Spatial and fractal characterization of soil properties across soil depth in an agricultural field, Northeast Iran

Year 2018, Volume: 7 Issue: 2, 93 - 102, 01.04.2018

Ali Keshavarzi Henry Oppong Tuffour Ali Bagherzadeh Duraisamy Vasu

https://doi.org/10.18393/ejss.339032

Cited By: 7

Abstract

The present study was conducted to explore the
fractal behavior and establish fractal dimensions of soil physical and chemical
properties (i.e., sand, silt, and clay contents, bulk density, degree of
moisture saturation, pH, organic carbon content, total nitrogen, available
phosphorus, and available potassium) to characterize their spatial patterns.
Soil samples were collected from 0-30 (surface) and 30-60 cm (subsurface)
depths from an agricultural field, Mashhad Plain, Northeast Iran. Descriptive statistics and fractal analysis
were used to describe the extent and form of variability. Spatial patterns of
the soil properties were estimated using GS+ 10.0 software.  Soil properties showed low to high variations
in both surface and subsurface layers across the field, where bulk density and
pH being the most reliable soil physical and chemical properties in the study
area. The variability was high (CV > 35%) for total N, available P,
available K and organic carbon in both surface and subsurface soils and it could
be attributed to management practices and micro-topographical variations as
these are the dynamic properties of soil. The
fractal dimension (D) values of soil physical properties ranged from 1.398 to
1.913 at the surface, and from 1.874 to 1.934 at the subsurface indicating both
short and long range variations. The D values for the chemical properties
ranged from 1.331 to 1.975, and 1.148 to 1.990 in the surface and subsurface
layers, respectively. The results showed that fractal analysis could be employed
to effectively describe the structure of soil heterogeneity in spatial scale
for effective agricultural and environmental management of soil.

Keywords

Fractal dimension, Hurst exponent, Spatial variability, Self-similarity, Semivariogram

References

• Beckett, P.H.T., Webster. R., 1971. Soil variability: A review. Soils and Fertilizers 34: 1-15.
• Bengough, A.G., Castrignano, A., Pagès, L., Van Noordwijk, L., 2000. Sampling strategies, scaling, and statistics. In: Root Methods Handbook. Smit, A.L., Benough, A.G., Engels, C., Van Noordwijk, M., Pellerin, S., Van de Gejin, S.C., (Eds). Berlin, Heidelberg, New York, USA. pp.147-174.
• Blake, G.R., Hartge, K.H., 1986. Bulk density. In: Methods of Soil Analysis Part 1 Physical and Mineralogical Methods. 2nd Edition, Klute, A., (Ed). American Society of Agronomy, Soil Science Society of America. Madison, Wisconsin, USA. pp. 363-375.
• Bogunovic, I., Mesic, M., Zgorelec, Z., Jurisic, A., Bilandzija, D. 2014. Spatial variation of soil nutrients on sandy-loamy soil. Soil and Tillage Research 144: 174-183.
• Burrough, P.A., 1983a. Multiscale sources of spatial variation in soil. I. The application of fractal concepts to nested levels of soil variation. European Journal of Soil Science 34(3): 577-597.
• Burrough, P.A., 1983b, Multiscale sources of spatial variation in soil. II. A non-Brownian fractal model and its application in soil survey. European Journal of Soil Science 34(3): 599-620.
• Camacho-Tamayo, J.H., Luengas, C.A., Leiva, F.R., 2008. Effect of agricultural intervention on spatial variability of some soils chemical properties in the eastern plains of Colombia. Chilean Journal of Agricultural Research 68(1): 42-55.
• Cambardella, C.A., Moorman, T.B., Parkin, T.B., Karlen, D.L., Novak, J.M., Turco, R.F., Konopka, A. E., 1994. Field-scale variability of soil properties in central Iowa soils. Soil Science Society of America Journal 58(5): 1501-1511.
• Florinsky, I.V., 2012. Influence of topography on soil properties. In: Digital terrain analysis in soil science and geology. Florinsky, I.V. (Ed.), Academic Press, San Diego, USA. pp. 145-149.
• 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 and Tillage Research 106(2): 185–193.
• Gardner, W.H., 1986. Water content. In: Methods of Soil Analysis Part 1 Physical and Mineralogical Methods. 2nd Edition, Klute, A., (Ed). American Society of Agronomy, Soil Science Society of America. Madison, Wisconsin, USA. pp. 493-544.
• Gee, G.W., Bauder, J.W., 1986. Particle size analysis. In: Methods of Soil Analysis Part 1 Physical and Mineralogical Methods. 2nd Edition, Klute, A., (Ed). American Society of Agronomy, Soil Science Society of America. Madison, Wisconsin, USA. pp. 383-411.
• Gessler, P.E., Chadwick, O.A., Chamran, F., Althouse, F., Holmes, K., 2000. Modeling soil-landscape and ecosystem properties using terrain attributes. Soil Science Society of America Journal 64(6): 2046-2056.
• Goovaerts, P., 1998. Geostatistical tools for characterizing the spatial variability of microbiological and physico-chemical soil properties. Biology and Fertility of Soils 27(4): 315-334.
• Göttlein, A., Stanjek, H., 1996. Micro-scale variation of solid-phase properties and soil solution chemistry in a forest podzol and its relation to soil horizons. European Journal of Soil Science 47(4): 627-636.
• Gupta, N., Rudra, R., Parkin, G., Whiteley, H.R. 2003. Fractal behaviour of soil physical and hydraulic properties. MODSIM03/Volume_02/A09/05. International Congress on Modelling and Simulation Proceedings. 14-17 July 2003, Townsville, Australia.
• Huang, X., Skidmore, E. L., Tibke, G., 1999. Spatial variability of soil properties along a transect CRP and Continuously Cropped Land. In: Sustaining the Global Farm. Stott, D.E., Mohtar, R.H., Steinhardt, G. C. (Eds.). Selected papers from the 10th International Soil Conservation Organization (2001). Purdue University and USDA-ARS National Soil Erosion Research Laboratory. pp.641-647.
• Keshavarzi, A., Omran, E.E., Bateni, S.M., Pradhan, B., Vasu, D., Bagherzadeh, A., 2016. Modeling of available soil phosphorus (ASP) using multi-objective group method of data handling. Modeling earth Systems and Environment 2:157.
• Kooch, Y., Theodose, T.A., Samonil, P., 2014. Role of deforestation on spatial variability of soil nutrients in a Hyrcanian Forest. ECOPERSIA 2(4): 779-803.
• Lark, R.M., 2000. Estimating variograms of soil properties by the method-of-moments and maximum likelihood. European Journal of Soil Science 51(4): 717–728.
• Law, M.C., Balasundram, S.K., Husni, M.H.A., Ahmed, O.H., Harun, M.H., 2009. Spatial variability of soil organic carbon in palm oil. International Journal of Soil Science 4(4): 93-103.
• Li, T., He, B., Zhang, Y., Tian, J., He, X., Yao, Y., Chen, X., 2016. Fractal analysis of soil physical and chemical properties in the five-tree cropping systems in the southwest China. Agroforestry Systems 90(3): 457-468.
• Liao, K., Lai, X., Zhou, Z., Zhu, Q., 2017. Applying fractal analysis to detect spatio-temporal variability of soil moisture content on two contrasting land use hillslopes. Catena 157: 163-172.
• Linsenmeier, A.W., Löhnertz, O., Lehnart, R., 2011. Geostatistical analysis and scaling of grapevine root distribution. South African Journal of Enology and Viticulture 32(2): 211-219.
• Mapfumo, E., Chanasky, D.S., Chaikowsky, C.L.A., 2006. Stochastic simulation of soil water status on reclaimed land in northern Alberta. Journal of Spatial Hydrology 6(1): 34-44.
• Miloš, B., Bensa, A., 2017. Fractal approach in characterization of spatial pattern of soil properties. Eurasian Journal of Soil Science 6(1): 20-27.
• Mohammadi, M., Shabanpour, M., Mohammadi, M.H., Davatgar, N., 2017. Characterizing spatial variability of soil textural fractions and fractal parameters derived from particle size distributions. Pedosphere [In Press].
• Nelson, D.W., Sommers, L.P., 1986. Total carbon, organic carbon and organic matter. In: Methods of Soil Analysis Part 2 Chemical and Microbiological Properties 2nd Edition, Page, A.L et al. (Eds). American Society of Agronomy, Soil Science Society of America. Madison, Wisconsin, USA. pp. 539-579.
• Oleschko, K., Korvin, G., Muñoz, A., Velazquez, J., Miranda, M. E., Carreon, D., Flores, L., Martínez, M., Velásquez-Valle, M., Brambila, F., Parrot, J.-F., Ronquillo, G., 2008. Mapping soil fractal dimension in agricultural fields with GPR. Nonlinear Processes Geophysics 15: 711-725.
• Pilesjő, P., Thylen, L., Persson, A. 2005. Topographical data for delineation of agricultural management. In: Precision agriculture 005 Stafford, J.V. (Ed.), Wageningen Academic Publishers, Uppsala, Sweden. pp. 819–826.
• Santra, P., Chopra, U.K., Chakraborty, D., 2008. Spatial variability of soil properties and its application in predicting surface map of hydraulic parameters in an agricultural farm. Current Science 95(7): 937-945.
• Sparks, D.L., Page, A.L., Helmke, P.A., Leoppert, R.H., 1996. Methods of Soil Analysis Part 3—Chemical Methods. SSSA Book Series 5.3. Soil Science Society of America, American Society of Agronomy, Madison, Wisconsin, USA.
• Sugihara, G., May, R.M., 1990. Applications of fractals in ecology. Trends in Ecological Evolution 5(3): 79-86.
• Thomas, G.W., 1996. Soil pH and soil acidity. In: Methods of Soil Analysis Part 2 Chemical and Microbiological Properties 2nd Edition, Page, A.L., et al. (Eds). American Society of Agronomy, Soil Science Society of America, Madison, Wisconsin, USA. pp. 475–490.
• Tuffour, H.O., 2015. Fractal scaling of the hydraulic and hydrologic properties of an Acrisol. Applied Research Journal 1(5): 320-326.
• Tuffour, H.O., Abubakari, A., Bashagaluke, J.B., Djagbletey, E.D., 2016. Mapping spatial variability of soil physical properties for site-specific management. International Research Journal of Engineering and Technology 3(2): 149-163.
• Tuffour, H.O., Bonsu, M., Khalid, A.A., Adjei-Gyapong, T., Atakora, W.K., 2013. Evaluation of spatial variability of soil organic carbon and pH in an uprooted oil palm field. Indian Journal of Applied Agricultural Research 1(1): 69-86.
• Vasu, D., Singh, S.K., Ray, S.K., Duraisami, V.P., Tiwary, P., Chandran, P., Nimkar, A.M., Anantwar, S.G., 2016. Soil quality index as a tool to evaluate crop productivity in semi-arid Deccan plateau, India. Geoderma 282: 70-79.
• Vasu, D., Singh, S.K., Sahu, N., Tiwary, P., Chandran, P., Duraisami, V.P., Ramamurthy, V., Lalitha, M., Kalaiselvi, B., 2017b. Assessment of spatial variability of soil properties using geospatial techniques for farm level nutrient management. Soil and Tillage Research 169: 25-34.
• Vasu, D., Singh, S.K., Tiwary, P., Chandran, P., Ray, S.K., Duraisami, V.P., 2017a. Pedogenic processes and soil–landform relationships for identification of yield-limiting soil properties. Soil Research 55(3):273-284.
• Vieira, S.R., Vidal‐Vázquez, E., Miranda, J.G.V., Paz-González, A., Paz‐Ferreiro, J., 2010. Fractal analysis and graph theory applied to the spatial and temporal variability of soil water content. Geophysical Research Abstracts Vol. 12, EGU2010-4223-2, EGU General Assembly 2010, Vienna, Austria.
• Walkley, A., Black, I.A. 1934. An examination of the Degtjareff method for determining soil organic matter and a proposed modification of the chromic acid titration method. Soil Science 37(1): 29–38.
• Wang, D,, Fu, B.J., Zhao, W., Hu, H., Wang, Y., 2008. Multifractal characteristics of soil particle size distribution under different land-use types on the Loess Plateau, China. Catena 72(1): 29–36.
• Wang, Y.Q., Shao, M.A., 2011. Spatial variability of soil physical properties in a region of the loess plateau of PR China subject to wind and water erosion. Land degradation and Development 24(3): 296-304.
• Western, A.W., Zhou, S.L.,, Grayson, R.B., McMahon, T.A., Blöschl, G., Wilson, D.J., 2004. Spatial correlation of soil moisture in small catchments and its relationship to dominant spatial hydrological processes. Journal of Hydrology 286(1-4): 113-134.
• Wilding, L.P., 1985. Spatial variability: Its documentation, accommodation and implication to soil surveys. In: Soil spatial variability. Nielsen, D.R. and Bouma, J. (Eds.), Pudoc. Wageningen, The Netherlands. pp.166-194.
• Yu, J., Lv, X., Bin, M., Wu, H., Du, S., Zhou, M., Yang, Y., Han, G., 2015. Fractal features of soil particle size distribution in newly formed wetlands in the Yellow River Delta. Scientific Reports 5: 10540.