MOMENT TENSOR DETERMINATION USING A NEW WAVEFORM INVERSION TECHNIQUE

In this study a new waveform inversion methodology was developed to determine the source parameters of an earthquake. This technique is based on analyzing data recorded both at teleseismic and regional distances. To apply the inversion three different methods, which are the normal equations, the QR-decomposition and the singular value decomposition (SVD), were successfully tested, similar results were obtained and the SVD method was selected. The proposed inversion methodology was applied to large, as well as to earthquakes of moderate magnitude. Analysis of moderate events is crucial for seismogenic volumes, where an important number of such earthquakes occur which allow the calculation of their source parameters. Thus, the seismotectonic characteristics of the study area can be determined. The proposed methodology is successfully applied to events located in Greece and its surrounding regions in near real time

Enhancement of urban pluvial flood risk management and resilience through collaborative modelling: a UK case study

This paper presents the main findings and lessons learned from the development and implementation of a new methodology for collaborative modelling, social learning and social acceptance of flood risk management technologies. The proposed methodology entails three main phases: (1) stakeholder analysis and engagement; (2) improvement of urban pluvial flood modelling and forecasting tools; and (3) development and implementation of web-based tools for collaborative modelling in flood risk management and knowledge sharing. The developed methodology and tools were tested in the Cranbrook catchment (London Borough of Redbridge, UK), an area that has experienced severe pluvial (surface) flooding in the past. The developed methodologies proved to be useful for promoting interaction between stakeholders, developing collaborative modelling and achieving social acceptance of new technologies for flood risk management. Some limitations for stakeholder engagement were identified and are discussed in the present paper

SOURCE PARAMETERS OF MODERATE AND STRONG EARTHQUAKES IN THE BROADER AREA OF ZAKYNTHOS ISLAND (W. GREECE) FROM REGIONAL AND TELESEISMIC DIGITAL RECORDINGS

The source parameters of all the moderate and strong events that occurred in the broader area of Zakynthos Island for the period 1997–2009 are determined using two different techniques depending on epicentral distance. For the strong events we employed teleseismic body-wave modeling between 30° and 90°, while for moderate events a regional moment tensor inversion approach was used. In both cases we used broadband waveform data with a good signal-to-noise ratio. The calculated focal mechanisms are representative of the displacement and strain fields of the broader area. Those associated with the Cephalonia transform fault are consistent with dextral strike-slip motion. The area between the island of Zakynthos and the Western coast of Peloponnese is also characterized by strike–slip faulting, while reverse faulting is mainly observed south of Zakynthos Island. Using both techniques, we also retrieved the source parameters of the biggest events of the seismic sequence of April 2006 near the southern coast of Zakynthos Island. The depths of the located events of the sequence vary mainly between 10 and 25 km. The fault plane solutions revealed thrust type faulting in all cases, something which can be related with upward motions in the southern part of the Island observed by DGPS measurements

HESS Opinions: "Climate, hydrology, energy, water: recognizing uncertainty and seeking sustainability"

Since 1990 extensive funds have been spent on research in climate change. Although Earth Sciences, including climatology and hydrology, have benefited significantly, progress has proved incommensurate with the effort and funds, perhaps because these disciplines were perceived as “tools” subservient to the needs of the climate change enterprise rather than autonomous sciences. At the same time, research was misleadingly focused more on the “symptom”, i.e. the emission of greenhouse gases, than on the “illness”, i.e. the unsustainability of fossil fuel-based energy production. Unless energy saving and use of renewable resources become the norm, there is a real risk of severe socioeconomic crisis in the not-too-distant future. A framework for drastic paradigm change is needed, in which water plays a central role, due to its unique link to all forms of renewable energy, from production (hydro and wave power) to storage (for time-varying wind and solar sources), to biofuel production (irrigation). The extended role of water should be considered in parallel to its other uses, domestic, agricultural and industrial. Hydrology, the science of water on Earth, must move towards this new paradigm by radically rethinking its fundamentals, which are unjustifiably trapped in the 19thcentury myths of deterministic theories and the zeal to eliminate uncertainty. Guidance is offered by modern statistical and quantum physics, which reveal the intrinsic character of uncertainty/entropy in nature, thus advancing towards a new understanding and modelling of physical processes, which is central to the effective use of renewable energy and water resources

Human brain mapping: a systematic comparison of parcellation methods for the human cerebral cortex

The macro-connectome elucidates the pathways through which brain regions are structurally connected or functionally coupled to perform a specific cognitive task. It embodies the notion of representing and understanding all connections within the brain as a network, while the subdivision of the brain into interacting functional units is inherent in its architecture. As a result, the definition of network nodes is one of the most critical steps in connectivity network analysis. Although brain atlases obtained from cytoarchitecture or anatomy have long been used for this task, connectivity-driven methods have arisen only recently, aiming to delineate more homogeneous and functionally coherent regions. This study provides a systematic comparison between anatomical, connectivity-driven and random parcellation methods proposed in the thriving field of brain parcellation. Using resting-state functional MRI data from the Human Connectome Project and a plethora of quantitative evaluation techniques investigated in the literature, we evaluate 10 subject-level and 24 groupwise parcellation methods at different resolutions. We assess the accuracy of parcellations from four different aspects: (1) reproducibility across different acquisitions and groups, (2) fidelity to the underlying connectivity data, (3) agreement with fMRI task activation, myelin maps, and cytoarchitectural areas, and (4) network analysis. This extensive evaluation of different parcellations generated at the subject and group level highlights the strengths and shortcomings of the various methods and aims to provide a guideline for the choice of parcellation technique and resolution according to the task at hand. The results obtained in this study suggest that there is no optimal method able to address all the challenges faced in this endeavour simultaneously

Robust whole-brain segmentation: Application to traumatic brain injury

We propose a framework for the robust and fully-automatic segmentation of magnetic resonance (MR) brain images called "Multi-Atlas Label Propagation with Expectation-Maximisation based refinement" (MALP-EM). The presented approach is based on a robust registration approach (MAPER), highly performant label fusion (joint label fusion) and intensity-based label refinement using EM. We further adapt this framework to be applicable for the segmentation of brain images with gross changes in anatomy. We propose to account for consistent registration errors by relaxing anatomical priors obtained by multi-atlas propagation and a weighting scheme to locally combine anatomical atlas priors and intensity-refined posterior probabilities. The method is evaluated on a benchmark dataset used in a recent MICCAI segmentation challenge. In this context we show that MALP-EM is competitive for the segmentation of MR brain scans of healthy adults when compared to state-of-the-art automatic labelling techniques. To demonstrate the versatility of the proposed approach, we employed MALP-EM to segment 125 MR brain images into 134 regions from subjects who had sustained traumatic brain injury (TBI). We employ a protocol to assess segmentation quality if no manual reference labels are available. Based on this protocol, three independent, blinded raters confirmed on 13 MR brain scans with pathology that MALP-EM is superior to established label fusion techniques. We visually confirm the robustness of our segmentation approach on the full cohort and investigate the potential of derived symmetry-based imaging biomarkers that correlate with and predict clinically relevant variables in TBI such as the Marshall Classification (MC) or Glasgow Outcome Score (GOS). Specifically, we show that we are able to stratify TBI patients with favourable outcomes from non-favourable outcomes with 64.7% accuracy using acute-phase MR images and 66.8% accuracy using follow-up MR images. Furthermore, we are able to differentiate subjects with the presence of a mass lesion or midline shift from those with diffuse brain injury with 76.0% accuracy. The thalamus, putamen, pallidum and hippocampus are particularly affected. Their involvement predicts TBI disease progression.This work was partially funded under the 7th Framework Programme by the European Commission (http://cordis.europa.eu/ist/, TBIcare: http://www.tbicare.eu/, last accessed: 8 December 2014). The research was further supported by the National Institute for Health Research (NIHR) Biomedical Research Centre (BRC) based at Imperial College Healthcare NHS Trust and Imperial College London. AH is supported by the Department of Health via the NIHR comprehensive BRC award to Guy’s & St Thomas’ NHS Foundation Trust in partnership with King’s College London and Kings College Hospital NHS Foundation Trust. This work was further supported by a Medical Research Council (UK) Program Grant (Acute brain injury: heterogeneity of mechanisms, therapeutic targets and outcome effects [G9439390 ID 65883]), the UK National Institute of Health Research Biomedical Research Centre at Cambridge, the Technology Platform funding provided by the UK Department of Health and an EPSRC Pathways to Impact award. VFJN is supported by a Health Foundation/Academy of Medical Sciences Clinician Scientist Fellowship. DKM is supported by an NIHR Senior Investigator Award. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. The funders had no role in study design, data collection and analyses, decision to publish, or preparation of the manuscript