Data Science For Water In California

Open Data Water

I was at the Open Water for California conference in Sacramento last week - a conference dedicated to data science for water, with a focus on California. The conference itself was well attended with people from many different sectors - academia, government, non-profits and community members. What was particularly interesting is that it had an entire track devoted to hackathons and building new tools to solve some of the pressing problems being faced in water today - as well as the more traditional sessions with talks on the latest research and tools for the water sector.

 

The hackathon were focused on issues related to understanding trash movement into water sources (especially plastic), building consumer confidence reports on water safety and tools to better understand drinking water sources. There was a lot of interest in water safety understandably, with Flint still fresh in our minds and the recent focus on water quality issues in California communities affected by the wildfires last year.

 

The traditional oral presentation sessions had researchers from academia, industry and government presenting their work. There was a lot of focus on using remote sensing data for water applications, with satellite data being the most popular data source since it’s the most widely available at this point. Some of the highlights included using satellite data to track plastic pollution from the San Francisco Bay, developing new tools to monitor mercury from space and developing the Open ET initiative to measure evapotranspiration from plants and hence water availability using drone imagery and satellite data. As has been the case for the last couple of years, water availability and tracking water use (both groundwater and surface water) were the areas that saw the most interest. However, there’s been a steady uptick in both researchers and startups looking at water quality data and ways to improve water quality using remote sensing data, robotics and machine learning. 

 

It’s interesting to see how data science is getting to be more of a focus in the different clean tech sectors with players from academia to industry and startups entering the conversation. We started with energy, then agriculture and now water is emerging as the latest clean tech sector where data science, machine learning and robotics are becoming essential tools in understanding and solving problems in the sector.


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