Reducing flood loss - A data-assimilation framework for improving forecasting capability in sparsely gauged regions. Floods are the biggest and severest natural disaster we face year after year. Furthermore, there has been little improvement in our capability to prevent flood damage over past decades. This research proposes a paradigm shift in the way flood forecasting, warning and evacuation proceeds, using 21st century technologies for collecting and incorporating flood related data into exist ....Reducing flood loss - A data-assimilation framework for improving forecasting capability in sparsely gauged regions. Floods are the biggest and severest natural disaster we face year after year. Furthermore, there has been little improvement in our capability to prevent flood damage over past decades. This research proposes a paradigm shift in the way flood forecasting, warning and evacuation proceeds, using 21st century technologies for collecting and incorporating flood related data into existing modelling platforms. It is argued that assimilating real-time satellite soil moisture data into flood models can increase accuracy manifold, even if the images are uncertain. The understanding gained in course of the proposed project has the potential to significantly reduce the damage caused year after year, especially in the data poor regions of the world.Read moreRead less
A real-time modelling of crowd dynamics for disaster prevention. This project aims to develop methods and technologies to enable urban planners to design infrastructures to ensure public safety in emergency situations and to enable emergency management to optimise effective response plans. Rapid population growth creates major challenges for urban management, which has a responsibility to ensure the safety of citizens in the case of emergencies. This project aims to develop a methodology to stud ....A real-time modelling of crowd dynamics for disaster prevention. This project aims to develop methods and technologies to enable urban planners to design infrastructures to ensure public safety in emergency situations and to enable emergency management to optimise effective response plans. Rapid population growth creates major challenges for urban management, which has a responsibility to ensure the safety of citizens in the case of emergencies. This project aims to develop a methodology to study pedestrian crowd dynamics under panic or extreme emergency conditions, using innovative experimental approaches with new multi-scale online simulation methods and optimisation techniques. The resultant methodology would support planning and prediction of pedestrian crowd movements based on data from past events as well as adaptive planning for live events as they unfold.Read moreRead less