Flash floods: A spatial and temporal analysis—A case study of the flash floods in southwestern Missouri in March 2008

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Sunday, 17 January 2010
Exhibit Hall B2 (GWCC)
Daniel A. Pollak, Pennsylvania State University & NCAR/SOARS, State College, PA

Handout (1.8 MB)

Floods are the leading cause of weather-related fatalities in the United States and the second most common cause of weather-related death worldwide. Of all floods, flash floods are found to be the most deadly with an average global mortality rate of 3.62%. This study performed a spatial and temporal analysis of flash flood risk using Geographic Information Systems (GIS) to analyze an event that occurred in southwestern Missouri in March 2008. The goals of the study were to identify different impacts of the disaster as indicated by flood reports; examine the social and natural factors that account for the spatial and temporal distribution and severity of the impacts; and to compare the results with a previous study of a flash flood event in France. In the Missouri case, the analysis confirmed that small catchments react faster than large catchments and to smaller amounts of rainfall. Seventy-seven percent of incidents (water rescues, fatalities, flooded homes, and flooded roads) occurred in catchments smaller than 200 km2. The study also showed that a majority of the severe impacts (water rescues, fatalities, and flooded homes) occurred after the rainfall had tapered off, perhaps indicating that people erroneously perceive the danger has passed once the rain has stopped. When looking at water rescues and fatalities, the results of this study found that fewer incidents occurred in medium size catchments (50-450 km2) than in either large (>450 km2) or small catchments (<50 km2). This is similar to the French study which found that no fatalities occurred in medium-sized catchments. Using GIS to examine flash flood risk, will take strides forward comparing human vulnerability with size of catchment. This project integrated qualitative and quantitative data using GIS.