New study shows how to account for snowpack loading in groundwater assessments

The Sierra Nevada Mountains accumulate massive amounts of snow, which can cause parts of the Central Valley, located to the west, to sink. This phenomenon has complicated groundwater assessments because the sinking is often mistaken as a depletion of aquifers. However, a recent study conducted by Stanford University has provided a solution to this problem, offering a more precise method of measuring groundwater levels.

The study, published in Geophysical Research Letters on April 28, proposes using satellite-based measurements of surface changes over time to monitor groundwater in regions like California’s Central Valley, where agriculture heavily relies on groundwater for irrigation during dry periods. However, to utilize this method effectively, it is crucial to understand the underlying causes of observed changes in elevation.

The research reveals that the accumulation of snow and ice in the Sierra Nevada during California’s wet season is the primary factor contributing to elevation changes in 60% of the Central Valley. When substantial amounts of snowfall occur in the Sierra, as was the case in the recent winter, with tens or even hundreds of feet of snow piling up, the valley floor sinks by a fraction of an inch to an inch.

While scientists had long suspected that snowpack in the nearby mountains affected groundwater assessments based on elevation changes, they lacked a quantitative approach to measure this impact. The study’s lead author, Seogi Kang, explains that they have now successfully untangled and isolated the effects of elevation changes caused by groundwater levels and snowpack loading.

Failure to account for the influence of snowpack loading could lead groundwater managers, who increasingly rely on elevation-based monitoring methods, to underestimate the actual water levels. Given the increasing frequency of weather extremes such as floods and droughts due to climate change, along with the need for long-term sustainability of groundwater resources, it is vital to provide managers with the latest technologies and insights. This study represents a significant advancement in using satellite data to accurately monitor the volume of stored groundwater in the Central Valley, according to senior author Rosemary Knight, a professor of geophysics at Stanford’s Doerr School of Sustainability.

The view from on high

To conduct their study, Kang and Knight extensively analyzed five years’ worth of elevation data using a technique called interferometric synthetic aperture radar (InSAR). InSAR involves measuring the time it takes for radar signals to bounce back from specific locations on the ground to a satellite at different intervals.

By examining these data over an extended period, valuable insights into underground water resources can be gained. The layers of sediment and clay beneath the surface of the Earth act as a sponge, and changes in groundwater levels affect the compaction of these layers, causing the ground surface to sink. In essence, excessive pumping of groundwater for drinking water and irrigation depletes aquifers, leading to the sinking of the land.

The InSAR dataset employed in this study covers nearly the entire 18,000 square miles of the Central Valley. Measurements were taken, on average, once a week between 2015 and 2019. Although the resolution is not flawless, with each data point representing an area roughly equivalent to a football field, it far surpasses traditional groundwater monitoring techniques that involve sporadic well drilling throughout the vast Central Valley and infrequent readings.

The snowpack effect

Kang developed a statistical machine learning program to effectively analyze the vast amount of InSAR data. The program clustered the data based on variations over time, allowing for the identification of similar patterns. These patterns were then compared to monthly average snowpack data in the Sierra Nevada Mountains during the same timeframe. This analysis enabled the researchers to distinguish between elevation changes caused by the snowpack effect and those resulting from the groundwater system in different parts of the Central Valley.

By utilizing InSAR data to fill in significant gaps in current groundwater monitoring practices, the Stanford researchers aim to provide valuable support and insights for groundwater management decisions. This includes determining when and where to limit pumping and how to allocate resources for new water delivery infrastructure.

The importance of sustainable water supply in the Central Valley, which plays a significant role in food production, is emphasized by Kang. Through a better understanding of the hydrogeophysics at play in the region, they strive to ensure the long-term sustainability of agricultural productivity in the area.

Source: Stanford University

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