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@ARTICLE{Kamali:906182,
      author       = {Kamali, Bahareh and Stella, Tommaso and Berg-Mohnicke,
                      Michael and Pickert, Jürgen and Groh, Jannis and Nendel,
                      Claas},
      title        = {{I}mproving the simulation of permanent grasslands across
                      {G}ermany by using multi-objective uncertainty-based
                      calibration of plant-water dynamics},
      journal      = {European journal of agronomy},
      volume       = {134},
      issn         = {1161-0301},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2022-01281},
      pages        = {126464},
      year         = {2022},
      abstract     = {The dynamics of grassland ecosystems are highly complex due
                      to multifaceted interactions among their soil, water, and
                      vegetation components. Precise simulations of grassland
                      productivity therefore rely on accurately estimating a
                      variety of parameters that characterize different processes
                      of these systems. This study applied three calibration
                      schemes – a Single-Objective (SO-SUFI2), a Multi-Objective
                      Pareto (MO-Pareto), and, a novel Uncertainty-Based
                      Multi-Objective (MO-SUFI2) – to estimate the parameters of
                      MONICA (Model for Nitrogen and Carbon Simulation)
                      agro-ecosystem model in grassland ecosystems across Germany.
                      The MO-Pareto model is based on a traditional Pareto
                      optimality concept, while the MO-SUFI2 optimizes multiple
                      target variables considering their level of prediction
                      uncertainty. We used measurements of leaf area index,
                      aboveground biomass, and soil moisture from experimental
                      data at five sites with different intensities of cutting
                      regimes (from two to five cutting events per season) to
                      evaluate model performance. Both MO-Pareto and MO-SUFI2
                      outperformed SO-SUFI2 during calibration and validation. The
                      comparison of the two MO approaches shows that they do not
                      necessarily conflict with each other, but MO-SUFI2 provides
                      complementary information for better estimations of model
                      parameter uncertainty. We used the obtained parameter ranges
                      to simulate grassland productivity across Germany under
                      different cutting regimes and quantified the uncertainty
                      associated with estimated productivity across regions. The
                      results showed higher uncertainty in intensively managed
                      grasslands compared to extensively managed grasslands,
                      partially due to a lack of high-resolution input information
                      concerning cutting dates. Furthermore, the additional
                      information on the quantified uncertainty provided by our
                      proposed MO-SUFI2 method adds deeper insights on confidence
                      levels of estimated productivity. Benefiting from additional
                      management data collected at high resolution and ground
                      measurements on the composition of grassland species
                      mixtures appear to be promising solutions to reduce
                      uncertainty and increase model reliability.},
      cin          = {IBG-3},
      ddc          = {640},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {2173 - Agro-biogeosystems: controls, feedbacks and impact
                      (POF4-217)},
      pid          = {G:(DE-HGF)POF4-2173},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000784446200004},
      doi          = {10.1016/j.eja.2022.126464},
      url          = {https://juser.fz-juelich.de/record/906182},
}