Sampling uncertainties and source <Emphasis Type="Italic">b</Emphasis> likelihood for the Gutenberg-Richter <Emphasis Type="Italic">b</Emphasis> value from the Aki-Utsu method

The Aki-Utsu method of Gutenberg-Richter (G-R) b value estimation is often misapplied so that estimations not using the G-R histogram are often meaningless because they are not based on adequate samples. We propose a method to estimate the likelihood Pr(b?b _m , N, M ₁, M ₂) that an observed b _m estimate, based on a sample of N magnitudes within an [M ₁????≤?ΔM/2,?M ₂?+?ΔM/2) range, where ΔM?=?0.1 is the usual rounding applied to magnitudes, is due to a “true” source b value, b, and use these likelihoods to estimate source b ranges corresponding to various confidence levels. As an example of application of the method, we estimate the b values before and after the occurrence of a 7.4-magnitude earthquake in the Mexican subduction zone, and find a difference of 0.82 between them with 100% confidence that the b values are different.     

Probabilistic leak detectability assessment via state estimation in water transport networks

Leak detectability or leakage awareness refers to the capability of sensing losses from a water supply system. Several methods exist in the technical literature to tackle this problem, but only few address it with a state estimation approach. The aim of this paper is to present a new methodology that enables probabilistic assessment of the extent to which water loss could be detected using state estimation by only analysing a single hydraulic state, i.e. one time period. Significant leaks are sensed by identifying unusually high normalised state estimation residuals, which can be identified based on the largest normalised residual test. More specifically, the probability of detecting leaks is computed here by working with the multivariate distribution among measurements and estimates to take into account the noisy nature of measurements with an analytical approach rather than with sampling experiments, which are time-consuming. The methodology set out herein also provides a procedure to systematically assess the minimum leak that could be detected in different parts of the network for a specific measurement setting and operating condition. The method has been applied to a water transport network case study to show its potential and to highlight the usefulness of such a tool for practitioners. The limitations of such a methodology are also discussed, including its possible use for on-line leak detection strategies.     

A geostatistical protocol to optimize spatial sampling of domestic drinking water supplies in remote environments

This paper deals with the design of optimal spatial sampling of water quality variables in remote regions, where logistics are complicated and the optimization of monitoring networks may be critical to maximize the effectiveness of human and material resources. A methodology that combines the probability of exceeding some particular thresholds with a measurement of the information provided by each pair of experimental points has been introduced. This network optimization concept, where the basic unit of information is not a single spatial location but a pair of spatial locations, is used to emphasize the locations with the greatest information, which are those at the border of the phenomenon (for example contamination or a quality variable exceeding a given threshold), that is, where the variable at one of the locations in the pair is above the threshold value and the other is below the threshold. The methodology is illustrated with a case of optimizing the monitoring network by optimal selection of the subset that best describes the information provided by an exhaustive survey done at a given moment in time but which cannot be repeated systematically due to time or economic constrains.     

On the significance of the climate-dataset time resolution in characterising wind-driven rain and simultaneous wind pressure. Part I: scalar approach

Stochastic Environmental Research and Risk Assessment - The joint action of wind-driven rain and wind pressure is the main cause of water penetration in building facades, which causes various...     

Empirical seismic vulnerability assessment of Icelandic buildings affected by the 2000 sequence of earthquakes

In June 2000, two Mw6.5 earthquakes occurred within a 4-day interval in the largest agricultural region of Iceland causing substantial damage and no loss of life. The distance between the earthquake epicentres and the fault rupture was approximately 15 km. Nearly 5000 low-rise residential buildings were affected, some of which were located between the faults and exposed to strong ground motion from both events. The post-earthquakes damage and repair costs for every residential building in the epicentral region were assessed for insurance purposes. The database is detailed and complete for the whole region and represents one of the best quality post-earthquake vulnerability datasets used for seismic loss estimation. Nonetheless, the construction of vulnerability curves from this database is hampered by the fact that the loss values represent the cumulative damage from two sequential earthquakes in some areas, and single earthquakes in others. A novel methodology based on beta regression is proposed here in order to define the geographical limits on areas where buildings sustained cumulative damage and predict the seismic losses for future sequence of events in each area. The results show that the average building loss in areas affected by a single event is below 10% of the building replacement value, whilst this increases to an average of 25% in areas affected by the two earthquakes. The proposed methodology can be used to empirically assess the vulnerability in other areas which experienced sequence of events such as Emilia-Romagna (Italy) in 2012.     

Tsunami hydrodynamic force on a building using a SPH real-scale numerical simulation

Natural Hazards - One of the most important aspects in tsunami studies is the behaviour of the wave when it approaches the coast. Information on physical parameters that characterize waves is often...     

Instability in spatial error models: an application to the hypothesis of convergence in the European case

This paper focuses on the hypothesis of stability in the mechanisms of spatial dependence that are usually employed in spatial econometric models. We propose a specification strategy for which the first step is to solve a local estimation algorithm, called the Zoom estimation. The aim of this stage is to detect problems of heterogeneity in the parameters and to identify the regimes. Then we resort to a battery of formal Lagrange Multipliers to test the assumption of stability in the processes of spatial dependence. The alternative hypothesis consists of the existence of several regimes in these parameters. A small Monte Carlo serves to confirm the behaviour of this strategy in a context of finite size samples. As an illustration, we solve an application to the case of the hypothesis of convergence for the per capita income in the European regions. Our results reveal the existence of a strong Centre-Periphery dichotomy in which instability extends to all the elements (coefficients of regression as well as parameters of spatial dependence) that intervene in a classical conditional β-convergence model.