Using Satellite Imagery with ET Weather Station Networks to Map Crop Water Use for Irrigation Scheduling: TOPS-SIMS.

Evapotranspiration estimates for scheduling irrigation must be field specific and real time.  Weather station networks provide daily reference ET values, but users need to select crop coefficients for their particular crop and field.  A prototype system has been developed that combines satellite imagery to estimate crop coefficients with reference ET from ground based weather stations to produce near real time crop water use estimate maps for California.  This Satellite Irrigation Management Support (SIMS) system uses NASA’s Terrestrial Observation and Prediction Systems (TOPS) to merge reflectance information from Landsat and MODIS satellite imagery with reference ET estimates from the California Irrigation Management Information System (CIMIS).  Crop coefficients are estimated from the normalized difference vegetation index (NDVI) each 8 days.  Reference ET is from CIMIS 2 km gridded ET values.  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 ground cover, basal crop coefficients, and basal evapotranspiration of a non-stressed crop.  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 ( http://ecocast.org/dgw/sims ).  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.