Agwa and Integration

8/3/2019 Agwa and Integration

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Darius SemmensDarius Semmens****,, Scott N. Miller, David Goodrich,Scott N. Miller, David Goodrich,

Ryan Miller, Mariano HernandezRyan Miller, Mariano Hernandez

USDAUSDA Agricultural Research ServiceAgricultural Research Service

Southwest Watershed Research CenterSouthwest Watershed Research Center

Tucson, AZTucson, AZ

(current address for Daruis: EPA, Las Vegas(current address for Daruis: EPA, Las Vegas

[email protected])[email protected])

Bill Kepner, Don EbertBill Kepner, Don EbertUSUS EPAEPA

Landscape Ecology BranchLandscape Ecology Branch

Las Vegas, NVLas Vegas, NV

GISGIS--BASED HYDROLOGIC MODELING:BASED HYDROLOGIC MODELING:

THE AUTOMATED GEOSPATIALTHE AUTOMATED GEOSPATIAL

WATERSHED ASSESSMENT TOOLWATERSHED ASSESSMENT TOOL


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Project Background & Acknowledgements

Long-Term Research Project

Landscape Ecology Branch 4 years

Interdisciplinary Watershed management

Landscape ecology

Atmospheric modeling

Remote sensing GIS

Multi-Agency USDA ARS

US EPA

USGS

Universities of Arizona & Wyoming US Army

NWS

Primary Support 2 Post-Doc

2 Ph.D.

1 Masters 2 Full time

USDA-ARSDavid Goodrich

Mariano Hernandez

Averill Cate

Shea Burns

Casey Tifft

Soren ScottLainie Levick

US-EPA

Bill Kepner

Darius Semmens

Dan HeggemBruce Jones

Don Ebert

University of Arizona

Phil Guertin

University of Wyoming

Scott Miller


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PC-based GIS tool for watershed modeling

KINEROS & SWAT (modular)

Investigate the impacts of land cover

change on runoff, erosion, water quality

Targeted for use by research scientists,

management specialists

technology transfer

widely applicable

Introduction


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Used with US-EPA Analytical Tool Interface forLandscape Assessment (ATtILA)

Simple, direct method for model parameterization

Provide accurate, repeatable results

Require basic, attainable GIS data

30m USGS DEM (free, US coverage)

STATSGO soil data (free, US coverage) US-EPA NALC & MRLC landscape data

(regional & free w/ US coverage)

Useful for scenario development, alternativefutures simulation work.

Objectives of the Automated Geospatial

Watershed Assessment (AGWA) tool


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Impacts of scale addressed using 2 models

(KINEROS & SWAT)

Temporal & spatial effects

Focus on relative change to reduce

confounding effects of changing rainfall Interested in both volume and rate of runoff

Water supply & water quality

Applicable across range of landscape,precipitation regimes

Semi-arid San Pedro

Humid Catskills#

#

After Omernick

Modeling the Impacts of Land Cover Change


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Range of characteristic space time scales

Hydrology and Human Activities

Small WS Models(e.g. KINEROS2)

Large WS Models(e.g. SWAT)


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(SWAT)

Daily time step

Distributed: empirical and physically-based model

Hydrology, sediment, nutrient, and pesticide yields

Larger watersheds (> 1,000 km2)

Similar effort used by BASINS

71

73

Soil Water and Assessment Tool

71

73

pseudo-channel 71

channel 73

Abstract Routing Representation

to nextchannel


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(KINEROS2)

Event-based (< minute time steps)

Distributed: physically-based model with

dynamic routing

Hydrology, erosion, sediment transport Smaller watersheds (< 100 km2)

72

Kinematic Runoff and Erosion Model

73

71

Abstract Routing Representation


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Where KINEROS2 Works

http://ialcworld.org/soils/surveys/states.html

http://science.nasa.gov/headlines/y2000/ast15

nov_1.htm

Arid and Semi-Arid WatershedsHeavily Urbanized Watersheds

Watersheds characterized by predominantly overland flow


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Watershed Discretization(model elements)

++

Land

Cover

Soil

Rain

Results

Run modeland import

results

Intersect model

elements with

Digital

Elevation

Model (DEM)

Sediment yield (t/ha)Sediment discharge (kg/s)

Water yield (mm)Channel Scour (mm)

Transmission loss (mm)Peak flow (m3/s or mm/hr)

Surface runoff (mm)Sediment yield (kg)

Percolation (mm)Runoff (mm or m3)

ET (mm)Plane Infiltration (mm)

Precipitation (mm)Channel Infiltration (m3/km)

SWAT OutputsKINEROS Outputs

AGWA Inputs and Outputs


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AGWA ArcView Interface


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Navigating Through AGWA

Subdivide Watershed Into Model Elements

SWAT KINEROS

Generate rainfall input files

Daily Rainfall from

Gauge locations

Thiessen map

Pre-defined continuous record

Storm Event from

NOAAAtlas-II

Pre-defined return-period / magnitude

Create-your-own

Intersect Soils & Land Cover

Generate Watershed Outline grid

polygon

Choose the modelto run

look-up tables


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Navigating Through AGWA, Contd

Subwatersheds & ChannelsContinuous Rainfall Records

Prepare inputdata

Run The Hydrologic Model & Import Results

Display Results

SWAT output:Runoff, water yield (mm)Evapotranspiration (mm)

Percolation (mm)

Transmission Losses (mm)

Sediment Yields (mm)

Channel & Plane ElementsEvent (Return Period) Rainfall

KINEROS output:Runoff (mm,m3)

Sediment Yield (kg/ha)

Infiltration (mm, in)

Transmission losses (m3/km)

Peak runoff rate (m3/s)

Peak sediment discharge (kg/s)

external to

AGWA

Visualization for

each model

element


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NLCD

Land cover A B C D Cover

High intensity residential (22) 81 88 91 93 15

Bare rock/sand/clay (31) 96 96 96 96 2

Forest (41) 55 75 80 50

Shrubland (51) 63 77 85 88 25

Grasslands/herbaceous (71) 80 87 93 70

Small grains (83) 65 76 84 88 80

CURVE NUMBER

Hydrologic Soil Group

SWAT Parameter Estimation

- Example: Curve Number from MRLC land cover

Higher numbers result in higher runoff


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Texture Ksat Suction Porosity Smax CV Sand Silt Clay Dist KffClay 0.6 407.0 0.475 0.81 0.50 27 23 50 0.16 0.34

Fractured Bedrock 0.6 407.0 0.475 0.81 0.50 27 23 50 0.16 0.05

Clay Loam 2.3 259.0 0.464 0.84 0.94 32 34 34 0.24 0.39

Sandy Clay Loam 4.3 263.0 0.398 0.83 0.60 59 11 30 0.40 0.36

Silt 6.8 203.0 0.501 0.97 0.50 23 61 16 0.23 0.49

Loam 13.0 108.0 0.463 0.94 0.40 42 39 19 0.25 0.42

Sandy Loam 26.0 127.0 0.453 0.91 1.90 65 23 12 0.38 0.32

Gravel 210.0 46.0 0.437 0.95 0.69 27 23 50 0.16 0.15

KINEROS Parameter Estimation

Parameters based on soil texture

Parameters based on land cover classification (NALC)

Land Cover Type Interception (mm/hr) Canopy (%) Manning's n

Forest 1.15 30 0.070Oak Woodland 1.15 20 0.040Mesquite Woodland 1.15 20 0.040Grassland 2.0 25 0.050Desertscrub 3.0 10 0.055Riparian 1.15 70 0.060

Agriculture 0.75 50 0.040Urban 0.0 0.0 0.010


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AZ061

Component 1

20%

Component 2

45% Component 3

35%

9 inches

Layer 1

Layer 2

Layer 3

2

2

5

Layers for component 3

Components for MUID AZ061

Intersection of model

element with soils map

AGWA Soil Weighting (KINEROS)

Area and depth weighting of soil

parameters

Area weighting of averaged

MUID values for each watershed

element

AZ076

AZ067


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Parameter Manipulation (optional)

Ksat

Can manually

change parameters

for each channel

and plane element

Stream channel attributes

Upland plane attributes Ksat


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Automated tracking of

simulation inputs

Calculate and viewdifferences between

model runs

Multiple simulation runs

for a given watershed

Color-ramping of

results for each

element to show

spatial variability

Visualization of Results


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Spatial and Temporal Scaling of Results

High urban growth

1973-1997Upper San Pedro

River Basin

#

#

ARIZONA

SONORA

Phoenix

Tucson

WY

Water yield change

between 1973 and 1997

SWAT Results

Sierra Vista Subwatershed

KINEROS Results

N

Forest

Oak Woodland

Mesquite

Desertscrub

Grassland

Urban1997 Land Cover

Concentrated urbanization

Using SWAT and KINEROS for integrated watershed assessment

Land cover change analysis and impact on hydrologic response


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Urbanization Effects (KINEROS2)

Pre-urbanization

1973 Land Cover

Post-urbanization

1997 Land Cover

Results from pre- and post-urbanization simulations using

the 10-year, 1-hour design storm event


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Limitations of GIS - Model Linkage

Model Parameters are based on look-up tables

- need for local calibration for accuracy- FIELD WORK!

Subdivision of the watershed is based on topography

- prefer it be based on intersection of soil, lc, topography

No sub-pixel variability in source (GIS) data

- condition, temporal (seasonal, annual) variability

- MRLC created over multi-year data capture

No model element variability in model input

-averaging due to upscaling

Mostuseful for relative assessmentunless calibrated


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Improvements in AGWA 1.4 and BASINS-AGWA

Run SWAT on a daily time step & visualize animated results

SSURGO soil parameterization for SWAT

Enhanced ground-water parameterization dialog for SWAT

Elevation bands for SWAT

FAO Soils international usage

Multiple hydraulic-geometry relations for channelcharacterization

Land-Cover Modification Tool


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Land-Cover Modification Tool Overview

Allows user to specify type and location of land-cover alterations by

either drawing a polygon on the display, or specifying a polygon map

Types of Land Cover Changes

Change entire user defined area to new land cover

e.g. to grassland Change one land cover type to another in user defined area

e.g. to simulate road restoration, change from barren to desert

scrub

Change land cover type within user supplied polygon map

e.g. to simulate a prescribed burn, change map of burnarea to barren

Create a random land cover pattern

e.g. to simulate burn pattern, change to 64% barren, 31%

desert scrub, and 5% mesquite woodland


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Integrating a Landscape/Hydrologic Analysis

for Watershed Assessment

Mariano Hernandez, William G. Kepner, Darius J. Semmens,

Donald W. Ebert, David C. Goodrich, Scott N. Miller

U.S. Department of Agriculture


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OBJECTIVES

Demonstrate the coordinated application of theAnalytical Tools Interface for Landscape

Assessments (ATtILA) and the Automated

Geospatial Watershed Assessment (AGWA) tool to:

Assess the contribution of different land-cover types

to surface runoff and sediment yield for the period 1993

to 1997

Identify subwatersheds with high sediment loadings

as a result of land-cover management


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BACKGROUND

Land use decisions can exacerbate:

Natural hazards and soil erosion

Alter hydrologic balance

Pollute surface and ground water

Destroy wildlife habitats

Increase air pollution

Diminish community quality life


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Upper San Pedro Watershed

(Arizona/Sonora)

7,600 km2

5,800 km2

Arizona/ 1,800 km2

Sonora

Elevation 900 2,900 m

Annual ppt. 30 75 cm

Sonoran/Chihuahuan Transition Zone


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METHODOLOGY

The general approach used in this study

was carried out as follows:

1) Discretization of the San Pedro River Basin into

reporting units or subwatersheds using AGWA

2) Computation of landscape metrics with ATtILA

a) Land use proportions

b) Number of patches

c) Patch density

d) Largest patch index

e) Average patch size

3) Characterization of Hydrologic Response Units

(HRUs) based on land use proportions for SWAT


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METHODOLOGY

4) Application of the AGWA tool to parameterize theSWAT model

5) Identification of subwatersheds with high sediment

yield based on land-cover type, slope steepness,

and average patch size


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2.88 - 84.21

1.20 - 2.88

0.55 - 1.20

0.00 - 0.55

Average Patch Size (ha)Percentage (%)

33.62 - 93.60

14.10 - 33.62

4.95 - 14.10

0.00 - 4.95

RESULTS

Percentage of agriculture and average patch size on

each individual subwatershed


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RESULTS

Spatially distributed average surface runoff and

average sediment yield for the period 1993 - 1997


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RESULTS

Sediment yield and mean annual surface runoff relationship


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RESULTS

Watershed Assessment

HRUs were ranked according to high contributing

sediment yield areas using the relationship between

sediment yield to mean annual surface runoff as a

function of four land cover types

The average slope (9%) and the average sediment

yield (0.8 t/ha) of all HRUs were used as cutoff

criteria

The selection process yielded eight HRUs; six are

classified as agriculture (Ag) and two as

desertscrub (Ds)


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RESULTS

Areas with high sediment yields for 1993 - 1997


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Highest contributions to sediment yield is produced

in areas with agriculture and desertscrub land cover

types

Average slope steepness, average annual sediment

yield, and average patch size were used to identify and

rank sensitive subwatersheds

CONCLUSIONS


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Simulating the Impact of Landscape Change

on Channel Geomorphology in Semi-Arid

Watersheds

Darius J. Semmens

U of AZ, USDA-ARS, U.S. EPA-LEBApril 2, 2004


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Introduction

To understand how an individual stream reach responds toexternal stresses it is necessary to study the channel network asa whole

Watershed-based models are thus necessary to evaluategeomorphic impacts of landscape change

Development of watershed-based geomorphic models is alsothe first step towards linking landscape and ecologicalindicators with surficial processes and response

Event-based watershed models simulate erosion and depositionbased on assumption that channel geometry is static during the

course of an event Prevents simulation of cumulative impacts from multiple events

No event-based watershed models for arid and semi-aridregions that can track cumulative adjustment of the channelnetwork in terms of channel width, depth, and slope.


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Approach

Implement channel-geometry adjustments inKINEROS2 based on total stream power minimization

Develop a GIS-based interface to facilitate modelparameterization, multiple-event simulations, andresults visualization


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KINEROS2 Geomorphic Model (K2G)

Width and depth adjusted to minimize total

stream power at end of each time step

Depth adjustments

Maximum erodible depth

Bank failure

Width adjustments Compound channels

Depth


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AGWA-G

GIS-based interface for K2G, customized

version of AGWA

Watershed delineation and discretization

Land cover and soils parameterization

Coordinates multiple consecutive simulations

and tracks cumulative outputs

Results visualization

Differencing results from two simulations

relative assessment


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Results

Simulations based on

Hydraulic-geometry

channels

1997 land cover

Wet (top), intermediate

(middle), and dry (bottom)

year simulation results

Erosion during wet year,

and deposition during

dry year

DecreasingPrecipitation

1964

1977

1978

Depth Changes Width Changes


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Results Relative Assessment

Significant differencesconcentrated on urbanizedtributary

Erosion increases withinurbanized area more

pronounced for wet year Reduced erosion or increased

deposition begins furtherupstream during drier year

Aggradation downstreamcharacterized by depthdecreases and width increases

DecreasingPrecipitation

1964

1977

Difference in

Depth Changes

Difference in

Width Changes


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Conclusions

Geomorphic response varies with rainfall record able to

resolve changing spatial patterns of sediment movement

Relative assessment useful for highlighting the relative

magnitude of geomorphic impacts associated with land-cover change

Assessment of channel stability, or vulnerability to

degradation will require simulations for a range of

rainfall records and durations more research needed

Linkages to riparian condition not yet established

Arid-region model at present

Documents

Agwa and Integration