Forecasting flood hazards in real time: a surrogate model for hydrometeorological events in an Andean watershed

María Teresa Contreras,Cristián Escauriaza,Jorge Gironás

doi:10.5194/nhess-20-3261-2020

Abstract

Abstract. Growing urban development, combined with the influence of El Niño and climate change, has increased the threat of large unprecedented floods induced by extreme precipitation in populated areas near mountain regions of South America. High-fidelity numerical models with physically based formulations can now predict inundations with a substantial level of detail for these regions, incorporating the complex morphology, and copying with insufficient data and the uncertainty posed by the variability of sediment concentrations. These simulations, however, typically have large computational costs, especially if there are multiple scenarios to deal with the uncertainty associated with weather forecast and unknown conditions. In this investigation we develop a surrogate model or meta-model to provide a rapid response flood prediction to extreme hydrometeorological events. Storms are characterized with a small set of parameters, and a high-fidelity model is used to create a database of flood propagation under different conditions. We use kriging to perform an interpolation and regression on the parameter space that characterize real events, efficiently approximating the flow depths in the urban area. This is the first application of a surrogate model in the Andes region. It represents a powerful tool to improve the prediction of flood hazards in real time, employing low computational resources. Thus, future advancements can focus on using and improving these models to develop early warning systems that help decision makers, managers, and city planners in mountain regions.

Highlights

Flash floods produced by extreme precipitation events have produced devastating consequences on cities and infrastructure in mountain regions (EEA, 2005; Wilby et al, 2008)
We evaluate the performance of the model based on the mean square error (MSE) and the percent of cases in which the high-fidelity value is within 1 standard deviation from the mean of the prediction (PWSD), considering the definition of Y (X) and s in Eq (9)
The simulation of flood hazards by extreme precipitation in mountain streams requires numerical models capable of capturing complex flows that are influenced by the geomorphic features of the channel and by high sediment concentrations that are common in these regions. In this investigation we develop two models for simulating the flow in an Andean watershed in central Chile: (1) a hydrologic model combined with a 2D hydrodynamic model that is coupled with the sediment concentration in mass and momentum and (2) a surrogate model that employs precalculated scenarios of the previous models, to interpolate new cases using kriging

Summary

Introduction

Flash floods produced by extreme precipitation events have produced devastating consequences on cities and infrastructure in mountain regions (EEA, 2005; Wilby et al, 2008). The piedmont has experienced a rapid urban growth, with cities occupying regions near river channels and increasing the exposure of communities and their infrastructure (Castro et al, 2019). In this context, assessing flood hazards and designing strategies to reduce the potential damages caused by flooding are critical in cities located near mountain rivers. Implementing efficient and accurate tools that facilitate real-time predictions of potential risks is a key component to provide decision makers with enough time for action and reduce the life-loss potential (Amadio et al, 2003; Resio et al, 2009; Toro et al, 2010; Taflanidis et al, 2013)

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Conclusion