How to make high-quality watershed maps for Wikipedia

Wikipedia has thousands of articles about rivers. What are the most important facts about a river? Some can be described with numbers, such as its length, width, or average flow.

I think that every Wikipedia article about a river should include a watershed map. A map can tell you so much, including the landscape features that affect a river’s flow and water quality.

You can make a high-quality map using the free Global Watersheds web app. It is fast and easy. The best part is that you can include a link to a live, interactive map. Below is an example, followed by step-by-step instructions.

Map of the Onibe River watershed in Madagascar. Created with the free Global Watersheds web app. Permalink to interactive map:
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New Features in the Global Watersheds Web App

I’m pleased to announce some new features and enhancements in the Global Watersheds web app.

You can now delineate watersheds that drain to a polyline or polygon feature. This is useful for finding the total drainage area for a section of coastline or for an inland lake — also known as “endorheic” lakes.

To use this feature, under Options, check the box for Delineate watersheds for a lake or coastline. On the left side of the map, you will see a new drawing toolbar. Select one of the drawing tools, and create a polyline, polygon, rectangle or circle. You can only draw one feature at a time. There are also little buttons to edit your feature or to delete it. Then click on the feature and then click the button Delineate! This feature is only available using MERIT data (not HydroSHEDS), and only in “lower-resolution” mode.

In the example below, I found the area that drains to the Gulf of Bejaia on the Mediterranean coast in Algeria, by drawing a line over the land near the coast:

The resulting drainage area includes two larger rivers or “wadis,” as well as many smaller coastal drainages.

The second new feature allows you to view the MERIT-Basins layers on the map. There are separate layers for “river reaches” and “unit catchments.” These are the data layers that the app uses to construct watersheds when you choose “MERIT” as your data source. To activate these layers, just click on these new layers. They are overlays, which will display on top of your chosen basemap.

Finally, a small but fun new feature: you can now change the color of your rivers and watershed boundaries. You’ll find the color selectors near the bottom of the Options pane on the left. I’m not sure this is very useful, but you can create some interesting effects:

Please let me know what you think of these new features. Did you find any bugs? How could you use them?

Demo: Use the Global Watersheds API and Python to automatically delineate watersheds

It seems that a few people are discovering the mghydro watershed delineation API. Last Monday, the API handled requests for 9,679 watersheds over the course of a few hours. (Someone is very interested in the watersheds of France!)

One way to use the API is with GIS software, to fetch watershed boundaries and river centerlines from the web app and display them in your desktop GIS. Another use is to automate your requests, rather than using the online map interface. This could be useful if you want to delineate hundreds (or thousands!) of watersheds. However, remember that the results of automated delineation are very often wrong, so you should visually check each one.

Here is a demo in Python of how you could use the API to download watersheds for multiple outlet points. Click on the filename at the bottom to go to Github, where you can download the Jupyter notebook.

How to use Python to delineate watersheds in the continental US with USGS web services

I recently tried my hand at using NLDI, the new water data web service from the U.S. Geological Survey. The service provides access to water data from the National Hydrography Dataset (NHD), version 2. I was specifically interested in using the NHD geodata to delineate watersheds. This data was digitized from 1:100,000-scale maps. (There is newer, more detailed data, called NHDPlus HR, for high-resolution, but no web service for these data yet.)

Snake River watershed upstream of the Lower Granite Dam in eastern Washington state (just a location I picked at random for this demo!)

It took me a couple days of tinkering to get the results I wanted, but the results look impressive and seem accurate. You can run the code yourself by downloading one of these files from GitHub Gists. (Or follow along below.)