TITLE:
Using River Altitude Determined from a SRTM DEM to Estimate Groundwater Levels of the Tokwe and Mutirikwi Watersheds in Zimbabwe
AUTHORS:
David Chikodzi, Godfrey Mutowo
KEYWORDS:
SRTM DEM, Groundwater Level, Kriging Interpolation, River Altitude
JOURNAL NAME:
Journal of Geographic Information System,
Vol.8 No.1,
February
22,
2016
ABSTRACT: Groundwater resources
provide most of the domestic water supply in rural Zimbabwe and support poverty
reduction through irrigation facilities. Most agricultural and environmental
plans need water table depth analysis as an input in designing best management
strategies. There are limited direct measurements of groundwater levels in
Zimbabwe due to high costs and the limited human expertise. The study is aimed
at coming up with a proof of concept that altitude of rivers as determined by
an SRTM digital elevation model can be used to estimate the levels of
groundwater in parts of Mutirikwi and Runde sub catchments of southern
Zimbabwe. The study also maps the groundwater levels of the area as determined
by river altitude from the digital elevation model. Firstly, the groundwater
levels for nine boreholes are measured. Secondly, the altitude of a river bed
nearest to each borehole site is extracted from a digital elevation model.
Finally, the Spearman’s correlation coefficient is used to determine the nature
and strength of the relationship between the two variables. Linear regression
analysis was also used to obtain the predictive equation of the relationship
and its coefficient of determination. After the relationship between
groundwater and river altitude is established, 9 new random points of river
altitude are generated across the study area interpolated using kriging
interpolation to give the estimated altitude of river altitude. The altitude of
groundwater is then determined by running the predictive equation Y = 0.8736 *
X + 0.852 obtained from regression analysis. The depth to groundwater level of
area is obtained by subtracting the determined groundwater altitude from the
SRTM DEM. The results show strong positive and statistically significant (ρ= 0.000,α= 0.01) correlation coefficient of
0.971 between measured groundwater levels and altitude of rivers. The
regression model shows a coefficient of determination (r2) of 0.975. The
research therefore determines that altitude of rivers and use of geostatistics
can produce physically plausible estimates of groundwater levels in the study
area.