def build_watershed(subbasinfile, flowfile, outletfile, damfile, gagefile,
landfile, aggregatefile, VAAfile, years, HUC8, output,
plots = True, overwrite = False, format = 'png'):
# create a dictionary to store subbasin data
subbasins = {}
# create a dictionary to keep track of subbasin inlets
inlets = {}
# read in the flow plane data into an instance of the FlowPlane class
sf = Reader(subbasinfile, shapeType = 5)
comid_index = sf.fields.index(['ComID', 'N', 9, 0]) - 1
len_index = sf.fields.index(['PlaneLenM', 'N', 8, 2]) - 1
slope_index = sf.fields.index(['PlaneSlope', 'N', 9, 6]) - 1
area_index = sf.fields.index(['AreaSqKm', 'N', 10, 2]) - 1
cx_index = sf.fields.index(['CenX', 'N', 12, 6]) - 1
cy_index = sf.fields.index(['CenY', 'N', 12, 6]) - 1
elev_index = sf.fields.index(['AvgElevM', 'N', 8, 2]) - 1
for record in sf.records():
comid = '{}'.format(record[comid_index])
length = record[len_index]
slope = record[slope_index]
tot_area = record[area_index]
centroid = [record[cx_index], record[cy_index]]
elevation = record[elev_index]
subbasin = Subbasin(comid)
subbasin.add_flowplane(length, slope, 0, centroid, elevation)
subbasins[comid] = subbasin
# read in the flowline data to an instance of the Reach class
sf = Reader(flowfile)
outcomid_index = sf.fields.index(['OutComID', 'N', 9, 0]) - 1
gnis_index = sf.fields.index(['GNIS_NAME', 'C', 65, 0]) - 1
reach_index = sf.fields.index(['REACHCODE', 'C', 8, 0]) - 1
incomid_index = sf.fields.index(['InletComID', 'N', 9, 0]) - 1
maxelev_index = sf.fields.index(['MaxElev', 'N', 9, 2]) - 1
minelev_index = sf.fields.index(['MinElev', 'N', 9, 2]) - 1
slopelen_index = sf.fields.index(['SlopeLenKM', 'N', 6, 2]) - 1
slope_index = sf.fields.index(['Slope', 'N', 8, 5]) - 1
inflow_index = sf.fields.index(['InFlowCFS', 'N', 8, 3]) - 1
outflow_index = sf.fields.index(['OutFlowCFS', 'N', 8, 3]) - 1
velocity_index = sf.fields.index(['VelFPS', 'N', 7, 4]) - 1
traveltime_index = sf.fields.index(['TravTimeHR', 'N', 8, 2]) - 1
for record in sf.records():
outcomid = '{}'.format(record[outcomid_index])
gnis = record[gnis_index]
reach = record[reach_index]
incomid = '{}'.format(record[incomid_index])
maxelev = record[maxelev_index] / 100
minelev = record[minelev_index] / 100
slopelen = record[slopelen_index]
slope = record[slope_index]
inflow = record[inflow_index]
outflow = record[outflow_index]
velocity = record[velocity_index]
traveltime = record[traveltime_index]
if isinstance(gnis, bytes): gnis = ''
subbasin = subbasins[outcomid]
flow = (inflow + outflow) / 2
subbasin.add_reach(gnis, maxelev, minelev, slopelen, flow = flow,
velocity = velocity, traveltime = traveltime)
inlets[outcomid] = incomid
# open up the outlet file and see if the subbasin has a gage or dam
sf = Reader(outletfile)
records = sf.records()
comid_index = sf.fields.index(['COMID', 'N', 9, 0]) - 1
nid_index = sf.fields.index(['NIDID', 'C', 7, 0]) - 1
nwis_index = sf.fields.index(['SITE_NO', 'C', 15, 0]) - 1
nids = {'{}'.format(r[comid_index]):r[nid_index] for r in records
if isinstance(r[nid_index], str)}
nwiss = {'{}'.format(r[comid_index]):r[nwis_index] for r in records
if r[nwis_index] is not None}
# open up the dam file and read in the information for the dams
sf = Reader(damfile)
records = sf.records()
name_index = sf.fields.index(['DAM_NAME', 'C', 65, 0]) - 1
nid_index = sf.fields.index(['NIDID', 'C', 7, 0]) - 1
long_index = sf.fields.index(['LONGITUDE', 'N', 19, 11]) - 1
lat_index = sf.fields.index(['LATITUDE', 'N', 19, 11]) - 1
river_index = sf.fields.index(['RIVER', 'C', 65, 0]) - 1
owner_index = sf.fields.index(['OWN_NAME', 'C', 65, 0]) - 1
type_index = sf.fields.index(['DAM_TYPE', 'C', 10, 0]) - 1
purp_index = sf.fields.index(['PURPOSES', 'C', 254, 0]) - 1
year_index = sf.fields.index(['YR_COMPL', 'C', 10, 0]) - 1
high_index = sf.fields.index(['NID_HEIGHT', 'N', 19, 11]) - 1
mstor_index = sf.fields.index(['MAX_STOR', 'N', 19, 11]) - 1
nstor_index = sf.fields.index(['NORMAL_STO', 'N', 19, 11]) - 1
area_index = sf.fields.index(['SURF_AREA', 'N', 19, 11]) - 1
# iterate through the subbasins and see if they have a dam
for comid, subbasin in subbasins.items():
if comid in nids:
# if the subbasin has a dam, find the data info in the file
nid = nids[comid]
r = records[[r[nid_index] for r in records].index(nid)]
subbasin.add_dam(nid,
r[name_index],
r[long_index],
r[lat_index],
r[river_index],
r[owner_index],
r[type_index],
r[purp_index],
r[year_index],
r[high_index],
r[mstor_index],
r[nstor_index],
r[area_index]
)
# open up the aggregate file to get the landuse group map
m, landtypes, groups = get_aggregate_map(aggregatefile)
# convert to a list of landuse names
names = [landtypes[group] for group in groups]
# read the land use data for each year into the subbasins
with open(landfile, 'rb') as f: landyears, landuse = pickle.load(f)
for comid in subbasins:
subbasin = subbasins[comid]
subbasin_data = landuse[comid]
for year, data in zip(landyears, zip(*subbasin_data)):
subbasin.add_landuse(year, names, data)
# create an instance of the watershed class
watershed = Watershed(HUC8, subbasins)
# open up the flowline VAA file to use to establish mass linkages
with open(VAAfile, 'rb') as f: flowlines = pickle.load(f)
# create a dictionary to connect the comids to hydroseqs
hydroseqs = {'{}'.format(flowlines[f].comid):
flowlines[f].hydroseq for f in flowlines}
# establish the mass linkages using a dictionary "updown" and a list of
# head water subbasins
updown = {}
for comid, subbasin in watershed.subbasins.items():
# get the flowline instance for the outlet comid
flowline = flowlines[hydroseqs[comid]]
# check if the subbasin is a watershed inlet or a headwater source
inlet = hydroseqs[inlets[comid]]
if flowlines[inlet].up in flowlines:
i = '{}'.format(flowlines[flowlines[inlet].up].comid)
subbasin.add_inlet(i)
elif flowlines[inlet].up != 0:
watershed.add_inlet(comid)
else:
watershed.add_headwater(comid)
# check if the subbasin is a watershed outlet, and if it is not, then
# find the downstream reach
if flowline.down in flowlines:
flowline = flowlines[flowline.down]
while '{}'.format(flowline.comid) not in subbasins:
flowline = flowlines[flowline.down]
updown[comid] = '{}'.format(flowline.comid)
else:
updown[comid] = 0
watershed.add_outlet('{}'.format(comid))
# open
watershed.add_mass_linkage(updown)
if output is None:
filename = os.getcwd() + '/watershed'
plotname = os.getcwd() + '/masslink.%s' % format
else:
filename = output + '/%s/watershed' % HUC8
plotname = output + '/%s/images/%smasslink.%s' % (HUC8, HUC8, format)
if not os.path.isfile(filename) or overwrite:
with open(filename, 'wb') as f: pickle.dump(watershed, f)
if not os.path.isfile(plotname) and plots or overwrite and plots:
plot_mass_flow(watershed, plotname)
# add the landuse
subbasin.add_landuse(1988, landuse_names, areas)
# create a dictionary of the subbasins
subbasins = {sname: subbasin}
# create an updown dictionary for the reach network (trivial with only 1)
updown = {}
# create an instance of the watershed class to store the data to build the model
watershed = Watershed(description, subbasins)
# add the network and the outlet subbasin
watershed.add_mass_linkage(updown)
watershed.add_outlet(sname)
# make the HSPFModel instance (the data for this example use the non-default
# option of English instead of metric units)
from pyhspf import HSPFModel
hspfmodel = HSPFModel(units = 'English')
# since the climate data are provided with hspexp in an export file called
# "huntobs.exp." WDMUtil has a method to automatically import the data to a
velocity = velocity)
# for simplicity just assume the same landuse types and areas
subbasin.add_landuse(2001, landuse_names, areas)
# and add the subbasin to the subbasins dictionary
subbasins[number] = subbasin
# now that that subbasins are specified it is possible to create an instance
# of the Watershed class that is used to build the HSPF input files.
watershed_name = 'Dave'
watershed = Watershed(watershed_name, subbasins)
# another key piece of information for the watershed is the flow network.
# it should be provided as an "updown" dictionary--that is, subbasin names
# are supplied as keys, and the dictionary returns the downstream subbasin
# names as values. So for this example the netword is just subbasin reach "100"
# goes into "101."
updown = {'100':'101'}
# add the mass linkage dictionary to the watershed
watershed.add_mass_linkage(updown)
# need to tell HSPF that subbasin "101" is an outlet where mass leaves. this
# information is needed because PyHSPF starts at the outlet and works
minelev = 90
flow = 12
subbasin.add_flowplane(length, planeslope, centroid, elev)
subbasin.add_reach(name,
maxelev,
minelev,
slopelen,
flow=flow,
velocity=velocity)
subbasin.add_landuse(2001, landuse_names, areas)
subbasins[number] = subbasin
# build the watershed
watershed = Watershed('Dave', subbasins)
# flow network dictionary
updown = {'100': '101'}
# add the info to the watershed and outlet
watershed.add_mass_linkage(updown)
watershed.add_outlet('101')
# names of the files used in the simulation (the HSPF input and output files
# are generated automatically); can also specify a directory to use elsewhere
filename = 'example06'
wdmoutfile = filename + '_out.wdm'
reachShp = shapefile.Reader(parentDir + shapeDir +
'/siletz_river_reaches_HSPF.shp')
basinRecords = basinShp.records()
reachRecords = reachShp.records()
# Send the import data to the pre-build processors
subbasins = create_subbasins(basinRecords, reachRecords, 2011, lc_codes,
hru_df, fTables)
flow_network = create_flownetwork(basinRecords)
# CREATE HSPF MODEL
watershedSiletz = Watershed("Siletz River", subbasins)
watershedSiletz.add_mass_linkage(flow_network)
for basin in range(0, len(basinRecords)):
if basinRecords[basin][6] == 0:
watershedSiletz.add_outlet(str(basin + 1)) # Assumes basin numbers
x = 1 # Don't need this but the loop wants to include 'hspfmodel...'
# Build the model
hspfmodel = HSPFModel(units='Metric')
filename = 'siletz_river'
# hydrology default values
landuse_names = ['Forest', 'Agriculture', 'Pasture/grass', 'Developed']
areas = [3078, 449, 540, 35]
# add the landuse
subbasin.add_landuse(1988, landuse_names, areas)
# add the subbasin to the dictionary
subbasins['32'] = subbasin
# create an instance of the watershed class from the subbasin information
watershed = Watershed(description, subbasins)
# add the network and the outlet subbasin
watershed.add_mass_linkage(updown)
watershed.add_outlet('30')
# since the climate data are provided with hspexp in an export file called
# "huntobs.exp." WDMUtil has a method to automatically import the data to a
# WDM file.
wdm = WDMUtil()
# the data from the export file (*.exp) provided with hspexp need to be
# imported into a wdm file. WDMUtil has a method for this.
# add the landuse
subbasin.add_landuse(1988, landuse_names, areas)
# create a dictionary of the subbasins
subbasins = {sname: subbasin}
# create an updown dictionary for the reach network (trivial with only 1)
updown = {}
# create an instance of the watershed class to store the data to build the model
watershed = Watershed(description, subbasins)
# add the network and the outlet subbasin
watershed.add_mass_linkage(updown)
watershed.add_outlet(sname)
# make the HSPFModel instance (the data for this example use the non-default
# option of English instead of metric units)
from pyhspf import HSPFModel
hspfmodel = HSPFModel(units='English')
# since the climate data are provided with hspexp in an export file called
# "huntobs.exp." WDMUtil has a method to automatically import the data to a
# hydrology default values
landuse_names = ['Forest', 'Agriculture', 'Pasture/grass', 'Developed']
areas = [3078, 449, 540, 35]
# add the landuse
subbasin.add_landuse(1988, landuse_names, areas)
# add the subbasin to the dictionary
subbasins['32'] = subbasin
# create an instance of the watershed class from the subbasin information
watershed = Watershed(description, subbasins)
# add the network and the outlet subbasin
watershed.add_mass_linkage(updown)
watershed.add_outlet('30')
# since the climate data are provided with hspexp in an export file called
# "huntobs.exp." WDMUtil has a method to automatically import the data to a
# WDM file.
wdm = WDMUtil()
# the data from the export file (*.exp) provided with hspexp need to be
# imported into a wdm file. WDMUtil has a method for this.
velocity=velocity)
# for simplicity just assume the same landuse types and areas
subbasin.add_landuse(2001, landuse_names, areas)
# and add the subbasin to the subbasins dictionary
subbasins[number] = subbasin
# now that that subbasins are specified it is possible to create an instance
# of the Watershed class that is used to build the HSPF input files.
watershed_name = 'Dave'
watershed = Watershed(watershed_name, subbasins)
# another key piece of information for the watershed is the flow network.
# it should be provided as an "updown" dictionary--that is, subbasin names
# are supplied as keys, and the dictionary returns the downstream subbasin
# names as values. So for this example the netword is just subbasin reach "100"
# goes into "101."
updown = {'100': '101'}
# add the mass linkage dictionary to the watershed
watershed.add_mass_linkage(updown)
# need to tell HSPF that subbasin "101" is an outlet where mass leaves. this
# information is needed because PyHSPF starts at the outlet and works
