• Korean Journal of Soil Science and Fertilizer
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• v.39 no.3
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• pp.123-135
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• 2006

Spatial variability and distribution map of soil properties and the relationships between soil properties and crop yields are not well characterized in agroecosystems that have been land leveled to facilitate more cultivation of the new reclaimed sloping highland. Potato, onion, carrot, Chinese cabbage and radish were grown on the coarse sandy loam soil in 2004. Soil moisture content, soil penetration resistance and crop yield were sampled in the $10m{\times}50m$ field consisted of five plots. Sampling sites of each cultivation plot were 33 for the soil moisture, 11 for the soil penetration and 33 for the crop yield. The results of semivariance analysis, most of models were shown spherical equation. The significant ranges of each spatial variability model for the soil moisture, soil penetration and crop yield were broad as 33-35 meters in the potato cultivation plot, and that in the Chinese cabbage cultivation plot was narrow as 5-6 meters. The coefficient of variances (C.V.) of moisture, penetration and yield were various from 14 to 59 percents in five cultivation plots. The highest C.V. of potato yield was 59 percents, and that of the radish cultivation plot was as low as 14 percents. The required sample numbers for the determination of soil moisture content, soil penetration resistance and crop yield with error 10% at 0.05 significant level were ranged 8-40 for soil moisture, 7-25 for soil penetration and 424-4,678 for crop yield. The variogram and distribution map by kriging described field characteristics well so that the spatial variability would be useful for soil management for better efficiency and precision agriculture in the reclaimed highland.

• Journal of Soil and Groundwater Environment
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• v.7 no.3
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• pp.3-17
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• 2002

Data analysis of groundwater monitoring wells and geostatistical methods are used to identify the local characteristics of sea water intrusion and the range of sea water intrusion at the southeastern coastal area of Busan, Korea. Rainfall and groundwater level of two monitoring wells show a linear correlation because of the direct groundwater recharge by the precipitation. However, rainfall and electric conductivity have the inverse relationship because of the increase of groundwater. Electric conductivity rapidly increased at 24m depth and exceeded 20,000$\mu\textrm{s}$/cm near 26m depth in the monitoring wells. The variations of groundwater level and electric conductivity show that the interface between sea water and fresh water tends to move upward when groundwater level goes down. In the cross correlation analysis, groundwater level versus rainfall represents the largest cross correlation coefficient in 0 time lag but the cross correlation coefficient of electric conductivity versus rainfall is the largest when the time lag is 9 days. This suggests that the fluctuations of groundwater level respond to rainfall in a short time, but the interface between sea water and fresh water respond very slow to rainfall. Horizontal extents of sea water intrusion are estimated to 14 m from the east of Line 1, and 25 m from the southeast end of Line 2 in the inversion of dipole-dipole profiling data of two survey lines. The data of VES by the Schulumberger array in May and July show lognormal distributions. In the kriged apparent resistivity and earth resistivity distributions, the resistivities of July are increased comparing to those of May. This reflects that the concentration of sea water in aquifer is reduced due to the increased groundwater recharge from the rainfall in June and July. In analyzing the vertical and horizontal apparent resistivities and earth resistivity distributions, the geostatistical methods are very useful to identify the variations of earth resistivity distributions at the coastal area.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.2
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• pp.357-367
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• 2018

Recent earthquakes in Gyeongju and Pohang have raised interest in liquefaction in South Korea. Liquefaction, which is a phenomenon that excessive pore pressure is generated and the shear strength of soil is decreased by repeated loads such as earthquakes, causes severe problems such as ground subsidence and overturning of structures. Therefore, it is necessary to identify and prepare for the possibility of liquefaction in advance. In general, the possibility of liquefaction is quantitatively assessed using the Liquefaction Potential Index (LPI), but it takes a lot of time and effort for performing site response analysis which is essential for the liquefaction evaluation. In this study, a simple method to evaluate the liquefaction potential without executing the site response analysis in a downtown area with a lot of borehole data was proposed. In this simple method, the correlation between the average shear wave velocity of the target location ground and the LPI divided by thickness of liquefiable layer was established. And the applicable correlation equation for various rock outcrop accelerations were derived. Using the 104 boreholes information in Seoul, the correlation equation between LPI and the shear wave velocity (ground water level: 0m, 1m, 2m, 3m) is obtained and the possibility of liquefaction occurrence in Seoul and Gyeongju is evaluated. The applicability of the proposed simple method was verified by comparing the LPI values calculated from the correlation equation and the LPI values derived using the existing site response analysis. Finally, the distribution map of LPI calculated from the correlation was drawn using Kriging, a geostatistical technique.

• Economic and Environmental Geology
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• v.38 no.4 s.173
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• pp.435-450
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• 2005

The purpose of the study is to analyze the hydrogeochemical characteristics by multivariate statistical method, to interpret the hydrogeochemical processes for the new variables calculated from principal components analysis (PCA), and to infer the groundwater flow and circulation mechanism by applying the geostatistical methods for each element and principal component. Chloride and nitrate are the most influencing components for groundwater quality, and the contents of $NO_3$ increased by the input of agricultural activities show the largest variation. The results of PCA, a multivariate statistical method, show that the first three principal components explain $73.9\%$ of the total variance. PC1 indicates the increase of dissolved ions, PC2 is related with the dissolution of carbonate minerals and nitrate contamination, and PC3 shows the effect of cation exchange process and silicate mineral dissolution. From the results of experimental semivariogram, the components of groundwater are divided into two groups: one group includes electrical conductivity (EC), Cl, Na, and $NO_3$, and the other includes $HCO_3,\;SiO_2,$ Ca, and Sr. The results for spatial distribution of groundwater components showed that EC, Cl, and Na increased with approaching the coastal line and nitrate has close relationship with the presence of agricultural land. These components are also correlated with the topographic features reflecting the groundwater recharge effect. The kriging analysis by using principal components shows that PC 1 has the different spatial distribution of Cl, Na, and EC, possibly due to the influence of pH, Ca, Sr, and $HCO_3$ for PC1. It was considered that the linear anomaly zone of PC2 in western area was caused by the dissolution of carbonate mineral. Consequently, the application of multivariate and geostatistical methods for groundwater in the study area is very useful for determining the quantitative analysis of water quality data and the characteristics of spatial distribution.

• Korean Journal of Soil Science and Fertilizer
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• v.22 no.4
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• pp.257-264
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• 1989

In order to study spatial variability of soil chemical properties across the land-partitioned boundary on Hwadong silt clay loam soil (Fine clayey, mixed, mesic family of Aquic Hapludalfs) in the experimental fie ld of the wheat and Barley Research Institute in Suwon, all measured data were analyzed by means of kriging, fractile diagram, smooth frequency distribution, and autocorrelation. Sampling for soil chemical property analysis was made at 225 intersections of 15x 15 grid with 10m interval from three soil depths (0-10cm, 25-35cm, 50-60cm) in the seven patitioned fields. 1. The coefficient of variance (CV) of various chemical properties varied from 5.4 to 72.7%. Soil pH was classified into the low variation group with CV smaller than 10%, while the other chemical properties belonged to the medium variation group with C.V. between 10 and 100% 2. The approximate number of soil samples for the determination of various chemical properties with error smaller than 10% were two for pH, ten for CEC, 15 for exchangeable Ca, 32 for total nitrogen content, 39 for exchangeable Mg, 40 for exchangeable K, 61 for exchangeable Na, 82 for organic matter content, 212 for available phosphate,. 3. Smooth frequency distribution and fractile diagram showed that available phosphate was in log-normal distribution while others were in normal distribution. 4. Serial correlation analysis revaled that the soil chemical properties had spatial dependence between two nearest neighbouring grid points. Autocorrelation analysis of chemcial properties measured between the serial grid points in the direction of south to north following land-partitioned boundary showed that the zone of influence showing stationarity ranged from 20 to 50m. In the direction of east to west accross land-partitioned boundary, the autocorrelogram of many chemical properies showed peaks with the periodic interval of 30m, which were similar to the partitioned land width. This reveals that the land-partitioned boundary causes soil variability.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.804-811
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• 2010

The lower portion of sloping paddy fields normally contains excessive moisture and the higher water table caused by the inflow of ground water from the upper part of the field resulting in non-uniform water content distribution. Four drainage methods namely Open Ditch, Vinyl Barrier, Pipe Drainage and Tube Bundle for multiple land use were installed within 1-m position from the lower edge of the upper embankment of sloping alluvial paddy fields. Knowledge of the spatial variability of soil water properties is of primary importance for management of agricultural lands. This study was conducted to evaluate the effect of drainage in the soil on spatial variability of soil water content using the geostatistical analysis. The soil water content was collected by a TDR (Time Domain Reflectometry) sensor after the installation of subsurface drainage on regular square grid of 80 m at 20 m paddy field located at Oesan-ri, Buk-myeon, Changwon-si in alluvial slopping paddy fields ($35^{\circ}22^{\prime}$ N, $128^{\circ}35^{\prime}$). In order to obtain the most accurate field information, the sampling grid was divided 3 m by 3 m unit mesh by four drainage types. The results showed that spatial variance of soil water content by subsurface drainage was reduced, though yield of soybean showed the same trends. Value of "sill" of soil water content with semivariogram was 9.7 in Pipe Drainage, 86.2 in Open Ditch, and 66.8 in Vinyl Barrier and 15.7 in Tube Bundle.

• Journal of Korean Society of Forest Science
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• v.110 no.3
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• pp.322-340
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• 2021

Due to climate change and its consequential spring temperature rise, flowering time of Robinia pseudoacacia has advanced and a simultaneous blooming phenomenon occurred in different regions in South Korea. These changes in flowering time became a major crisis in the domestic beekeeping industry and the demand for accurate prediction of flowering time for R. pseudoacacia is increasing. In this study, we developed and compared performance of four different models predicting flowering time of R. pseudoacacia for the entire country: a Single Model for the country (SM), Modified Single Model (MSM) using correction factors derived from SM, Group Model (GM) estimating parameters for each region, and Local Model (LM) estimating parameters for each site. To achieve this goal, the bloom date data observed at 26 points across the country for the past 12 years (2006-2017) and daily temperature data were used. As a result, bloom dates for the north central region, where spring temperature increase was more than two-fold higher than southern regions, have advanced and the differences compared with the southwest region decreased by 0.7098 days per year (p-value=0.0417). Model comparisons showed MSM and LM performed better than the other models, as shown by 24% and 15% lower RMSE than SM, respectively. Furthermore, validation with 16 additional sites for 4 years revealed co-krigging of LM showed better performance than expansion of MSM for the entire nation (RMSE: p-value=0.0118, Bias: p-value=0.0471). This study improved predictions of bloom dates for R. pseudoacacia and proposed methods for reliable expansion to the entire nation.