Lee, Sang Eun;Choi, I Song;Lee, In Ho;Hong, Dae Byuk;Oh, Jong Min
Journal of Environmental Impact Assessment
/
v.20
no.5
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pp.651-661
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2011
The purpose of this study is to estimate the characteristics and pollutant loadings of non-point pollutants that flowed in the streams on precipitation for pollutant loading reduction of Hwa-sung lake inflow streams. Although it has been made an effort to improve the water quality of Hwa-sung basin through the strategies for the preservation of water quality, it is shown that the water quality is not greatly improved. Because it has been industrialized and urbanized near Hwa-sung basin so that it is difficult to reduce the water pollution due to the increase in pollutant loadings of point and non-point sources. In this study, it is investigated the outflow characteristics of non-point pollutants that discharged with storm runoff and estimated the effect of runoff on Hwa-sung basin. The final goal of this study is to utilize the basic information for proper management and strategies of non-point sources on Hwa-sung basin. At the result of inflow streams, Ja-an stream that has the greatest pollutant loadings on precipitation is strongly influenced on the water quantity of Hwa-sung basin. On the other hand, it is shown that Nam-yang stream is strongly influenced on the SS concentration of Hwasung basin among them. Also, all streams; Nam-yang, Ja-ahn, Ah-eun stream; has the degree of slope more than or near 1 in the correlation results so that they have strong pollutant loading impact and the concentration of SS is the highest among other pollutants. So, specific studies on initial rain phenomena are more necessary to manage the pollutants economically. Also, the proper control of SS concentration is required to manage the effluent pollutants effectively on precipitation. So, it is necessary to consider the strategies for non-point pollutants as well as point pollutants when the new management is imposed to reduce the pollutant load for improvement of Hwa-sung basin.
Kwak, Sungjin;Bhattrai, Bal Dev;Gim, Giyoung;Kang, Phil-Goo;Heo, Woomyung
Korean Journal of Ecology and Environment
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v.51
no.1
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pp.135-147
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2018
In order to investigate the runoff characteristics of nonpoint source pollutants in the Lake Doam watershed, water quality and flow rate were monitored for 38-rainfall events from 2009 to 2016. The EMC values of SS, COD, TN and TP were in the range of 33~2,169, 3.5~56.9, 0.09~7.65 and $0.06{\sim}2.21mg\;L^{-1}$, respectively. As a result of analyzing the effect of rainfall factor on the nonpoint source pollutant load, EMCs of SS, COD and TP showed a statistically significant correlation with rainfall (RA) (p<0.01) and SS showed highly significant correlation with maximum rainfall intensity (MRI, R=0.48). The load ranges of SS, COD, TN and TP were 10.4~11,984.6, 1.1~724.4, 0.6~51.6 and $0.03{\sim}22.85ton\;event^{-1}$, respectively, showing large variation depending on the characteristics of rainfall events. The effect of rainfall on the load was analyzed. SS, COD and TP showed a positive correlation, but TN did not show any significant correlation. The annual load of SS was the highest with $88,645tons\;year^{-1}$ in 2011 when rainfall was the highest with 1,669 mm. The result of impact analysis of nonpoint source pollution reduction project and land-use change on runoff load showed that pollutant load significantly reduced from 2009 to 2014 but SS and TP loads were increased from 2014 to 2016 due to increase in construction area. Therefore, we suggested that nonpoint source pollution abatement plan should be continued to reduce the soil loss and pollutants during rainfall, and countermeasures to reduce nonpoint source pollution due to construction need to be established.
Journal of The Korean Society of Agricultural Engineers
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v.62
no.1
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pp.39-50
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2020
The objective of this study was to assess the livestock nonpoint source pollutant impact on water quality in Namgang dam watershed using the HSPF (Hydrological Simulation Program-Fortran) model. The input data for the HSPF model was established using the landcover, digital elevation, and watershed and river maps. In order to apply the pollutant load to the HSPF model, the delivery load of the livestock nonpoint source in the Namgang dam watershed was calculated and used as a point pollutant input data for the HSPF model. The hydrologic and water quality parameters of HSPF model were calibrated and validated using the observed runoff data from 2007 to 2015 at Sancheong station. The R2 (Determination Coefficient), RMSE (Root Mean Square Error), NSE (Nash-Sutcliffe efficiency coefficient), and RMAE (Relative Mean Absolute Error) were used to evaluate the model performance. The simulation results for annual mean runoff showed that R2 ranged 0.79~0.81, RMSE 1.91~2.73 mm/day, NSE 0.7~0.71 and RMAE 0.37~0.49 mm/day for daily runoff. The simulation results for annual mean BOD for RMSE ranged 0.99~1.13 mg/L and RMAE 0.49~0.55 mg/L, annual mean TN for RMSE ranged 1.65~1.72 mg/L and RMAE 0.55 mg/L, and annual mean TP for RMSE ranged 0.043~0.055 mg/L and RMAE 0.552~0.570 mg/L. As a result of livestock nonpoint pollutant loading simulation for each sub-watersehd using the HSPF model, the BOD ranged 16.6~163 kg/day, TN ranged 27.5~337 kg/day, TP ranged 1.22~14.1 kg/day.
Window interface to Hydrological Simulation Program-FORTRAN (WinHSPF) developed by the United States Environmental Protection Agency (EPA) was applied to the upstream of Nam-Han river watershed to examine its applicability for loading estimates in watershed scale and to evaluate non-point source control scenarios using BMPRAC in WinHSPF. The WinHSPF model was calibrated and verified for water flow using Ministry of Construction and Transportation (MOCT, 3 stations, 2003~2005) and water qualities using Ministry of Environment (MOE, 5 station, 2000~2006). Water flow and water quality simulation results were also satisfactory over the total simulation period. But outliers were occurred in the time series data of TN and TP at some regions and periods. Therefore, it required more profit calibration process for more various parameters. As a result, all the study was performed within the expectation considering the complexity of the watershed, pollutant sources and land uses intermixed in the watershed. The estimated pollutant load for annual average about $BOD_5$, T-N and T-P respectively. Nonpoint source loading had a great portion of total pollutant loading, about 86.5~95.2%. In WinHSPF, BMPRAC was applied to evaluate non-point source control scenarios (constructed wetland, wet detention ponds and infiltration basins). All the scenarios showed efficiency of non-point source removal. Overall, the HSPF model is adequate for simulating watersheds characteristics, and its application is recommended for watershed management and evaluation of best management practices.
Journal of The Korean Society of Agricultural Engineers
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v.49
no.2
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pp.61-74
/
2007
A mathematical modeling program called Hydrological Simulation Program-FORTRAN (HSPF) developed by the United States Environmental Protection Agency (EPA) was applied to Hwaseong watershed. It was run under BASINS (Better Assessment Science for Integrating Point and Nonpoint Sources) program, and the model was validated using monitoring data of $2002{\sim}2005$. The model efficiency of runoff ranged from good to fair in comparison between simulated and observed data, while it was from very good to poor in the water quality parameters. But its reliability and performance were within the expectation considering complexity of the watershed and pollutant sources. The nonpoint source (NPS) loading for T-N and T-P during the monsoon rainy season (June to September) was about 80% of total NPS loading, and runoff volume was also in a similar range. However, NPS loading for BOD ($55{\sim}60%$) didn't depend on rainfall because BOD was mostly discharged from point source (more than 70%). And water quality was not necessarily high during the rainy season, and showed a decreasing trend with increasing water flow. BASINS/HSPF was applied to the Hwaseong watershed successfully without difficulty, and it was found that the model could be used conveniently to assess watershed characteristics and to estimate pollutant loading including point and nonpoint sources in watershed scale.
Objective: The objective of this study was to suggest a method through which load duration curve was used to assess the achievement of water quality targets in accordance with the criteria for pollutant load depending on flow rate variation. Methods: The stage-discharge curve and flow duration curve of Jungnang Stream were deduced. Using water quality targets and measurement of the stream, the flow duration curve was also drawn. Based on these, the feasibility of achievement of water quality targets in respect to flow rate was assessed. Results: In terms of the load duration curve of the stream, it was observed that excess of criteria for concentrations of $BOD_5$, $COD_{Mn}$ and SS frequently occurred. On the other hand, when the flow rate was low, the concentrations of T-N and T-P exceeded the criteria. Conclusions: Through the load duration curve, the overall water quality of Jungnang Stream was understood. When the flow rate is high, management of point source of $BOD_5$, $COD_{Mn}$ and SS is needed to achieve water quality targets for Jungnang Stream. On the other hand, when the flow rate is low, the management of non-point source T-N and T-P is necessary to attain the water quality goal.
Proceedings of the Korea Water Resources Association Conference
/
2015.05a
/
pp.221-221
/
2015
Sustainable use of water resource and conservation of water quality are essential problems in the world. Especially, problems of water quality are serious one for human health as well as ecological system of all creatures on the earth. Recently, the importance of total effluent load as well as the concentrations of pollutant materials has been recognized not only for the conservation of water quality but also for sustainable water use in watersheds. However, the measurement or estimation of total effluent load from non-point source area such as farm lands or forests may be more difficult because both of concentration and discharge of the water are greatly changed depending on various factors especially metrological conditions such as rainfall, while the measurement from a point source area may be easy because the concentration of pollutant materials and amount of discharge water are relatively steady. Therefore, the total effluent load from a non-point source is often estimated by statistical relationships between concentration and discharge, which is called as L-Q equation. However, a lot of work and time are required to collect and analyze water samples and to get the accurate relationship or regressive equation. So, we proposed a new system for direct measurement of total effluent load of water quality from non-point source areas to solve the problem. In this system, the overflow depth at a hydraulic weir is measured with a pressure gage every hourly interval to calculate the amount of hourly discharge at first. Then, the operating time of a small electric pump to collect an amount of water which is proportional to the discharge is calculated to intake the water into a storage tank. The stored water is taken out a few days later in a case of storm event or several weeks later in a case of non-rainfall event and the concentrations of water quality such as total nitrogen and phosphorous are analyzed in a laboratory. Finally, total load of the water quality can be calculated by multiplying the concentration by the total volume of discharge. The system was installed in a small experimental forestry watershed to check the performance and know the total load of water quality from the forest. It was found that the system to collect a proportional amount of water to actual discharge operated perfectly and a total load of water quality was analyzed accurately. As the result, it was expected that the system will be very available to know the total load from a non-point source area.
In this study, regression equation was analyzed to estimate non-point source (NPS) pollutant loads in orchard area. Many factors affecting the runoff of NPS pollutant as precipitation, storm duration time, antecedent dry weather period, total runoff density, average storm intensity and average runoff intensity were used as independent variables, NPS pollutant was used as a dependent variable to estimate multiple regression equation. Based on the real measurement data from 2008 to 2012, we performed correlation analysis among the environmental variables related to the rainfall NPS pollutant runoff. Significance test was confirmed that T-P ($R^2=0.89$) and BOD ($R^2=0.79$) showed the highest similarity with the estimated regression equations according to the NPS pollutant followed by SS and T-N with good similarity ($R^2$ >0.5). In the case of regression equation to estimate the NPS pollutant loads, regression equations of multiplied independent variables by exponential function and the logarithmic function model represented optimum with the experimented value.
Recently, the population growth and agricultural development are rapidly undergoing in the South-West Texas. The junction of three river basins such as Lavaca river basin, Colorado-Lavaca Coastal basin and Lavaca-Guadalupe Coastal basin, are interesting for non-point and point source pollutant modeling: Especially, the 2 basins are an intensively agricultural region (Colorado-Lavaca Coastal/Lavaca-Guadalupe Coastal basins) and several cities are rapidly extended. In case of the Lavaca river basin, there are many range land. Several habitat types wide-spread over three relatively larger basins and five wastewater discharge regions are located in there. There are different hazardous substances which have been released. Total nutrient loads are composed of land surface load and river load as Non-point source and discharge from wastewater facilities as point source. In 3 basins region, where point and non-point sources of poll Jtion may be a big concern, because increasing fertilizers and pesticides use and population cause. This project objective seeks to how to assess and control the accumulation of non-point and point source and discuss the main impacts of agriculture and environmental concern as non-point source with water quality related to pesticides, fertilizer, and nutrients and as point source with wasterwater discharge from cities. The GIS technique has been developed to aid in the point and non-point source analysis of impacts to natural resource within watershed. This project shows the losses in $kg/km^2/year$ of BOD (Biological Oxygen Demand), TN (Total Nitrogen) and TP (Total Phosphorus) in the runoff from the surface of 3 basins. In the next paper, sediment contamination will show how to evaluate in Estuarine habitats of these downstream.
Kim, Jonggun;Park, Youn Shik;Lee, Seoro;Shin, Yongchul;Lim, Kyoung Jae;Kim, Ki-sung
Journal of The Korean Society of Agricultural Engineers
/
v.59
no.4
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pp.97-107
/
2017
This study is to determine the coefficients of regression equations and to select the optimal regression equation in the LOADEST model after classifying the whole study period into 5 flow conditions for 16 watersheds located in the Nakdonggang waterbody. The optimized coefficients of regression equations were derived using the gradient descent method as a learning method in Tensorflow which is the engine of machine-learning method. In South Korea, the variability of streamflow is relatively high, and rainfall is concentrated in summer that can significantly affect the characteristic analysis of pollutant loads. Thus, unlike the previous application of the LOADEST model (adjusting whole study period), the study period was classified into 5 flow conditions to estimate the optimized coefficients and regression equations in the LOADEST model. As shown in the results, the equation #9 which has 7 coefficients related to flow and seasonal characteristics was selected for each flow condition in the study watersheds. When compared the simulated load (SS) to observed load, the simulation showed a similar pattern to the observation for the high flow condition due to the flow parameters related to precipitation directly. On the other hand, although the simulated load showed a similar pattern to observation in several watersheds, most of study watersheds showed large differences for the low flow conditions. This is because the pollutant load during low flow conditions might be significantly affected by baseflow or point-source pollutant load. Thus, based on the results of this study, it can be found that to estimate the continuous pollutant load properly the regression equations need to be determined with proper coefficients based on various flow conditions in watersheds. Furthermore, the machine-learning method can be useful to estimate the coefficients of regression equations in the LOADEST model.
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