Statystyczne pomiary rozkładu granulometrycznego jako wskaźniki odwzorowania dynamiki sedymentacji wodnej w czwartorzędzie
Abstract
STATISTICAL MEASUREMENTS OF GRANULOMETRIC DISTRIBUTION AS INDICES FOR RECONSTRUCTING DYNAMICS OF FLUVIAL SEDIMENTATION IN THE QUATERNARY
Summary
A model of geological structure was made with the use of trend surface maps and discriminant function. Analysis of that model made it possible to assume existence of five environments of sedimentation of non-cohesive soils in the area studied. This subdivision into five sedimentary environments was subsequently verified with the use of statistical techniques involving correlation and regression analysis of statistical indices of distribution of fractions. On that basis there were distinguished environmentally-sensitive statistical parameters (in that scheme of analysis) which made possible preliminary approximation of the dynamics of sedimentation of the environments analysed. Moreover, a hypothesis was put forward that it is possible to use statistical-mathematic analysis in lithological-facies identification of non-cohesive soils. However, it is a working hypothesis requiring further multiple tests.
Summary
A model of geological structure was made with the use of trend surface maps and discriminant function. Analysis of that model made it possible to assume existence of five environments of sedimentation of non-cohesive soils in the area studied. This subdivision into five sedimentary environments was subsequently verified with the use of statistical techniques involving correlation and regression analysis of statistical indices of distribution of fractions. On that basis there were distinguished environmentally-sensitive statistical parameters (in that scheme of analysis) which made possible preliminary approximation of the dynamics of sedimentation of the environments analysed. Moreover, a hypothesis was put forward that it is possible to use statistical-mathematic analysis in lithological-facies identification of non-cohesive soils. However, it is a working hypothesis requiring further multiple tests.