Thu, Aug 18, 2022: 5:00 PM-6:30 PM
ESA Exhibit Hall
Background/Question/Methods: Mountain lakes serve as important headwaters and habitats while also contributing to the overall aesthetic value of mountain landscapes. However, mountain lakes have experienced intensified algal productivity due to rising temperatures and increased nitrogen and phosphorus deposition resulting in negative impacts on water quality, ecological function, aesthetics and human health. Due to the remote location of these lakes, monitoring algal productivity is difficult and infrequent. Remote sensing has been suggested to evaluate and monitor these lakes but unlike larger and lower elevation water bodies where this has been successful, mountain lakes are often small, occupy environments that prevent year-round open water observations, are frequently cloud-covered, and have relatively low productivity values. These barriers have prevented reliable and transferable remote sensing methods for monitoring mountain lake productivity. We evaluated the suitability of remotely sensed methods for monitoring mountain lakes by compiling in-situ data of chlorophyll a measurements from lakes across North America and Europe and comparing these to Sentinel-2 and Landsat images. Multiple bands and indices, levels of image preprocessing, and lake characterization were compared to in-situ chlorophyll a data that spanned from the 1980s to 2021 to identify the optimal approach for remote sensing of mountain lakes.
Results/Conclusions: Image availability and usability was less than 50% and image capture date to in-situ sample collection date matchups were approximately 10%, highlighting the challenge with monitoring these lakes. Relationships between in-situ and satellite-derived chlorophyll estimates were sensitive to multiple factors, and varied depending on lake morphometry (shallow versus deep lakes) and trophic function (e.g., oligotrophic, eutrophic). Using images process to surface reflectance provided more reliable correlations compared to images processed to top-of-atmosphere. The combined dataset of these highly valuable, geographically diverse in-situ mountain lake chlorophyll measurements allows for continued development of remote sensing techniques. The additional productivity observations across seasons and years supplied by the remote sensing show some surprising productivity spatiotemporal trends that are continuing to be investigated. This study provides one of the most comprehensive efforts to find consistent remote sensing derived indices to monitor mountain lake algal productivity.
Results/Conclusions: Image availability and usability was less than 50% and image capture date to in-situ sample collection date matchups were approximately 10%, highlighting the challenge with monitoring these lakes. Relationships between in-situ and satellite-derived chlorophyll estimates were sensitive to multiple factors, and varied depending on lake morphometry (shallow versus deep lakes) and trophic function (e.g., oligotrophic, eutrophic). Using images process to surface reflectance provided more reliable correlations compared to images processed to top-of-atmosphere. The combined dataset of these highly valuable, geographically diverse in-situ mountain lake chlorophyll measurements allows for continued development of remote sensing techniques. The additional productivity observations across seasons and years supplied by the remote sensing show some surprising productivity spatiotemporal trends that are continuing to be investigated. This study provides one of the most comprehensive efforts to find consistent remote sensing derived indices to monitor mountain lake algal productivity.