University of Eswatini (UNESWA)
More about University of Eswatini (UNESWA), Eswatini
The Kingdom of Eswatini remains highly vulnerable to the impacts of climate change and variability. Furthermore, the country has very limited skills to research its effects on one of its important sectors, which is the water sector. The current university curricula do not offer specialization around issues of climate change and water supply, in particular, groundwater supply. In Swaziland, as in most African countries, climate change has led to overall warming and drying with disrupted precipitation patterns of the entire water cycle consequently leading to an increased frequency and intensity of droughts and floods. These extreme weather events are making water resources scarce, unpredictable, and polluted.
The negative impacts are not only on the agricultural and surface water sectors but are also likely to be considerable on the underground water sources as well. Groundwater reserves, which are an important source of water for many rural communities in Eswatini, are greatly reduced as a result of decreased rainfall intensity and concomitant increases in surface runoff. With the experiences that Eswatini has in underground water resources management, the University of Eswatini is better placed to lead Africa in research on the same. Utilizing the skills that the University of Eswatini has in Artificial Intelligence (AI) and modeling, they bring to this consortium expertise in utilizing AI in modeling underground water resources. For more information about UNESWA click here.
This consortium brings together current research advances that focus on the modeling of hydrological fluxes and water resources variables (e.g. water vapor, relative humidity, rainfall, snowfall, runoff/streamflow, soil moisture, recharge, groundwater, etc.) using AI techniques (e.g. artificial neural network, wavelet analysis, support vector machine, classification and regression trees, etc.). Programs offered are :
- Master of Science in Computer Science.
- Master of Science in Environmental Resources Management.
- PhD in Computer Science
- PhD in Environmental Science using AI.
Eswatini can also benefit from the data analytics skills from the Master of Science in Big Data that is offered by NUST, Zimbabwe. At the same time, the AI and geospatial data analysis techniques that have been perfected by UNESWA will serve to upskill and enhance the competences of NUST Zimbabwe students and staff. The objectives are to facilitate:
- Water resources modeling using AI techniques and their hybrid with other data-driven models.
- Forecasting of hydrological variables using machine learning algorithms.
- Prediction of hydrogeological variables employing hybrid models.
- Modelling storage of water in the environment through novel data-driven tools.
- Assessing changes in subsurface hydrologic components under the changing climate.
- Reducing uncertainty in the estimation of surface water as well as groundwater resources.
- Precise evaluation of hydro-hazards using advanced data-driven models.
- Understanding interactions between climate and hydrology by adopting modern statistical tools.
- Analyzing the impact of climate change on hydro-climate extremes using artificial intelligence techniques.
- Establishing linkages of water with geological, biogeochemical, atmospheric, and ecological systems using artificial intelligence techniques.
- “Big-data” applications for water resources management using artificial intelligence/machine learning tools
CONNECT WITH US:
University of Eswatini
Private Bag 4
Kwaluseni, M201, Eswatini
Tel: +268 2517-0000
Email: uneswa@localhost