• Korean Journal of Soil Science and Fertilizer
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• v.49 no.1
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• pp.93-114
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• 2016

As a means of improving Korean Soil Classification System, we have reviewed Australian Soil Classification System by comparing Soil Taxonomy and FAO/WRB Classification System. Australian Soil Classification System is composed of 14 of Order, 87 of Sub-order, 556 of Great-group, 2,451 of Sub-group, and 7,276 of Family. Interestingly, soil order has the Anthroposols which is not classified with Soil Taxonomy, and the classification for some of soils is based on soil texture abruption horizon and soil structure. Seven of 14 soil orders are classified with an old version based on soil color rather than morphological characteristics. The distribution scale of Australian soil order is the largest in Tenosols, and followed by Kandosols, Rudosols, Sodosols and Vertisols in Australia.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.3
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• pp.153-162
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• 2015

Land information is important for the international agricultural companies. This study investigated the agriculture and soil information in Sri Lanka. This study is the results from investigation of soil properties and agricultural properties determined by the Soil Taxonomy classification system for the soils in Sri Lanka. The order of the main agricultural imports in Sri Lanka was wheat > refined Sugar > dry Onion > Rice > Lentils. The climate of Sri Lanka is divided into three climatic zones. There are a wet zone, an intermediate zone, and a dry zone. Rainfall of the wet zone was $3,000-5,000mm\;year^{-1}$. The rainfall of the dry zone was less than $1,000m^{-1}$. The intermediate zone was in the middle area. Soil series of Sri Lanka were 109 in total. Detailed information of soil series was: 6 of soil Orders, 15 of Suborders, 39 of Great groups, and 56 of Subgroups. Soil texture of topsoil was much more coarse, but subsoil was gravelly coarse soil. Soil of Sri Lanka was classified as a Soil Order. The orders were Entisols > Alfisols > Ultisols > Inceptisols > Histosols > Vertisols.

• Korean Journal of Soil Science and Fertilizer
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• v.46 no.2
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• pp.92-98
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• 2013

The objective of this study was to establish the decision criteria of soil suitability for Korean Black raspberry using soil morphological and physical properties. The investigation was carried out in Gochang, Sunchang, Jeongeup, Pohang, and Hoengseong districts in Korea. The obtained results showed that factors related to the decision criteria of the soil suitability for Korean Black raspberry cultivation were soil texture, soil drainage class, land slope, and available soil depth. The criteria of the best suitability soil for Korean Black raspberry was valley/fan or hill geomorphology, well or moderately drainage class, B-slope(2-7%), coarse loamy soil texture family, less than <15% gravel contents, and available soil depth deeper than 100cm. The area criteria of soil suitability for Korean Black raspberry of Gochang was more than 50% including best and suitable areas.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.57-70
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• 2017

In this study, we evaluated daily root zone soil moisture dynamics and agricultural drought using a near-surface soil moisture data assimilation scheme with Soil Moisture Active & Passive (SMAP, $3km{\times}3km$) soil moisture footprints under different hydro-climate conditions. Satellite-based LANDSAT and MODIS image footprints were converted to spatially-distributed soil moisture estimates based on the regression model, and the converted soil moisture distributions were used for assessing uncertainties and applicability of SMAP data at fields. In order to overcome drawbacks of the discontinuity of SMAP data at the spatio-temporal scales, the data assimilation was applied to SMAP for estimating daily soil moisture dynamics at the spatial domain. Then, daily soil moisture values were used to estimate weekly agricultural drought based on the Soil Moisture Deficit Index (SMDI). The Yongdam-dam and Soyan river-dam watersheds were selected for validating our proposed approach. As a results, the MODIS/SMAP soil moisture values were relatively overestimated compared to those of the TDR-based measurements and LANDSAT data. When we applied the data assimilation scheme to SMAP, uncertainties were highly reduced compared to the TDR measurements. The estimated daily root zone soil moisture dynamics and agricultural drought from SMAP showed the variability at the sptio-temporal scales indicating that soil moisture values are influenced by not only the precipitation, but also the land surface characteristics. These findings can be useful for establishing efficient water management plans in hydrology and agricultural drought.

• Korean Journal of Soil Science and Fertilizer
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• v.46 no.6
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• pp.536-541
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• 2013

In Soil Taxonomy system, anthropogenic soils are still classified as Entisols since the International Classification Committee for Anthropogenic Soils is in the process of classifying anthropogenic soils as new orders. In reality, it is difficult to characterize anthropogenic soils because Soil Taxonomy (ST) system does not distinguish between natural and anthropogenic Entisols. On the other hand, World Reference Base for soil resources (WRB) considers human impacts on soils and contains an independent category of anthropogenic soils, which makes easier to understand anthropogenic soil characteristics than Soil Taxonomy system. A remodeled paddy field (Gasan) was selected to classify by ST and WRB. Soil samples were taken to analyze chemical and physical properties. Based on the results of the analyses, the ST system classified Gasan as coarse loamy, mixed, mesic, Aquic Udorthents while the WRB did as Stagnic Urbic Technosols (Oxyaquic, Arenic). As a conclusion, the WRB classification information of the anthropogenic provides more detail characteristics of the anthropogenic soils.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.2
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• pp.100-105
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• 2017

Various methods for assessing soil total nitrogen (TN) and inorganic N content have been developed to manage nutrient and to understand N cycle in soil. This paper address the technical procedures in arable soil samples to conduct soil sampling, sample preparation, and measuring total N and inorganic N. Among various methods for measuring soil total nitrogen contents, Kjeldahl distillation and Indophenol blue method have widely used due to reliability and economic advances. Also, two methods can analyze more samples at the same time compared with other nitrogen measuring methods. For evaluating inorganic N content, mainly in forms of nitrate-N ($NO_3{^-}-N$) and ammonium-N ($NH_4{^+}-N$), extraction with a single reagent such as 2M KCl has been employed, followed by Kjeldahl distillation or indophenol blue methods.

• Korean Journal of Soil Science and Fertilizer
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• v.42
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• pp.28-52
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• 2009

• Korean Journal of Agricultural Science
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• v.43 no.4
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• pp.537-546
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• 2016

The development of models for agriculture systems, especially for crop production, has supported the prediction of crop yields under various environmental change scenarios and the selection of better crop species or cultivar. Crop models could be used as tools for supporting reasonable nutrient management approaches for agricultural land. This paper outlines the simplified structure of main crop models (crop growth model, crop-soil model, and crop-soil-environment model) frequently used in agricultural systems and shows diverse application of their simulated results. Crop growth models such as LINTUL, SUCROS, could provide simulated data for daily growth, potential production, and photosynthesis assimilate partitioning to various organs with different physiological stages, and for evaluating crop nutrient demand. Crop-Soil models (DSSAT, APSIM, WOFOST, QUEFTS) simulate growth, development, and yields of crops; soil processes describing nutrient uptake from root zone; and soil nutrient supply capability, e.g., mineralization/decomposition of soil organic matter. The crop model built for the DSSAT family software has limitations in spatial variability due to its simulation mechanism based on a single homogeneous field unit. To introduce well-performing crop models, the potential applications for crop-soil-environment models such as DSSAT, APSIM, or even a newly designed model, should first be compared. The parameterization of various crops under different cultivation conditions like those of intensive farming systems common in Korea, shortened crop growth period, should be considered as well as various resource inputs.

• Journal of Korean Society on Water Environment
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• v.24 no.2
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• pp.185-194
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• 2008

There is increased soil erosion potential at highland agricultural crop fields because of its topographic characteristics and site-specific agricultural management practices performed at these areas. The agricultural upland fields are usually located at the sloping areas, resulting in higher soil loss, pesticides, and nutrients in case of torrential rainfall events or typhoon, such as 2002 Rusa and 2003 MaeMi. At the highland agricultural fields, the soil reconditioning have been performed every year to decrease damage by continuous cropping and pests. Also it has been done to increase crop productivity and soil fertility. The increased amounts of soil used for soil reconditioning are increasing over the years, causing significant impacts on water quality at the receiving water bodies. In this study, the field investigation was done to check soil reconditioning status for potato, carrot, and cabbage at the Doam-dam watershed. With these data obtained from the field investigation, the Soil and Water Assesment Tool (SWAT) model was used to simulate the soil loss reduction with environment-friendly and agronomically enough soil reconditioning. The average soil reconditioning depth for potato was 34.3 cm, 48.3 cm for carrot, and 31.2 cm for cabbage at the Doam-dam watershed. These data were used for SWAT model runs. Before the SWAT simulation, the SWAT ArcView GIS Patch, developed by the Kangwon National University, was applied because of proper simulation of soil erosion and sediment yield at the sloping watershed, such as the Doam-dam watershed. With this patch applied, the Coefficient of Determination ($R^2$) value was 0.85 and the Nash-Sutcliffe Model Efficiency (EI) was 0.75 for flow calibration. The $R^2$ value was 0.87 and the EI was 0.85 for flow validation. For sediment simulation, the $R^2$ value was 0.91 and the EI was 0.70, indicating the SWAT model predicts the soil erosion processes and sediment yield at the Doam-dam watershed. With the calibrated and validated SWAT for the Doam-dam watershed, the soil erosion reduction was investigated for potato, carrot, and cabbage. For potato, around 19.3 cm of soil were over applied to the agricultural field, causing 146% of more soil erosion rate, approximately 33.3 cm, causing 146% of more soil erosion for carrot, and approximately 16.2 cm, causing 44% of more soil erosion. The results obtained in this study showed that excessive soil reconditioning are performed at the highland agricultural fields, causing severe muddy water issues and water quality degradation at the Doam-water watershed. The results can be used to develop soil reconditioning standard policy for various crops at the highland agricultural fields, without causing problems agronomically and environmentally.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.1
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• pp.21-28
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• 2009

Detailed information on soil characteristics is of great importance for the use and conservation of soil resources that are essential for human welfare and ecosystem sustainability. This paper introduces soil inventory of Korea focusing on national soil database establishment, information systems, use, and future direction for natural resources management. Different scales of soil maps surveyed and soil test data collected by RDA (Rural Development Administration) were computerized to construct digital soil maps and database. Soil chemical properties and heavy metal concentrations in agricultural soils including vulnerable agricultural soils were investigated regularly at fixed sampling points. Internet-based information systems for soil and agro-environmental resources were developed based on 'National Soil Survey Projects' for managing soil resources and for providing soil information to the public, and 'Agroenvironmental Change Monitoring Project' to monitor spatial and temporal changes of agricultural environment will be opened soon. Soils data has a great potential of further application in estimation of soil carbon storage, water capacity, and soil loss. Digital mapping of soil and environment using state-of-the-art and emerging technologies with a pedometrics concept will lead to future direction.