A large amount of buildings was damaged or destroyed by the 2011 Great East Japan tsunami. Numerous field surveys were conducted in order to collect the tsunami inundation extents and building damage data in the affected areas. Therefore, this event provides us with one of the most complete data set among tsunami events in history. In this study, fragility functions are derived using data provided by the Ministry of Land, Infrastructure and Transportation of Japan, with more than 250,000 structures surveyed. The set of data has details on damage level, structural material, number of stories per building and location (town). This information is crucial to the understanding of the causes of building damage, as differences in structural characteristics and building location can be taken into

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[1] Intensive geothermal exploitation at The Geysers geothermal area, California, induces myriads of small-magnitude earthquakes that are monitored by a dense, permanent, local seismometer network. Using this network, tomographic inversions were performed for the three-dimensional V p and V p /V s structure of the reservoir for April 1991, February 1993, December 1994, October 1996, and August 1998. The extensive low-V p /V s anomaly that occupies the reservoir grew in strength from a maximum of 9% to a maximum of 13.4% during the 7-year study period. This is attributed to depletion of pore liquid water in the reservoir and replacement with steam. This decreases V p by increasing compressibility, and increases V s because of reduction in pore pressure and the drying of argillaceous minerals, e.g., illite, which increase the shear modulus. These effects serendipitously combine to lower V p /V s , resulting in a strong overall effect that provides a convenient tool for monitoring reservoir depletion. Variations in the V p and V s fields indicate that water depletion is the dominant process in the central part of the exploited reservoir, and pressure reduction and mineral drying in the northwest and southeast parts of the reservoir. The rate at which the V p /V s anomaly grew in strength in the period 1991-1998 suggests most of the original anomaly was caused by exploitation. Continuous monitoring of V p , V s , and V p /V s is an effective geothermal reservoir depletion monitoring tool and can potentially provide information about depletion in parts of the reservoir that have not been drilled.

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The velocity and dynamic pressure of debris flows are critical determinants of the impact of these natural phenomena on infrastructure. Therefore, the prediction of these parameters is critical for hazard assessment and vulnerability analysis. We present here an approach to predict the velocity of debris flows on the basis of the energy line concept. First, we obtained empirically and field-based estimates of debris flow peak discharge, mean velocity at peak discharge and velocity, at channel bends and within the fans of ten of the debris flow events that occurred in May 1998 in the area of Sarno, Southern Italy. We used this data to calibrate regression models that enable the prediction of velocity as a function of the vertical distance between the energy line and the surface. Despite the complexity in morphology and behaviour of these flows, the statistical fits were good and the debris flow velocities can be predicted with an associated uncertainty of less than 30% and less than 3 m s − − − − −1 Figure 1. Shaded relief of the Sarno area within the regional context. Grey indicates the source areas, white the transport zones and black the deposition areas. Two or more source areas (e.g. Lav-2) or two inundation areas that merged (e.g. Ep-6) were combined in this analysis. Velocity data were collected at channel bends and within the deposition areas of Ep-2, Ep-3, Ep-4, Ep-5, Ep-6, Ep-7, Lav-1, Lav-2, Quin-6 and Sia-2.The efforts to explain and predict debris flow behaviour have traditionally involved the development of rheological models, where the mass and momentum balance equations are solved using some type of relationship between shear stress and strain rate (e.g. Johnson and Rodine, 1984;Macedonio and Pareschi, 1992;O'Brien et al., 1993;Ayotte and Hungr, 2000). The macroscopic behaviour of debris flows may be also reproduced with a two-parameter Voelmy type model, where the resisting stress at the base is parameterized by a sliding friction and a rate-dependent turbulent term (Körner, 1976;Ayotte and Hungr, 2000;Hungr et al., 2005;Rickenmann, 2005) or with one-dimensional flow-routing models, where the energy dissipation is parameterized by a single roughness coefficient, e.g. Manning's n (Chow, 1959;Pierson, 1995;Rickenmann and Koch, 1997). Recently, Iverson (2003) developed an alternative to fixedrheology models that is able to describe the behaviour of the mixture from the onset of motion through deposition and post-depositional consolidation, with no definition of rheological parameters required (see also Iverson, 1997;Iverson and Denlinger, 2001;Denlinger and Iverson, 2001;and Rickenmann, 2005, for a useful review).Empirically based methodologies may be also used to predict the parameters necessary to quantify the destructive power of debris flows. The mobility ratio (Δ H/L) can be used for run-out distance prediction (Corominas, 1996;Iverson, 1997;Rickenmann, 1999;Toyos et al., 2007b) and first order approximations of velocity histories of debris flows (see, e.g., Malin and Sheridan, 1982). The princ...

The main motivation of this paper is to shed new light on the problem of spatial identification of urban and rural areas globally, and to provide a compatible disaggregation framework for linking associated country-specific, non-spatial data compilations, such as building type inventories. Existing homogeneously setup global urban extent models commonly ignore local-level specifics. While global consistency and regional comparability of urban characteristics are much strived-for goals in the global development and remote sensing communities, non-conformity at the national level often renders such models inapplicable for effective decision-making. Furthermore, the focus on identifying 'urban' leads to an illdefined 'rural', which is simply defined by contrast as 'everything else'; a questionable definition when referring to strongly spatially localized residential patterns. In this paper we introduce the novel iURBAN geospatial modeling approach, identifying Urban-Rural patterns in Built-up-Adjusted and Nationally-adaptive manner. The model operates at global scale, but at the same time conforms to country specifics. In this model, high-resolution, satellitederived, built-up data is used to consistently detect global human settlements at unprecedented spatial detail. In combination with global gridded population data, and with reference to national level statistical information on urban population ratios globally compiled in the annually-released UN World Urbanization Prospects, iURBAN identifies matching urban extents. Additionally, a novel reallocation algorithm is introduced which addresses the poor representation of rural areas that is inherent in existing global population grids. Associating all of the population with inhabitable, built-up area and conforming to national urban-rural ratios, iURBAN sets a new standard by enabling careful consideration of both urban and rural as opposed to traditional urban-biased approaches.

Interdisciplinary work in science has been driven in recent years at least partly by new technologies that meet the needs of several disciplines simultaneously. Geographical Information Systems (GIS) technology is used by geographers, archaeologists, geologists and a wide range of others in the social and natural sciences for storage, manipulation and mapping of data with a spatial reference. To illustrate the inherently interdisciplinary nature of GIS, a case study of an Environmental Impact Assessment (EIA) using GIS is presented in this paper. The environmental issues dealt with relate to archaeology, land use, transport, water, geology, ecology and noise. An initial GIS study identifying major environmental concerns suggests that the site is unsuitable. However, implementation of suitable mitigation measures, as evaluated using GIS, allows such concerns to be alleviated. The GIS approach is thus useful not only in site selection but also for evaluating the acceptability of mitigation measures.

Abstract. Rapid impact assessments immediately after disasters are crucial to enable rapid and effective mobilization of resources for response and recovery efforts. These assessments are often performed by analysing the three components of risk: hazard, exposure and vulnerability. Vulnerability curves are often constructed using historic insurance data or expert judgments, reducing their applicability for the characteristics of the specific hazard and building stock. Therefore, this paper outlines an approach to the creation of event-specific vulnerability curves, using Bayesian statistics (i.e., the zero-one inflated beta distribution) to update a pre-existing vulnerability curve (i.e., the prior) with observed impact data derived from social media. The approach is applied in a case study of Hurricane Dorian, which hit the Bahamas in September 2019. We analysed footage shot predominantly from unmanned aerial vehicles (UAVs) and other airborne vehicles posted on YouTube in the first 10 days after the disaster. Due to its Bayesian nature, the approach can be used regardless of the amount of data available as it balances the contribution of the prior and the observations.