Globally, it is widely known that floods remain the most frequent and devastating natural hazards. Likewise, there is recent evidence showing an increase in the number of extreme flood events observed around the world. Therefore, it is imperative to develop an integrated flood assessment framework that enables a better understanding of both, the generation of these events and the interaction of key variables within the hydro-meteorological system. The aim of this investigation is to study the propagation of meteorological uncertainty to a numerically estimated flood map. For such purpose, we utilise a cascade modelling approach comprised by a Numerical Weather Prediction Model (NWP), a rainfall-runoff model and a standard 2D hydrodynamic model. Uncertainty is considered in the meteorological model (Weather Research and Forecasting model) using a multi-physics ensemble technique considering twenty four parameterization schemes. The resulting precipitation fields are used as input in a distributed hydrological model to generate spaghetti plots, which are then employed as forcing in a 2D hydrodynamic model. The approach is utilised for the reproduction of an extreme flood event in southern Mexico, for which field data (rain gauges) and satellite imagery are available. Although there are more uncertainties involved in the determination of a flooded area, the methodology represents a robust approach to acknowledge the propagation from the meteorological model to the flood map. Thus, it favours preventive action in the generation of better flood management strategies.
Rodríguez-Rincón, Juan Pablo; Breña-Naranjo, José Agustín; and Pedrozo-Acuña, Adrián, "Uncertainty Propagation In A Hydro-Meteorological Approach: From The Cloud To The Flood Map." (2014). CUNY Academic Works.