Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 5.154 IF 5.154
  • IF 5-year value: 5.697 IF 5-year
    5.697
  • CiteScore value: 5.56 CiteScore
    5.56
  • SNIP value: 1.761 SNIP 1.761
  • IPP value: 5.30 IPP 5.30
  • SJR value: 3.164 SJR 3.164
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 59 Scimago H
    index 59
  • h5-index value: 49 h5-index 49
Discussion papers
https://doi.org/10.5194/gmd-2019-117
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-117
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model description paper 02 Jul 2019

Model description paper | 02 Jul 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

FORHYCS v1.0: A spatially distributed model combining hydrology and forest dynamics

Matthias J. R. Speich1,2,3,4, Massimiliano Zappa2, Marc Scherstjanoi1,5, and Heike Lischke1 Matthias J. R. Speich et al.
  • 1Dynamic Macroecology, Swiss Federal Research Institute WSL, 8903 Birmensdorf, Switzerland
  • 2Hydrological Forecasts, Swiss Federal Research Institute WSL, 8903 Birmensdorf, Switzerland
  • 3Department of Environmental Systems Science, ETH Zurich, 8092 Zurich, Switzerland
  • 4Biometry and Environmental Systems Analysis, University of Freiburg, 79085 Freiburg i. Br., Germany
  • 5Institute of Climate-Smart Agriculture, Johann Heinrich von Thünen Institute, 38116 Braunschweig, Germany

Abstract. We present FORHYCS (FORests and HYdrology under Climate Change in Switzerland), a distributed ecohydrological model to assess the impact of climate change on water resources and forest dynamics. FORHYCS is based on the coupling of the hydrological model PREVAH and the forest landscape model TreeMig. In a coupled simulation, both original models are executed simultaneously and exchange information through shared variables. The simulated canopy structure is summarized by the leaf area index (LAI), which affects local water balance calculations. On the other hand, an annual drought index is obtained from daily simulated potential and actual transpiration. This drought index affects tree growth and mortality, as well as a species-specific tree height limitation. The effective rooting depth is simulated as a function of climate, soil and simulated above-ground vegetation structure. Other interface variables include stomatal resistance and leaf phenology.

Case study simulations with the model were performed in the Navizence catchment in the Central Swiss Alps, with a sharp elevational gradient and climatic conditions ranging from dry inneralpine to high alpine. In a first experiment, the model was run for 500 years with different configurations. The results were compared against observations of vegetation properties from national forest inventories, remotely sensed LAI and high-resolution canopy height maps from stereo aerial images. Two new metrics are proposed for a quantitative comparison of observed and simulated canopy structure. In a second experiment, the model was run for 130 years under idealized climate change scenarios: daily temperature was increased by up to 6 K, and precipitation altered by 10 %, with a gradual change over 35 years.

The first experiment showed that model configuration greatly influences simulated vegetation structure. In particular, simulations where height limitation was dependent on environmental stress showed a much better fit to canopy height observations. Spatial patterns of simulated LAI were more realistic than for uncoupled simulations of the forest landscape model, although some model deficiencies are still evident. Under idealized climate change scenarios, the effect of the coupling varied regionally, with the greatest effects on simulated streamflow (up to 40 mm y−1 difference with respect to a simulation with static vegetation parameters) seen at the valley bottom and in regions currently above the treeline. This case study shows the importance of coupling hydrology and vegetation dynamics to simulate the impact of climate change on ecosystems. Nevertheless, it also highlights some challenges of ecohydrological modelling, such as the need to realistically simulate plant response to increased CO2 concentrations, and process uncertainty regarding future land cover changes.

Matthias J. R. Speich et al.
Interactive discussion
Status: open (until 27 Aug 2019)
Status: open (until 27 Aug 2019)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement
Matthias J. R. Speich et al.
Matthias J. R. Speich et al.
Viewed  
Total article views: 161 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
112 44 5 161 12 4 6
  • HTML: 112
  • PDF: 44
  • XML: 5
  • Total: 161
  • Supplement: 12
  • BibTeX: 4
  • EndNote: 6
Views and downloads (calculated since 02 Jul 2019)
Cumulative views and downloads (calculated since 02 Jul 2019)
Viewed (geographical distribution)  
Total article views: 80 (including HTML, PDF, and XML) Thereof 80 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Cited  
Saved  
No saved metrics found.
Discussed  
No discussed metrics found.
Latest update: 20 Jul 2019
Publications Copernicus
Download
Short summary
Climate change is expected to substantially affect natural processes, and simulation models are a valuable tool to anticipate these changes. In this study, we combine two existing models that each describe one aspect of the environment: forest dynamics and the terrestrial water cycle. The coupled model better described observed patterns in vegetation structure. We also found that including the effect of water availability on tree height and rooting depth improved the model.
Climate change is expected to substantially affect natural processes, and simulation models are...
Citation