• Smart Structures and Systems
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• v.26 no.6
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• pp.781-796
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• 2020

Prediction of total sediment load is essential in an extensive range of problems such as the design of the dead volume of dams, design of stable channels, sediment transport in the rivers, calculation of bridge piers degradation, prediction of sand and gravel mining effects on river-bed equilibrium, determination of the environmental impacts and dredging necessities. This paper is aimed to investigate and predict the total sediment load of the Wadi Arbaat in Eastern Sudan. The study was estimated the sediment load by separate total sediment load into bedload and Suspended Load (SL), independently. Although the sediment records are not sufficient to construct the discharge-sediment yield relationship and Sediment Rating Curve (SRC), the total sediment loads were predicted based on the discharge and Suspended Sediment Concentration (SSC). The turbidity data NTU in water quality has been used for prediction of the SSC in the estimation of suspended Sediment Yield (SY) transport of Wadi Arbaat. The sediment curves can be used for the estimation of the suspended SYs from the watershed area. The amount of information available for Khor Arbaat case study on sediment is poor data. However, the total sediment load is essential for the optimal control of the sediment transport on Khor Arbaat sediment and the protection of the dams on the upper gate area. The results show that the proposed model is found to be considered adequate to predict the total sediment load.

• Journal of Korean Society on Water Environment
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• v.27 no.3
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• pp.293-299
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• 2011

The quantity of a discharge load can change with changes in rainfall in the area with a combined sewer system (CSS). To evaluate the implementation appropriately in the management of total maximum daily loads (TMDLs), the effects of rainfall changes should be considered in the estimation of the discharge load. The rainfall condition for the estimation of the discharge load in a certain year should be standardized to the same rainfall condition as that of the reference year. However, the calculation process is very complicated with its potential limitations. This study investigated and developed relatively simple methods for estimating the discharge load. Load conversion method (LCM) is designed to convert the discharge load under the current rainfall condition into that of the reference rainfall conditions. Simple rainfall data method (SRDM) is to simplify the estimation process of the discharge load by the simple conversion of rainfall data. These methods were applied to calculate the discharge load and examine the estimation results. From the results of this study the application of these methods may be useful for estimating the discharge load in the TMDL process.

• Journal of Korean Society on Water Environment
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• v.32 no.4
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• pp.375-383
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• 2016

Total Pollution Load Control (TPLC) calculates and manages the allowable pollutant load that is discharged from the watershed, which can meet the water quality target. Delivery Ratio (DR) is generally used for predicting the variation of pollutant mass balance between the pollutants discharged from the watershed and a certain point in the stream, and it is very important for estimation of accurate allowable pollutant load. The concept of DR in TPLC is different from prevalent DR, because DR in TPLC includes both the discharge of pollutants from the watershed and the delivery mechanism. Therefore, DR in TPLC should be estimated by using a proper and unified methodology. The appropriate method and equation for estimation of DR in TPLC was developed through the review of various methodologies, and the applicability of the equation was evaluated in a study area (Geumho A). Determination coefficients (R²) of regression were shown to be relatively high (BOD 0.71~0.87, T-N 0.86~0.90, T-P 0.62~0.69). Applicability of the developed methodology and equations was evaluated as appropriate for TPLC, and it is suggested.

• IE interfaces
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• v.16 no.1
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• pp.16-26
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• 2003

In Korea, cooling power load, which occupies about 20% of peak load in 2000 and fluctuates depending on the popular usage of air conditioning systems, has been recently the focus of the load management. The first work of KEPCO (Korea Electric Power Corporation) to regulate cooling load as low as possible was to estimate its approximate scale and to develop the indirect methods to estimate it from the available time series data for the average hourly loads. However, KEPCO would like to have their methods improved both theoretically and practically. In this paper, we analyze their current indirect methods and detect their faults to design better indirect estimation methods. Under one of the assumptions of "no cooling load in April or May", the linear relationship between basic loads and GDP's, and the normalized seasonal factors of the Winters' multiplicative seasonal model, we provide ten indirect estimation methods in total and suggest the estimated cooling load(1988-1999) based on our various indirect methods.

• Journal of Korean Society on Water Environment
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• v.22 no.6
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• pp.977-981
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• 2006

In order to improve water quality in drinking water sources, Ministry of Environment (MOE) was implemented total water pollution load management (TWPLM) in all the major river basins. From the experience of the application of TWPLM, we could find some problems relating the target watershed, standard operating procedure (SOP) of establishment and implementation plan, water quality and flow rate, design flow, water quality model, margin of safety (MOS), and estimation of wasteload were found. The authors were reviewed ongoing TWPLM and presented the improvement schemes for a successful TWPLM. For the application of these suggestions, further detailed studies should be done to implement TWPLM in the future.

• Journal of Korean Society on Water Environment
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• v.31 no.6
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• pp.653-664
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• 2015

TPLMS (Total water pollutant load management system) that is the most powerful water-quality protection program have been implemented since 2004. In the implementation of TPLMS, target water-quality and permissible discharged load from each unit watershed can be decided by water-quality modeling. And NPS (Non-point sources) discharge coefficients associated with certain (standard) flow are used on estimation of input data for model. National Institute of Environmental Research (NIER) recommend NPS discharge coefficients as 0.15 (Q₂₇₅) and 0.50 (Q₁₈₅) in common for whole watershed in Korea. But, uniform coefficient is difficult to reflect various NPS characteristics of individual watershed. Monthly NPS discharge coefficients were predicted and estimated using surface flow and water-quality from HSPF watershed model in this study. Those coefficients were plotted in flow duration curve of study area (Palger stream and Geumho C watershed) with monthly average flow. Linear regression analysis was performed about NPS discharge coefficients of BOD, T-N and T-P associated with flow, and R² of regression were distributed in 0.893~0.930 (Palger stream) and 0.939~0.959 (Geumho C). NPS Discharge coefficient through regression can be estimated flexibly according to flow, and be considered characteristics of watershed with watershed model.

• Journal of Korean Society on Water Environment
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• v.33 no.5
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• pp.531-537
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• 2017

The biologic Oxygen Demand (BOD) is a reliable and generally accepted indicator of water pollution by organic pollutants. Accordingly, estimation of BOD export from paddies carries important implications fwith regard to water management in rural areas. In this study, hydrology and BOD concentration were monitored during the period 2008 through 2012, in an effort to understand the characteristics of BOD export from paddy fields. The findings demonstrated that BOD load by rainfall above 50 mm. occupied about 50 % of total load, whereas the load by less than ten mm. rainfall occupied about 29 % of the total load during periods of stormy activity. It therefore seems that it could be possible to reduce the BOD load up to 29 % during storm periods, when drainage control conducted for rainfall less than ten mm.(an amount which is relatively easy to manage). The documented mean loads of storm and non-storm were $17.1kg\;ha^{-1}\;yr^{-1}$ and $11.2kg\;ha^{-1}\;yr^{-1}$, respectively. The BOD load during the significant rainfall period was similar to the renewed unit load by NIER (2014). However, there were substantial differences between unit load and actual load when the non-storm load was incorporated into the BOD load estimation from paddy fields. In view of the foregoing, it is felt that, the non-storm load needs to be further considered and managed for the successful implementation of Total Maximum Daily Load (TMDL) program.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.3
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• pp.15-22
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• 2019

In order to preserve water environment, Total Maximum Daily Load(TMDL) is used to manage the total amount of pollutant from various sources, and the annual average load of source is calculated by the unit load method. Determination of the unit load requires reliable data accumulation and analysis based on a reasonable estimation method. In this study, we propose a revised unit load estimation method by analyzing the unit load calculation procedure of National Institute of Environment Research(NIER) method. Both methods were tested using observed runoff ratio and water quality data of rice paddy fields. The estimated values with the respective NIER and revised NIER methods were highly correlated each other. However, the Event Mean Concentration(EMC) and the runoff ratio considered in the NIER method appeared to be influenced by rainfall classes, and the difference in unit load increases as the runoff and EMC increase. The error can be further increased when the EMC and runoff ratio are changed according to changes in rainfall patterns by climate change and change of agricultural activities. Therefore, it is recommended to calculate unit load by applying the revised NIER method reflecting the non point pollution runoff characteristics for different rainfall classes.

• Journal of Korean Society on Water Environment
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• v.24 no.4
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• pp.452-457
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• 2008

Nonpoint source (NPS) pollution is caused by rainfall moving over and through the ground. As the runoff moves, it picks up and carries away various pollutants from NPS. The discharge pattern of NPS pollutant loads is affected by the distribution of the rainfall during the year. This study analysed relationship between the rainfall event and the stream flow rate, and estimated the rainfall discharge ratio on the specific design flow which can be used as nonpoint discharge coefficient for the estimation of NPS pollution load. It is considered that nonpoint discharge coefficient can be effectively used for the calculation of NPS pollution load at the time of water quality modelling for the management of Total maximum daily load (TMDL).

• Magazine of the Korean Society of Agricultural Engineers
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• v.38 no.1
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• pp.90-97
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• 1996

In Korea, total sediment discharge of a river has been estimated simply by using certain sediment transport formulas including, among others, Einstein's formula. Those formular, however, are known not to be reliable enough for the result calculated by them to be used directly to river planning and management. Therefore, the study used the Modified Einstein Procedure to the estimation of total sediment discharge, because this method is reliable estimated by measurement. Here, measurement of sediment discharge used depth integrating method. The major results obtained from the study for estimation by depth integrating method of sediment discharge in Naeseong stream are as follow; 1 The sedeiment characteristics of Naeseong stream are; The distribution of sediment grain size shows that silt and clay are 55% and sand is 45%. and the bed load sediment grain size is constituted that sand contained with the grain size from O.062mm to 2.0mm is 80% 2. The sediment rating formulas derived from the regression analysis between the sediment discharge and flow discharge are; Seogpo-Gyo : Qs=$0.017 \times 10^{-4} Q^{2.352}$, where discharge is l0cms $0.074 \times 10^{-4} Q^{2.066}$, where discharge is l0cms