Mapping of groundwater potential zones across Ghana using remote sensing, geographic information systems, and spatial modeling

Environ Monit Assess. 2013 Apr;185(4):3561-79. doi: 10.1007/s10661-012-2810-y. Epub 2012 Aug 16.

Abstract

Groundwater development across much of sub-Saharan Africa is constrained by a lack of knowledge on the suitability of aquifers for borehole construction. The main objective of this study was to map groundwater potential at the country-scale for Ghana to identify locations for developing new supplies that could be used for a range of purposes. Groundwater potential zones were delineated using remote sensing and geographical information system (GIS) techniques drawing from a database that includes climate, geology, and satellite data. Subjective scores and weights were assigned to each of seven key spatial data layers and integrated to identify groundwater potential according to five categories ranging from very good to very poor derived from the total percentage score. From this analysis, areas of very good groundwater potential are estimated to cover 689,680 ha (2.9 % of the country), good potential 5,158,955 ha (21.6 %), moderate potential 10,898,140 ha (45.6 %), and poor/very poor potential 7,167,713 ha (30 %). The results were independently tested against borehole yield data (2,650 measurements) which conformed to the anticipated trend between groundwater potential and borehole yield. The satisfactory delineation of groundwater potential zones through spatial modeling suggests that groundwater development should first focus on areas of the highest potential. This study demonstrates the importance of remote sensing and GIS techniques in mapping groundwater potential at the country-scale and suggests that similar methods could be applied across other African countries and regions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Environmental Monitoring / methods*
  • Geographic Information Systems*
  • Ghana
  • Groundwater / analysis*
  • Groundwater / chemistry
  • Remote Sensing Technology*
  • Water Resources / analysis*
  • Water Resources / statistics & numerical data
  • Water Supply / analysis*
  • Water Supply / statistics & numerical data