连续GPS观测中的相关噪声分析

分析了中国地壳运动观测网络GPS基准站位置时间序列中相关噪声的特性.利用最大似然估计反演了幂指数噪声的谱指数;考察了多种噪声模型,发现除闪烁噪声之外,约50%台站的东分量中的相关噪声可用"随机漫步噪声+一阶高斯-马尔可夫噪声"模型来描述,与其它分析机构产出的全球解并不一致,显示出处理策略的不同能够造成相关噪声的差异.白噪声和闪烁噪声的大小存在明显的地理分异,东南沿海台站的噪声要大于西北内陆台站.考虑相关噪声时,各站的速率估计方差要增大一个数量级以上,水平分量多在1mm/a以内,而垂向分量则较大.     

Improved edge detection mapping through stacking and integration: a case study in the Bathurst Mining Camp

Airborne geophysical surveys provide spatially continuous regional data coverage, which directly reflects subsurface petrophysical differences and thus the underlying geology. A modern geologic mapping exercise requires the fusion of this information to complement what is typically limited regional outcrop. Often, interpretation of the geophysical data in a geological context is done qualitatively using total field and derivative maps. With a qualitative approach, the resulting map product may reflect the interpreter's bias. Source edge detection provides a quantitative means to map lateral physical property changes in potential and non‐potential field data. There are a number of Source edge detection algorithms, all of which apply a transformation to convert local signal inflections associated with source edges into local maxima. As a consequence of differences in their computation, the various algorithms generate slightly different results for any given source depth, geometry, contrast, and noise levels. To enhance the viability of any detected edge, it is recommended that one combines the output of several Source edge detection algorithms. Here we introduce a simple data compilation method, deemed edge stacking, which improves the interpretable product of Source edge detection through direct gridding, grid addition, and amplitude thresholding. In two examples, i.e., a synthetic example and a real‐world example from the Bathurst Mining Camp, New Brunswick, Canada, a number of transformation algorithms are applied to gridded geophysical data sets and the resulting Source edge detection solutions combined. Edge stacking combines the benefits and nuances of each Source edge detection algorithm; coincident or overlapping and laterally continuous solutions are considered more indicative of a true edge, whereas isolated points are taken as being indicative of random noise or false solutions. When additional data types are available, as in our example, they may also be integrated to create a more complete geologic model. The effectiveness of this method is limited only by the resolution of each survey data set and the necessity of lateral physical property contrasts. The end product aims at creating a petrophysical contact map, which, when integrated with known lithological outcrop information, can be led to an improved geological map.     

Spatial variability of E. coli in an urban salt-wedge estuary

This study investigated the spatial variability of a common faecal indicator organism, Escherichia coli, in an urban salt-wedge estuary in Melbourne, Australia. Data were collected through comprehensive depth profiling in the water column at four sites and included measurements of temperature, salinity, pH, dissolved oxygen, turbidity, and E. coli concentrations. Vertical variability of E. coli was closely related to the salt-wedge dynamics; in the presence of a salt-wedge, there was a significant decrease in E. coli concentrations with depth. Transverse variability was low and was most likely dwarfed by the analytical uncertainties of E. coli measurements. Longitudinal variability was also low, potentially reflecting minimal die-off, settling, and additional inputs entering along the estuary. These results were supported by a simple mixing model that predicted E. coli concentrations based on salinity measurements. Additionally, an assessment of a sentinel monitoring station suggested routine monitoring locations may produce conservative estimates of E. coli concentrations in stratified estuaries.     

A direct scaling analysis for the sea level rise

The estimation of long-term sea level variability is of primary importance for a climate change assessment. Despite the value of the subject, no scientific consensus has yet been reached on the existing acceleration in observed values. The existence of this acceleration is crucial for coastal protection planning purposes. The absence of the acceleration would enhance the debate on the general validity of current future projections. Methodologically, the evaluation of the acceleration is a controversial and still open discussion, reported in a number of review articles, which illustrate the state-of-art in the field of sea level research. In the present paper, the well-proven direct scaling analysis approach is proposed in order to describe the long-term sea level variability at 12 worldwide-selected tide gauge stations. For each of the stations, it has been shown that the long-term sea level variability exhibits a trimodal scaling behaviour, which can be modelled by a power law with three different pairs of shape and scale parameters. Compared to alternative methods in literature, which take into account multiple correlated factors, this simple method allows to reduce the uncertainties on the sea level rise parameters estimation.     

Effect of the span of Australian GPS coordinate time series in establishing an optimal noise model

The span of coordinate time series affects the determination of an optimal noise model. We analyzed position data recorded for 10 continuous Global Positioning System(GPS) sites from 1998.0 to mid-2009 on the Australian Plate to estimate the best noise model and thereafter obtain the true uncertainties of the velocity, employing the maximum likelihood estimation(MLE) method. MLE was employed to analyze the data in four ways. In the first two analyses, the noise was assumed to be a combination of flicker noise and white noise for the raw time series and spatially filtered time series. In the final two analyses, the spectral indices and amplitudes were simultaneously estimated for a power law noise plus white noise model for the raw time series and spatially filtered time series. We conclude that the noise model of GPS time series in Australia can be best described as the combination of flicker noise and white noise. Velocity uncertainties fall below ~0.2 mm/yr when the time span exceeds ~9.5 years. A comparison of noise amplitudes and maximum likelihood estimation values between the raw and spatially filtered time series suggests that traditional spatial filtering to remove common-mode errors might not be applicable to the raw time series of this region.     

Inversion of elongated magnetic anomalies using magnitude transforms

The calculable magnitudes of the anomalous magnetic field from simple 2D sources and their gradients and Laplacians appear as ratios that can be synthesized in functional forms, corresponding to the different source shapes. Field components and first‐order derivatives are involved in the inversion procedures presented. The structural index and source depth are estimated independently of each other. The applied functions allow magnetic profiles and magnetic maps to be shape‐ and depth‐converted with immediate imaging of the inversion results. The contours of these functions outline elongated loops around the 2.5D anomaly axis on magnetic maps. The width of the loops reflects the depth and structural index N of the source in the scale units of the inverted map. Model and field tests illustrate the effectiveness of this approach for fast automatic inversion of large sets of magnetic data for depth, shape, length and location of simple sources.     

Regional differences in hydrological response to canopy interception schemes in a land surface model

Two different canopy interception schemes are applied to the parameterization of the hydrological processes in the Community Land Model version 3. One scheme treats rainfall and canopy water storage as spatially uniform within each model grid cell, and the other scheme considers sub‐grid variability of rainfall and water storage in the parameterization of canopy hydrological processes. The hydrological responses to differences between these two schemes in different regions are studied. It is found that the impact of the sub‐grid variability in the tropical regions is generally greater than the extra‐tropical regions. However, such impact can't be negligible for the extra‐tropical regions. Soil water in the total 3.4 m soil depth increases by 3% for Central‐South Europe, and vegetation temperature increases by 0.14 °C for Southeastern United States if the regional averages are considered. The magnitude of the impact is greater if the analysis focuses on the specific grid cells in these regions. The impact is tightly correlated with rainfall amount and vegetation density. The correlation coefficient between such impact and rainfall amount and vegetation density varies with regions and hydrological variables, with the largest value of 0.92 for interception loss in Amazonia. Our results indicate that the impact of the sub‐grid variability on hydrological processes in the extra‐tropical areas is also important, although rainfall amount and vegetation density in these areas are not as high as in the tropical areas. Copyright © 2013 John Wiley & Sons, Ltd.     

Latin hypercube approach to estimate uncertainty in ground water vulnerability

A methodology is proposed to quantify prediction uncertainty associated with ground water vulnerability models that were developed through an approach that coupled multivariate logistic regression with a geographic information system (GIS). This method uses Latin hypercube sampling (LHS) to illustrate the propagation of input error and estimate uncertainty associated with the logistic regression predictions of ground water vulnerability. Central to the proposed method is the assumption that prediction uncertainty in ground water vulnerability models is a function of input error propagation from uncertainty in the estimated logistic regression model coefficients (model error) and the values of explanatory variables represented in the GIS (data error). Input probability distributions that represent both model and data error sources of uncertainty were simultaneously sampled using a Latin hypercube approach with logistic regression calculations of probability of elevated nonpoint source contaminants in ground water. The resulting probability distribution represents the prediction intervals and associated uncertainty of the ground water vulnerability predictions. The method is illustrated through a ground water vulnerability assessment of the High Plains regional aquifer. Results of the LHS simulations reveal significant prediction uncertainties that vary spatially across the regional aquifer. Additionally, the proposed method enables a spatial deconstruction of the prediction uncertainty that can lead to improved prediction of ground water vulnerability.     

Uncertainty in floodplain delineation: expression of flood hazard and risk in a Gulf Coast watershed

This paper investigates the development of flood hazard and flood risk delineations that account for uncertainty as improvements to standard floodplain maps for coastal watersheds. Current regulatory floodplain maps for the Gulf Coastal United States present 1% flood hazards as polygon features developed using deterministic, steady‐state models that do not consider data uncertainty or natural variability of input parameters. Using the techniques presented here, a standard binary deterministic floodplain delineation is replaced with a flood inundation map showing the underlying flood hazard structure. Additionally, the hazard uncertainty is further transformed to show flood risk as a spatially distributed probable flood depth using concepts familiar to practicing engineers and software tools accepted and understood by regulators. A case study of the proposed hazard and risk assessment methodology is presented for a Gulf Coast watershed, which suggests that storm duration and stage boundary conditions are important variable parameters, whereas rainfall distribution, storm movement, and roughness coefficients contribute less variability. The floodplain with uncertainty for this coastal watershed showed the highest variability in the tidally influenced reaches and showed little variability in the inland riverine reaches. Additionally, comparison of flood hazard maps to flood risk maps shows that they are not directly correlated, as areas of high hazard do not always represent high risk. Copyright © 2012 John Wiley & Sons, Ltd.     

Evaluating the use of a gridded climate surface for modelling groundwater recharge in a semi‐arid region (Okanagan Basin,Canada)

Spatially distributed groundwater recharge was simulated for a segment of a semi‐arid valley using three different treatments of meteorological input data and potential evapotranspiration (PET). For the same area, timeframe, land cover characteristics and soil properties, groundwater recharge was estimate using (i) single‐station climate data with monthly PET calculated by the Thornthwaite method; (ii) single‐station climate data with daily PET calculated by the Penman–Monteith method; and (iii) daily gridded climate data with spatially distributed PET calculated using the Penman–Monteith method. For each treatment, the magnitude and distribution of actual evapotranspiration (AET) for summer months compared well with those estimated for a 5‐year crop study, suggesting that the near‐surface hydrological processes were replicated and that subsequent groundwater recharge rates are realistic. However, for winter months, calculated AET was near zero when using the Thornthwaite PET method. Mean annual groundwater recharge varied from ～3·2 to 10·0 mm when PET was calculated by the Thornthwaite method, and from ～1·8 to 7·5 mm when PET was calculated by the Penman–Monteith method. Comparisons of bivariate plots of seasonal recharge rates estimated from single‐station versus gridded surface climate reveal that there is greater variability between the different methods for spring months, which is the season of greatest recharge. Furthermore, these seasonal differences are shown to provide different results when compared to the depth to water table, which could lead to different results of evaporative extinction depth. These findings illustrate potential consequences of using different approaches for representing spatial meteorological input data, which could provide conflicting predictions when modelling the influence of climate change on groundwater recharge. Copyright © 2010 John Wiley & Sons, Ltd.     

Measurement of shallow shear wave velocities at a rock site using the ReMi technique

Shallow shear wave velocities beneath a rock site are characterized using the refraction microtremor (ReMi) technique developed by Louie [Faster, better: shear-wave velocity to 100 m depth from ReMi arrays. Bull Seism Soc Am 2001; 91: 347–64]. Ground motion from a passing train enabled capture of energy propagating parallel to the recording array. This allowed evaluation of the variation of the minimum phase-velocity of the dispersion curve envelope and better estimation of the true minimum velocity beneath the site. We use a new method to image and evaluate the dispersion curve envelope via power–slowness profiles through the slowness–frequency plots introduced by Louie [Faster, better: shear-wave velocity to 100 m depth from ReMi arrays. Bull Seism Soc Am 2001; 91: 347–64]. Data illustrated the frequency dependency of dispersion curve uncertainties, with greater uncertainty occurring at low frequencies. These uncertainties map directly into uncertainty of the inverted velocity–depth profile. Above 100 m depth velocities are well constrained with 10% variability. Variability is greatly reduced when the energy propagation is along the geophone array. Greater velocity variation is observed below 100 m depth.     

An algorithm to calculate the gravity anomaly of sedimentary basins with exponential density-depth relationships

We derive wavenumber domain expressions to calculate the gravity anomaly of a body with irregular bounding surfaces and an exponential density‐depth relationship. We apply the method to sedimentary basins, which commonly have this type of geometry and density distribution. The mathematical formulation also allows the exponential density‐depth relationship to be measured from an arbitrary irregular surface rather than the top surface. Using this arrangement, the gravity anomaly of exhumed sedimentary basins can be predicted if the amount of eroded section can be estimated. The corresponding inverse algorithms are also derived. Examples of the use of the forward algorithms, from the Galicia Interior Basin and the Central Irish Sea Basin, are used to illustrate these methods.     

Moment and Bayesian wavelet regression from spatially correlated functional data

A new wavelet-based estimation methodology, in the context of spatial functional regression, is proposed to discriminate between small-scale and large scale variability of spatially correlated functional data, defined by depth-dependent curves. Specifically, the discrete wavelet transform of the data is computed in space and depth to reduce dimensionality. Moment-based regression estimation is applied for the approximation of the scaling coefficients of the functional response. While its wavelet coefficients are estimated in a Bayesian regression framework. Both regression approaches are implemented from the empirical versions of the scaling and wavelet auto-covariance and cross-covariance operators, characterizing the correlation structure of the spatial functional response. Weather stations in ocean islands display high spatial concentration. The proposed estimation methodology overcomes the difficulties arising in the estimation of ocean temperature field at different depths, from long records of ocean temperature measurements in these stations. Data are collected from The World-Wide Ocean Optics Database. The performance of the presented approach is tested in terms of 10-fold cross-validation, and residual spatial and depth correlation analysis. Additionally, an application to soil sciences, for prediction of electrical conductivity profiles is also considered to compare this approach with previous related ones, in the statistical analysis of spatially correlated curves in depth.     

High-frequency maximum observable shaking map of Italy from fault sources

We present a strategy for obtaining fault-based maximum observable shaking (MOS) maps, which represent an innovative concept for assessing deterministic seismic ground motion at a regional scale. Our approach uses the fault sources supplied for Italy by the Database of Individual Seismogenic Sources, and particularly by its composite seismogenic sources (CSS), a spatially continuous simplified 3-D representation of a fault system. For each CSS, we consider the associated Typical Fault, i.e., the portion of the corresponding CSS that can generate the maximum credible earthquake. We then compute the high-frequency (1–50?Hz) ground shaking for a rupture model derived from its associated maximum credible earthquake. As the Typical Fault floats within its CSS to occupy all possible positions of the rupture, the high-frequency shaking is updated in the area surrounding the fault, and the maximum from that scenario is extracted and displayed on a map. The final high-frequency MOS map of Italy is then obtained by merging 8,859 individual scenario-simulations, from which the ground shaking parameters have been extracted. To explore the internal consistency of our calculations and validate the results of the procedure we compare our results (1) with predictions based on the Next Generation Attenuation ground-motion equations for an earthquake of M_w 7.1, (2) with the predictions of the official Italian seismic hazard map, and (3) with macroseismic intensities included in the DBMI04 Italian database. We then examine the uncertainties and analyse the variability of ground motion for different fault geometries and slip distributions.     

The influence of groundwater depth on coastal dune development at sand flats close to inlets

A cellular automata model is used to analyze the effects of groundwater levels and sediment supply on aeolian dune development occurring on sand flats close to inlets. The model considers, in a schematized and probabilistic way, aeolian transport processes, groundwater influence, vegetation development, and combined effects of waves and tides that can both erode and accrete the sand flat. Next to three idealized cases, a sand flat adjoining the barrier island of Texel, the Netherlands, was chosen as a case study. Elevation data from 18 annual LIDAR surveys was used to characterize sand flat and dune development. Additionally, a field survey was carried out to map the spatial variation in capillary fringe depth across the sand flat. Results show that for high groundwater situations, sediment supply became limited inducing formation of Coppice-like dunes, even though aeolian losses were regularly replenished by marine import during sand flat flooding. Long dune rows developed for high sediment supply scenarios which occurred for deep groundwater levels. Furthermore, a threshold depth appears to exist at which the groundwater level starts to affect dune development on the inlet sand flat. The threshold can vary spatially depending on external conditions such as topography. On sand flats close to inlets, groundwater is capable of introducing spatial variability in dune growth, which is consistent with dune development patterns found on the Texel sand flat.     

Flow and entrapment of dense nonaqueous phase liquids in physically and chemically heterogeneous aquifer formations

The migration and entrapment of dense nonaqueous phase liquids (DNAPLs) in aquifer formations is typically believed to be controlled by physical heterogeneities. This belief is based upon the assumption that permeability and capillary properties are determined by the soil texture. Capillarity and relative permeability, however, will also depend on porous medium wettability characteristics. This wettability may vary spatially in a formation due to variations in aqueous phase chemistry, contaminant aging, and/or variations in mineralogy and organic matter distributions. In this work, a two-dimensional multiphase flow simulator is modified to simulate coupled physical and chemical formation heterogeneity. To model physical heterogeneity, a spatially correlated permeability field is generated, and then related to the capillary pressure-saturation function according to Leverett scaling. Spatial variability of porous medium wettability is assumed to be correlated with the natural logarithm of the intrinsic permeability. The influence of wettability on the hysteretic hydraulic property relations is also modeled. The simulator is then employed to investigate the potential influence of coupled physical and chemical heterogeneity on DNAPL flow and entrapment. For reasonable ranges of wettability characteristics, simulations demonstrate that spatial variations in wettability can have a dramatic impact on DNAPL distributions. Higher organic saturations, increased lateral spreading, and decreased depth of infiltration were predicted when the contact angle was varied spatially. When chemical heterogeneity was defined by spatial variation of organic-wet solid fractions (fractional wettability porous media), however, the resultant organic saturation distributions were more similar to those for perfectly water-wet media, due to saturation dependent wettability effects on the hydraulic property relations.     

Small scale spatial variability of snow density and depth over complex alpine terrain: Implications for estimating snow water equivalent

This study analyzes spatial variability of snow depth and density from measurements made in February and April of 2010 and 2011 in three 1–2 km² areas within a valley of the central Spanish Pyrenees. Snow density was correlated with snow depth and different terrain characteristics. Regression models were used to predict the spatial variability of snow density, and to assess how the error in computed densities might influence estimates of snow water equivalent (SWE).The variability in snow depth was much greater than that of snow density. The average snow density was much greater in April than in February. The correlations between snow depth and density were generally statistically significant but typically not very high, and their magnitudes and signs were highly variable among sites and surveys. The correlation with other topographic variables showed the same variability in magnitude and sign, and consequently the resulting regression models were very inconsistent, and in general explained little of the variance. Antecedent climatic and snow conditions prior to each survey help highlight the main causes of the contrasting relation shown between snow depth, density and terrain. As a consequence of the moderate spatial variability of snow density relative to snow depth, the absolute error in the SWE estimated from computed densities using the regression models was generally less than 15%. The error was similar to that obtained by relating snow density measurements directly to adjacent snow depths.     

Spatially smoothed seismicity modeling of seismic hazard in Slovenia

A progress report on the mapping effort for construction of a peak ground acceleration (PGA) map of Slovenia for 475-year return period for rock and firm soil is presented. The methodology is similar to that recently applied in Central and Eastern United States. It is based on historical seismicity spatially smoothed to different length scales. The procedure is described by Frankel (1995). He uses the characteristic earthquake recurrence relationship and in his firt version four different seismicity models. We also use four seismicity models. But instead of characteristic earthquake recurrence, we use the doubly truncated exponential magnitude-frequency relationship; no evidence of characteristic earthquakes in Slovenia has been found yet. Three of our models are similar to Frankel's first three models. Model 1 uses spatially smoothed activity rate based on magnitude 3.7 and above events since 1880. Model 2 deals with spatially smoothed activity rate based on magnitude 5.0 abd above events since 1690. Model 3 smoothes the observed activity over the entire region; it represents a uniform seismicity zone. Frankel skipped this model in his latest version (Frankel et al. 1996). In model 4, we introduce a new approach of calculating seismic activity rate taking into account released seismic energy. The ground motion attenuation model of Pugliese and Sabetta (1989) is used for all models. PGA maps for models 1, 2, 3 and 4 have been calculated, and a weighted mean map derived from them. A map of model 1 has been compared with the corresponding source zone map; the two maps do not differ significantly. A worst-case map derived from all four models has also been produced.