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Prepare Multiprocessing Workflow
Alan D. Snow edited this page Jun 1, 2016
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#How to import
from AutoRoutePy.prepare import prepare_autoroute_multiprocess
#Function
prepare_autoroute_multiprocess(watershed_folder,
autoroute_executable_location,
stream_network_shapefile,
log_directory,
land_use_raster="",
manning_n_table="",
dem_extension='img',
river_id='COMID',
slope_id='SLOPE',
streamflow_id="",
default_manning_n=0.035,
return_period="",
return_period_file="",
rapid_output_file="",
date_peak_search_start=None,
date_peak_search_end=None,
num_cpus=-17)| Variable | Data Type | Description | Default |
|---|---|---|---|
| watershed_folder | String | Main directory where the sub folders with elevation DEM files are stored. | |
| autoroute_executable_location | String | Path to AutoRoute executable. | |
| stream_network_shapefile | String | Path to stream network shapefile with unique id and slope for each stream segment. | |
| log_directory | String | Path to output logs for the preparation runs. | |
| land_use_raster | String | (Optional) Land use raster covering the entire watershed domain whereby Manning's n rasters can be generated for the individual tiles. | |
| manning_n_table | String | (Optional) Table of values to convert land use raster values to Manning's n values. NOTE: These are available in the AutoRoute repository. | |
| dem_extension | String | (Optional) This is the extension of the DEM raster you are using (e.g. tif, asc, img ...). | "img" |
| river_id | String | (Optional) This is the unique identifier field in the stream network shapefile. | "COMID" |
| slope_id | String | (Optional) This is the slope field in the stream network shapefile. | "SLOPE" |
| streamflow_id | String | (Optional) This is the streamflow peak field in the stream network shapefile. | |
| default_manning_n | Float | (Optional) This is the value of Mannning's n used in the simulation when there are missing values or no Manning's n raster. | 0.035 |
| return_period | String | (Optional) This is the value of the field in the return period file generated by RAPIDpy. Valid values include: 'max_flow','return_period_20','return_period_10', and 'return_period_2'. | |
| return_period_file | String | (Optional) This is the path to the return period file generated by RAPIDpy. | |
| rapid_output_file | String | (Optional) This is the path to a CF compliant RAPID Qout output file. | |
| date_peak_search_start | datetime | (Optional) This constrains the start of the search for the peak in the RAPID Qout file. | |
| date_peak_search_end | datetime | (Optional) This constrains the end of the search for the peak in the RAPID Qout file. | |
| num_cpus | Int | (Optional) This is the number of CPUs to use in the process. | Use all CPUs |
Here are examples of using multiprocessing to prepare input for AutoRoute. This requires each elevation DEM file to be inside of its own folder within the main watershed folder.
WARNING: The land use raster must be in the same projection as your elevation raster! If it is not in the same projection, either reproject using a GIS tool or use the reproject_lu_raster function (from RAPIDpy.prepare import reproject_lu_raster).
####Mode 1: Basic (NO STREAMFLOW) In this example, it shows how to prepare inputs with just an elevation DEM and stream network shapefile.
from AutoRoutePy.prepare import prepare_autoroute_multiprocess
prepare_autoroute_multiprocess(watershed_folder='/autoroute-io/input/watershed_directory',
autoroute_executable_location='/AutoRoute/src/autoroute',
stream_network_shapefile='/path/to/river_network.shp',
log_directory="/path/to/logs",
#dem_extension='img',
#river_id='COMID',
#slope_id='SLOPE',
#default_manning_n=0.035,
num_cpus=4
)####Mode 2: Basic+Land Use (NO STREAMFLOW) WARNING: The land use raster must be in the same projection as your elevation raster! If it is not in the same projection, either reproject using a GIS tool or use this script.
from AutoRoutePy.prepare import reproject_lu_raster
dem_raster = '/autoroute-io/input/watershed-directory/sub_area-directory/elevation.img'
land_use_raster = '/autoroute_prepare/watershed-directory/NLCD2011_LC.tif'
reprojected_land_use_raster = '/autoroute_prepare/watershed-directory/NLCD2011_LC_repr.tif'
reproject_lu_raster(dem_raster, land_use_raster, reprojected_land_use_raster)Once your land use raster is in the correct projection, use this process to generate the manning n raster.
from AutoRoutePy.prepare import prepare_autoroute_multiprocess
land_use_to_mannning_n_table = '/AutoRoute/mannings_n_tabes/AR_Manning_n_for_NLCD_LOW.txt'
prepare_autoroute_multiprocess(watershed_folder='/autoroute-io/input/watershed_directory',
autoroute_executable_location='/AutoRoute/src/autoroute',
stream_network_shapefile='/path/to/river_network.shp',
log_directory="/path/to/logs",
land_use_raster=reprojected_land_use_raster,
manning_n_table=land_use_to_mannning_n_table,
#dem_extension='img',
#river_id='COMID',
#slope_id='SLOPE',
#default_manning_n=0.035,
#num_cpus=1
)####Mode 3: Streamflow Note: You can run with or without land use as shown in Mode 1 & Mode 2. This is the same for Mode 3, however only the basic mode will be shown here.
#####Mode 3.1: Streamflow from RAPID output In this mode it will search for the peak from the entire simulation unless bounds are given from date_peak_search_start or from the date_peak_search_end.
from datetime import datetime
from AutoRoutePy.prepare import prepare_autoroute_multiprocess
prepare_autoroute_multiprocess(watershed_folder='/autoroute-io/input/watershed_directory',
autoroute_executable_location='/AutoRoute/src/autoroute',
stream_network_shapefile='/path/to/river_network.shp',
log_directory="/path/to/logs",
#dem_extension='img',
#river_id='COMID',
#slope_id='SLOPE',
#default_manning_n=0.035,
rapid_output_file="/path/to/Qout.nc",
#date_peak_search_start=datetime(1990, 1, 1), #optional
#date_peak_search_end=datetime(1990, 3, 5), #optional
#num_cpus=1
)#####Mode 3.2: Streamflow from shapefile field
from AutoRoutePy.prepare import prepare_autoroute_multiprocess
prepare_autoroute_multiprocess(watershed_folder='/autoroute-io/input/watershed_directory',
autoroute_executable_location='/AutoRoute/src/autoroute',
stream_network_shapefile='/path/to/river_network.shp',
log_directory="/path/to/logs",
#dem_extension='img',
#river_id='COMID',
#slope_id='SLOPE',
streamflow_id='Flow_500',
#default_manning_n=0.035,
#num_cpus=1
)#####Mode 3.3: Streamflow from return period file
from AutoRoutePy.prepare import prepare_autoroute_multiprocess
prepare_autoroute_multiprocess(watershed_folder='/autoroute-io/input/watershed_directory',
autoroute_executable_location='/AutoRoute/src/autoroute',
stream_network_shapefile='/path/to/river_network.shp',
log_directory="/path/to/logs",
#dem_extension='img',
#river_id='COMID',
#slope_id='SLOPE',
#default_manning_n=0.035,
#NOTE: valid return_periods -> 'max_flow','return_period_20','return_period_10','return_period_2'
return_period="return_period_20",
return_period_file="/path/to/return_period.nc",
#num_cpus=1
)