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Get_StreamStats.py
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Get_StreamStats.py
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#!/usr/bin/env python
# coding: utf-8
# In[1]:
import dataretrieval.nwis as nwis
##https://streamstats-python.readthedocs.io/en/latest/gallery_vignettes/plot_get_characteristics.html
import streamstats
import pandas as pd
import numpy as np
import time
from progressbar import ProgressBar
def get_USGS_site_info(site_ids, Preloaded_data):
#set up Pandas DF for state streamstats
Streamstats_cols = ['NWIS_siteid','Lat', 'Long', 'Drainage_area_mi2', 'Mean_Basin_Elev_ft', 'Perc_Forest', 'Perc_Develop',
'Perc_Imperv', 'Perc_Herbace', 'Perc_Slop_30', 'Mean_Ann_Precip_in']
NWIS_Stats = pd.DataFrame(columns = Streamstats_cols)
print('Calculating NWIS streamflow id characteristics for ', len(site_ids), 'sites')
if Preloaded_data == False:
pbar = ProgressBar()
for site in pbar(site_ids):
print('NWIS site: ', site)
#try:
NWISinfo = nwis.get_record(sites=site, service='site')
lat, lon = NWISinfo['dec_lat_va'][0],NWISinfo['dec_long_va'][0]
#This sources the prestored data
try:
ws = streamstats.Watershed(lat=lat, lon=lon)
except:
print('502 error, StreamStats down, using backup files')
ws = pd.read_csv('./Data/StreamStats_All.csv')
ws['NWIS_site_id'] = ws['NWIS_site_id'].astype(str)
ws = ws[ws.NWIS_site_id == site]
NWISindex = ['NWIS_site_id', 'Lat', 'Long', 'Drainage_area_mi2', 'Mean_Basin_Elev_ft', 'Perc_Forest', 'Perc_Develop',
'Perc_Imperv', 'Perc_Herbace', 'Perc_Slop_30', 'Mean_Ann_Precip_in']
print('Retrieving Drainage Area')
try:
darea = ws.get_characteristic('DRNAREA')['value']
except KeyError:
darea = np.nan
except ValueError:
darea = np.nan
except AttributeError:
darea = ws['Drainage_area_mi2'].values[0]
print('Retrieving Mean Catchment Elevation')
try:
elev = ws.get_characteristic('ELEV')['value']
except KeyError:
elev = np.nan
except ValueError:
elev = np.nan
except AttributeError:
elev = ws['Mean_Basin_Elev_ft'].values[0]
print('Retrieving Catchment Land Cover Information')
try:
forest = ws.get_characteristic('FOREST')['value']
except KeyError:
forest = np.nan
except ValueError:
forest = np.nan
except AttributeError:
forest = ws['Perc_Forest'].values[0]
try:
dev_area = ws.get_characteristic('LC11DEV')['value']
except KeyError:
dev_area = np.nan
except ValueError:
dev_area = np.nan
except AttributeError:
dev_area = ws['Perc_Develop'].values[0]
try:
imp_area = ws.get_characteristic('LC11IMP')['value']
except KeyError:
imp_area = np.nan
except ValueError:
imp_area = np.nan
except AttributeError:
imp_area = ws['Perc_Imperv'].values[0]
try:
herb_area = ws.get_characteristic('LU92HRBN')['value']
except KeyError:
herb_area = np.nan
except ValueError:
herb_area = np.nan
except AttributeError:
herb_area = ws['Perc_Herbace'].values[0]
print('Retrieving Catchment Topographic Complexity')
try:
perc_slope = ws.get_characteristic('SLOP30_10M')['value']
except KeyError:
perc_slope = np.nan
except ValueError:
perc_slope = np.nan
except AttributeError:
perc_slope = ws['Perc_Slop_30'].values[0]
print('Retrieving Catchment Average Precip')
try:
precip = ws.get_characteristic('PRECIP')['value']
except KeyError:
precip = np.nan
except ValueError:
precip = np.nan
except AttributeError:
precip = ws['Mean_Ann_Precip_in'].values[0]
NWISvalues = [site,
lat,
lon,
darea,
elev,forest,
dev_area,
imp_area,
herb_area,
perc_slope,
precip]
print(NWISvalues)
Catchment_Stats = pd.DataFrame(data = NWISvalues, index = NWISindex).T
NWIS_Stats = NWIS_Stats.append(Catchment_Stats)
if Preloaded_data == True:
print('StreamStats downloaded files')
ws = pd.read_csv('./Data/StreamStats_All.csv')
ws['NWIS_site_id'] = ws['NWIS_site_id'].astype(str)
pbar = ProgressBar()
for site in pbar(site_ids):
print('NWIS site: ', site)
NWISinfo = nwis.get_record(sites=site, service='site')
lat, lon = NWISinfo['dec_lat_va'][0],NWISinfo['dec_long_va'][0]
ws1 = ws[ws.NWIS_site_id == site].copy()
NWISindex = ['NWIS_site_id', 'Lat', 'Long', 'Drainage_area_mi2', 'Mean_Basin_Elev_ft', 'Perc_Forest', 'Perc_Develop',
'Perc_Imperv', 'Perc_Herbace', 'Perc_Slop_30', 'Mean_Ann_Precip_in']
darea = ws1['Drainage_area_mi2'].values[0]
elev = ws1['Mean_Basin_Elev_ft'].values[0]
forest = ws1['Perc_Forest'].values[0]
dev_area = ws1['Perc_Develop'].values[0]
imp_area = ws1['Perc_Imperv'].values[0]
herb_area = ws1['Perc_Herbace'].values[0]
perc_slope = ws1['Perc_Slop_30'].values[0]
precip = ws1['Mean_Ann_Precip_in'].values[0]
NWISvalues = [site,
lat,
lon,
darea,
elev,forest,
dev_area,
imp_area,
herb_area,
perc_slope,
precip]
print(NWISvalues)
Catchment_Stats = pd.DataFrame(data = NWISvalues, index = NWISindex).T
NWIS_Stats = NWIS_Stats.append(Catchment_Stats)
colorder =['NWIS_site_id', 'Lat', 'Long', 'Drainage_area_mi2', 'Mean_Basin_Elev_ft', 'Perc_Forest',
'Perc_Develop','Perc_Imperv', 'Perc_Herbace', 'Perc_Slop_30', 'Mean_Ann_Precip_in']
NWIS_Stats = NWIS_Stats[colorder]
NWIS_Stats.reset_index(drop = True, inplace = True)
return NWIS_Stats
# In[ ]: