Development of the Flash Development of the Flash Flood Potential (FFPI)Flood Potential (FFPI)

The The Flash Flood Potential IndexFlash Flood Potential Index

for Central NY and Northeast PAfor Central NY and Northeast PA

byby

Jim BrewsterJim Brewster

WFO Binghamton, NYWFO Binghamton, NY

Moneypenny Creek Flash Flood – May Moneypenny Creek Flash Flood – May 20042004

BackgroundBackground Flooding is WFO Binghamton’s Flooding is WFO Binghamton’s

#1 High Impact Hazard #1 High Impact Hazard Central NY and Northeast PA Central NY and Northeast PA

have highly variable geography, have highly variable geography, land cover and use.land cover and use. Steep, rocky terrain along with flatter Steep, rocky terrain along with flatter

sandy plainssandy plains Areas of urbanizationAreas of urbanization Wide range of forest coverWide range of forest cover Similar soil typesSimilar soil types

Experienced forecasters Experienced forecasters understand some areas are more understand some areas are more prone to flash flooding than prone to flash flooding than others.others.

But, Where and to what extent? But, Where and to what extent?

Flash Flood Potential Index (FFPI)Flash Flood Potential Index (FFPI)

Developed by hydrologist Greg Smith, CBRFC Developed by hydrologist Greg Smith, CBRFC (2003).(2003).

He understood that geographical features play a He understood that geographical features play a key role in flash flooding. key role in flash flooding.

Developed as background information to be Developed as background information to be incorporated into production of better gridded incorporated into production of better gridded Flash Flood GuidanceFlash Flood Guidance

Using the FFPI, the roles of land, vegetation and Using the FFPI, the roles of land, vegetation and urbanization in flash flooding are visualized.urbanization in flash flooding are visualized.

““Guesswork” to the flash flood problem is Guesswork” to the flash flood problem is reducedreduced

Methodology for creating Methodology for creating FFPIFFPI

Collected available geographic data setsCollected available geographic data sets Using GIS Using GIS

Projected datum to Albers Equal AreaProjected datum to Albers Equal Area Re-sampled data sets to 90 meter resolutionRe-sampled data sets to 90 meter resolution Reclassified data to a standard indexReclassified data to a standard index

Mathematically develop a new geographic index Mathematically develop a new geographic index grid…the FFPIgrid…the FFPI

The DataThe Data Four geographic data sets :Four geographic data sets :

Slope derived from the USGS DEM Slope derived from the USGS DEM (Digital Elevation Model)(Digital Elevation Model)

MLRC Land Use/Land Cover GridMLRC Land Use/Land Cover Grid AVHRR Forest Density GridAVHRR Forest Density Grid STATSGO Soil Type ClassificationSTATSGO Soil Type Classification

Slope IndexSlope Index Exponentially scaled Exponentially scaled

from 1-10from 1-10 USGS & engineering USGS & engineering

studiesstudies ~30% slope is rated ~30% slope is rated

strong-very strong slope.strong-very strong slope. Approx 20Approx 20oo angle. angle.

Indexed >30% as 10.Indexed >30% as 10.

Indexed Land Use/Land Indexed Land Use/Land CoverCover

Much of region shares a Much of region shares a similar indexsimilar index

Mixed forest & grassland.Mixed forest & grassland. Mild-Moderate effect on Mild-Moderate effect on

hydrologyhydrology Swamp/water 1-2Swamp/water 1-2 Urban areas 8-10Urban areas 8-10

Indexed Forest DensityIndexed Forest Density High density forest areas High density forest areas

are given a low potential are given a low potential flood index.flood index. Higher uptake rate of Higher uptake rate of

moisturemoisture

Low density areas are Low density areas are given high potential given high potential index.index. Lower uptake rate of Lower uptake rate of

moisturemoisture

Indexed Soil Texture ClassIndexed Soil Texture ClassClass FFPI1 – Sand 2

2 – Loamy Sand 4

3 – Sandy Loam 3

4 - Silty Loam 4

5 – Silt 5

6 – Loam 6

7 – Sandy Clay Loam

7

8 – Silty Clay Loam 7

9 – Clay Loam 8

10 – Sandy Clay 7

11 – Silty Clay 8

12 – Clay 9

13 – Organic Matter

5

14 – Bedrock 10

Methodology ReviewMethodology Review

Weight average the geographic layers.Weight average the geographic layers. FFPI = (1.5*Slope + LC + Soils + Forest)NFFPI = (1.5*Slope + LC + Soils + Forest)N

Local adjustment to calculationLocal 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 = (FFPI = (1.51.5*Slope + LC + Soils + *Slope + LC + Soils + 0.50.5*Forest)/N*Forest)/N Raw grid is then zonally averaged into the Raw grid is then zonally averaged into the

FFMP basins.FFMP basins.

90 Meter Resolution90 Meter Resolution Warm colors = High PotentialWarm colors = High Potential Cool colors = Low PotentialCool colors = Low Potential

FFPI mapped to FFMP BasinsFFPI mapped to FFMP Basins Fit our conceptual Fit our conceptual

flash flood model.flash flood model. New realizations, New realizations,

especially the especially the areas of areas of lowlow FF FF potential.potential.

Differentiates the Differentiates the “best of the worst” “best of the worst” basins in an area basins in an area generally known generally known for high flash flood for high flash flood potential.potential.

FFPI VersatilityFFPI Versatility

Flexible Formatting

ESRI Shape file

KML/KMZ

GeoTifGoogle Earth

BMP GRx Analyst

Flexible Formatting

ESRI Shape file

KML/KMZ

GeoTifGoogle Earth

BMP GRx Analyst

Case ExampleCase Example

Fatal Gorge FloodFatal Gorge Flood

Storm Total PrecipitationStorm Total Precipitation

90 m High Resolution90 m High ResolutionHigh resolution GIS imagery of FFPI can be useful to customers and partners for identifying local, potential floodproblem areas that may not be already known.

High resolution GIS imagery of FFPI can be useful to customers and partners for identifying local, potential floodproblem areas that may not be already known.

SummarySummary The FFPI was developed in Binghamton due to the The FFPI was developed in Binghamton due to the

important need to have a static geophysical important need to have a static geophysical reference grid which better illustrates how local reference grid which better illustrates how local earth system features contribute to flash flooding. earth system features contribute to flash flooding.

The FFPI is best used operationally when mapped The FFPI is best used operationally when mapped to the AWIPS FFMP basins for comparison with to the AWIPS FFMP basins for comparison with other flash flood tools and techniques. other flash flood tools and techniques.

Through GIS technology, the index could be Through GIS technology, the index could be developed by any local office.developed by any local office. Note: The original developer Note: The original developer has a project underwayhas a project underway

with Office of Hydrology to further develop and expand with Office of Hydrology to further develop and expand the FFPI nationally.the FFPI nationally.

Questions ?Questions ?

Reduced false alarmsReduced false alarms Two warnings - Pike County, PA and Oneida County, Two warnings - Pike County, PA and Oneida County,

NY were not issued. Follow-up confirmed no floodingNY were not issued. Follow-up confirmed no flooding

Increased Lead TimeIncreased Lead Time Boosted forecaster confidence that additional rain Boosted forecaster confidence that additional rain

would lead to flash flooding (Warn on Forecast) –would lead to flash flooding (Warn on Forecast) –Major flash flooding resulted in Delaware County, NYMajor flash flooding resulted in Delaware County, NY

First Year PerformanceFirst Year Performance