Improving the simulation of permanent grasslands across Germany by using multi-objective uncertainty-based calibration of plant-water dynamics

Kamali, Bahareh; Stella, Tommaso; Berg-Mohnicke, Michael; Pickert, Jürgen; Groh, Jannis; Nendel, Claas

doi:10.1016/j.eja.2022.126464

Cited by 5 publications

(6 citation statements)

References 55 publications

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“…As a generic crop model, MONICA requires species-specific parameters to represent the growth and development of a specific plant. For multi-species grass vegetation, we calibrated parameters to observe growth patterns, as previously described by Kamali [49].…”

Section: Modelling Approachmentioning

confidence: 99%

“…Agriculture 2024, 14, x FOR PEER REVIEW 7 of 18 plant. For multi-species grass vegetation, we calibrated parameters to observe growth patterns, as previously described by Kamali [49].…”

Section: Modelling Approachmentioning

confidence: 99%

“…From the whole dataset, the data from 2014 to 2019 was selected as the calibration dataset. The parameters selected for model calibration were taken from Kamali [49].…”

Section: Modelling Approachmentioning

confidence: 99%

“…Furthermore, MONICA is also designed to reproduce soil organic matter turnover, nitrification, and denitrification in response to soil moisture levels, soil mineralogy, and temperature; this ensures that the indirect effect of soil moisture on plant growth (because of moisture's relationship with nitrogen availability) is also reproduced. Finally, MONICA also simulates ascending soil moisture in the unsaturated fringe above WTD, the survival of grass stolons over winter to regrow in the following season, and the necrosis/senescence of root and leaf parts on a daily basis [49]. All in all, when we approached the task of simulating vegetation growth dynamics in response to changing groundwater levels, we did so under the assumption that MONICA would be fit for this purpose.…”

Section: Simulating the Processes Leading To The Grassland Yield Patt...mentioning

confidence: 99%

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Challenges of Including Wet Grasslands with Variable Groundwater Tables in Large-Area Crop Production Simulations

Khaledi,

Kamali,

Lischeid

et al. 2024

Agriculture

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Large-scale assessments of agricultural productivity necessitate integrated simulations of cropland and grassland ecosystems within their spatiotemporal context. However, simultaneous simulations face limitations due to assumptions of uniform species distribution. Grasslands, particularly those with shallow groundwater tables, are highly sensitive to water availability, undergoing rapid species composition changes. We hypothesised that predicting above-ground biomass (AGB) remains challenging due to these dynamic responses. Ten years of data from four lysimeters at a German wet grassland site, with varying water table treatments, was utilised to test this hypothesis. Correlation analysis revealed a strong positive indirect effect of the water regime on AGB, with a one-year time lag (r = 0.97). The MONICA model initially exhibited fair agreement (d = 0.69) in simulating Leaf-Area-Index (LAI) but performed poorly in replicating AGB (d = 0.3). After removing the species composition change effect from the LAI and AGB datasets, the simulation notably improved, with the overall relative root mean square error (rRMSE) of AGB decreasing from 1.55 to 0.90 between the first and second simulations. This demonstrates MONICA’s ability to predict grass growth patterns amidst changing water supply levels for constant species composition. However, it needs a competition model to capture biomass growth changes with varying water supply.

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Section: Modelling Approachmentioning

confidence: 99%

“…Agriculture 2024, 14, x FOR PEER REVIEW 7 of 18 plant. For multi-species grass vegetation, we calibrated parameters to observe growth patterns, as previously described by Kamali [49].…”

Section: Modelling Approachmentioning

confidence: 99%

“…From the whole dataset, the data from 2014 to 2019 was selected as the calibration dataset. The parameters selected for model calibration were taken from Kamali [49].…”

Section: Modelling Approachmentioning

confidence: 99%

Section: Simulating the Processes Leading To The Grassland Yield Patt...mentioning

confidence: 99%

See 2 more Smart Citations

Challenges of Including Wet Grasslands with Variable Groundwater Tables in Large-Area Crop Production Simulations

Khaledi,

Kamali,

Lischeid

et al. 2024

Agriculture

Self Cite

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“…CC BY 4.0 License. (Wöhling et al, 2013;Kamali et al, 2022). The spatial aspect may be dealt with in a similar manner.…”

Section: Introductionmentioning

confidence: 99%

Biogeochemical model Biome-BGCMuSo v6.2 provides plausible and accurate simulations of carbon cycle in Central European beech forests

Merganičová,

Merganič,

Dobor

et al. 2024

Preprint

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Abstract. Process-based ecosystem models are increasingly important for predicting forest dynamics under future environmental conditions, which may encompass non-analogous climate coupled with unprecedented disturbance regimes. However, challenges persist due to the extensive number of model parameters, scarce calibration data, and the trade-offs between the local precision and the model wide-ranging applicability. In this paper, we describe a protocol that allows a modeller to collect transferable ecosystem properties based on ecosystem characteristic criteria and to compile the parameters that need to be described in the field. We applied the procedure to develop a new parameterization for the European beech (Fagus sylvatica L.) for the Biome-BGCMuSo model, the most advanced member of the Biome-BGC family. For model calibration and testing, we utilized multiyear forest carbon data from 87 plots distributed across five European countries. The initial values of 48 new ecophysiological parameters were defined based on the literature review. The final values of 6 calibrated parameters were optimised for single sites as well as for multiple sites using the Generalised Likelihood Uncertainty Estimation and model output conditioning that ensured plausible simulations based on user-defined ranges of carbon stock output variables (carbon stock in aboveground wood biomass, soil, and litter) and finding the intersections of site-specific plausible parameter hyperspaces. To support the model use, we tested the model performance in simulating tree aboveground wood, soil, and litter carbon across a large geographical gradient of Central Europe and evaluated the trade-offs between parameters tailored to single plots and parameters estimated using multiple sites. Our findings indicated that parameter sets derived from single sites provided an improved local accuracy of simulations of aboveground wood, soil, and litter carbons stocks by 35 %, 55 %, and 11 % in comparison to the a priori parameter set. However, their broader applicability was very limited. A multi-site optimised parameter set, on the other hand, performed satisfactorily across the entire geographical domain studied here, including sites not involved in the parameter estimation, but the errors were on average by 26 %, 35 % and 9 % greater for the aboveground wood, soil, and litter carbons stocks than those obtained with the site-specific parameter sets. Importantly, model simulations demonstrated plausible responses across large-scale environmental gradients, featuring a clear production optimum of beech that aligns with empirical studies. These findings suggest that the model is capable of accurately simulating the dynamics of the European beech across its range and can be used for more comprehensive experimentations.

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Quest to find compromised spatial and temporal resolutions for integrating remote sensing data with an agro-ecosystem model for grasslands

Kamali,

Ahmadi,

Gaiser

et al. 2024

International Journal of Applied Earth Observation and Geoinfor

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Improving the simulation of permanent grasslands across Germany by using multi-objective uncertainty-based calibration of plant-water dynamics

Cited by 5 publications

References 55 publications

Challenges of Including Wet Grasslands with Variable Groundwater Tables in Large-Area Crop Production Simulations

Challenges of Including Wet Grasslands with Variable Groundwater Tables in Large-Area Crop Production Simulations

Biogeochemical model Biome-BGCMuSo v6.2 provides plausible and accurate simulations of carbon cycle in Central European beech forests

Quest to find compromised spatial and temporal resolutions for integrating remote sensing data with an agro-ecosystem model for grasslands

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