Synthetic coral-reef terraces and variations of Quaternary sea level

Coral-reef terraces on tectonically elevated coasts provide important data on variations of sea level. In this paper a systematic approach is presented for the construction of synthetic reef terraces. Idealized reef terraces are generated assuming a constant rate of tectonic uplift ν and a harmonic variation of sea level with amplitudeh_wo and period τ. It is further assumed that coral terraces grow only during periods of relative sea-level rise. The behavior is governed by the parameter u = τυ/2π h_wo. If u > 1 no reef terraces form. If 0.217 < u < 1 a discontinuous series of terraces form on the uplifting basement. If 0 < u < 0.217 the basement is covered with coral and a series of coral terraces forms on this coral. Uplifted coral-reef terraces on the Huon Peninsula, Papua New Guinea, compare reasonably well with terraces generated by our model with τ = 20,000 years andh_wo = 21.4 m. We also compare the observed terraces with model terraces using the paleo sea level inferred from¹⁸O/¹⁶O data. The observed terraces are qualitatively similar to those predicted using the oxygen isotope data, however, the model terraces require larger relative sea-level variations with a near 20,000 year period than those inferred directly from the¹⁸O/¹⁶O data.     

A Bayesian approach to inverse modelling of stratigraphy, part 2: Validation tests

A novel inverse modelling method is applied to the problem of constraining the environmental parameters (e.g. relative sea level, sediment supply) that control stratigraphic architecture. This technique links forward modelling of shallow-marine wave/storm-dominated stratigraphy to a combination of inverse methods formulated in a Bayesian framework. We present a number of examples in which relative sea-level and sediment-supply curves were inferred from synthetic vertical successions of grain size (e.g. wells) and synthetic thickness curves (e.g. seismically derived isopachs) extracted from a forward model simulation. These examples represent different scenarios that are designed to test the impact of data distribution, quantity and quality on the uncertainty of the inferred parameters. The inverse modelling approach successfully reproduces the gross stratigraphic architectures and relative sea level and sediment-supply histories of the synthetic forward model simulation, within the constraints of the modelled data quality. The relative importance of the forcing parameters can be evaluated by their sensitivity and impact on the inverted data. Of equal importance, the inverse results allow complete characterisation of the uncertainties inherent to the stratigraphic modelling tool and to the data quality, quantity and distribution. The numerical scheme also successfully deals with the problem of non-uniqueness of the solution of the inverse problem. These preliminary results suggest that the inverse method is a powerful tool in constraining stratigraphic architecture for hydrocarbon reservoir characterisation and modelling, and it may ultimately provide a process-based geological complement to standard geostatistical tools.     

Migrating pingos in the permafrost region of the Tibetan Plateau, China and their hazard along the Golmud–Lhasa railway

Most pingos in the permafrost region of the high northern Tibetan Plateau form along active fault zones and many change position annually along the zones and thus appear to migrate. The fault zones conduct geothermal heat, which thins permafrost, and control cool to hot springs in the region. They maintain ground-water circulation through broken rock in an open system to supply water for pingo growth during the winter in overlying fluvial and lacustrian deposits. Springs remain after the pingos thaw in the summer. Fault movement, earthquakes and man's activities cause the water pathways supplying pingos to shift and consequently the pingos migrate.

The hazard posed to the new Golmud–Lhasa railway across the plateau by migrating pingos is restricted to active fault zones, but is serious, as these zones are common and generate large earthquakes. Pingos have damaged the highway and the oil pipeline adjacent to the railway since 2001. One caused tilting and breaking of a bridge pier and destroyed a highway bridge across the Chumaerhe fault. Another has already caused minor damage to a new railway bridge. Furthermore, the construction of a bridge pier in the North Wuli fault zone in July–August 2003 created a conduit for a new spring, which created a pingo during the following winter. Measures taken to drain the ground-water via a tunnel worked well and prevented damage before the railway tracks were laid. However, pier vibrations from subsequent train motion disrupted the drain and led to new springs, which may induce further pingo growth beneath the bridge.

The migrating pingos result from active fault movement promoting artesian ground-water circulation and changing water pathways under the seasonal temperature variations in the permafrost region. They pose a serious hazard to railway construction, which, in turn can further disturb the ground-water conduits and affect pingo migration.     

Assessing future risk: quantifying the effects of sea level rise on storm surge risk for the southern shores of Long Island, New York

Sea level rise threatens to increase the impacts of future storms and hurricanes on coastal communities. However, many coastal hazard mitigation plans do not consider sea level rise when assessing storm surge risk. Here we apply a GIS-based approach to quantify potential changes in storm surge risk due to sea level rise on Long Island, New York. We demonstrate a method for combining hazard exposure and community vulnerability to spatially characterize risk for both present and future sea level conditions using commonly available national data sets. Our results show that sea level rise will likely increase risk in many coastal areas and will potentially create risk where it was not before. We find that even modest and probable sea level rise (.5 m by 2080) vastly increases the numbers of people (47% increase) and property loss (73% increase) impacted by storm surge. In addition, the resulting maps of hazard exposure and community vulnerability provide a clear and useful example of the visual representation of the spatial distribution of the components of risk that can be helpful for developing targeted hazard mitigation and climate change adaptation strategies. Our results suggest that coastal agencies tasked with managing storm surge risk must consider the effects of sea level rise if they are to ensure safe and sustainable coastal communities in the future.     

Quantitative textural analysis of packings of elongate crystals

The spatial distribution of grains in a solidifying igneous rock controls the physical properties of the crystal mush, and in turn is controlled by the rate of crystal growth and accumulation. A predominant non-spherical habit for igneous minerals brings into question the use of spherical particles in reference packings used for quantification of spatial distribution. Furthermore, variations of crystal clustering/ordering with length scale require spatial statistics which take into account the distribution of particles beyond nearest neighbours. Using random close packings of spherocylinders, we demonstrate the importance of aspect ratio for the aggregation index (usually known as R) and show that packings of spherical particles have more structure than packings of rods. The spatial distribution functions demonstrate that the plagioclase grains in the colonnade from the Holyoke basalt are clustered on a length scale of 0.5 mm. Understanding the controls on grain spatial distribution in igneous rocks will depend on the application of these techniques to well-understood environments.     

Inverse Analysis of Deep Excavation Using Differential Evolution Algorithm

This paper presents the applications of the differential evolution (DE) algorithm in back analysis of soil parameters for deep excavation problems. A computer code, named Python‐based DE, is developed and incorporated into the commercial finite element software ABAQUS, with a parallel computing technique to run an FE analysis for all trail vectors of one generation in DE in multiple cores of a cluster, which dramatically reduces the computational time. A synthetic case and a well‐instrumented real case, that is, the Taipei National Enterprise Center (TNEC) project, are used to demonstrate the capability of the proposed back‐analysis procedure. Results show that multiple soil parameters are well identified by back analysis using a DE optimization algorithm for highly nonlinear problems. For the synthetic excavation case, the back‐analyzed parameters are basically identical to the input parameters that are used to generate synthetic response of wall deflection. For the TNEC case with a total of nine parameters to be back analyzed, the relative errors of wall deflection for the last three stages are 2.2, 1.1, and 1.0%, respectively. Robustness of the back‐estimated parameters is further illustrated by a forward prediction. The wall deflection in the subsequent stages can be satisfactorily predicted using the back‐analyzed soil parameters at early stages. Copyright © 2014 John Wiley & Sons, Ltd.     

Monthly prediction of rainfall over India and its homogeneous zones during monsoon season: a supervised principal component regression approach on general circulation model products

A supervised principal component regression (SPCR) technique has been employed on general circulation model (GCM) products for developing a monthly scale deterministic forecast of summer monsoon rainfall (June–July–August–September) for different homogeneous zones and India as a whole. The time series of the monthly observed rainfall as the predictand variable has been used from India Meteorological Department gridded (1°?×?1°) rainfall data. Lead 0 (forecast initialized in the same month) monthly products from GCMs are used as predictors. The sources of these GCMs are International Research Institute for Climate and Society, Columbia University, National Center for Environmental Prediction, and Japan Agency for Marine Earth Science and Technology. The performance of SPCR technique is judged against simple ensemble mean of GCMs (EM) and it is found that over almost all the zones the SPCR model gives better skill than EM in June, August, and September months of monsoon. The SPCR technique is able to capture the year to year observed rainfall variability in terms of sign as well as the magnitude. The independent forecasts of 2007 and 2008 are also analyzed for different monsoon months (Jun–Sep) in homogeneous zones and country. Here, 1982–2006 have been considered as development year or training period. Results of the study suggest that the SPCR model is able to catch the observational rainfall over India as a whole in June, August, and September in 2007 and June, July, and August in 2008.     

Potential environmental issues of CO2 storage in deep saline aquifers: Geochemical results from the Frio-I Brine Pilot test,Texas, USA

Sedimentary basins in general, and deep saline aquifers in particular, are being investigated as possible repositories for large volumes of anthropogenic CO₂ that must be sequestered to mitigate global warming and related climate changes. To investigate the potential for the long-term storage of CO₂ in such aquifers, 1600 t of CO₂ were injected at 1500 m depth into a 24-m-thick “C” sandstone unit of the Frio Formation, a regional aquifer in the US Gulf Coast. Fluid samples obtained before CO₂ injection from the injection well and an observation well 30 m updip showed a Na–Ca–Cl type brine with ∼93,000 mg/L TDS at saturation with CH₄ at reservoir conditions; gas analyses showed that CH₄ comprised ∼95% of dissolved gas, but CO₂ was low at 0.3%. Following CO₂ breakthrough, 51 h after injection, samples showed sharp drops in pH (6.5–5.7), pronounced increases in alkalinity (100–3000 mg/L as HCO₃) and in Fe (30–1100 mg/L), a slug of very high DOC values, and significant shifts in the isotopic compositions of H₂O, DIC, and CH₄. These data, coupled with geochemical modeling, indicate corrosion of pipe and well casing as well as rapid dissolution of minerals, especially calcite and iron oxyhydroxides, both caused by lowered pH (initially ∼3.0 at subsurface conditions) of the brine in contact with supercritical CO₂.