Evaluating relative sensitivity of SWAT‐simulated nitrogen discharge to projected climate and land cover changes for two watersheds in North Carolina,USA

We investigated how projected changes in land cover and climate affected simulated nitrate (NO₃^?) and organic nitrogen discharge for two watersheds within the Neuse River Basin, North Carolina, USA, for years 2010–2070. We applied the Soil and Water Assessment Tool watershed model to predict nitrogen discharge using (1) atmospheric carbon dioxide (CO₂) concentrations predicted by the Intergovernmental Panel on Climate Change, (2) land cover change predicted by the Integrated Climate and Land Use Change project and (3) precipitation and temperature simulated by two statistically downscaled and bias‐corrected Global Circulation Models. We determined the sensitivity of simulated nitrogen discharge to separate changes in each treatment [(1) CO₂, (2) land cover and (3) precipitation and temperature (PT)] by comparing each treatment to a reference condition. Results showed that nitrogen discharges were most sensitive to changes in PT over the 60‐year simulation. Nitrogen discharges had similar sensitivities to the CO₂ and land cover treatments, which were only one‐tenth the influence of the PT treatment. Under the CO₂ treatment, nitrogen discharges increased with increasing ambient CO₂. NO₃^? discharge decreased with increased urbanization; however, organic nitrogen had a varied response. Under the PT treatment, there was high spatial variability in nitrogen discharges. In a single year, certain sub‐basins showed an 80% increase in nitrogen discharge relative to reference, while others showed a 400% decrease. With nitrogen discharge showing high sensitivity to PT change, we suggest that more emphasis should be placed on investigating impacts of PT on nutrient transport in the Neuse River Basin. Published 2015. This article is a U.S. Government work and is in the public domain in the USA     

Discriminating between tectonic and eustatic controls on the stratigraphic record in the Paris basin

The quantification of tectonic and eustatic factors in the control of the sedimentary record is one of the main questions in sedimentary basin dynamics. We propose two methods allowing: (i) 3D measurement of accommodation at basin scale and (ii) to decipher between local (10–100 km wavelength) and basin-scale accommodation. The local signal is necessarily of tectonic origin, the basin-scale signal is of both eustatic and large tectonic origin. The measurement of accommodation requires (a) high-resolution time-lines calibrated in ages (sequence stratigraphy on well-logs and biostratigraphy on cores), (b) decompacted lithologies (well-logs), and (c) palaeodepth/palaeoaltitude (sedimentology and well-logs). Application of these methods to the intracratonic Paris basin during the Lias (early Jurassic) suggests a tectonic origin for the 1–5 Myr stratigraphic cycles, with basin-scale flexure during transgressive half-cycles, and 10–100 km uplift of basement units, during regressive half-cycles.     

The Global Earthquake Vulnerability Estimation System (GEVES): an approach for earthquake risk assessment for insurance applications

For the insurance and reinsurance industries, earthquake loss estimation is crucial not only to adequately price its product but also to manage the accumulation risk in the face of the ever-increasing exposure in highly seismic regions. Changes in the built environment and a continuously evolving earthquake science make it a necessity for the industry to constantly refine earthquake loss estimation models. In particular, it has been recognized for a long time that the vulnerability of buildings to ground shaking is a key parameter in any earthquake risk model. Current methods tend either to rely on the limited historical damage and loss data or on the numerical simulation of the response of individual buildings to the ground-shaking produced by earthquakes. Although both methods have their advantages and pitfalls, we are proposing here a simple solution, using transparent input data, that can be realistically used for the needs of the insurance and reinsurance industry, whether detailed information about the insured structures is available or not. The resulting product is known as GEVES (Global Earthquake Vulnerability Estimation System). It is primarily intended for evaluating the mean damage ratio (MDR) suffered by a portfolio of buildings classified by use, under the action of a given earthquake scenario (i.e. an earthquake of given size at a given distance from the portfolio of buildings). A key assumption was that macroseismic intensity rather than spectral displacement would be the basis of loss estimation. The paper describes the model with emphasis on its structure and the justification for the assumptions made. In addition to a new set of earthquake vulnerability functions, the paper also provides recommendations on some aspects of the earthquake hazard, in particular about how to define macroseismic intensity at the site of interest, for a given earthquake scenario. This paper also discusses validation of the GEVES model against calculated vulnerability approaches, and the treatment of uncertainty within the model.     

Automation of the Filament Tracking in the Framework of the HELIO Project

We present a new method to automatically track filaments over the solar disk. The filaments are first detected on Meudon Spectroheliograph Hα images of the Sun, applying the technique developed by Fuller, Aboudarham, and Bentley (Solar Phys. 227, 61, 2005). This technique combines cleaning processes, image segmentation based on region growing, and morphological parameter extraction, including the determination of filament skeletons. The coordinates of the skeleton pixels, given in a heliocentric system, are then converted to a more appropriate reference frame that follows the rotation of the Sun surface. In such a frame, a co-rotating filament is always located around the same position, and its skeletons (extracted from each image) are thus spatially close, forming a group of adjacent features. In a third step, the shape of each skeleton is compared with its neighbours using a curve-matching algorithm. This step will permit us to define the probability [P] that two close filaments in the co-rotating frame are actually the same one observed on two different images. At the end, the pairs of features, for which the corresponding probability is greater than a threshold value, are associated using tracking identification indices. On a representative sample of filaments, the good agreement between automated and manual tracking confirms the reliability of the technique to be applied on large data sets. This code is already used in the framework of the Heliophysics Integrated Observatory (HELIO) to populate a catalogue dedicated to solar and heliospheric features (HFC). An extension of this method to other filament observations, and possibly sunspots, faculae, and coronal-holes tracking, can also be envisaged.     

Storm event sediment fingerprinting for temporal and spatial sediment source tracing

Sediment fingerprinting has been widely used to distinguish discrete sediment sources; however, application to intra-storm sediment source variability has received relatively little focus despite the benefit being long recognized. In this investigation, sediment fingerprinting was applied to a 53-hr storm event sampled hourly to determine sediment source dynamics throughout the event. Sediment sources were differentiated using 16 variables, and source contribution determined using Bayesian and Frequentist mixing models for comparison. Both models provided comparable source predictions for the dominant source estimates and the general temporal pattern. The Frequentist model appeared to exhibit some unreliable values coinciding with low GOF and attributed to inherent model structure. The Bayesian model showed higher uncertainty, likely due to the “process error” utilized associated with single sample mixtures. High variability in sediment source contribution was observed between hourly time steps; however, local smoothing reveals temporal trends during the event. A higher average proportion of mudstone is found in the falling limb (0.544) compared with the rising limb (0.464), and the reverse is observed for mountain range (0.218 vs. 0.283) and unconsolidated (0.073 vs. 0.055). In the initial hours of the storm, mudstone source contribution significantly drops, whereas mountain range and unconsolidated contributions peak. The SSC-Q clockwise hysteresis indicates proximal sediment sources, suggesting the mudstone sediment is stored channel sediment and easily entrained. This sediment flushes through, coinciding with a drop as the distal mountain range and unconsolidated sources arrive to peak contribution. The wider Manawatū discharge and sediment load then arrive, delivering increasing levels of mudstone throughout the remainder of the event while mountain range sediment diminishes. Spatial representation of the sediment source contribution was derived from distributing sediment source loads to the spatial extent of the source material according to sub-catchment sediment loads and was weighted according to slope. This provided an effective means to visualize the origin of the sediment and a better spatial interpretation of sediment fingerprinting results, which is typically limited by poor spatial resolution.     

An improved glacial isostatic adjustment model for the British Isles

The glacial isostatic adjustment (GIA) of the British Isles is of interest due to the constraints that can be provided on key model parameters such as the global meltwater signal, local ice sheet history and viscoelastic earth structure. A number of recent studies have modelled relative sea‐level (RSL) data from this region to constrain model parameters. As indicated in these studies, the sensitivity of these data to both local and global parameters results in a highly non‐unique problem. This study aims to address this inherent non‐uniqueness by combining a previously published British–Irish ice model that is based on the most recent geomorphological data with a new global ice sheet model that provides an accurate prediction of eustatic sea‐level change. In addition, constraints from Global Positioning System (GPS) measurements of present‐day vertical land motion are considered alongside the entirety of RSL data from both Great Britain and Ireland. A model solution is found that provides a high‐quality fit to both the RSL data and the GPS data. Within the range of earth viscosity values considered, the optimal data model fits were achieved with a relatively thin lithosphere (71 km), upper mantle viscosities in the range 4–6 × 10²⁰ Pa s and lower mantle viscosities ≥ 3 × 10²² Pa s. Copyright © 2011 John Wiley & Sons, Ltd.