Nutrient dynamics along a river continuum: combining sensor data, experiments, and time series analyses to identify local to watershed scale drivers of nutrient cycling

沿河流连续体的养分动态：结合传感器数据、实验和时间序列分析来识别养分循环的局部到流域规模的驱动因素

基本信息

批准号：
1707042
负责人：
Ricardo Gonzalez-Pinzon
金额：
$ 32.97万
依托单位：
University of New Mexico
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：
2017-08-15 至 2021-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1707042&HistoricalAwards=false
关键词：
Nutrient dynamics along river continuum

项目摘要

PI Name: Ricardo Gonzalez-PinzonProposal Number: 1707042The objective of this project is to develop a spatially and temporally holistic, watershed-level understanding of nutrient dynamics in arid land river networks. Excess nutrient loading is one of the most common and disruptive disturbances to river ecosystems, and the negative impacts extend to downstream lakes, aquifers and coastal waters that are highly susceptible to nutrient loading. Results from this project will provide methods to assess the transport and fate of carbon and nutrients in river networks, promote a more complete understanding of the complex connections between water resources, food production, and nutrient cycles, and provide information about ways to reduce pollution and increase nutrient recycling.The PIs will leverage existing state-of-the-art sensor technology to continuously monitor water quality parameters, nitrate, phosphate, and dissolved organic carbon for two years along a river continuum that spans four orders of magnitude in mean annual discharge, ~2000 m in altitude, and ~500 km of stream length. Every three weeks during this period a recently developed, high-information-yield field experiment will be conducted at each study site to quantify nutrient uptake parameters at the hourly time scale. A time-series analysis toolbox will then be used to combine the continuous water quality data with the hourly experimental data to quantify how stream metabolism and nutrient uptake dynamics vary along the river continuum at a variety of time scales and to identify the most important factors in creating this variability. This project will advance the current understanding of nutrient dynamics in streams due to the use of: 1) multi-year, all season monitoring, which will expand the traditional trend of collecting data for short time periods, 2) simultaneous monitoring of numerous stream orders, 3) multi-parameter data collection, which will provide necessary context to more fully understand nutrient dynamics considering transport and stoichiometric constraints, and 4) state-of-the-art time-series analyses that enable the construction of parsimonious models capable of representing temporal (multi-season) and spatial (entire continuum) nutrient uptake and transport processes.

PI名称：Ricardo Gonzalez-PinzonPropoposal编号：1707042该项目的目的是在空间和时间上开发对干旱地Land River Networks中营养动态的分水岭级别的了解。过量的营养负荷是对河流生态系统的最常见和破坏性干扰之一，负面影响延伸至下游湖泊，含水层和沿海水域，这些湖泊非常容易受到营养负荷的影响。 Results from this project will provide methods to assess the transport and fate of carbon and nutrients in river networks, promote a more complete understanding of the complex connections between water resources, food production, and nutrient cycles, and provide information about ways to reduce pollution and increase nutrient recycling.The PIs will leverage existing state-of-the-art sensor technology to continuously monitor water quality parameters, nitrate, phosphate, and dissolved organic carbon for two years along一条河连续体在平均年度排放中跨越四个数量级，高度约为2000 m，溪流长度约为500 km。在此期间，每三个星期都会在每个研究地点进行一个最近开发的高信息收益现场实验，以量化营养摄取参数，以小时的时间尺度进行量化。然后，将使用时间序分析工具箱将连续的水质数据与每小时的实验数据相结合，以量化流媒体代谢和营养吸收动力学在河流连续体中如何在各种时间尺度上变化，并确定创建这种变异性的最重要因素。由于使用：1）多年，所有季节监控，该项目将提高对流中营养动态的最新理解，这将扩大在短时间内收集数据的传统趋势，2）同时监视许多流订单，3）3）多参数数据收集，这将提供必要的上下文，以便更多地理解营养的动态。启用能够代表时间（多季节）和空间（整个连续性）营养摄取和运输过程的模型模型的构建。

项目成果

期刊论文数量（7）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Spatiotemporal Variability in Transport and Reactive Processes Across a First‐ to Fifth‐Order Fluvial Network

一阶到五阶河流网络中输运和反应过程的时空变化

DOI：
10.1029/2019wr026303
发表时间：
2020
期刊：
Water Resources Research
影响因子：
5.4
作者：
Gootman, Kaylyn S.;González‐Pinzón, Ricardo;Knapp, Julia L. A.;Garayburu‐Caruso, Vanessa;Cable, Jaye E.
通讯作者：
Cable, Jaye E.

Water quality impacts of urban and non-urban arid-land runoff on the Rio Grande

DOI：
10.1016/j.scitotenv.2020.138443
发表时间：
2020-08-10
期刊：
SCIENCE OF THE TOTAL ENVIRONMENT
影响因子：
9.8
作者：
Regier, Peter J.;Gonzalez-Pinzon, Ricardo;Khandewal, Aashish
通讯作者：
Khandewal, Aashish

Linking Hydrobiogeochemical Processes and Management Techniques to Close Nutrient Loops in an Arid River

将水生地球化学过程与管理技术联系起来，以闭合干旱河流的养分循环

DOI：
10.3389/frwa.2020.00022
发表时间：
2020
期刊：
Frontiers in Water
影响因子：
2.9
作者：
Bicknell, Kelsey;Regier, Peter;Van Horn, David J.;Feeser, Kelli L.;González-Pinzón, Ricardo
通讯作者：
González-Pinzón, Ricardo

The understudied winter: Evidence of how precipitation differences affect stream metabolism in a headwater

研究不足的冬季：降水差异如何影响源头河流代谢的证据

DOI：
10.3389/frwa.2022.1003159
发表时间：
2022
期刊：
Frontiers in Water
影响因子：
2.9
作者：
Nichols, Justin;Khandelwal, Aashish Sanjay;Regier, Peter;Summers, Betsy;Van Horn, David J.;González-Pinzón, Ricardo
通讯作者：
González-Pinzón, Ricardo

Introducing the Self‐Cleaning FiLtrAtion for Water quaLity SenSors ( SC‐FLAWLeSS ) system

水质传感器自清洁过滤 (SC-FLAWLeSS) 系统简介

DOI：
10.1002/lom3.10377
发表时间：
2020
期刊：
Limnology and Oceanography: Methods
影响因子：
0
作者：
Khandelwal, Aashish;González‐Pinzón, Ricardo;Regier, Peter;Nichols, Justin;Van Horn, David J.
通讯作者：
Van Horn, David J.