Analiza przestrzenna zawartości miedzi w środowisku gruntowo-wodnym Legnicko-Głogowskiego Okręgu Miedziowego

• Autorzy: Namysłowska-Wilczyńska B. , Pyra J.

Warianty tytułu

EN

Spatial analysis of copper content in soil-water environment of Legnica-Głogów copper district

• Języki publikacji: PL

Abstrakty

EN

The paper presents the results of the application of geostatistical methods to the spatial analysis of the variation of Cu content in the soil-water environment of the Legnica-Głogów Copper District . an industrial area with the predominance of copper ore mining and smelting in the industrial mix. Semivariogram function analysis, ordinary kriging and kriging with external drift, were used to analyse the environmental conditions. The comprehensive set of soil Cu content data was characterized by a large number of samples (n = 908) uniformly covering the area of LGCD. The data were the determinations of the Cu content in the near-surface layer of soil. The empirical Cu content semivariograms were approximated by the spherical model, the exponential model and the linear model combined with the nugget effect. Cu content averages Z were estimated at 6120 nodes of an elementary grid using ordinary (point) kriging. The elementary field dimensions were 1km´1km. The data sets for underground waters were based on a much smaller sample size (n = 31). The information, on Cu content, was collected from a network of piezometers and wells irregularly located over the analysed area. Similarly as for soil, semivariograms were computed for the Cu content in underground waters. Then the semivariograms were approximated by the spherical model and the linear model with the nugget effect. Taking into account the parameters values of the theoretical models fitted to the semivariograms, averages Z of the Cu content in the waters at 6120 nodes of the same elementary grid as the one adopted for soil were estimated using ordinary kriging. Then kriging with external drift was applied to estimate underground waters Cu content averages Z*. The data from the preceding ordinary kriging computations, i.e. estimated averages Z of the Cu content in the surface layer of soil, were used. The raster maps of the distributions of averages Z, i.e. the kriged estimates of soil contamination with Cu, constituted the background (external drift) used for the more accurate computation of underground waters Cu content averages Z The detailed analysis of the different factors which affect the spatial distribution of the elements content in the environment, such as the geological structure of the subsoil and the surface formations, the environment.s pH, the atmospheric factors and the effects of the mining and smelting operations, made it possible to determine more precisely the genesis of the analysed elements content in the natural environment and to classify it as pollution or natural geochemical enrichments.

Słowa kluczowe

PL

zawartość miedzi; geostatystyka; wody podziemne

EN

copper grade; geostatistics; undrground water

• Wydawca: Polskie Towarzystwo Informacji Przestrzennej
• Czasopismo: Roczniki Geomatyki
• Rocznik: 2005
• Tom: T. 3, z. 4
• Strony: 137--147
• Opis fizyczny: Bibliogr. 14 poz.

Twórcy

autor

Namysłowska-Wilczyńska B.

autor

Pyra J.

• Instytut Geotechniki i Hydrotechniki Politechniki Wrocławskiej,

Bibliografia

• 1. Goovaerts P., Webster R., 1994: Scale-dependent correlation between topsoil copper and cobalt concentrationsin Scotland. European Journal of Soil Science 45, March, p. 79-95.
• 2. Huczyński B., 1983: Warunki przyrodnicze produkcji rolnej, woj. legnickie. Instytut Uprawy, Nawożenia I Gleboznawstwa, Puławy.
• 3. ISATIS Software Manual 3rd Edition. Geovariances and Ecole des Mines de Paris, Avon Cedex, France, November 2001.
• 4. Kabata-Pendias A., 1995: Podstawy oceny chemicznego zanieczyszczenia gleb. Państwowa Inspekcja Ochrony Środowiska Warszawa, Instytut Uprawy, Nawożenia i Gleboznawstwa, Puławy.
• 5. Mucha J., 1994: Metody geostatystyczne w dokumentowaniu złóż. Wydawnictwo AGH, Kraków, s. 155.
• 6. Mucha J., 2001: Bariery i ograniczenia geostatystycznej oceny parametrów złożowych. Kwartalnik AGH Geologia, t. 27, z. 2-4, Kraków, s.641-657.
• 7. Mucha J., 2002: Struktura zmienności zawartości Zn i Pb w Śląsko-krakowskich złożach rud Zn-Pb. Wydawnictwo Instytutu Gospodarki Surowcami Mineralnymi i Energią PAN, Kraków, s. 146.
• 8. Namysłowska-Wilczyńska B., Pyra J., 2002: Ocena stanu zanieczyszczenia gruntów i wód podziemnych LGOM miedzią i cynkiem na podstawie integracji danych srodowiskowych. IV Forum Inżynierii Ekologicznej .Ekotechnologie XXI Wieku., Konferencja Krajowa 2002, Nałęczów.
• 9. Namysłowska-Wilczyńska B., Pyra J., 2002: Integration of data from soil and underground waters monitoring networks by kriging with external drift. 2002 Annual Conference of the International Association for Mathematical Geology (IAMG) . Creation, Management, Distribution, Access and Exploitation of Digital Spatial Data. Berlin.
• 10. Namysłowska-Wilczyńska B., Wilczyński A., 2000: Badania geostatystyczne rozkładu zawartości metali ciężkich w gruntach. Geoinformatica Polonica nr 2, Kraków, s. 51-65.
• 11. Nieć M., Kokesz Z., 1988: Metody geostatystyczne w rozpoznawaniu i dokumentowaniu złóż (przewodnik metodyczny). Wydawnictwo Akademii Górniczo-Hutniczej, Kraków, s. 29.
• 12. Ratha D.S., Venkataraman G., 1994: Multivariate statistical analysis of soil geochemical data from mining areas of Goa, India. Sciences De La Terre Informatique Geologique, no 32, p. 471-487.
• 13. Wackernagel H., 1998: Multivariate Geostatistics: an Introduction with Applications. 2nd edition, Springer, Berlin, p. 291.
• 14. Webster R., Atteia O., Dubois J.P., 1994: Coregionalization of trace metals in the soil in the Swiss Jura. European Journal of Soil Science 45, June 1994, p. 205-218.