The use of the GIS Kriging technique to determine the spatial changes of natural radionuclide concentrations in soil and forest cover
© Dindaroğlu; licensee BioMed Central Ltd. 2014
Received: 27 March 2014
Accepted: 16 October 2014
Published: 25 October 2014
The distribution of radionuclides occurring naturally in the earth depends on bedrock characteristics. Therefore, the spatial distribution of radionuclides is not uniform. Consequently, radionuclide information is vitally important in determining and monitoring the spatial variation of the radionuclide concentrations that are over the limits for the sustainable environment and human health.
This research was carried out using GIS methods and geostatistical analysis as Kriging techniques to reveal the spatial variation of the 226Ra, 232Th and 40 K concentrations of natural radionuclides in the Çoruh and Aras Basin. The spatial variations of the detected radionuclides were correlated with soil groups and forest cover.
In the study area, 43.17% of the concentration of 40 K, 26.67% of the concentration of 226Ra and 28.16% of the 232Th concentration was determined to be over the average limits. Concentrations of radionuclides that are over the average limits have been found to be on basalt and chestnut soils. Brown and reddish brown soils have a low concentration of the spatial distribution of the radionuclides. Statistically positive correlations were detected (0.865 **) between the 226Ra and 232Th. In addition, a positive relationship between forest cover and 226Ra and a negative relationship between 232Th and 40 K were identified.
Excessive exposure to radiation may cause cancer and hereditary diseases. Ecological environments include the soil and the plants. Hence, the periodical monitoring of the spatial variation in concentrations of radionuclides is very important for the health of future generations.
KeywordsNatural radionuclide Kriging technique Soil Forest cover
Radioactive features have existed in our world since its formation. High concentrations of natural radionuclides are found in volcanic, phosphate, granite and salt rock. Rain and other water discharge crumble these rocks into very small pieces and mixes them into the groundwater. Thus, rocks increase the natural radioactivity of the soil.
The direction of the movement and the speed of the radionuclides in the soil depends on natural processes (e.g., soil structure, content of the plant species, irrigation conditions, weather conditions and accumulation) ,. In some areas, the natural radionuclide concentrations are above the established limits according to UNSCEAR. If the concentration of natural radioactive elements goes over the average limits, there can be negative effects on human health . Therefore, the spatial distribution of the concentrations of natural radionuclides in the soil has to be determined. It is possible to use CBS and geostatistical analysis to obtain these values.
Geostatistical techniques are a useful component of GIS applications that are frequently applied. Geostatistics involves the analysis and estimation techniques used to obtain the value of a variable dispersed in time and location.
Kriging is one of the best and most widely-known techniques used in spatial linear predictions. Kriging methods have different flexible forms, according to the survey area and data -. Kriging can also reveal the reliability of the estimated surface ,.
Geostatistical methods also allow for examining a relationship with spatial variations of radionuclides between forest cover and soil groups. Radioactive elements in the soil do not indicate a uniform distribution in the earth. Therefore, the concentrations of radionuclides should be checked regularly as an important step in protection from the negative effects of radioactivity -.
Radionuclide concentrations may be caused by the high amount of organic matter in the soil. As such, radionuclides can be absorbed by the forest soil ,. Some radionuclide compounds build up in the humic acids in the soil organic layer ,.
Measuring the radioactivity concentration in the soil, as well as the concentrations in the plants and the water, is necessary to estimate the concentrations of radionuclides ,. This study used 226Ra, 232Th and 40 K concentration values measured periodically by TAEK . Spatial distributions were determined according to UNSCEAR (2000) , who used a kriging technique in the Çoruh and Aras Basin and the surrounding areas. The statistical relationships between the spatial variations, forest cover and soil groups were analyzed.
Materials and methods
Sampling methods and analysis
Concentrations of radioactive elements (226Ra, 232Th and 40 K) for determining soil sampling were carried out by the provincial offices of the Ministry of Environment and Urbanization. Surface soil sampling was conducted at 46 points. The concentration of radioactivity in the surface soil samples was determined by the Atomic Research Council of Turkey .
Natural radioactivity the concentration range and average values
Natural radionuclides (Bq/kg)
To conduct the geostatistical analysis, the "Kriging" interpolation technique was used within the spatial analyst extension module in ArcGIS 9.3 software. The spatial analyses were carried out with prepared maps using this technique. Concentrations of 226Ra, 232Th and 40 K were determined for the distribution area. The experimental variogram model was constructed using the Kriging method, with data obtained from the research area. The spatial transformation was performed to determine the most appropriate model to use with the parameters of the generated maps.
Z(si) is the measured value at the location (i th),
λi is the unknown weight for the measured value at the location (i th) and
s0 is the estimation location.
The unknown weight (λp) depends on the distance to the location of the prediction and the spatial relationships among the measured values.
The Kriging interpolation technique is made possible by transferring data into the GIS environment. In this way, analysis in areas that have no data can be conducted. The following criteria were used to evaluate the model: the average error (ME) must be close to 0 and the square root of the estimated error of the mean standardized (RMSS) must be close to 1 . While implementing the models, the anisotropy effect was surveyed.
Results and discussion
Anisotropic variogram models were preferred. The 226Ra, 232Th and 40 K concentration values showed a directional change. The spatial dependencies (Nugget/Sill ratio) were found to be related to the degree of autocorrelation between the sampling points. If the spatial dependence was higher between the sample points, the spatial correlation was very high. The spatially dependent variables were classified as: strongly spatially dependent if the ratio was ≤25%, mid-spatial-dependent if the ratio was 25% - 75% and weakly spatially dependent if the ration was ≥75% ,-.
Sill, (Co + C)
0.2695 x +18.32
0.5063 x +15.33
0.1596 x +381.99
The sample point data will involve converting the spatial data of the 226Ra, 232Th and 40 K concentrations used in the interpolation for kriging. The lowest error rate models were chosen; they were the “Exponential” and “Stable” models. The maps were produced and field data were obtained in accordance with this kriging model.
Spatial distribution of 226Ra:
The prediction map, according to the optimized model, was determined during the cross-validation process. The 226Ra concentration prediction map shows the log 226Ra. The dataset for the 226Ra concentration has a high kurtosis and is positively skewed, so it is not a normal distribution. The data log transformation was applied to be closer to a normal distribution. After the log transformation was conducted, the 226Ra concentrations were found to be approximately normally distributed.
Spatial distribution of 232Th
Spatial distribution of 40 K
The relationship between forest cover and natural radionuclides
Correlations test result between radionuclides and forest cover
Spatial changes of great soil groups and radionuclides in the soil
Spatial changes between radionuclides and great soil groups
Spatial changes of the radionuclides concentration (Hectare)
Great soil goups
Under optimal concentrations (<400 Bg/kg)
Upper optimal concentrations (>400 Bg/kg)
Under optimal concentrations (<35 Bg/kg)
Upper optimal concentrations (>35 Bg/kg)
Under optimal concentrations (<45 Bg/kg)
Upper optimal concentrations (>45 Bg/kg)
Limeless Brownish Soils
Limeless Brown Forest Soils
Brown Forest Soils
High Mountain Soils
Reddish Yellow Podsol Soils
Reddish Brown Soils
Brown soils, High Mountain soils, Reddish Brown soils and Reddish Yellow Podsol soils in areas containing high concentrations of 226Ra and 232Th radionuclides had no spatial distribution pattern. In areas with Brown soils and Reddish Brown soils, high concentrations of 40 K radionuclides had no spatial distribution pattern (Table 4).
In summary, changes in the concentrations of radionuclides in the soil depend on the formation of iron oxide and other elements. Some of the acids formed in the soil, through calcium carbonate found in the environment, prevent the retention of the radionuclides. Therefore, radionuclide concentrations in the rocks can be reduced with calcium carbonate; this, in turn, reduces the level of external radiation ,. According to the Anonymous , some rocks and a soil type typical of the specific radioactivity values was identified in the follow: For 40 K; Granite (1000 Bq/kg), clay stone (700 Bq/kg), Sandstone (350 Bq/kg) Basalt (250 Bq/kg) and limestone (90 Bq/kg). For 232Th; Granite (80 Bq/kg), clay stone (50 Bq/kg), Sandstone (10 Bq/kg), Basalt (10 Bq/kg) and Limestone (7 Bq/kg). Local distribution values can vary greatly according to changing areas ,.
Over time, the infiltration of radionuclides has resulted in high radionuclide concentrations in the lower soil layers. The radionuclides in these lower soil layers can move upwards through the roots of plants and be transferred to the plant during the growth process. Since radionuclides can have detrimental health effects on humans, it is important to determine the spatial variation of concentrations of radioactive elements.
This research was conducted to examine to spatial distribution of natural radioactive element (226Ra, 232Th and 40 K) concentrations and their relationship with soil groups and forest cover using the Kriging method. According to the statistical analyses, positive correlations were detected between the 226Ra and the 232Th (0.865**), as well as between the 40 K and 232Th (0.718*). Negative correlations between forest cover and 226Ra were found, while positive correlations between 232Th and 40 K were detected.
The basalt and chestnut soils in the study area were found to have above average concentrations of radionuclides. The Brown soils, High Mountain soils, Reddish Brown soils and Reddish Yellow Podsol soils did not have high concentrations of 226Ra and 232Th. The Brown soils and the Reddish Brown soils also did not have high concentrations of 40 K.
Radionuclides are present in different concentrations in the soil, plants and water, which comprise parts of the basic food chain. Excessive exposure to radiation can lead to cancer; it is also the cause of hereditary diseases. Therefore, spatial variations of radioactive element concentrations need to be monitoring for the sustainability of a healthy environment.
Authors present their great thanks to Turkey Atomic Energy Agency for data supply.
- Theodorsson P: Measurements of Weak Radioactivity. World Scientific Pub. Co, Singapore; 1997.Google Scholar
- TAEK: Resource of natural radiation. Accessed on: 11.03.2014., [http://www.taek.gov.tr/bilgi-kosesi/184-radyasyon-insan-ve-cevre/radyasyonla-birlikte-yasiyoruz/501-dogal-radyasyon-kaynaklari.html]
- UNSCEAR: Report on sources and effects of ionizing radiation to the general assembly, United Nations, Vienna. 2000, Accessed on: 25.02.2014., [http://www.unscear.org/unscear/en/publications/2000_1.html]
- Robertson GP: Geostatistics in ecology: interpolation with known variance. Ecology 1987, 68: 744–748. 10.2307/1938482View ArticleGoogle Scholar
- Cressie NAC: Statistics for Spatial Data. John Wiley and Sons, Inc, Canada; 1993.Google Scholar
- Goovaerts P: Geostatistics for Natural Resources Evaluation. Oxford University Press, New York; 1997.Google Scholar
- Ecker MD: Geostatistics: Past, Present and Future, Encyclopedia of Life Support Systems (EOLSS), Developed under the Auspices of the UNESCO. Eolss Publishers, Oxford, UK; 2004.Google Scholar
- Isaaks EH, Srivastava RM: An Introduction to Applied Geostatistics. Oxford University Press, New York; 1989.Google Scholar
- Brown RB, Huddleston JH: Presentation of statistics data on Map units to the user. In spatial variabilities of soil and landform. SSSA Special 1991, 28: 127–147.Google Scholar
- Khan HM, Khan K, Atta MA, Jan F: Measurement of gamma activity of soil samples of Charsadda district of Pakistan. J Chem Soc Pakistan 1994, 16: 183–188.Google Scholar
- Rühm W, Kammerer L, Hiersche L, Wirth E: Migration of 137Cs and 134Cs in different forest soil layers. J Environ Radioact 1996, 33: 63–75. 10.1016/0265-931X(95)00069-MView ArticleGoogle Scholar
- Rosén K, Öborn I, Lönsjö H: Migration of radiocaesium in Swedish soil profiles after the Chernobyl accident, 1987-1995. J Environ Radioact 1999, 46: 45–66. 10.1016/S0265-931X(99)00040-5View ArticleGoogle Scholar
- Bergman R: The distribution of radioactive caesium in boreal forest ecosystems. In Nordic Radioecology, the Transfer of Radionuclides through Nordic Ecosystems to Man. Studies in Environmental Science 1994, 62: 335–379. (ed. H. Dahlgaard) Elsevier, New York, NY 10.1016/S0166-1116(08)71718-7View ArticleGoogle Scholar
- Gorham E: A comparison of natural and fallout radioactivity in Ontario soils under pine. Can J Bot 1963, 4: 11309–11319. USAGoogle Scholar
- Degering D, Schlenker S, Unterricker S: Radionuclide Behaviour in Natural Organic Matter (Peat, Cola and Forest Soil Surfaces). Paul Scherrer Institut, Pontresina, Switzerland; 2000.Google Scholar
- Sokolik GA, Ivanova TG, Leinova SL, Ovsiannikova SV, Kimlenko IM: Migration ability of radionuclides in soil-vegetative cover of Belarus after Chernobyl accident. Environ Int 2001, 26: 183–187. 10.1016/S0160-4120(00)00104-5View ArticleGoogle Scholar
- UNSCEAR: Sources and Effects of Ionizing Radiation, Report of the General Assembly With Scientific Annex B. United Nations Publicaitons, New York; 1993.Google Scholar
- Hölgye Z, Malý M: Sources, vertical distribution, and migration rates of 239, 240 Pu, 238 Pu, and 137 Cs in grassland soil in three localities of central Bohemia. J Environ Radioact 2000, 47: 135–147. 10.1016/S0265-931X(99)00036-3View ArticleGoogle Scholar
- TAEK: Turkey Atomic Energy Agency: Turkey Atlas of Environmental Radioactivity. Ankara: 2014. Accessed on: 26.03.2014., [http://www.taek.gov.tr/radyasyon-izleme/turkiye-cevresel-radyasyon-atlasi.html]
- OGM: Forest Cover Map. OGM Publications, Ankara; 2012.Google Scholar
- ESRİ: The principels of geostatistical analysis. 2013, 54. 22.02.2014., [http://maps.unomaha.edu/Peterson/gisII/ESRImanuals/Ch3_Principles.pdf]
- Johnston K, Hoef M, Krivoruchko K, Lucas N: Using ArcGIS Geostatistical Analyst. ESRI, New York; 2001.Google Scholar
- Clark I: Practical Geostatistics. Applied Science Publishers Ltd., London; 1979.Google Scholar
- Trangmar BB, Yost RS, Uehara G: Application of geostatic to spatial studies of soil properties. Advances in Argon 1985, 38: 45–94.Google Scholar
- Cambardella CA, Moorman TB, Novak JM, Parkin TB, Karlen DL, Turco RF, Konopka AE: Field-scale variability soil properties in Central Iowa soils. Soil Sci Soc Am J 1994, 58: 1501–1511. 10.2136/sssaj1994.03615995005800050033xView ArticleGoogle Scholar
- Erşahin S: Alluvial soil in a field, some physical and chemical properties of the spatial variability of the determination. SU Journal of the Faculty of Agriculture 1999, 13: 34–41.Google Scholar
- Chelmicki V, Mietelski JW, Macharski P, Swicchowicz J: Natural Factors of Cs-137 Rcdistribution in Soil. Institute of Nuclear Physics Cracow, Report No. 1615lD, Poland; 1993.Google Scholar
- NCRP: National Council on Radiation Protection and Measurements. 1975.Google Scholar
- Özger AG: District of Ceyhan, Yumurtal K and Pozantı Determination of Natural Radioactivity Levels. In M.Sc. Thesis. Graduate School of Science, Çukurova University; 2005.Google Scholar
- Anonymous: Federal Ministry for the Environment, Nature Conservation and Nuclear Safety, environmental radioactivity and radiation exposure, Annual Report, Bonn. 1995.Google Scholar
- Atakan Y: Natural radioactivity, natural and human created in the radiation doses. 2008.Google Scholar
- Vukašinović I, Đorđević A, Rajković M, Todorović D, Pavlović V: Distribution of natural radionuclides in anthrosol-type soil. Turk J Agric 2010, 34: 539–546.Google Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.