## 4 Conclusions  
In this work, we improve the representation of surface processes that occur in the Pampa biome through the use of a hierarchical and multi-objective calibration applied to the INLAND model. The AMALGAM algorithm enabled the calibration of the model based on multiple objective functions (two metrics and four model outputs) used in a hierarchical time sequence that follows the biogeophysical and biogeochemical processes of natural systems. The calibration results were evaluated based on data collected from an experimental site with vegetation representative of the Pampa biome. In general, the simulations satisfactorily represented energy and mass changes occurring within the examined ecosystem. For the calibration period, the simulation of net radiation generated the best results. After \(Rr\) calibration, the average diurnal cycle and daily mean of \(Rn\) generated satisfactory statistics (e.g., there was a reduction of roughly 65% in mean absolute error). For daily averages, latent heat flux was slightly overestimated but with a magnitude of error comparable to related works in the literature. Values such as the RMSE were decreased by approximately 10% in relation to those of the default simulation. On the other hand, the sensible heat flux was systematically overestimated by the model. This characteristic of the model, which has also been reported in other works, may be related to deficiencies of physical parameterizations used by the model to represent heat transfer between vegetation and the atmosphere. Slight underestimates of the net CO2 exchange of the ecosystem were observed and mainly in relation to annual accumulation. Despite this, the INLAND representation of \(NEE\) was substantially  
Figure 17: Scatterplots of the simulated hourly values against data observed from the Santa Maria experimental site from January to December, 2018. (**a**) Net radiation, \(Rn\) [W m\({}^{-2}\)]; (**b**) latent heat flux, \(LE\) [W m\({}^{-2}\)]; (**c**) sensible heat flux, \(H\) [W m\({}^{-2}\)]; and (**d**) net ecosystem exchange of CO2, \(NEE\) [\(\mu\)mol CO2 m\({}^{-2}\)s\({}^{-1}\)]. improved after calibration, reducing the absolute mean error of daily values by more than 69%. Nocturnal assimilation was systematically underestimated while daytime values and mainly for between 9 a.m. and 3 p.m. were overestimated by the model. This problem may be associated with an underestimation of diurnal respiration rates, whose origins may be associated with errors of coefficients related to soil respiration or soil carbon content. To investigate this problem, it is necessary to collected field measurements that allow for more accurate comparisons. This is an important theme to be explored in future work. Surface cover plays a key role in physical and ecological processes that occur throughout the atmospheric boundary layer. Especially for surfaces covered by native vegetation, understanding interactions between the land surface and atmosphere and the role of vegetation in physical and ecological processes that govern biosphere behavior has expanded significantly in recent years. As a result, LSEMs are increasingly being designed to represent more complex processes at different time scales. Of course, in increasing the variety and complexity of representations of natural processes using surface models we must examine more processes in a more complex manner. Therefore, it is necessary to apply robust methodologies to calibrate and validate such models using experimental data. This work is the first to accomplish the multi-objective calibration of an LSEM for a site with vegetation representative of the Pampa biome. It should be noted that studies considering flux data for multiple experimental sites with similar vegetation are necessary to eliminate effects of differences in ecosystem composition. In addition, as the biome has the presence of C3 and C4 plants and has the constant presence of cattle, a new PFT could be included in the model by modeling these biome features.