• The Journal of Engineering Geology
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• v.16 no.4 s.50
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• pp.393-402
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• 2006

The contamination characteristics of BTEX and TPH components in silty soils with the oil leakage event from point source were studied. The over ratios of three soil pollution standard for TPH component were $1.5{\sim}1.7$ times higher than that of BTEX component. The mean and maximum values of BTEX and TPH components with sample points were B-zone > A-zone > C-zone, and the highest concentrations were measured at $1{\sim}2m$ depth below surface. BTEX and TPH components were increased with linear distance in zone within 120 m and 80 m from point source. For the zone more than 120 m, BTEX and TPH concentrations were under soil pollution standard. The cutoff values of indicator kriging using BTEX and TPH components were defined as confirmative limit, warn- ing limit and counterplan limit. The variograms of indicator-transformed data were selected linear model. The contamination ranges of BTEX and TPH components using confirmative limit and warning limit were estimated similar, but the contamination range of those using counterplan limit was much reduced. The maximum contamination probabilities were estimated by probability maps usinB confirmative limit, warning limit and counterplan limit. The maximum contamination probabilities with three soil pollution standard were estimated 26%, 26% and 13% for BTEX component, and 44%, 38% and 26% for TPH component.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.4
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• pp.527-533
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• 2011

Decomposition of compost applied to soils is affected basically by its biological stability; but, many other chemical properties of the compost may also influence compost organic-C mineralization. This study was conducted to investigate the principal substrate quality factors of composts that determine C mineralization of compost with similar stability degree (SD). Three composts samples with similar SD but different chemical properties such as pH, C/N, $K_2SO_4$-extractable C, and molar ratio of $NH_4^+$ to $NO_3^-$ were mixed with an acid loamy soil and $CO_2$ emission was monitored during the laboratory incubation for 100 days. Temporal pattern of cumulative compost organic-C mineralization expressed as % of total organic C ($C_{%\;TOC}$) followed double exponential first order kinetics model and the $C_{%\;TOC}$ ranged from 4.8 to 11.8% at the end of incubation. The pattern of C%TOC among the composts was not coincident with the SD pattern (40.1 to 58.6%) of the composts; e.g. compost with the lowest SD resulted in the least $C_{%\;TOC}$ and vice versa. This result indicates that SD of compost can not serve as a concrete predictor of compost mineralization as SD is subject not only to maturity of compost but also to characteristics of co-composting materials such as rice hull (low SD) and sawdust (high SD). Meanwhile, such pattern of $C_{%\;TOC}$ collaborated with pH, C/N, $K_2SO_4$-extractable C, and molar ratio of $NH_4^+$ to $NO_3^-$ of the composts that are regarded as chemical indices of the progress of composting. Therefore, for better prediction of compost mineralization in soils, it is necessary to consider both SD and other chemical indices (pH, C/N, and molar ratio of $NH_4^+$ to $NO_3^-$).

• Journal of the Korean Geotechnical Society
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• v.33 no.2
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• pp.17-26
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• 2017

Pile foundations that support offshore structures or transmission towers are dominantly subjected to cyclic lateral loads due to wind and waves, causing permanent displacement which can severely affect stability of the structures. In this study, a series of cyclic lateral load tests were conducted on a pre-installed aluminum flexible pile in sandy soil with three different relative densities (40%, 70% and 90%) in order to evaluate the permanent displacement of a cyclic laterally loaded pile. Test results showed that the cyclic lateral loads accumulated the irreversible lateral displacement, so-called permanent displacement. As the number of cyclic lateral load increased, accumulated permanent displacement increased, but the permanent displacement due to one loading cycle gradually decreased. In addition, the permanent displacement of a pile increased with decrement of relative density and decreased by soil saturation. From the test results, the normalized permanent displacement defined as the cumulative permanent displacement to the initial permanent displacement ratio was investigated, and empirical equations for predicting the normalized permanent displacement was developed in terms of relative density of the soil and the number of cyclic lateral load.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.164-175
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• 2019

The Tor Tong Daeng Irrigation Project with the irrigation area of 61,400 hectares is located in the Ping Basin of the Upper Central Plain of Thailand where farmers depended on both surface water and groundwater. In the drought year, water storage in the Bhumipol Dam is inadequate to allocate water for agriculture, and caused water deficit in many irrigation projects. Farmers need to find extra sources of water such as water from farm pond or groundwater as a supplement. The operation of Bhumipol Dam and irrigation demand estimation are vital for irrigation water allocation to help solve water shortage issue in the irrigation project. The study aims to determine the smart dam operation system to mitigate water shortage in this irrigation project via introduction of machine learning to improve dam operation and irrigation demand estimation via soil moisture estimation from satellite images. Via ANN technique application, the inflows to the dam are generated from the upstream rain gauge stations using past 10 years daily rainfall data. The input vectors for ANN model are identified base on regression and principal component analysis. The structure of ANN (length of training data, the type of activation functions, the number of hidden nodes and training methods) is determined from the statistics performance between measurements and ANN outputs. On the other hands, the irrigation demand will be estimated by using satellite images, LANDSAT. The Enhanced Vegetation Index (EVI) and Temperature Vegetation Dryness Index (TVDI) values are estimated from the plant growth stage and soil moisture. The values are calibrated and verified with the field plant growth stages and soil moisture data in the year 2017-2018. The irrigation demand in the irrigation project is then estimated from the plant growth stage and soil moisture in the area. With the estimated dam inflow and irrigation demand, the dam operation will manage the water release in the better manner compared with the past operational data. The results show how smart system concept was applied and improve dam operation by using inflow estimation from ANN technique combining with irrigation demand estimation from satellite images when compared with the past operation data which is an initial step to develop the smart dam operation system in Thailand.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.187-195
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• 2019

The needs for precise diagnostics and farm management-decision aids have increased to reduce the risk of climate change and environmental stress. Crop simulation models have been widely used to search optimal solutions for effective cultural practices. However, limited knowledge on physiological responses to environmental variation would make it challenging to apply crop simulation models to a wide range of studies. Advanced research facilities would help investigation of plant response to the environment. In the present study, the sunlit controlled environment chambers, known as Korean SPAR (Soil-Plant-Atmosphere-Research) system, was developed by renovating existing SPAR system. The Korean SPAR system controls and monitors major environmental variables including atmospheric carbon dioxide concentration, temperature and soil moisture. Furthermore, plants are allowed to grow under natural sunlight. Key physiological and physical data such as canopy photosynthesis and respiration, canopy water and nutrient use over the whole growth period are also collected automatically. As a case study, it was shown that the Korean SPAR system would be useful for collection of data needed for understanding the growth and developmental processes of a crop, e.g., soybean. In addition, we have demonstrated that the canopy photosynthetic data of the Korean SPAR indicate the precise representation of physiological responses to environment variation. As a result, physical and physiological data obtained from the Korean SPAR are expected to be useful for development of an advanced crop simulation model minimizing errors and confounding factors that usually occur in field experiments.

• The Journal of Engineering Geology
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• v.28 no.4
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• pp.605-618
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• 2018

Korea follows the slope design criteria during construction. It was enacted by the Ministry of Land, Transport and Maritime Affairs. There are cases where the Soil-nail is designed as a measure to secure slope stability. The arrangement of the soil-nail may be arranged at equal intervals or may be arranged differently depending on the soil failure model. The optimum design of the countermeasure method is determined by securing stability of the slope through optimization of dimensions and shape. However, when uniform nails are placed at low elevations in slopes, the standard safety factor is exceeded, which may hinder economic design. It is preferable to arrange the reinforcement of the nails over the entire slope. When the horizontal spacing of the nails was topology optimized according to the slope height, it was possible to minimize the amount of reinforcement while satisfying the standard safety factor. Since the active load is reduced in the section where the slope height is lowered, the safety factor after reinforcement may be excessively increased. Therefore, the phase optimization method is proposed as an economical optimal design method using the reinforcing shape density. In addition, a relational expression was designed to optimize the horizontal spacing by slope height.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.4
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• pp.459-466
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• 2021

The present study was conducted to propose future research directions for weed management by examining the current trends of research on weed occurrence according to cropping systems. The cropping systems are developed for the efficient use of arable land, and the weed flora changes according to the management practices of a given cropping system. In particular, weed occurrence can be reduced by altering the soil environment. In addition, cultivation methods, such as tillage, affect the weed seed bank in the soil, thus altering the pattern of weed occurrence. Here, we propose three weed management practices according to the cropping system. First, it is necessary to develop a model that can classify weed species by analyzing young seedlings and can predict the flora in the field. Second, it is important to manage the cropping system history and establish a database of agricultural information, which can be linked to meteorological and geographic data. Third, it is critical to estimate the weed occurrence and soil seed bank dynamics, based on which a cropping system platform and digitalization technology can be developed. In the future, the prediction of weed occurrence and control according to the cropping system will contribute to sustainable agriculture by reducing the use of herbicides and solving the problems of resistant weeds.

• Journal of Korean Society of Forest Science
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• v.111 no.3
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• pp.428-434
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• 2022

This study was conducted to derive the site index of forest productivity of Robinia pseudoacacia (honey plant) to characterize suitable planting sites and to investigate the effect of the site environmental factors on the site index using the quantification theory I method. The data used in the analysis were growth factors (stand age, dominant height, etc.) of the 6th national forest resources survey and various site environmental factors of a forest soil map (1:5,000). The average site index value of the R. pseudoacacia stand in Korea was 14 (range, 8 to 18). The environmental factors affecting the site index were parent rock, climatic zone, soil texture, local topography, and altitude. The accuracy of the estimation model using quantification theory I was only 33%. However, the correlation between the site index and the site environmental factors was statistically significant at the 1% level. Results of quantification analysis between site index and site environmental factors revealed that metamorphic and igneous rocks received high grades as parent rocks, climate zones received higher grades than central temperate zone, clay loam and silt loam received high grades in soil texture, and hillside received a high grade in local topography. Analysis of the partial correlation between site topographical factors and forest productivity (site index) found that soil class and altitude were partially correlated to x by 0.4129 and 0.4023, respectively, indicating that these factors are the most influential variables.

• Journal of the Korean Geotechnical Society
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• v.40 no.1
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• pp.5-14
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• 2024

PHC piles demonstrate superior resistance to compression and bending moments, and their factory-based production enhances quality assurance and management processes. Despite these advantages that have resulted in widespread use in civil engineering and construction projects, the design process frequently relies on empirical formulas or N-values to estimate the soil-pile friction, which is crucial for bearing capacity, and this reliance underscores a significant lack of experimental validation. In addition, environmental factors, e.g., the pH levels in groundwater and the effects of seawater, are commonly not considered. Thus, this study investigates the influence of vibrating machine foundations on PHC pile models in consideration of the effects of varying pH conditions. Concrete model piles were subjected to a one-month conditioning period in different pH environments (acidic, neutral, and alkaline) and under the influence of seawater. Subsequent repeated direct shear tests were performed on the pile-soil interface, and the disturbed state concept was employed to derive parameters that effectively quantify the dynamic behavior of this interface. The results revealed a descending order of shear stress in neutral, acidic, and alkaline conditions, with the pH-influenced samples exhibiting a more pronounced reduction in shear stress than those affected by seawater.

• Journal of Korea Water Resources Association
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• v.57 no.9
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• pp.615-626
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• 2024

To accurately and efficiently monitor soil moisture (SM) across South Korea, this study developed a SM estimation model that integrates the cloud computing platform Google Earth Engine (GEE) and Automated Machine Learning (AutoML). Various spatial information was utilized based on Terra MODIS (Moderate Resolution Imaging Spectroradiometer) and the global precipitation observation satellite GPM (Global Precipitation Measurement) to test optimal input data combinations. The results indicated that GPM-based accumulated dry-days, 5-day antecedent average precipitation, NDVI (Normalized Difference Vegetation Index), the sum of LST (Land Surface Temperature) acquired during nighttime and daytime, soil properties (sand and clay content, bulk density), terrain data (elevation and slope), and seasonal classification had high feature importance. After setting the objective function (Determination of coefficient, R² ; Root Mean Square Error, RMSE; Mean Absolute Percent Error, MAPE) using AutoML for the combination of the aforementioned data, a comparative evaluation of machine learning techniques was conducted. The results revealed that tree-based models exhibited high performance, with Random Forest demonstrating the best performance (R² : 0.72, RMSE: 2.70 vol%, MAPE: 0.14).