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BRIEF RESEARCH REPORT article

Front. Environ. Sci.
Sec. Freshwater Science
Volume 12 - 2024 | doi: 10.3389/fenvs.2024.1473726
This article is part of the Research Topic Nitrate from Field to Stream: Characterization and Mitigation View all articles

Quantifying rain-driven NO3-N dynamics in a headwater: Value of applying SISO System Identification to multiple variables monitored at the same high frequency

Provisionally accepted
Nick A. Chappell Nick A. Chappell *
  • Lancaster University, Lancaster, United Kingdom

The final, formatted version of the article will be published soon.

    Nitrate-nitrogen (NO3-N) concentration is a key variable affecting the ecosystem services supported by headwater streams. The availability of such data monitored continuously at a high frequency (in parallel to hydrometric and other water quality data) potentially permits greater insight into the dynamics of this key variable. This study demonstrates how Single-Input Single-Output (SISO) System Identification tools can make better use of these high frequency data to identify a reduced number of numerical characteristics that support new explanatory hypotheses of rain-driven NO3-N dynamics. A second-order watershed managed for commercial forestry in upland Wales (UK) provided the illustrative data. Fifteen-minute rainfall time-series were used to simulate NO3-N concentration dynamics, and the potentially associated dynamics in dissolved organic carbon (DOC) and runoff, monitored at the same high resolution for two 30-day periods with a differing temperature regime. The approach identified robust, high efficiency models needing few parameters. Comparison of only threederived Dynamic Response Characteristics (DRCs) of the δ, TC and SSG for the three variables for the two different periods, led to new hypotheses of rain-driven NO3-N dynamics for further exploratory field investigation.

    Keywords: CAPTAIN Toolbox, dissolved organic carbon, high frequency, nitrate, Stream, system identification, watershed

    Received: 31 Jul 2024; Accepted: 02 Sep 2024.

    Copyright: © 2024 Chappell. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Nick A. Chappell, Lancaster University, Lancaster, United Kingdom

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