The Impact of Sediment and Carbon Fluxes on the Biogeochemistry of Methane and Sulfur in Littoral Baltic Sea Sediments (Himmerfjärden, Sweden)

Three sediment stations in Himmerfjärden estuary (Baltic Sea, Sweden) were sampled in May 2009 and June 2010 to test how low salinity (5–7 ‰), high primary productivity partially induced by nutrient input from an upstream waste water treatment plant, and high overall sedimentation rates impact the sedimentary cycling of methane and sulfur. Rates of sediment accumulation determined using ²¹⁰Pb_excess and ¹³⁷Cs were very high (0.65–0.95 cm?year^?1), as were the corresponding rates of organic matter accumulation (8.9–9.5 mol C?m^?2?year^?1) at all three sites. Dissolved sulfate penetrated <20 cm below the sediment surface. Although measured rates of bicarbonate methanogenesis integrated over 1 m depth were low (0.96–1.09 mol?m^?2?year^?1), methane concentrations increased to >2 mmol?L^?1 below the sulfate–methane transition. A steep gradient of methane through the entire sulfate zone led to upward (diffusive and bio-irrigative) fluxes of 0.32 to 0.78 mol?m^?2?year^?1 methane to the sediment–water interface. Areal rates of sulfate reduction (1.46–1.92 mol?m^?2?year^?1) integrated over the upper 0–14 cm of sediment appeared to be limited by the restricted diffusive supply of sulfate, low bio-irrigation (α?=?2.8–3.1 year^?1), and limited residence time of the sedimentary organic carbon in the sulfate zone. A large fraction of reduced sulfur as pyrite and organic-bound sulfur was buried and thus escaped reoxidation in the surface sediment. The presence of ferrous iron in the pore water (with concentrations up to 110 μM) suggests that iron reduction plays an important role in surface sediments, as well as in sediment layers deep below the sulfate–methane transition. We conclude that high rates of sediment accumulation and shallow sulfate penetration are the master variables for biogeochemistry of methane and sulfur cycling; in particular, they may significantly allow for release of methane into the water column in the Himmerfjärden estuary.     

The year-long unprecedented European heat and drought of 1540 – a worst case

The heat waves of 2003 in Western Europe and 2010 in Russia, commonly labelled as rare climatic anomalies outside of previous experience, are often taken as harbingers of more frequent extremes in the global warming-influenced future. However, a recent reconstruction of spring–summer temperatures for WE resulted in the likelihood of significantly higher temperatures in 1540. In order to check the plausibility of this result we investigated the severity of the 1540 drought by putting forward the argument of the known soil desiccation-temperature feedback. Based on more than 300 first-hand documentary weather report sources originating from an area of 2 to 3 million km², we show that Europe was affected by an unprecedented 11-month-long Megadrought. The estimated number of precipitation days and precipitation amount for Central and Western Europe in 1540 is significantly lower than the 100-year minima of the instrumental measurement period for spring, summer and autumn. This result is supported by independent documentary evidence about extremely low river flows and Europe-wide wild-, forest- and settlement fires. We found that an event of this severity cannot be simulated by state-of-the-art climate models.     

Sensitivity Analysis of a Combined Groundwater Flow and Solute Transport Model Using Local-Grid Refinement: A Case Study

Combining groundwater flow models with solute transport models represents a common challenge in groundwater resources assessments and contaminant transport modeling. Groundwater flow models are usually constructed at somewhat larger scales (involving a coarser discretization) to include natural boundary conditions. They are commonly calibrated using observed groundwater levels and flows (if available). The groundwater solute transport models may be constructed at a smaller scale with finer discretization than the flow models in order to accurately delineate the solute source and the modeled target, to capture any heterogeneity that may affect contaminant migration, and to minimize numerical dispersion while still maintaining a reasonable computing time. The solution that is explored here is based on defining a finer grid subdomain within a larger coarser domain. The local-grid refinement (LGR) implemented in the Modular 3D finite-difference ground-water flow model (MODFLOW) code has such a provision to simulate groundwater flow in two nested grids: a higher-resolution sub-grid within a coarse grid. Under the premise that the interface between both models was well defined, a comprehensive sensitivity and uncertainty analysis was performed whereby the effect of a parameter perturbation in a coarser-grid model on transport predictions using a higher-resolution grid was quantified. This approach was tested for a groundwater flow and solute transport analysis in support of a safety evaluation of the future Belgian near-surface radioactive waste disposal facility. Our reference coarse-grid groundwater flow model was coupled with a smaller fine sub-grid model in two different ways. While the reference flow model was calibrated using observed groundwater levels at a scale commensurate with that of the coarse-grid model, the fine sub-grid model was used to run a solute transport simulation quantifying concentrations in a hypothetical well nearby the disposal facility. When LGR coupling was compared to a one-way coupling, LGR was found to provide a smoother flow solution resulting in a more CPU-efficient transport solution. Parameter sensitivities performed with the groundwater flow model resulted in sensitivities at the head observation locations. These sensitivities identified the recharge as the most sensitive parameter, with the hydraulic conductivity of the upper aquifer as the second most sensitive parameter in regard to calculated groundwater heads. Based on one-percent sensitivity maps, the spatial distribution of the observations with the highest sensitivities is slightly different for the upper aquifer hydraulic conductivity than for recharge. Sensitivity analyses were further performed to assess the prediction scaled sensitivities for hypothetical contaminant concentrations using the combined groundwater flow and solute transport models. Including all pertinent parameters into the sensitivity analysis identified the hydraulic conductivity of the upper aquifer as the most sensitive parameter with regard to the prediction of contaminant concentrations.     

Estimation of Hydraulic Conductivity and Its Uncertainty from Grain-Size Data Using GLUE and Artificial Neural Networks

Various approaches exist to relate saturated hydraulic conductivity (K _s) to grain-size data. Most methods use a single grain-size parameter and hence omit the information encompassed by the entire grain-size distribution. This study compares two data-driven modelling methods??multiple linear regression and artificial neural networks??that use the entire grain-size distribution data as input for K _s prediction. Besides the predictive capacity of the methods, the uncertainty associated with the model predictions is also evaluated, since such information is important for stochastic groundwater flow and contaminant transport modelling. Artificial neural networks (ANNs) are combined with a generalised likelihood uncertainty estimation (GLUE) approach to predict K _s from grain-size data. The resulting GLUE-ANN hydraulic conductivity predictions and associated uncertainty estimates are compared with those obtained from the multiple linear regression models by a leave-one-out cross-validation. The GLUE-ANN ensemble prediction proved to be slightly better than multiple linear regression. The prediction uncertainty, however, was reduced by half an order of magnitude on average, and decreased at most by an order of magnitude. This demonstrates that the proposed method outperforms classical data-driven modelling techniques. Moreover, a comparison with methods from the literature demonstrates the importance of site-specific calibration. The data set used for this purpose originates mainly from unconsolidated sandy sediments of the Neogene aquifer, northern Belgium. The proposed predictive models are developed for 173 grain-size K _s-pairs. Finally, an application with the optimised models is presented for a borehole lacking K _s data.     

Gas migration through Opouawe Bank at the Hikurangi margin offshore New Zealand

This study presents 2D seismic reflection data, seismic velocity analysis, as well as geochemical and isotopic porewater compositions from Opouawe Bank on New Zealand’s Hikurangi subduction margin, providing evidence for essentially pure methane gas seepage. The combination of geochemical information and seismic reflection images is an effective way to investigate the nature of gas migration beneath the seafloor, and to distinguish between water advection and gas ascent. The maximum source depth of the methane that migrates to the seep sites on Opouawe Bank is 1,500–2,100 m below seafloor, generated by low-temperature degradation of organic matter via microbial CO₂ reduction. Seismic velocity analysis enabled identifying a zone of gas accumulation underneath the base of gas hydrate stability (BGHS) below the bank. Besides structurally controlled gas migration along conduits, gas migration also takes place along dipping strata across the BGHS. Gas migration on Opouawe Bank is influenced by anticlinal focusing and by several focusing levels within the gas hydrate stability zone.     

Variscan orogeny in Corsica: new structural and geochronological insights,and its place in the Variscan geodynamic framework

In Western Corsica, remnants of pre-batholitic lithological and metamorphic assemblages are preserved as km-scale septa enclosed within Lower Carboniferous to Early Permian plutons. Two groups of septa were recognized: (1) the Argentella and Agriates-Tenda fragments correspond to Neoproterozoic rocks deformed and metamorphosed during the Cadomian–Panafrican orogeny, and (2) the Zicavo, Porto-Vecchio, Solenzara–Fautea, Belgodère, Topiti, and Vignola fragments consist of Variscan metamorphic rocks. The lithological content and the main ductile deformation events for each septum are presented. In the Zicavo, Porto-Vecchio, and Topiti septa, a top-to-the-SW ductile shearing (D1 event) coeval with an amphibolite facies metamorphism is responsible for crustal thickening at ca 360 Ma. This main event was preceded by eclogite and granulite facies metamorphic events preserved as restites within migmatites dated at ca 345–330 Ma. A top-to-the-SE ductile shearing (D2 event) coeval with the crustal melting accommodated the exhumation of the D1 event. In contrast, the Belgodère segment is peculiar as it exhibits a top-to-the-E vergence, although retrogressed high-pressure rocks are also recognized. The pre-Permian fragments are arranged in four NW–SE-striking stripes that define a SW–NE zoning with (1) a Western domain in Topiti, Vignola, Zicavo, Porto-Vecchio, and Solenzara–Fautea; (2) a Neoproterozoic basement with its unconformable Early Paleozoic sedimentary cover in Argentella; (3) an Eastern metamorphic domain in Belgodère; (4) another Neoproterozoic basement with its Upper Paleozoic sedimentary cover in Agriates-Tenda. The Argentella basement is separated from the Western and Eastern domains by two sutures: S1 and S2. The Variscan Corsica represents the Eastern part of the Sardinia–Corsica–Maures segment. The comparison of this segment with other Variscan domains allows us to propose some possible correlations. We argue that the Western domain, Argentella, Belgodère, and Agriates-Tenda domains can be compared with the Southern Variscan belt exposed in French Massif Central–Southern Massif Armoricain, Armorica microblock, Léon block, respectively.     

Suitability of Existing Numerical Model Codes and Thermodynamic Databases for the Prognosis of Calcite Dissolution Processes in Near-Surface Sediments Due to a CO2 Leakage Investigated by Column Experiments

Among the risks of CO₂ storage is the potential of CO₂ leakage into overlaying formations and near-surface potable aquifers. Through a leakage, the CO₂ can intrude into protected groundwater resources, which can lead to groundwater acidification followed by potential mobilisation of heavy metals and other trace metals through mineral dissolution or ion exchange processes. The prediction of pH buffer reactions in the formations overlaying a CO₂ storage site is essential for assessing the impact of CO₂ leakages in terms of trace metal mobilisation. For buffering the pH-value, calcite dissolution is one of the most important mechanisms. Although calcite dissolution has been studied for decades, experiments conducted under elevated CO₂ partial pressures are rare. Here, the first study for column experiments is presented applying CO₂ partial pressures from 6 to 43 bars and realising a near-natural flow regime. Geochemical calculations of calcite dissolution kinetics were conducted using PHREEQC together with different thermodynamic databases. Applying calcite surface areas, which were previously acquired by N₂-BET or calculated based on grain diameters, respectively, to the rate laws according to Plummer et al. (Am J Sci 278:179–216, doi:10.2475/ajs.278.2.179, 1978) or Palandri and Kharaka (US Geol Surv Open file Rep 2004–1068:71, 2004) in the numerical simulations led to an overestimation of the calcite dissolution rate by up to three orders of magnitude compared to the results of the column experiments. Only reduction of the calcite surface area in the simulations as a fitting procedure allowed reproducing the experimental results. A reason may be that the diffusion boundary layer (DBL), which depends on the groundwater flow velocity and develops at the calcite grain surface separating it from the bulk of the solution, has to be regarded: The DBL leads to a decrease in the calcite dissolution rate under natural laminar flow conditions compared to turbulent mixing in traditional batch experiments. However, varying the rate constants by three orders of magnitudes in a field scale PHREEQC model simulating a CO₂ leakage produced minor variations in the pH buffering through calcite dissolution. This justifies the use of equilibrium models when calculating the calcite dissolution in CO₂ leakage scenarios for porous aquifers and slow or moderate groundwater flow velocities. However, the selection of the thermodynamic database has an impact on the dissolved calcium concentration, leading to an uncertainty in the simulation results. The resulting uncertainty, which applies also to the calculated propagation of an aquifer zone depleted in calcite through dissolution, seems negligible for shallow aquifers of approximately 60 m depth, but amounts to 35 % of the calcium concentration for aquifers at a depth of approximately 400 m.     

A new geospatial overlay method for the analysis and visualization of spatial change patterns using object-oriented data modeling concepts

Traditional geographic information system (GIS)-overlay routines usually build on relatively simple data models. Topology is – if at all – calculated on the fly for very specific tasks only. If, for example, a change comparison is conducted between two or more polygon layers, the result leads mostly to a complete and also very complex from–to class intersection. A lot of additional processing steps need to be performed to arrive at aggregated and meaningful results. To overcome this problem a new, automated geospatial overlay method in a topologically enabled (multi-scale) framework is presented. The implementation works with polygon and raster layers and uses a multi-scale vector/raster data model developed in the object-based image analysis software eCognition (Trimble Geospatial Imaging, Munich, Germany). Advantages are the use of the software inherent topological relationships in an object-by-object comparison, addressing some of the basic concepts of object-oriented data modeling such as classification, generalization, and aggregation. Results can easily be aggregated to a change-detection layer; change dependencies and the definition of different change classes are interactively possible through the use of a class hierarchy and its inheritance (parent–child class relationships). Implementation is exemplarily shown for a change comparison of CORINE Land Cover data sets. The result is a flexible and transferable solution which is – if parameterized once – fully automated.     

Satellite-based peatland mapping: Potential of the MODIS sensor

Peatlands play a major role in the global carbon cycle but are largely overlooked in current large-scale vegetation mapping efforts. In this study, we investigated the potential of the Moderate Resolution Imaging Spectroradiometer (MODIS) to capture the extent and distribution of peatlands in the St. Petersburg region of Russia by analyzing the relationships between peatland cover fractions derived from reference maps and  1-km resolution MODIS Nadir BRDF-Adjusted Reflectance (NBAR) data from year 2002.First, we characterized and mapped 50 peatlands from forest inventory and peat deposit inventory data. The peatlands represent three major nutritional types (oligotrophic, mesotrophic, eutrophic) and different sizes (0.6–7800 ha). In addition, parts of 6 peatlands were mined for peat and these were mapped separately. The reference maps provided information on peatland cover for 1105 MODIS pixels. We performed regression analysis on 50% of the pixels and reserved the remainder for model validation. Canonical correlation analysis on the MODIS reflectance bands and the peatland cover fractions produced a multi-spectral peatland cover index (PCI), which served as the predictor in a reduced major axis (RMA) regression model. The results suggest a high potential for mapping peatlands with MODIS. The RMA regression models explained much of the variance in the PCI (r² = 0.74 for mined and r² = 0.81 for unmined peatlands). Model validation showed high correlation between observed versus predicted peatland cover (mined: r = 0.87; unmined: r = 0.92). We used the models to derive peatland cover estimates for the St. Petersburg region and compared the results to current MODIS land cover maps.