Estimation of crop water use for different cropping systems in the Texas High Plains using remote sensing
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The spectral crop coefficient (Ksc) is a novel approach for estimating the water use of field crops. In this study, Ksc is evaluated from remote sensing observations (satellite or aircraft imagery) of the field in question and, thus, is specific to the crop growth characteristics in the field. This approach assumes that the crop is acclimated to its environment and determines crop water use (CWU) based on the product of potential evapotranspiration and remotely sensed crop ground cover (GC). Because the remotely sensed measurements of GC are infrequent over the growing season, these measurements are used in a crop model to simulate values of GC for each day of the growing season, resulting in a crop coefficient curve (known as the spectral crop coefficient – Ksc) that is specific to the field, crop, and growing conditions. The method used for estimating the GC from remote sensing data involves the Perpendicular Vegetation Index (PVI). GC is calculated by dividing the average PVI for a field by the value of PVI for full canopy point. Statistical analysis of estimated and field-measured GC from a large number of fields indicates that the procedure for estimating crop GC from remote sensing imagery is accurate so that, on average, estimates of GC determined using this procedure should be within 6 percent of their true values. The seasonal CWU estimated by this method showed differences in water utilization by individual fields. Comparison of these seasonal CWU values among the fields in the study was effective in showing differences related to year, crop, and irrigation type. Comparing daily values of CWU estimated using the Ksc method and the regular crop coefficient method recommended for crops in the Texas High Plains with actual measurements of evapotranspiration made using the eddy covariance method showed that the Ksc method was consistently more accurate than the regular crop coefficient method.