Empirical modelling of site-specific errors in continuous GPS data

Continuous global positioning system (GPS) stations propagate biases and spurious signals into the derived parameter time series when the measurements are subject to site-specific effects, such as multipath. This is a particular problem in the investigation of geophysical and atmospheric phenomena where signals may be small in magnitude. A methodology to remove these erroneous signals from long-term time series will significantly increase the usefulness of the derived time series. This work provides the theoretical basis for use of an empirical site model (ESM) derived from post-fit phase residuals to mitigate unmodelled site-specific errors. Additionally, we also investigate the effectiveness of applying an ESM to a regional GPS network and a short baseline solution. Under most observing scenarios, we show that the ESM approach is predicted to improve the precision and accuracy of the site coordinates. However, it is important to note that we found some scenarios where the ESM can introduce a bias. For instance, when the antenna is mounted close to the ground. In this scenario, for a short baseline, we observed the introduction of a 4-mm bias in height. Use of an ESM for the same short baseline with an uncalibrated radome substantially improves the results by removing a large bias of over 10 mm in height. Similarly, application of an ESM derived from historic data yields similar improvements. This demonstrates that the ESM can be a powerful tool when applied to appropriate site-specific configurations and could potentially be implemented in routine GPS analysis for a broad range of applications.     

SPIRE point source photometry: within the Herschel interactive processing environment (HIPE)

The different algorithms appropriate for point source photometry on data from the SPIRE instrument on-board the Herschel Space Observatory, within the Herschel Interactive Processing Environment (HIPE) are compared. Point source photometry of a large ensemble of standard calibration stars and dark sky observations is carried out using the 4 major methods within HIPE: SUSSEXtractor, DAOphot, the SPIRE Timeline Fitter and simple Aperture Photometry. Colour corrections and effective beam areas as a function of the assumed source spectral index are also included to produce a large number of photometric measurements per individual target, in each of the 3 SPIRE bands (250, 350, 500μm), to examine both the accuracy and repeatability of each of the 4 algorithms. It is concluded that for flux densities down to the level of 30mJy that the SPIRE Timeline Fitter is the method of choice. However, at least in the 250 and 350μm bands, all 4 methods provide photometric repeatability better than a few percent down to at approximately 100mJy. The DAOphot method appears in many cases to have a systematic offset of ～8 % in all SPIRE bands which may be indicative of a sub-optimal aperture correction. In general, aperture photometry is the least reliable method, i.e. largest scatter between observations, especially in the longest wavelength band. At the faintest fluxes, <30mJy, SUSSEXtractor or DAOphot provide a better alternative to the Timeline Fitter.     

The contribution of faint active galactic nuclei to the hard X-ray background

Hard X-ray selection is the most efficient way to discriminate between accretion-powered sources, such as active galactic nuclei (AGN), and sources dominated by starlight. Hard X-rays are also less affected than other bands by obscuration. We have therefore carried out the BeppoSAX High Energy Large Area Survey (HELLAS) in the largely unexplored 5–10 keV band, finding 180 sources in ∼50 deg² of sky with flux≳5×10⁻¹⁴ erg cm⁻² s⁻¹. After correction for the non-uniform sky coverage this corresponds to resolving about 30 per cent of the hard cosmic X-ray background (XRB). Here we report on a first optical spectroscopic identification campaign, finding 12 AGN out of 14 X-ray error boxes studied. Seven AGN show evidence for obscuration in X-ray and optical bands, a fraction higher than in previous ROSAT or ASCA – ROSAT surveys (at 95–99 and 90 per cent confidence levels respectively), thus supporting the scenario in which a significant fraction of the XRB is created by obscured AGN.     

Aeolian sediment fingerprinting using a Bayesian mixing model

Identifying sand provenance in depositional aeolian environments (e.g. dunefields) can elucidate sediment pathways and fluxes, and inform potential land management strategies where windblown sand and dust is a hazard to health and infrastructure. However, the complexity of these pathways typically makes this a challenging proposition, and uncertainties on the composition of mixed‐source sediments are often not reported. This study demonstrates that a quantitative fingerprinting method within the Bayesian Markov Chain Monte Carlo (MCMC) framework offers great potential for exploring the provenance and uncertainties associated with aeolian sands. Eight samples were taken from dunes of the small (~58 km²) Ashkzar erg, central Iran, and 49 from three distinct potential sediment sources in the surrounding area. These were analyzed for 61 tracers including 53 geochemical elements (trace, major and rare earth elements (REE)) and eight REE ratios. Kruskal–Wallis H‐tests and stepwise discriminant function analysis (DFA) allowed the identification of an optimum composite fingerprint based on six tracers (Rb, Sr, ⁸⁷Sr, (La/Yb)_n, Ga and δCe), and a Bayesian mixing model was applied to derive the source apportionment estimates within an uncertainty framework. There is substantial variation in the uncertainties in the fingerprinting results, with some samples yielding clear discrimination of components, and some with less clear fingerprints. Quaternary terraces and fans contribute the largest component to the dunes, but they are also the most extensive surrounding unit; clay flats and marls, however, contribute out of proportion to their small outcrop extent. The successful application of these methods to aeolian sediment deposits demonstrates their potential for providing quantitative estimates of aeolian sediment provenances in other mixed‐source arid settings, and may prove especially beneficial where sediment is derived from multiple sources, or where other methods of provenance (e.g. detrital zircon U–Pb dating) are not possible due to mineralogical constraints. Copyright © 2017 John Wiley & Sons, Ltd.     

Glimpses of oceanic lithosphere of the Challenger Deep forearc segment in the southernmost Marianas: The 143°E transect, 5800–4200 m

We studied nine samples of igneous rocks from the inner wall of the Mariana Trench above the Challenger Deep from 4150 to 6100 m depth recovered by manned submersible and ROV. Samples from two regions that bracket the Moho were studied: (i) 7 samples from a N‐S transect a few km to the west of the Shinkai Seep Field; and (ii) 2 samples from the Shinkai Seep Field. Transect samples include olivine‐2 pyroxene hornblendites, amphibole basalts, basaltic andesite, and hornblende andesite. We analyzed three transect samples for ⁴⁰Ar/³⁹Ar ages; two yielded good plateau ages of 46.5 ±0.5 Ma (hornblendite) and 46.60 ±0.15 Ma (hornblende andesite). These results combined with previously published results, indicate that this crust formed during an intense 46–47 Ma magmatic episode that occurred 5–6 my after subduction initiation. Hornblendites and hornblende basalts formed from primitive magmas, as shown by high MgO (11–21 wt%), Ni (222–885 ppm) and Cr (412–1145 ppm) contents. Electron microprobe analyses indicate that hornblende is Na‐rich (up to 3.0 wt% Na₂O) and that many samples have an atypically large range in plagioclase composition (i.e. individual samples have An < 10 to An 90 plagioclase). Two subgroups can be identified: a mostly deeper depleted suite and a mostly shallower enriched suite. These results indicate that (i) the crust–mantle boundary in this region is transitional, occurring over a ~ 1.5 km interval, with interlayered peridotite and hornblendites between 5800 and 4300 m; and (b) extension to form the Challenger Deep forearc segment occurred by combined stretching of old crust and injection of young basaltic magmas. In contrast to the mostly fresh nature of transect samples, the two samples from the Shinaki Seep Field are intensely altered peridotite and basalt.     

Upscaling site‐scale ecohydraulic models to inform salmonid population‐level life cycle modeling and restoration actions – Lessons from the Columbia River Basin

With high‐resolution topography and imagery in fluvial environments, the potential to quantify physical fish habitat at the reach scale has never been better. Increased availability of hydraulic, temperature and food availability data and models have given rise to a host of species and life stage specific ecohydraulic fish habitat models ranging from simple, empirical habitat suitability curve driven models, to fuzzy inference systems to fully mechanistic bioenergetic models. However, few examples exist where such information has been upscaled appropriately to evaluate entire fish populations. We present a framework for applying such ecohydraulic models from over 905 sites in 12 sub‐watersheds of the Columbia River Basin (USA), to assess status and trends in anadromous salmon populations. We automated the simulation of computational engines to drive the hydraulics, and subsequent ecohydraulic models using cloud computing for over 2075 visits from 2011 to 2015 at 905 sites. We also characterize each site's geomorphic reach type, habitat condition, geomorphic unit assemblage, primary production potential and thermal regime. We then independently produce drainage network‐scale models to estimate these same parameters from coarser, remotely sensed data available across entire populations within the Columbia River Basin. These variables give us a basis for imputation of reach‐scale capacity estimates across drainage networks. Combining capacity estimates with survival estimates from mark–recapture monitoring allows a more robust quantification of capacity for freshwater life stages (i.e. adult spawning, juvenile rearing) of the anadromous life cycle. We use these data to drive life cycle models of populations, which not only include the freshwater life stages but also the marine and migration life stages through the hydropower system. More fundamentally, we can begin to look at more realistic, spatially explicit, tributary habitat restoration scenarios to examine whether the enormous financial investment on such restoration actions can help recover these populations or prevent their extinction. Copyright © 2017 John Wiley & Sons, Ltd.     

How many measurements are required to construct an accurate sand budget in a large river? Insights from analyses of signal and noise

Morphological change in river channels is frequently evaluated in the context of mass balance sediment budgets. In a closed sediment budget, measurements of sediment influx and efflux are coupled with measured changes in channel topography to provide both spatial and temporal resolution, and independent estimates of the mass balance. For sediment budgets constructed over long river segments (~10² channel widths or greater) and long periods (~2 years or longer), spatial and temporal accumulation of measurement uncertainty, compounded by inadequate sampling frequency or spatial coverage, may produce indeterminate results. The degree of indeterminacy may be evaluated in the context of a signal-to-noise ratio (SNR), which is a function of the magnitude of the mass balance and the magnitudes of potential systematic uncertainties associated with measurements and incomplete sampling. We report on a closed sand budget consisting of measurements of flux and two morphological surveys for a 50-km segment of a large river over a 3-year period. Accurate reporting of the magnitude and sign of the change in sand storage was only possible by using state-of-the-art techniques with high temporal frequency and large spatial extent. Together, a sand flux and morphological mass balance revealed that sand evacuation was temporally concentrated (~100% of mass change occurred during 19% of the study period) and highly localized (70% of mass change occurred in 12% of the study segment). A SNR analysis revealed that uncertainty resulting from undersampling may approach or exceed that caused by measurement uncertainty and that daily sampling of suspended-sand concentration or repeat mapping of at least 50% of the river segment was required to determine the sand budget with SNR > 1. The approach used here to analyze sand budget uncertainty is especially applicable to other river systems with large temporal variability in sediment transport and large spatial variability in erosion and deposition. © 2018 John Wiley & Sons, Ltd.     

Integrated Storage and Querying of Spatially Varying Data Quality Information in a Relational Spatial Database

This article investigates a new, integrated technique for storing and retrieving spatially varying data quality information in a relational spatial database. Rather than storing global data quality statements, the system enables data quality information to be referenced to a spatial framework, individual spatial objects, or even parts of spatial objects. The integrated model, called as RDBMS for Spatial Variation in Quality (RSVQ), allows flexible storage of spatially varying data quality information, and seamless querying irrespective of the underlying storage model. RSVQ is founded on a formal model of relational databases, defining a new derived, polymorphic query operator      to join quality data with spatial data. The      operator is implemented in an extension to SQL as a new WITHQUALITY keyword. A performance evaluation of RSVQ was conducted, using an Oracle Spatial database and a case study of cadastral data for parts of Victoria, Australia. The results of this evaluation demonstrated that the system is practical and efficient for a wide range of queries, as well as indicating the performance trade-offs associated with the different data quality storage models. Using the integrated RSVQ approach provides the potential for a single, consistent, database engine for a wide range of existing and proposed spatial data quality management systems.