S97
Extreme flooding of the Oneida River Basin in Upstate New York on 28 June 2013: a case study

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Sunday, 4 January 2015
Justin J. Hartnett, Syracuse University, Syracuse, NY; and P. Gao

On 28 June 2013, Oneida Creek in upstate New York experienced its largest flooding event on record since 1950. Maximum flood discharges during the event exceeded 11,000 ft3 s-1, nearly doubling the previous maximum on record (6380 ft3 s-1). Due to the extensive flooding, the return frequency for the 2013 event was calculated at approximately 85 years. Yet, the total daily rainfall during the event had a considerably smaller return frequency (approximately 3 years). This discrepancy led to a sizable underestimation of water discharge and total volume of surface water for the event using the Dynamic Watershed Simulation Model (DWSM). The purpose of this study is to examine the cause of the extreme flooding on 28 June 2013, even though daily rainfall totals were not extreme.

Rainfall intensity and rainfall distribution within the watershed were identified as two potential factors which led to the extreme flooding on 28 June. Rainfall intensity is examined using hourly rainfall data obtained as gridded shapefiles from the National Weather Service's National Mosaic. Also, archived NEXRAD data for the Binghamton, New York radar is obtained from the National Climate Data Center's online database. In addition to the hourly rainfall, the spatial distribution of daily rainfall is examined using gridded shapefiles accessed from the National Weather Service's Advanced Hydrologic Prediction Service. River discharge rates and total volume of surface water for the Oneida Creek were obtained from the United States Geological Survey's surface-water historical instantaneous data for New York. To understand the uniqueness of the June 2013 event, the hydrological and meteorological characteristics of the event are compared with the 8 September 2011 (6280 ft3 s-1) and 30 March 2014 floods (4260 ft3 s-1).

After analyzing the rainfall patterns of the different flooding events, it was found that even though 24-hour rainfall totals for the September 2011 event were nearly double (12.2 cm) rainfall totals for the June 2013 event (6.8 cm), the peak flow of the river was considerably larger for the June 2013 event. Results of this study suggest that the June 2013 event was considerably larger than the September 2011 and March 2014 events because of the rainfall intensity and the location of the heaviest rainfall for the event. Hourly maximum rainfall totals for all three events were comparable (0.18 cm difference); however, there was a larger difference in multi-hour precipitation totals and the duration of high hourly rainfall rates. Compared to the other two flooding events, the June 2013 event had a higher two, three, and six-hour rainfall rate. Similarly, the rainfall duration for hourly precipitation rates greater than 0.76 cm was considerably longer (five consecutive hours) for the June 2013 event, than the September 2011 (three consecutive hours) and March 2014 (two consecutive hours) events. It was also determined that the location of the most intense rainfall likely influenced the flooding levels, as heavy rainfall for the June 2013 event was concentrated to the southern extent of the entire Oneida Basin. Since the Oneida River flows south-to-north, the water that enters in the southern branches flows throughout the majority of the river channel until it filters into Oneida Lake.

Results from this study suggest that the controlling factors in extreme flooding for the Oneida Creek Basin are rainfall rates per hour, and the duration and location of high hourly rainfall rates. Understanding the factors that led to the 2013 extreme flooding event will better prepare forecasters and civilians within the Oneida Creek Basin, and other river basins in New York State, for future flooding events. The incorporation of rainfall rates and locations in models will result in more accurate flooding predictions, and increase the potential to save lives and property.