A Comparison of Some Interpolation Techniques for Determining Spatial Distribution of Nitrogen Compounds in Groundwater
Tóm tắt
Từ khóa
Tài liệu tham khảo
Bernard-Jannin L, Sun X, Teissier S et al (2017) Spatio-temporal analysis of factors controlling nitrate dynamics and potential denitrification hot spots and hot moments in groundwater of an alluvial floodplain. Ecol Eng 103:372–384. https://doi.org/10.1016/j.ecoleng.2015.12.031
Boesch DF, Brinsfield RB, Magnien RE (2001) Chesapeake Bay eutrophication: scientific understanding, ecosystem restoration, and challenges for agriculture. J Environ Qual 30:303–320
Duchon J (1977) Splines minimizing rotation-invariant semi-norms in Sobolev spaces. Springer, Berlin, pp 85–100
Franke R, Nielson G (1980) Smooth interpolation of large sets of scattered data. Int J Numer Methods Eng 15:1691–1704. https://doi.org/10.1002/nme.1620151110
Golden Software LLC (2018) Surfer®16. Golden, Colorado. www.goldensoftware.com
Hardy RL (1971) Multiquadric equations of topography and other irregular surfaces. J Geophys Res 76:1905–1915. https://doi.org/10.1029/JB076i008p01905
Hardy RL (1990) Theory and applications of the multiquadric-biharmonic method. Comput Math Appl 19:163–208. https://doi.org/10.1016/0898-1221(90)90272-L
Hong N, White JG, Weisz R et al (2007) Groundwater nitrate spatial and temporal patterns and correlations. Vadose Zone J 6:53. https://doi.org/10.2136/vzj2006.0065
Isaaks EH, Srivastava RM (1989) An introduction to applied geostatistics. Oxford University Press, Oxford
Kazemi E, Karyab H, Emamjome M-M (2017) Optimization of interpolation method for nitrate pollution in groundwater and assessing vulnerability with IPNOA and IPNOC method in Qazvin plain. J Environ Health Sci Eng 15:23. https://doi.org/10.1186/s40201-017-0287-x
Kennedy CD, Genereux DP, Corbett DR, Mitasova H (2009) Spatial and temporal dynamics of coupled groundwater and nitrogen fluxes through a streambed in an agricultural watershed. Water Resour Res. https://doi.org/10.1029/2008wr007397
Li J (2016) Assessing spatial predictive models in the environmental sciences: accuracy measures, data variation and variance explained. Environ Model Softw 80:1–8. https://doi.org/10.1016/J.ENVSOFT.2016.02.004
Li J, Heap AD (2011) A review of comparative studies of spatial interpolation methods in environmental sciences: performance and impact factors. Ecol Inform 6:228–241. https://doi.org/10.1016/J.ECOINF.2010.12.003
Ohmer M, Liesch T, Goeppert N, Goldscheider N (2017) On the optimal selection of interpolation methods for groundwater contouring: an example of propagation of uncertainty regarding inter-aquifer exchange. Adv Water Resour 109:121–132. https://doi.org/10.1016/j.advwatres.2017.08.016
Orlik T, Jóźwiakowski K, Marzec M (2005) The role of grassland in reducing surface pollution from agriculture in a hilly terrain (in Polish). Acta Agrophys 5:93–101
R Core Team (2018) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.r-project.org/
Rocha H (2009) On the selection of the most adequate radial basis function. Appl Math Model 33:1573–1583
Shepard D (1968) A two-dimensional interpolation for irregularly-spaced data function. In: Proceedings of the 1968 ACM national conference. New York, USA, pp 517–523
Spalding RF, Exner ME (1993) Occurrence of nitrate in groundwater—a review. J Environ Qual 22:392–402. https://doi.org/10.2134/jeq1993.00472425002200030002x
Wackernagel H (2003) Multivariate geostatistics. An introduction with applications, 3rd edn. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-05294-5_1
Willmott CJ (1981) On the validation of models. Phys Geogr 2:184–194. https://doi.org/10.1080/02723646.1981.10642213