Efficient monitoring of groundwater level changes using compressive remote sensing

In this paper, we propose and discuss the applicability of compressive sensing (CS) for the remote measurement and analysis of groundwater level changes. For this purpose, we consider three watersheds in Turkey and utilize the data acquired by the Gravity Recovery and Climate Experiment (GRACE) satellite at these watersheds. These watersheds are Fırat (Euphrates), Kızılırmak, and Büyük Menderes (Greater Menderes). The data collected by the GRACE satellite have a temporal resolution on the order of months, however, due to operation and maintenance considerations it is known that some of the GRACE data may be missing. Using the time series data collected between 2002 and 2019 at these three watersheds we show that the time series of the groundwater table (GWT) can be reconstructed using CS which utilizes fewer samples than the classical Shannon’s theorem states. Thus, when the CS technique is utilized, measurement times and hardware storage requirements of groundwater sensing systems can be significantly reduced where some errors can be observed in the reconstruction of the GWT level. In some cases, such parameters can be exactly reconstructed by CS even in the presence of missing data if certain sparsity and sampling conditions are satisfied. The CS-based GWT reconstruction technique proposed in this paper can also be extended to measure and analyze other types of data such as in situ groundwater levels, groundwater velocities, and groundwater volume flux data in hydrology and hydraulics.