TY - JOUR
T1 - Groundwater of Abu Dhabi Emirate
T2 - A regional assessment by means of remote sensing and geographic information system
AU - Elmahdy, Samy Ismail
AU - Mohamed, Mohamed Mostafa
N1 - Publisher Copyright:
© Saudi Society for Geosciences 2015.
PY - 2015/12
Y1 - 2015/12
N2 - Mapping of geological, topographical, and hydrological elements is critical for understanding and assessing the regional hydrological setting in an arid region. In this study, a synergistic approach has been developed, which uses a combination of remote sensing data and geographic information system (GIS) to map factors controlling groundwater recharge, discharge, and quality across the Abu Dhabi Emirate. The Spectral Angel Mapper (SAM) algorithm, which uses a n-D angle to match the pixels to reference spectra, was used to map new water-bearing rocks, and the deterministic eight-node (D8) algorithm, which allows flow to only one of the eight neighbors based on the direction of steepest descent, was used to map paleochannels. The terrain category was applied to simulate seawater intrusion from digital elevation model (DEM). New maps of lithology, normalized difference vegetation index (NDVI), and paleochannels were derived and interpreted from multi-sources of remote sensing data. The study indicated that the area was produced by a fluvial and eolian process and recharged by local, intermediate, and regional flows. The results showed that the Oman and Hafeet Mountains are the natural sources of groundwater recharge as well as HCO3, Ca, Na, and Mg in groundwater. The mapped factors were spatially correlated with hydrologic anomalies observed in groundwater wells. The integrated approach is timely, cost-effective, and can be used in arid regions for numerical modeling as well as water balance analysis.
AB - Mapping of geological, topographical, and hydrological elements is critical for understanding and assessing the regional hydrological setting in an arid region. In this study, a synergistic approach has been developed, which uses a combination of remote sensing data and geographic information system (GIS) to map factors controlling groundwater recharge, discharge, and quality across the Abu Dhabi Emirate. The Spectral Angel Mapper (SAM) algorithm, which uses a n-D angle to match the pixels to reference spectra, was used to map new water-bearing rocks, and the deterministic eight-node (D8) algorithm, which allows flow to only one of the eight neighbors based on the direction of steepest descent, was used to map paleochannels. The terrain category was applied to simulate seawater intrusion from digital elevation model (DEM). New maps of lithology, normalized difference vegetation index (NDVI), and paleochannels were derived and interpreted from multi-sources of remote sensing data. The study indicated that the area was produced by a fluvial and eolian process and recharged by local, intermediate, and regional flows. The results showed that the Oman and Hafeet Mountains are the natural sources of groundwater recharge as well as HCO3, Ca, Na, and Mg in groundwater. The mapped factors were spatially correlated with hydrologic anomalies observed in groundwater wells. The integrated approach is timely, cost-effective, and can be used in arid regions for numerical modeling as well as water balance analysis.
KW - Al Ain
KW - GIS
KW - Groundwater
KW - Paleochannels
KW - Remote sensing
KW - UAE
UR - http://www.scopus.com/inward/record.url?scp=84949085718&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84949085718&partnerID=8YFLogxK
U2 - 10.1007/s12517-015-1932-2
DO - 10.1007/s12517-015-1932-2
M3 - Article
AN - SCOPUS:84949085718
SN - 1866-7511
VL - 8
SP - 11279
EP - 11292
JO - Arabian Journal of Geosciences
JF - Arabian Journal of Geosciences
IS - 12
M1 - A077
ER -