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.

The purpose of this study at water quality pollutants to propose proper management method for the Osu-A unit watershed which is the influent tributary located upstream of the Sumjin -river among the 13 unit watersheds in the Sumjin-river water system. Analyzed the correlation between flow-pollution loading and the correlation between land use type, BOD and TP items, and analyzed 8-day intervals Cumulative Flow Duration Curve (CFDC) and Load Duration Curve (LDC) to evaluate water quality damage. As a result, both BOD and TP were larger than 1 and the concentration of water pollutants increased with increasing flow. BOD was positively correlated with Urban and Field, and TP was positively correlated with Field with 0.710. As a result of the LDC, BOD was analyzed that the target water quality was achieved with the excess rate of less than 50%, and TP exceeded the target water quality by 50.1%. BOD usually exceeded the standard value (exceedance probability 50%) at low flow zone and On the other hand, TP usually exceeded the standard value at high flow zone. Monthly BOD (April to June) and TP (May to August) exceeded the standard. Sewage Wastewater treatment and non-point pollution control is Osu-A unit watersheds are effective in improving BOD and TP.

In this study, seasonal Mann - Kendall test method was applied to 12 stations of the water quality measurement network of Nam-River based on data of BOD, COD, TN and TP for 11 years from January 2005 to December 2015 The changes of water quality at each station were examined through linear trends and the tendency of water quality change during the study period was analyzed by applying the locally weighted scatter plot smoother (LOWESS) method. In addition, spatial trends of the whole Nam-River were examined by items. The flow-adjusted seasonal Kendall test was performed to remove the flow at the water quality measurement station. As a result, BOD, COD concentration showed "no trand" and TN and TP concentration showed "down trand" in regional Kendall test throughout the study period. BOD and TP concentration in "no trand", COD, and TN concentration showed an "up trand" tendency in Nam-River dam. LOWESS analysis showed no significant water quality change in most of the analysis items and stations, but water quality fluctuation characteristics were shown at some stations such as NR1 (Kyungho-River 1), NR2 (Kyungho-River 2), NR3 (Nam-River), NR6 (Nam-River 2A). In addition, the flow-adjusted seasonal Kendall results showed that the BOD concentration was "up trand" due to the flow at the NR3 (Nam-River) station. The COD concentration was "up trand" due to the flow at NR1 (Kyungho-River 1) and NR2 (Kyungho-River 2) located upstream of the Nam-River. The effect of influent flow on water quality varies according to each site and analysis item. Therefore, for the effective water quality management in the Nam-River, it is necessary to take measures to improve the water quality at the point where the water quality is continuously "up trand" during the study period.

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.

In recent years, the United States has used the Load Duration Curve (LDC) method to identify water pollution problems, considering the size of the pollutant load in the entire stream flow condition to effectively evaluate Total Maximum Daily Loads (TMDLs). A study on the improvement of the target water quality evaluation method was carried out by comparing evaluations of two consecutive years of water quality and LDC data for 41 unit watersheds (14 main streams and 27 tributaries). As a result, the achievement rate of the target water quality evaluation method, according to current regulations, was 68-93%, and that by the LDC method was 82-93%. Evaluating the target water quality using the LDC method results in a reduction in the administrative burden and the total amount of planning as compared to the current method.

To certificate change in the geochemical characteristics of surface sediments in the main stream of the Nakdong River, surface sediments from 12 sampling sites during the first and second half year (total 24 sampling sites) were collected and analyzed for grain size, ignition loss, total organic carbon and heavy metal content. Surface sediments mainly composed of sand (coarse and medium sand) and fining changed from the first half to the second half of the year. Ignition loss, total organic carbon and heavy metals content increased in the second half of the year. Some heavy metals (Zn, Ni and Cu) were found to be at the lowest effect levels according to Ontario sediment quality guidelines. Additionally, most heavy metals were found to be at the non polluted level and level I according to USEPA sediment quality standards and National Institute of Environmental Research sediment pollution evaluation standard, respectively. The enrichment factor (< 1) and index of geoaccmulation (< 0) were non polluted in the study area. The correlation analysis results showed that ignition loss, total organic carbon and heavy metal content were highly correlated with grain size. Regarding changes in geochemical characteristics of surface sediments in the study area, grain size fine and organic matter and heavy metal content increased in the second half year. Nonetheless these results indicated pollution levels that did not adversely affect the benthos.

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.

In this study, we analyzed on-site monitoring data for 15 tributaries in Geumho watersheds for 3 years (2011-2013) in order to sort out priorities on water quality characteristics and improvement. As a result of estimating contribution to contamination of the tributary rivers, Dalseocheon showed the highest load densities, despite the smallest watershed area, with 22.7% BOD5, 30.7% CODMn, 31.3% TOC and 47.6% TP. After conducting PCA (principal component analysis) and FA (factor analysis) to analyze water quality characteristics of the tributary rivers, the first factor was classified as CODMn, TOC, EC, TP and BOD5, the second factor as pH, Chl-a and DO, the third factor as water temperature and TN, and the fourth factor as SS and surface flow. In addition, arithmetical sum of each factor’s scores based on grading criteria revealed that Dalseocheon and Namcheon were classified into Group A for their highest scores - 96 and 93, respectively -, and selected as rivers that require water environmental management measures the most. Also, water environmental contamination inspection showed that Palgeocheon had the most number of aquatic factors to be controlled: BOD5, CODMn, SS, TOC, T-P, Chl-a, etc.

Ministry of Environment has been operating water quality monitoring network in order to obtain the basic data for the water environment policies and comprehensively understand the water quality status of public water bodies such as rivers and lakes. The observed water quality data is very important to analyze by applying statistical methods because there are seasonal fluctuations. Typically, monthly water quality data has to analyze that the transition comprise a periodicity since the change has the periodicity according to the change of seasons. In this study, trends, SOM and RDA analysis were performed at the Mulgeum station using water quality data for temperature, BOD, COD, pH, SS, T-N, T-P, Chl-a and Colon-bacterium observed from 1989 to 2013 in the Nakdong River. As a result of trends, SOM and RDA, the Mulgeum station was found that the water quality is improved, but caution is required in order to ensure safe water supply because concentrations in water quality were higher in the early spring(1~3 month) the most.

The government has conducted a plan of total maximum daily loads(TMDL), which divides with unit watershed, for management of stable water quality target by setting the permitted total amount of the pollutant. In this study, BOD concentration trends over the last 10 years from 2005 to 2014 were analyzed in the Geumho river. Improvement effect of water quality throughout the implementation period of TMDL was evaluated using the seasonal Mann-Kendall test and a LOWESS(locally weighted scatter plot smoother) smooth. As a study result of the seasonal Mann-Kendall test and the LOWESS smooth, BOD concentration in the Geumho river appeared to have been reduced or held at a constant. As a result of quantitatively analysis for BOD concentration with exploratory data analysis(EDA), the mean and the median of BOD concentration appeared in the order of GH8 〉GH7 〉GH6 〉GH5 〉GH4 〉GH3 〉GH2 〉GH1. The monthly average concentration of BOD appeared in the order of Apr 〉Mar 〉Feb 〉May 〉Jun 〉Jul 〉Jan 〉Aug 〉Sep 〉Dec 〉Nov 〉Oct. As a result of the outlier, its value was the most frequent in February, which is estimated 1.5 times more than July, and was smallest frequent in July. The outlier in terms of water quality management is necessary in order to establish a management plan for the contaminants in watershed.

As a result of analysis based on the observed data for BOD, COD and TOC in order to manage non-biodegradable organics in the Geumho River, COD/BOD ratio was analyzed as the occupying predominance proportion. In this study, the classification(changes in water quality measurement : increase, equal, decrease) and measurement of BOD and COD were analyzed for trends over the past 10 years from 2005 to 2014 in the Geumho River. The Geumho River is expected to need non-biodegradable organics management because BOD was found to be reduced 61.1% and COD was found to be increased 50%. As a result of the analysis of land use, the Geumho-A is a unit watershed area of 921.13 km2, which is the most common area that is occupied by forests. The Geumho-B is a unit watershed area of 436.8 km2, which is the area that is highest occupied by agriculture and grass of 24.84%. The Geumho-C is a unit watershed area of 704.56 km2 accounted for 40.29% of the entire watershed, which is the area that is occupied by urban of 15.12%. Load of non-biodegradable organics, which is not easy biodegradable according to the discharge, appeared to be increased because flow coefficient of COD and TOC at the Geumho-B were estimated larger than 1 value. The management of non-point sources of agricultural land is required because the Geumho-B watershed area occupied by the high proportion of agriculture and field. In this segment it showed to increase the organics that biodegradation is difficult because the ratio of BOD and TOC was decreased rapidly from GR7 to GR8. Thus, countermeasures will be required for this.

In this study, it is an object to develop a regression model for the estimation of TOC (total organic carbon) concentration using investigated data for three years from 2010 to 2012 in the Gam Stream unit watershed, and applied in 2009 to verify the applicability of the regression model. TOC and CODMn (chemical oxygen demand) were appeared to be derived the highest correlation. TOC was significantly correlated with 5 variables including BOD (biological oxygen demand), discharge, SS (suspended solids), Chl-a (chlorophyll a) and TP (total phosphorus) of p<0.01. As a result of PCA (principal component analysis) and FA (factor analysis), COD, TOC, SS, discharge, BOD and TP have been classified as a first factor. TOCe concentration was estimated using the model developed as an independent variable BOD5 and CODMn. R squared value between TOC and measurement TOC is 0.745 and 0.822, respectively. The independent variable were added step by step while removing lower importance variable. Based on the developed optimal model, R squared value between measurement value and estimation value for TOC was 0.852. It was found that multiple independent variables might be a better the estimation of TOC concentration using the regression model equation(in a given sites).