Accurate characterization of aquifers remains challenging for large-scale systems because of the spatial heterogeneity of hydraulic properties and temporal variability of hydrologic inputs. This study highlights the importance of integrating geological, hydrogeological and geophysical approaches to characterize an aquifer and evaluate groundwater productivity. Data from geological maps, drill logs, a pumping test, vertical electrical soundings (VES) and different field hydrogeological studies were combined and applied to a heavily extracted aquifer system—Lake Haramaya watershed, Ethiopia. From the geological characterization, the aquifer was found to be a single heterogeneous and anisotropic unconfined unit. Significant differences were found between the three-dimensional geological models of the aquifer developed from the drill logs and VES data; the VES data were likely affected by moisture content. The pumping-test and VES data were combined to estimate transmissivity (T; 126.5 ± 25.8 m2/day) and hydraulic conductivity (K; 4.1 ± 1.0 m/day). This combined use allowed for a reduction in uncertainty (40.1% for T and 33.3% for K) compared with values estimated from the VES data alone. The combined approach also allowed for much greater spatial coverage and a higher resolution characterization of the aquifer. The available volume of groundwater resource in the system was estimated at ~0.62 ± 0.09 km3. The groundwater extraction rate was ~30,120 m3/day, approximately double the estimated sustainable yield of the aquifer (15,720 m3/day). This showed that the current exploitation rate could exhaust groundwater resources in 27–32 years and should be reduced by 50% to ensure sustainability of the groundwater resource.
CITATION STYLE
Shishaye, H. A., Tait, D. R., Befus, K. M., & Maher, D. T. (2019). An integrated approach for aquifer characterization and groundwater productivity evaluation in the Lake Haramaya watershed, Ethiopia. Hydrogeology Journal, 27(6), 2121–2136. https://doi.org/10.1007/s10040-019-01956-7
Mendeley helps you to discover research relevant for your work.