Stochastic and analytical approaches for sediment accumulation in river reservoirs

ABSTRACT

Sediment accumulation in a river reservoir is studied by stochastic time series models and analytical approach. The first-order moving average process is found the best for the suspended sediment discharge time series of the Juniata River at Newport, Pennsylvania, USA. Synthetic suspended sediment discharges are first generated with the chosen model after which analytical expressions are derived for the expected value and variance of sediment accumulation in the reservoir. The expected value and variance of the volume of sediment accumulation in the reservoir are calculated from a thousand synthetic time series each 38 years long and compared to the analytical approach. Stochastic and analytical approaches perfectly trace the observation in terms of the expected value and variability. Therefore, it is concluded that the expected value and variance of sediment accumulation in a reservoir could be estimated by analytical expressions without the cost of synthetic data generation mechanisms.     

长短期记忆神经网络(LSTM)模型在低能见度预报中的应用

利用浙江省义乌市2015—2019年逐小时气象观测数据(相对湿度、风速、地气温差、能见度)和空气质量指数(Air Quality Index, AQI)数据, 分析了义乌地区低能见度天气(观测能见度lt; 10 km)的分布特征和气象要素条件。利用长短期记忆神经网络(Long Short Term Memory Neural Network, LSTM)模型对逐小时能见度进行模拟, 分别对比了观测能见度作为输入变量与否的模拟效果; 根据义乌地区低能见度天气条件的特征, 将模拟时段分为三个时期(11月至翌年2月, 3—6月, 7—10月), 对比了分时期模拟的效果; 以及评估了模型的预报步长。结果表明: 高湿、高污染、气温高于地温和低风速是义乌地区低能见度天气的主要特征。LSTM模型对单站能见度有较好的模拟效果, 当输入参数中加入历史观测能见度时, 能大幅提高模拟准确度, 日均能见度模拟结果均方根误差RMSE=0.63 km, 平均绝对误差MAE=0.51 km, 拟合优度R²=0.99;分时期进行模拟能得到更精准的模拟结果。本研究中选用的输入要素在冬季(11月至翌年2月)模拟效果最好, RMSE=2.35 km, MAE=1.46 km, 低能见度均方根误差RMSE_10 km=1.81 km, 低能见度平均绝对误差MAE_10 km=1.13 km, R²=0.83; 3—6月的模拟中, 输入变量中不加AQI模拟效果更好, 这意味着3—6月义乌地区的低能见度天气以雾天气为主导, 加入过多变量并不一定能提高模型准确度; 随着预报步长增大, 模型预报效果变差, 预测步长等于3 h, R²=0.71, 预测结果已不具备实际应用意义。     

Coupling numerical simulation with remotely sensed information for the study of frozen soil dynamics

The acquisition of spatial-temporal information of frozen soil is fundamental for the study of frozen soil dynamics and its feedback to climate change in cold regions. With advancement of remote sensing and better understanding of frozen soil dynamics, discrimination of freeze and thaw status of surface soil based on passive microwave remote sensing and numerical simulation of frozen soil processes under water and heat transfer principles provides valuable means for regional and global frozen soil dynamic monitoring and systematic spatial-temporal responses to global change. However, as an important data source of frozen soil processes, remotely sensed information has not yet been fully utilized in the numerical simulation of frozen soil processes. Although great progress has been made in remote sensing and frozen soil physics, yet few frozen soil research has been done on the application of remotely sensed information in association with the numerical model for frozen soil process studies. In the present study, a distributed numerical model for frozen soil dynamic studies based on coupled water-heat transferring theory in association with remotely sensed frozen soil datasets was developed. In order to reduce the uncertainty of the simulation, the remotely sensed frozen soil information was used to monitor and modify relevant parameters in the process of model simulation. The remotely sensed information and numerically simulated spatial-temporal frozen soil processes were validated by in-situ field observations in cold regions near the town of Naqu on the East-Central Tibetan Plateau. The results suggest that the overall accuracy of the algorithm for discriminating freeze and thaw status of surface soil based on passive microwave remote sensing was more than 95%. These results provided an accurate initial freeze and thaw status of surface soil for coupling and calibrating the numerical model of this study. The numerically simulated frozen soil processes demonstrated good performance of the distributed numerical model based on the coupled water-heat transferring theory. The relatively larger uncertainties of the numerical model were found in alternating periods between freezing and thawing of surface soil. The average accuracy increased by about 5% after integrating remotely sensed information on the surface soil. The simulation accuracy was significantly improved, especially in transition periods between freezing and thawing of the surface soil.     

富贺钟钨锡多金属矿集区成矿规律及成矿模式

成岩、成矿的时空关系及矿化特征综合研究表明,桂东北富贺钟地区钨锡多金属成矿主要与燕山期姑婆山复式岩体中晚期的细粒花岗岩有关,但成岩与成矿之间存在一定时差.区内矿化具有上锡下钨的垂向分带特征,细粒花岗岩侵入层位的不同制约了矿化类型及成矿元素组合.成矿作用过程中有幔源流体的参与,中泥盆统郁江组砂页岩和东岗岭组灰岩夹白云质灰岩之间的“硅-钙界面”对锡成矿具有重要的控制作用,也是锡矿就位的重要场所.细粒花岗岩体周缘的“硅-钙界面”附近是寻找锡多金属矿的远景地段.     

层状地基静压桩贯入过程机理试验

通过在多层软粘土地基中静力压入单桩的室内模型试验,对模型桩在整个沉桩过程中压桩力、桩动端阻力及桩动侧阻力随桩贯入深度的变化情况进行了研究,获得了桩在贯入不同土层分界面时阻力的变化规律以及桩周土体应力的分布特征。并对开口管桩和闭口管桩贯入试验情况进行了比较分析,揭示了不同桩端形式桩在贯入过程中桩动侧摩阻力的发展规律,以及分层土体中开口管桩贯入过程中土塞的变化情况。试验结果表明：在粘性土中沉桩时,压桩阻力主要来自桩端向下穿越土体产生的端阻力,而侧摩阻力较小;由于桩侧水平应力的释放使得同一深度点上的动摩阻力随着桩的下沉表现出不同程度的降低,出现摩擦疲劳。     

利用Sentinel-1影像监测土地回填导致的地表形变

在机场填海区地表稳定散射的范围内,本文运用合成孔径雷达干涉测量(InSAR)技术对机场地表形变安全性进行了监测分析,反演获得了研究区域范围内的年形变速率数据结果和高分辨率形变时序结果,并以此分析了香港国际机场的地表形变区在监测周期内的形变时空分布特征.为证明监测结果的精度和可靠性,本文采用全球导航卫星系统(GNSS)观...     

电子政务空间辅助决策综合数据管理研究与实践

本文通过对电子政务数据特点和处理要求的分析,提出了电子政务空间辅助决策综合数据模型。在此基础上,作者完成了电子政务空间辅助决策综合数据管理方法研究与实践。实现了多种类型数据的管理,扩展并完善了基于空间数据的电子政务应用数据管理的内容和技术。     

传统海图和电子海图一体化数据模型的构建与应用研究

针对国内在一定时期内既要生产传统纸质海图保证传统导航,又要生产电子海图满足电子导航的需求,构建了一个能够包容S-57电子海图和传统海图信息全集的一体化海图数据模型,基于此模型分析了两种数据到一体化数据模型的转换机制,并应用此模型开发原型系统,实现了二者之间的一体化组织和切换显示,为探索传统海图和电子海图的数据融合提供了思路和参考。     

高空急流对一次强沙尘暴过程沙尘传输的影响

使用GRAPES_SDM沙尘暴数值模式,对2011年4月28-30日中国北方强沙尘暴天气进行分析,讨论高空急流在此次过程中对沙尘传输的影响,得出以下结论:（1）GRAPES_SDM沙尘暴模式较好地模拟了此次沙尘暴过程的范围和强沙尘暴中心,整体模拟效果较好;（2）沙尘天气发生时间及移动路径与200 hPa高空急流的加强、移动发展有很好的对应关系;（3）高空强纬向风速的加强能够促使中低层形成垂直环流圈,其下沉支流使高空动量有效下传到近地面,进而在地面形成大风及扬沙和沙尘暴天气,强沙尘暴中心位于此垂直环流圈的下沉支;（4）等熵位涡与高空急流及地面沙尘浓度分布演变有很好的对应关系,等熵位涡位于高空急流北侧,地面沙尘浓度中心位于高空急流出口区、等熵位涡中心西南侧、等值线密集带;高层高值位涡区向下延伸的路径与高空急流北侧纬向风速等值线密集带有非常好的对应关系。本文还通过对高空急流轴线动力、热力结构垂直剖面的分析,探讨了高空急流对大范围沙尘天气影响的可能机制。     

A BRIEF INTRODUCTION TO THE NEW METHOD FOR RIVER PROFILE ANALYSIS: Integral Approach

The topography and geomorphology of active orogens result from the interaction of tectonics and climate. In most orogens, a fluvial channel is most sensitive to the coupling between tectonics, lithology, and climate. Meanwhile, the related signals have been recorded by both the drainage geometry and channel longitudinal profile. Thus, how to extract tectonic information from fluvial channels has been a focused issue in geologic and geomorphologic studies. The well known stream-power river incision model bridges the gap between tectonic uplift, river incision and channel profile change, making it possible to retrieve rock uplift pattern from river profiles. In this model, the river incision rate depends on the rock erodibility, contributing drainage area and river gradient. The steady-state form of the river incision model predicts a power-law scaling between the drainage area and channel gradient. Via a linear regression to the log-transformed slope-area data, the slope and intercept are channel concavity and steepness indices, respectively. The concavity relates to lithology, climatic setting and incision process while the channel steepness can be used to map the spatial pattern of rock uplift. For its simple calculation process, the slope-area analysis has been widely used in the study of tectonic geomorphology during past decades. However, to calculate river slope, the coarse channel elevation data must be smoothed, re-sampled, and differentiated without any reasonable smooth window or rigid mathematical fundamentals. One may lose important information and derive stream-power parameters with high uncertainties. In this paper, we introduce the integral approach, a procedure that has been widely used in the latest four years and demonstrated to be a better method for river profile analysis than the traditional slope-area analysis. Via the integration to the steady-state form of the stream-power river incision equation, the river longitudinal profile can be converted into a straight line of which the independent variable is the integral quantity χ with the unit of distance and the dependent variable is the relative channel elevation. We can calculate the linear correlation coefficient between elevation and χ based on a series of concavity values and find the best linear fit to be the reasonable channel concavity index. The slope of the linear fit to the χ value and elevation is simply related to the ratio of the uplift rate to the erodibility. Without calculating channel slope, the integral approach makes up for the drawback of the slope-area analysis. Meanwhile, via the integral approach, a steady-state river profile can be expressed as a continuous function, which can provide theoretical principle for some geomorphic parameters (e.g., slope-length index, hypsometric integral). In addition, we can determine the drainage network migration direction using this method. Therefore, the integral approach can be used as a better method for tectonogeomorphic research.