Improvement of the hydrology-soil relationship in a vegetation model based on functional attributes

• Grant number: 19/13173-7
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: August 01, 2019
• End date: July 31, 2020
• Field of knowledge: Biological Sciences - Ecology - Ecosystems Ecology
• Principal Investigator: David Montenegro Lapola
• Grantee: Gabriel Banstarck Marandola
• Host Institution: Centro de Pesquisas Meteorológicas e Climáticas Aplicadas à Agricultura (CEPAGRI). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 15/02537-7 - AmazonFACE/ME: the Amazon-FACE Model-Experiment integration project - the role of biodiversity and climate feedbacks, AP.PFPMCG.JP

Abstract

The development of vegetation models that represent edaphic patterns and their relations with the hydrological cycle in a more reliable way is essential for the study of the impacts of climate change in the terrestrial ecosystems, especially in regions where the hydrological cycle impacts go beyond its own area as the Amazon basin. Therefore, this proposal intend to improve the representation of the hydrological cycle in the trait-based vegetation model CAETÊ (Carbon and Ecosystem functional Trait Evaluation model). For such upgrade, the soil textures of the entire globe will be included through a reference map, in addition to the inclusion of multiple soil layers. With a satisfactory simulation of the soil layers, the functional traits may be explored through the model in different manners, which can lead to a more accurate vegetation representation. Posteriorly, a drought sensibility analysis will be realized, reducing precipitation by 50%, in which it will be possible to compare the version developed with previous and experimental data through variables such as NPP, GPP, biomass, soil water and evapotranspiration.