Tag: water security

Update on Healthy Waters Research Projects at UWE 

Author rosieperrett | Posted on

By Rosie Perrett, Dr Connie Tulloch, and Matt Coombs 

The Healthy Waters blog is back! Our research group are currently working on three government funded research projects monitoring the health of rivers using sensors to measure various biological and physiochemical parameters. 

In 2022, no rivers in the UK were classified as having good overall health, which can be largely attributed to discharges of sewage effluent and agricultural runoff into rivers (The Rivers Trust, 2024). Collecting water quality data allows us to detect and monitor the impacts of pollution events in rivers and can inform evidence driven decision-making to improve river health and water safety.  

All three projects are using in-situ sensing technologies and spot sampling (paired with laboratory analysis) to assess UK river quality. However, each project is measuring slightly different water quality parameters according to the project aims and deliverables. 

Collecting water quality data with Chelsea fluorescence-based sensors and Xylem sondes

Development of an Innovative Intelligent Multiparameter Fluorometer to Sense the Impact of Organic Pollution on River Health 

Project partners: University of the West of England (UK academics), Chelsea Technologies (UK sensor manufacturers), The Rivers Trust (river conservation experts) 

This project is funded by Innovate UK and aims to develop and deploy a new multiparameter fluorescence-based sensor measuring organic pollution, algae (phytoplankton), and bacterial contamination. The new sensor technology will provide data on river health, for which there is currently a lack of data on since commercially available sensors predominantly measure physiochemical parameters.  

Following sensor development, prototypes will be deployed at three locations in the River Dart, collecting water quality and river health data in real time. River water samples will be collected for laboratory analysis involving: measurements of BOD5, microbial enumeration (heterotrophic bacteria and fecal indicator organisms), as well as carbon and nutrient concentrations.  

Another field trip with the Chelsea and Xylem sensors

The sensor will be low cost, making it accessible for community groups. AI and machine learning will be used to create a Water Quality Index by combining the measurement of the new parameters with additional real-time data, enabling interpretation of sensor data regarding river health. 

This new sensing technology will enable accurate, high-resolution monitoring of the impact of pollution discharges on bacterial contamination and organic pollution in rivers, improving the way we monitor and determine river health. 

MaD-OPS project – Monitoring and Detection of Organic Pollution from Sewage in rivers. 

Funded by the Natural Environment Research Council (NERC), the MaD-OPS project aims to investigate the impact of pollution from both point sources (like sewage discharges) and diffuse sources (like agricultural run-off) on river health.  

Using fluorescence-based sensors supplied by our industry partner Chelsea Technologies and multiparameter Xylem EXO sondes, we will monitor a range of physical, chemical and biological water quality parameters.  

Our sensors will be connected to custom WATR tech environmental monitoring platforms, and data will be continuously uploaded and accessed through a cloud-based system. 

This forms the basis of our sensor network to monitor river health in our demonstrator catchment – The Bidwell Brook. 

Bidwell Brook, Devon

Alongside continuous sensor data provided to us via our sensor network; we’ll also be taking regular spot samples for ground truthing. Looking into nutrient concentrations, total carbon, biochemical oxygen demand (BOD5), faecal indicators, as well as DNA extraction for microbial communities. 

By linking our data with hydrological data – provided by the Environment Agency and event duration monitoring data (EDM) – provided by South West Water, we will create a Water Quality Index using AI and machine learning. This will provide a platform for communities to assess the health of their local rivers and see the impact of pollution events in real time, empowering them to take action when necessary. 

TWIN–Waters: Management of water resources: resilience, adaptation and mitigation to hydroclimatic extreme events and management tools. 

This project is funded by the European Commision and UK Research and Innovation (UKRI) with support and collaboration from the University of Lund (Sweden), The University of The West of England (UK) and Wrocław University of Environmental and Life Sciences (Poland). 

The Project aims to integrate AI and Machine Learning with GIS and large data sets to create a digital platform for water quality monitoring. This digital platform will act as the “Digital Twin” of the water source which will be a valuable management tool. 

There are three phases to the project with UWE primarily involved in providing data from a range of novel sensors being used across other similar projects (MaD-OPS & Multiparameter Fluorometer).  

The project is currently in Phase One which aims to identify monitoring sites in each of the three countries.  At these sites, water quality sensors will be deployed to collect data which will be used in the GIS modelling alongside satellite data. 

In addition to this, each university partner will print and build 8 3D-Printable open-source microscopes designed by OpenFlexture. These microscopes will be used identification of Algae species, citizen science and public engagement events.  

3D microscopes at the Festival of Nature

UWE have seven monitoring sites across the River Dart and Bidwell Brook, from which data from sensors and traditional water quality parameters from laboratory analysis are being collected. The same sample sites are being used as the other projects within our research group as this will allow cross project data sharing, ultimately leading to a more comprehensive understanding of the catchment.  

The next stage of the project is to develop a functional model for each of the three catchments using the sensor data coupled with satellite data. This will require regularly uploading data to the digital platform for the AI and Machine Learning aspect of the model. The model will then begin to make assumptions and eventually make predictions to allow accurate water quality management. 

We’ll be posting on the Healthy Waters blog every month, with our next post being an introduction to the team.

How to measure water security?

Author Anna Jones | Posted on

Photo: Figure 1. Haitians queue for water in Carrefour-Feuilles Slum. The experiential scale-based metrics attempt to capture other sides of water (in)security, such as the burden associated with queuing for water. Photo by United Nations Photo

This blog is a summary of a published open access article: Octavianti and Staddon (2021). A review of 80 assessment tools measuring water security. WIREs Water. https://doi.org/10.1002/wat2.1516

Adapted by Dr Thanti Octavianti

There are many definitions of water security. It could simply refer to water for domestic use, such as for drinking and cooking, or it could mean water in every aspect of life, including water for the environment, water for economic development and water associated with hazards, such as floods and droughts.

These diverse conceptions also lead to different methods to measure water security. Chad Staddon and I systematically reviewed 107 publications proposing methods and tools to measure water security, and we found:

  1. There are two dominant research clusters in the field:
    • metrics that are based on the physical availability of water with measurement ranging from municipal to global scale and usually expressed in a volumetric unit. We group them as “resource-based metrics”.
    • metrics that are based on people’s experiences with water, usually measured at individual or household level and asking, for example, if one has worried about water or if one has had to change their plans because of their water situations. We group them as “experiential scale-based metrics”.

The former cluster is bigger compared with the latter, which is emerging.

  1. Both clusters are quite distinct in their characteristics. For example, resource-based metrics were mostly formulated by natural scientists and engineers. Domains of measurement vary from metrics solely focusing on freshwater resources to some with a very broad focus (to include water-related disasters, biodiversity, among others).

On the contrary, most experiential scale-based metrics have strong social science elements in them. Water supply and hygiene and their relations to well-being are the main domains being measured.

By understanding the landscape, we argue that the more local the level of measurement and the more specific water domains included, the more meaningful and actionable recommendations would be.

Finally, measuring water security is a resource-intensive process. Selecting which approach to use will be based on the purpose of the investigation and scholarly interests, and we hope this paper would be able to help researchers and practitioners make some informed choices when developing or using a water security metric.

Short bio:

Dr Thanti Octavianti is a Lecturer in Applied Geography, Department of Geography and Environmental Management, UWE Bristol. She is a social scientist with research interest in water security measurement and urban flood resilience.