Multi-site land surface model optimization: An exploration of objective functions

Fischer, Graciela Redies; Costa, Marcos Heil; Murta, Fabrício Z.; Malhado, Ana C. M.; Aguiar, Leonardo José Gonçalves; Ladle, Richard J.

doi:10.1016/j.agrformet.2012.11.021

Cited by 5 publications

(4 citation statements)

References 41 publications

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“…Regarding turbulent flux parameters (level 2), parameter V max (the maximum velocity of carboxylation) stands out, representing a measure of the process through which enzyme Rubisco produces carbon compounds that become sugars and starches. This parameter has a direct impact on gross primary productivity (GPP) levels and consequently on NEE and can be considered representative of large regions provided that they include plant cover with similar plant species [9].…”

Section: Discussionmentioning

confidence: 99%

“…On the other hand, the metric used for LE, H, and NEE was RMSE for a better representation of these fluxes in average terms. The parameters calibrated in this work are presented in Table 2 following the studies developed by [9,13,25]…”

Section: Rmsementioning

confidence: 99%

“…This set of parameters is called default parameters. However, the use of default parameters in the LSEM can generate incorrect representations of the land surface in different regions [7][8][9]. Therefore, the LSEM models must be carefully calibrated to minimizing errors in different regions regarding the local complexity of the soil, vegetation, and climatology.…”

Section: Introductionmentioning

confidence: 99%

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Energy and CO2 Fluxes over Native Fields of Southern Brazil through Multi-Objective Calibration of INLAND Model

et al. 2020

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Land surface/ecosystem models (LSEMs) play a key role in understanding the Earth’s climate. They represent ecosystem dynamics by simulating fluxes occurring between the biosphere and atmosphere. However, for a correct flux simulation, it is critical to calibrate the model using robust and state-of-the-art calibration techniques. In this work, we optimize parameters of the Integrated Model of Land Surface Processes (INLAND) using the hierarchical multi-objective calibration method (AMALGAM) to improve the representation of surface processes in a natural ecosystem over the Pampa biome in South America. The calibration was performed using experimental data of energy and CO2 flux collected in a native field located in southern Brazil. We compared simulations using the default and calibrated parameter set. The results show that the calibration of the model significantly improved all fluxes analyzed. The mean errors and bias values were significantly reduced, and the seasonality of fluxes was better represented. This work is one of the first to apply a multi-objective calibration in an LSEM to represent surface fluxes in the Pampa biome, presenting a consistent set of parameters for future applications used in studies of biome land use and land cover.

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Section: Discussionmentioning

confidence: 99%

Section: Rmsementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Energy and CO2 Fluxes over Native Fields of Southern Brazil through Multi-Objective Calibration of INLAND Model

et al. 2020

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“…(5) Model parameterization Previous modifications of the IBIS model [41] suggested that accurate model results were dependent upon the accurate calibration of stomatal conductance coefficients (m, b), leaf respiration parameter (γ), and the maximum rubisco capacity (Vmax). For the photosynthesis of vegetation in arid regions, these parameters were set to γ = 0.025, m = 4.0, b = 0.04, and Vmax = 25 molCO 2 m −2 s −1 [42].…”

Section: Model Description and Developmentmentioning

confidence: 99%

Improving the Model Performance of the Ecosystem Carbon Cycle by Integrating Soil Erosion–Related Processes

Zhang,

et al. 2023

Atmosphere

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Soil erosion is a key factor in soil quality degradation and carbon balance in arid ecosystems. However, many models ignore the soil erosion process in arid regions, which may lead to limits in our understanding of ecosystem processes in arid regions. In this study, we added the soil erosion process according to field observed data of soil hydrothermal regimes and carbon flux. We validated this coupling version of IBIS (Integrated Biosphere Simulator) and RUSLE (RU–IBIS) by examining four different vegetation types and the carbon budget in the arid region on the Loess Plateau (LP). Our results indicated that the coupling model (RU–IBIS) produced more reliable simulations of the soil water content (with the r from 0.23–0.90 to 0.71–0.97) and evaporation (ET) (the average r was 0.76) and significantly improved the simulation of the leaf area index (LAI) (the average r was 0.95) and net primary production (NPP) (the average r was 0.95). We also conducted sensitivity experiments to determine how soil texture and aerodynamic roughness (Z0m) affect the soil water content. Moreover, it was revealed that specific leaf area (SLA) plays a key role in the simulation of NPP and NEE. Our study suggests that the coupled soil erosion process and parameterization can effectively improve the performance of IBIS in arid regions. These results need to be considered in future Earth system models.

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Warming could shift steppes to carbon sinks and meadows to carbon sources in permafrost regions: Evidence from the improved IBIS model

et al. 2021

CATENA

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Multi-site land surface model optimization: An exploration of objective functions

Cited by 5 publications

References 41 publications

Energy and CO2 Fluxes over Native Fields of Southern Brazil through Multi-Objective Calibration of INLAND Model

Energy and CO2 Fluxes over Native Fields of Southern Brazil through Multi-Objective Calibration of INLAND Model

Improving the Model Performance of the Ecosystem Carbon Cycle by Integrating Soil Erosion–Related Processes

Warming could shift steppes to carbon sinks and meadows to carbon sources in permafrost regions: Evidence from the improved IBIS model

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