EP41C:
Soil State Characteristics: From Observations to Data Assimilation and Modeling I Posters

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Session ID#: 13819

Session Description:
Soil state characteristics provide crucial input for land surface interactions, hydrologic processes, boundary layer meteorology, mobility models, and climate. Recently, there has been increased monitoring/mapping of large-scale soil state characteristics. The state-of-the-art in soil moisture sensing at various spatio-temporal scales is ever changing (e.g. TDR, COSMOS, DTS, SMOS, MODIS, SMAP). Data assimilation of soil moisture and inclusion of soil state characteristics in forecast modeling data present significant challenges due to the variability in observations, observation types, and uncertainty associated with observations. Further challenges arise due to the mathematical and computational stability of the forecast models observations are drawn into. This session addresses current research on soil state characteristics from observations to data assimilation to impacts on forecast model output. Acceptable topics: advances in in situ, proximal, and remote sensing techniques, polysaccharide content in soil crust, HPC for data assimilation or modeling, V&V for spatio-temporally varying data.
Primary Convener:  Laura Clemente-Harding, Pennsylvania State University Main Campus, University Park, PA, United States; US Army Corps of Engineers Geospatial Research Laboratory, Alexandria, VA, United States
Conveners:  Andmorgan Fisher, US Army Corps of Engineers Geospatial Research Laboratory, Alexandria, VA, United States; George Mason University Fairfax, Fairfax, VA, United States and Michael Lewis, George Mason University Fairfax, Fairfax, VA, United States; US Army Corps of Engineers Geospatial Research Laboratory, Alexandria, VA, United States
Chairs:  Laura Clemente-Harding, Pennsylvania State University Main Campus, University Park, PA, United States; US Army Corps of Engineers Geospatial Research Laboratory, Alexandria, VA, United States and Andmorgan Fisher, US Army Corps of Engineers Geospatial Research Laboratory, Alexandria, VA, United States; George Mason University Fairfax, Fairfax, VA, United States
OSPA Liaison:  Laura Clemente-Harding, Pennsylvania State University Main Campus, University Park, PA, United States; US Army Corps of Engineers Geospatial Research Laboratory, Alexandria, VA, United States
Co-Organized with:
Hydrology, Atmospheric Sciences, Biogeosciences, Global Environmental Change, and Hydrology

Cross-Listed:
  • A - Atmospheric Sciences
  • B - Biogeosciences
  • GC - Global Environmental Change
  • H - Hydrology

Proposed Co-Organized Session with:
  • A - Atmospheric Sciences
  • B - Biogeosciences
  • GC - Global Environmental Change
  • H - Hydrology
Index Terms:

0486 Soils/pedology [BIOGEOSCIENCES]
1640 Remote sensing [GLOBAL CHANGE]
1866 Soil moisture [HYDROLOGY]
3322 Land/atmosphere interactions [ATMOSPHERIC PROCESSES]

Abstracts Submitted to this Session:

A Biogeotechnical engineering approach to Combat Desertification (130843)
Ilhan Chang1, Jooyoung Im2, Gye Chun Cho3 and So-Jung Lee1, (1)KICT Korea Institute of Construction Technology, Goyang, Korea, Republic of (South), (2)KAIST Korea Advanced Institute of Science and Technology, Department of Civil and Environmental Engineering, Daejeon, South Korea, (3)KAIST, Daejeon, Korea, Republic of (South)
Clustering of soil moisture time series pattern for selecting representative point on mountainous hillslopes in South Korea (134020)
Eunhyung Lee1, Minji Cho1 and Sanghyun Kim2, (1)Pusan National University, Busan, Korea, Republic of (South), (2)Pusan National University, Busan, South Korea
Validation of Soil Water Content Estimation Method on Agricultural Regions in South Korea (140091)
Yonghee Shin, APEC Climate Center, Busan, South Korea and Miah Kim, APEC Climate Center, Climate Prediction, Busan, Korea, Republic of (South)
A 30 meter soil properties map of the contiguous United States for use in remote sensing and land surface models (144429)
Nathaniel W. Chaney, Duke University, Durham, United States, Cristine Morgan, Texas A&M University, College Station, TX, United States, Alex McBratney, University of Sydney, Sydney, Australia, Eric F Wood, Princeton University, Civil and Environmental Engineering, Princeton, NJ, United States and Yohannes Yimam, Texas A&M University College Station, College Station, TX, United States
Soil Crust Mapping and Estimation of Soil Hydraulic Properties in the Semi-Arid Walnut Gulch Catchment based on Remote Sensing Data (149322)
Rike Becker and Prof. Mekonnen K Gebremichael, PhD, University of California Los Angeles, Los Angeles, CA, United States
Downscaling Coarse Scale Microwave Soil Moisture Product using Machine Learning (152799)
Peyman Abbaszadeh, Portland State University, Civil and Environmental Engineering, Portland, United States, Hamid Moradkhani, Portland State University, Portland, OR, United States and Hongxiang Yan, Portland State University, Civil and Environmental Engineering, Portland, OR, United States
Soil moisture and its impact on the East Asian summer monsoon (153390)
Zhiyan Zuo and Renhe Zhang, CAMS Chinese Academy of Meteorological Sciences, Beijing, China
Comparison of Three Methods for Vertical Interpolation of Soil Moisture (160284)
Ning Zhang, Ohio State University Main Campus, Columbus, OH, United States and Steven M Quiring, Ohio State University Main Campus, Department of Geography, Columbus, OH, United States
Estimating soil moisture exceedance probability from antecedent rainfall (162063)
Collin Cronkite-Ratcliff, U.S. Geological Survey, Menlo Park, CA, United States, Julie Kalansky, Center for Western Weather and Water Extremes (CW3E), Scripps Institution of Oceanography, University of California San Diego, San Diego, United States, Jonathan D Stock, USGS, Geology, Minerals, Energy, and Geophysics Science Center, Moffett Field, United States and Brian D Collins, USGS Landslide Hazards Program, Menlo Park, United States
Modeling the Impact of Soil Conditions on Global Water Balance (162614)
Pei-Ling Wang, University of Victoria, Pacific Climate Impacts Consortium, Victoria, BC, Canada and Johannes J Feddema, University of Victoria, Victoria, BC, Canada
Disaggregation of remotely sensed soil moisture under all sky condition using machine learning approach in Northeast Asia (173019)
Seongkyun Kim1, Hyunglok Kim2, Minha Choi1 and Kiyoung Kim3, (1)Sungkyunkwan University, Water Resources and Remote Sensing Laboratory, Department of Water Resources, Graduate School of Water Resources, Suwon, Korea, Republic of (South), (2)Sungkyunkwan University, Water Resources and Remote Sensing Laboratory, Department of Water Resources, Graduate School of Water Resources, Suwon, Gyeonggi-do, Korea, Republic of (South), (3)Sungkyunkwan University, Suwon, Gyeonggi-do, Korea, Republic of (South)
Towards the Relationship Between Surface Roughness in Active and Passive Microwave Remote Sensing (176423)
Ying Gao, Monash University, Melbourne, VIC, Australia, Jeffrey P Walker, Monash University, Department of Civil Engineering, Clayton, VIC, Australia, Rocco Panciera, UNICEF, New York, United States and Dongryeol Ryu, University of Melbourne, Parkville, VIC, Australia
Relate Watershed Erosion Estimation to Bankfull Channel Dimension (180636)
Tiao J Chang1, Hong Zhou2, Ivan Caballero1 and Yanhui Fang1,3, (1)Ohio University, Department of Civil Engineering, Athens, OH, United States, (2)Civil Engineer, iDesign Engineering, Inc., Silver Spring, MD, United States, (3)Ohio University, Athens, OH, United States
Comparison of soil moisture interpolation methods at regional scale --Case study in Oklahoma (197243)
Chen Zhao, Ohio State University Main Campus, Columbus, OH, United States, Steven M Quiring, Ohio State University Main Campus, Department of Geography, Columbus, OH, United States and Shanshui Yuan, Texas A&M University, College Station, United States
An isotope study (δ18O and δD) of water movements on the Loess Plateau of China in arid and semiarid climates (127053)
Hao Wan, IEE Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China

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