Drought is a natural disaster that can have serious social impacts. Drought's impact ranges from water supply for humans to ecosystems, but the impact of drought on river water quality requires careful investigation. In general, drought occurs meteorologically and is classified as agricultural drought, hydrological drought, and environmental drought. In this study, the BOD environmental drought is defined using the bivariate copula joint probability distribution model between the meteorological drought index and the river BOD, and based on this, the environmental drought condition index (EDCI-BOD) was proposed. The results of examining the proposed index using past precipitation and BOD observation data showed that EDCI-BOD expressed environmental drought well in terms of river BOD water quality. In addition, by classifying the calculated EDCI-BOD into four levels, namely, 'attention', 'caution', 'alert', and 'seriousness', a practical monitoring stage for environmental drought of BOD was constructed. We further estimated the sensitivity of the stream BOD to meteorological drought, and through this, we could identify the stream section in which the stream BOD responded relatively more sensitively to the occurrence of meteorological drought. The results of this study are expected to provide information necessary for river BOD management in the event of meteorological droughts.
KSCE Journal of Civil and Environmental Engineering Research
/
v.30
no.5B
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pp.471-477
/
2010
In this study, the variability of the Horton index which is ratio of vaporization and wetting water is investigated using a conceptual soil water balance model. From the proposed model, the steady-state soil water probabilistic density function is derived through meteorological and watershed characteristics and then the sensitivity of Horton index to the precipitation occurrence rate and the mean of wet day precipitation is examined. As a result, the inter-annual variability of the Horton index is lower than that of precipitation and they showed the strong negative correlation. It is also shown that although precipitation is not varied, the Horton index can be varied due to the fluctuation of the precipitation occurrence rate and the mean of wet day precipitation. In addition, it is presented that there is a non-linear relationship which has a critical point switching proportional or inverse relationship between the Horton index and two main characteristics of precipitation process.
Background: There is no standard treatment for patients with platinum-resistant or refractory epithelial ovarian cancer. Single agent chemotherapies have evidence of more efficacy and less toxicity than combination therapy. Most are very expensive, with appreciable toxicity and minimal survival. Since it is difficult to make comparison between outcomes, economic analysis of single-agent chemotherapy regimens and best supportive care may help to make decisions about an appropriate management for the affected patients. Objective: To evaluate the cost effectiveness of second-line chemotherapy compared with best supportive care for patients with platinum-resistant or refractory epithelial ovarian cancer. Materials and Methods: A Markov model was used to estimate the effectiveness and total costs associated with treatments. The hypothetical patient population comprised women aged 55 with platinum-resistant or refractory epithelial ovarian cancer. Four types of alternative treatment options were evaluated: 1) gemcitabine followed by BSC; 2) pegylated liposomal doxorubicin (PLD) followed by BSC; 3) gemcitabine followed by topotecan; and 4) PLD followed by topotecan. Baseline comparator of alternative treatments was BSC. Time horizon of the analysis was 2 years. Health care provider perspective and 3% discount rate were used to determine the costs of medical treatment in this study. Quality-adjusted life-years (QALY) were used to measure the treatment effectiveness. Treatment effectiveness data were derived from the literature. Costs were calculated from unit cost treatment of epithelial ovarian cancer patients at various stages of disease in King Chulalongkorn Memorial Hospital (KCMH) in the year 2011. Parameter uncertainty was tested in probabilistic sensitivity analysis by using Monte Carlo simulation. One-way sensitivity analysis was used to explore each variable's impact on the uncertainty of the results. Results: Approximated life expectancy of best supportive care was 0.182 years and its total cost was 26,862 Baht. All four alternative treatments increased life expectancy. Life expectancy of gemcitabine followed by BSC, PLD followed by BSC, gemcitabine followed by topotecan and PLD followed by topotecan was 0.510, 0.513, 0.566, and 0.570 years, respectively. The total cost of gemcitabine followed by BSC, PLD followed by BSC, gemcitabine followed by topotecan and PLD followed by topotecan was 113,000, 124,302, 139,788 and 151,135 Baht, respectively. PLD followed by topotecan had the highest expected quality-adjusted life-years but was the most expensive of all the above strategies. The incremental cost-effectiveness ratios (ICER) of gemcitabine followed by BSC, PLD followed by BSC, gemcitabine followed by topotecan and PLD followed by topotecan was 344,643, 385,322, 385,856, and 420,299 Baht, respectively. Conclusions: All of the second-line chemotherapy strategies showed certain benefits due to an increased life-year gained compared with best supportive care. Moreover, gemcitabine as second-line chemotherapy followed by best supportive care in progressive disease case was likely to be more effective strategy with less cost from health care provider perspective. Gemcitabine was the most cost-effective treatment among all four alternative treatments. ICER is only an economic factor. Treatment decisions should be based on the patient benefit.
Korean Journal of Construction Engineering and Management
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v.6
no.4
s.26
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pp.80-90
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2005
Activity durations retain probabilistic and stochastic natures due to diverse factors causing the delay or acceleration of activity completion. These natures make the final project duration to be a random variable. These factors are the major source of financial risk. Extending the Stochastic Project Scheduling Simulation system (SPSS) developed in previous research; this research presents a method to estimate how the final project duration behaves when activity durations change randomly. The final project cost is estimated by considering the fluctuation of indirect cost, which occurs due to the delay or acceleration of activity completion, along with direct cost assigned to an activity. The final project cost is estimated by considering how indirect cost behaves when activity duration change. The method quantifies the amount of contingency to cover the expected delay of project delivery. It is based on the quantitative analysis to obtain the descriptive statistics from the simulation outputs (final project durations). Existing deterministic scheduling method apply an arbitrary figures to the amount of delay contingency with uncertainty. However, the stochastic method developed in this research allows computing the amount of delay contingency with certainty and certain degree of confidence. An example project is used to illustrate the quantitative analysis method using simulation. When the statistical location and shape of probability distribution functions defining activity durations change, how the final project duration and cost behave are ascertained using automated sensitivity analysis method
To cope with the limits of conventional O-D trip matrix collecting methods, several approaches have been developed. One of them is bilevel Programming method Proposed by Yang(1995), which uses Sensitivity Analysis Based(SAB) algorithm to solve Generalized Least Square(GLS) problem. However, the SAB a1gorithm has revealed two critical short-comings. The first is that when there exists a significant difference between target O-D matrix and true O-D matrix, SAB algorithm may not produce correct solution. This stems from the heavy dependance on the historical O-D information, in special when gravel Patterns are dramatically changed. The second is the assumption of iterative linear approximation to original Problem. Because of the approximation, SAB algorithm has difficulty in converging to Perfect Stackelberg game condition. So as to avoid the Problems. we need a more robust and stable solution method. The main purpose of this Paper is to show the problem of the dependency of Previous models and to Propose an alternative solution method to handle it. The Problem of O-D matrix estimation is intrinsically nonlinear and nonconvex. thus it has multiple solutions. Therefore it is necessary to require a method for searching globa1 solution. In this paper, we develop a solution algorithm combined with genetic algorithm(GA) , which is widely used as probabilistic global searching method To compare the efficiency of the algorithm, SAB algorithm suggested by Yang et al. (1992,1995) is used. From the results of numerical example, the Proposed algorithm is superior to SAB algorithm irrespective of travel patterns.
Journal of the Korean Society of Hazard Mitigation
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v.8
no.6
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pp.149-153
/
2008
The pollutant capacity occurred before and after the development of a watershed should be quantitatively estimated and controlled for the minimization of water contamination. The Ministry of Environment suggested a guideline for the legal management of nonpoint source from 2006. However, the rational method for the determination of treatment capacity from nonpoint source proposed in the guideline has the problem in the field application because it does not reflect the project based cases and overestimates the pollutant load to be reduced. So, we perform the standard rainfall analysis by analytical probabilistic method for the estimation of an additional pollutant load occurred by a project and suggest a methodology for the estimation of contaminant capacity instead of a simple rational method. The suggested methodology in this study could determine the reasonable capacity and efficiency of a treatment facility through the estimation of pollutant load from nonpoint source and from this we can manage the watershed appropriately. We applied a suggested methodology to the projects of housing land development and a dam construction in the watersheds. When we determine the treatment capacity by a rational method without consideration of the types of projects we should treat the 90% of pollutant capacity occurred by the development and to do so, about 30% of the total cost for the development should be invested for the treatment facility. This requires too big cost and is not realistic. If we use the suggested method the target pollutant capacity to be reduced will be 10 to 30% of the capacity occurred by the development and about 5 to 10% of the total cost can be used. The control of nonpoint source must be performed for the water resources management. However it is not possible to treat the 90% of pollutant load occurred by the development. The proper pollutant capacity from nonpoint source should be estimated and controlled based on various project types and in reality, this is very important for the watershed management. Therefore the results of this study might be more reasonable than the rational method proposed in the Ministry of Environment.
Journal of Korean Society of Coastal and Ocean Engineers
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v.31
no.3
/
pp.158-169
/
2019
A probabilistic model that can predict the residual useful lifetime of structure is formulated by using the gamma process which is one of the stochastic processes. The formulated stochastic model can take into account both the sampling uncertainty associated with damages measured up to now and the temporal uncertainty of cumulative damage over time. A method estimating several parameters of stochastic model is additionally proposed by introducing of the least square method and the method of moments, so that the age of a structure, the operational environment, and the evolution of damage with time can be considered. Some features related to the residual useful lifetime are firstly investigated into through the sensitivity analysis on parameters under a simple setting of single damage data measured at the current age. The stochastic model are then applied to the rubble-mound breakwater straightforwardly. The parameters of gamma process can be estimated for several experimental data on the damage processes of armor rocks of rubble-mound breakwater. The expected damage levels over time, which are numerically simulated with the estimated parameters, are in very good agreement with those from the flume testing. It has been found from various numerical calculations that the probabilities exceeding the failure limit are converged to the constraint that the model must be satisfied after lasting for a long time from now. Meanwhile, the expected residual useful lifetimes evaluated from the failure probabilities are seen to be different with respect to the behavior of damage history. As the coefficient of variation of cumulative damage is becoming large, in particular, it has been shown that the expected residual useful lifetimes have significant discrepancies from those of the deterministic regression model. This is mainly due to the effect of sampling and temporal uncertainties associated with damage, by which the first time to failure tends to be widely distributed. Therefore, the stochastic model presented in this paper for predicting the residual useful lifetime of structure can properly implement the probabilistic assessment on current damage state of structure as well as take account of the temporal uncertainty of future cumulative damage.
Journal of Korean Society of Coastal and Ocean Engineers
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v.35
no.2
/
pp.23-32
/
2023
Probabilistic and deterministic analyses are implemented for the armor units of rubble foundation mound of composite breakwaters which is needed to protect the upright section against the scour of foundation mounds. By a little modification and incorporation of the previous empirical formulas that has commonly been applied to design the armor units of foundation mound, a new type formula of stability number has been suggested which is capable of taking into account slopes of foundation mounds, damage ratios of armor units, and incident wave numbers. The new proposed formula becomes mathematically identical with the previous empirical formula under the same conditions used in the developing process. Deterministic design have first been carried out to evaluate the minimum weights of armor units for several conditions associated with a typical section of composite breakwater. When the slopes of foundation mound become steepening and the incident wave numbers are increasing, the bigger armor units more than those from the previous empirical formula should be required. The opposite trends however are shown if the damage ratios is much more allowed. Meanwhile, the reliability analysis, which is one of probabilistic models, has been performed in order to quantitatively verify how the armor unit resulted from the deterministic design is stable. It has been confirmed that 1.2% of annual encounter probability of failure has been evaluated under the condition of 1% damage ratio of armor units for the design wave of 50 years return period. By additionally calculating the influence factors of the related random variables on the failure probability due to those uncertainties, it has been found that Hudson's stability coefficient, significant wave height, and water depth above foundation mound have sequentially been given the impacts on failure regardless of the incident wave angles. Finally, sensitivity analysis has been interpreted with respect to the variations of random variables which are implicitly involved in the formula of stability number for armor units of foundation mound. Then, the probability of failure have been rapidly decreased as the water depth above foundation mound are deepening. However, it has been shown that the probability of failure have been increased according as the berm width of foundation mound are widening and wave periods become shortening.
Hydrologic dam risk analysis depends on complex hydrologic analyses in that probabilistic relationship need to be established to quantify various uncertainties associated modeling process and inputs. However, the systematic approaches to uncertainty analysis for hydrologic risk analysis have not been addressed yet. In this paper, two major innovations are introduced to address this situation. The first is the use of a Hierarchical Bayesian model based regional frequency analysis to better convey uncertainties associated with the parameters of probability density function to the dam risk analysis. The second is the use of Bayesian model coupled HEC-1 rainfall-runoff model to estimate posterior distributions of the model parameters. A reservoir routing analysis with the existing operation rule was performed to convert the inflow scenarios into water surface level scenarios. Performance functions for dam risk model was finally employed to estimate hydrologic dam risk analysis. An application to the Dam in South Korea illustrates how the proposed approach can lead to potentially reliable estimates of dam safety, and an assessment of their sensitivity to the initial water surface level.
Kim, Jin-Young;Kim, Tae-Heon;Kim, You-Seong;Kim, Jae-Hong
Journal of the Korean Geotechnical Society
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v.31
no.8
/
pp.51-62
/
2015
It is not possible to provide resonable evidence for embankment (or dam) overtopping in geotechnical engineering, and conventional analysis by hydrologic design has not provided the evidence for the overflow. However, hydrologic design analysis using Copula function demonstrates the possibility that dam overflow occurs when estimating rainfall probability with rainfall data for 40 years based on fluctuating water level of a dam. Hydrologic dam risk analysis depends on complex hydrologic analyses in that probabilistic relationship needs to be established to quantify various uncertainties associated with modeling process and inputs. The systematic approaches to uncertainty analysis for hydrologic risk analysis have not been addressed yet. In this paper, the initial level of a dam for stability of a dam is generally determined by normal pool level or limiting the level of the flood, but overflow of probability and instability of a dam depend on the sensitivity analysis of the initial level of a dam. In order to estimate the initial level, Copula function and HEC-5 rainfall-runoff model are used to estimate posterior distributions of the model parameters. For geotechnical engineering, slope stability analysis was performed to investigate the difference between rapid drawdown and overtopping of a dam. As a result, the slope instability in overtopping of a dam was more dangerous than that of rapid drawdown condition.
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