Urban Seismic Risk Evaluation: A Holistic Approach

Risk has been defined, for management purposes, as the potential economic, social and environmental consequences of hazardous events that may occur in a specified period of time. However, in the past, the concept of risk has been defined in a fragmentary way in many cases, according to each scientific discipline involved in its appraisal. From the perspective of this article, risk requires a multidisciplinary evaluation that takes into account not only the expected physical damage, the number and type of casualties or economic losses, but also the conditions related to social fragility and lack of resilience conditions, which favour the second order effects (indirect effects) when a hazard event strikes an urban centre. The proposed general method of urban risk evaluation is multi hazard and holistic, that is, an integrated and comprehensive approach to guide decision-making. The evaluation of the potential physical damage (hard approach) as the result of the convolution of hazard and physical vulnerability of buildings and infrastructure is the first step of this method. Subsequently, a set of social context conditions that aggravate the physical effects are also considered (soft approach). In the method here proposed, the holistic risk evaluation is based on urban risk indicators. According to this procedure, a physical risk index is obtained, for each unit of analysis, from existing loss scenarios, whereas the total risk index is obtained by factoring the former index by an impact factor or aggravating coefficient, based on variables associated with the socio-economic conditions of each unit of analysis. Finally, the proposed method is applied in its single hazard form to the holistic seismic risk evaluation for the cities of Bogota (Colombia) and Barcelona (Spain).     

A model for estimating the value of sampling programs and the optimal number of samples for contaminated soil

A model is presented for estimating the value of information of sampling programs for contaminated soil. The purpose is to calculate the optimal number of samples when the objective is to estimate the mean concentration. A Bayesian risk–cost–benefit decision analysis framework is applied and the approach is design-based. The model explicitly includes sample uncertainty at a complexity level that can be applied to practical contaminated land problems with limited amount of data. Prior information about the contamination level is modelled by probability density functions. The value of information is expressed in monetary terms. The most cost-effective sampling program is the one with the highest expected net value. The model was applied to a contaminated scrap yard in Göteborg, Sweden, contaminated by metals. The optimal number of samples was determined to be in the range of 16–18 for a remediation unit of 100 m². Sensitivity analysis indicates that the perspective of the decision-maker is important, and that the cost of failure and the future land use are the most important factors to consider. The model can also be applied for other sampling problems, for example, sampling and testing of wastes to meet landfill waste acceptance procedures.     

Theory and application for retrieval and fusion of spatial and temporal quantitative information from complex natural environment

This paper briefly presents the research progress of the State Major Basic Research Project 2001CB309400, “Theory and Application for Retrieval and Fusion of Spatial and Temporal Quantitative Information from Complex Natural Environment”. Based on the rapid advancement of synthetic aperture radar (SAR) imagery technology, information theory of fully polarimetric scattering and applications in polarimetric SAR remote sensing are developed. To promote the modeling of passive microwave remote sensing, the vector (polarized) radiative transfer theory (VRT) of complex natural media such as inhomogeneous, multi-layered and 3-dimensional VRT is developed. With these theoretical progresses, data validation and retrieval algorithms for some typical events and characteristic parameters of earth terrain surfaces, atmosphere, and oceans from operational and experimental remote sensing satellites are studied. Employing remote sensing, radiative transfer simulation, geographic information systems (GIS), land hydrological process, and data assimilation, the Chinese land data assimilation system (CLDAS) is established. Towards the future development of China’s microwave meteorological satellites, employing remote sensing data of currently available SSM/I (special sensor microwave/imager), AMSU (advanced microwave sounding unit), MTI (microwave temperature imager), etc., with ground-based measurements, several operational algorithms and databases for atmospheric precipitation, water vapor and liquid water in clouds, and other hydrological/hydrological applications are developed. To advance China’s SAR and InSAR (interferometric SAR) technologies, the image processing and analysis of ERS (European remote sensing), Radarsat SAR, and Chinese SAR, etc., the software platforms are accomplished. Based on the researches of multi-information fusion, some simulations, identification, and information extractions of the targets from complex background clutter scenes are studied. Some experiments of radio wave propagation in anomalous atmospheric status are also carried out. Translated from Advances in Earth Science, 2007, 22(2): 111–125 [译自: 地球科学进展]     

Slowness-backazimuth weighted migration: A new array approach to a high-resolution image

We have developed a new array method combining conventional migration with a slowness-backazimuth deviation weighting scheme. All seismic traces are shifted based on the theoretical traveltime of the scattered wave from specific gridpoints in a 3-D volume. Observed slowness and backazimuth are calculated for each raypath and compared with theoretical values in order to estimate slowness and backazimuth deviations. Subsequently, stacked energy calculated by a conventional migration method is weighted by the slowness and backazimuth deviations to suppress any arrival energy whose slowness and backazimuth are inconsistent with the expected theoretical values. This new method was applied to two P- wave data sets which comprise (1) underside reflections at the 410 and 660 km mantle discontinuities and (2) D" reflections as well as their corresponding synthetic data sets. The results show that the weighting scheme dramatically increases the resolution of the migrated images and enables us to obtain well-constrained, focused images, making upper-mantle discontinuities and D" reflections more distinct by reducing their surrounding energy.     

Whole mantle SH velocity model constrained by waveform inversion based on three-dimensional Born kernels

A whole mantle SH velocity model is obtained by using a unique data set and techniques. Body and surface waveforms including major and multi-orbit phases are used as a data set and are inverted by using 3-D Born kernels. The resultant model, SH18CE, reveals the different natures of the two major upwelling systems: the strong low velocity anomalies beneath Africa extend for more than 1000 km from the core–mantle boundary (CMB), whereas those beneath the Pacific are restricted to 300–400 km from the CMB. The results also show the variable natures of stagnant slabs on the 670 discontinuity around Japan: the depths of the strongest high velocity anomalies within the stagnant slabs are different region by region, which is consistent with the detailed delay time tomography model in this area.     

Determination of earthquake early warning parameters, τc and Pd, for southern California

We explore a practical approach to earthquake early warning in southern California by determining a ground-motion period parameter  τ _c   and a high-pass filtered displacement amplitude parameter Pd from the initial 3 s of the P waveforms recorded at the Southern California Seismic Network stations for earthquakes with M > 4.0. At a given site, we estimate the magnitude of an event from  τ _c   and the peak ground-motion velocity ( PGV ) from Pd . The incoming three-component signals are recursively converted to ground acceleration, velocity and displacement. The displacements are recursively filtered with a one-way Butterworth high-pass filter with a cut-off frequency of 0.075 Hz, and a P -wave trigger is constantly monitored. When a trigger occurs,  τ _c   and Pd are computed. We found the relationship between  τ _c   and magnitude ( M ) for southern California, and between Pd and PGV for both southern California and Taiwan. These two relationships can be used to detect the occurrence of a major earthquake and provide onsite warning in the area around the station where onset of strong ground motion is expected within seconds after the arrival of the P wave. When the station density is high, the methods can be applied to multistation data to increase the robustness of onsite early warning and to add the regional warning approach. In an ideal situation, such warnings would be available within 10 s of the origin time of a large earthquake whose subsequent ground motion may last for tens of seconds.