Kirsty Gibson is a Hydrogeologist at Umvoto. Kirsty grew up in Pretoria and from a young age enjoyed nature and the outdoors. Kirsty has a BSc. (Hons) Geology from Rhodes University and a MSc Hydrogeology from the University of the Free State. Her MSc, titled “The Application of Machine Learning for Groundwater Level Prediction in the Steenkoppies Compartment of the Gauteng and North-West Dolomite Aquifer, South Africa”, contributed to a WRC report published as part of the Big Data Analytics and Transboundary Water in Southern Africa collaboration. During Kirsty’s MSc she learnt various aspects of machine learning and coding, and how they can contribute to sustainable groundwater management.
Since joining Umvoto in January 2021, Kirsty has been involved in a variety of hydrogeological activities, including groundwater protection zone delineation and vulnerability mapping, analysis and supervision of test pumping, and hydrogeological conceptual model development. Kirsty uses various software, such as R, Python, QGIS and SQL database systems for hydrogeological work and has used her programming skills to enhance Umvoto’s data analysis and management through streamlining and automation.
In addition to enjoying fieldwork, Kirsty also has a keen interest in data analysis and machine learning which she intends to further expand on. She enjoys the diverse dynamics at the Umvoto office as well as the after-work runs in Muizenberg with her colleagues.
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Groundwater Databases in South Africa
Data for Groundwater Management Groundwater systems are dynamic due to differing properties of the aquifer, … Read more
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Machine Learning For Groundwater Level Prediction
Groundwater in the Steenkoppies compartment is extensively used for agriculture practices that can potentially lead … Read more