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Assessment of groundwater vulnerability using remote sensing, susceptibility index, and WetSpass model in an arid region (Biskra, SE Algeria)

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Abstract

Biskra region currently shows signs of stress and a high risk of groundwater contamination by various chemicals and pesticides. For this purpose, a modified integrated susceptibility index (SI) is coupled with remote sensing (RS) and WetSpass model to assess the sensitivity of the groundwater and the risk of pollution in the most exploited aquifer (Quaternary aquifer) in the study area. The results of the modified SI model show that a major part of the aquifer is at risk of contamination if the farmers do not implement good agricultural practices. Four sensitivity levels are considered, reflecting a vulnerability rating that ranges from low to very high. The very high category is observed in the agricultural areas with an estimated pollution index ranging from 84 to 90.57, while a large part of the aquifer shows a high vulnerability to contamination (64 < SI ≤ 84). This category is found in areas characterized by the dominance of bare soil. In urban areas, the vulnerability level decreases to low category (37 < SI ≤ 45). However, the area of forests is classified as moderate to vulnerability (45 < SI ≤ 64). The different statistical and GIS methods confirm the reliability of the obtained SI map. The combination of the SI method with WetSpass model and RS can give a reliable map to help and assist the authorities and decision-makers in groundwater resources planning and the implementation of monitoring programs and networks to control the quality of groundwater in arid environments.

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Khomri Zinne-eddine: Writing original draft, conceptualization, and formal analysis; Mohamed Naçer Chabaca: Writing review and editing; Samir Boudibi: Mapping, software modeling, conceptualization, and interpretation of the results; Sarmad Dashti Latif: Writing review and editing.

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Correspondence to Sarmad Dashti Latif.

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Khomri, Ze., Chabaca, M.N., Boudibi, S. et al. Assessment of groundwater vulnerability using remote sensing, susceptibility index, and WetSpass model in an arid region (Biskra, SE Algeria). Environ Monit Assess 194, 505 (2022). https://doi.org/10.1007/s10661-022-10189-3

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