The danger of mapping risk from multiple natural hazards

In recent decades, society has been greatly affected by natural disasters (e.g. floods, droughts, earthquakes), losses and effects caused by these disasters have been increasing. Conventionally, risk assessment focuses on individual hazards, but the importance of addressing multiple hazards is now recognised. Two approaches exist to assess risk from multiple-hazards; the risk index (addressing hazards, and the exposure and vulnerability of people or property at risk) and the mathematical statistics method (which integrates observations of past losses attributed to each hazard type). These approaches have not previously been compared. Our application of both to China clearly illustrates their inconsistency. For example, from 31 Chinese provinces assessed for multi-hazard risk, Gansu and Sichuan provinces are at low risk of life loss with the risk index approach, but high risk using the mathematical statistics approach. Similarly, Tibet is identified as being at almost the highest risk of economic loss using the risk index, but lowest risk under the mathematical statistics approach. Such inconsistency should be recognised if risk is to be managed effectively, whilst the practice of multi-hazard risk assessment needs to incorporate the relative advantages of both approaches

Time-series analysis: how to apply and interpret the fast Fourier transform

Many natural hazards have cyclic/periodic behaviour, e.g. radon, earthquakes (under some circumstances), annual/seasonal droughts and floods, whereas others are anomalous, apparently random with regard to time, e.g. earthquakes and volcanic eruptions(under most circumstances). For the cyclic cases, an analysis of past time-series can yield an expectation and perhaps some degree of forecasting, even if only at the level of 'more probable' and 'less probable' times of occurrence. This is the background for this short-course: we need to be able to analyse a sequential record of events, i.e. a time-series, for cyclic/periodic features. More specifically, the aim of this short-course is to provide an introduction to and overview of what is arguably the key technique of time-series analysis in this context: the Fast (Discrete) Fourier Transform. The focus will be on application of the Fast Fourier Transform, as implemented in many software packages, and interpretation of the output. Anticipating that most of those who attend will be 'technique users' rather than 'technique developers', coverage of the underlying mathematics will be kept to a necessary minimum to facilitate informed interpretation of the Fast (Discrete) Fourier Transform

Mapping landslide susceptibility from small datasets: A case study in the Pays de Herve (E Belgium)

A landslide susceptibility map is proposed for the Pays de Herve (E Belgium), where large landslides affect Cretaceous clay outcrop areas. Based on a Bayesian approach, this GIS-supported probabilistic map identifies the areas most susceptible to deep landslides. The database is comprised of the source areas of ten pre-existing landslides (i.e. a sample of 154 grid cells) and of six environmental data layers, namely lithology, proximity to active faults, slope angle and aspect, elevation and distance to the nearest valley-floor. A 30-m-resolution DEM from the Belgian National Geographical Institute is used for the analysis. Owing to the small size of the sample, a special cross-validation procedure of the susceptibility map is performed, which uses in an iterative way each of the landslides to test the predictive power of the map derived from the other landslides. Four different sets of variables are used to produce four susceptibility maps, whose prediction curves are compared. While the prediction rates associated with the models not involving the “proximity to active fault” criterion are comparable to those of the models considering this variable, strong weaknesses inherent in the fault data on which the latter rely suggest that the final susceptibility map should be based on a model that excludes any reference to fault. This highlights the difference between a triggering factor and determining factors, and in the same time broadens the scope of the produced map. A single reactivated slide is also used to test the possibility of predicting future reactivation of existing landslides in the area. Finally, the need for geomorphological control over the mathematical treatment is underlined in order to obtain realistic prediction maps

Session keynote: Radon, Health and Natural Hazards and IGCP Project 571

The first annual end-of-year meeting of IGCP Project 571 (Radon, Health and Natural Hazards) was held at the 2010 EGU General Assembly and a total of 28 presentations, comprising six oral and 22 poster presentations, were made. This marked several successful developments from the previous year’s inaugural meeting held at the 2009 EGU General Assembly. Subsequently, formal communications networks have been confirmed between lead groups in the UK, France, Poland, India and Taiwan and an Indian national Project-571 working group has been established. In addition, these networks are extending to include contacts and collaborations in/with Hungary, Slovenia, Austria, the Czech Republic, Greece, Trinidad & Tobago, Spain, Japan, Canada and Israel. Currently, there is a UK-India Commonwealth Fellowship hosted by Kingston and Northampton Universities to support one of the Project’s Indian co-leaders to advance Project activities in data-logging and analysis. The presentation will comprise a review of the second year and set out objectives for the third and subsequent years, and will introduce and overview the Project sessions and presentations at the 2011 EGU General Assembly

Petrography and geochemistry of the magnesites and dolostones of the Ediacaran Ibor Group (635 to 542 Ma), Western Spain: Evidences of their hydrothermal origin

The Ediacaran deposits (between 635 and 542 Ma) of the Central Zone of the Iberian Massif consist of alternating siliciclastic and carbonate beds. These carbonates are dolostones and magnesites which are interpreted to have been formed by the replacement of primary peritidal limestones. Through petrographic and geochemical analyses, we recognize different types of dolomites (D1 to D4) and magnesites (M1 and M2). Despite distinct petrographic features of the four types of dolomite, their oxygen and carbon isotopes overlap with δ18O values ranging from +15.45 to +17.51‰ (SMOW) and δ13C from −0.13 to 3.21‰ PDB. Sr isotope values for D1 and D2 range from 0.7028 to 0.7091. Magnesites (M1 and M2) show oxygen values higher than +17.87.0‰, and δ13C values show the same variability as for the dolomites. D3 and D4 oxygen isotope values are between +18.91 and 19.61, and the carbon isotope values range are similar to the other diagenetic phases. Sr isotope values for the magnesites and late dolomites (D3 and D4) are 0.7095 to 0.7104, being higher than those of the D1 and D2 dolomites. D1 is a relatively early dolomite phase formed by the replacement of fine grained peritidal limestones. The coarser crystal size of D2, which shows similar geochemical features as D1, suggests formation by dolomitization of coarser grained limestones. The replacement of D1 and D2 by M1 and M2 advanced along stylolites, fractures and bedding planes. This replacement is interpreted to have occurred by hydrothermal fluids, which is suggested by the presence of talc and forsterite. D3, a coarse dolomite, completely destroyed any previous texture and D4 (dolomite cement) post-dates magnesite formation. Interactions of hydrothermal fluids with the prior carbonates reset the oxygen isotopes of the earlier dolomite. The study of these magnesites and related dolostones may offer new insights into the model of formation of sparry magnesites hosted by mixed siliciclastic–carbonate platform deposits. The establishment of the factors and mechanism that control the diagenetic evolution of these carbonates has a great importance in order to understand and predicts porosity and permeability variations of rocks formed under similar geological conditions