Notícia
Palestra internacional promovida pelo Programa de Pós-graduação em Sensoriamento Remoto (PPG-SER)
São José dos Campos-SP, 17 de outubro de 2019
Data: 21/10/2019 – segunda-feira
Horário: 14h00
Local: Auditório do LabGeo- INPE/SJCampos
Title: Modeling hydrological dynamics in floodplains and exploring impacts of extreme events on the riverside population
Summary:
The occurrence of extreme events of flood and drought in the Amazon River basin has been growing in the last decade and influences the ecological dynamics of the floodplains and the riverside population which needs to adapt to these changes. Some recent results obtained from hydrological and hydrodynamic modeling of Curuai and Janauacá floodplains will be presented. In particular an analysis of the latest flood events (2009, 2012, 2014) in terms of flood pattern (extent / duration of flood) will be presented. The results show that flood amplitude is not necessarily associated with longer flood duration. From these considerations it will be presented a preliminary analysis of the adequacy between perceptions of the actors of the river regime changes and the potential consequences for the activities carried out by the riverside population (mainly the livestock activity).
Dr Marie-Paule Bonnet is hydrologist specialized in hydrological and biogeochemistry modeling of tropical wetlands using advanced remote sensing techniques such as satellite altimetry. She has done researches in an interdisciplinary and international environment looking at key issues impacting sustainability and development in South countries and always in contact with local to international stakeholders. She uses several types of models from differential equations systems to agent-based models in function of the key issue under study. At present she coordinates the BONDS – Balancing biOdiversity conservatioN with Development in Amazon wetlandS, an interdisciplinary project involving an international research team working with a wide range of tools spanning from fish DNA to satellite data.
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