Let it Rain on your mesh Integrating Hydrologic and ......o Wetting-drying Structures (levees,...
Transcript of Let it Rain on your mesh Integrating Hydrologic and ......o Wetting-drying Structures (levees,...
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Reinaldo Garcia, Hydronia LLC
Pilar Garcia Navarro, University of Zaragoza
(UZ)
Javier Fernandez Pato, UZ
Mario Morales, UZ
Jacinto Artigas, Hydronia LLC
Let it Rain on your mesh
Integrating Hydrologic and Hydraulic
Modeling to Simulate Hurricane Flooding in
Coastal Areas
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Flooding caused by Hurricanes and Tropical Storms
Storm surge / Sea level rise
River flooding
Local rainfall / runoff
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Sturm Surge
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Sea Level Rise
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http://pubs.usgs.gov/pp/2007/1751/professional-paper/tile7-8/hurricanes.htm
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beaverriverwatershed.ca
Hydrologic model Runoff, losses, and Q(t) hydrograph
Hydraulic model Flood routing [depths and velocities]
Integrated Hydrologic and Hydraulic model Runoff, losses, and Flood routing [depths and velocities]
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Integrated Hydrologic-Hydraulic Modeling Challenges
Urban environment (buildings, streets, etc.)o Resolve complex terrain and geometry
o Wetting-drying
Structures (levees, walls, roads)o Geometrical adaptation to arbitrary polylines
Multiple inflow/outflow boundarieso Water may enter and leave mesh during simulation
o Discharge and stage BCs
Combined forcingo Extreme rainfall + storm surge
Extremely long model runtimeso Large meshes required
o Rapid changes in depths and velocities
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• Rainfall-Infiltration
• Bridges, Dam-breach
• Culverts, Weirs, Gates
• Sediment Transport
• Mud-debris Flow
• Water Quality
• Oil Spills
•
• Finite-Volume
• Wet-Dry bed
• Supercritical-Subcritical flows
• GPU based
• Flexible Mesh
• High-Performance
• Multiple-processors
• GPU
• English, SI Units
• SMS, QGIS GUIs Capabilities
Performance
Numerical Engine
ComponentsModules
RiverFlow2D Hydrologic-Hydraulic Model
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Flexible Mesh
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Accuracy
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HYDROLOGIC COMPONENT
Rainfall/Evaporation
o Spatially distributed, varied in time
o Rainfall input: Radar, gauges, etc.
o ASCII Grid or polygon input
Infiltration loses
o Spatially distributed
parameters/methods
o Horton
o Green-Ampt
o SCS-CN
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Addressing Computational Challenge with RiverFlow2D
GPU
CPU Central Processing Unit (OpenMP)
GPU Video Cards
GPUs 5000+ processors (cores)
Requires specialized programming (NVIDIA CUDA)
GPU CARDNumber of
CoresMemory
GBCost US$
GTX 1080 Ti 3,584 11 700
Tesla K80 2,496 12 3,000
Tesla P100 3,584 16 6,000
Tesla V100 5,120 16 19,500
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Evolution of RiverFlow2D GPU Performance
Test 1
Previous
MaxPresent Max
Speedup Speedup
Mesh1 19,079 00:00:08:14 00:00:00:41 00:00:00:23 00:00:00:24 00:00:00:32 00:00:00:18 00:00:00:18 00:00:00:38 00:00:00:13 00:00:00:11 27 45Mesh2 154,880 00:03:23:47 00:00:04:36 00:00:05:12 00:00:03:38 00:00:03:19 00:00:02:42 00:00:02:38 00:00:02:44 00:00:01:24 00:00:00:51 75 238Mesh3 1,878,607 08:23:17:47 00:02:41:46 00:04:17:00 00:02:32:06 00:01:54:58 00:01:49:04 00:01:28:04 00:01:08:28 00:00:33:40 00:00:18:49 188 687
Mesh No. CellsIntel CPU 1-
coreGTX 780 Tesla c2075 Tesla k20 Tesla V100Titan Black Tesla K40 Tesla K80 Tesla P100GTX 1080 Ti
2013 2015 2016 2018
~ 9 days vs 20 minutes
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RiverFlow2D GPU in the Cloud
Google or Amazon Cloud Services
Create Virtual Machines with top of the line GPU hardware
Cost effective: < US$ 2/hour
Drawback…Data transfer to and from the Cloud…
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Hurricane Sandy flooding Simulations
• Oct. 2012• 5-7 in. rainfall
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ddd
Q vs. time
Free
WSEL vs. time
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Observed Flooding vs RiverFlow2D Flooding Area
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NYC
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Final Comments
Integrated hydrologic-hydraulic modeling is more realistic
Taking advantage of GPU technology makes possible using high
resolution and large meshes
Use of Cloud services (e.g. Google, Amazon) minimizes modeling
costs
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Thank you!Questions?