- Role
- Finalist
- Region
- Manitoba Schools Science Symposium
- Pronouns
- he/him/his
Aadhi Chandrasekaran
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Project
A Novel Approach to Algal Bloom Prevention Using Daphnia magna and Predictive AI Models
Project #7118
Harmful algal blooms, exemplified by the states of emergency declared in Florida in 2016 and 2018, are frequently increasing. Urban expansion exacerbates this issue by increasing polluted runoff into watersheds. This study examined the potential toxicity of Red River water with simulated sediment runoff on Daphnia magna. Daphnia cultures were exposed to varying concentrations of Red River water with simulated sediment runoff, and their viability was monitored at 24, 48, 72, 96, and 120 hours. Integrating bioassays with AI and machine learning algorithms enhances predictive accuracy for water quality issues, enabling early prevention of harmful algal blooms in the Red River, a vital water source for Manitoba, and a key resource for agriculture, cultural practices, and tourism. Results demonstrated concentration-dependent fluctuations in Daphnia magna viability, indicating the presence of nutrients and harmful substances in Red River water. This study underscores the significant environmental impacts of urban runoff on aquatic ecosystems.
- Challenge
- Environment and Climate Change
- Category
- Junior
- Type
- Innovation