Estimation of Groundwater Recharge in the Lobo Catchment (Central-Western Region of Côte d’Ivoire)

Abstract

Determination of groundwater recharge is a major challenge in areas where rainfall is generally abundant. Variability and uncertainty are inherent in the estimation of recharge, and several methods are therefore recommended for its estimation at a regional level. In this study, we evaluated several methods for estimating recharge: the web GIS-based automated hydrological analysis tool (WHAT), water table fluctuation (WTF), hydrograph analyses, a recession curve displacement method, graphical separation, and empirical formulas. The annual recharge estimated by combining direct recharge and base-flow varied from 84 mm in 2019 to 66.4 mm in 2020. The mean direct recharge was about 44 mm in 2018 and 57.3 mm in 2019, representing about 4% and 5% of the respective rainfall. In 2020, this direct recharge was 43 mm, or about 6% of rainfall, around 25% lower than in 2019. Base-flow separation methods and recession curve displacement generally gave low results, whereas modified empirical formulas gave results close to those of the WTF method and were considered more consistent and reasonable. The regression curve displacement method implemented in the United States geologic survey (USGS) RORA program was found to be unsuitable for the study area. However, the other methods presented more reasonable results and could be used to estimate groundwater recharge in the study area.

The Nationwide Water Budget Estimation in the light of the New Permeability Map of Italy

“…The aquifer recharge is a very complex process to evaluate, which is affected by many, factors: meteorological, hydrological, geological, morphological, topographical, soil type, vegetation, human, etc. Nevertheless, differently from the major part of groundwater recharge studies that have usually been done at a small-scale (i.e. focusing on a small area) or relating to particular groundwater body or particular lithology (Allocca et al 2013;Jean Olivier et al 2022), BIGBANG model is implemented to provide estimations of water balance components at macro-region or national scale, and therefore it has been possible to discard all the details of the processes and utilize a very simplified schematization (Yeh 2007;Johnson 2012). Consequently, the results of the study should be interpreted whereas these are estimates at a macro-regional scale and through a simplified model.…”

Quantitative Assessment of Water Resources: Empirical Methods and Mapping Recharge Zones: Case Study (Eastern Tunisia)

“…Chaturvedi established an empirical relationship in 1936 [5] to evaluate groundwater recharge (Re) as a function of annual rainfall (RF). This formula is applicable when precipitation exceeds 15 in/yr (Chaturvedi, 1973;Jean et al, 2022).…”

“…Consequently, the recharge percentage from precipitation will be approximately 0% RF=14 and 18% if RF equals. In this equation, the minimum limit considers factors such as runoff, soil moisture deficit, interception, and evaporative water loss (Kumar and Seethapathi, 2002;Jean et al, 2022).…”

“…In 1973, Sehgal suggested the following empirical formula [7] for estimating Re (Jean, et al, 2022).…”

“…Various empirical relationships, such as Chaturvedi, modified Chaturvedi, Sehgal, Krishna Rao, and Bhattacharya, are employed for groundwater recharge estimation. Among these, Bhattacharya has been widely utilized for its reliability in identifying suitable areas for groundwater recharge (Oke et al, 2013;Msaddek et al, 2017;Nithya et al, 2019;Ahmad et al, 2020;Andualem et al, 2021;Jean Olivier et al, 2022;Gumuła-Kawęcka et al, 2022;Msaddek et al, 2021).…”