Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Surface Soil Moisture and Groundwater Assessment and Monitoring using Remote Sensing Models: A Preview

502 views

Published on

This preview is part of the requirement for a comprehensive analysis of remotely sensed surface soil moisture and groundwater assessment and monitoring for global environmental and climate change presented by Christina Geller, candidate for the degree of MSc in Geographic Information Science for Development, and Environment and Jenkins Macedo, candidate for the MS in Environmental Science and Policy at the Department of International Development, Community, and Environmental at Clark University.

Published in: Education, Technology
  • Be the first to comment

Surface Soil Moisture and Groundwater Assessment and Monitoring using Remote Sensing Models: A Preview

  1. 1. Surface and Ground Water Resources Monitoring Christina Geller Jenkins Macedo Remote Sensing for Global Environmental Change October 28, 2013
  2. 2. WHY MONITOR SURFACE & GROUNDWATER RESOURCES 1. To assess above and below ground water resources pertinent to Earth’s climate system. 1. Key to understanding the hydrological cycles. 1. To understand the implications of soil water storage on water and energy fluxes at land surfaces and atmosphere. 1. For estimating surface and groundwater availability and retrievals.
  3. 3. Surface Soil Moisture Approaches: 1. remote sensing observations a. Advanced Microwave Scanning Radiometer-Earth Observing System (AMSRE) on the Aqua satellite b. ERS Advanced Microwave Instrument scatterometer c. European Space Agency’s Soil Moisture and Ocean Salinity satellite (SMOS) 2. land surface models 3. in situ field measurements Soil-Vegetation-Atmosphere Transfer (SVAT) models: ● combine land surface and atmosphere processes modeling using both water and energy balances ● utilizes Common Land Model
  4. 4. Soil Water Storage Monitoring, Estimation, and Retrievals Approaches: 1. groundwater storage monitoring (Syed et al., 2008) a. Gravity Recovery and Climate Experiment (GRACE)-Terrestrial Water Storage Changes (TWSC) b. Global Land Data Assimilation System (GLDAS) 1. soil moisture estimation & groundwater variations (Swenson et al., 2008) a. in situ soil moisture observations b. DOE Atmospheric Radiation Measurement (DOE ARM) 1. global soil moisture retrievals (Reichle et al., 2007) a. NASA Catchment Land Surface Model (CLSM) b. Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) on the Aqua satellite c. Scanning Multichannel Microwave Radiometer (SMMR).
  5. 5. http://www.youtube.com/watch?v=rtSxeHEl8CI
  6. 6. Selected Publications Choi, M., Jacobs, J.M., and Bosch, D.D. (2008). Remote Sensing Observatory Validation of Surface Soil Moisture using Advanced Microwave Scanning Radiometer E, Common Land Model, and Ground-based Data: Case Study in SMEX03 Little River Region, Georgia, U.S. Water Resources Research, Vol. 44, pg. 1-14. de Jeu, A.M., Wagner, W., Holmes, T.R.H., Dolman, A.J., van de Giesen, N.C., and Friesen, J. (2008). Global Soil Moisture Patterns Observed by Space Borne Microwaves Radiometers and Scatterometers. Survey Geophysics, Vol. 29, pg. 399-420. Reichle, R.H., Koster, R.D., Lui, P., Mahanama, S.P.P., Njoku, E.G., and Owe, M., (2007). Comparison and Assimilation of Global Soil Moisture Retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) and the Scanning Multichannel Microwave Radiometer (SMMR). Journal of Geophysical Research, Vol. 112, pg. 1-14. Swenson, S., Famiglietti, J., Basara, J., and Wahr, J. (2008). Estimating Profile Soil Moisture and Groundwater Variations using Gravity Recovery and Climate Experiment (GRACE) and Oklahoma Mesonet Soil Moisture Data. Water Resource Research, Vol. 44, pg. 1-12. Syed, T.H., Famiglietti, J.S., Rodell, M., Chen, J., and Wilson, C.R. (2008). Analysis of Terrestrial Water Storage Changes from Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS). Water Resources Research, Vol. 44, pg. 1-15.

×