H024
Advancing Soil Moisture Science via Monitoring, Modeling, and Remote Sensing

Session ID#: 161949

Session Description:
The status of soil moisture across a national scale is of interest to meteorologists, hydrologists, climatologists, agronomists, and resource managers. The National Coordinated Soil Moisture Monitoring Network was developed to provide a framework for national scale soil moisture monitoring activities, with a focus on utility and resilience. Papers are called for on all aspects of soil moisture science, including in situ monitoring, remote sensing, and modeling. Soil moisture is an essential climate and agricultural variable, impacting many applications, therefore also of interest are studies using large-scale soil moisture estimates, as this will help to guide the development of the national network.
Index Terms:

1839 Hydrologic scaling [HYDROLOGY]
1855 Remote sensing [HYDROLOGY]
1866 Soil moisture [HYDROLOGY]
1875 Vadose zone [HYDROLOGY]


Primary Convener:  Michael H Cosh, USDA-ARS Hydrology and Remote Sensing Laboratory, Beltsville, United States
Convener:  Todd G Caldwell, USGS Nevada Water Science Center, Carson City, United States
 
Generation of High Spatial and Temporal Resolution Rootzone Soil Moisture Data Series from Satellite Sources Using ML-Based Approach (1043260)
Adrija Roy1, Subimal Ghosh1 and Parag Suresh Narvekar2, (1)Indian Institute of Technology Bombay, Mumbai, India, (2)Massachusetts Inst of Tech, Cambridge, MA, United States
 
Next Generation USGS Soil Moisture Monitoring Activities to Improve National Water Availability Assessments (1045723)
Todd G Caldwell1, Gwendolyn Davies1, Michelle A Stern2, Mathieu Marineau2, Brandon Fleming3,4, Mitchell Weaver4, Graham A Sexstone5, Suzanne Paschke5, Michael R McHale6, Meredith Reitz7 and Brian Pellerin8, (1)USGS Nevada Water Science Center, Carson City, United States, (2)USGS California Water Science Center Sacramento, Sacramento, United States, (3)USGS, Catonsville, MD, United States, (4)USGS Pennsylvania Water Science Center New Cumberland, New Cumberland, United States, (5)USGS Colorado Water Science Center Lakewood, Lakewood, United States, (6)USGS, New York Water Science Center, Troy, United States, (7)USGS, Hydrologic Remote Sensing Branch, WMA Observing Systems Division, Reston, United States, (8)USGS Water Mission Area, Reston, United States
 
Geospatial analysis of soil moisture content on restored wet meadows using satellite and unmanned aerial system images (1049609)
Yetunde Rotimi, Gunnison, CO, UNITED STATES, Jennie DeMarco, Southwestern University, Biology and Environmental Studies, Georgetown, TX, United States; Western Colorado University, Gunnison, United States, Andrew Breibart, Bureau of Land Management, Gunnison, Hydrology, Gunnison, Colorado, United States, Ian Breckheimer, Western Colorado University, School of Environment and Sustainability, Gunnison, CO, United States, Teresa Chapman, The Nature Conservancy, Boulder, United States and Phil Crossley, Western Colorado University, Gunnison, CO, United States
 
Perspectives on Small-Scale Variability in Soil Moisture Monitoring for Irrigation Scheduling (1050720)
Tsz Him Lo1, Jacob P. Rix1, Drew M. Gholson1, Mary Love Tagert2 and H. C. (Lyle) Pringle III3, (1)Mississippi State University, National Center for Alluvial Aquifer Research, Stoneville, Mississippi, United States, (2)Mississippi State University, Department of Agricultural and Biological Engineering, Mississippi State, Mississippi, United States, (3)Mississippi State University, Delta Research and Extension Center, Stoneville, Mississippi, United States
 
Development and Applications of a Soil Moisture Validation Tool for the UFS Prototype Experiments (1056306)
Youlong Xia, I. M. Systems Group, Inc., Camp Springs, MD, United States, Michael Barlage, NOAA/NCEP/EMC, College Park, United States, Daryl Kleist, NOAA/NWS/NCEP/EMC, College Park, MD, United States, Eunkyo Seo, George Mason University Fairfax, Fairfax, VA, United States and Azadeh Gholoubi, IMSG@NCEP/EMC, College Park, United States
 
A Performance Analysis on Soil Dielectric Models Over Organic Soils in Alaska for Passive Microwave Remote Sensing of Soil Moisture (1072778)
Runze Zhang, University of Virginia, Engineering Systems and Environment, Charlottesville, VA, United States, Steven Chan, Jet Propulsion Lab, Pasadena, CA, United States, Rajat Bindlish, Goddard Earth Sciences Technology and Research, Greenbelt, United States and Venkataraman (Venkat) Lakshmi, University of Virginia, Engineering Systems and Environment, Charlottesville, United States
 
Comparing the Characteristics on Soil-Atmosphere Interaction Between Two Tea Fields Managed by Different Strategies (1077341)
Siang-Heng Wang, National Taiwan University, International Degree Program in Climate Change and Sustainable Development, Taipei, Taiwan and Jehn-Yih Juang, National Taiwan University, Department of Geography, Taipei, Taiwan
 
Validation of downscaled soil moisture using brightness temperatures (1081116)
Ziyue Zhu1, Bin Fang2 and Venkataraman (Venkat) Lakshmi2, (1)University of Virginia, University of Virginia, Engineering Systems and Environment, Charlottesville, United States, (2)University of Virginia, Engineering Systems and Environment, Charlottesville, United States
 
An Improved SMAP Soil Moisture Retrieval using Deep Neural Network-based inversion of a Passive Microwave Radiative Transfer Model (1084039)
Jaese Lee1, Jungho Im2 and Bokyung Son2, (1)Ulsan National Institute of Science and Technology, Urban and Environmental Engineering, Ulsan, Korea, Republic of (South), (2)Ulsan National Institute of Science and Technology, Urban and Environmental Engineering, Ulsan, South Korea
 
Soil Moisture Profile Estimation by Combining P-band SAR Polarimetry with Soil Hydrological Modeling (1086785)
Anke Fluhrer1,2, Thomas Jagdhuber3,4, Carsten Montzka5, Maike Schumacher6, Hamed Alemohammad7, Alireza Tabatabaeenejad8, Harald Kunstmann2,9 and Dara Entekhabi10, (1)German Aerospace Center DLR Oberpfaffenhofen, Microwaves and Radar Institute, Oberpfaffenhofen, Germany, (2)Augsburg University, Institute of Geography, Augsburg, Germany, (3)Institute of Geography, University of Augsburg, Augsburg, Germany, (4)Microwaves and Radar Institute, German Aerospace Center, Wessling, Germany, (5)Forschungszentrum Jülich, Institute of Bio and Geosciences (Agrosphere, IBG-3), Jülich, Germany, (6)Geodesy Group, Department of Planning, Aalborg University, Aalborg, Denmark, (7)Radiant Earth Foundation, Washington, DC, United States, (8)The Aerospace Corporation El Segundo, El Segundo, United States, (9)Karlsruhe Institute of Technology (KIT), Campus Alpin - Institute of Meteorology and Climate Research (IMK-IFU), Garmisch-Partenkirchen, Germany, (10)Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, Cambridge, MA, United States
 
Microwave Emission Model Parameter Tuning for Surface Soil Moisture Retrievals Using UAV Mounted Dual Polarization L-Band Radiometer (1090865)
Santiago Hoyos1, Hernan A Moreno1 and Stephanie N Marquez2, (1)University of Texas at El Paso, Earth, Environmental and Resource Sciences, El Paso, United States, (2)University of Texas at El Paso, Earth, Environmental and Resource Sciences, El Paso, TX, United States
 
Multi-Scale Intercomparison of Surface Soil Moisture in the Chihuahuan Desert using Orbital, Sub-Orbital and Ground-Based Measurements (1096026)
Stephanie N Marquez1, Hernan A Moreno2, Santiago Hoyos2, Xiwu Zhan3 and Jifu Yin4, (1)University of Texas at El Paso, Earth, Environmental and Resource Sciences, El Paso, TX, United States, (2)University of Texas at El Paso, Earth, Environmental and Resource Sciences, El Paso, United States, (3)NOAA/NESDIS/STAR, College Park, MD, United States, (4)NOAA, College Park, United States
 
Are Soil Moisture Recession Slopes Good Predictors of Relative Wetness Across Landscape Positions? (1097340)
Menberu Meles, Sustainable Agricultural Water Systems, USDA-ARS, Davis, United States, Scott Raulerson, University of Georgia, Warnell School of Forestry and Natural Resources, Athens, United States, C. Rhett Jackson, University of Georgia, Warnell School of Forestry and Natural Resources, Athens, GA, United States, Benjamin Rau, USDA Forest Service Northern Research Station, Timber and Watershed Laboratory, Parsons, United States, David C Goodrich, USDA-ARS Southwest Watershed Research Center, Tucson, AZ, United States and Scott Alan Bradford, USDA, ARS, US Salinity Laboratory, Riverside, CA, United States
 
Deriving Physical Origins to The Albedo-Tau Model and Its Performance in Predicting Microwave Emissions from Vegetated Land Surfaces (1103313)
Kaiqi Chen, Zhejiang University, Hangzhou, China and Shurun Tan, Zhejiang University, Zhejiang University/University of Illinois at Urbana-Champaign Institute, Haining, China
 
Assimilating SMAP-based Soil Moisture Products into EPIC Crop Model for Improved Simulation of Surface and Subsurface Soil Moisture (1103786)
Rohit Nandan, University of Maryland College Park, College Park, MD, United States, Varaprasad Bandaru, USDA-ARS, Maricopa, United States, Michael Cosh, USDA ARS, Baltimore, United States, Sandeep Naga, University of Maryland College Park, College Park, United States, Pradeep Wagle, USDA-ARS Grazinglands Research Laboratory, El Reno, United States, Nicanor Saliendra, USDA Agriculture Research Service, Mandahn, United States, Mark A Liebig, USDA-ARS NGPRL, Mandan, United States, Curtis Dinneen Jones, University of Maryland College Park, geographical sciences, College Park, MD, United States, Rajat Bindlish, Goddard Earth Sciences Technology and Research, Greenbelt, United States, Kelly Thorp, US Department of Agriculture, U.S. ALARC Maricopa, AZ, Beltsville, MD, United States and Christopher Owen Justice, University of Maryland, Department of Geographical Sciences, College Park, United States
 
Benefits of Hyper-Resolution Land Surface Modeling for Soil Moisture Estimation: Analysis over a Catchment in India (1106003)
Vishnu U Krishnan1, Karthikeyan Lanka1, Noemi Vergopolan2 and J. Indu1, (1)Indian Institute of Technology Bombay, Mumbai, India, (2)Princeton / GFDL, Atmospheric and Ocean Sciences Program, Princeton, NJ, United States
 
Calculating a Minimum Colocation Period for Successful Inter-Calibration of In Situ Soil Moisture Sensors (1106420)
Victoria A Walker, ORISE (USDA-ARS), Beltsville, United States, Michael H Cosh, USDA-ARS Hydrology and Remote Sensing Laboratory, Beltsville, United States and Tyson E. Ochsner, Oklahoma State University, Plant and Soil Sciences, Stillwater, OK, United States
 
Evaluation of Global Products and High-Resolution Model-Based Surface Soil Moisture Retrieval with Respect to Ground Truth Data over Alpine Grasslands in Tibetan Plateau (1108051)
Aida Taghavi, Technical University of Braunschweig, Braunschweig, Germany, Markus Gerke Prof, Technical University of Braunschweig, Institute of Geodesy and Photogrammetry, Braunschweig, Germany and Björn Riedel, Technical University of Braunschweig, Institute für Geodäsie und Photogrammetrie, Braunschweig, Germany
 
Improving Point-Scale Soil Moisture Prediction Using Data Assimilation Approach in mesoscale Hydrological Model (mHM) (1108717)
Eshrat Fatima1, Rohini Kumar2, Martin Schrön3, Shabeh Ul Hasson4, Maren Kaluza2, Luis Samaniego2, Sascha E Oswald1 and Sabine Attinger2, (1)University of Potsdam, Institute of Earth and Environmental Science, Potsdam, Germany, (2)Helmholtz Centre for Environmental Research GmbH – UFZ, Computational Hydrosystems, Leipzig, Germany, (3)Helmholtz Centre for Environmental Research GmbH – UFZ, Monitoring and Exploration Technologies, Leipzig, Germany, (4)Universität Hamburg, Department of Earth System Sciences, Hamburg, Germany
 
Flash drought monitoring of agriculture systems using multi-source remote sensing and soil moisture data fusion in East Asia (1126073)
Won-Ho Nam1, Xiang Zhang2, Jason Otkin3, Mark D. Svoboda4, Brian Wardlow5, Tsegaye Tadesse6, Christopher Hain7, Vikalp Mishra8, Song Feng9 and Michael J Hayes6, (1)Hankyong National University, School of Social Safety and Systems Engineering, Anseong, South Korea, (2)China University of Geosciences (Wuhan), National Engineering Research Center of Geographic Information System, School of Geography and Information Engineering, Wuhan, China, (3)University of Wisconsin-Madison, CIMSS/SSEC, Madison, United States, (4)University of Nebraska-Lincoln, National Drought Mitigation Center, Lincoln, NE, United States, (5)University of Nebraska-Lincoln, Lincoln, NE, United States, (6)University of Nebraska-Lincoln, School of Natural Resources, Lincoln, United States, (7)National Integrated Drought Information System, Boulder, United States, (8)University of Alabama in Huntsville, Huntsville, AL, United States, (9)University of Arkansas, Fayetteville, AR, United States
 
Mapping Root Zone Soil Moisture for Irrigation Management by Artificial Intelligence Using Data from Both Satellite Soil Moisture Products and In-Situ Observations (1136083)
Ziwen Yu1, Chi Zhang2, Jasmeet Judge3, Sandra Guzman4, George Vellidis5, Andre da Silva6, William Lusher2 and Pam Knox7, (1)University of Florida, Ft Walton Beach, FL, United States, (2)University of Florida, Gainesville, United States, (3)Center for Remote Sensing, Agricultural and Biological Engineering, University of Florida, Gainesville, FL, United States, (4)University of Florida, Ft Walton Beach, United States, (5)University of Georgia, Athens, GA, United States, (6)Auburn University, Auburn, United States, (7)University of Georgia, Watkinsville,, United States
 
Soil Moisture Prediction Using Hydrological Model and Machine Learning Method (1140971)
Chu Kang1, Wu Tsung-Hsi2, Meng-Ju Chung1, Chien-Chih Chen2, Ming-Hsu Li1, Pei-Yuan Chen1 and Xiang Feng Hong3, (1)Graduate Institute of Hydrologic and Oceanic Sciences,National Central University, Taoyuan, Taiwan, (2)Department of Earth Sciences, National Central University, Taoyuan, Taiwan, (3)ABEL TECHNOLOGY CONSULTANTS CO., LTD., Taoyuan, Taiwan
 
Spatio-temporal Soil Moisture Estimation using Water Cloud Model and Sentinel-1 & -2 Satellite Images. (1144157)
Jeehun Chung1, Wonjin Jang1, Hyungjin Shin2 and Seongjoon Kim3, (1)Konkuk University, Graduate School, Department of Civil, Environmental and Plant Engineering, Seoul, South Korea, (2)Rural Research Institute, Ansan, Gyeonggi-do, South Korea, (3)Konkuk University, College of Engineering, Division of Civil and Environmental Engineering, Seoul, South Korea
 
High Spatial Resolution Soil Moisture Mapping using L-band UAV Sensor (1146395)
Kyung Yoon Kim1, Runze Zhang1, Bin Fang2, Jack Steward Elston3, Andrew Russ4, Michael Cosh5 and Venkataraman (Venkat) Lakshmi2, (1)University of Virginia, Engineering Systems and Environment, Charlottesville, VA, United States, (2)University of Virginia, Engineering Systems and Environment, Charlottesville, United States, (3)Black Swift Technologies, Boulder, CO, United States, (4)NASA Goddard Space Flight Cen., Greenbelt, MD, United States, (5)USDA ARS, Baltimore, United States
 
An Evaluation of Remotely Sensed Soil Moisture Extremes (1148308)
Ronald Leeper, Organization Not Listed, Washington, DC, United States; North Carolina Institute for Climate Studies, North Carolina State University, Asheville, NC, United States and Michael A Palecki, NOAA National Centers for Environmental Information, Asheville, NC, United States
 
Retrieval of Daily Soil Moisture for South Korea Using Machine Learning with Satellite Images, Numerical Weather Prediction Data, and Topographic Data (1157969)
Soo-Jin Lee, Geomatics Research Institute, Pukyong National University, Busan, South Korea and Yang-Won Lee, Department of Spatial Information Engineering, Division of Earth Environmental System Science, Pukyong National University, Busan, South Korea
 
Antecedent soil moisture condition and receiving rainfall predict high streamflow in flashing watershed in Hawaiʻi (1159427)
Yinphan Tsang1, Maxime Gayte2 and Yu-Fen Huang2, (1)University of Hawaiʻi at Mānoa, Natural Resources and Environmental Management, Honolulu, United States, (2)University of Hawaiʻi at Mānoa, Natural Resources and Environmental Management, Honolulu, HI, United States
 
Relating in-situ soil moisture data to remotely sensed spectral profiles (1177957)
Meredith Reitz, USGS, Hydrologic Remote Sensing Branch, WMA Observing Systems Division, Reston, United States and Todd G Caldwell, USGS Nevada Water Science Center, Carson City, United States
 
Initial down scaling of SMERGE, preliminary results from the MOISST site in Oklahoma (1178214)
Kenneth J Tobin and Marvin E Bennett, Texas A&M International University, Laredo, TX, United States
 
A New Dielectric Imaging Station for Characterizing the Microwave Behavior of Permafrost Active Layer Organic Soil (1179672)
Kazem Bakian Dogaheh and Mahta Moghaddam, University of Southern California, Ming Hsieh Department of Electrical and Computer Engineering, Los Angeles, CA, United States
 
Effect of temperature changes on water infiltration into bridge abutment backfill by solving coupled heat and moisture equations (1188164)
Hamidreza Jalili1, Alireza Bakhshaee2, Farhad Jazaei1 and Claudio I Meier3, (1)University of Memphis, Civil Engineering, Memphis, United States, (2)University of Memphis, Civil Engineering, Memphis, TN, United States, (3)University of Memphis, Department of Civil Engineering, Memphis, TN, United States
 
Controls of within field soil moisture variability in three agricultural fields in the US Midwest (1188976)
Yi Yang, University of Illinois at Urbana Champaign, Urbana, IL, United States, Bin Peng, University of Illinois at Urbana Champaign, Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, Urbana, United States, Kaiyu Guan, University of Illinois at Urbana Champaign, Department of Natural Resources and Environmental Sciences, College of Agricultural, Consumer and Environmental Sciences, Urbana, United States, Ming Pan, Center for Western Weather and Water Extremes, San Diego, United States and Michael Cosh, USDA ARS, Baltimore, United States
 
Sensitivity of Root-zone Soil Moisture Retrieval to Observation Parameters in Signals of Opportunity Reflectometry (1191447)
Seho Kim, Purdue University, West Lafayette, IN, United States, James L Garrison, Purdue University, School of Aeronautics and Astronautics, West Lafayette, IN, United States and Mehmet Kurum, Mississippi State University, Mississippi State, MS, United States
 
Physics-guided Bayesian Estimation of Rainfall from Soil Moisture Data (1192905)
Yifu GAO, University of California Irvine, Irvine, CA, United States, Jasper A Vrugt, UC-Irvine, Irvine, CA, United States and Efi Foufoula-Georgiou, University of California Irvine, Department of Civil and Environmental Engineering, Irvine, United States
 
Soil Water Content Estimation Using Drone-Based Ground Penetrating Radar and Machine Learning Techniques (1194929)
Milad Vahidi, Ph.D. student, School of Plant and Environmental Sciences (SPES), Blacksburg, United States, Sanaz Shafian, Assistant Professor, School of Plant and Environmental Sciences (SPES), Blacksburg, United States and Umme Fatema Piu, Ph.D student, SPES, Blacksburg, United States
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