Research Project: Reduction of hydrological uncertainties in embedded catchment through the forecasting of recursive flow and the use of Volunteered Geographic Information
Abstract: The traditional approach of hydrological forecasting in real time considers that the input, state and output processes of the hydrological model are subject to dynamic uncertainties that are updated continuously. Decisions have to be taken in real time considering not only uncertainty but also the perception of vulnerable communities. Precisely, the community has to play a major role in the management of natural disasters as they are directly affected. Therefore, the work focuses on flood forecasting, using both official data and data provided for by the population in order to reduce the uncertainty in forecasting floods. Additionally, it is intended that the method can be implemented in real-time to different catchments in Brazil.
Researcher: Camilo Ernesto Restrepo Estrada
Category: PhD Research Project
Scholarship: Coordination for the Improvement of Higher Education Personnel (CAPES)