Much has been done and is still being done regarding the study of transboundary aquifers. Organizations such as UNESCO and OTCA have made great efforts in studying the worldwide situation. Such efforts have resulted in improving the knowledge about these aquifers and their complex relationship with water resources, society, ecology and politics. However, there are areas where remoteness hampers gaining knowledge and developing studies, such as in the western Amazon region. From 2011 to 2013, Brazilian researchers from UFRJ, working together with Spanish specialists from UPC, gathered and synthetized geological and hydrogeological data on western Amazon, in South America, which a transboundary multilayer aquifer. Data was integrated into a Geographical Information System (GIS) and a Visual- MODFLOW-3D simplified numerical model was constructed. The about 2.7·106 km2 Tikuna Aquifer conceptual flow system was identified and preliminary characterized. It extends from the Subandean Amazon area, where recharge is produced in rainy areas and probably by infiltration of melt glaciers waters. Groundwater flows through Cretaceous layers, attaining depths over 2 km. Groundwater partially outflow in some points of the Peruvian basins of Marañón and Putumayo, according to the numerical model. Results explain the evidences from fieldwork. Grundwater partially flows to the Brazilian territory to finally outflow and recharge the Alter do Chão aquifer, which is the most known subunit of the Amazon Aquifer System. The Tikuna aquifer boundaries were identified and stratigraphic data of the seven sedimentary basins that form this aquifer could be merged to define the aquifer. Hydrochemical data were also used for a better understanding of groundwater characteristics. The initial step has been done and new extension are in course, but further studies are needed and have been identified, especially considering the relationships between surface and groundwater in the complex Amazonian ecosystem and the future challenges posed by climate variability and the effects of the possible climate change previsions.