Takunda Ben

ABSTRACT

There have been challenges in groundwater prospecting especially in the Midlands Province of

Zimbabwe. Prospecting has not been accurate with frequent occurrences of dry holes for both

geophysical and traditional groundwater prospecting techniques. The study involved an

assessment of the suitability of using plant indicators for ground water prospecting in the

Midlands Province of Zimbabwe. To achieve this, indicator species were first identified and

their abundances and biometric characteristics were used to predict borehole yields and depths.

The study area is dominated by bush and tree savanna and hence it was necessary to establish

and eliminate baseline species from the study. After elimination of baseline species, five species

were identified as indicators. The relationships between indicator species’ biometric

characteristics / species abundances and borehole depths / yields were determined through

regression analysis. Identified species were Acacia burkei benth, Acacia negrecens,

Lonchocarpus capassa, Piliostigma thonningii and Sclerocarya birrea caffra. Acacia burkei

benth, Acacia negrecens and Lonchocarpus capassa were the most powerful indicators in that

order in terms of yield prediction respectively. Piliostigma thonningii and Sclerocarya birrea

caffra showed the ability to form combinations with both Acacia negrecens and Lonchocarpus

capassa but however they were not confined to any yield ranges. The biometric characteristics of

the indicator species had weak correlations with borehole depth and yields (0 < R < 0.38). The

study also showed that there exists a strong positive linear relationship between the abundance of

Acacia negrecens (R = 0.68) and the yield of boreholes. Finally, Sclerocarya birrea caffra was

discovered to also have a strong linear relationship (R = 0.78) with borehole depth. The

identified indicator species can be used for identification of ground water sites but it is not

possible to predict the yield and depth of boreholes using species’ biometric characteristics in the

study area.