Water Resources Research Act Program

Details for Project ID 2019NY191B

Hyperspectral drone detection of harmful algal blooms: Ground truthing new approaches for water quality assessment

Institute: New York
Year Established: 2019 Start Date: 2019-03-31 End Date: 2020-02-28
Total Federal Funds: $20,000 Total Non-Federal Funds: $40,006

Principal Investigators: Dr. Timothy de Smet

Abstract: Harmful algal blooms (HAB)s are an increasing threat to freshwater quality, public health, and aquatic ecosystems, costing New York State millions of dollars in annual damages. Yet the frequency, magnitude, and duration of HABs is poorly documented for inland freshwater lakes and ponds. Current field-based sampling followed by laboratory analysis to detect and monitor HABs is expensive, labor intensive, and slow, delaying critical management decisions. The utility of satellite-based multispectral remote sensing to rapidly detect, monitor, and forecast HABs has been demonstrated at large oceanographic scales; however, low spatial and spectral resolution and inadequate revisit time severely limit the usefulness of satellite-based remote sensing techniques for inland freshwater ponds and lakes. We propose to conduct a pilot study aimed at assessing the utility of efficient low-cost unmanned autonomous vehicle systems and spectral sensors for the rapid real-time detection and monitoring of HABs on Chautauqua and Seneca Lakes. The research will result in the production of chlorophyll-a and cyanobacteria concentration maps, the development of a hyperspectral calibration methodology, and development of an algorithm for cyanobacteria detection, which will advance the state of hyperspectral best practices. This new state-of-the-art research methodology will allow for targeted assessment, monitoring, and design of HABs management plans that can be adapted for other impacted water bodies in New York State and implemented by managers at the NYSDEC, NYSDOH, and NYSDAM.