Articles | Volume 17, issue 2
Hydrol. Earth Syst. Sci., 17, 735–749, 2013
https://doi.org/10.5194/hess-17-735-2013
Hydrol. Earth Syst. Sci., 17, 735–749, 2013
https://doi.org/10.5194/hess-17-735-2013

Research article 20 Feb 2013

Research article | 20 Feb 2013

Modelling soil temperature and moisture and corresponding seasonality of photosynthesis and transpiration in a boreal spruce ecosystem

S. H. Wu1,* and P.-E. Jansson1 S. H. Wu and P.-E. Jansson
  • 1Department of Land and Water Resources Engineering, Royal Institute of Technology (KTH), Brinellvägen 28, 100 44 Stockholm, Sweden
  • *now at: National Centre for Science and Technology Evaluation, 100081 Bejing, China

Abstract. Recovery of photosynthesis and transpiration is strongly restricted by low temperatures in air and/or soil during the transition period from winter to spring in boreal zones. The extent to which air temperature (Ta) and soil temperature (Ts) influence the seasonality of photosynthesis and transpiration of a boreal spruce ecosystem was investigated using a process-based ecosystem model (CoupModel) together with eddy covariance (EC) data from one eddy flux tower and nearby soil measurements at Knottåsen, Sweden. A Monte Carlo-based uncertainty method (GLUE) provided prior and posterior distributions of simulations representing a wide range of soil conditions and performance indicators. The simulated results showed sufficient flexibility to predict the measured cold and warm Ts in the moist and dry plots around the eddy flux tower. Moreover, the model presented a general ability to describe both biotic and abiotic processes for the Norway spruce stand. The dynamics of sensible heat fluxes were well described by the corresponding latent heat fluxes and net ecosystem exchange of CO2. The parameter ranges obtained are probably valid to represent regional characteristics of boreal conifer forests, but were not easy to constrain to a smaller range than that produced by the assumed prior distributions. Finally, neglecting the soil temperature response function resulted in fewer behavioural models and probably more compensatory errors in other response functions for regulating the seasonality of ecosystem fluxes.

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