2019 CSDMS meeting-086: Difference between revisions

From CSDMS
(Created page with "{{CSDMS meeting personal information template-2019 |CSDMS meeting first name=Elchin |CSDMS meeting last name=Jafarov |CSDMS meeting institute=Los Alamos National Laboratory |C...")
 
No edit summary
 
Line 25: Line 25:
}}
}}
{{CSDMS meeting abstract yes no 2019
{{CSDMS meeting abstract yes no 2019
|CSDMS meeting abstract submit=No
|CSDMS meeting abstract submit=Yes
}}
{{CSDMS meeting abstract title temp2019
|CSDMS meeting abstract title=Estimation of soil properties by coupled inversion of geophysical and hydrothermal data
}}
{{CSDMS meeting abstract template 2019
|CSDMS meeting abstract=Observations of the spatial and temporal evolution of thaw and soil moisture changes are needed to understand thermo-hydrologic dynamics in periglacial regions and to inform models that forecast changes in the Arctic. However, obtaining spatially and temporally distributed observations in the Arctic is difficult. Here we develop and investigate the use and accuracy of the parameter estimation algorithm in recovering soil physical properties. We tested our parameter estimation (PE) approach with synthetic data from a continuously modeled electric resistivity tomography transect and co-located synthetic temperature and soil moisture data. The results indicate that developed PE approach is able to identify synthetic porosities and thermal conductivities.
}}
}}
{{CSDMS meeting abstract title temp2019}}
{{CSDMS meeting abstract template 2019}}
{{blank line template}}
{{blank line template}}

Latest revision as of 15:21, 8 March 2019





Log in (or create account for non-CSDMS members)
Forgot username? Search or email:CSDMSweb@colorado.edu



Browse  abstracts



Estimation of soil properties by coupled inversion of geophysical and hydrothermal data

Elchin Jafarov, Los Alamos National Laboratory Los Alamos New Mexico, United States. elchin@lanl.gov


Observations of the spatial and temporal evolution of thaw and soil moisture changes are needed to understand thermo-hydrologic dynamics in periglacial regions and to inform models that forecast changes in the Arctic. However, obtaining spatially and temporally distributed observations in the Arctic is difficult. Here we develop and investigate the use and accuracy of the parameter estimation algorithm in recovering soil physical properties. We tested our parameter estimation (PE) approach with synthetic data from a continuously modeled electric resistivity tomography transect and co-located synthetic temperature and soil moisture data. The results indicate that developed PE approach is able to identify synthetic porosities and thermal conductivities.