• Asian Journal of Business Environment
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• v.11 no.4
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• pp.17-29
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• 2021

Purpose: The aim of this study is to explore the dynamic linkage between conditional stock market volatility and macroeconomic uncertainty of Bangladesh. Research design, data, and methodology: This study uses monthly data covering the time period from January 2005 to December 2018. A comprehensive set of macroeconomic variables, namely industrial production index (IP), consumer price index (CPI), broad money supply (M2), 91-day treasury bill rate (TB), treasury bond yield (GB), exchange rate (EX), inflow of foreign remittance (RT) and stock market index of DSEX are used for analysis. Symmetric and asymmetric univariate GARCH family of models and multivariate VAR model, along with block exogeneity and impulse response functions, are implemented on conditional volatility series to discover the possible interactions and causal relations between macroeconomic forces and stock return. Results: The analysis of the study exhibits time-varying volatility and volatility persistence in all the variables of interest. Moreover, the asymmetric effect is found significant in the stock return and most of the growth series of macroeconomic fundamentals. Results from the multivariate VAR model indicate that only short-term interest rate significantly influence the stock market volatility, while conditional stock return volatility is significant in explaining the volatility of industrial production, inflation, and treasury bill rate. Conclusion: The findings suggest an increasing interdependence between the money market and equity market as well as the macroeconomic fundamentals of Bangladesh.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.5
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• pp.1039-1049
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• 2015

The inflow estimation at large multipurpose dam reservoir is carried out by considering the water balance among the discharge, the storage change during unit time interval obtained from the observed water level near dam structure and area-volume curve. This method can be ideal for level pool reservoir but include potential errors when the inflow is influenced by the water level slope due to backwater effects from upstream flood inflows and strong wind induced by typhoon. In addition, the other uncertainties arisen from the storage reduction due to sedimentation after the dam construction and water level noise due to mechanical vibration transmitted from the electric power generator. These uncertainties impedes the accurate hydraulic inflow measurement requiring exquisite hydrometric data arrangement for reservoir waterbody. In this study, the distributed hydrologic model using UBC-3P boundary setting was applied and its feasibility was evaluated. Finally, the modeling performance has been verified since the calculated determination coefficient has been in between 0.96 to 0.99 after comparing with observed peak inflow and total inflow at Namgang dam reservoir.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.5
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• pp.1-12
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• 2015

The study aimed to project inflows and demmands for the agricultural reservoir watersheds in South Korea considering a variety of regional characteristics and the uncertainty of future climate information. The study bias-corrected and spatially downscaled retrospective daily Global Climate Model (GCM) outputs under Representative Concentration Pathways (RCP) 4.5 and 8.5 emission scenarios using non-parametric quantile mapping method to force Soil and Water Assessment Tool (SWAT) model. Using the historical simulation, the skills of un-calibrated SWAT model (without calibration process) was evaluated for 5 reservoir watersheds (selected as well-monitored representatives). The study then, evaluated the performance of 9 GCMs in reproducing historical upstream inflow and irrigation demand at the five representative reservoirs. Finally future inflows and demands for 58 watersheds were projected using 9 GCMs projections under the two RCP scenarios. We demonstrated that (1) un-calibrated SWAT model is likely applicable to agricultural watershed, (2) the uncertainty of future climate information from different GCMs is significant, (3) multi-model ensemble (MME) shows comparatively resonable skills in reproducing water balances over the study area. The results of projection under the RCP 4.5 and RCP 8.5 scenario generally showed the increase of inflow by 9.4% and 10.8% and demand by 1.4% and 1.7%, respectively. More importantly, the results for different seasons and reservoirs varied considerably in the impacts of climate change.

• Journal of Environmental Science International
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• v.26 no.9
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• pp.1031-1043
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• 2017

Recently severe drought caused the water shortage around the western parts of Chungcheongnamdo province, South Korea. A Diversion tunnel from the Geum river to the Boryong dam, which is the water supply dam for these areas has been proposed to solve this problem. This study examined hydraulic impacts on the Geum river associated with the diversion plan assuming the severe drought condition of 2015 would persist for the simulation period of 2016. The hydraulic simulation model was verified using hydrologic and hydraulic data including hourly discharges of the Geum river and its 8 tributaries, fluctuation of tidal level at the mouth of the river, withdrawals and return flows and operation records of the Geum river barrage since Feb. 1, 2015 through May 31, 2015. For the upstream boundary condition of the Geum river predicted inflow series using the nonlinear regression equation for 2015 discharge data was used. In order to estimate the effects of uncertainty in inflow prediction to the results total four inflow series consisting of upper limit flow, expected flow, lower limit flow and instream flow were used to examine hydraulic impacts of the diversion plan. The simulation showed that in cases of upper limit and expected flows there would be no problem in taking water from the Geum river mouth with a minimum water surface level of EL(+) 1.44 m. Meanwhile, the simulation also showed that in cases of lower limit flow and instream flow there would be some problems not only in taking water for water supply from the mouth of the Geum river but also operating the diversion facility itself with minimum water surface levels of EL(+) 0.94, 0.72, 0.43, and 0.14 m for the lower limit flow without/with diversion and the instream flow without/with diversion, respectively.

• Journal of Korea Water Resources Association
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• v.31 no.1
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• pp.45-57
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• 1998

The purpose of this paper is to develop a neural network model in order to forecast flood inflow into the reservoir that has the nature of uncertainty and nonlinearity. The model has the features of multi-layered structure and parallel multi-connections. To develop the model. backpropagation learning algorithm was used with the Momentum and Levenberg-Marquardt techniques. The former technique uses gradient descent method and the later uses gradient descent and Gauss-Newton method respectively to solve the problems of local minima and for the speed of convergency. Used data for learning are continuous fixed real values of input as well as output to emulate the real physical aspects. after learning process. a reservoir inflows forecasting model at flood period was constructed. The data for learning were used to calibrate the developed model and the results were very satisfactory. applicability of the model to the Chungju Mlultipurpose Reservoir proved the availability of the developed model.

• Journal of Korea Water Resources Association
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• v.55 no.6
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• pp.405-419
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• 2022

Flood frequency analysis commonly used to design the hydraulic structures to minimize flood damage includes uncertainty. Therefore, the most appropriate design flood within a uncertainty should be selected in the final stage of a hydraulic structure, but related studies were rarely carried out. The total expected cost function introduced into the flood frequency analysis is a new approach for determining the optimal design flood. This procedure has been used as UNCODE (UNcertainty COmpliant DEsign), but the application has not yet been introduced in South Korea. This study introduced the mathematical procedure of UNCODE and calculated the optimal design flood using the annual maximum inflow of hydroelectric dams located in the Bukhan River system and results were compared with that of the existing flood frequency. The parameter uncertainty was considered in the total expected cost function using the Gumbel and the GEV distribution, and the Metropolis-Hastings algorithm was used to sample the parameters. In this study, cost function and damage function were assumed to be a first-order linear function. It was found that the medians of the optimal design flood for 4 Hydroelectric dams, 2 probability distributions, and 2 return periods were calculated to be somewhat larger than the design flood by the existing flood frequency analysis. In the future, it is needed to develop the practical approximated procedure to UNCODE.

• Nuclear Engineering and Technology
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• v.50 no.6
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• pp.829-841
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• 2018

An experiment was conducted for the OECD/NEA ROSA-2 Project using the large-scale test facility (LSTF), which simulated a 17% hot leg intermediate-break loss-of-coolant accident in a pressurized water reactor (PWR). In the LSTF test, core uncovery started simultaneously with liquid level drop in crossover leg downflow-side before loop seal clearing, and water remaining occurred on the upper core plate in the upper plenum. Results of the uncertainty analysis with RELAP5/MOD3.3 code clarified the influences of the combination of multiple uncertain parameters on peak cladding temperature within the defined uncertain ranges. For studying the scaling problems to extrapolate thermal-hydraulic phenomena observed in scaled-down facilities, an experiment was performed for the OECD/NEA PKL-3 Project with the Primarkreislaufe Versuchsanlage (PKL), as a counterpart to a previous LSTF test. The LSTF test simulated a PWR 1% hot leg small-break loss-of-coolant accident with steam generator secondary-side depressurization as an accident management measure and nitrogen gas inflow. Some discrepancies appeared between the LSTF and PKL test results for the primary pressure, the core collapsed liquid level, and the cladding surface temperature probably due to effects of differences between the LSTF and the PKL in configuration, geometry, and volumetric size.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.171-171
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• 2020

Decision making strategies should consider both adaptiveness and robustness in order to deal with two main characteristics of climate change: non-stationarity and deep uncertainty. Especially, robust strategies are different from traditional optimal strategies in the sense that they are satisfactory over a wider range of uncertainty and may act as a key when confronting climate change. In this study, a new framework named Robust Stochastic Dynamic Programming (R-SDP) is proposed, which couples previously developed robust optimization (RO) into the objective function and constraint of SDP. Two main approaches of RO, feasibility robustness and solution robustness, are considered in the optimization algorithm and consequently, three models to be tested are developed: conventional-SDP (CSDP), R-SDP-Feasibility (RSDP-F), and R-SDP-Solution (RSDP-S). The developed models were used to derive optimal monthly release rules in a single reservoir, and multiple simulations of the derived monthly policy under inflow scenarios with varying mean and standard deviations are undergone. Simulation results were then evaluated with a wide range of evaluation metrics from reliability, resiliency, vulnerability to additional robustness measures. Evaluation results were finally visualized with advanced visualization tools that are used in multi-objective robust decision making (MORDM) framework. As a result, RSDP-F and RSDP-S models yielded more risk averse, or conservative, results than the CSDP model, and a trade-off relationship between traditional and robustness metrics was discovered.

• Journal of the Korean Geotechnical Society
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• v.15 no.5
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• pp.217-228
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• 1999

The three methods of analysis (i) REV(representative elemental volume), (ii) non-REV and (iii) joint network analysis are introduced in this paper to analyze the groundwater flow in jointed rock mass and the inflow into underground excavations. The results from those methods are compared one another to reveal their characteristics by varying the number of joints and the diameter of the opening. The pre-processor, the so-called sequential analysis, is introduced to predict the equivalent hydraulic conductivity of a jointed rock mass having a number of intersecting joints. Using the finite element mesh, joint map and sequential analysis, the equivalent hydraulic conductivities are calculated for all 445 elements. The hydraulic inhomogeneity and the determination of the representative properties of jointed rock masses are discussed. In the REV analysis where the entire rock mass is homogenized through the representative properties, the inflow is increased regularly and consistently by increasing the joint density, the opening size and the conductivity contrast value. Though the non-REV analysis showed irregular variation of the inflow due to the local inhomogeneity allowed to individual elements, the inflow approached the REV results as the characteristic length increases. The joint network analysis showed the most sensitive reaction to the joint density, the opening size and the presence of the network crossing the opening. The reliability of the network analysis depends on the geometric data of individual joints. In view of the limited field data on joint geometry and possible uncertainty the REV and non-REV methods are considered more practical and rational than the joint network analysis.

• Journal of Korea Water Resources Association
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• v.57 no.4
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• pp.289-300
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• 2024

The purpose of this study is to evaluate the applicability of the GRM (Grid based rainfall-Runoff Model) to the continuous simulation by simulating the dam inflow. The GRM was previously developed for the simulation of rainfall-runoff events but has recently been improved to enable continuous simulation. The target watersheds are Chungju dam, Andong dam, Yongdam dam, and Sumjingang dam basins, and runoff models were constructed with the spatial resolution of 500 m × 500 m. The simulation period is 21 years (2001 to 2021). The simulation results were evaluated over the 17 year period (2005 to 2021), and were divided into three data periods: total duration, wet season (June to September), and dry season (October to May), and compared with the observed daily inflow of each dam. Nash-Sutcliffe efficiency (NSE), Kling-Gupta efficiency (KGE), correlation coefficient (CC), and total volume error (VE) were used to evaluate the fitness of the simulation results. As a result of evaluating the simulated dam inflow, the observed data could be well reproduced in the total duration and wet season, and the dry season also showed good simulation results considering the uncertainty of low-flow data. As a result of the study, it was found that the continuous simulation technique of the GRM model was properly implemented and the model was sufficiently applicable to the simulation of dam inflow in this study.