Using The Inverted Distance Weighting Method (IDW) to Produce Maps of Some Soil Properties at the Agricultural Research Station, University of Tripoli

Authors

  • Magda Bashir El-beshti Department of Soil and Water, Faculty of Agriculture, University of Tripoli, Tripoli, Libya
  • Abuabdalla Saad Sherif Department of Soil and Water, Faculty of Agriculture, University of Tripoli, Tripoli, Libya
  • Ehab Mohamed Sagar Department of Soil and Water, Faculty of Agriculture, University of Tripoli, Tripoli, Libya

DOI:

https://doi.org/10.54172/mjsc.v34i4.207

Keywords:

Inverted Distance Weighting, Bulk Density, Volumetric Water Content, Soil Salinity, Soil pH

Abstract

The objective of the study was to determine the spatial differences of some physical and chemical properties of the soil samples of the research stations of the Faculty of Agriculture/University of Tripoli in April 2013. The results were used to produce spatial maps in order to find out the spacial distribution for the following properties: Bulk density (BD), Gravimetric water content (GWC), soil salinity (EC) and soil pH using the inverse distance weighting (IDW) method. The study was conducted on an area of approximately 13000 m2 and was divided into a 12 m x11 m grid to produce 100 survey units and 36 units were chosen and coordinated by a portable GPS device to collect the samples. Tests were performed for both BD and GWC from depths 0-10 cm, 10-20 cm and 20- 30cm, while EC and pH analysis where done for samples from a depth of 30 cm. Spatial maps were produced of continuous surfaces and quality that differed from one property to another according to the Root Mean Square Error (RMSE) values. Based on the results, the values of RMSE varied (0.71, 0.82, and 0.86) for the GWC and (0.06, 0.13, 0.08) for the BD properties of the three depths, respectively. Where as the RMSE values were (0.15, 0.84) for the pH and EC properties respectively. The low RMSE values for BD maps at the first and third depths and the pH map showed a higher quality index for the maps. While the relatively high RMSE values showed that the maps produced for both EC and GWC properties were lower quality. This study concluded that it is possible to produce spatial maps of different quality for some soil properties within the field using IDW. These maps can therefore be used to predict BD and pH properties in the field, while they are difficult to predict for EC and GWC. Therefore, it is recommended to continue to explore the possibility of producing high-quality maps in other ways for these two properties, taking into account the increase in the number of the samples.

 

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References

امحمد، مفتاح علي محمد.) 2015(. تقييم وتخريط ملوحة التربة للمحاصيل المروية باستخدام طرق الإحصاء المكاني (Geostatistics) والدراسات الحقلية بمنطقة سواوة. رسالة ماجستير، جامعة طرابلس، طرابلس-ليبيا.

الجبوري، ثاير حبيب؛ منعم نصيف جاسم المزروعي ومنذر صائل الجبوري. ) 2015(. التحليل المكاني لخصائص ترب ناحية المنصورية. مجلة ديالي. (65): 58-84.

العالم، مختار محمود. (2017). التغايرات المكانية لبعض خواص التربة الكيميائية لمنطقة سهل الجفارة (حالة دراسية: طرابلس، وادي المجينين، بن غشير). المجلة الليبية للعلوم الزراعية. 22 (1): 19-34.

المحميد، عبد الحليم علي سليمان. (1999). التغايرات المكانية والزمنية لبعض صفات الترب في وسط السهل الرسوبي العراقي – اطروحة دكتوراه-كلية الزراعة/ جامعة بغداد.

جبير، أمل راضي. (2013(. دراسة التغايرات المكانية واستحصال العينات لبعض صفات التربة في شمال تكريت باستخدام مفاهيم الإحصاء الجيولوجي عن طريق المعلومات الجغرافية (GIS). مجلة الفرات الزراعية. 5 (3): 268-279.

سليمان. عبد الحليم علي وأمل راضي جبير. (2014). دراسة التغايرات المكانية لبعض الصفات الفيزيائية والكيميائية للتربة في وسط السهل الرسوبي باستخدام مفاهيم الإحصاء البيدولوجي. مجلة جامعة تكريت للعلوم الزراعية. 14 (1): 236-245.

شرف. محمد ابراهيم محمد. (2017). المرجع في نظم المعلومات الجغرافية. دار المعرفة الجامعية. جامعة الاسكندرية، مصر. ص 328.

صادق، منير هاشم؛ هادي عبد الأمير العجيلي وسعد شاكر العزاوي. (2014). دراسة مقارنة تقنيات التقدير لرسم خرائط بعض الصفات الفيزياوية للتربة. مجلة جامعة كربلاء. 12 (2): 221-232.

Aishah, A.W.; Zauyah. S; Anuar. A.R; and Fau-ziah.C.I . (2010). Spatial variability of se-lected chemical characteristics of padoly Soils in Sawah Sempadan , Selangor ,Malaysia. Malaysian J of soil Sci, vol.14:27 -39

Arshad, M.A.; B. Lowery and B. Grossman (1996). Physical tests for monitoring soil quality. In: Doran, J.W. and A.J. Jones (Eds). Methods for assessing soil quality. SSSA Spec. Publ. 49. Soil Science Socie-ty of America, Inc., Madison, Wisconsin, USA, p.123-142. DOI: https://doi.org/10.2136/sssaspecpub49.c7

Bogunović, I., Dekemati, I., Magdić, I., Vrbanić, M., Matošić, S., Mesić, M. (2016). Spatial modeling for describing spatial variability of soil physical prop-erties in eastern Croatia. Poljop-rivreda,22: 2016 (1) 46-52. DOI: https://doi.org/10.18047/poljo.22.1.7

Burrough, P. A. (1989). Fuzzy Mathematical Methods for Soil Survey and Land Eval-uation. Journal of Soil Science, 40: 447- 492. DOI: https://doi.org/10.1111/j.1365-2389.1989.tb01290.x

Burrough, P. A. (1993). Problems of Superim Posed Effects in The Statistical Study of The Spatial Variation of Soil Agricultural .Water Management, Netherlands, 6: 123 - 143. DOI: https://doi.org/10.1016/0378-3774(83)90004-5

Burrough, P. A., and McDonnell. R. A. (1998). Principles of Geographic Information Systems. Oxford, Oxford University Press.

Burrough, P.A. (1986). Principles of Geographic Information Systems for Land Resources Assessment. Oxford, Oxford University Press. DOI: https://doi.org/10.1080/10106048609354060

Camachu, T.; Jesus, H.; Luengas C. A. and Fa-bio R. L. (2009). Effect of Agricultural Intervention on the Spatial Variability of Some Soils Chemical Properties in the Eastern Plains of Colombia. Chilean Jour-nal of Agricultural Research 68(1): 42 -55. DOI: https://doi.org/10.4067/S0718-58392008000100005

Carter, M.R. and B.C. Ball (1993). Soil porosi-ty. In: Carter, M. R (Eds). Soil sampling and methods of analysis. Canadian Socie-ty of soil science. Lewis Publishers. ISBN 0-87371-861-5.

Chang, K. (2002). Introduction to Geographic Information Systems McGraw-Hill, New York.

Chile`s, J. P. and Delfiner, P. (1999). Geostatis-tics: Modeling Spatial Uncertainty. John Wiley & Sons, Inc., New York.

Corwin, D.L. and Lesch, S. M. (2005). Charac-terizing Soil Spatial Variability with Ap-parent Soil Electrical Conductivity Part 11. Case Study .Computers and Electron-ics in Agriculture, 46:135 -152. DOI: https://doi.org/10.1016/j.compag.2004.11.003

De la Rosa, D. (1979). Relation of Several Pe-dological Characteristics to Engineering Qualities of Soil. Journal of Soil Science, 30: 793 –799. DOI: https://doi.org/10.1111/j.1365-2389.1979.tb01028.x

ESRI. (2012). Environmental Systems Re-search Institute, Using ArcGIS geostatis-tical analyst USA.

Fahad, A. A.; Shib, R. M.; Al-Siaykaly, A. A. and Razaq, I. B. (1993). Spatial Variabil-ity of Field Soil Salinity Using Geostatis-tical Techniques. Basra, Journal Agricul-tural Science, 6 (1).

Gotway, C. A; Ferguson, R. B; Hergert, G. W; and Peterson, T.A .(1996). Comparison of kriging and inverse-distance methods for mapping soil parameters. Soil Science So-ciety of America Journal ,60: 1237-1247. DOI: https://doi.org/10.2136/sssaj1996.03615995006000040040x

Hendershort, W.H.; H. Lalande and M. Du-quette (1993). Soil reaction and ex-changeable acidity. In: Carter. M.R. (Eds). Soil Sampling and methods of soil analysis (pp. 141-145). Canadian Soc. Soil Sci., Lewis Publishers London.

Hosseini, E.; Gallich, J. and Marcot, D. (2009). Theoretical and Experimental Perfor-mance of Spatial Interpolation Methods for Soil salinity analysis. Transactions of the American Society of Agricultural and Biological Engineers, 37:1799 - 1907. DOI: https://doi.org/10.13031/2013.28269

Hudnall W.; A.Bekele. (2006). Spatial Variabil-ity of soil chemical properties of a prai-rieforest transition in Louisiana. Plant Soil, v. 280, p. 7-21. DOI: https://doi.org/10.1007/s11104-005-4983-4

Krasilinkov,P.; F.Carre; L. Montanarella. (2008). Soil geography and geostatistics.

Lascano ,R.J. and Hatfield. J.L.(2001). Spatial variability of evaporation long two tran-sects of a bare soil .Soil Sci.Soc Am.J. 56:341 -346. DOI: https://doi.org/10.2136/sssaj1992.03615995005600020002x

Mabit, L. and Bernard C .(2010). Spatial distri-bution and content of soil organic matter in an agricultural field in eastern Canada, as estimated from geostatistical tools. Earth Surface Process and Landforms, 35: 278- 283 DOI: https://doi.org/10.1002/esp.1907

Mardia, K. V. and Jupp, P. F. 2000. Direc-tional Statistics. John Wiley & Sons, Ltd, Chichester. DOI: https://doi.org/10.1002/9780470316979

Moradi, M., D. Ghonchehpour, A. Majidi, and V.M. Nejad.(2012). Geostatistic ap-proaches for investigating of soil hydrau-lic conductivity in Shahrekord Plain, Iran. Amer. J. Math. And statistics 2(6): 164-168. DOI: https://doi.org/10.5923/j.ajms.20120206.01

Mulla, D. J. )1997(. Geostatistics, remote sens-ing and precision farming. In: Precision Agriculture: Spatial and Temporal Varia-bility of Environmental Quality. John Wiley & Sons, Ltd, Chichester.

Nikpey M, Sedighkia M, and Nateghi M B (2017). Comparison of Spatial Interpola-tion Methods for Mapping the Qualitative Properties of Soil. Advances in Agricul-tural Science, 5: 1-15.

Peterson, M. (2017). Advances in Cartography and GIScience. Selection from the Inter-national Cartographic Conference 2017. Washington. DOI: https://doi.org/10.1007/978-3-319-57336-6

Rosenbaum, M.; and Söderstoröm, M. )1996(.Geostatistices as an aid to map-ping. In 1996 ESRI European User Con-ference. London, UK.

Santra, P.; Chopra, U. K. and Chkraborty, D. (2008). Spatial Variability of Soil Proper-ties and its Application in Predicting Sur-face Map of Hydraulic Parameters in an Agricultural Farm. Current Science, 95: 937-945.

Talkkari, A.; Lauri, J. and Markku Y. H. (2002). Geostatistical Prediction of Clay Percentage Based on Soil Survey Data Agricultural Journal, 11: 381- 390. DOI: https://doi.org/10.23986/afsci.5738

Tunçay, T; Bayramin, I; Atalay, F; and Unver, I. (2016). Assessment of Inverse Distance Weighting (IDW) Interpolation on Spatial Variability of Selected Soil Properties in the Cukurova Plain. Journal of Agricul-tural Sciences. 22: 377-384. DOI: https://doi.org/10.15832/ankutbd.257726

Usowicz, B.; Hajnos, M.; Sokololwska, Z.; J.zefaciuk, G.; Bowanko, G. and Kos-sowski, J. (2004). Spatial Variability of Physical and Chemical Soil Properties in a Field and Commune Scale. Acta Ag-rophys, 3:5 – 90.

Usowicz,B. and Lipiec, J. ((2017. Spatial varia-bility of soil properties and cereal yield in a cultivated field on sandy soil. Soil & Tillage Research 174 :241–250. DOI: https://doi.org/10.1016/j.still.2017.07.015

Uyan, M. and Cay, T. )2010(. Geostatistical methods for mapping groundwater nitrate concentrations. Paper presented at the 3rd international conference on cartography and GIS. Nessebar, Bulgaria. Vineeth, P.; Teja. K. and Raghuveer.D. (n.d) https://www.slideshare.net/penchalavineeth/inverse-distance-weighting

Weber,D., and E.J. England, )1992(. Evalua-tion and comparison of spatial interpola-tions.Math. Geol., 26: 381-391 DOI: https://doi.org/10.1007/BF00891270

Webster, R., and Oliver. M. )2001(. Geostatis-tics for Environmental Scientists John Wiley & Sons, Chichester.

White, J. G.; Welch, R. M. and Norvell, W. A. )1997(. Soil Zinc Map of USA Using Ge-ostatististics and Geographic Information System. Soil Science Society of America Journal, 61:185 -194. DOI: https://doi.org/10.2136/sssaj1997.03615995006100010027x

Wollenhaupt, N.C., Wolkowski. R.P, and Clayton, M.K. )1994(. Mapping soil test phosphorous and potassium for variable-rate fertilizer application. J. Prod. Agric, 7: 441- 448 DOI: https://doi.org/10.2134/jpa1994.0441

Published

2019-12-31 — Updated on 2019-12-31

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El-beshti م. ب. ., Sherif أ. س. ., & Sagar إ. م. (2019). Using The Inverted Distance Weighting Method (IDW) to Produce Maps of Some Soil Properties at the Agricultural Research Station, University of Tripoli. Al-Mukhtar Journal of Sciences, 34(4), 315–327. https://doi.org/10.54172/mjsc.v34i4.207

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