Development of tools for improved groundwater management using satellite imagery, field data, and hydrological modeling

Project: ResearchInternational collaboration

Research areas and keywords


  • Groundwater, InSAR, Management, TRMM, Precipitation


The planned project is a multidisciplinary research cooperation between the Center for
Groundwater Evaluation and Management at Stanford University and the Department of Water
Resources Engineering at Lund University. The project aim is to develop a new method to increase
the quality of subsurface water monitoring/management and to decrease the currently high costs
for field measurements with the aid of satellite imagery. The intention is to combine the
hydrological modeling knowledge of the Water Resources Engineering Department with
geophysics and remote sensing knowledge of the world leading scholars at the Center for
Groundwater Evaluation and Management at Stanford University to advance existing approaches
to groundwater management.
We will investigate ways in which satellite measured land deformation data can be used to
interpolate and extrapolate hydraulic head measurement in time and space. The ultimate goal for
this multidisciplinary approach is to create centralized systems for monitoring and modeling of
subsurface water resources. The expected results of this study will have a significant contribution
in irrigated agricultural sustainability by developing new methods to increase the quality of
subsurface water monitoring and by decreasing costs for field soil water and groundwater
measurements. This will significantly advance existing approaches to groundwater management
and may specifically be a boost for groundwater monitoring in data-poor regions of the world.
Effective start/end date2015/01/012018/12/31

Collaborative partners


Related research output

Hossein Hashemi, Nordin, M., Lakshmi, V., Huffman, G. J. & Knight, R., 2017 Sep, In : Journal of Hydrometeorology. 18, p. 2491-2509 19 p.

Research output: Contribution to journalArticle

Hossein Hashemi, Matias Nordin, Venkat Lakshmi, and Rosemary Knight, 2016 Dec 12.

Research output: Contribution to conferencePoster

View all (2)