Hyen g Chun

A Comparison of Spatial Variation on Anthropogenic Soils

In this study, spatial analyses of chemical properties were studied to find inter-relation among these properties from 5 year old general paddy field after arable land rearrangement and remodeled paddy field near 4 river project. In addition, comparison of spatial variations between two paddy fields was performed to characterize paddy fields by different formation and provide interpretation of these variations and parameters (Semivariogram and Kriging) from spatial analyses. Total of 400 (20×20) soil samples were taken at 5 m interval from 1 ha of 5 year old general paddy field and analyzed. Total number of 54 (6×9) soil samples were taken from remodeled paddy fields at 10m interval for the analyses. The results of pH, available Phosphate and organic matter among the analyzed results were used for interpretation. The pH values were relatively high from Gumi region. The values of available Phosphate and organic matter showed greater variant coefficients and this represented that there were greater heterogeneity in available phosphate and organic matter distributions across one paddy field. The values of skewness and kurtosis as absolute values, showed almost normal distributions. The paddy field in Ansung had available Phosphate (72.8) ≒ pH (73.8) and greater values of organic matter (159.3), while upland in Gumi had the range value of organic (6.5) < available Phosphate (33.5) < pH (46.6). Based on these results, younger soils (0 year old) require more sampling to characterize the whole field than 5 year old soils.

Comparison of Soil Pore Properties between Anthropogenic and Natural Paddy Field Soils From Computed Tomographic Images

Human influence on soil formation has dramatically increased with human civilization and industry development. Increase of anthropogenic soils induced researches on the anthropogenic soils; classification, chemical and physical characteristics of anthropogenic soils and plant growth from anthropogenic soils. However there have been no comprehensive analyses on soil pore or physical properties of anthropogenic soils from 3 dimensional images in Korea. The objectives of this study were to characterize physical properties of anthropogenic paddy field soils by depth and to find differences between natural and anthropogenic paddy field soils. Soil samples were taken from two anthropogenic and natural paddy field soils; anthropogenic (A_c) and natural (N_c) paddy soils with topsoil of coarse texture and anthropogenic (A_f) and natural (N_f) paddy soils with topsoil of fine texture. The anthropogenic paddy fields were reestablished during the Arable Land Remodeling Project from 2011 to 2012 and continued rice farming after the project. Natural paddy fields had no artificial changes or disturbance in soil layers up to 1m depth. Samples were taken at three different depths and analyzed for routine physical properties (texture, bulk density, etc.) and pore properties with computer tomography (CT) scans. The CT scan provided 3 dimensional images at resolution of 0.01 mm to calculate pore radius size, length, and tortuosity of soil pores. Fractal and configuration entropy analyses were applied to quantify pore structure and analyze spatial distribution of pores within soil images. The results of measured physical properties showed no clear trend or significant differences across depths or sites from all samples, except the properties from topsoils. The results of pore morphology and spatial distribution analyses provided detailed information of pores affected by human influences. Pore length and size showed significant decrease in anthropogenic soils. Especially, pores of A_c had great decrease in length compared to N_c. Fractal and entropy analyses showed clear changes of pore distributions across sites. The topsoil layer of A_c showed more degradation of pore structure than that of N_c, while pores of A_f topsoil did not show significant degradation compared with those of N_f. These results concluded that anthropogenic soils with coarse texture may have more effects on pore properties than ones with fine texture. The reestablished paddy fields may need more fundamental remediation to improve physical conditions.

Computer Tomography as a Tool for Physical Analysis in an Anthropogenic Soil

Human influence on soil formation has dramatically increased as the development of human civilization and industry. Increase of anthropogenic soils induced research of those soils; classification, chemical and physical characteristics and plant growth of anthropogenic soils. However there have been no reports on soil pore properties from the anthropogenic soils so far. Therefore the objectives of this study were to test computer tomography (CT) to characterize physical properties of an anthropogenic paddy field soil and to find differences between natural and anthropogenic paddy field soils. Soil samples of a natural paddy field were taken from Ansung, Gyeonggi-do (Ansung site), and samples of an anthropogenic paddy field were from Gumi in Gyeongsangnam-do (Gasan) where paddy fields were remodeled in 2011-2012. Samples were taken at three different depths and analyzed for routine physical properties and CT scans. CT scan provided 3 dimensional images to calculate pore size, length and tortuosity of soil pores. Fractal analysis was applied to quantify pore structure within soil images. The results of measured physical properties (bulk density, porosity) did not show differences across depths and sites, but hardness and water content had differences. These differences repeated within the results of pore morphology. Top soil samples from both sites had greater pore numbers and sizes than others. Fractal analyses showed that top soils had more heterogeneous pore structures than others. The bottom layer of the Gasan site showed more degradation of pore properties than ploughpan and bottom layers from the Ansung site. These results concluded that anthropogenic soils may have more degraded pore properties as depth increases. The remodeled paddy fields may need more fundamental remediation to improve physical conditions. This study suggests that pore analyses using CT can provide important information of physical conditions from anthropogenic soils.

Predicting Organic Matter content in Korean Soils Using Regression rules on Visible-Near Infrared Diffuse Reflectance Spectra

This study investigates the prediction of soil OM on Korean soils using the Visible-Near Infrared (Vis-NIR) spectroscopy. The ASD Field Spec Pro was used to acquire the reflectance of soil samples to visible to near-infrared radiation (350 to 2500 ㎚). A total of 503 soil samples from 61 Korean soil series were scanned using the instrument and OM was measured using the Walkley and Black method. For data analysis, the spectra were resampled from 500-2450 nm with 4 nm spacing and converted to the 1 st derivative of absorbance (log (1/R)). Partial least squares regression (PLSR) and regression rules model (Cubist) were applied to predict soil OM. Regression rules model estimates the target value by building conditional rules, and each rule contains a linear expression predicting OM from selected absorbance values. The regression rules model was shown to give a better prediction compared to PLSR. Although the prediction for Andisols had a larger error, soil order was not found to be useful in stratifying the prediction model. The stratification used by Cubist was mainly based on absorbance at wavelengths of 850 and 2320 ㎚, which corresponds to the organic absorption bands. These results showed that there could be more information on soil properties useful to classify or group OM data from Korean soils. In conclusion, this study shows it is possible to develop good prediction model of OM from Korean soils and provide data to reexamine the existing prediction models for more accurate prediction.

Review of Soil Structure Quantification from Soil Images

Soil structure plays an important role in ecological system, since it controls transport and storage of air, gas, nutrients and solutions. The study of soil structure requires an understanding of the interrelations and interactions between the diverse soil components at various levels of organization. Investigations of the spatial distribution of pore/particle arrangements and the geometry of soil pore space can provide important information regarding ecological or crop system. Because of conveniences in image analyses and accuracy, these investigations have been thrived for a long time. Image analyses from soil sections through impregnated blocks of undisturbed soil (2 dimensional image analyses) or from 3 dimensional scanned soils by computer tomography allow quantitative assessment of the pore space. Image analysis techniques can be used to classify pore types and quantify pore structure without inaccurate or hard labor in laboratory. In this paper, the last 50 years of the soil image analyses have been presented and measurements on various soil scales were introduced, as well. In addition to history of image analyses, a couple of examples for soil image analyses were displayed. The discussion was made on the applications of image analyses and techniques to quantify pore/soil structure.

Use of the Quantitatively Transformed Field Soil Structure Description of the US National Pedon Characterization Database to Improve Soil Pedotransfer Function

Soil hydraulic properties such as hydraulic conductivity or water retention which are costly to measure can be indirectly generated by soil pedotransfer function (PTF) using easily obtainable soil data. The field soil structure description which is routinely recorded could also be used in PTF as an input to reduce the uncertainty. The purposes of this study were to use qualitative morphological soil structure descriptions and soil structural index into PTF and to evaluate their contribution in the prediction of soil hydraulic properties. We transformed categorical morphological descriptions of soil structure into quantitative values using categorical principal component analysis (CATPCA). This approach was tested with a large data set from the US National Pedon Characterization database with the aid of a categorical regression tree analysis. Six different PTFs were used to predict the saturated hydraulic conductivity and those results were averaged to quantify the uncertainty. Quantified morphological description was successively used in multiple linear regression approach to predict the averaged ensemble saturated conductivity. The selected stepwise regression model with only the transformed morphological variables and structural index as predictors predicted the Ksat with r 2 = 0.48 (p = 0.018), indicating the feasibility of CATPCA approach. In a regression tree analysis, soil structure index and soil texture turned out to be important factors in the prediction of the hydraulic properties. Among structural descriptions size class turned out to be an important grouping parameter in the regression tree. Bulk density, clay content, W33 and structural index explained clusters selected by a two step clustering technique, implying the morphologically described soil structural features are closely related to soil physical as well as hydraulic properties. Although this study provided relatively new method which related soil structure description to soil structure index, the same approach should be tested using a datasets containing the actual measurement of hydraulic properties. More insight on the predictive power of soil structure index to estimate hydraulic properties would be achieved by considering measured the saturated hydraulic conductivity and the soil water retention.

Spatial Analyses of Soil Chemical Properties from a Remodeled Paddy Field as Affected by Wet Land Leveling

Uniformity and leveled distributions of soil chemicals across paddy fields are critical to manage optimal crop yields, reduce environmental risks and efficiently use water in rice cultivation. In this study, an investigation of spatial distributions on soil chemical properties was conducted to evaluate the effect of land leveling on mitigation of soil chemical property heterogeneity from a remodeled paddy field. The spatial variabilities of chemical properties were analyzed by geostatistical analyses; semivariograms and kriged simulations. The soil samples were taken from a 1 ha paddy field before and after land leveling with sufficient water. The study site was located at Bon-ri site of Dalseong and river sediments were dredged from Nakdong river basins. The sediments were buried into the paddy field after 50 cm of top soils at the paddy field were removed. The top soils were recovered after the sediments were piled up. In order to obtain the most accurate spatial field information, the soil samples were taken at every 5 m by 5 m grid point and total number of samples was 100 before and after land leveling with sufficient water. Soil pH increased from 6.59 to 6.85. Geostatistical analyses showed that chemical distributions had a high spatial dependence within a paddy field. The parameters of semivariogram analysis showed similar trends across the properties except pH comparing results from before and after land leveling. These properties had smaller “sill” values and greater “range” values after land leveling than ones from before land leveling. These results can be interpreted as land leveling induced more homogeneous distributions of soil chemical properties. The homogeneous distributions were confirmed by kriged simulations and distribution maps. As a conclusion, land leveling with sufficient water may induce better managements of fertilizer and water use in rice cultivation at disturbed paddy fields.