• Geotechnical Engineering
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• v.9 no.3
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• pp.77-90
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• 1993

In the settlement analysis of shallow foundation soil properties, loads and soil strata involve many uncertainties so it is necessary to do analysis of settlement that considers the probabilistic properties of each variable. This study is performed to probabilistic analysis for settlement of shallow foundation consisted of individual footings by using Monte Carlo Method. To consider the uncertainty of variables, both the soil properties and loads are assumed to be normal distribution random variables and get settlement mean and coefficient of variation of individual footing. And the settlement of each individual footing is also assumed to be normal distribution. Settlement of each individual footing which considers the probability of soft soil pockets in soil strata follows Markov process. Then it is performed to do sensitivity analysis which is involved to excess probability of allowable criteria of maxi mum settlement and differential settlement according to varity of each variable. It is thought to be proper that the settlement analysis of shallow foundation should be analyzed considering uncertainty of variables and soil stratum conditions.

• Journal of Korean Society on Water Environment
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• v.29 no.5
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• pp.681-690
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• 2013

Watershed models have been increasingly used to support an integrated management of land and water, non-point source pollutants, and implement total daily maximum load policy. However, these models demand a great amount of input data, process parameters, a proper calibration, and sometimes result in significant uncertainty in the simulation results. For this reason, uncertainty analysis is necessary to minimize the risk in the use of the models for an important decision making. The objectives of this study were to evaluate three different uncertainty analysis algorithms (SUFI-2: Sequential Uncertainty Fitting-Ver.2, GLUE: Generalized Likelihood Uncertainty Estimation, ParaSol: Parameter Solution) that used to analyze the sensitivity of the SWAT(Soil and Water Assessment Tool) parameters and auto-calibration in a watershed, evaluate the uncertainties on the simulations of runoff and sediment load, and suggest alternatives to reduce the uncertainty. The results confirmed that the parameters which are most sensitive to runoff and sediment simulations were consistent in three algorithms although the order of importance is slightly different. In addition, there was no significant difference in the performance of auto-calibration results for runoff simulations. On the other hand, sediment calibration results showed less modeling efficiency compared to runoff simulations, which is probably due to the lack of measurement data. It is obvious that the parameter uncertainty in the sediment simulation is much grater than that in the runoff simulation. To decrease the uncertainty of SWAT simulations, it is recommended to estimate feasible ranges of model parameters, and obtain sufficient and reliable measurement data for the study site.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.5
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• pp.944-958
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• 2011

Soil hydraulic properties such as hydraulic conductivity or water retention which are costly to measure can be indirectly generated by soil pedotransfer function (PTF) using easily obtainable soil data. The field soil structure description which is routinely recorded could also be used in PTF as an input to reduce the uncertainty. The purposes of this study were to use qualitative morphological soil structure descriptions and soil structural index into PTF and to evaluate their contribution in the prediction of soil hydraulic properties. We transformed categorical morphological descriptions of soil structure into quantitative values using categorical principal component analysis (CATPCA). This approach was tested with a large data set from the US National Pedon Characterization database with the aid of a categorical regression tree analysis. Six different PTFs were used to predict the saturated hydraulic conductivity and those results were averaged to quantify the uncertainty. Quantified morphological description was successively used in multiple linear regression approach to predict the averaged ensemble saturated conductivity. The selected stepwise regression model with only the transformed morphological variables and structural index as predictors predicted the $K_{sat}$ with $r^2$ = 0.48 (p = 0.018), indicating the feasibility of CATPCA approach. In a regression tree analysis, soil structure index and soil texture turned out to be important factors in the prediction of the hydraulic properties. Among structural descriptions size class turned out to be an important grouping parameter in the regression tree. Bulk density, clay content, W33 and structural index explained clusters selected by a two step clustering technique, implying the morphologically described soil structural features are closely related to soil physical as well as hydraulic properties. Although this study provided relatively new method which related soil structure description to soil structure index, the same approach should be tested using a datasets containing the actual measurement of hydraulic properties. More insight on the predictive power of soil structure index to estimate hydraulic properties would be achieved by considering measured the saturated hydraulic conductivity and the soil water retention.

• Journal of Korea Water Resources Association
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• v.56 no.1
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• pp.35-43
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• 2023

Future runoff analysis is influenced by climate change scenarios and hydrologic model parameters, with uncertainties. In this study, the uncertainty of future runoff analysis according to the shared socioeconomic pathway (SSP) scenario and hydrologic model parameters was analyzed. Among the SSP scenarios, the SSP2-4.5 and SSP5-8.5 scenarios were used, and the soil and water assessment tool (SWAT) model was used as the hydrologic model. For the parameters of the SWAT model, a total of 11 parameter were optimized to the observed runoff data using SWAT-CUP. Then, uncertainty analysis of future estimated runoff compared to the observed runoff was performed using jensen-shannon divergence (JS-D), which can calculate the difference in distribution. As a result, uncertainty of future runoff was analyzed to be larger in SSP5-8.5 than in SSP2-4.5, and larger in the far future (2061-2100) than in the near future (2021-2060). In this study, the uncertainty of future runoff using future climate data according to the parameters of the hydrologic model is as follows. Uncertainty was greatly analyzed when parameters used observed runoff data in years with low flow rates compared to average years. In addition, the uncertainty of future runoff estimation was analyzed to be greater for the parameters of the period in which the change in runoff compared to the average year was greater.

• Korean Journal of Environmental Agriculture
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• v.39 no.3
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• pp.237-245
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• 2020

BACKGROUND: The closed chamber method is the most commonly used for measuring greenhouse gas emissions from upland fields. This method has the advantages of being simple, easily available and economical. However, uncertainty estimation is essential for accurate assessment of greenhouse gas emissions and verification of emission reductions. The nitrous oxide emissions from upland field is very important for the nitrogen budget in the agriculture sectors. Although assessment of uncertainty components affecting nitrous oxide emission from upland field is necessary to take account of dispersion characteristics, research on these uncertainty components is very rare to date. This study aims at elucidation of influencing factors on measurement uncertainty of nitrous oxide concentrations measured by an automated open closed chamber method from upland field. METHODS AND RESULTS: The nitrous oxide sampling system is located in the upland field in Gyeonggi-do Agricultural Research and Extension Services (37°13'22"N, 127°02'22"E). The primary measurement uncertainty components influencing nitrous oxide concentrations (influencing factors) investigated in this research are repeatability, reproducibility and calibration in the aspects of nitrous oxide sampling and analytical instrumentation. The magnitudes of the relative standard uncertainty of each influencing factor are quantified and compared. CONCLUSION: Results of this study show what influencing factors are more important in determination of nitrous oxide concentrations measured using the automated open closed chambers located in the monitoring site. Quantifying the measurement uncertainty of the nitrous oxide concentrations in this study would contribute to improving measurement quality of nitrous oxide fluxes.

• Water for future
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• v.27 no.2
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• pp.129-137
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• 1994

The surface hydrology of large land areas is susceptible to several preferred stable states with transitions between stable states induced y stochastic fluctuation. This comes about due to the close coupling of land surface and atmospheric interaction. An interesting and important issue is the duration of residence in each mode. Mean transtion times between the stable modes are analyzed for different model parameters or climatic types. In an example situation of this differential equation exhibits a bimodal probability distribution of soil moisture states. Uncertainty analysis regarding the model parameters is performed using a Monte-Carlo simulation method. The method developed in this research may reveal some important characteristics of soil moisture or precipitation over a large area, in particular, those relating to abrupt changes in soil moisture or precipitation having extremely variable duration.

• Korean Journal of Environmental Agriculture
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• v.33 no.1
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• pp.30-36
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• 2014

BACKGROUND: Best management practices are often implemented to control nonpoint source pollutants. Best management practices need to be simulated and analyzed for effective Best management practices implementations. Filter strip is one of effective Best management practices in agricultural areas. METHODS AND RESULTS: Soil and Water Assessment Tool model was selected to explore the effectiveness of filter strip to control total phosphorous in Golji watershed. Soil and Water Assessment Tool model was calibrated for flow and total phosphorous by Sequential Uncertainty Fittin ver.2 algorithm provided in Soil and Water Assessment Tool-Calibration and Uncertainty Procedures. Three scenarios defined by filter strip width were applied. The filter strip width of 5 m was able to reduce the most amount of total phosphorous. In other words, the total phosphorous reduction by filter strip of 5 m was 28.0%, while the reduction was 17.5% by filter strip of 1 m. However, the reduction per unit filter strip width were 17.4%, 8.0%, and 4.5% for 1 m, 3 m, and 5 m of filter strips, respectively. CONCLUSION: Best management practices need to be simulated and analyzed so that the BMP scenario can be cost-effective. A large size of BMP might be able to control large amount of pollutants, however it would not be indicated as a cost-effective strategy.

• Journal of the Earthquake Engineering Society of Korea
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• v.16 no.3
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• pp.35-42
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• 2012

We propose a probabilistic method to evaluate the uniform hazard spectra (UHS) of the soil of nuclear power plant(NPP) sites corresponding to that of a bedrock site. To do this, amplification factors on the surface of soil sites were estimated through site response analysis while considering the uncertainty in the earthquake ground motion and soil deposit characteristics. The amplification factors were calculated by regression analysis with spectral acceleration because these two factors are mostly correlated. The proposed method was applied to the evaluation of UHS for the KNGR (Korean Next Generation Reactor) and the APR1400 (Advanced Power Reactor 1400) nuclear power plant sites of B1, B4, C1 and C3. The most dominant frequency range with respect to the annual frequency of earthquakes was evaluated from the UHS analysis. It can be expected that the proposed method will improve the results of integrated risk assessments of NPPs rationally. We expect also that the proposed method will be applied to the evaluation of the UHS and of many other kinds of soil sites.

• Journal of the Korean Geotechnical Society
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• v.35 no.12
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• pp.45-58
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• 2019

In this study, a stochastic analysis procedure based on numerical analysis was proposed to evaluate a kind of intensity-duration rainfall threshold for the initiation of slope failure due to rainfall infiltration. Fragility curves were generated as a function of rainfall intensity-duration from the results of probabilistic slope stability analysis by MCS considering the uncertainty of the soil shear strength, reflecting the results of infiltration analysis of rainfall over time. In the probabilistic analysis, slope stability analyses combined with the infiltration analysis of rainfall were performed to calculate the limit state function. Using the derived fragility curves, a chart showing the relationship between rainfall intensity and slope failure-time was developed. It is based on a probabilistic analysis considering the uncertainty of the soil properties. The proposed probabilistic failure distribution analysis could be beneficial for analyzing the time-dependent failure process of soil slopes due to rainfall infiltration, and for predicting when the slope failure should occur.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.138-142
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• 2005

The change of precipitation and temperature due to the global. warming eventually caused the variation of water availability in terms of potential evapotranspiration, soil moisture, and runoff. In this reason national long-term water resource planning should be considered the effect of climate change. Study of AOGCM-based scenario to proposed the plausible future states of the climate system has become increasingly important for hydrological impact assessment. Future climate changes over East Asia are projected from the coupled atmosphere-ocean general circulation model (AOGCM) simulations based on Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2 and B2 scenarios using multi-model ensembles (MMEs) method (Min et al. 2004). MME method is used to reduce the uncertainty of individual models. However, the uncertainty increases are larger over the small area than the large area. It is demonstrated that the temperature increases is larger over continental area than oceanic area in the 21st century.