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.

A GIS-based AHP Method for Groundwater Potential Zone Assessment: A Review

Scientific and academic researches and studies trying to present a multi-range of techniques and methods focusing on groundwater pollution, potentials, assessment, and prediction, Groundwater is the most important resource of fresh water now and many researchers trying to cover all about this resource to get sustainable development. This review aims to create an overview of groundwater analysis and forecasting methods. The study is based on the need to select and group research papers into best-defined methodological categories. The article gives an overview of recent advancements in groundwater potential zone analysis approaches, as well as ongoing research objectives based on that overview. This review has overviewed papers and researches been published last decade 2010 -2020 have been done depending on the data sources from the global online database, which could obtain many papers and research studying the groundwater potential zones and other aspects related to groundwater. The aim of reviewing multiple types of research and papers on determining groundwater potential zones by applying the best techniques and selecting the most suitable factors that affect groundwater potential zones.

Multi-Criteria Decision Making and Dempster-Shafer Model Based Delineation of Groundwater Prospect Zones From A Semi-Arid Environment

The present study illustrates the delineation of the groundwater potential zones in one of the most critical and drought affected areas under Bundelkhand region of Uttar Pradesh. Hydrological evaluations were carried out in district Mahoba using GIS tools and remote sensing data which ultimately yielded several thematic maps, such as lineament density, land use/land cover, drainage density, lithology, slope, geomorphology, wetness index (WTI), altitude and soil. CartoDEM data which have spatial resolution of 30m i.e. equivalent to one arc second were used to create digital elevation model, drainage density, altitude, WTI and slope. The thematic layers were assigned relative weightages as per their groundwater potential prospects under multi-criteria decision making (MCDM) method through analytical hierarchy process (AHP). To recognize the groundwater potential zone, weighted overlay analysis was performed using ArcMap software. Additionally, for testing of the Dempster-Shafer model, 16 borewells in high potential areas have been selected. Based on the probability of the groundwater occurrence, the belief factor was equated. Further combining the weighted layers, groundwater potential zones were obtained. The groundwater potential maps illustrate five zones having different potential in the Mahoba district. According to the AHP model the north-west side of the study area is characterized with very good potential zones whereas the north-east and south-east region constitute medium and poor groundwater potential zones respectively. It reflects that more than 50% of the area is having medium groundwater potential while 30 percent of the area falls under low potential zone. 10% of the study area falls under very good groundwater potential zones. According to the DS model, very high groundwater zones constitute only 7% and the remaining area falls under poor potential. Overall accuracy of the DS model was higher than AHP model.

Exploration of groundwater potential zones using analytical hierarchical process (AHP) approach in the Godavari river basin of Maharashtra in India

Total natural and groundwater resources play the most crucial role in developing ecological, biological and socioeconomic doings. Various parameters like land use, geology, elevation, slope, lineament, lineament density, drainage density and geomorphology affect the groundwater development of recharge and its accessibility. In this research, geographical information system (GIS), remote sensing, weighted overlay analysis and analytical hierarchy process (AHP) methods have been used for groundwater prospects mapping, and identifying suitable solutions site for soil and water conservation structures. To calculate the weights were assigned to every layers component in the determination of affecting factors. The weighted overlay analysis (WOA) tool is applied to give the sub-parameter ratings based on the scientific literature. The final map of potential groundwater zone map has prepared using Arc GIS 10.1 software and AHP methods. About 49.71% of the areas fall under the 'good potential zone, 41.05% falls under the 'moderate potential zone', and 9.22% falls under the 'poor zone by using AHP technique. Groundwater potential zone map is depend on the weighted overlay analysis and analytical hierarchy process (AHP) methods. The highest GWP is located in the lower part of the basin due to the best surface runoff gathering, infiltration situations and subsurface storage volume. The present study procedure, methods and outcomes can be valuable to estimate the suitable groundwater zones parallel to improve the dry land area in the semi-arid and arid regions of India.

Evaluation of Groundwater Potential Zone Using Remote Sensing and Geographical Information System: in Kaffa Zone, South Western Ethiopia

This study focused on delineating the groundwater potential and recharge area for Kaffa Zone by the method of remote sensing and ArcGIS 10.4 software analysis techniques. There are six main influencing factors (rainfall, slope, land use/cover, lineaments, drainage density, and Lithology) selected for groundwater recharge zone mapping. The thematic maps were scanned, geo-referenced, and classified as suitable for groundwater using ArcGIS 10.4. The methods to assess the potential zone were using weight overlay analysis and hierarchy of analytical process algorithm. The result obtained the potential of ground water were discussed recharge zones into four major categories: very good, good, and moderate and low. This can help for better planning and management the potential resource of groundwater. The results analyzed the groundwater potential that were subdivided in to low, moderate, high, and very high groundwater potentials areas that cover 1664.1,7682.9, 958.27, and 192.78 km2 respectively. The prediction accuracy was checked based on the borehole yield observed and predicted data of respective locations within the selected area. The prediction accuracy obtained (68.42%) reflects that the present study's method was produced significantly reliable and precise results.