Public Funding for Ambiental Technical Solutions Limited

Floods are the most common natural disaster and the leading cause of natural disaster fatalities worldwide. There were 539,811 deaths (range: 510,941 to 568,680), 361,974 injuries and 2,821,895,005 people affected by floods between 1980 and 2009 (Source: PLOS). Globally, economic losses due to flooding increased from roughly US$7 billion per year in the 1980s to US$24 billion per year in 2001-11 (adjusted for inflation). Flood forecasting is one of the most challenging and difficult problems in hydrology. It is also one of the most important problems in hydrology due to its critical contribution in reducing economic and human damages. In many regions of the world, flood forecasting is one of the few feasible options to manage floods. Reliability of forecasts has increased in recent years due to the integration of meteorological and hydrological modelling capabilities, improvements in data collection through satellite observations, and advancements in knowledge and algorithms for analysis and communication of uncertainties. However, scalability of flood forecasting technologies is still limited by the time and resources it takes to calibrate (or tune) parameters in hydrological models such that the forecasts are accurate. This project aims to address this question of scalability by utilising the recent advancements in AI and Machine Learning along with the wealth of data now available to automate the process of calibration. We will use the probabilistic programming approach which enables data, expert human knowledge and machine learning to work together to provide optimal, rigorous and reproducible automatic calibrations. Achieving an automatic Machine Learning calibration of hydrological models would remove the current bottleneck, enabling faster and more accurate flood forecasts. This will permit more flood forecasts over wider areas, all of which leads to less economic damage and a reduction in the risk and negative impact that flooding can bring to peoples' lives.

A consortium of flood risk modelling company Ambiental and the geoscience research organisation British Geological Survey are embarking on a project that seeks to prove a new computer modelling technique which better represents the role of groundwater (water flowing underground) during flood events. Flooding can occur when the groundwater table exceeds the ground surface, but a high water table can also exacerbate flooding from heavy rainfall. Flooding can also occur in urban areas behind flood defences where groundwater is forced through the rock by high river levels. Successful completion of this project will pave the way to a new flood modelling framework which will allow us to clarify the level of risk properties are facing from this phenomena (which occurred throughout much of the south-west and Thames valley flooding of winter 2013-14). There are a multitude of benefits, including new insight when planning flood defences, better preparedness when preparing for impending floods and improved knowledge about the actual level of risk in ‘high-susceptibility’ areas.

Awaiting Public Project Summary

Awaiting Public Project Summary

Awaiting Public Project Summary

Awaiting Public Project Summary

Awaiting Public Project Summary

Awaiting Public Project Summary

Awaiting Public Project Summary

Awaiting Public Project Summary

Awaiting Public Project Summary

Awaiting Public Project Summary

Awaiting Public Project Summary

Awaiting Public Project Summary

Awaiting Public Project Summary

Awaiting Public Project Summary

Awaiting Public Project Summary

Awaiting Public Project Summary

Awaiting Public Project Summary

A consortium of flood risk modelling company Ambiental and the British Geological Survey are embarking on a feasibility study that seeks to prove a new modelling technique which better represents the role of groundwater during flood events. Flooding can occur when the groundwater table exceed ground surface, but a high water table can also exacerbate flooding from heavy rainfall. Flooding can also occur in urban areas behind flood defences where groundwater is forced through the soil by high river levels. Successful completion of this project will pave the way to a new flood modelling framework which will allow us to clarify the level of risk properties are facing from this phenomena (which occurred throughout much of the south-west and Thames valley flooding of winter 2013-14). There are a multitude of benefits, including new insight when planning flood defences, better preparedness when preparing for impending floods and improved knowledge about the actual level of risk in ‘high-susceptibility’ areas.

This project will bring in selected Earth Observation imagery providers and customers. The technology idea – called Floodscape - involves deployment of a new generation of cloud piercing satellites, image processing technology, high performance computing and internet-based digital mapping with the purpose of improving post-event flood response, and insurance loss estimation internationally.