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An operational framework for flood risk assessment in ungauged urban areas is developed within the implementation of the EU Floods Directive in Greece, and demonstrated for Volos metropolitan area, central Greece, which is frequently affected by intense storms causing fluvial flash floods. A scenario-based approach is applied, accounting for uncertainties of key modeling aspects. This comprises extreme rainfall analysis, resulting in spatially-distributed Intensity-Duration-Frequency (IDF) relationships and their confidence intervals, and flood simulations, through the SCS-CN method and the unit hydrograph theory, producing design hydrographs at the sub-watershed scale, for several soil moisture conditions. The propagation of flood hydrographs and the mapping of inundated areas are employed by the HEC-RAS 2D model, with flexible mesh size, by representing the resistance caused by buildings through the local elevation rise method. For all hydrographs, upper and lower estimates on water depths, flow velocities and inundation areas are estimated, for varying roughness coefficient values. The methodology is validated against the flood event of the 9th October 2006, using observed flood inundation data. Our analyses indicate that although typical engineering practices for ungauged basins are subject to major uncertainties, the hydrological experience may counterbalance the missing information, thus ensuring quite realistic outcomes.

Abstract. Probabilistic flood inundation mapping is performed and analysed at the ungauged Xerias stream reach, Volos, Greece. The study evaluates the uncertainty introduced by the roughness coefficient values on hydraulic models in flood inundation modelling and mapping. The wellestablished one-dimensional (1-D) hydraulic model, HEC-RAS is selected and linked to Monte-Carlo simulations of hydraulic roughness. Terrestrial Laser Scanner data have been used to produce a high quality DEM for input data uncertainty minimisation and to improve determination accuracy on stream channel topography required by the hydraulic model. Initial Manning's n roughness coefficient values are based on pebble count field surveys and empirical formulas. Various theoretical probability distributions are fitted and evaluated on their accuracy to represent the estimated roughness values. Finally, Latin Hypercube Sampling has been used for generation of different sets of Manning roughness values and flood inundation probability maps have been created with the use of Monte Carlo simulations. Historical flood extent data, from an extreme historical flash flood event, are used for validation of the method. The calibration process is based on a binary wet-dry reasoning with the use of Median Absolute Percentage Error evaluation metric. The results show that the proposed procedure supports probabilistic flood hazard mapping at ungauged rivers and provides water resources managers with valuable information for planning and implementing flood risk mitigation strategies.

Providing accurate predictions of the thermodynamic properties of highly polar and hydrogen bonding compounds and their mixtures is challenging from a theoretical perspective. The combination of an equation of state (EoS) based on the statistical associating fluid theory (SAFT) with a group contribution (GC) methodology offers both accuracy and predictive capability for the thermodynamic properties of mixtures. In our current work, the SAFT-γ Mie equation of state is used to capture the underlying complexity of systems in which specific interactions (e.g., hydrogen bonding, dipolar interactions, chemical association) play an important role, by incorporating highly versatile association-site schemes to model mixtures in which unlike induced association interactions occur; this is done by assigning to the functional groups a number of association sites that are inactive in the pure fluid, but become active in certain mixtures. We refer to this type of association mechanism as "unlike induced" association and to the sites involved in this interaction as "unlike induced" association sites. The concept of unlike induced association sites is applied here to develop reliable SAFT-γ Mie group contribution models to describe the properties of acetone, alkyl carboxylic acids, and their mixtures with water and n-alkanes. The parameter table of available SAFT-γ Mie models is expanded to incorporate the corresponding group interaction parameters for acetone, which is treated as a molecular group, the carboxyl group COOH, and their unlike interaction group parameters with water, and the methyl CH 3 , methanediyl CH 2 , and methanetriyl CH alkyl groups. In particular, one unlike induced site is used with the acetone model to mediate hydrogen-bonding of the acetone oxygen in mixtures containing hydrogen-bond donors, and two pairs of unlike induced sites are included on the COOH group to mediate hydrogen-bond formation in mixtures of carboxylic acids and hydrogen-bond donors. The models developed allow for the successful description of the complex fluid-phase behaviour of the relevant binary and ternary mixtures, including accurate predictions of systems which have not been used to determine the model parameters.