Correction to: Spatial distribution and estimation of rainfall trends and erosivity in the Epitácio Pessoa reservoir catchment,Paraíba,Brazil

Natural Hazards - The article “Spatial distribution and estimation of rainfall trends and erosivity in the Epitácio Pessoa reservoir catchment, Paraíba, Brazil”, written by da...     

Comparing access for all: disability-induced accessibility disparity in Lisbon

It is well known that individual impairments create disparities in the accessibility of individuals to opportunities, lengthening the distances or time needed to reach them or even completely impeding access. However, the accurate calculation and representation of these disparities remain a major challenge for urban and transportation planners. In this paper, we adopt the concept of accessibility disparity, originally applied to measure place accessibility by different modes of transport, to measure and represent the accessibility of individuals with physical disabilities compared to those without disabilities. We use spatial network analysis to calculate spatial connectivity and the accessibility of Lisbon’s city center, revealing what we define as ‘disability-induced accessibility disparity’. Our results reveal not only the locations responsible for reduced accessibility, i.e., barriers and/or deterrents to movement, but also how much any given disparity reduces the accessibility of an individual, allowing the use of this methodology by planners to identify critical areas and to design inclusive public spaces.     

A new dynamical Climatology: Its aim and method

Summary By dynamical climatology is understood here the branch of mathematical meteorology which aims at a deduction of the mean properties of the atmospheric perturbations that are compatible with a given mean field of temperature, wind and pressure. First of all, the fundamental equations of the author's theory of perturbations are recalled and a general equation for the pressure variations at sea level is deduced. From this equation the different elements of dynamical climatology are then derived, for instance the stability of the mean field, the mean trajectories of the perturbations, the frequencies with which they are visited, the regions of deepening and filling or of birth and death of the perturbations, etc. These results explain many observational facts and empirical rules about the mean behaviour of the atmospheric disturbances at sea level throughout the year.

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Zusammenfassung Unter dynamischer Klimatologie wird hier der Zweig der mathematischen Meteorologie verstanden, der auf die Ableitung der mittleren Eigenschaften atmosphärischer Störungen, die mit einem gegebenen mittleren Temperatur-, Wind- und Druckfeld vereinbar sind, abzielt. Zunächst wird an die fundamentalen Gleichungen der Störungstheorie des Verfassers erinnert, um dann die allgemeine Gleichun; der Druckschwankungen auf dem Meeresniveau abzuleiten. Diese Gleichung führt dann zur Bestimmung der verschiedenen Elemente der dynamischen Klimatologie, z. B. zur Bestimmung der Stabilität des mittleren Feldes, der mittleren Trajektorien der Störungen, der Häufigkeit, mit welcher diese durchlaufen werden, der Gebiete der Vertiefung und Auffüllung oder des Entstehens und Verschwindens der Störungen usw.

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Résumé On entend ici par climatologie dynamique la partie de la météorologie mathématique qui a pour but la déduction des propriétés moyennes des perturbations atmosphériques qui sont compatibles avec un champ moyen donné de température, vent et pression. Tout d'abord on rappelle les équations fondamentales de la théorie des perturbations de l'auteur et l'on en déduit une équation générale des variations de la pression au niveau de la mer. Cette équation conduit à la détermination des éléments de la climatologie dynamique, tels que la stabilité du champ moyen, les trajectoires moyennes des perturbations, la fréquence avec laquelle elles sont parcourues, les régions de creusement et de comblement ou de naissance et de disparition des perturbations, etc. Ces résultats expliquent de nombreux faits d'observation et des règles empiriques sur le comportement moyen des perturbations atmosphériques au niveau de la mer pour les différentes époques de l'année.

     

Multiple Random Walk Simulation: A Fast Method to Map Grade Uncertainty with Large Datasets

Multiple Random Walk Simulation consists of a methodology adapted to run fast simulations if close-spaced data are abundant (e.g., short-term mining models). Combining kriging with the simulation of random walks attempts to approximate traditional simulation algorithm results but at a computationally faster way when there is a large amount of conditioning samples. This paper presents this new algorithm illustrating the situations where the method can be used properly. A synthetic study case is presented in order to illustrate the Multiple Random Walk Simulation and to analyze the speed and goodness of its results against the ones from using Turning Bands Simulation and Sequential Gaussian Simulation.     

Tectonic setting of the Azores Plateau deduced from a OBS survey

The studies of Azores seismicity generally show shocks with either normal faulting or right-lateral strike-slip along the ESE direction, compatible with a eastward relative motion of the Eurasian (EU) relative to the African (AF) plate. However, the 1 January 1980 earthquake was interpreted as a clear left-lateral strike-slip shock along the N150E direction. This pattern is difficult to explain in terms of the relative motion between the EU, AF and North American (NA) plates: all available models for the present day movement of this triple junction fail to explain the regional variability in the stress conditions of the area. Here we present data from a 34-day long Ocean Bottom Seismograph array deployment. We show that the seismicity is distributed along a band aligned with the island chain itself, and is concentrated along several faults with an approximate N150E strike, cutting the Azores plateau in all the area covered by the OBS network. The combination of these new results with other geophysical data permits us to conclude that the tectonic setting of the Azores plateau is characterised by the existence of two sets of faults, in the N120E and N150E directions, defining several crustal blocks, whose relative motion accommodates the interaction of the three megaplates. The deformation of these tectonic blocks is probably driven by the shear between the EU and AF plates. This model explains well the spatial variability of the stress conditions in the Azores domain, the combination of dextral and sinistral strike slip mechanisms and the observed seismotectonics of the Azores islands.     

Estimation of extreme Component-wise Excess design realization: a hydrological application

The classic univariate risk measure in environmental sciences is the Return Period (RP). The RP is traditionally defined as “the average time elapsing between two successive realizations of a prescribed event”. The notion of design quantile related with RP is also of great importance. The design quantile represents the “value of the variable(s) characterizing the event associated with a given RP”. Since an individual risk may strongly be affected by the degree of dependence amongst all risks, the need for the provision of multivariate design quantiles has gained ground. In contrast to the univariate case, the design quantile definition in the multivariate setting presents certain difficulties. In particular, Salvadori, G., De Michele, C. and Durante F. define in the paper called “On the return period and design in a multivariate framework” (Hydrol Earth Syst Sci 15:3293–3305, 2011) the design realization as the vector that maximizes a weight function given that the risk vector belongs to a given critical layer of its joint multivariate distribution function. In this paper, we provide the explicit expression of the aforementioned multivariate risk measure in the Archimedean copula setting. Furthermore, this measure is estimated by using Extreme Value Theory techniques and the asymptotic normality of the proposed estimator is studied. The performance of our estimator is evaluated on simulated data. We conclude with an application on a real hydrological data-set.     

Smoothing and high risk areas detection in space-time disease mapping: a comparison of P-splines,autoregressive, and moving average models

Recently, several models have been proposed for smoothing risks in disease mapping. These models consider different ways of introducing both spatial and temporal dependence as well as spatio-temporal interactions. In this work, a comparison among some autoregressive, moving average, and P-spline models is performed. Firstly, brain cancer mortality data are used to analyze the degree of smoothness introduced by these models. Secondly, two separate simulation studies (one model-based and the other model-free) are carried out to evaluate the model performance in terms of bias, variability, sensitivity, and specificity. We conclude that P-spline models seem to be a good alternative to autoregressive and moving average models when analyzing highly sparse disease mapping data.     

Seasonal copula models for the analysis of glacier discharge at King George Island,Antarctica

Modelling glacier discharge is an important issue in hydrology and climate research. Glaciers represent a fundamental water resource when melting of ice and snow contributes to runoff. Glaciers are also studied as natural global warming sensors. GLACKMA association has implemented one of their Pilot Experimental Catchment areas at the King George Island in the Antarctica which records values of the liquid discharge from Collins glacier. In this paper, we propose the use of time-varying copula models for analyzing the relationship between air temperature and glacier discharge, which is clearly non constant and non linear through time. A seasonal copula model is defined where both the marginal and copula parameters vary periodically along time following a seasonal dynamic. Full Bayesian inference is performed such that the marginal and copula parameters are estimated in a one single step, in contrast with the usual two-step approach. Bayesian prediction and model selection is also carried out for the proposed model such that Bayesian credible intervals can be obtained for the conditional glacier discharge given a value of the temperature at any given time point. The proposed methodology is illustrated using the GLACKMA real data where there is, in addition, a hydrological year of missing discharge data which were not possible to measure accurately due to problems in the sounding.     

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.