Intensity–duration–frequency curves exploiting neighbouring extreme precipitation data

ABSTRACT

Records of precipitation extremes are essential for hydrological design. In urban hydrology, intensity–duration–frequency curves are typically estimated from observation records. However, conventional approaches seldom consider the areal extent of events. If they do, duration-dependent area reduction factors are used, but precipitation is measured at only a few locations. Due to the high spatial variability of precipitation, it is relatively unlikely that a gauged observation network will capture the extremes that occur during a precipitation event. Therefore, the area reduction approach cannot be regarded as the reduction of an observed maximum. To investigate precipitation extremes, spatial aspects need to be considered using different approaches. Here, we both address the conventional practice of area reduction and consider a within-area chance of increased precipitation, defined as the maximum precipitation intensity observed in a cluster within a selected domain. The results show that (1) the risk of urban flooding is routinely underestimated in current design practice, and (2) traditional calculations underestimate extremes by as much as 30–50%. We show how they can be revised sensibly.     

From marginal to conditional probability functions of parameters in a conceptual rainfall–runoff model: an event-based approach

ABSTRACT

A parameter estimation strategy for a conceptual rainfall–runoff (CRR) model applied to a storm sewer system in an urban catchment (Chassieu, Lyon, France) is proposed on the basis of event-by-event Bayesian local calibrations. The marginal distribution formed by locally-estimated parameters is divided into conditional functions, clustering the event-based parameters based on their transferability to similar rainfall events. The conditional functions showed to be consistent with an observed bimodality in the marginal representation, reflecting two different hydrological conditions mainly related to the magnitude of the rainfall intensities (high or low). The improvements achieved by expressing the parameter probability functions into a conditional form are shown in terms of accuracy (Nash-Sutcliffe efficiency criterion), precision (average relative interval length) and reliability (percentage of coverage) for simulating flow rate in 255 and 110 calibration/verification events.     

Application of remote sensing for investigating mining geological hazards

Abstract

To investigate geological mining hazards using digital techniques such as high-resolution remote sensing, a semi-automatically geological mining hazards extraction method is proposed based on the case of the Shijiaying coal mine, located in Fangshan District, Beijing, China. In the method, the vegetation is first removed using the normalized difference vegetation index (NDVI) on the GeoEye-1 data. Then, geological mining hazards interpretation features are determined after color enhancement using principal component analysis (PCA) transformation. Bitmaps mainly covered by geological mining hazards are isolated by masking operation in the environment for visualizing images software. Next, each bitmap is classified into a two-valued imagery using support vector machine algorithm. In the two-valued imagery, 1 denotes the geological mining hazards, while 0 denotes none. Afterwards, the two-valued imagery is converted into a vector graph by corresponding functions in the ArcGIS software and no geological mining hazards regions in the vector graph are deleted manually. Finally, the correlation between factors (such as mining activity, lithology, geological structure, and slope) and geological mining hazards is analyzed using a logistic regression and a hazardous-area forecasting model is built. The results of field verification show that the accuracy of the geological mining hazards extraction method is 98.1% and the results of the hazardous-area forecasting indicate that the logistic regression is an effective model in assessing geological hazard risks and that mining activity is the main contributing factor to the hazards, while geological structure, slope, lithology, roughness of the surface, and aspect are the secondary.     

A modified stochastic neighbor embedding for multi-feature dimension reduction of remote sensing images

In automated remote sensing based image analysis, it is important to consider the multiple features of a certain pixel, such as the spectral signature, morphological property, and shape feature, in both the spatial and spectral domains, to improve the classification accuracy. Therefore, it is essential to consider the complementary properties of the different features and combine them in order to obtain an accurate classification rate. In this paper, we introduce a modified stochastic neighbor embedding (MSNE) algorithm for multiple features dimension reduction (DR) under a probability preserving projection framework. For each feature, a probability distribution is constructed based on t-distributed stochastic neighbor embedding (t-SNE), and we then alternately solve t-SNE and learn the optimal combination coefficients for different features in the proposed multiple features DR optimization. Compared with conventional remote sensing image DR strategies, the suggested algorithm utilizes both the spatial and spectral features of a pixel to achieve a physically meaningful low-dimensional feature representation for the subsequent classification, by automatically learning a combination coefficient for each feature. The classification results using hyperspectral remote sensing images (HSI) show that MSNE can effectively improve RS image classification performance.     

组合法精化胶州市大地水准面

本文利用全球重力位模型、胶州市地面重力观测数据、胶州市GPS水准数据和数字地面模型(DTM),采用组合法应用移去-恢复技术计算剩余大地水准面,并与地球位模型计算的高程异常进行拟合,得到该地区重力似大地水准面,再和布测、计算得到的GPS/水准所构成的几何大地水准面拟合,利用多项式拟合完成系统改正,获得最终的大地水准面结果及相关的精度信息。     

基于GPS的列控轨道地图数据生成方法研究

为满足列车运行控制及列车定位不同层次的需求,将轨道地图数据分为轨道专用数据、轨道线路数据及地形环境数据,并对轨道地图线路数据按照不同尺度划分为特征点层及插值点层,形成列控轨道地图结构.针对原始GPS地图测量数据,采用多点加权距离检验及Kalman估计差值检验实现错误数据剔除;根据轨道曲线特征对原始数据进行划分,通过在各...     

基于非下采样Contourlet变换的极化SAR图像融合与去噪

针对非下采样Contourlet变换(NSCT)在处理噪声影像中具有的优势,以及同极化SAR图像(HH、VV)之间的相关性与互补性,本文实验了一种基于非下采样Contourlet变换的极化图像融合方法。该方法首先对每个极化图像进行多尺度、多方向分解,然后对不同分解子带系数分别采用有利于斑点噪声去除和信息增强的融合规则进行融合,最终通过NSCT反变换得到融合图像。通过信息熵、相关系数以及等效视数等指标的评价,验证了该方法可以有效地实现信息增强,同时该方法也在一定程度上降低了斑点噪声的负面影响。     

三维全景虚拟地震台站的建立

三维全景是一种基于静态图像的真实场景虚拟现实技术,首先简要叙述该技术的主要原理和技术路线,基于此建立了可以在网络上发布和浏览的三维全景虚拟地震台站系统,该技术丰富了防震减灾宣传工作的手段和内容.     

中国实施铁路电气化的节能减排量估算

基于中国铁路部门逐年统计数据,计算了1975-2007年中国电气化铁路带来的逐年节能量和CO2、烟尘、SO2、CO、NOx与CnHm的直接减排量,并分析了其变化特点.结果表明,33年来电气化铁路使得中国铁路运输行业年均节省123.0万t标准煤的能源消耗,节能量年均增长13.9万t标准煤;CO2、烟尘、SO2、CO、NO...     

Recovery from the impact of light reduction on the seagrass Amphibolis griffithii, insights for dredging management

A large-scale, manipulative experiment was conducted to examine the extent and rate of recovery of meadows of the temperate Australian seagrass, Amphibolis griffithii to different light-reduction scenarios typical of dredging operations, and to identify potential indicators of recovery from light reduction stress. Shade cloth was used to mimic different intensities, durations and start times of light reduction, and then was removed to assess the recovery. The meadow could recover from 3 months of light stress (5-18% ambient) following 10 months re-exposure to ambient light, even when up to 72% of leaf biomass was lost, much faster recovery rates than has previously been observed for large seagrasses. However, when the meadow had been shaded for 6-9 months and more than 82% of leaf biomass was lost, no recovery was detected up to 23 months after the light stress had ceased, consistent with other studies. Five potential indicators of recovery were recommended.