High Resolution Flash Flood Potential Index for Customers and Partners Jim Brewster WFO Binghamton, NY Moneypenny Creek Flash Flood – May 2004.

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Presentation transcript:

High Resolution Flash Flood Potential Index for Customers and Partners Jim Brewster WFO Binghamton, NY Moneypenny Creek Flash Flood – May 2004

Background Flooding is WFO Binghamton’s #1 High Impact Hazard Flooding is WFO Binghamton’s #1 High Impact Hazard Central NY and Northeast PA have highly variable geography, land cover and use. Central NY and Northeast PA have highly variable geography, land cover and use. Steep, rocky terrain along with flatter sandy plains Steep, rocky terrain along with flatter sandy plains Areas of urbanization Areas of urbanization Wide range of forest cover Wide range of forest cover Similar soil types Similar soil types Experienced forecasters realized that some areas are more prone to flash flooding than others. Experienced forecasters realized that some areas are more prone to flash flooding than others. But, Where and to what extent? But, Where and to what extent?

Flash Flood Potential Index (FFPI) Developed by hydrologist Greg Smith, CBRFC (2003). Developed by hydrologist Greg Smith, CBRFC (2003). Geographical features play a key role in flash flooding Geographical features play a key role in flash flooding Developed as background information to be incorporated into production of better gridded Flash Flood Guidance Developed as background information to be incorporated into production of better gridded Flash Flood Guidance Using the FFPI, the roles of land, vegetation and urbanization in flash flooding are visualized Using the FFPI, the roles of land, vegetation and urbanization in flash flooding are visualized “Guesswork” to the flash flood problem is reduced “Guesswork” to the flash flood problem is reduced

Methodology for creating FFPI Collected available geographic data sets Collected available geographic data sets Used GIS technology to resample, project and index the data into to a common value Used GIS technology to resample, project and index the data into to a common value Mathematically develop a new geographic index grid…the FFPI Mathematically develop a new geographic index grid…the FFPI

The Data Four geographic data sets : Four geographic data sets : Slope derived from the USGS DEM (Digital Elevation Model) Slope derived from the USGS DEM (Digital Elevation Model) MLRC Land Use/Land Cover Grid MLRC Land Use/Land Cover Grid AVHRR Forest Density Grid AVHRR Forest Density Grid STATSGO Soil Type Classification STATSGO Soil Type Classification

Slope Index Exponentially scaled from 1-10 Exponentially scaled from 1-10 USGS & engineering studies USGS & engineering studies ~30% slope is rated strong-very strong slope. ~30% slope is rated strong-very strong slope. Approx 20 o angle. Approx 20 o angle. Indexed >30% as 10. Indexed >30% as 10.

Indexed Land Use/Land Cover Much of region shares a similar index Much of region shares a similar index Mixed forest & grassland. Mixed forest & grassland. Mild-Moderate effect on hydrology Mild-Moderate effect on hydrology Swamp/water 1-2 Swamp/water 1-2 Urban areas 8-10 Urban areas 8-10

Indexed Forest Density High density forest areas are given a low potential flood index. High density forest areas are given a low potential flood index. Low density areas are given high potential index. Low density areas are given high potential index.

Indexed Soil Class ClassFFPI 1 – Sand2 2 – Loamy Sand4 3 – Sandy Loam3 4 - Silty Loam4 5 – Silt5 6 – Loam6 7 – Sandy Clay Loam7 8 – Silty Clay Loam7 9 – Clay Loam8 10 – Sandy Clay7 11 – Silty Clay8 12 – Clay9 13 – Organic Matter5 14 – Bedrock10

Methodology Review Weight average the geographic layers. Weight average the geographic layers. FFPI = (1.5*Slope + LC + Soils + Forest)/N FFPI = (1.5*Slope + LC + Soils + Forest)/N Local adjustment to calculation Local adjustment to calculation Reviewed against historical events Reviewed against historical events Flash flooding occurs in our forested areas. Flash flooding occurs in our forested areas. Is that element really much of an influence here? Is that element really much of an influence here? FFPI = (1.5*Slope + LC + Soils + 0.5*Forest)/N FFPI = (1.5*Slope + LC + Soils + 0.5*Forest)/N Raw grid is then averaged to individual basins. Raw grid is then averaged to individual basins.

90 Meter Resolution 90 Meter Resolution Warm colors = High Potential Warm colors = High Potential Cool colors = Low Potential Cool colors = Low Potential

FFPI mapped to FFMP Basins Fit our historical events Fit our historical events New realizations, especially the low FF potential areas. New realizations, especially the low FF potential areas. Differentiates the “best of the worst” basins in an area generally known for high flash flood potential. Differentiates the “best of the worst” basins in an area generally known for high flash flood potential.

FFPI Versatility  Exportable to other platforms  KML/KMZ  GeoTiff  Google Earth  ESRI shape file  Exportable to other platforms  KML/KMZ  GeoTiff  Google Earth  ESRI shape file

High Resolution in Action November 16, 2006 Flash Flooding & Mud slides

Case Example

Fatal Gorge Flood

Storm Total Precipitation

90 m - High Resolution Use of high resolution FFPI in a GIS environment can benefit emergency managers, planning boards, town highway departments, and other local officials and groups. Glen Brook Fatalities

Summary The FFPI was developed in Binghamton due to the important need to have a static geophysical reference grid which better illustrates how local earth system features contribute to flash flooding. The FFPI was developed in Binghamton due to the important need to have a static geophysical reference grid which better illustrates how local earth system features contribute to flash flooding. The FFPI is best used in flood operations when mapped to our AWIPS FFMP basins for comparison with other flash flood tools and techniques. The FFPI is best used in flood operations when mapped to our AWIPS FFMP basins for comparison with other flash flood tools and techniques. Through GIS technology, the index can be exported to many formats for use by other government agencies, customers and partners for planning and mitigation. Through GIS technology, the index can be exported to many formats for use by other government agencies, customers and partners for planning and mitigation. Please send requests for GIS FFPI layers to Please send requests for GIS FFPI layers to

Questions ? Reduced false alarms Reduced false alarms Two warnings - Pike County, PA and Oneida County, NY were not issued. Follow-up confirmed no flooding Two warnings - Pike County, PA and Oneida County, NY were not issued. Follow-up confirmed no flooding Increased Lead Time Increased Lead Time Boosted forecaster confidence that additional rain would lead to flash flooding (Warn on Forecast) – Major flash flooding resulted in Delaware County, NY Boosted forecaster confidence that additional rain would lead to flash flooding (Warn on Forecast) – Major flash flooding resulted in Delaware County, NY First Year Performance