Fachbereich Geowissenschaften

Water Transport through Plants

How can biological optimisation principles be used to improve simple hydrodynamic models of transpiration by vegetation?

PhD Researcher: Atefeh Hosseini
Supervisors: Thilo Streck (University of Hohenheim), Sebastian Gayler (University of Hohenheim), Aaron Berg (University of Guelph)

Projekt Overview

Annually, terrestrial plants recycle more than half of the global precipitation (Chahine, 1992). Stomata as major transpiration regulators play an important role in determining the efficiency of plant water uptake (carbon gained/water loss) in response to environmental and physiological conditions.

To investigate the impact of environmental change (e.g. climate change) on transpiration and hydrological cycle, it is necessary to integrate biological principles of plant water flux to hydrodynamic models. Also parameterization of stomatal conductance is a key element in the simulation of crop productivity and water-use efficiency in agricultural ecosystems.

Until now, only few models have been developed which combine biological processes such as stomatal regulation with descriptions of the coupled fluxes of water and carbon-dioxide in the soil–plant–atmosphere continuum.

The aim of this study is to integrate the optimal water-use hypothesis (Schymanski et al. 2008; Konrad et al.) to calculate stomata conductance in photosynthesis using an empirical hydrodynamic model of water transport through plants (Janott et al., 2011). The performance of the combined model will be tested against multiple datasets on the evapotranspiration of field crops, e.g. corn (Zea mays) and wheat (Triticum aestivum), and soil moisture dynamics originating from the southwestern part of Germany. Simulation will take place at field and catchment scale to investigate environmental impacts on the contribution of plants to the hydrological cycle. In particular, adaptation and mitigation strategies (replacing crop species and cultivars, shifts in sowing and harvest dates) will be used to analyze climate change scenarios such as elevated atmospheric CO2-concentrations, temperature increase and precipitation change.