Details of Grant 

EPSRC Reference:	EP/P029221/1
Title:	Flood Prediction using real time sensing Emergency Water Information Networks over mobile phone networks and WiFi (EWIN)
Principal Investigator:	Edwards, Dr RM
Other Investigators:	Lepper, Dr PA Rangel Licea, Dr V V Pattison, Dr I Aquino, Dr R Mendoza Cano, Dr O Lopez de la Cruz, Dr J
Researcher Co-Investigators:
Project Partners:	Dynamic Flow Technology Ltd (DFTL) Siteldi
Department:	Electronic, Electrical & Systems Enginee
Organisation:	Loughborough University
Scheme:	GCRF (EPSRC)
Starts:	01 May 2017	Ends:	30 April 2021	Value (£):	1,485,560
EPSRC Research Topic Classifications:	Science and Technology Studies Water Engineering
EPSRC Industrial Sector Classifications:	Environment Water
Related Grants:
Panel History:	Panel Date Panel Name Outcome 17 Mar 2017 EPSRC GCRF 1 Meeting A - 17 March 2017 Announced
Summary on Grant Application Form
We are working on ways to monitor flooding in real time using remote water sensing over cellular phone systems. With the predicted impacts of climate change flooding will be a global problem. Minutes of advance warning are important and modern flood warning systems are critical for a country to protect its people and develop and grow its towns and cities. Flooding is the most serious of natural disasters mankind has to cope with in terms of loss of life and the long term effects of flooding have severely adverse social consequences. Unlike the UK that has a mature flood defence system, many countries have not been able to afford the technology and have poor response to flooding. However, many developing countries do now have access to modern cellular phone networks in their towns and cities. So in this project we will discover how to use mobile phone networks combined with WiFi to help countries tackle climate change. Two teams of researchers from the UK and Mexico, supported by small companies with experts in the fields of water engineering and embedded electronics have come to together to investigate how real time flood monitoring can be done over modern phone systems to provide modern water engineering infrastructure in a cost effective way to quickly make countries vulnerable to flooding more resilient to this most serious of natural disasters. To improve flood prediction several areas of research need to be addressed. Concisely, the data for real time flood prediction needs be sensed in the right place and at the right time, transmitted in harsh conditions, fused in the cloud and used to make reliable flood prediction models. our research addresses each of these areas using UK expertise in Water Engineering and Radio Communications to complement Mexican knowledge of Water Engineering, Data Networks and Enterprise. At the end of the project we will have measured parts of and modelled a complete flood prediction network for Mexico and in the process understood how water behaves before, during and after flooding. Mexico is a country of extremes with a dry season where hardly any rain falls and rainy season with volumes of water in rivers unseen in the UK. For the UK climate change is predicted to mean more dynamic and intensive large scale weather effects so there are significant benefits the United Kingdom as well as Mexico and many other countries. Combined with background research, prototyping of sensors packages and waterway modelling, our teams will be conducting a series of highly targeted field trials - small scale in the UK where rivers and lakes and relatively predictable and medium scale in Mexico where we will seek flood events to be studied in real time. Two new exciting water sensing technologies, one that uses Doppler radar and another that using similar techniques to face recognition will be used for the first time in this work to detect the water conditions prior and during a flood event. The two techniques are special because they do not need to be in the water and are therefore much harder to wash away than traditional sensors. We intend to use a portable system that can be deployed quickly in areas that may flood to give much needed advanced warning and monitor water levels during the time before the water recedes.
Key Findings
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Organisation Website:	http://www.lboro.ac.uk