Multidecadal Remote Sensing of Inland Water Dynamics

Abstract

Remote sensing approaches to measuring inland water dynamics date back more than 50 years. These approaches rely on the unique spectral properties of different waterbodies to delineate surface extents and estimate optically active water quality parameters. Until recently, inland water remote sensing focused largely on localized study domains due to limitations in modelling methods, computing power, and data access. Recent advances in these areas have created novel opportunities for data-driven-multidecadal remote sensing of inland waters at the landscape scale. Here, I highlight the history of inland water remote sensing along with the dominant methodologies, water quality constituents, and limitations involved. I then use this background to contextualize three macroscale inland water remote sensing studies of increasing complexity. The first combines field measurements with remotely sensed surface water extents to identify the impacts of small-scale gold mining in Peru. Our results suggest that mining is leading to synergistic increases in lake area and mercury loading that are significantly heightening exposure risk for people and wildlife. I move from measuring lake extents in Peru to measuring lake color in over 26,000 lakes across the United States. This analysis shows that lake color seasonality can be generalized into five distinct phenology groups that follow well-known patterns of algae growth and succession. The stability of a given lake (i.e. the likelihood it will move from one phenology group to another) is tied to lake and landscape level characteristics including climate and population density. Finally, I move from simple parameters such as quantity and color to estimating multidecadal changes in water clarity in U.S. lakes. I show that lake water clarity in the U.S. has increased by an average of 0.52 cm yr-1 since 1984, largely as a result of extensive U.S. freshwater pollution abatement measures. In combination, these three studies highlight that data intensive remote sensing approaches are expanding the capabilities of inland water remote sensing from local to global scales, and that macroscale remote sensing of inland waters reveals trends and processes that are unobservable using field data alone.Doctor of Philosoph