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.
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REFERENCES
Ayers, R. S., and Westcot, D. W. (1976). “Water quality for agriculture.” Irrigation and Drainage Paper 29. Food and Agriculture Organization of the United Nations, Rome.
Boydell, B., and McBratney, A. B. (1999). “Identifying potential within-field management zones from cotton yield estimates.” Precision Agriculture ’99. Proc. of the 2nd European Conf. on Precision Agriculture, J. V. Stafford, ed., SCI, London, 331–341.
Burgess, T. M., and Webster, R. (1980). “Optimal interpolation and isarithmic mapping of soil properties.” J. Soil Science, 31(2), 333–341.
Cain, D. (1997). “U.S. Geological survey data collection center and studies in the Arkansas River basin.” Colorado Water: Newsletter of the Water Center at Colorado State University, Colorado State Univ., Fort Collins, CO.
Eldeiry, A., and Garcia, L. A. (2008a). “Detecting soil salinity in alfalfa fields using spatial modeling and remote sensing.” Soil Sci. Soc. Am. J., 72(1), 201–211.
Eldeiry, A., and Garcia, L. A. (2008b). Spatial modeling of soil salinity using remote sensing, GIS, and field data, VDM, Saarbruken, Germany.
Eldeiry, A., and Garcia, L. A. (2010). “Comparison of ordinary kriging, regression kriging, and cokriging techniques to estimate soil salinity using landsat images.” J. Irrig. Drain. Eng., 136(6), 355–364.
Eldeiry, A., and Garcia, L. A. (2011). “Using indicator kriging technique for soil salinity and yield management.” J. Irrig. Drain. Engin., 137(2), 82–93.
Eldeiry, A., Garcia, L. A., and Reich, R. M. (2008). “Soil salinity sampling strategy using spatial modeling techniques, remote sensing, and field data.” J. Irrig. Drain. Eng., 134(6), 768–777.
Ferguson, R. B., Hergert, G. W., and Penas, E. J. (2000). “Corn.” Nutrient Management for Agronomic Crops in Nebraska. EC 01-155., R. B. Ferguson, ed., Univ. of Nebraska, Lincoln, NE, 75–83.
Fleming, K. L., Westfall, D. G., Wiens, D. W., Rothe, L. E., Cipra, J. E., and Heerman, D. F. (1999). “Evaluating farmer developed management zone maps for recision farming.” Proc. of the 4th Int. Conf. on Precision Agriculture, 1998, P. C. Robert, R. H. Rust, W. E. Larson, eds., American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Madison, WI, 335– 344.
Fraisse, C., Sudduth, K., Kitchen, N., and Fridgen, J. (1999). “Use of unsupervised clustering algorithms of delineating within-field management zones.” Paper 993043, American Society of Agricultural Engineers (ASAE), St. Joseph, MI.
Frasier, W. M., Waskom, R. M., Hoag, D. L., and Bauder, T. A. (1999). “Irrigation management in Colorado: Survey data and findings.” Technical Rep. TR 99-5, Agricultural Experiment Station, Colorado State Univ., Fort Collins, CO.
Fridgen, J., Fraisse, C., Kitchen, N., and Sudduth, K. (2000). “Delineation and analysis of site-specific management zones.” Second Int. Conf. on Geospatial Information in Agriculture and Forestry, B. J. Petoskey, ed., ERIM International, Ann Arbor, MI, 402–411.
Gates, T. K., Burkhalter, J. P., Labadie, J. W., Valliant, J. C., and Broner, I. (2002). “Moitoring and modeling flow and salt transport in a salinity-threatened irrigated valley.” J. Water Resour. Plann. Manage., 128(2), 87–99.
Ghassemi, F., Jakeman, A. J., and Nix, H. A. (1995). Salinisation of land and water resources: Human causes, extent, management, and case studies, Univ. of New SouthWales, Sydney, Australia.
Halvorson, J. J., Smith, J. L., Bolton, H., and Rossi, R. E. (1995). “Evaluating shrub-associated patterns of soil properties in a shrub-steppe ecosystem using multiple-variable geostatistics.” Soil Sci. Soc. Am. J., 59(5), 1476–1487.
Hochstrasser, U. W. (1965). Handbook of mathematical functions, M. Abramowitz and I. A. Stegun, ed., Dover, Mineola, NY.
Jones, R., and Marshall, G. (1992). “Land salinisation, waterlogging and the agricultural benefits of a surface drainage scheme in Benerembah irrigation district.” Rev. Market Agric. Econ., 60(02), 173–189.
Journel, A. G. (1983). “Nonparametric estimation of spatial distributions.” Math. Geol., 15(3), 445–468.
Journel, A. G., and Huijbregts, Ch. J. (1978). Mining characteristics, Academic Press, New York.
Maas, E. V., and Hoffman, G. J. (1977). “Crop salt tolerance—Current assessment.” J. Irrig. and Drain Div., 103(2), 115–134.
Matheron, G. (1976). “A simple substitute for conditional expectation: The disjunctive kriging.” Advanced Geostatistics in the Mining Industry Proceedings of the North Atlantic Treaty Organization (NATO) Advanced Study Institute, M. Guarascio, M. David, and C. Huijbregts, eds., D. Reidel, Dordrecht, Holland, 221–236.
Miles, D. L. (1977). “Salinity in the Arkansas Valley of Colorado.” Environmental Protection Agency Region VIII, Denver.
Postel, S. (1989). “Water for agriculture: Facing the limits.” Worldwatch Paper 93, Worldwatch Institute, Washington, D.C.
Russo, D. (1984a). “Design of an optimal sampling network for estimating the variogram.” Soil Sci. Soc. Am. J., 48(4), 708–716.
Russo, D. (1984b). “A geostatistical approach to the trickle irrigation design in a heterogenous soil. 2. A field test.” Water Resources Res., 20(5), 543–552.
Schepers, J. S., Schlemmer, M. R., and Ferguson, R. B. (2000). “Site-specific considerations for managing phosphorus.” J. Environ. Qual., 29(1), 125–130.
Stafford, J. V., Lark, R. M., and Bolam, H. C. (1998). “Using yield maps to regionalize fields into potential management units.” Proc. of the 4th Int. Conf. on Precision Agriculture, P. C. Robert, ed., American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Madison, WI, 225–237.
Storey, R., and Jones, R. G. W. (1978). “Salt stress and comparative physiology in the Gramineae. I. Ion relations of two salt-and water-stressed barley cultivars, California Mariout and Arimar.” Aust. J. Plant Physiol., 5(6), 801–816.
Tanji, K. K., ed. (1990). Agricultural salinity assessment and management, (ASCE Manuals and Reports on Engineering Practice No. 71), ASCE, New York.
Triantafilis, J., Odeh, I. O. A., and McBratney, A. B. (2001). “Five geostatistical models to predict soil salinity from electromagnetic induction data across irrigated cotton.” Soil Sci. Soc. Am. J., 65(3), 869–878.
Van Meirvenne, M., and Goovaerts, P. (2001). “Evaluating the probability of exceeding a site-specific soil cadmium contamination threshold.” Geoderma, 102(1-2), 75–100.
von Steiger, B., Webster, R., Schulin, R., and Lehmann, R. (1996). “Mapping heavy metals in polluted soil by disjunctive kriging.” Environ. Pollut., 94(2), 205–215.
Webster, R., and Burgess, T. M. (1980). “Optimal interpolation and isarithmic mapping of soil properties. 3. Changing drift and universal kriging.” J. Soil Sci., 31(3), 505–524.
Webster, R., and Oliver, M. A. (1989). “Optimal interpolation and isarithmic mapping of properties. VI. Disjunctive kriging and mapping conditional probability.” J. Soil Sci., 40(3), 497–517.
Wichelns, D. (1999). “An economic model of waterlogging and salinization in arid regions.” Ecol. Econ., 30(3), 475–491.
Wittler, J. M., Cardon, G. E., Gates, T. K., Cooper, C. A., and Sutherland, P. L. (2006). “Calibration of electromagnetic induction for regional assessment of soil water salinity in an irrigated valley.” J. Irrig. Drain. Eng., 132(5), 436–444.
Wood, G., Oliver, M. A., and Webster, R. (1990). “Estimating soil salinity by disjunctive kriging.” Soil Use Manage., 6(3), 97–104.
Yates, S. R., Warrick, A. W., Matthias, A. D., and Musil, S. (1988). “Spatial variability of remotely sensed surface temperatures at field scale.” Soil Sci. Soc. Am. J., 52(1), 40–45.
Yates, S. R., Warwick, A. W., and Myers, D. E. (1986a). “Disjunctive kriging. 1. Overview of estimation and conditional probability.” Water Resour. Res., 22(5), 615–622.
Yates, S. R., Warwick, A. W., and Myers, D. E. (1986b). “Disjunctive kriging. 2. Examples.” Water Resour. Res., 22(5), 623–630.
Yates, S. R., and Yates, M. V. (1988). “Disjunctive kriging as an approach to management decision making.” Soil Sci. Soc. America J., 52(6), 1554–1558.
Zirschky, J. (1985). “Geostatistics for environmental monitoring and survey design.” Environ. Int., 11(6), 515–524.
Zirschky, J., and Harris, D. J. (1986). “Geostatistical analysis of hazardous waste site data.” J. Environ. Eng., 112(4), 770–784.
Zirschky, J. H., Keary, G. P., Gilbert, R. O., and Middlebrooks, E. J. (1985). “Spatial estimation of hazardous waste site data.” J. Environ. Eng., 111(6), 777–789.
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Published In
Journal of Irrigation and Drainage Engineering
Volume 138 • Issue 3 • March 2012
Pages: 211 - 224
Copyright
© 2012 American Society of Civil Engineers.
History
Received: Sep 1, 2010
Accepted: Jun 23, 2011
Published online: Feb 15, 2012
Published in print: Mar 1, 2012
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