• Membrane and Water Treatment
• /
• 제13권5호
• /
• pp.219-225
• /
• 2022

5th Assessment Report of the Intergovernmental Panel on Climate Change Weather (AR5) predicts that recent severe hydrological events will affect the quality of water and increase water pollution. To analyze changes in water quality due to future climate change, input data (precipitation, average temperature, relative humidity, average wind speed, and solar radiation) were compiled into a representative concentration curve (RC), defined using 8.5. AR5 and future use are calculated based on land use. Semi-distributed emission model Calculate emissions for each target period. Meteorological factors affecting water quality (precipitation, temperature, and flow) were input into a multiple linear regression (MLR) model and an artificial neural network (ANN) to analyze the data. Extensive experimental studies of flow properties have been carried out. In addition, an Acoustic Doppler Velocity (ADV) device was used to monitor the flow of a large open channel connection in a wastewater treatment plant in Ho Chi Minh City. Observations were made along different streams at different locations and at different depths. Analysis of measurement data shows average speed profile, aspect ratio, vertical position Measure, and ratio the vertical to bottom distance for maximum speed and water depth. This result indicates that the transport effect of the compound was considered when preparing the hazard analysis.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
• /
• pp.663-665
• /
• 2003

A field spectroradiometer SE-590 was used to measure the spectral reflectance of water body. The reflectance was calculated as the ratio of surface water radiance to the standard whiteboard radiance nearly measured at the same time. Water samples were taken simultaneously for determining their chlorophyll-a, suspended solid (SS) and transparency. The relationships between those water quality parameters and spectral reflectance were analy zed using stepwise multiple regression to derive optimal prediction models . The multiple regression was also applied to the SE-590 simulated SPOT bands. The SPOT image of the same day was also analyzed using the same method to compare the statistical results. It showed that the multiple regression models using the SE-590 reflectance data got the best water quality prediction results. The evaluated RMS error of chlorophyll-a, SS and transparency of water quality parameters were 0.57 ug/l, 0.2 mg/l and 0.17 m, respectively, and the RMS errors were 0.36 ug/l, 0.49 mg/l and 0.42 m for SPOT data, respectively. The SE-590 simulated SPOT three bands data obtained the worst results and the RMS errors were 1.77 ug/l, 0.49 mg/l and 0.37 m, respectively.

• 한국환경과학회지
• /
• 제12권3호
• /
• pp.299-306
• /
• 2003

The purpose of this study is to investigate the characteristics of water quality in Jeju harbor and to estimate pollutant loadings discharged into Jeju Harbor. To know characteristics of water quality in Jeju harbor, and pollutant loadings of Sanzi river, we have investigated from August, 2000 to May, 2001. The results showed that the concentrations of COD, DIN and DIP were in the range of 1.00∼4.85 mg/L (mean 2.15 mg/L), 2.14∼74.0 $\mu\textrm{g}$-at/L(mean 12.20 $\mu\textrm{g}$-at/L) and 0.52∼4.00 $\mu\textrm{g}$-at/L(mean 1.18 $\mu\textrm{g}$-at/L), respectively. These values were under III class of seawater quality criteria. The ratio of nitrogen to phosphorus was lower than 16 except for Station 1 in Jeju harbor. Therefore, nitrogen was playing an important role in phytoplankton growth as limiting factor in Jeju harbor. The mean values of eutrophication index were exceeding 1, which was the eutrophication criteria. The results of estimating pollutant loadings at Sanzi river are 0.30 ton/day for COD, 300 kg/day for DIN and 18.0 kg/day for DIP, respectively.

• 한국수자원학회논문집
• /
• 제33권1호
• /
• pp.73-85
• /
• 2000

농촌 소하천의 수리학적 및 수질특성을 반영한 모형을 개발하였다. 모형구조 설계시 제어체적 기법을 활용하여 하천 형상, 수질 및 유량의 변화가 심한 농촌 유역의 소하천에 대한 수질의 모의하였다. 개발한 모형에 난수발생기법을 도입하여 최적 반응계수와 모형구조를 추정하였다. 또한 모형 보정기준의 일반화를 위해 동의지표와 효율계수를 도입하여 매개변수추정의 신뢰성 향상을 도모했다. 모형의 적용성을 검증하기 위해 경남 김해시 한림면 용덕천에서 수질을 채취하여 분석하였다. 관측된 자료와 개발된 모형의 비교연구를 통해 대상유역의 소하천에서 일어나는 수질 반응계수들과 그 변동성을 추정하였다.

• 한국환경과학회지
• /
• 제11권9호
• /
• pp.945-954
• /
• 2002

The objective okgf this study is understanding and evaluation of temporal and spatial variation of pollutant loads by input sources for water quality management in Kamak Bay. Flow rate of rivers and ditches ranges from about $2,592-63,072m^3/d$ in October to $864-55,296m^3/d$ in January. In particular, the R2 predominated flow rate among input sources. Total COD, BOD, DIN and DIP loadings in January were about 896kg/d, 718kg/d, 2,152kg/d, and 154kg/d, respectively, which exceeded those of October. Lower POC/TOC levels are estimated in R2, and also in October. Temporal variation of pollutant loads were closely related to the human activity. Total discharging loadings of BOD, TN and TP by unit loading estimation were 4,993.0kg/d, 2,558.7kg/d, and 289.2kg/d, respectively, and were mainly affected by the population. Runoff ratio of BOD was about 0.14 in January Mean $NH_4^＋_-N$ and $PO_4\;^{3-}-P$ loadings from sediment were 16.23mg/$m^2$/d and 7.26mg/$m^2$/d, respectively. For the improvement of water quality in this area, not only pollutant loads of rivers and ditches but also benthic flux from sediment should be reduced within the limits of the environmental capacity.

• 한국환경과학회지
• /
• 제18권9호
• /
• pp.971-981
• /
• 2009

An objective of this study is as follows: 1) performing sensitivity analysis and parameter estimation of RMA2 and RMA4 models for the West-Nakdong River, 2) drawing up alternatives of gates-operation for water-quality enhancement, and 3) quantitative evaluation of methodology of 'flow-restoration by gates-operation' among 'Comprehensive Plan Improving Water-Quality in the West-Nakdong River(WNR)' with the target water-quality(BOD at Nakbon-N point: below 4.3 mg/L). The parameters for the RMA2 (depth-averaged two-dimensional flow model) and RMA4 (depth-averaged two-dimensional water-quality model) were determined by sensitivity analysis. Result of parameter estimation for RMA2 and RMA4 models is $1,000\;Pa{\cdot}s$ of the eddy viscosity, 20 of the Peclet number, 0.025 of the Manning coefficient, and $1.0\;m^2/s$ of the diffusion coefficient. We have evaluated the effects of water-quality enhancement of the selected alternatives by numerical simulation technique with the models under the steady-state flow condition and the time-variant transport condition. Because of no-resuspension from river bottom and considering BOD as conservative matter, these simulation results slightly differ from real phenomena. In the case of $50\;m^3/s$ of Daejeo-gate inflow, two-dimensional flow pn results result represents that small velocity occurs in the Pyungkang Stream and no flow in the Maekdo River. In the WNR, there occurs the most rapid flow near timhae-bridge. In the WNR, changes of water-quality for the four selected simulation cases(6, 10, 30, $50\;m^3/s$ of the Daejeo-gate inflow) were predicted. Since the Daejeo-Gate and the Noksan-Gate can be opened up to 7 days, it would be found that sustainable inflow of $30\;m^3/s$ at the Daejeo-gate makes BOD in the WNR to be under the target of water-quality.

• 한국환경과학회지
• /
• 제10권2호
• /
• pp.119-127
• /
• 2001

The Keum river is one of the important river in Korea and has a drainage area of 9,873$\textrm{km}^2$. The Keum river is deepening pollution state due to development of the lower city and construction of a industrial complex. The water quality of the Keum river come to eutrophication state and belong to III grade of water quality standard. The concentration BOD in river is affected by the organic loading from a tributary and the algae biomass that largely happen to under eutrophication state. In the eutrophic water mass such as the Keum river, the autochthonous BOD was very important part for making a decision of water quality management, because it was accounted for majority of the total BOD. The purpose of this study was to survey the chatacteristics of water quality in summer and to estimate reaction coefficient. Also, we studied to correlationship between chlorophyll a and BOD(COD) for estimation of the autochthonous BOD. The correlationship between chlorophyll a and BOD(COD) were obtained through the culture experiment of phytoplankton in the laboratory. The results of this study may be summarized as follows ; The characteristics of water quality in summer were belong to III~IV grade of water quality standard as BOD and nutritive condition is very high. The BOD, ammonia nitrogen and phosphate loadings in Miho stream which inflowing untreated sewage from Chungju city was occupied with 64.07%, 26.36%, 46.08%, respectively. Maximum nutrient uptake (Vmax) was 0.4400$\mu$M/hr as substrate of ammonia nitrogen, 0.1652$\mu$M/hr as substrate of phosphate. Maximum specific growth rate ($\mu$max) was 1.2525$hr^{-1}$ as substrate of ammonia nitrogen, 1.5177$hr^{-1}$ as substrate of phosphate. The correlation coefficient between chlorophyll a and BOD by the culture experiment were found to be 0.911~0.935 and 0.942~0.947 in the case adding nutrient and no adding nutrient, respectively. The correlation coefficient between chlorophyll a and COD through the culture experiment were found to be 0.918~0.977 and 0.880~0.931 in the case adding nutrient and no adding nutrient, respectively. The autochthonous BOD(COD) was estimated to the relationship between BOD(COD) and chlorophyll a. The regression equation were found to be autochthonous BOD=(0.045~0.073)${\times}chlorophyll$ a and autochthonous $COD=(0.137~0.182){\times}chlorophyll$ a.

• 한국지반환경공학회 논문집
• /
• 제3권4호
• /
• pp.11-17
• /
• 2002

본 논문의 목적은 섬진다목적댐 유역의 하천을 대상으로 강우시에 단기 수질상태를 예측하기 위하여 병렬다중결선의 계층구조를 갖는 신경망이론을 이용하였다. 본 연구에 적용한 신경망이론의 학습알고리즘으로는 역전파알고리즘을 사용하였으며, 최적모형의 개발을 위해 모멘트법-적응학습율기법을 이용하였다. 하천 수질오염 부하량에 영향을 미치는 요소로서 상류로부터 유입되는 유입량과 수질인자인 BOD, COD, SS를 고려하였다. 섬진다목적댐 유역에 대해 단기 수질을 예측할 수 있는 다층신경망모형을 개발하기 위해 은닉층 노드수와 학습회수에 변화를 주어 각 수질인자별로 4가지씩 총 12개의 모형을 구성하여 학습을 실시하였다. 제안된 신경망모형의 검증을 위해 학습시키지 않은 수질자료를 예측한 결과 양호한 것으로 분석되었고, 하천수계의 단기 수질오염 예측에 활용할 수 있을 것으로 사료되었다.

• 대한원격탐사학회지
• /
• 제33권2호
• /
• pp.111-123
• /
• 2017

피코시아닌(phycocyanin, PC) 색소는 부영양화 된 담수역에서의 남조류를 정량하는 지표로 활용된다. 남조류의 대발생에 의한 잠재적 위험성으로인해 조기 경보 발령이 중요하지만, 혼탁한 수체 내 소량으로 추정되는 PC 농도를 정확하게 산정하는 것은 분광학적으로 매우 복잡하고 어렵다. 이를 위해 현장에서 측정 된 원격반사도로부터 PC 및 물 이외의 입자성 물질에 의한 흡수계수를 분리하여 기존 PC 농도를 추정하는 방법을 개선하여 낮은 농도에서도 향상 된 결과를 보였다. 본 연구에서 제안 된 IOPs 변환 모델 적용 결과 PC 흡수계수 $R^2$는 0.8 이상으로 $a_{pc}(620)$를 적절히 재현하였다. 또한 알고리즘은 기존 널리 사용되는 반경험적 알고리즘에 비해 $0.71{\leq}R^2{\leq}0.85$, $rRMSE{\leq}39.4%$, 그리고 $RE{\leq}78.0%$로 정확도 높은 결과를 보였다. 특히, PC 농도가 $50mg/m^3$ 이하 및 PC: Chl-a ratio가 낮은 조건에서도 잘 예측됨을 확인할 수 있었다.

• 한국농공학회논문집
• /
• 제47권7호
• /
• pp.67-75
• /
• 2005

It has been well-known that the Nonpoint Source (NPS) pollutions are the primary contributors to water quality degradation in the receiving water bodies as well as the Point Source (PS) pollutions. To develop an effective management practice for water quality improvement, pollutant loads must be first estimated. In many studies, the Numeric Integration (NI) method has been used because of its ease of application, irrespective of the total number of samples collected for each storm event. Thus, there have been needs for more accurate pollutant load estimation with a limited number of water quality samples. In this study, NI method and regression method using the USGS ESTIMATOR model were comparatively used to calculate the pollutant loads for the Wolgokri watershed, Gangwon Province. The $NO_{3}$-N, T-N, and T-P loads using NI method and ESTIMATOR model were 13.85 kg/ha, 45.92 kg/ha, and 1.887 kg/ha, and 11.93 kg/ha,43.20 kg/ha, and 1.650 kg/ha, respectively. The estimated loads using ESTIMATOR model were lower than those using NI method by $86\%$, $94\%$, and $87\%$. These discrepancies in the estimated loads using a different load estimation method could be explained in that the total number of samples were not sufficient enough for NI method. Thus, ESTIMATOR model is recommended for the frequently stream discharge and less frequently measured water quality data.