Assessing Risks to Infrastructure Projects in the Middle East

World Weather Open Science Conference 2014
“The weather: what’s the outlook?”
Session: SCI-PS212
WHI – Improved understanding of and techniques for Decision Making
Wednesday, August 20th, 10:30 am
Assessing Risks to Infrastructure Projects in
the Middle East from Drifting and
Blowing Sand Using WRF
J. Wayne Boulton, Stuart Carmichael, Jeff Lundgren, Duncan Phillips, Ewan Crosbie
RWDI, Guelph, Ontario, Canada
Giles Wiggs
University of Oxford, School of Geography and the Environment, Oxford, UK
Cheryl Mckenna-Neuman
Trent University, Department of Geography, Peterborough, Ontario, Canada
www.rwdi.com
Introduction
Divisions
Presentation outline
1. Problem Definition
2. Wind Blown Sand
3. Filling the Gaps
4. Assessing Risks
5. Mitigation Options
6. Conclusions
2
(Dammam, KSA © Boulton, 2012)
PROBLEM DEFINITION
3
Sand & Railways
• Increased inspections, maintenance and cleaning
• Loss of void space in ballast affects track damping
• Reduced speeds and schedule delays
• Derailment, fouling of switches and culverts, etc.
(al Hail, KSA © Boulton, 2012)
4
Scarcity of Observations
Wind Speed (m/s)
• Meteorology varies widely over large areas
• Limited observations of sufficient number,
duration, and quality
RKT
DBX
SHJ
AUH
AAN
5
Adapted without permission from “K. Pye and H. Tsoar, Aeolian Sand and Sand Dunes, Springer, 2009.”
WIND BLOWN SAND
6
Physics of Wind & Sand
Wind Speed Threshold
• Minimum wind speed to
initiate saltation (m·s-1)
Saltation
• Hop length and trajectory
depend on surface, sand,
and wind
Images adapted without permission from “K. Pye, Aeolian Dust and Dust Deposits, Academic Press, 1987.”
Sand Flux
• Sand transport rate
(kg·m-1·yr-1)
7
Wind Tunnel Testing
Testing UAE sand in Trent University Wind Tunnel (TEWT)
Sand Flux Eq’n
© C. McKenna Neuman
© C. McKenna Neuman
8
(Madinat Zayed, UAE © Boulton, 2012)
FILLING THE GAPS
9
WRF Model Configuration
• Measurements take too long for design purposes
• Modelled wind fields make a good surrogate
o WRF version 3.2.1
o 2001 to 2012 (inclusive) with nudging
o 35 vertical levels (20 levels from 0 to 2000 m)
o Nested 36, 12, and 4 km resolution grids
o > 400,000 CPU hours
o 4 km grid = 2.0 Gb / day = 8.6 Tb
10
WRF Model Configuration
11
(Al Ain, UAE © Boulton, 2011)
ASSESSING RISKS
12
Sand Transport Maps
Annual flux potential in kg·m-1·yr-1 (sample year)
13
Sand Transport Maps
Annual hours above threshold (sample year)
Dubai
Abu Dhabi
Al Ain
Liwa
14
Wind & Sand Roses
• Select representative WRF grid cells
• Extract hours for wind speed > threshold
• Create roses and develop climate models
Winds > 6.0 m·s-1
All Winds
15
Wind & Sand Roses
• Compute sand flux magnitude, duration, and frequency
• Compute net drift vector and drift potential
Sand Flux &
Drift Vector
Annual Sand Flux
(kg·m-1·yr-1)
16
Wind & Sand Roses
• Map sand flux roses along proposed alignment
17
Input to Engineering Design
• Extreme value analysis of individual “events” using a
modified Fischer-Tippett Type 1 probability distribution
• Probability based on rank of storm and number of
independent storms per epoch
• Convert to Return Period in days
Event Duration
Sand Flux (kg∙m‐1) per “Event”
18
Input to Engineering Design
EXAMPLE: Typical bi-modal wind regime
Annual Statistics
Hours Above Threshold (hrs∙yr‐1)
1152
Events per Year
21
Total Sand Flux (1000 kg∙m‐1∙yr‐1)
9.3
Total Volume (m3∙m‐1∙yr‐1)
5.9
Blowing Sand Event Return Periods
1‐Month
1‐Year 5‐Year Storm Duration (hours)
10
Sand Flux (kg∙m‐1∙yr‐1)
200
Storm Duration (hours)
17
Sand Flux (kg∙m‐1∙yr‐1)
500
Storm Duration (hours)
21
Sand Flux (kg∙m‐1∙yr‐1)
950
19
Input to Engineering Design
EXAMPLE: Star dunes formed by multi-modal winds
with low net migration / drift ratio
Sand Flux (1000 kg·m-1·yr-1)
6.7
Net Sand Drift (1000 kg·m-1·yr-1)
0.7
Drift Potential (%)
9.8
(Adapted without permission from: http://www.nps.gov/grsa/naturescience/ dune‐types.htm)
(Al Ain, UAE © Boulton, 2012)
20
MITIGATION OPTIONS
21
Mitigation
Computational Fluid Dynamics (CFD) model of wind at
macro-scale (1 km to 10’s of m)
Existing Terrain Modified Terrain 22
Mitigation
Assess mitigation options at the track scale (100’s of m to
10’s of cm) using CFD
• Combinations of berms, trenches, walls, fences, etc.
• Surface shear velocity (U*) and 3-D winds used to
assess sand entrainment, transport, deposition risk
23
Mitigation
Different mitigation measures
applied along track segments to
assess impacts on wind (U, U*)
and sand transport (Q, Hrs > Ut)
No Mitigation
OPTION 1
OPTION 2 24
Mitigation
Revised mitigation measures applied along track
segments and modelled to assess residual risk
25
Mitigation
Field trials are ongoing…
(Madinet Zayed, UAE © Boulton, 2012)
(Madinat Zayed, UAE © Boulton, 2012)
(Madinet Zayed, UAE © Boulton, 2012)
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(Liwa, UAE © Boulton, 2012)
CONCLUSIONS
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Conclusions
•
•
•
•
•
•
Wind and sand highly variable in space and time
Wind and sand always strive to achieve equilibrium
Storms can deliver large quantities of sand quickly
Mitigation must work with Mother Nature
No single solution fits all locations or projects
New science / engineering tools allow for more
holistic assessments
UAE (© Boulton, 2009)
UAE (© Boulton, 2009)
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Acknowledgements
Project funding provided by:
• Saudi Rail (SAR)
• Etihad Rail (ER)
• SDT JV
(Liwa, UAE © Wiggs, 2012)
THANK YOU!
(Madinet Zayed, UAE © Boulton, 2012)
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