본 연구는 낙동강 본류에 서식하는 Pectinatella magnifica의 출현양상을 조사하기 위해 발생시기인 2014년 7월~11월 동안 기본 분포조사와 출현밀도가 높은 지역을 대상으로 집중조사를 실시하였다. 그 결과, 낙동강 본류 구간 내 Pectinatella magnifica의 부착기질은 인공적으로 형성된 기질에서 12.3%, 자연기질에서 87.7%로써 자연기질에서 매우 높게 확인되었으나 자연기질에 포함된 식물군락의 특정 종에 따른 선호하는 정도는 유의한 차이를 보이지 않았다. 반면 본 조사 결과에서는 고착대상으로 하는 기질의 분포 정도의 차이는 P. magnifica의 분포 차이에 영향을 미치고 있음을 보여주었다. 그러므로 태형동물이 선호하는 출현기질의 증가는 P. magnifica의 성장 및 분포에 영향을 미치는 요인 중 하나로써 작용될 것으로 사료된다.

To investigate the distribution characteristics of grain size and organic matter of surface sediments from the Nakdong-Goryeong Mid-watershed, surface sediments were collected and analyzed. The samples were collected from six sited at four different times between May 2013 and May 2014. The were analyzed for grain size, water content, ignition loss, chemical oxygen demand, total organic carbon and total nitrogen. The surface sediments were mainly composed of medium sand (mean 44.7%) and coarse sand (mean 32.8%) and became coarser in May 2014. Fine sediments at the site NG-2 were poorly sorted and positively skewed, and occur in a tributary environment that is relatively low-energy compared with the other sites. The water content at the studied sites (15.3 ~ 34.9%) averaged 20.25%, and ignition loss (0.4 ~ 5.8%) and total nitrogen (274 ~ 2493 mg/kg) averaged 1.33% and, 696 mg/kg, respectively. These values indicated that the sediments were not seriously contaminated when compared with the sediment pollution evaluation standard of the National Institute of Environmental Research. The chemical oxygen demand (mean 0.17%) was at the non-polluted level compared with United States Environmental Protection Agency sediment quality standards. The total organic carbon (mean 0.18%) at all sites except site NG-2 (lowest effect level) was the no effect level of the Ontario sediment quality guidelines. The COD/IL (0.02 ~ 0.20) and C/N (0.73 ~ 6.76) were less than 1 and 10, respectively. Organic matter in the study area produced naturally from aquatic organisms. Results of principal component analysis showed that fine sediments (very fine sand and silt) were significantly affected by organic matters (ignition loss, chemical oxygen demand, total organic carbon and total nitrogen). In addition, the highest organic matters content in the study area occurred at the site with the finest sediments (NG-2).

Multifunctional weirs constructed through the Four Major Rivers Restoration Project are operated as management water levels. The purpose of this study was to evaluate the effect of water level in the main stem on the tributary water level according to multifunctional weir operation, because the operation of multifunctional weirs for water level management influences the drainage of tributaries. In this study, water level pressure gauges were installed and spatial and temporal water quality was observed. The LOcally Weighted Scatterplot Smoothing (LOWESS) technique was applied to the Nakdong River and the Baekcheon Junction, both upstream of the Gangjeong-Goryeong weir, in order to analyze water quality trends. When considering the overall analysis and observations, it was found that the water quality forecasting point located at the Baekcheon estuary point should be transferred to the Dosung Bridge, which is located upstream of the Sunwon Bridge.

As part of the Four Major Rivers Restoration Project, multifunctional weirs have been constructed in the rivers and operated for river-level management. As the weirs play a role in draining water from tributaries, the aim of this study was to determine the influence of the weirs on the water level of the Nam River, which is one of the Nakdong River’s tributaries. Self-organizing maps (SOMs) and a locally weighted scatterplot smoothing (LOWESS) technique were applied to analyze the patterns and trends of water level and quality of the Nakdong River, considering the operation of the Changnyeong-Haman weir, which is located where the Nam River flows into the Nakdong River. The software program HEC-RAS was used to find the boundary points where the water is well drained. Per the study results at the monitoring points ranging between the junction of the two rivers and 17.5 km upstream toward the Nam River, the multifunctional weir influenced the water level at the Geoyrong and Daesan observation stations on the Nam River and the water quality based on automatic monitoring at the Chilseo station on the Nakdong River was affected strongly by the Nakdong River and partly by the Nam River.

For the development of flow duration curves for the management of 41 Total Maximum Daily Load (TMDL) units of the Nakdong River basin, first, an equation for estimating daily flow rates as well as the level of correlation (correlation and determination coefficients) was extrapolated through regression analysis of discrete (Ministry of Environment) and continuous (Ministry of Land, Infrastructure and Transportation) measurement data. The equation derived from the analysis was used to estimate daily flow rates in order to develop flow duration curves for each TMDL unit. By using the equation, the annual flow duration curves and flow curves, for the entire period and for each TMDL unit of the basin, were developed to be demonstrated in this research. Standard flow rates (abundant-, ordinary-, low- and drought flows) for major flow duration periods were calculated based on the annual flow duration curves. Then, the flow rates, based on percentile ranks of exceedance probabilities (5, 25, 50, 75, and 95%), were calculated according to the flow duration curves for the entire period and are suggested in this research. These results can be used for feasibility assessment of the set values of primary and secondary standard flow rates for each river system, which are derived from complicated models. In addition, they will also be useful for the process of implementing TMDL management, including evaluation of the target level of water purity based on load duration curves.

Recently IPCC (International Panel on Climate Change, 2007) pointed out that global warming is a certain ongoing process on the earth, due to which water resources management is becoming one of the most difficult tasks with the frequent occurrences of extreme floods and droughts. In this study we made runoff predictions for several control points in the Geum River by using the watershed runoff model, SSARR (Streamflow Synthesis and Reservoir Regulation Model), with daily RCP 4.5 and RCP 8.5 scenarios for 100 year from 1st Jan 2006 to 31st Dec 2100 at the resolution of 1 km given by Climate Change Information Center. As a result of, the Geum River Basin is predicted to be a constant flow increases, and it showed a variation in the water circulation system. Thus, it was found that the different seasonality occurred.

This study was performed to analyze the effects of a water circulation green area plan on non-point source pollution in Gimhae South Korea. A quantitative analysis of Arc-GIS data was conducted by applying a watershed model based on Fortran to investigate the changes to direct runoff and pollution load. Results showed that prior to the implementation of the water circulation green area plan in Gimhae, direct runoff was 444.05 m3/year, total biological oxygen demand (BOD) pollution load was 21,696 kg/year, and total phosphorus (TP) pollution load was 1,743 kg/year. Implementation of the development plan was found to reduce direct runoff by 2.27%, BOD pollution load by 1.16% and TP pollution load by 0.19% annually. The reduction in direct runoff and non-point source pollution were attributed to improvements in the design of impermeable layers within the city.

The MFFn(Mass first flush), EMCs(Event mean concentrations) and runoff loads were analyzed for various rainy events(monitoring data from 2011 to 2012) in transportation area(rail road in station). The pollutant EMCs by volume of stormwater runoff showed the BOD5 9.6 ㎎/L, COD 29.9 ㎎/L, SS 16.7 ㎎/L, T-N 3.271 ㎎/L, T-P 0.269 ㎎/L in the transportation areas(Railroad in station). The average pollutant loading by unit area of stormwater runoff showed the BOD5 27.26 kg/㎢, COD 92.55 kg/㎢, SS 50.35 kg/㎢, T-N 10.13 kg/㎢ and T-P 10.13 kg/㎢ in the transportation areas. Estimated NCL-curve(Normalized cumulated-curve) was evaluated by comparison with observed MFFn. MFFn was estimated by varying n-value from 10% to 90% on the rainy events. The n-value increases, MFFn is closed to '1'. As time passed, the rainfall runoff was getting similar to ratio of pollutants accumulation. The result of a measure of the strength of the linear relationship between observed data and expected data under model was good.

This study analyzed the characteristics of stormwater runoff by rainfall type in orchard areas and transportation areas for 2 years(2010~2011year). Effluents were monitored to calculate the Event Mean Concentrations(EMCs) and runoff loads of each pollutant. The pollutant EMCs by volume of stormwater runoff showed the ranges of BOD 0.9~13.6 ㎎/L, COD 13.7~45.2 ㎎/L, SS 4.1~236.4 ㎎/L, T-N 2.123~21.111 ㎎/L, T-P 0.495~2.214 ㎎/L in the orchard areas, and was calculated as BOD 2.3~22.5㎎ /L, COD 4.4~91.1 ㎎/L, SS 4.3~138.3 ㎎/L, T-N 0.700~13.500 ㎎/L, T-P 0.082~1.345 ㎎/L in the transportation areas. The correlation coefficient of determination in the orchard area was investigated in the order of Total Rainfall(0.81) > Total Runoff(0.76) > Rainfall Intensity(0.56) > Rainfall Duration(0.46) > Antecedent Dry Days(0.27). Also, in the case of the transportation area was investigated in the order of Total Rainfall (0.55) > Total Runoff(0.54) > Rainfall Intensity(0.53) > Rainfall Duration(0.24) > Antecedent Dry Days(0.14). As the result, comparing valuables relating to runoff of non-pollutant source between orchard areas and transportation areas, orchard area(R2 ≥ 0.5 : X3, X4, X5) was investigated to have more influence of diverse independent valuables compared to the transportation area(R2 ≥ 0.5 : X3, X4) and the difference of discharge influence factor by the land characteristics appeared apparently.

Loading of NPS pollutant was valued through simulation by using BASINS/HSPF model which can simulate runoff volume in rainfall by time. For the verification of the model, it was analyzed the scatter diagram of the simulation value and measure value of water quality and runoff volume in Dongcheon estuary. Using the built model, a study on the time-variant characteristics of runoff and water quality was simulated by being classified into four cases. The result showed the simulation value was nearly same as that of the measured runoff. In the result of fit level test for measured value and simulated value, correlation of runoff volume was computed high by average 0.86 and in the water quality items, fit level of simulation and measurements was high by BOD 0.82, T-N 0.85 and T-P 0.79.

The MFFn(Mass First Flush) was analyzed for various rainy events(monitoring data from 2008 to 2009) in Transportation area(Highway, National road, Trunk road). Estimated MFFn using SWMM was evaluated by comparison with observed MFFn. MFFn was estimated by varying n-value from 10% to 90% on the rainy events. The n-value increases, MFFn is closed to '1'. As time passed, the rainfall runoff was getting similar to ratio of pollutants accumulation. The result of a measure of the strength of the linear relationship between observed data and expected data under model was good (R2=0.89). Pollutants runoff loads by volume showed Highway 26.6%, National road 44.8%, Trunk road 35.0% at the MFF20(20% by total runoff). A case of MFF30, pollutants runoff loads by volume showed Highway 40.2%, National road 54.3%, Trunk road 46.8%. According to the results, Initial precipitation basis were Highway MFF30, National road MFF20, Trunk road MFF30 when the Non-Point source control facilities set up.

In this study, occurrence status of nonpoint pollutants and characteristics of discharge by each nonpoint pollutants were examined through monitoring on nonpoint pollutants caused when raining in vineyard belonging to the agricultural area of various land use patterns. Also, the first flush analysis limited to studies on the existing non-percolation area was applied to percolation area to ascertain availability and criteria of study. Various water quality and sluice of nonpoint pollutants were analyzed, based on which discharge of nonpoint pollutants in agricultural area was ascertained to be influenced greatly by artificial factors such as period, cultivation, management, etc. Meanwhile, the first flush phenomenon at agricultural area was ascertained to occur, and the first flush was quantified through calculation of the first flush ratio. If MFF30 is based, discharge load by each nonpoint pollutants caused when raining was investigated to include 40.8% on the basis of total discharge. In case of SS in pollutants showed the highest first flush phenomenon of 64.8%. Through such a result, calculation possibility of the initial rain criteria was ascertained, and it was determined that reliability-assured criteria were calculated through further monitoring.

This study analyzed the characteristics of stormwater runoff in the orchard areas and quantitatively estimated effluence of nonpoint source pollutants for the volume of runoff. Two target areas under vine cultivation were each 2,000㎡ and 1,800㎡, located in Gyeongju City. Since grape was the only crop on the target area, the characteristics of stormwater runoff at vineyard could be evaluated independently. A total of 51 rainfall events in the vineyard area during two years(2008-2009) was surveyed, and 19 of them became stormwater runoff, with rainfall ranging 16.5 - 79.7 mm and antecedent dry period of 1-13 days. The pollutant runoff loads by volume of stormwater runoff showed BOD ranging 19.5 - 45.3% in 30% of runoff volume. The average pollution discharge rate was 32.4%, indicating small first flush effect of BOD. The range of SS concentrations was 5 –52.0% in 10% of runoff volume, showing the average 28.7% of discharge rate, about 3 times more than rainfall effluent. TOC and TN appeared to be similar to the results of BOD, the average discharge rate of 30.9% and 30.6% for TOC and TN, respectively, for 30% of stormwater runoff volume. Average discharge rate of COD and TP in the same runoff volume was 35.1% and 36%, respectively, showing comparatively high discharge ratio. As the targeted vineyard area was permeable land, the pollution load ratio against rainfall-runoff volume appeared to be 1:1, implying no strong first flush effect for all the survey items.

Milyanggang mid-watershed is located in downstream of Nakdong river basin. The pollutants from that watershed have an direct effect on Nakdong river water quality and it's control is important to manage a water quality of Nakdong river. A target year of Milyanggang mid-watershed water environment management plan is 2013. To predict a water quality at downstream of Milyang river, we have investigated and forecasted the pollutant source and it's loading. There are some plan to construction the sewage treatment plants to improve the water quality of Milyang river. Those are considered on predicting water quality. As results, it is shown that the population of Milyanggang mid-watershed is 131,857 and sewerage supply rate is 62.2% and the livestock is 1,775.300 in 2006. It is estimated that the population is 123,921, the sewerage supply rate is 75.5% in 2013. The generated loading of BOD and TP is 40,735 kg/day and 2,872 kg/day in 2006 and discharged loading is 11,818 kg/day and 722 kg/day in 2006 respectively. Discharged loadings were forecasted upward 1.0% of BOD and downward 2.7% of TP by 2013. The results of water quality prediction of Milyanggang 3 site were 1.6 mg/L of BOD and 0.120 mg/L of TP in 2013. It is over the target water quality at that site in 2015 about 6.7% and 20.0% respectively. Consequently, there need another counterplan to reduce the pollutants in that mid-watershed by 2015.

Growth in population and urbanization has progressively increased the loading of pollutants from nonpoint sources as well as point sources. Especially in case of road regions such as city trunk road, national road and highway are rainfall and pollutants runoff intensive landuses since they are impervious and emit a lot of pollutants from vehicle activity. This research was conducted to investigate the nonpoint sources concentration and quantifying stormwater pollutants which are contained in rainfall runoff water. Three different monitoring sites in Jinju and Changwon city were equipped with an automatic rainfall gauge and flow meter for measuring rainfall and the volume of rainfall runoff. In the case of average EMC value, city trunk road was shown the highest value in target water quality items like as BOD, COD, SS, TN and TP. Or the amount of runoff loads by water quality items showed the highest value in city trunk road. And runoff load in city trunk road was 43.8 times high value compared to highway by value of city trunk road 356.7 ㎎/㎡, highway 8.150 ㎎/㎡, national road 19.99 ㎎/ ㎡ in the case of BOD.

Agriculture nonpoint pollution source is a significant contributor to water quality degradation. To establish effective water quality control policy, environpolitics establishment person must be able to estimate nonpoint source loads to lakes and streams. To meet this need for orchard area, we investigated a real rainfall runoff phenomena about it. We developed nonpoint source runoff estimation models for vineyard area that has lots of fertilizer, compost specially between agricultural areas. Data used in nonpoint source estimation model gained from real measuring runoff loads and it surveyed for two years(2008-2009 year) about vineyard. Nonpoint source runoff loads estimation models were composed of using independent variables(rainfall, storm duration time(SDT), antecedent dry weather period(ADWP), total runoff depth(TRD), average storm intensity(ASI), average runoff intensity(ARI)). Rainfall, total runoff depth and average runoff intensity among six independent variables were specially high related to nonpoint source runoff loads such as BOD, COD, TN, TP, TOC and SS. The best regression model to predict nonpoint source runoff load was Model 6 and regression factor of all water quality items except for was R² =0.85.