Modeling Groundwater Flow System of a Drainage Basin in the Basement Complex Environment of Southwestern Nigera

Akinwumiju, Akinola S.; Olorunfemi, M. O.

doi:10.5194/ica-proc-1-2-2018

Cited by 3 publications

(1 citation statement)

References 14 publications

(16 reference statements)

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“…The resistivity and thickness of aquiferous layer have been successful evaluated for groundwater potential. On the other hand, relatively high overburden thickness enhances the productivity of boreholes in some parts of the basement complex of southwestern Nigeria (Olorunfemi andOlorunniwo 1987: Mogaji 2016a). These parameters were further reprocessed using the established groundwater flow equations reported in the studies of Mogaji and Lim, (2020) and Akintorinwa et al (2020) to determine the second order hydrogeologic factors relevant to groundwater prediction modeling.…”

Section: Geoelectrical Predictors Modeling Approach (Gpma)mentioning

confidence: 99%

Groundwater Potentiality Prediction Using AHP-MCDA and GBT Model in a Typical Basement Complex, Nigeria: Insights From Remote Sensing and Geophysical Datasets

Olumide

James

Anthony

2022

Preprint

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Delineation of geologic features that are capable of hosting water in economic quantity in the Basement Complex has been a major concern because they are usually localized due to restricted fractured and weathered rock. To effectively evaluate the groundwater potentiality prediction index (GPPI) accuracy of an area, solely depends on the groundwater potentiality predictors (GPPs) considered and the statistical model used in analyzing the data. Therefore, the acquired remotely sensed and geophysical depth sounding database processed using autopartial curve matching software and computer aided iteration to determine was analyzed using the conventional Analytical Hierarchy Process (AHP) model and the machine learning Gradient Boosting Tree (GBT) data driven model. Such a data driven model (GBT) is efficient in solving complex and cognitive problems in high uncertainty and complex environments. Twelve (12) groundwater potentiality predictors (GPPs) namely: Digital Elevation Model (DEM), Slope (S), Drainage Density (Dd), Land Use (Lu), Aquifer Resistivity (ρa), Aquifer Thickness (h), Overburden Thickness (b), Aquifer Hydraulic Conductivity (k), Aquifer Transmissivity (Tr), Aquifer Storativity (St), Aquifer Diffusivity (D), Aquifer Reflection Coefficient (Rc). The efficacy of GBT model was applied using the Salford Predictive Modeler 8.0 software. The data were partitioned into training and test dataset in ratio 90:10 using k-10 cross validation techniques. Their prediction importance was determined and the groundwater potentiality prediction index calculated and processed in the ArcGIS environment to produce the groundwater potential prediction index (GPPI) map of the investigated area. The investigated area was classed into three (3) zonations of low, moderate and high groundwater potential with about 56% classed within the low groundwater potential zone. Fifteen (15) water column measurement from wells was used to validate the developed model by calculating the predictive correlation accuracy (PCA) using the spearman's correlation analysis. The AHP-GPPI and GBT-GPPI model gave a correlation of (rs = 0.66; p = .007) and (rs = 0.74; p = .002) respectively. In conclusion, the model has proven that the drop in aquifer resistivity doesn't necessitate the presence of groundwater but rather several parameter should be integrated together to better understand the true nature of the aquifer.

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Section: Geoelectrical Predictors Modeling Approach (Gpma)mentioning

confidence: 99%

Groundwater Potentiality Prediction Using AHP-MCDA and GBT Model in a Typical Basement Complex, Nigeria: Insights From Remote Sensing and Geophysical Datasets

Olumide

James

Anthony

2022

Preprint

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Assessment of Aquifer Resistivity, Hydrogeochemistry and Groundwater Quality in Osogbo Metropolis, Southwestern Nigeria

Ogungbesan,

Bayowa,

Eluwole

et al. 2024

Preprint

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The Ibadan Hydrogeophysics Research Site (IHRS)—An Observatory for Studying Hydrological Heterogeneities in A Crystalline Basement Aquifer in Southwestern Nigeria

Doro

Adegboyega

Aizebeokhai

et al. 2023

Water

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Crystalline basement aquifers are important drinking water sources in Nigeria and several sub-Saharan African countries. However, an understanding of their local flow and transport processes and pathways is missing due to limited research. The implication has been their suboptimal management, with frequently reported dry wells and groundwater contaminations. To address this challenge, the Ibadan Hydrogeophysics Research Site was established in 2019 as the first field-scale hydrogeological research laboratory in Nigeria to advance understanding of the geologic, hydraulic, and hydrogeochemical variabilities within crystalline basement aquifers. The over 22,500 m2 research site with a 50 m × 50 m area used for active hydraulic testing is located within the University of Ibadan campus and is instrumented with four initial test wells extending through the weathered and fractured zones to a depth of 30 m each. Preliminary hydrogeological and geophysical studies focused on obtaining a conceptual model and knowledge of hydraulic heterogeneities to aid in detailed experimental and numerical studies. A combination of lithological logs and electrical resistivity revealed areas with subvertical fractures as low-resistivity zones (< 200 Ωm), and a pumping test revealed a hydraulic conductivity range of 1.9 × 10−10 to 7.2 × 10−6 m/s. The drawdown–time curve shows flow from single-plane vertical fractures. The results of this study will serve as a basis for further targeted field and numerical studies for the investigation of variability in groundwater flow in complex crystalline basement aquifers. The presented field site is posed to support the adaptation and development of field methods for studying local heterogeneities within these aquifers in Nigeria.

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Modeling Groundwater Flow System of a Drainage Basin in the Basement Complex Environment of Southwestern Nigera

Cited by 3 publications

References 14 publications

Groundwater Potentiality Prediction Using AHP-MCDA and GBT Model in a Typical Basement Complex, Nigeria: Insights From Remote Sensing and Geophysical Datasets

Groundwater Potentiality Prediction Using AHP-MCDA and GBT Model in a Typical Basement Complex, Nigeria: Insights From Remote Sensing and Geophysical Datasets

Assessment of Aquifer Resistivity, Hydrogeochemistry and Groundwater Quality in Osogbo Metropolis, Southwestern Nigeria

The Ibadan Hydrogeophysics Research Site (IHRS)—An Observatory for Studying Hydrological Heterogeneities in A Crystalline Basement Aquifer in Southwestern Nigeria

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