Vegetation optimality has been shown to be a promising way forward in land surface modelling in order to reduce data requirements and improve simulations under change (Schymanski et al., 2015, 2009). In addition, it was shown that state-of-the-art land surface models have great difficulty to simulate water and carbon fluxes in tropical savanna ecosystems (Whitley et al., 2016). In this study, we evaluate the Vegetation Optimality Model (VOM), which optimizes vegetation properties and dynamics to maximize the Net Carbon Profit, i.e. the total carbon uptake by photosysthesis minus carbon costs related to maintenance of foliage, roots and the water transport system. The VOM couples a vegetation model with a soil water balance model. The vegetation is schematized as two big leaves, one representing the annual grasses and one representing the perennial trees. Vegetation properties such as rooting depths and projective cover are optimized to maximize the Net Carbon Profit. The model has been applied over six study sites along the North-Australian Tropical Transect, which has a strong rainfall gradient from North to South. In addition, all modelling and analysis steps have been carried out in an open science approach, where all scientific steps have been recorded using the open source tool Renku (renkulab.io). Preliminary results show that the VOM provides satisfactory fluxes of evaporation and assimilation in comparison with flux tower data along the North-Australian Tropical Transect, equivalent or better to previous modelling efforts. In addition, an analysis will be presented on the effects of different hydrological parameterizations. The results obtained thus far suggest that optimizing for Net Carbon Profit leads to a reduced need for vegetation data in comparison with other land surface models. The results also show that especially for the drier study sites, the modelled assimilation shows an increased discrepancy with observations. References Schymanski, S.J., Roderick, M.L., Sivapalan, M., 2015. Using an optimality model to understand medium and long-term responses of vegetation water use to elevated atmospheric CO2 concentrations. AoB PLANTS 7, plv060. https://doi.org/10.1093/aobpla/plv060 Schymanski, S.J., Sivapalan, M., Roderick, M.L., Hutley, L.B., Beringer, J., 2009. An optimality‐based model of the dynamic feedbacks between natural vegetation and the water balance. Water Resources Research 45. https://doi.org/10.1029/2008WR006841 Whitley, R., Beringer, J., Hutley, L.B., Abramowitz, G., De Kauwe, M.G., Duursma, R., Evans, B., Haverd, V., Li, L., Ryu, Y., Smith, B., Wang, Y.-P., Williams, M., Yu, Q., 2016. A model inter-comparison study to examine limiting factors in modelling Australian tropical savannas. Biogeosciences 13, 3245–3265. https://doi.org/10.5194/bg-13-3245-2016

Funded by the Luxembourg National Research Fund, ATTRACT programme (A16/SR/11254288)