玉树7.1级地震震后损失快速评估

2010年4月14日7时49分,在青海省玉树县发生里氏7.1级地震,震中位于北纬33.2°、东经96.6°,震源深度为14 km.在玉树地震发生后,基于经验模型的震后损失快速评估方法,用较少的信息和数据,对玉树地震灾情进行了快速应急评估,绘制了经验等震线图,给出了房屋损失的初步评估结果,与最终的损失调查统计结果相比,震...     

The use of isotopes in evolving groundwater circulation models of regional continental aquifers: The case of the Guarani Aquifer System

The Guarani Aquifer System (GAS) has been studied since the 1970s, a time frame that coincides with the advent of isotopic techniques in Brazil. The GAS isotope data from many studies are organized in different phases: (a) the advent of isotope techniques, (b) consolidation and new applications, (c) isotope assessments and hydrochemistry evolution, and (d) a roadmap to a new conceptual model. The reasons behind the phases, their methodological approaches, and impacts on the regional flow conceptual models are examined. Starting with local δ²H and δ¹⁸O assessments of values for water fingerprinting and estimates of recharge palaeoclimate scenarios, studies evolved to more integrated approaches based on multiple tracers. Stable isotope application techniques were consolidated during the 1980s, when new dating approaches dealing with radiogenic and heavy isotopes were introduced. Through the execution of an international transboundary project, the GAS was studied and extensively sampled for isotopes. These results have triggered wider application of isotope techniques, reflecting also world research trends. Presently, hydrochemical evolution models along flow lines from recharge to discharge areas, across large‐scale tectonic features within the entire sedimentary basin, are being combined with residence time estimates at GAS outcrop areas and deep confined units. In a complex system, it is normal that many, and even contradictory hypotheses are proposed, but isotope techniques provide a unique chance to test them. Stable isotope assessments are still needed near recharge areas, and they can be combined with groundwater classical dating procedures, complemented by newer techniques (³H‐³He, CFCs, and SF₆)_. Recent noble gas sampling and world pioneer analytical efforts focused on the confined units in the GAS will certainly led to new findings on the overall GAS circulation. The objective of this article is to discuss how isotope information can contribute to the evolution of conceptual groundwater flow models for regional continental aquifers, such as the GAS.     

Predicting Water Resource Impacts of Unconventional Gas Using Simple Analytical Equations

The rapid expansion in unconventional gas development over the past two decades has led to concerns over the potential impacts on groundwater resources. Although numerical models are invaluable for assessing likelihood of impacts at particular sites, simpler analytical models are also useful because they help develop hydrological understanding. Analytical approaches are also valuable for preliminary assessments and to determine where more complex models are warranted. In this article, we present simple analytical solutions that can be used to predict: (1) the spatial extent of drawdown from horizontal wells drilled into the gas‐bearing formation, and rate of recovery after gas production ceases; (2) the potential for upward transport of contaminants from the gas‐bearing formation to shallow aquifers during hydraulic fracturing operations when pressures in the gas‐bearing formation are greatly increased; and (3) the potential downward leakage of water from shallow aquifers during depressurization of gas‐bearing formations. In particular, we show that the recovery of pressure after production ceases from gas‐bearing shale formations may take several hundred years, and we present critical hydraulic conductivity values for intervening aquitards, below which the impact on shallow aquifers will be negligible. The simplifying assumptions inherent in these solutions will limit their predictive accuracy for site‐specific assessments, compared to numerical models that incorporate knowledge of spatial variations in formation properties and which may include processes not considered in the simpler solutions.     

Review of Gould–Dincer reservoir storage–yield–reliability estimates

The Gould–Dincer suite of techniques (normal, log-normal and Gamma), which is used to estimate the reservoir capacity–yield–reliability (S–Y–R) relationship, is the only known available procedure in the form of a simple formula, based on annual streamflow statistics, that allows one to compute the S–Y–R relationship for a single storage capacity across the range of annual streamflow characteristics observed globally. Several other techniques are available but they are inadequate because of the restricted range of flows on which they were developed or because they are based on the Sequent Peak Algorithm or are not suitable to compute steady-state reliability values. This paper examines the theoretical basis of the Gould–Dincer approach and applies the three models to annual streamflow data for 729 rivers distributed world-wide. The reservoir capacities estimated by the models are compared with equivalent estimates based on the Extended Deficit Analysis, Behaviour analysis and the Sequent Peak Algorithm. The results suggest that, in the context of preliminary water resources planning, the Gould–Dincer Gamma model provides reliable estimates of the mean first passage time from a full to empty condition for single reservoirs. Furthermore, the storage estimates are equivalent to deficits computed using the Extended Deficit Analysis for values of drift between 0.4 and 1.0 and the values are consistent with those computed using a Behaviour simulation or a Sequent Peak Algorithm. Finally, a sensitivity analysis of the effect on storage of the four main streamflow statistics confirms that the influential ones are mean and standard deviation, while effects of skew and serial correlation are orders of magnitude lower. This finding suggests that the simple reduced form of the Gould–Dincer equation may profitably be used for regional studies of reservoir reliability subject to climate change scenarios based on regional statistics, without having to perform calculations based on time series, which may not be easily obtained.     

Field study of hydrogeologic characterization methods in a heterogeneous aquifer

Hydraulic conductivity (K) and specific storage (S(s)) are required parameters when designing transient groundwater flow models. The purpose of this study was to evaluate the ability of commonly used hydrogeologic characterization approaches to accurately delineate the distribution of hydraulic properties in a highly heterogeneous glaciofluvial deposit. The metric used to compare the various approaches was the prediction of drawdown responses from three separate pumping tests. The study was conducted at a field site, where a 15 m × 15 m area was instrumented with four 18-m deep Continuous Multichannel Tubing (CMT) wells. Each CMT well contained seven 17 cm × 1.9 cm monitoring ports equally spaced every 2 m down each CMT system. An 18-m deep pumping well with eight separate 1-m long screens spaced every 2 m was also placed in the center of the square pattern. In each of these boreholes, cores were collected and characterized using the Unified Soil Classification System, grain size analysis, and permeameter tests. To date, 471 K estimates have been obtained through permeameter analyses and 270 K estimates from empirical relationships. Geostatistical analysis of the small-scale K data yielded strongly heterogeneous K fields in three-dimensions. Additional K estimates were obtained through slug tests in 28 ports of the four CMT wells. Several pumping tests were conducted using the multiscreen and CMT wells to obtain larger scale estimates of both K and S(s). The various K and S(s) estimates were then quantitatively evaluated by simulating transient drawdown data from three pumping tests using a 3D forward numerical model constructed using HydroGeoSphere (Therrien et al. 2005). Results showed that, while drawdown predictions generally improved as more complexity was introduced into the model, the ability to make accurate drawdown predictions at all CMT ports was inconsistent.     

The displacement coefficient method in near‐source conditions

The use of nonlinear static procedures for performance‐based seismic design (PBSD) and assessment is a well‐established practice, which has found its way into modern codes for quite some time. On the other hand, near‐source (NS) ground motions are receiving increasing attention, because they can carry seismic demand systematically different and larger than that of the so‐called ordinary records. This is due to phenomena such as rupture forward directivity (FD), which can lead to distinct pulses appearing in the velocity time‐history of the ground motion. The framework necessary for taking FD into account in probabilistic seismic hazard analysis (PSHA) has recently been established. The objective of the present study is to discuss the extension of nonlinear static procedures, specifically the displacement coefficient method (DCM), with respect to the inelastic demand associated with FD. In this context, a methodology is presented for the implementation of the DCM toward estimating NS seismic demand, by making use of the results of NS‐PSHA and a semi‐empirical equation for NS‐FD inelastic displacement ratio. An illustrative application of the DCM, with explicit inclusion of NS‐pulse‐like effects, is given for a set of typical plane R/C frames designed under Eurocode provisions. Different scenarios are considered in the application and nonlinear dynamic analysis results are obtained and discussed with respect to the static procedure estimates. Conclusions drawn from the results may help to assess the importance of incorporating NS effects in PBSD. Copyright © 2014 John Wiley & Sons, Ltd.     

Evaluation of the exact conditional spectrum and generalized conditional intensity measure methods for ground motion selection

Two existing, contemporary ground motion selection and modification procedures – (i) exact conditional spectrum (CS‐exact) and (ii) generalized conditional intensity measure (GCIM) – are evaluated in their ability to accurately estimate seismic demand hazard curves (SDHCs) of a given structure at a specified site. The amount of effort involved in implementing these procedures to compute a single SDHC is studied, and a case study is chosen where rigorous benchmark SDHCs can be determined for evaluation purposes. By comparing estimates from ground motion selection and modification procedures with the benchmark, we conclude that estimates from CS‐exact are unbiased in many of the cases considered. The estimates from GCIM are even more accurate, as they are unbiased for most – but not all – of the cases where estimates from CS‐exact are biased. We find that it is possible to obtain biased SDHCs from GCIM, even after employing a very diverse collection of intensity measures to select ground motions and implementing its bias‐checking feature, because it is usually difficult to identify intensity measures that are truly ‘sufficient’ for the response of a complex, multi‐degree‐of‐freedom system. Copyright © 2015 John Wiley & Sons, Ltd.     

The estimation of earthquake-generated additional tension in a suspension bridge cable

A simple formula, equation (15), is derived for the peak additional cable tension that can be expected in a suspension bridge undergoing earthquake excitation. The method involves application of the response spectrum technique and rests on several plausible assumptions. The formula gives a reasonable upper bound, suitable for preliminary design estimates, irrespective of whether the ground motions at each end are in-phase or, as is probable with a long span bridge, whether they are out-of-phase.     

Estimating minimum streamflow from measurements at ungauged sites in regions with streamflow‐gauging networks

Estimation of low flows in rivers continues to be a vexing problem despite advances in statistical and process‐based hydrological models. We develop a method to estimate minimum streamflow at seasonal to annual timescales from measured streamflow based on regional similarity in the deviations of daily streamflow from minimum streamflow for a period of interest. The method is applied to 1,019 gauged sites in the Western United States for June to December 2015. The gauges were clustered into six regions with distinct timing and magnitude of low flows. A gamma distribution was fit each day to the deviations in specific discharge (daily streamflow divided by drainage area) from minimum specific discharge for gauges in each region. The Kolmogorov–Smirnov test identified days when the gamma distribution was adequate to represent the distribution of deviations in a region. The performance of the gamma distribution was evaluated at gauges by comparing daily estimates of minimum streamflow with estimates from area‐based regression relations for minimum streamflow. Each region had at least 8 days during the period when streamflow measurements would provide better estimates than the regional regression equation, but the number of such days varied by region depending on aridity and homogeneity of streamflow within the region. Synoptic streamflow measurements at ungauged sites have value for estimating minimum streamflow and improving the spatial resolution of hydrological model in regions with streamflow‐gauging networks.     

Modeling spatially correlated spectral accelerations at multiple periods using principal component analysis and geostatistics

Regional seismic risk assessments and quantification of portfolio losses often require simulation of spatially distributed ground motions at multiple intensity measures. For a given earthquake, distributed ground motions are characterized by spatial correlation and correlation between different intensity measures, known as cross‐correlation. This study proposes a new spatial cross‐correlation model for within‐event spectral acceleration residuals that uses a combination of principal component analysis (PCA) and geostatistics. Records from 45 earthquakes are used to investigate earthquake‐to‐earthquake trends in application of PCA to spectral acceleration residuals. Based on the findings, PCA is used to determine coefficients that linearly transform cross‐correlated residuals to independent principal components. Nested semivariogram models are then fit to empirical semivariograms to quantify the spatial correlation of principal components. The resultant PCA spatial cross‐correlation model is shown to be accurate and computationally efficient. A step‐by‐step procedure and an example are presented to illustrate the use of the predictive model for rapid simulation of spatially cross‐correlated spectral accelerations at multiple periods.     

Estimating Land Surface Evaporation: A Review of Methods Using Remotely Sensed Surface Temperature Data

This paper reviews methods for estimating evaporation from landscapes, regions and larger geographic extents, with remotely sensed surface temperatures, and highlights uncertainties and limitations associated with those estimation methods. Particular attention is given to the validation of such approaches against ground based flux measurements. An assessment of some 30 published validations shows an average root mean squared error value of about 50 W m^?2 and relative errors of 15–30%. The comparison also shows that more complex physical and analytical methods are not necessarily more accurate than empirical and statistical approaches. While some of the methods were developed for specific land covers (e.g. irrigation areas only) we also review methods developed for other disciplines, such as hydrology and meteorology, where continuous estimates in space and in time are needed, thereby focusing on physical and analytical methods as empirical methods are usually limited by in situ training data. This review also provides a discussion of temporal and spatial scaling issues associated with the use of thermal remote sensing for estimating evaporation. Improved temporal scaling procedures are required to extrapolate instantaneous estimates to daily and longer time periods and gap-filling procedures are needed when temporal scaling is affected by intermittent satellite coverage. It is also noted that analysis of multi-resolution data from different satellite/sensor systems (i.e. data fusion) will assist in the development of spatial scaling and aggregation approaches, and that several biological processes need to be better characterized in many current land surface models.     

Conditional spectrum‐based ground motion selection. Part II: Intensity‐based assessments and evaluation of alternative target spectra

In a companion paper, an overview and problem definition was presented for ground motion selection on the basis of the conditional spectrum (CS), to perform risk‐based assessments (which estimate the annual rate of exceeding a specified structural response amplitude) for a 20‐story reinforced concrete frame structure. Here, the methodology is repeated for intensity‐based assessments (which estimate structural response for ground motions with a specified intensity level) to determine the effect of conditioning period. Additionally, intensity‐based and risk‐based assessments are evaluated for two other possible target spectra, specifically the uniform hazard spectrum (UHS) and the conditional mean spectrum (CMS, without variability).It is demonstrated for the structure considered that the choice of conditioning period in the CS can substantially impact structural response estimates in an intensity‐based assessment. When used for intensity‐based assessments, the UHS typically results in equal or higher median estimates of structural response than the CS; the CMS results in similar median estimates of structural response compared with the CS but exhibits lower dispersion because of the omission of variability. The choice of target spectrum is then evaluated for risk‐based assessments, showing that the UHS results in overestimation of structural response hazard, whereas the CMS results in underestimation. Additional analyses are completed for other structures to confirm the generality of the conclusions here. These findings have potentially important implications both for the intensity‐based seismic assessments using the CS in future building codes and the risk‐based seismic assessments typically used in performance‐based earthquake engineering applications. Copyright © 2013 John Wiley & Sons, Ltd.     

Towards constraining the magnitude of global agricultural sediment and soil organic carbon fluxes

Reliable quantitative data on the extent and rates of soil erosion are needed to understand the global significance of soil‐erosion induced carbon exchange and to underpin the development of science‐based mitigation strategies, but large uncertainties remain. Existing estimates of agricultural soil and soil organic carbon (SOC) erosion are very divergent and span two orders of magnitude. The main objective of this study was to test the assumptions underlying existing assessments and to reduce the uncertainty associated with global estimates of agricultural soil and SOC erosion. We parameterized a simplified erosion model driven by coarse global databases using an empirical database that covers the conterminous USA. The good agreement between our model results and empirical estimates indicate that the approach presented here captures the essence of agricultural erosion at the scales of continents and that it may be used to predict the significance of erosion for the global carbon cycle and its impact on soil functions. We obtained a global soil erosion rate of 10.5 Mg ha^‐1 y^‐1 for cropland and 1.7 Mg ha^‐1 y^‐1 for pastures. This corresponds to SOC erosion rates of 193 kg C ha^‐1 y^‐1 for cropland and 40.4 kg C ha^‐1 y^‐1 for eroding pastures and results in a global flux of 20.5 (±10.3) Pg y^‐1 of soil and 403.5 (±201.8) Tg C y^‐1. Although it is difficult to accurately assess the uncertainty associated with our estimates of global agricultural erosion, mainly due to the lack of model testing in (sub‐)tropical regions, our estimates are significantly lower than former assessments based on the extrapolation of plot experiments or global application of erosion models. Our approach has the potential to quantify the rate and spatial signature of the erosion‐induced disturbance at continental and global scales: by linking our model with a global soil profile database, we estimated soil profile modifications induced by agriculture. This showed that erosion‐induced changes in topsoil SOC content are significant at a global scale (an average SOC loss of 22% in 50 years) and agricultural soils should therefore be considered as dynamic systems that can change rapidly. Copyright © 2011 John Wiley & Sons, Ltd.     

Alternative non‐linear demand estimation methods for probability‐based seismic assessments

Alternative non‐linear dynamic analysis procedures, using real ground motion records, can be used to make probability‐based seismic assessments. These procedures can be used both to obtain parameter estimates for specific probabilistic assessment criteria such as demand and capacity factored design and also to make direct probabilistic performance assessments using numerical methods. Multiple‐stripe analysis is a non‐linear dynamic analysis method that can be used for performance‐based assessments for a wide range of ground motion intensities and multiple performance objectives from onset of damage through global collapse. Alternatively, the amount of analysis effort needed in the performance assessments can be reduced by performing the structural analyses and estimating the main parameters in the region of ground motion intensity levels of interest. In particular, single‐stripe and double‐stripe analysis can provide local probabilistic demand assessments using minimal number of structural analyses (around 20 to 40). As a case study, the displacement‐based seismic performance of an older reinforced concrete frame structure, which is known to have suffered shear failure in its columns during the 1994 Northridge Earthquake, is evaluated. Copyright © 2008 John Wiley & Sons, Ltd.     

Models to determine first-order rate coefficients from single-well push-pull tests

Push-pull tests (PPTs) have been successfully employed to quantify various microbially mediated processes in the subsurface. Current models for determining first-order rate coefficients (k) from PPTs assume complete and instantaneous mixing of injected test solution in the portion of the aquifer investigated by the test, i.e., the system is treated like a well-mixed reactor. Here we present two alternative models to estimate k that are based on different mixing assumptions, i.e., plug-flow and variably mixed reactor models. Rate coefficients estimated by the models were compared using a sensitivity analysis and numerical simulations of PPTs. Results indicated that all models yielded reasonably accurate k estimates (errors < 13%), while best accuracy (errors < 1%) was obtained using the variably mixed reactor model. The well-mixed reactor model generally overestimated true (simulation input) k values, whereas true k values were consistently underestimated by the plug-flow reactor model. However, estimates of k obtained with the latter models bracketed true k values in all cases. As the variably mixed reactor model is more difficult to apply, we suggest using the well-mixed and plug-flow reactor models to obtain intervals for k estimates that will encompass true k values with high certainty. In an example application, we used all models to reanalyze a published PPT data set to obtain k estimates for nitrate consumption in a petroleum-contaminated aquifer. Similar results were obtained for all three models (relative differences < 10% between k estimates), indicating that all three models are robust tools for estimating k values from PPT experimental data.     

Spectrometric gamma radiation of shale cores applied to sweet spot discrimination in Eastern Pomerania,Poland

This paper describes the application and calculation of hydrocarbon anomalies in two different boreholes located in Eastern Pomerania (northern Poland). Spectrometric data from borehole geophysical probe (borehole 1) and portable gamma logger (borehole 2) were used to analyze shale formations. The results from borehole 1 presented a statistically significant, moderate correlation between calculated hydrocarbon anomalies and hydrocarbon saturation data obtained from well log interpretation. Borehole 2 has been analyzed focusing on the gamma radiation of the core samples, and the positive results of borehole 1. Hydrocarbon anomalies calculated from spectral gamma radiation are reliable indicators of sweet spots, based solely on a cursory evaluation of core measurements. These preliminary information acquired from gamma-ray measurements could help increase sampling precision of further geochemical analysis.     

A nonparametric characterization of vertical ground motion effects

Design guidelines have traditionally oversimplified the vertical ground motion effects by defining a constant vertical‐to‐horizontal response spectral ratio (V/H). With the recognition that such practice is not always conservative, recent studies have proposed improvements to the representation of vertical seismic effects in design codes, based on empirical ground motion relations. Conventional empirical modeling requires selecting the functional form of the predictive model. Because of the complicated nature of ground motions, identification of the underlying function is a challenge. A related drawback to this approach is its high susceptibility to overfitting, especially with today's highly complex models. To address these issues, this paper proposes a nonparametric approach to characterize the vertical seismic effects. Using support vector machines, the V/H ratio is determined without an assumed functional form. The accuracy of the model is measured by adopting an epsilon‐insensitive residual function with a regularization term added to prevent overfitting. An example application using ground motion records from strike‐slip and normal faulting earthquakes is presented, and the results are compared with a current empirical model, for different magnitude, distance, and local soil conditions. The median V/H estimates from the two models are shown to be in good general agreement. The standard deviation estimates from the proposed model are consistently larger than the estimates from the empirical model. The results from this study show that the proposed method is a viable alternative and offers the opportunity to characterize vertical seismic effects without an assumed functional form. Copyright © 2011 John Wiley & Sons, Ltd.     

Benefits and Cautions in Data Assimilation Strategies: An Example of Modeling Groundwater Recharge

Assimilating recent observations improves model outcomes for real-time assessments of groundwater processes. This is demonstrated in estimating time-varying recharge to a shallow fractured-rock aquifer in response to precipitation. Results from estimating the time-varying water-table altitude (h) and recharge, and their error covariances, are compared for forecasting, filtering, and fixed-lag smoothing (FLS), which are implemented using the Kalman Filter as applied to a data-driven, mechanistic model of recharge. Forecasting uses past observations to predict future states and is the current paradigm in most groundwater modeling investigations; filtering assimilates observations up to the current time to estimate current states; and FLS estimates states following a time lag over which additional observations are collected. Results for forecasting yield a large error covariance relative to the magnitude of the expected recharge. With assimilating recent observations of h, filtering and FLS produce estimates of recharge that better represent time-varying observations of h and reduce uncertainty in comparison to forecasting. Although model outcomes from applying data assimilation through filtering or FLS reduce model uncertainty, they are not necessarily mass conservative, whereas forecasting outcomes are mass conservative. Mass conservative outcomes from forecasting are not necessarily more accurate, because process errors are inherent in any model. Improvements in estimating real-time groundwater conditions that better represent observations need to be weighed for the model application against outcomes with inherent process deficiencies. Results from data assimilation strategies discussed in this investigation are anticipated to be relevant to other groundwater processes models where system states are sensitive to system inputs.     

2021年5月22日青海玛多MS 7.4地震灾害损失快速评估分析

2021年5月22日青海玛多M_S 7.4地震表现为灾情重、伤亡轻的特点,采用极震区烈度估计、烈度衰减关系、人员伤亡评估3种烈度衰减模型进行灾害损失快速评估,与地震现场调查结果进行对比,可知对于此次玛多M_S 7.4地震,3种模型评估与地震现场调查结果存在偏差,认为主要由地震影响场分布、人口分布、房屋建筑（抗震能力）、地形地貌、次生灾害等因素不同所致。结果显示,通过提高地震影响场评估的精准性及人口分布、房屋建筑等数据空间分布的准确性和后期专家干预等措施,均可有效提升地震灾害损失快速评估精准性。     

The potential of different ANN techniques in evapotranspiration modelling

The potential of three different artificial neural network (ANN) techniques, the multi‐layer perceptrons (MLPs), radial basis neural networks (RBNNs) and generalized regression neural networks (GRNNs), in modelling of reference evapotranspiration (ET₀) is investigated in this paper. Various daily climatic data, that is, solar radiation, air temperature, relative humidity and wind speed from two stations, Pomona and Santa Monica, in Los Angeles, USA, are used as inputs to the ANN techniques so as to estimate ET₀ obtained using the FAO‐56 Penman–Monteith (PM) equation. In the first part of the study, a comparison is made between the estimates provided by the MLP, RBNN and GRNN and those of the following empirical models: The California Irrigation Management Information System (CIMIS) Penman (1985), Hargreaves (1985) and Ritchie (1990). In this part of the study, the empirical models are calibrated using the standard FAO‐56 PM ET₀ values. The estimates of the ANN techniques are also compared with those of the calibrated empirical models. Mean square errors, mean absolute errors and determination coefficient statistics are used as comparing criteria for the evaluation of the models' performances. Based on the comparisons, it is found that the MLP and RBNN techniques could be employed successfully in modelling the ET₀ process. In the second part of the study, the potential of ANN techniques and the empirical methods in ET₀ estimation using nearby station data is investigated. Among the models, the calibrated Hargreaves model is found to perform better than the others. Copyright © 2007 John Wiley & Sons, Ltd.