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Spatial variability analysis and mapping of soil physical and chemical attributes in a salt-affected soil

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Abstract

Knowledge of inherent spatial variability of soil physical and chemical properties is needed for more accurate site-specific management of soil nutrients. In this study we investigated the spatial variability of a wide range of soil physical and chemical properties including soil texture fractions (percentages of sand, silt, and clay denoted as Sand, Silt and Clay, respectively), soil water content (WC), bulk density (BD), gypsum, organic carbon (OC), electrical conductivity (EC), pH, Ca, Mg, Na, exchangeable sodium percentage (ESP), sodium absorption ratio (SAR), available phosphorous (AP), and available potassium (AK) in a saline-alkaline soil catena in Sistan Plain, southeast of Iran. Soil samples were collected from two depths (0–15 and 15–30 cm) on a nearly regular grid at 113 sites over an 85-ha agricultural field. Statistical analysis of soil properties showed that Na, Mg, Ca, WC, EC, ESP, and SAR have a large coefficient of variation (CV) (more than 50%) and BD and pH have a low CV (less than 15%) for both layers. The correlation among soil properties varies for two layers; while Silt, WC, EC, ESP, Na, and gypsum are statistically (p < 0.01 and p < 0.05) correlated with most of physical and chemical properties in topsoil, Sand, EC, and OC are the most dominant properties in subsoil. Geostatistical autocorrelation analysis of soil properties were examined based on the “range of spatial continuity” and “nugget to sill” ratio. Accordingly, AP and subsoil ESP have the lowest spatial correlation while texture fractions are the most auto-correlated variables in space. The spatial structure of soil properties followed either a spherical or an exponential model with a minimum correlation distance of 70 m for AP to almost 800 m for soil fractions. The results indicated that spatial continuity generally increases and decreases with depth for soil physical and chemical properties, respectively. The difference in spatial variability of soil properties could be attributed to internal factors (e.g., the forming processes of soil) as well as external factors (e.g., human activities). The maps of soil physical and quality parameters were generated using either kriging or inverse distance weighting methods depending on cross-validation results. In general, topsoil layer has a greater amount of EC, ESP, SAR, pH, Na, Ca, Mg, and OC than subsoil while Silt, WC, and gypsum were often higher in subsoil. OC maps showed that the whole area is relatively low in organic carbon, mainly due to hot and dry climate and windy conditions in Sistan. The maps of soil nutrients provide useful information for adapting an efficient and precision agricultural production management.

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References

  • Abegaz A, Adugna A (2015) Effects of soil depth on the dynamics of selected soil properties among the highlands resources of northeast Wollega, Ethiopia: are these sign of degradation? Solid Earth Discussions 7(3)

  • Adhikari G, Bhattacharyya KG (2015) Correlation of soil organic carbon and nutrients (NPK) to soil mineralogy, texture, aggregation, and land use pattern. Environ Monit Assess 187:735

    Google Scholar 

  • Afrasiab P, Delbari M (2013) Assessing the risk of soil vulnerability to wind erosion through conditional simulation of soil water content in Sistan plain, Iran. Environ Earth Sci 70:2895–2905

    Google Scholar 

  • Amini M, Afyuni M, Khademi H, Abbaspour KC, Schulin R (2005) Mapping risk of cadmium and lead contamination to human health in soils of Central Iran. Sci Total Environ 347:64–77

    Google Scholar 

  • Ayoubi SH, Mohammad Zamani S, Khormali F (2012) Spatial variability of some soil properties for site specific farming in northern Iran. Intl J Plant Prod 1(2):225–236

    Google Scholar 

  • Basso B, Ritchie JT (2015) Simulating crop growth and biogeochemical fluxes in response to land management using the SALUS model. In: The ecology of agricultural landscapes: long-term research on the path to sustainability. Oxford University press, New York, NY USA, pp 252–274

    Google Scholar 

  • Basso B, Bertocco M, Sartori L, Martin EC (2007) Analyzing the effects of climate variability on spatial pattern of yield in a maize-wheat-soybean rotation. Eur J Agron 26:82–91

    Google Scholar 

  • Bhatti AU, Bakhsh A, Afzal M, Gurmani AH (1999) Spatial variability of soil properties and wheat yields in an irrigated field. Commun Soil Sci Plant Anal 30:1279–1290

    Google Scholar 

  • Blake GR, Hartge KH (1986) Bulk density. In: Klute, a., Ed., methods of soil analysis, part 1-physical and mineralogical methods, 2nd ed. agronomy monograph 9, am Soc Agron-soil Sci Soc am, Madison

  • Blumfield TJ, Zhi-Hong XU, Prasolova NV (2007) Sampling size required for determining soil carbon and nitrogen properties at early establishment of second rotation hoop pine plantations in subtropical Australia. Pedosphere 17:706–711

    Google Scholar 

  • Boekhold AE, Van der Zee SE (1992) Significance of soil chemical heterogeneity for spatial behavior of cadmium of cadmium in field soils. Soil Sci Soc Am J 56:747–754

    Google Scholar 

  • Bogunovic I, Trevisani S, Seput M, Juzbasic D, Durdevic B (2017) Short-range and regional spatial variability of soil chemical properties in an agro-ecosystem in eastern Croatia. Catena 154:50–62

    Google Scholar 

  • Bouma J, Stoorvogel J, van Alphen BJ, Booltink HWG (1999) Pedology, precision agriculture, and the changing paradigm of agricultural research. Soil Sci Soc Am J 63(6):1763–1768

    Google Scholar 

  • Box GE, Cox DR (1964) An analysis of transformations. J Royal Stat Soc Series B (Methodological) 26:211–252

    Google Scholar 

  • Brouder SM, Hofmann BS, Morris DK (2005) Mapping Soil pH. Soil Sci Soc Am J 69:427–442

    Google Scholar 

  • Brus DJ, Heuvelink GBM (2007) Optimization of sample patterns for universal kriging of environmental variables. Geoderma 138:86–95

    Google Scholar 

  • Burgess TM, Webster R (1980) Optimal interpolation and isar1thmic mapping of soil properties. Eur J Soil Sci 31:315–331

    Google Scholar 

  • Callesen I, Liski J, Raulund-Rasmussen K, Olsson MT, Tau-Strand L, Vesterdal L, Westman CJ (2003) Soil carbon stores in Nordic well-drained forest soils—relationships with climate and texture class. Glob Chang Biol 9:358–370

    Google Scholar 

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

    Google Scholar 

  • Cemek B, Guler M, Kilic K, Demir Y, Arslan H (2007) Assessment of spatial variability in soil properties as related to soil salinity and alkalinity in Bafra plain in northern Turkey. Environ Monit Assess 124:223–234

    Google Scholar 

  • Chung CK, Chong SK, Varsa EC (1995) Sampling strategies for fertility on a stoy silt loam soil. Commun Soil Sci Plant Anal 26(5-6):741–763

    Google Scholar 

  • Clark I (1979) Practical geostatistics. Applied Science Publishers, London

    Google Scholar 

  • Delbari M, Afrasiab P, Loiskandl W (2009) Using sequential Gaussian simulation to assess the field-scale spatial uncertainty of soil water content. Catena 79:163–169

    Google Scholar 

  • Delbari M, Loiskandl W, Afrasiab P (2010) Uncertainty assessment of soil organic carbon content spatial distribution using geostatistical stochastic simulation. Soil Res 48:27–35

    Google Scholar 

  • Delbari M, Afrasiab P, Loiskandl W (2011) Geostatistical analysis of soil texture fractions on the field scale. Soil Water Res 6:173–189

    Google Scholar 

  • Eswaran H, Reich PF (2005) World soil map. In: Hillel D, Hatfield JL (eds) Encyclopedia of soils in the environment (Vol. 3). Elsevier, Amsterdam

    Google Scholar 

  • Evrendilek F, Celik I, Kilic S (2004) Changes in soil organic carbon and other physical soil properties along adjacent Mediterranean forest, grassland, and cropland ecosystems in Turkey. J Arid Environ 59:743–752

    Google Scholar 

  • Fu W, Tunney H, Zhang C (2010) Spatial variation of soil nutrients in a dairy farm and its implications for site-specific fertilizer application. Soil Tillage Res 106:185–193

    Google Scholar 

  • Gallardo A, Paramá R (2007) Spatial variability of soil elements in two plant communities of NW Spain. Geoderma 139:199–208

    Google Scholar 

  • Gee GW, Bauder JW (1986) Particle-size analysis, hydrometer method. In a Klute et al. (eds.) methods of soil analysis, part I.3rd ed., am Soc Agron, Madison

  • Geypens M, Vanongeval L, Vogels N, Meykens J (1999) Spatial variability of agricultural soil fertility parameters in a gleyic podzol of Belgium. Precis Agric 1:319–326

    Google Scholar 

  • Gomez JA, Vanderlinden K, Nearing MA (2005) Spatial variability of surface roughness and hydraulic conductivity after disk tillage: implications for runoff variability. J Hydrol 311:143–156

    Google Scholar 

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

  • Goovaerts P (1998) Geostatistical tools for characterizing the spatial variability of microbiological and physico-chemical soil properties. Biol Fertil Soils 27:315–334

    Google Scholar 

  • Goovaerts P (1999) Geostatistics in soil science: state of the art and perspectives. Geoderma 89:1–45

    Google Scholar 

  • Goovaerts P, AvRuskin G, Meliker J, Slotnick M, Jacquez G, Nriagu J (2005) Geostatistical modeling of the spatial variability of arsenic in groundwater of Southeast Michigan. Water Resour Res 41:1–19

    Google Scholar 

  • Gotway CA, Ferguson RB, Hergert GW, Peterson TA (1996) Comparison of kriging and inverse-distance methods for mapping soil parameters. Soil Sci Soc Am J 60:1237–1247

    Google Scholar 

  • Goulard M, Voltz M (1992) Linear coregionalization model: tools for estimation and choice of cross-variogram matrix. Math Geol 24(3):269–286

    Google Scholar 

  • Guo Y, Amundson R, Gong P, Yu Q (2006) Quantity and spatial variability of soil carbon in the conterminous United States. Soil Sci Soc Am J 70(2):590–600

    Google Scholar 

  • Haan CT (2002) Statistical methods in hydrology. The Iowa State University Press

  • Hirzel A, Guisan A (2002) Which is the optimal sampling strategy for habitat suitability modelling. Ecol Model 157:331–341

    Google Scholar 

  • Huang X, Skidmore EL, Tibke G (2001) Spatial variability of soil properties along a transect of CRP and continuously cropped land. Sustaining the Global Farm: 24–29

  • 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

    Google Scholar 

  • Isaaks EH, Srivastava RM (1989) Applied Geostatistics: Oxford University press, New York

  • Jawad IT, Taha MR, Majeed ZH, Khan TA (2014) Soil stabilization using lime: advantages, disadvantages and proposing a potential alternative. Res J Appl Sci Eng Technol 8:510–520

    Google Scholar 

  • Journel AG, Huijbregts CJ (1978) Mining geostatistics. Academic press, London

    Google Scholar 

  • Karlen DL, Wollenhaupt NC, Erbach DC, Berry EC, Swan JB, Eash NS, Jordahl JL (1994) Long-term tillage effects on soil quality. Soil Tillage Res 32:313–327

    Google Scholar 

  • Kerry R, Oliver MA (2004) Average variograms to guide soil sampling. Intl J Appl Earth Obs 5(4):307–325

    Google Scholar 

  • Kravchenko A, Bullock DG (1999) A comparative study of interpolation methods for mapping soil properties. Agron J 91:393–400

    Google Scholar 

  • Lal R (1990) Soil erosion and land degradation: the global risks. In advances in soil science. Springer, New York

    Google Scholar 

  • Lal R (2015) Restoring soil quality to mitigate soil degradation. Sustainability 7:5875–5895

    Google Scholar 

  • Laslett GM, McBratney AB, Pahl P, Hutchinson MF (1987) Comparison of several spatial prediction methods for soil pH. Eur J Soil Sci 38:325–341

    Google Scholar 

  • Lehmann J, Schroth G (2003) Nutrient leaching. Trees, crops, and soil fertility: concepts and research methods. Wallingford, UK: CAB international: 151-166

  • Li J, Okin GS, Alvarez L, Epstein H (2008) Effects of wind erosion on the spatial heterogeneity of soil nutrients in two desert grassland communities. Biogeochemistry 88:73–88

    Google Scholar 

  • Ma Y, Minasny B, Wu C (2017) Mapping key soil properties to support agricultural production in eastern China. Geoderma Reg 10:144–153

    Google Scholar 

  • MacCarthy DS, Agyare WA, Vlek PLG, Adiku SGK (2013) Spatial variability of some soil chemical and physical properties of an agricultural landscape. West Afr J Appl Ecol 21(2013):47–61

    Google Scholar 

  • McBratney AB, Webster R (1983) How many observations are needed for regional estimation of soil properties? Soil Sci 135:177–183

    Google Scholar 

  • McGrath D, Zhang C, Carton OT (2004) Geostatistical analyses and hazard assessment on soil lead in Silvermines area, Ireland. Environ Pollut 127:239–248

    Google Scholar 

  • McGrath D, Zhang C (2003) Spatial distribution of soil organic carbon concentrations in grassland of Ireland. Appl Geochem 18(10):1629–1639

    Google Scholar 

  • Mirakzehi K, Pahlavan-Rad MR, Shahriari A, Bameri A (2018) Digital soil mapping of deltaic soils: a case of study from Hirmand (Helmand) river delta. Geoderma 313:233–240

    Google Scholar 

  • Morgan RPC (2005) Soil erosion and conservation. Blackwell Science Ltd., Oxford, p 304

    Google Scholar 

  • Mulla DJ (1991) Using geostatistics and GIS to manage spatial patterns in soil fertility. In: Kranzler G (ed) Automated Agriculture for the 21st Century. Am. Soc. Ag. Eng, St. Joseph, pp 336–345

    Google Scholar 

  • Nichols JD (1984) Relation of organic carbon to soil properties and climate in the southern Great Plains 1. Soil Sci Soc Am J 48:1382–1384

    Google Scholar 

  • Norušis MJ (2002) SPSS 11.0 guide to data analysis. Prentice Hall, Upper Saddle River

    Google Scholar 

  • USDA-NRCS (1996) Soil survey laboratory methods manual. Soil survey investigations report 42, Version 3.0. US Department of Agriculture, Natural Resources Conservation Service, Washington, DC

  • Olsen SR, Cole CV, Watanabe FS, Dean LA (1954) Estimation of available phosphorous in soil by extraction with sodium bicarbonate. USDA. Cire. 939. U. S. Gov. print. Office, Washington D.C.

  • Ontl TA, Schulte LA (2012) Soil carbon storage. Nat Educ Knowledge 3:35

    Google Scholar 

  • Reeves DW (1997) The role of soil organic matter in maintaining soil quality in continuous cropping systems. Soil Tillage Res 43:131–167

    Google Scholar 

  • Rhoades JD (1996) Salinity: electrical conductivity and total dissolved solids. Methods of soil analysis part 3-chemical methods, am Soc Agron, Medison

  • Robertson GP (2008) GS+: Geostatistics for the environmental sciences. Gamma Design Software, Plainwell

    Google Scholar 

  • Robinson TP, Metternicht G (2006) Testing the performance of spatial interpolation techniques for mapping soil properties. Comput Electron Agric 50:97–108

    Google Scholar 

  • Rosemary F, Indraratne SP, Weerasooriya R, Mishra U (2017) Exploring the spatial variability of soil properties in an Alfisol soil catena. Catena 150:53–61

    Google Scholar 

  • Safadoust A, Doaei N, Mahboubi AA, Mosaddeghi MR, Gharabaghi B, Voroney P, Ahrens B (2016a) Long-term cultivation and landscape position effects on aggregate size and organic carbon fractionation on surface soil properties in semi-arid region of Iran. Arid Land Res Manag 30:345–361

    Google Scholar 

  • Safadoust A, Amiri Khaboushan E, Mahboubi AA, Gharabaghi B, Mosaddeghi MR, Ahrens B, Hassanpour Y (2016b) Comparison of three models describing bromide transport affected by different soil structure types. Arch Agron Soil Sci 62:674–687

    Google Scholar 

  • Sakin E (2012a) Organic carbon organic matter and bulk density relationships in arid-semi arid soils in Southeast Anatolia region. Afr J Biotechnol 11:1373–1377

    Google Scholar 

  • Sakin E (2012b) Relationships between of carbon, nitrogen stocks and texture of the Harran plain soils in southeastern Turkey. Bulgarian J Agri Sci 18:626–634

    Google Scholar 

  • Salem BB (1989) Arid zone forestry: a guide for field technicians (no. 20). Food and agriculture organization (FAO)

  • Schepers JS, Schlemmer MR, Ferguson RB (2000) Site-specific considerations for managing phosphorus. J Environ Qual 29:125–130

    Google Scholar 

  • Schollenberger CJ, Simon RH (1945) Determination of exchange capacity and exchangeable bases in soil-ammonium acetate method. Soil Sci 59:13–24

    Google Scholar 

  • Sharma P, Singh G, Singh RP (2011) Conservation tillage, optimal water and organic nutrient supply enhance soil microbial activities during wheat (Triticum aestivum L.) cultivation. Braz J Microbiol 42:531–542

    Google Scholar 

  • Shukla MK, Slater BK, Lal R, Cepuder P (2004) Spatial variability of soil properties and potential management classification of a chernozemic field in lower Austria. Soil Sci 169(12):852–860

    Google Scholar 

  • Soil Survey Division Staff (2017) Soil survey manual. 4th In USDA Handbook 18, USDA-Nat. Resour. Conserv. Serv., Ed Ditzler C, Scheffe K, Monger HC, Government Printing Office, Washington DC

  • Stang C, Gharabaghi B, Rudra R, Golmohammadi G, Mahboubi AA, Ahmed SI (2016) Conservation management practices: success story of the hog creek and sturgeon river watersheds, Ontario, Canada. J Soil and Water Conserv 71:237–248

    Google Scholar 

  • Sun B, Zhou S, Zhao Q (2003) Evaluation of spatial and temporal changes of soil quality based on geostatistical analysis in the hill region of subtropical China. Geoderma 115:85–99

    Google Scholar 

  • Tabor JA, Warrick AW, Myers DE, Pennington DA (1985) Spatial variability of nitrate in irrigated cotton: II. soil nitrate and correlated variables 1. Soil Sci Soc Am J 49(2):390–394

    Google Scholar 

  • Tanner S, Katra I, Haim A, Zaady E (2016) Short-term soil loss by eolian erosion in response to different rain-fed agricultural practices. Soil Tillage Res 155:149–156

    Google Scholar 

  • Thayer WC, Griffith DA, Goodrum PE, Diamond GL, Hassett JM (2003) Application of geostatistics to risk assessment. Risk Anal 23:945–960

    Google Scholar 

  • Thomas GW (1996) Soil pH and soil activity. In: Sparks DL et al (eds) Method of soil analysis, part 3. Am Soc Agron, Medison

    Google Scholar 

  • Trangmar BB, Yost RS, Uehara G (1985) Application of geostatistics to spatial studies of soil properties. Adv Agron 38:45–94

    Google Scholar 

  • US Salinity Laboratory Staff (1954) Diagnosis and improvement of saline and alkali soils. USDA Handbook 60. US Government Printing Office, Washington D C

    Google Scholar 

  • Vachaud G, Chen T (2002) Sensitivity of computed values of water balance and nitrate leaching to within soil class variability of transport parameters. J Hydrol 264:87–100

    Google Scholar 

  • Van Alphen JG, de los Ríos Romero F (1971) Gypsiferous soils: notes on their characteristics and management (no. 12). ILRI

  • Vasu D, Singh SK, Sahu N, Tiwary P, Chandran P, Duraisami VP, Kalaiselvi B (2017) Assessment of spatial variability of soil properties using geospatial techniques for farm level nutrient management. Soil Tillage Res 169:25–34

    Google Scholar 

  • Walter C, McBratney AB, Douaoui A, Minasny B (2001) Spatial prediction of topsoil salinity in the Chelif Valley, Algeria, using local ordinary kriging with local variograms versus whole-area variogram. Soil Res 39(2):259–272

    Google Scholar 

  • Wang G, Gertner G, Howard H, Anderson A (2008) Optimal spatial resolution for collection of ground data and multi-sensor image mapping of a soil erosion cover factor. J Environ Manag 88:1088–1098

    Google Scholar 

  • Warrick AW (1998) Spatial variability. In: Hillel D (ed) Environmental soil physics. Academic Press, San Diego

    Google Scholar 

  • Wollenhaupt NC, Wolkowski RP, Clayton MK (1994) Mapping soil test phosphorus and potassium for variable-rate fertilizer application. J Prod Agri 7:441–448

    Google Scholar 

  • Yan H, Wang S, Wang C, Zhang G, Patel N (2005) Losses of soil organic carbon under wind erosion in China. Glob Chang Biol 11:828–840

    Google Scholar 

  • Yu J, Li Y, Han G, Zhou D, Fu Y, Guan B, Wang G, Ning K, Wu H, Wang J (2014) The spatial distribution characteristics of soil salinity in coastal zone of the Yellow River Delta. Environ Earth Sci 72:589–599

    Google Scholar 

  • Zhang C (2006) Using multivariate analyses and GIS to identify pollutants and their spatial patterns in urban soils in Galway, Ireland. Environ Pollut 142(3):501–511

    Google Scholar 

  • Zhang WT, Hong-Qi WU, Hai-Bin GU, Guang-Long FENG, Ze WANG, Sheng JD (2014) Variability of soil salinity at multiple spatio-temporal scales and the related driving factors in the oasis areas of Xinjiang, China. Pedosphere 24:753–762

    Google Scholar 

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Delbari, M., Afrasiab, P., Gharabaghi, B. et al. Spatial variability analysis and mapping of soil physical and chemical attributes in a salt-affected soil. Arab J Geosci 12, 68 (2019). https://doi.org/10.1007/s12517-018-4207-x

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