Stochastic weather generators combined with hydrological models have been proposed for continuous synthetic simulation to estimate return periods of extreme floods. Yet, this approach relies upon the length and spatial distribution of the precipitation input data series, which often are scarce, especially in arid and semiarid regions. In this work, we present a new approach for the estimation of extreme floods based on the continuous synthetic simulation method supported with inputs of (a) a regional study of extreme precipitation to improve the calibration of the weather generator (GWEX), and (b) non-systematic flood information (i.e., historical information and/or palaeoflood records) for the validation of the generated discharges with a fully distributed hydrological model (TETIS). The results showed that this complementary information of extremes allowed for a more accurate implementation of both the weather generator and the hydrological model. This, in turn, improved the flood quantile estimates, especially for those associated with return periods higher than 50 years but also for higher quantiles (up to approximately 500 years). Therefore, it has been proved that continuous synthetic simulation studies focused on the estimation of extreme floods should incorporate a generalized representation of regional extreme rainfall and/or non-systematic flood data, particularly in regions with scarce hydrometeorological records.

No abstract

Excess surface water on roadways due to storm events can cause hazardous scenarios for traffic. The design of efficient road and transportation facility drainage systems is a major challenge. Different approaches to limit excess surface water can be found in the drainage design standards of different countries. This document presents a method based on hydraulic numerical simulation and the assessment of grate inlet efficiency using the Iber model. The method is suitable for application to design criteria according to the regulations of different countries. The presented method facilitates sensitivity analyses of the performance of different scupper dispositions through the total control of the hydraulic behavior of each of the grate inlets considered in each scenario. The detailed hydraulic information can be the basis of different solution comparisons to make better decisions and obtain solutions that maximize efficiency.

<p>Una adecuada caracterización de las avenidas extremas es clave para el correcto diseño de las infraestructuras y la estimación del riesgo de inundación de una determinada área. Sin embargo, la escasa longitud de los registros pluviométricos y de aforos unido con la baja probabilidad de ocurrencia de este tipo de eventos hace que, a día de hoy, su adecuada estimación presente todavía grandes dificultades. Este trabajo presenta una metodología para la estimación de las avenidas extremas mediante la generación continua de series de precipitación a través de generadores meteorológicos y la integración de información de varios tipos (sistemática y no sistemática). Los resultados obtenidos en el caso de estudio, la Rambla de la Viuda, indican que el uso conjunto de series sintéticas continúas generadas mediante un generador meteorológico estocástico, un modelo hidrológico y la integración de registros sistemáticos y no sistemáticos reduce la incertidumbre de la estimación de avenidas extremas.</p>

Stochastic weather generators combined with hydrological models have been proposed for continuous synthetic simulation to estimate return periods of extreme floods. Yet, this approach relies upon the length and spatial distribution of the precipitation input data series, which often are scarce, especially in arid and semiarid regions. In this work, we present a new approach for the estimation of extreme floods based on the continuous synthetic simulation method supported with inputs of (a) a regional study of extreme precipitation to improve the calibration of the weather generator (GWEX), and (b) non-systematic flood information (i.e., historical information and/or palaeoflood records) for the validation of the generated discharges with a fully distributed hydrological model (TETIS). The results showed that this complementary information of extremes allowed for a more accurate implementation of both the weather generator and the hydrological model. This, in turn, improved the flood quantile estimates, especially for those associated with return periods higher than 50 years but also for higher quantiles (up to approximately 500 years). Therefore, it has been proved that continuous synthetic simulation studies focused on the estimation of extreme floods should incorporate a generalized representation of regional extreme rainfall and/or non-systematic flood data, particularly in regions with scarce hydrometeorological records.