A feasible methodology for groundwater resource modelling for sustainable use in sparse-data drylands: Application to the Amtoudi Oasis in the northern Sahara.

In a previous paper, the Amtoudi Oasis, a remote area in the northern Sahara in southern Morocco, was chosen to model the dynamics of groundwater-dependent economics under different scenarios of water availability, both the wet 2009-2010 and the average 2010-2011 hydrological years. Groundwater imbalance was reflected by net aquifer recharge (R) less than groundwater allotment for agriculture and urban uses in the average year 2010-2011. Three key groundwater sustainability issues from the hydrologic perspective were raised for future research, which are addressed in this paper. Introducing a feasible methodology for groundwater resource modelling for sustainable use in sparse-data drylands, this paper updates available databases, compiles new databases, and introduces new formulations to: (1) refine the net groundwater balance (W) modelling for years 2009-2010 and 2010-2011, providing the magnitude of net lateral inflow from adjacent formations (RL ), the largest R component contributing to the oasis; (2) evaluate the non-evaporative fraction of precipitation (P) (B) from 1973 onward as a proxy of the potential renewable water resource available for use; and (3) define the critical balance period for variables to reach a comparable stationary condition, as prerequisite for long-term modelling of W. RL was about 0.07-fold P and 0.85-fold R. Historical yearly B-to-P ratios were 0.02 for dry, 0.04 for average, and 0.07 for wet hydrological years; the average yearly P being 124mm. A critical 17-year balance period with stable relative error below 0.1 was defined from the 44-year P and B time-series statistical study. This is the monitoring period proposed for the stationary evaluation of the variables involved in the long-term modelling of W. This paper seeks to offer a feasible methodology for groundwater modelling addressed for planning sustainable water policies in sparse-data drylands.