Predicting Post-Wildfire Watershed Runoff Using ArcGIS ......from a wildfire exposes soil to erosion, which may increase runoff, causing flooding, sediments may move downstream and

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Predicting Post-Wildfire Watershed Runoff Using ArcGIS Modelbuilder

Richard Easterbrook

Abstract

The Department of the Interior’s National Interagency Burned Area Emergency Response

(BAER) teams address post-wildfire effects on a landscape with the goal of stabilizing the fragile

condition of the land to protect life, property, water quality and ecosystems. Loss of vegetation

from a wildfire exposes soil to erosion, which may increase runoff, causing flooding, sediments

may move downstream and damage houses or fill reservoirs, and put endangered species and

community water supplies at risk. BAER Team hydrologists requested a GIS tool that would

automate the process of predicting post-wildfire watershed runoff. ArcGIS Model Builder was

selected because it makes use of existing tools within ArcToolbox and can be modified with

custom models and scripts. A custom set of tools has been created in Model Builder that predicts

pre and post-wildfire watershed runoff for a selected rain event. These tools are easy to run

within a custom dialog and the results are easily repeatable.

Introduction

BEAR Team Hydrologists, Soil Scientists and Geologists analyze post wildfire conditions to

model erosion potential, peak flow and sediment delivery of burned watersheds. To predict

watershed peak flows, team specialists have used a conglomeration of ArcView 3.x Avenue1

scripts to derive a Modified Rational Method result (Parenti 2003). These scripts proved to be

1 An object-oriented programming language on which ArcView 3.x is based. Avenue provides tools for customizing ArcView 3.x and developing applications.

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unstable, especially with someone not proficient in ArcView. In 2005, BAER team GIS

Specialists agreed to make ArcGIS the standard software for incidents. This necessitated the

development of a peak flow toolset that would work within the ArcGIS environment. ArcGIS

ModelBuilder was selected as the platform because: 1) Models utilize existing spatial analysis

tools within ArcToolbox, 2) Models document the analysis process, 3) Models can be modified

with custom script, but don’t require programming unless looping is required, 4) Models can be

executed from a user-friendly/customizable graphical user interface (Figure1), and 5) Model

results are easily repeatable.

Figure 1 – BAER Watershed Tools in ArcMap

The primary purpose of this toolset is to compare watershed peak runoff before and after a

wildfire for a designed storm event. This contributes to the assessment of watershed damage

caused by the wildfire. BEAR Team Hydrologists, Soil Scientists and Geologists must identify

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value-at-risk2 (VAR) in the fire area, determine whether they are in danger from a peak flow

event and if so, prescribe what measures must be taken to protect these VAR’s. Often, these

watersheds are very large and un-gauged (no stream gauge records are available), necessitating

the need for prediction methods. Two runoff methods were selected for this toolset: The SCS

CN method and the Rational method. The SCS CN method is used for watersheds greater than

200-acres, while the Rational method is ideal for small watersheds (<= 200-acres).

1.1 Soil Conservation Service (SCS) Curve Number Method (CN)

The SCS CN Method estimates direct runoff from rainfall for a given watershed. Direct runoff is

a collective term that includes channel runoff3, surface runoff4 and subsurface flow5 (1999

USDA). “The principle application of the method is in estimating quantities of runoff in flood

hydrographs or in relation to flood peak rates” (Mockus 1972). This method uses curve numbers

to indicate the proportions of surface and subsurface flow, larger curve numbers represent a

greater proportion of surface runoff. Curve numbers are derived from the tables in Appendices

A through D by determining the hydrologic soil group, vegetation cover and condition and burn

severity. Soil hydrologic groups are called A, B, C and D, in order of the greatest infiltration

capacity to the least. Burn severity is derived from the Remote Sensing Applications Center’s

Burned Area Reflectance Classification (BARC) theme. The BARC theme is created from

remotely sensed imagery by analyzing the healthy vegetation signatures for the burned area.

This theme is then modified using field verifications of watershed response parameters to

2 Life, property, and critical natural and cultural resources. 3 Rainfall that falls on a watercourse. 4 Generated when the rainfall rate exceeds the infiltration rate. 5 Horizontal movement of infiltrated water in soil.

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produce a burn severity map. The following SCS CN equation is used for watersheds greater

than 10 square miles:

Equation 1.1

l

p

TDAQ Q+⎟

⎠⎞

⎜⎝⎛

=

2

484

The following SCS CN equation is used for watersheds less than or equal to 10 square miles:

Equation 1.2

pp

TAQ Q 484

=

where

Qp = Peak rate of discharge in cubic feet per second (cfs)

A = Drainage area (square miles)

Q = Accumulated runoff in inches over the drainage area

D = Duration of the storm in hours

Equation 1.3

( )( )c

c

S.P)S.PQ

8020 2

+−

=

where

P = Accumulated rainfall depth in inches (the hypothetical storm event)

Sc = Potential maximum retention by the soil after runoff begins

Equation 1.4

101000−=

CNSc

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where

CN = Curve number (as determined from soil hydro group, vegetation and burn severity)

Tl = Lag time in hours

Equation 1.5

( )( )5.0

7.08.0

*19001

SSLT c

l+

=

where

L = Length of drainage area in feet (greatest flow length in the watershed)

S = Average watershed slope in percent

where

Tp = Time to peak in hours

Equation 1.6

fcp WTT =

where

Wf = Watershed width factor (Appendix E)

Tc = Time of concentration in hours

Equation 1.7

6.l

cTT =

1.2 Rational Method

The simplest approach to determining peak flow is the Rational method. The Rational method is

used primarily for computing peak flows for small urban or rural watersheds. This method uses

runoff coefficients to indicate the ratio that the peak rate of runoff bears to the average rate of

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rainfall. Runoff coefficients are derived from the tables in Appendices F and G by determining

the vegetation cover and burn severity.

Equation 1.8

IACQ '=

where

Q = Peak rate of discharge in cubic feet per second (cfs)

C’ = Runoff coefficient modified by vegetation and watershed response (Appendices F &

G)

I = Rainfall intensity (inches per hour)

A = Drainage area (acres)

Model Methodology

2.1 Project Data Import

The first step in the peak runoff process is to create the necessary project folders in ArcCatalog

that store the project data (Data folder), the BAER Watershed Tools toolset (Tools folder), and

help files and images (Help folder) (Figure 2). Each of these three directories is created under

the C:\baerfire directory.

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Figure 2 – BAER Watershed Tools directory organization.

Next, a personal geodatabase is created (runoff.mdb) under the Data folder and all necessary

project data is imported into it using the Fire Data Import model (Figure 3).

baerfire

Data Tools Help

Runoff.mdb

BAER Watershed Tools.tbx Document

Images

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Figure 3 – Simplified Fire Data Import model

2.1. Analysis Area

Figure 4 illustrates how the runoff toolset determines the extent of the area to be analyzed.

Drainage basins6 are created from a digital elevation model (DEM), and only those which

intersect the fire perimeter are selected and used to clip the DEM. This procedure/model reduces

the size of the original DEM so only those drainage areas disturbed by the wildfire are analyzed

in the runoff model.

6 A drainage basin is an area that drains water and other substances to a common outlet as concentrated drainage.

CREATE PERSONAL

GDB

30-Meter

DEM

NRCS

Soils

Vegetation

Theme

Fire

Perimeter

Burn

Severity

Runoff.mdb

FEATURE CLASS

TO FEATURE CLASS

FIREDEM

SOIL

VEG

FIREPERM

BURNSEVER

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Figure 4- Simplified Analysis Area model

2.2 Hydrology

To determine peak flow from a watershed it is necessary to model the movement of water across

a surface. This surface is represented by a digital elevation model (DEM). The second step in

the runoff toolset applies multiple hydrology tools to the analysis area’s DEM in order to derive

flow characteristics (Figure 5). The Stream Tools model identifies and fills any sinks that exist

30-Meter

DEM

CREATE BASIN TOOL

DEM

BASINS

SELECT BY LOCATION

(INTERSECT)

EXTRACT BY

MASK

ANALYSIS AREA DEM

FIRE

PERIMETER

SELECTED

BASINS

FEATURE ENVELOPE TO

POLYGON

BASIN

ENVELOPES

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in the DEM, creates a flow direction7 raster, a flow accumulation8 raster, a stream network9

raster, a stream order10 raster, a stream link11 raster and a stream feature class.

Figure 5 – Simplified Stream Tools model

7 Direction from each cell to its steepest down slope neighbor. 8 Accumulated flow to each cell. 9 Delineated from flow accumulation using a threshold value (stream network = setnull [flow accumulation < threshold value, 1]). 10 Stream segments assigned a numeric order representing branches of a linear network (Strahler Method). 11 Stream sections assigned unique IDs between network intersections.

ANALYSIS

AREA DEM

FILL

FILLED

DEM

FLOW

DIRECTION

FLOW

DIRECTION

FLOW

ACCUMULATION

FLOW ACCUMULA

-TION

STEAM

NETWORK

FLOW ACCUMULATION

THRESHOLD (PARAMETER)

STREAM

NETWORK

STREAM

ORDER

VECTOR

STEAMS

STREAM

LINK

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2.3 Storm Events

To predict peak runoff from a watershed it is necessary to determine the number of inches of

rainfall produced from a theoretical storm event. Scanned NOAA Atlas 2 (Precipitation

Frequency Atlas for the Western United States, 1973) isopluvial precipitation frequency maps

(http://www.wrcc.dri.edu/pcpnfreq.html) can be downloaded and used to estimate the number of

inches produced from a desired storm event. This number is input into the various Storm Event

models to create a constant value raster layer representing inches produced from the storm. Two

year, 5 year, 10 year, 25 year, 50 year, and 100 year storms, over a 6 or 24 hour period can be

modeled (Figure 6).

Figure 6 – Storm Event model

A subset (2 yr 6 hr, 2 yr 24 hr, 100 yr 6 hr and 100 yr 24 hr) of these spatial datasets are also

provided in ArcInfo ASCII grid format

(http://www.nws.noaa.gov/ohd/hdsc/noaaatlas2.htm#na2map). The asciigrid command can be

used to import these ASCII files into a raster format readable by ESRI software. This continuous

raster layer must be divided by 100,000 to calculate inches.

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NOAA Atlas 2 has been superceded by NOAA Atlas 14 for Arizona, Nevada, New Mexico, Utah

and southern California. NOAA Atlas 14 (http://hdsc.nws.noaa.gov/hdsc/pfds/pfds_gis.html)

models 2 year, 5 year, 10 year, 25 year, 50 year, 100 year, 200 year, 500 year and 1000 year

storms, over 5, 10, 15, 30, 60 minute, 2, 3, 6, 12, 24, 48 hour, and 4, 7, 10, 20, 40, 45, 60 day

periods. This continuous raster layer is available in ESRI grid format and must be divided by

1,000 to calculate its values into inches. The above mentioned continuous data grids can replace

the constant value raster created by the runoff model, but no models currently exist in the toolset

that projects and extracts the necessary rainfall data.

2.4 Soils, Vegetation and Burn Severity

As mentioned earlier, the SCS CN method uses curve numbers to indicate the proportion of

surface runoff. Curve numbers are derived from the tables in Appendices A through D by

determining the hydrologic soil group, vegetation cover and condition, and burn severity. The

Rational method uses runoff coefficients to indicate the ratio that the peak rate of runoff bears to

the average rate of rainfall. Runoff coefficients are derived from the tables in Appendices F and

G by determining the vegetation cover and burn severity. In order to assign curve cumbers and

runoff coefficients to watersheds the soils, vegetation and burn severity feature classes must be

combined. The forth step in the runoff toolset overlays these three feature classes and creates

attribute fields to hold values for vegetation class, soil hydro group, pre and post curve number

and pre and post runoff coefficients (Figure 7).

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Figure 7 – Simplified Soils, Vegetation & Burn Severity model

2.5 Soil Hydro Group

The fifth step in the runoff estimation process is to populate the newly created Soil Hydro Group

field in the soilvegfire feature class. This is accomplished by writing a SQL query that selects

polygons belonging to a certain soil hydro group and then assigning them with the proper group

letter (Figure 8). There is a separate model for each soil hydro group (A through D).

VEG

SOIL

INTERSECT

ADD FIELD

VEG_SOIL

UNION

BURNSEVER

SOILVEGFIRE

ADD FIELD

SOILVEGFIRE

FINAL

VEG CLASS

SOIL GROUP

PRE/POST CN

PRE/POST RC

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Figure 8 – Simplified version of the Soil Hydro Group and Vegetation Class models

2.6 Vegetation Class

The sixth step in the runoff estimation process is to populate the newly created Vegetation Class

field in the soilvegfire feature class. This is accomplished by writing a SQL query that selects

polygons belonging to one of the twelve vegetation classes and then assigning them with the

proper class (Figure 8). There is a separate model for each of the vegetation classes (Annual

Grass, Aspen, Barren/Rock/Soil, Broad Leaf Chaparral, Conifer, Grass/Forb, Mountain

Brush/Oak, Narrow Leaf Chaparral, Oak Woodland, Pinyon/Juniper, Riparian and Sagebrush).

2.7 Pre-Wildfire Curve Numbers

Pre-wildfire curve numbers are calculated using four models, one for each soil hydro groups

within the toolset. Each model requires the user to input a curve number for each of the twelve

vegetation classes (Figure 9). These models perform a select query on the soilvegfire feature

SOILVEGFIRE

SELECT

LAYER BY

ATTRIBUTE

SQL SELECT QUERY

CALCULATE

FIELD

SOILVEGFIRE

(SELECTED)

SOILVEGFIRE

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class to select all polygons that are of a certain soil hydro group and vegetation class to calculate

the pre-wildfire curve numbers utilizing the user values. Pre-wildfire curve numbers provided in

Appendices A through D are for the western United States and provide different curve numbers

for vegetation conditions (i.e., good, fair, poor and prescribed fire).

Figure 9 – Pre-Curve Number model for soil hydro group C

2.8 Post-Wildfire Curve Numbers

Post-wildfire curve numbers are calculated in a similar fashion except that burn severity must be

taken into account. Nine models are required for the toolset to populate the post-curve number

field in the soilvegfire feature class. There is a model for each combination of soil hydro group,

and high and moderate burn severity, and one for low burn severity and unburned areas. Areas

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that have low burn severity or were unburned have identical curve numbers for pre and post-

wildfire. Post-wildfire curve numbers are also provided in Appendices A through D and supply

additional numbers for areas determined to be hydrophobic. The presence of hydrophobic soils

is determined in the field by Watershed Specialists (Figure 10).

Figure 10 – Testing for hydrophobic soil conditions

2.9 Pre-Wildfire Runoff Coefficients

Pre-wildfire curve numbers are calculated using one model within the toolset that groups the

twelve vegetation classes into eight classes so that runoff coefficients can be applied to each

polygon in the soilvegfire feature class. This model requires the user to input a curve number

(from Appendix F) for each of the grouped vegetation classes (Figure 11).

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Figure 11 – Pre-Runoff Coefficient model user interface

2.10 Post-Wildfire Runoff Coefficients

Post-wildfire runoff coefficients are assigned based on the level of burn severity. The Post-

Runoff Coefficient model (Figure 12) applies multiple SQL queries to the soilvegfire feature

class to select burn severity and calculate the runoff coefficient using the values from Appendix

G.

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Figure 12 – Post-Runoff Coefficient model user interface

2.11 Create Watersheds

The Create Watersheds model (Figure 13) does exactly as it says; it creates watersheds using the

pour point (values-at-risk) feature class and the flow accumulation and flow direction raster

layers created in the Stream Tools model. Before this model is run, it is strongly recommended

that users manually snap the points in the pour point feature class to the streams feature class

(created in the Stream Tools model) using ArcMap. This procedure will ensure that pour points

snap to the proper stream segment for watershed creation.

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Figure 13 – Create Watershed model

2.12 Lag Time & Time of Concentration

“Time of concentration is the time it takes for water to travel from the most hydraulically distant

point in a watershed to its outlet [pour point]” (SCS 1973). Lag time is the delay in time after a

storm event occurs and before runoff reaches its maximum peak (Kent 1972). Lag time can be

considered a weighted time of concentration. The Lag Time & Time of Concentration model

uses the Equations 1.4, 1.5 and 1.7 to calculate the potential maximum retention by the soil after

runoff begins, lag time and time of concentration. Figure 14 illustrates that this model has three

embedded models that calculate watershed slope (Figure 15), mean watershed curve number

(Figure 16) and watershed flow length (Figure17). The time of concentration raster will later be

used by the SCS CN equation to determine peak runoff.

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Figure 14 – The Lag Time & Time of Concentration model

Figure 15 – Slope model

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Figure 16 – Curve Number Mean model

Figure 17 – Simplified Watershed Flow Length model

2.13 SCS CN Peak Flow Method

The SCS CN peak flow model (Figure 18) requires that three parameters be inputted by the user:

watershed width factor (Appendix E), a storm event raster and the storm duration (in hours).

These parameters are passed to the two embedded models to calculate peak flow for watersheds

greater than and less than or equal to 10 square miles.

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Figure 18 – SCS CN Peak Flow model

Figure 19 illustrates the model that calculates peak flow for watersheds less than or equal to 10

square miles. It uses Equation 1.2 to calculate the SCS CN peak flow. This model has three

embedded models that calculate watershed size in square-miles (Figure 21), accumulated runoff

for the watershed (Figure 22) and a watershed size conditional statement (Figure 23). The

accumulated runoff model uses Equation 1.4 to calculate the potential maximum retention by the

soil after runoff begins, and Equation 1.3 to calculate accumulated runoff. The watershed size

conditional statement model determines whether a watershed is greater than or less than or equal

to 10 square miles. In Figure 19, if the watershed is less than or equal to 10 square miles, Con

Less Than 10 will equal “1”, otherwise it will have a value of “0”. These values are multiplied

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by the peak flow value and passed to the SCS CN Peak Flow model. The SCS CN Peak Flow

model adds the peak flow values calculated by the Less Than 10sq-miles and Greater Than 10sq-

miles models to determine peak flow rate in cubic feet per second.

Figure 19 – Less than 10sq-miles model

Figure 20 illustrates the model that calculates peak flow for watersheds greater than 10 square

miles. It uses Equation 1.1 to calculate the SCS CN peak flow. This model has three embedded

models that calculate watershed size in square-miles (Figure 21), accumulated runoff for the

watershed (Figure 22) and a watershed size conditional statement (Figure 23). The accumulated

runoff model uses Equation 1.4 to calculate the potential maximum retention by the soil after

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runoff begins, and Equation 1.3 to calculate accumulated runoff. The watershed size conditional

statement model determines whether a watershed is greater than or less than or equal to 10

square miles. In Figure 20, if the watershed is greater than 10 square miles, Con Greater Than

10 will equal “1”, otherwise it will have a value of “0”. These values are multiplied by the peak

flow value and passed to the SCS CN Peak Flow model. The SCS CN Peak Flow model adds the

peak flow values calculated by the Less Than 10sq-miles and Greater Than 10sq-miles models to

determine peak flow rate in cubic feet per second.

Figure 20 – Greater than 10sq-miles model

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Figure 21 – Watershed Sq-Miles model

Figure 22 – Accumulated Runoff model

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Figure 23 – Watershed Size model

2.14 Rational Peak Flow Method

The Rational Peak Flow model (Figure 24) uses Equation 1.8 to calculate peak flow for a

watershed. This model requires the user to input the storm event raster and has two embedded

models that calculate the runoff coefficient mean for a watershed (Figure 25) and the watershed

acreage (Figure 26).

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Figure 24 – Rational Peak Flow model

Figure 25 – Runoff Coefficient Mean model

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Figure 26 – Watershed Acreage model

2.15 Watershed Runoff

The final model in the runoff toolset is Watershed Runoff. This model converts the toolsets

raster layers (i.e., SCS CN and Rational method peak flows, Time of Concentration, Curve

Numbers and Runoff Coefficients) to feature classes, unions these new layers and adds their

attributes to the Watershed feature class (Figure 27). It also calculates the peak flow percent

increase for the SCS CN and Rational methods and percent decrease for time of concentration.

This vector polygon layer can then be easily interpreted in ArcMap by the BAER Watershed

Team.

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Figure 27 – Example of output from the Watershed Runoff model.

Conclusions

The process of predicting pre and post-wildfire runoff from a watershed has many complex

steps. ModelBuilder was used to create custom models that quickly produce runoff results for

various storm events that are easily repeatable, documented and packaged into a user-friendly

ArcGIS toolset. Once fully implemented, the BAER Watershed Runoff toolset will standardize

the process of predicting runoff for DOI BAER Teams.

Formal quality control has not been conducted on the models contained within the BAER

Watershed Runoff toolset. It is recommended that BAER Team GIS Specialists and Watershed

Group members cooperatively scrutinize these models for errors, inconsistencies and areas of

improvement. An ideal time to perform this task would be during the 2006 BAER Team

meeting.

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Peak runoff results from this toolset have not been compared to peak runoff from gauged

watershed to verify results. Comparing the results of this toolset with the peak runoff from a

control watershed is very important. This process will illustrate the accuracy of the toolset in

predicting runoff and determine whether the calculations need to be adjusted by a constant to

bring the results closer to a true runoff value. StreamStats

(http://water.usgs.gov/osw/streamstats/index.html) is a web based program developed by the

USGS to predict runoff from un-gauged watersheds. Unfortunately the model is currently

functional for Idaho, Washington and Vermont only. Once more western states are operational,

this program will be used to verify results of the BAER Watershed Runoff toolset.

If more than one pour point (value-at-risk) is used to create watersheds in the Create Watersheds

model, it is possible that two or more pour points may fall within the same drainage area. Output

from ArcGIS’s Watershed tool is a raster layer. Raster layers do not allow overlap between

watersheds. Figure 28 illustrates this problem. Watershed 1 & 2 were created from two

different pour points, but they are both within the same drainage area. Peak runoff from

watershed 1 should also take into account the drainage area in watershed 2 but this is not

possible with the current toolset. Because of this issue, it is suggested that the toolset be run with

only one pour point at a time. Future versions will fix this limitation by looping the watershed

creation and runoff estimation processes with either programming script or new looping

capabilities in ArcMap 9.2.

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Figure 28 – Overlap between watersheds in the same drainage area

Acknowledgements

I would like to thank Shauna Jensen, Hydrologist for the Dolores Public Lands Office, for

guiding me through the runoff estimation process. Her knowledge of the hydrology and the

hydrologic equations enabled me to develop the runoff toolset. Vicki Magnis, Geographer for

the Intermountain Geographic Resources Information Management Team, for writing Python

12script that will enable the toolset to work with overlap between watersheds in future versions.

Annette Parsons, RSAC/BAER Liaison for the Forest Service Remote Sensing Applications

Center, also deserves to be mentioned for taking time out of her very busy schedule to test the

12 A COM-compliant scripting language used to customize/automate geoprocessing tasks in ArcGIS.

2 1

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runoff toolset and providing valuable comments. Last but not least, Richard Schwab, National

Burned Area Emergency Response Coordinator, for his overall support of this endeavor.

Appendixes

Curve Numbers

A - Hydro Group A Curve Numbers

Adjusted for

Hydrophobicity

Vegetation Type Good Rx Fire Fair Poor

Mod Burn

High Burn

Mod Burn

High Burn

Oak-Aspen-Mtn Brush 20 33 77 77 82.25 98.00 Herbaceous-Grass-Brush 51 65 77 77 82.25 82.25 Conifer 27 38 36 45 77 77 82.25 98.00 Sagebrush-Grass 30 55 77 77 82.25 82.25 Oak Woodland 32 47 44 55 77 77 82.25 98.00 Pinyon Juniper 30 59 77 77 82.25 98.00 Broad Leaf Chaparral 31 41 40 53 77 77 82.25 98.00 Narrow Leaf Chaparral 55 67 55 70 77 77 82.25 98.00 Barren 77 77 77 77 77 82.25 82.25 Annual Grass 38 51 49 65 77 77 82.25 82.25

B - Hydro Group B Curve Numbers

Adjusted for

Hydrophobicity


Mod Burn

High Burn

Mod Burn

High Burn

Oak-Aspen-Mtn Brush 30 53 48 66 63 86 71.75 98.00 Herbaceous-Grass-Brush 62 76 74 85 81 86 85.25 85.25 Conifer 55 63 60 66 73 86 79.25 98.00 Sagebrush-Grass 35 60 51 67 65 86 73.25 73.25 Oak Woodland 58 69 65 73 80 86 84.50 98.00 Pinyon Juniper 41 68 58 75 77 86 82.25 98.00 Broad Leaf Chaparral 57 67 63 70 75 86 80.75 98.00 Narrow Leaf Chaparral 65 77 72 82 77 86 89.00 98.00 Barren 86 86 86 86 86 86 89.00 98.00 Annual Grass 61 74 69 78 83 86 86.75 86.75

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C - Hydro Group C Curve Numbers

Adjusted for

Hydrophobicity


Mod Burn

High Burn

Mod Burn

High Burn


D - Hydro Group D Curve Numbers

Adjusted for

Hydrophobicity


Mod Burn

High Burn

Mod Burn

High Burn


E - Watershed Width Factor Average

Watershed Width (Feet)

Width Factor

0-600 1.24 600-1200 1.10

1200-2400 1.00 2400 0.89

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Runoff Coefficients

F - Pre Fire Runoff Coefficients

Vegetation Type Runoff

Coefficient Riparian 0.02 Sagebrush/Other Shrubs 0.18 Rock/Soils 0.50 Grass/Forb 0.20 Conifer 0.10 Aspen 0.08 Pinyon/Juniper 0.20 Gambel Oak 0.12

G - Post Fire Runoff Coefficients

Watershed Response

K (mm/hr)

Runoff Rate (mm/hr)

% Runoff / Runoff Coefficient

Natural (Unburned) 85 9 10 / 0.10 Low 60 34 36 / 0.36 Moderate 43 52 55 / 0.55 High 25 69 73 / 0.73

References

Parenti, M. & Associates (2003): Modified Rational GIS Flow Model Users Guide 1.0. 2003 Kent, M. Kenneth (1972): National Engineering Handbook, Section 4, Hydrology, Chapter 15. Travel Time, Time of Concentration and Lag, 1972, p. 2 Mockus, Victor (1972): National Engineering Handbook, Section 4, Hydrology, Chapter 10. Estimation of Direct Runoff from Storm Rainfall, 1972, p. 1 National Employee Development Center, Natural resources Conservation Service, United States Department of Agriculture (1999): Engineering Hydrology Training Series, Module 205 – SCS Runoff Equation, 1999, p. 2 Soil Conservation Service, U.S. Department of Agriculture (1973): A Method for Estimating Volume and Rate of Runoff in Small Watersheds, SCS-TP-149, Revised April 1973, p. 7

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Author Information

Richard Easterbrook

GIS Specialist

Grand Teton National Park

P.O. Drawer 170

Moose, WY 83012

307-739-3493

307-739-3490 (FAX)

[email protected]

Documents

Predicting Post-Wildfire Watershed Runoff Using ArcGIS ......from a wildfire exposes soil to erosion, which may increase runoff, causing flooding, sediments may move downstream and