EGU2020-10954
https://doi.org/10.5194/egusphere-egu2020-10954
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Monitoring and predicting water quality for smart urban water infrastructure

Elisa Coraggio1, Dawei Han1, Theo Tryfonas1, and Weiru Liu2
Elisa Coraggio et al.
  • 1Civil Engineering Department, University of Bristol, Bristol, BS8 1TR, UK
  • 2Computer Science Department, University of Bristol, Bristol, BS8 1UB, UK

Water resources management is a delicate, complex and challenging task. It involves monitoring quality, quantity, timing and distribution of water in order to meet the needs of the population’s usage demand. Nowadays these decisions have to be made in a continuously evolving landscape where quantity and quality of water resources change in time with uncertainty.

Throughout history, access to clean water has always been a huge desire from urban settlements. People built towns and villages close to water sources. In most cases, streams brought clean water in and washed away polluted water. Nowadays the largest strains on water quality typically occur within urban areas, with degradation coming from point and diffuse sources of pollutants and alteration of natural flow through built-up areas.

Municipalities are acting to reduce the impact of climate change on existing cities and meet the needs of the growing urban population. In many places around the world costal flood defences were built involving construction of barriers that lock the tide and keep the water coming from in-land rivers creating reservoirs close to the shore.

These man-made barriers stop the natural cleaning action of the tide on transitional waters. This causes severe water quality problems like eutrophication and high levels of bacteria. On the positive side, these water reservoirs are used as recreational water, drinking water, agricultural water. As many more people are moving to live in urban areas, its overall demand for clean water and discharge of polluted water is constantly growing. Hence monitoring and foreseeing water quality in these urban surface waters is fundamental in order to be able to meet the water demand in future scenarios.

Many cities have already successfully implemented smart water technologies in many types of the water infrastructures. Monitoring water quality has always been a challenging and costly task. It has been so far the most difficult water characteristic to monitor remotely in real time. Lack of high frequency and accurate data has always been one of the main challenges. Today, using information and communication technologies (ICT) is possible to set up a real time water quality monitoring system that will allow to deepen the understanding of water quality dynamics leading to a better management of urban water resources.

A case study will be presented where a real time water quality monitoring system for the surface water of Bristol Floating Harbour has been deployed in the UK and water quality data have been analysed using artificial intelligence algorithms in order to understand the link between ambient weather data (i.e., precipitation, temperature, solar radiation, wind, etc.) and surface water pollution. Preliminary results of a water quality prediction model will also be presented showing the capabilities of predicting water quality as a new tool in municipality’s decision-making processes and water resources management.

How to cite: Coraggio, E., Han, D., Tryfonas, T., and Liu, W.: Monitoring and predicting water quality for smart urban water infrastructure, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10954, https://doi.org/10.5194/egusphere-egu2020-10954, 2020

This abstract will not be presented.