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重要的服务，如饮用水、渔业和娱乐。其中许多水体正在变暖，气温上升正在导致许多水质特征的变化。为了预测未来大陆范围的水质状况，关键是要估计全美湖泊的水温趋势，并了解温度如何影响这些生态系统的水质。一个关键的挑战是，很难预测水温上升的速度，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。这项研究将使用创新的建模工具来了解历史(1979-2016)并估计未来(到2105年)全美2400个湖泊的湖温和水质状况。这项研究的结果为预测和理解未来十年内陆水体的大陆尺度变化提供了机会。这项研究将解决内陆水体升温速率受跨尺度相互作用调节的假设，其中湖泊形状和水体透明度等局部特征调节湖泊温度对大尺度气象强迫的响应。这种跨尺度的相互作用可能会影响水质和湖泊碳循环发生宏观尺度变化的可能性和大小。这项工作将为美国毗邻的2400个湖泊在2105年产生当地规模的气象强迫估计，以应对多种气候情景。这些大气数据将与在基于水动力过程的湖泊模拟模型中每个地点测量的湖泊特定变量一起使用，以产生水温、层化和冰盖预测。然后，基于已知的温度依赖关系，估计的水温将被用于估计碳加工率的未来变化。总而言之，这些结果将被用来评估未来气候情景对湖泊和水库碳循环的影响，以及水生碳排放发生大规模变化的可能性。这项研究将通过新课程模块的开发支持一名博士后学者和更多本科生的培养，建模框架将自由分布，为了解和预测大陆尺度的内陆水体水质提供一种新的机制。

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.