It’s possible that I shall make an ass of myself. But in that case one can always get out of it with a little dialectic. I have, of course, so worded my proposition as to be right either way (K.Marx, Letter to F.Engels on the Indian Mutiny)
Wednesday, November 13, 2024
Extreme weather accelerates nitrate pollution in groundwater
Heavy rains can cause contamination in just 10 days
University of California - Davis
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UC Davis researchers insert a device that continuously collects water samples underground, providing real-time data on nitrate contaminant movement.
Extreme weather spurred by climate change, including droughts and heavy rains, may increase the risk of nitrates from fertilizers ending up in groundwater, according to a recent study from researchers at the University of California, Davis. The study found heavy rains after a drought caused nitrates to seep 33 feet under farm fields in as little as 10 days. The study was published in Water Resources Research.
“The conventional wisdom was that it could take several weeks to years for nitrates to move from the crop root zones to reach groundwater,” said corresponding author Isaya Kisekka, a professor in the Departments of Land, Air and Water Resources and Biological and Agricultural Engineering. “We found these extreme events, such as California’s atmospheric rivers, are going to move nitrate more quickly.”
In this study, different methods were used to measure how much nitrate, a component of nitrogen fertilizer, was seeping down through the soil in a tomato and cucumber crop near Esparto, California. Scientists conducted their research from 2021 until 2023 when California was experiencing periods of drought followed by atmospheric rivers. They measured nitrate during both the growing seasons and the rainy seasons.
Drought can leave more nitrogen in soil
Previous studies have shown about 40% of nitrogen fertilizer used for vegetables isn’t absorbed by the plants but remains in the soil. During droughts, crops don’t use nitrogen efficiently, leading to excess nitrogen in the soil. This study found that if a drought is then followed by heavy rainfall, that sudden burst of water causes nitrate to seep in groundwater more quickly. The nitrate concentration in the shallow groundwater exceeded the U.S. Environmental Protection Agency maximum contaminant level of 10 milligrams per liter for drinking water.
“In California, we often say we swing between droughts and floods,” said Kisekka. “These extreme events that come with climate change are going to make the risk of these chemicals ending up in our drinking water much more severe.”
Groundwater is the primary source of drinking water for most of California’s Central Valley. In some regions, such as the Tulare Lake Basin, nearly one-third of drinking and irrigation wells exceed the EPA’s safe nitrate level. High nitrate levels in drinking water can increase health risks, especially for young children. It may also increase the risk of colorectal cancer.
Need for real-time soil nitrate monitoring
Central Valley farmers are required to report to the Regional Water Board how much nitrogen they applied to their field and how much was removed as part of the crop’s yield. The study compared different ways of monitoring when nitrate from fertilizers seep into groundwater. Kisekka said the results highlight the need for affordable, real-time soil nitrate monitoring tools to help farmers manage fertilizer use efficiently.
By using conservation practices that limit leftover nitrates in the crop’s root zone after harvest, farmers can help reduce nitrate contamination in groundwater.
This study's data will also help improve a model called SWAT, which is used to track nitrate seepage into groundwater across California's Central Valley. This effort is part of the Central Valley Water Board’s program to regulate irrigated farmlands.
Other UC Davis authors include Iael Raij Hoffman, Thomas Harter and Helen Dahlke.
The study was supported by the USDA Natural Resource Conservation Service through its Conservation Effects Assessment Project. The national project is designed to assess the effectiveness of conservation practices across different watersheds. The study also had support from the USDA National Institute of Food and Agriculture.
Assessing Nitrate Leaching During Drought and Extreme Precipitation: Exploring Deep Vadose‐Zone Monitoring, Groundwater Observations, and Field Mass Balance
Lehigh partners with North Carolina A&T to enhance flood damage mapping with AI and advanced radar
Universities to collaborate in National Science Foundation-funded effort to transform flood damage assessments through the agency’s “HBCU Excellence in Research” program
Lehigh University
One only needs to glance at the news, social media, or even just out the window to understand the devastation caused by flooding. Recent back-to-back major hurricanes have brought catastrophic rainfall that has devastated communities across the southeastern United States.
With climate change, experts predict these extreme weather events will increasingly become the norm. Among the many ways that researchers are devising strategies to protect and assist vulnerable areas, one such effort involves increasing the speed and accuracy of damage assessments.
“Research shows that if you can save a single day in the initial response phase, it could save thousands of days in the recovery phase because the effect is logarithmic,” says Lehigh University researcher Maryam Rahnemoonfar, an associate professor of computer science and engineering with a joint appointment in the Department of Civil and Environmental Engineering.
This collaboration between Lehigh and NCAT grew out of efforts within Lehigh's Interdisciplinary Research Institutes (IRIs) to foster cross-institutional partnerships that address critical challenges.
A ‘more comprehensive picture’ of disaster zones
Current post-disaster damage assessments typically rely on data from time-consuming manual methods, like ground-based gauges, and remote sensing technologies, such as satellite imagery. Although useful, such tools are localized and provide only a fragmented view of affected areas. They also lack multi-resolution data.
“Optical imagery doesn’t allow you to see below the surface, so you can miss critical information about what’s under the water, like roads and bridges,” says Rahnemoonfar. “But with radar sensors, you can detect submerged objects and get a more comprehensive picture.”
The team will combine multi-modal data sources—including satellite, UAV (unmanned aerial vehicle), and various remote-sensing technologies, such as optical, SAR (Synthetic Aperture Radar), and LiDAR (Light Detection and Ranging)—into a novel framework that automatically extracts spatial and temporal features from these data streams. And they’ll combine all of that with an innovative vision language model that the Lehigh team led by Rahnemoonfar will create.
“Vision language models will be built into a flying or ground-based robot that a response team can communicate with,” she says. “First responders might ask questions like, ‘What roads are flooded?’ or ‘Which neighborhoods are under water?’ and based on the robot’s answer, the team could more efficiently allocate their resources. We’re combining the language and visual domains.”
Rahnmoonfar has developed such models in the past for RGB sensors, but the algorithms that powered them are fully supervised, meaning they require a huge amount of labeled training data in order to identify and learn patterns. Her team will develop a self-supervised algorithm that requires far less data and will use information from their multi-modal data sources and from previous floods.
“Ultimately, we want to develop a system that can assist the rapid response and recovery required after weather disasters,” she says.
Lehigh’s IRIs: Seeding collaborations
The partnership between Lehigh and NCAT was initially facilitated by a seed grant from the Institute for Data, Intelligent Systems, and Computation (I-DISC), one of Lehigh’s three Interdisciplinary Research Institutes (IRIs)
“The goal of all Lehigh’s IRIs is to bring faculty from different areas of expertise and different backgrounds together to address major societal problems,” says Himanshu Jain, T.L. Diamond Distinguished Chair in Engineering and Applied Science and a professor of materials science and engineering. Jain recently stepped down as inaugural director of Lehigh’s Institute for Functional Materials and Devices (I-FMD), a role he held since 2018.
In his capacity as a faculty member, Jain has worked with HBCUs for the past 20 years—including a teaching stint at Tuskegee University—and through his work with I-FMD, he connected with Lehigh alum Jagannathan Sankar '83 PhD, a distinguished professor in NCAT’s Department of Mechanical Engineering.
“NCAT’s researchers are highly regarded,” says Jain, “and through our connection with Professor Sankar, we started developing ideas around how we could bring our faculty together.”
The discussions eventually led to Jain organizing “seed interactions”—virtual meetings where faculty from both institutions could brainstorm possible collaborations. Jain also established seed funding within Lehigh’s IRIs to help potential ideas get off the ground.
As a participant in these meetings, Rahnemoonfar met a colleague at NCAT, Leila Hashemi Beni, an associate professor in the Department of Built Environment, whose research area and interests complemented her own. With the seed funding, Rahnemoonfar and Beni were able to refine the idea that eventually led to the funded NSF award.
“What we wanted to demonstrate with these seed interactions is that they’re effective and lead to fruitful collaboration,” says Jain. “It’s the beginning of what we want to establish as a track record of our institutions successfully working together. What we ultimately want from the IRIs is for them to help incubate focused research centers devoted to addressing big, consequential societal issues. With NCAT, we are not only technically interested in each other’s expertise, but we have a scientific synergy that can have a significant impact on some of the world’s biggest problems.”
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