Hydrology Research (Jan 2024)

A review on sources of uncertainties for groundwater recharge estimates: insight into data scarce tropical, arid, and semiarid regions

  • Tsegamlak Diriba Beyene,
  • Fasikaw Atanaw Zimale,
  • Sirak Tekleab Gebrekristos

DOI
https://doi.org/10.2166/nh.2023.221
Journal volume & issue
Vol. 55, no. 1
pp. 51 – 66

Abstract

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Successful sustainable groundwater management requires accurate information on recharge for a given aquifer system. However, recharge estimates are usually used in relative terms rather than an absolute sense. A review of available studies on groundwater recharge estimate uncertainty as well as tools for uncertainty analysis was conducted. Nonetheless, except for the handful of studies that have conducted proper uncertainty analysis, most were inclined to implement multiple methods as an indication of the range of uncertainty. The global trend indicates that considering the significant number of methods for recharge estimation, very little has been done to assess the uncertainty of each method. Therefore, more attention should be given to the individual uncertainty analysis of selected methods as much as using multiple methods recommended for investigating uncertainty. Insight from the review indicates that, when used carefully, tracer-based analysis can be effective and coupling is required for uncertainty analysis. Furthermore, spatial uncertainty due to input data could potentially be minimized by using input data from multiple sources. Better conceptualization of the hydrogeological process can reduce the uncertainty of numerical modelling. This review is limited to widely used methods and excludes uncertainty due to inappropriate method implementation and controlled experimental uncertainties. HIGHLIGHTS The review article summarizes the uncertainties in estimating recharge using widely applied methods.; The review article highlights methods for investigating the related uncertainties.; This review highlights exertions made to quantify the uncertainty of recharge estimation globally.;

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