With a focus on the development of data structures and mathematical models, MAD will explore new digitalisation opportunities within the water sector.
Over the past few years, the University of Cape Town (UCT) and the University of Kwa-Zulu Natal (KZN) have been creating mathematical models that are used as engineering tools for decision making in the design and operation of wastewater treatment systems. The universities have created significant outputs in terms of research that are known for internationally, but there has been very little uptake from stakeholders within the water sector. David Ikumi, senior lecturer at UCT says that the MAD division is aimed at bridging the gap between researchers and stakeholders within the water sector and will also work to improve representation from Africa with regard to data and modelling in the industry.“Water cuts across many different disciplines and data is collected from farmers and biotechnologists to civil engineers and bankers. Data goes hand in hand with modelling as models are mechanisms generate data. Therefore, MAD would also focus on effective methods of collecting data and data management.”
Objectives:- Demystify modelling and data science
- Improve accessibility to tools, data and expertise
- Raise the profile of modelling and data science practitioners
- Provide a platform for showcasing output
- Establish a network of data sources
- Foster discipline cross pollination
- Inform and support end users
- Support research and development
- The organisation of workshops and seminars to promote interaction, exchange of ideas and raising awareness around data and modelling, amongst academics and practitioners of the water and sanitation sector. Topics will include:
- Presentation of new unit processes or integrated system-wide models
- Conversion of process models into simpler user-friendly tools
- Identification of critical water analysis needs
- Improvement of water quality laboratory methods
- The development of education and training in modelling and data management for practicing wastewater treatment engineers through providing continuous professional development courses and training programmes.
- Design and establishment of a water and sanitation laboratory network. Within the network, a user-friendly protocol shall be developed for the collection, storage and, where possible, publication, of data in a centralised open access platform.
- Development of think tanks (or working groups) and online forums, involving collaborative efforts between stakeholders to pursue different topics and projects that could impact the development of water and sanitation sector (bioprocess modelling, digital twin development, integrated modelling, evaluative techniques, food-water- energy nexus, tracking of micropollutants).