Simulating Human-Flood Interactions for Flood Risk Management using Agent-Based Modelling
Integrated flood risk management involves a large portfolio of options for mitigating risks that include hard (engineered methods such as dams and floodways) and soft structural (nature-based such as wetland protection, upper watershed restoration and rain gardens), non-structural, and recovery responses. An example of non-structural responses is flood warnings, emergency services supported by individual and collective actions and the use of mitigation and resilience measures. Agent-based model (ABM) approaches allow for the representation of social interaction in human and natural domains and for the investigation of the emergence of adaptive, collective responses to changing environmental management practices. Agent-Based Modelling is applied in a variety of contexts; from physical modelling, socio-ecological modelling and social behaviour modelling, to more complex modelling such as coupled human and natural systems or environmental modelling.
In this project, I developed a hydraulic model and an Agent-Based Model (ABM) based on geospatial information, disaster psychology and decision-making theories for simulating the human-flood interaction to evaluate the effectiveness of flood risk communication systems, social vulnerability and determining the critical factors that govern the effectiveness of the evacuation process due to extreme flood events, considering the road network, the information dissemination among people, local information centres and the lead-time of the early warning system.
This project was the thesis from my MSc. Degree at Technische Universität Dresden, Germany.
Javed Ali
Doctoral Researcher
My research involves multi-hazards risk assessment and analyzing compound climate and weather extreme events to better understand their interrelationships at different spatial and temporal scales as well as assessing their corresponding socio-economic impacts using machine learning and statistical methods.