Skip to main content
Log in

Spatial variability of salinity and alkalinity of a field having salination risk in semi-arid climate in northern Turkey

  • Original Article
  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

Spatial variability of salinity and alkalinity is important for site-specific management since they are the most important factors influencing soil quality and agricultural production. The objectives of this study were to analyze spatial variability in salinity and alkalinity and some soil properties affecting salinity and alkalinity, using classical statistics and geostatistical methods, in an irrigated field with low-quality irrigation water diverted from drainage canals. A field of 5 da was divided into 10m × 10m grids (5 lines in the east-west direction and 10 lines in the north-south direction). The soil samples were collected from three depths (0-30, 30-60 and 60-90cm) at each grid corner. The variation coefficients of OM and sand contents were higher than other soil properties. OM had the maximum variability, with a mean of 1.63% at 0-30cm depth and 0.71% at 30-60cm depth. Significant correlations occurred between ESP, EC and each of Ca, Mg, K and CaCO3 contents of the soils (p<0.01). Experimental semivariograms were fitted to spherical and gaussian models. All geostatistical range values were greater than 36m. The soil properties had spatial variability at small distances at 60-90cm depth. EC was variable within short distances at 30-60cm depth. The nugget effect of ESP increased with soil depth. Kriged contour maps revealed that soils had a salinisation and alkalisation tendency at 60-90cm depth based on spatial variance structure of the EC and ESP values. Spatial variability in EC and ESP can depend on ground water level, quality of irrigation water, and textural differences.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Ayers, R.S. & Westcot, D.W. (1989). Water Quality for Agriculture. FAO Irrigation and Drainage. Paper no: 29, pp. 1–174, Rome.

  • Bohn, H.L., McNeal, B.L. & O'Connor, G.A. (1985). Soil chemistry (329 pp). New York: Wiley.

    Google Scholar 

  • Boivin, P., Favre, F., Hammecker, C., Maeght, J.L., Delariviere, J., Poussin, J.C., & Wopereis, M. C. S. (2002). Processes driving soil solution chemistry in a flooded rice-cropped vertisol: analysis of long-time monitoring data. Geoderma, 110, 87–107.

    Article  CAS  Google Scholar 

  • Burgess, T.M. & Webster, R. (1980). Optimal interpolation and isarithmic mapping of soil properties. I. The semi-variogram and punctual kriging. Journal of Soil Science, 31, 315–331.

    Article  Google Scholar 

  • Cambardella, C.A. & Karlen, D.L. (1999). Spatial analysis of soil fertility parameters. Precision Agriculture 1, 5–14.

    Article  Google Scholar 

  • Ceuppens, J., Wopereis, M.C.S. & Miezan, K.M. (1997). Soil salinization processes in rice irrigation schemes in the Senegal River delta. Soil Science Society of American Journal, 61(4), 1122–1130.

    Article  CAS  Google Scholar 

  • Dolittle, J.A., Sudduth, K.A., Kitchen, N.R., & Indorante, S.J. (1994). Estimating depth to claypans using electromagnetic induction methods. Journal of Soil Water Conservaton, 49, 572–575.

    Google Scholar 

  • Gee, G.W. & Bouder, J.W. (1986). Particle size analysis. In: Klute, A. (Ed.), Methods of soil analysis. Part 1. Physical and mineralogical methods (2nd ed., pp. 825–844) Madison, WI: Agronomy monography no: 9, ASA and SSSA.

    Google Scholar 

  • Goovaerts, R. (1997). Geostatistics for natural resources evaluation (483 pp). New York: Oxford University Press.

    Google Scholar 

  • GS+5.1. (2001). Gamma design software. MI, USA.: Plainwell.

  • Isaaks, E.H. & Srivastava, R.M. (1989). An introduction to applied geostatistics (561 pp). New York: Oxford Uni. Press, Inc.

    Google Scholar 

  • Kachanoski, R.G., Gregorich, E.G., & Van Wesenbeck, I. J. (1988). Estimating spatial variations of soil water content using non-containing electromagnetic inductive methods. Canadian Soil Science, 68, 715–722.

    Article  Google Scholar 

  • Kelleners, T.J. & Chaudhry, M.R. (1998). Drainage water salinity of tube wells and pipe drains: A case study from Pakistan. Agriculture Water Management 37, 41–53.

    Article  Google Scholar 

  • Kí lí ç, K., Özgöz, E., & Akbaş, F. (2004). Assessment of spatial variability in penetration resistance as related to some soil physical properties of two Fluvents in Turkey. Soil & Tillage Research, 76, 1–11.

    Article  Google Scholar 

  • Miyamoto, S., Chacon, A., Hossain, M., & Martinez, I. (2005). Soil salinity of urban turf areas irrigated with saline water: I. Spatial variability. Landscape and Urban Planning, 71, 233–241.

    Google Scholar 

  • Miyamoto, S. & Chacon, A. (2005). Soil salinity of urban turf areas irrigated with saline water: II. Soil factors. Landscape and Urban Planning. (in Press)

  • Miyamoto, S. & Cruz, I. (1987). Spatial variability of soil salinity in furrow-irrigated torrifluvents. Soil Science Society of American Journal, 51, 1019–1025.

    Article  Google Scholar 

  • Mulla, D.J. & McBratney, A.B. (2000). Soil spatial variability (pp. A-321–A-352). In: M.E. Sumner (Ed.), Handbook of soil science. Boca Raton, FL, USA.: CRC Press.

    Google Scholar 

  • Nelson, D.W. & Sommers, l.E. (1982). Total carbon, organic carbon and organic matter. In: Page, A. L., et al., (Eds.). Part 2. Methods of soil analysis (2nd ed., pp. 539–577). Madison, WI: ASA Publ. Vol. 9 ASA and SSSA.

    Google Scholar 

  • Nielsen, D.R., Tillotson, P.M., & Vieira, S.R. (1983). Analyzing field-measured soil-water properties. Agricultural Water Management 6, 93–109.

    Article  Google Scholar 

  • Postel, R. (1989). Water of agriculture: Facing the limits, worldwatch paper. Washington D.C.: 93 Worldwatch Ins.

    Google Scholar 

  • Rhoades, J.D. (1986). Cation exchange capacity. In C. A. Francis et al. (ed.) Methods of soil analysis (pp. 149–158). Madison, WI.: Part 2. 2nd ed. Agron. Monogr. 9. ASA and SSSA.

    Google Scholar 

  • Rhoades, J.D., Kandioh, A.P., & Mashali, A.M. (1992). The Use of Saline Waters for Crop Production. FAO irrigation and Drainage Paper 48, Food and Agricultural Organization of The United Nations, Rome Italy.

  • Saltalí , K. & Derici, M.R. (1999). Salinity status and seasonal movement of salts in Kazova soils of Tokat in Turkey. Gaziosmanpasa University of Agricultur Faculty Journal, 16, 203–215.

    Google Scholar 

  • Saltalí , K., Kí lí ç, K., Durak, A., & Kí lí ç, M. (1999). The determination of water quality of some drainage channels at Kaz Lake of Tokat province in Turkey. Gaziosmanpasa University of Agricultur Faculty Journal, 16, 193–203.

    Google Scholar 

  • Seatz, L.F. & Peterson, H.B. (1965). Acid, alkaline, saline, and sodic soils. In: Bear, F. E. (Ed.), Chemistry of the soil (pp. 292–319). New York: Reinhold Pub.

    Google Scholar 

  • Sharma, D.P. & Rao, K.V.G.K. (1998). Strategy for long term use of saline drainage water for irrigation in semi-arid regions. Soil&Tillage Research, 48, 287–295.

    Google Scholar 

  • SPSS (2000). SPSS for Windows. Student Version. USA.: Release 10.0.9. SPSS Inc.

    Google Scholar 

  • State Water Works. (1999). The detailed land classification and drainage reports in Kazova Province in Turkey. Upper Yesilirmak Project, 2, 17–790. Ankara, Turkey.

    Google Scholar 

  • Sudduth, K.A., Kitchen, N.R., & Drummond, S.T. (1999). Soil conductivity sensing on claypan soils: Comparison of electromagnetic induction and direct methods. In: P. C. Robert, R. H. Rust, & W. E. Larson (Eds.), Proceedings of the 4th Int. Conference On Precision Agriculture (pp. 979–990). St. Paul, MN, July 19–22 1998. Madison, WI: ASA-CSSA-SSSA.

    Google Scholar 

  • Taşova, H. (1997). Classification, survey and mapping of soils in the kazova agriculture working. Gaziosmanpaşa Uni. Grad. Sch. Nat. App. Sci., Dept. Soil Sci., PhD Thesis, 187 pp.

  • Trangmar, B.B., Yost,R.S., & Uehara, G. (1985). Application of geostatistics to spatial stu-dies of soil properties. Advancement in Agronomy, 38, 45–94.

    Google Scholar 

  • Utset, A., Ruiz, M.E., Herrera, J. & de Leon, D.P. (1998). A geostatistical method for soil salinity sample site spacing. Geoderma, 86, 143–151.

    Article  Google Scholar 

  • van Asten, P.J.A., Barbiero, L., Wopereis, M.C.S., Maeght, J.L. & van der Zee, S.E.A.T.M. (2003). Actual and potential salt-related soil degradation in an irrigated rice scheme in the Sahelian zone of Mauritania. Agricultural Water Management, 60, 13–32.

    Article  Google Scholar 

  • Warrick, A.W., Myers, D.E. & Nielsen, D.R. (1986). Geostatistical methods applied to soil science. SSSA, Agronomy Monograph no. 9.

  • Webster, R. (1985). Quantitative Spatial Analysis of Soil in The Field. Advancement in Soil Science, 3, 1–70.

    Google Scholar 

  • Webster, R., (2001). Statistics to support soil research and their presentation. European Journal of Soil Science, 52, 331–340.

    Article  CAS  Google Scholar 

  • Webster, R. & Oliver, M.A. (1990). Statistical methods in soil and land resource survey (316 pp). Oxford Univ. Press.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kenan Kılıç.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kılıç, K., Kılıç, S. Spatial variability of salinity and alkalinity of a field having salination risk in semi-arid climate in northern Turkey. Environ Monit Assess 127, 55–65 (2007). https://doi.org/10.1007/s10661-006-9258-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10661-006-9258-x

Keywords

Navigation