The value of cross-disciplinary approaches for plant water uptake modelling
- 1ZALF, IBG, Germany (maren.dubbert@zalf.de)
- 2Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
- 3Institute for Atmospheric and Earth System Research (INAR), University of Helsinki, Helsinki, Finland
- 4Ecosystem Physiology, University of Freiburg, Freiburg, Germany
In recent years, research interest in plant water uptake strategies has significantly grown in many disciplines such as hydrology, plant ecology and ecophysiology. Quantitative modelling approaches to estimate plant water uptake and the spatio-temporal dynamics significantly advanced from different disciplines across scales. Despite this progress, major limitations, i.e. to predict plant water uptake under drought or it´s impact at large-scales remain. These are less attributed to limitations in process understanding, but rather to a lack of implementation of cross-disciplinary insights in plant water uptake model structure.
The main goal of this presentation is to highlight how the 4 dominant model approaches, e.g. Feddes approach, hydrodynamic approach, optimality and statistical approaches, can be and have been used to create interdisciplinary hybrid models enabeling a holistic system understanding that e.g. embeds plant water uptake plasticity into a broader conceptual view of soil-plant feedbacks of water, nutrient and carbon cycling or reflects observed drought responses of plant-soil feedbacks and their dynamics under e.g. drought. Specifically, we provide examples of how integration of Bayesian and hydrodynamic approaches might overcome challenges in interpreting plant water uptake related to e.g. different travel and residence times of different plant water sources or trade-offs between root system optimization to forage for water and nutrients during different seasons and phenological stages.
How to cite: Dubbert, M., Couvreur, V., Kübert, A., Holz, M., and Werner, C.: The value of cross-disciplinary approaches for plant water uptake modelling, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-8981, https://doi.org/10.5194/egusphere-egu23-8981, 2023.