The aim of this project is to develop a decision-support framework to assess sustainability of small-scale water treatment systems in the context of developing countries. Although many technologies are technically viable and performing, numerous community-scale systems turn out to be unsustainable after installation and fail to provide safe water over time. The study will carefully investigate the multidisciplinary factors that affect the sustainability in the context of developing countries. This information will be used to develop a multi-criteria decision analysis (MCDA) framework that will allow the sustainability assessment of real systems, thus providing a support to stakeholders in deciding the best way forward, and hopefully helping to bring us closer to universal access to safe drinking water.

Project outline

Small-scale systems for water treatment can contribute to the provision of safe water in areas not served by conventional systems, such as rural or peri-urban areas. However, this context can prove itself challenging due to availability of resources, organizational support, among other critical factors. The observed moderate success of these systems derives from some important criteria not being met. The constraints that threaten the long-term functionality of the local schemes are not necessarily related to performance of the technologies, but to a series of influential factors of environmental, technical, governmental, economic or social nature.

Hence, the evaluation of the success of these systems in providing safe water in the long term is a complex problem. Some well-established assessment methodologies such as Life Cycle Analysis or Cost-Benefit Analysis do not consider socioeconomic factors and would not provide a good sustainability evaluation in this context.

Integrating different sustainability factors such as economic, environmental and especially social aspects is crucial for providing a more comprehensive evaluation. This project will use Multi-criteria Decision Analysis (MCDA) in order to simultaneously evaluate different criteria and their quantitative and qualitative attributes.

This will allow the development of a decision support framework, built considering different factors and with the participation of stakeholders. This theoretical framework development will be combined to ongoing case studies in developing countries.

Science

This project combines water engineering with decision sciences in the context of developing countries. The evaluation of water treatment technologies in developing countries will need to consider different aspects that can be crucial to the success of a water scheme. The use of MDCA is also a growing methodology that can provide a useful alternative to integrate qualitative and quantitative criteria in complex problems. This project will integrate different aspects in one universal and holistic decision support framework, focusing on ensuring high acceptance of the decision-making process by stakeholders. The applicability of the framework will be evaluated by case studies in developing countries.

Impact

Even though access to safe drinking water and sanitation has been recognized by the United Nations as a human right, providing universal access to basic needs is still an important challenge of today, and as such was set as one of the Sustainable Development Goals (SDG) in the 2030 Agenda for Sustainable Development.

844 million people still lack basic drinking water services, with the majority living in developing countries, where investing in small-scale water systems can be the only option to provide safe water to a community. The sustainability of such systems is crucial since their failure represents waste of resources and more importantly a step back in terms of quality of life and public health.

This project will help to provide information regarding the sustainability of small-scale systems in developing countries and deliver a tool with the potential to help decision-makers choose the best alternative for communities in developing countries.

This is the PhD project of Juliana Marcal, funded by WISE CDT. The project is supervised by Dr Junjie Shen, Professor Jan Hofman, Professor Julie Barnett and Dr Haibao Wen.