EGU2020-18266
https://doi.org/10.5194/egusphere-egu2020-18266
EGU General Assembly 2020
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Heavily data-constrained mechanistic ecohydrological modeling can guide management of pre-Alpine grasslands in the present and future climate

Martina Botter1, Matthias Zeeman2, Paolo Burlando1, and Simone Fatichi1,3
Martina Botter et al.
  • 1Institute of Environmental Engineering, ETH Zurich, Switzerland (botter@ifu.baug.ethz.ch)
  • 2Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research – Atmospheric Environmental Research, Garmisch-Partenkirchen, Germany
  • 3Department of Civil and Environmental Engineering, National University of Singapore, Singapore

The pressure of climate change and increasing food demand on agricultural systems made management strategies crucial for matching the production goals without affecting water quantity and quality. This is, for instance, the case for managed grasslands in the Alpine and pre-alpine regions. This study combines a large suite of observations from the TERENO observatory and ScaleX campaigns with mechanistic modeling, in order to analyze the response of managed grasslands north of the Alps to different climatic conditions and management strategies, aimed at evaluating changes in the ecohydrological response, as well as carbon, water and nutrient fluxes.  

First, we used the data to evaluate the performance of the mechanistic Tethys-Chloris (T&C) model, which fully integrates the solution of surface energy balance and hydrological budget with vegetation dynamics and soil biogeochemistry, for the period 2012-2016. This is characterized by significant climatic inter-annual variability and including the extraordinarily warm year 2015. The observations cover three different grassland sites composed by flux towers, soil moisture and temperature probes, lysimeters, nutrient leaching and dedicated vegetation sampling campaigns, allowing an unprecedented validation opportunity of model skills for multiple variable and temporal scales. The observed system response, in terms of water, energy and nutrients dynamics, are successfully reproduced, which increases confidence on the model capability to reproduce the feedbacks among hydrology, vegetation growth and soil biogeochemistry. The results highlight the impact of an early begin of the growing season on the vegetation productivity and nutrients leaching in years with reduced snow cover,  as well as the effects of summer drought on vegetation productivity.

Second, numerical experiments are used to test the response of this ecosystem to different grassland fertilization and cutting scenarios in the present climate and in warmer and CO2 enriched conditions. Of particular interest are the number and timing of grass cuts and fertilizer applications that could optimize grassland productivity without compromising water quality in a warmer climate.

How to cite: Botter, M., Zeeman, M., Burlando, P., and Fatichi, S.: Heavily data-constrained mechanistic ecohydrological modeling can guide management of pre-Alpine grasslands in the present and future climate, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18266, https://doi.org/10.5194/egusphere-egu2020-18266, 2020.

This abstract will not be presented.