Multi-scale modeling of three-phase–three-component processes in heterogeneous porous media

Flow and transport processes in porous media occur on different spatial and temporal scales and may also be locally different. Additionally, the structure of the porous medium itself generally shows a high dependence on the spatial scale.     

Detection and Analysis of Near-Surface Explosions on the Kola Peninsula

Seismic and infrasonic observations of signals from a sequence of near-surface explosions at a site on the Kola Peninsula have been analyzed. NORSAR’s automatic network processing of these events shows a significant scatter in the location estimates and, to improve the automatic classification of the events, we have performed full waveform cross-correlation on the data set. Although the signals from the different events share many characteristics, the waveforms do not exhibit a ripple-for-ripple correspondence and cross-correlation does not result in the classic delta-function indicative of repeating signals. Using recordings from the ARCES seismic array (250 km W of the events), we find that a correlation detector on a single channel or three-component station would not be able to detect subsequent events from this source without an unacceptable false alarm rate. However, performing the correlation on each channel of the full ARCES array, and stacking the resulting traces, generates a correlation detection statistic with a suppressed background level which is exceeded by many times its standard deviation on only very few occasions. Performing f-k analysis on the individual correlation coefficient traces, and rejecting detections indicating a non-zero slowness vector, results in a detection list with essentially no false alarms. Applying the algorithm to 8 years of continuous ARCES data identified over 350 events which we confidently assign to this sequence. The large event population provides additional confidence in relative travel-time estimates and this, together with the occurrence of many events between 2002 and 2004 when a temporary network was deployed in the region, reduces the variability in location estimates. The best seismic location estimate, incorporating phase information for many hundreds of events, is consistent with backazimuth measurements for infrasound arrivals at several stations at regional distances. At Lycksele, 800 km SW of the events, as well as at ARCES, infrasound is detected for most of the events in the summer and for few in the winter. At Apatity, some 230 km S of the estimated source location, infrasound is detected for most events. As a first step to providing a Ground Truth database for this useful source of infrasound, we provide the times of explosions for over 50 events spanning 1 year.     

Effectiveness of a market-based instrument for the allocation of water in a tropical river environment

The seasonal nature of Australia’s tropical rivers means that connected groundwater aquifers are an important source of both consumptive and non-consumptive water, particularly during the dry season. The management of these common pool groundwater resources is one of the predominant water issues facing northern Australia. A national program of water reform stipulates the expansion of water trading as a key instrument for water allocation. The effectiveness of new institutional arrangements such as water markets will be determined mostly by how well they coordinate with local environmental requirements, local institutions and local norms. This paper describes a novel application of combined field work, institutional analysis, experimental economics and agent-based modeling to the analysis of a potential water market in the Katherine region of the Northern Territory, Australia. The effectiveness of different versions of the policy instrument is assessed in light of local conditions. Instruments that enable personal relationships and local institutions and norms to play a role in water management are found to be more effective in terms of both farming income and environmental impact.     

Petrology and geochronology of basalt breccia from the 1996 earthquake swarm of Loihi seamount, Hawaii: magmatic history of its 1996 eruption

 Samples of basalt were collected during the Rapid Response cruise to Loihi seamount from a breccia that was probably created by the July to August 1996 Loihi earthquake swarm, the largest swarm ever recorded from a Hawaiian volcano. ²¹⁰Po–²¹⁰Pb dating of two fresh lava blocks from this breccia indicates that they were erupted during the first half of 1996, making this the first documented historical eruption of Loihi. Sonobuoys deployed during the August 1996 cruise recorded popping noises north of the breccia site, indicating that the eruption may have been continuing during the swarm. All of the breccia lava fragments are tholeiitic, like the vast majority of Loihi's most recent lavas. Reverse zoning at the rim of clinopyroxene phenocrysts, and the presence of two chemically distinct olivine phenocryst populations, indicate that the magma for the lavas was mixed just prior to eruption. The trace element geochemistry of these lavas indicates there has been a reversal in Loihi's temporal geochemical trend. Although the new Loihi lavas are similar isotopically and geochemically to recent Kilauea lavas and the mantle conduits for these two volcanoes appear to converge at depth, distinct trace element ratios for their recent lavas preclude common parental magmas for these two active volcanoes. The mineralogy of Loihi's recent tholeiitic lavas signify that they crystallized at moderate depths (∼8–9 km) within the volcano, which is approximately 1 km below the hypocenters for earthquakes from the 1996 swarm. Taken together, the petrological and seismic evidence indicates that Loihi's current magma chamber is considerably deeper than the shallow magma chamber (∼3–4 km) in the adjoining active shield volcanoes. Received: 21 August 1997 / Accepted: 15 February 1998     

Truncation of the distribution of ground-motion residuals

Recent studies to assess very long-term seismic hazard in the USA and in Europe have highlighted the importance of the upper tail of the ground-motion distribution at the very low annual frequencies of exceedance required by these projects. In particular, the use of an unbounded lognormal distribution to represent the aleatory variability of ground motions leads to very high and potentially unphysical estimates of the expected level of shaking. Current practice in seismic hazard analysis consists of truncating the ground-motion distribution at a fixed number (ε _max) of standard deviations (σ). However, there is a general lack of consensus regarding the truncation level to adopt. This paper investigates whether a physical basis for choosing ε _max can be found, by examining records with large positive residuals from the dataset used to derive one of the ground-motion models of the Next Generation Attenuation (NGA) project. In particular, interpretations of the selected records in terms of causative physical mechanisms are reviewed. This leads to the conclusion that even in well-documented cases, it is not possible to establish a robust correlation between specific physical mechanisms and large values of the residuals, and thus obtain direct physical constraints on ε _max. Alternative approaches based on absolute levels of ground motion and numerical simulations are discussed. However, the choice of ε _max is likely to remain a matter of judgment for the foreseeable future, in view of the large epistemic uncertainties associated with these alternatives. Additional issues arise from the coupling between ε _max and σ, which causes the truncation level in terms of absolute ground motion to be dependent on the predictive equation used. Furthermore, the absolute truncation level implied by ε _max will also be affected if σ is reduced significantly. These factors contribute to rendering a truncation scheme based on a single ε _max value impractical.     

Modelling peak accelerations from earthquakes

This paper deals with the prediction of peak horizontal accelerations with emphasis on seismic risk and insurance concerns. Non‐linear mixed effects models are used to analyse well‐known earthquake data and the consequences of mis‐specifying assumptions on the error term are quantified. A robust fit of the usual model, using recently developed robust weighted maximum likelihood estimators, is presented. Outlying data are automatically identified and subsequently investigated. A more appropriate model accounting for the extreme value nature of the responses, is also developed and implemented. The implication on acceleration predictions is demonstrated. Copyright © 2006 John Wiley & Sons, Ltd.