Probabilistic floodplain hazard mapping: managing uncertainty by using a bivariate approach for flood frequency analysis

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 sources of uncertainty include statistical analysis of extremes events, definition of hydrological input, channel and floodplain topography representation, the choice of effective hydraulic roughness coefficients. The classical procedure to estimate flood discharge for a chosen probability of exceedance is to deal with a rainfallrunoff model associating to risk the same return period of original rainfall, in accordance with the iso-frequency criterion. Alternatively, a flood frequency analysis to a given record of discharge data is applied, but again the same probability is associated to flood discharges and respective risk. Moreover, since flood peaks and corresponding flood volumes are variables of the same phenomenon, they should be, directly, correlated and, consequently, multivariate statistical analyses must be applied. This study presents an innovative approach to obtain flood hazard maps where hydrological input (synthetic flood design event) to a 2D hydraulic model has been defined by generating flood peak discharges and volumes from: a) a classical univariate approach, b) a bivariate statistical analysis, through the use of copulas. The univariate approach considers flood hydrographs generation by an indirect approach (rainfall-runoff transformation using input rainfall hydrographs derived from IDF curves) and a direct approach (statistical inference on measured flood peaks). In the bivariate approach synthetic hydrographs were generated by means two different approaches: an indirect one, where rainfall were generated by a stochastic bivariate rainfall generator to be entered a distributed conceptual rainfall-runoff model that consisted of a soil moisture routine and a flow routing routine; and a direct one, where stochastic generation of flood peaks and flow volumes have been obtained via copulas, which are capable to describe and model the correlation between these two variables. Finally, to highlight the advantages of the presented approach, probabilistic flood hazard maps (including uncertainty) derived by bivariate models are compared to maps from univariate analysis. The procedure is applied to a real case study located in the southern part of Sicily, Italy, where flood hazard and risk maps have been obtained and compared

A novel approach to flood risk assessment: the Exposure-Vulnerability matrices

The classical approach to flood defence, focused on reducing the probability of flooding through hard defences, has been gradually substituted by flood risk management approach, which accepts the idea of coping with floods, and aims at reducing both probability and the consequences of flooding. In this view, the concept of vulnerability becomes central, such as the (non-structural) measures for its increment. However, the evaluations for the effectiveness and methods of non-structural measure and the vulnerability are less studied, compared to the structural solutions. In this paper, we adopted the Longano catchment in Sicily, Italy, as the case study. The methodology developed in the work enabled a qualitative evaluation of the consequences of floods, based on a crisscross analysis of vulnerability curves and classes of exposure for assets at risk. A GIS-based tool was used to evaluate each element at risk inside an Exposure-Vulnerability matrix. The construction of an E-V matrix allowed a better understanding of the actual situation within a catchment and the effectiveness of non-structural measures for a site. Referring directly to vulnerability can also estimate the possible consequences of an event even in those catchments where the damage data are absent. The instrument proposed can be useful for authorities responsible for development and periodical review of adaptive flood risk management plans

What if quality of damage data is poor: an exposure-vulnerability approach for flood vulnerability assessment

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Flood risk assessment using a novel exposure-vulnerability matrices approach

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On the use of innovative post-event data for reducing uncertainty in calibrating flood propagation models

Hydraulic models for flood propagation description are an essential tool in many fields and are used, for example, for flood hazard and risk assessments, evaluation of flood control measures, etc. However, the calibration of these models is still underdeveloped in contrast to other models like e.g. hydrological models essentially for lacking of specific data, because extreme flood events occur rarely and very rarely are monitored. Very often calibration data, when available, consist of water depths measure in some scattered points. For an inundation event occurred on November 2011 in Sicily, new sources of data were available due to the availability of many videos recorded by ‘common’ people using new technologies. These videos allowed to derive flow velocities and estimate flow discharges in some parts of the inundated area. These pieces of information have been used together with the measured water depths to improve GLUE calibration of a two-dimensional finite element flood propagation model and reduce equifinality in its predictions

Organic pollutants in sea-surface microlayer and aerosol in thecoastal environment of Leghorn—(Tyrrhenian Sea)

The levels of dissolved and particle-associated n-alkanes, alkylbenzenes, phthalates, PAHs, anionic surfactants and surfactant fluorescent organic matter ŽSFOM. were measured in sea-surface microlayer ŽSML. and sub-surface water ŽSSL. samples collected in the Leghorn marine environment in September and October 1999. Nine stations, located in the Leghorn harbour and at increasing distances from the Port, were sampled three times on the same day. At all the stations, SML concentrations of the selected organic compounds were significantly higher than SSL values and the enrichment factors ŽEFsSML concentrationrSSL concentration. were greater in the particulate phase than in the dissolved phase. SML concentrations varied greatly among the sampling sites, the highest levels Žn-alkanes 3674 mgrl, phthalates 177 mgrl, total PAHs 226 mgrl. being found in the particulate phase in the Leghorn harbour. To improve the knowledge on pollutant exchanges between sea-surface waters and atmosphere, the validity of spray drop adsorption model ŽSDAM. was verified for SFOM, surface-active agents, such as phthalates, and compounds which can interact with SFOM, such as n-alkanes and PAHs. q2001 Elsevier Science B.V. All rights reserved

Advances in estrogen receptor biology: prospects for improvements in targeted breast cancer therapy

Estrogen receptor (ER) has a crucial role in normal breast development and is expressed in the most common breast cancer subtypes. Importantly, its expression is very highly predictive for response to endocrine therapy. Current endocrine therapies for ER-positive breast cancers target ER function at multiple levels. These include targeting the level of estrogen, blocking estrogen action at the ER, and decreasing ER levels. However, the ultimate effectiveness of therapy is limited by either intrinsic or acquired resistance. Identifying the factors and pathways responsible for sensitivity and resistance remains a challenge in improving the treatment of breast cancer. With a better understanding of coordinated action of ER, its coregulatory factors, and the influence of other intracellular signaling cascades, improvements in breast cancer therapy are emerging

Derivation of flood frequency curves in poorly gauged Mediterranean catchments using a simple stochastic hydrological rainfall-runoff model

In this paper a Monte Carlo procedure for deriving frequency distributions of peak flows using a semi-distributed stochastic rainfall-runoff model is presented. The rainfall-runoff model here used is very simple one, with a limited number of parameters and practically does not require any calibration, resulting in a robust tool for those catchments which are partially or poorly gauged.The procedure is based on three modules: a stochastic rainfall generator module, a hydrologic loss module and a flood routing module. In the rainfall generator module the rainfall storm, i.e. the maximum rainfall depth for a fixed duration, is assumed to follow the two components extreme value (TCEV) distribution whose parameters have been estimated at regional scale for Sicily. The catchment response has been modelled by using the Soil Conservation Service-Curve Number (SCS-CN) method, in a semi-distributed form, for the transformation of total rainfall to effective rainfall and simple form of IUH for the flood routing. Here, SCS-CN method is implemented in probabilistic form with respect to prior-to-storm conditions, allowing to relax the classical iso-frequency assumption between rainfall and peak flow. The procedure is tested on six practical case studies where synthetic FFC (flood frequency curve) were obtained starting from model variables distributions by simulating 5000 flood events combining 5000 values of total rainfall depth for the storm duration and AMC (antecedent moisture conditions) conditions. The application of this procedure showed how Monte Carlo simulation technique can reproduce the observed flood frequency curves with reasonable accuracy over a wide range of return periods using a simple and parsimonious approach, limited data input and without any calibration of the rainfall-runoff model