Arslan, H. (2012). Spatial and temporal mapping of groundwater salinity using ordinary kriging and indicator kriging: The case of Bafra Plain, Turkey. Agric Water Manag 113: 57–63.
Babu, B.S. (2016.) Comparative Study on the Spatial Interpolation Techniques in GIS. International Journal of Scientific & Engineering Research, Volume 7, Issue 2. ISSN 2229-5518.
Bahrami Jovein, E. and Hosseini, S.M. (2015). A Systematic Comparison of Geostatistical Methods for Estimation of Groundwater Salinity in Desert Areas Case Study: Feyz Abad-Mahvelat Plain. Iran-Water Resources Research, Volu- me 11, No 2 (In Persian).
Barca, E. and Passarella, G. (2007). Spatial evaluation of the risk of groundwater quality degradation. A comparison bet- ween disjunctive kriging and geostatist- ical simulation. Environ Monit Assess 137: 261–273.
Chiu, C., lin, P. and Lu, K. (2009). GIS-based Tests for Qual- ity Control of Meteorological Data and Spatial Inter- polation of Climate Data. Mountain Research and Development 29(4): 339–349.
Dowd, P.A. (1982). Lognormal kriging: the general case. Math. Geol 14(5): 474–500.
Duffy, D.J. and Germani, A. (2013). C# for Financial Markets, Chapter 13: Inte- rpolation Methods in Interest Rate App- lications. The Wiley Finance Series, 97 8-0-470-03008-0, 856p.
Gol, C., Bulut, S. and Bolat, F. (2017). Co- mparison of different interpolation met- hods for spatial distribution of soil orga- nic carbon and some soil properties in the Black Sea backward region of Turk- ey. Journal of African Earth Sciences 134: 85–91.
Gong, G., Mattevada, S. and O’Bryant, SE. (2014). Comparison of the accuracy of kriging and IDW interpolations in esti- mating groundwater arsenic concentrat- ions in Texas. Environ Res 130: 59–69.
Hua, Z., Debai, M. and Cheng, W. (2009). Optimization of the spatial interpolation for groundwater depth in Shule River Basin. Environmental Science and Info- rmation Application Technology.
Isaaks, E. H. and Serivastava, R. M. (1989) . An introduction to applied geostatistic- s. Oxford University Press, 561p.
Joseph, J., Sharif, HO., Sunil, T. and Ala- mgir, H. (2013). Application of validati- on data for assessing spatial interpolati- on methods for 8-h ozone or other spar- sely monitored constituents. Environ Pollut 178 :411–418.
Keblouti, M., Ouerdachi, L. and Boutagha- ne, H. (2012). Spatial interpolation of annual precipitation in Annaba-Algeria-comparison and evaluation of methods. Energy Procedia 18: 468–475.
Khattak, A., Ahmed, N., Hussein, I., Qazi, A., Alikhan, S., Rehman, A. and Iqbal, N. (2014). Spatial distribution of salinit- y in shallow Groundwater used for crop irrigation. Pak. J. Bot 46(2): 531–537.
Kravchenko, A.K. and Bullock, D.G. (1999). A comparative study of interpolat- ion methods for mapping soil properties. Agronomy Journal 91: 393–400.
Krivoruchko, K. (2011). Spatial Statistical Data Analysis for GIS Users. Esri Press, Redlands, CA, 928p.
Lee, J.J., Jang, C.S., Wang, S.W. and Liu, C.W. (2007). Evaluation of potential health risk of arsenic-affected ground- water using indicator kriging and dose response model. Sci Total Environ 384: 151–162.
Liu, C.W., Jang, C.S. and Liao, C.M. (2004). Evaluation of arseic contaminat- ion potential using indicator kriging in the Yun-Lin aquifer (Taiwan). Sci Total Environ 321: 173–188.
Martinez-Cob, A. (1996). Multivariate ge- ostatistical analysis of evapotranspirati- on and precipitation in mountainous ter- rain. J Hydrol 174: 19–35.
Mirzaei, R. and Sakizadeh, M. (2015). Comparison of interp- olation methods for the estimation of groundwater conta- mination in Andimeshk-Shush Plain, Southwest of Iran. Environ Sci Pollut Res 23: 2758–2769.
Moyeed, R.A. and Papritz, A. (2002). An empirical comparison of kriging metho- ds for nonlinear spatial point prediction. Mathematical Geology 34(4): 365–386.
Njeban, H.S. (2018). Comparison and Evaluation of GIS-Based Spatial Interp- olation Methods for Estimation Ground- water Level in AL-Salman District- Southwest Iraq. Journal of Geographic Information System 10: 362–380.
Plouffe, C.C.F., Robertson, C. and Chandr- apala, L. (2015). Comparing interpolati- on techniques for monthly rainfall ma- pping using multiple evaluation criteria and auxiliary data sources: A case study of Sri Lanka. EnvironModel Softw 65: 57–71.
Rhoades, J.D.,
Chanduvi, F. and
Lesch, S. (1999). Soil salinity assessment: meth- ods and interpretations of electrical con- ductivity measurements. FAO irrigation and drainage paper No. 57, Food and Agriculutre Organization of the United Nations: Rome, Italy, 165p.
Rufo, M., Antolín, A., Paniagua, J.M. and Jiménez, A. (2018). Optimization and comparison of three spatial interpolatio- n methods for electromagnetic levels in the AM band within an urban area. Env- ironmental Research 162: 219–225.
Salekin, S., Burgess, J.H., Morgenroth, J., Mason, E.G. and Meason, D.F. (2018). A Comparative Study of Three Non-Geostatistical Methods for Optimising Digital Elevation Model Interpolation. International Journal of Geo-Informati- on 7(8): 300.
Schloeder, C.A., Zimmerman, N.E. and Jacobs, M.J. (2001). Comparison of methods for interpolating soil propert- ies using limited data. Soil Science Soc- iety of Ameri- can Journal 65: 470–479.
Szypuła, B. (2016). Geomorphometric co- mparison of DEMs built by different interpolation methods. Landform Anal- ysis, 32: 45–58.
Wang, X., ang, Y., Cao, Z., Zou, W., Wang, L., Yu, G., Yu, B. and Zhang, J. (2013). Comparison Study on Linear In- terpolation and Cubic B-Spline Interpo- lation Proper Orthogonal Decompositi- on Methods. Advances in Mechanical Engineering, Article ID 561875.
Yao, L., Huo, Z., Feng, S., Mao, M., Kang, S., Chen, J., Xu, J. and Steenhuis, T. S. (2014). Evaluation of spatial interpolati- ion methods for groundwater level in an arid inland oasis, northwest China. Env- ironmental Earth Sciences 71:1911–1924.
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