Geostatistical modeling of geochemical variables in 3D

Abstract

Geostatistical mapping of soil properties in 3D refers to the application of geostatistical methods to the soil data in order to produce maps of soil properties at different depths. Through two separate studies, this thesis elaborates on two different approaches for 3D soil mapping. At first, the well established Spline-Than-Krige approach for the mapping of soil pollutants atmospherically deposited from the copper smelting plant, was used. In the absence of the monitoring data, which can be used for a detailed characterization of the plume spreading process, this study was confined to the consideration of terrain exposure to explain spatial trend in arsenic distribution at different depths. This study aims to explore the extent to which the commonly available information, such as the prevailing wind direction, or the location of the source of pollution, in combination with the digital terrain model, can be used to quantify the terrain exposure, and hence to improve the spatial prediction of the arsenic concentration at several soil depths. Next, the innovative geostatistical approach to 3D mapping of soil properties, based on soil profile data, was proposed. It provides the semi-automatic way for 3D modeling of soil variables, prediction over the regular grids (rasters) and also the evaluation of prediction accuracy. Methodologically, this approach operates within the 3D regression kriging framework. 3D trend model is conceptualized as hierarchical or non-hierarchical linear interaction model. This means that the model includes the interactions between the spatial covariates and depth in the hiearchial or non-hierarchial manner. The trend modeling is based on the application of the penalized regression technique, lasso. The lasso uses a specific regularization penalty in a fitting procedure to enable the efficient parameter estimation and variable selection (including interaction terms) at the same time...

Geostatistiˇcko kartiranje zemljišta u 3D odnosi se na primenu geostatistiˇckih metoda na zemljišnim podacima u cilju izrade karata zemljišnih karakteristika jednog podruˇcja, koje se odnose na razliˇcite dubine zemljišta. U okviru dve nezavisne studije, ova doktorska disertacija razmatra dva razliˇcita pristupa geostatistiˇckog modeliranja zemljišta u 3D. U okviru prve studije, "Spline-Than-Krige" metod je koriš´cen za kartiranje koncentracije arsena u zemljištu, u blizini Rudarsko-topioniˇcarskog basena Bor, na tri razliˇcite dubine (0-5 cm, 5-15 cm i 15-30 cm). Dugogodišnje emitovanje nepreˇciš´cenih materija iz topionice rudnika u atmosferu, dovelo je do zagadjenja zemljišta u okolini, taloženjem štetnih materija nošenih vetrom. U odsustvu podataka kojima bi se detaljnije mogao opisati proces raspršivanja štetnih materija, ova studija se ograniˇcila na analizu izloženosti terena uticaju vetra, a time i procesu zagad¯enja. Predstavljen je inovativan pristup kvantifikaciji izloženosti terena izvoru zagad¯enja. Na osnovu opšte dostupnih podataka, kreirano je nekoliko parametara kojima se kvantifikuje geometrijska i topografska izloženost svake tacˇke terena izvoru zagad¯enja. Tako kreirani parametri, iskorišc´eni su za opisivanje prostornog trenda koncentracije arsena na tri razliˇcite dubine. Definisani trendovi, koriš´ceni su u okviru regresionog kriginga, za prostornu predikciju. Na taj naˇcin pokušalo se odgovoriti na pitanje, u kojoj meri, opšte dostupni podaci, kao što su pravac dominantnog vetra ili poznavanje taˇcne lokacije izvora zagadjenja u kombinaciji sa digitalnim modelom terena, mogu biti iskoriš´ceni da bi se unapredila preciznost prostorne predikcije zemljišnih zagadjivaˇca, kako na površinskim slojevima tako i na ve´cim dubinama...