Ecohydrology is the interdisciplinary study of the interactions between Earth's hydro- and biosphere. For example, the modulation of the hydrological cycle through transpiration, plant water use, influence of flora and fauna on overland flow, as well as water-driven disturbances on ecosystems such as pathogen transport, drought, and flooding.
We use theoretical methods to understand ecohydrological processes in terrestrial ecosystems, including urbanised areas. Our research foci are concept development, model-based hypothesis testing, and tool development.
Terrestrial ecohydrology considers ecohydrological processes in terrestrial environmental systems. We numerically study plant response to hydrological extrema such as droughts and floods. Here, we are interested in the emerging flux re-scaling processes at the hillslope and catchment scale that are modulated by vegetation dynamics. Applications include determining wildfire resilience of ecosystems and watershed management.
Urban ecohydrology is the study of ecohydrological processes in urban areas. The defining characteristic of the urban area is the high degree of surface sealing, leading to substantial ecological and hydrological disconnectivity. We are studying the impact of urbanisation on ecohydrological processes using theoretical tools such as computational models and data-driven approaches. Applications include assessing the potential of green infrastructure to restore the water balance and provide urban cooling.
High-performance computing for ecohydrological applications
Advances in computer technology have radically increased computing capabilities. However, the recent development of heterogeneous computer architectures in the current generation of supercomputing clusters poses a challenge, because writing parallelised code that performs similarly well across all these different architectures is non-trivial. Our group is part of the SERGHEI developer team, which aims to develop and maintain an open source high-performance code for ecohydrological simulations. SERGHEI can be run with similar performance on a broad range of computer architectures, ranging from personal computers to multi-GPU supercomputing clusters.
- Simulation & Data Laboratory Terrestrial Systems, Forschungszentrum Jülich
- Geochemistry Department, Lawrence Berkeley National Laboratory
- Computational Hydraulics Group, Universidad de Zaragoza