In order to estimate the non-point pollution loads from each watersheds among 209 watersheds, the calibration and validation of HSPF model were carried out based on 2012 in 2013 years. In the case of flow rate, R2 of calibration and validation were 0.71~0.93 and 0.71~0.79, which were relatively good values. With the respect to calibration of water quality, % differences between measured and simulated values were 0.4 ~ 9.7 of DO, BOD 0.5 ~ 30.2% and TN 1.9~28.6% except for Hwhangkang B site. In case of validation, DO was 0.2 ~ 13.7%, BOD 1.3~23% and TN 0.5~24.3% excluding Hwhangkang B. However, since the concentration of TP was very small compared with other items, the range of difference was large as 0.8~55.3%. level. As the result of calculating annual accumulative BOD loads for each watershed, it was found that RCH 123 (Uryeong, Gyeongsangnamdo), RCH 121 (Jinju, Gyeongsangnamdo) and RCH 92 (Daegu) were the high ranked. The unit watersheds including various landuse type susch as forest and agricultural sites in mainstream areas have a higher BOD nonpoint pollution load than those in dam regions. However, the results of the annual cumulative loading of the basins for nutrients did not appear to be consistent with the BOD annual cumulative loading ranks. Other factors that represent watershed characteristics such as landslope and soiltypes, including landuse pattern, have been found to be closely related to nonpoint pollutant loads.
Journal of Korean Society of Environmental Engineers
/
v.30
no.1
/
pp.97-105
/
2008
Nitrogen budgets in Korea in 2005 were estimated using a mass balance approach. Major nitrogen fluxes were divided into three sections: cities, agricultural area, and forest. Nitrogen inputs were chemical and biological fixation, dry and wet deposition, imported food and feed, while crop uptake, volatilization, denitrification, leaching, runoff, and forest consumption were nitrogen outputs. Non-point source(NPS) pollution budgets were also estimated by mass balance approach. Annual total nitrogen inputs budgets were 1,442,254 ton$\cdot$yr$^{-1}$, and outputs were 814,415 ton$\cdot$yr$^{-1}$. Approximately 19.4% of nitrogen input leaked to river and seawater as NPS pollution. It contains nitrogen input 21 percent more than the previous research in 2002. Especially the change of government plans affect nitrogen budget. As a result, in the output field, the whole nitrogen amount due to landfill reduce from 20 percent to less than 1 percent.
This study was conducted to evaluate the influence of pollutant loads on the water quality in the Mankyeong River from January 2002 to December 2004. The BOD level in upstream ranged from 0.58 to 1.57 mg $L^{-1}$, which would be in I grade according to water quality criteria by Ministry of Environment but BOD level in midstream and downstream was III grade. T-N contents were high in midstream and the average T-P level ranged from 0.06 to 2.70 mg $L^{-1}$. The point raw loads of BOD was high in Iksancheon, Mokcheonpo and Cheongha basin. The point raw loads of T-N and T-P were high in Iksancheon and Cheongha watershed. The non-point low loads of BOD were 3,931 kg $day^{-1}$, 2,870 kg $day^{-1}$ and 2,827 kg $day^{-1}$ in Mokcheonpo, Top and Jeonju watershed, respectively. The major source of BOD effluent load was population, that of T-N and T-P effluent loads was livestock. The delivered load of T-N were high in Jeonju, Mokcheonpo, Gosan, Iksancheon watershed in order. The delivered load of T-N was high in Jeonju watershed and that of T-P was high in Jeonju and Iksancheon watershed. The delivery ratio of BOD and T-N at dry season were below 100% except Mokcheonpo watershed. The delivery ratio of BOD and T-N at raining season were high in Gosan watershed.
Pollutant unit load developed by Ministry of Environment (MOE) in 1995 has been a tool commonly used for water quality management and environmental policy decision. In spite of the convenience of the method in application, the shortcoming of the method has been criticized especially for nonpoint source pollution from paddy field. In this paper the estimation procedures of pollutant unit load from paddy field in the major river basins (Han, Nakdong, Geum, and Youngsan river) were investigated, and some suggestions of improvement measures of the unit-load estimation were made. The investigation showed that the distributions of rainfall, run-off, and run-off ratio, which are the most important factors affecting discharge amount of pollutants, were not similar among river basins. Such differences seemed to result in a greater unit loads estimation at Han river and at Nakdong river watersheds compared to the others. Therefore, it is not likely to be rationale to compare unit load among the watersheds without consideration of such differences. We conclude that estimation of unit-load through an intensive monitoring of pollutant discharge is crucial for better estimation of unit-load. When such an intensive monitoring is not easy due to labor and expense restriction, we suggest that unit-load should be estimated based on the storm-events which is a representative rainfall-runoff event of the area.
As a drinking water source of 26 millions people of Seoul metropolitan region, Han river is one of the most important basin. Managing the Non-point source pollution which is regarded as the main cause of water pollution including refractory organic matter is important thing. This research investigates the runoff characteristics of organic matters from main 3 rivers (South Han, North Han, Kyungan). Water quality measurement items include not only carbon-based TOC (Total Organic Carbon), DOC (Dissolved Organic Carbon), POC (Particulate Organic Carbon) but also R-TOC (Refractory Total Organic Carbon), R-DOC (Refractory Dissolved Organic Carbon), R-POC (Refractory Particulate Organic Carbon) is researched. The research shows that R-TOC takes approximately 61~83% of TOC. Most of the R-TOC is consist of R-DOC (72~77%). Refractory organic matter have a stable runoff characteristics compared to other organic matter. The organic matter concentrations of South Han river and Kyungan river are the highest in spring time and show a gradual decline. The concentrations of Kyunan river is the highest. Kyungan river's small area and the high city land use ratio seem to be the reason. Loading of organic matter in summer time takes the most loading (62~84%). TOC loadings per unit area of each river is Kyungan river ($1.22ton/km^2$), South Han river ($1.01ton/km^2$), North Han river ($0.91ton/km^2$).
Arguably many studies point out that regional innovation capabilities are accepted as a major source of growth for the sustainable regional economy. Recently, a smart specialisation strategy that should reflect regional characteristics in the policy implementation process of the regional innovation system has been proposed, but empirical studies have only presented limited results. This study attempts to overcome limitations by approaching smart specialisation as a supplementary strategy for existing regional innovation research. To this end, smart specialisation was not an alternative strategy for the regional innovation system, but rather the institutional elements of regional innovation capabilities, and the relationship between regional innovation capabilities and the local economy was analyzed to identify the impact of smart specialisation on the local economy. A study was conducted through a panel model consisting of 16 cities and provinces in Korea and 10 years from 2009-2018, and the FGLS model was finally used through the process of searching for an appropriate panel model. As a result of the study, smart specialisation consisting of industry related variety and non-related variety had a positive effect on the local economy. In addition, other regional innovation capabilities measured by dividing them into base and facilitating factors also had a positive effect on the local economy, reaffirming the results of positive research between existing regional innovation and the local economy. This study is meaningful in that smart specialisation lacking in domestic research was viewed as an institutional element of regional innovation capabilities, and it was measured through regional industry-related variety and non-related variety.
As a result of the growing livestock industry, varieties of organic solid and waste biomass are be generated in swine breeding and slaughtering stages. Anaerobic digestion is a promising alternative for the treatment of livestock waste biomass, as well as for the material recovery and energy production. Objectives of this study were to analyze the biochemical methane potential of swine waste biomasses that were generated from swine pen and slaughterhouse and to investigate the material recovery and methane yield per head. As pig waste biomass, swine slurry, blood, intestine residue, and digestive tract content were collected for investigation from pig farmhouse and slaughterhouse. The $B_{th}$ (Theoretical methane potential) and $B_0$ (Biochemical methane potential) of swine slurry generating in swine breeding stage were 0.525 and $0.360Nm^3\;kg^{-1}-VS_{added}$, the ratio of degradation ($B_0/B_{th}$) was 68.6%. $B_{th}$ of blood, intestine residue, and digestive tract content were 0.539, 0.664, and $0.517Nm^3\;kg^{-1}-VS_{added}$, and $B_0$ were 0.405, 0.213, and $0.240Nm^3\;kg^{-1}-VS_{added}$, respectively. And the ratio of degradation showed 75.1, 32.1, and 46.4% in blood, intestine residue, and digestive tract content. Material yield of swine waste biomass was calculated as TS 73.79, VS 46.75, TN 5.58, $P_2O_5$ 1.94, and $K_2O$$2.91kg\;head^{-1}$. And methane yield was $16.58Nm^3\;head^{-1}$. In the aspect that slaughterhouse is a large point source of waste biomass, while swine farmhouse is non-point source, the feasibility of an anaerobic digestion using the slaughtering waste biomass need to be assessed in the economical aspect between the waste treatment cost and the profitable effect by methane production.
To understand the status of water quality and work out a suitable countermeasures in Seonakdong watershed which has poor agro- environmental condition because of severe point and non-point source pollution by popularized city and near sea, we investigated the pollution sources and water quality from '03 and '05 and the result were mapped with GIS and RS for end-users's convenient comprehense and conjunction of water quality and geological data. The most degraded tributary was Hogeo stream which was affected directly by highly popularized Gimhae city, the main pollution source of the watershed. The pollution of tributaries in watershed increased the T-N of main body that reached over 4 mg/L during dry season. Pyeonggang stream and the lower part of main water way were suffered from high salt contents induced near sea and the EC value of those area were increased to 2.25 dS/m. The delivered loads of T-N and T-P were largest in Joman river as 56% and 61% of total delivered loads 1mm tributaries because of lots of stream flow. When Management mandate for irrigation water in Seonakdong river watershed was mapped for estimating integrated water quality as the basis of classification of EC and T-N contents in water, Hogeo and Shineo catchments were showed the requiring countermeasures none against nutrients hazard and Pyeonggang catchment was the vulnerable zone against nutrients and salts hazard. As the result, Seonakdong watershed had very various status of water quality by characteristics of catchments and countermeasures for improving water quality and crop productivity safely should changed depend on that.
A mathematical modeling program called Hydrological Simulation Program-FORTRAN (HSPF) developed by the United States Environmental Protection Agency(EPA) was applied to the Yongdam Watershed to examine its applicability for loading estimates in watershed scale. 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 ${\sim}$ 2003. The model efficiency of runoff was high in comparison between simulated and observed data, while it was relatively low in the water quality parameters. But its reliability and performance were within the expectation considering complexity of the watershed and pollutant sources and land uses intermixed in the watershed. The estimated pollutant load from Yongdam watershed for BOD, T-N and T-P was 1,290,804 kg $yr{-1}$, 3,753,750 kg $yr{-1}$ and 77,404 kg $yr{-1}$,respectively. Non-point source (NPS) contribution was high showing BOD 57.2%, T-N 92.0% and T-P 60.2% of the total annual loading in the study area. The NPS loading during the monsoon rainy season (June to September) was about 55 ${\sim}$ 72% of total NPS loading, and runoff volume was also in a similar rate (69%). However, water quality was not necessarily high during the rainy season, and showed a decreasing trend with increasing water flow. Overall, the BASINS/HSPF was applied to the Yongdam watershed successfully without difficulty, and it was found that the model could be used conveniently to assess watershed characteristics and to estimate pollutant loading in watershed scale.
Kim, Jin-Ho;Kim, Chan-Yong;Lee, Seong-Tae;Choi, Chul-Mann;Jung, Goo-Bok;Lee, Jong-Sik;Kim, Won-Il
Korean Journal of Environmental Agriculture
/
v.26
no.2
/
pp.99-106
/
2007
This study was focused on understanding the agricultural non-point sources pollution in 72 rural catchments of Nakdong river watershed from 2001 to 2005 every two year. Also. Pearson correlations between water quality and basin characteristic were computed. Water quality of this study watershed was better in 2003 than any other period. The water quality of upstream was recorded from 0.040 to 0.510 dS/m in EC, from 3.55 to 22.60 mg/L in DO, from 0.32 to 16.64 mg/L in T-N, from 0.00 to 12.21 mg/L in $NO_3-N$, from 0.000 to 0.860 mg/L in T-P, and from 0.000 to 0.640 mg/L in $PO_4-P$. A the downstream, EC was measured from 0.030 to 0.520 dS/m, DO from 4.13 to 18.36 mg/L, T-N from 0.38 to 26.88 mg/L, $NO_3-N$ from 0.10 to 20.12 mg/L, T-P from 0.002 to 0.820 mg/L, $PO_4-P$ from 0.002 to 0.690 mg/L. But there was no difference between upstream and downstream for the water quality. Based on the correlation analysis between water quality and land use, correlation between BOD and residential was the highest positive correlation of 0.541 (p<0.01), and correlation between $PO_4-P$ and forest was the highest negative correlation of -0.451 (p<0.01). Also, T-N, $NO_3-N$, and pH were not correlated with all basin characteristics and basin was not correlated with all water quality parameter. According to the correlation residential was causative of growing worst for water quality, and forest was causative of improving for water quality.
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