GSSHA User's Manual
From Gsshawiki
Table of Contents
- 3 Project File
- 3.1 Required Inputs
- 3.2 Mapping Table – Optional
- 3.3 Overland Flow – Required
- 3.4 Interception – Optional
- 3.5 Rainfall Input and Options – Required
- 3.6 Infiltration – Optional
- 3.7 Channel Routing – Optional
- 3.8 Continuous Simulations – Optional
- 3.9 Saturated Groundwater Flow – Optional
- 3.10 Soil Erosion – Optional
- 3.11 Constituent Transport – Optional
- 3.12 Subsurface Drainage Network – Optional
- 3.13 Output Files – Required
- 4 General
- 4.1 Units
- 4.2 Grid Size
- 4.3 Total Event Simulation Time
- 4.4 Coordinate System
- 4.5 Map Headers
- 4.6 Watershed Mask
- 4.7 Elevation Map
- 4.8 Optimizations
- 10 Soil Erosion
- 12 Mapping Table
- 12.1 File Description
- 12.2 Index Maps
- 12.3 Grid-based Mapping Tables
- 12.4 ID Line Format
- 12.5 Example Mapping Table File
- 12.6 Stream Mapping Tables
- 12.7 Sediment Erosion Mapping Tables
- 12.7 Constituent Mapping Tables
- 14 Output
- 14.1 Required Flags and Files
- 14.2 Run Summary File
- 14.3 Optional Flags
- 14.4 Time Series Data at Internal Locations
- 14.5 WMS Hydrograph File
- 14.6 Time Series Maps
- 16 Building a Model
- 16.1 Delineating the Watershed
- 16.2 Selecting a Grid Size
- 16.3 Overland Flow Routing
- 16.4 Infiltration
- 16.5 Channel Routing
- 16.6 Single Event Calibration
- 16.7 Long-term Simulations
- 16.8 Saturated Groundwater Modeling
- 16.9 Calibration and Verification
- 16.10 Sediment Transport
- 16.11 Contaminant Transport
- 17 GSSHA File Formats
- 17.1 Project File
- 17.2 Mapping Tables
- 17.3 Stream Network Files
- 17.4 GRASS grid files
- 17.5 Nutrient Files
- 17.6 Time and Elevation Series Files
- 18 Alternate Run Modes
- 18.1 MPI and OpenMP Parallelization
- 18.2 Simulation Setup for Alternate Run Modes
- 18.3 Batch Mode Runs
- 18.4 Automated Calibration with Shuffled Complex Evolution
- 18.5 Monte Carlo Runs
- 18.6 ERDC Automated Model Calibration Software
- 18.6.1 Efficient Local Search
- 18.6.2 Multistart
- 18.6.3 Trajectory Repulsion
- 18.6.4 Effective and Efficient Stochastic Global Optimization
- 18.7 Inset Models
- 20 Frozen Soil