4th GEOSS Science and Technology Stakeholder Workshop
March 24-26, 2015, Norfolk, VA, USA

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Use of Surface-Dynamic Models for Identifying Environmental Indicators and Processes

JP Syvitski, Community Surface Dynamics Modeling System — CSDMS, University of Colorado, Boulder, CO, USA

The three pillars of 21st century environmental cyber-infrastructure are: 1) satellite observations, 2) field observations, and 3) model simulations. While our 20th century efforts using this combination are legion, we now recognize the effort to develop effective state-of-the-art operational workflows. Each of the three pillars, on their own, contains substantive bias and error. Field observations also tend to be expensive and seldom offer the same spatial coverage as satellite systems or numerical models. Satellite systems have both spatial and temporal restrictions, based on the nature of the orbit, data transfer limitations, and other environmental restrictions (e.g. cloud cover, atmospheric moisture). Model simulations offer great temporal and spatial resolution, but are labor-intensive, and affected by model simplicity, computational resources, and efficiency of the code itself. However when combined, these cyber-infrastructure pillars offer greatly reduced bias and error. Three examples highlight the role of model simulations in 21st century environmental cyber-infrastructure.

The first example highlights the application of nested and coupled models used to assess the role of hurricanes on offshore infrastructure. The Gulf of Mexico is a mature offshore petroleum production area generating more than 1.7 mb of oil per day, through more than 3,500 oil platforms, connected by 28,000 miles of underwater pipes, all exposed to different types of structural damage associated with extreme oceanic and atmospheric events. About 5% of broken or damaged underwater pipes are by sudden and violent sediment flows. Short-lived hurricanes can generate 10m waves during their passage and both liquefy and re-suspend seafloor sediment, and thereby induce turbidity currents. The U.S. Bureau of Ocean Energy Management has overseen the development of a complex array of nested and coupled numerical models for determining the locations most likely impacted by turbidity currents, and the factors that precondition or trigger such flows. The workflow includes: 1) modeling the flux of water and sediment from rivers into the Gulf, augmented by field data; 2) ingesting outer boundary conditions from more regional oceanographic models, and seabed sediment textures; 3) employing a high resolution (10 km) wave action model and 4) a lower resolution (1 km) ocean circulation model, to support 5) a wave-driven sediment-suspension model, and 6) a gravity flow setup model to determine the location and duration of areas of potential turbidity current generation. A Navier-Stokes Reynolds Averaged version is then used to route the sediment flows down canyons, providing estimates of bottom shear stress needed for ascertaining possible damage to offshore infrastructure.

The second example highlights how models are used to assess the importance of environmental processes and parameters. In coastal deltas, surface elevation change is complex, involving: crustal motion, climate and runoff, vegetation dynamics, sedimentation, sediment compaction, and sediment transport by waves, tides and currents. Few existing instruments can measure the impact of all of these processes, and none resolve elevation changes across all pertinent spatial and temporal scales. No numerical model fully captures these terrestrial and subaqueous dynamics, although recent versions of Delft3D capture many of the morphodynamic impacts. When applied to the Louisiana coast, both cold fronts and hurricanes are shown to cause erosion of the Mississippi delta. Although a single hurricane can move more sediment, cold fronts are more critical for delta evolution as they transport much more sediment away from the coast due to their higher frequency nature. Waves intensify sediment erosion, and aboveground vegetation reduces the amount of erosion. Models can capture the impact of plausible scenarios, such as how the order or frequency of weather events influences delta stability. Combined with observing systems, model applications offer guidance to stakeholders needing information on our disappearing deltas.

Measurements of river discharge and watershed runoff are essential to water resources management, efficient hydropower generation, accurate flood prediction and control, and improved understanding of the global water cycle. Our third example focuses on river floods. Optical (near-infrared) and SAR satellite systems are great for mapping flood inundation but cannot on their own detect cause. As the number of large and devastating floods have increased over the last couple of decades, it remains important to ascribe a cause to these floods, such as from the intensification of the hydrological cycle or changing weather patterns either due to climate change, or from infrastructure failure of levees, barrages and diversions. Orbital (advanced) microwave sensors can measure river discharge variation in a manner closely analogous to its measurement at ground stations. For international measurements, hydrological modeling provides the needed calibration of sensor data to discharge. Comparison with gauging station data commonly indicates a need of small positive bias removal for both the modeled discharge and the satellite-observed runoff, highlighting the importance of all three pillars of 21st century environmental cyber-infrastructure.