Abstract
Rapid and unchecked growths of private tubewells in poor water quality zones of Punjab province, Pakistan are the major sources of environmental degradation through the deployment of agricultural stresses on the underlying aquifer. There are broadly two environmental menaces associated with these agricultural stresses, increase of non-point source pollution loads at the surface and instigation of problem of secondary salinity (SS). The present study is applied vertical electrical soundings with Schlumberger electrode configuration having maximum current electrodes separation 300 m to assess the potential of freshwater layer lying over the saline groundwater. Primarily, the collected earth’s resistivities were converted to groundwater quality using groundwater electrical conductivity (EC) from exploratory wells drilled at regular interval in the entire Thal Doab. Secondly, based on these EC values, the study area is divided into three different tubewell suitability classes as high, moderate and low with interpreted EC values as less than 1.5 dS/m, between 1.5 and 2.5 dS/m and greater than 2.5 dS/m, respectively. The spatial distribution maps of these suitability classes are done at six depth zones (0–50, 50–100, 100–150, 150–200, 200–250, 250–300 m). Results indicate that there is an inverse relationship between the surface water recharge and SS which should be used for both tubewell depth as well as site optimization and a check on their future growth rates. In this way the eco-friendly agricultural growth rates can be established in Tehsil Kot Adhu, Thal Doab, Pakistan and the other areas having similar hydrogeological conditions.
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Acknowledgement
The first author is thankful to Mr. Naveed Iqbal (Scientific officer PCRWR) and Dr. A.D Khan (PCRWR) for providing usual information as well as guidance required for the analysis.
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Hussain, Y., Ullah, S.F., Akhter, G. et al. Groundwater quality evaluation by electrical resistivity method for optimized tubewell site selection in an ago-stressed Thal Doab Aquifer in Pakistan. Model. Earth Syst. Environ. 3, 15 (2017). https://doi.org/10.1007/s40808-017-0282-3
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DOI: https://doi.org/10.1007/s40808-017-0282-3