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

淡水湖和水库为社会提供了重要的服务，如饮用水、渔业和娱乐。这些水体中的许多都在变暖，气温上升导致许多水质特征发生变化。为了在大陆尺度上预测未来的水质状况，估计美国各地湖泊的水温趋势并了解温度如何影响这些生态系统的水质是至关重要的。一个关键的挑战是，很难预测水温变暖的速度，因为大气和水质特征相互作用，影响这些水体对气温上升的反应。本研究将使用创新的建模工具来了解美国各地2400个湖泊的历史（1979-2016）和估计未来（到2105）湖泊的温度和水质条件。这项研究的结果为预测和了解未来几十年内陆水体的大陆尺度变化提供了机会。本研究将解决内陆水体变暖速率受跨尺度相互作用调节的假设，其中湖泊形状和水的清晰度等局部特征调节湖泊温度如何响应大尺度气象强迫。这种跨尺度的相互作用可能调节了水质和湖泊碳循环宏观尺度变化的可能性和幅度。这项工作将根据多种气候情景，在美国邻近地区2400个湖泊的局地尺度上对到2105年的气象强迫作出估计。在基于水动力过程的湖泊模拟模型中，这些大气数据将与在每个站点测量的湖泊特定变量一起使用，以产生水温、分层和冰盖预测。根据已知的温度依赖性，估计的水温将用于估计未来碳处理速率的变化。这些结果将被用于评估未来气候情景对湖泊和水库碳循环的影响，以及水生碳外排发生大规模变化的可能性。本研究将通过开发新的课程模块，为培养一名博士后和更多本科生提供支持，并将模型框架免费发布，为大陆尺度上内陆水体水质的理解和预测提供一种新的机制。

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.