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

MSB-ECA：评估跨尺度相互作用对次大陆湖泊热趋势和碳循环的影响

基本信息

批准号：
1638704
负责人：
Kevin Rose
金额：
$ 29.97万
依托单位：
Rensselaer Polytechnic Institute
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-01-01 至 2019-12-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1638704&HistoricalAwards=false
关键词：
MSB ECA Assessing effects cross

项目摘要

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.

淡水湖泊和水库为社会提供重要的服务，例如饮用水、渔业和娱乐。许多水体正在变暖，气温上升导致许多水质特征发生变化。为了预测大陆范围内未来的水质状况，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至关重要。一个关键的挑战是很难预测水温变暖速率，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美国 2400 个湖泊的历史（1979-2016）并估计未来（到 2105 年）的湖泊温度和水质状况。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一个机会。这项研究将解决以下假设：内陆水体变暖速率受到跨尺度相互作用的调节，其中湖泊形状等局部特征水的透明度调节着湖泊温度对大规模气象强迫的反应。这种跨尺度的相互作用可能会调节水质和湖泊碳循环宏观尺度变化的可能性和幅度。这项工作将为美国本土 2400 个湖泊提供截至 2105 年局部尺度的气象强迫估计，以应对多种气候情景。这些大气数据将与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、分层和冰盖预测。然后，估计的水温将用于根据已知的温度依赖性来估计碳处理速率的未来变化。这些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流出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培养一名博士后学者和更多本科生，并且模型框架将免费分发，以提供一种新的机制来理解和预测大陆范围内陆水体的水质。

项目成果

期刊论文数量（15）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

A river runs through it

一条河从中流过

DOI：
10.1126/science.aam8047
发表时间：
2017-04
期刊：
Science
影响因子：
56.9
作者：
Rose; Kevin C.
通讯作者：
Kevin C.

Global lake response to the recent warming hiatus

全球湖泊对近期变暖中断的反应

DOI：
10.1088/1748-9326/aab9d7
发表时间：
2018-04-26
期刊：
Environmental Research Letters
影响因子：
6.7
作者：
L. Winslow;Taylor H. Leach;K. Rose
通讯作者：
K. Rose

Decoupled trophic responses to long‐term recovery from acidification and associated browning in lakes

湖泊酸化和相关褐变的长期恢复对营养反应的解耦

DOI：
10.1111/gcb.14580
发表时间：
2019-02-27
期刊：
Global Change Biology
影响因子：
11.6
作者：
Taylor H. Leach;L. Winslow;N. Hayes;K. Rose
通讯作者：
K. Rose

Characterizing hydrologic networks: Developing a tool to enable research of macroscale aquatic networks

表征水文网络：开发一种工具来研究宏观水生网络

DOI：
10.5281/zenodo.1169399
发表时间：
2018-04
期刊：
Environmental modelling & software
影响因子：
4.9
作者：
Luke A. Winslow; Tobi H.
通讯作者：
Tobi H.

Patterns and drivers of deep chlorophyll maxima structure in 100 lakes: The relative importance of light and thermal stratification: Patterns and drivers of DCM structure across lakes

100 个湖泊深层叶绿素最大值结构的模式和驱动因素：光和热分层的相对重要性：跨湖泊 DCM 结构的模式和驱动因素

DOI：
10.1002/lno.10656
发表时间：
2018-03
期刊：
Limnology and Oceanography
影响因子：
4.5
作者：
Leach, Taylor H.;Beisner, Beatrix E.;Carey, Cayelan C.;Pernica, Patricia;Rose, Kevin C.;Huot, Yannick;Brentrup, Jennifer A.;Domaizon, Isabelle;Grossart, Hans;Ibelings, Bastiaan W.;et al
通讯作者：
et al