Computation of carbon and water cycles in forest ecosystems from a biogeochemical model with remotely sensed data

This work is intended to test and to evaluate how well a regional biogeochemical model is able to represent the major processes of the hydrologic and carbon cycles of ecosystems of coniferous, growing up in three areas with different climates in Brazil. The model uses Leaf Area Index, LAI, as the main input variable. LAI is generally accepted as the single most important parameter characterizing the exchange of mass and energy in forested areas. It has been demonstrated that LAI can be estimated from remotely sensed data, on the basis of the correlation between this vegetation structure parameter and vegetation index such as NDVI. Radar data potential remains to be further investigated. Simulation of real world LAI and sensitivity analysis on some critical parameters were used to test the suitability of the model to represent the processes involved. Patterns of vegetation that should be tied to variations on LAI were found through digital image manipulation. The results demonstrated that the model was able to show the relative differences for both water and carbon cycles associated with the three selected test Sites. Also, the model was capable of depict efficiently the interaction between climatic parameters and the biophysical processes occurring in the selected forest ecosystem The follow up is to fit the model with independent measurements of heat fluxes above the canopy and to validate it against measurements of net primary production and hydrologic variables. The results obtained from digital classification suggest that LAI values are homogeneous in all test sites. Then, the use of a unique regional value within the simulations realized is felt to be valid.