NATHAN FOSTER

WARM SEASON WORKSHOP

5/2 /12

The Flash Flood Potential Index (FFPI) Project at BTV

Flash Flooding Overview

We all know the factors that determine the occurrence of flash flooding Rainfall rates Thunderstorm training Antecedent conditions

Non-meteorological factors also help determine the occurrence of flash flooding: Soil type (sandy soil vs. clay) Land use (open water vs. urban development) Slope (mountainous terrain vs. flat land) Forest canopy density

We have conceptual models of these non-meteorological factors. Can they be quantified?

FFPI Background

FFPI was created by Greg Smith, Senior Hydrologist at the Colorado Basin River Forecast Center

A simple numerical index tied to runoff response potential

Attempts to account for land-surface features that affect hydrologic response (non-meteorological factors) Forest canopy density Slope Land cover (land use) Soil type

Meant to account for multiple characteristics in a river basin and highlight its susceptibility to flash flooding

FFPI Background

Represent real world digitally, through a GIS

For each layer, reclassify and index the input on a 1-10 scale to represent FFPI

Average all input data for each grid cell over the analysis area

FFPI Background

Final step, average across FFMP stream basins

We monitor rainfall and flash flooding potential on a basin by basin basis

Knowing the underlying susceptibility of these basins to flash flooding could speed up the warning decision making process and increase lead time

Also, could help us decide when not to warn, which could potentially decrease false alarms

BTV FFPI - Forest Canopy Density

Percentage of forest canopy cover

Important to flash flooding because dense forest cover will intercept falling rain and slow its ground arrival

Ranges from 0-100%

Plenty of national forest land in mountains, high percentage there

BTV FFPI - Forest Canopy Density

Reclassified as: 91-100 = 1 81-90 = 2 71-80 = 3 61-70 = 4 51-60 = 5 41-50 = 6 31-40 = 7 21-30 = 8 11-20 = 9 0-10 = 10

BTV FFPI - Slope

Slope calculated from a digital elevation model

Important to flash flooding because a higher slope will increase the runoff speed and cause water to be funneled into one area and collect

Weighted 3x higher than other layers

BTV FFPI – Land Cover

Affects flash flooding because varying land cover types affect runoff potential and rate of absorption into the ground

Land cover types: 11 = Open water 21 = Developed, open space 22 = Developed, low intensity 23 = Developed, medium

intensity 24 = Developed, high intensity 31 = Barren land

(rock/sand/clay) 41 = Deciduous forest 42 = Evergreen forest 43 = Mixed forest 52 = Shrub/scrub 71 = Grassland/herbaceous 81 = Pasture/hay 82 = Cultivated crops 90 = Woody wetlands 95 = Emergent herbaceous

wetlands

BTV FFPI – Land Cover

Reclassified: 11 (Open water) = 1 21 (Developed, open space)

= 7 22 (Developed, low intensity)

= 8 23 (Developed, medium

intensity) = 9 24 (Developed, high

intensity) = 10 31 (Barren land

(rock/sand/clay))) = 8 41 (Deciduous forest) = 5 42 (Evergreen forest) = 3 43 (Mixed forest) = 4 52 (Shrub/scrub) = 6 71 (Grassland/herbaceous) =

6 81 (Pasture/hay) = 5 82 (Cultivated crops) = 5 90 (Woody wetlands) = 2 95 (Emergent herbaceous

wetlands) = 2

BTV FFPI – Hydrologic Soil Group

Hydrologic soil groups are based on estimates of runoff potential. Soils are assigned to one of four groups according to the rate of water infiltration when the soils are not protected by vegetation, are thoroughly wet, and receive precipitation from long-duration storms.

Reclassified:

Group A. Soils having a high infiltration rate (low runoff potential) when thoroughly wet. These consist mainly of deep, well drained to excessively drained sands or gravelly sands. These soils have a high rate of water transmission.

Group B. Soils having a moderate infiltration rate when thoroughly wet. These consist chiefly of moderately deep or deep, moderately well drained or well drained soils that have moderately fine texture to moderately coarse texture. These soils have a moderate rate of water transmission.

Group C. Soils having a slow infiltration rate when thoroughly wet. These consist chiefly of soils having a layer that impedes the downward movement of water or soils of moderately fine texture or fine texture. These soils have a slow rate of water transmission.

Group D. Soils having a very slow infiltration rate (high runoff potential) when thoroughly wet. These consist chiefly of clays that have a high shrink-swell potential, soils that have a high water table, soils that have a claypan or clay layer at or near the surface, and soils that are shallow over nearly impervious material. These soils have a very slow rate of water transmission.

BTV FFPI – Impervious Surfaces

An impervious surface increases the flash flooding threat because all water is converted to runoff

Impervious surfaces range from 0-100%

Reclassified: 91-100 = 10 81-90 = 9 71-80 = 8 61-70 = 7 51-60 = 6 41-50 = 5 31-40 = 4 21-30 = 3 11-20 = 2 0-10 = 1

GSP FFPI – Average Values

GSP FFPI – FFMP Basin Average

Minimum Value: 2.8Tributary to Little

River

Summary and Future Work

FFPI attempts to quantify the relative susceptibility of a stream basin to flash flooding, regardless of meteorological factors

When compared to past flash flood events, there appears to be a positive correlation suggesting FFPI would provide beneficial information

Important to remember, flash flooding can occur anywhere regardless of FFPI

FFPI is not meant to be a predictive indicator, rather another piece of information to consider during flash flood warning operations (confidence modifier)

Perhaps it will prove most beneficial in areas where there is a relative minimum of information (sparsely populated areas, lack of gage data, poor radar coverage, etc.)

Summary and Future Work

Next step is to implement operationally

Would probably get the most use and be most efficient if it can be viewed directly in AWIPS

A basic web page version. KML.

Additional datasets?

Movement downstream

References

FFPI Resources Greg Smith, CBRFC Blair Halloway, Jim Brewster, NWS Binghamton, NY

GIS Datasets Seamless Data Warehouse (http://seamless.usgs.gov/) State Soil Geographic (STATSGO) data (

http://www.nws.noaa.gov/oh/hrl/dmip/soil.html)