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451 to 460 of 750 Results

Mesh Resolution of HEC-RAS Models: Average Point Spacing of 7.5m-15.0m Jun 9, 2020 - Roughness Scenarios FLUD Research Group, 2020, "Mesh Resolution of HEC-RAS Models: Average Point Spacing of 7.5m-15.0m", https://doi.org/10.18738/T8/CES19C, Texas Data Repository, V1 Shapefiles of Computational Meshes for HEC-RAS Models for that have an average point spacing of 7.5m, 10.0m, 12.5m, and 15.0m (original). Created with the export feature of RAS-Mapper for HEC-RAS v 5.0.7 (Brunner, 2016) Brunner, G.W. (2016). HEC-RAS: River Analysis System, 2D Mod...
Hydrodynamic Model Input Data Jun 9, 2020 - Roughness Scenarios FLUD Research Group, 2020, "Hydrodynamic Model Input Data", https://doi.org/10.18738/T8/CNCXAN, Texas Data Repository, V1 Shapefiles and tables of values that are important for setting up a HEC-RAS model simulation for the Mission River Floodplain. Included in this dataset are the roughness patches that have Manning’s N values assigned to each patch for each of the five roughness scenarios (baseline...
Flow Inundation Extents: Baseline Roughness Scenario Jun 9, 2020 - Roughness Scenarios FLUD Research Group, 2020, "Flow Inundation Extents: Baseline Roughness Scenario", https://doi.org/10.18738/T8/KBN60V, Texas Data Repository, V1 Polygon shapefiles that represent flow inundation extents. These extents are derived from water surface elevations from the HEC-RAS 5.0.7 2D hydrodynamic model (Brunner, 2016), and associated with flow stages (1.0 – 11.63m) at 0.25m interval (N=44). These flow stages were output...
Flow Inundation Extents: Landcover +5% Roughness Scenario Jun 9, 2020 - Roughness Scenarios FLUD Research Group, 2020, "Flow Inundation Extents: Landcover +5% Roughness Scenario", https://doi.org/10.18738/T8/Z2CPJ1, Texas Data Repository, V1 Polygon shapefiles that represent flow inundation extents. These extents are derived from water surface elevations from the HEC-RAS 5.0.7 2D hydrodynamic model (Brunner, 2016), and associated with flow stages (1.0 – 11.63m) at 0.25m interval (N=44). These flow stages were output...
Flow Inundation Extents: Landcover +10% Roughness Scenario Jun 9, 2020 - Roughness Scenarios FLUD Research Group, 2020, "Flow Inundation Extents: Landcover +10% Roughness Scenario", https://doi.org/10.18738/T8/YCKBGY, Texas Data Repository, V1 Polygon shapefiles that represent flow inundation extents. These extents are derived from water surface elevations from the HEC-RAS 5.0.7 2D hydrodynamic model (Brunner, 2016), and associated with flow stages (1.0 – 11.63m) at 0.25m interval (N=44). These flow stages were output...
Flow Inundation Extents: Landcover +25% Roughness Scenario Jun 9, 2020 - Roughness Scenarios FLUD Research Group, 2020, "Flow Inundation Extents: Landcover +25% Roughness Scenario", https://doi.org/10.18738/T8/MZQ3O8, Texas Data Repository, V1 Polygon shapefiles that represent flow inundation extents. These extents are derived from water surface elevations from the HEC-RAS 5.0.7 2D hydrodynamic model (Brunner, 2016), and associated with flow stages (1.0 – 11.63m) at 0.25m interval (N=44). These flow stages were output...
Flow Inundation Extents: Landcover +50% Roughness Scenario Jun 9, 2020 - Roughness Scenarios FLUD Research Group, 2020, "Flow Inundation Extents: Landcover +50% Roughness Scenario", https://doi.org/10.18738/T8/AQL6EC, Texas Data Repository, V1 Polygon shapefiles that represent flow inundation extents. These extents are derived from water surface elevations from the HEC-RAS 5.0.7 2D hydrodynamic model (Brunner, 2016), and associated with flow stages (1.0 – 11.63m) at 0.25m interval (N=44). These flow stages were output...
Maximum Entropy machine learning model output using all digitized downed trees with three variables and regularization multiplier of 1.0 Jun 9, 2020 - Environmental Analyses FLUD Research Group, 2020, "Maximum Entropy machine learning model output using all digitized downed trees with three variables and regularization multiplier of 1.0", https://doi.org/10.18738/T8/GK5DBZ, Texas Data Repository, V1 This dataset (multiple outputs files in a compressed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using all digitized downed trees (N=9505) and includes the three environmental varia...
Maximum Entropy machine learning model output using all digitized downed trees with three variables and regularization multiplier of 3.0 Jun 9, 2020 - Environmental Analyses FLUD Research Group, 2020, "Maximum Entropy machine learning model output using all digitized downed trees with three variables and regularization multiplier of 3.0", https://doi.org/10.18738/T8/EQUZO5, Texas Data Repository, V1 This dataset (multiple outputs files in a compressed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using all digitized downed trees (N=9505) and includes the three environmental varia...
Maximum Entropy machine learning model output using all digitized downed trees with three variables and regularization multiplier of 6.0 Jun 9, 2020 - Environmental Analyses FLUD Research Group, 2020, "Maximum Entropy machine learning model output using all digitized downed trees with three variables and regularization multiplier of 6.0", https://doi.org/10.18738/T8/WHS3BR, Texas Data Repository, V1 This dataset (multiple outputs files in a compressed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using all digitized downed trees (N=9505) and includes the three environmental varia...

Mesh Resolution of HEC-RAS Models: Average Point Spacing of 7.5m-15.0m

Jun 9, 2020 - Roughness Scenarios

FLUD Research Group, 2020, "Mesh Resolution of HEC-RAS Models: Average Point Spacing of 7.5m-15.0m", https://doi.org/10.18738/T8/CES19C, Texas Data Repository, V1

Shapefiles of Computational Meshes for HEC-RAS Models for that have an average point spacing of 7.5m, 10.0m, 12.5m, and 15.0m (original). Created with the export feature of RAS-Mapper for HEC-RAS v 5.0.7 (Brunner, 2016) Brunner, G.W. (2016). HEC-RAS: River Analysis System, 2D Mod...

Hydrodynamic Model Input Data

Jun 9, 2020 - Roughness Scenarios

FLUD Research Group, 2020, "Hydrodynamic Model Input Data", https://doi.org/10.18738/T8/CNCXAN, Texas Data Repository, V1

Shapefiles and tables of values that are important for setting up a HEC-RAS model simulation for the Mission River Floodplain. Included in this dataset are the roughness patches that have Manning’s N values assigned to each patch for each of the five roughness scenarios (baseline...

Flow Inundation Extents: Baseline Roughness Scenario

Jun 9, 2020 - Roughness Scenarios

FLUD Research Group, 2020, "Flow Inundation Extents: Baseline Roughness Scenario", https://doi.org/10.18738/T8/KBN60V, Texas Data Repository, V1

Polygon shapefiles that represent flow inundation extents. These extents are derived from water surface elevations from the HEC-RAS 5.0.7 2D hydrodynamic model (Brunner, 2016), and associated with flow stages (1.0 – 11.63m) at 0.25m interval (N=44). These flow stages were output...

Flow Inundation Extents: Landcover +5% Roughness Scenario

Jun 9, 2020 - Roughness Scenarios

FLUD Research Group, 2020, "Flow Inundation Extents: Landcover +5% Roughness Scenario", https://doi.org/10.18738/T8/Z2CPJ1, Texas Data Repository, V1

Flow Inundation Extents: Landcover +10% Roughness Scenario

Jun 9, 2020 - Roughness Scenarios

FLUD Research Group, 2020, "Flow Inundation Extents: Landcover +10% Roughness Scenario", https://doi.org/10.18738/T8/YCKBGY, Texas Data Repository, V1

Flow Inundation Extents: Landcover +25% Roughness Scenario

Jun 9, 2020 - Roughness Scenarios

FLUD Research Group, 2020, "Flow Inundation Extents: Landcover +25% Roughness Scenario", https://doi.org/10.18738/T8/MZQ3O8, Texas Data Repository, V1

Flow Inundation Extents: Landcover +50% Roughness Scenario

Jun 9, 2020 - Roughness Scenarios

FLUD Research Group, 2020, "Flow Inundation Extents: Landcover +50% Roughness Scenario", https://doi.org/10.18738/T8/AQL6EC, Texas Data Repository, V1

Maximum Entropy machine learning model output using all digitized downed trees with three variables and regularization multiplier of 1.0

Jun 9, 2020 - Environmental Analyses

FLUD Research Group, 2020, "Maximum Entropy machine learning model output using all digitized downed trees with three variables and regularization multiplier of 1.0", https://doi.org/10.18738/T8/GK5DBZ, Texas Data Repository, V1

This dataset (multiple outputs files in a compressed folder) is output from a run of the Maxent ML Model (Phillips et.al., 2006, url: https://biodiversityinformatics.amnh.org/open_source/maxent/) using all digitized downed trees (N=9505) and includes the three environmental varia...

Maximum Entropy machine learning model output using all digitized downed trees with three variables and regularization multiplier of 3.0

Jun 9, 2020 - Environmental Analyses

FLUD Research Group, 2020, "Maximum Entropy machine learning model output using all digitized downed trees with three variables and regularization multiplier of 3.0", https://doi.org/10.18738/T8/EQUZO5, Texas Data Repository, V1

Maximum Entropy machine learning model output using all digitized downed trees with three variables and regularization multiplier of 6.0

Jun 9, 2020 - Environmental Analyses

FLUD Research Group, 2020, "Maximum Entropy machine learning model output using all digitized downed trees with three variables and regularization multiplier of 6.0", https://doi.org/10.18738/T8/WHS3BR, Texas Data Repository, V1

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