Articles | Volume 8, issue 4
Hydrol. Earth Syst. Sci., 8, 751–763, 2004
https://doi.org/10.5194/hess-8-751-2004

Special issue: Assessing nitrogen dynamics in European ecosystems: integrating...

Hydrol. Earth Syst. Sci., 8, 751–763, 2004
https://doi.org/10.5194/hess-8-751-2004

  31 Aug 2004

31 Aug 2004

Towards reduced uncertainty in catchment nitrogen modelling: quantifying the effect of field observation uncertainty on model calibration

K. J. Raat, J. A. Vrugt, W. Bouten, and A. Tietema K. J. Raat et al.
  • Centre for Geo-Ecological Research (ICG), Institute for Biodiversity and Ecosystem Dynamics (IBED) - Physical Geography, Universiteit van Amsterdam, Nieuwe Achtergracht 166, NL-1018WV Amsterdam, The Netherlands
  • E-mail for corresponding author: k.raat@science.uva.nl

Abstract. The value of nitrogen (N) field measurements for the calibration of parameters of the INCA nitrogen in catchment model is explored and quantified. A virtual catchment was designed by running INCA with a known set of parameters, and field "measurements" were selected from the model run output. Then, using these measurements and the Shuffled Complex Evolution Metropolis algorithm (SCEM-UA), four of the INCA model parameters describing N transformations in the soil were optimised, while the measurement uncertainty was increased in subsequent steps. Considering measurement uncertainty typical for N field studies, none of the synthesised datasets contained sufficient information to identify the model parameters with a reasonable degree of confidence. Parameter equifinality occurred, leading to considerable uncertainty in model parameter values and in modelled N concentrations and fluxes. Fortunately, combining the datasets in a multi-objective calibration was found to be effective in dealing with these equifinality problems. With the right choice of calibration measurements, multi-objective calibrations resulted in lower parameter uncertainty. The methodology applied in this study, using a virtual catchment free of model errors, is proposed as a useful tool foregoing the application of a N model or the design of a N monitoring program. For an already gauged catchment, a virtual study can provide a point of reference for the minimum uncertainty associated with a model application. When setting up a monitoring program, it can help to decide what and when to measure. Numerical experiments indicate that for a forested, N-saturated catchment, a fortnightly sampling of NO3 and NH4 concentrations in stream water may be the most cost-effective monitoring strategy.

Keywords: INCA, nitrogen model, parameter uncertainty, multi-objective calibration, virtual catchment, experimental design