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CREST-PRF: Constraining Spatiotemporal Nutrient Dynamics Along An Arid-Land River Continuum

CREST-PRF: Constraining Spatiotemporal Nutrient Dynamics Along An Arid-Land River Continuum
CREST-PRF:约束干旱地区河流连续体的时空养分动态
批准号:
1720912
负责人:
Peter Regier
金额:
$20.0万
依托单位:
依托单位国家:
美国
项目类别:
Fellowship Award
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-10-01 至 2019-09-30

项目摘要

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中文摘要
翻译
CREST项目中的科学和技术卓越研究中心-博士后研究奖学金(CREST-PRF)轨道为CREST中心具有巨大潜力的初学者提供支持,并为他们提供培训和研究经验,这些培训和研究经验将拓宽视野,促进跨学科互动,并使他们在科学界处于领导地位。该CREST-PRF项目与新墨西哥大学CREST水与环境中心(CWE)的研究重点一致。该项目的目标是确定在多个空间(河流)和时间(数小时至数年)尺度上,在干旱-陆地河网中,溶解有机碳组成的纵向变化如何控制养分吸收、动态和输出。干旱土地养活了大约三分之一的世界人口和一半的农业。由于多种相互竞争的压力因素(如水坝、持续降水、火山灰输入和蒸散增加)以及对水资源的过度依赖,干旱-陆地河流系统的抗逆性通常较差,更容易受到水质退化的影响,包括富营养化。该项目的结果将为评估干旱河流系统中碳和营养物质的去向和运输提供工具,并提供科学知识,以支持多部门解决方案的开发,旨在改善干旱大都市地区的营养物质循环,在食物、水和能源的背景下。拟议的研究将使用最先进的传感器技术,在两年内连续监测硝酸盐、磷酸盐、溶解有机碳和辅助水质参数,河流连续体的年平均流量为四个数量级,海拔约2000米,河流长度约500公里。将在传感器站点每三周进行一次高信息产量实验,以量化碳和养分的吸收速率,同时对溶解的有机碳成分进行实验室分析。该研究方法通过将连续的传感器数据、现场实验和实验室测量与时间序列分析和基于数据的建模技术相结合,利用“大数据”的力量。该项目收集的关于整个河网的化学、生物、水文学和生态之间相互联系的时空综合信息将产生数据集和建模方法,以便为淡水资源的适应性管理提供信息,并为干旱陆地河流的总最大日负荷制定准则。将连续测量与复杂的环境参数关联起来的新的代理关系的发展,对于改变目前对流域营养循环的理解和促进淡水生物地球化学具有巨大的潜力。
英文摘要
The Centers of Research Excellence in Science and Technology-Postdoctoral Research Fellowship (CREST-PRF) track within the CREST program supports beginning CREST Center investigators with significant potential and provides them with training and research experiences that will broaden perspectives, facilitate interdisciplinary interactions and establish them in positions of leadership within the scientific community. This CREST-PRF project is aligned with the research focus of the CREST Center for Water and the Environment (CWE) at the University of New Mexico. The objective of this project is to determine how longitudinal changes in the composition of dissolved organic carbon control nutrient uptake dynamics and export in arid-land river networks at multiple spatial (reach to river) and temporal (hours to years) scales. Arid lands support approximately a third of the world's population and half of the world's agriculture. Due to multiple competing stressors (e.g., dams, constant dewatering, fire ash inputs and increased evapotranspiration), and overreliance on water resources, arid-land river systems are typically less resilient and more vulnerable to water quality degradation, including eutrophication. Results from this project will provide tools to assess the fate and transport of carbon and nutrients in arid river systems, and scientific knowledge to support the development of multi-sector solutions aimed at improving nutrient recycling in arid metropolitan areas, within the context of the food, water and energy nexus.The proposed research will continuously monitor nitrate, phosphate, dissolved organic carbon, and ancillary water quality parameters using state-of-the-art sensor technology for two years along a river continuum spanning four orders of magnitude in mean annual discharge, ~2000 m in altitude and ~500 km of stream length. High-information-yield experiments to quantify carbon and nutrient uptake rates will be conducted every three weeks at the sensor sites along with laboratory analysis of dissolved organic carbon composition. The research approach harnesses the power of "big data" by combining continuous sensor data, field experiments, and laboratory measurements with time-series analysis and data-based modeling techniques. Spatiotemporally comprehensive information about the interconnections between chemistry, biology, hydrology and ecology along an entire river network collected by this project will generate datasets and modeling approaches to inform adaptive management of freshwater resources and establish guidelines for total maximum daily loads in arid land rivers. Development of novel proxy relationships correlating continuous measurements to complex environmental parameters holds great potential to transform current understanding of watershed nutrient cycling and advance freshwater biogeochemistry.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1016/j.mex.2019.03.014
发表时间: 2019-01-01
期刊: METHODSX
影响因子: 1.9
作者: [Regier, Peter, Briceno, Henry, Boyer, Joseph N.]
通讯作者: Boyer, Joseph N.
DOI: 10.1016/j.jaridenv.2019.03.003
发表时间: 2019-06
期刊: Journal of Arid Environments
影响因子: 2.7
作者: [Julia L. Wise;David Van Horn;A. Diefendorf;P. Regier;T. Lowell;C. Dahm]
通讯作者: Julia L. Wise;David Van Horn;A. Diefendorf;P. Regier;T. Lowell;C. Dahm
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