Small steps and giant leaps? - Purdue...

Small steps and giant leaps? (Thoughts for the future based on a decade of progress in

© John Wainwright: [email protected]

(Thoughts for the future based on a decade of progress in understanding and modelling hydrologic and erosion processes)

John WainwrightDepartment of Geography, University of Sheffield(Durham University from 1/10/11)

ISELE September 20th 2011 Anchorage

…with a little help from:

• Tony Parsons

• Eva Müller

• Laura Turnbull

• Richard Brazier

• James Cooper

• Peter Biró

• James Millington

• Irantzu LexartzaArtza

• Tristan Ibrahim

• Becky Briant


• Ben Kitchener

• Graham Hargrave

• Ed Long

• Mark Powell

• Greg Okin

• Jill Stewart

• Banti Fenti

• Roger Simanton

• Yuichi Onda

• Tomomi Furukawa

• Eiichiro Obana

• Becky Briant

• Gareth Mottram

• Brandon Bestelmeyer

• Ed Fredrickson

• Bill Schlesinger

• Athol Abrahams

• Andy Baird

• Nikki Dodd

• Sarah Dunn

• …

The problem


Overall framework

space travel distance

Lajeunesse

et al. (2010) WRR

Geomorphology


time

space-time(process)

methodology?

virtual velocity

connectivity

Wainwright et al. (2011) Geomorphology

A small step backwards ...

• Why model? Epstein’s Sixteen Reasons Other Than Prediction to Build Models (JASSS vol. 11, no. 4 12):

1. Explain (very distinct from predict)

10. Demonstrate tradeoffs / suggest efficiencies


predict)

2. Guide data collection

3. Illuminate core dynamics

4. Suggest dynamical analogies

5. Discover new questions

6. Promote a scientific habit of mind

7. Bound (bracket) outcomes to plausible ranges

8. Illuminate core uncertainties.

9. Offer crisis options in near-real time

suggest efficiencies

11. Challenge the robustness of prevailing theory through perturbations

12. Expose prevailing wisdom as incompatible with available data

13. Train practitioners

14. Discipline the policy dialogue

15. Educate the general public

16. Reveal the apparently simple (complex) to be complex (simple)

A simple exercise in data collection? (A historical step backwards)

A journey of a thousand


A

B

C

a thousand miles begins with a single step

Lao-Tzu

upslope

downslope© John Wainwright: [email protected]

Parsons et al. (1993)

What do we measure when we measure “erosion”?


Conventional (implicit) assumption

Assuming limited transport distances

fluxyield

Assuming exponential transport distances(and uniform slope conditions)

0.8

0.9

1

sedim

ent-deliv

ery

ratio 4 2

1 0.5

λ =

“


0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 20 40 60 80 100slope length m

sedim

ent-deliv

ery

ratio

1 0.5

0.25 0.1

0.05 0.01

(effective)

“

(Wainwright et al., 2001)

dueKLxu

xLx

x

9/42

)(

1)( −+

∫=+ϕ

-1

1 mm

2 mm

∫+

=+Lx

x

dELx ξξϕ .)()(

Analytical scaling based on sediment flux


distance m

sedim

ent flux g s

-1 2 mm

4 mm

Theoretical curves for interrill erosion based on travel distance (Parsons et al., 2004)

Instrument housing


Rain gauge

2 m2 plot reservoir

21 m2 plot reservoirs

housing

Flume

21 m2 & 2 m2

116 m2 & 2 m2© John Wainwright: [email protected]

302 m2 &2 m2

57 m2 & 2 m2

sedim

ent flux g s

-1

1 mm

2 mm

dueKLxu

xLx

x

9/42

)(

1)( −+

∫=+ϕ

0.6

0.7

0.8

∫+

=+Lx

x

dELx ξξϕ .)()(

Analytical scaling based on sediment flux


distance m

sedim

ent flux g s

4 mm

0

0.1

0.2

0.3

0.4

0.5

0.6

0 5 10 15 20 25 30

Measured on interrill plots at Walnut Gulch (Parsons et al., 2006)

Theoretical curves for interrill erosion based on travel distance (Parsons et al., 2004)

MAHLERAN

et al . (2008a) ESPL


Wainwright et al

time silt & clay sand

min Measured Modelled Measured Modelled

0 - 4 32 % 28 % 68 % 72 %

5 - 9 53 % 26 % 47 % 74 %

10 - 20 27 % 28 % 73 % 72 %


Wainwright et al. (2008b) ESPL

5

6

7

8

9

modelle

d s

edim

ent k

g

equation 19

equation 20b

1:1


0

1

2

3

4

0 1 2 3 4 5 6 7 8 9

observed sediment kg

modelle

d s

edim

ent k

g

Wainwright et al. (2008c) ESPL

57 m2116 m2


21 m2302 m2

Wainwright et al. (2008c) ESPL

Wainwright et al. (2008c) ESPL© John Wainwright: [email protected]

Back to the data ...© John Wainwright: [email protected]

MAHLERAN - Marker in Cell

Cooper et al. (forthcoming)


flow depth marker particles

Cooper

Magnetite study 16 years later...

total erosion 0·697 kg m−1

depth of soil loss 0·033 mm a−1


Parsons et al. (2010)

background

Simulation of markers moving

away from

seedline

MAHLERAN - Marker in Cell


seedline

Cooper et al. (forthcoming)

New techniques

Dynamics of Runoff And Erosion Modelling (DRÆM)


www.shef.ac.uk/draem

200 – 212 μm dry sand

2.5 mm droplet impacting at 5.94 m s-1

Dynamics of Runoff And Erosion Modelling (DRÆM)ti

me


3.5 mm droplet impacting at 6.13 m s-1

200 – 212 μm dry sand

Image sequence at 3000 fpsSequence duration 0.11 s

Trajectories of splashed particlestim

e

260

280

300

320

340

0 100 200 300 400 500 600 700 800 900

260

280

300

320

340

360

380

Interaction of single water droplet with a flat surface – Particle TrackingR

aw

Im

ag

e

(pix

els

)

Ce

ntr

e l

oca

tio

ns

of

ide

nti

fie

d

pa

rtic

les



0 100 200 300 400 500 600 700 800 900

360

380

Ce

ntr

e l

oca

tio

ns

of

ide

nti

fie

d

pa

rtic

les

Long et al. (forthcoming)

200 250 300 350 400 450 500 550 600 650 700

260

280

300

320

340

360

380

Velocity (m s-1)

Displacement (mm)

Dis

pla

cem

en

t (m

m)

3000 fps, 1024 x 512 pixels (64.6 mm x 32.4 mm), 0.063 mm/pixel resolution

Water diameter = 2 mm, Sand Dia. < 212 µm, Height 0.5 m, Impact velocity = 2.8 m s-1

Pa

rtic

le t

rack

s a

nd

ass

oci

ate

d v

elo

city

pro

file



Surface-profile measurement taken using

calibrated images of the sand surface Long et al. (forthcoming)

Red


Further developments:

tracking of multiple particle

sizes simultaneously in 3D


Green

BlueColoured particles 0.2 – 0.6 mm

...with neutral buoyancy

particles to track flow fields

RFID tagging of particles


Moving up in Scale


Wainwright (2010)

Changes in measured water and sediment flux as

0

2000

4000

6000

8000

10000

12000

0 10 20 30 40 50 60

Qt (l)

Plot 1: grassPlot 2: grass shrubPlot 3: shrub grassPlot 4: shrub

Connectivity : joined-up thinking?(1)

54.5%bare

(2)57.0%


flux as vegetation structure changes from grass to shrub

0 10 20 30 40 50 60

ER (mm)

0

2000

4000

6000

8000

10000

12000

0 10 20 30 40 50

Sedim

ent y

ield

(g)

ER (mm)

Plot 1: grass

Plot 2: grass shrub

Increasing connectivity

Turnbull et al. (2010) Hydol Proc(2010) Ecosystems

(3)73.8%

(4)76.7%

Tarbush

Grass

GrassTarbush

800%

1000%

1200%

Water800%

1000%

1200%

Grass

downslope of shrubs:

Shrubs

downslope of grass:

The importance of place


Grass

300 m 140 m upslope 140 m downslope

0%

200%

400%

600%

800%

-140 -90 -40 10 60 110

distance from ecotone m

change in flu

x

Water

Sediment

Ammonium

0%

200%

400%

600%

800%

-140 -90 -40 10 60 110

change in

flu

x

distance from ecotone m

Water Water

Sediment Sediment

Ammonium Ammonium

Müller et al. (2008) Ecological Modelling

Complexity and evolution

Chaos is merely order waiting to be deciphered

José Saramago

Top-down (Newtonian*)• Grid- or element-based (usually fixed)• Imposed model structure across entire domain

. (2006) WRR


domain• Assumes system “knows” about all other parts• Represents dynamics but in a static way

Bottom-up (Darwinian*)• Cell-, particle- or individual-based (and may change through time)• Model based on local interactions or rules• Only interacting elements “know” about each other• Can represent evolutionary dynamics

*terms of Newman et al. (2006)

Longer time scales


Relative temperature change over 742 ka based on EPICA DOME C core of Augustin et al. (2004)

0 1 2

0

1

2Small changes in catchment structure

Produce complex patterns in


0

1

2

Wainwright (2006) Catena

Produce complex patterns in catchment runoff and

sediment flux as a result of changing climate

... which are even more complex when rainfall and temperature

change are asynchronous

Comparison against sedimentary data


Briant et al. (forthcoming)

CybErosion


• Incorporates dynamic behaviour of animals and

vegetation and effects of human decision-makingWainwright (2008); Wainwright and Millington (2010)

Closing Thoughts

• Models have various uses, so too must data

• What are the inbuilt assumptions of existing models (and thus data)?


thus data)?

• Parameterization based on physical principles rather than empirical convenience ...

An example of limited parameterization data

• The threshold for flow detachment for mixtures of particle sizes can be γ

θ

β

β1 β2

A


particle sizes can be demonstrated to vary significantly about the threshold for a uniform particle size ...

• ... so threshold parameters cannot be independent of each other (and must change dynamically)

θ

0

0.05

0.1

0.15

0.2

0.25

0.05 0.15 0.25 0.35 0.44 0.54 0.64 0.74 0.84 0.93 1.03 1.13

critical threshold velocity m s-1

frequency

125 µm

2 mm

125 µµµµm

500 µµµµm

4 mm

Wainwright et al. (2003)

Closing Thoughts• Models have various uses, so too must data

• What are the inbuilt assumptions of existing models (and thus data)?


• ... and thus also be dynamic

• ... and reflect uniqueness of place

• What do models produce? And is it the same with data?

• So what are we actually doing when we compare models with data?

• Parameterization based on physical principles rather than empirical convenience ...

Closing Thoughts

• How “valid” are “validation” data?

• Most data have implicit scales which need to be recognized when parameterizing models


recognized when parameterizing models

• Calibration is NEVER the last step of a study (nor is application of a calibrated model)

• Connectivity means seeing the environment as a whole

• ... which means also speaking to other environmental (including social) scientists (disciplinary connectivity)

• Complex response means we need to test the limits of existing reductionist approaches

Thank you for listening!


Questions?

ReferencesParsons, AJ, J Wainwright and AD Abrahams 1993 ‘Tracing sediment movement on semi-arid

grassland using magnetic susceptibility’, Earth Surface Processes and Landforms 18, 721–732.

Wainwright, J, AJ Parsons, DM Powell and RE Brazier 2001 ‘A new conceptual framework for understanding and predicting erosion by water from hillslopes and catchments’, in JC Ascough II and DC Flanagan (eds) Soil Erosion Research for the 21st Century. Proceedings of the International Symposium, 607–610, American Society of Agricultural Engineers, St

Joseph, MI.

Brazier, RE, DM Powell, AJ Parsons and J Wainwright 2003 ‘Monitoring and modelling runoff in semi-arid areas from the hillslope to the watershed scale’, in KG Renard, SA McElroy, WJ Gburek, HE Canfield and RL Scott (eds) First Interagency Conference on Research in the Watersheds (Benson, AZ, October 27–30, 2003), 101–106, USDA-ARS, Washington DC.

Powell, DM, RE Brazier, J Wainwright and AJ Parsons 2003 ‘Stream bed scour and fill in low-order ephemeral stream channels’, in KG Renard, SA McElroy, WJ Gburek, HE Canfield and

Müller, EN, J Wainwright and AJ Parsons 2007 ‘The stability of vegetation boundaries and the propagation of desertification in the American Southwest: a modelling approach’, Ecological Modelling 208, 91–101.

Parsons, AJ, J Wainwright, RE Brazier and DM Powell 2008 ‘Is sediment delivery a fallacy? Reply’, Earth Surface Processes and Landforms 33, 1360–1361. DOI: 10.1002/esp.1627.

Parsons, AJ, J Wainwright, RE Brazier and DM Powell 2008 ‘Scale relationships in hillsloperunoff and erosion. Reply’, Earth Surface Processes and Landforms 33, 1637–1638. DOI: 10.1002/esp.1628.

Tatard, L, O Planchon, J Wainwright, G Nord, D Favis-Mortlock, N Silvera, O Ribolzi, M Estevesand C-H Huang 2008 ‘Measurement and modelling of high-resolution flow-velocity data under simulated rainfall on a low-slope sandy soil’, Journal of Hydrology 348, 1–12. doi: 10.1016/j.jhydrol.2007.07.016.

Wainwright, J, AJ Parsons, EN Müller, RE Brazier, DM Powell and B Fenti 2008 ‘A transport-distance approach to scaling erosion rates: 1. background and model development’, Earth Surface Processes and Landforms 33, 813–826. DOI: 10.1002/esp.1624

Wainwright, J, AJ Parsons, EN Müller, RE Brazier, DM Powell and B Fenti 2008 ‘A transport-distance approach to scaling erosion rates: 2. Sensitivity and evaluation of MAHLERAN’, Earth Surface Processes and Landforms 33, 962–984. DOI: 10.1002/esp.1623


order ephemeral stream channels’, in KG Renard, SA McElroy, WJ Gburek, HE Canfield and RL Scott (eds) First Interagency Conference on Research in the Watersheds (Benson, Az, October 27–30, 2003), 180–185, USDA-ARS, Washington DC.

Parsons, AJ, J Wainwright, DM Powell, J Kaduk and RE Brazier 2004 ‘A conceptual model for understanding and predicting erosion by water’, Earth Surface Processes and Landforms 29 (10), 1293–1302.

Powell, DM, RE Brazier, J Wainwright, AJ Parsons and J Kaduk 2005 ‘Stream-bed scour and fill in low-order dryland channels’, Water Resources Research 41, W05019, doi:10.1029/2004WR003662.

Parsons, AJ, J Wainwright, RE Brazier and DM Powell 2006 ‘Is sediment delivery a fallacy?’, Earth Surface Processes and Landforms 31, 1325–1328.

Parsons, AJ, RE Brazier and J Wainwright 2006 ‘A conceptual model for sediment and nutrient fluxes from rural land’, International Journal of Biodiversity Science and Management 2, 1–3.

Parsons, AJ, RE Brazier, J Wainwright and DM Powell 2006 ‘Scale relationships in hillsloperunoff and erosion’, Earth Surface Processes and Landforms 31, 1384–1393.

Powell, DM, RE Brazier, J Wainwright, AJ Parsons and M Nichols 2006 ‘Spatial patterns of scour and fill in dryland sand bed streams’, Water Resources Research 42, W08412, doi:10.1029/2005WR004516.

Powell, DM, RE Brazier, AJ Parsons, J Wainwright and M Nichols 2007 ‘Sediment transfer and storage in dryland headwater streams’, Geomorphology88, 152–166.

Brazier, RE, AJ Parsons, J Wainwright, DM Powell and WH Schlesinger 2007 ‘Upscalingunderstanding of nutrient dynamics associated with overland flow in a semi-arid environment’, Biogeochemistry 82, 265–278.Doi: 10.1007/s10533-007-9070-x

Müller, EN, J Wainwright and AJ Parsons 2007 ‘The impact of connectivity on the modelling of water fluxes in semi-arid shrubland environments’, Water Resources Research 43, W09412, doi:10.1029/2006WR005006.

Surface Processes and Landforms 33, 962–984. DOI: 10.1002/esp.1623

Wainwright, J, AJ Parsons, EN Müller, RE Brazier, DM Powell and B Fenti 2008 ‘A transport-distance approach to scaling erosion rates: 3. Evaluating scaling characteristics of MAHLERAN’, Earth Surface Processes and Landforms 33, 1113–1128, DOI: 10.1002/esp.1622

Wainwright, J, AJ Parsons, EN Müller, RE Brazier and DM Powell 2009 ‘Response to Hairsine’sand Sander’s “Comment on ‘A transport-distance based approach to scaling erosion rates:’ Parts 1, 2 and 3 by Wainwright et al.”’, Earth Surface Processes and Landforms 34, 886–890, DOI: 10.1002/esp.1781.

Wainwright, J, AJ Parsons, EN Müller, RE Brazier and DM Powell 2009 ‘Response to Kinnell’s“Comment on ‘A transport-distance approach to scaling erosion rates: 3. Evaluating scaling characteristics of MAHLERAN’”’, Earth Surface Processes and Landforms 34, 1320–1321.

Brazier, RE, J Wainwright and AJ Parsons 2010 ‘Scaling soil-erosion models in space and time', in RPC Morgan and MA Nearing (eds) Handbook of Erosion Modelling, 98–116, Wiley-Blackwell, Chichester.

Parsons, AJ, J Wainwright, T Furukawa and Y Onda 2010 ‘Using sediment travel distance to estimate medium-term erosion rates: a sixteen-year record’. Earth Surface Processes and Landforms 35, 1694–1700. DOI: 10.1002/esp.2011.

Turnbull, L, J Wainwright and RE Brazier 2010 ‘Hydrology, erosion and nutrient transfers over a transition from semi-arid grassland to shrubland in the South-Western USA: a modelling assessment’. Journal of Hydrology 388, 258–272, DOI:10.1016/j.jhydrol.2010.05.005.

Wainwright, J, AJ Parsons, EN Müller, RE Brazier and DM Powell 2010 ‘Standing proud: a response to “Soil-erosion models: where do we really stand?” by Smith et al.’, Earth Surface Processes and Landforms 35, 1349–1356. DOI: 10.1002/esp.2047

Turnbull, L, J Wainwright and RE Brazier 2011 ‘Nitrogen and phosphorus dynamics during runoff events over a transition from grassland to shrubland in the south-western United States’. Hydrological Processes 25, 1–17. DOI: 10.1002/hyp.7806

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