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Spatial prediction of soil phosphorous using soil electrical conductivity as secondary information

Research Paper | March 1, 2016

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Nikou Hamzehpour, Sara Mola Ali Abasiyan

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J. Bio. Env. Sci.8( 3), 88-95, March 2016


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Soil phosphorus (P) plays an important role in soil fertility and availability of micronutrients in soil, especially in arid and semiarid regions. Therefore, monitoring soil P condition is of great importance. The aim of the present study was to investigate the spatial variation of soil phosphorus by taking into account top soil EC data as secondary information. The research was performed on a grid of 0.75-1 km in an area of 367 km2. Soil phosphorus (P), Potassium (K), Zinc (Zn), Iron (Fe), Copper (Cu), Manganese (Mn), Organic Matter (O.M) and electrical conductivity (EC) were measured. Then variogram was built for P dataset and spatial prediction was done on a grid of 500 m using kriging estimator with taking into account the mean variation. Afterwards soil EC was used as covariate to develop cross-semivarograms in prediction of soil P using co-kriging method. Cross-validating the results from P predictions using only kriging estimator to that of co-kriging with EC data revealed that co-kriging offered better estimations with ME and MSE of 0.11 and 0.149, respectively. Kriging estimator had more smoother and diffused boundaries than that of co-kriging and resulted in more bias estimations (ME and MSE of -0.18 and -0.326, respectively). According to the results, co-kriging method and soil EC could be used successfully in improving spatial prediction of soil phosphor.


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Spatial prediction of soil phosphorous using soil electrical conductivity as secondary information

Acosta JA, Faz A, Jansen B, Kalbitz K, Martinez-Martinez S. 2011. Assessment of salinity status in intensively cultivated soils under semiarid climate, Murcia, SE Spain. Journal of Arid Environments 75, 1056-1066.

Chen Y, Liu R, Sun CH, Zhang P, Feng CH, Shen ZH. 2012. Spatial and temporal variations in nitrogen and phosphorous nutrients in the Yangtze River Estuary. Marine and Pollution Bulletin 64(10), 2083-2089.

Christakos G, Bogaert P, Serre ML. 2002. Temporal GIS. Advanced Functions for Field-Based Applications. Springer-Verlag, New York NY.

De Clercq WP, Van Meirvenn M, Fey MV. 2009. Prediction of the soil-depth salinity-trend in a vineyard after sustained irrigation with saline water. Agricultural Water Management 96, 395-404.

Giordano R, Liersch S, Vurro M, Hirsch D. 2010. Integrating local and technical knowledge to support soil salinity monitorinf in the Amudarya river basin. Journal of Environmental Management 91, 1718-1729.

Goetz RU, Keusch A. 2005. Dynamic efficiency of soil erosion and phosphor reduction policies combining economic and biophysical models. Ecological Economics 52(2), 201-218.

Hendricks GS, Shukla S, Obreza TA, Harris WG. 2014. Measurement and modeling of phosphorous transport in shallow groundwater environments. Journal of Contaminant Hydrology 164, 125-137.

Juan P, Mateu J, Jordan MM, Mataix-Solera J, Melendez-Pastor I, Navarro-Pedreno J. 2011. Journal of Geochemical Exploration 108, 62-72.

Leopold U, Heuvelink GBM, Tiktak A, Finke PA, Schoumans O. 2006. Accounting for change of support in spatial accuracy assessment of modelled soil mineral phosphorous concentration. Geoderma 130(3-4), 368-386.

Li KL, Chen J, Tan MZ, Zhao BZ, Mi SX, Shi XZ. 2011. Spatio-Temporal variability of soil salinity in Alluvial Plain of the lower reaches of the Yellow River- a case study. Pedosphere 21(6), 793-801.

Li J, Heap AD. 2008. A Review of Spatial Interpolation Methods for Environmental Scientists. Geoscience Australia, Canberra, Australia.

Malins D, Metternicht G. 2006. Assessing the spatial extent of dryland salinity through fuzzy modeling. Ecological Modelling 193, 387-411.

Marquez Molina JJ, Sainato CM, Urricariet AS, Losinno BN, Heredia OS. 2014. Bulk electrical conductivity as an indicator of spatial distribution of nitrogen and phosphorous at feedlots. Journal of Applied Geophyscics 111, 156-172.

Mouazen AM, Kuang B. 2016. On-line visible and near infrared spectroscopy for in-field phosphorous management. Soil and Tillage Research 155, 471-477.

Mondal MK, Bhuiyan SI, Franco DT. 2001. Soil salinity reduction and prediction of salt dynamics in the coastal ricelands of Bangladesh. Agricultural Water Management 47, 9-23.

OHalloran IP, Kachanoski RG, Stewart JWB. 1985. Spatial variability of soil phosphorus as influences by soil texture and management. Canadian Journal of Soil Science 65(3), 475-487.

Page T, Haygarth PhM, Beven KJ, Joynes A, Butler T, Keeler Ch, Freer J, Owens Ph N, Wood GA. 2005. Spatial variability of soil phosphorus in relation to the topographic index and critical source areas: sampling for assessing risk to water quality. Journal of Environmental Hazard 2263-2277.

Peck AJ, Hatton T. 2003. Salinity and the discharge of salts from catchments in Australia Journal of Hydrology 272, 191-202.

Pease LM, Odour P, Padmanabhan G. 2010. Estimating sediment, nitrogen, and phosphorous loads from the Pipestem Creek watershed, North Dakota, using AnnAGNPS. Computer and Geosciences 36(3), 282-291.

Piotrowaska-Dlugosz AP, Lemanowicz J, Dlugosz J, Spychaj-Fabisiak E, Gozdowski D, and Rybacki M. 2016.Spatiotemporal variations of soil properties in a plot scale: a case study of soil phosphorus forms and related enzymes. Journal of soils and Sediments 16(1), 62-76.

Roger A, Libohova Z, Rossier N, Joost S, Maltas A, Frossard E, Sinaj S. 2014. Spatial variability of soil phosphorus in the Fribourg canton, Switzerland. Geoderma 217-218, 26-36.

Shi LL, Shen MX, Lu ChY, Wang HH, Zhou XW, Jin MJ, Wu TD. 2015. Soil phosphorus dynamic, balance and critical P values in long-term fertilization experiment in Taihu Lake region, China. Journal of Integrative Agriculture 14(12), 2446-2455.

Stein A, Corsten LCA. 1991. Universal kriging and cokriging as a regression procedure. Biometrics 47, 575–587.

Triantafilis J, Odeh IOA, Warr B, Ahmed MF. 2004. Mapping of salinity risk in the lower Namoi valley using non-linear kriging methods. Agricultural Water Management 69, 203-231.