Late Quaternary sea‐level change and evolution of Belfast Lough,Northern Ireland: new offshore evidence and implications for sea‐level reconstruction

The interplay of eustatic and isostatic factors causes complex relative sea‐level (RSL) histories, particularly in paraglacial settings. In this context the past record of RSL is important in understanding ice‐sheet history, earth rheology and resulting glacio‐isostatic adjustment. Field data to develop sea‐level reconstructions are often limited to shallow depths and uncertainty exists as to the veracity of modelled sea‐level curves. We use seismic stratigraphy, 39 vibrocores and 26 radiocarbon dates to investigate the deglacial history of Belfast Lough, Northern Ireland, and reconstruct past RSL. A typical sequence of till, glacimarine and Holocene sediments is preserved. Two sea‐level lowstands (both max. ?40 m) are recorded at c. 13.5 and 11.5k cal a bp . Each is followed by a rapid transgression and subsequent periods of RSL stability. The first transgression coincides temporally with a late stage of Meltwater Pulse 1a and the RSL stability occurred between c. 13.0 and c. 12.2k cal a bp (Younger Dryas). The second still/slowstand occurred between c. 10.3 and c. 11.5k cal a bp . Our data provide constraints on the direction and timing of RSL change during deglaciation. Application of the Depth of Closure concept adds an error term to sea‐level reconstructions based on seismic stratigraphic reconstructions.     

Evaluating new fault-controlled hydrothermal dolomitization models: Insights from the Cambrian Dolomite,Western Canadian Sedimentary Basin

Fault-controlled hydrothermal dolomitization in tectonically complex basins can occur at any depth and from different fluid compositions, including ‘deep-seated’, ‘crustal’ or ‘basinal’ brines. Nevertheless, many studies have failed to identify the actual source of these fluids, resulting in a gap in our knowledge on the likely source of magnesium of hydrothermal dolomitization. With development of new concepts in hydrothermal dolomitization, the study aims in particular to test the hypothesis that dolomitizing fluids were sourced from either seawater, ultramafic carbonation or a mixture between the two by utilizing the Cambrian Mount Whyte Formation as an example. Here, the large-scale dolostone bodies are fabric-destructive with a range of crystal fabrics, including euhedral replacement (RD1) and anhedral replacement (RD2). Since dolomite is cross-cut by low amplitude stylolites, dolomitization is interpreted to have occurred shortly after deposition, at a very shallow depth (<1 km). At this time, there would have been sufficient porosity in the mudstones for extensive dolomitization to occur, and the necessary high heat flows and faulting associated with Cambrian rifting to transfer hot brines into the near surface. While the δ¹⁸O_water and ⁸⁷Sr/⁸⁶Sr ratios values of RD1 are comparable with Cambrian seawater, RD2 shows higher values in both parameters. Therefore, although aspects of the fluid geochemistry are consistent with dolomitization from seawater, very high fluid temperature and salinity could be suggestive of mixing with another, hydrothermal fluid. The very hot temperature, positive Eu anomaly, enriched metal concentrations, and cogenetic relation with quartz could indicate that hot brines were at least partially sourced from ultramafic rocks, potentially as a result of interaction between the underlying Proterozoic serpentinites and CO₂-rich fluids. This study highlights that large-scale hydrothermal dolostone bodies can form at shallow burial depths via mixing during fluid pulses, providing a potential explanation for the mass balance problem often associated with their genesis.     

Towards a Digital Earth: using archetypes to enable knowledge interoperability within geo-observational sensor systems design

Earth System Science (ESS) observational data are often inadequately semantically enriched by geo-observational information systems to capture the true meaning of the associated data sets. Data models underpinning these information systems are often too rigid in their data representation to allow for the ever-changing and evolving nature of ESS domain concepts. This impoverished approach to observational data representation reduces the ability of multi-disciplinary practitioners to share information in a computable way. Object oriented techniques that are typically employed to model data in a complex domain (with evolving domain concepts) can unnecessarily exclude domain specialists from the design process, invariably leading to a mismatch between the needs of the domain specialists, and how the concepts are modelled. In many cases, an over simplification of the domain concept is captured by the computer scientist. This paper proposes that two-level modelling methodologies developed by health informaticians to tackle problems of domain specific use-case knowledge modelling can be re-used within ESS informatics. A translational approach to enable a two-level modelling process within geo-observational sensor systems design is described. We show how the Open Geospatial Consortium’s (OGC) Observations & Measurements (O&M) standard can act as a pragmatic solution for a stable reference-model (necessary for two-level modelling), and upon which more volatile domain specific concepts can be defined and managed using archetypes. A rudimentary use-case is presented, followed by a worked example showing the implementation methodology and considerations leading to an O&M based, two-level modelling design approach, to realise semantically rich and interoperable Earth System Science based geo-observational sensor systems.     

Dissolved nitrous oxide (N2O) dynamics in agricultural field drains and headwater streams in an intensive arable catchment

Indirect nitrous oxide (N₂O) emissions produced by nitrogen (N) leaching into surface water and groundwater bodies are poorly understood in comparison to direct N₂O emissions from soils. In this study, dissolved N₂O concentrations were measured weekly in both lowland headwater streams and subsurface agricultural field drain discharges over a 2‐year period (2013–2015) in an intensive arable catchment, Norfolk, UK. All field drain and stream water samples were found to have dissolved N₂O concentrations higher than the water–air equilibrium concentration, illustrating that all sites were acting as a net source of N₂O emissions to the atmosphere. Soil texture was found to significantly influence field drain N₂O dynamics, with mean concentrations from drains in clay loam soils (5.3 μg N L^?1) being greater than drains in sandy loam soils (4.0 μg N L^?1). Soil texture also impacted upon the relationships between field drain N₂O concentrations and other water quality parameters (pH, flow rate, and nitrate (NO₃) and nitrite (NO₂) concentrations), highlighting possible differences in N₂O production mechanisms in different soil types. Catchment antecedent moisture conditions influenced the storm event mobilisation of N₂O in both field drains and streams, with the greatest concentration increases recorded during precipitation events preceded by prolonged wet conditions. N₂O concentrations also varied seasonally, with the lowest mean concentrations typically occurring during the summer months (JJA). Nitrogen fertiliser application rates and different soil inversion regimes were found to have no effect on dissolved N₂O concentrations, whereas higher N₂O concentrations recorded in field drains under a winter cover crop compared to fallow fields revealed cover crops are an ineffective greenhouse gas emission mitigation strategy. Overall, this study highlights the complex interactions governing the dynamics of dissolved N₂O concentrations in field drains and headwater streams in a lowland intensive agricultural catchment.     

Characterization of dissolved organic matter across the Subtropical Convergence off the South Island,New Zealand

Dissolved organic matter (DOM) was investigated along a gradient across the Subtropical Convergence (STC) off the South Island, New Zealand. Ultrahigh resolution electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS), excitation emission matrix fluorescence (EEM) spectroscopy, and molecular lignin analysis techniques were used to study this DOM. The analysis revealed a group of compounds found only in the coastal DOM samples, which were also characterized by an elevated terrestrial DOM fluorescence pattern and elevated lignin content if compared to the offshore samples. This group exhibited a high degree of carbon unsaturation, as evident from high double bond equivalence minus oxygen values (DBE-O > 9) and maximum fluorescence intensity. Sulfur-containing molecular formulae for summer DOM samples were much more abundant across the entire transect of the STC compared to winter and exhibited distinctly different hydrogen:carbon and oxygen:carbon elemental ratios, suggesting a possible correlation between biological activity and sulfur compounds. The molecular formulae common to all STC samples were compared with those calculated for DOM extracted from freshwater collected from a stream discharging into Doubtful Sound (West Coast, New Zealand). ESI-FT-ICR-MS measurements undertaken in negative electrospray ionization (ESI?) mode indicated that 30% of the molecular formulae were present in both types of DOM, while in positive ESI mode (ESI+) over 90% of the formulae were present in all samples. Hence, a significant portion of the molecular formulae assigned to the solid-phase extractable DOM pool (SPE-DOM) appear to be identical in oceanic and freshwater samples.     

Analysis of the interannual variability of annual daily extreme water levels in the St Lawrence River and Lake Ontario from 1918 to 2010

We compared the interannual variability of annual daily maximum and minimum extreme water levels in Lake Ontario and the St Lawrence River (Sorel station) from 1918 to 2010, using several statistical tests. The interannual variability of annual daily maximum extreme water levels in Lake Ontario is characterized by a positive long‐term trend showing two shifts in mean (1929–1930 and 1942–1943) and a single shift in variance (in 1958–1959). In contrast, for the St Lawrence River, this interannual variability is characterized by a negative long‐term trend with a single shift in mean, which occurred in 1955–1956. As for annual daily minimum extreme water levels, their interannual variability shows no significant long‐term change in trend. However, for Lake Ontario, the interannual variability of these water levels shows two shifts in mean, which are synchronous with those for maximum water levels, and a single shift in variance, which occurred in 1965–1966. These changes in trend and stationarity (mean and variance) are thought to be due to factors both climatic (the Great Drought of the 1930s) and human (digging of the Seaway and construction of several dams and locks during the 1950s). Despite this change in means and variance, the four series are clearly described by the generalized extreme value distribution. Finally, annual daily maximum and minimum extreme water levels in the St Lawrence and Lake Ontario are negatively correlated with Atlantic multidecadal oscillation over the period from 1918 to 2010. Copyright © 2013 John Wiley & Sons, Ltd.     

Combining two filter paper‐based analytical methods to monitor temporal variations in the geochemical properties of fluvial suspended particulate matter

Many of the commonly used analytical techniques for assessing the properties of fluvial suspended particulate matter (SPM) are neither cost effective nor time efficient, making them prohibitive to long‐term high‐resolution monitoring. We present an in‐depth methodology utilizing two types of spectroscopy which, when combined with automatic water samplers, can generate accurate, high‐temporal resolution SPM geochemistry data, inexpensively and semi‐destructively, directly from sediment covered filter papers. A combined X‐ray fluorescence spectroscopy and diffuse reflectance infrared Fourier transform spectroscopy approach is developed to estimate concentrations for a range of elements (Al, Ca, Ce, Fe, K, Mg, Mn, Na, P, Si, Ti) and compounds (organic carbon, Al_dithionate, Al_oxalate, Fe_dithionate, and Fe_oxalate) within SPM trapped on quartz fibre filters at masses as low as 3 mg. Calibration models with small prediction errors are derived, along with mass correction factor models to account for variations in retained SPM mass. Spectral pre‐processing methods are shown to enhance the reproducibility of results for some compounds, and the importance of filter paper selection and homogeneous sample preparation in minimizing spectral interference is emphasized. The geochemical signal from sediment covered filter papers is demonstrated to be time stable enabling samples to be stored for several weeks prior to analysis. Example results obtained during a heavy precipitation event in October 2012 demonstrate the methodology presented here has considerable potential to be utilized for high‐resolution monitoring of SPM geochemistry under a range of in‐stream hydrological conditions. Copyright © 2013 John Wiley & Sons, Ltd.     

Assessing vulnerability due to sea-level rise in Maui, Hawai‘i using LiDAR remote sensing and GIS

Sea-level rise (SLR) threatens islands and coastal communities due to vulnerable infrastructure and populations concentrated in low-lying areas. LiDAR (Light Detection and Ranging) data were used to produce high-resolution DEMs (Digital Elevation Model) for Kahului and Lahaina, Maui, to assess the potential impacts of future SLR. Two existing LiDAR datasets from USACE (U.S. Army Corps of Engineers) and NOAA (National Oceanic and Atmospheric Administration) were compared and calibrated using the Kahului Harbor tide station. Using tidal benchmarks is a valuable approach for referencing LiDAR in areas lacking an established vertical datum, such as in Hawai‘i and other Pacific Islands. Exploratory analysis of the USACE LiDAR ground returns (point data classified as ground after the removal of vegetation and buildings) indicated that another round of filtering could reduce commission errors. Two SLR scenarios of 0.75 (best-case) to 1.9 m (worst-case) (Vermeer and Rahmstorf Proc Natl Acad Sci 106:21527–21532, 2009) were considered, and the DEMs were used to identify areas vulnerable to flooding. Our results indicate that if no adaptive strategies are taken, a loss ranging from $18.7 million under the best-case SLR scenario to $296 million under the worst-case SLR scenario for Hydrologically Connected (HC; marine inundation) and Hydrologically Disconnected (HD; drainage problems due to a higher water table) areas combined is possible for Kahului; a loss ranging from $57.5 million under the best-case SLR scenario to $394 million under the worst-case SLR scenario for HC and HD areas combined is possible for Lahaina towards the end of the century. This loss would be attributable to inundation between 0.55 km² to 2.13 km² of area for Kahului, and 0.04 km² to 0.37 km² of area for Lahaina.     

Incorporating uncertainty of future sea-level rise estimates into vulnerability assessment: A case study in Kahului, Maui

Accurate sea-level rise (SLR) vulnerability assessments are essential in developing effective management strategies for coastal systems at risk. In this study, we evaluate the effect of combining vertical uncertainties in Light Detection and Ranging (LiDAR) elevation data, datum transformation and future SLR estimates on estimating potential land area and land cover loss, and whether including uncertainty in future SLR estimates has implications for adaptation decisions in Kahului, Maui. Monte Carlo simulation is used to propagate probability distributions through our inundation model, and the output probability surfaces are generalized as areas of high and low probability of inundation. Our results show that considering uncertainty in just LiDAR and transformation overestimates vulnerable land area by about 3 % for the high probability threshold, resulting in conservative adaptation decisions, and underestimates vulnerable land area by about 14 % for the low probability threshold, resulting in less reliable adaptation decisions for Kahului. Not considering uncertainty in future SLR estimates in addition to LiDAR and transformation has variable effect on SLR adaptation decisions depending on the land cover category and how the high and low probability thresholds are defined. Monte Carlo simulation is a valuable approach to SLR vulnerability assessments because errors are not required to follow a Gaussian distribution.