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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Water Management and Systems Research » Research » Publications at this Location » Publication #283927

Title: Evaluating Remote Sensing-based Crop Water Use Monitoring Methods Using Soil Moisture Sensors

item CHAVEZ, JOSE - Colorado State University
item TAGHVAEIAN, SALEH - Colorado State University
item Trout, Thomas

Submitted to: Biological Engineering (ASABE)
Publication Type: Proceedings
Publication Acceptance Date: 7/15/2012
Publication Date: 7/29/2012
Citation: Chavez, J.L., Taghvaeian, S., Trout, T.J. 2012. Evaluating Remote Sensing-based Crop Water Use Monitoring Methods Using Soil Moisture Sensors. Biological Engineering (ASABE). 2012 ASABE Annual meeting Paper Paper number 12.

Interpretive Summary:

Technical Abstract: Competition for limited water supplies continues to exert pressure on agriculture. In addition, climate change, urban growth, and drought influence how farmers manage their water supplies. Water transfers from agriculture to other uses are on the rise. To avoid drying farms one alternative water management strategy is to deficit irrigate. However, to perform a successful managing irrigation under a deficit irrigation regime an accurate crop water consumption monitoring method is required. The objective of this study was to evaluate a crop water stress model that is based on the difference between canopy radiometric temperature and air temperature. Three irrigation treatments were imposed on corn plots grown in northeastern Colorado in 2011. The treatments were: TrT 1 full irrigation (six irrigations), TrT 2 deficit irrigation (two irrigations), and TrT 3 reduced irrigation (six irrigation but half the amount of TrT 1). A local weather station located on a grass field was used to compute reference evapotranspiration. Derived crop water stress indices and water use amounts were evaluated with ET values derived from a Neutron probe-based soil water balance and with a surface energy balance model considering inputs from a remote sensing system. Results indicated that relatively low errors in ET estimation are possible if surface radiometric temperature is acquired earlier in the day. Keywords. Evapotranspiration, crop water stress, remote sensing, deficit irrigation