known unknowns measuring and linking geomorphic and biological

responses to dam removal

D. Tullos, Oregon State University02.20.07 - Ecohydraulics

dam removal

dam removal as restoration

restoration is:• reconnecting

habitats and material transport

• releasing 18M yds3 of sediment?

effectiveness monitoring

geomorphic where will the sediment go?

how long will it take to get there?biological

how long does “recovery” take?is ecological recovery detectable?

effectiveness monitoring

well-designed studies will:– consider the size of the dam as well as

indicators of response magnitude– illustrate recovery trajectory of the river– test hypotheses and inform science

effectiveness monitoring - challenges

• how to distinguish the removal signal?• what are realistic expectations for

recovery following removal?• how long will recovery take? • does the recovery extent/timing scale with

dam size?• what site-specific hypotheses/questions

are appropriate and measurable?

the known unknowns

“As we know, There are known knowns.

There are things we know we know. We also know

There are known unknowns. That is to say

We know there are some things We do not know.

But there are also unknown unknowns, The ones we don't know

We don't know."

“I’m not going to give you a number for it because it is not my business to do intelligent work.”

known unknowns of dam removal

• history and philosophy

• case studies on the Sprague, Rogue, and Calapooia Rivers, Oregon

• issues in study design of effectiveness monitoring

• towards known knowns

history and philosophy

why dam removal?

• Federal Energy Resource Commission (FERC) relicensing hydropower projects at expiration of 30,50 year licenses

• 85% of dams in the US will reach the end of their working life by the 2020 (FEMA 1999)

• restoring continuums and reconnecting threatened and endangered fish to habitats upstream

why dam removal?• Oregon Chub (Oregonichthys crameri) – E• Columbia River Chum Salmon (Oncorhynchus keta) – T• Oregon Coast Coho Salmon (O. kisutch) – T• Southern Oregon Coho Salmon (O. kisutch) – T• Upper Willamette River Steelhead (O. mykiss irideus) – T• Lower Columbia River Steelhead (O. mykiss irideus) – T• Middle Columbia River Steelhead (O. mykiss gairdneri) –T• Snake River Steelhead (O. mykiss gairdneri) – T• Snake River Sockeye Salmon (O. nerka) – E• Upper Columbia River Spring Chinook Salmon (O. tshawytscha) – E• Lower Columbia River Chinook Salmon (O. tshawytscha) – T• Upper Willamette River Chinook Salmon (O. tshawytscha) – T• Bull Trout (Salvelinus confluentus) - T • Hutton Spring Tui Chub (Gila bicolor sap.) – T• Borax Lake Chub (Gila boraxobius) – E• Bosket Spring Speckled Dace (Rhinichthys osculus ssp) – T• Warner Sucker (Catostomus warnerensis) - T• Snake River Chinook Salmon - Spring/Summer (O. tshawytscha) – T• Snake River Chinook Salmon -Fall (O. tshawytscha) – T• Lower Columbia River Coho Salmon (O. kisutch) - E• Lahontan Cutthroat Trout (O. clarki henshawi) –T• Lost River Sucker (Deltistes luxatus) – E• Shortnose Sucker (Chasmistes brevirostris) - E Source - ODFW 2004

status of dam removal

• approximately 450 dams removed in US in the last 100 years (AR/FE/TU 1999)

• about 90 percent of Oregon’s small dams are more than half a century old (Brown 2006)

(Heinz Center 2002)

what we know we don’t know

• lack of examples from which to derive expectations

• the utility of existing information is limited: – unsystematic reporting, – insufficient integration of existing data and information

about the river, – a failure to centralize data management (Heinz

Center 2002) – less than 5% of removals resulted in published

ecological research (Hart et al. 2002)

case studies

dam removalChiloquin damRiver: Sprague, OregonHeight: 21’Purpose: irrigation diversionConstructed: 1914Removal: 2008

Savage RapidsRiver: Rogue, OregonHeight: 39’Purpose: irrigation diversionConstructed: 1921Removal: 2008

dam removalSodom damRiver: Calapooia, OregonHeight: 15’Purpose: mill diversionConstructed: 1940sRemoval: 2009

Brownsville damRiver: Calapooia, OregonHeight: 7’Purpose: mill diversion, estheticsConstructed: 1960’sRemoval: 2007

effective monitoringphysical

– substrate size distribution– discharge – channel geometry– mapping facies/features

chemical– temperature– SSC/turbidity

biological– vegetation– benthic macroinverts– habitat quality– fish

ambitious monitoringwith the objectives of:• documenting geomorphic and

biological responses• evaluating reliability of

indicators– responsiveness to dam removal– detectability– feasibility of measurement

• satisfy permit requirements, scientific interest, and stakeholder outcomes

flytyingworld.com (above)

massaudobonblogs.com (below)

issues in study design

• not replicates – “one of several identical experiments, procedures, or samples”

• not observational studies –more than purely descriptive

• case studies – documents recovery and advances science

issues in study design

• begin with BACI (Before After Control Impact)– reference– reservoir– downstream

• some pre-removal data, sometimes• some control at reference, sometimes

only part of BACI is the Impact?

issues in study design

• regularly spaced transects - status based, reach-wide assessment

• irregular transects along targeted response areas – testing responses at areas of geomorphologically and ecologically significance

recovery assessment vs. hypothesis testing?

issues in study designreach-wide assessments• deepest pools and riffles

often did not fall along regular transects (also see Stewart 2006)

• pebble counts characterized surface substrates coarser than bulk samples

targeted response areas• issues in reliability and

resources of technology

deciding on a study design…

deciding on monitoring objectives

– informing stakeholders – reach-wide assessment of recovery

– improving predictability and advancing the science – targeted hypothesis testing

– or both?

deciding on a study design…deciding on relevant geomorphic processes and biological

responses

1. uncertainty in geomorphic processes = f (dam effect size) 1. feature formation/erosion2. narrowing/widening3. aggradation/degradation

2. baseline assessments can inform hypotheses about geomorphic processes and monitoring strategy1. volume of stored sediment/average annual sediment discharge2. T*, S*3. width of reservoir/width of channel

however…

issues in study design

uncertainty in biological responses• how many more fish?• how long before we see more fish?• is dam removal responsible for more fish?• is change detectable?

known unknowns

statistical power analysis

• power (precision, repeatability) = the probability of detecting a change given that a change has truly occurred

• based on:– effect size– sample size– α– variance of the indicator– statistical model

Required power for Effect Size

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0 0.2 0.4 0.6 0.8 1

power

effe

ct s

ize

\

0

200

400

600

800

1000

1200

1400

% changeno of fish

adult coho population estimates

beyond a black BACI box

issues with BACI for dam removal– US/DS not independent– short/absent pre-removal– highly variability of indicators– ‘random’ effects

value of p values?

reducing uncertainty

• adult migration timing and attempts• larval drift outmigration• community composition• genetics• spawner recruitment• primary/secondary productivity

theme?

image: Colorado State University

mechanistic monitoring?

$$$$$how to choose?

direct vs. indirect effects = satisfied stakeholders?

mechanistic monitoring

– size of dam influence, removal strategy, and operation– ecological condition

– land use and geologic history

Hart et al. 2002

towards known knowns

learning from history(we’re all lunatics, knaves, and fools)

• all are lunatics, but he who can analyze his delusions is called a philosopher (i.e. PhD)

• HISTORY, n. an account mostly false, of events mostly unimportant, which are brought about by rulers mostly knaves, and soldiers mostly fools.

(Ambrose Bierce)

effectiveness monitoring- a process

1. define monitoring objectives2. identify relevant and accessible existing data resources3. define study design and identify reaches of interest4. baseline assessment

• analysis of aerial photograph/historical records• surveys of reservoir and downstream features (e.g. bars, margins,

islands, pools, riffle crests)• habitat quality• bed material characteristics• hydrology and suspended sediment regimes

5. determine dam ‘effect size’ and define appropriate monitoring questions and metrics

6. pre-removal monitoring7. drawdown and removal monitoring8. post-removal monitoring

integrating existing data resources

• local (city, county resources)• state (ODEQ)• federal agencies (USACE, BLM, USDA,

USEPA, USBR)• universities & NGOs

how to utilize and integrate existing information?

inconsistency of data resources• diverse data formats and types:

– qualitative, quantitative, semi-quantitative– statistical, probabilistic – frequency, timing, location of sampling

• needed: development of a centralized andsystematic framework, including dam removal:

– metadata– data repository – data management standards

effectiveness monitoring- a process

1. define monitoring objectives2. identify relevant and accessible existing data resources3. define study design and identify reaches of interest4. baseline assessment

• analysis of aerial photograph/historical records• surveys of reservoir and downstream features (e.g. bars, margins,

islands, pools, riffle crests)• habitat quality• bed material characteristics• hydrology and suspended sediment regimes

5. determine dam ‘effect size’ and define appropriate monitoring questions and metrics

6. pre-removal monitoring7. drawdown and removal monitoring8. post-removal monitoring

appropriate questions1. linking ecological and

geomorphic processes2. selecting appropriate metrics

and methods:• uncertainty/error• data type (quantitative or

qualitative descriptive, probabilistic, statistical)

• advantages• disadvantages• $/activity

3. resources availability

questions, metrics, & methods

data collection - data analysis

• statistical - ANOVA• probabilistic – RYI• descriptive – distributions• illustrative – recovery trajectories

data analysis - probabilistic

• likelihood predictions with error envelopes– RYI to erode X% of stored sediment– RYI required to flush downstream deposited

sediment

Lorang and Aggett 2005

data analysis - distributions

USGS 2006

data analysis - illustrative

0

5

10

15

20

25

30

35

40

0 10 20 30 40 50 60 70 80 90 100

% substrate coarse gravel

% m

ayfli

es

pre-removalyear 1

year 2

year 3

questions?

acknowledgements

phil kaufmann

phil larson

george pess

cara walter

gordon grant

For more information:http://rivers.bee.oregonstate.edu