MRA: Continental scale controls on instream and catchment contributions to greenhouse gas fluxes from rivers

MRA：大陆范围内对河流内和流域温室气体通量贡献的控制

基本信息

批准号：
2106071
负责人：
Emily Bernhardt
金额：
$ 69.95万
依托单位：
Duke University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-08-01 至 2026-07-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2106071&HistoricalAwards=false
关键词：
MRA Continental scale controls instream

项目摘要

The primary goal of this project is to derive a robust and defensible estimate of the greenhouse gases emitted to the atmosphere from the rivers of the United States and to build predictions of how these gas emissions are likely to change in coming decades. The greenhouse gases emitted from rivers are both delivered from their surrounding watersheds and produced by river organisms. River and watershed characteristics such as river structure, groundwater exchange, algal production, respiration, temperature, and contributing land types can affect the rates at which rivers produce and release carbon dioxide and other greenhouse gases. However, scaling these known factors to continuous, widespread predictions of river greenhouse gas dynamics remains difficult because of limited sampling times and locations across this expansive suite of variables. This data limitation has now been overcome for river monitoring sites included in the National Ecological Observatory Network (NEON). Using data collected from 26 NEON river sites across the United States, researchers will build models of continuous gas emissions. We will take advantage of the wide variation in watershed and channel characteristics across sites to build statistical models that allow us to estimate riverine greenhouse gas fluxes across the entire continent, and to identify those sites where gas emissions are most likely to respond strongly to rising temperatures or altered hydrology. This project will also train early-career scientists, including underrepresented groups, in field ecology and the processing and interpretation of large data sets to make better predictions of global change.This proposal seeks to answer three questions: (1) How do greenhouse gas (GHG) fluxes vary across streams and rivers of the continental U.S.? (2) What channel and catchment properties are associated with the highest riverine releases of carbon dioxide, methane, and nitrous oxide from rivers? and (3) what channel characteristics are associated with the highest instream contribution (e.g., primary production and respiration) to riverine GHG emissions? Using the diverse portfolio of hydrologic, biogeochemical, and geomorphic data collected by the National Ecological Observatory Network (NEON) at its 26 wadeable stream locations, we will leverage level 0 data (including discrete estimates of GHG concentrations and solute chemistry in the channel and in groundwater along with continuous measures of hydrology, pH, conductivity, and dissolved oxygen from the channel) to build robust estimates of annual GHG emissions from all 26 sites. We will link these GHG fluxes with concurrent estimates of stream metabolism, rates of groundwater inflow, and groundwater-surface water GHG exchange, and use reaeration models to discriminate between instream and catchment derived GHG contributions to riverine GHG fluxes. We will refine and test our data-derived models with intensive field work at a subset of NEON sites and at a field site in North Carolina where we conduct detailed empirical research.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目的主要目标是对美国河流排放到大气中的温室气体进行可靠且可靠的估计，并预测这些气体排放在未来几十年可能如何变化。河流排放的温室气体既来自周围流域，又由河流生物产生。河流和流域特征，例如河流结构、地下水交换、藻类产生、呼吸、温度和贡献土地类型，可以影响河流产生和释放二氧化碳和其他温室气体的速率。然而，由于这套广泛的变量的采样时间和位置有限，将这些已知因素扩展到对河流温室气体动态的连续、广泛的预测仍然很困难。国家生态观测站网络（NEON）中的河流监测点现已克服了这一数据限制。研究人员将利用从美国 26 个 NEON 河流站点收集的数据建立连续气体排放模型。我们将利用不同地点的流域和河道特征的巨大差异来建立统计模型，使我们能够估计整个大陆的河流温室气体通量，并确定气体排放最有可能对气温上升做出强烈反应的地点或改变水文。该项目还将培训早期职业科学家，包括代表性不足的群体，进行实地生态学以及大数据集的处理和解释方面的培训，以便更好地预测全球变化。该提案旨在回答三个问题：（1）温室气体（美国大陆各溪流和河流的温室气体通量有所不同？ (2) 哪些河道和流域特性与河流中二氧化碳、甲烷和一氧化二氮的最高河流释放量相关？ (3) 哪些河道特征与河流内对河流温室气体排放的最高贡献（例如初级生产和呼吸）相关？利用国家生态观测站网络 (NEON) 在其 26 个涉水溪流位置收集的水文、生物地球化学和地貌数据的多样化组合，我们将利用 0 级数据（包括对河道和河流中的温室气体浓度和溶质化学的离散估计）地下水以及对水文、pH、电导率和渠道溶解氧的连续测量），以对所有 26 个地点的年度温室气体排放量进行可靠的估计。我们将把这些温室气体通量与河流代谢、地下水流入速率和地下水-地表水温室气体交换的同步估计联系起来，并使用再曝气模型来区分河流内和流域内的温室气体对河流温室气体通量的贡献。我们将在 NEON 站点的子集和北卡罗来纳州的一个现场进行详细的实证研究，通过深入的现场工作来完善和测试我们的数据衍生模型。该奖项反映了 NSF 的法定使命，并通过评估被认为值得支持利用基金会的智力优势和更广泛的影响审查标准。