Estimating Aquifer System Storage Loss With Water Levels, Pumping and InSAR Data in the Parowan Valley, Utah. Issue 4 (26th April 2023)
- Record Type:
- Journal Article
- Title:
- Estimating Aquifer System Storage Loss With Water Levels, Pumping and InSAR Data in the Parowan Valley, Utah. Issue 4 (26th April 2023)
- Main Title:
- Estimating Aquifer System Storage Loss With Water Levels, Pumping and InSAR Data in the Parowan Valley, Utah
- Authors:
- Smith, Ryan
Li, Jiawei
Grote, Katherine
Butler, Jim - Abstract:
- Abstract: In the Parowan Valley of Utah, groundwater levels have declined by as much as 30 m over the past 50 years with accompanying subsidence rates of up to 5 cm/year. Traditional methods to estimate groundwater storage change use a combination of groundwater level and storativity estimates, but there is often considerable uncertainty in these. In this study, we demonstrate a new method that relies on a combination of geodetic data from InSAR, as well as groundwater level and pumping data, to estimate both the total groundwater storage loss and the percentages of storage loss in fine‐ and coarse‐grained layers within an aquifer system. We find that when aggregated over all of Parowan Valley, fine‐ and coarse‐grained layers account for roughly equal portions of the total groundwater storage loss. However, in confined aquifers, fine‐grained layers account for most of the storage loss. This has important implications on the source of groundwater in depleting aquifer systems, as many models do not account for fine‐grained layers as a source of water. We find that in the Parowan Valley, the aquifer depletion is roughly 12.5% of the volume of pumped groundwater, meaning that the remainder of pumped groundwater is sourced from net inflow. This study presents the first method that combines geodetic and in situ groundwater data to provide estimates of groundwater storage change that account for both coarse‐ and fine‐grained intervals, which are typically present in significantAbstract: In the Parowan Valley of Utah, groundwater levels have declined by as much as 30 m over the past 50 years with accompanying subsidence rates of up to 5 cm/year. Traditional methods to estimate groundwater storage change use a combination of groundwater level and storativity estimates, but there is often considerable uncertainty in these. In this study, we demonstrate a new method that relies on a combination of geodetic data from InSAR, as well as groundwater level and pumping data, to estimate both the total groundwater storage loss and the percentages of storage loss in fine‐ and coarse‐grained layers within an aquifer system. We find that when aggregated over all of Parowan Valley, fine‐ and coarse‐grained layers account for roughly equal portions of the total groundwater storage loss. However, in confined aquifers, fine‐grained layers account for most of the storage loss. This has important implications on the source of groundwater in depleting aquifer systems, as many models do not account for fine‐grained layers as a source of water. We find that in the Parowan Valley, the aquifer depletion is roughly 12.5% of the volume of pumped groundwater, meaning that the remainder of pumped groundwater is sourced from net inflow. This study presents the first method that combines geodetic and in situ groundwater data to provide estimates of groundwater storage change that account for both coarse‐ and fine‐grained intervals, which are typically present in significant amounts in the major unconsolidated aquifer systems of the world. Plain Language Summary: As surface water becomes more scarce, groundwater represents an important source of freshwater. However, it is being depleted in many basins of the western US and world. The Parowan Valley, in southwest Utah, has seen groundwater levels decline by as much as 30 m over the past 50 years. This has resulted in subsidence rates of up to 5 cm/year. Monitoring groundwater storage loss is critical for implementing sustainable groundwater management plans. Subsidence can be measured with a satellite data set called InSAR (Interferometric Synthetic Aperture Radar) with high accuracy. This can then be coupled with ground‐based measurements to improve our understanding of groundwater storage loss. We implement this method in the Parowan Valley, and find that roughly half of the estimated groundwater storage loss comes from consolidation of fine‐grained materials within the aquifer, which are typically ignored in groundwater budgets. We also find that groundwater depletion is roughly 12.5% of the volume of pumped groundwater, meaning that if pumping were reduced by that amount, depletion of groundwater would likely cease. However, changing recharge and inflow of groundwater could result in renewed depletion in the future (5–10 years), and re‐assessing the water budget regularly is crucial for effective management. Key Points: New method developed to estimate groundwater storage loss using InSAR, groundwater‐level and pumping data Fine‐grained layers account for most aquifer storage loss in confined aquifers Water lost from fine‐grained layers is a significant but unsustainable source of water for confined aquifers … (more)
- Is Part Of:
- Water resources research. Volume 59:Issue 4(2023)
- Journal:
- Water resources research
- Issue:
- Volume 59:Issue 4(2023)
- Issue Display:
- Volume 59, Issue 4 (2023)
- Year:
- 2023
- Volume:
- 59
- Issue:
- 4
- Issue Sort Value:
- 2023-0059-0004-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2023-04-26
- Subjects:
- InSAR -- groundwater -- sustainability -- groundwater management -- groundwater storage
Hydrology -- Periodicals
333.91 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1944-7973 ↗
http://www.agu.org/pubs/current/wr/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1029/2022WR034095 ↗
- Languages:
- English
- ISSNs:
- 0043-1397
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9275.150000
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British Library HMNTS - ELD Digital store - Ingest File:
- 27108.xml