Abstract
AbstractHurricane 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.
Highlights
The present paper presents such a simplified methodology which accounts for meteorological and land-surface components together in a flood hazard risk forecast index (FHRFI), by combining information from the main flood-generating land-surface area within the meteorological hazard warning to create a spatial flood hazard index
This can be critically important for emergency responders to target their efforts better, either by suggesting evacuation routes or by deploying assistance in targeted areas, by issuing flood warnings according to the extreme forecast index (EFI)/shift of tails (SoT) used in the flood hazard risk forecasting index (FHRFI) forecasts
Warnings based on numerical weather prediction (NWP) reforecast climatologies, such as that used in the European runoff index based on climatology flash-flood indicator within the European Flood Awareness System (EFAS) (Raynaud et al, 2015), can be used to tackle the underestimation problem, but typically thresholds are derived from a single control reforecast member, ignoring uncertainty in the simulations
Summary
Flooding is a devastating natural hazard, with over 1 million deaths attributed to storms and floods between 1970 and 2012, and over US$400 billion in economic losses at the global scale (Golnaraghi et al, 2014). Such systems can rely on, for example, limited area models (LAMs) or radar/nowcasting methods, and applications to flash floods exist in Europe (as part of the EFAS) (Thielen et al, 2009; Raynaud et al, 2015), in northern America (Gourley et al, 2017), southern Africa (Georgakakos et al, 2013), Australia and other regions (Hapuarachchi and Wang, 2008) Where such systems are absent, global NWP are possible alternatives owing to their ability to capture the synoptic signals that can result in localized extreme events at the medium range (3–14 days ahead), they generally do not reproduce fine spatial scale processes, such as convection, responsible for intense precipitation (Emerton et al, 2016) and driving pluvial and urban flooding. Houston metropolitan area following Hurricane Harvey during August 26–28, 2017, and benchmarked against a meteorological forecast index as a proof of concept to generate surface flood-risk warnings in a large conurbation, but the approach could be extended globally
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