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Multispectral Autonomous Sensing for High-Resolution Mapping of Coupled Aquatic Stressors: Microplastics and Algal Bloom

CSEF · 2026 Earth & Environmental Sciences(Senior Division)

Dhruv Yadati

Overview

Harmful algal blooms cause over $1 billion in damages annually, and microplastics compound this threat by transporting toxins, fostering algal biofilms, and accelerating cyanobacteria growth. However, no instrument can detect both stressors in situ, leaving their co-occurrence poorly understood. This work presents the first field-validated autonomous platform for simultaneous in situ detection and spatial mapping of algal growth and microplastic contamination from the same water parcel. A custom-built multispectral sensor exploits chlorophyll-a absorption (blue/red) and microplastic Mie scattering (near-infrared) to compute two novel indices: an Algal Growth Index (AGI) and Microplastic Index (MPI). Integrated into an autonomous surface vehicle, the system collected over 10,000 georeferenced measurements across Bay Area water bodies. Nighttime sensing revealed a critical limitation in conventional monitoring: daytime measurements collapsed 88% of readings to the detection floor, while nighttime operation increased signal variability from 11% to 43% and revealed nearly 6x higher co-occurrence detection (23% vs 4%). Calibration confirmed accurate, independent detection across algae, microplastic, and sediment conditions. Observed co-occurrence significantly exceeded chance expectations (p<0.001), reaching 33% in highly contaminated zones. Independent Random Forest models trained on large-scale NASA (n=23,570) and NOAA (n=16,713) datasets corroborated elevated contamination at the survey site. To address spatial autocorrelation bias in directional surveys, a novel PCA-aligned elliptical holdout method was developed, achieving >90% hotspot prediction accuracy and outperforming conventional circular holdout (R² = 0.93 vs 0.81). This work demonstrates a low-cost framework for integrated, high-resolution monitoring of coupled aquatic stressors.

Competition history

  • CSEF 2026 Earth & Environmental Sciences(Senior Division) · Entry S-08-13

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