Analysing principal components of physiographic factors affecting groundwater occurrences within Keffi, North­-Central Nigeria

The aim of the study is to employ remotely sensed data and evaluate the principal components (PC) of physiographic variables like topography, drainage, slope and wetness. These variables may wield physiographic influence on groundwater. The software ENVI 5.0 and GLOBAL MAPPER 15 were used to obtain...

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Main Authors: Ebenezer A. Kudamnya, Aneikan Edet, Azubuike S. Ekwere
Format: Article
Language:English
Published: Elsevier 2021-12-01
Series:Egyptian Journal of Remote Sensing and Space Sciences
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1110982321000569
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author Ebenezer A. Kudamnya
Aneikan Edet
Azubuike S. Ekwere
author_facet Ebenezer A. Kudamnya
Aneikan Edet
Azubuike S. Ekwere
author_sort Ebenezer A. Kudamnya
collection DOAJ
description The aim of the study is to employ remotely sensed data and evaluate the principal components (PC) of physiographic variables like topography, drainage, slope and wetness. These variables may wield physiographic influence on groundwater. The software ENVI 5.0 and GLOBAL MAPPER 15 were used to obtain these information from Landsat ETM+ and SRTM-DEM, while ARCMAP 10.3 was used to perform the extraction of slope data. Principal component analysis (PCA) revealed that there was very strong negative loading of Eigen Values for the variables; topography, wetness, and drainage density within PC1, PC2, and PC4, respectively. However, slope showed a very strong positive loading of Eigen Values in PC3. PC3 multiplied by −1 was then performed in order to realise a more ideal relationship between these physiographic variables and the availability of groundwater. It showed weak positive Eigen Values of +0.031 and +0.012 for wetness and slope respectively, although their influence on groundwater occurrence is not very strong. Three classes namely; low, moderate, and high groundwater potentials were well-defined based on these physiographic variables using multi-fractal analysis (MFA). The regions delineated are 26%, 65%, and 9% respectively, in terms of percentage areal coverage. Therefore, variables other than the physiographic influences exert stronger influences on the spatial distribution of groundwater in the study area.
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spelling doaj.art-2f5842bb50d04497bd9b1207d06b0a0d2022-12-21T18:44:38ZengElsevierEgyptian Journal of Remote Sensing and Space Sciences1110-98232021-12-01243665674Analysing principal components of physiographic factors affecting groundwater occurrences within Keffi, North­-Central NigeriaEbenezer A. Kudamnya0Aneikan Edet1Azubuike S. Ekwere2Corresponding author.; Department of Geology, University of Calabar, Calabar, Cross River State Nigeria, NigeriaDepartment of Geology, University of Calabar, Calabar, Cross River State Nigeria, NigeriaDepartment of Geology, University of Calabar, Calabar, Cross River State Nigeria, NigeriaThe aim of the study is to employ remotely sensed data and evaluate the principal components (PC) of physiographic variables like topography, drainage, slope and wetness. These variables may wield physiographic influence on groundwater. The software ENVI 5.0 and GLOBAL MAPPER 15 were used to obtain these information from Landsat ETM+ and SRTM-DEM, while ARCMAP 10.3 was used to perform the extraction of slope data. Principal component analysis (PCA) revealed that there was very strong negative loading of Eigen Values for the variables; topography, wetness, and drainage density within PC1, PC2, and PC4, respectively. However, slope showed a very strong positive loading of Eigen Values in PC3. PC3 multiplied by −1 was then performed in order to realise a more ideal relationship between these physiographic variables and the availability of groundwater. It showed weak positive Eigen Values of +0.031 and +0.012 for wetness and slope respectively, although their influence on groundwater occurrence is not very strong. Three classes namely; low, moderate, and high groundwater potentials were well-defined based on these physiographic variables using multi-fractal analysis (MFA). The regions delineated are 26%, 65%, and 9% respectively, in terms of percentage areal coverage. Therefore, variables other than the physiographic influences exert stronger influences on the spatial distribution of groundwater in the study area.http://www.sciencedirect.com/science/article/pii/S1110982321000569PhysiographicPCAExtractionGroundwaterEigen-valuesPotentials
spellingShingle Ebenezer A. Kudamnya
Aneikan Edet
Azubuike S. Ekwere
Analysing principal components of physiographic factors affecting groundwater occurrences within Keffi, North­-Central Nigeria
Egyptian Journal of Remote Sensing and Space Sciences
Physiographic
PCA
Extraction
Groundwater
Eigen-values
Potentials
title Analysing principal components of physiographic factors affecting groundwater occurrences within Keffi, North­-Central Nigeria
title_full Analysing principal components of physiographic factors affecting groundwater occurrences within Keffi, North­-Central Nigeria
title_fullStr Analysing principal components of physiographic factors affecting groundwater occurrences within Keffi, North­-Central Nigeria
title_full_unstemmed Analysing principal components of physiographic factors affecting groundwater occurrences within Keffi, North­-Central Nigeria
title_short Analysing principal components of physiographic factors affecting groundwater occurrences within Keffi, North­-Central Nigeria
title_sort analysing principal components of physiographic factors affecting groundwater occurrences within keffi north central nigeria
topic Physiographic
PCA
Extraction
Groundwater
Eigen-values
Potentials
url http://www.sciencedirect.com/science/article/pii/S1110982321000569
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