Impact of Urban Growth on Groundwater Levels using Remote Sensing - Case Study: Erbil City, Kurdistan Region of Iraq

Abstract

Remote sensing and Geographic Information Systems (GIS) have been broadly used to detect and analyze urban expansion that is one of the most significant issues facing researchers of urban issues. In the current paper, setting out to examine the applicability of remote sensing and GIS to detect urbanization and its effect on quantities of groundwater spatio-temporal data, Landsat image 5-TM and 8-OLI were utilized. The images were classified into urban and non-urban through supervised classification (maximum likelihood logarithm) to provide an urban growth map over a period of ten years. Regression analysis was utilized to identify the relationship between urbanization and groundwater level. In addition, the Markov and the CA- models were used to forecast an urban growth map. The study points out that Erbil city has experienced remarkable changes to its urban areas which have increased by 278% between 2004 and 2014.  In contrast, the level of groundwater has declined by more than 54%. The prediction model result of the CA-Markov also indicated that built up areas would continue to increase by 37% to 64% between 2020 and 2025; the average of groundwater depth therefore will continue to decrease by 23% in 2025, depending on regression analysis.

Keywords: groundwater level, urbanization, remote sensing, prediction groundwater depth, regression analysis