水下圆形浅滩附近波浪绕射的计算

采用波数矢量无旋和波能守恒方程对圆形浅滩附近水域波浪绕射进行了数值计算,计算模型中采用Ｂａｔｔｊｅｓ关系与波数矢量无旋,波能量守恒方程一起联合求解圆形浅滩附近水域波浪折射影响下的波浪要素。本文的数值计算模型对圆形浅滩水域波浪折射绕射现象的验证结果表明,计算所得结果与试验结果是吻合的,数学模型是可靠和合理的,具有实用价值。     

内蒙古呼伦湖表层沉积物的矿物组成和沉积速率

呼伦湖表层沉积物的取样和分析表明,沉积物主要由碎屑矿物和自生碳酸盐矿物组成。碳酸盐含量为10％—18％。碳酸盐沉积作用与湖水的较高含盐量和碳酸盐过饱和度有关。湖泊中心HL8号柱样的~(210)Pb测定结果是,10cm以上平均沉积速率0.25cm/a,10—12cm为0.05cm/a。60年代开始随湖泊水位上涨沉积物输入量迅速加大。     

基于Ecopath模型的舟山海域褐菖鲉(Sebastiscus marmoratus)生态容量评估

根据2021年渔业资源调查数据构建了含有23个功能组的舟山海域生态系统Ecopath模型,分析了当前舟山海域生态系统总体特征并估算了褐菖鲉在舟山海域的生态容量。结果表明:舟山海域生态系统营养级范围为1.000 (浮游植物和有机碎屑)～4.277 ( 鳐类),石首鱼科、虾类和 鳐类为舟山海域生态系统中的关键种。碎屑食物链和牧食食物链是舟山海域生态系统主要的食物链。碎屑和浮游植物对食物网的贡献率分别为61.32%和38.69%。始于浮游植物和碎屑的营养传递效率分别是9.34%和10.50%,系统总营养传递效率是9.82%。总初级生产量/总呼吸量为2.26,系统连接指数为0.372,系统杂食性指数为0.222。生态系统总体特征反映了舟山海域生态系统的成熟状态较低,生态系统处于不稳定阶段,容易受到外界环境变化的影响。根据模型估算,当褐菖鲉生物量增加至8.6倍时,褐菖鲉达到生态容量0.007 95 t/km²,此时生态系统仍保持平衡,且生态系统总体特征基本稳定。因此,褐菖鲉在舟山海域尚有较大增殖潜力。     

Sedimentary characteristics and genetic mechanism of the giant ancient pockmarks in the Qiongdongnan Basin,northern South China Sea

In the late Miocene, giant ancient pockmarks, which are fairly rare globally, developed in the Qiongdongnan Basin. In this paper, to determine the sedimentary characteristics and genetic mechanism of these giant ancient pockmarks in the Yinggehai Formation of the Qiongdongnan Basin, based on high-resolution 3D seismic data and multiattribute fusion technologies, we analyzed the planar distribution and seismic facies of the ancient pockmarks and compared the characteristics of the ancient pockmar...     

Aliphatic biomarker signatures of early Oligocene-early Miocene source rocks in the central Qiongdongnan Basin: Source analyses of organic matter

The geochemical signatures of fifty-four rock samples and three supplementary drill stem test(DST) oils from the Yacheng-Sanya formations in the central Qiongdongnan Basin(CQB) were analysed. Reconstruction of the early Oligocene-early Miocene(36–16 Ma) palaeovegetation and source analyses of organic matter(OM) were conducted using aliphatic biomarkers in ancient sediments and DST oils. Both the interpreted aquatic and terrigenous OM contributed to the CQB source rocks(SRs) but had varying relat...     

2016-2020年黄河三角洲尾闾河道悬浮泥沙时空分布

三角洲河道悬浮泥沙的时空分布与河口流路稳定性及水下三角洲发育密切相关。基于Sentinel-2高分辨率卫星影像反演悬沙浓度,结合河道形态和水动力数值模拟,分析了近年来黄河尾闾河道悬沙的时空分布特征和影响因素。结果表明：2016-2020年,黄河尾闾河道平均悬沙浓度具有显著的洪枯季差异和不同的沿程分布;洪季悬沙浓度受上游来沙和底沙起动共同控制,王家庄和清加2断面是底沙起动再悬浮的主要断面;径流流速的增大对不同河段悬沙浓度的影响不尽相同,河口段悬沙浓度更易受径流流速的影响;以王家庄断面为界,上下游悬沙浓度分别呈现“深泓低两岸高”和“深泓高两岸低”两种截然不同的分布模式;尾闾河道悬沙浓度对调水调沙响应敏感,2018年调水调沙期间悬沙浓度达到10.75 g/L,但随着河床底沙粗化,尾闾河道悬沙浓度对调水调沙的响应敏感性下降。     

Modified state–space procedures for pseudodynamic testing

The existing on‐line numerical integration algorithms are derived from the Newmark method, which is based on an approximation of derivatives in the differential equation. The state–space procedure (SSP), based on an interpolation of the discrete excitation signals for piecewise convolution integral, has been confirmed as more reliable than the Newmark method in terms of numerical accuracy and stability. In an attempt to enhance the pseudodynamic test, this study presents an on‐line integration algorithm (referred to as the OS–SSP method) via an integration of the state–space procedure with Nakashima's operator‐splitting concept. Numerical stability and accuracy assessment of the proposed algorithm in addition to the explicit Newmark method and the OS method were investigated via an eigenvalue, frequency‐domain and time‐domain analysis. Of the on‐line integration algorithms investigated, the OS–SSP method is demonstrated as the most accurate method with an acceptable stability (although not unconditionally stable) characteristic. Therefore, the OS–SSP method is the most desirable method for pseudodynamic testing if the numerical stability criterion (Δt/T⩽0.5) is ensured for every vibration mode involved. Copyright © 2001 John Wiley & Sons, Ltd.     

Threshold criterion for debris flow initiation in seasonal gullies

A series of flume experiments were done to investigate the effect of grain composition on the critical gradient and discharge of debris flows initiated in seasonal gullies. The results indicated that the critical gradient and discharge for debris flow initiation decrease initially, and then increase as the mass content of fine particles (<2 mm) increases. As the mass content of fine particles increases, the angle of repose, permeability of widely graded gravel soils, and the incipient motion conditions of the coarse grains in non-uniform sediments decrease at first, and then increase. The mass content of fine particles of all inflection points is the same. The theoretical model based on the combination of hydrodynamic force and shear stress is more applicable to the prediction of the critical gradient for debris flow initiation. The critical discharge model considering the effect of non-homogeneity of the soil and the size of coarse and fine grains provides a more accurate prediction of debris flow initiation than other models based on the mean diameter.     

Complexity analysis of precipitation using the Lempel–Ziv algorithm and a multi-scaling approach: a case study in Jilin province,China

Precipitation is an important part of the hydrologic cycle, and its complexity is closely related to surface runoff and changing groundwater dynamics, which in turn influences the accuracy of precipitation forecasts. In this study, we used the Lempel–Ziv algorithm (LZA) and a multi-scaling approach to assess precipitation complexity for 1958–2011 by analyzing time series data from 28 gauging stations located throughout Jilin province, China. The spatial distribution of normalized precipitation complexity was measured by LZA, a symbolic dynamics algorithm, and by a multi-scaling approach, which is described by fractals. In addition, the advantages and limitations of these two methods were investigated. The results indicate that both methods are applicable and consistent for calculating precipitation complexity, and that the degree of relief is a primary factor controlling precipitation complexity in the mountainous area; in the plain terrain, however, the prominent influencing factor is climate.     

Comparison of parameter uncertainty analysis techniques for a TOPMODEL application

Parameter uncertainty in hydrologic modeling is crucial to the flood simulation and forecasting. The Bayesian approach allows one to estimate parameters according to prior expert knowledge as well as observational data about model parameter values. This study assesses the performance of two popular uncertainty analysis (UA) techniques, i.e., generalized likelihood uncertainty estimation (GLUE) and Bayesian method implemented with the Markov chain Monte Carlo sampling algorithm, in evaluating model parameter uncertainty in flood simulations. These two methods were applied to the semi-distributed Topographic hydrologic model (TOPMODEL) that includes five parameters. A case study was carried out for a small humid catchment in the southeastern China. The performance assessment of the GLUE and Bayesian methods were conducted with advanced tools suited for probabilistic simulations of continuous variables such as streamflow. Graphical tools and scalar metrics were used to test several attributes of the simulation quality of selected flood events: deterministic accuracy and the accuracy of 95 % prediction probability uncertainty band (95PPU). Sensitivity analysis was conducted to identify sensitive parameters that largely affect the model output results. Subsequently, the GLUE and Bayesian methods were used to analyze the uncertainty of sensitive parameters and further to produce their posterior distributions. Based on their posterior parameter samples, TOPMODEL’s simulations and the corresponding UA results were conducted. Results show that the form of exponential decline in conductivity and the overland flow routing velocity were sensitive parameters in TOPMODEL in our case. Small changes in these two parameters would lead to large differences in flood simulation results. Results also suggest that, for both UA techniques, most of streamflow observations were bracketed by 95PPU with the containing ratio value larger than 80 %. In comparison, GLUE gave narrower prediction uncertainty bands than the Bayesian method. It was found that the mode estimates of parameter posterior distributions are suitable to result in better performance of deterministic outputs than the 50 % percentiles for both the GLUE and Bayesian analyses. In addition, the simulation results calibrated with Rosenbrock optimization algorithm show a better agreement with the observations than the UA’s 50 % percentiles but slightly worse than the hydrographs from the mode estimates. The results clearly emphasize the importance of using model uncertainty diagnostic approaches in flood simulations.