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Year 2014, Volume: 1 Issue: 2, 186 - 195, 30.09.2014
https://doi.org/10.19159/tutad.27089

Abstract

This study was conducted to examine spatial variability of soil fertility depending on the level of selected soil fertility parameters in Fener Village located on Bafra Alluvial Deltaic Plain by means of Soil Fertility Index (SFI) model using geostatistics and Geographic Information System (GIS) technique. Fifteen soil properties [available macronutrient elements (nitrogen, phosphorous, potassium, calcium, magnesium, sodium), available micronutrient elements (iron, copper, zinc, manganese), and other soil properties (texture class, organic matter, pH, electrical conductivity, CaCO3)] at the depths of 0-30 cm and 30-60 cm were evaluated using SFI model for each georeferenced point. A total of 140 grid points were obtained and soil samples collected from surface (0-30 cm) and subsurface (30-60 cm) depths of each grid centre are 131 and 124, respectively. Geostatistical method was used to generate SFI distribution maps for surface and subsurface soils of the study area. According to the results of SFI distributions for both depths, 80.18% of the study area has good (S1) and moderate fertility (S2), 19.06% has marginal fertility (S3), 0.75% has poor fertility in surface depth, while 38.83% of the study area has good (S1) and moderate fertility (S2), 41.30% marginal fertility (S3) and 19.87% has poor fertility in subsurface depth. Consequently, findings of this study showed that geostatistical modelling was useful in the determination of the spatial variability structure and spatial dependency of investigated soil properties and nutrients

References

  • Abbasi, M.K., Zafar, M., Sultan, T., 2010. Changes in soil properties and microbial indices across various management sites in the mountain environments of Azad Jammu and Kashmir. Communications in Soil Science and Plant Analysis, 41: 768-782.
  • Alexander, J., Fielding, C.R., Pocock, G.D., 1999. Floodplain Behaviour of the Burdekin River, Tropical North Queensland, Australia. In Anderson, M. G., Walling, D. E. and Bates, P. D. (eds.) Floodplain Processes. Wiley, Chichester. pp. 27-40.
  • Anonymous, 1990a. Analytical for Atomic Absorption Spectro Photometry. Connecticut, Perkin Elmer, Norwalk.
  • Anonymous, 1990b. Micronutrient, Assessment at the Country Level: An International Study. FAO Soil Bulletin by Sillanpaa, Rome.
  • Anonymous, 1992. Procedures for Collecting Soil Samples and Methods of Analysis for Soil Survey. Soil Surv Invest Rep I US Gov Print Office, Washington DC.
  • Anonymous, 1999. Soil Survey Staff, Soil Taxonomy. A Basic of Soil Classification for Making and Interpreting Soil Survey. USDA Handbook No 436, Washington DC.
  • Arshad, M.A., Martin, S., 2002. Identifying critical limits for soil quality indicators in agro-ecosystems. Agriculture Ecosystem and Environment, 88: 153- 160.
  • Boruvka, L., Vacek, O., Jehlicka, J., 2005. Principal component analysis as a tool to indicate the origin of potentially toxic elements in soils. Geoderma, 128: 289-300.
  • Boyer, J.S., 1982. Plant productivity and environment. Science, 218: 443-448.
  • Chaudhury, J., Mandal, U.K., Sharma, K.L., Ghosh, H., Mandal, B., 2005. Assessing soil quality under long- term rice-based cropping system. Communications in Soil Science and Plant Analysis, 36: 1141-1161.
  • Chen, L.D., Wang, J., Fu, B.J., Qiu, Y., 2001. Land-use change in a small catchment of northern Loess Plateau, China. Agriculture Ecosystem and Environment, 86: 163-172.
  • Dalal, R.C., Moloney, D., 2000. Sustainability indicators of soil health and biodiversity. In Hale, P., Petrie, A., Moloney, D. and Sattler, P. (eds.) Management for sustainable ecosystems. Centre for Conservation Biology, University of Queensland, Brisbane, pp. 101-108.
  • Di, H.J., Trangmar, B.B., Kemp, R.A., 1989. Use of Geostatistics in Designing Sampling Strategies for Soil Survey. Soil Science Society of America Journal, 53: 1163-1167.
  • Ditzler, C.A., Tugel, A.J., 2002. Soil quality field tools: Experiences of USDA-NRCS Soil Quality Institute. Agronomy Journal, 94: 33-38.
  • Doran, J.W., Parkin, T.B., 1994. Defining and assessing soil quality. In Doran, J. W., Coleman, D. C., Bezdicek, D. F. and Stewart, B. A. (eds.) Defining soil quality for a sustainable environment. SSSA and ASA, Madison, Wisconsin, pp. 3-21.
  • Graf, W.L., 1982. Spatial variations of fluvial processes in semi-arid lands. In Thorn, C. E. (ed.) Space and time in Geomorphology. Allen and Unwin, Boston.
  • Hani, A., Pazira, E., Manshouri, M., Kafaky, S.B., Tali, M.G., 2010. Spatial distribution and mapping of risk elements pollution in agricultural soils of southern Tehran, Iran. Plant Soil Environment, 56(6): 288- 296.
  • Hazelton, P., Murphy, B., 2007. Interpreting Soil Test Results. What do the Numbers Mean? CSIRO Publishing, Melbourne.
  • Isaaks, H.E., Srivastava, R.M., 1989. An Introduction to Applied Geostatistics. Oxford University Press, Nelson, D.W., Sommers, L.E., 1982. Total Carbon, Oxford.
  • Larson, W.E., Pierce, F.J., 1991. Conservation and enhancement of soil quality. In Proceedings of the International Workshop on Evaluation for Sustainable Land Management in the Developing World, International Board for Soil Research and Management, Bangkok, pp. 175-203.
  • Lindsay, W.L., Norvell, W.A., 1978. Development of a DTPA soil test for zinc, iron, manganese and copper. Soil Science Society of America Journal, 42: 421- 428.
  • Loganathan, P., Hedley, M.J., Wallace, G.C., Roberts, A.H.C., 2001. Effect of soil cultivation and winter pugging on fluorine distribution in soil profiles under pasture following long-term applications of phosphate fertilizers. Environmental Pollution, 115: 275-282.
  • Lu, D., Moran, E., Mausel, P., 2002. Linking Amazonian secondary succession forest growth to soil properties. Land Degradation and Development, 13: 331-343.
  • Moran, E.F., Brondizion, E.S., Tucker, J.M., Da Silva- Forsberg, M.C., McCracken, S., Falesi, I., 2000. Effects of soil fertility and land use on forest succession in Amazonia. Forest Ecology and Management, 139: 93-108.
  • Mueller, T.G., Pierce, F.J., Schabenberger, O., Warncke, D.D., 2001. Map Quality for Site-Specific Fertility Management. Soil Science Society of America Journal, 65(5): 1547-1558. Organic Carbon and Organic matter. In Page, L. A., Miller, R. H. and Keeney, D. R. (eds.) Methods of Soil Analysis, Part II, Chemical and Microbiological Methods, 2nd edn. ASA, Madison, Wisconsin, pp. 539-579.
  • Park, S.J., Vlek, P.L.G., 2002. Environmental correlation of three-dimensional soil spatial variability: A comparison of three adaptive techniques. Geoderma, 109(1-2): 117-140.
  • Robertson, G.P., 2008. GS+: Geostatistics for the environmental sciences. USA: Gamma design software, Plainwell, Michigan.
  • Weber, G.B., Gobat, J.M., 2006. Identification of facies models in alluvial soil formation: The case of a Swiss Alpine Floodplain. Geomorphology, 74: 181- 195.
  • Whelan, B.M., McBratney, A.B., Rossel, R.A., 1996. Spatial prediction for precision agriculture. Precision Agriculture Proceedings of the 3rd International Conference, Madison, pp. 331-342.
  • Wolf, B., 1971. The Determination of Boron in Soil Extracts, Plant Materials, Composts, Manures, Water and Nutrient Solutions. Soil Science and Plant Analysis, 2: 363-374.

Distribution and Evaluation of Soil Fertility Based on Geostatistical Approach in Bafra Deltaic Plain

Year 2014, Volume: 1 Issue: 2, 186 - 195, 30.09.2014
https://doi.org/10.19159/tutad.27089

Abstract

This study was conducted to examine spatial variability of soil fertility depending on the level of selected soil fertility parameters in FenerVillagelocated on Bafra Alluvial Deltaic Plain by means of Soil Fertility Index (SFI) model using geostatistics and Geographic Information System (GIS) technique. Fifteen soil properties [available macronutrient elements (nitrogen, phosphorous, potassium, calcium, magnesium, sodium), available micronutrient elements (iron, copper, zinc, manganese), and other soil properties (texture class, organic matter, pH, electrical conductivity, CaCO3)] at the depths of 0-30 cm and 30-60 cm were evaluated using SFI model for each georeferenced point. A total of 140 grid points were obtained and soil samples collected from surface (0-30 cm) and subsurface (30-60 cm) depths of each grid centre are 131 and 124, respectively. Geostatistical method was used to generate SFI distribution maps for surface and subsurface soils of the study area. According to the results of SFI distributions for both depths, 80.18% of the study area has good (S1) and moderate fertility (S2), 19.06% has marginal fertility (S3), 0.75% has poor fertility in surface depth, while 38.83% of the study area has good (S1) and moderate fertility (S2), 41.30% marginal fertility (S3) and 19.87% has poor fertility in subsurface depth. Consequently, findings of this study showed that geostatistical modelling was useful in the determination of the spatial variability structure and spatial dependency of investigated soil properties and nutrients.

References

  • Abbasi, M.K., Zafar, M., Sultan, T., 2010. Changes in soil properties and microbial indices across various management sites in the mountain environments of Azad Jammu and Kashmir. Communications in Soil Science and Plant Analysis, 41: 768-782.
  • Alexander, J., Fielding, C.R., Pocock, G.D., 1999. Floodplain Behaviour of the Burdekin River, Tropical North Queensland, Australia. In Anderson, M. G., Walling, D. E. and Bates, P. D. (eds.) Floodplain Processes. Wiley, Chichester. pp. 27-40.
  • Anonymous, 1990a. Analytical for Atomic Absorption Spectro Photometry. Connecticut, Perkin Elmer, Norwalk.
  • Anonymous, 1990b. Micronutrient, Assessment at the Country Level: An International Study. FAO Soil Bulletin by Sillanpaa, Rome.
  • Anonymous, 1992. Procedures for Collecting Soil Samples and Methods of Analysis for Soil Survey. Soil Surv Invest Rep I US Gov Print Office, Washington DC.
  • Anonymous, 1999. Soil Survey Staff, Soil Taxonomy. A Basic of Soil Classification for Making and Interpreting Soil Survey. USDA Handbook No 436, Washington DC.
  • Arshad, M.A., Martin, S., 2002. Identifying critical limits for soil quality indicators in agro-ecosystems. Agriculture Ecosystem and Environment, 88: 153- 160.
  • Boruvka, L., Vacek, O., Jehlicka, J., 2005. Principal component analysis as a tool to indicate the origin of potentially toxic elements in soils. Geoderma, 128: 289-300.
  • Boyer, J.S., 1982. Plant productivity and environment. Science, 218: 443-448.
  • Chaudhury, J., Mandal, U.K., Sharma, K.L., Ghosh, H., Mandal, B., 2005. Assessing soil quality under long- term rice-based cropping system. Communications in Soil Science and Plant Analysis, 36: 1141-1161.
  • Chen, L.D., Wang, J., Fu, B.J., Qiu, Y., 2001. Land-use change in a small catchment of northern Loess Plateau, China. Agriculture Ecosystem and Environment, 86: 163-172.
  • Dalal, R.C., Moloney, D., 2000. Sustainability indicators of soil health and biodiversity. In Hale, P., Petrie, A., Moloney, D. and Sattler, P. (eds.) Management for sustainable ecosystems. Centre for Conservation Biology, University of Queensland, Brisbane, pp. 101-108.
  • Di, H.J., Trangmar, B.B., Kemp, R.A., 1989. Use of Geostatistics in Designing Sampling Strategies for Soil Survey. Soil Science Society of America Journal, 53: 1163-1167.
  • Ditzler, C.A., Tugel, A.J., 2002. Soil quality field tools: Experiences of USDA-NRCS Soil Quality Institute. Agronomy Journal, 94: 33-38.
  • Doran, J.W., Parkin, T.B., 1994. Defining and assessing soil quality. In Doran, J. W., Coleman, D. C., Bezdicek, D. F. and Stewart, B. A. (eds.) Defining soil quality for a sustainable environment. SSSA and ASA, Madison, Wisconsin, pp. 3-21.
  • Graf, W.L., 1982. Spatial variations of fluvial processes in semi-arid lands. In Thorn, C. E. (ed.) Space and time in Geomorphology. Allen and Unwin, Boston.
  • Hani, A., Pazira, E., Manshouri, M., Kafaky, S.B., Tali, M.G., 2010. Spatial distribution and mapping of risk elements pollution in agricultural soils of southern Tehran, Iran. Plant Soil Environment, 56(6): 288- 296.
  • Hazelton, P., Murphy, B., 2007. Interpreting Soil Test Results. What do the Numbers Mean? CSIRO Publishing, Melbourne.
  • Isaaks, H.E., Srivastava, R.M., 1989. An Introduction to Applied Geostatistics. Oxford University Press, Nelson, D.W., Sommers, L.E., 1982. Total Carbon, Oxford.
  • Larson, W.E., Pierce, F.J., 1991. Conservation and enhancement of soil quality. In Proceedings of the International Workshop on Evaluation for Sustainable Land Management in the Developing World, International Board for Soil Research and Management, Bangkok, pp. 175-203.
  • Lindsay, W.L., Norvell, W.A., 1978. Development of a DTPA soil test for zinc, iron, manganese and copper. Soil Science Society of America Journal, 42: 421- 428.
  • Loganathan, P., Hedley, M.J., Wallace, G.C., Roberts, A.H.C., 2001. Effect of soil cultivation and winter pugging on fluorine distribution in soil profiles under pasture following long-term applications of phosphate fertilizers. Environmental Pollution, 115: 275-282.
  • Lu, D., Moran, E., Mausel, P., 2002. Linking Amazonian secondary succession forest growth to soil properties. Land Degradation and Development, 13: 331-343.
  • Moran, E.F., Brondizion, E.S., Tucker, J.M., Da Silva- Forsberg, M.C., McCracken, S., Falesi, I., 2000. Effects of soil fertility and land use on forest succession in Amazonia. Forest Ecology and Management, 139: 93-108.
  • Mueller, T.G., Pierce, F.J., Schabenberger, O., Warncke, D.D., 2001. Map Quality for Site-Specific Fertility Management. Soil Science Society of America Journal, 65(5): 1547-1558. Organic Carbon and Organic matter. In Page, L. A., Miller, R. H. and Keeney, D. R. (eds.) Methods of Soil Analysis, Part II, Chemical and Microbiological Methods, 2nd edn. ASA, Madison, Wisconsin, pp. 539-579.
  • Park, S.J., Vlek, P.L.G., 2002. Environmental correlation of three-dimensional soil spatial variability: A comparison of three adaptive techniques. Geoderma, 109(1-2): 117-140.
  • Robertson, G.P., 2008. GS+: Geostatistics for the environmental sciences. USA: Gamma design software, Plainwell, Michigan.
  • Weber, G.B., Gobat, J.M., 2006. Identification of facies models in alluvial soil formation: The case of a Swiss Alpine Floodplain. Geomorphology, 74: 181- 195.
  • Whelan, B.M., McBratney, A.B., Rossel, R.A., 1996. Spatial prediction for precision agriculture. Precision Agriculture Proceedings of the 3rd International Conference, Madison, pp. 331-342.
  • Wolf, B., 1971. The Determination of Boron in Soil Extracts, Plant Materials, Composts, Manures, Water and Nutrient Solutions. Soil Science and Plant Analysis, 2: 363-374.
There are 30 citations in total.

Details

Journal Section Research Article
Authors

Mustafa Sağlam

Orhan Dengiz

Publication Date September 30, 2014
Published in Issue Year 2014 Volume: 1 Issue: 2

Cite

APA Sağlam, M., & Dengiz, O. (2014). Distribution and Evaluation of Soil Fertility Based on Geostatistical Approach in Bafra Deltaic Plain. Türkiye Tarımsal Araştırmalar Dergisi, 1(2), 186-195. https://doi.org/10.19159/tutad.27089
AMA Sağlam M, Dengiz O. Distribution and Evaluation of Soil Fertility Based on Geostatistical Approach in Bafra Deltaic Plain. TÜTAD. October 2014;1(2):186-195. doi:10.19159/tutad.27089
Chicago Sağlam, Mustafa, and Orhan Dengiz. “Distribution and Evaluation of Soil Fertility Based on Geostatistical Approach in Bafra Deltaic Plain”. Türkiye Tarımsal Araştırmalar Dergisi 1, no. 2 (October 2014): 186-95. https://doi.org/10.19159/tutad.27089.
EndNote Sağlam M, Dengiz O (October 1, 2014) Distribution and Evaluation of Soil Fertility Based on Geostatistical Approach in Bafra Deltaic Plain. Türkiye Tarımsal Araştırmalar Dergisi 1 2 186–195.
IEEE M. Sağlam and O. Dengiz, “Distribution and Evaluation of Soil Fertility Based on Geostatistical Approach in Bafra Deltaic Plain”, TÜTAD, vol. 1, no. 2, pp. 186–195, 2014, doi: 10.19159/tutad.27089.
ISNAD Sağlam, Mustafa - Dengiz, Orhan. “Distribution and Evaluation of Soil Fertility Based on Geostatistical Approach in Bafra Deltaic Plain”. Türkiye Tarımsal Araştırmalar Dergisi 1/2 (October 2014), 186-195. https://doi.org/10.19159/tutad.27089.
JAMA Sağlam M, Dengiz O. Distribution and Evaluation of Soil Fertility Based on Geostatistical Approach in Bafra Deltaic Plain. TÜTAD. 2014;1:186–195.
MLA Sağlam, Mustafa and Orhan Dengiz. “Distribution and Evaluation of Soil Fertility Based on Geostatistical Approach in Bafra Deltaic Plain”. Türkiye Tarımsal Araştırmalar Dergisi, vol. 1, no. 2, 2014, pp. 186-95, doi:10.19159/tutad.27089.
Vancouver Sağlam M, Dengiz O. Distribution and Evaluation of Soil Fertility Based on Geostatistical Approach in Bafra Deltaic Plain. TÜTAD. 2014;1(2):186-95.

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