• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.4
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• pp.221-237
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• 2005

For developing the site-specific fertilizer management strategies of crop, it is essential to know the spatial variability of soil factors and to assess their influence on the variability of crop growth and yield. In 2002 and 2003 cropping seasons within-field spatial variability of rice growth and yield was examined in relation to spatial variation of soil properties in the· two paddy fields having each area of ca. $6,600m^2$ in Suwon, Korea. The fields were managed without fertilizer or with uniform application of N, P, and K fertilizer under direct-seeded and transplanted rice. Stable soil properties such as content of clay (Clay), total nitrogen (TN), organic mater (OM), silica (Si), cation exchange capacity (CEC), and rice growth and yield were measured in each grid of $10\times10m$. The two fields showed quite similar spatial variation in soil properties, showing the smallest coefficient of variation (CV) in Clay $(7.6\%)$ and the largest in Si $(21.4\%)$. The CV of plant growth parameters measured at panicle initiation (PIS) and heading stage (HD) ranged from 6 to $38\%$, and that of rice yield ranged from 11 to $21\%$. CEC, OM, TN, and available Si showed significant correlations with rice growth and yield. Multiple linear regression model with stepwise procedure selected independent variables of N fertilizer level, climate condition and soil properties, explaining as much as $76\%$ of yield variability, of which $21.6\%$ is ascribed to soil properties. Among the soil properties, the most important soil factors causing yield spatial variability was OM, followed by Si, TN, and CEC. Boundary line response of rice yield to soil properties was represented well by Mitcherich equation (negative exponential equation) that was used to quantify the influence of soil properties on rice yield, and then the Law of the Minimum was used to identify the soil limiting factor for each grid. This boundary line approach using five stable soil properties as limiting factor explained an average of about $50\%$ of the spatial yield variability. Although the determination coefficient was not very high, an advantage of the method was that it identified clearly which soil parameter was yield limiting factor and where it was distributed in the field.

• Geomechanics and Engineering
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• v.36 no.6
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• pp.631-640
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• 2024

In the traditional slope stability analysis, ignoring the spatial variability of slope soil will lead to inaccurate analysis. In this paper, the K-L series expansion method is adopted to simulate random field of soil strength parameters. Based on Random Limit Equilibrium Method (RLEM), the influence of variation coefficient and fluctuation range on reliability of soil slope supported by micro-pile is investigated. The results show that the fluctuation ranges and the variation coefficients significantly influence the failure probability of soil slope supported by micro-pile. With the increase of fluctuation range of soil strength parameters, the mean safety factor of the slope increases slightly. The failure probability of the soil slope increases with the increase of fluctuation range when the mean safety factor of the slope is greater than 1. The failure probability of the slope increases by nearly 8.5% when the fluctuation range is increased from δ_v=2 m to δ_v =8 m. With the increase of the variation coefficient of soil strength parameters, the mean safety factor of the slope decreases slightly, and the probability of failure of soil slope increases accordingly. The failure probability of the slope increases by nearly 31% when the variation coefficient increases from COV_c=0.2, COV_φ=0.05 to COV_c=0.5, COV_φ=0.2.

• Geomechanics and Engineering
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• v.23 no.5
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• pp.419-429
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• 2020

To investigate the effect of spatial variability on hydraulic properties of unsaturated soils, a numerical model is set up which can simulate seepage process in an unsaturated heterogeneous soil. The unsaturated heterogeneous soil is composed of matrix sand embedded with a small proportion of clay for simulating the heterogeneity. Soil-water characteristic curve and unsaturated hydraulic conductivity curve of the unsaturated soil are expressed by Van Genuchten model. Hydraulic parameters of the matrix sand are considered as random fields. Different autocorrelation lengths (ACLs) of hydraulic parameter of the matrix sand and different proportions of clay are assumed to investigate the influence of spatial variability on the equivalent hydraulic properties of the heterogeneous soil. Four model sizes are used in the numerical experiments to investigate the influence of scale effects and to determine the sizes of representative volume element (RVE) in the numerical simulations. Through a number of Monte Carlo simulations of unsaturated seepage analysis, the means and the coefficients of variations (COVs) of the equivalent hydraulic parameters of the heterogeneous soil are calculated. Simulations show that the ACL and model size has little influence on the means of the equivalent hydraulic parameters, but they have a large influence on the COVs of the equivalent hydraulic parameters. The size of an RVE is mainly affected by the ACL and the proportion of heterogeneity. The influence of spatial variability on the hydraulic parameters of the heterogeneous unsaturated soil can be used as a guidance for geotechnical reliability analysis and design related to unsaturated soils.

• Journal of Korean Society on Water Environment
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• v.37 no.3
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• pp.204-216
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• 2021

It is important to understand the factors influencing the temporal and spatial variability of water quality in order to establish an effective customized management strategy for contaminated aquatic ecosystems. In this study, the spatial diversity of the 5-year (2015 - 2019) average total phosphorus (TP) concentration observed in 40 Total Maximum Daily Loads unit-basins in the Nakdong River watershed was analyzed using 50 predictive variables of watershed characteristics, climate characteristics, land use characteristics, and soil characteristics. Cross-correlation analysis, a two-stage exhaustive search approach, and Bayesian inference were applied to identify predictors that best matched the time-averaged TP. The predictors that were finally identified included watershed altitude, precipitation in fall, precipitation in winter, residential area, public facilities area, paddy field, soil available phosphate, soil magnesium, soil available silicic acid, and soil potassium. Among them, it was found that the most influential factors for the spatial difference of TP were watershed altitude in watershed characteristics, public facilities area in land use characteristics, and soil available silicic acid in soil characteristics. This means that artificial factors have a great influence on the spatial variability of TP. It is expected that the proposed statistical modeling approach can be applied to the identification of major factors affecting the spatial variability of the temporal average state of various water quality parameters.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.5
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• pp.81-90
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• 2016

Due to droughts and water shortages causing severe damage to crops and other vegetations, much attention has been given to efficient irrigation for upland farming. However, little information has been known to measure soil moisture levels in a field scale and apply their spatial variability for proper irrigation scheduling. This study aimed to characterize the spatial variability and temporal stability of soil water contents at depths of 10 cm, 20 cm and 30 cm on flat (loamy soil) and hill-slope fields (silt-loamy soil). Field monitoring of soil moisture contents was used for variogram analysis using GS+ software. Kriging produced from the structural parameters of variogram was applied for the means of spatial prediction. The overall results showed that the surface soil moisture presented a strong spatial dependence at the sampling time and space in the field scale. The coefficient variation (CV) of soil moisture was within 7.0~31.3 % in a flat field and 8.3~39.4 % in a hill-slope field, which was noticeable in the dry season rather than the rainy season. The drought assessment analysis showed that only one day (Dec. 21st) was determined as dry (20.4 % and 24.5 % for flat and hill-slope fields, respectively). In contrary to a hill-slope field where the full irrigation was necessary, the centralized irrigation scheme was appeared to be more effective for a flat field based on the spatial variability of soil moisture contents. The findings of this study clearly showed that the geostatistical analysis of soil moisture contents greatly contributes to proper irrigation scheduling for water-efficient irrigation with maximal crop productivity and environmental benefits.

• Geomechanics and Engineering
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• v.12 no.3
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• pp.483-503
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• 2017

Uncertainty is a fact belonging to engineering practice. An important uncertainty that sets geotechnical engineering is the variability associated with the properties of soils or, more precisely, the characterization of soil profiles. The reason is due largely to the complex and varied natural processes associated with the formation of soil. Spatial variability analysis for the study of the stability of natural slopes, complementing conventional analyses, is able to incorporate these uncertainties. In this paper the characterization is performed in back-analysis for a case of landslide occurred to verify afterwards the presence of the conditions of shear strength at failure. This approach may support designers to make more accurate estimates regarding slope failure responding, more consciously, to the legislation dispositions about slope stability evaluation and future design. By applying different kriging techniques used for spatial analysis it has been possible to perform a 3D-slope reconstruction. The predictive analysis and the areal mapping of the soil mechanical characteristics would support the definition of priority interventions in the zones characterized by more critical values as well as slope potential instability. This tool of analysis aims to support decision-making by directing project planning through the efficient allocation of available resources.

• Agricultural and Biosystems Engineering
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• v.6 no.2
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• pp.39-46
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• 2005

Because soil compaction is a concern in crop production and environmental pollution, quantification and management of spatial and vertical variability in soil compaction for soil strength) would be a useful aspect of site -specific field management. In this paper, a soil strength profile sensor (SSPS) that could take measurements continuously while traveling across the field was developed and the performance was evaluated through laboratory and field tests. The SSPS obtained data simultaneously at 5 evenly spaced depths up to 50 em using an array of load cells, each of which was interfaced with a soil-cutting tip. Means of soil strength measurements collected in adjacent, parallel transects were not significantly different, confirming the repeatability of soil strength sensing with the SSPS. Maps created with sensor data showed spatial and vertical variability in soil strength. Depth to the restrictive layer was different for different field locations, and only 5 to 16% of the tested field areas were highly compacted.

• Proceedings of the Korean Quaternary Association Conference
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• 2005.06a
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• pp.7-11
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• 2005

The soil erosion processes have estimated using spatial distribution of 137Cs radionuclide in Granite and Sedimentary Hillslopes in South Korea. The local variability of 137Cs inventory indicates that was related positively to organic matter content, clay content and water content and negatively to hydraulic permeability and slope gradient for bulk samples in different landforms within Granite and Sedimentary rock basins. The vertical variability of 137Cs inventory shows that most of 137Cs concentration and organic matter were accumulated between 0 and 2cms and gradually decrease with soil depth in incremental samples in both basins. The vertical variability of 137Cs inventories shows that 137Csinventories increase as we go to toward downslope in both basins. Finally, the soil loss values indicate that hillslope erosion processes are more intensive in Granite rock basin than those in Sedimentary rock basin.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4B
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• pp.329-334
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• 2006

The spatial variability of the L- and C- band large scale remotely sensed soil moisture data, obtained during the Southern Great Plain 1999 Experiment (SGP'99), was characterized. The results demonstrate that soil moisture data using L-band show the break in statistical symmetry (multiscaling behavior) with the variation of scale of observation, which is similar to that of the soil property such as sand content. Also, soil moisture data using C-band show single scaling behavior with the variation of scale of observation, which is similar to that of the vegetation condition. The results should be considered during downscaling the Global soil moisture data using AMSR instrument.

• Journal of Biosystems Engineering
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• v.39 no.1
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• pp.39-46
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• 2014

Purpose: Monitoring and control of environmental condition is highly important for optimum control of the conditions, especially in greenhouses and plant factories, and the condition is not uniform within the facility. Objectives of the study were to investigate variability in soil water content and to provide information useful for better irrigation control. Methods: Experiments were conducted in a strawberry-growing greenhouse (greenhouse 1) and a cherry tomato-growing greenhouse (greenhouse 2) in winter. Soil water content, electrical conductivity (EC), and temperature were measured over the entire area, at different distances from an irrigation pump, and on ridge and furrow areas. Results: When measured over the entire greenhouse area, soil water content decreased and temperature and electrical conductivity increased over time from morning to afternoon after irrigation. Water content decreased by distance from the irrigation pump up to 70 m and increased after that, and temperature showed an inverse pattern. Soil water contents on the ridge were lower than those on the furrow, and the differences were 10.2~18.4%, indicating considerable variability. The lowest EC were observed on the furrow and highest values were observed on the ridge. Soil water contents were less and temperature levels were greater at the window side than in the center locations. Conclusions: Selection of number and location of soil water content sensor would be the first step for better water content monitoring and irrigation control. Results of the study would provide basic data useful for optimum sensor location and control for underground greenhouse environment.