What can we learn from multi-data calibration of a process-based ecohydrological model?

Sylvain Kuppel, Doerthe Tetzlaff, Marco P. Maneta, Chris Soulsby

Research output: Contribution to journalArticlepeer-review

44 Scopus citations


We assessed whether a complex, process-based ecohydrological model can be appropriately parameterized to reproduce the key water flux and storage dynamics at a long-term research catchment in the Scottish Highlands. We used the fully-distributed ecohydrological model EcH2O, calibrated against long-term datasets that encompass hydrologic and energy exchanges, and ecological measurements. Applying diverse combinations of these constraints revealed that calibration against virtually all datasets enabled the model to reproduce streamflow reasonably well. However, parameterizing the model to adequately capture local flux and storage dynamics, such as soil moisture or transpiration, required calibration with specific observations. This indicates that the footprint of the information contained in observations varies for each type of dataset, and that a diverse database informing about the different compartments of the domain, is critical to identify consistent model parameterizations. These results foster confidence in using EcH2O to contribute to understanding current and future ecohydrological couplings in Northern catchments.

Original languageEnglish
Pages (from-to)301-316
Number of pages16
JournalEnvironmental Modelling and Software
StatePublished - Mar 2018


  • Catchment hydrology
  • EcHO
  • Ecohydrology
  • Information content
  • Multi-objective calibration
  • Process-based modelling


Dive into the research topics of 'What can we learn from multi-data calibration of a process-based ecohydrological model?'. Together they form a unique fingerprint.

Cite this