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• 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.