Effect of Time Window on Satellite and Ground-Based Data for Estimating Chlorophyll-a in Reservoirs

Abstract

Algal blooms in freshwater ecosystems can negatively impact aquatic and human health. Satellite remote sensing of chlorophyll a (Chl-a) is often used to help determine the severity of algal blooms. However, satellite revisit flyover schedules may not match the erratic nature of algal blooms. Studies have paired satellite and ground-based data that were not collected on the same day, assuming Chl-a concentrations did not change significantly by the flyover date. We determined the effects of an increasing time window between satellite overpass dates and field-based collection of Chl-a on algorithms for Landsat 5, Landsat 8, and Sentinel-2, using 14 years (2006–2020) of Chl-a data from 10 Oklahoma reservoirs. Multiple regression models were built, and selected statistics were used to rank the time windows. The Sentinel-2 results showed strong relationships between Chl-a and satellite data collected up to a ±5-day window. The strength of these relationships decreased beyond a ±3-day time window for Landsat 8 and a ±1-day time window for Landsat 5. Our results suggest that the time window between field sampling and satellite overpass can impact the use of satellite data for Chl-a monitoring in reservoirs. Furthermore, longer time windows can be used with higher resolution (spatial, spectral) satellites.