Hydrologic Sciences and remote sensing
University of Minnesota
College of Science & Engineering
Department of Civil, Environmental and Geo-Engineering
Saint Anthony Falls Laboratory
Tel: (612) 301-1483
Office: 378 (SAFL), 162 (CEGE)
Curriculum Vitae: (PDF)
Physical and data-science hydrology, satellite hydrometeorology, microwave remote sensing, inverse problems, data assimilation, land-atmosphere interactions, precipitation, soil moisture and snow processes.
Statistical learning, mathematical optimization, image processing, computational harmonic analysis and Earth big-data analytics.
Postdoctoral Research, Georgia Institute of Technology
Ph.D., University of Minnesota, Water Resources and Hydrology
M.Sc., University of Minnesota, Mathematics
M.Sc., Iran University of Science and Tech., Environmental Engineering
M.Sc., Iran University of Science and Tech., Structural Engineering
B.Sc., Iran University of Science and Tech., Civil Engineering
Hydrologic sciences and remote Sensing (HydSens) laboratory is an academic team in the Saint Anthony Falls Laboratory (SAFL) at the University of Minnesota.
The overarching goal is to uncover physical mechanisms describing hydrologic water cycle through modern data science approaches and provide solutions for sustainable developments across water and food systems.
November 2021, Ardeshir Ebtehaj received funding from the NASA's Precipitation Measurement Mission (PMM) Science Team to advance the knowledge in convective precipitation data assimilation and nowcasing through theories of optimal mass transport, machine learning and artificial intelligence.
November 2021, HydSens received funding from the office of vice president for research (OVPR) to purchase a spectroradiometer for advancing the science of environmental remote sensing.
Aug 2020, Ardeshir Ebtehaj's proposal to the Legislative
Citizen Commission on Minnesota Resources (LCCMR) is selected for funding to advance the knowledge and develop technologies for remote sensing of microplastics in surface waters.
July 2020, Ardeshir Ebtehaj received funding from NASA's Remote Sensing Theory (RST) program in Earth Science to advance our knowledge in inversion of land and atmospheric radiative transfer models for improved remote sensing of frozen components of the hydrologic cycle using satellite data.
May 2020: We released a new global data set of monthly changes in surface soil moisture using the observations by the NASA's Gravity Recovery and Climate Experiment (GRACE) satellite.