Abstract:
Quantification of groundwater recharge is a crucial prerequisite for sustainable
groundwater resource management, particularly in semi-arid areas where there are large
demands for groundwater supplies. This research presents an alternative approach for
recharge estimation based on the soil water balance technique. The purpose is to
develop a model which provides a suitable balance between physical credibility and
data which realistically can be gathered.
A spreadsheet model was written based on the conceptual representation of the principal
physical processes which actually affect recharge in a semi-arid area. Alternative
procedures were included in order to represent: (a) the estimation of runoff, (b) the
inclusion of the period with predominant bare soil evaporation and (c) the accounting
for evapotranspiration following rainfall on dry soil.
The model was tested using real data from a semi-arid region (Northeast Nigeria)
making use of selected periods of days and years in order to illustrate the principal
model characteristics. The results were presented in the form of diagrams and graphs
helping to visualise the interactions between the physical components and the effect of
the additional procedures on recharge estimation.
The credibility of the model was investigated using an alternative concept of "analysis
of plausibility". This concept makes use of as wide as possible a range of quantitative
and qualitative information from the hydrological system in order to verify the
robustness of the model when extensive datasets required by conventional validation
techniques are not available. The results suggested that the modelled recharge is
physically sound and it is in line with the overall determination of recharge in semi-arid
areas by a range of methods.
The soil water balance model was utilised to explore important aspects of recharge in
semi-arid regions showing the effect of the field variability on the model's output. The
preliminary results show that the developed concept reasonably represents the inherent
field variability, thus corroborating the strength of the approach for recharge estimation
in semi-arid regions.
