Nogales Wash at Nogales Water Level
Live river level, flow, historical records and forecast for Nogales Wash at Nogales in AZ, United States, built from official government gauge data.
- Location AZ, United States
- Watershed upper santa cruz
- Primary gauge 09481000 (USGS)
About Nogales Wash at Nogales
Nogales Wash in the Upper Santa Cruz watershed in Arizona.
What the record shows
The station record runs for more than 16 years, and it shows a wide range for a channel that can change fast after storms.
The highest level on record is 20.59 ft (6.28 m) in December 2012. The lowest is -35.56 ft (-10.84 m) in September 2013. Those two marks tell you this gauge can sit far apart from one season to another, and that any bank, crossing, or low-water intake here has to be built with that spread in mind.
The seasonal pattern is tight on paper but still matters on the ground. August is the highest typical month at 2.12 ft (0.65 m), while June is the lowest typical month at 2.07 ft (0.63 m). The typical annual swing is 0.6 in (1.5 cm). For a wash, that small monthly spread says the everyday signal is subdued; the bigger concern is what happens when a storm arrives.
I do not have a fastest 24-hour rise for this site in the record provided, so I cannot say how much warning the wash gives in one day.
The watershed
This gauge drains 29.3 sq mi (75.9 km2) upstream of the station. That is the catchment that matters for this reading, not the full watershed name on a map.
For neighbours, the key point is that a small upstream area can still send a sharp pulse through a wash after summer thunderstorms. Between events, flow can be much lower than the storm-time peaks shown by the record. In winter, the larger regional rivers are more often tied to storms and high-country snowmelt, but this site’s record is the one to watch for local rise and fall at the crossing.
Reading the hero number
The hero number on this page is today’s reading compared with the median for this calendar day across the station record. That is more useful than raw elevation because it shows whether the wash is running above or below its usual level for this date.
This station is operated by the USGS. With more than 16 years on record, the daily median gives a better sense of what is normal here than a single height by itself. For cottagers, anglers, and anyone watching access routes, that comparison is the practical one: it tells you whether the wash is behaving like a typical day or leaning toward the high or low edge of its record.
How this page is built
Readings come from official government gauges and are rolled into daily records: the daily mean, high and low for every day on record. Each calendar day gets its own baseline from the full history, so the level you see is compared against what this specific date usually looks like rather than an annual average.
How Nibi Metrics works · Water stories
Nibi Metrics - live water levels, flow, and forecasts for 17,900+ lakes and rivers
Real-time water levels, forecasts, and alerts for lakes and rivers in a growing number of countries. Built on official government data.
Nibi Metrics tracks more than 17,900 gauged lakes and rivers in a growing number of countries, reading directly from official federal monitoring networks: the Water Survey of Canada, the United States Geological Survey, Quebec's provincial hydrometric network, the Environment Agency for England, the Scottish Environment Protection Agency, Natural Resources Wales, the Office of Public Works in Ireland (waterlevel.ie), the Norwegian Water Resources and Energy Directorate (NVE), the State of Queensland's water monitoring network, and on the Great Lakes the Canadian Hydrographic Service and NOAA. Every number on the platform is measured, not modelled - taken from a government gauge on the water itself and compared against that location's own historical record for this exact date.
What you can see for any monitored lake or river
The level right now, in feet or metres, updated as the source agency publishes new readings - for many stations that is every five to fifteen minutes. How today compares to typical: every location carries its own typical-for-this-date band built from its historical record, so a reading is never just a number - it is above, below, or near what this water usually does on this calendar day. Which way it is moving: a measured RISING, FALLING, or STEADY verdict computed from the gauge's own recent readings, with the rate of change - the difference between a flood ending and one beginning. What comes next: level forecasts up to 72 hours ahead, driven by the gauge's recent behaviour, upstream water, and quantitative precipitation forecasts, alongside live radar, lightning, and weather for the surrounding region.
Alerts that watch the water for you
Set a threshold on any location - a level, a distance above typical, or a rate of climb - and Nibi emails or notifies you the moment the gauge crosses it. Cottagers use it for spring freshet, anglers for river conditions, marinas and municipalities for operations. The scanning runs around the clock against the same measured data shown on every page.
Where Nibi comes from
Nibi means water in Anishinaabemowin. The platform began at a family cottage on Lake Muskoka, Ontario, where the spring melt floods the shoreline most years and the only forecast was standing on the dock, looking, and guessing. It grew into an independent, member-funded platform run by Muskoka Research Inc. - no investors, no data resale, and a privacy policy shorter than most cookie banners. The core data is free for everyone, forever; paid plans add automation like multi-location alerts, deep history, and reports.
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The core promise is simple: the water data is free, for everyone, forever. Live levels, maps, radar, and recent history never sit behind a paywall. Paid plans fund the platform by adding automation - multi-location alerts, decades of history, longer forecasts, and PDF reports - so the people who need more carry the cost for everyone who just needs to check the lake before driving up. There are no investors and no advertising deals shaping what the data says.
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