modeling long-term progressive erosion at the west valley site 2018/qpm... · modeling long-term...
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Modeling long-term progressive erosion
at the West Valley site
Erosion Working Group modeling team:
Gregory E. Tucker1, Katherine R. Barnhart1, Sandra G. Doty, Rachel Glade2,
Mary C. Hill3 , Matthew Rossi1, Charles M. Shobe1
1 – CIRES and Department of Geological Sciences, University of Colorado, Boulder
2 – INSTAAR and Department of Geological Sciences, University of Colorado, Boulder
3 –Department of Geology, University of Kansas
West Valley Quaterly Public Meeting, February 28, 2018
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Approach involves six major steps
DEVELOPA SET OFEROSIONMODELS
ANALYZESENSITIVITY
TO INPUTS & PARAMETERS
CALIBRATEBASED ON
GEOLOGIC PAST (13,000 YRS)
VALIDATEUSING
SECONDWATERSHED
IDENTIFYBEST-
PERFORMINGMODELS
PROJECT POTENTIALFUTURE EROSION,WITH QUANTIFIED
UNCERTAINTIES
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Models simulate long-term erosion at gridded locations in a drainage basin
• Developed 37 process models
• Each model incorporates:– Mass movement
– Hydrology
– Channel/gully erosion
– Material properties
• Grid resolution is 24’
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SDA
WVDP
Erosion Working Group Study 1 data allow reconstruction of past topography and downcutting history
modern topography
alternative reconstructions of paleo (~13 ka) topography, with post-glacial ravines filled in
3 k
m
Downcutting history at outlet
(data from Erosion Working Group Study 1;R. Young & M. Wilson)
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Input parameter ranges are informed by results from Erosion Working Group field studies
Soil / till erodibility
Soil infiltration capacity
Channel grainsize
SOURCE: S. Bennett (2017)Report of the West Valley Erosion Working Group Study 2: Recent Erosion and Deposition Processes.
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Sensitivity analysis shows low sensitivity to downcutting history or paleo-topography
EXAMPLE OF SENSITIVITY TO PARAMETERS, INITIAL CONDITIONS, AND LOWERING HISTORY FOR MODEL “BasicRt” 6
K1 = till erodibilityK2 = rock erodibilityD = soil transport efficiencyWc = contact-zone thickness
Models and parameters are tested by comparing observed and simulated modern topography
MODERN TOPOGRAPHY (CENTER) COMPARED WITH FOUR MODEL RUNS
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Calibration used to test and rank models and identify best parameters
• At least two possible reasons for a poor fit:1. Poor model2. Great model but wrong parameter choice
• Calibration provides:– Optimal parameter values– Measure of goodness of fit for each model
• Calibration performed on CU’s Summit supercomputer– Project overall required over 1.3 million CPU hours– 34 of 37 successfully calibrated
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Moderntopography
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Example Calibration: Basic Model(rank 25 of 34)
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Observed versus modeled terrain:Basic model
OBSERVED BASIC MODEL (rank 25 of 34)
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Calibration example #2:Model “BasicChRtTh”(rank 1 of 34)
DRAFT calibration,to be revised.Model BasicChRtTh.Duration 13,000 years.
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Observed versus modeled terrain:Erosion threshold, nonlinear hillslope law, rock and till
OBSERVED BASIC MODELWITH EROSION THRESHOLD,NONLINEAR HILLSLOPE LAW,AND ROCK AND TILL UNITS
(rank 1 of 34)
DRAFT calibration,Model BasicChRtTh.Duration 13,000 years.
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SUMMARY OF CALIBRATION RESULTS
LOWER SCORE (VERTICAL AXIS) INDICATES A BETTER-PERFORMING MODEL 14
Models were validated by running on a nearby watershed of similar size and relief
OBSERVED
SIMULATED
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SDA
WVDP
Models that performed well in calibration also performed well in validation tests
• Top 9 models in calibration and validation selected for erosion projection
• Top-performing models distinguish between glacial sediments & bedrock16
Future projections quantify uncertainty in five main areas:
• Future climate: run three alternative scenarios
• Future downcutting on Buttermilk: run three alternative scenarios
• Terrain modification by humans: run ensemble of simulations with random +/-5’ elevation perturbations
• Model structure: run 9 different models
• Model parameters: propagate calibration uncertainty forward into prediction (seven models only due to compute time limits)
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Sensitivity tests examine uncertainty from two additional sources:
• Potential for upper Franks capture by gully: run capture-from-southeast scenario
• Potential for rapid Buttermilk widening: run capture-from-east scenario
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Scenarios for future climate were developed using MACA climate-model downscaling product
Data source: Multivariate Adaptive Constructed Analogs (MACA) Datasetshttps://climate.northwestknowledge.net/MACA/
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Three future climate
scenarios1. Representative Concentration
Pathway (RCP) 8.5: Increase mean wet day totals to 2100, then stabilize
2. Representative Concentration Pathway (RCP) 4.5: Increase mean wet day totals that level off by 2100
3. No change in mean wet day precipitation
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MEAN ANNUAL PRECIPITATION
MEAN WET-DAY PRECIPITATION
PRECIPITATION FREQUENCY
Three scenarios for future downcutting on Buttermilk Creek
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Erosion projections plotted for 25 selected points at site
• Time intervals of 100 years
• All model and scenario projection runs store data for every grid location
• Parameter uncertainty runs focus only on the 25 points
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SDANDA
Dominant source(s) of uncertainty may vary from one location to another, and through time
• Sources include:
– Unknown future climate
– Unknown future rate of lowering in surrounding areas
– Small variations or perturbations in topography
– Parameters in erosion models
– Model structure
• Side-by-side comparison of projections with two different models illustrates model structure uncertainty
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MODEL “BasicRt”10,000-year run
Lowering scenario 2
MODEL “BasicChRtTh”10,000-year run
Lowering scenario 2
Example of model structure uncertainty
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Example of uncertainty in initial topography
(representing human modification of landscape)
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800 802 842
0.0 2.5 5.0 7.5 10.0 0.0 2.5 5.0 7.5 10.0 0.0 2.5 5.0 7.5 10.0
1300
1325
1350
1375
Model Time (ka)
Ele
vatio
n (
ft)
lowering_future
lowering_future_1
lowering_future_2
lowering_future_3
climate_future
constant_climate
RCP45
RCP85
sew SDA2 IC Uncertainty
MODEL
Example of erosion
projections at a point, with uncertainty arising from
parameter value uncertainty
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800
0.0 2.5 5.0 7.5 10.0
1320
1340
1360
1380
Model Time (ka)
Ele
vaio
n (
ft)
lowering_future
lowering_future_1
lowering_future_2
lowering_future_3
climate_future
constant_climate
RCP45
RCP85
At-a-point predictions with uncertainty bounds,combining all quantified
uncertainty sources
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SDA4 SDA5 SDA6 UFrankEdge1 UFrankEdge2
ProcessBLD QuarryEdge SDA1 SDA2 SDA3
NDA1 NDA2 NDA3 NDA4 NDA5
HLWT1 HLWT2 Lagoon2 Lagoon3 LFrankEdge
ErdmanEdge GullyHead1 GullyHead2 GWPlume1 GWPlume2
0.0 2.5 5.0 7.5 10.00.0 2.5 5.0 7.5 10.00.0 2.5 5.0 7.5 10.00.0 2.5 5.0 7.5 10.00.0 2.5 5.0 7.5 10.0
1200
1250
1300
1350
1400
1200
1250
1300
1350
1400
1200
1250
1300
1350
1400
1200
1250
1300
1350
1400
1200
1250
1300
1350
1400
Model Time (ka)
Ele
va
tio
n (
mu
lti−
mod
el expecte
d v
alu
e ±
2σ
, ft
)
Method
Model 842 Only
Nine Model Average:Independent
Nine Model Average:Combined
Model−CalibrationUncertainty Approach
Independent
Combined
Comparison of Three Uncer tainty Quantification Methods
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Relative contributions of different sources of uncertainty, by location and time
Example of ensemble-based projected erosion maps
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EXPECTED EROSION UPPER 95% PERCENTILELOWER 95% PERCENTILE
9-M
OD
EL C
OM
PO
SITE
Summary of uncertainty results
• Major sources of uncertainty in future erosion estimates include:– Initial topography / human modification of landscape
– Model structure
– Model parameters
• Other sources are:– Climate
– Downcutting in Buttermilk valley
• Degree of uncertainty and relative importance of different sources varies among locations
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= Model selection and calibration}
Erosion modeling provides information for further erosion assessment:
• Calculations of potential future erosion at each model grid cell
• Calculations include quantitative estimates of uncertainty in model structure, future climate, initial topography, and future Buttermilk Creek downcutting
• Estimates of uncertainty arising from model parameters are provided 7 models at 25 selected points– Workflow and codes available to perform calculations for other models
and/or locations
• Scenarios also calculated for potential capture of upper Franks Creek by gully erosion to the southeast or Buttermilk valley widening near Heinz Creek fan
• Process model results provide basis for probabilistic modeling of erosion using multiple alternative scenarios
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QUESTIONS?
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