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The effects of hydrometer reading times on the spatial variability of soil textures in southeast Iran

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Abstract

Soil texture is an important physical soil property that may contribute to variations in many soil functions as well as nutrient storage and availability, water retention, and soil erosion. Although several methods for determining the texture classes of soil particles have been proposed, differences among hydrometer reading times have presented challenges in determining the precise soil texture classes. Therefore, this study was conducted to evaluate the effects of hydrometer reading time on the spatial variability of soil textures in the Rafsanjan area, southeast Iran. To accomplish this, 77 soil samples were collected on a 500-m square sampling grid from depths of 0–40, 40–80, and 80–120 cm, and their particle sizes were determined through analysis for 40 s, 2 h, 6.5 h, and 8 h using the Bouyoucos hydrometer method. The results showed a strong spatial correlation in the soil particles among sampling soil layers and across the study area. Moreover, the differences among hydrometer reading times did not have a significant impact on determination of coarse soil texture classes, although they did influence determination of the finer classes. Although the 8 h reading time provided the most accurate response with respect to mechanical analysis of a soil, after 6.5 h the hydrometer could also largely (more than 80.0 %, on average) achieve this goal. Additionally, the 2 h hydrometer reading time could also be useful for the initial assessment or general overview of the soil texture in a certain region; however, it is not recommended for precision agriculture or site-specific management.

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References

  • Bailey TC, Gatrell AC (1998) Interactive spatial data analysis. Addison Wesley Longman, London

    Google Scholar 

  • Bouyoucos GJ (1962) Hydrometer method improved for making particle size analysis of soils. Agron J 54:464–465

    Article  Google Scholar 

  • Brejda JJ, Moorman TB, Smith JL, Karlen DL, Allan DL, Dao TH (2000) Distribution and variability of surface soil properties at a regional scale. Soil Sci Soc Am J 64:974–982

    Article  Google Scholar 

  • Burrough PA (1993) Soil variability: a late 20th century view. Soils Fert 56:529–562

    Google Scholar 

  • Cambardella CA, Karlen DK (1999) Spatial analysis of soil fertility parameters. Precision Agri 1:5–14

    Article  Google Scholar 

  • Cambardella CA, Moorman TB, Parkin TB, Karlen DL, Turco RF, Konopka AE (1994) Field scale variability of soil properties in Central Iowa soils. Soil Sci Soc Am J 58:1501–1511

    Article  Google Scholar 

  • Congalton RG (1991) A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environ 37:35–46

    Article  Google Scholar 

  • Cooper LT, Haverland RL, Hendricks DM, Knisel WG (1984) Microtrac particle size analyser: an alternative particle size determination method for sediment and soils. Soil Sci 138:138–146

    Article  Google Scholar 

  • Cosby BJ, Hornberger GM, Clapp RB, Ginn TR (1984) A statistical exploration of the relationships of soil moisture characteristics to the physical properties of soils. Water Resour Res 20:682–690

    Article  Google Scholar 

  • Day PR (1965) Particle fractionation and particle size analysis. In: Black CA et al (eds) Methods of soil analysis. Part 1. Agronomy series No. 9, Madison, pp 545–567

    Google Scholar 

  • Elghamry W, Elashkar M (1962) Simplified textural classification triangles. Soil Sci Soc Am Proc 26:612–613

    Article  Google Scholar 

  • Esfandiarpoor Borujeni I, Mohammadi J, Salehi MH, Toomanian N, Poch RM (2010) Assessing geopedological soil mapping approach by statistical and geostatistical method: a case study in the Borujen region, Central Iran. Catena 82:1–14

    Article  Google Scholar 

  • Gascóz G, Lobo MC, Guerrero F (2003) Heavy metals mass balance in a Typic Xerofluvenst treated with aerobically digested sewage sludges. Electron J Environ Agric Food Chem 2:356–364

    Google Scholar 

  • Gee GW, Bauder JW (1986) Particle-size analysis. In: Klute A (ed) Methods of soil analysis. Part 1. Agronomy series No. 9, Madison, pp 383–411

    Google Scholar 

  • GEOEAS (1991) Environmental monitoring systems laboratory office of research and development. US Environmental Protection Agency, Las Vegas

    Google Scholar 

  • Gil M, Rodriguez-Sinobas L, Sanchez R, Juana L (2010) Evolution of the spherical cavity radius generated around a subsurface drip emitter. Irrigation hydraulics research group, technical university of Madrid. Biogeosciences Discuss 7:1935–1958

    Article  Google Scholar 

  • Goovaerts P (1997) Geostatistics for natural resources evaluation. Oxford University Press, New York

    Google Scholar 

  • Granados FL, Exposito MJ, Atenciano S, Ferrer AG, Orden MS, Torres LG (2002) Spatial variability of agricultural soil parameters in southern Spain. Plant and Soil 246:97–105

    Article  Google Scholar 

  • Green AJ (1981) Particle size analysis. In: McKeague JA (ed) Manual on soil sampling and methods of analysis. Canadian Society of Soil Science, Ottawa, pp 7–29

    Google Scholar 

  • Greenwood DJ, Neeteson JJ, Draycott A (1985) Response of potatoes to N fertilizer: dynamic model. Plant and Soil 85:185–203

    Article  Google Scholar 

  • Hengl T, Husnjak S (2006) Evaluating adequacy and usability of soil maps in Croatia. Soil Sci Soc Am J 70:920–929

    Article  Google Scholar 

  • Hosseinifard SJ, Khademi H, Kalbasi M (2010) Different forms of soil potassium as affected by the age of pistachio (Pistachio vera L.) trees in Rafsanjan, Iran. Geoderma 155:289–297

    Article  Google Scholar 

  • Huang SW, Jin JY, Yang LP, Bai YL (2006) Spatial variability of soil nutrients and influencing factors in a vegetable production area of Hebei Province in China. Nutr Cycl Agroecos 75:201–212

    Article  Google Scholar 

  • Iqbal J, Thomasson JA, Jenkins JN, Owens PR, Whisler FD (2005) Spatial variability analysis of soil physical properties of alluvial soils. Soil Sci Soc Am J 69:1338–1350

    Article  Google Scholar 

  • Isaaks EH, Srivastava RM (1989) An introduction to applied geostatistics. Oxford University Press, New York

    Google Scholar 

  • ITC (2007) ILWIS 3.4 for windows. Institute for Aerospace Surveys and Earth Sciences, The Netherlands.

  • Khoshgoftarmanesh AH (2007) Evaluation of plant nutrition status and optimum fertilizer management (in Persian). Isfahan University of Technology, Isfahan

    Google Scholar 

  • Koukoulas S, Blackburn GA (2001) Introducing new indices for accuracy evaluation of classified images representing semi-natural woodland environments. Photogram Eng Remote Sensing 67:499–510

    Google Scholar 

  • Kravchenko AN (2003) Influence of spatial structure on accuracy of interpolation methods. Soil Sci Soc Am J 67:1564–1571

    Article  Google Scholar 

  • Legros JP (2006) Mapping of the soil (in French). Science Publishers, NH, USA

    Google Scholar 

  • Lewis GC, Fosberg MA, Falen AL (1984) Identification of loess by particle size distribution using the Coulter Counter TA II. Soil Sci 137:172–176

    Article  Google Scholar 

  • Li J, Heap AD (2008) A review of spatial interpolation methods for environmental scientists. Geoscience publication, Australia

    Google Scholar 

  • Manteghi N (1977) Methods and laboratory analyses on soil and water samples (in Persian). Water and Soil Research Institute, Publication No 168, Tehran

    Google Scholar 

  • McBratney AB, Pringle MJ (1999) Estimating average and proportional variograms of soil properties and their potential use in precision agriculture. Precision Agri 1:219–236

    Article  Google Scholar 

  • Meirvenne MV, Cleemput LV (2005) Pedometrical techniques for soil texture mapping at different scales. Environ Soil-Landscape Model 3011:323–342

    Google Scholar 

  • Okae-Anti D, Ogoe JI (2006) Analysis of variability of some properties of a semideciduous forest soil. Commun Soil Sci Plant Analy 37:211–223

    Article  Google Scholar 

  • Pannatier Y (1996) VARIOWIN: software for spatial data analysis in 2D. Springer, New York

    Book  Google Scholar 

  • Park SJ, Vlek PLG (2002) Environmental correlation of three-dimensional soil spatial variability: a comparison of three adaptive techniques. Geoderma 10:117–140

    Article  Google Scholar 

  • Regalado CM, Ritter A (2005) Characterizing water dependent soil repellency with minimal parameter requirement. Soil Sci Soc Am J 69:1955–1966

    Article  Google Scholar 

  • Rossi J, Govaerts A, Vos BD, Verbist B, Vervoort A, Poesen J, Muys B, Deckers J (2009) Spatial structures of soil organic carbon in tropical forests, a case study of Southeastern Tanzania. Catena 77:19–27

    Article  Google Scholar 

  • Santra P, Chopra UK, Chakraborty D (2008) Spatial variability of soil properties and its application in predicting surface map of hydraulic parameters in an agricultural farm. Current Sci 95:937–945

    Google Scholar 

  • Schloeder CA, Zimmerman NE, Jacobs MJ (2001) Comparison of methods for interpolating soil properties using limited data. Soil Sci Soc Am J 65:470–479

    Article  Google Scholar 

  • Shirazi MA, Boersma L (1984) A unifying quantitative analysis of soil texture. Soil Sci Soc Am J 48:142–147

    Article  Google Scholar 

  • Sparks DL, Liebhardt WC (1982) Temperature effects on potassium exchange and selectivity in Delaware soils. Soil Sci 133:10–17

    Article  Google Scholar 

  • Stocks GG (1851) On the effect of the lateral friction of fluids on the motion of pendulums. Trans Cambridge Phil Soc 9:8–106

    Google Scholar 

  • Thrikawala S, Weersink A, Kachanoski G, Fox G (1999) Economic feasibility of variable-rate technology for nitrogen on corn. Am J Agri Econ 81:914–927

    Article  Google Scholar 

  • Trangmar BB, Yost RS, Uehara G (1985) Application of geostatistics to spatial studies of soil properties. Adv Agron 38:45–93

    Article  Google Scholar 

  • Vicente-Serrano SM, Saz-Sánchez MA, Cuadrat JM (2003) Comparative analysis of interpolation methods in the middle Ebro Valley, Spain: application to annual precipitation and temperature. Climate Research 24:161–180

    Article  Google Scholar 

  • Wang Y, Zhang X, Huang C (2009) Spatial variability of soil total nitrogen and soil total phosphorus under different land uses in a small watershed on the Loess Plateau, China. Geoderma 150:141–149

    Article  Google Scholar 

  • Webster R, Oliver MA (2001) Geostatistics for environmental scientists. Wiley, Chichester

    Google Scholar 

  • Wei JB, Xiao DN, Zeng H, Fu YK (2008) Spatial variability of soil properties in relation to land use and topography in a typical small watershed of the black soil region, northeastern China. Environ Geology 53L:1663–1672

    Article  Google Scholar 

  • Weiss EL, Frock NH (1976) Rapid analysis of particle size distribution by laser light scattering. Powder Technol 14:287–293

    Article  Google Scholar 

Download references

Acknowledgments

Financial and technical support for this research from Soil Science Department, Vali-e-Asr University of Rafsanjan is acknowledged.

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Authors and Affiliations

  1. College of Agriculture, Vali-e-Asr University of Rafsanjan, P.O. Box 518, Rafsanjan, Iran

    Alireza Owji

  2. Soil Science Department, College of Agriculture, Vali-e-Asr University of Rafsanjan, P.O. Box 518, Rafsanjan, Iran

    Isa Esfandiarpour Boroujeni & Ardavan Kamali

  3. Institute of Pistachio Research, Rafsanjan, Iran

    Seyed Javad Hosseinifard

  4. College of Agriculture, Shahrekord University, P.O. Box 115, Shahrekord, Iran

    Mohsen Bagheri Bodaghabadi

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  1. Alireza Owji
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  2. Isa Esfandiarpour Boroujeni
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  3. Ardavan Kamali
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  4. Seyed Javad Hosseinifard
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  5. Mohsen Bagheri Bodaghabadi
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Correspondence to Isa Esfandiarpour Boroujeni.

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Owji, A., Esfandiarpour Boroujeni, I., Kamali, A. et al. The effects of hydrometer reading times on the spatial variability of soil textures in southeast Iran. Arab J Geosci 7, 1491–1499 (2014). https://doi.org/10.1007/s12517-012-0786-0

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  • DOI: https://doi.org/10.1007/s12517-012-0786-0

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