On the Intensity Virtual Area Characterization in the Intensity Distribution Modelling by Macroseismic Planes     

Domenica Termini  Antonio Teramo  Carla Bottari 《Pure and Applied Geophysics》2005,162(4):699-705

A procedure is proposed for the reconfiguration of the macroseismic planes relative to earthquakes that, being characterized by a reduced number of points of observed intensity due to a lack of information, or having the epicenter very close to the coastline, are characterized by an incomplete distribution of observed intensity levels. The design of a plurality of virtual areas, through which a distribution of intensity consistent with an anisotropic model of attenuation is depicted, allows a reliable determination of macroseismic parameters of the same seismic event.  相似文献   

Kinetic energy–rainfall intensity relationship for Central Cebu, Philippines for soil erosion studies     

Ricardo L. Fornis  Hans R. Vermeulen  Jan D. Nieuwenhuis 《Journal of Hydrology》2005,300(1-4):20-32

In the study of soil erosion, specifically on detachment of soil particles by raindrop impact, kinetic energy is a commonly suggested indicator of the raindrop's ability to detach soil particles from the soil mass. Since direct measurement of kinetic energy requires sophisticated and costly instruments, the alternative approach is to estimate it from rainfall intensity. The present study aims at establishing a relationship between rainfall intensity and kinetic energy for rainfalls in Central Cebu, Philippines as a preface of a wider regional investigation.

Drop size distributions of rainfalls were measured using the disdrometer RD-80. There are two forms of kinetic energy considered here. One is kinetic energy per unit area per unit time (KE_R, J m⁻² h⁻¹) and the other is kinetic energy per unit area per unit depth (KE, J m⁻² mm⁻¹). Relationships between kinetic energy per unit area per unit time (KE_R) and rainfall intensity (I) were obtained using linear and power relations. The exponential model and the logarithmic model were fitted to the KE–I data to obtain corresponding relationships between kinetic energy per unit area per unit depth of rainfall (KE) and rainfall intensity (I). The equation obtained from the exponential model produced smaller standard error of estimates than the logarithmic model.  相似文献   

Macroseismic Intensity Modelling of Earthquakes in Southern Spain: Attenuation and Tectonic Implications     

Tiziana Tuvè  Antonio Teramo  Jesus Ibañez  Carla Bottari  Domenica Termini 《Pure and Applied Geophysics》2005,162(4):747-760

A modelling of the observed macroseismic intensity of historical and instrumental earthquakes in southern Spain is proposed, with the aim of determining the macroseismic parameters for seismic hazard evaluation in a region in which the characterization of intensity distribution of seismic events shows different levels of difficulty referable to the complex faults system of the area in study. The adopted procedure allows an analytical determination of epicenters and principal attenuation directions of earthquakes with a double level of verification with reference to the maximum shaking area and structural lineaments of the region, respectively. The analyses, carried out on a suitable number of events, highlight, therefore, some elements for a preliminary characterization of a seismic zonation on the basis of the consistency between seismic intensity distribution of earthquakes and corresponding structural framework.  相似文献   

Developing efficient scalar and vector intensity measures for IDA capacity estimation by incorporating elastic spectral shape information     

Dimitrios Vamvatsikos  C. Allin Cornell 《地震工程与结构动力学》2005,34(13):1573-1600

Scalar and vector intensity measures are developed for the efficient estimation of limit‐state capacities through incremental dynamic analysis (IDA) by exploiting the elastic spectral shape of individual records. IDA is a powerful analysis method that involves subjecting a structural model to several ground motion records, each scaled to multiple levels of intensity (measured by the intensity measure or IM), thus producing curves of structural response parameterized by the IM on top of which limit‐states can be defined and corresponding capacities can be calculated. When traditional IMs are used, such as the peak ground acceleration or the first‐mode spectral acceleration, the IM‐values of the capacities can display large record‐to‐record variability, forcing the use of many records to achieve reliable results. By using single optimal spectral values as well as vectors and scalar combinations of them on three multistorey buildings significant dispersion reductions are realized. Furthermore, IDA is extended to vector IMs, resulting in intricate fractile IDA surfaces. The results reveal the most influential spectral regions/periods for each limit‐state and building, illustrating the evolution of such periods as the seismic intensity and the structural response increase towards global collapse. The ordinates of the elastic spectrum and the spectral shape of each individual record are found to significantly influence the seismic performance and they are shown to provide promising candidates for highly efficient IMs. Copyright © 2005 John Wiley & Sons, Ltd.  相似文献   

华蓥山隧道岩溶发育强度垂直分带     

熊道锟  傅荣华 《岩土工程技术》2005,19(4):186-190

论述了华蓥山隧道的岩溶发育特征,根据岩溶发育强度的划分依据和划分标准,结合岩溶发育的历史,采用类比判别法、主因素判别法和综合判别法对岩溶发育强度作了垂直分带,据此预测的溶洞规模与实际情况吻合。  相似文献   

Fracture mechanics analysis of multiple cracks in anisotropic media     

Chia‐Huei Tu  C.‐S. Chen  T.‐T. Yu 《国际地质力学数值与分析法杂志》2011,35(11):1226-1242

This paper presents a single‐domain boundary element method (BEM) for linear elastic fracture mechanics analysis in the two‐dimensional anisotropic material. In this formulation, the displacement integral equation is collocated on the un‐cracked boundary only, and the traction integral equation is collocated on one side of the crack surface only. A special crack‐tip element was introduced to capture exactly the crack‐tip behavior. A computer program with the FORTRAN language has been developed to effectively calculate the stress intensity factors of an anisotropic material. This BEM program has been verified having a good accuracy with the previous researches. Furthermore, by analyzing the different anisotropic degree cracks in a finite plate, we found that the stress intensity factors of crack tips had apparent influence by the geometry forms of cracks and media with different anisotropic degrees. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

Exploration of remotely sensed forest structure and ultrasonic range sensor metrics to improve empirical snow models          下载免费PDF全文

Andrés Varhola  Nicholas C. Coops  Younes Alila  Markus Weiler 《水文研究》2014,28(15):4433-4448

Current methods to estimate snow accumulation and ablation at the plot and watershed levels can be improved as new technologies offer alternative approaches to more accurately monitor snow dynamics and their drivers. Here we conduct a meta‐analysis of snow and vegetation data collected in British Columbia to explore the relationships between a wide range of forest structure variables – obtained from Light Detection and Ranging (LiDAR), hemispherical photography (HP) and Landsat Thematic Mapper – and several indicators of snow accumulation and ablation estimated from manual snow surveys and ultrasonic range sensors. By merging and standardizing all the ground plot information available in the study area, we demonstrate how LiDAR‐derived forest cover above 0.5 m was the variable explaining the highest percentage of absolute peak snow water equivalent (SWE) (33%), while HP‐derived leaf area index and gap fraction (45° angle of view) were the best potential predictors of snow ablation rate (explaining 57% of variance). This study reveals how continuous SWE data from ultrasonic sensors are fundamental to obtain statistically significant relationships between snow indicators and structural metrics by increasing mean r² by 20% when compared to manual surveys. The relationships between vegetation and spectral indices from Landsat and snow indicators, not explored before, were almost as high as those shown by LiDAR or HP and thus point towards a new line of research with important practical implications. While the use of different data sources from two snow seasons prevented us from developing models with predictive capacity, a large sample size helped to identify outliers that weakened the relationships and suggest improvements for future research. A concise overview of the limitations of this and previous studies is provided along with propositions to consistently improve experimental designs to take advantage of remote sensing technologies, and better represent spatial and temporal variations of snow. 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   

Revised runoff curve number for runoff prediction in the Loess Plateau of China     

Wenhai Shi  Ni Wang  Miaomiao Wang  Donghao Li 《水文研究》2021,35(10):e14390

The soil conservation service (now Natural Resources Conservation Service) Curve Number (SCS-CN), one of the most commonly used methods for surface runoff prediction. The runoff calculated by this method was very sensitive to CN values. In this study, CN values were calculated by both arithmetic mean (CN_C) and least square fit method (CN_F) using observed rainfall-runoff data from 43 sites in the Loess Plateau region, which are considerably different from the CN₂ values obtained from the USDA-SCS handbook table (CN_T). The results showed that using CN_C instead of CN_T for each watershed produce little improvement, while replacing CN_T with CN_F improves the performance of the original SCS-CN method, but still performs poorly in most study sites. This is mainly due to the SCS-CN method using a constant CN value and discounting of the temporal variation in rainfall-runoff process. Therefore, three factors—soil moisture, rainfall depth and intensity—affecting the surface runoff variability are considered to reflect the variation of CN in each watershed, and a new CN value was developed. The reliability of the proposed method was tested with data from 38 watersheds, and then applied to the remaining five typical watersheds using the optimized parameters. The results indicated that the proposed method, which boosted the model efficiencies to 81.83% and 74.23% during calibration and validation cases, respectively, performed better than the original SCS-CN and the Shi and Wang (2020b) method, a modified SCS-CN method based on tabulated CN value. Thus, the proposed method incorporating the influence of the temporal variability of soil moisture, rainfall depth, and intensity factors suggests an accurate runoff prediction for general applications under different hydrological and climatic conditions on the Loess Plateau region.  相似文献   

真三维立体显示技术在不动产登记统一平台中的应用研究     

陈育新 《测绘与空间地理信息》2016,(5):107-109

随着国家不动产统一登记制度的实施,城市房屋、林地、草原、土地等不动产统一整合、调查和管理工作迫在眉睫。基于机载多角度倾斜摄影和激光雷达扫描技术的创新,真三维数据可为不动产登记提供真实统一、高精度、多层次的空间载体,保证了城市不动产登记应用创新和制度创新。  相似文献