A material model for inelastic rock deformation with spatial variation of pore pressure

This paper sets forth the theoretical background and basic numerical expressions for the incorporation of elastic-plastic constitutive equations for ductile rock into a finite element computer code. The derivation of an expression for the total strain rate is performed both for a total stress formulation and for a formulation that employs the concept of effective stress for inelastic behaviour. Specific expressions for the incremental strain rate are presented for the case of a porous material having a quadratic initial yield surface and observing the associated flow rule with a special hardening law for subsequent plastic deformation. A final section of the paper summarizes the expressions required to insert the quadratic yield surface model into a finite element code.     

Net primary productivity of forest stands in New Hampshire estimated from Landsat and MODIS satellite data

Background

A simulation model that relies on satellite observations of vegetation cover from the Landsat 7 sensor and from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate net primary productivity (NPP) of forest stands at the Bartlett Experiment Forest (BEF) in the White Mountains of New Hampshire.

Results

Net primary production (NPP) predicted from the NASA-CASA model using 30-meter resolution Landsat inputs showed variations related to both vegetation cover type and elevational effects on mean air temperatures. Overall, the highest predicted NPP from the NASA-CASA model was for deciduous forest cover at low to mid-elevation locations over the landscape. Comparison of the model-predicted annual NPP to the plot-estimated values showed a significant correlation of R² = 0.5. Stepwise addition of 30-meter resolution elevation data values explained no more than 20% of the residual variation in measured NPP patterns at BEF. Both the Landsat 7 and the 250-meter resolution MODIS derived mean annual NPP predictions for the BEF plot locations were within ± 2.5% of the mean of plot estimates for annual NPP.

Conclusion

Although MODIS imagery cannot capture the spatial details of NPP across the network of closely spaced plot locations as well as Landsat, the MODIS satellite data as inputs to the NASA-CASA model does accurately predict the average annual productivity of a site like the BEF.     

Artificial Sweeteners Identify Spatial Patterns of Historic Landfill Contaminated Groundwater Discharge in an Urban Stream

Leachate-contaminated groundwater from historical municipal landfills, typically lacking engineered liners and leachate collection systems, poses a threat to nearby urban streams, particularly to benthic ecosystems. Effective monitoring and assessment of such sites requires understanding of the spatial patterns (i.e., two-dimensional footprint) of contaminated groundwater discharge and associated controlling factors. However, discharges from groundwater contaminated by modern wastewater can complicate site assessments. The objectives of this study were to (1) demonstrate the use of artificial sweeteners (AS): saccharin (SAC), cyclamate (CYC), acesulfame (ACE), and sucralose (SUC), to distinguish groundwater discharge areas influenced by historic landfill leachate (elevated SAC and sometimes CYC; low ACE and SUC concentrations) from those influenced by wastewater (high ACE and SUC concentrations), and (2) investigate contaminant discharge patterns for two gaining urban stream reaches adjacent historic landfills at base flows. Contaminant discharge patterns revealed by the AS were strongly controlled by hyporheic flow (low AS concentrations), particularly for the straight reach, and stream sinuosity, particularly for the meandering reach. These patterns were different and the contaminant footprint coverage (<25% of streambed area) much less than most past studies (typically >50% coverage), likely due to the homogeneous streambed-aquifer conditions and shallow, narrow landfill plume in this setting.     

Apportioning deformation among depth intervals in an aquifer system using InSAR and head data

Land surface subsidence due to excessive groundwater pumping is an increasing concern in California, USA. Interferometric Synthetic Aperture Radar (InSAR) is a remote sensing technique for measuring centimeter-to-millimeter surface deformation at 10–100 m spatial resolution. Here, a data-driven approach that attributes deformation to individual depth intervals within an aquifer system by integrating head data acquired from each of three screened intervals in a monitoring well with InSAR surface deformation measurements was developed. The study area was the Colusa Basin in northern Central Valley. To reconstruct the surface deformation history over the study area, 13 ALOS-PALSAR scenes acquired between 2006 and 2010 were processed. Up to ~3-cm year^?1 long-term subsidence and up to ~6 cm seasonal subsidence were observed using the InSAR technique. The technique developed in this paper integrates the InSAR-observed seasonal deformation rate and the co-located head measurements in multiple depth intervals to estimate the elastic skeletal storage coefficient, the time delay between the head change and the observed deformation, and subsequently the deformation of each depth interval. This technique can be implemented when hydraulic head measurements within each depth interval are not correlated with each other. Using this approach, the depth interval that contributed the most to the total subsidence, as well as storage parameters for all intervals, are estimated. The technique can be used for identification of the depth interval within the aquifer system responsible for deformation.

     

Constraints on the source of Cu in a submarine magmatic-hydrothermal system,Brothers volcano,Kermadec island arc

Most magmatic-hydrothermal Cu deposits are genetically linked to arc magmas. However, most continental or oceanic arc magmas are barren, and hence new methods have to be developed to distinguish between barren and mineralised arc systems. Source composition, melting conditions, the timing of S saturation and an initial chalcophile element-enrichment represent important parameters that control the potential of a subduction setting to host an economically valuable deposit. Brothers volcano in the Kermadec island arc is one of the best-studied examples of arc-related submarine magmatic-hydrothermal activity. This study, for the first time, compares the chemical and mineralogical composition of the Brothers seafloor massive sulphides and the associated dacitic to rhyolitic lavas that host the hydrothermal system. Incompatible trace element ratios, such as La/Sm and Ce/Pb, indicate that the basaltic melts from L’Esperance volcano may represent a parental analogue to the more evolved Brothers lavas. Copper-rich magmatic sulphides (Cu?>?2 wt%) identified in fresh volcanic glass and phenocryst phases, such as clinopyroxene, plagioclase and Fe–Ti oxide suggest that the surrounding lavas that host the Brothers hydrothermal system represent a potential Cu source for the sulphide ores at the seafloor. Thermodynamic calculations reveal that the Brothers melts reached volatile saturation during their evolution. Melt inclusion data and the occurrence of sulphides along vesicle margins indicate that an exsolving volatile phase extracted Cu from the silicate melt and probably contributed it to the overlying hydrothermal system. Hence, the formation of the Cu-rich seafloor massive sulphides (up to 35.6 wt%) is probably due to the contribution of Cu from a bimodal source including wall rock leaching and magmatic degassing, in a mineralisation style that is hybrid between Cyprus-type volcanic-hosted massive sulphide and subaerial epithermal–porphyry deposits.     

New insights into volcanic processes from deep mining of the southern diatreme within the Argyle lamproite pipe,Western Australia

Underground mining and deep drilling of the richly diamondiferous ~1.2 Ga Argyle lamproite in Western Australia has prompted a re-evaluation of the geology of the pipe. Argyle is considered to be a composite pipe that formed by the coalescence of several diatremes and has been offset and elongated by post-emplacement faulting. Recent geological studies have recognised at least five distinct volcaniclastic lamproite lithofacies with differing diamond grades. The new data suggest that the centre of the southern (main) diatreme is occupied by well-bedded, olivine lamproite lapilli tuff with very high diamond grades (>10 ct/t). Characteristic features include a clast-supported fabric and high modal abundance of densely packed lamproite lapilli and coarse-grained, likely mantle-derived olivine now replaced by serpentine and/or talc. The persistence of small-scale graded and cross-bedding in this lithofacies to depths of ~1.5 km below the original surface prior to erosion suggests phreatomagmatic volcanism forming the diatreme was syn-eruptively accompanied by subsidence of the tephra, maintaining a steep-walled diatreme in the water-saturated country rock sediments.

     

Quantifying Metabolically Driven pH and Oxygen Fluctuations in US Nearshore Habitats at Diel to Interannual Time Scales

We compiled and examined 15 years (2002–2016) of high-frequency monitoring data from the National Estuarine Research Reserve System (NERRS) to characterize diel to interannual variability of pH and dissolved oxygen (DO, % saturation) across 16 diverse, shallow-water habitats along the US Atlantic, Gulf of Mexico, Caribbean, and Pacific coasts. We asked whether these systems exhibit a common pH/DO relationship, whether there were detectable interannual trends in temperature, pH, and DO within and across systems, and how pH/DO dynamics would relate to measured levels of nutrients and chlorophyll. Our analyses confirmed that large, metabolically driven, and thus concurrent fluctuations of pH and DO are a unifying feature of nearshore habitats. Moreover, we derived well-constrained relationships that predict (i) monthly mean pH or (ii) mean diel pH fluctuations across systems based on habitat mean salinity and (i) mean DO or (ii) mean diel DO fluctuations. This suggests that common metabolic principles drive diel to seasonal pH/DO variations within as well as across a diversity of estuarine environments. Yearly pH and DO anomalies did not show monotonous trends over the study period and differed considerably between sites and regions. However, weekly anomalies of means, diel minima, and diel ranges of pH and DO changed significantly over time and were strongly correlated to temperature anomalies. These general patterns lend strong empirical support to the notion that coastal acidification—in addition to being driven by eutrophication and atmospheric CO₂ increases—is exacerbated simply by warming, likely via increasing community respiration. Nutrient and chlorophyll dynamics were inversely related in these shallow, well-mixed systems, but higher nutrient levels were still associated with lower pH and lower DO levels in most, but not all, systems. Our analyses emphasize the particular dynamics of nearshore habitats and the critical importance of NERRS and its system-wide monitoring program.     

An acoustic emission landslide early warning system for communities in low-income and middle-income countries

Early warning systems for slope instability are needed to alert users of accelerating slope deformation behaviour, enable evacuation of vulnerable people, and conduct timely repair and maintenance of critical infrastructure. Communities exposed to landslide risk in low- and middle-income countries seldom currently instrument and monitor slopes to provide a warning of instability because existing techniques are complex and prohibitively expensive. Research and field trials have demonstrated conclusively that acoustic emission (AE) monitoring can be an effective approach to detect accelerating slope movements and to subsequently communicate warnings to users. The objective of this study was to develop and assess a simple, robust, low-cost AE monitoring system to warn of incipient landslides, which can be widely deployed and operated by communities globally to help protect vulnerable people. This paper describes a novel AE measurement sensor that has been designed and developed with the cost constrained to a few hundred dollars (US). Results are presented from physical model experiments that demonstrate performance of the AE system in measuring accelerating deformation behaviour, with quantifiable relationships between AE and displacement rates. Exceedance of a pre-determined trigger level of AE can be used to communicate an alarm to users in order to alert them of a slope failure. Use of this EWS approach by communities worldwide would reduce the number of fatalities caused by landslides.     

Evaluation of Goddard’s LiDAR,hyperspectral, and thermal data products for mapping urban land-cover types

Goddard’s LiDAR (Light Detection And Ranging), hyperspectral and thermal (G-LiHT) airborne imager is a new system to advance concepts of data fusion for worldwide applications. A recent G-LiHT mission conducted in June 2016 over an urban area opens a new opportunity to assess the G-LiHT products for urban land-cover mapping. In this study, the G-LiHT hyperspectral and LiDAR-canopy height model (LiDAR-CHM) products were evaluated to map five broad land-cover types. A feature/decision-level fusion strategy was developed to integrate two products. Contemporary data processing techniques were applied, including object-based image analysis, machine-learning algorithms, and ensemble analysis. Evaluation focused on the capability of G-LiHT hyperspectral products compared with multispectral data with similar spatial resolution, the contribution of LiDAR-CHM, and the potential of ensemble analysis in land-cover mapping. The results showed that there was no significant difference between the application of the G-LiHT hyperspectral product and simulated Quickbird data in the classification. A synthesis of G-LiHT hyperspectral and LiDAR-CHM products achieved the best result with an overall accuracy of 96.3% and a Kappa value of 0.95 when ensemble analysis was applied. Ensemble analysis of the three classifiers not only increased the classification accuracy but also generated an uncertainty map to show regions with a robust classification as well as areas where classification errors were most likely to occur. Ensemble analysis is a promising tool for land-cover classification.