用的LAI地面测量数据，从时空连续性、时空一致性、精度和准确性等方面对中国区域的MuSyQ LAI产品进行定性和定量分析与评价。结果表明：（1） MuSyQ LAI产品在保证精度优于MODIS产品的情况下，时间分辨率和时空连续性均有提高。MuSyQ LAI与其他LAI产品（MODIS c5，GLASS LAI）在整体上有很好的一致性（RMSE=1.0，RMSE=0.81），但对常绿阔叶林高值处的描述不稳定；（2） 与LAI地面测量数据相比，MuSyQ LAI产品与地面参考图对比结果较好（最高相关性（R²=0.54）和较低总体误差（RMSE=0.96）），其在阔叶作物生长季高值处有些许低估且在某些阔叶林站点有些高估。整体上，MuSyQ LAI产品呈现出较高的精度，可靠的空间分布和连续稳定的时间分布，且对森林LAI的描述具有更可靠的动态范围。  相似文献