Abstract
Flooding during extreme weather events damages critical infrastructure, property, and threatens lives. Hurricane María devastated Puerto Rico (PR) on 20 September 2017. Sixty-four deaths were directly attributable to the flooding. This paper describes the development of a hydrologic model using the Gridded Surface Subsurface Hydrologic Analysis (GSSHA), capable of simulating flood depth and extent for the Añasco coastal flood plain in Western PR. The purpose of the study was to develop a numerical model to simulate flooding from extreme weather events and to evaluate the impacts on critical infrastructure and communities; Hurricane María is used as a case study. GSSHA was calibrated for Irma, a Category 3 hurricane, which struck the northeastern corner of the island on 7 September 2017, two weeks before Hurricane María. The upper Añasco watershed was calibrated using United States Geological Survey (USGS) stream discharge data. The model was validated using a storm of similar magnitude on 11–13 December 2007. Owing to the damage sustained by PR’s WSR-88D weather radar during Hurricane María, rainfall was estimated in this study using the Weather Research Forecast (WRF) model. Flooding in the coastal floodplain during Hurricane María was simulated using three methods: (1) Use of observed discharge hydrograph from the upper watershed as an inflow boundary condition for the coastal floodplain area, along with the WRF rainfall in the coastal flood plain; (2) Use of WRF rainfall to simulate runoff in the upper watershed and coastal flood plain; and (3) Similar to approach (2), except the use of bias-corrected WRF rainfall. Flooding results were compared with forty-two values of flood depth obtained during face-to-face interviews with residents of the affected communities. Impacts on critical infrastructure (water, electric, and public schools) were evaluated, assuming any structure exposed to 20 cm or more of flooding would sustain damage. Calibration equations were also used to improve flood depth estimates. Our model included the influence of storm surge, which we found to have a minimal effect on flood depths within the study area. Water infrastructure was more severely impacted by flooding than electrical infrastructure. From these findings, we conclude that the model developed in this study can be used with sufficient accuracy to identify infrastructure affected by future flooding events.
Highlights
Worldwide, floods affect more people than any other natural disaster, costing $104 billion annually on average [1]
Hydrologic Modelling Approaches (HMAs) 1 and 2 in Figure 14 show how the significant amount of discharge reported by the United States Geological Survey (USGS) stream discharge station affected the lower area of the Añasco watershed, especially along the coastal zone
The model produced a large extent and depth compared to the other HMAs (Figures 15 and 16)
Summary
Floods affect more people than any other natural disaster, costing $104 billion annually on average [1]. Nicholls et al [5] describe various impacts caused by flooding as direct and indirect, immediate and long-term, and tangible and intangible. The latter impact (intangible) is not often taken into account and can include psychological effects of the loss of loved ones, displacement, and property damage. In addition to threatening human life, flooding impacts critical infrastructure. When Hurricane María hit Puerto Rico (PR) in September 2017, most large and small powerlines were knocked down. The dam at the Guajataca Reservoir in northwest PR was severely damaged, threatening flash flooding and leaving the population without water for many months. As a consequence of the devastation of Hurricane María, the Joint Operational Catastrophic
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