• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.4
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• pp.57-66
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• 2016

Harmonized World Soil Database (HWSD) including the global soil information has been implemented to the runoff analysis in many watersheds of the world. However, its accuracy can be a critical issue in the modeling because of the limitation the low resolution reflecting the physical properties of soil in a watershed. Accordingly, this study attempted to assess the effect of HWSD in modeling by comparing parameters of the rainfall-runoff model using HWSD with the detailed soil map. For this, Grid based Rainfall-runoff Model (GRM) was employed in the Hyangseok watershed. The results showed that both of two soil maps in the rainfall-runoff model are able to well capture the observed runoff. However, compared with the detailed soil map, HWSD produced more uncertainty in the GRM parameters related to soil depth and hydraulic conductivity during the calibrations than the detailed soil map. Therefore, the uncertainty from the limited information on soil texture in HWSD should be considered for better calibration of a rainfall-runoff model.

• Journal of Biosystems Engineering
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• v.27 no.3
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• pp.259-266
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• 2002

It is crucial to know spatial soil variability for precision farming. However, it is time-consuming, and difficult to measure spatial soil properties. Therefore, there are needs fur sensing technology to estimate spatial soil variability, and for electronic mapping technology to store, manipulate and process the sampled data. This research was conducted to develop a real-time soil organic matter sensor and an electronic mapping system. A soil organic matter sensor was developed with a spectrophotometer in the 900∼1,700 nm range. It was designed in a penetrator type to measure reflectance of soil at 15cm depth. The signal was calibrated with organic matter content (OMC) of the soil which was sampled in the field. The OMC was measured by the Walkeley-Black method. The soil OMCs were ranged from 0.07 to 7.96%. Statistical partial least square and principle component regression analyses were used as calibration methods. Coefficient of determination, standard error prediction and bias were 0.85 0.72 and -0.13, respectively. The electronic mapping system was consisted of the soil OMC sensor, a DGPS, a database and a makeshift vehicle. An algorithm was developed to acquire data on sampling position and its OMC and to store the data in the database. Fifty samples in fields were taken to make an N-fertilizer dosage map. Mean absolute error of these data was 0.59. The Kring method was used to interpolate data between sampling nodes. The interpolated data was used to make a soil OMC map. Also an N-fertilizer dosage map was drawn using the soil OMC map. The N-fertilizer dosage was determined by the fertilizing equation recommended by National Institute of Agricultural Science and Technology in Korea. Use of the N-fertilizer dosage map would increase precision fertilization up to 91% compared with conventional fertilization. Therefore, the developed electronic mapping system was feasible to not only precision determination of N-fertilizer dosage, but also reduction of environmental pollution.

• Journal of Environmental Science International
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• v.22 no.9
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• pp.1079-1088
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• 2013

The objective of this paper is compare to landuse type for calculating peak flood and soil loss in rapidly expansion urban area. This study compares two landuse maps, including numerical landuse map and aerial photograph landuse map, for calculating the ratio of urban and agriculural area, curve number, time of concentration, peak flood discharge, and soil loss. It is found that flood discharge calculated using aerial photograph landuse map are larger than that calculated using numerical landuse map, and soil loss calculated using aerial photograph landuse map are smaller than that calculated using numerical landuse map. Results also indicate that landuse chage in rapidly expansion urban area significantly influences flood discharge and soil loss.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.17-24
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• 2016

At present, summer cloudburst and local torrential rainfalls have increased in this country, because of climatic change. Therefore, studies on prevention of soil loss have been actively proceeded, and Korea Forest Service has offered landslide hazard map. Landslide hazard map divides risks into 5 classes, by giving weight with 9 kinds of elements. In August 25 2014, soil loss occurred in the whole Oryun Tunnel, Geumjeong-gu, Busan, because of local torrential heavy rain. As a result of comparing with landslide hazard map, the area where soil loss occurred in reality is a safety zone on hazard map. Rainfall, soil map, geological map, forest type map, gradient, drainage network, watershed, basin shape, and efflux of the whole Oryun Tunnel where soil loss occurred were analyzed. As a result of an analysis, it is judged that soil, forest type, much efflux and peak discharge, degree of water network and basin shape of a place where landslide occurred are causes of soil loss. It is judged that efflux, peak discharge, and basin shape by the localized rainfall that is not considered in landslide hazard map of them are the biggest causes of soil loss. It is judged that efflux, peak discharge, degree of water network and basin shape by the rainfall are important through a study on a causual analysis on soil loss in the whole Oryun Tunnel where is one of occurrence area where a lot of propertywere lost by the record local torrential rainfalls. A localized torrential downpour should be prepared by considering these elements on judgement of a landslide hazard area.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.11 no.2
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• pp.1-9
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• 2008

The objective of the study is 10 know the relation of landslide occurrence with using TPI (Topographic Position Index) in the Pyungchang County. Total 659 landslide scars were detected from aerial photographs. To analyze TPI, 100m SN (Small-Neighborhood) TPI map, 500m LN (Large-Neighborhood) TPI map, and slope map were generated from the DEM (Digital Elevation Model) data which are made from 1 : 5,000 digital topographic map. 10 classes clustered by regular condition after overlapping each TPI maps and slope map. Through this process, we could make landform classification map. Because it is only to classify landform, 7 classes were finally regrouped by the slope angle information of landslide occurrence detected from aerial photography analysis. The accuracy of reclassified map is about 46%.

• Journal of Biosystems Engineering
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• v.30 no.2 s.109
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• pp.127-133
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• 2005

Precision tillage is designed to till lands variably according to their firmness. Therefore, it is necessary to measure soil firmness in fields and present it in a form with which the variable tillage on be performed. Such forms may be classified into two categories: sensor-based and map-based forms. The map-based approach appears to be inevitable until the technology develops high enough to secure the sensor-based approaches. The first step for map-based precision tillage may be to develop a tillage recommendation map. In this study, a tractor-mountable automatic soil firmness measurement system was developed to construct a cone index map. The system is comprised of three ASAE Standard cone penetrometers and a hydraulic unit for controlling operation of the penetrometers. The system is designed to conduct stop-and-go measurements in fields. The measurements from the three penetrometers are transferred to a microcomputer and the average cone index was calculated. This average cone index was taken as soil firmness of the location where the measurement was made. The cone indices thus determined were used to construct a cone index map using the ArcView software. The system also displays the soil penetration resistance, cone index and soil depth as the cone penetrates into the soil. The field performance of the system was evaluated and the cone index maps at different depths were also presented.

• Journal of Environmental Science International
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• v.12 no.4
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• pp.447-459
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• 2003

This study was carried out to develop an efficient process far the elimination of phenol pollutant from soils. An microwave-assisted process (MAP) and a conventional Soxhlet extraction method (SEM) were employed to extract phenol from two types of soils. The effects of extraction methods, aged time of the spiked soil samples, extraction solvent and extraction time on the extraction performance were compared. Our results demonstrate that the recoveries from standard soil spiked were at least 10% higher fer MAP than these f3r the conventional Soxhlet. The extraction time by MAP requires significantly shelter time (1 min) than 15 h of the conventional Soxhlet. The recoveries from non-contaminated soil spiked with phenol were also almost identical f3r above results. The reduction of the extraction times with efficiency higher than that afforded by the conventional Soxhlet technique supports the suitability of the MAP method.

• Journal of Environmental Impact Assessment
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• v.25 no.6
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• pp.525-531
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• 2016

This study integrates the Universal Soil Loss Equation(USLE) with GIS method to assess the soil erosion for national land cover map between 2007 and 2014. The land cover change map and C factors of USLE were applied to the estimation of spatial distribution of sediment yield. However, they generated distinct results because of differences in their applied methods and calculation processes of national land cover map. To generate the USLE model, C factors of MOE(Ministry of Environment) were compared with soil erosion of Inje stadium development area at the Naerin watershed in Gangwon province to 2014. The several thematic maps of research area such as land cover map, topographic and soil maps, together with tabular precipitation data used for soil erosion calculation. The land cover change were carried with level-2 and high level land cover map of MOE and estimated maximum double of soil erosion.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.254-261
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• 2000

Soil chemical properties, relief of field surface, SPAD values and grain yield were investigated in a 0.5ha paddy field in 1999 to obtain basic field information for precision agriculture. Descriptive statistics of field information showed that the coefficient of variation ranged from 1.63% to 38.7%. Field information showed a high spatial dependence for within paddy field. The ranges of spatial dependence were from 15m to 60m, respectively. Kriged maps enable the visualization and comparison the spatial variability of field information. The causes of spatial variability of the field information could be explained rationally by a field management map. Grain yield was negatively correlated with pH, relief values, whereas, was positively correlated with total C, total N, C/N ratio, mineralizable N, available P and exchangeable K, Ca at the significant level of 1 %.

• Journal of Korea Water Resources Association
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• v.32 no.2
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• pp.163-176
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• 1999

Hydrology-based topographical informations generated by GIS techniques could be changed according to the selection of base map, algorithm of extraction, and so on. The purpose of this paper is to investigate the variation of SCS CN extracted by GIS technique and to propose the effective strategy for applying GIS to the rainfall-runoff simulation in ungaged basin. For experimental implementation, GIS spatial data, such as reconnaissance soil map, detailed interpretative soil map, landuse planning map and remotely sensed data(Landsat TM), were collected and generated to calculate the amount of effective rainfall in Pyungchang river basin. In applying SCS Runoff Curve Number to the test basin, the hydrological attribute data were analyzed. In addition, the characteristics of runoff responses according to the selection of GIS spatial data for SCS CN were reviewed. This study shows the applicability of GIS techniques to runoff simulation in ungaged basin by comparing with the measured flood hydrograph. It has been found that the detained interpretative soil map and remote sensing data are appropriate for calculating of SCS CN.