Location: Water Management and Systems ResearchTitle: Satellite irrigation management support with the terrestrial observation and prediction system: A framework for integration of satellite & surface observations to support improvements in agricultural water resource management
|Melton, Forrest - California State University|
|Johnson, Lee - National Aeronautics And Space Administration (NASA)|
|Lund, Chris - California State University|
|Pierce, Lars - California State University|
|Michaelis, Andrew - California State University|
|Hiatt, Samuel - California State University|
|Guzman, Alberto - California State University|
|Adhikari, Diganta - California State University|
|Prudy, Adam - California State University|
|Rosevelt, Carolyn - California State University|
|Votava, Kpetr - California State University|
|Temesgen, Bekele - California Department Of Water Resources|
|Frame, Kent - California Department Of Water Resources|
|Sheffner, Edwin - National Aeronautics And Space Administration (NASA)|
|Nemani, Ramakrishna - National Aeronautics And Space Administration (NASA)|
Submitted to: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/1/2012
Publication Date: 12/1/2012
Citation: Melton, F., Johnson, L., Lund, C., Pierce, L., Michaelis, A., Hiatt, S., Guzman, A., Adhikari, D., Prudy, A.J., Rosevelt, C., Votava, K., Trout, T.J., Temesgen, B., Frame, K., Sheffner, E., Nemani, R. 2012. Satellite irrigation management support with the terrestrial observation and prediction system: A framework for integration of satellite & surface observations to support improvements in agricultural water resource management. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 5(6): 1709–1721.
Interpretive Summary: TOPS-SIMS employs a “system of systems” approach and applies the TOPS modeling framework to ingest observations from satellite and surface sensor networks to provide new data and information products to agricultural producers and water managers via easily accessible web interfaces and web services. The current framework provides capabilities for near real-time mapping of indicators of crop canopy development and crop water consumption at field scales over 6 million ha of California farmland. Integration of satellite-derived estimates of basal crop evapotranspiration with observations of soil moisture from surface sensor networks offers promise for supporting agricultural producers and water managers working to optimize management of agricultural water resources. Use of the NEX computing architecture enables rapid processing of large volumes of satellite data and facilitates implementation of TOPS-SIMS over regions potentially as large as the western U.S. TOPS-SIMS is designed to integrate additional models and data services to support forecasting of crop irrigation requirements at weekly to seasonal lead times, and concurrent modeling of actual and potential evapotranspiration. Future integration of observations from a constellation of moderate resolution satellites would support further improvements in the frequency and long-term operational reliability of satellite-derived estimates of evapotranspiration and other hydrologic parameters.
Technical Abstract: In California and other regions vulnerable to water shortages, satellite-derived estimates of key hydrologic parameters can support agricultural producers and water managers in maximizing the benefits of available water supplies. The Satellite Irrigation Management Support (SIMS) project combines NASA's Terrestrial Observation and Prediction System (TOPS), Landsat and MODIS satellite imagery, and surface sensor networks to map indicators of crop irrigation demand and develop information products to support irrigation management and other water use decisions. TOPS-SIMS provides the computing and data processing systems required to support automated, near real-time integration of observations from satellite and surface sensor networks, and generates data and information in formats that are convenient for agricultural producers, water managers, and other end users. Using the TOPS modeling framework to integrate data from multiple sensor networks in near real-time, SIMS currently maps crop fractional cover, basal crop coefficients, and basal crop evapotranspiration. Map products are generated at 30 meter resolution on a daily basis over approximately 6 million ha of California farmland. TOPS-SIMS is a fully operational prototype, and a publicly available beta-version of the web interface is being pilot tested by farmers, irrigation consultants, and water managers in California. Data products are distributed via dynamic web services, which support both visual mapping and time-series queries, to allow users to obtain information on spatial and temporal patterns in crop canopy development and water requirements. As part of the TOPS-SIMS project, wireless sensor networks and surface renewal instrumentation have also been deployed on several commercial farms to monitor evapotranspiration and soil moisture, and provide data for use in verification of TOPS-SIMS estimates. TOPS-SIMS is an application framework that demonstrates the value of integrating multi-disciplinary Earth observation systems to provide benefits for water resource management.