Towards operational quantification of GHG exchange in heterogeneous agricultural landscapes and experimental plots

With the increasing  need to mitigate rising atmospheric greenhouse gas (GHG) concentrations more attention is being directed at the quantification  of the GHG exchange characteristics of heterogenous landscape assemblages that vary in land cover and land use.   Whilst emission-limiting or uptake-enhancing management actions are often being proposed for specific land use most remain to be experimentally tested and  validated at the landscape scale. This is a challenge because the typical size of different landscape elements  (fields, afforested areas and unmanaged land at hectare scale) or experimental fields where emission reduction measures are being tested, is at the lower limit of what micrometeorological techniques such as eddy covariance measurements can deal with. With large heterogeneity the use  of chamber measurements is also limited. The investments to be made in equipment are a challenge for operational monitoring of GHG budgets.

To address this we assess the feasibility of several options to acquire appropriate data in a way that is achievable for stakeholders, such as land managers and regional authorities. We use existing and new flux data from an agricultural landscape in the North of the Netherlands  to: 1) compare paired eddy covariance (EC) data and automatic chamber (AC) data to test the representativity of small footprints. Results from a test site on drained meadows show almost identical CO₂ fluxes. Future research should compare grass length and soil moisture of EC- and AC footprints; 2) test simplified alternatives to EC, such as those relying on concentration variances. Data from the peat meadow site suggest that time-averaged fluxes can be estimated in an empirical way with reasonable accuracy from concentration variances; 3) analyze the value of information gathered with mobile, roving/temporary EC approaches interpolated with gap filling models. The indications are  that the values and variability of fluxes is largely  conserved and predictable within seasons In all these analyses, we will consider the tradeoffs between the need for accuracy and pragmatism in operational practice.