Continuous data assimilation for downscaling large-footprint soil moisture retrievals

Muhammad U. Altaf, Raghavendra B. Jana, Ibrahim Hoteit, Matthew F. McCabe

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Soil moisture is a key component of the hydrologic cycle, influencing processes leading to runoff generation, infiltration and groundwater recharge, evaporation and transpiration. Generally, the measurement scale for soil moisture is found to be different from the modeling scales for these processes. Reducing this mismatch between observation and model scales in necessary for improved hydrological modeling. An innovative approach to downscaling coarse resolution soil moisture data by combining continuous data assimilation and physically based modeling is presented. In this approach, we exploit the features of Continuous Data Assimilation (CDA) which was initially designed for general dissipative dynamical systems and later tested numerically on the incompressible Navier-Stokes equation, and the Benard equation. A nudging term, estimated as the misfit between interpolants of the assimilated coarse grid measurements and the fine grid model solution, is added to the model equations to constrain the model's large scale variability by available measurements. Soil moisture fields generated at a fine resolution by a physically-based vadose zone model (HYDRUS) are subjected to data assimilation conditioned upon coarse resolution observations. This enables nudging of the model outputs towards values that honor the coarse resolution dynamics while still being generated at the fine scale. Results show that the approach is feasible to generate fine scale soil moisture fields across large extents, based on coarse scale observations. Application of this approach is likely in generating fine and intermediate resolution soil moisture fields conditioned on the radiometerbased, coarse resolution products from remote sensing satellites.

Original languageEnglish
Title of host publicationRemote Sensing for Agriculture, Ecosystems, and Hydrology XVIII
EditorsChristopher M. U. Neale, Antonino Maltese
ISBN (Electronic)9781510604001
ISBN (Print)978-1-5106-0401-8
Publication statusPublished - 2016
Externally publishedYes
EventRemote Sensing for Agriculture, Ecosystems, and Hydrology XVIII - Edinburgh, United Kingdom
Duration: 26 Sep 201628 Sep 2016

Publication series

NameProceedings of SPIE


ConferenceRemote Sensing for Agriculture, Ecosystems, and Hydrology XVIII
Country/TerritoryUnited Kingdom


  • CDA
  • Continuous Data Assimilation
  • Modeling
  • Remote Sensing
  • Scaling
  • Soil Moisture
  • Vadose Zone


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