A Monte Carlo simulation study of the factors influencing the performance of flood early warning systems

Abstract:

In recent decades, flood early warning systems (FEWSs) have been widely used as complementary non-structural mitigation measures in order to improve the population resilience to floods. FEWS research focusses mainly on flood forecasting techniques or social aspects of warning response, and end-to-end modelling frameworks that represent the entire FEWS forecast-decisionresponse/impact chain are rarely developed. A generic Monte Carlo simulation framework has been developed that represents an end-to-end FEWS in a versatile way, allowing factors influencing FEWS performance to be explored which cannot be analysed easily based on limited realworld data. The framework has been applied to a simulated generic fluvial case, where factors influencing FEWS performance in terms of reliability and economic effectiveness are explored. A new reliability performance measure based on inundation maps has been proposed. The framework has also been used to explore factors controlling the performance of a simulated FEWS representing an urban polder in Nanjing, China, with performance metrics based on waterlogging and pumping costs. For the generic fluvial case, the main results show that: i) the correlation between forecasts and observed values controls reliability; ii) probabilistic forecasts based on optimising a probabilistic threshold are robust to forecast biases in the mean and variance, iii) a FEWS based on uncertain forecasts is characterised by an optimal lead time that represents a balance between an adequate time to act in response and a reasonably good forecast; iv) the performance of the proactive action is the most …

Año de publicación:

2021

Keywords:

Fuente:

google