• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.574-574
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• 2016

유역으로 유입되는 오염물질의 발생원은 점오염원과 비점오염원으로 구분할 수 있으며 점오염원의 경우 생활하수, 산업폐수, 그리고 축산폐수에 대해 처리시설 확충 및 기술개발을 통해 관리하고 있다. 비점오염원에서의 오염물질 유출은 토지이용, 강우, 불특정적인 오염물질 투입상태 등에 따라 다르며, 지역적 특성에 영향을 받기 때문에 불확실성이 고려되어야 한다. 특히 농촌지역에서의 비점오염은 접근이 어렵고 관리주체가 모호하여 좀처럼 규명되지 않았으며, 전국적으로 그 영향이 정량화되지 않아 실질적인 관리 및 대책마련에 어려움이 있었다. 특히, 가축분뇨의 발생으로부터 처리, 자원화에 이르기까지 각 관리체계에 있어서 축산비점오염의 배출경로와 수계오염부하량, 수질환경 영향을 정밀하게 분석하여 향후 대책마련을 위한 기초자료를 확보할 필요가 있다. 또한 전국적으로 비점오염이 수계에 미치는 영향과, 그 중 축산비점오염의 영향을 면밀히 분석하여 향후 정책 및 제도개선을 위한 과학적 기초자료로서 활용할 필요가 있다. 따라서 본 연구에서는 축산 밀집 지역을 대상으로 오염원 조사를 통해 강우시 비점오염 모니터링 지점을 선정 하였으며, 년5회씩 강우 모니터링을 하여 기초데이터를 축적 하였다. 대상지역은 강원도 횡성군에 위치한 일리천 유역이며 농가 수는 총 90개의 농가가 위치하고 있는데 그 중 돼지 1,467마리, 한우 1,957마리, 젖소 581마리, 개 2,880마리, 닭 75,000마리, 사슴 4마리로 조사되었다. 대상유역을 대상으로 배출부하량을 조사한 결과 BOD 배출부하량은 총 509.3 kg/day, T-N 배출부하량은 총 331.5 kg/day, T-P 배출부하량은 총 28.3 kg/day로 조사되었다. 유출특성을 파악하기 위하여 유량가중평균농도(Event Mean Concentration, EMC)를 산정한 결과 BOD의 경우 MW-4에서 1.2 mg/L - 7.2 mg/L, MW-5에서 0.8 mg/L - 6.3 mg/L, MW-7에서 0.7 mg/L - 5.2 mg/L의 범위를 보였다. T-N의 경우 MW-4에서 1.426 mg/L - 5.321 mg/L, MW-5에서 1.205 mg/L - 4.27 mg/L, MW-7에서 0.989 mg/L - 3.859 mg/L의 범위를 보였다. T-P의 경우 MW-4에서 0.245 mg/L - 0.632 mg/L, MW-5에서 0.236 mg/L - 0.596 mg/L, MW-7에서 0.213 mg/L - 0.521 mg/L의 범위를 보였다. 본 연구에서 EMC를 산정한 방법은 평시 수질 및 유량을 정하는 기준에 따라 값이 많이 달라질 수 있다. 따라서 합리적으로 평시 부하량을 제외하고 강우시의 영향을 파악할 수 있는 EMC 산정방법에 대한 추가적인 고찰이 필요할 것으로 사료된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.282-282
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• 2021

강우시 농경지와 축산시설로부터 유출되는 비점오염물질은 하류 수계의 수질과 수생태계에 악영향을 미친다. 이에 따라 환경부에서는 비점오염원관리지역을 지정하고 다양한 비점오염 저감 대책을 시행하고 있다. 본 연구에서는 비점오염원관리지역으로 지정된 안동댐 하류 중 송야천 유역을 대상으로 강우유출수 모니터링을 수행하였으며, 모니터링 결과를 바탕으로 강우시 비점오염물질 유출 특성을 분석하였다. 모니터링 기간은 2020년 6월부터 11월까지 총 5회의 강우사상에 대하여 상·하류와 유입하천을 포함한 총 8개의 모니터링 지점을 대상으로 강우사상별 유량가중평균농도(Event Mean Concentration, EMC), 오염부하, 단위면적당 오염부하를 산정하였으며, 오염원 그룹별 비점배출부하를 산정하여 오염 기여도를 분석하였다. 강우유출수 조사결과를 이용한 EMC 농도 산정 결과 유입하천인 오산천 지점이 SS와 TOC 항목을 제외한 모든 수질항목의 EMC 농도가 가장 큰 것으로 나타났다. 단위면적당 오염부하를 산정하여 비교 분석한 결과 T-P 항목의 단위면적당 오염부하는 물한천 지점(0.69 kg/ha)과 오산천 지점(0.69 kg/ha)이 크게 나타났다. 결과와 같이 오산천 지점과 물한천 지점이 오염정도가 큰 것으로 나타났으며, 이에 따른 상류 오염원 현장 정밀조사를 수행하였다. 조사 결과 강우발생시 상류에 위치한 농경지와 축사에서 발생하는 오염원이 하천으로 유입되고 있었으며, 여러 축사에서 배출되고 있는 유입수를 채취하여 분석한 결과 T-P 농도가 평균 0.935 mg/L로 높게 나타났다. 전국오염원조사자료(국립환경과학원, 2017) 내용을 참조하여 송야천 유역의 오염원 그룹별 비점배출부하를 산정해 오염 기여도를 분석한 결과, T-P 항목의 경우 축산계와 토지계의 비점배출부하가 전체 비점배출부하의 약 63%와 37%를 차지해 비점배출부하 기여도가 큰 것으로 나타났다. 이와 같이 송야천 유역의 경우 강우시 농경지와 축산시설에서 배출되는 오염물질이 하천 수질오염에 상당한 기여를 하고 있는 것으로 보여지며, 비점오염원 발생에 대한 대책 마련이 필요할 것으로 사료된다. 본 연구 결과는 송야천 유역의 비점오염 저감 대책 수립을 위한 기초자료로 활용할 수 있을 것으로 판단된다.

• Journal of Wetlands Research
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• v.18 no.3
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• pp.275-281
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• 2016

This study was conducted to analyze the runoff characteristics of the highway depending on the number of vehicles and to provide the installation proposal of an NPS pollution reduction facility. There were a total of 5 monitoring sites used for the study namely, Gyeongbu, Seohaean, Honam and Tongyeoung Dageon highway. Monitoring events started from 2006 until 2015 having a total of 44 storm events. According to monitoring statistics, the average antecedent dry days (ADD) and rainfall was 6.2 days and 19.2 mm, respectively. The Gyeongbu Highway (H-4) was recorded having the highest Average Daily Traffic and Catchment Area (ADT/CA) with $49.4car/day{\cdot}m^2$ while other site were less than $10car/day{\cdot}m^2$. The average concentration of the NPS pollutants generated from monitoring sites were 63.5 mg/L(TSS), 24.9 mg/L(BOD), 3.35 mg/L(TN), 0.63 mg/L(TP) and 298 ug/L(Total Zn). This exhibited lower values in comparison to the remarks of highway related runoff EMC values published in Korea. Moreover, through the results of the correlation analysis between the contaminant concentration and ADT/CA, $R^2$ value of SS showed the highest correlation with 585. Through the correlation equation between ADT/CA and EMC of TSS, when there is 73.7 mg/L of TSS EMC found from a domestic highway, ADT/CA ratio is normally $13car/day{\cdot}m^2$. Therefore, in a case of more than 13 cars passing through a certain area, the area can be considered and present as the point of generation of nonpoint source pollutants. Also, in this study, since it considered a unit area ADT indicated in previous studies, it was determined that it has a high applicability and utilization in generalized units than conventional study which were conventionally done.

• Magazine of the Korean Society of Agricultural Engineers
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• v.19 no.1
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• pp.4296-4311
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• 1977

This study was conducted to derive an Instantaneous Unit Hydrograph for the accurate and reliable unitgraph which can be used to the estimation and control of flood for the development of agricultural water resources and rational design of hydraulic structures. Eight small watersheds were selected as studying basins from Han, Geum, Nakdong, Yeongsan and Inchon River systems which may be considered as a main river systems in Korea. The area of small watersheds are within the range of 85 to 470$\textrm{km}^2$. It is to derive an accurate Instantaneous Unit Hydrograph under the condition of having a short duration of heavy rain and uniform rainfall intensity with the basic and reliable data of rainfall records, pluviographs, records of river stages and of the main river systems mentioned above. Investigation was carried out for the relations between measurable unitgraph and watershed characteristics such as watershed area, A, river length L, and centroid distance of the watershed area, Lca. Especially, this study laid emphasis on the derivation and application of Instantaneous Unit Hydrograph (IUH) by applying Nash's conceptual model and by using an electronic computer. I U H by Nash's conceptual model and I U H by flood routing which can be applied to the ungaged small watersheds were derived and compared with each other to the observed unitgraph. 1 U H for each small watersheds can be solved by using an electronic computer. The results summarized for these studies are as follows; 1. Distribution of uniform rainfall intensity appears in the analysis for the temporal rainfall pattern of selected heavy rainfall event. 2. Mean value of recession constants, Kl, is 0.931 in all watersheds observed. 3. Time to peak discharge, Tp, occurs at the position of 0.02 Tb, base length of hlrdrograph with an indication of lower value than that in larger watersheds. 4. Peak discharge, Qp, in relation to the watershed area, A, and effective rainfall, R, is found to be {{{{ { Q}_{ p} = { 0.895} over { { A}^{0.145 } } }}}} AR having high significance of correlation coefficient, 0.927, between peak discharge, Qp, and effective rainfall, R. Design chart for the peak discharge (refer to Fig. 15) with watershed area and effective rainfall was established by the author. 5. The mean slopes of main streams within the range of 1.46 meters per kilometer to 13.6 meter per kilometer. These indicate higher slopes in the small watersheds than those in larger watersheds. Lengths of main streams are within the range of 9.4 kilometer to 41.75 kilometer, which can be regarded as a short distance. It is remarkable thing that the time of flood concentration was more rapid in the small watersheds than that in the other larger watersheds. 6. Length of main stream, L, in relation to the watershed area, A, is found to be L=2.044A0.48 having a high significance of correlation coefficient, 0.968. 7. Watershed lag, Lg, in hrs in relation to the watershed area, A, and length of main stream, L, was derived as Lg=3.228 A0.904 L-1.293 with a high significance. On the other hand, It was found that watershed lag, Lg, could also be expressed as {{{{Lg=0.247 { ( { LLca} over { SQRT { S} } )}^{ 0.604} }}}} in connection with the product of main stream length and the centroid length of the basin of the watershed area, LLca which could be expressed as a measure of the shape and the size of the watershed with the slopes except watershed area, A. But the latter showed a lower correlation than that of the former in the significance test. Therefore, it can be concluded that watershed lag, Lg, is more closely related with the such watersheds characteristics as watershed area and length of main stream in the small watersheds. Empirical formula for the peak discharge per unit area, qp, ㎥/sec/$\textrm{km}^2$, was derived as qp=10-0.389-0.0424Lg with a high significance, r=0.91. This indicates that the peak discharge per unit area of the unitgraph is in inverse proportion to the watershed lag time. 8. The base length of the unitgraph, Tb, in connection with the watershed lag, Lg, was extra.essed as {{{{ { T}_{ b} =1.14+0.564( { Lg} over {24 } )}}}} which has defined with a high significance. 9. For the derivation of IUH by applying linear conceptual model, the storage constant, K, with the length of main stream, L, and slopes, S, was adopted as {{{{K=0.1197( {L } over { SQRT {S } } )}}}} with a highly significant correlation coefficient, 0.90. Gamma function argument, N, derived with such watershed characteristics as watershed area, A, river length, L, centroid distance of the basin of the watershed area, Lca, and slopes, S, was found to be N=49.2 A1.481L-2.202 Lca-1.297 S-0.112 with a high significance having the F value, 4.83, through analysis of variance. 10. According to the linear conceptual model, Formular established in relation to the time distribution, Peak discharge and time to peak discharge for instantaneous Unit Hydrograph when unit effective rainfall of unitgraph and dimension of watershed area are applied as 10mm, and $\textrm{km}^2$ respectively are as follows; Time distribution of IUH {{{{u(0, t)= { 2.78A} over {K GAMMA (N) } { e}^{-t/k } { (t.K)}^{N-1 } }}}} (㎥/sec) Peak discharge of IUH {{{{ {u(0, t) }_{max } = { 2.78A} over {K GAMMA (N) } { e}^{-(N-1) } { (N-1)}^{N-1 } }}}} (㎥/sec) Time to peak discharge of IUH tp=(N-1)K (hrs) 11. Through mathematical analysis in the recession curve of Hydrograph, It was confirmed that empirical formula of Gamma function argument, N, had connection with recession constant, Kl, peak discharge, QP, and time to peak discharge, tp, as {{{{{ K'} over { { t}_{ p} } = { 1} over {N-1 } - { ln { t} over { { t}_{p } } } over {ln { Q} over { { Q}_{p } } } }}}} where {{{{K'= { 1} over { { lnK}_{1 } } }}}} 12. Linking the two, empirical formulars for storage constant, K, and Gamma function argument, N, into closer relations with each other, derivation of unit hydrograph for the ungaged small watersheds can be established by having formulars for the time distribution and peak discharge of IUH as follows. Time distribution of IUH u(0, t)=23.2 A L-1S1/2 F(N, K, t) (㎥/sec) where {{{{F(N, K, t)= { { e}^{-t/k } { (t/K)}^{N-1 } } over { GAMMA (N) } }}}} Peak discharge of IUH) u(0, t)max=23.2 A L-1S1/2 F(N) (㎥/sec) where {{{{F(N)= { { e}^{-(N-1) } { (N-1)}^{N-1 } } over { GAMMA (N) } }}}} 13. The base length of the Time-Area Diagram for the IUH was given by {{{{C=0.778 { ( { LLca} over { SQRT { S} } )}^{0.423 } }}}} with correlation coefficient, 0.85, which has an indication of the relations to the length of main stream, L, centroid distance of the basin of the watershed area, Lca, and slopes, S. 14. Relative errors in the peak discharge of the IUH by using linear conceptual model and IUH by routing showed to be 2.5 and 16.9 percent respectively to the peak of observed unitgraph. Therefore, it confirmed that the accuracy of IUH using linear conceptual model was approaching more closely to the observed unitgraph than that of the flood routing in the small watersheds.

• Tuberculosis and Respiratory Diseases
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• v.45 no.1
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• pp.153-168
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• 1998

Background: The existing data indicate that obstructive sleep apnea syndrome contributes to the development of cardiovascular dysfunction such as systemic hypertension and cardiac arrhythmias, and the cardiovascular dysfunction has a major effect on high long-term mortality rate in obstructive sleep apnea syndrome patients. To a large extent the various studies have helped to clarify the pathophysiology of obstructive sleep apnea, but many basic questions still remain unanswered. Methods: In this study, the influence of obstructive sleep apnea on systemic blood pressure, cardiac rhythm and urinary catecholamines concentration was evaluated. Over-night polysomnography, 24-hour ambulatory blood pressure and ECG monitoring, and measurement of urinary catecholamines, norepinephrine (UNE) and epinephrine (UEP), during waking and sleep were undertaken in obstructive sleep apnea syndrome patients group (OSAS, n=29) and control group (Control, n=25). Results: 1) In OSAS and Control, UNE and UEP concentrations during sleep were significantly lower than during waking (P<0.01). In UNE concentrations during sleep, OSAS showed higher levels compare to Control (P<0.05). 2) In OSAS, there was a increasing tendency of the number of non-dipper of nocturnal blood pressure compare to Control (P=0.089). 3) In both group (n=54), mean systolic blood pressure during waking and sleep showed significant correlation with polysomnographic data including apnea index (AI), apnea-hypopnea index (AHI), arterial oxygen saturation nadir ($SaO_2$ nadir) and degree of oxygen desaturation (DOD). And UNE concentrations during sleep were correlated with AI, AHI, $SaO_2$ nadir, DOD and mean diastolic blood pressure during sleep. 4) In OSAS with AI>20 (n==14), there was a significant difference of heart rates before, during and after apneic events (P<0.01), and these changes of heart rates were correlated with the duration of apnea (P<0.01). The difference of heart rates between apneic and postapneic period (${\Delta}HR$) was significantly correlated with the difference of arterial oxygen saturation between before and after apneic event (${\Delta}SaO_2$) (r=0.223, P<0.001). 5) There was no significant difference in the incidence of cardiac arrhythmias between OSAS and Control In Control, the incidence of ventricular ectopy during sleep was significantly lower than during waking. But in OSAS, there was no difference between during waking and sleep. Conclusion : These results suggested that recurrent hypoxia and arousals from sleep in patients with obstructive sleep apnea syndrome may increase sympathetic nervous system activity, and recurrent hypoxia and increased sympathetic nervous system activity could contribute to the development of cardiovascular dysfunction including the changes of systemic blood pressure and cardiac function.