Evaluation and comparison of satellite precipitation estimates with reference to a local area in the Mediterranean Sea

Precipitation is one of the major variables for many applications and disciplines related to water resources and the geophysical Earth system. Satellite retrieval systems, rain-gauge networks, and radar systems are complementary to each other in terms of their coverage and capability of monitoring precipitation. Satellite-rainfall estimate systems produce data with global coverage that can provide information in areas for which data from other sources are unavailable. Without referring to ground measurements, satellite-based estimates can be biased and, although some gauge-adjusted satellite-precipitation products have been already developed, an effective way of integrating multi-sources of precipitation information is still a challenge.In this study, a specific area, the Sicilia Island (Italy), has been selected for the evaluation of satellite-precipitation products based on rain-gauge data. This island is located in the Mediterranean Sea, with a particular climatology and morphology, which can be considered an interesting test site for satellite-precipitation products in the European mid-latitude area. Four satellite products (CMORPH, PERSIANN, PERSIANN-CCS, and TMPA-RT) and two GPCP-adjusted products (TMPA and PERSIANN Adjusted) have been selected. Evaluation and comparison of selected products is performed with reference to data provided by the rain-gauge network of the Island Sicilia and by using statistical and graphical tools. Particular attention is paid to bias issues shown both by only-satellite and adjusted products. In order to investigate the current and potential possibilities of improving estimates by means of adjustment procedures using GPCC ground precipitation, the data have been retrieved separately and compared directly with the reference rain-gauge network data set of the study area.Results show that bias is still considerable for all satellite products, then some considerations about larger area climatology, PMW-retrieval algorithms, and GPCC data are discussed to address this issue, along with the spatial and seasonal characterization of results. © 2013 Elsevier B.V

An Advanced Pavement Management System based on a Genetic Algorithm for a Motorway Network

Maintenance and improvement, through the rehabilitation, of the road infrastructure is a strategic and priority objective for road agencies, nevertheless the economic resources required are often inadequate. Within road management, the pavement management system (PMS) plays an essential role because of both the money needed and the performance that should be provided in terms of safety, ride quality and transport cost. The PMS is based on searching for a balanced solution between the lowest cost and the increased level of performance (i.e. pavement condition). In this paper a PMS multi-objective optimization method, was proposed, using a genetic algorithm (GA) to identify the best solution considering different rehabilitation strategies. The multi-objective optimization GA permits a set of optimal solutions (the Pareto solution set) that takes into account all the considered constraints. Finally on the basis of a specific criteria the best solution was selected in relation to the ranking of the priorities of the agency. A detailed numerical study was conducted on the Italian A18 motorway and the results showed that the proposed model PMS-GA is a suitable support to the decision making process

Seismic Vulnerability of the Italian Roadway Bridge Stock

This study focuses on the seismic vulnerability evaluation of the Italian roadway bridge stock, within the framework of a Civil Protection sponsored project. A comprehensive database of existing bridges (17,000 bridges with different level of knowledge) was implemented. At the core of the study stands a procedure for automatically carrying out state-of-the-art analytical evaluation of fragility curves for two performance levels – damage and collapse – on an individual bridge basis. A webGIS was developed to handle data and results. The main outputs are maps of bridge seismic risk (from the fragilities and the hazard maps) at the national level and real-time scenario damage-probability maps (from the fragilities and the scenario shake maps). In the latter case the webGIS also performs network analysis to identify routes to be followed by rescue teams. Consistency of the fragility derivation over the entire bridge stock is regarded as a major advantage of the adopted approach

Daily rainfall statistics in Sicily (1920-2000)

Rainfall characteristics are crucial for vegetation patterns formation and evolution in Mediterranean ecosystems. Changes in rainfall frequency and intensity could cause vegetation water stress for some plant species and benefit, at the same time, other species, driving coexistence and competition dynamics. The changes in the precipitation characteristics are sometimes more important than the changes in the total amount of precipitation in determining the partitioning between green and blue water with several implications for both the vegetation communities health and water resource management. Decreasing rainfall is a clear signature of climate change in Mediterranean countries. Annual and winter totals have been demonstrated to decrease in the past century and GCMs forecast a progressive worsening of the current situation even if it is still not clear if and how rainfall could be modified in its temporal and seasonal patterns. This study aims to analyze daily rainfall properties in Sicily in the last century. Namely the daily depths and interarrival times between events are investigated in about 50 stations, also characterizing seasonal rainfall features. The presence of significant trend has been detected using the non parametric Mann Kendall test

Climate changes effects on vegetation in Mediterranean areas

The Mediterranean ecosystems evolved under climatic conditions characterized by precipitations markedly out of phase with the growing period for the vegetation there established. In such environments, deep and shallow rooted species cohabit and compete each other. The formers, being characterized by deeper root, are able to utilize the water stored during the dormant season, while the conditions of shallow rooted plant are closely related to the intermittence of the precipitations. A numerical model has been here used in order to carry out an analysis of the potential climate changes influence on the vegetation state in a typical Mediterranean environment, such as Sicilian one. The most important consequences arising from climate changes in the Mediterranean area, due to the CO2 increase, are the temperatures raise and the contemporaneous rainfall reduction. Probably, this reduction could be accompanied by an increase in events intensity and, at the same time, by a decrease in the number of annual events. There are very few information about possible changes in the distribution of the rainfall events over the year. However, according to the analysis of the recorded trend, it is possible to predict that the rainfall reduction will be mainly concentrated during the autumnal and wintry months. The goal of this work is a quantitative evaluation of the effects due to the climatic forcing changes, on vegetation water stress. In particular, great attention is paid to the effects that rainfall decrease may have on vegetation, by itself or coupled with the temperature increase. A detailed investigation on the influence of the variations in rainfall seasonality, frequency and intensity is carried out. In this work two vegetation covers, with shallow and deep rooting depth (grass and tree) laying on three different soil types (loamy sand, sandy loam and clay) are considered. Simulations on Mediterranean ecosystems have lead to recognize the role of the rainfall amount, frequency and temporal distribution. Rainfall decrease increases the vegetation water stress much more than temperature increase do. Intense and rare rainfall events, as they are expected to be, could attenuate the effects of rainfall reduction because of the less interception correlated to them. The future rainfall distribution over the year is also crucial for vegetation water stress. If the current ratio between the growing season and the dormant season rainfall will be kept, trees and grasses will suffer a common increase of water stress, which seems more severe for trees than for grasses. Otherwise, if the rainfall reduction will be concentrated during the wintry periods, as emerges from literature, grasses will have some advantages over the trees species. In this conditions grasses will keep the water stress similar to the nowadays value, while trees will suffer for the lack of the winter recharge increasing their water stress

Business model scaling and growth hacking in digital entrepreneurship

Creating an innovative product and validating an innovative business model may not be enough for digital startups to be competitive. To grow fast and expand globally, digital startups need to innovate their business model during the scaling phase. A pragmatic approach has recently been proposed to support digital entrepreneurs engaging in business-model innovation during the scaling phase (i.e., business-model scaling), a strategy known as growth hacking. However, we know little about its theoretical grounding and how effective growth hacking is, as businesses lack methodologies to assess its effectiveness before committing resources and investments. To fill this gap, we developed a method for supporting business- model scaling through simulation modeling and provided an illustrative application to the PayPal case. By doing so, we contribute to the ongoing debate on scalability in digital entrepreneurship

Ecohydrology in Mediterranean areas: a numerical model to describe growing seasons out of phase with precipitations

International audienceThe probabilistic description of soil moisture dynamics is a relatively new topic in hydrology. The most common ecohydrological models start from a stochastic differential equation describing the soil water balance, where the unknown quantity, the soil moisture, depends both on spaces and time. Most of the solutions existing in literature are obtained in a probabilistic framework and under steady-state condition; even if this last condition allows the analytical handling of the problem, it has considerably simplified the same problem by subtracting generalities from it. The steady-state hypothesis, appears perfectly applicable in arid and semiarid climatic areas like those of African's or middle American's savannas, but it seems to be no more valid in areas with Mediterranean climate, where, notoriously, the wet season foregoes the growing season, recharging water into the soil. This moisture stored at the beginning of the growing season (known as soil moisture initial condition) has a great importance, especially for deep-rooted vegetation, by enabling survival in absence of rainfalls during the growing season and, however, keeping the water stress low during the first period of the same season. The aim of this paper is to analyze the soil moisture dynamics using a simple non-steady numerical ecohydrological model. The numerical model here proposed is able to reproduce soil moisture probability density function, obtained analytically in previous studies for different climates and soils in steady-state conditions; consequently it can be used to compute both the soil moisture time-profile and the vegetation static water stress time-profile in non-steady conditions. Here the differences between the steady-analytical and the non-steady numerical probability density functions are analyzed, showing how the proposed numerical model is able to capture the effects of winter recharge on the soil moisture. The dynamic water stress is also numerically evaluated, implicitly taking into account the soil moisture condition at the beginning of the growing season. It is also shown the role of different annual climatic parameterizations on the soil moisture probability density function and on the vegetation water stress evaluation. The proposed model is applied to a case study characteristic of Mediterranean climate: the watershed of Eleuterio in Sicily (Italy)

A metabolomic approach to animal vitreous humor topographical composition: A pilot study

The purpose of this study was to evaluate the feasibility of a 1H-NMR-based metabolomic approach to explore the metabolomic signature of different topographical areas of vitreous humor (VH) in an animal model. Five ocular globes were enucleated from five goats and immediately frozen at 280uC. Once frozen, three of them were sectioned, and four samples corresponding to four different VH areas were collected: the cortical, core, and basal, which was further divided into a superior and an inferior fraction. An additional two samples were collected that were representative of the whole vitreous body. 1H-NMR spectra were acquired for twenty-three goat vitreous samples with the aim of characterizing the metabolomic signature of this biofluid and identifying whether any site-specific patterns were present. Multivariate statistical analysis (MVA) of the spectral data were carried out, including Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and Partial Least Squares Discriminant Analysis (PLS-DA). A unique metabolomic signature belonging to each area was observed. The cortical area was characterized by lactate, glutamine, choline, and its derivatives, N-acetyl groups, creatine, and glycerol; the core area was characterized by glucose, acetate, and scyllo-inositol; and the basal area was characterized by branched-chain amino acids (BCAA), betaine, alanine, ascorbate, lysine, and myo-inositol. We propose a speculative approach on the topographic role of these molecules that are mainly responsible for metabolic differences among the as-identified areas. 1H-NMR-based metabolomic analysis has shown to be an important tool for investigating the VH. In particular, this approach was able to assess in the samples here analyzed the presence of different functional areas on the basis of a different metabolite distribution.The purpose of this study was to evaluate the feasibility of a 1H-NMR-based metabolomic approach to explore the metabolomic signature of different topographical areas of vitreous humor (VH) in an animal model. Five ocular globes were enucleated from five goats and immediately frozen at -80°C. Once frozen, three of them were sectioned, and four samples corresponding to four different VH areas were collected: the cortical, core, and basal, which was further divided into a superior and an inferior fraction. An additional two samples were collected that were representative of the whole vitreous body. 1H-NMR spectra were acquired for twenty-three goat vitreous samples with the aim of characterizing the metabolomic signature of this biofluid and identifying whether any site-specific patterns were present. Multivariate statistical analysis (MVA) of the spectral data were carried out, including Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and Partial Least Squares Discriminant Analysis (PLS-DA). A unique metabolomic signature belonging to each area was observed. The cortical area was characterized by lactate, glutamine, choline, and its derivatives, N-acetyl groups, creatine, and glycerol; the core area was characterized by glucose, acetate, and scyllo-inositol; and the basal area was characterized by branched-chain amino acids (BCAA), betaine, alanine, ascorbate, lysine, and myo-inositol. We propose a speculative approach on the topographic role of these molecules that are mainly responsible for metabolic differences among the as-identified areas. 1H-NMR-based metabolomic analysis has shown to be an important tool for investigating the VH. In particular, this approach was able to assess in the samples here analyzed the presence of different functional areas on the basis of a different metabolite distribution. © 2014 Locci et al

NGAL and metabolomics: The single biomarker to reveal the metabolome alterations in kidney injury

Conditions affecting kidney structure and function can be considered acute or chronic, depending on their duration. Acute kidney injury (AKI) is one of a number of acute kidney diseases and consists of an abrupt decline in kidney function after an injury leading to functional and structural changes. The widespread availability of enabling technologies has accelerated the rate of novel biomarker discovery for kidney injury. The introduction of novel biomarkers in clinical practice will lead to better preventative and therapeutic interventions and to improve outcomes of critically ill patients. A number of biomarkers of functional change and cellular damage are under evaluation for early diagnosis, risk assessment, and prognosis of AKI. Neutrophil gelatinase-associated lipocalin (NGAL) has emerged as the most promising biomarker of kidney injury; this protein can be measured by commercially available methods in whole blood, plasma, serum, and urine. Concomitantly, metabolomics appears to be a snapshot of the chemical fingerprints identifying specific cellular processes. In this paper, we describe the role of NGAL for managing AKI and the potential benefits deriving from the combined clinical use of urine NGAL and metabolomics in kidney disease