Chappell, Nick A. (2024) Quantifying rain-driven NO 3 -N dynamics in headwater : value of applying SISO system identification to multiple variables monitored at the same high frequency. Frontiers in Environmental Science, 12: 1473726. ISSN 2296-665X
Full text not available from this repository.Abstract
The 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 a 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 (United Kingdom) 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 three derived dynamic response characteristics (DRCs) of 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.