National Ground-Water Monitoring Network (NGWMN)

The National Ground-Water Monitoring Network (NGWMN) brings groundwater data from many state, federal, and local agencies into a single location. USGS exposes it through a dedicated OGC API (https://api.waterdata.usgs.gov/ngwmn/ogcapi), which dataretrieval wraps in the dataretrieval.ngwmn module — a sibling of dataretrieval.waterdata built on the same shared OGC engine, so chunking, pagination, and result shaping behave the same.

There are five getters:

Function	Description
get_sites	Monitoring-location (well) metadata
get_water_level	Water-level observations
get_lithology	Lithology (geologic material) logs
get_well_construction	Well-construction records
get_providers	Contributing data providers

Unlike the main Water Data collections, NGWMN aggregates locations from many agencies, so monitoring_location_id values use agency prefixes besides USGS- (e.g. MBMG-702934, AKDNR-535134236016630).

from dataretrieval import ngwmn

Providers

List the organizations contributing data, optionally filtered by state.

providers, md = ngwmn.get_providers(state="WI")
print(f"{len(providers)} providers in WI")
providers.head()

Retrieving: providers · 1 page · 37 rows
No API key detected — register for higher rate limits at https://api.waterdata.usgs.gov/signup/

37 providers in WI

	id	agency_name	agency_code	organization_type	state	link
0	WI001	WISCONSIN DEPARTMENT OF NATURAL RESOURCES, WI	WI001	NWIS	WI
1	WI002	EAST CENTRAL WISCONSIN REGIONAL PLANNING COM, WI	WI002	NWIS	WI
2	WI003	DAIRYLAND POWER COOPERATIVE, WI	WI003	NWIS	WI
3	WI004	NORTHERN STATES POWER COMPANY, WI	WI004	NWIS	WI
4	WI005	WISCONSIN STATE LABORATORY OF HYGIENE, WI	WI005	NWIS	WI

Sites

get_sites returns well metadata. Sites carry geometry by default, so the result is a GeoDataFrame; pass skip_geometry=True to drop it.

sites, md = ngwmn.get_sites(state="Wisconsin")
print(f"{len(sites)} NGWMN sites in Wisconsin")
sites[["monitoring_location_id", "monitoring_location_name", "national_aquifer_description"]].head()

Retrieving: sites · 1 page · 175 rows

175 NGWMN sites in Wisconsin

	monitoring_location_id	monitoring_location_name	national_aquifer_description
0	USGS-423114090161101	LF-01/02E/33-0057	Cambrian-Ordovician aquifer system
1	USGS-423214087503801	KE-01/22E/13-0046	Silurian-Devonian aquifers
2	USGS-423312088350401	WW-01/16E/10-2194	Sand and gravel aquifers (glaciated regions)
3	USGS-423523088244901	2N18E-31.8a	Sand and gravel aquifers (glaciated regions)
4	USGS-423532088254601	WW-02/17E/36-0037	Cambrian-Ordovician aquifer system

Water levels

get_water_level returns the observations for one or more sites. A two-element datetime=[start, end] restricts the record to a time window; a list of monitoring_location_ids fans out across sites and is unioned.

import pandas as pd
import matplotlib.pyplot as plt

site = "USGS-272838082142201"
wl, md = ngwmn.get_water_level(monitoring_location_id=site)
print(f"{len(wl)} water-level observations at {site}")

wl["sample_time"] = pd.to_datetime(wl["sample_time"], errors="coerce", utc=True)
wl = wl.dropna(subset=["sample_time"]).sort_values("sample_time")
depth = pd.to_numeric(wl["water_depth_below_land_surface_ft"], errors="coerce")

fig, ax = plt.subplots(figsize=(9, 4))
ax.plot(wl["sample_time"], depth, lw=0.8)
ax.invert_yaxis()  # depth increases downward
ax.set(xlabel="Date", ylabel="Depth to water (ft below land surface)",
       title=f"NGWMN water levels \u2014 {site}")
plt.tight_layout()
plt.show()

Retrieving: waterLevelObs · 1 page · 16,065 rows

16065 water-level observations at USGS-272838082142201

Restrict to a date range, or query several sites at once (they fan out and union):

windowed, md = ngwmn.get_water_level(
    monitoring_location_id=site, datetime=["2022-01-01", "2024-01-01"]
)
print(f"{len(windowed)} observations in 2022\u20132024")

multi, md = ngwmn.get_water_level(
    monitoring_location_id=["USGS-272838082142201", "USGS-404159100494601"]
)
print(f"{multi['monitoring_location_id'].nunique()} sites, {len(multi)} observations")

Retrieving: waterLevelObs · 1 page · 559 rows

559 observations in 2022–2024

Retrieving: waterLevelObs · 1 page · 16,325 rows

2 sites, 16325 observations

Well construction and lithology

Construction records describe a well’s physical build-out; lithology logs describe the geologic materials with depth.

construction, md = ngwmn.get_well_construction(monitoring_location_id=site)
construction[["monitoring_location_obs_number", "type", "material", "depth_from", "depth_to"]].head()

Retrieving: constructionObs · 1 page · 2 rows

	monitoring_location_obs_number	type	material	depth_from	depth_to
0	1	casing	NaN	0	208
1	2	screen	Screen, Type Not Known	208	1123

lithology, md = ngwmn.get_lithology(monitoring_location_id="AKDNR-535134236016630")
lithology[["lithology_depth_from", "lithology_depth_to", "lithology_description"]].head()

Retrieving: lithologyObs · 1 page · 1 rows

	lithology_depth_from	lithology_depth_to	lithology_description
0	0	70	glacial alluvium