Baptiste Dafflon
2022
- Dafflon, Baptiste, et al. “A Distributed Temperature Profiling System for Vertically and Laterally Dense Acquisition of Soil and Snow Temperature”. The Cryosphere, vol. 16, no. 2, 2022, pp. 719-36, https://doi.org/10.5194/tc-16-719-2022.
- Arendt, Carli A., et al. “Increased Arctic NO3− Availability As a Hydrogeomorphic Consequence of Permafrost Degradation and Landscape Drying”. Nitrogen, vol. 3, no. 2, 2022, pp. 314-32, https://doi.org/10.3390/nitrogen3020021.
- Wielandt, Stijn, et al. “Low-Power, Flexible Sensor Arrays With Solderless Board-to-Board Connectors for Monitoring Soil Deformation and Temperature”. Sensors, vol. 22, no. 7, 2022, p. 2814, https://doi.org/10.3390/s22072814.
- Shirley, Ian A., et al. “Rapidly Changing High-Latitude Seasonality: Implications for the 21st Century Carbon Cycle in Alaska”. Environmental Research Letters, vol. 17, no. 1, 2022, p. 014032, https://doi.org/10.1088/1748-9326/ac4362.
- Bennett, Katrina E., et al. “Spatial Patterns of Snow Distribution for Improved Earth System Modelling in the Arctic”. The Cryosphere, 2022, https://doi.org/https://doi.org/10.5194/tc-2021-341.
2021
- Uhlemann, Sebastian, et al. “Geophysical Monitoring Shows That Spatial Heterogeneity in Thermohydrological Dynamics Reshapes a Transitional Permafrost System”. Geophysical Research Letters, vol. 48, no. 6, 2021, https://doi.org/10.1029/2020GL091149.
- Wainwright, Haruko M., et al. “High-Resolution Spatio-Temporal Estimation of Net Ecosystem Exchange in Ice-Wedge Polygon Tundra Using In Situ Sensors and Remote Sensing Data”. Land, vol. 10, no. 7, 2021, p. 722, https://doi.org/10.3390/land10070722.
2020
- Jafarov, Elchin E., et al. “Estimation of Subsurface Porosities and Thermal Conductivities of Polygonal Tundra by Coupled Inversion of Electrical Resistivity, Temperature, and Moisture Content Data”. The Cryosphere, vol. 14, no. 1, 2020, pp. 77-91, https://doi.org/10.5194/tc-14-77-2020.
- Wales, Nathan A., et al. “Understanding the Relative Importance of Vertical and Horizontal Flow in Ice-Wedge Polygons”. Hydrology and Earth System Sciences, vol. 24, no. 3, 2020, pp. 1109-2, https://doi.org/10.5194/hess-24-1109-2020.
2019
- Léger, Emmanuel, et al. “A Distributed Temperature Profiling Method for Assessing Spatial Variability in Ground Temperatures in a Discontinuous Permafrost Region of Alaska”. The Cryosphere, vol. 13, 2019, pp. 2853-67, https://doi.org/10.5194/tc-13-2853-2019.
- Arora, Bhavna, et al. “Evaluating Temporal Controls on Greenhouse Gas (GHG) Fluxes in an Arctic Tundra Environment: An Entropy-Based Approach”. Science of The Total Environment, vol. 649, 2019, pp. 284-99, https://doi.org/10.1016/j.scitotenv.2018.08.251.
2018
- Bisht, Gautam, et al. “Impacts of Microtopographic Snow Redistribution and Lateral Subsurface Processes on Hydrologic and Thermal States in an Arctic Polygonal Ground Ecosystem: A Case Study Using ELM-3D v1.0”. Geoscientific Model Development, vol. 11, no. 1, 2018, pp. 61-76, https://doi.org/https://doi.org/10.5194/gmd-11-61-2018.
- Tran, Anh Phuong, et al. “Spatial and Temporal Variations of Thaw Layer Thickness and Its Controlling Factors Identified Using Time-Lapse Electrical Resistivity Tomography and Hydro-Thermal Modeling”. Journal of Hydrology, vol. 561, 2018, pp. 751-63, https://doi.org/10.1016/j.jhydrol.2018.04.028.
2017
- Dafflon, Baptiste, et al. “Coincident Aboveground and Belowground Autonomous Monitoring to Quantify Covariability in Permafrost, Soil, and Vegetation Properties in Arctic Tundra”. Journal of Geophysical Research: Biogeosciences, vol. 122, no. 6, 2017, pp. 1321-42, https://doi.org/10.1002/2016JG003724.
- Tran, Anh Phuong, et al. “Coupled Land Surface-Subsurface Hydrogeophysical Inverse Modeling to Estimate Soil Organic Content and Explore Associated Hydrological and Thermal Dynamics in an Arctic Tundra”. The Cryosphere, vol. 11, 2017, pp. 2089-0, https://doi.org/10.5194/tc-11-2089-2017.
- Wu, Yuxin, et al. “Electrical and Seismic Response of Saline Permafrost Soil During Freeze - Thaw Transition”. Journal of Applied Geophysics, vol. 146, 2017, pp. 16-26, https://doi.org/10.1016/j.jappgeo.2017.08.008.
- Wainwright, Haruko M., et al. “Mapping Snow Depth Within a Tundra Ecosystem Using Multiscale Observations and Bayesian Methods”. The Cryosphere, vol. 11, no. 2, 2017, pp. 857-75, https://doi.org/10.5194/tc-11-857-2017.
- Léger, Emmanuel, et al. “Quantification of Arctic Soil and Permafrost Properties Using Ground-Penetrating Radar and Electrical Resistivity Tomography Datasets”. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 10, 2017, pp. 4348-59, https://doi.org/10.1109/JSTARS.2017.2694447.
2016
- Dafflon, Baptiste, et al. “Geophysical Estimation of Shallow Permafrost Distribution and Properties in an Ice-Wedge Polygon-Dominated Arctic Tundra Region”. GEOPHYSICS, vol. 81, no. 1, 2016, pp. WA247 - WA263, https://doi.org/10.1190/geo2015-0175.1.
- Dafflon, Baptiste, et al. “Quantification of Arctic Soil and Permafrost Properties Using Ground Penetrating Radar”. 2016 16th International Conference on Ground Penetrating Radar (GPR) , 2016, https://doi.org/10.1109/ICGPR.2016.7572663.
2015
- Wainwright, Haruko M., et al. “Identifying Multiscale Zonation and Assessing the Relative Importance of Polygon Geomorphology on Carbon Fluxes in an Arctic Tundra Ecosystem”. Journal of Geophysical Research: Biogeosciences, vol. 120, no. 4, 2015, pp. 788-0, https://doi.org/10.1002/2014JG002799.
2014
- Gangodagamage, Chandana, et al. “Extrapolating Active Layer Thickness Measurements across Arctic Polygonal Terrain Using LiDAR and NDVI Data Sets”. Water Resources Research, vol. 50, no. 8, 2014, pp. 6339-57, https://doi.org/10.1002/2013WR014283.
2013
- Dafflon, Baptiste, et al. “Electrical Conductivity Imaging of Active Layer and Permafrost in an Arctic Ecosystem, through Advanced Inversion of Electromagnetic Induction Data”. Vadose Zone Journal, vol. 12, no. 4, 2013, https://doi.org/10.2136/vzj2012.0161.
- Hubbard, Susan S., et al. “Quantifying and Relating Land-Surface and Subsurface Variability in Permafrost Environments Using LiDAR and Surface Geophysical Datasets”. Hydrogeology Journal, vol. 21, no. 1, 2013, pp. 149-6, https://doi.org/10.1007/s10040-012-0939-y.