Flood hazard risk forecasting index (FHRFI) for urban areas: The Hurricane Harvey case study

Abstract

Abstract Hurricane Harvey caused at least 70 confirmed deaths, with estimated losses in the Houston urban area of Texas reaching above US$150 billion, making it one of the costliest natural disasters ever in the United States. The study tests two types of forecast index to provide surface flooding (inundation) warning over the Houston area: a meteorological index based on a global numerical weather prediction (NWP) system, and a new combined meteorological and land surface index, the flood hazard risk forecasting index (FHRFI), where land surface is used to condition the meteorological forecast. Both indices use the total precipitation extreme forecast index (EFI) and shift of tails (SoT) products from the European Centre for Medium‐Range Weather Forecasts (ECMWF) medium‐range ensemble forecasting system (ENS). Forecasts at the medium range (3–14 days ahead) were assessed against 153 observed National Weather Service (NWS) urban flood reports over the Houston urban area between August 26 and 29, 2017. It is shown that the method provides skilful forecasts up to four days ahead using both approaches. Moreover, the FHRFI combined index has a hit ratio of up to 74% at 72 hr lead time, with a false‐alarm ratio of only 45%. This amounts to a statistically significant 20% increase in performance compared with the meteorological indices. This first study demonstrates the importance of including land‐surface information to improve the quality of the flood forecasts over meteorological indices only, and that skilful flood warning in urban areas can be obtained from the NWP using the FHRFI.

Keywords

• ensemble prediction, extreme weather, flash flood