Using Disjunctive Kriging as a Quantitative Approach to Manage Soil Salinity and Crop Yield

Abstract

Disjunctive kriging (DK) is a nonlinear geostatistical model that provides unbiased estimates of the conditional probability (CP) that the true value of the property of interest does not exceed a defined threshold. It has important implications in aiding management decisions by providing growers with a quantitative input that can be used for evaluating the variability of the crop productivity at different zones in fields. The objectives of this study are (1) to identify the yield potential percentage (YP%) for several crops at different zones in fields under multiple soil salinity thresholds; (2) to evaluate the YP% of whole fields for several crops under multiple soil salinity thresholds; and (3) to provide guidelines to help growers decide which crops to grow. To achieve these objectives, the DK technique was applied to data from a project conducted in the southeastern part of the Arkansas River Basin in Colorado to generate CP maps. Two data sets of soil salinity (316 and 136 points) that were collected in two fields in 2004 and 2005 were used to generate the CP maps and to evaluate different scenarios of the expected YP% of several crops at multiple soil salinity thresholds. These data sets represented a wide range of soil salinity conditions to evaluate a wide variety of crops (i.e., a larger set of crops than those grown in the study area) in accordance with their soil salinity tolerance, The following crops were evaluated: the field crops, barley, sorghum, and corn; the fruit crops, pomegranate, apples, and strawberries; the vegetable crops, beets, tomatoes, and lettuce; and the forage crops, barley (i.e., hay), crested wheat grass, and alfalfa. This selection was set so that the three crops of each type represented high, moderate, and low soil salinity tolerances. Scenarios were created for each of the aforementioned crops and the DK technique was applied to each scenario to generate CP maps and to evaluate the expected YP%. The results of this study show that the CP maps generated by using the DK technique give an accurate characterization and quantification of the different zones of the fields. CP maps can be used to assess the expected YP% of whole fields for several crops under multiple soil salinity thresholds. On knowing the YP% of different areas, a management decision action can be undertaken to manage the productivity of a field in low productivity areas by selecting another crop or adjusting inputs such as fertilizer, seeding rates, and herbicides.