A team of hydrologists has produced what its members describe as a more complete way to track water in the Colorado River basin, a development that comes as Arizona braces for continued, mandatory reductions in its share of river deliveries. The researchers modified a standard modeling tool to incorporate satellite measurements of near-surface soil moisture and basin-scale changes in total water storage, bringing previously unobserved components of the system into routine forecasts. Lead author Zhaocheng Wang, an ASU research scientist, said the results show that treating river flow alone as the primary indicator of availability can miss important processes elsewhere on the landscape.
The Colorado River provides water to roughly 40 million people across seven U.S. states and Mexico, and prolonged drought combined with rising temperatures has pushed major reservoirs to historically low levels. In that context, even modest improvements in forecasts can have wide-ranging consequences for decision-makers who set reservoir releases, implement conservation measures and allocate shortages among states and users. The study was carried out through the Center for Hydrologic Innovations, a pillar of the Arizona Water Innovation Initiative at ASU’s Julie Ann Wrigley Global Futures Laboratory, in collaboration with the Ira A. Fulton Schools of Engineering and with support from NASA’s Earth Science Division and the Central Arizona Project.
Dam and intake towers on the Colorado River — infrastructure whose reservoir levels and releases factor into the ASU-led study sharpening basin water forecasts.
At the center of the work is the Variable Infiltration Capacity model, commonly known as VIC, which hydrologists use to simulate how precipitation becomes runoff, how soils wet and dry, and how water moves through a basin. For decades many such models have been calibrated primarily to match streamflow observations — the volume of water moving past key gauging points — but that practice can produce a model that reproduces river flows while misrepresenting how much water is stored in snowpacks, soils and underground. The new research demonstrates that adding satellite-derived observations into the calibration and evaluation process reduces those blind spots and yields a model that aligns with multiple independent measures of the basin’s water state.
Satellite missions operated by NASA were used to provide measurements not readily accessible from ground observations: near-surface soil moisture and changes in total water storage that include contributions from groundwater. When those datasets were integrated with the VIC framework, the model did more than reproduce flows at downstream measurement points; it also matched the timing and magnitude of changes in soil moisture and the basin-scale gains and losses of stored water. The research team reports that the enhanced model successfully tracked how water is stored during wet periods and depleted during drought, processes that are critical to understanding how much water will ultimately reach key reservoirs such as Lake Powell.
Satellite view of Colorado River reservoirs and the adjacent urban area, the type of remote-sensing imagery used in the ASU study to track hidden water dynamics.
Water managers rely on model outputs to make operational and policy decisions, and the study highlights ways that conventional approaches can lead to overestimates of available water or delays in recognizing emerging shortages. Dry soils, for example, can soak up a large fraction of incoming moisture from rain or snowmelt, reducing the runoff that ultimately contributes to river flow and reservoir inflows. Swastik Ghimire, a co-author on the study and recipient of a first-place research award from the Central Arizona Project, pointed to modeling results that show even a near-average snowpack may fail to produce expected streamflow if antecedent soil moisture is low. That linkage between soil moisture and eventual river delivery is one of the pathways the enhanced model captures more explicitly.
Project participants emphasize practical consequences for operations on the Colorado Basin. For agencies like the Central Arizona Project, which coordinates deliveries and drought responses for Arizona, a more holistic picture of hydrologic conditions strengthens planning around conservation triggers, reservoir release strategies and interstate negotiations. Nolie Templeton, a senior policy analyst in CAP’s Colorado River Programs Department, said the study’s broader representation of hydrologic processes yields “additional insights to what CAP ultimately needs to know: how much water is in the river, and how that can vary depending on wet or dry conditions.” The ability to spot hidden declines in soil moisture or subsurface stores earlier could allow managers to act sooner to stretch supplies or reduce risk to critical infrastructure.
The researchers acknowledge that uncertainty still remains in aspects of the system that are difficult to observe and represent, particularly deeper groundwater processes and limitations in the satellite products used for evaluation. They call for continued work that combines multiple observational platforms with model development to narrow those uncertainties. Enrique Vivoni, the study’s senior author and a professor of hydrosystems engineering, said the improvements represent an important step toward a more complete understanding of basin hydrology and stressed the necessity of better monitoring and prediction as the Southwest experiences increasing water stress.
The study, published in Scientific Reports, demonstrates how remote sensing can be harnessed to improve conventional hydrologic tools and provides a pathway for operational centers and water managers to incorporate broader observational evidence into short- and long-term forecasting. By using satellite measurements to peer into soils and subsurface storages that are not captured by stream gauges alone, the research offers a technical advance intended to make water forecasts in the Colorado River basin more robust as the region adapts to persistent drought and evolving demand patterns.