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EEWR Brown Bag Seminar with Noemi Vergopolan da Rocha, Graduate Student

Speaker: Noemi Vergopolan da Rocha, Graduate Student
Series: EEWR Brown Bag Seminars
Location: Engineering Quad E225
Date/Time: Friday, May 3, 2019, 12:00:00 p.m. - 01:00:00 p.m.


Hyper-resolution hydrological modeling and remote sensing for soil moisture prediction at the decision-making scales

Noemi Vergopolan da RochaSoil moisture plays an essential role in controlling the exchanges of water, energy, and carbon at the land-atmosphere interface, with important implications for hydrology and water management. Microwave-based satellite remote sensing offers unique opportunities for monitoring of soil moisture at large-scale and frequent temporal intervals. However, the coarse spatial resolution of the spaceborne sensors limits its applications for field-scale decision making.

On Friday, I will present a downscaling framework that combines a hyper-resolution land surface model (LSM), a  brightness temperature radiative transfer model (RTM), and a Kalman filter to downscale the 36-km Soil Moisture Active Passive (SMAP) product to 30-m spatial resolution. The approach is demonstrated using HydroBlocks simulations over the United States. The results show substantial improvements in terms of correlation and bias when validated against in-situ observations. This work highlights the promising potential of hyper-resolution land surface modeling to bridge the gap between coarse-scale remotely-sensed retrievals and fine-scale water management applications.