Search results for "Hazard map"

showing 10 items of 10 documents

Thematic vent opening probability maps and hazard assessment of small-scale pyroclastic density currents in the San Salvador volcanic complex (El Sal…

2021

The San Salvador volcanic complex (El Salvador) and Nejapa-Chiltepe volcanic complex (Nicaragua) have been characterized by a significant variability in eruption style and vent location. Densely inhabited cities are built on them and their surroundings, including the metropolitan areas of San Salvador (∼2.4 million people) and Managua (∼1.4 million people), respectively. In this study we present novel vent opening probability maps for these volcanic complexes, which are based on a multi-model approach that relies on kernel density estimators. In particular, we present thematic vent opening maps, i.e., we consider different hazardous phenomena separately, including lava emission, small-scale…

010504 meteorology & atmospheric sciencesLavaPyroclastic rockVolcanismHazard analysis010502 geochemistry & geophysicsHazard mapvolcanic hazard mapping01 natural sciencesEnvironmental technology. Sanitary engineeringGPhreatomagmatic eruptionGeography. Anthropology. Recreation[SDU.STU.VO]Sciences of the Universe [physics]/Earth Sciences/VolcanologyGE1-350TD1-10660105 earth and related environmental sciencesgeographyQE1-996.5geography.geographical_feature_categoryGeologyEnvironmental sciencesThematic mapVolcano13. Climate actionGeneral Earth and Planetary Sciencesvent opening hazard map San Salvador volcano Nejapa-Chiltepe volcanic zoneGeologySeismology
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Probabilistic floodplain hazard mapping: managing uncertainty by using a bivariate approach for flood frequency analysis

2014

Floods are a global problem and are considered the most frequent natural disaster world-wide. Many studies show that the severity and frequency of floods have increased in recent years and underline the difficulty to separate the effects of natural climatic changes and human influences as land management practices, urbanization etc. Flood risk analysis and assessment is required to provide information on current or future flood hazard and risks in order to accomplish flood risk mitigation, to propose, evaluate and select measures to reduce it. Both components of risk can be mapped individually and are affected by multiple uncertainties as well as the joint estimate of flood risk. Major sour…

Flood frequency analysis bivariate approachhazard mappingSettore ICAR/02 - Costruzioni Idrauliche E Marittime E Idrologia
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Assessment of the interpretability of data mining for the spatial modelling of water erosion using game theory

2021

Abstract This study undertook a comprehensive application of 15 data mining (DM) models, most of which have, thus far, not been commonly used in environmental sciences, to predict land susceptibility to water erosion hazard in the Kahorestan catchment, southern Iran. The DM models were BGLM, BGAM, Cforest, CITree, GAMS, LRSS, NCPQR, PLS, PLSGLM, QR, RLM, SGB, SVM, BCART and BTR. We identified 18 factors usually considered as key controls for water erosion, comprising 10 factors extracted from a digital elevation model (DEM), three indices extracted from Landsat 8 images, a sediment connectivity index (SCI) and three other intrinsic factors. Three indicators consisting of MAE, MBE, RMSE, and…

Hazard (logic)Hazard map010504 meteorology & atmospheric sciencesMean squared error04 agricultural and veterinary sciencesCatchment managementcomputer.software_genre01 natural sciencesShapley additive explanationsSupport vector machineErosionTopological index040103 agronomy & agricultureFeature (machine learning)Permutation feature importance measure0401 agriculture forestry and fisheriesSpatial mappingData miningDigital elevation modelGame theorycomputer0105 earth and related environmental sciencesEarth-Surface ProcessesMathematicsInterpretability
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Geo-hazards of the San Vito peninsula offshore (southwestern Tyrrhenian Sea)

2021

Geomorphological Tools for Mapping Natural Hazards.-- 12 pages, 7 figures, supplemental material https://doi.org/10.1080/17445647.2020.1866703.-- Software: The geomorphological main map and the Figures in the text were compiled using GLOBAL MAPPER, Surfer and Quantum-G GIS Software and redesigned to print with Adobe Illustrator

Hazard mappingMarine geo-hazardSettore GEO/02 - Geologia Stratigrafica E Sedimentologica010504 meteorology & atmospheric sciencesGeography Planning and DevelopmentSubmarine canyon010502 geochemistry & geophysics01 natural sciencesSlope failurePeninsulaEarth and Planetary Sciences (miscellaneous)Slope failure0105 earth and related environmental sciencesG3180-9980geographygeography.geographical_feature_categoryContinental shelfLandslidelanguage.human_languageSubmarine canyonOceanographylandslides Marine geo-hazard slope failure southern Tyrrhenian Sea submarine canyonSouthern Tyrrhenian SeaMapslanguageSubmarine pipelineSicilianGeologyLandslides
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Pluvial flooding in urban areas: the role of surface drainage efficiency

2018

Pluvial flooding in urban areas may derive from the limited or temporarily reduced efficiency of surface drainage, even when the underlying storm sewers are properly designed. This study focuses on the impact of uncertainties in the operational condition of the surface drainage system on pluvial flood hazard. The flood propagation model FLURB-2D is implemented on a selected study area in the town of Genoa (Italy). Synthetic hyetographs based on the Chicago and bivariate copula methods with suitable return periods are used as input. While simulating the design rainfall, inlet operational conditions are varied stochastically using a Monte Carlo approach. Results confirm that microtopography h…

Hazard mapsHazard maps; inlet efficiency; modelling; pluvial flooding; surface drainage.Hazard mapsurface drainageHazard maps; Inlet efficiency; Modelling; Pluvial flooding; Surface drainage;Inlet efficiencySettore ICAR/02 - Costruzioni Idrauliche E Marittime E Idrologiainlet efficiencyPluvial floodingpluvial floodingModelling
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Estimation of flood inundation probabilities using global hazard indexes based on hydrodynamic variables

2008

In this paper a new procedure to derive flood hazard maps incorporating uncertainty concepts is presented. The layout of the procedure can be resumed as follows: (1) stochastic input of flood hydrograph modelled through a direct Monte-Carlo simulation based on flood recorded data. Generation of flood peaks and flow volumes has been obtained via copulas, which describe and model the correlation between these two variables independently of the marginal laws involved. The shape of hydrograph has been generated on the basis of a historical significant flood events, via cluster analysis; (2) modelling of flood propagation using a hyperbolic finite element model based on the DSV equations; (3) de…

HydrologyHazard (logic)Flood inundation Flood risk Hazard index Frequency analysis Uncertainty analysis GLUE procedure.Flood mythSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaFlood inundation Flood risk Frequency analysis GLUE procedure Hazard index Uncertainty analysisHazard indexHydrographflood inundation hazard mapFinite element methodGLUE procedureGeophysicsFlow (mathematics)Geochemistry and PetrologyFlood inundationStatistics100-year floodFlood riskUncertainty analysisFlood map uncertainty MonteCarlo approach GLUE methodology hazard index.Frequency analysisGLUEGeologyUncertainty analysis
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Probabilistic Flood Hazard Mapping Using Bivariate Analysis Based on Copulas

2017

This study presents a methodology to extract probabilistic flood hazard maps in an area subject to flood risk, taking into account uncertainties in the definition of design hydrographs. Particularly, the authors present a new method to produce probabilistic inundation and flood hazard maps in which the hydrological input (i.e., synthetic flood design event) to a 2D hydraulic model has been obtained by using a bivariate statistical analysis (copulas) to generate flood peak discharges and volumes. This study also aims to quantify the contribution of boundary conditions’ uncertainty in order to evaluate the effect of this uncertainty source on probabilistic flood hazard mapping. Different comb…

Multivariate statisticsFlood myth0208 environmental biotechnologyCopula (linguistics)Settore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaProbabilistic logicHydrograph02 engineering and technologyBuilding and ConstructionBivariate analysisFlood Risk Mapping020801 environmental engineeringRisk managementFlood hazard mapping100-year floodStatisticsEconometricsEnvironmental scienceFlood risk and hazard mapping; Uncertainty analysis; Copula; Sicily.Uncertainty analysisSafety Risk Reliability and QualityUncertainty analysisCivil and Structural Engineering
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Can uncertainty in flood hazard estimation be reduced by using high detailed topographic data for floodplain modelling?

2011

Floods are considered the most frequent natural disaster world-wide and may have serious socio economic impacts in a community. In order to accomplish flood risk mitigation, flood risk analysis and assessment are required to provide information on current or future flood hazard and risks. Hazard and risk maps involve different data, expertise and effort, depending also on the end-users. More or less advanced deterministic approaches can be used, but intuitively probabilistic approaches seem to be more correct and suited for modelling flood inundation given typical uncertainties. Two very important matters remain open for research: the calibration of hydraulic models (oriented towards the es…

Settore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaRisk map hazard map flood inondation model calibration uncertainty evaluation LISFLOOD-FP model
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Rockfall hazards of Mount Pellegrino area (Sicily, Southern Italy)

2020

A map derived by rockfall analysis at Mount Pellegrino is presented herein. The study area is affected by several phenomena of rockfall which caused numerous damage and a strong social and economic impact. Official reports and maps that give a general assessment of rockfall hazard are available in this respect, however, it would be advisable to provide a more specific cartographic support useful for land management and planning. The drafting of new maps showing the rockfall runout areas is an additional tool that may be used in conjunction with the existing maps as a means of risk mitigation and reduction. On the basis of geological, geomorphological, and geomechanical analysis and exploiti…

geographyG3180-9980geography.geographical_feature_categorySettore ICAR/07 - Geotecnica010504 meteorology & atmospheric sciencesland use planning risk Rockfall hazard map runout areaSettore GEO/04 - Geografia Fisica E Geomorfologiarunout areaGeography Planning and Developmentland use planningLand-use planning010502 geochemistry & geophysics01 natural sciencesMountRockfallrockfall hazard mapMapsEarth and Planetary Sciences (miscellaneous)Physical geographySettore GEO/05 - Geologia ApplicataGeology0105 earth and related environmental sciencesriskJournal of Maps
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Evaluating the Efficiency of Different Regression, Decision Tree, and Bayesian Machine Learning Algorithms in Spatial Piping Erosion Susceptibility U…

2020

Piping erosion is one form of water erosion that leads to significant changes in the landscape and environmental degradation. In the present study, we evaluated piping erosion modeling in the Zarandieh watershed of Markazi province in Iran based on random forest (RF), support vector machine (SVM), and Bayesian generalized linear models (Bayesian GLM) machine learning algorithms. For this goal, due to the importance of various geo-environmental and soil properties in the evolution and creation of piping erosion, 18 variables were considered for modeling the piping erosion susceptibility in the Zarandieh watershed. A total of 152 points of piping erosion were recognized in the study area that…

pipinglcsh:Sdeep learninggeoinformaticshazard mappingnatural hazarderosionsusceptibilityBayesian generalized linear model (Bayesian GLM)lcsh:Agriculturemachine learningspatial modelinggeohazardbig datasupport vector machinedata sciencerandom forestLand
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