Cumulative Ordinary Kriging interpolation model to forecast radioactive fallout, and its application to Chernobyl and Fukushima assessment: a new method and mini review

Külahcı F., Şen Z.

Environmental Science and Pollution Research, vol.29, no.43, pp.64298-64311, 2022 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Review
  • Volume: 29 Issue: 43
  • Publication Date: 2022
  • Doi Number: 10.1007/s11356-022-21921-4
  • Journal Name: Environmental Science and Pollution Research
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, ABI/INFORM, Aerospace Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, EMBASE, Environment Index, Geobase, MEDLINE, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Page Numbers: pp.64298-64311
  • Keywords: Model, Radioactive fallout, Spatial analysis, Interpolation, Weighting methods
  • Istanbul Medipol University Affiliated: Yes


The Cumulative Ordinary Kriging (COK) interpolation method has been proposed for the spatial prediction of atmospheric radioactive fallout in any given region. COK is built on the Ordinary Kriging and Cumulative Semivariogram methods and combines all their advantages to achieve statistically significant results. It is verified in this paper the reliability of the results from COK with other well-known Modified Shepard’s Method (MSM), Inverse Distance Square (INDSQ), Polynomial Regression (PR), Natural Neighbour (NN), Radial Basis (RB), and Kriging Method interpolation methods. The model is tested in detail and in every possible way in two and three dimensions and applied to real-time Cs-134 and Cs-137 radioactive fallout data from the Chernobyl and Fukushima reactor accidents by combining both experimental and theoretical results. The results obtained from the applications for all interpolation methods are included in the supplementary materials section at the end of the article for the benefit of the readers. COK can also be used for spatial modelling of any particle at micro or macro scale. It can contribute significantly to environmental quality, ecological, and human health.