Estimation of heavy metal sorption in German soils using artificial neural networks

Geoderma

Volumn 152, Issue 1-2, 2009, Pages 104-112

  Anagu, Ihuaku ^a   Ingwersen, Joachim ^a   Utermann, Jens ^b   Streck, Thilo ^a  

^a UNIVERSITY OF HOHENHEIM   (Germany)

^b FEDERAL INSTITUTE FOR GEOSCIENCES AND NATURAL RESOURCES BGR   (Germany)

Author keywords

Artificial neural networks; Heavy metals; Modelling; Multiple linear regression; Sorption

Indexed keywords

AGRICULTURAL SITES; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORK MODELS; ARTIFICIAL NEURAL NETWORKS; GERMANY; HEAVY METALS IN SOIL; HUMAN ACTIVITIES; MEAN ERRORS; METAL SORPTION; MODELLING; MULTIPLE LINEAR REGRESSION; MULTIPLE LINEAR REGRESSIONS; PHASE CONCENTRATION; ROOT MEAN SQUARE ERRORS; SOIL DATA; SOIL PROPERTY; SOLUTION PHASE; SORPTION MODELS; VERSATILE TOOLS;

BACKPROPAGATION; CADMIUM; CHROMIUM; COMPOSITE MICROMECHANICS; GEOLOGIC MODELS; LEAD; METALS; NEURAL NETWORKS; REGRESSION ANALYSIS; RISK ASSESSMENT; RISK MANAGEMENT; RISK PERCEPTION; SOILS; SORPTION; ZINC;

SOIL POLLUTION;

ARTIFICIAL NEURAL NETWORK; DATA ACQUISITION; HEAVY METAL; MULTIPLE REGRESSION; NUMERICAL MODEL; SAMPLING; SOIL PROPERTY; SORPTION; SUBSOIL; TOPSOIL;

CENTRAL EUROPE; EURASIA; EUROPE; GERMANY;

EID: 67650552421     PISSN: 00167061     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.geoderma.2009.06.004     Document Type: Article

References (51)

1. Adriano D.C. Trace Elements in the Terrestrial Environment (1986), Springer-Verlag, New York
2. Altfelder S., Duijnisveld W.H.M., Streck T., Meyenburg G., and Utermann J. Quantifying the influence of uncertainty and variability on groundwater risk assessment for trace elements. Vandose Zone J. 6 (2007) 668-678
3. Andersen P.R., and Christensen T.H. Distribution coefficients of Cd, Co, Ni and Zn in soils. J. Soil Sci. 39 (1988) 15-22
4. Baker L. Development of class pedotransfer functions of soil water retention - a refinement. Geoderma 144 (2008) 225-230
5. Behrens T., Förster H., Scholten T., Steinrüken U., Spies E., and Goldschmitt M. Digital soil mapping using artificial neural networks. J. Plant Nutr. Soil Sci. 168 (2005) 21-33
6. Berthouex P.M., and Brown L.C. Statistics for Environmental Engineers. 2nd Edition (2002), CRC Press, Boca, Raton, FL.
7. Brallier S., Harrison R.B., Henry C.L., and Dongsen X. Liming effects on availability of Cd, Cu, Ni, and Zn in a soil amended with sewage sludge 16 years previously. Water Air Soil Poll. 86 (1996) 195-206
8. Buszewski B., and Kowalkowski T. A new model of heavy metal transport in the soil using non-linear artificial neural networks. Environ. Eng. Sci. 23 4 (2006) 589-595
9. Elzinga E.J., Van Grinsven J.J.M., and Swartjes F.A. General purpose Freundlich isotherms for cadmium, copper and zinc in soils. Eur. J. Soil Sci. 50 (1999) 139-149
10. Fausett L.V. Fundamentals of Neural Networks: Architectures, Algorithms, and Applications (1994), Prentice Hall, Englewood Cliff, N.J.
11. Geman S., Bienenstock E., and Doursat R. Neural networks and the bias/variance dilemma. Neural Comput. 4 (1992) 1-58
12. Gurney K. An Introduction to Neural Networks (1997), UCL press, London
13. Haykin S. Neural Networks, a Comprehensive Foundation (1994), Macmillan, New York
14. Hecht-Nielsen R. Neurocomputing (1990), Addison-Wesley, Reading, Mass.
15. Ilyin I., Rosovskaya O., Tranikov O., Aas W., Hettelingh J.P., and Reinds G.J. Heavy metals: transboundary pollution of the environment. EMEP Status Report 2/2008 (Joint MSC-E & CCC & CCE Report). Convention on Long-range Transboundary Air Pollution (2008)
16. Hunter A., Kennedy L., Henry J., and Ferguson R.I. Application of neural networks and sensitivity analysis to improve prediction of trauma survival. Comput. Meth. Prog. Bio. 62 (2000) 11-19
17. Ingwersen, J., 2001. The environmental fate of cadmium in the soils of the waste water irrigation area of Braunschweig - measurement, modeling and assessment. Ph.D. thesis, Technischen Universität Carolo-Wilhelmina, Germany.
18. Ingwersen J., and Streck T. Modeling the environmental fate of cadmium in a large wastewater irrigation area. J. Environ. Qual. 35 (2006) 1702-1714
19. Jacobson A.R., McBride M.B., Baveye P., and Steenhuis T.S. Environmental factors determining the trace-level sorption of silver and thallium to soils. Sci. Total Environ. 345 (2005) 191-205
20. Koekkoek E.J.W., and Booltink H. Neural networks models to predict soil water retention. Eur. J. Soil Sci. 50 (1999) 489-495
21. Kookana R.S., and Naidu R. Effect of soil solution composition on cadmium transport through variable charge soil. Geoderma 84 (1998) 235-248
22. Lilliefors H.W. On the Kolmogorov-Smirnov test for normality with mean and variance unknown. J. Am. Stat. Assoc. 62 (1967) 399-402
23. Loague K., and Green R.E. Statistical and graphical methods for evaluating solute transport models: overview and application. J. Contam. Hydrol. 7 (1991) 51-73
24. Long D.T. Geochemical behavior of chromium/water-sediment systems. Preliminary Report, EPA Grant no. R808306010 (1983), Mich State Univ., East Lansing, MI
25. McBratney A.B., Cattle S.R., and Vervoort R.W. From pedotransfer functions to soil inference system. Geoderma 109 (2002) 41-73
26. McBratney A.B., Mendoca Santos M.L., and Minasny B. On digital soil mapping. Geoderma 117 (2003) 3-52
27. Minasny B., and McBratney A.B. The Neuro-m method for neural network parametric pedotransfer functions. Soil Sci. Soc. Am. J. 66 (2002) 352-361
28. Minasny B., Hopmans J.W., Harter T., Eching S.O., Tuli A., and Denton M.A. Neural networks prediction of soil hydraulic functions for alluvial soils using multistep outflow data. Soil Sci. Soc. Am. J. 68 (2004) 417-429
29. Moor C., Lymberopoulou T., and Dietrich V.J. Determination of heavy metals in soil, sediments and geological materials by ICP-AES and ICP-MS. Microchim. Acta 136 (2001) 123
30. Morshed J., and Kaluarachchi J.J. Parameter estimation using artificial neural network and genetic algorithm for free-product migration and recovery. Water Resour. Res. 34 5 (1998) 1101-1113
31. Oertel A.C. Relationship between trace-element concentrations in soil and parent material. J. Soil Sci. 12 (1961) 119-128
32. Persson M., Sivakumar B., Berndtsson R., Jacobson O.H., and Schjonning P. Predicting the diaelectric constant water content relationship using artificial neural networks. Soil Sci. Soc. Am. J. 66 (2002) 1424-1429
33. Reinds G.J., Bril J., De Vries W., Groenenberg J.E., and Breeuwsma A. Critical loads and excess loads of cadmium, copper and lead for European forest soils. DLO Winand Staring Centre Report 96, Wageningen, The Netherlands (1995)
34. Rieuwerts J.S., Thornton I., Farago M.E., and Ashmore M.R. Factors influencing metal bioavailability in soils: preliminary investigations for the development of critical loads approach for metals. Chem. Spec. Bioavailab. 10 2 (1998) 61-75
35. Römkens P.F.A.M., and Salomons W. Cd, Cu and Zn solubility in arable and forest soils: consequences of land use changes for metal mobility and risk assessment. Soil Sci. 163 (1998) 859-871
36. Schaap M.G., and Bouten W. Modelling water retention curves of sandy soils using neural networks. Water Resour. Res. 32 10 (1996) 3033-3040
37. Schaap M.G., Leij F.J., and van Genuchten M.T. Neural networks analysis for hierarchical prediction of soil hydraulic properties. Soil Sci. Soc. Am. J. 62 (1998) 847-855
38. Schug B., Düring R.-A., and Gäth S. Improved cadmium sorption isotherms by the determination of initial contents using the radioisotope 109 Cd. J. Plant Nutr. Soil Sci. 163 (2000) 197-202
39. Southard A.R., and Miller R.W. Parent material-clay relations in some northern Utah soils. Technical Paper 439 (1965), Utah agr. Exp. Sta., Logan
40. Springob G., and Böttcher J. Parameterization and regionalization of Cd sorption characteristics of sandy soils. I. Freundlich type parameters. J. Plant Nutr. Soil Sci. 161 (1998) 689-696
41. Springob G., and Böttcher J. Parameterization and regionalization of Cd sorption characteristics of sandy soils. II. Regionalization: Freundlich k estimates by pedotransfer functions. J. Plant Nutr. Soil Sci. 161 (1998) 689-696
42. Streck T., and Richter J. Heavy metal displacement in a sandy soil at the field scale: I. Measurements and parameterization of sorption. J. Environ. Qual. 26 (1997) 49-56
43. Streck T., and Richter J. Heavy metal displacement in a sandy soil at the field scale: II. Modeling. J. Environ. Qual. 26 (1997) 56-62
44. Thanabalasingam P., and Pickering W.F. Specific sorption of Antimony (III) by the hydroxides of Mn, Fe and Al. Water Air Soil Poll. 49 (1990) 175-185
45. Tiktak A., Alkemade J.R.M., Van Grinsven J.J.M., and Makaske G.B. Modeling cadmium accumulation at a regional scale in the Netherlands. Nutr, Cycl. Agroecosys. 50 (1998) 209-222
46. Turkey J.W. Exploratory Data Analysis (1977), Reading, M.A, Addison-Wesley
47. Utermann J., Meyenburg G., Altfelder S., Gäbler H., Duijnisveld W., Bahr A., and Streck T. Entwicklung eines Verfahrens zur Quantifizierung von Stoffkonzentrationen im Sickerwasser auf der Grundlage chemischer und physikalischer Pedotransferfunktionen. Final report. BMBF Forschungsvorhaben 02WP0206 (2005)
48. van der Zee S.E.A.T.M., and van Riemsdijk W.H. Transport of reactive solute in spatially variable soil systems. Water Resour. Res. 23 (1987) 2059-2069
49. Vidal M., Santos M.J., Abrao T., Rodriguez J., and Rigol A. Modelling competitive metal sorption in a mineral soil. Geoderma 149 (2009) 189-198
50. Wilkens B.J., Brummel N., and Loch J.P.G. Influence of pH and zinc concentration on cadmium sorption in acid, sandy soils. Water Air Soil Poll. 101 (1998) 349-362
51. Wösten J.H.M., Finke P.A., and Jansen M.J.W. Comparison of class and continuous pedotransfer functions to generate soil hydraulic characteristics. Geoderma 66 (1995) 227-237