Modeling groundwater total dissolved solid from derived electromagnetic data using multiple linear regression analysis: a case study of groundwater contamination

Ameloko Anthony Aduojo,Ayolabi Elijah Adebowole,Okezie Uchegbulam

doi:10.1007/s40808-020-00796-9

Ameloko Anthony Aduojo, Ayolabi Elijah Adebowole + Show 1 more

Open Access

https://doi.org/10.1007/s40808-020-00796-9

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Abstract

The high concentration of total dissolved solids (TDS) and other physicochemical parameters in groundwater around dumpsites have been used to implicate contamination from decomposed waste materials. A simple multiple linear regression (MLR) TDS model that integrates the TDS data derived from boreholes and hand-dug wells to the geophysical parameters obtained from the frequency-domain electromagnetic (EM) data was developed in this research. This is with a view to efficiently monitor groundwater resources and exploration around the Olusosun dumpsite and its communities. With the aid of the MLR equation, the observed TDS concentration of water samples collected from boreholes and hand-dug wells, and the corresponding estimated ground conductivity data in the vertical dipole mode (VD 40) and horizontal dipole modes (HD 40 and HD 20), obtained from geophysical surveys were regressed in Microsoft Excel software to generate a MLR TDS model. The integrity of the derived TDS model was appraised to examine the possibility of deploying it to investigate the TDS content of groundwater around the study area. The EM data and the resistivity models obtained around the study area confirmed contamination going on around the dumpsite. The developed TDS model can be put to use with high confidence, for groundwater TDS prediction around the study area where there are only terrain conductivity data but with no boreholes parameters. Also, terrain conductivity data alone can be applied to the model to predict the concentration of TDS in groundwater where there are no boreholes and hand-dug wells, therefore reducing the cost and time of determining and monitoring both parameters independently. With the aid of the ArcGIS software, the TDS model was used to generate TDS estimate map for the area. The knowledge of the TDS variability in such a map could give a clue about the integrity of the underground water around the site.

Highlights

The use of geophysical tools for contamination studies around dumpsites and hydrocarbon depots is increasingly gaining ground and cannot be over-emphasized
Through the instrumentality of the Microsoft Excel Software, a simple multiple linear regression total dissolved solids (TDS) model was developed for predicting the TDS content of groundwater around the Olusosun dumpsite
The development of the TDS model was achieved by regressing the terrain conductivity data (VD 40, VD 20, and HD 40) obtained around the area with observed TDS values obtained from water samples from boreholes and hand-dug wells in the study area

Summary

Introduction

The use of geophysical tools for contamination studies around dumpsites and hydrocarbon depots is increasingly gaining ground and cannot be over-emphasized. The primary threat of contamination to groundwater emanates from the leachate formed from waste materials, which most often contain toxic chemical substances, mainly when wastes of industrial origins are involved (Enekwechi and Longe 2007). It has been, previously documented that leachates from dumpsites for non-toxic waste could contain complex organic compounds, chlorinated hydrocarbons, and metals at concentrations, which becomes a threat to both ground and surface water. According to Enekwechi and Longe (2007), the volume of leachate produced is hugely dependent on the area of the landfill, the meteorological and hydrogeological factors and the integrity of capping

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