pc-based gis tool for watershed modeling –kineros & swat (modular) investigate the impacts of...
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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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• Develop landscape assessment tool for land managers using indicators
• Advance scientific understanding of principles governing watershed response to change
land cover changes in the US and associated impacts on runoff volume, water quality
• Investigate historical changes using repeat imagery (San Pedro, Catskill/Delaware)
• Investigate spatially distributed hydrologic processes using single scenes (Las Vegas)
• Forward looks with simulations
Objectives of the Research
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Introduction
• Hydrologic Modeling in GIS
– The Shape and characteristics of the earth’s surface is useful for many fields of study.
– Understanding how changes in the composition of an area will affect water flow is important!
What happens when residential development occurs?How does this affect the watershed?How can these affects be mitigated?
– Best Management Practices (BMPs)
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Introduction
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Introduction
Topographic Maps
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A watershed boundary can be sketched by starting at the outlet point and following the height of land defining the drainage divides using the contours on a map.
Outlet Point
Traditional watershed delineation had been done manually usingContours on a topographic map.
Introduction
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Introduction: Terminology
• Drainage system - The area upon which water falls and the network through which it travels to an outlet.
• Drainage Basin - an area that drains water and other substances to a common outlet as concentrated flow (watersheds, basins, catchments, contributing area).
• Subbasin - That upstream area flowing to an outlet as overland flow
• Drainage Divide - The boundary between two basins. This is an area of divergent flow.
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GIS Background
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GIS Background
• Raster Data Structure– Much of the data we will use in this class
will be “Raster” data.– Raster formatted data is much more
suitable for many types of landscape modeling, including hydrologic analysis.
– Inputs such as elevation can only be processed as a raster data set
– Raster is Faster, Vector is Corrector
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GIS Background
Raster
Vector
Real World
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GIS Background: DEMs
• Digital Elevation Models (DEM)– A DEM is a digital representation of the
elevation of a land surface.– X,Y and Z value– The USGS is the major producer of DEM’s
in the Nation
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GIS Background: DEMs
•DEM’s consist of an array of data representing DEM’s consist of an array of data representing elevation sampled at regularly spaced intervalselevation sampled at regularly spaced intervals
XX
YY
ELEVATION VALUES
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GIS Background: DEMs
• Two Scales of DEMs Available– 1:24,000 Scale
Level 1 - 30 meter spacing– Errors up to 15 meters inherent in data– Developed using automated methods from air photos– Systematic errors evident as banding– Not appropriate for hydrologic modeling
Level 2- 30 meter spacing– Matches map accuracy of 1:24,000 scale quads– Developed by scanning published quads– Appropriate for hydrologic modeling
– 1 Degree (~250,000) scale - 93 meter spacingAppropriate for regional analysis (not for AGWA)
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GIS Background: DEMs
• Preprocessing DEMs– DEMs typically require some type of
preprocessing prior to hydrologic modeling to remove errors inherent in the data. This type of processing can greatly increase the accuracy of a DEM..
– Primary error found in DEMs are “Sinks”A sink is an erroneous depression created by
the DEM interpolation routineSinks are usually small and cause drainage
basins to be incorrectly delineated
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GIS Background: DEMs
100 100 100 100
100 97 96 95100
1001009998100
100 100 100 100 101
Stream
100-meter Elevationcontour
Sink Area
100 Cell Elevation
Cells containing the contour are assigned the value of the contour,all other cells are interpolated. Sinks are always possible in areaswhere contours converge near a stream.
An example Sink
100
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• Generating Surface Parameters– Flow across a surface will always be in the
steepest down-slope direction– Known as “Flow Direction” this is the basis of all
further watershed modeling processes.– Once the direction of flow is known it is possible to
determine which and how many cells flow into any given cell!
– This information is used to determine watershed boundaries and stream networks.
GIS Background: Surface Parameters
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• Generating Surface Parameters - Flow Direction– In ArcView Spatial Analyst, the output of a
Flow Direction is a grid whose values can range from 1 to 255 based on the direction water would flow from a particular cell. The cells are assigned valued as shown below.
GIS Background: Flow Direction
32 64128
16 1
8 4 2Target Cell
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• Generating Surface Parameters - Flow Direction– If a cell is lower than its eight neighbors, that cell is
given the value of its lowest neighbor and flow is defined towards this cell.
– If a cell has the same slope in all directions the flow direction is undefined (lakes)
– If a cell has the same slope in multiple directions and is not part of a sink the flow direction is calculated by summing the multiple directions
GIS Background: Flow Direction
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GIS Background: Flow Direction
2 2 2 1 128
1 1 1 12864
3264128128128
128 64 64 32 80
Flow Direction Surface
100 100 100 100 94
100 97 96 95100
1001009998100
100 100 100 100 101
Original Surface
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• Generating Surface Parameters - Flow Accumulation– If we know where the flow is going then we can
figure out what areas (cells) have more water flowing through them than others.
– By tracing backwards up the flow direction grid we can figure the number of cells flowing into all cells in a study area
– Accumulated flow is calculated as the accumulated number of all cells flowing into each downslope cell.
GIS Background: Flow Accumulation
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• Generating Surface Parameters - Flow Accumulation– For an accumulation surface the value of
each cell represents the total number of cells that flow into an individual cell
– Cells that have high accumulation are areas of concentrated flow and may be used to identify stream channels.
GIS Background: Flow Accumulation
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Flow Direction Surface
GIS Background: Flow Accumulation
0 0 0 0 18
0 3 8 150
00220
0 0 0 0 0
Flow Accumulation Surface
2 2 2 1 128
1 1 1 12864
3264128128128
128 64 100 32 80
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GIS Background: Flow Accumulation
Flow Accumulation Surface
DEM Flow Direction Flow Accumulation
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AGWA
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• Integrated with US-EPA Analytical Tool Interface for Landscape 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)
• Useful for scenario development, alternative futures simulation work.
Objectives of AGWA
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Natural Condition
Decreased Vegetation
Increased VelocityIncreased Runoff
Increased Erosion
Decreased Water Quality
Land cover changeDegradation
UrbanizationWoody plant invasion
infiltration interception evapotranspiration surface roughness
soil moistureflood hazard groundwater recharge
Land Cover & Hydrologic Response
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Navigating Through AGWA
Subdivide Watershed Into Model Elements
SWAT KINEROS
generate rainfall input files
Thiessen map from…Gauge locationsPre-defined continuous record
Storm Event from…Pre-defined return-period / magnitude“Create-your-own”
Intersect Soils & Land Cover
Generate Watershed Outline
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Navigating Through AGWA, Cont’d…
Subwatersheds & ChannelsContinuous Rainfall Records
prepare input data
Run The Hydrologic Model & Import Results
Display Results
For subwatershed elements:•Precipitation (mm)•Evapotranspiration (mm)•Percolation (mm)•Surface Runoff (mm)•Transmission Losses (mm)•Water Yield (mm)•Sediment Yields (t/ha)
Channel & Plane ElementsEvent (Return Period) Rainfall
For Plane & Channel Elements:•Runoff (mm, m3)•Sediment Yield (kg)•Infiltration (mm)•Peak runoff (mm/hr, m3/sec)•Peak sediment discharge (ks/sec)
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ArcView working directory –secondary or temporary
coverages, grids, and tables
Spatial data –primary coverages and grids
Simulation input/output –Separate directories for
each simulation
AGWA directory –primary tables, AV project
file, and model executables
Suggested File Structure for AGWA
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Hydrologic Modeling & AGWA
AGWAGIS DataRainfall
RunoffErosion
Assumptions
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PROCESS
runoff, sediment hydrographtime
runo
ff
STATSGONALC, MRLCUSGS 7.5' DEM
Conceptual Design of AGWA
Build Model Input Files
Derive Secondary Parameterslook-up tables
Characterize Model Elementsf (landcover, topography, soils)
Discretize Watershedf (topography)
View Model Resultslink model to GIS
Build GIS Database
PRODUCTS
ContributingSource Area
Gravelly loam Soil Ks = 9.8 mm/hr G = 127 mm Por. = 0.453
inte
nsity
time
10-year, 30-minute event
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1992 NALC Hillshade DEM STATSGO
ForestOak WoodlandsMesquite WoodlandsGrasslandsDesertscrubRiparianAgricultureUrbanWaterBarren / Clouds
Land Cover
0 5 10 km
N
GIS Data Layers for AGWA Upper San Pedro Basin, SE Arizona
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CSA: 2.5% (6.9 km2)44 watershed elements29 channel elements
CSA: 20% (55 km2)8 watershed elements5 channel elements
CSA: 5% (13.8 km2)23 watershed elements15 channel elements
CSA: 10% (27.5 km2)11 watershed elements7 channel elements
0 5 10 km
N
the influence of CSA on watershed complexityAutomated Watershed Characterization
Note channel initiationPoint changing with CSA
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64
74
5431 41
1121
51
24
14
4434
9484
0 10 20 km
N
11
14
pseudo-channel 11
channel 14
Abstract Routing Representation
to channel 64
Watershed Configuration for SWAT channel and subwatershed hydrology
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Watershed Configuration for KINEROS
71
7372
74
71
73
72
74
0 5 kmN
Abstract Routing Representation
upland, lateral and channel elements in cascade
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Characterizing the Watershed
complex topography land cover soils high spatial variability complex watershed response
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Characterizing the Watershed
• Homogeneous planes
• Hydrologic parameters represent intersections of topo., cover, soil
• Information loss as f (geometric complexity)
• Scaling issues
Watershed modeling relies on condensing spatialdata into appropriate units for representing processes
leaves plenty of room for error!
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BEGIN PLANE ID = 71, LEN = 1303.0, AREA = 10783378.3 SL = 0.029, MAN = 0.052, X = 593519.0, Y = 3505173.5 CV = 0.92, PRINT = 1 KS = 7.94, G = 118.14, DIST = 0.3, POR = 0.459, ROCK = 0.43 FR = 0.49, 0.33, 0.17, SPLASH = 24.42, COH = 0.006, SMAX = 0.93 INTER = 2.56, CANOPY = 0.133, PAVE = 0.00END PLANE BEGIN PLANE ID = 72, LEN = 765.0, AREA = 4357163.9 SL = 0.043, MAN = 0.054, X = 591637.8, Y = 3507025.3 CV = 0.93, PRINT = 1 KS = 7.77, G = 116.95, DIST = 0.3, POR = 0.459, ROCK = 0.43 FR = 0.49, 0.33, 0.16, SPLASH = 24.61, COH = 0.006, SMAX = 0.93 INTER = 2.85, CANOPY = 0.112, PAVE = 0.00END PLANE BEGIN PLANE ID = 73, LEN = 945.0, AREA = 7405044.9 SL = 0.038, MAN = 0.052, X = 593864.3, Y = 3507560.5 CV = 0.95, PRINT = 1 KS = 8.19, G = 114.97, DIST = 0.3, POR = 0.459, ROCK = 0.43 FR = 0.5, 0.33, 0.16, SPLASH = 24.91, COH = 0.006, SMAX = 0.93 INTER = 2.6, CANOPY = 0.137, PAVE = 0.00END PLANE
71
73
72
74
KINEROS ParameterLook-Up Table
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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 NUMBERHydrologic Soil Group
Curve Number From MRLC
Higher numbers result in higher runoff
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N
Contributing Source Area: 2000 acres - ~5% of total watershed area20 subwatershed elements19 channels
STATSGO ID: AZ061Grassland & desertscrubModerate relief
Sample Watershed Configuration - SWAT
Watershed ID: 7Area: 11.8 km2Slope: 3.7 %Cover: 12.8 %Ks: 18.1 mm/hrCN: 71.8Soil Hyd. Group: BMultiple Soil Horizons
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N
Contributing Source Area: 2000 acres - ~5% of total watershed area33 planes - 7 upland elements - 25 lateral element19 channels
STATSGO ID: AZ061Grassland & desertscrubModerate relief
Sample Watershed Configuration - KINEROS
Watershed ID: 73Area: 7.45 km2Slope: 3.53 %Width: 945 mLength: 7876 mInterception: 2.60 mmCover: 13.70 %Manning's n: 0.052Pavement: 0.00 %Splash: 24.91Rock: 0.43Ks: 6.67 mm/hrSuction: 115 mmPorosity: 0.459Max saturation: 0.93Cv of Ks: 0.95Sand: 50 %Silt: 33 %Clay: 17 %Distribution: 0.30Cohesion: 0.006
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0 1 2 3 5 rainfall depth (mm)
Summer convective stormAugust 11, 2000 high spatial variability high temporal variability difficult to characterize flashy runoff response short duration (45 min)
Winter frontal stormJanuary 13, 2001 low spatial variability low temporal variability lead to little or no runoff long duration (3 hours)
0 5 kmN
Rainfall Characteristics in SE Arizona
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What Could Possibly Go Wrong??
SYSTEMIC ERRORS
These are “hidden” & include:
• Poor conceptual model
• Programming errors AGWA, SWAT, KINEROS
• Poor process representation
• Errors in GIS data Land cover, soils
• Assumptions in the look-up tables
PROCESSING ERRORS
These are “visible” & include:
•Errors in GIS data DEM
•Lack of input data GIS, rainfall
•AGWA fails to characterize watershed
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Rainfall-Runoff Process in SE Arizona
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Spatial Distribution of Rain Gauges
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Typical Distribution Upper San Pedro Basin 6100 km2
15 rain gauges
High Density Watershed Walnut Gulch Exp. WS 148 km2
89 rain gauges
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after Osborne et al., 1985**
Design Storms stored in AGWA
5 yr 30 min10 yr 30 min100 yr 30 min5 yr 60 min10 yr 60 min100 yr 60 min
“create your own”
Sample Design Rainfall Events for KINEROS
Time (min)
Inte
nsity
(m
m/h
r)
100-year, 60-minute
5-year, 30-minute
10-year, 60-minute
** Data reduced “on the fly” for watershed area
0 20 40 60
0
40
80
120
160
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Limitations of GIS - Model Linkage
• Model Parameters are based on look-up tables- need for local calibration for accuracy
• Subdivision of the watershed is based on topography- prefer it 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
• Most useful for relative assessment unless calibrated
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AGWA Gone Awry
Problems Running AGWA
- DEM pre-processing sinks indeterminate boundary converging flow lack of defined flow path (big flat area)
- User error clicking on hill slope
- Data coverage no overlap in GIS data suitability of GIS data f (scale, model)
when good software goes bad
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30m DEM – Level I USGS - unfiltered, unfilled - contains many sinks - has poor drainage - watershed delineation fails
10m DEM from Air Photos - still contains some sinks - exhibits better drainage - boundary is correct - there are still internal failures
10m DEM improved - filtered using high filter - filled to remove 222 sinks - no sinks at the end - good drainage pattern - watershed succeeds; good boundary
smoothing
Watersheds Generated From Different DEMs
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Same points, tolerances, settingsnote differences in results
30m DEM
10m DEM
Parallel channels affect drainage
Sinks interrupt flow
Streams Generated From Different DEMs
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Example of DEM Processing To Avoid Problems
Problem: 30m DEM contains sinks, poor flow direction, and cannot create correct watershedSolution: Filter and fill the DEM before analysis
Negative:
• streams running across the watershed divide
• boundary extends beyond the correct position
smoothing can be good & bad
Positives: • better definition of channels• no sinks• hydrologic connectivity
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Get the Best Available Data!
USGS level 1 USGS level 2
inaccurate flow
minimum CSA lower for Level II
DEM error… banding better boundary
bottom linejunk in = junk out
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User Error
User selected a watershed outlet missed the channel and grabbed a separate basin could also fail to generate a watershed entirely
user selected here
should have selected over here
AGWA Helps With This Problem - AGWA uses a search radius to find maximum flow accumulation - can move the point downstream - use a point coverage to specify outlet
user selects hereAGWA uses here
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Lack of GIS Data Coverage
Commensurate Land Cover, DEM, STATSGO - simple to determine - AGWA can handle small errors through averaging
Land cover does not extend fully
Watershed boundary
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Relative vs. Absolute Change
• Availability of repeat classified imagery for change detection- NALC
• Calibration data set for absolute change analysis- USGS runoff gauging station- Internal validation preferable to calibrating solely on outlet
• Plenty of rainfall data for the time periods - NWS gauges- Potentially NEXRAD radar data
• Confounding effects of land cover change & rainfall data- Uniform vs. distributed rainfall
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Extra Slides Follow
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AGWA Processing Time
Discretization levelWatershed Area (km2)
Boundary Delineation
CSA 20% CSA 10% CSA 2.5%
150 * 0:03 0:22 0:25 0:37
150 0:56 0:28 0:35 0:43
750 1:18 0:48 1:13 1:30
1940 2:03 2:50 2:45 3:20
3370 3:03 5:37 5:43 6:13
7550 6:50 9:05 9:30 10:36
* Data was clipped to a small buffer around watershed
benchmarks on a PIII, 866 MHz, 256 Mb RAM
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Curve Number Modeling
+
Rai
nfal
l
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Determining Curve Numbers