Adele Young

Adele is from the twin island of Trinidad and Tobago. She is now a fulltime PhD fellow in the Netherlands at IHE Delft with the Flood Resilience Group and at the Delft Technical University (TUDelft) in the Civil Engineering and Geosciences faculty. Adele holds an MSc. in Water Science and Engineering with a specialisation in Hydraulic Engineering and River Basin Development from IHE Delft and an MSc. in Civil and Environmental Engineering from the University of the West Indies, St Augustine. Prior to returning to further her studies, she practised for over eight years as a civil engineer on several flood hydrological studies and drainage infrastructure design and construction management projects in Trinidad and Tobago. Her past work experience combined with her current research has made her interested in alternative solutions to address flood risk management challenges.

Adele is also an active member of the Water Youth Network's Disaster Risk Reduction thematic group and co-coordinator of the Early Warning systems Young Professionals group; connecting young professionals across disciplines in EWS. As a volunteer, she has hosted and convened young professional networking sessions at Europan Geo-Science Union (EGU) Conference, early warning system-focused sessions at Multi-Hazard Early Warnings System International Conference (MHEWS-IC), Understanding Risk and COP 26.

As of 2021, Adele holds the position of Chair in IHE Delft's PhD Association Board (PAB).

With the risk of pluvial flooding on the rise as more cities are challenged by a changing climate and local drivers: increased urbanisation and inadequate sewer systems. Sustainable flood risk management requires a hybrid of structural and non-structural measures to ensure water hazard resilient cities. In this regard, flood forecasting and early warning systems have been proposed as a “low regret” measure to reduce flood risk and increase preparedness through forecast-based actions. Nevertheless, many cities do not have the capabilities (data-scarce regions) to produce high-quality rainfall forecasts and well-calibrated flood forecasts (timing, water levels, extent and impact). As a result, there is a cascading effect on the ability to make and provide good reliable decisions given the uncertainty in the forecast or inaccuracy in the input data. For example, decisions in anticipatory flood management (to start pumping or not) become problematic given its dependence on the knowledge generated from uncertain data and the consequences of an incorrect prediction and/or action.

Probabilistic forecast “ knowledge” is beneficial in quantifying uncertainty and has been hailed as a means to support decision making but there is no one consensus on the most suitable and effective way to incorporate them into the decision-making framework. However, to what extent do inherent spatiotemporal inaccuracies influence probabilities and thus the resultant decision has not been considered especially in data scare regions. In this regard, the proposed research will focus on providing understanding on how the influence of the varying degrees of input data, particularly forecast rainfall spatial and temporal distributions will ultimately affect the ability to make decisions.

The research will be carried out in the coastal city of Alexandria in Egypt which experiences flooding due to extreme precipitation during the winter months. Alexandria is a data-scarce region with limited availability of rainfall gauges, high-resolution precipitation forecast and data to build flood forecast models. Activities include developing a Weather Research and Forecasting (WRF) model, an urban hydrodynamic model and a probabilistic decision model for Alexandria city. The objective of this research is not to make forecasts more accurate but rather to highlight the interdependences of the flood forecast and decision-making chain in Alexandria in order to address what decision can be made given the quality of forecast. The success of such an approach will support robust anticipatory forecast-based decision-making in Alexandria and other data-scarce regions given limitations in high-resolution data availability while increasing preparedness and strengthening resilience against future extreme events.

A complete list of publications can be found in ResearchGate.

Living with floods challenge - Nosso mural de cheias. Collaborate with HKV on an idea to raise awareness of flood risk and preparedness in vulnerable peri-urban communities in Mozambique. The idea called "Nosso mural de cheias" means "Our Floor Mural' in Portuguese. More information at https://www.facebook.com/nossomuraldecheias
Convener European Geoscience Union (EGU) 2021 short course on An interdisciplinary approach to Forecasting and Early Warning Systems https://meetingorganizer.copernicus.org/EGU21/session/38934
Crowdsourcing for improving pluvial flood forecast and decision making. Presented at the Caribbean Water and Wastewater (CWWA) Virtual Conference 2020. My presentation proposed the use of crowdsourced data and machine learning methods to improve pluvial flood forecasting in the city of Port of Spain, Trinidad and Tobago. Video can be viewed here.
Webinar: Managing flood risk in semi-arid data scarce regions, 2018. Webinar can be viewed here.