Spain’s worst recorded drought in 2024 is literally lifting the land surface in the south-east, as lost water weight allows the ground to spring upward. This project uses GPS stations to measure that vertical displacement and then reverse-engineers how much terrestrial water storage has been lost during drought periods. Current monitoring relies on sparse well data and satellite gravity readings that lack the temporal resolution to track rapid changes. By inverting decade-long GNSS displacement records, the researchers aim to produce continuous, high-accuracy estimates of water loss and, crucially, to distinguish between surface water depletion and groundwater over-extraction from collapsing aquifer systems. If successful, the technique could give regional water managers a cheap, real-time drought indicator that works even where monitoring networks are thin. The work is applied fundamental science: it tests whether geodetic inversion can become a reliable operational tool for allocating increasingly scarce water resources across arid southern Europe.
View original technical description
This project aims to study the interannual trends of terrestrial water storage (TWS) in the arid region of south-eastern Spain. Over the recent years, southern Europe has faced multiple severe droughts, brought about by complex climactic drivers and anthropogenic effects. Spain has suffered recurring droughts throughout the 2000s, with the latest in 2024 being the worst recorded drought in Spanish history. The 6th IPCC report projected an increase of drought severity, duration and frequency in warmer climates, in part due to global warming exacerbating extreme weather events. The monitoring of TWS in this deeply drought-prone region is vital to enable appropriate management and allocation of increasingly vulnerable water resources in the future. Terrestrial water availability is a crucial component of the hydrological cycle and an important indicator of drought. It is influenced by both climate variability and climate change, as well as human impacts on the water cycle. Therefore, understanding its spatiotemporal variability is of paramount importance for assessing the effects of the climate on TWS. Geodetic techniques, that utilise GNSS and GRACE, can measure the vertical land displacement and gravitational changes that occur in response to surface water loading changes, and invert the measurements to estimate TWS loss. During periods of drought, the decrease in surface water and groundwater loading cause vertical displacements, which occurs through two processes. A decrease in surface water loading causes an elastic (reversible) response, resulting in land uplift. However, where underground aquifer systems are being overexploited, changes in pore structure within the aquifer system can cause poroelastic land subsidence. This project will use Global Navigation Satellite System (GNSS) stations in south-eastern Spain to monitor changes in surface deformation over time. We will invert the vertical displacement time series from the past decade to estimate the loss of TWS during drought periods. This can be further applied to studying the partitioning of TWS, using poroelastic subsidence measurements in conjunction with auxiliary hydrological data to isolate groundwater storage changes. This will aid future management of groundwater resources. Subsequently, we will use a GNSS and Gravity Recovery and Climate Experiment (GRACE) joint inversion to increase the spatial resolution of data in the study region. GRACE provides measurements in gravity anomalies, caused by changes in TWS. GNSS provides regular, highly accurate measurements of vertical displacement signals, and GRACE can provide monthly estimates of TWS but with a continuous spatial resolution. Combining these two sources of data may improve the estimates of TWS changes. There have been no GNSS or GRACE TWS studies focusing thus far on south-eastern Spain. This project aims to demonstrate that geodetic techniques can successfully monitor TWS changes over time, and that vertical displacement signals can be a reliable drought indicator for the future, aiding policy makers in their water management decisions.
Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.
Is something wrong? Let us know