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Vadose zone classification and aquifer vulnerability of the Molototsi and Middle Letaba Quaternary Catchments, Limpopo Province, South Africa

The aquifer vulnerability of the Molototsi (B81G) and Middle Letaba (B82D) quaternary catchments was assessed to determine the influence of the vadose zone on the groundwater regime. Anecdotal evidence indicated that the aquifers may be vulnerable to pollution. The aquifer vulnerability was assessed by developing a new method RDSS. The RDSS method was developed by combining relevant vulnerability parameters of DRASTIC, GOD, EPIK, SEEPAGE, COP and SINTACS. RDSS evaluates the vadose zone as a pathway for pollutants by using the following four parameters namely: Recharge, Depth to water table, Soil type and Slope. Recharge was estimated using the Chloride-mass balance method. Depth to water table was measured in the field using a dipmeter. For inaccessible boreholes, data was requested from Groundwater Project Consulting Company. The seepage behaviour (soil type) was determined using parameters such as hydraulic conductivity, infiltration and percolation. Percolation and hydraulic conductivity was determined by undertaking percolation tests in accordance with SABS 0252-2:1993. Infiltration was determined using the double ring infiltrometer. Slopes were determined from the digital elevation method using ArcGIS software. High recharge was revealed in the lower parts of both B81G and B82D. Shallow depth to water level was revealed on the upper part of B82D and extended towards the lower part of B81G. Soil type relates to saturated vertical hydraulic conductivity, which was rated to be high in the northeast of B81G. Gentle (high influence due to preferential infiltration to runoff) slopes extend from the south towards the northern parts of both B81G and B82D. The four parameters (recharge, depth to water table, soil type, and slope) were overlaid using Weighted Sum, Weighted Overlay and Raster Calculator to produce the final vulnerability map. When using Weighted Overlay and Weighted Sum, rasters were given different percentages of influence in different scenarios. The Weighted Overlay tool inputs multiple rasters and sets all weights equal to 100%. The Weighted Sum tool inputs multiple rasters and sets all weight equal to 1.0. When using the Raster Calculator, rasters were evaluated by being added together without multiplying by the percentage of influence. The results obtained are discussed in detail with reference to the degree of vulnerability of these two densely populated rural areas. / Dissertation (MSc)--University of Pretoria, 2013. / Geology / unrestricted

Identiferoai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:up/oai:repository.up.ac.za:2263/24856
Date21 May 2013
CreatorsMakonto, Olma Tsakani
ContributorsVan Wyk, Yazeed, olma@webmail.co.za, Dippenaar, Matthys Alois
Source SetsSouth African National ETD Portal
Detected LanguageEnglish
TypeDissertation
Rights© 2013 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria

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