Evaluation of spatial variability of some soil chemical and physical properties in Foumanat Plain paddies using geostatistic methods

Document Type : Research Paper

Authors

1 Scientific Member, Department of Agronomy Sari Agricultural Sciences and Natural Resources University

2 Sari Agricultural Sciences and Natural Resources University

3 Guilan University

4 Tehran University

Abstract

Background and objectives: Since the soil is considered as the most important source of nutrients, understanding the spatial variation and geographical distribution patterns of nutrients is crucial for the proper management and the right application of fertilizers. Nowadays, soil management based on spatial variability of soil properties in crop growth is necessary (Morales et al, 2011; Bijanzadeh et al, 2014). However, accurate estimates of soil properties in all areas are not time and cost effective. Therefore, interpolation is a suitable solution to estimate not sampled areas. There are different techniques for predicting the soil characteristics in not sampled areas such as geostatistics (Mohammadi, 2007). Therefore, this study aimed to evaluate the physical and chemical properties of some soil paddy fields in Foumanat, Guilan province using the geostatistics technique.
Materials and methods: The present study was performed in Foumanat plain during two cropping seasons of 2013 and 2014. Soil samples were taken from 45 fields and geographic coordinates were recorded. Soil properties including electrical conductivity, cation exchange capacity, organic matter, pH, clay, silt, sand were measured. Interpolating of variables were investigated with kriging (KG) and inverse distance weighting (IDW) methods with power one to five. The best interpolation method was selected using evaluating statistics such as Mean Absolute Error (MAE), Mean Bias Error (MBE) and Root Mean Square Error (RMSE).
Results: Results indicated that electrical conductivity, cation exchange capacity, pH and silt fitted by an exponential model while two parameters of organic matter and sand along with clay were fitted by the spherical and Gaussian models, respectively. High determination coefficients for sand, clay and electrical conductivity were 0.95, 0.83 and 0.80, respectively. According to the calculated variograms, electrical conductivity and sand exhibited a medium spatially structured variability whereas highly structured variability was observed for soil CEC, organic matter, pH, clay and silt. Least nugget effect among the studied variables was allocated to CEC, organic matter and sand. The results showed that the IDW method provided more accurate and less error for CEC, organic matter, pH and silt in the study area as compared to the kriging method. Moreover, there were not differences between the two methods of IDW and kriging in terms of electrical conductivity, clay and sand parameters.
Conclusion: Overall, the fertility of paddy fields was statistically different. The most coefficient of variation (CV) from 15 to 24 percent, the average variation were found in electrical conductivity, sand and clay while the amount of CV in the cation exchange capacity, organic matter, pH and silt were recorded lower than 15% (low diversity). In the studied characteristics, two types of medium and strong structures were observed. In general, the results of this study can be used to estimate the fertility and physical and chemical characteristics of rice farms. Therefore, these results could help to adopt crop improvement methods including crop choice and site-specific fertilizer recommendations to optimum management of inputs and sustainable production.

Keywords

References

Ayoubi, Sh., Mohammadzamani, S. and Khormali, F. 2007. Prediction total N by organic matter content using some geostatistic approaches in part of farm land of Sorkhankalateh, Golestan Province. Journal of agricultural sciences and natural resources, 14(4): 78-87 (In Persian with English Summary).
Bhatti, A. U., Mulla, D. J. and Frazier, B. E. 1991. Estimation of soil properties and wheat yields on complex eroded hills using geostatistics and thematic mapper images. Remote Sensing of Environment, 37(3): 181-191.
Bijanzadeh, E., Mokarram, M. and Naderi, R. 2014. Applying Spatial Geostatistical Analysis Models for Evaluating Variability of Soil Properties in Eastern Shiraz, Iran. Iran Agricultural Research, 33(2): 35-46.
Brye, K. R., Staton, N. A., Mozaffari, M., Savin, M. C., Norman, R. J. and Miller, D. M. 2004. Short- term effects of land leveling on soil chemical properties and their relationships with microbial biomass. Soil Science Society of America Journal, 68: 924-934.
Cahan, M.D., Hummel, J.W. and Brouer, B. H. 1994. Spatial analysis of soil fertility for site-specific crop management. Soil Science Society of America Journal, 39: 247-250.
Cambardella, C. A., Moorman, T. B., Parkin, T. B., Karlen, D. L., Novak, J. M., Turco, R. F., and Konopka, A. E. 1994. Field-scale variability of soil properties in central Iowa soils. Soil Science Society of America Journal, 58: 1501-1511.
Cetin, M. and Kirda, C. 2003. Spatial and temporal changes of soil salinity in a cotton field irrigated with low-quality water. Journal of Hydrology, 272: 238–249.
Chapman, H. D. 1965. Cation-exchange capacity. Methods of soil analysis. Part 2. Chemical and microbiological properties (methods of soil analysis). Monograph, 9(2): 891-901.
Dahiya, I.S., Richter, J. and Malik, R.S. 1984. Soil spatial variability: A review. International Journal of Tropical Agricultural, 11(1): 1-102.
Davatgar, N., Zare, A., Shakouri Katigari, M., Rezaei, L., Kavoosi, M., Sheikh Eslam, h. and Ajili Lahiji, A. 2015. Fertility Status of Paddy Soils in Guilan Province. Land Management Journal, 3(1): 1-13 (In Persian).
Foroughifar, H., Jafarzadah, A. A., Torabi Gelsefidi, H., Aliasgharzadah, N., Toomanian, N. and Davatgar, N. 2011. Spatial Variations of Surface Soil Physical and Chemical Properties on Different Landforms of Tabriz Plain. Water and soil science, 21(3): 1-21 (In Persian).
Gee G. W. and Bauder J. W. 1986. Particle-size analysis. In: Klute, A. (Ed), Methods of Soil Analysis. Part 1. 2nd ed. Agron. Monogr. 9. ASA. Madison. WI. 636 pp.
Hamidiyanpour, M., Saligeh, M. and Falah Ghlhari, Gh. A. 2013. Applaying Types of Interpolation Methods for Spatial Analysis and Monitoring of SPI Drought Case study: Khorasan Razavi. Geography and development Iranian journal , 11 (30): 57-70 (In Persian).
Hossein Alizadeh, M., Ayoubi, S. A. and Shataee, Sh. 2006. Comparison of various interpolation methods on evaluation some surface soil properties (case study: mehr watershed of sabzevar). Journal of Agricultural Sciences and Natural Resources, 13(5): 152-162 (In Persian with English Summary).
Jafari, M., Asgari, H. M., Moazami, M., Tahmoures, M. and Beniaz, M. 2008. Investigaation of spatial distribution of soil properties by use of geostatistical methods. Pajouhesh-Va-Sazandegi, 21(3): 177-185 (In Persian).
Jafarnia, Sh. and Akbarinia, M. 2014. Investigation of spatial distribution of soil and water properties by use of geostatistical in Mangrove forest of Qeshm Island. Iranian Journal of Forest and Poplar Research , 22(4): 673-686 (In Persian).
Jiang, P., and Thelen, K. D. 2004. Effect of soil and topographic properties on crop yield in a north-central corn–soybean cropping system. Agronomy journal, 96(1): 252-258.
Khoramizadeh, F., Davatgar, N., Tehrani, M. M., Ghasemi Dehkordi, V. R. and Asaadi Oskuie, E. 2015. Evaluation of spatial variability of available iron and its affecting factors in paddy soils (Case study: Central paddy fields of Guilan). Journal of Soil Management and Sustainable, 4(4): 255-274 (In Persian with English Summary).
Liu, N., Bond, G.M., Abel, A., McPherson, B.J. and Stringer, J. 2006. Biometric sequestration of CO2 in carbonate forms: Role of produced waters and other brines. Fuel Processing Technology, 86:1615-1625.
Liu, Y., Zhang, J. L. B., and Bi, J. 2013. Spatial multi-scale variability of soil nutrients in relation to environmental factors in a typical agricultural region, Eastern China. Science of the Total Environment, 450-451: 108-119.
López-Granados, F., Jurado-Expósito, M., Atenciano, S., García-Ferrer, A., Sánchez de la Orden, M. and García-Torres, L. 2002. Spatial variability of agricultural soil parameters in southern Spain. Plant and Soil, 246: 97–105.
McLean EO, 1982. Soil pH and lime requirement. Pp. 199-224. In: Page AL, Miller, RH and Keeny, DR(Eds): Methods of soil analysis. Part 2. Chemical and microbiological properties. Second edition. America Society of Agronomy and Soil Science Society of America, Madison, WI.
Mohammadi, J. 2006. Pedometrics (spatial statistics). Pelk Publication. Tehran, 453p (In Persian).
Mohammadi, J. 2007. Reviewing the basics geostatistic and its application in soil. Science of Soil and Water, 15 (1): 99-121.
Mohammad Zamani, S., Ayoubi, Sh., Khormali, F. 2007. Spatial Variability of Wheat Yield and Soil Properties in a Selected Agricultural Land of Sorkhankalateh. Journal of Water and Soil Science, 11 (40):79-92 (In Persian).
Morales, L. A., Vázquez, E. V. and Paz-Ferreiro, J. 2011. Spatial and temporal variability of Mehlich-1 extractable Fe, Mn and Zn over a rice field as a function of lime amendment. Stochastic environmental research and risk assessment , 25(8): 1039-1048.
Nayanaka, V. G. D., Vitharana, W. A. U. and Mapa, R. B. 2010. Geostatistical Analysis of Soil Properties to Support Spatial Sampling in a Paddy Growing Alfisol. Tropical Agricultural Research, 22(1): 34-44.
Owliaie, H.R., Keshavarzi, M.and Adhami, E. 2015. Comparison between physicochemical properties and clay mineralogy of paddy soils of Noorabad (Fars Province) and adjacent virgin lands. Journal of Soil Management and Sustainable, 4(4): 105-125 (In Persian with English Summary).
Page, A.L., Miller, R.H., and Keeeney, D.R. 1982. Methods of soil analysis. Part2-Chemical and Microbiological methods. Seconds edition, Soil Science Society of America, Inc. Publisher Madison, Wisconsin, USA.
Paz-Gonzalez, A., Viera, S.R., and Toboada castro, M.T. 2000. The effect of cultivation on the spatial variability of selected properties of an umbric horizon. Geoderma, 97: 273-292.
Pirysahragard, H., and Piry, J. 2016. Analysis of spatial structure of some soil properties using geostatistical methods (Case study: west rangelands of Taftan-Khash). Rangeland, 10: 224-236.
Ponnamperuma, F.N., 1978. Electrochemical changes in submerged soils and the growth of rice. Soils and rice, 191: 421-441.
Rezaei, M., Davatgar, N., Tajdari, K. and Abolpour, B. 2010. Investigation the Spatial Variability of Some Important Groundwater Quality Factors in Guilan, Iran. Journal of Water and Soil, 24(5): 932-941 (In Persian).
Rezazadehshamkhal, S., Gholamalizadeh Ahangar, A., Gazmeh, S., Froghifar, H. and Bameri, A. 2016. Evaluation of Different Interpolation Methods in Spatial Estimation of Soil Properties in Sistan Plain. Water and soil science, 26 (2): 151-162 (In Persian with English Summary).
Rizwan, M., Siddique, M. T., Ahmed, H., Iqbal, M. and Ziad, T. 2016. Spatial variability of selected physico-chemical properties and macronutrients in the shale and sandstone derived soils. Soil & Environment,Soil Environ. 35(1): 12-21.
Roger, A., Libohova, Z., Rossier, N., Joost, S., Maltas, A., Frossard, E., and Sinaj, S. 2014. Spatial variability of soil phosphorus in the Fribourg canton, Switzerland. Geoderma, 217-218: 26-36.
Sarmadian, F. and Taghi zadeh Mehrjerdi, R. 2010. A Comparison of Interpolation Methods for Preparing Soil Quality Maps: Case study: (Agricultural Faculty Experimental Field). Iranian journal of soil and water research, 40(2): 157-165 (In Persian).
Sendecor, G.W., and Cochran, W.G. 1980. Statistical methods. 8th ed. Lowa State Univ. Lowa, USA. 503p.
Simmonds, M. B., Plant, R. E., Pena-Barragan J. M., van Kessel, C., Hill, J. and Linquist, B. A. 2013. Underlying causes of yield spatial variability and potential for precision management in rice systems. Precision Agriculture, 14(5): 512–540.
Sun, B., Zhou, Sh., and 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.
Tewolde, M. G., Beza, T. A., Costa, A. C. and Painho, M. 2010. Comparison of different interpolation techniques to map temperature in the southern region of Eritrea. Paper presented at the 13th AGILE International Conference on Geographic Information Science. Guimarães, Portugal,1-5.
Torabi golsefidi, H., Davatgar, N. and Ghasemi, Sh. 2016. Spatial Variability and Mapping of Some Physico-Chemical Properties in Surface Soils and Influence of Land Use Management on Them in Agricultural Lands South of Tehran. Iranian journal of soil research, 30(2): 215-226 (In Persian).
Trangmar, B. B., Yost, R. S. and Uehara, G. 1986. Application of geostatistics to spatial studies of soil properties. Advances in agronomy, 38: 45-94.
Tsegaye, T. and Hill, R. L. 1998. Intensive tillage effects on spatial variability of soil test, plant growth, and nutrient uptake measurements. Soil Science, 163(2): 155-165.
Van Meirvenne, M., 1991, Characterization of soil spatial variation using geostatistics. Ph.D. thesis, university of Gent, Belgium, academic press, 168 pp.
Vieira, S. R., Hatfield, J. L., Nielsen, D. R. and Biggar, J. W. 1983. Geostatistical theory and application to variability of some agronomical properties: University of California, Division of Agricultural Sciences. 75 p.
Wackernagel, H. 2013. Multivariate geostatistics: an introduction with applications (3rd ed.). Verlag Berlin Heidelberg: Springer Science & Business Media. 388 p.
Webster, R. and Oliver, M. A. 2007. Geostatistics for environmental scientists (Second Edition ed.). The Atrium, Southern Gate, Chichester, England: John Wiley & Sons. 330 p.
Xing, Z. Y., Yue, S. Y., Xu, Z. D., Kai, M. and Herbert, S. J. 2007. Spatial variability of nutrient properties in black soil of northeast China. Pedosphere, 17(1): 19-29.
Xiong, W., I. Holman, D. Conway, E. Lin and Y. Li. 2008. A crop model cross calibration for use in region climate impacts studies. Ecological Modelling, 213: 365-380.
Yanai, J., Lee, C. K., Umeda, M. and Kosaki, T. 2000. Spatial variability of soil chemical properties in a paddy field. Soil Science and Plant Nutrition, 46(2): 473-482.
Yasrebi, J., Saffari, M., Fathi, H., Karimian, N., Moazallahi, M. and Gazni, R. 2009. Evaluation and comparison of ordinary kriging and inverse distance weighting methods for prediction of spatial variability of some soil chemical parameters. Research Journal of Biological Sciences, 4(1), 93-102.
Yemefack, M., Rossiter, D. G. and yomgang, R. N. 2005. Multi-scale characterization of soil variability within an agricultural landscape mosaic system in southern Cameroon. Geoderma, 125:117-143.
Zareian, F., Mahmoudi, J. and Javadi, M.R. 2015. Predicating the Spatial Variability of Some Soil Properties by Using Geostatistic Methods in Darreh Viseh, Karaj. Iranian journal of soil research, 28(3): 511-520 (In Persian).
Zhao, Y., Xu, X., Darilek, J. L., Huang, B., Sun, W. and Shi, X. 2009. Spatial variability assessment of soil nutrients in an intense agricultural area, a case study of Rugao County in Yangtze River Delta Region, China. Environmental Geology, 57(5): 1089–1102.
Applied Field Crops Research
Volume 31, Issue 4 - Serial Number 121
papers
January 2019
Pages 50-71

Files

Share

How to cite

Statistics