Identification of coherent flood regions across Europe by using the longest streamflow records

This study compiles a new dataset, consisting of the longest available flow series from across Europe, and uses it to study the spatial and temporal clustering of flood events across the continent. Hydrological series at 102 gauging stations were collected from 25 European countries. Five geographically distinct large-scale homogeneous regions are identified: (i) an Atlantic region, (ii) a Continental region, (iii) a Scandinavian region, (iv) an Alpine region, and (v) a Mediterranean region. The months with a higher likelihood of flooding were identified in each region. The analysis of the clustering of annual counts of floods revealed an over-dispersion in the Atlantic and Continental regions, forming flood-rich and flood-poor periods, as well as an under-dispersion in the Scandinavian region that points to a regular pattern of flood occurrences at the inter-annual scale. The detection of trends in flood series is attempted by basing it on the identified regions, interpreting the results at a regional scale and for various time periods: 1900-1999; 1920-1999; 1939-1998 and 1956-1995. The results indicate that a decreasing trend in the magnitude of floods was observed mainly in the Continental region in the period 1920-1999 with 22% of the catchments revealing such a trend, as well as a decreasing trend in the timing of floods in the Alpine region in the period 1900-1999 with 75% of the catchments revealing this trend. A mixed pattern of changes in the frequency of floods over a threshold and few significant changes in the timing of floods were detected

Impact of Leaf Removal, Applied Before and After Flowering, on Anthocyanin, Tannin, and Methoxypyrazine Concentrations in ‘Merlot’ (Vitis viniferaL.) Grapes and Wines

7siThe development and accumulation of secondary metabolites in grapes determine wine color, taste, and aroma. This study aimed to investigate the effect of leaf removal before flowering, a practice recently introduced to reduce cluster compactness and Botrytis rot, on anthocyanin, tannin, and methoxypyrazine concentrations in Merlot' grapes and wines. Leaf removal before flowering was compared with leaf removal after flowering and an untreated control. No effects on tannin and anthocyanin concentrations in grapes were observed. Both treatments reduced levels of 3-isobutyl-2-methoxypyrazine (IBMP) in the grapes and the derived wines, although the after-flowering treatment did so to a greater degree in the fruit specifically. Leaf removal before flowering can be used to reduce cluster compactness, Botrytis rot, and grape and wine IBMP concentration and to improve wine color intensity but at the expense of cluster weight and vine yield. Leaf removal after flowering accomplishes essentially the same results without loss of yield. © 2016 American Chemical Society.reservedmixedSivilotti, Paolo; Herrera, Jose Carlos; Lisjak, Klemen; Baša Česnik, Helena; Sabbatini, Paolo; Peterlunger, Enrico; Castellarin, Simone DiegoSivilotti, Paolo; Herrera, Jose Carlos; Lisjak, Klemen; Baša Česnik, Helena; Sabbatini, Paolo; Peterlunger, Enrico; Castellarin, Simone Dieg

Non-coding-regulatory regions of human brain genes delineated by bacterial artificial chromosome knock-in mice

Background The next big challenge in human genetics is understanding the 98% of the genome that comprises non-coding DNA. Hidden in this DNA are sequences critical for gene regulation, and new experimental strategies are needed to understand the functional role of gene-regulation sequences in health and disease. In this study, we build upon our HuGX (\u27high-throughput human genes on the X chromosome’) strategy to expand our understanding of human gene regulation in vivo. Results In all, ten human genes known to express in therapeutically important brain regions were chosen for study. For eight of these genes, human bacterial artificial chromosome clones were identified, retrofitted with a reporter, knocked single-copy into the Hprt locus in mouse embryonic stem cells, and mouse strains derived. Five of these human genes expressed in mouse, and all expressed in the adult brain region for which they were chosen. This defined the boundaries of the genomic DNA sufficient for brain expression, and refined our knowledge regarding the complexity of gene regulation. We also characterized for the first time the expression of human MAOA and NR2F2, two genes for which the mouse homologs have been extensively studied in the central nervous system (CNS), and AMOTL1 and NOV, for which roles in CNS have been unclear. Conclusions We have demonstrated the use of the HuGX strategy to functionally delineate non-coding-regulatory regions of therapeutically important human brain genes. Our results also show that a careful investigation, using publicly available resources and bioinformatics, can lead to accurate predictions of gene expression

Frequency and Spatial Variability of European Record Floods

Regional envelope curves (RECs) have been used to characterize the flooding potential of regions worldwide. However, a comprehensive assessment for Europe is still missing. In this study we use the largest European flood database to quantify the magnitude of record floods, their dependence on catchment size, and the amount of available independent information, which is needed for estimatinig the REC's exceedance probability. We propose a framework for estimating REC parameters across large areas, consisting in partitioning the domain according to the observation density and estimating the REC slope through quantile regression. The results show that the REC parameters vary substantially across Europe. The envelope unit flood associated with a catchment area of 1,000 km2 varies between 0.1 and 6 m3s−1km−2 and is highest in Mediterranean and Alpine areas and lowest in central-eastern Europe. The slope of the envelope varies between 0 and −1 and is larger in Southern Europe than in Northern Europe. These differences are explained by steeper landscape in mountaineous regions and localized short duration storms producing large floods in small catchments in the Mediterranean, whose intensities are larger than in other parts of Europe. Based on the framework of probabilistic envelope curves we show that, despite the uneven observation density, the obtained RECs are associated with comparable exceedance probabilities

Machine-learning blends of geomorphic descriptors: value and limitations for flood hazard assessment across large floodplains

Recent literature shows several examples of simplified approaches that perform flood hazard (FH) assessment and mapping across large geographical areas on the basis of fast-computing geomorphic descriptors. These approaches may consider a single index (univariate) or use a set of indices simultaneously (multivariate). What is the potential and accuracy of multivariate approaches relative to univariate ones? Can we effectively use these methods for extrapolation purposes, i.e., FH assessment outside the region used for setting up the model? Our study addresses these open problems by considering two separate issues: (1) mapping flood-prone areas and (2) predicting the expected water depth for a given inundation scenario. We blend seven geomorphic descriptors through decision tree models trained on target FH maps, referring to a large study area (∼ 105 km2). We discuss the potential of multivariate approaches relative to the performance of a selected univariate model and on the basis of multiple extrapolation experiments, where models are tested outside their training region. Our results show that multivariate approaches may (a) significantly enhance flood-prone area delineation (accuracy: 92%) relative to univariate ones (accuracy: 84%), (b) provide accurate predictions of expected inundation depths (determination coefficient ∼0.7), and (c) produce encouraging results in extrapolation

In situ observations of the atomistic mechanisms of Ni catalyzed low temperature graphene growth.

The key atomistic mechanisms of graphene formation on Ni for technologically relevant hydrocarbon exposures below 600 °C are directly revealed via complementary in situ scanning tunneling microscopy and X-ray photoelectron spectroscopy. For clean Ni(111) below 500 °C, two different surface carbide (Ni2C) conversion mechanisms are dominant which both yield epitaxial graphene, whereas above 500 °C, graphene predominantly grows directly on Ni(111) via replacement mechanisms leading to embedded epitaxial and/or rotated graphene domains. Upon cooling, additional carbon structures form exclusively underneath rotated graphene domains. The dominant graphene growth mechanism also critically depends on the near-surface carbon concentration and hence is intimately linked to the full history of the catalyst and all possible sources of contamination. The detailed XPS fingerprinting of these processes allows a direct link to high pressure XPS measurements of a wide range of growth conditions, including polycrystalline Ni catalysts and recipes commonly used in industrial reactors for graphene and carbon nanotube CVD. This enables an unambiguous and consistent interpretation of prior literature and an assessment of how the quality/structure of as-grown carbon nanostructures relates to the growth modes.L.L.P. acknowledges funding from Area di Ricerca Scientifica e Tecnologica of Trieste and from MIUR through Progetto Strategico NFFA. C.A. acknowledges support from CNR through the ESF FANAS project NOMCIS. C.A. and C.C. acknowledge financial support from MIUR (PRIN 2010-2011 nº 2010N3T9M4). S.B. acknowledges funding from ICTP TRIL program. S.H. acknowledges funding from ERC grant InsituNANO (n°279342). R.S.W. acknowledges funding from EPSRC (Doctoral training award), and the Nano Science & Technology Doctoral Training Centre Cambridge (NanoDTC). The help of C. Dri and F. Esch (design) and P. Bertoch and F. Salvador (manufacturing) in the realization of the high temperature STM sample holder is gratefully acknowledged. We acknowledge the Helmholtz-Zentrum-Berlin Electron storage ring BESSY II for provision of synchrotron radiation at the ISISS beamline and we thank the BESSY staff for continuous support of our experiments.This is the accepted manuscript. The final version is available from ACS at http://pubs.acs.org/doi/abs/10.1021/nn402927q

Colour assessment outcomes – a new approach to grading the severity of color vision loss

INTRODUCTION: Recent studies have shown that a significant percentage of subjects with anomalous, congenital trichromacy can perform the suprathreshold, colour-related tasks encountered in many occupations with the same accuracy as normal trichromats. In the absence of detailed, occupation-specific studies, an alternative approach is to make use of new findings and the statistical outcomes of past practices that have been considered safe to produce graded, justifiable categories of colour vision that can be enforced. METHODS: We analyzed traditional color assessment outcomes and measured severity of colour vision loss using the CAD test in 1363 subjects (336 normals, 705 deutan, 319 protan and 3 tritan). The severity of colour vision loss was measured in each subject and statistical, pass / fail outcomes established for each of the most commonly used, conventional colour assessment tests and protocols. RESULTS: The correlation between the number of Ishihara (IH) test plates subjects fail and the severity of RG colour vision loss was very poor. The 38 plates IH test has high sensitivity when no errors are allowed (i.e., only 0.71% deutans and 0.63% protans pass). Protocols based on zero errors are uncommon since 18.15% of normal trichromats fail. The most common protocols employ either the 24 or the 14 plates editions with two or less errors. These protocols pass almost all normal trichromats, but the deutans and some protans that also pass (when two or less errors are allowed) can be severely deficient. This is simply because the most challenging plates have not been included in the 24 and 14 plates editions. As a result, normals no longer fail, but the deutans and protans that pass have more severe loss of colour vision since they fail less challenging plates. The severity of colour vision loss was measured in each subject and statistical, pass / fail outcomes established for each of the most commonly used, conventional colour assessment tests and protocols. DISCUSSION: Historical evidence and new findings that relate severity of loss to the effective use of colour signals in a number of tasks provide the basis for a new colour grading system based on six categories. A single colour assessment test is needed to establish the applicant’s Colour Vision category which can range from ‘supernormal’ (CV0), for the most stringent, colour-demanding tasks, to ‘severe colour deficiency’, when red / green colour vision is either absent or extremely weak (CV5)

Large-scale stochastic flood hazard analysis applied to the Po River

Reliable hazard analysis is crucial in the flood risk management of river basins. For the floodplains of large, developed rivers, flood hazard analysis often needs to account for the complex hydrology of multiple tributaries and the potential failure of dikes. Estimating this hazard using deterministic methods ignores two major aspects of large-scale risk analysis: the spatial–temporal variability of extreme events caused by tributaries, and the uncertainty of dike breach development. Innovative stochastic methods are here developed to account for these uncertainties and are applied to the Po River in Italy. The effects of using these stochastic methods are compared against deterministic equivalents, and the methods are combined to demonstrate applications for an overall stochastic hazard analysis. The results show these uncertainties can impact extreme event water levels by more than 2 m at certain channel locations, and also affect inundation and breaching patterns. The combined hazard analysis allows for probability distributions of flood hazard and dike failure to be developed, which can be used to assess future flood risk management measures

RIO SOLIETTE (HAITI): AN INTERNATIONAL INITIATIVE FOR FLOOD-HAZARD ASSESSMENT AND MITIGATION

Natural catastrophic events are one of most critical aspects for health and economy all around the world. However, the impact in a poor region can impact more dramatically than in others countries. Isla Hispaniola (Haiti and the Dominican Republic), one of the poorest regions of the planet, has repeatedly been hit by catastrophic natural disasters that caused incalculable human and economic losses. After the catastrophic flood event occurred in the basin of River Soliette on May 24th, 2004, the General Direction for Development and Cooperation of the Italian Department of Foreign Affairs funded an international cooperation initiative (ICI) coordinated by the University of Bologna, that involved Haitian and Dominican institutions.Main purpose of the ICI was hydrological and hydraulic analysis of the May 2004 flood event aimed at formulating a suitable and affordable flood risk mitigation plan, consisting of structural and non-structural measures. In this contest, a topographic survey was necessary to realize the hydrological model and to improve the knowledge in some areas candidates to be site for mitigation measures.To overcome the difficulties arising from the narrowness of funds, surveyors and limited time available for the survey, only GPS technique have been used, both for framing aspects (using PPP approach), and for geometrical survey of the river by means of river cross-sections and detailed surveys in two areas (RTK technique). This allowed us to reconstruct both the river geometry and the DTM’s of two expansion areas (useful for design hydraulic solutions for mitigate flood-hazard risk)

Testing empirical and synthetic flood damage models: The case of Italy

Flood risk management generally relies on economic assessments performed by using flood loss models of different complexity, ranging from simple univariable models to more complex multivariable models. The latter account for a large number of hazard, exposure and vulnerability factors, being potentially more robust when extensive input information is available. We collected a comprehensive data set related to three recent major flood events in northern Italy (Adda 2002, Bacchiglione 2010 and Secchia 2014), including flood hazard features (depth, velocity and duration), building characteristics (size, type, quality, economic value) and reported losses. The objective of this study is to compare the performances of expert-based and empirical (both uni- and multivariable) damage models for estimating the potential economic costs of flood events to residential buildings. The performances of four literature flood damage models of different natures and complexities are compared with those of univariable, bivariable and multivariable models trained and tested by using empirical records from Italy. The uni- and bivariable models are developed by using linear, logarithmic and square root regression, whereas multivariable models are based on two machine-learning techniques: random forest and artificial neural networks. Results provide important insights about the choice of the damage modelling approach for operational disaster risk management. Our findings suggest that multivariable models have better potential for producing reliable damage estimates when extensive ancillary data for flood event characterisation are available, while univariable models can be adequate if data are scarce. The analysis also highlights that expert-based synthetic models are likely better suited for transferability to other areas compared to empirically based flood damage models