From protecting biodiversity to ensuring the safety of drinking water, the biochemical composition of rivers across the United States is critical to human and environmental well-being. Studies have found that human activity and urbanization are causing salinization (increase in salinity) of freshwater sources across the country. Excess salt can make water undrinkable, increase water treatment costs, and harm freshwater fish and wildlife.
As salinity increases, so does alkalinity over time, and previous studies have suggested that salt addition may promote alkalinization. But unlike excess salinity, alkalinization is positive for the environment because of its ability to neutralize the acidity of water and absorb carbon dioxide from the earth’s atmosphere, a key factor in combating climate change. can affect. Understanding the ongoing processes that influence salinity and alkalinity therefore has important implications for the environment and health.
A team of researchers from Syracuse University and Texas A&M University applied machine learning models to determine where and how much human activity contributes to hydrogeochemical changes, such as increasing salinity and alkalinity in U.S. rivers. I investigated whether
Using data from 226 river monitoring sites across the United States, the group built two machine learning models to predict monthly salinity and alkalinity levels at each site. These sites were chosen because they have documented long-term continuous water quality measurements for at least 30 years. The model explored a range of watersheds, from urban to rural. A watershed is an area where all flowing surface water converges at one point, such as a river or lake. We evaluated 32 watershed factors ranging from hydrology, climate, geology, soil chemistry, land use and land cover to pinpoint the factors contributing to increased salinity and alkalinity. The researchers’ model determined that human activity was the primary contributor to the salinity of U.S. rivers, but the increase in alkalinity was attributed primarily to natural phenomena rather than human activity.
The team includes researchers from Syracuse University, Tao Wen, assistant professor in the School of Humanities and Sciences, Department of Earth and Environmental Sciences (EES), Beibei E, an EES graduate student, and Charles T. Driscoll, professor at the University of Environmental Systems. was Shuang Zhang, Distinguished Professor in the School of Engineering and Computer Science and Assistant Professor at Texas A&M, recently published his findings in General Environmental Science.
What causes salinization and alkalinization?
Results from the group’s sodium prediction model were consistent with previous studies, detecting that human activities, such as road salt application, contribute significantly to the salinity of U.S. rivers. The model specifically reveals population density and the proportion of impervious surfaces (artificial surfaces such as roads) as her two most important factors in increasing salinity in U.S. rivers.
According to Wen, the accuracy of the salinity model was an important proof-of-concept for the research team.
“Regarding the causes of river salinity, the results of our machine learning model were consistent with those of previous studies that focused on field observations, laboratory work and statistical analysis,” Wen said. “This proved our approach worked.”
The team turned to alkalinity because the salinity results confirmed the accuracy of the team’s model. Their model identified that natural processes are the main contributors to variations in river alkalinity, in contrast to previous studies that identified human activity as the main cause of alkalinization. (Kaushal et al., 2018). They found that local climatic and hydrogeological conditions, such as runoff, sediment, soil pH, and moisture, were the features that most influenced river alkalinity.
important for the carbon cycle
Their findings have important implications for the environment and climate, as river alkalinity forms an important relationship in the carbon cycle. Consider the movement of carbon during a storm. When it rains, carbon dioxide in the atmosphere combines with water to form carbonic acid. When carbonic acid reaches the ground and contacts certain rocks, it triggers a chemical reaction that extracts gaseous carbon dioxide from the atmosphere and transports it to the ocean via inland water systems such as lakes and rivers. This natural process, known as rock weathering, continuously erodes rock over millions of years, sequestering her CO2 in the atmosphere. It is also a major regulated substance for greenhouse gases that cause global warming.
“Rock weathering is a major source of alkalinity in natural waters and one of the main ways to lower carbon dioxide in the air,” says Weng. Think of this as his feedback loop. Too much carbon dioxide in the atmosphere increases temperatures and accelerates the weathering of rocks. The accelerated weathering of rocks and the dissolution of more rocks in the basin increases alkalinity and reduces carbon dioxide.
“Alkalinity is a key component of the carbon cycle,” Wen says. “We found that natural processes are the main drivers of alkalinization, but these natural factors can still be modified by humans. “Because of the variability in water levels, addressing the alkalinization of U.S. rivers will require more investment in restoring the natural conditions of watersheds and tackling global warming and climate change.”
The team’s findings may inform future research into enhancing the weathering of rocks, which breaks them up and spreads them across fields. Dispersing rock dust over a large area increases the amount of contact between rain and rocks, promoting carbon removal from the atmosphere. Wen said the team’s model helps answer questions about the evolution of natural conditions in different regions, and is a critical step needed to more effectively implement enhanced rock weathering. rice field.
This research was funded by a $460,000 National Science Foundation grant awarded to Wen.
Quote:
E. Beibei, S. Zhang, CT Driscoll, Wen, T., Human and natural influences on freshwater salinization and alkalinization in the United States: a machine learning approach. Science of Integrated Environment (2023), https://doi.org/10.1016/j.scitotenv.2023.164138
