Potential Impacts of Climate Change and Variability on Groundwater Resources in Nigeria

Climate change observed over the past decades has been consistently associated with modifications of components of the hydrological systems such as precipitation patterns, sea surface temperature, accelerated melting of glacier and ice caps, soil temperature and moisture, surface runoff and stream flow. Such changes are known to influence subsurface hydrological systems, which could lead to changes in groundwater recharge, discharge and storage of many aquifers. Although, there are uncertainties in the characterisation of climate change induced groundwater impacts due to largely multi-scale local and regional heterogeneity, there is need to evaluate groundwater resources, quality and vulnerability to climate change and variability. This paper attempts to assess the potential impacts of climate change and variability on groundwater resources availability and sustainability in Nigeria

Anomaly Effects of Arrays for 3d Geoelectrical Resistivity Imaging using Orthogonal or Parallel 2d Profiles

The effectiveness of using a net of orthogonal or parallel sets of two-dimensional (2D) profiles for threedimensional (3D) geoelectrical resistivity imaging has been evaluated. A series of 2D apparent resistivity data were generated over two synthetic models which represent geological or environmental conditions for a typical weathered profile and waste dump site, respectively, commonly associated with geophysical applications for hydrogeological, environmental and engineering investigations. Several minimum electrode separations and inter-line spacing were used to generate the apparent resistivity data for each electrode array with a view to determining the optimum inter-line spacing relative to the minimum electrode separation. The 2D apparent resistivity data for each array were collated to 3D data sets. The effectiveness and efficiency of the arrays in 3D geoelectrical resistivity imaging were evaluated by determining the mean absolute anomaly effects of the electrodes arrays on the synthetic models. The anomaly effects observed in dipole-dipole (DDP), pole-dipole (PDP) and Wenner- Schlumberger (WSC) arrays were generally larger than that observed in other arrays considered. The least anomaly effect on the synthetic models was observed in pole-pole (PP) array. This indicates that DDP, PDP and WSC arrays are more sensitive to 3D features. In all the arrays, the anomaly effects observed in the data set generated using the conventional square grids were slightly larger than those from parallel or orthogonal 2D profiles. This slight increase is attributed to the increased data density and is insignificant when compared with those of parallel and orthogonal 2D profiles. Hence, the use of parallel or orthogonal 2D profiles for 3D geoelectrical resistivity survey is effective

Effectiveness of 3D Geoelectrical Resistivity Imaging using Parallel 2D Profiles

Acquisition geometry for 3D geoelectrical resistivity imaging in which apparent resistivity data of a set of parallel 2D profiles are collated to 3D dataset was evaluated. A set of parallel 2D apparent resistivity data was generated over two model structures. The models, horst and trough, simulate the geological environment of a weathered profile and refuse dump site in a crystalline basement complex respectively. The apparent resistivity data were generated for Wenner–alpha, Wenner–beta, Wenner–Schlumberger, dipole–dipole, pole–dipole and pole–pole arrays with minimum electrode separation, a (a = 2, 4, 5 and 10 m) and inter-line spacing, L (L = a, 2a, 2.5a, 4a, 5a and 10a). The 2D apparent resistivity data for each of the arrays were collated to 3D dataset and inverted using a full 3D inversion code. The 3D imaging capability and resolution of the arrays for the set of parallel 2D profiles are presented. Grid orientation effects are observed in the inversion images produced. Inter-line spacing of not greater than four times the minimum electrode separation gives reasonable inverse models. The resolution of the inverse models can be greatly improved if the 3D dataset is built by collating sets of orthogonal 2D profile

Multiple-gradient array for near-surface electrical resistivity tomography

The use of most conventional arrays for near-surface electrical resistivity tomography (ERT) surveys is usually cumbersome, time consuming and labour intensive. Thus, data acquisition teams are often tempted to reduce the data density with a view of speeding up field operation and minimizing the survey cost. This tends to significantly degrade the quality and resolution of the resulting resistivity images. In this presentation, multiple-gradient array, a non-conventional electrode configuration, has been used to conduct rapid and cost effective near-surface ERT without compromising the data density

SUBSOIL CHARACTERIZATION USING GEOELECTRICAL AND GEOTECHNICAL INVESTIGATIONS: IMPLICATIONS FOR FOUNDATION STUDIES

Electrical resistivity tomography (ERT) has been combined with geotechnical techniques such as cone penetrating tests, standard penetrating test and laboratory tests for detailed characterization of near-surface strata. This approach can be very helpful in conducting preliminary investigations towards a robust foundation design at a building construction site. Two ERT lines were conducted for 2D geoelectrical resistivity measurements using Wenner array configuration in combination with four cone penetrating data. Through the inversion of ERT data, two geoelectrical layers were interpreted to be loose silty sand and compacted clayey sand lithological units with the resistivity values ranging 50 - 280 ohmm and 10 - 74 ohmm respectively. A water-saturated portion with resistivity values <=3 ohmm due to lagoon-water incursion was equally observed at the base of the second clayey sand layer in ERT line T2. The average cone penetrometer (CPT) value of about 110 kg/cm2 (11 MPa) with an average SPT ‘N’ value of 25 was measured between 6.75 - 30.0 m, indicating that the geomaterials within this depths range are of good geotechnical properties. Laboratory tests conducted on the representative soil samples at 3.75 m depth gives a moisture content (MC) of 66%. This is attributed to the clay contents within the soil samples. The Liquid Limit (WL), Plastic Limit (WP) and Plasticity Index (PI) tests of the soil samples gives 84%, 30% and 54% respectively. The results of the proposed approach, encompassing both geophysical and geotechnical methods has helped to steer the choice of the foundation for the investigated building towards a pile-type foundation rather than a shallow one. The pile foundation will cause the higher loadings to transmit the loads to a stable soil layer within the subsurface

Application of Artificial Neural Network for the Inversion of Electrical Resistivity Data

The inversion of most geophysical data sets is complex due to the inherent non-linearity of the inverse problem. This usually leads to non-uniqueness of solutions to the inverse problem. Artificial neural network (ANN) has been used effectively to address several non-linear and non-stationary inverse problems. This study is essentially an assessment of the effectiveness of estimating subsurface resistivity model parameters from apparent resistivity measurements using ANN. Multi-layered earth models for different geologic environments were used to generate synthetic apparent resistivity data. The synthetic apparent resistivity data were generated using linear filter method embedded in the RES1D program. Neural network toolbox on MATLAB was used to design, train and test a developed neural network that was employed in the inversion of the apparent resistivity sounding data sets. Resilient feed-forward back propagation algorithm was used to train the network. The network was trained with 50% of the synthetic apparent resistivity data sets and their corresponding multi-layered earth models. 25% of the data set was used to test the network and the network was validated with another 25% of the data set. The network was then used to invert field data obtained from Iyanna- Iyesi, southwestern Nigeria. The results obtained from ANN responses were compared with that of a conventional geoelectrical resistivity inversion program (WINRESIST); the results indicate that ANN is effective in the inversion of geoelectrical resistivity sounding data for multi-layered earth models