# SNOTEL Snowpack by Radius: % of Median & Daily History (NRCS) (`bigsky-data-tools/snotel-snowpack-percent-of-median`) Actor

Every SNOTEL site within a radius of your resort, reservoir or ranch, nearest first: snow water, % of median, median peak SWE and date, 1- and 7-day change. Filter by watershed (HUC); get the latest reading or daily history for any date range.

- **URL**: https://apify.com/bigsky-data-tools/snotel-snowpack-percent-of-median.md
- **Developed by:** [BigSky Data Tools](https://apify.com/bigsky-data-tools) (community)
- **Categories:** Other
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## SNOTEL Snowpack & % of Median by Radius: data from the USDA NRCS Air and Water Database (SWE, Snow Depth, Precipitation)

Get **snow water equivalent (SWE), percent of median, snow depth, season precipitation and temperature** from about 900 automated **SNOTEL** mountain stations, using **USDA NRCS** data. Search **by radius around any point**, by state, by watershed (HUC prefix) or by station, and get the latest reading or one row per station per day for any date range. Each row includes the station's **median peak SWE and median peak date**. **No API key, no login.** Published by BigSky Data Tools.

> **NOT FOR SAFETY-CRITICAL USE: data may be delayed or incomplete; not for life-safety, navigation or emergency decisions; use official NRCS sources.**
>
> **Quality flags:** this Actor does not output per-value NRCS quality-control or quality-assurance flags. Check the NRCS AWDB source if you need them.

> **NRCS data condition:** NRCS: "The data you have obtained from this automated Natural Resources Conservation Service database are subject to revision regardless of indicated Quality Assurance level. Data are released on condition that neither the NRCS nor the United States Government may be held liable for any damages resulting from its use." Our cleaning does not make the data final. Each row carries this condition in a `dataNotice` field.

### Why use this snowpack data tool?

- 📍 **Radius search, nearest first**: "every SNOTEL site within 40 miles of this resort, reservoir or ranch". Each row has `distanceMiles`.
- 📊 **% of median computed for you**: `swePctOfMedian` and `precipPctOfMedian`, next to the raw values and the daily medians NRCS publishes.
- 🏔️ **Peak context**: `medianPeakSweIn` and `medianPeakDate` tell you where the season usually tops out.
- 🌊 **Watershed filter**: `hucPrefix` selects stations by hydrologic unit (e.g. 1401 Colorado headwaters).
- 🗓️ **Two modes**: latest reading per station, or daily history for a date range.
- 📈 **Change fields**: `sweChange1dIn`, `sweChange7dIn` and `snowDepthChange1dIn` show melt or new snow at a glance.

### How it compares

In our Apify Store search on 2026-10-31 we did not find another Actor offering all of the features marked **Yes** below together; some alternatives offer individual features, as the "Typical alternatives" column shows. The Store may have changed since.

| | This tool | Typical alternatives |
|---|---|---|
| Radius search, nearest first | **Yes** | By state |
| Watershed (HUC) filter | **Yes** | No |
| Daily history for a date range | **Yes** | Latest reading only |
| % of median and median peak | **Yes** | Yes |

### Who uses it

Water utilities and irrigation districts, hydropower operators, commodity and energy traders, ag lenders and ranchers, ski resorts and outdoor businesses, avalanche and backcountry apps, reinsurance and flood analysts, and researchers.

### Input example

```json
{ "latitude": "39.6403", "longitude": "-106.3742", "radiusMiles": 40 }
```

Daily history for a state: `{ "mode": "daily", "states": ["UT"], "startDate": "2026-03-01", "endDate": "2026-03-05" }`

### Output example

```json
{ "stationId": "842", "stationTriplet": "842:CO:SNTL", "stationName": "Vail Mountain", "state": "CO", "county": "Eagle",
  "huc": "140100030102", "elevationFt": 10290.0, "latitude": 39.61765, "longitude": -106.38019, "distanceMiles": 1.6,
  "date": "2026-10-30", "sweIn": 0.3, "sweMedianIn": 1.0, "swePctOfMedian": 30, "snowDepthIn": 0,
  "precipAccumIn": 1.2, "precipAccumMedianIn": 2.8, "precipPctOfMedian": 43, "tempObsF": 38.7, "tempMaxF": 50.2, "tempMinF": 35.2,
  "medianPeakSweIn": 20.8, "medianPeakDate": "04-27",
  "source": "USDA NRCS Air and Water Database (SNOTEL)", "sourceUrl": "https://wcc.sc.egov.usda.gov/nwcc/site?sitenum=842" }
```

Export to JSON, CSV, Excel or XML, or use the Apify API, Make, Zapier or n8n. Schedule it daily during snow season.

### Pricing

**$7 per 1,000 results** ($0.007 per result) plus a $0.01 start fee per run.

Pay per result: you pay for each row saved. Latest mode returns one row per station (about 900 for the whole network). Daily mode returns one row per station per day, so cap it with dates and `maxResults`. Free-plan users can try it within their monthly platform credit.

### FAQ

**Where does the data come from?** From the public Air and Water Database web service of the USDA Natural Resources Conservation Service (National Water and Climate Center). Recent values are provisional. Source data are works of the U.S. federal government (USDA NRCS) and generally not subject to U.S. copyright (17 U.S.C. 105). This is not a license or warranty; third-party or foreign rights may apply. You are responsible for how you use the data.
**Why is % of median empty?** Early or late in the season the NRCS median can be zero, and for some stations and dates (new stations, or gaps in the record) NRCS publishes no median at all. Each row's `pctOfMedianNote` says which: `median is 0 (early/late season)` or `NRCS publishes no median for this station/date`. If SWE and precipitation differ, the note is prefixed, for example `SWE: median is 0 (early/late season)`. If NRCS has no reading at all, the note says so, for example `precip: no NRCS precipitation reading for this station/date` (or `SWE: no NRCS snow water equivalent reading for this station/date`). Multiple reasons are joined with `; `. The note is empty when both percentages are computed.
**Is this tool run by the data agency?** No. BigSky Data Tools is independent and not affiliated with or endorsed by USDA or NRCS. Do not use it for avalanche or safety decisions.

**Is the data guaranteed?** No. The tool and data are provided as is, without warranty of accuracy, completeness or timeliness, and values can differ from the source agency's official products.

# Actor input Schema

## `mode` (type: `string`):

Latest = most recent day with data per station. Daily = one row per station per day between start and end date.

## `states` (type: `array`):

Two-letter codes of SNOTEL states (AK, AZ, CA, CO, ID, MT, NM, NV, OR, SD, UT, WA, WY). Leave empty for all ~900 stations.

## `latitude` (type: `string`):

Optional. With longitude and radius, returns stations near this point, nearest first (e.g. 39.6403 for Vail, CO).

## `longitude` (type: `string`):

Optional, e.g. -106.3742.

## `radiusMiles` (type: `integer`):

Search radius around the center point.

## `hucPrefix` (type: `string`):

Optional hydrologic unit code prefix, e.g. 1401 (Colorado headwaters) or 17 (Pacific Northwest).

## `stationIds` (type: `array`):

Optional SNOTEL station numbers or triplets, e.g. 335 or 335:CO:SNTL.

## `startDate` (type: `string`):

YYYY-MM-DD. Default: 7 days ago.

## `endDate` (type: `string`):

YYYY-MM-DD. Default: today.

## `maxResults` (type: `integer`):

Maximum rows to save (each saved row is one billable result).

## Actor input object example

```json
{
  "mode": "latest",
  "states": [
    "CO"
  ],
  "radiusMiles": 50,
  "maxResults": 5000
}
```

# Actor output Schema

## `dataset` (type: `string`):

Default dataset containing all output records

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "states": [
        "CO"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("bigsky-data-tools/snotel-snowpack-percent-of-median").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "states": ["CO"] }

# Run the Actor and wait for it to finish
run = client.actor("bigsky-data-tools/snotel-snowpack-percent-of-median").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "states": [
    "CO"
  ]
}' |
apify call bigsky-data-tools/snotel-snowpack-percent-of-median --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,bigsky-data-tools/snotel-snowpack-percent-of-median"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/77HnDPnHLDwbV2O7R/builds/eCSUO3mIGf9CBtqI3/openapi.json