Towards Sustainable Groundwater Management: Predicting Deformation Scenarios with Coupled Hydrogeophysical Models
Abstract
Land subsidence due to groundwater extraction can cause a permanent loss of groundwater storage, and thus mitigating this is crucial for sustainable groundwater management. One challenge in effective mitigation is accurately predicting the effect of groundwater pumping on land deformation due to uncertainty in subsurface hydrostratigraphy. In this study, we demonstrate how a coupled hydrogeophysical model, combining geophysical and InSAR data, can improve estimates of subsidence by providing information about the subsurface layers that are deforming. Using this model, we estimate future scenarios of subsidence, and the potential of managed aquifer recharge for reducing subsidence. We find that if no management changes are made, roughly ~2 m of subsidence will occur from 2019 to 2038, but that active managed aquifer recharge could reduce land subsidence by as much as ~4 m. This model can enable water managers to mitigate subsidence by prioritizing areas for managed aquifer recharge.
Recommended Citation
R. G. Smith and R. Knight, "Towards Sustainable Groundwater Management: Predicting Deformation Scenarios with Coupled Hydrogeophysical Models," International Geoscience and Remote Sensing Symposium (IGARSS), pp. 5061 - 5064, IEEE Geoscience and Remote Sensing Society, Oct 2020.
The definitive version is available at https://doi.org/10.1109/IGARSS39084.2020.9324482
Meeting Name
International Geoscience and Remote Sensing Symposium, IGARSS 2020 (2020: Sep. 26-Oct. 2, Virtual)
Department(s)
Geosciences and Geological and Petroleum Engineering
Research Center/Lab(s)
Center for High Performance Computing Research
Keywords and Phrases
climate change; groundwater; InSAR; near-surface geophysics; subsidence
International Standard Book Number (ISBN)
978-172816374-1
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2020 IEEE Geoscience and Remote Sensing Society, All rights reserved.
Publication Date
02 Oct 2020
