We have developed an applied example to download information and groundwater levels for one well and multiple wells with Python and the dataretrieval package. The tutorial stores information and levels on a csv file an can be easily applied for streamflow and water quality data stored on the NWIS.

More information about NWIS:

https://nwis.waterdata.usgs.gov/nwis

More information about the USGS dataretrieval package:

https://github.com/USGS-python/dataretrieval

Tutorial

Code

#!pip install -U dataretrieval

import dataretrieval.nwis as nwis
import pandas as pd

---

For one station

site = '401612074483401'

Get site info

siteInfo = nwis.get_info(sites=site)
siteInfo[0]

	agency_cd	site_no	station_nm	site_tp_cd	lat_va	long_va	dec_lat_va	dec_long_va	coord_meth_cd	coord_acy_cd	…	local_time_fg	reliability_cd	gw_file_cd	nat_aqfr_cd	aqfr_cd	aqfr_type_cd	well_depth_va	hole_depth_va	depth_src_cd	project_no
0	USGS	401612074483401	210545– MW-2Br	GW	401612.53	744832.14	40.270147	-74.808928	N	1	…	Y	C	YYYYNYNN	N300ERLMZC	231LCKG	NaN	60	60	D	NAWC

1 rows × 42 columns

wellInfoDf = siteInfo[0][['site_no','dec_lat_va','dec_long_va','dec_coord_datum_cd','alt_va','alt_datum_cd','well_depth_va']]
wellInfoDf = wellInfoDf.rename(columns={'site_no':'SiteNo',
                                'dec_lat_va':'Latitude',
                                'dec_long_va':'Longitude',
                                'dec_coord_datum_cd':'LatLonDatum',
                                'alt_va':'SurfaceElevation',
                                'alt_datum_cd':'WellHole',
                                'well_depth_va':'ElevationDatum'}) 
wellInfoDf = wellInfoDf.set_index('SiteNo')
wellInfoDf

	Latitude	Longitude	LatLonDatum	SurfaceElevation	WellHole	ElevationDatum
SiteNo
401612074483401	40.270147	-74.808928	NAD83	157.48	NAVD88	60

Get groundwater levels

wellDf = nwis.get_record(sites=site, service='gwlevels', start='2000-01-01')
wellDf.head()

	agency_cd	site_no	site_tp_cd	lev_va	sl_lev_va	sl_datum_cd	lev_status_cd	lev_agency_cd	lev_dt_acy_cd	lev_acy_cd	lev_src_cd	lev_meth_cd	lev_age_cd
datetime
2000-05-18 14:39:00+00:00	USGS	401612074483401	GW	10.78	NaN	NaN	1	USGS	m	NaN	S	T	A
2000-10-23 18:10:00+00:00	USGS	401612074483401	GW	11.05	NaN	NaN	1	USGS	m	NaN	S	T	A
2001-03-29 16:20:00+00:00	USGS	401612074483401	GW	6.94	NaN	NaN	1	USGS	m	NaN	S	T	A
2001-10-23 15:02:00+00:00	USGS	401612074483401	GW	14.32	NaN	NaN	1	USGS	m	NaN	S	S	A
2003-01-31 16:28:00+00:00	USGS	401612074483401	GW	11.25	NaN	NaN	1	USGS	m	NaN	S	S	A

gwWellDf = wellDf[['site_no','site_tp_cd','lev_va']]
gwWellDf = gwWellDf.rename(columns={
    'site_no':'SiteNo',
    'site_tp_cd':'Type',
    'lev_va':'gwLevel'})
gwWellDf

	SiteNo	Type	gwLevel
datetime
2000-05-18 14:39:00+00:00	401612074483401	GW	10.78
2000-10-23 18:10:00+00:00	401612074483401	GW	11.05
2001-03-29 16:20:00+00:00	401612074483401	GW	6.94
2001-10-23 15:02:00+00:00	401612074483401	GW	14.32
2003-01-31 16:28:00+00:00	401612074483401	GW	11.25
2003-03-19 19:22:00+00:00	401612074483401	GW	9.37
2003-03-24 15:26:00+00:00	401612074483401	GW	8.53
2004-05-11 15:00:00+00:00	401612074483401	GW	7.63
2005-06-30 15:55:00+00:00	401612074483401	GW	12.91
2006-06-01 15:36:00+00:00	401612074483401	GW	11.62
2017-11-03 17:25:00+00:00	401612074483401	GW	12.91
2019-05-23 15:41:00+00:00	401612074483401	GW	8.17

---

For many groundwater wells

wellsDf = pd.read_csv('../Txt/NAWC2018reportedWLs.txt',delimiter='t')
wellList = list(wellsDf.NWISnumber)
wellList[:5]

[401612074483401,
 401609074483402,
 401605074485102,
 401619074484801,
 401614074483101]

sitesInfo = nwis.get_info(sites=wellList)

wellsInfoDf = sitesInfo[0][['site_no','dec_lat_va','dec_long_va','dec_coord_datum_cd','alt_va','alt_datum_cd','well_depth_va']]
wellsInfoDf = wellsInfoDf.rename(columns={'site_no':'SiteNo',
                                'dec_lat_va':'Latitude',
                                'dec_long_va':'Longitude',
                                'dec_coord_datum_cd':'LatLonDatum',
                                'alt_va':'SurfaceElevation',
                                'alt_datum_cd':'WellHole',
                                'well_depth_va':'ElevationDatum'}) 
wellsInfoDf = wellsInfoDf.set_index('SiteNo')
wellsInfoDf.to_csv('../Csv/gwWells.csv')
wellsInfoDf.head()

	Latitude	Longitude	LatLonDatum	SurfaceElevation	WellHole	ElevationDatum
SiteNo
401603074485301	40.267533	-74.814331	NAD83	150.02	NAVD88	48.0
401605074483401	40.268033	-74.809100	NAD83	143.39	NAVD88	75.0
401605074485102	40.268289	-74.813811	NAD83	149.03	NAVD88	7.0
401606074485001	40.268364	-74.813592	NAD83	149.29	NAVD88	13.0
401606074485101	40.268328	-74.813725	NAD83	148.36	NAVD88	13.0

wellsDf = nwis.get_record(sites=wellList, service='gwlevels', start='2000-01-01')
wellsDf.head()

		agency_cd	site_tp_cd	lev_va	sl_lev_va	sl_datum_cd	lev_status_cd	lev_agency_cd	lev_dt_acy_cd	lev_acy_cd	lev_src_cd	lev_meth_cd	lev_age_cd
site_no	datetime
401603074485301	2000-05-18 17:50:00+00:00	USGS	GW	7.92	NaN	NaN	1	USGS	m	NaN	S	S	A
	2000-10-23 14:25:00+00:00	USGS	GW	7.65	NaN	NaN	1	USGS	m	NaN	S	S	A
	2001-03-29 18:04:00+00:00	USGS	GW	7.82	NaN	NaN	1	USGS	m	NaN	S	S	A
	2001-10-23 17:35:00+00:00	USGS	GW	11.81	NaN	NaN	1	USGS	m	NaN	S	S	A
	2003-03-19 21:51:00+00:00	USGS	GW	6.62	NaN	NaN	1	USGS	m	NaN	S	S	A

gwWellsDf = wellsDf[['site_tp_cd','lev_va']]

gwWellsDf.index.set_names(['SiteNo','Datetime'], inplace=True)

gwWellsDf = gwWellsDf.rename(columns={
    'site_tp_cd':'Type',
    'lev_va':'gwLevel'})

gwWellsDf.to_csv('../Csv/gwLevels.csv')

gwWellsDf

		Type	gwLevel
SiteNo	Datetime
401603074485301	2000-05-18 17:50:00+00:00	GW	7.92
	2000-10-23 14:25:00+00:00	GW	7.65
	2001-03-29 18:04:00+00:00	GW	7.82
	2001-10-23 17:35:00+00:00	GW	11.81
	2003-03-19 21:51:00+00:00	GW	6.62
…	…	…	…
401625074484001	2005-06-30 14:10:00+00:00	GW	18.71
	2006-06-01 16:32:00+00:00	GW	18.09
	2017-11-03 17:58:00+00:00	GW	14.85
	NaN	GW	16.27
	NaN	GW	15.14

651 rows × 2 columns

Input files

You can download the input files from this link.

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