# this example uses a daily time step (pyhspf needs time step in minutes) tstep = 60 * 24 # import the Watershed and Subbasin classes to use to build the model from pyhspf import Watershed, Subbasin # make a subbasin (the hspexp daily example file has only 1 subbasin) # need to assign a name to the subbasin, which (unfortunately) has to be # a string variable of length of at most 15 sname = 'patuxent' subbasin = Subbasin(sname) # overland flow plane info length = 300 # ft planeslope = 0.38 # flow plane slope elev = 0 # not used for hydrology centroid = [0,0] # not sued for hydrology # add the flow plane info for the subbasin subbasin.add_flowplane(length, planeslope, centroid, elev) # subbasin reach info; as above this isn't all directly needed by HSPF but is # needed to build the watershed
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)
# drains to, and landuse (or other category data) to sudivide the subbasin
# into homogeneous land segments.
from pyhspf import Subbasin
# keep up with the subbasins using the "subbasin" dictionary
subbasins = {}
# call the first subbasin "100"
number = '100'
# create subbasin "100"
subbasin = Subbasin(number)
# subbasins are defined by many attributes, which are grouped into categories
# in PyHSPF Subbasin class instances including:
#
# --the flowplane (length, slope, centroid, average elevation)
#
# --the reach (name, upstream elevation, downstream elevation, length,
# optionally average flow rate and velocity)
#
# --the landuse categories to be used by the model and the corresponding areas
# within each subbasin
#
# --the inlets and outlets from the watershed
# flow plane parameters for the subbasin
end = datetime.datetime(2003, 1, 1)
# 4-hour timestep
tstep = 240
# imports from pyhspf
from pyhspf import Watershed, Subbasin, HSPFModel, WDMUtil
subbasins = {} # subbasin dictionary
# provide subbasin attributes
number = '100' # subbasin number
subbasin = Subbasin(number) # created subbasin "100"
length = 100 # m
planeslope = 0.02 # -
area = 100 # km2
elev = 100 # m
centroid = [-90, 40] # long, lat
name = 'stream' # something descriptive
maxelev = 110 # elevation at the top of the reach (m)
minelev = 100 # elevation at the bottom of the reach (m)
slopelen = 10 # the reach length (km)
flow = 12 # the average flow must be in cfs
velocity = 1 # velocity must be in fps
landuse_names = ['Developed', 'Agriculture', 'Forest']
areas = [20, 40, 40]
# add the data for subbasin 100
# 3 subbasins/reaches; the right and left branch feed the main channel;
# call the left and right branches 31 and 32, and main branch 30
updown = {
'32': '30',
'31': '30',
}
# keep track of the subbasins
subbasins = {}
# provide land info for subbasin 30
subbasin = Subbasin('30')
# overland flow plane info -- these need to be modified to agree with example
# later although the difference is very small and not really based on physical
# parameters.
length = 700 # ft
planeslope = 0.05 # flow plane slope
elev = 0
centroid = [0, 0]
# add the flow plane info for the subbasin
subbasin.add_flowplane(length, planeslope, centroid, elev)
# subbasin reach info (conistent with hspexp/data/hunthour/hunting.uci file)
