| 1 | """ |
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| 2 | ----------------------------------------------------------------- model_run.py |
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| 3 | ANUGA RURAL FLOOD MODELLING TEMPLATE (Domain Construction & Execution) |
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| 4 | Script for building the model domain and setting initial conditions and |
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| 5 | (temporally varying) boundary conditions appropriate to the particular |
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| 6 | scenario-event before running (evolving) the simulation. |
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| 7 | |
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| 8 | Most model data for the run is read in or otherwise referenced in |
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| 9 | model_data.py and imported into model_run.py to create the model mesh and |
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| 10 | domain before running the simulation. |
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| 11 | |
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| 12 | Code Version : 1.00 June 2008 Initial release |
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| 13 | Author : E Rigby (0437 250 500) ted.rigby@rienco.com.au |
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| 14 | |
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| 15 | ------------------------------------------------------------------------------- |
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| 16 | """ |
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| 17 | |
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| 18 | #------------------------------------------------------------------------------ |
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| 19 | # Import necessary modules |
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| 20 | #------------------------------------------------------------------------------ |
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| 21 | |
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| 22 | # Standard python modules |
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| 23 | import os |
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| 24 | import time |
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| 25 | import sys |
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| 26 | |
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| 27 | # Related ANUGA modules |
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| 28 | from anuga.shallow_water import Domain |
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| 29 | from anuga.shallow_water import Reflective_boundary |
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| 30 | from anuga.shallow_water import Dirichlet_boundary |
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| 31 | from anuga.shallow_water import Time_boundary |
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| 32 | from anuga.shallow_water import Transmissive_Momentum_Set_Stage_boundary |
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| 33 | from anuga.shallow_water.shallow_water_domain import Inflow |
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| 34 | from anuga.abstract_2d_finite_volumes.util import file_function |
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| 35 | from anuga.abstract_2d_finite_volumes.quantity import Quantity |
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| 36 | from anuga.pmesh.mesh_interface import create_mesh_from_regions |
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| 37 | from anuga.utilities.polygon import read_polygon, plot_polygons, Polygon_function |
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| 38 | from anuga.alpha_shape.alpha_shape import alpha_shape_via_files |
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| 39 | |
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| 40 | |
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| 41 | # Model specific imports |
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| 42 | import model_data # Defines and provides the scenario-event specific data |
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| 43 | import get_tuflow_data # Provides the routines to read in tuflow specific data |
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| 44 | |
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| 45 | ##################################################################################### |
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| 46 | # # |
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| 47 | # S I M U L A T I O N M A I N L I N E # |
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| 48 | # # |
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| 49 | ##################################################################################### |
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| 50 | |
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| 51 | t0 = time.time() # record start time of this run (secs) |
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| 52 | print model_data.basename+' >>>> Comencing model_run.py code execution at t= %.2f hours' %(float(time.time()-t0)/3600.0) |
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| 53 | |
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| 54 | ##################################################################################### |
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| 55 | # # |
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| 56 | # CREATE THE TRIANGULAR MESH # |
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| 57 | # # |
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| 58 | ##################################################################################### |
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| 59 | |
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| 60 | # Note: The mesh is created based on overall clipping polygon with a tagged |
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| 61 | # boundary and interior regions as defined in model_data.py along with |
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| 62 | # resolutions (maximal area per triangle) for each interior polygon |
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| 63 | |
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| 64 | print model_data.basename+' >>>> Creating variable mesh within bounding_poly reflecting regional resolutions' |
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| 65 | # Create the mesh reflecting the bounding (default) and internal region mesh resolutions set in model_data.py |
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| 66 | # with boundary tags as defined in model_data.py |
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| 67 | |
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| 68 | create_mesh_from_regions(model_data.bounding_polygon, |
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| 69 | boundary_tags = model_data.boundary_strings, |
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| 70 | maximum_triangle_area = model_data.default_res, |
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| 71 | minimum_triangle_angle=30.0, |
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| 72 | interior_regions = model_data.interior_resregions, |
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| 73 | filename = model_data.mesh_filename, |
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| 74 | use_cache=True, |
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| 75 | verbose=model_data.anuga_verbose) |
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| 76 | |
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| 77 | |
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| 78 | domain |
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| 79 | domain.forcing_terms.append(hydrograph) |
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| 80 | |
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| 81 | print model_data.basename+' >>>> Completed assignment of %i inflow hydrographs at t= %.2f hours ' %(len(model_data.infl |
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| 82 | print model_data.basename+' >>>> Completed mesh creation at t= %.2f hours ' %(float(time.time()-t0)/3600.0) |
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| 83 | |
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| 84 | ###################################################################################### |
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| 85 | # # |
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| 86 | # CREATE THE COMPUTATIONAL DOMAIN # |
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| 87 | # # |
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| 88 | ###################################################################################### |
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| 89 | |
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| 90 | print model_data.basename+' >>>> Creating domain from mesh and setting domain parameters' |
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| 91 | # create domain from mesh meshname |
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| 92 | domain = Domain(model_data.mesh_filename, use_cache=True, verbose=model_data.anuga_verbose) |
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| 93 | print domain.statistics() # confirm what has been done |
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| 94 | |
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| 95 | # set base domain parameters |
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| 96 | domain.set_name(model_data.basename) # already created in model_data.py |
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| 97 | domain.set_datadir(model_data.results_dir) # already created and/or checked in model_data.py |
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| 98 | domain.set_quantities_to_be_stored(['stage', 'xmomentum', 'ymomentum']) |
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| 99 | domain.set_minimum_storable_height(0.01) # Remove very shallow water depths from sww |
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| 100 | domain.set_maximum_allowed_speed(8.0) # Allow Maximum velocity of 8m/s.... |
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| 101 | |
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| 102 | ###################################################################################### |
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| 103 | # # |
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| 104 | # ASSIGN THE DOMAIN INITIAL CONDITIONS # |
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| 105 | # # |
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| 106 | ###################################################################################### |
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| 107 | |
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| 108 | #------------------------------------------------------------------------------------- |
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| 109 | # This section assigns the initial (t=0) conditions for the domain |
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| 110 | # Domain initial conditions can be fixed, read from a file, or from a function |
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| 111 | # Note also that anuga permits almost all initial conditions to subsequently vary |
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| 112 | # with time, so while the following conditions apply to the whole domain at t=0 |
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| 113 | # all can be modified within the evolve time loop. In this way scour, deposition, |
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| 114 | # blockage, changes in roughness etc with time can be explicitly included in a simulation |
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| 115 | #------------------------------------------------------------------------------------- |
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| 116 | |
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| 117 | print model_data.basename+' >>>> Assigning initial conditions to %s domain' %(model_data.basename) |
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| 118 | |
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| 119 | # Elevation data may be assigned to the domain from a csv or (NetCDF) pts file. |
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| 120 | |
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| 121 | # For a smaller csv that will be read in repeatedly, best to use geospatial_data to readin and |
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| 122 | # export_point_file to save the points permanently in a NetCDF *.pts file. This runs faster |
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| 123 | # than the block read of a csv - but - is limited to about 6 million points. |
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| 124 | # Alternatively - by directly assigning elevation from a csv file can take advantage of the block |
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| 125 | # read in domain.set_quantity so the elevation dataset can be virtually unlimited in size. |
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| 126 | |
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| 127 | # In this simulation the size of the elevation dataset is to large for conversion to a (NetCDF) |
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| 128 | # pts format so data is read in from the raw csv file. |
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| 129 | |
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| 130 | domain.set_quantity('elevation', |
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| 131 | filename = model_data.elev_filename, |
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| 132 | use_cache=True, |
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| 133 | verbose=model_data.anuga_verbose, |
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| 134 | alpha=0.01) |
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| 135 | |
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| 136 | |
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| 137 | # Set the intial water level (stage) across the domain |
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| 138 | InitialWaterLevel = model_data.InitialWaterLevel # At t=0 water surface is in this model at initial lake level (0.3m) |
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| 139 | if domain.get_quantity('elevation') < InitialWaterLevel: # This can create ponds if land is below initial tailwater level |
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| 140 | domain.set_quantity('stage', InitialWaterLevel) # set initial stage at initial tailwater level (wet) |
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| 141 | else: |
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| 142 | domain.set_quantity('stage', expression='elevation') # else set initial stage at land level (dry) |
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| 143 | |
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| 144 | |
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| 145 | # Assign uniform initial friction value to domain mesh centroids as initial condition |
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| 146 | # Note need to re-assess initial friction value based on rough_polys read in from tuflow |
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| 147 | # files and computed depth during evolve time loop!!!! |
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| 148 | domain.set_quantity('friction', model_data.default_n, location = 'centroids') |
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| 149 | |
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| 150 | |
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| 151 | |
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| 152 | |
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| 153 | ####################################################################################### |
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| 154 | # # |
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| 155 | # ASSIGN THE (TEMPORAL) SUBAREAL INFLOWS TO THE DOMAIN # |
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| 156 | # # |
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| 157 | ####################################################################################### |
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| 158 | |
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| 159 | #-------------------------------------------------------------------------------------- |
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| 160 | # This section reads the local or total temporal inflows read in in model_data.py from |
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| 161 | # the Tuflow ts1 files and stored as NETCDF tms file in the tms_files subdirectory, |
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| 162 | # into the domain. |
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| 163 | # |
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| 164 | # Note: The current ANUGA inflow function 'pours' flow onto the domain within a circle |
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| 165 | # or polygonal area specified by the user at the specified temporal rate. |
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| 166 | # EHR -- the above inflows should eventually be augmented by inflows at the boundary |
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| 167 | # (total as distinct from local hydrographs) to better correspond with conventional |
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| 168 | # flood modelling. |
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| 169 | #-------------------------------------------------------------------------------------- |
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| 170 | |
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| 171 | print model_data.basename+" >>>> Assigning the inflow hydrographs from the (%s) tms files directory" %(model_data.tms_dir) |
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| 172 | |
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| 173 | |
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| 174 | inflow_fields=[] |
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| 175 | # read in each line of inflow_hydrographs[tms_filename,xcoord,ycoord] and assign as inflow hydrograph to domain |
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| 176 | for i in range(len(model_data.inflow_hydrographs)) : |
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| 177 | |
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| 178 | tms_filename = model_data.inflow_hydrographs[i][0] # extract the inflow hydro tms_filename |
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| 179 | xcoord = model_data.inflow_hydrographs[i][1] # extract the inflow hydro xcoord |
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| 180 | ycoord = model_data.inflow_hydrographs[i][2] # extract the inflow hydro ycoord |
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| 181 | print model_data.basename+' >>>> Reading inflow hydrograph from %s at %7.2f %7.2f and appending to forcing terms ' %(tms_filename,xcoord,ycoord) |
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| 182 | |
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| 183 | # convert time series to temporal function |
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| 184 | flowrate = file_function(tms_filename, quantities='value',boundary_polygon=None) |
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| 185 | hydrograph = Inflow(domain,center=(xcoord,ycoord),radius=10, rate=flowrate ) |
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| 186 | |
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| 187 | # append hydrograph to domain |
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| 188 | domain.forcing_terms.append(hydrograph) |
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| 189 | |
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| 190 | print model_data.basename+' >>>> Completed assignment of %i inflow hydrographs at t= %.2f hours ' %(len(model_data.inflow_hydrographs),float(time.time()-t0)/3600.0) |
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| 191 | |
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| 192 | |
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| 193 | ####################################################################################### |
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| 194 | # # |
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| 195 | # ASSIGN THE (TEMPORAL) DOWNSTREAM BOUNDARY CONDITIONS TO THE DOMAIN # |
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| 196 | # # |
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| 197 | ####################################################################################### |
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| 198 | |
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| 199 | |
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| 200 | print model_data.basename+' >>>> Assigning the DSBC from the (%s) tms files directory ' %(model_data.tms_dir) |
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| 201 | print model_data.basename+' >>>> Available boundary tags are ', domain.get_boundary_tags() |
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| 202 | |
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| 203 | # convert dsbc time series to function of time |
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| 204 | tms_filename=model_data.dsbc_hydrographs[0] |
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| 205 | lake_stage = file_function(tms_filename,quantities='value',boundary_polygon=None) |
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| 206 | # Note: will need to be modified if more than one dsbcis to be applied |
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| 207 | print model_data.basename + ' >>>> Applying dsbc %s to model at the Lake_bdry ' %(tms_filename) |
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| 208 | |
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| 209 | MaMt_bdry = Reflective_boundary(domain) # all reflective except lake as using inflow() |
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| 210 | Mriv_bdry = Reflective_boundary(domain) # Really redundant untill get boundary inflows |
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| 211 | Cbck_bdry = Reflective_boundary(domain) |
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| 212 | WFra_bdry = Reflective_boundary(domain) |
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| 213 | EFra_bdry = Reflective_boundary(domain) |
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| 214 | |
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| 215 | lake_bdry = Transmissive_Momentum_Set_Stage_boundary(domain=domain,function=lake_stage) |
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| 216 | closed_bdry = Reflective_boundary(domain) |
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| 217 | |
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| 218 | # boundary conditions for current scenario |
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| 219 | domain.set_boundary({'Lake': lake_bdry, |
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| 220 | 'MaMt': MaMt_bdry, |
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| 221 | 'Mriv': Mriv_bdry, |
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| 222 | 'Cbck': Cbck_bdry, |
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| 223 | 'WFra': WFra_bdry, |
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| 224 | 'EFra': EFra_bdry, |
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| 225 | 'exterior': closed_bdry }) # this relates to the residue of the bounding poly not explicitly asigned above |
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| 226 | |
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| 227 | print model_data.basename+' >>>> Completed assignment of %i dsbc boundary conditions to domain at t= %.2f hours ' %(len(model_data.dsbc_hydrographs),float(time.time()-t0)/3600.0) |
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| 228 | |
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| 229 | |
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| 230 | ####################################################################################### |
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| 231 | # # |
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| 232 | # READ IN THE (TEMPORALLY DEPTH DEPENDENT) SURFACE ROUGHNESS (FRICTION) PARAMETERS # |
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| 233 | # # |
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| 234 | ####################################################################################### |
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| 235 | |
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| 236 | #--------------------------------------------------------------------------------------- |
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| 237 | # This section creates a new domain quantity mat_RID and assigns surface roughness IDs (RID) |
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| 238 | # values to this quantity for later use in the evolve loop where RID is used with depth to |
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| 239 | # compute a depth dependent friction at each time step. |
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| 240 | # |
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| 241 | # Note that because the polys read in should but may not cover the entire bounding poly area |
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| 242 | # It is necessarry to declare a default material as in Tuflow applying the default to mat_RID |
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| 243 | # across the whole bounding poly area before applying (overwriting) with the actual RID polys |
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| 244 | # and their RID values obtained from the 2d_mat mid/mif files!!!! |
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| 245 | #-------------------------------------------------------------------------------------- |
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| 246 | |
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| 247 | print model_data.basename+' >>>> Creating and assigning mat_RID (surface Roughness ID)instance for use in evolve' |
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| 248 | |
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| 249 | # Create an instance of a new domain quantity called mat_RID to store the surface Roughness IDs - fill initially with zeros |
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| 250 | mat_RID = Quantity(domain) |
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| 251 | if model_data.model_verbose : |
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| 252 | print ' ++++ Created a zeroed domain quantity of %s and length %i called mat_RID' %( type(mat_RID),len(mat_RID) ) |
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| 253 | |
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| 254 | # Set all of the RID values initially to one fixed default value (makes sure all elements have a RID) |
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| 255 | mat_RID.set_values(numeric=model_data.default_RID,location='centroids',verbose=True) |
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| 256 | if model_data.model_verbose : |
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| 257 | print ' ++++ Initially filled mat_RID with the specified default RID value of %i ' %( model_data.default_RID ) |
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| 258 | |
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| 259 | # Assign model_data.mat_RID_list values to domain.from model_data.mat_poly_list |
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| 260 | for i in range(len(model_data.mat_RID_list)) : |
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| 261 | mat_RID.set_values(numeric=model_data.mat_RID_list[i],polygon=model_data.mat_poly_list[i]) |
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| 262 | if model_data.model_verbose : |
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| 263 | print ' ++++ Upgraded mat_RID spatially with the values set in the mif/mid files ' |
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| 264 | |
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| 265 | |
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| 266 | # Dump some RIDS to confirm assignment occured as intended |
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| 267 | if model_data.model_verbose : |
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| 268 | print ' ++++ Check printout of RID assignments to centroids of elements nos 100 200 and 300' |
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| 269 | print ' ++++ Element 100s RIDs ', mat_RID.get_values(location='centroids',indices=[100]) |
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| 270 | print ' ++++ Element 200s RIDs ', mat_RID.get_values(location='centroids',indices=[200]) |
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| 271 | print ' ++++ Element 300s RIDs ', mat_RID.get_values(location='centroids',indices=[300]) |
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| 272 | |
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| 273 | print model_data.basename+' >>>> Completed assignment of material (surface roughness) RIDs and default n to domain at t= %.2f hours ' %(float(time.time()-t0)/3600.0) |
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| 274 | |
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| 275 | print model_data.basename+' >>>> Completed domain construction at t= %.2f hours ' %(float(time.time()-t0)/3600.0) |
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| 276 | |
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| 277 | |
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| 278 | ######################################################################################### |
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| 279 | # # |
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| 280 | # RUN THE SIMULATION # |
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| 281 | # # |
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| 282 | ######################################################################################### |
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| 283 | |
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| 284 | #---------------------------------------------------------------------------------------- |
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| 285 | # This section starts the analysis of flow through the domain up to the specified finaltime |
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| 286 | # All time is in seconds |
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| 287 | # |
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| 288 | # Note: The internal computational timestep is set at each timestep to meet a CFL=1 limit. |
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| 289 | # It is therefore important to examine the mesh statistics to see that there are no |
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| 290 | # unintended small triangles, particularly in areas of deeper water as DT=DX/(g*H)**0.5 |
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| 291 | # Yieldstep is the interval at which results are saved to the output (sww) file |
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| 292 | #---------------------------------------------------------------------------------------- |
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| 293 | |
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| 294 | # Note: 'friction' is recomputed as a function of depth and location at each timestep( now each steptime!!) |
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| 295 | |
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| 296 | # EHR - could reduce recalc of friction to say every steptime??? this would markedly speedup?? Done?? |
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| 297 | # EHR - need to set a startime and use in domain.set_time(starttime) to restrict to area of data of interest |
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| 298 | # not clear how initial conditions etc fit in to a start not at t=0??? |
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| 299 | # EHR - could restrict update of friction to wet cells only as well |
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| 300 | |
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| 301 | print model_data.basename+' >>>> Starting the simulation for ',model_data.catchment,'-',model_data.simclass,'-',model_data.scenario,'-',model_data.event |
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| 302 | starttime = 0 # start simulation at t=0 EHR not yet implemented ??????? |
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| 303 | endtime = 9000 # end at 9000 secs (150min) - Increase to 40hrs when debugged!!!!!!!! |
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| 304 | steptime = 300 # write sww file results out every 300secs = 5min |
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| 305 | lastprintstep = 0 # initialise lastprintstep |
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| 306 | print model_data.basename+' >>>> Simulation is for %.2f hours with output to the sww file at %.0f minute intervals ' %(float(endtime/3600.0),float(steptime/60.0)) |
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| 307 | |
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| 308 | |
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| 309 | for t in domain.evolve(yieldstep = steptime, finaltime = endtime): |
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| 310 | |
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| 311 | domain.write_time() # confirm t each steptime |
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| 312 | domain.write_boundary_statistics(tags='Lake', quantities='stage') # indicate bdry stats each steptime |
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| 313 | depth = domain.create_quantity_from_expression('stage - elevation') # create depth instance for this timestep |
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| 314 | |
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| 315 | |
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| 316 | print ' ++++ Recomputing friction at t= ', t |
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| 317 | |
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| 318 | noelementsupdated = 0 # intialise update check |
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| 319 | # rebuild the 'friction' values adjusted for depth |
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| 320 | for i in domain.get_wet_elements(): # loop for each wet element in domain |
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| 321 | |
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| 322 | element_RID_value=mat_RID.get_values(location='centroids', |
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| 323 | indices=[i]) # get current elements centroidal RID value |
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| 324 | |
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| 325 | # print ' ++++ Element %i centroidal element_RID_value is %s' %( i,element_RID_value[0] ) |
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| 326 | for k in range(len(model_data.mat_roughness_data_list)): # loop for each matl in tmf list |
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| 327 | if int(element_RID_value[0]) == int( model_data.mat_roughness_data_list[k][0] ) : # got tmf line for that matl |
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| 328 | # print ' ++++ found tmf match for RID %i of %s ' %( int(element_RID_value[0]),model_data.mat_roughness_data_list[k][8].rstrip(' ') ) |
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| 329 | d1 = float(model_data.mat_roughness_data_list[k][4]) |
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| 330 | n1 = float(model_data.mat_roughness_data_list[k][5]) |
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| 331 | d2 = float(model_data.mat_roughness_data_list[k][6]) |
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| 332 | n2 = float(model_data.mat_roughness_data_list[k][7]) |
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| 333 | noelementsupdated = noelementsupdated + 1 # increment update counter start at zeroth element |
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| 334 | if depth.get_values(location='centroids', |
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| 335 | indices=[i]) <= d1 : # recompute friction values from depth for this element get_tuflow_data.py |
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| 336 | |
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| 337 | domain.set_quantity('friction', |
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| 338 | numeric=n1, |
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| 339 | location='centroids', |
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| 340 | indices=[i], |
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| 341 | verbose=model_data.anuga_verbose) |
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| 342 | |
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| 343 | elif depth.get_values(location='centroids', |
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| 344 | indices=[i]) >= d2 : |
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| 345 | domain.set_quantity('friction',numeric=n2,location='centroids', |
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| 346 | indices=[i],verbose=model_data.anuga_verbose) |
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| 347 | else : |
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| 348 | n3 = n1+(n2-n1)/(d2-d1)* ( depth.get_values(location='centroids',indices=[i])[0] ) |
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| 349 | domain.set_quantity('friction',numeric=n3,location='centroids', |
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| 350 | indices=[i],verbose=model_data.anuga_verbose) |
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| 351 | |
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| 352 | |
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| 353 | if model_data.model_verbose : |
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| 354 | |
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| 355 | friction = domain.get_quantity('friction') |
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| 356 | |
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| 357 | print " ++++ Check some RID,depth, friction values returned during this timestep " |
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| 358 | print " element 100 ", mat_RID.get_values(location='centroids',indices=[100]), depth.get_values(location='centroids',indices=[100]), friction.get_values(location='centroids',indices=[100]) |
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| 359 | |
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| 360 | print " element 200 ", mat_RID.get_values(location='centroids',indices=[200]), depth.get_values(location='centroids',indices=[200]), friction.get_values(location='centroids',indices=[200]) |
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| 361 | |
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| 362 | print " element 300 ", mat_RID.get_values(location='centroids',indices=[300]), depth.get_values(location='centroids',indices=[300]), friction.get_values(location='centroids',indices=[300] ) |
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| 363 | |
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| 364 | |
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| 365 | |
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| 366 | |
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| 367 | |
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| 368 | print model_data.basename+' >>>> ',model_data.catchment,'-',model_data.simclass,'-',model_data.scenario,'-',model_data.event,' -- Simulation completed succesfully' |
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| 369 | print model_data.basename+' >>>> Completed ', endtime/3600.0, 'hours of model simulation at t= %.2f hours' %(float(time.time()-t0)/3600.0) |
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| 370 | |
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