Estimativa dos parâmetros de distribuição e profundidade do sistema radicular pela calibração de modelos micrometeorológicos aplicação à floresta tropical Amazônica

• Ano de defesa: 2010
• Autor(a) principal: Imbuzeiro, Hemlley Maria Acioli
• Orientador(a): Costa, Marcos Heil
• Banca de defesa: Gonçalves, Luís Gustavo Gonçalves de , Costa, José Maria Nogueira da , Justino, Flávio Barbosa
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Viçosa
• Programa de Pós-Graduação: Doutorado em Meteorologia Agrícola
• Departamento: Agrometeorologia; Climatologia; Micrometeorologia
• País: BR
• Palavras-chave em Português: Calibração; Sistema radicular; Modelos micrometeorológicos
• Palavras-chave em Inglês: Calibration; Root system; Micrometeorological models
• Área do conhecimento CNPq: CNPQ::CIENCIAS EXATAS E DA TERRA::GEOCIENCIAS::METEOROLOGIA::MICROMETEOROLOGIA
• Link de acesso: http://locus.ufv.br/handle/123456789/1497

In this work we calibrated the land-surface model IBIS estimating the parameters based on the optimization of net radiation (Rn) partitioning between sensible heat flux (H) and latent heat flux (LE). We used micrometeorological databases, measurements of soil samples properties and soil moisture and temperature obtained from the site of the National Forest of Tapajós km83 (FNT-K83). The methodology is based on the premise that the partition between the heat fluxes is a function of water stress, which depends on the depth and vertical distribution of the root system. It is the first time that it is used boundary conditions, associated with soil physical properties, with different levels of uncertainties and the errors introduced by these uncertainties. The simulations run by IBIS were organized into three groups according to the different types of data and boundary conditions, with different levels of uncertainty. In the first group, the model operates in normal mode, simulating LE using data from physical properties of soil estimated from global database of soil properties. In these simulations group, the uncertainty is greater because the soil physical properties are determined by tables of representative values for each type of soil granulometrial. In the second group, the model uses soil parameters obtained locally from soil water retention curve samples collected in the FNT-K83 to simulate LE. In this group, the uncertainty is reduced because the soil properties are determined locally. In the third group, the model simulates LE forcing conditions with soil temperature and soil moisture data measured in the experimental site FNT-K83. In this group, the uncertainty is smaller, because the model uses real data of soil moisture. For the calibration procedure each group of simulations obtained ZR and β2 parameters that optimized the statistics of the correlation coefficient (ρ) and the slope of the linear regression line between the simulates and observed data (α), and the minimization of the mean absolute error (MAE), the maximum bias (Bmáx) and the objective function (F(ZR,β2)). Before starting the calibration itself, a sensitivity analysis of the modelsimulated was performed for ZR and β2 parameters. In this analysis, it was observed in all simulations groups that the IBIS is sensitive to ZR and β2 parameters, except in the third group of simulations that showed no sensitivity to β2 parameter. After the sensitivity analysis was performed, a calibration procedure was performed involving around 120 simulations, for all groups of simulations that used different boundary conditions. The new set of parameters calibrated for each group of simulations, presented different results. The calibrated parameters using data from physical properties of soil estimated from the global database of soil properties were ZR = 4 m and β2 = 0,999, while the calibrated parameters for the simulations that used soil parameters obtained locally from the soil water retention curve samples, were ZR = 30 m e β2 = 0,999, whereas the calibrate parameters for simulations that uses soil temperature and soil moisture data measured in the experimental site FNT-K83, were ZR = 3 m e β2 = 0,999. In general, the best estimated parameters are ZR= 30 m e β2 = 0,999 for FNT-K83. The analysis of the errors introduced by the boundary conditions related to soil physical properties showed that the choice of boundary conditions influence the volumetric soil water content profile simulated by IBIS, therefore, the amount of water available for the processes of evaporation, transpiration and consequently the partition of Rn into H and LE. These analyses indicate that the boundary condition that produces small errors is that use local data of temperature and moisture soil profiles to run the model. However, these data sets are scarce, restricted to some experiments and localities. Thus, the boundary condition using soil parameters obtained from soil samples collectedlocally would be the best option because it produces satisfactory results and can be easily obtained at the experimental site. The conclusions and difficulties in this work encountered duringimplementation have important implications. Firstly, it is probably a real requirement to understand better the root system on general ecossystems. This would involve, for example, more measurements of depth and distribution of the root system characteristics to validate the estimation of these parameters. Secondly, the creation of a protocol for measurements in fieldexperiments, those standardize some basic measurements such as soil samples, which could be used to estimate soil parameters to be used by models.