• Title/Summary/Keyword: Stochastic Water Quality Model

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Analysis for Efficiency in the Oyster, Mussel Aquaculture Household using SFA (SFA를 이용한 굴, 홍합 양식어가의 효율성 분석)

  • Kim, Tae-Hyun;Park, Cheol-Hyung
    • The Journal of Fisheries Business Administration
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    • v.47 no.2
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    • pp.1-14
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    • 2016
  • This study applied the Stochastic Frontier Analysis to estimate which independent variable affects to efficiency of aquaculture household. This study used wage and facility scale as input variables, sales volume as an output variable to estimate efficiency. Also, the study used region, species, water quality to estimate technical inefficiency factors of the model. The data used for this study were obtained by the operating costs survey using 1:1 interview method. The study selected translog production model with technical inefficiency term estimated as half-normal distribution. In addition, the study used pearson and spearman correlation coefficient among efficiency estimating models. Also, the study analysed differences among estimated efficiencies through t-test, and showed us 0.1793 in species, 0.4677 between Geojae and Masan.

Forecasting of Dissolved Oxygen at Kongju Station using a Transfer Function Noise Model (전이함수잡음모형에 의한 공주지점의 용존산소 예측)

  • 류병로;조정석;한양수
    • Journal of Environmental Science International
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    • v.8 no.3
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    • pp.349-354
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    • 1999
  • The transfer function was introduced to establish the prediction method for the DO concentration at the intaking point of Kongju Water Works System. In the mose cases we analyze a single time series without explicitly using information contained in the related time series. In many forecasting situations, other events will systematically influence the series to be forecasted(the dependent variables), and therefore, there is need to go beyond a univariate forecasting model. Thus, we must bulid a forecasting model that incorporates more than one time series and introduces explicitly the dynamic characteristics of the system. Such a model is called a multiple time series model or transfer function model. The purpose of this study is to develop the stochastic stream water quality model for the intaking station of Kongju city waterworks in Keum river system. The performance of the multiplicative ARIMA model and the transfer function noise model were examined through comparisons between the historical and generated monthly dissolved oxygen series. The result reveal that the transfer function noise model lead to the improved accuracy.

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Stochastic Programming Model for River Water Quality Management (추계학적 계획모형을 이용한 하천수질관리)

  • Cho, Jae Heon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.14 no.1
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    • pp.231-243
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    • 1994
  • A stochastic programming model for river water quality management was developed. River water quality, river flow, quality and flowrate of the wastewater treatment plant inflow were treated as random variables in the model. Withdrawal for water supply and submerged weir reaeration were included in the model itself. A probabilistic model was formulated to compute the expectation and variance of water quality using Streeter-Phelps equation. Chance constraints of the optimization problem were converted to deterministic equivalents by chance constrained method. Objective function was total annual treatment cost of all wastewater treatment plants in the region. Construction cost function and O & M cost function were derived in the form of nonlinear equations that are functions of treatment efficiency and capacity of treatment plant. The optimization problem was solved by nonlinear programming. This model was applied to the lower Han River. The results show that the reliability to meet the DO standards of the year 1996 is about 50% when the treatment level of four wastewater treatment plants in Seoul is secondary treatment, and BOD load from the tributary inflows is the same as present time. And when BOD load from Tanchon, Jungrangchon, and Anyangchon is decreased to 50%, the reliability to meet the DO standards of the year 1996 is above 60%. This results indicated that for the sake of the water quality conservation of the lower Han River, water quality of the tributaries must be improved, and at least secondary level of treatment is required in the wastewater treatment plants.

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Water Quality Forecasting System by Reliability Analysis in the Nakdong River (낙동강에서의 신뢰도해석에 의한 수질예보시스템의 개발)

  • Han, Geon-Yeon;Kim, Sang-Ho
    • Journal of Korea Water Resources Association
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    • v.30 no.4
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    • pp.411-420
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    • 1997
  • QUAL2E-AFOSM model is developed to forecast the water quality by reliability analysis in the Nakdong River. A varied-flow analysis is performed for the reach of Waegwan to Mulgeum to estimate hydraulic parameters. An optimization technique by BFGS method is applied to determine the optimum reaction parameters and calibrations and verifications are performed based on these parameters. A reliability analysis for the stochastic analysis in a river is studied using the AFOSM method. The variations of water quality and discharge in the headwater, tributaries, and reaction coefficients are considered. Risks of violating existing water quality standards at several loactions in the Nakdong River are computed by using the QUAL2E-AFOSM method. The computed results computed by QUAL2E-AFOSM model agree with those of the Monte-Carlo method in QUAL2EU model.

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Statistical Analysis of Water Quality in the Downstream of the Han River (한강하류부 수질의 통계학적 해석)

  • 백경원;정용태;한건연;송재우
    • Water for future
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    • v.29 no.2
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    • pp.179-190
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    • 1996
  • The characteristics of water quality in the downstream of the Han River were analyzed by statistical techniques. Basic characteristics, areal and temporal variations, and correlations of water quality data were investigated. Monthly water quality data have been investigated systematically by exploring data analysis, including time series plot, summary statistics, distribution test, time dependence test, seasonality test and flow relatedness test. Results show that water quality data in this river have seasonality. And applicability of stochastic models such as Thomas-Fiering model and ARMA(1,1) model was identified. From the examination of water quality data related to discharge, it was found that DO and SS are sensitive to water temperature rather than discharge, while BOD and COD are sensitive to discharge at dry seasons. Seasonal periodicities were identified in all water quality variables from the cross correlation analysis.

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Application of Realtime Monitoring of Oceanic Conditions in the Coastal Water for Environmental Management

  • Choi, Yang-Ho;Ro, Young-Jae
    • Journal of the korean society of oceanography
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    • v.39 no.2
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    • pp.148-154
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    • 2004
  • This study describes the realtime monitoring system for water quality conditions in coastal waters. Some issues on the data qualify control and quality analysis are examined along with examples of erroneous data. Three different cases of database produced by the realtime monitoring system are presented and analyzed, namely 1) hypoxic condition, 2) over-saturated D.O. and 3) short-term variability of temperature and D.O. In utilizing the realtime database, D.O. prediction and warning models are developed based on autoregressive stochastic process. The model is very simple, yet, users in various levels from powerful and useful with its ability to send warning messages to users in varous levels from governmental administrative staff to local fisherman, and give them some allowances to cope with the situation.

Reservoir Operating System Using Sampling Stochastic Dynamic Programming for the Han River Basin (표본 추계학적 동적계획법을 사용한 한강수계 저수지 운영시스템 개발)

  • Eum, Hyung-Il;Park, Myung-Ky
    • Journal of Korea Water Resources Association
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    • v.43 no.1
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    • pp.67-79
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    • 2010
  • Korea water resources corporation (K-Water) has developed the real-time water resources management system for the Nakdong and the Geum River basin to efficiently operate multi-purpose dams in the basins. This study has extended to the Han River basin for providing an effective ending target storage of a month to the real-time water resources management system using Sampling Stochastic Dynamic Programming (SSDP), consequently increasing the efficiency of the reservoir system. The optimization model were developed for three reservoirs, named Soyang, Chungju, and Hwacheon, with high priority in terms of the amounts of effective capacity and water supply for the basin. The number of storage state variable for each dam to set an optimization problem has been assigned from the results of sensitivity analysis. Compared with the K-water operating policy with the target water supply elevations, the optimization model suggested in this study showed that the shortfalls are decreased by 37.22 MCM/year for the required water demands in the basin, even increasing 171 GWh in hydro electronic power generation. In addition, the result of a reservoir operating system during the drawdown period applied to real situation demonstrates that additional releases for water quality or hydro electronic power generation would be possible during the drawdown period between 2007 and 2008. On the basis of these simulation results, the applicability of the SSDP model and the reservoir operating system is proved. Therefore, the more efficient reservoir operation can be achieved if the reservoir operating system is extended further to other Korean basins.

Time series Analysis of State-space Model and Multiplication ARIMA Model in Dissolved Oxygen Simulation (용존산소 농도모의시 상태공간모형과 승법 ARIMA모형의 시계열 분석)

  • 이원호;서인석;한양수
    • Journal of environmental and Sanitary engineering
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    • v.15 no.2
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    • pp.65-74
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    • 2000
  • The purpose of this study is to develop the stochastic stream water quality model for the intake station of Chung-Ju city waterworks in the Han river system. This model was based on the theory of Box-Jenkins Multiplicative ARIMA(SARIMA) and the state space model to simulate changes of water qualities. Variable of water qualities included in the model are temperature and dissolved oxygen(DO). The models development were based on the data obtained from Jan. 1990 to Dec. 1997 and followed the typical procedures of the Box-Jenkins method including identification and estimation. The seasonality of DO and temperature data to formulate for the SARIMA model are conspicuous and the period of revolution was twelve months. Both models had seasonality of twelve months and were formulates as SARIMA {TEX}$(2,1,1)(1,1,1)_{12}${/TEX} for DO and temperature. The models were validated by testing normality and independency of the residuals. The prediction ability of SARIMA model and state space model were tested using the data collected from Jan. 1998 to Oct. 1999. There were good agreements between the model predictions and the field measurements. The performance of the SARIMA model and state space model were examined through comparisons between the historical and generated monthly dissolved oxygen series. The result reveal that the state space model lead to the improved accuracy.

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Performance Evaluation of Rainfall Disaggregation according to Temporal Scale of Rainfall Data (강우자료의 시간해상도에 따른 강우 분해 성능 평가)

  • Lee, Jeonghoon;Jang, Juhyoung;Kim, Sangdan
    • Journal of Wetlands Research
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    • v.20 no.4
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    • pp.345-352
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    • 2018
  • In this study, rainfall data with various temporal scales (3-, 6-, 12-, 24-hr) are disaggregated into 1-hourly rainfall data to evaluate the performance of rainfall disaggregation technique. The rainfall disaggregation technique is based on a database generated by the stochastic point rainfall model, the Neyman-Scott Rectangular Pulse Model (NSRPM). Performance evaluation is carried out using July rainfall data of Ulsan, Changwon, Busan and Milyang weather stations in Korea. As a result, the rainfall disaggregation technique showed excellent performance that can consider not only the major statistics of rainfall but also the spatial correlation. It also indirectly shows the uncertainty of future climate change scenarios with daily temporal scale. The rainfall disaggregation technique is expected to disaggregate the future climate change scenarios, and to be effective in the future watershed management.

Application of rock mass index in the prediction of mine water inrush and grouting quantity

  • Zhao, Jinhai;Liu, Qi;Jiang, Changbao;Defeng, Wang
    • Geomechanics and Engineering
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    • v.30 no.6
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    • pp.503-515
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    • 2022
  • The permeability coefficient is an essential parameter for the study of seepage flow in fractured rock mass. This paper discusses the feasibility and application value of using readily available RQD (rock quality index) data to estimate mine water inflow and grouting quantity. Firstly, the influence of different fracture frequencies on permeability in a unit area was explored by combining numerical simulation and experiment, and the relationship between fracture frequencies and pressure and flow velocity at the monitoring point in fractured rock mass was obtained. Then, the stochastic function generation program was used to establish the flow analysis model in fractured rock mass to explore the relationship between flow velocity, pressure and analyze the universal law between fracture frequency and permeability. The concepts of fracture width and connectivity are introduced to modify the permeability calculation formula and grouting formula. Finally, based on the on-site grouting water control example, the rock mass quality index is used to estimate the mine water inflow and the grouting quantity. The results show that it is feasible to estimate the fracture frequency and then calculate the permeability coefficient by RQD. The relationship between fracture frequency and RQD is in accordance with exponential function, and the relationship between structure surface frequency and permeability is also in accordance with exponential function. The calculation results are in good agreement with the field monitoring results, which verifies the rationality of the calculation method. The relationship between the rock mass RQD index and the rock mass permeability established in this paper can be used to invert the mechanical parameters of the rock mass or to judge the permeability and safety of the rock mass by using the mechanical parameters of the rock mass, which is of great significance to the prediction of mine water inflow and the safety evaluation of water inrush disaster management.