Transcript Flash Flood Potential Index

Flash Flood Potential Index
Greg Smith – AHPS/ Flash Flood Services FFPI Program Lead
Senior Hydrologist
Colorado Basin River Forecast Center
FFPI Dataset for AFG
Offices offering review, feedback, recommendations, for the FFPI concept
Define direction/continuation of this project
Define an operational concept
Fairbanks CWA FFPI
FFPI Datasets for Review
Analyze and provide feedback - compare known flash flood areas
Compare/log FFPI indices corresponding with this seasons events
Feedback, guidance, & value of this type of information
Reasoning – Method – Examples
FFPI Concept:
simple numerical index
tied to runoff response potential
Attempts to account for those land-surface
features affecting hydrologic response
Flash Flood Factors
Meteorological Factors
Vertical Moisture Flux
Mean Wind Speed & Cell Movement
Atmospheric Cap
Rainfall Rates & Duration
Storm Cell Propagation/Training
Quasi-Stationary Systems
Storm Movement
Lifting Mechanisms (Orographic Enhancement)
Moisture Source (warm-cool rain process)
Non-Meteorological Factors
Basin Geometry
Slope
Forest / Vegetation cover
Soil Type
Land-Use Practices (Urbanization)
Wildfire Activity
Basin Geometry (Hydraulic)
Antecedent Soil Moisture (Hydrologic)
Physiographic
Runoff Response
Flash Flood Potential
The Motivation (Influenced by Western Region issues & needs)
 FFMP emphasized need for improved & finer resolution FF information
 FFG is coarse, non-existent, or “rule-of-thumb based”
Basins with different physical features respond the same
 Local office request for additional FF information and better guidance
 Modernized FFG method issues
Scale, model coverage, soil moisture dependency, bankfull definitions
Flash Flood Guidance: Local and ‘Rule-of-Thumb” procedures lack spatial resolution
Implication: All basins have the same hydrologic response
Flash Flood Precipitation Thresholds
Pre-defined Climate Zones
Largest exceeds 13,000 KM2
Observed Precipitation
FFMP Flash Flood Basins
Areas range from 15-130 KM2
Scale Issue: Precipitation Thresholds and Radar Observed Precipitation
Coarse Resolution FFG
CNRFC FFG
CBRFC FFG
Developing a Flash Flood Potential Index
How do you account for multiple
characteristics in a small river basin?
?
Vegetation type
or density
Soil type
Wildfire
Slopes
Land Use
FFPI Method
Obtain raster (gridded) datasets representing
the features of interest.
Forest Density
Elevation/Slope
Methods
FFPI Method
GIS world (raster)
Re-classifying datasets - elevation
Real world
Flash Flood
Potential Index
(FFPI) Values
Relative
Reclassification
User
defined
processes
Map world (DEM)
1
2
3
4
5
6
7
8
9
10
Decreasing
Hydrologic
Response
Increasing
Math world (eqns)
Data Re-classification
Re-Classify Data: Equal Interval Classification for 10 categories
Attributes for Forest
Density Texture Layer
Attributes for Soil
Texture Layer
Count
Sand_l1 Silt_l1
Clay_l1
5389
92
5
3
6778
83
11
6
1533
74
17
9
1760
65
24
12
2796
56
30
15
12623
47
32
21
10734
37
36
27
2205
28
27
45
48955
19
27
55
281
10
46
44
7356
0
0
0
Bedrock/Impervious
1
2
3
4
5
6
7
8
9
10
Decreasing
Hydrologic
Response
Increasing
Count
190646
279946
282587
319984
256793
581571
1339600
343955
483725
42490504
Density
91-100%
81-90%
71-80%
61-70%
51-60%
41-50%
31-40%
21-30%
11%-20%
0-10%
Methods
FFPI Method: Re-classifying datasets – Land Use
NLCD Categories (Ranking)
Commercial/Industrial/Transportation
10
High Intensity Residential
Increasing
Bare Rock
Low Intensity Residential
Quarries-Strip Mines-Gravel Pits
Shrubland
Hydrologic
Row Crops
Response
Orchards/Vineyards
Grassland
Pasture-Hay
Deciduous Forest
Evergreen Forest
Decreasing
Mixed Forest
Woody Wetlands
Perennial ice - snow
Open Water
NLCD - National Land Cover Data Classification Code 1992
1
Methods
FFPI Method
Using Geographic Information System (GIS)
Gather digital data for different layers
Soil type
Forest density/cover
Slope
Land use/urbanization
Resample and Geo-register Data
Consistent resolution
Same projection/datum
Overlapping grid cells representing same
location on the surface of the Earth
FFPI Method
Creating a single FFPI layer
7
3
Hydrologic response
Greater response
and potential
Slope
7
1
3
8
Forest Density
3
6
4
9
6
Land Use
4
Soil
9
Flash Flood
Potential Index
10
Lesser response
and potential
FFPI Method
Scale Issues and characteristics :
Not all layers can be viewed as equal to one another
Not all layers respond in a linear fashion
Layer 1
1
Layer 2
1 2
Layer 3
1
FFPI
1
2
3
3
2
3
4
4
5
6
7
5
4 5 6
6
7
8
Greater response and potential
Lesser response and potential
8
9
10
7 8
9 10
9 10
10
AFG Slope FFPI
Response Potential
1
Lower
2
3
4
5
6
7
8
9
10
Higher
Data Source: Derived from USGS 2 arc-second DEM
AFG Land FFPI
Response Potential
1
Lower
2
3
4
5
6
7
8
9
10
Higher
Data Source: NLCD 2001 Land Cover
AFG Forest FFPI
Response Potential
1
Lower
2
3
4
5
6
7
8
9
10
Higher
Data Source: AVHRR Derived Tree Cover Data
Global Land Cover Institute - UMD
AFG Gridded FFPI
Combination of slope, soil
type, land-use, & forest
density FFPI layers.
Response Potential
1
Lower
2
3
4
5
6
7
8
9
10
Higher
AFG Gridded FFPI
Summed to a
Basin Layer
Response Potential
1
Lower
2
3
4
5
6
7
8
9
10
Higher
Alaska HUC Basins
Accumulated hydrologic
response information is
displayed as one value
Land Use
Soil type
Vegetation type
and density
1
Decreasing Potential
Slopes
FFPI
10
Increasing Potential
Comparing FFPI Basins and Reality
Higher FFPI values (darker) – Basins in
Capitol Reef National Park
Lower FFPI values (lighter) – Near Moquith
Mountain – gradually sloped, sandy basins
Flash Flood Potential Index Concept
Simple index
Accounts for those land-surface features affecting hydrologic response
Rank drainage basins
Higher index values  greater hydrologic response  greater flash flood threat
Index flexibility
Identify flash flood prone areas
Supplement existing methods (classify basins)
Use with areal or rules of thumb  better qualify basins response
Incorporate into alternative methods for generating flash flood guidance
FFPI in the Operational Warning Environment
NWS - Warning Decision Training Branch - Advanced Warning Operations Course
Flash Flood
Occurred
Operational Use
WFO – Salt Lake City
FFPI Display: These basins on the North Fork
received the heaviest rainfall rates with total
rainfall amounts exceeding FFG by over ½ inch.
Radar reflectivity (above) and storm total
precip (below). FFG was exceeded but a FF
Warning was not issued.
Basins of the North Fork drainage that feed
the Escalante River. Basins are on the eastern
slope of the range but it is heavily forested.
CNRFC FFG Comparison
NWSRFS Derived
FFPI based gridded FFG
FFPI: Potential Operational Applications
Account For Wildfire
Overlapping Fires near Tucson, AZ 2002-2003
UTAH
NEVADA
Bullock Fire
Summer 2002
30,563 acres
(128 km2)
ARIZONA
MODIS - NASA Image
Aspen Fire
June 2003
84,750 acres
(343 km2)
Wildfire effects
High Burn Severity:
All vegetation blackened, deep soil
heating killing roots/seeds, “baking” of
the soil surface.
Moderate Burn Severity:
Patchwork of green and burnt areas.
Intermediate between “high” and “low”
severity levels.
Low Burn Severity:
Most vegetation untouched by fire. No
significant effect on soil properties or
water repellency.
How to apply fire burn severity information ?
High Burn:
Completely remove forest density
Maximize soil hydrologic response (max FFPI)
Moderate Burn:
Reduce forest density 50%
Increase soil FFPI 50%
Low or non burn:
No change to hydrologic response
Aspen Fire Burn Severity Perimeter
and Pre-fire FFPI Grids:
Pre-Fire FFPI Grids
Aspen Fire Perimeter
Severe Burn
Moderate Burn
NWSRFS Segment
Boundaries
FFPI
Decreasing Flash
Flood Potential
Increasing Flash
Flood Potential
Fire Modification to FFPI Grids
FFPI
Decreasing Flash
Flood Potential
Before Aspen Fire
Increasing Flash
Flood Potential
After Aspen Fire
Completed
Status of FFPI
Development
FGZ: Flagstaff
GJT: Grand Junction
PSR: Phoenix
RSA: CNRFC
SLC: Salt Lake
TWC: Tucson
VEF: Las Vegas
ABQ: Albuquerque
RNK: Roanoke/Blacksburg
SGF: Springfield, MO
AFG: Fairbanks
SJU: San Juan PR
GJT: Grand Junction CO
AHPS supported test sites
FFPI 2008 Plan
Summer 2008 (Evaluation):
Deliver FFPI to test sites for review, comment, evaluation, recommendation
Log summer events – compare with FFPI indices
Autumn 2008 (conops recommendations):
Provide a possible CONOPS summary to AHPS FF Services Team
Recommendations from field offices decide the fate/direction of this project
Ongoing Work:
Enhance FFPI by including a dynamic soil moisture layer
Establish an automated method to obtain and modify FFPI based on wildfire data
Recommendations To Date:
Generate statistical FFG relating flash flood event data to FFPI indices
Do FFPI indices show a relation to precipitation return frequencies ?
Allow users to freely weigh and manipulate datasets (“FFA System”?)
Get FFPI information into FFMP (format issue)