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

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.

Application of Remote Sensing in Natural Sciences

Generally, the term biomass is used for all materials originating from photosynthesis. However, biomass can equally apply to animals. Conservation and management of biomass is very important. There are various ways and methods for biomass evaluation. One of these methods is remote sensing. Remote sensing provides information about biomass, but also about biodiversity and environmental factors estimation over a wide area. The great potential of remote sensing has received considerable attention over the last few decades in many different areas in biological sciences including nutrient status assessment, weed abundance, deforestation, glacial features in Arctic and Antarctic regions, depth sounding of coastal and ocean depths, and density mapping.

On the investigation of vertical uncertainty of depth sounding in a shallow environment with muddy seabed: Preliminary results from a launch operation of a dual-frequency echosounder

Hydrographic echosounder has been the standard instrument that provides a measure of water depths. In a muddy environment, this detection is not as straightforward as it seems; low gradient of acoustic impedance presence within the water-sediment interface resulting in vertical separation of liquid-solid boundary detected by different frequencies of depth sounding system. In this study, we investigate the depths measured by a dual-frequency hydrographic echosounder in a muddy environment, coupled with a simultaneous probing of the water-seabed interface by means of a free-falling cone penetrometer. We intend to understand the extent of the uncertainty of a depth-sounding system to precisely locate the liquid-solid boundary within the water-seabed interface, specifically at Patimban coasts, situated in the north coast part of Java Island, where muddy sediments dominate the seabed. From our investigation, we found that standard high-frequency sounding (200 kHz) underestimates the physical depth by 0.26 ± 0.17 m, while standard low-frequency sounding (24 kHz) overestimates the physical depth by 0.23 ± 0.19 m and tends to give inconsistent measures. Our study suggests the importance of considering these measures of discrepancy when depth sounding is being carried out in a muddy environment.

Joint inversion of magnetotelluric tippers and geomagnetic depth sounding transfer functions constrains electrical conductivity beneath islands

<p>Geomagnetic field variations recorded at island geomagnetic observatories are one of the data sources that can be used to constrain the electrical conductivity beneath oceans. Hitherto, magnetotelluric (MT) tippers (period range from a few minutes to 3 hours) and geomagnetic depth sounding (GDS) transfer functions (TFs; period range from 6 hours to a few months) were inverted separately to reveal the electrical conductivity structure underneath island observatories.  In this study, we develop a quasi 1-D tool to simultaneously invert MT tippers and GDS TFs. To account for source complexity, we resort to GDS TFs that relates a set of spherical harmonics coefficients describing the source (of ionospheric or magnetospheric origin) to a locally measured vertical magnetic field component. Joint inversion of multiple data sets from different sources helps to improve vertical resolution and reduce uncertainties in the recovered conductivity models. The stochastic optimization method, known as Covariance Matrix Adaptation Evolution Strategy, is applied to solve the inverse problem. The term “quasi” is used here to stress the fact that during 1-D inversion the 3-D forward modeling operator is exploited to account for the ocean induction effect (OIE), which is known to strongly influence the island electromagnetic (EM) responses. To efficiently model MT tippers and GDS TFs, the Cartesian-to-Cartesian and spherical-to-Cartesian 3-D EM modeling engines, based on a nested integral equation approach, are adopted. We apply the developed tool to jointly invert MT tippers and GDS TFs estimated at Honolulu geomagnetic observatory, located at Oahu island (Hawaii) in Pacific Ocean, and discuss the recovered conductivity structure.</p>

Electrical Conductivity Evidence for the Existence of a Mantle Plume Beneath Tarim Basin

This paper proposes using a simulated annealing (SA) calculation to perform one-dimensional inversion of Geomagnetic Depth Sounding (GDS) to obtain the conductivity information of the lower mantle beneath the Tarim area, to calculate the temperature of the lower mantle according to the relevant formula of the petrophysical experiment, and to provide evidence of the existence of the Tarim mantle plume. The data used for inversion originate from the China Geomagnetic Network Center. This article uses theoretical data to prove that the simulated annealing algorithm can invert the true conductivity model when the data do not contain noise. However, when the data contain noise, it is more accurate to use the statistical expected value of the high-quality conductivity model during the simulated annealing inversion process as the optimal conductivity model rather than the classic simulated annealing algorithm. The simulated annealing inversion results of only four stations in Tarim area show that the conductivity of the top of the lower mantle and the upper part of the mantle transition zone in Tarim area is higher than the global average, and it is speculated that the temperature is 150k–450k higher than the global average. This is important evidence for the existence of the mantle plume beneath the Tarim Basin.

Bathymetric Survey and Topography Changes Investigation of Part of Badagry Creek and Yewa River, Lagos State, Southwest Nigeria

Bathymetry survey of Part of Badagry Creek and Yewa River was conducted with the aim of investigating the topography changes in depth between two epoch dataset by calculating the volume of sediment and dredged material between the two periods. Depth sounding at 100m interval, data grid of 100 m interval, constant vessel speed of 2.2 m/secs (8Km/hr) for data capture, data storage at interval of 30 Secs was ensured at both the creek and the river. Seabed topography changes of Part of Badagry Creek and Yewa River was investigated. The two dataset investigated was the data acquired in September 2008 and November 2015. Data acquisition was done using digital echo sounder SDE28, Handheld Real time Kinematic (RTK) Global Positioning System (GPS) in acquiring the spatial coordinates (x, y) and water depth (z). Six (6) wrecks (Shipping Boat) were determined along both the creek and the river. The initial processing was carried out with the use of HYPACK 2008 software for data sorting. ArcGIS 10.2.1 was used for data analysis as well as graphics design. The processed depths were presented in form of tables, map/plan and charts. The result showed that In 2008, the depth observed ranges from (-0.5 to 10.4) m while in 2015, the depth observed ranges from (-0.32 to 10.85) m which implies that some area have been cut. Also, the results of the volume of deposited sediments and dredged material are computed as 10.55 x 106 m3 and 7.24 x 106 m3. It showed from the result that volume of accreted sediment is greater than volume of the material dredged. Increase in volume of sediment deposited could be as a result of the adjoining river Yewa flowing into the larger river (tributaries) of the Badagry Creek. Therefore, further studies need to carry out in order to know the source of accreted mass through integrated coastal management plan.

Emerging Remote Sensing Methods in Underwater Archaeology

As a critical first step in underwater research, the authors stress the importance of using geophysics for detecting, locating, and determining the extent of archaeological deposits. Magnetometry, multibeam depth sounding, side-scan sonar, sub-bottom profiling, airborne bathymetric LiDAR (ABL), and ground-penetrating radar (GPR) are discussed. The hydrographic GPR case study of stratigraphy and bathymetry took place at the Ryan-Harley site. The ABL case study took place at the Lake George Point Site.

On the Application of Coefficient of Anisotropy as an Index of Groundwater Potential in a Typical Basement Complex of Ado Ekiti, Southwest, Nigeria

This paper examines the application of the Dar Zarrouk parameter, the Coefficient of Anisotropy to Groundwater Potential Evaluation in a typical Basement Complex Terrain of Ado-Ekiti Southwest, Nigeria. A regional Geoelectric Depth sounding was carried out across the metropolis using the Schlumberger electrode array. Resistivity-depth image in terms of layer thickness and resistivity was used to compute the Coefficients of Anisotropy for the VES locations occupied. Thematic maps of the geoelectric parameters were generated using the Concept of Geographical Information System (GIS). Comparative Map Analysis revealed that a range of 1.3 to 1.6 Anisotropy values was observed across the zones characterized by thick overburden, Weathered Basement Thickness in excess of 25m, low weathered basement resistivity, fractured bedrock and basement depressions in the study area. Anisotropy values ranging from 1.8 to 2.8 were observed across the basement ridges and zones characterized by thin overburden, Weathered Basement Thickness of generally less than 15m and Weathered Basement resistivity greater than 1500 Ω-m with least groundwater potential. The regions of Anisotropy values ranging from 1.3 to 1.6 are demarcated as high groundwater potential zones. Areas characterized by higher Anisotropy values can be associated with low porosity and permeability with less hydro geological appeal.