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|CSDMS meeting abstract presentation=The Earth’s surface is a boundary layer between internally-driven geodynamics and atmospheric forcing. In much of what we do as landscape modellers, our analysis of Earth surface can be enhanced by consideration and understanding of the substrate acted upon by hillslope, riverine and glacial processes. To explore the influence of crustal strength on patterns of fluvial incision, we use a conservative scaling rule to relate rock erodibility to field measurements of cohesive strength. In other models, grain sizes produced upon the erosion of rock are made a function of field measured fracture density values. By combining 3D geodynamic codes with landscape evolution models we are able to explore the sensitivity of surface processes to topographic and tectonic stresses, geological history, fault damage, seismic accelerations, pore pressures, and fluid flow. We present several examples where useful interpretations were made by integrating field, lab, and experimental data with geodynamic models, landscape evolution models, or a combination of both. Our examples are bias toward collisional settings – the Himalaya, the Southern Alps and Taiwan, but the approach is equally valid when considering strike-slip or extensional settings. | |CSDMS meeting abstract presentation=The Earth’s surface is a boundary layer between internally-driven geodynamics and atmospheric forcing. In much of what we do as landscape modellers, our analysis of Earth surface can be enhanced by consideration and understanding of the substrate acted upon by hillslope, riverine and glacial processes. To explore the influence of crustal strength on patterns of fluvial incision, we use a conservative scaling rule to relate rock erodibility to field measurements of cohesive strength. In other models, grain sizes produced upon the erosion of rock are made a function of field measured fracture density values. By combining 3D geodynamic codes with landscape evolution models we are able to explore the sensitivity of surface processes to topographic and tectonic stresses, geological history, fault damage, seismic accelerations, pore pressures, and fluid flow. We present several examples where useful interpretations were made by integrating field, lab, and experimental data with geodynamic models, landscape evolution models, or a combination of both. Our examples are bias toward collisional settings – the Himalaya, the Southern Alps and Taiwan, but the approach is equally valid when considering strike-slip or extensional settings. | ||
|CSDMS meeting youtube code= | |CSDMS meeting youtube code=LQU2ANwaJ_I | ||
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|Working group member=Terrestrial Working Group, Geodynamics Focus Research Group | |Working group member=Terrestrial Working Group, Geodynamics Focus Research Group | ||
|CSDMS meeting presentation=Phaedra_Upton_CSDMS_2015_annual_meeting.pdf | |||
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Revision as of 11:10, 8 August 2018
CSDMS 2015 annual Meeting - Models meet data, data meet models
Models meet Data, Earth Surface meet Geodynamics
Abstract
The Earth’s surface is a boundary layer between internally-driven geodynamics and atmospheric forcing. In much of what we do as landscape modellers, our analysis of Earth surface can be enhanced by consideration and understanding of the substrate acted upon by hillslope, riverine and glacial processes. To explore the influence of crustal strength on patterns of fluvial incision, we use a conservative scaling rule to relate rock erodibility to field measurements of cohesive strength. In other models, grain sizes produced upon the erosion of rock are made a function of field measured fracture density values. By combining 3D geodynamic codes with landscape evolution models we are able to explore the sensitivity of surface processes to topographic and tectonic stresses, geological history, fault damage, seismic accelerations, pore pressures, and fluid flow. We present several examples where useful interpretations were made by integrating field, lab, and experimental data with geodynamic models, landscape evolution models, or a combination of both. Our examples are bias toward collisional settings – the Himalaya, the Southern Alps and Taiwan, but the approach is equally valid when considering strike-slip or extensional settings.
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