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

Academic Article

Abstract

  • AbstractNitrogen (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, NO3, and NH4+ 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 NH4+ 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.
  • Authors

  • Murray, Desneiges S
  • Moges, Edom
  • Larsen, Laurel
  • Shattuck, Michelle
  • McDowell, William H
  • Wymore, Adam
  • Status

    Publication Date

  • October 2023
  • Has Subject Area

    Published In

    Digital Object Identifier (doi)

    Volume

  • 59
  • Issue

  • 10