Hydrologic network metrics based on Hydrologic network metrics based on functional distance and stream dischargefunctional distance and stream discharge

David Theobald & Mary Kneeland

Natural Resource Ecology Lab

Dept of Recreation & Tourism

Colorado State University

Fort Collins, CO 80523 USAMay 16, 2003

Goal: develop approaches for spatio-temporal design and modeling in order to further our understanding of aquatic resources

Objectives, to develop:1. spatio-temporal models for a continuous

response, 2. spatio-temporal models for count and/or

categorical data, 3. design and analysis methods for data collected

at different scales.

STARMAP ProjectsSTARMAP Projects

1. Combining environmental datasets (Hoeting)

2. Local inferences (Briedt)

3. Development and evaluation of landscape indicators (Theobald)

4. Extension and outreach (Urquhart)

5. Integration and coordination (Urquhart)

Big questions:Big questions: Broad-scale processes (e.g., acid deposition in

Mid-Atlantic region) to watershed processes Probability-based sampling for state compliance

to CWA Sampling perennial/intermittent streams (I.e.

flow all year for most years)– What is perennial and shouldn’t be? (~24%)– What is not included and should be? (~18%)

Fragmentation of hydrologic regime on biodiversity

Goals of indicator developmentGoals of indicator development

Develop and evaluate landscape-level indicators suitable for spatial and temporal analyses of EMAP data

Investigate limitations of currently-available data and offer new, robust methodologies

Overview of presentationOverview of presentation

Link watershed and hydrologic network: “…in every respect, the valley rules the stream.” – Hynes 1975

From surrogates to direct measuresTowards network-based metrics

Indicators that measure Indicators that measure watershed characteristics and watershed characteristics and aquatic ecology: Reviewsaquatic ecology: Reviews1. Land use in entire watershed vs. riparian buffer

(IBI):- watershed better: Richards et al. 1996- buffer better: Arya (1999); Lammert and Allan (1999)

2. Other indicators:- road density (Bolstad and Swank)- dam density (Moyle and Randall 1998)- amount of roads near streams (Moyle & Randall) and Arya (1999)

Key: measuring watershed-Key: measuring watershed-stream linkage?stream linkage?1. Lumped measures

- %, #, density

2. Spatially-explicit- Euclidean distance

3. Network-based (directional, cumulative)- Strahler stream order- Length of stream line- Watershed area

4. Direct network-based- Discharge?!

1. Lumped1. Lumped % agricultural, % urban Ave road density Dam density (Moyle and Randall 1998)

# mines Road length w/in riparian zone

EPA. 1997. An ecological assessment of the US Mid-Atlantic Region: A landscape atlas.

Southern Rockies Ecosystem Project. 2000.

1. Lumped (cont.)1. Lumped (cont.)

ArcINFO, Basinsoft (Harvey and Eash 1996):– Drainage area, shape, relief– # O1 streams, main channel length,

stream density

2. Spatially-explicit, 2. Spatially-explicit, Distance:Distance:

As the crow flies (Euclidean)

3. Network-based3. Network-basedDistance:Distance:

As the seed floats (downstream)

Distance:Distance: As the fish swims

(down & up stream)

Distance:Distance: Upstream length

- mainstem (2)- arbolate (1+2+3+4)

Upstream66 km

Downstream298 km

MainstemUpstream37 km

Network16 km (down)6 km (up)

RWTools ArcView v3 extension

Direct measuresDirect measures

Surrogate, e.g. Strahler order:

The usefulness of stream order assumes, with a sufficiently large sample, that order is proportional to stream discharge – Strahler 1957

Ordinal data

Not robust to data artifacts

Link watershed and networkLink watershed and network 1 to 1 relationship

between stream reach and catchment

Need robust method of delineation for

large extents

Pilot area: Colorado, YampaPilot area: Colorado, Yampa

““Smart bump” delineationSmart bump” delineation1. Reach catchment

- flowdirection 30 m DEM- watershed from buffered hydrology (USGS NHD 1:100K)

2. Differentiate local ridges (artifacts) from true catchment boundary - “smart bump” using ZONALMIN

3. Remove conversion slivers at shared boundaries- regiongroup- if <10 cells, NIBBLE

Currently, 1-2 days processing time per basin

Comparison of automated vs. Comparison of automated vs. hand-delineatedhand-delineated

1. Randomly selected 111 (out of 2151 watersheds)

2. Computed area of automated vs. hand-delineated (“truth”)

3. RMSE = 204.39 (in ha)4. Mean error 2.4%5. Challenges in defining

commensurate watersheds

Hand-Hand-delineated delineated “truth” “truth” watershedswatersheds11% error

Reaches are linked to catchmentsReaches are linked to catchments

1 to 1 relationship Properties of the

watershed can be linked to network for accumulation and networking operations

Ordinal value (order) to real value (length, area, etc.)

NetworkingNetworking

Import into ArcGIS Geometric Network

Use networking tools, e.g.

1. Set flag

2. Trace upstream

3. Trace downstream

4. Direct metric: stream discharge4. Direct metric: stream discharge

Physical-based model:

Q = Precipitation –Evapotranspiration

Q is VMAD (Virgin Mean Annual Discharge)

USGS Stream Gauges

R2=0.7282

P-value=3.407e-006

Surrogate Surrogate Direct metric Direct metric

OrderAreaDischarge

Fragmentation and flow regulationFragmentation and flow regulation

Deynesius and Nilsson, Science (1994) – 77% of upper 1/3 of northern hemisphere rivers are strongly or moderately affected- F = regulated/total channel length- R = % of VMAD (cumulative reservoir live, gross capacity)

RCL

TCL

Alteration of natural flow regimeAlteration of natural flow regime

Accumulation of dam storage

Tributaries below dams mediating flow modification?

Flow modificationFlow modification

How to measure relative modification of hydrologic regime?1. Degree of modification to flow = cumulative annual flow – cum. dam max. storage:

Q’ = Q-S2. Proportion of modified to VMAD (“natural”) flow:

F = Q’/Q

High

Dam “shadow”

Reservoirs

Or/COOr/CO

Table of output dataExpand this to other factors: e.g.,

geology, vegetation, etc.Linked to rest of data

EMAP sitesEMAP sitesSITE_ID UTM_X UTM_Y Perennial VMAD (acft) may_flow oct_flow Basin Area (m2)dam_accumWCON99-0003 286761 4459213 no 1049 88 84 2181600 0WCON99-0007 327707 4257031 no 61145 4329 4979 174219300 0WCON99-0022 343400 4324332 no 2411 173 163 3762000 0WCON99-0027 299456 4472729 no 2901 253 267 7587000 0WCON99-0043 167974 4475774 no 1395 147 170 4833900 0WCON99-0050 241385 4357041 no 2441 224 232 6010200 0WCON99-0056 384823 4369339 no 105055 8593 6186 200349900 2160WCON99-0057 219593 4317281 no 110797 12869 10499 156833100 637WCON99-0072 261920 4504833 no 29455 2800 2562 75493800 0WCON99-0081 251563 4506939 no 19761 1918 1754 51792300 0WCON99-0085 236471 4250961 no 5561 405 555 17300700 0WCON99-0087 313770 4326421 no 106587 6298 6434 119459700 0WCON99-0088 294571 4319625 no 149910 12227 15358 243615600 17589WCON99-0100 229070 4540158 no 13088 1411 1210 42529500 0WWYN99-0024 233606 4565619 no 41630 5581 3716 232304400 0WWYP99-0589 304096 4550484 yes 27982 2552 1950 55316700 0WCOP99-0578 330168 4537347 yes 186077 16419 10856 267651000 0WCOP99-0512 306389 4503840 yes 160393 13697 10608 239858100 0WCOP99-0565 307627 4499698 yes 186182 15957 12556 291218400 0WCOP99-0601 253215 4480887 yes 4340038 379626 331549 8267067900 519759WCOP99-0596 379359 4450211 yes 194238 15918 13611 379411200 3865WCOP99-0571 337832 4415185 yes 4899263 450024 319170 10753651800 16681192WCOP99-0595 267481 4391449 yes 61407 5532 4571 113334300 0WCOP99-0517 248712 4390205 yes 1215 110 105 2119500 0WCOP99-0570 210402 4371194 yes 49830 4651 4371 110944800 0WCOP99-0505 291346 4345579 yes 4018 296 390 5058000 0WCOP99-0594 160492 4344097 yes 26186703 2114426 2185258 64065845872 18371090WCOP99-0503 364245 4335445 yes 17514 1347 1128 25980300 0WCOP99-0501 255370 4295958 yes 1503776 115988 142188 2908662300 125267WCOP99-0501 255388 4295958 yes 1503776 115988 142188 2908662300 125267WCOP99-0597 286917 4274224 yes 13965 987 915 23783400 0WCOP99-0567 204620 4268705 yes 19670 999 2327 31345200 0WCOP99-0561 354155 4250546 yes 53912 3739 4235 147976200 920WCOP99-0574 290214 4210647 yes 102709 7073 8079 159713100 0

OregonOregonSITE_ID perennial Albers X Albers Y VMAD (acft) Catch Area (m2)WORN99-0016 no -2094094 1095330 12873 13126500WORN99-0025 no -2119705 1035322 24151 23542200WORN99-0088 no -2124416 1118661 3450 3390300WORN99-0096 no -2064091 1187865 2785 3070800WORP99-0516 yes -2061698 1191106 5609 5822100WORP99-0666 yes -2091159 1176117 15139 14463000WORP99-0597 yes -2089295 1166791 34608465 26957114154WORP99-0597 yes -2089295 1166791 34608465 26957114154WORP99-0501 yes -2025974 1121503 696628 402086700WORP99-0735 yes -2083158 1130921 80251 65678400WORP99-0657 yes -2047240 1108615 2272 1138500WORP99-0519 yes -2130764 1089984 16583292 13528536554WORP99-0507 yes -2134772 1081048 970218 916844404WORP99-0669 yes -2129081 1025428 2162883 1829772000WORP99-0669 yes -2129081 1025428 2162883 1829772000WORP99-0659 yes -2126543 996469 13135 10544400WORP99-0503 yes -2081208 966596 14100 9510300

+ dam accumulation+ overlap of catchment area

Within catchment hydrologic Within catchment hydrologic distancedistance

Moved from basins, HUCs and watersheds to stream reach catchments

Within catchment:– Distance along hydro network

distance (distance along the network upstream of pour point)

– Allocation (using flat weight surface)

1

ChallengesChallenges

DataNHD 1:100KDams – NID

Processesnatural flowdiversionsET

Data: attribute errorsData: attribute errors

Irrigation canals and pipelines incorrectly attributed as river/stream

Data: Data: positional positional errorerror

Spatial location of dam locations is imprecise

??

Data: Data: duplicatesduplicates

Stagecoach reservoir is duplicated – Challenges of understanding diverse datasets

Data: Data: missing missing data?data?

?

ScaleScale

Dam on tributary that is not in 1:100K network

NID dams (red) > 50’ high, many other dams (in yellow) and other structures!

Dam dataDam data

Western Water Assessment, Figure 7

Network metricsNetwork metrics

Have foundation – direct measure Build on/refine existing metrics:

– # first order streams– Main-channel length– Total stream length– Drainage density = stream length /

catchment area Examine location within network and

make available to statistical models

EMAP EMAP sitessites

Euclidean distanceEuclidean distance

1

2• Use x,y to create

distance matrix

• Reasonable for broad-scale processes

Hydrologic distanceHydrologic distance

1

2• Follows stream

network

3

4

Spatial weightsSpatial weights

11 2

3 54

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

1 0 1 0 0

0 1 0 1 0

W =

Functional distanceFunctional distance

• Reflect distance

weighted by:- Stream gradient

- Geology

- Land use

- Etc.

1.7

1.2

1.9

1.0

A

B

C

Functional weighting Functional weighting

1

1 2 3

54

0 0 0 0 0 0 0

0.7 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0.7 0 0 0

0.2 0.8 0 0.2 0.8 0 0

0.1 0.2 1.0 0.1 0.2 1.0 0

W =

6 7

E.g., downstream hydrology

Connectivity matrixConnectivity matrix

To/ from 1 2 3 4 5 6 7

1

2

3 1 1

4 1 1 1

5

6

7 1 1 1 1 1 1

Functional spatial weightsFunctional spatial weights

Station Discharge (kacft)

1 1501

2 4

3 1515

4 9651

5 84

6 82

7 9972

1

2

34

56

7

Station Order Area overlap

(%, km2)

Length (m)

Discharge

1 3 5 5 98%=2900/2952 4532 99.00%

1 4 5 5 11%=2900/25316 42568 15.00%

1 7 5 5 11%=2900/26001 58389 15.00%

2 3 1 5 0.4%=14/2952 23121 0.20%

2 4 1 5 0.05%=14/25316 59715 0.04%

2 7 1 5 11%=14/26001 75536 0.04%

3 4 5 5 11%=2952/25316 38105 15.00%

3 7 5 5 11%=2952/26001 53925 15.00%

4 7 5 5 97%=25316/26001 15820 96.00%

5 7 2 5 0.5%=145/26001 54964 0.80%

6 7 4 5 0.5%=140/26001 30933 0.80%

Incorporate watershed conditions? Incorporate watershed conditions?

1

1 2 3

54

0 1 0 0 0 0 0

1 0 0 0 1 1 0

0 0 0 0 0 0 0

0 0 0 0 1 0 0

0 1 0 1 0 1 0

0 1 0 0 1 0 1

0 0 0 0 0 1 0

W =

6 7

E.g., macroinvertebrates

ChallengesChallenges

Generating spatial weights matrix– O(n2) O(n)?

Functional (cost-weighted) spatial weights table

ProductsProducts

Watershed-reach network databaseGIS-based tool to develop

functional spatial weights matrixArcGIS extension for hydrologic

network metrics

Thanks! Comments? Questions? Work funded by: US-EPA STAR Cooperative agreement CR829095 awarded

to CSU STARMAP: www.stat.colostate.edu/~nsu/starmap RWTools: email davet@nrel.colostate.edu