Development of Crop Coefficients Using Remote Sensing-Based Vegetation Index and Growing Degree Days

Abstract

Abstract. Water is scarce in many regions of the world, especially in arid and semi-arid regions. It is critical, therefore, that farmers have accurate estimates of crop water requirements so they can apply irrigation water more efficiently. A widely recommended method for estimating crop water demand is the use of reference evapotranspiration (ETr) and a crop coefficient (Kc). The main objective of this study was development of crop coefficients using remotely sensed vegetation index and growing degree days (GDD) for silage corn in Northern MA©xico. Clear sky images from Landsat TM (Path 30, Row 42) were used during 2011, 2012, and 2013. The relationship between Normalized Difference Vegetation Index (NDVI) derived from remote sensing and Kc from tabulated values was established. This relationship was used to estimate new local Kc for the three years of study. The linear regression equations between Kc adjusted and day after planting (DAP) was developed using the average of three years. As well as, a second-order polynomial equation between Kc adjusted and GDD from a local agroclimatic station was generated. The output (linear and polynomial Eq.) of Kc adjusted for NDVI and GDD methods were multiplied by reference ET to calculate actual crop ET. Results show high relationship between Kc FAO-56 and NDVI (0.99) and Kc adjusted and GDD (0.98). Crop coefficients derived from vegetation index and GDD were useful methods to estimate actual crop ET and supply appropriate amounts of water. The crop ET method should be used instead of reference ET for irrigation scheduling in the Region Lagunera, MA©xico. Using this method producers can improve the estimation of crop water demand and conserve irrigation water.