Estimation of subsurface porosities and thermal conductivities of polygonal tundra by coupled inversion of electrical resistivity, temperature, and moisture content data
Abstract
Studies indicate greenhouse gas emissions following permafrost thaw will amplify current rates of atmospheric warming, a process referred to as the permafrost carbon feedback. However, large uncertainties exist regarding the timing and magnitude of the permafrost carbon feedback, in part due to uncertainties associated with subsurface permafrost parameterization and structure. Development of robust parameter estimation methods for permafrost-rich soils is becoming urgent under accelerated warming of the Arctic. Improved parameterization of the subsurface properties in land system models would lead to improved predictions and a reduction of modeling uncertainty. In this work we set the groundwork for future parameter estimation (PE) studies by developing and evaluating a joint PE algorithm that estimates soil porosities and thermal conductivities from time series of soil temperature and moisture measurements and discrete in-time electrical resistivity measurements. The algorithm utilizes the Model-Independent Parameter Estimation and Uncertainty Analysis toolbox and coupled hydrological–thermal–geophysical modeling. We test the PE algorithm against synthetic data, providing a proof of concept for the approach. We use specified subsurface porosities and thermal conductivities and coupled models to set up a synthetic state, perturb the parameters, and then verify that our PE method is able to recover the parameters and synthetic state. Tomore »
- Authors:
-
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Water Research Inst., Hanoi (Vietnam)
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER); USDOE Office of Science (SC). Biological and Environmental Research (BER) (SC-23)
- OSTI Identifier:
- 1599848
- Alternate Identifier(s):
- OSTI ID: 1606940; OSTI ID: 1659183
- Report Number(s):
- LA-UR-19-23188
Journal ID: ISSN 1994-0424; ark:/13030/qt7jr302k2
- Grant/Contract Number:
- AC02-05CH11231; AC05-00OR22725; 89233218CNA000001
- Resource Type:
- Accepted Manuscript
- Journal Name:
- The Cryosphere (Online)
- Additional Journal Information:
- Journal Name: The Cryosphere (Online); Journal Volume: 14; Journal Issue: 1; Journal ID: ISSN 1994-0424
- Publisher:
- European Geosciences Union
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; Computer Science; Earth Sciences; Mathematics
Citation Formats
Jafarov, Elchin E., Harp, Dylan R., Coon, Ethan T., Dafflon, Baptiste, Tran, Anh Phuong, Atchley, Adam L., Lin, Youzuo, and Wilson, Cathy J. Estimation of subsurface porosities and thermal conductivities of polygonal tundra by coupled inversion of electrical resistivity, temperature, and moisture content data. United States: N. p., 2020.
Web. doi:10.5194/tc-14-77-2020.
Jafarov, Elchin E., Harp, Dylan R., Coon, Ethan T., Dafflon, Baptiste, Tran, Anh Phuong, Atchley, Adam L., Lin, Youzuo, & Wilson, Cathy J. Estimation of subsurface porosities and thermal conductivities of polygonal tundra by coupled inversion of electrical resistivity, temperature, and moisture content data. United States. https://doi.org/10.5194/tc-14-77-2020
Jafarov, Elchin E., Harp, Dylan R., Coon, Ethan T., Dafflon, Baptiste, Tran, Anh Phuong, Atchley, Adam L., Lin, Youzuo, and Wilson, Cathy J. Wed .
"Estimation of subsurface porosities and thermal conductivities of polygonal tundra by coupled inversion of electrical resistivity, temperature, and moisture content data". United States. https://doi.org/10.5194/tc-14-77-2020. https://www.osti.gov/servlets/purl/1599848.
@article{osti_1599848,
title = {Estimation of subsurface porosities and thermal conductivities of polygonal tundra by coupled inversion of electrical resistivity, temperature, and moisture content data},
author = {Jafarov, Elchin E. and Harp, Dylan R. and Coon, Ethan T. and Dafflon, Baptiste and Tran, Anh Phuong and Atchley, Adam L. and Lin, Youzuo and Wilson, Cathy J.},
abstractNote = {Studies indicate greenhouse gas emissions following permafrost thaw will amplify current rates of atmospheric warming, a process referred to as the permafrost carbon feedback. However, large uncertainties exist regarding the timing and magnitude of the permafrost carbon feedback, in part due to uncertainties associated with subsurface permafrost parameterization and structure. Development of robust parameter estimation methods for permafrost-rich soils is becoming urgent under accelerated warming of the Arctic. Improved parameterization of the subsurface properties in land system models would lead to improved predictions and a reduction of modeling uncertainty. In this work we set the groundwork for future parameter estimation (PE) studies by developing and evaluating a joint PE algorithm that estimates soil porosities and thermal conductivities from time series of soil temperature and moisture measurements and discrete in-time electrical resistivity measurements. The algorithm utilizes the Model-Independent Parameter Estimation and Uncertainty Analysis toolbox and coupled hydrological–thermal–geophysical modeling. We test the PE algorithm against synthetic data, providing a proof of concept for the approach. We use specified subsurface porosities and thermal conductivities and coupled models to set up a synthetic state, perturb the parameters, and then verify that our PE method is able to recover the parameters and synthetic state. To evaluate the accuracy and robustness of the approach we perform multiple tests for a perturbed set of initial starting parameter combinations. In addition, we varied types and quantities of data to better understand the optimal dataset needed to improve the PE method. The results of the PE tests suggest that using multiple types of data improve the overall robustness of the method. Our numerical experiments indicate that special care needs to be taken during the field experiment setup so that (1) the vertical distance between adjacent measurement sensors allows the signal variability in space to be resolved and (2) the longer time interval between resistivity snapshots allows signal variability in time to be resolved.},
doi = {10.5194/tc-14-77-2020},
journal = {The Cryosphere (Online)},
number = 1,
volume = 14,
place = {United States},
year = {2020},
month = {1}
}
Web of Science
Works referenced in this record:
An Algorithm for Least-Squares Estimation of Nonlinear Parameters
journal, June 1963
- Marquardt, Donald W.
- Journal of the Society for Industrial and Applied Mathematics, Vol. 11, Issue 2
The Electrical Resistivity Log as an Aid in Determining Some Reservoir Characteristics
journal, December 1942
- Archie, G. E.
- Transactions of the AIME, Vol. 146, Issue 01
Microtopographic control on the ground thermal regime in ice wedge polygons
journal, January 2018
- Abolt, Charles J.; Young, Michael H.; Atchley, Adam L.
- The Cryosphere, Vol. 12, Issue 6
A method for the solution of certain non-linear problems in least squares
journal, January 1944
- Levenberg, Kenneth
- Quarterly of Applied Mathematics, Vol. 2, Issue 2
Dependence of the evolution of carbon dynamics in the northern permafrost region on the trajectory of climate change
journal, March 2018
- McGuire, A. David; Lawrence, David M.; Koven, Charles
- Proceedings of the National Academy of Sciences, Vol. 115, Issue 15
Sensitivity of airborne geophysical data to sublacustrine and near-surface permafrost thaw
journal, January 2015
- Minsley, B. J.; Wellman, T. P.; Walvoord, M. A.
- The Cryosphere, Vol. 9, Issue 2
Estimation of soil thermal properties using in-situ temperature measurements in the active layer and permafrost
journal, January 2009
- Nicolsky, D. J.; Romanovsky, V. E.; Panteleev, G. G.
- Cold Regions Science and Technology, Vol. 55, Issue 1
Constitutive Model for Unfrozen Water Content in Subfreezing Unsaturated Soils
journal, January 2014
- Painter, Scott L.; Karra, Satish
- Vadose Zone Journal, Vol. 13, Issue 4
Integrated surface/subsurface permafrost thermal hydrology: Model formulation and proof-of-concept simulations: INTEGRATED PERMAFROST THERMAL HYDROLOGY
journal, August 2016
- Painter, Scott L.; Coon, Ethan T.; Atchley, Adam L.
- Water Resources Research, Vol. 52, Issue 8
A synthesis dataset of permafrost-affected soil thermal conditions for Alaska, USA
journal, January 2018
- Wang, Kang; Jafarov, Elchin; Overeem, Irina
- Earth System Science Data, Vol. 10, Issue 4
Spatial Patterns of Soil Organic Carbon in the Contiguous United States
journal, January 1994
- Kern, Jeffrey S.
- Soil Science Society of America Journal, Vol. 58, Issue 2
Effect of soil property uncertainties on permafrost thaw projections: a calibration-constrained analysis
journal, January 2016
- Harp, D. R.; Atchley, A. L.; Painter, S. L.
- The Cryosphere, Vol. 10, Issue 1
Moisture content measurements of moss (Sphagnum spp.) using commercial sensors
journal, January 2004
- Yoshikawa, Kenji; Overduin, Pier Paul; Harden, Jennifer W.
- Permafrost and Periglacial Processes, Vol. 15, Issue 4
Modeling the role of preferential snow accumulation in through talik development and hillslope groundwater flow in a transitional permafrost landscape
journal, October 2018
- Jafarov, Elchin E.; Coon, Ethan T.; Harp, Dylan R.
- Environmental Research Letters, Vol. 13, Issue 10
Three-dimensional modelling and inversion of dc resistivity data incorporating topography - I. Modelling
journal, August 2006
- Rücker, Carsten; Günther, Thomas; Spitzer, Klaus
- Geophysical Journal International, Vol. 166, Issue 2
A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code
journal, May 1979
- McKay, M. D.; Beckman, R. J.; Conover, W. J.
- Technometrics, Vol. 21, Issue 2
Using in-situ temperature measurements to estimate saturated soil thermal properties by solving a sequence of optimization problems
journal, January 2007
- Nicolsky, D. J.; Romanovsky, V. E.; Tipenko, G. S.
- The Cryosphere, Vol. 1, Issue 1
Coincident aboveground and belowground autonomous monitoring to quantify covariability in permafrost, soil, and vegetation properties in Arctic tundra: ABOVEGROUND AND BELOWGROUND CODYNAMICS
journal, June 2017
- Dafflon, Baptiste; Oktem, Rusen; Peterson, John
- Journal of Geophysical Research: Biogeosciences, Vol. 122, Issue 6
Permafrost Stores a Globally Significant Amount of Mercury
journal, February 2018
- Schuster, Paul F.; Schaefer, Kevin M.; Aiken, George R.
- Geophysical Research Letters, Vol. 45, Issue 3
Coupled land surface–subsurface hydrogeophysical inverse modeling to estimate soil organic carbon content and explore associated hydrological and thermal dynamics in the Arctic tundra
journal, January 2017
- Tran, Anh Phuong; Dafflon, Baptiste; Hubbard, Susan S.
- The Cryosphere, Vol. 11, Issue 5
Degrading permafrost puts Arctic infrastructure at risk by mid-century
journal, December 2018
- Hjort, Jan; Karjalainen, Olli; Aalto, Juha
- Nature Communications, Vol. 9, Issue 1
Permafrost is warming at a global scale
journal, January 2019
- Biskaborn, Boris K.; Smith, Sharon L.; Noetzli, Jeannette
- Nature Communications, Vol. 10, Issue 1
Time domain reflectometry as a field method for measuring water content and soil water electrical conductivity at a continuous permafrost site
journal, October 1997
- Boike, Julia; Roth, Kurt
- Permafrost and Periglacial Processes, Vol. 8, Issue 4
Pan-Arctic ice-wedge degradation in warming permafrost and its influence on tundra hydrology
journal, March 2016
- Liljedahl, Anna K.; Boike, Julia; Daanen, Ronald P.
- Nature Geoscience, Vol. 9, Issue 4
Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83)
journal, January 2015
- Atchley, A. L.; Painter, S. L.; Harp, D. R.
- Geoscientific Model Development, Vol. 8, Issue 9
Numerical modeling of permafrost dynamics in Alaska using a high spatial resolution dataset
journal, January 2012
- Jafarov, E. E.; Marchenko, S. S.; Romanovsky, V. E.
- The Cryosphere, Vol. 6, Issue 3
The Effect of Soil Thermal Conductivity Parameterization on Surface Energy Fluxes and Temperatures
journal, April 1998
- Peters-Lidard, C. D.; Blackburn, E.; Liang, X.
- Journal of the Atmospheric Sciences, Vol. 55, Issue 7
Datasets of seed mucilage traits for Arabidopsis thaliana natural accessions with atypical outer mucilage
journal, March 2021
- Cambert, Mireille; Berger, Adeline; Sallé, Christine
- Scientific Data, Vol. 8, Issue 1
A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code
journal, February 2000
- Mckay, M. D.; Beckman, R. J.; Conover, W. J.
- Technometrics, Vol. 42, Issue 1
Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83)
journal, January 2015
- Atchley, A. L.; Painter, S. L.; Harp, D. R.
- Geoscientific Model Development Discussions, Vol. 8, Issue 4