Drop a raindrop anywhere in the world and watch where it ends up

• river-runner

  71 375 7.9 Svelte

  Uses USGS/MERIT Basin data to visualize the path of a rain droplet to its endpoint.

Hey everyone, glad you all are enjoying the project!

To address some of the points I'm seeing, it's not perfect right now, which is why we've considered this a beta release. In particular, there are some issues around name coverage abroad and around engineered features (dams, canals, etc.). A lot of known issues are documented at the top of this page: https://ksonda.github.io/global-river-runner/. Ultimately, we made as much progress as we could, including a lot of manual name suggestions before launching, and decided to publish the tool in beta, with an understanding that we'd take suggestions and otherwise work to improve the tool/data over time.

To the points about the distance the paths are starting from a click, it does round coordinates to some extent. As much as I'd like to be more exact, we're stuck with a limited number of "flowlines" in our dataset and it will look for the closest one, which isn't always as close as we'd like. It's most useful for understanding watersheds in broad strokes, but often falls a little short when it comes to the novelty of literally tracing from your address.

For both specificity and some of the canal issues, the US-only version of this tool is better than this one (https://river-runner.samlearner.com/) with the obvious limitation that the paths are only within the US.

If you have any issues/feedback/suggestions regarding the UI and have a minute, would really appreciate if you're able to submit them as issues in the project repo on Github: https://github.com/sdl60660/river-runner If you're experiencing routing/naming issues, you can submit issues in this repo: https://github.com/ksonda/global-river-runner

Again, thanks for giving the project a look! You can check out some of my other work here: https://www.samlearner.com/ or on my Github (https://github.com/sdl60660).

I'd also like to shout out other other people who worked to make this happen: Dave Blodgett (https://github.com/dblodgett-usgs), Kyle Onda (https://github.com/ksonda), and Ben Webb (https://github.com/webb-ben).

• global-river-runner

  1 29 2.6 Python

  Let's make a global river runner

Hey everyone, glad you all are enjoying the project!

To address some of the points I'm seeing, it's not perfect right now, which is why we've considered this a beta release. In particular, there are some issues around name coverage abroad and around engineered features (dams, canals, etc.). A lot of known issues are documented at the top of this page: https://ksonda.github.io/global-river-runner/. Ultimately, we made as much progress as we could, including a lot of manual name suggestions before launching, and decided to publish the tool in beta, with an understanding that we'd take suggestions and otherwise work to improve the tool/data over time.

To the points about the distance the paths are starting from a click, it does round coordinates to some extent. As much as I'd like to be more exact, we're stuck with a limited number of "flowlines" in our dataset and it will look for the closest one, which isn't always as close as we'd like. It's most useful for understanding watersheds in broad strokes, but often falls a little short when it comes to the novelty of literally tracing from your address.

For both specificity and some of the canal issues, the US-only version of this tool is better than this one (https://river-runner.samlearner.com/) with the obvious limitation that the paths are only within the US.

If you have any issues/feedback/suggestions regarding the UI and have a minute, would really appreciate if you're able to submit them as issues in the project repo on Github: https://github.com/sdl60660/river-runner If you're experiencing routing/naming issues, you can submit issues in this repo: https://github.com/ksonda/global-river-runner

Again, thanks for giving the project a look! You can check out some of my other work here: https://www.samlearner.com/ or on my Github (https://github.com/sdl60660).

I'd also like to shout out other other people who worked to make this happen: Dave Blodgett (https://github.com/dblodgett-usgs), Kyle Onda (https://github.com/ksonda), and Ben Webb (https://github.com/webb-ben).

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