The study, led by Stephanie Bringeland of Queen’s University together with colleagues from Aquanty Inc., the Canadian Geodetic Survey, and Alberta Environment and Protected Areas, focused on the Alberta portion of the South Saskatchewan River Basin (SSRB), a vast drainage network spanning the eastern slopes of the Rocky Mountains across roughly 17 percent of Alberta’s land area. This is no sleepy backwater: the basin hosts the Bow, Oldman, and Red Deer Rivers, feeds one of Canada’s most productive agricultural regions, and supplies water to growing cities. Agriculture alone consumes 85 percent of all surface water used in the basin — compared with a national average of just 9 percent — and the Bow, Oldman, and South Saskatchewan Rivers have already reached their allocation limits, meaning no new water rights can be granted.

To track how the basin’s total water budget has shifted, the researchers turned to the Gravity Recovery and Climate Experiment (GRACE) and its successor, GRACE Follow-On. These twin-satellite missions measure tiny variations in Earth’s gravitational field caused by the movement of mass across the planet’s surface. When snow accumulates, soils saturate, or aquifers fill, the ground beneath them becomes fractionally heavier — and the satellites detect it. The result is a monthly estimate of terrestrial water storage anomaly (TWSA): the combined weight of surface water, soil moisture, groundwater, and snow, expressed in centimetres of equivalent water height relative to a 2004–2009 baseline. The team used two independent GRACE processing approaches — NASA’s Jet Propulsion Laboratory mascon solution and a custom method from the Canadian Geodetic Survey — to bracket the range of possible satellite estimates.

Satellite gravimetry, however, has a fundamental limitation: it sees only the sum of all water stores, not the individual components. To unpack that total, the researchers employed HydroGeoSphere (HGS), a fully integrated groundwater–surface water model that simultaneously solves the three-dimensional Richards equation for variably saturated subsurface flow, the two-dimensional diffusion wave equation for overland flow, and Manning’s equation for open-channel river flow. The SSRB implementation is staggering in scale: more than 666,000 nodes and 1.2 million finite elements across twelve mesh layers, 740 distinct porous media zones, and 14,125 kilometres of discretely resolved rivers, all driven by a 10-kilometre-resolution daily climate dataset. The model was validated against weekly naturalized river flows at four gauging stations and groundwater levels at 79 observation wells, showing strong agreement with both.

When the researchers compared the HGS-derived TWSA with the satellite estimates over the 2002–2019 period, the correspondence was striking. Both captured the same seasonal heartbeat — storage peaking in April and May just before spring snowmelt, then bottoming out in August and September — and both reproduced the same interannual swings, including the recovery from the severe 1999–2004 Prairie drought, the decline into the 2008–2010 drought, a wet spell after 2010, and a gradual descent that culminated in drought by spring 2019. The comparison also exposed a telling discrepancy: the GRACE-derived seasonal amplitude (9.2 to 11.1 centimetres of equivalent water height) exceeded the model-based estimates (7.5 to 7.8 centimetres), suggesting that global land surface models and even high-resolution regional models may underestimate seasonal storage swings by 15 to 32 percent.

With the model validated against the satellites, the team could finally dissect the basin’s water storage into its constituent parts. The results were illuminating. Soil moisture proved the most volatile component, swinging dramatically with the seasons and with drought years such as 2003 and 2017. Snowpack showed strong seasonal variability but smaller interannual differences. Groundwater, by contrast, behaved like a slow-moving reservoir — heavily dampened, with a muted seasonal signal but pronounced multi-year cycles. This separation matters enormously for water managers: it revealed, for instance, that the catastrophic 2013 floods in southern Alberta may have been worsened by years of positive groundwater anomalies, which left the landscape with less capacity to absorb the torrential rainfall that triggered the disaster.

The most surprising discovery emerged from a time-frequency analysis of the storage records. Using continuous wavelet transforms and Lomb-Scargle periodograms, the researchers detected a harmonic signal in the basin’s water storage with a period of roughly 2.7 to 3.0 years — and this interannual pulse was strongest not in soils or rivers, but in the groundwater component, which showed a spectral peak of 82 decibels at a 2.8-year period. When the team compared this signal against major oceanic climate indices, the Oceanic Niño Index (ONI) — a measure of sea surface temperature anomalies in the east-central tropical Pacific — emerged as the clear winner. The smoothed interannual component of the basin’s water storage showed a moderate negative correlation with the ONI (correlation coefficient of −0.38), and both series shared the same 2.7–3.0-year periodicity. In plain terms: when the tropical Pacific runs warm during El Niño conditions, southern Alberta tends to run dry, with reduced snowpack and negative water storage anomalies. The North Atlantic Oscillation, by contrast, showed no significant link to the basin’s hydrology.

The implications stretch well beyond academic curiosity. Climate projections indicate that the Canadian Prairies will face more frequent and severe drought as temperatures rise, with evapotranspiration increasing and snowpack declining — one study cited in the paper projects up to an 11 percent decrease in maximum annual snow water equivalent for every degree of warming in the region’s grassland basins. Because snowmelt from the Rocky Mountains supplies roughly 80 percent of the Bow River’s streamflow, shrinking snowpacks threaten the very foundation of the basin’s water supply. At the same time, the character of El Niño itself is changing: multi-year ENSO events are becoming more frequent, and central Pacific El Niño events are increasing relative to their eastern Pacific counterparts. If prolonged warm-phase ENSO episodes translate into extended dry spells in the SSRB, the region could face longer and harsher droughts than its water management systems were designed to withstand.

The researchers are candid about the limitations of their approach. GRACE data has no true ground-truth comparison, so errors can only be estimated theoretically, and any inaccuracies in the models used to correct for effects like glacial isostatic adjustment propagate into the final storage estimates. The HGS model, despite its sophistication, slightly overestimated late-summer storage relative to the satellites, and its cumulative-sum processing method may amplify small errors over time. Yet the study’s central methodological lesson stands: neither satellites nor models alone can fully characterize a complex hydrological system. The satellites provide independent, near-uniform coverage that no network of ground instruments could match in a sparsely populated region, while the model supplies the component-level detail that gravity measurements inherently lack. Together, they form a powerful validation loop.

For the farmers, municipalities, and ecosystems of southern Alberta, the work offers something increasingly precious in a warming world: a clearer picture of where the water is, how it moves, and what drives its comings and goings. By revealing that the basin’s groundwater pulses in step with the tropical Pacific, the study opens the door to longer-lead forecasting of water availability — potentially giving managers months of warning before drought conditions take hold. As the authors note, future work will extend the analysis to the basin’s distinct physiographic regions to identify the primary drivers of storage change in each. In a basin where every new water allocation is already off the table, understanding the invisible rhythms of water storage may be the difference between sustainable management and crisis.

Subject of Research: Terrestrial water storage change in the South Saskatchewan River Basin assessed with GRACE/GRACE-FO satellite gravimetry and integrated hydrological modelling

Article Title: Investigating terrestrial water storage change in a western Canadian river basin with GRACE/GRACE-FO and fully-integrated groundwater – surface water modelling

Article References: Bringeland, S., Frey, S. K., Fotopoulos, G., Crowley, J., Xu, S., Khader, O., Eum, H., Farjad, B., Erler, A. R., & Gupta, A. (2026). Investigating terrestrial water storage change in a western Canadian river basin with GRACE/GRACE-FO and fully-integrated groundwater – surface water modelling. Hydrology and Earth System Sciences, 30(18), 6057-6073. https://doi.org/10.5194/hess-30-6057-2026

Image Credits: AI Generated

DOI: 10.5194/hess-30-6057-2026

Keywords: GRACE, GRACE-FO, terrestrial water storage, groundwater, soil moisture, snowpack, South Saskatchewan River Basin, HydroGeoSphere, El Niño Southern Oscillation, drought, Canadian Prairies, hydrological modelling