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

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

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

Safer_RAIN: A DEM-based hierarchical filling-&-spilling algorithm for pluvial flood hazard assessment and mapping across large urban areas

The increase in frequency and intensity of extreme precipitation events caused by the changing climate (e.g., cloudbursts, rainstorms, heavy rainfall, hail, heavy snow), combined with the high population density and concentration of assets, makes urban areas particularly vulnerable to pluvial flooding. Hence, assessing their vulnerability under current and future climate scenarios is of paramount importance. Detailed hydrologic-hydraulic numerical modeling is resource intensive and therefore scarcely suitable for performing consistent hazard assessments across large urban settlements. Given the steadily increasing availability of LiDAR (Light Detection And Ranging) high-resolution DEMs (Digital Elevation Models), several studies highlighted the potential of fast-processing DEM-based methods, such as the Hierarchical Filling-&-Spilling or Puddle-to-Puddle Dynamic Filling-&-Spilling Algorithms (abbreviated herein as HFSAs). We develop a fast-processing HFSA, named Safer_RAIN, that enables mapping of pluvial flooding in large urban areas by accounting for spatially distributed rainfall input and infiltration processes through a pixel-based Green-Ampt model. We present the first applications of the algorithm to two case studies in Northern Italy. Safer_RAIN output is compared against ground evidence and detailed output from a two-dimensional (2D) hydrologic and hydraulic numerical model (overall index of agreement between Safer_RAIN and 2D benchmark model: sensitivity and specificity up to 71% and 99%, respectively), highlighting potential and limitations of the proposed algorithm for identifying pluvial flood-hazard hotspots across large urban environments

Electro-chemical deposition of zinc oxide nanostructures by using two electrodes

One of the most viable ways to grow nanostructures is electro deposition. However, most electrodeposited samples are obtained by three-electrode electrochemical cell. We successfully use a much simpler two-electrode cell to grow different ZnO nanostructures from common chemical reagents. Concentration, pH of the electrolytes and growth parameters like potentials at the electrodes, are tailored to allow fast growth without complexity. Morphology and surface roughness are investigated by Scanning Electron and Air Force Microscopy (SEM and AFM) respectively, crystal structure by X-Ray Diffraction measurements (XRD) and ZnO stoichiometry by core level photoemission spectroscopy (XPS)

Fruit ripening in Vitis vinifera: spatiotemporal relationships among turgor, sugar accumulation, and anthocyanin biosynthesis

This study reports the first observations indicating the spatiotemporal relationships among genetic and physiological aspects of ripening in the berry of Vitis vinifera. At the onset of ripening in the red flesh variety Alicante Bouschet, colour development began in the flesh at the stylar end of the fruit and progressed toward the pedicel end flesh and into the skin. Tissue solute potential and cell turgor also decreased first in the flesh. The decrease in flesh solute potential was due to accumulation of sugars, glucose and fructose, an accumulation that is integral to ripening. Expression of the anthocyanin biosynthesis-related genes VvMybA and VvUFGT was linearly related to the decrease in solute potential. Expression of VvMybA, and to a lesser extent VvUFGT, was correspondingly low in green tissue, higher in the red, stylar end flesh of berries beginning to ripen, and greatest in red berries. In contrast, expression of the abscisic acid biosynthesis-related genes VvNCED1 and VvNCED2 was not correlated with the other spatiotemporal aspects of the onset of ripening. These results, together with earlier work showing that sugar accumulation and acid loss also begin in the stylar flesh in other varieties, indicate that ripening in the grape berry originates in the stylar end flesh

Expansion and subfunctionalisation of flavonoid 3',5'-hydroxylases in the grapevine lineage

<p>Abstract</p> <p>Background</p> <p>Flavonoid 3',5'-hydroxylases (F3'5'Hs) and flavonoid 3'-hydroxylases (F3'Hs) competitively control the synthesis of delphinidin and cyanidin, the precursors of blue and red anthocyanins. In most plants, <it>F3'5'H </it>genes are present in low-copy number, but in grapevine they are highly redundant.</p> <p>Results</p> <p>The first increase in <it>F3'5'H </it>copy number occurred in the progenitor of the eudicot clade at the time of the γ triplication. Further proliferation of <it>F3'5'H</it>s has occurred in one of the paleologous loci after the separation of Vitaceae from other eurosids, giving rise to 15 paralogues within 650 kb. Twelve reside in 9 tandem blocks of ~35-55 kb that share 91-99% identity. The second paleologous <it>F3'5'H </it>has been maintained as an orphan gene in grapevines, and lacks orthologues in other plants. Duplicate <it>F3'5'H</it>s have spatially and temporally partitioned expression profiles in grapevine. The orphan <it>F3'5'H </it>copy is highly expressed in vegetative organs. More recent duplicate <it>F3'5'H</it>s are predominately expressed in berry skins. They differ only slightly in the coding region, but are distinguished in the structure of the promoter. Differences in <it>cis</it>-regulatory sequences of promoter regions are paralleled by temporal specialisation of gene transcription during fruit ripening. Variation in anthocyanin profiles consistently reflects changes in the <it>F3'5'H </it>mRNA pool across different cultivars. More <it>F3'5'H </it>copies are expressed at high levels in grapevine varieties with 93-94% of 3'5'-OH anthocyanins. In grapevines depleted in 3'5'-OH anthocyanins (15-45%), fewer <it>F3'5'H </it>copies are transcribed, and at lower levels. Conversely, only two copies of the gene encoding the competing F3'H enzyme are present in the grape genome; one copy is expressed in both vegetative and reproductive organs at comparable levels among cultivars, while the other is transcriptionally silent.</p> <p>Conclusions</p> <p>These results suggest that expansion and subfunctionalisation of <it>F3'5'H</it>s have increased the complexity and diversification of the fruit colour phenotype among red grape varieties.</p

Biosynthesis and Cellular Functions of Tartaric Acid in Grapevines

Tartaric acid (TA) is an obscure end point to the catabolism of ascorbic acid (Asc). Here, it is proposed as a “specialized primary metabolite”, originating from carbohydrate metabolism but with restricted distribution within the plant kingdom and lack of known function in primary metabolic pathways. Grapes fall into the list of high TA-accumulators, with biosynthesis occurring in both leaf and berry. Very little is known of the TA biosynthetic pathway enzymes in any plant species, although recently some progress has been made in this space. New technologies in grapevine research such as the development of global co-expression network analysis tools and genome-wide association studies, should enable more rapid progress. There is also a lack of information regarding roles for this organic acid in plant metabolism. Therefore this review aims to briefly summarize current knowledge about the key intermediates and enzymes of TA biosynthesis in grapes and the regulation of its precursor, ascorbate, followed by speculative discussion around the potential roles of TA based on current knowledge of Asc metabolism, TA biosynthetic enzymes and other aspects of fruit metabolism

Ponderación de la información generada en la Estación Experimental Agropecuaria Oliveros del INTA (INTA EEA Oliveros) mediante el proceso analítico jerárquico

En el siglo XXI, el subsistema de conocimiento científico-tecnológico se convirtió en el principal componente del capital cultural de un país viabilizando el desarrollo socioeconómico y la potencialidad de los países desarrollados. El Instituto Nacional de Tecnología Agropecuaria (INTA) es un organismo de ciencia y tecnología de Argentina entre cuyos objetivos está la generación y transferencia de conocimiento científico al sector agropecuario. Dicha información se genera en estaciones experimentales agropecuarias e institutos de investigación que lo integran y que abordan los problemas del sector en distintas regiones el país. Los sectores destinados a la investigación, experimentación y transferencia del conocimiento tienen como producto las publicaciones científicas, manuales, informes técnicos, cursos y talleres entre otros. Los objetivos de este estudio fueron: 1) clasificar la formas de presentación del conocimiento producido en la EEA Oliveros, así como seleccionar y definir los criterios y alternativas requeridos en la ponderación de este y 2) aplicar la ponderación a la producción de conocimientos de la EEA Oliveros para el año 2014. Para clasificar, agrupar y ponderar el producto de la investigación/extensión generada por el INTA Oliveros se reunió un equipo de investigadores y extensionistas de la institución. El Proceso Analítico Jerárquico (AHP) fue utilizado para el presente estudio. Este permite, a partir de valoraciones preasignadas, priorizar un conjunto de elementos, según los juicios, y preferencias de los individuos del equipo, adoptando un valor consensuado. Los resultados mostraron que los productos generados como información original (IO=revistas con y sin referato, así como presentación a congresos) representaron el 60.8% de la producción de conocimiento total; la información elaborada (IE=libros, capítulos libros, manuales y producción audiovisual) representó el 10.8% y la transferencia de conocimiento (TC=cursos, jornadas y disertaciones), el 28.4%. La metodología empleada resultó útil para ponderar la generación de conocimiento. Estos resultados pueden ser utilizados para comparar la producción de conocimiento entre períodos, entre unidades, consensuando los criterios con un equipo representativo de las estas, e incluso para ser utilizadas como insumo en análisis o evaluaciones de otras temáticas. De todas maneras, es aconsejable revisar y adecuar periódicamente los criterios y alternativas seleccionadas para acompañar los posibles cambios en enfoques y desarrollos que ocurren en investigación, según los períodos que se van atravesando.The scientific and technological knowledge subsystem becomes one of the main components of a country cultural capital, fostering its economic development. The National Institute of Agricultural Technology (INTA) is a science and technology body in Argentina whose objectives include the generation and transfer of scientific knowledge to the agricultural sector through experimental stations and research institutes located in different regions of the country. Research, experimentation and knowledge transfer produce scientific publications, manuals, technical reports, courses, congress presentations and workshops. The objectives of this study were: 1) to classify the way of featuring knowledge production in the EEA Oliveros, as well as to select and define the criteria and alternatives used for weighting (without seeking to qualify it) the original and elaborate knowledge produced, and 2) to apply the weighting to the EEA Oliveros’ knowledge production for the year 2014. A team of researchers and extensionists was gathered to classify, group and weight the research/extension produced by the EEA Oliveros. The Analytic Hierarchy Process (AHP) method was used for this study. It allows to prioritize a set of elements based on an established valuation scale, according to the team individuals’ judge, preferences and agreement. The results showed that the products generated as original information (OI=journals with and without peer review and congress presentation) accounted for 60.8% of total knowledge production; elaborated information (EI=books, book’s chapters, manuals and audiovisual production) 10.8% and the knowledge transfer (KT=courses, seminars and lectures) 28.4%.The methodology was useful to weigh the generation of knowledge. These results can be used to compare the production of knowledge between periods, between INTA units by the consensus of the criteria used, and even it can be used as input for analysis or evaluation of other issues. However, it is desirable to periodically review and adjust the selected criteria and alternatives to join the possible research changes along the periods that go through on approaches and developments.EEA OliverosFil: Rotolo, Gloria Claudia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; ArgentinaFil: Milo Vaccaro, Marcelo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; ArgentinaFil: Hoyos Mallqui, M. Pontificia Universidad Católica Argentina. Campus Rosario. Facultad de Química e Ingeniería; ArgentinaFil: Bacigaluppo, Silvina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; ArgentinaFil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; ArgentinaFil: Castellarin, Julio Manuel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentin

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.</p