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

项目名称：Ricardo gonzalez - pinzon项目编号：1707042该项目的目标是在空间和时间上全面地了解干旱陆地河流网络的营养动态。过量的营养负荷是对河流生态系统最常见和最具破坏性的干扰之一，其负面影响延伸到下游湖泊、含水层和沿海水域，这些地区极易受到营养负荷的影响。该项目的成果将为评估河网中碳和营养物质的运输和命运提供方法，促进对水资源、粮食生产和营养循环之间复杂联系的更全面了解，并为减少污染和增加营养物质循环提供信息。pi将利用现有的最先进的传感器技术，沿着平均年流量4个数量级、海拔2000米、河流长度500公里的河流连续两年连续监测水质参数、硝酸盐、磷酸盐和溶解有机碳。在此期间，每三周将在每个研究地点进行一项最新开发的高信息量田间试验，以每小时时间尺度量化营养吸收参数。然后，将使用时间序列分析工具箱将连续的水质数据与每小时的实验数据结合起来，量化河流在不同时间尺度上的代谢和营养摄取动态变化，并确定造成这种变化的最重要因素。该项目将通过使用以下方法，促进目前对河流中营养动态的理解：1)多年，全季节监测，这将扩展传统的短时间收集数据的趋势；2)同时监测多个流阶；3)多参数数据收集，这将提供必要的背景，更全面地了解考虑运输和化学计量约束的营养动态；4)最先进的时间序列分析，使构建能够表示时间（多季节）和空间（整个连续统）养分吸收和运输过程的简约模型成为可能。

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.