Performing Spatial Variabilityof Peat Depth by Using Geostatistics

M. Edi Armanto,Dedi Setiabudidaya,Ngudiantoro Ngudiantoro,Mohd. Zuhdi,M. Amin

doi:10.1051/e3sconf/20186804021

Abstract

Geostatistics has been knowns as a reliable tool to explore variability in space of any measured parameter. This research aims to study how peat depth change and vary in space using geostatistics aproach. The research took place in a peat land inMuaro Jambi district, Jambi province of Indonesia. The three different areas of peat depth [very deep (area A), deep (area B) and shallow (area C)] were purposely selected to investigate through borehole. From the total 120 boreholes, peat depth data were analyses using ArcGIS geostatistical analyses.The result showed that peat variability in shallow area is higher than that of deep and very deep area.It is also found that the reliable sampling distance in peat exploration should not be less than 230 meter in very deep area, 275 meter in deep area and 41 meter in shallow area.

Highlights

Peat is organic material which is accumulated from plant materials which are not completely decomposed due to anaerobic and water-saturated condition[1]
Peat depthdoes vary but either not distribute randomly in landscape; there is always a spatial correlation that can explain the distribution of its magnitudes[5][6].In order to represent the spatial correlation, geostatistics has been known to be used, especially due to its specific tool called variogram
The main descriptive statistics of the three areas are presented in Table 1 and provide information about the central tendency and variability of peat depth

Summary

Introduction

Peat is organic material which is accumulated from plant materials which are not completely decomposed due to anaerobic and water-saturated condition[1]. Peat was formed under the influence of high water levels, so that litter accumulation of plants is growing and will result dome-shaped peats. Peat depthdoes vary but either not distribute randomly in landscape; there is always a spatial correlation that can explain the distribution of its magnitudes[5][6].In order to represent the spatial correlation, geostatistics has been known to be used, especially due to its specific tool called variogram. The method of geostatistics provide a set of statistical tools for incorporating the spatial coordinates of observations in data processing

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Conclusion