Dar Zarrouk Parameters for Delineation of Groundwater Potential Zones in Geriyo Irrigation Floodplain of River Benue, Adamawa State, Northeastern Nigeria
Current Journal of Applied Science and Technology · pp. 1–15 · Published 28 May 2018
10.9734/CJAST/2018/41905Abstract
The study is aimed at delineating groundwater potential zones of the alluvial formations using Dar Zarrouk Parameters and groundwater flow direction on the floodplain. This will help the farmers to utilise the floodplain shallow wells during the dry season farming. Shallow wells on the floodplain of River Benue are the primary sources of water supply for irrigation activities. The floodplain is underlain by Bima sand stones. Twenty-four profiles of vertical electric soundings using Schlumberger array method with the aid of a sensitive ABEM Signal Averaging System (SAS) was used to investigate. The results were then compared with the alluvial floodplain lithologies at each sounding points with resistivity values ranging between 0.146 Ωm to 9,873.6 Ωm and depths varying from 0.2 to 38.33 m. The geoelectric sequence of the alluvial formations of the floodplain reveals semi aquifer system. The aquifer hydraulic characteristics indicated that the transverse resistance, R ranged between 2,626.70 Ωm2 to 241,252.38 Ωm2 with a mean value of 45,172.17 Ωm2. The longitudinal conductance, S ranged between 0.001 to 0.221 with an average value of 0.036. The hydraulic conductivity value across the floodplain ranges between 0.21 m/day to 29.06 m/day with a mean value of 11.22 m2/day. The transmissivity values obtained for the various layers ranges between 1.68 m2/day to 808.16 m2/day with an average value of 214.07 m2/day. Three groundwater potential zones were delineated on the floodplain. The results of the hydraulic head reveal that the water levels in the floodplain are higher than the River and recharge the River.
Cited by 5
Debasis Ghosh, Mrinal Mandal, Monali Banerjee · Groundwater for Sustainable Development · 2020
Rajasekhar M., Sudarsana Raju G., Bramaiah C. · Remote Sensing of Land · 2019
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