US river discharge anomaly pulse (15 gages, daily)

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Per-gage-day streamflow anomaly signals for 15 major U.S. river gaging stations (Potomac, Delaware, Susquehanna, Hudson, James, Suwannee, Missouri, Mississippi x3, Ohio x2, Yellowstone, Columbia, Willamette): the trailing 90 complete days of USGS daily-mean discharge (parameter 00060, ft³/s) transformed into a seasonal day-of-year percentile (±15-day window over the trailing 365 days; documented 15-value minimum), 30/90-day z-scores, week-over-week change of 7-day means, a documented drought/flood severity class, and a 0–100 anomaly score (|percentile − 50| × 2). Genuine USGS gaps stay null (never interpolated); provisional values are subject to USGS revision. Primary key: (site_no, date). Join keys: site_no (USGS station number), date (ISO). Cadence: daily; as_of is the last complete UTC day, so identical input re-ingests as a no-op. USGS data is U.S. public domain — commercial_use = yes. Sample use: filter as_of = the latest date and order by anomaly_score desc for today's most anomalous rivers.

Source: USGS River Discharge Anomaly Pulse
Rows: 1,350
Columns: 19
Source cadence: Daily
Last refreshed: Sep 28, 2026
Theme: environment

Column	Type	Description
as_of	string	Last complete UTC day of the fetch window. Fixed per run so identical input produces an identical content hash. (unit: date)
date	string	The gage-day the anomaly metrics describe (ISO date). Panel covers as_of−89d … as_of. (unit: date)
site_no	string	USGS station number (e.g. '07010000' = Mississippi River at St. Louis). Join key. (unit: id)
station_name	string	Official USGS station name from the Water Services response.
river	string	River name parsed from the panel label (e.g. 'Potomac River').
country	string	Canonical country name (all gages are in the United States).
country_code	string	ISO alpha-3 country code (USA). Join key. (unit: code)
latitude	float	Gage latitude from the Water Services site metadata. (unit: degrees)
longitude	float	Gage longitude from the Water Services site metadata. (unit: degrees)
discharge_cfs	float	USGS daily-mean streamflow discharge. Null when USGS publishes no value for the day (genuine upstream gap — never filled or interpolated). (unit: ft3/s)
data_status	string	USGS qualifier for the daily value: 'provisional' (subject to revision) or 'approved'.
doy_percentile	float	Seasonal percentile: 100 × #{seasonal reference values < discharge} / n_ref, where the reference set is the same gage's values within ±15 days of day-of-year over the trailing 365 days (target day excluded). Null when n_ref_days < 15. (unit: percentile)
n_ref_days	integer	Number of seasonal reference values behind doy_percentile (transparency for the 15-value minimum). (unit: count)
z_30d	float	z-score of discharge vs the prior 30 complete days (minimum 15 valid values; 0.0 when history is perfectly flat). (unit: z)
z_90d	float	z-score of discharge vs the prior 90 complete days (minimum 30 valid values). (unit: z)
wow_change_pct	float	Week-over-week change (%) of 7-day mean discharge: 100 × (mean(last 7d) − mean(prior 7d)) / mean(prior 7d); null when either block has <5 valid values or the prior mean is zero. (unit: percent)
anomaly_class	string	Documented severity class from doy_percentile: drought_watch (<10), below_normal (<25), normal (≤75), above_normal (≤90), flood_watch (>90); no_data when discharge is null, insufficient_history when the percentile is null but discharge exists.
anomaly_score	float	\|doy_percentile − 50\| × 2 on a 0–100 scale (0 = perfectly seasonal-normal, 100 = most extreme); null when doy_percentile is null. (unit: score)
row_hash	string	SHA-256 (16 hex chars) over the row's content fields; identical input yields an identical hash, so a re-run on an unchanged feed is a no-op. (unit: hash)

First 10 sample rows — a preview, not the complete dataset.

as_of	date	site_no	station_name	river	country	country_code	latitude	longitude	discharge_cfs	data_status	doy_percentile	n_ref_days	z_30d	z_90d	wow_change_pct	anomaly_class	anomaly_score	row_hash
2026-09-27	2026-06-30	01358000	HUDSON RIVER AT GREEN ISLAND NY	Hudson River	United States	USA	42.752	-73.689	6,450	provisional	43.33	30	-0.515	-0.705	3.83	normal	13.3	dd13d6cf71b31d77
2026-09-27	2026-06-30	01463500	Delaware River at Trenton NJ	Delaware River	United States	USA	40.222	-74.778	3,880	provisional	44.83	29	-0.561	-1.187	14	normal	10.3	8c5b09be2bb9a3e4
2026-09-27	2026-06-30	01578310	SUSQUEHANNA RIVER AT CONOWINGO, MD	Susquehanna River	United States	USA	39.658	-76.174	17,000	provisional	66.67	30	0.017	-0.908	-14.19	normal	33.3	27621bd6aea65374
2026-09-27	2026-06-30	01646500	POTOMAC RIVER NEAR WASH, DC LITTLE FALLS PUMP STA	Potomac River	United States	USA	38.95	-77.128	2,500	provisional	43.33	30	-0.589	-0.546	0.68	normal	13.3	95e9e2c4d98fa427
2026-09-27	2026-06-30	02037500	JAMES RIVER NEAR RICHMOND, VA	James River	United States	USA	37.563	-77.547	1,080	provisional	33.33	30	-0.663	-0.93	-6.59	normal	33.3	7eb19873657ace15
2026-09-27	2026-06-30	02323500	SUWANNEE RIVER NEAR WILCOX, FLA.	Suwannee River	United States	USA	29.59	-82.937	5,230	provisional	73.33	30	3.237	3.692	15.09	normal	46.7	00ad68bb785a7a74
2026-09-27	2026-06-30	03294500	OHIO RIVER AT LOUISVILLE, KY	Ohio River	United States	USA	38.28	-85.799	120,000	provisional	92.59	27	0.195	-0.239	31.23	flood_watch	85.2	5ee7dac02c17a6c4
2026-09-27	2026-06-30	03303280	OHIO RIVER AT CANNELTON DAM AT CANNELTON, IN	Ohio River	United States	USA	37.9	-86.706	177,000	provisional	90	30	0.684	0.292	42.71	above_normal	80	4223ecbb94a3effe
2026-09-27	2026-06-30	06329500	Yellowstone River near Sidney MT	Yellowstone River	United States	USA	47.677	-104.155	14,700	provisional	83.33	30	-0.658	0.587	5.22	above_normal	66.7	73862f523e0c8733
2026-09-27	2026-06-30	06934500	Missouri River at Hermann, MO	Missouri River	United States	USA	38.71	-91.439	133,000	approved	53.33	30	-0.874	-0.078	-9.94	normal	6.7	3c049329276e8686

Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).

cURL

curl "https://datazimuts.com/v1/datasets/usgs_discharge_anomaly/usgs_river_discharge_anomaly_daily" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/usgs_discharge_anomaly/usgs_river_discharge_anomaly_daily").json()
print(ds["title"], ds["rows"], "rows")

# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
    print(row)

API endpoint: https://datazimuts.com/v1/datasets/usgs_discharge_anomaly/usgs_river_discharge_anomaly_daily

Tip: fetch /llms.txt for the full machine-readable catalog.

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Pinned to snapshot 20260928T224839Z-2b58739e2e93 and its content hash, so readers get exactly the data you used.

APA

USGS River Discharge Anomaly Pulse. (2026). US river discharge anomaly pulse (15 gages, daily) [Data set, snapshot 20260928T224839Z-2b58739e2e93, sha256 2b58739e2e93]. Datazimuts. Retrieved 2026-09-29, from https://datazimuts.com/en/datasets/usgs_discharge_anomaly/usgs_river_discharge_anomaly_daily?snapshot=20260928T224839Z-2b58739e2e93

BibTeX

@misc{dz_usgs_discharge_anomaly_usgs_river_discha_2b58739e,
  title        = {{US river discharge anomaly pulse (15 gages, daily)}},
  author       = {{USGS River Discharge Anomaly Pulse}},
  year         = {2026},
  publisher    = {Datazimuts},
  howpublished = {\url{https://datazimuts.com/en/datasets/usgs_discharge_anomaly/usgs_river_discharge_anomaly_daily?snapshot=20260928T224839Z-2b58739e2e93}},
  note         = {Snapshot 20260928T224839Z-2b58739e2e93, sha256 2b58739e2e933a69be4dbb3e7f80591087edff74d45e67aae45e71095182f165; accessed 2026-09-29}
}

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US river discharge anomaly pulse (15 gages, daily)

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