The San Luis Valley (SLV) is an 8000 km2 valley, located on the northern side of the Colorado-New Mexico border.
The San Luis valley has a vibrant agricultural economy that is highly dependent on the effective management of the limited water resources. The Rio Grand Decision Support System (RGDSS), a Colorado-state-funded project includes a hydrogeologic database and a MODFLOW finite-difference groundwater flow model. The critical challenge for the RGDSS, is acquiring sufficient data to characterize the spatially heterogeneous, time-varying behavior of the groundwater system.
Interferometric Synthetic Aperture Radar (InSAR) has emerged as a remote sensing method that can provide data to help constrain large-scale hydrogeologic models. The question we ask: How can we use InSAR data to model the response of the aquifer system?
Demonstrated the advantages of InSAR measurements for basin-wide characterization of aquifer storage properties and groundwater levels over an entire agricultural basin (Chen et al., 2016).
Designed a new algorithm for retrieving InSAR deformation measurements over areas with severe vegetation decorrelation such as SLV using adaptive phase interpolation between persistent scatterer (PS) pixels (Chen et al., 2015).
Estimated the uncertainty in the InSAR deformation measurements and propagated this uncertainty through the data processing chain (Reeves et al., 2014a).
Adapted a time-series processing algorithm such that high quality data are selected based upon the uncertainty of the final deformation time-series (Reeves et al., 2014b).
Identified similar seasonal trends in hydraulic head measurements and InSAR deformation measurements in the San Luis Valley (Reeves et al., 2011).
Verified that high quality InSAR deformation measurements can be made in agricultural areas like the San Luis Valley (Reeves et al., 2011).
Using the relationship between InSAR measured deformation data and hydraulic head data we are investigating ways that the deformation data can be used to interpolate and extrapolate hydraulic head measurements in time and space.
Chen, J. (2016), Using spaceborne imaging radar to characterize groundwater levels and aquifer properties, The University of Texas at Austin, Austin, Texas
Chen, J., H. A. Zebker and R. Knight (2015), A persistent scatterer method for retrieving accurate InSAR ground deformation maps over vegetation-decorrelated areas, American Geophysical Union, Fall Meeting 2015, San Francisco, California
Chen, J., R. Knight and H. A. Zebker (2014), Mapping groundwater levels in the San Luis Valley, Colorado, using InSAR, Seismo Lab Seminar, California Institute of Technology, Pasadena, California
Chen, J., R. Knight and H. A. Zebker (2014), The use of InSAR data to map hydraulic head levels in the San Luis Valley, Colorado, American Geophysical Union, Fall Meeting 2014, San Francisco, California.