The use of geographic information systems and remote sensing to evaluate climate change effect on groundwater: application to Mostaganem Plateau, Northwest Algeria

Abstract

Effects of climate change in semi-arid areas occur in drought events, which affect aquifers whose recharge depends essentially on precipitation. The objective of this study is to evaluate the relationship between depth to groundwater (DTW), precipitation, Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST), in the alluvial aquifer of Mostaganem Plateau, Algeria over 2000, 2005, 2010-2011 and 2014-2015. This is caried out through an adaptive methodology, using remote sensing, Geographic Information Systems (GIS), and statistical analysis: correlation analysis and Multiple Linear Regression (MLR). The results indicate a 62 mm decline in precipitation from 2000 to 2015, inducing shifts in spatial patterns. This resulted in an increase of DTW (4 m to 10 m). The strong negative correlation between decreased precipitation and increased DTW, supported by an R2 value of -0.80, is evident. Moreover, NDVI and LST values increased notably by 0.034 and 3.38°C, respectively. The relationship between DTW, NDVI, and LST showed a diminishing negative correlation. The MLR reaffirmed the influence of precipitation and highlighted the impact of human activity on DTW and drought indicators effectiveness. High NDVI values indicated intensive groundwater pumping, while elevated LST contributed to DTW decrease due to increased evaporation rates caused by changes in crop types resulting from human actions. This study contributes to the understanding of the dynamic interactions between DTW, precipitation, and anthropogenic activities and gives insight to decision makers regarding irrigation strategies.

Keywords

• climate change
• Land Surface Temperature (LST)
• Normalized Difference Vegetation Index (NDVI)
• precipitation
• Multiple Linear Regression (MLR)
• Geographic Information Systems (GIS)