• Journal of Korean Society of Forest Science
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• v.103 no.1
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• pp.98-104
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• 2014

This study aims to predict the amount of soil loss from Mt. Palgong's small basin, by using influence factors derived from related models, including RUSLE and MUSLE models, and verify the validity of the model through a comparative analysis of the predicted values and measured values, and the results are as follows: The amount of soil loss were greatly affected by LS factor. In comparison with the measured value of the amount of total soil loss, the predicted values by the two models (RUSLE and MUSLE), appeared to be higher than those of the measured soil loss. Predicted values by RUSLE were closer to values of measured soil loss than those of MUSLE. However, coefficient of variation of MUSLE were lower, but two model's coefficient of variation in similar partial patterns in the prediction of soil loss. RUSLE and MUSLE, prediction soil loss models, proved to be appropriate for use in small mountainous basin. To improve accuracy of prediction of soil loss models, more effort should be directed to collect more data on rainfall-runoff interaction and continuous studies to find more detailed influence factors to be used in soil loss model such as RUSLE and MUSLE.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.529-534
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• 2009

Climate models, both global and regional, have increased in sophistication and are being run at increasingly higher resolutions. The Land Surface Models (LSMs) coupled to these climate models have evolved from simple bucket models to sophisticated Soil-Vegetation-Atmosphere Transfer (SVAT) schemes needed to support complex linkages and processes. However, some underpinnings of terrestrial hydrologic parameterizations so crucial in the predictions of surface water and energy fluxes cause model errors that often manifest as non-linear drifts in the dynamic response of land surface processes. This requires the improved parameterizations of key processes for the terrestrial hydrologic scheme to improve the model predictability in surface water and energy fluxes. The Common Land Model (CLM), one of state-of-the-art LSMs, is the land component of the Community Climate System Model (CCSM). However, CLM also has energy and water biases resulting from deficiencies in some parameterizations related to hydrological processes. This research presents the implementation of a selected set of parameterizations and their effects on the runoff prediction. The modifications consist of new parameterizations for soil hydraulic conductivity, water table depth, frozen soil, soil water availability, and topographically controlled baseflow. The results from a set of offline simulations are compared with observed data to assess the performance of the new model. It is expected that the advanced terrestrial hydrologic scheme coupled to the current CLM can improve model predictability for better prediction of runoff that has a large impact on the surface water and energy balance crucial to climate variability and change studies.

• Journal of the Korean Geotechnical Society
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• v.20 no.7
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• pp.171-181
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• 2004

This study was conducted to explore the tensile strength models in granular soil at the full range of unsaturated state. Direct tension experiments were carried out with a newly developed direct tension technique. The measured experimental data were compared with theoretical models developed by Rumpf and Schubert for monosized ideal particulate solids at the unsaturated state. To do this, the soil-water characteristic curve obtained from a suction-saturation experiment was used to define the unsaturation state and the negative pore water pressure with different water content levels, which are important factors in theoretical tensile strength models. The nonlinear behavior of the tensile strength for unsaturated granular soil at the pendular state is appropriately simulated with Rumpf's model. For the funicular and capillary states, the predicted trend by Schubert's model is properly matched with the experimental data: tensile strength steadily increases and reaches a maximum value and then decreases until it reaches zero. This comparison supports the concept that the tensile strength of unsaturated real granular soil can be approximately simulated with theoretical models.

• Geomechanics and Engineering
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• v.20 no.3
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• pp.191-205
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• 2020

Soil shear strength parameters play a remarkable role in designing geotechnical structures such as retaining wall and dam. This study puts an effort to propose two accurate and practical predictive models of soil shear strength parameters via hybrid artificial neural network (ANN)-based models namely genetic algorithm (GA)-ANN and particle swarm optimization (PSO)-ANN. To reach the aim of this study, a series of consolidated undrained Triaxial tests were conducted to survey inherent strength increase due to addition of polypropylene fibers to sandy soil. Fiber material with different lengths and percentages were considered to be mixed with sandy soil to evaluate cohesion (as one of shear strength parameter) values. The obtained results from laboratory tests showed that fiber percentage, fiber length, deviator stress and pore water pressure have a significant impact on cohesion values and due to that, these parameters were selected as model inputs. Many GA-ANN and PSO-ANN models were constructed based on the most effective parameters of these models. Based on the simulation results and the computed indices' values, it is observed that the developed GA-ANN model with training and testing coefficient of determination values of 0.957 and 0.950, respectively, performs better than the proposed PSO-ANN model giving coefficient of determination values of 0.938 and 0.943 for training and testing sets, respectively. Therefore, GA-ANN can provide a new applicable model to effectively predict cohesion of fiber-reinforced sandy soil.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.4
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• pp.1-11
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• 2013

Unsaturated hydraulic conductivity function is one of key parameters to solve the flow phenomena in problems of landslide. Prediction models for hydraulic conductivity function related to soil-water retention curve equations in many geotechnical applications have been still used instead of direct measurement of the hydraulic conductivity function since prediction models from soil-water retention curve equations are attractive for their fast and easy use and low cost. However, many researchers found that prediction models for the hydraulic conductivity function can not predict the hydraulic conductivity exactly in comparison with experimental outputs. This research introduced an inverse analysis to evaluate the hydraulic conductivity function corresponding to experimental output from the flow pump system. Optimisation process was carried out to obtain the hydraulic conductivity function. This research showed that the inverse analysis with flow pump system was suitable to assess the hydraulic conductivity in unsaturated soil, and the prediction models for the hydraulic conductivity were led to the significant discrepancy from actual experimental outputs.

• Journal of Korean Society of Forest Science
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• v.90 no.1
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• pp.133-138
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• 2001

Increased base cation loss and Al mobilization, a consequence of soil acid neutralization responses, are common in air polluted areas showing forest decline. The prediction models of acid neutralization responses were developed by using indicators of soil acidification level(pH, and base saturation) in order to assess the forest soil sensitivity to acidification. The soil acidification level was greatest in Namsan followed by Kanghwa, Ulsan, and Hongcheon, being contrary to regional total $ANC_H$ pattern through soil columns leached with additional acid ($16.7mmol_c\;H^+/kg$), Both base exchange and Al dissolution were main acid neutralization processes in all study regions. There were low base exchange and high Al dissolution in the regions of the low total $ANC_H$. The $ANC_M$ by sulfate adsorption was greatest in Hongcheon compared with other regions even though the AN rate was very low as 6.4%. Coefficients of adjusted determination of simple and multiple regression models between soil acidification level indicators and the acid neutralization responses were more than 0.52(p<0.04) and 0.89(p<0.01), respectively. The result suggests that soil pH and base saturation are available indicators for predicting the acid neutralization responses. These prediction models could be used as an useful method to measure forest soil sensitivity to acidification.

• International Journal of Concrete Structures and Materials
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• v.8 no.3
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• pp.239-249
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• 2014

In this paper, the analysis of a numerical study of pile-soil interaction subjected to axial and lateral loads is presented. An analysis of the composite pile-soil system was performed using the finite difference (FD) software LPILE. Two three dimensional, finite element (FE) models of pile-soil interaction have been developed using Abaqus/Cae and SAP2000 to study the effect of lateral loading on pile embedded in clay. A lateral displacement of 2 cm was applied to the top of the pile, which is embedded into the concrete pile cap, while maintaining a zero slope in a guided fixation. A comparison between the bending moments and lateral displacements along the depth of the pile obtained from the FD solutions and FE was performed. A parametric study was conducted to study the effect of crucial design parameters such as the soil's modulus of elasticity, radius of the soil surrounding the pile in Abaqus/Cae, and the number of springs in SAP2000. A close correlation is found between the results obtained by the FE models and the FD solution. The results indicated that increasing the amount of clay surrounding the piles reduces the induced bending moments and lateral displacements in the piles and hence increases its capacity to resist lateral loading.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.4
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• pp.21-27
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• 2011

Soil stress distribution under loading is one of the important problems in civil engineering. Many models have been proposed to interpret the stress distribution in soil and most models assume that the soil is homogeneous and isotropic. Therefore, the actual stress distribution may be different. In addition, With the increase of the top load, soil stress does not increase linearly. In this study, vertical stress changes in sandy soil according to top load increase were measured through experiments. Experimental results, vertical soil stress due to top load increase showed an initial nonlinear behavior and when the load increases to some extent, vertical soil stress showed a linear behavior. ${\alpha}$ value obtained by existing theories always 1.00. But, ${\alpha}$ value by experiment was observed from 0.91 to 1.22 and ${\alpha}$ value was increased with increasing distance from the loading plate.

• Structural Engineering and Mechanics
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• v.88 no.3
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• pp.273-285
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• 2023

This study examines how the interaction between soil and a wind turbine's supporting system affects the optimal design. The supporting system resting on an elastic soil foundation consists of a steel conical tower and a concrete circular raft foundation, and it is subjected to wind loads. The material cost of the supporting system is aimed to be minimized employing various metaheuristic optimization algorithms including teaching-learning based optimization (TLBO). To include the influence of the soil in the optimization process, modified Vlasov and Gazetas elastic soil models are integrated into the optimization algorithms using the application programing interface (API) feature of the structural analysis program providing two-way data flow. As far as the optimal designs are considered, the best minimum cost design is achieved for the TLBO algorithm, and the modified Vlasov model makes the design economical compared with the simple Gazetas and infinitely rigid soil models. Especially, the optimum design dimensions of the raft foundation extremely reduce when the Vlasov realistic soil reactions are included in the optimum analysis. Additionally, as the designated design wind speed is decreased, the beneficial impact of soil interaction on the optimum material cost diminishes.

• Korean Journal of Soil Science and Fertilizer
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• v.40 no.5
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• pp.429-434
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• 2007

This study was conducted to estimate site productivity of Quercus acutissima and Quercus mongolica by four forest climatic zones. We used site environmental variables (28 geographical and pedological factors) and site index as a site productivity indicator from nation-wide 23,315 stands. Based on multiple regression analysis between site index and major environmental variables, the best-fit multivaliate models were made by each species and forest climatic zone. Most of site index prediction models by species were regressed with seven to eight factors, including altitude, relief, soil depth, and soil moisture etc. For those models, three evaluation statistics such as mean difference, standard deviation of difference, and standard error of difference were applied to the test data set for the validation of the results. According to the evaluation statistics, it was found that the models by climatic zones and species fitted well to the test data set with relatively low bias and variation. Also having above middle of site index range, total area of productive sites for the two Quercus spp. estimated by those models would be about 6% of total forest area. Northern temperate forest zone and central temperate forest zone had more productive area than southern temperate forest zone and warm temperate forest zone. As a result, it was concluded that the regressive prediction with site environmental variables by climatic zones and species had enough estimation capability of forest site productivity.