Project Update: Upper Great Lakes StudyShore Protection

Teleconference29 March 2011

Mike Davies, Ph.D., P.Eng.Coldwater Consulting Ltd.

OutlineShore Protection Performance Indicators -       Review and discussion of model operation and results by

Coldwater Consulting Ltd. (conference call) -       Application in the Shared Vision Model and interpretation of

metrics for 

o       Regulation plan evaluation o       Water level “restoration” o       Multi-lake regulation and AM

 -       Performance indicator fact sheet 

Draft report - updateVersion 0.11 transmitted last week.Subsequent changes:

We have moved Sections 5.6 and 5.7 to Chapter 7 (“Interpretation”).

Chapter 6 has become a part of Chapter 5.

Working on data gaps / future needs and Conclusions.

Model operation (function)Using Available:• Wave, • Surge, • Bathymetric and • Profile dataDeveloped• Wave transformation model (shoaling and refraction to pre-process

WIS to 10m contour then linear theory (shoaling with breaking) to toe of structure

• Wave runup and overtopping model (probability-based using Eurotop)

• Downcutting model (Parametric toe scour – PTS, based on CPE simulations including reflection effects)

Combined these ‘process’ models to simulate time evolution of damage

• “Life-Cycle simulations”• One month time-step

Model operation (mechanics)UGLSP – Stand-alone model for prediction of life-cycle performance

and cost of ownership of coastal structuresSAT - .dll version of UGLSP suitable for operation from within Excel

(integrated into SVM).

Methodology

107 yr Simulations (month-by-month)

Erodibility Index

Structure

geometry

Offshore waves,Surge

Stochastic Structures• 1,000 statistically-derived

structures• Summary statistics

•Plan 77b•Plan 1887•Plan MH•Plan S4S•...Water

level scenario

s

25 sites

The ‘Stochastic Structure’Probability-based representation of coastal structuresUses the observed statistical distribution of structure characteristicsExtended throughout Upper Great Lakes domain using design water

level scalingA 1,000 structure sample is generated that matches the target

statistical distributionSplit between Class 1 and Class 2 structures is 65/35%Crest elevations are defined relative to the 100-yr design water levelToe elevations are defined relative to chart datum

Type Class 1 Class 2Revetment 82% 29% 71%Wall 18% 90% 10%

Structure data

Structure geometries and characteristics come from three datasets

Lake and Cook Counties, IL

Racine County, WI

Collingwood-Wasaga, ON

Structure dataCrest and Toe DistributionCrest elevations from the three datasets collected in Lakes Michigan

and Huron (CD = 176.0 m) were combined to produce a single dataset. Only structures broadly classified as revetment and seawalls were included.

Crest elevation data from various Lake Michigan locations

and fitted normal (Gaussian) distribution

0

0.02

0.04

0.06

0.08

0.1

0.12

0 2 4 6 8 10 12

Pr

m, CD

Michigan-Huron data

Normal distribution

Stochastic StructuresMichigan-HuronStructure Type

Mean (m, CD)

Standard deviation

(m)Notes

Crest 3.044 0.803Revetment Toe 0.0 0.5 Cannot be higher than 1 m below crestSeawall Toe -1.0 1.0 Cannot be higher than 1 m below crestBerm - - Must be 1 m below crest and 1 m above toe,

or taken as toe elevation (i.e., no berm)

0

10

20

30

40

50

60

-4 -2 0 2 4 6

Coun

t

Elevation (m, CD)

toe

berm

crest

0

50

100

150

200

250

300

350

400

-4 -2 0 2 4 6

Coun

t

Elevation (m, CD)

toe

crest

SuperiorStructure Type

Mean (m, CD)

Standard deviation

(m)Notes

Crest 1.844 0.304Revetment Toe 0.0 0.5 Cannot be higher than 1 m below crestSeawall Toe -1.0 1.0 Cannot be higher than 1 m below crestBerm - - Must be 1 m below crest and 1 m above toe,

or taken as toe elevation (i.e., no berm)

Probabilistic SimulationsLoop through all study sites (25)

Loop through all months (12x107)Loop through all structures (1,000) Loop through all regulation plans (p77, 1887, S4H, MH,

etc.)Downcutting – transform Heq from 10m contour to structureD/C uses a randomly generated wave of Heq from µ,σ(Heq) of

monthDowncutting (parametric toe scour)Runup wave transformation is similar but with Hmax (the

expected max Hs that month) and associated monthly surge (random # based on µ,σ(Surge) of month)

Wave runup computed using Eurotop (2007)Overtopping uses cdf of Hs for that monthWave overtopping - Eurotop(2007), adapted for low-crested

structures and to ensure smooth transitions between various algorithms P(f)OTStructure maintenance costs

Rebuild costOvertopping cost = P(f)OT x rebuild cost

Structure costsCosts are based on the monthly cost of ownership.

Overtopping cost = P(f) OT x rebuild costRebuild cost is computed each month based on structure type & height.Degradation cost = linear depreciation (50yrs for Class 1, 25 yrs for Class 2-)Cost for month = max(Overtopping, Degradation)

Overtopping failure occurs when P(f) OT>0.5; Flag to output, triggers re-buildStructure is rebuilt with crest 25% higher; structure has 12 month rebuild window. During rebuild window, structure cannot fail a second time.

Downcutting cost increases cost of ownership by virtue of increased depth, taller structure being required.

Downcutting allows large waves to reach the structure; increasing likelihood of failure due to overtopping.

Growth algorithm: If downcutting deepens the toe, the crest height grows at a rate of 0.2

(Class 1) or 0.3 (Class 2) x the downcutting. This is based on Eurotop algorithms to maintain constant OT performance.

25 Modelling zones

Zones are spatially distributed throughout Superior and Huron-Michigan

Summary ‘forcing’ statistics are shown below.

25 Modelling zonesShore classification database used

to identify substrates susceptible to downcutting

Erodibility index was developed to guide calculation of downcutting – a major factor for shore protection in areas of erodible beds.

25 Modelling zonesExtent of shore protection varies

widely from 0 in NE Superior to 62% near Chicago

SurgeStatistical analysis of 2yr return period surge elevations based on measured data (green diamonds)

WavesWaves are based on available hindcast datasets

Results

Total Costs

Example results: Plan 130

InterpretationTotal Costs relative to 77A

The numbered plans (Plan 122 through to Plan 130) all produce fairly similar results. For this reason, only results for Plan 55M49, Plan 126 and Plan BAL1 are discussed further

Spatial pattern of cost difference 55M49

Spatial pattern of cost difference BAL1

Cost and downcutting impact of 126 vs 77A

Overtopping 126 vs 77A

Dry times 1930s

Wet times 1960s

End