Monitoring spatiotemporal variation of groundwater level and salinity under land use change using integrated field measurements, GIS, geostatistical, and remote-sensing approach: case study of the Feija aquifer, Middle Draa watershed, Moroccan Sahara

Environ Monit Assess. 2021 Nov 4;193(12):769. doi: 10.1007/s10661-021-09581-2.

Abstract

The cultivation of watermelons has been a fast growing agriculture industry in the arid, desert regions of Morocco, relying on groundwater pumping and transformation of rangelands to farms due to growing demand for the fruit in national and international markets. This study aims to measure the impact of watermelon expansion on groundwater resources in the Feija Basin, which is one of the largest watermelon cultivation areas in Southern Morocco. Field measurements, statistics, Kriging interpolation, and regression methods were used to measure the temporal variations in the groundwater level (GL) and salinity between 2013 and 2018 to determine the correlation between different parameters. Remote sensing data was also used to monitor the watermelon cultivation expansion. Results show a rapid expansion of agricultural areas from just 185.11 ha in 2007 to 2560.1 ha in 2018. The groundwater level declined rapidly by about 10 m below ground level during the 5 years of the study period. Additionally, the decline was accompanied by a significant increase in electrical conductivity (salinity) values over the same time interval from 1077.55 to 1211.9 µS/cm. As a consequence of the continuous overexploitation and unsustainable management, a lot of wells have run dry and there have been drinking water shortages in the city of Zagora, the closest city nearby. Results can help target efforts to improve the implementation of conservation strategies to ensure the sustainability of water use and food production in this region of Morocco.

Keywords: Cover change; Feija Plain; Groundwater depletion; Kriging; Land use; Remote-sensing; WEAP.

MeSH terms

  • Agriculture
  • Environmental Monitoring
  • Geographic Information Systems
  • Groundwater*
  • Salinity*