Assessing Risks to Infrastructure Projects in the Middle East from Drifting and Blowing Sand Using WRF

Transcription

1 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 20 th, 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

2 Introduction Divisions Presentation outline 1. Problem Definition 2. Wind Blown Sand 3. Filling the Gaps 4. Assessing Risks 5. Mitigation Options 6. Conclusions 2

3 (Dammam, KSA Boulton, 2012) PROBLEM DEFINITION 3

4 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

5 Scarcity of Observations Meteorology varies widely over large areas Limited observations of sufficient number, duration, and quality Wind Speed (m/s) DBX SHJ RKT AUH AAN 5

6 Adapted without permission from K. Pye and H. Tsoar, Aeolian Sand and Sand Dunes, Springer, WIND BLOWN SAND 6

7 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, Sand Flux Sand transport rate (kg m -1 yr -1 ) 7

8 Wind Tunnel Testing Testing UAE sand in Trent University Wind Tunnel (TEWT) Sand Flux Eq n C. McKenna Neuman C. McKenna Neuman 8

9 (Madinat Zayed, UAE Boulton, 2012) FILLING THE GAPS 9

10 WRF Model Configuration Measurements take too long for design purposes Modelled wind fields make a good surrogate o WRF version 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

11 WRF Model Configuration 11

12 (Al Ain, UAE Boulton, 2011) ASSESSING RISKS 12

13 Sand Transport Maps Annual flux potential in kg m -1 yr -1 (sample year) 13

14 Sand Transport Maps Annual hours above threshold (sample year) Dubai Abu Dhabi Al Ain Liwa 14

15 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

16 Wind & Sand Roses Compute sand flux magnitude, duration, and frequency Compute net drift vector and drift potential Annual Sand Flux (kg m -1 yr -1 ) Sand Flux & Drift Vector 16

17 Wind & Sand Roses Map sand flux roses along proposed alignment 17

18 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

19 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 (m 3 m 1 yr 1 ) 5.9 Blowing Sand Event Return Periods 1 Month Storm Duration (hours) 10 Sand Flux (kg m 1 yr 1 ) Year Storm Duration (hours) 17 Sand Flux (kg m 1 yr 1 ) Year Storm Duration (hours) 21 Sand Flux (kg m 1 yr 1 )

20 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: dune types.htm) (Al Ain, UAE Boulton, 2012) 20

21 MITIGATION OPTIONS 21

22 Mitigation Computational Fluid Dynamics (CFD) model of wind at macro-scale (1 km to 10 s of m) Existing Terrain Modified Terrain 22

23 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

24 Mitigation Different mitigation measures applied along track segments to assess impacts on wind (U, U*) and sand transport (Q, Hrs > U t ) No Mitigation OPTION 1 OPTION 2 24

25 Mitigation Revised mitigation measures applied along track segments and modelled to assess residual risk 25

26 Mitigation Field trials are ongoing (Madinet Zayed, UAE Boulton, 2012) (Madinat Zayed, UAE Boulton, 2012) (Madinet Zayed, UAE Boulton, 2012) 26

27 (Liwa, UAE Boulton, 2012) CONCLUSIONS 27

28 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) 28

29 Acknowledgements Project funding provided by: Saudi Rail (SAR) Etihad Rail (ER) SDT JV (Liwa, UAE Wiggs, 2012) (Madinet Zayed, UAE Boulton, 2012) THANK YOU! 29