H090
Remote Sensing of Soil Processes
Session ID#: 160884
Session Description:
Beyond the Darcy scale, vadose zone processes are governed by the soil-vegetation-climate interaction, and thus, evolve with spatial scale. Beyond point/field scale, observational constraints severely restrict direct measurements of several elements of water, carbon, and nutrient cycle in the vadose zone. Hence, remote sensing observations from satellites or Unmanned Aerial Vehicles serve as valuable proxies in understanding these processes at large spatial scales. This session invites studies on process-understanding of vadose zone beyond the Darcy scale using remote sensing for (but not limited to) scaling and data assimilation, studying land-atmospheric interactions, understanding soil moisture dynamics and controls, soil hydraulic parameterization, monitoring and modeling of the soil carbon cycle, nutrient transport and recycling and surface-rootzone connectivity. Applications of soil moisture observing platforms/ products (SMAP, SMOS, SENTINEL-1, CYGNSS, etc.), multi/hyperspectral remote sensing (MODIS, LANDSAT, SENTINEL-2, etc.), large-scale reanalysis dataset, etc. for studying vadose zone processes are invited.
Index Terms:
1813 Eco-hydrology [HYDROLOGY]
1855 Remote sensing [HYDROLOGY]
1866 Soil moisture [HYDROLOGY]
1875 Vadose zone [HYDROLOGY]
Primary Convener: Vinit Sehgal, Texas A&M University College Station, Water Management and Hydrological Science, College Station, TX, United States
Conveners: Binayak Mohanty, Texas A&M University, Department of Biological and Agricultural Engineering, College Station, TX, United States, Nandita Gaur, University of Georgia, Crop and Soil Sciences, Athens, United States and Dhruva Kathuria, NASA Goddard Space Flight Center, Greenbelt, United States; Morgan State University, Baltimore, CA, United States
Student/Early Career Convener: Vinit Sehgal, Texas A&M University, College Station, TX, United States
HydroBlocks: An efficient and effective modeling framework to represent field-scale heterogeneity in Earth system models (Invited) (1047663)
Nathaniel W. Chaney1, Noemi Vergopolan2, Laura Torres Torres Rojas1, Luiz Bacelar3, Jiaxuan Cai1, Daniel Guyumus4, Tyler Waterman3, Chengcheng Xu1 and Enrico Zorzetto5, (1)Duke University, Civil and Environmental Engineering, Durham, NC, United States, (2)Princeton / GFDL, Atmospheric and Ocean Sciences Program, Princeton, NJ, United States, (3)Duke University, Durham, NC, United States, (4)Duke University, Civil and Environmental Engineering, Durham, United States, (5)Princeton University, Atmospheric and Oceanic Sciences, Princeton, NJ, United States
Remote Sensing and Modeling of Global Scale Groundwater Recharge and Groundwater Storage Changes Using SMAP, GRACE/FO, and GLDAS (Invited) (1052439)
James S Famiglietti, Global Institute for Water Security, University of Saskatchewan, Saskatoon, SK, Canada, Adam Purdy, University of San Francisco, San Francisco, United States, Xander Huggins, University of Victoria, Department of Civil Engineering, Victoria, BC, Canada, Matthew Rodell, NASA GSFC HSL, Greenbelt, United States and Hrishi Chandanpurkar, University of Saskatchewan, Global Institute for Water Security, Saskatoon, SK, Canada
What Are the Preferential Hydrologic States of Global Surface Soil Moisture? (1081880)
Vinit Sehgal, Texas A&M University College Station, Water Management and Hydrological Science, College Station, TX, United States and Binayak Mohanty, Texas A&M University, Department of Biological and Agricultural Engineering, College Station, TX, United States
Characterising Satellite Soil Moisture Drying Rates Using a Bivariate Recursive Filtering Approach (1135514)
Jhilam Sinha1, Ashish Sharma1, Lucy Amanda Marshall1 and Seokhyeon Kim2, (1)University of New South Wales, School of Civil and Environmental Engineering, Sydney, NSW, Australia, (2)Kyung Hee University, Department of Civil Engineering, Yongin, South Korea
The effect of soil fraction thresholding on clay content mapping using airborne hyperspectral AVIRIS-NG data (1143442)
Elizabeth Baby George1, Cecile Gomez2,3 and D. Nagesh Kumar1, (1)Indian Institute of Science, Department of Civil Engineering, Bangalore, India, (2)LISAH, University of Montpellier, IRD, INRAE, Institut Agro, Montpellier, France, (3)Indo-French Cell for Water Sciences, IRD, Indian Institute of Science, Bengaluru, India
Lab Spectroscopy for Soil Texture Classification (1144969)
Chirag Ternikar, Indian Institute of Science, Bangalore, Department of Civil Engineering, Bangalore, India, Cecile Gomez, LISAH, University of Montpellier, IRD, INRAE, Institut Agro, Montpellier, France and D. Nagesh Kumar, Indian Institute of Science, Department of Civil Engineering, Bangalore, India
Global Coupling of the Terrestrial Water and Carbon Cycles (1149364)
Deanroy Mbabazi, Texas A&M University College Station, College Station, TX, United States, Vinit Sehgal, Texas A&M University, College Station, TX, United States and Binayak Mohanty, Texas A&M University, Department of Biological and Agricultural Engineering, College Station, TX, United States
Soil erosion risk scenarios in the Mediterranean environment using the RUSLE model, remote sensing, and GIS. An application model for Medjerda and Mellegue catchments (North of Algeria). (1180216)
Amine Menasria1,2, Mohammed Meddi2 and Hamadi Habaieb3, (1)Budapest, Budapest, HUNGARY, (2)Higher National School for Hydraulics; Blida; LGEE, Algeria., Blida, Algeria, (3)National Agronomic Institute; University of Carthage; Tunis; Tunisia., Tunis, Tunisia
Enhancing soil moisture predictions across CONUS using Big Data fusion (1180600)
Dhruva Kathuria, NASA Goddard Space Flight Center, Greenbelt, United States, Binayak Mohanty, Texas A&M University, Department of Biological and Agricultural Engineering, College Station, TX, United States and Matthias Katzfuss, Texas A&M University, Department of Statistics, College Station, United States
Evaluating the Presence of Preferential Flow Using Remote Sensing, Inverse Modeling, and Machine Learning Algorithms (1181473)
Leah Kocian, Texas A&M University College Station, College Station, TX, United States and Binayak Mohanty, Texas A&M University, Department of Biological and Agricultural Engineering, College Station, TX, United States
Revisiting Soil Hydrology Across Scales - From Point to Remote Sensing Footprint Scale (1195089)
Binayak Mohanty1, Nandita Gaur2, Vinit Sehgal2, Deanroy Mbabazi1 and Samagra Rana3, (1)Texas A&M University College Station, College Station, TX, United States, (2)Texas A&M University, College Station, TX, United States, (3)Texas A & M University, College Station, TX, United States
