Carolina Rogelis Prada

Biography

Maria Carolina Rogelis was born in Bogota, Colombia. She possesses a BSc. in Civil Engineering (1999) from The Universidad Nacional de Colombia, an MEng. Water Resources Management (2001) from Los Andes University (Bogota – Colombia) and an MSc. Hydraulic Engineering – River basin development (with distinction, 2004) from UNESCO-IHE Delft, the Netherlands. In 2009 she was accepted as PhD candidate at UNESCO-IHE Delft in the project Operational Flood Forecasting, Warning and Response for Multi-Scale Flood Risks in Developing Cities. From 2005 to 2011 Mrs. Rogelis worked in the development and operation of flood forcasting systems as well as flood risk assessment in the Direccion de Prevencion y Atencion de Emergencias de Bogota and from October 2011 she has been working as consultant for the World Bank.

Publications

• C. Rogelis, M. Werner (2012), Spatial interpolation for real time rainfall field estimation in areas with complex topography. (Under review).

Topic

Summary of research

Flood warning and forecasting systems can help to reduce the effects of flooding by allowing people to be evacuated from areas at risk, and to move vehicles and personal possessions to safety. With sufficient warning, temporary defenses can also be installed, and river and tidal control structures operated to mitigate the effects of flooding. The efficiency of flood warning in managing risks is high as indicated by the United Nations Institute for Strategic Disaster Response; --the overall number of deaths due to all natural disasters is decreasing, and this has been attributed to investing in early warning and preparedness programs. The operation of a flood warning and response system is the most effective method for reducing the risk of loss of life and economic losses.

Developing cities represent a challenge for flood early warning, taking into account the persistent lack of data, limited resources and often complex climatic, hydrologic and hydraulic conditions. Furthermore, efficient decision support and targeted dissemination of information are important needs, in such a way that warnings derived from these systems can properly be understood to provide real protection to those at risk.

This research is aimed at developing and demonstrating methods for reliable operational forecasting of flood hazards in developing cities, considering hazards at different spatial and temporal scales. Taking into account the typical poor data environment of developing cities, the methods proposed should be reliable and robust to data scarcity and anthropogenic and long term climatic changes. A key issue is looking at providing adequate tools to decision makers that allow proper interpretation of the result of models to effectively protect those at risk. Furthermore, the methods proposed must take into account the highly dynamic nature of flood risk.

The research started from a hazard and risk framework that must be established for effective implementation of flood early warning, and will address the components of flood early warning systems, investigating methods that provide reliability at the operational level at different spatial and temporal scales. Uncertainty and verification techniques will be used as the main tools for understanding and effectively advancing insight in the reliability of information that can be provided to decision makers and communities.

To this end each of the components of a flood early warning system will be addressed, looking for methods to reduce uncertainty and to interpret this uncertainty under an operational environment in a study case for which Bogota (Colombia) was chosen. The choice of this city is due to the variety of its hydrography and meteorological complexity, and above all because it represents the typical case of a developing city where urban dynamics and natural variability mix to create a complex flood risk scenario, under lack of data.

Funding Source: UPARF