Bibliographic Details
| Title: |
Estimation of Infiltration Parameters for Groundwater Augmentation in Cape Town, South Africa. |
| Authors: |
Mavundla, Kgomoangwato Paul, Okedi, John, Kalumba, Denis, Armitage, Neil Philip |
| Source: |
Hydrology (2306-5338); Apr2025, Vol. 12 Issue 4, p87, 43p |
| Subject Terms: |
ARTIFICIAL groundwater recharge, WATER supply, RUNOFF, HYDRAULIC conductivity, WATER table, STORMWATER infiltration |
| Abstract: |
In early 2018, Cape Town, South Africa, experienced severe water shortages during the worst drought in nearly a century (2015–2017), underscoring the need to diversify water resources, including groundwater. This study evaluated infiltration rates and hydraulic properties of three representative stormwater ponds in the Zeekoe Catchment, Cape Town, to assess their feasibility as recharge basins for transferring detained stormwater runoff into the underlying aquifer. Field infiltration data were analysed to estimate hydraulic properties, while laboratory permeability tests and material classification on 36 soil samples provided inputs for numerical modelling using HYDRUS 2-D software. Simulations estimated recharge rates and indicated wetting front movement from pond surfaces to the water table (~5.5 m depth) ranged between 15 and 140 h. The results revealed field hydraulic conductivity values of 0.3 to 19.9 cm/h, with laboratory estimates up to 103% higher due to controlled conditions. Simulated infiltration rates were 67–182% higher than field measurements, attributed to idealised assumptions. Despite these variations, ponds in the central catchment exhibited the highest infiltration rates, indicating suitability for artificial recharge. Explicit recognition of pond-specific infiltration variability significantly contributes to informed urban water security planning, enabling targeted interventions to optimise groundwater recharge initiatives. [ABSTRACT FROM AUTHOR] |
|
Copyright of Hydrology (2306-5338) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Complementary Index |