Estimating groundwater abstraction for irrigation in a data-scarce semi-arid region using optical and InSAR time-series analysis: the Tensift catchment, Morocco

Abstract

In Morocco, the expansion of irrigated agriculture has intensified groundwater abstraction and increased pressure on overexploited aquifer systems. Moreover, the substantial lack of pumping measurement data represents a critical limitation for water resources management. To address this gap, the present study quantifies groundwater abstraction at the perimeter scale during agricultural season (2015–2016) in the Tensift catchment, using an integrated methodology combining optical and radar remote sensing (Sentinel-1,-2) with field-based observations. The results show that the total groundwater abstraction reached 4.13 × 10 6 m 3 with a monthly average of 344,515 m 3 . During the April–August period, groundwater supplied 36.1% of crop water requirements, while dam releases contributed 63.9%. These estimates were validated against pumping records from monitoring wells, where field measurements quantified groundwater and dam release contributions of 45% and 55%, respectively. The water balance assessment indicated a total agricultural water supply of 18.8 × 10 6 m 3 .yr −1 , consistent with crop water requirements estimated at 17.8 × 10 6 m 3 .yr −1 . InSAR-derived land subsidence analysis revealed marked spatial heterogeneity, with maximum subsidence rates reaching 6.5 mm.yr −1 , concentrated in the northern sector and isolated central clusters. Overlap analysis showed a co-occurrence rate of 70.6% between high-abstraction and subsidence zones. The spatial Pearson correlation between land subsidence and groundwater abstraction ranges from 0.39 to 0.71. This study demonstrates that the proposed approach provides a robust and scalable framework for groundwater abstraction monitoring in data-scarce environments.