An analysis modeling of the hydrological cycle and impacts of increased atmospheric CO2 concentration in the Amazon

• Grant number: 15/03759-3
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: January 01, 2016
• End date: December 31, 2016
• Field of knowledge: Biological Sciences - Ecology - Ecosystems Ecology
• Principal Investigator: David Montenegro Lapola
• Grantee: Yuri Silva de Souza
• Host Institution: Instituto de Biociências (IB). Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Rio Claro , SP, Brazil

Abstract

Modeling systems are important in the context of environmental sciences because they can simultaneously aggregate and isolate many environmental factors, transforming them into good tools for assessing the impacts of future climate change. This paper aims at two proposals: 1- validation and calibration of a water balance model using updated input data; 2- application of this model in the Amazon forest, in line with the AmazonFACE project, seeking to improve understanding of the effects of increased CO2 in the water dynamics of this biome. The model to be used it comes to the water balance sub-model-CPTEC Potential Vegetation Model 2. The model validation and calibration of this sub-model will take place through the protocols provided by the International Land Model Benchmarking Project (I-LAMB), so it will be possible to know if the model has a consistent performance for applications that it proposes (climate change impacts on the hydrological cycle). The importance of upgrading an existing model, studying its sub-models, is to make possible the reduction of errors that it may present, approaching the representations of real-world scenarios with greater reliability. After the first rigorous evaluation of the sub-model, it will be tested its applicability in the Amazon biome in conjunction with the ongoing project Amazon-FACE, which uses eCO2 closes to 600 ppmv. The work of modeling as the hydrological cycle of the Amazon rainforest may be affected by increasing the concentration of CO2 in the future could generate preliminary hypotheses subject to tests by experiments in Amazon-FACE project.