Jun 14, 2023

A Machine Learning Approach to Freshwater Analysis Details Share This From protecting biodiversity to ensuring the safety of drinking water, the biochemical makeup of rivers and streams around the United States is critical for human and environmental welfare. From protecting biodiversity to ensuring the safety of drinking water, the biochemical makeup of rivers and streams around the United States is critical for human and environmental welfare. Studies have found that human activity and urbanization are driving salinization (increased salt content) of freshwater sources across the country. In excess, salinity can make water undrinkable, increase the cost of treating water, and harm freshwater fish and wildlife. Along with the rise in salinity has also been an increase in alkalinity over time, and past research suggests that salinization may enhance alkalinization. But unlike excess salinity, alkalinization can have a positive impact on the environment due to its ability to neutralize water acidity and absorb carbon dioxide in the Earth’s atmosphere – a key component to combating climate change. Therefore, understanding the processes at play which are affecting salinity and alkalinity have important environmental and health implications. A team of researchers from Syracuse University and Texas A&M University have applied a machine learning model to explore where and to what extent human activities are contributing to the hydrogeochemical changes, such as increases in salinity and alkalinity in U.S. rivers. Syracuse University researchers co-authored a study exploring the extent to which human activities are contributing to hydrogeochemical changes in U.S. rivers. The image above is Mills River in Pisgah National Forest, North Carolina. (Photo Credit: Syracuse University)