Aquifers productivity in the Pan-African context

Arétouyap, Zakari; Nouayou, Robert; Philippe, Njandjocknouck; Asfahani, Jamal

doi:10.1007/s12040-015-0561-1

Cited by 22 publications

(6 citation statements)

References 20 publications

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“…In addition to these two main factors, there is the topography which, according to [30], is the main factor which would influence the shape of the VES curves, especially within a terrain whose lithological nature is homogeneous. Aquifers resistivity obtained (50 to 671 Ω.m) are in conformity with the Resistivity values of Pan-African aquifers explored by [31]. These resistivity values show that granitoid formation at level explored are highly weathered and/or fractured.…”

Section: Diversity Of Ves Curves and Borehole Productivitysupporting

confidence: 85%

Assessment of Hydrogeoelectrical Characteristics of Crystalline Aquifers and Groundwaters Quality in Adamawa Plateau: Case of Mbakaou (Adamawa - Cameroon)

Zebaze¹,

Njueya²,

Kwekam³

et al. 2020

EESRJ

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Population in Adamawa Plateau faced to borehole failure and return to alternative water supply structures (wells and catchments) with a doubtful quality. This study was carried out to highlight the location of aquifers, their hydrodynamics characteristics and groundwaters quality in Mbakaou locality, which belong to the Adamawa Region. Combination of geological and geoelectrical surveys at 10 stations, with hydrodynamic study of 4 boreholes were carried out to characterize aquifers. Hydrochemical analysis of 10 waters samples has been done to determine physico-chemical water quality and origin of waters mineralization. Geological studies show that basement rocks, which constitute fractured aquifers, consists of a large assemblage of granitoid. Geophysics and drilling data highlight superficial aquifers located between 2 and 17 m and fractured aquifers located between 11 and 74 m, with resistivity ranging from 50 to 671 Ω.m. The borehole have yield varying between 2.80 and 5.14 m3/h. Transmissivity and permeability ranging from 10-6 to 10-5 m2/s and 10-7 to 10-6 m/s respectively, indicating that aquifers are semi-permeable. Waters are of good quality compared to WHO norms and weakly mineralized (35 to 247.9 mg/l). Piper diagram show that calcium and magnesium bicarbonate facies is dominant. Mineralisation of water is mainly influenced by water-rock interaction through silicate weathering.

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Section: Diversity Of Ves Curves and Borehole Productivitysupporting

confidence: 85%

Assessment of Hydrogeoelectrical Characteristics of Crystalline Aquifers and Groundwaters Quality in Adamawa Plateau: Case of Mbakaou (Adamawa - Cameroon)

Zebaze¹,

Njueya²,

Kwekam³

et al. 2020

EESRJ

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“…The parameter to be estimated is measured discretely and then, to obtain the continuous information, kriging technique is used. Nowadays, this technique based on semivariogram is used by so many scientists in various fields as civil protection (Zamani and Mirabadi 2011), meteorology (Caridad and Jury 2013; Arétouyap et al 2014a), geochemistry (Gorai and Kumar 2013; Méli’i et al 2013; Arétouyap et al 2014b; Nshagali et al 2015; Arétouyap et al 2015). If authors do not take into account the paramount impact of the semivariogram model in such investigations, the survey will be sketchy and results untruthful.…”

Section: Discussionmentioning

confidence: 99%

“…In this experimental analysis, we used dataset of aquifer resistivity computed using the vertical electrical sounding conducted in the Pan-African context of Adamawa-Cameroon (Arétouyap et al 2015). This field campaign was carried out in order to characterize local aquifers.…”

Section: Methodsmentioning

confidence: 99%

“…Arétouyap et al (2014a, b, 2015) used geostatistics to analyze the spatial distribution of climate parameters in central Africa, the groundwater quality index in the Adamwa-Cameroon region and to characterize aquifers in the Pan-African context; Binita et al (2015) to investigate temporal and spatial assessment of climate change vulnerability; Chaney and Rojas-Guyler (2015) to establish the geographic variability in adolescent drug use and to correlate factors of use; Keumseok et al (2015) to build up spatial patterns of simulated obesity prevalence were compared with measures of low income and food accessibility; Mishra and Chaudhuri (2015) to characterize spatio-temporal trends in vegetation greenness in Uttarakhand Himalayas; Zunkel (2015) to establish a network of all 14 tornado sirens and examined the number of residents included and not included in that network, Teikeu Assatse et al (2016) to assess water quality.…”

Section: Introductionmentioning

confidence: 99%

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Lessening the adverse effect of the semivariogram model selection on an interpolative survey using kriging technique

et al. 2016

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Objective Many parameters in environmental, scientific and human sciences investigations need to be interpolated. Geostatistics, with its structural analysis step, is widely used for this purpose. This precious step that evaluates data correlation and dependency is performed thanks to semivariogram. However, an incorrect choice of a semivariogram model can skew all the prediction results. The main objectives of this paper are (1) to simply illustrate the influence of the choice of an inappropriate semivariogram model and (2) to show how a best-fitted model can be selected. This may lessen the adverse effect of the semivariogram model selection on an interpolation survey using kriging technique.MethodsThe influence of the semivariogram model selection is highlighted and illustrated by thematic maps drawn using four different models (Gaussian, magnetic, spherical and exponential). Then, a guideline to select the most suitable model, using mean error (ME), mean square error (MSE), root mean square error (RMSE), average standard error (ASE), and root mean square standardized error (RMSSE), is proposed.ResultsThe choice of a semivariogram model seriously influences the results of a kriging survey at both endpoints and amplitude of the range of the estimated values. However, the direction of variation of the interpolated values is independent of the semivariogram model: different semivariogram models (with the same characteristics) produce different thematic maps but, the areas of minimum and maximum values remain unchanged. Yet, the suitable model can be selected by means of ME, MSE, RMSE, ASE and RMSSE.ConclusionThe present article illustrates how the use of an inappropriate semivariogram model can seriously distort the results of an evaluation, assessment or prediction survey. To avoid such an inconveniency, a methodical approach based on the computation and analysis of ME, RMSE, ASE, RMSSE and MSE is proposed.

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“…Electrical resistivity geophysical prospecting technique has been extensively utilized by many researchers in various domains of groundwater studies (Adiat et al 2013). For instance, vertical electrical sounding (VES) technique can significantly contribute to the accurate location of aquifer not only through the development of its geometry (Zakari et al 2015) but also by establishing relationship between the hydrogeological and geoelectrical parameters (Adiat et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Prediction of groundwater level in basement complex terrain using artificial neural network: a case of Ijebu-Jesa, southwestern Nigeria

et al. 2019

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Empirical relationship between geoelectric parameters and groundwater level in boreholes/wells has not been established. Also, prediction of groundwater level from geoelectric parameters had hitherto not been reported. In order to overcome these challenges, the capability of artificial neural network (ANN) to model nonlinear system was explored in this study to predict groundwater level from geoelectric parameters. To achieve the above objectives, the ground water level (GWL) of all the accessible wells in the study area was obtained and this was used as the output parameter for the ANN model. A total of fifty-one (51) parametric vertical electrical soundings (VES) stations were occupied at each of the well location by adopting Schlumberger array configuration with electrode spacing (AB/2) ranging from 1 to 100 m. The VES data were quantitatively interpreted to generate geoelectric parameters believed to be controlling the groundwater flow and storage in the area. These parameters served as input for ANN model. The capability of ANN as a nonlinear modeling system was thereafter applied to produce a model that can predict the GWL from the input parameters. The efficiency of the model was evaluated by estimating the mean square error (MSE) and the regression coefficient (R) for the model. The results established that seasonal variation has little effect on the water fluctuation in the wells. Two aquifer types, weathered and fractured basement aquifer types, were delineated in the area. The results of the ANN model validation showed low MSE of 0.0014286 and the high regression coefficient (R) of 0.98731. This indicates that ANN can be used to predict GWL in a basement complex terrain with reasonably good accuracy. It is concluded that the ANN can effectively predict GWL from geoelectric parameters.

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Aquifers productivity in the Pan-African context

Cited by 22 publications

References 20 publications

Assessment of Hydrogeoelectrical Characteristics of Crystalline Aquifers and Groundwaters Quality in Adamawa Plateau: Case of Mbakaou (Adamawa - Cameroon)

Assessment of Hydrogeoelectrical Characteristics of Crystalline Aquifers and Groundwaters Quality in Adamawa Plateau: Case of Mbakaou (Adamawa - Cameroon)

Lessening the adverse effect of the semivariogram model selection on an interpolative survey using kriging technique

Prediction of groundwater level in basement complex terrain using artificial neural network: a case of Ijebu-Jesa, southwestern Nigeria

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