Geomorfologický Geomorfologické sborník mapování 2 a inventarizace tvarů ČAG, ZČU v Plzni, 2003 Analysis of spatial variability of aeolian sandswith geostatistical methods Jolanta Pełka-Gościniak pelka@us.edu.pl University of Silesia, Faculty of Earth Sciences, 41-200 Sosnowiec, ul. Będzińska 60, Poland Statistical methods are widely applied in geographical investigations (GREGORY, 1976). Among them the most useful are analyses of trend. Analysis of surface trend enables the illustration of spatial tendencies of defined phenomena size to increase or decrease (DOMINIK, RUSZKOWSKI & STUDNICKI, 1984). By means of this method it is also possible to compare properties with each other. It is of essential importance when the observing of spatial changes character in investigated phenomena on source maps ( RUNGE, 1992) is difficult. Method of surface trend is especially useful when research workers do not limit themselves to essential components of spatial series, but they also manage to explain dependence of an effect upon the cause between series component and explanatory variables. Such approach to the analy sis of surface trend is possible in geophysics and geology as well as in geomorphology (CZYŻ, 1978). This elaboration is an attempt to solve problems connected with spatial variability of sandy deposits by means of different mathematical -geostatistical methods in relatively small area of Starczynów Desert (PEŁKA-GOŚCINIAK, 2000). To solve problem above-mentioned, the detailed field study was carried out, during which 450 sand samples were collected from aeolian cover sands and selected dunes in a series of knot points of square net. The whole material was subjected to laboratory investigation, which included standard analyses of grain size distribution according to equations of R. L. FOLK and W. C. WARD (1957), quartz grain abrasion 1 0.8 mm, applying methods of morphoscopy by A. CAILLEUX (1942) and mechanical graniformametry by B. KRYGOWSKI (1964). The statistics compilation of data allowed mapping of textural parameters trends as well as spatial distribution. First of all these data were subjected to smoothing by movable mean, which allowed avoiding factors, resulting from the nature of samples collected, i.e. randomness of place, influence of pulsatory and fluctuational changes in the environment and laboratory investigations (compare RACINOWSKI, SZCZYPEK & WACH, 2001). Therefore textural parameters can be the reflection of general picture of deposits properties and can be compared. Thanks to smoothing the results from direct observations are in a clear way well-ordered, what facilitates to find regularities in spatial distribution (compare RACINOWSKI, 1986) (Fig. 1). 177
Fig. 1. Spatial distribution of variability of mean grain diameter Mz (in mm) for raw data (A) and averaged (smoothed) data (B). 178
According to R. RACINOWSKI (1981) smoothing allows eliminating pulsatory influences connected with temporary changes in the sedimentation environment, but the most preferred method to avoid cyclic changes, being the reflection of seasonal sedimentation tendencies is method of surface trend. The last-mentioned method also allows making the lithodynamical regionalisation of the sedimentation environment. The smoothed data were the base to make maps of spatial distribution of particular parameters of grain size distribution and quartz grain abrasion by means of interpolation method. In this paper the author presents stages of research work on the base of only one parameter mean grain diameter Mz (in mm). The following stage was making spatial schemes of surface simple and cubic trends (Fig. 2A, B). These data were also the base to make a complex estimation of given parameters anomalies, what is very valuable in the lithodynamical inference. For a set of particular parameters, smoothed by a movable mean, average values and their confidence intervals (at the level of 0.95) were calculated (Fig. 3). It was assumed, that parameters within this interval characterise the average conditions of the analysed sand, while those beyond the intervals (positive or negative anomalies) indicate a relative predominance of deposition (accumulation) or redeposition (deflation) processes. A B Fig. 2. Spatial distribution of surface simple trend (A) and surface cubic trend (B) for mean grain diameter Mz (mm) The method of surface simple trend presents only general tendencies of changes in textural deposits properties in connection with anemological conditions (Fig. 2A). Method of surface cubic trend was the base to evaluate quality of the aeolian environment through total comparison of all textural parameters. On the base of knowledge of sandy material tendencies to move the summarising maps were constructed, where the areas of deflative, accumulative and transitional character were divided (Fig. 4). This method in a wider way allows observing the relief influence. Map of anomalies (Fig. 5) presents similar character of deposits to map made by means of surface cubic trend. But it is more detailed considering the local conditions connected with relief as well as with anemological conditions. 179
It seems that mathematical-geostatistical methods used in the elaboration can be applied in geomorphological investigations on spatial pro blems. From methods proposed the most effective to make qualitative evaluation of the aeolian environment of Starczynów desert appeared the method of anomalies. It was the best to observe the dependence of separated regions on morphology. To find the influence of anemological conditions the best is the method of surface simple trend. Spatial distribution of surface simple trend and surface cubic trends are the proof that the agreement between tendencies in change in basic textural parameters and anemological conditions and relief occurs. Investigations on textural features confirm and verify the detailed geomorphological mapping. Fig. 3. Spatial distribution of anomalies of grain size values. The scheme in the right bottom corner presents conditions for hig her lithodynamical activity (deflation). 180
Fig. 4. Differentiation of areas in respect of grain size distribution, made by means of surface cubic trend: 1 areas of deflation character, 2 areas of transition character, 3 areas of accumulative character Fig. 5. Differentiation of areas in respect of grain size distribution, made by means of method of anomalies: 1 areas of deflation character, 2 areas of transition character, 3 areas of accumulative character 181
References CAILLEUX A., 1942: Les actions éoliennes périglaciaires en Europe. Mem. Soc. Geol. France, 21, 46. CZYŻ T., 1978: Metody generalizacji układów przestrzennych, PWN, Warszawa-Poznań. DOMINIK A., RUSZKOWSKI J. & STUDNICKI T., 1984: Geografia ekonomiczna. Przewodnik metodyczny i przykłady analizy zagadnień geograficznych metodami kartograficznoilościowymi, AE, Katowice. FOLK R. L., WARD W.C., 1957: Brazos river bar: a study in the significance of grain size parameters, Journal. Sed. Petrol., 27, 1. GREGORY S., 1976: Metody statystyki w geografii, PWN, Warszawa. KRYGOWSKI B., 1964: Graniformametria mechaniczna. Teoria, zastosowanie, PTPN, Prace Komisji Geograf. -Geolog., t. II, z.4, Poznań. PEŁKA-GOŚCINIAK J., 2000: Przestrzenna zmienność piasków eolicznych Pustyni Starczynowskiej, UŚ WNoZ, Sosnowiec. RACINOWSKI R., 1981: Znaczenie formy opracowania wyników uziarnienia osadów dla litodynamicznej charakterystyki strefy brzegowej, Inżynieria Morska, 2. RACINOWSKI R., 1986: Krótkookresowa zmienność wygładzonych wskaźników litologicznych rumowiska z dolnej części strefy potoku przyboju między Niechorzem a Trzęsaczem, Peribalticum, t. IV, Wrocław- Warszawa. RACINOWSKI R., SZCZYPEK T. & WACH J, 2001: Prezentacja i interpretacja wyników badań uziarnienia osadów czwartorzędowych, UŚ, Katowice. RUNGE J., 1992: Wybrane zagadnienia analizy przestrzennej w badaniach geograficznych, Katowice, Prace Naukowe UŚ nr 469. Streszczenie Analiza przestrzennej zmienności piasków eolicznych za pomocą metod geostatystycznych Aby w pełni zrozumieć działalność wiatru należy posiąść wiedzę na temat terytorialnej zmienności materiału transportowanego i akumulowanego przez czynnik eoliczny. W pracy podjęto próbę wyjaśnienia tego problemu za pomocą metod matematycznogeostatystycznych. Wyniki standartowych analiz laboratoryjnych piasków eolicznych (uziarnienie i obtoczenie) zebranych w regularnych odstępach na obszarze Pustyni Starczynowskiej poddano obróbce statystycznej. Na wstępie wyeliminowano czynniki przypadkowe. Następnie wykonano mapy rozkładu przestrzennego poszczególnych wskaźników uziarnienia i obtoczenia dla danych surowych i uśrednionych, wykorzystując metodę interpolacji. Wykonano również schematy przestrzenne trendu powierzchniowego o postaci liniowej pierwszego stopnia oraz sześciennego (trzeciego stopnia) (rys. 1A i B). Uśrednione dane posłużyły również do oceny wskaźników uziarnienia i obtoczenia poprzez zbiorczą analizę anomalii tych parametrów. Wykorzystując metody trendu przestrzennego trzeciego stopnia i anomalii wykonano kompleksową ocenę wskaźników uziarnienia i obtoczenia, czego efektem były mapy zróżnicowania obszarów (rys. 2, 3, 4). Dokonano również oceny wykorzystanych metod pod kątem ich użyteczności w geomorfologii. 182