MSB-ECA: Assessing the effects of cross-scale scale interactions mediating sub-continental lake thermal trends and carbon cycling

Rensselaer Polytechnic Institute, Troy NY

Investigators

Abstract

Freshwater lakes and reservoirs provide important services to society, such as drinking water, fisheries, and recreation. Many of these waterbodies are warming, and rising temperatures are causing changes in many water quality characteristics. In order to predict future water quality conditions at the continental-scale, it is critical to estimate water temperature trends in lakes throughout the United States and understand how temperature affects the water quality of these ecosystems. A key challenge is that it is difficult to predict water temperature warming rates because both atmospheric and water quality characteristics interact to influence how these waterbodies respond to rising air temperatures. This research will use innovative modeling tools to understand historic (1979-2016) and estimate future (through 2105) lake temperatures and water quality conditions in 2400 lakes located throughout the United States. The results of this research represent an opportunity to predict and understand continental-scale changes in inland waterbodies in coming decades. This research will address the hypothesis that Inland water body warming rates are regulated by cross-scale interactions, where local features such as lake shape and water clarity regulate how lake temperatures respond to large-scale meteorological forcing. This cross-scale interaction may mediate the likelihood and magnitude of macroscale changes in water quality and lake carbon cycling. This work will generate meteorological forcing estimates through the year 2105 at a local scale for 2400 lakes throughout the contiguous United States and in response to multiple climate scenarios. This atmospheric data will be used with lake specific variables measured at each site in a hydrodynamic process-based lake simulation model to produce water temperatures, stratification, and ice cover predictions. The estimated water temperatures will then be used to estimate future changes in carbon processing rates based on known temperature dependencies. Together, the results will be used to assess the implications of future climate scenarios on lake and reservoir carbon cycling and the likelihood of large-scale changes in aquatic carbon efflux. This research will support the training of one postdoctoral scholar and many more undergraduate students through new course module development, and the modeling framework will be distributed freely to provide a novel mechanism to understand and predict water quality in inland water bodies at a continental scale.