Synchrony of Nitrogen Wet Deposition Inputs and Watershed Nitrogen Outputs Using Information Theory

IF 4.6 1区 地球科学 Q2 ENVIRONMENTAL SCIENCES Water Resources Research Pub Date : 2023-10-01 DOI:10.1029/2023wr034794
Desneiges S. Murray, Edom Moges, Laurel Larsen, Michelle D. Shattuck, William H. McDowell, Adam S. Wymore
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Abstract

Abstract Nitrogen (N) wet deposition chemistry impacts watershed biogeochemical cycling. The timescale and magnitude of (a)synchrony between wet deposition N inputs and watershed N outputs remains unresolved. We quantify deposition‐river N (a)synchrony with transfer entropy (TE), an information theory metric enabling quantification of lag‐dependent feedbacks in a hydrologic system by calculating directional information flow between variables. Synchrony is defined as a significant amount of TE‐calculated reduction in uncertainty of river N from wet deposition N after conditioning for antecedent river N conditions. Using long‐term timeseries of wet deposition and river DON, NO 3 − , and NH 4 + concentrations from the Lamprey River watershed, New Hampshire (USA), we constrain the role of wet deposition N to watershed biogeochemistry. Wet deposition N contributed information to river N at timescales greater than quick‐flow runoff generation, indicating that river N losses are a lagged non‐linear function of hydro‐biogeochemical forcings. River DON received the most information from all three wet deposition N solutes while wet deposition DON and NH 4 + contributed the most information to all three river N solutes. Information theoretic algorithms facilitated data‐driven inferences on the hydro‐biogeochemical processes influencing the fate of N wet deposition. For example, signals of mineralization and assimilation at a timescale of 12 to 21‐weeks lag display greater synchrony than nitrification, and we find that N assimilation is a positive lagged function of increasing N wet deposition. Although wet deposition N is not the main driver of river N, it contributes a significant amount of information resolvable at time scales of transport and transformations.
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基于信息论的氮湿沉降输入与流域氮输出的同步性
氮(N)湿沉积化学影响流域生物地球化学循环。湿沉积N输入和流域N输出之间(a)同步的时间尺度和幅度仍未确定。我们用传递熵(TE)来量化沉积-河流N (a)的同步性,传递熵(TE)是一种信息理论度量,通过计算变量之间的方向信息流来量化水文系统中滞后依赖的反馈。同步被定义为在对先前的河流N条件进行调节后,通过TE计算的湿沉积N对河流N不确定性的显著减少。利用美国新罕布什尔州七目鱼河流域湿沉降和河流DON、NO 3−和nh4 +浓度的长期时间序列,研究了湿沉降N对流域生物地球化学的影响。湿沉积氮在时间尺度上对河流氮的贡献大于速流径流,表明河流氮损失是水文-生物地球化学强迫的滞后非线性函数。河流DON从三种湿沉积N溶质中获得的信息最多,而湿沉积DON和nh4 +对三种河流N溶质的信息贡献最多。信息理论算法促进了数据驱动的对影响N湿沉降命运的水文-生物地球化学过程的推断。例如,矿化和同化信号在滞后12至21周的时间尺度上比硝化表现出更大的同动性,我们发现N同化是N湿沉降增加的正滞后函数。虽然湿沉降N不是河流N的主要驱动因素,但它在运输和转换的时间尺度上提供了大量可解析的信息。
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来源期刊
Water Resources Research
Water Resources Research 环境科学-湖沼学
CiteScore
8.80
自引率
13.00%
发文量
599
审稿时长
3.5 months
期刊介绍: Water Resources Research (WRR) is an interdisciplinary journal that focuses on hydrology and water resources. It publishes original research in the natural and social sciences of water. It emphasizes the role of water in the Earth system, including physical, chemical, biological, and ecological processes in water resources research and management, including social, policy, and public health implications. It encompasses observational, experimental, theoretical, analytical, numerical, and data-driven approaches that advance the science of water and its management. Submissions are evaluated for their novelty, accuracy, significance, and broader implications of the findings.
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