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

淡水湖泊和水库为社会提供重要的服务，如饮用水，渔业和娱乐。这些水体中有许多正在变暖，气温上升导致许多水质特征发生变化。为了预测未来的水质状况在大陆尺度上，它是至关重要的，以估计在整个美国的湖泊水温趋势，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，很难预测水温变暖率，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）和估计未来（通过2105）湖泊温度和水质条件在2400湖泊位于整个美国。这项研究的结果代表了一个机会，预测和了解内陆水体在未来几十年的大陆尺度的变化，这项研究将解决的假设，即内陆水体变暖率是由跨尺度的相互作用，如湖泊的形状和水的清晰度调节湖泊温度如何响应大尺度的气象强迫。这种跨尺度的相互作用可能介导的可能性和规模的水质和湖泊碳循环的宏观变化。这项工作将产生到2105年的气象强迫估计，在当地规模的2400个湖泊在整个美国接壤，并在应对多种气候情景。这些大气数据将与在每个站点测量的湖泊特定变量一起用于基于水动力过程的湖泊模拟模型，以产生水温、分层和冰盖预测。然后，估计的水温将用于基于已知的温度依赖性来估计碳处理速率的未来变化。总之，研究结果将用于评估未来气候情景对湖泊和水库碳循环的影响，以及水生碳排放发生大规模变化的可能性。这项研究将通过新的课程模块开发支持一名博士后学者和更多的本科生的培训，建模框架将免费分发，以提供一种新的机制来理解和预测内陆水体的水质。

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.