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United States Department of Agriculture

Agricultural Research Service

Research Project: USING REMOTE SENSING & MODELING FOR EVALUATING HYDROLOGIC FLUXES, STATES, & CONSTITUENT TRANSPORT PROCESSES WITHIN AGRICULTURAL LANDSCAPES
2011 Annual Report


1a.Objectives (from AD-416)
Develop new remote sensing, modeling and data assimilation techniques to improve the monitoring of hydrologic fluxes and agricultural pollutant pathways at the field, watershed and regional scale.


1b.Approach (from AD-416)
Effective management of these watersheds requires detailed process-level understanding concerning the complex hydrologic and constitutive flux pathways that govern: the availability of root-zone soil moisture, the delivery of agricultural pollutants to surface water bodies and feedbacks operating along the soil-plant-atmosphere continuum. The inability to measure the relative magnitude of these pathways hampers the development of effective water management strategies at watershed- and regional-scales. This project attempts to develop novel remote sensing and modeling tools to better characterize key hydrologic and constitutive flux pathways operating within agricultural watersheds. An overarching theme of the project is that the integration of remote sensing products into models can enhance the utility of models for critical agricultural applications.


3.Progress Report
This project attempts to develop novel remote sensing and modeling tools to better characterize key hydrologic and constitutive flux pathways operating within agricultural watersheds. Fifth year project milestones focused on the application of new remote sensing and modeling tools within a quasi-operational system and frequently required some level of successful technology transfer. Examples of such activities include the implementation of a near-real-time operational drought monitoring system at National Oceanic and Atmospheric Administration (NOAA) using USDA ARS thermal remote sensing and modeling tools, and the establishment of an operational linkage between USDA Foreign Agriculture Service (FAS) and root-zone soil moisture estimates derived at USDA ARS using innovative microwave remote sensing and data assimilation strategies. Other related work focused on the development of agricultural applications and ground-based soil moisture instrumentation for the expected 2014 launch of the National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) mission and simplified methods for using remote sensing to account for variability in atmospheric properties and potential errors in heat flux estimation. The fifth year in the project also saw the culmination of research aimed at improving our ability to characterize regional-water quality in the Chesapeake Bay region. Example output from such work include an improved understanding of water quality model output sensitivity to input parameter uncertainty and the development of new remote sensing algorithms for mapping wetland function and extent.


4.Accomplishments
1. Improved agricultural drought detection using remote sensing. Drought-related reductions in agricultural productivity have profound impacts on regional food security and global agricultural commodity markets. Our ability to mitigate these impacts is frequently limited by difficulties in accurately detecting the onset and severity of agricultural drought - particularly in underdeveloped regions of the world prone to food insecurity. In response to this challenge, ARS scientists have examined the microwave and thermal radiative signature of agricultural landscapes undergoing drought and developed a series of satellite remote sensing tools for inferring availability of root-zone soil water over large geographic regions. Compared to existing drought detection strategies (based primarily on rainfall observations), these satellite-based strategies allow for earlier detection of agricultural drought and a more spatially detailed spatial description of its extent and severity. Such improvements will eventually enhance our ability to mitigate the impact of agricultural drought on global food markets and better anticipate the social/political consequences of changes in food availability and price. These technologies (and/or the data sets they create) are currently being shared with operational drought monitoring activities at the USDA Foreign Agricultural Service, the National Oceanic and Atmospheric Administration, National Environmental Satellite Data and Information Service, and the National Drought Mitigation Center.

2. Quantification of chemical transport times between agricultural fields and stream channels. Quantifying chemical transit times through soil is critical for understanding and predicting the impact of agricultural production and management on local water quality. Slower water flow through continuous soil (i.e. matrix flow) typically eliminates excess nutrients and yields cleaner stream water than faster flow through existing openings in the soil matrix (i.e. preferential flow). A series of chemical transit experiments with soluble tracers at a field site in Beltsville, Maryland demonstrated that matrix and preferential flow occurred simultaneously in the field, and that both preferential and matrix flow processes dominate transport times at different locations within the field. This finding indicates that both matrix and preferential flow must be considered to accurately model soil water pathways between agricultural fields and stream channels. This has potentially profound implications on the development of robust watershed-scale models for predicting the impact of conservation practices on regional-scale water quality. Consequently, this work is of major interest to regulatory agencies like the U.S. Environmental Protection Agency, as well as, the U.S. Nuclear Regulatory Commission and U.S. National Resources Conservation Research Service.

3. Validation of the first satellite developed specifically for soil moisture mapping. The European Space Agency Soil Moisture and Ocean Salinity Mission (SMOS) launched in late 2009 represents the first deployment of a satellite sensor developed specifically for the remote detection of surface soil moisture. Previous USDA ARS research contributed to establishing the feasibility of the unique SMOS antennae design and measurement strategy. In this investigation, SMOS soil moisture products were compared to ARS watershed soil moisture networks across the U.S. to validate their accuracy. Results provided a key early indication that SMOS will be able to achieve its goal of estimating soil moisture to within an accuracy of 0.04 m3m-3 (volume of water per volume of soil). Validated soil moisture products from SMOS have the potential to dramatically improve the accuracy and timeliness of weather, climate, and agricultural assessments and forecasts used by the United States Department of Agriculture, the National Oceanic and Atmospheric Administration, and other federal agencies.


Review Publications
Anderson, M.C., Kustas, W.P., Norman, J., Hain, C., Mecikalski, J., Schultz, L., Gonzalez-Dugo, M.P., Cammalleri, C., D'Urso, G., Pimstein, A., Gao, F. 2011. Mapping daily evapotranspiration at field to global scales using geostationary and polar orbiting satellite imagery. Hydrology and Earth System Sciences. 15:223-239.

Crow, W.T., Van Den Berg, M.J. 2010. An improved approach for estimating observation and model error parameters for soil moisture data assimilation. Water Resources Research. 46:W12519-1 - W12519-12.

Hunt, E.R., Li, L., M, T.Y., Jackson, T.J. 2011. Comparison of vegetation water contents derived from shortwave-infrared and passive-microwave sensors over central Iowa. Remote Sensing of Environment. 115:2376-2383.

Jackson, T.J., Cosh, M.H., Bindlish, R., Starks, P.J., Bosch, D.D., Seyfried, M.S., Goodrich, D.C., Moran, M.S. 2010. Validation of advanced microwave scanning radiometer soil moisture products. IEEE Transactions on Geoscience and Remote Sensing. 48:4256-4272.

Crow, W.T., Wagner, W., Naeimi, V. 2010. The impact of radar incidence angle on soil moisture retrieval skill. Geoscience and Remote Sensing Letters. 7(3):501-505.

Carmello, C., Anderson, M.C., Ciraolo, G., D'Urso, G., Kustas, W.P., Loggia, G., Minacapilli, M. 2010. The impact of in-canopy wind attenuation formulations onheat flux estimation using the remote sensing-based two-source model for an open orchard canopy in southern Italy. Hydrology and Earth System Sciences. 14:2643-2659.

Ryu, D., Jackson, T.J., Bindlish, R., Le Vine, D., Haken, M. 2010. Soil moisture retrieval using a two-dimenional L-band synthetic aperture radiometer in a semi-arid environment. IEEE Transactions on Geoscience and Remote Sensing. 48:4273-4284.

Yakirevich, A., Gish, T.J., Simunek, J., Van Genuchten, M.T., Pachepsky, L., Nicholson, T.J. 2009. Potential impact of seepage face on solute transport to a pumped well. Vadose Zone Journal. 9:686-696.

Miralles, D.G., Holmes, T.R., DeJeu, R., Gash, J.H., Dolman, A.J., Meesters, A. 2011. Global land-surface evaporation estimated from satellite-based observations. Hydrology and Earth System Sciences. 15:453-459.

Entekhabi, D., Reichle, R.H., Crow, W.T., Koster, R.D. 2010. Performance metrics for soil moisture retrievals and applications requirements. Journal of Hydrometeorology. 11:832-840.

Ray, R., Jacobs, J., Cosh, M.H. 2010. Landslide susceptibility mapping using downscaled AMSR-E soil moisture: A case study from Cleveland Corral, California, US. Remote Sensing of Environment. 114:2624-2636.

Reichle, R.H., Bosilovich, M.G., Crow, W.T., Koster, R.D., Kumar, S.V., Mahanama, S.P., Zaitchik, B.F. 2009. Recent advances in land data assimilation at the NASA Global Modeling and Assimilation Office. In: Pard, S.K., editor. Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications. London, United Kingdom: Springer-Verland. p. 407-428.

Whitall, D., Hively, W.D., Leight, A.K., Hapeman, C.J., Mcconnell, L.L., Fisher, T., Codling, E.E., Rice, C., Mccarty, G.W., Sadeghi, A.M. 2010. Pollutant fate and spatio-temporal variability in the choptank river estuary: factors influencing water quality. Science of the Total Environment. 408:2096-2108.

Miralles, D., Gash, J., Holmes, T.R., De Jeu, R., Dolman, H. 2010. Global canopy interception from satellite observations. Journal of Geophysical Research. 115:D16122.

Narvekar, P.S., Heygster, G., Jackson, T.J., Bindlish, R., Macelloni, G., Notholt, J. 2010. Passive polarimetric microwave signatures observed over Antarctica. IEEE Transactions on Geoscience and Remote Sensing. 48:1059-1075.

Mirales, D., De Jeu, R., Gash, J., Holmes, T.R., Dolman, A.J. 2011. Magnitude and variability of land evaporation and its components at the global scale. Hydrology and Earth System Sciences. 15:967-981.

Joseph, A.T., Van Der Velde, R., O'Neill, P.E., Choudhury, B.J., Kim, E., Gish, T.J. 2010. L band brightness temperature observations over a corn canopy during the entire growth cycle. Sensors. 10:6980-7001.

Last Modified: 10/23/2014
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