Assessing the Value of Using a Remote Sensing-Based Evapotranspiration Map in Site-Specific Management

Abstract

ABSTRACT In the glaciated regions of the northern Great Plains, water - either too much or too little - influences soil development, carbon storage, and plant productivity. Integrating site-specific water variability information directly into management is difficult. Simulation models that employ remotely sensed data can generate hard to measure values such as evapotranspiration (ET). This information can be used to identify management zones. The objective of this study was to determine if the METRIC (Mapping Evapotranspiration at High Resolution and with Internalized Calibration) model, which uses weather station and remote sensing data can be used as a tool in site-specific management. This study was conducted on a 65 ha corn (Zea mays L.) field located in east central South Dakota. The METRIC model used Landsat 7 data collected on August 4, 2001 to calculate ET values with spatial resolution of 30 m. ET values were correlated with corn yield (r = 0.85**), apparent electrical conductivity (ECa; r = 0.71**), soil organic carbon (SOC; r = 0.32*), and pH (r = 0.28*). In the footslope positions, high ET values were associated with high corn yields, SOC, EC a , and pH values, while in the summit/shoulder areas low ET values were associated with low yields, SOC, ECa, and pH values. The strong relationship between ET and productivity was attributed to landscape processes that influenced plant available water, which in turn influenced productivity. Cluster analysis of the ET and EC data showed that these data bases complimented each other. Remote sensing-based ET data was most successful in identifying areas where water stress reduced corn yields, while ECa was most successful in identifying high yielding management zones. Findings from this study suggest that remote sensing-based ET estimates can be used to improve management zone delineation.