SWMM과 인공신경망을 이용한 미 계측 하천의 클로로필a 추정에 관한 연구

강태욱 ( Tae Uk Kang ),이상호 ( Sang Ho Lee ),김일규 ( Il Kyu Kim ),이남주 ( Nam Ju Lee ) 한국물환경학회 2011 한국물환경학회지 Vol.27 No.5

Chlorophyll-a is a major water quality indicator for an algal bloom in streams and lakes. The purpose of the study is to estimate chlorophyll-a concentration in tributaries of the Seonakdonggang by an artificial neural network (ANN). As the tributaries are ungauged streams, a watershed runoff and quality model was used to simulate water quality parameters. The tributary watersheds include urban area and thus Storm Water Management Model (SWMM) was used to simulate TN, TP, BOD, COD, and SS. SWMM, however, can not simulate chlorophyll-a. The chlorophyll-a series data from the tributaries were estimated by the ANN and the simulation results of water quality parameters using SWMM. An assumption used is as follows: the relation between water quality parameters and chlorophyll-a in the tributaries of the Seonakdonggang would be similar to that in the mainstream of the Seonakdonggang. On the assumption, the measurement data of water quality and chlorophyll-a in the mainstream of the Seonakdonggang were used as the learning data of the ANN. Through the sensitivity analysis, the learning data combination of water quality parameters was determined. Finally, chlorophyll-a series were estimated for tributaries of the Seonakdonggang by the ANN and TN, TP, BOD, COD, and temperature data from those streams. The relative errors between the estimated and measured chlorophyll-a were approximately 40~50%. Though the errors are somewhat large, the estimation process for chlorophyll-a may be useful in ungauged streams.

TiCl₄ 응집을 이용한 조류제거

김경민(Kyung-Min Kim),오흥현(Heung-Hyun Oh),박지원(Ji-Won Park),최종진(Jong-Jin Choi),안종화(Johng-Hwa Ahn) 대한환경공학회 2019 대한환경공학회지 Vol.41 No.6

본 연구에서는 응집제 TiCl4의 조류제거 효율을 관찰하기 위해 jar test를 이용하여 급속교반속도(110~170 rpm), 완속교반속도(20~60 rpm), 주입농도(0.02~0.48 mM), pH (1~12) 등에 따른 클로로필 a 및 탁도 제거율을 관찰하였다. 실험기간 동안 사용한 시료의 클로로필 a는 105.7 ± 10.2 μg/L, 탁도는 17.5 ± 5.7 NTU (nephelometry turbidity unit)였다. 급속교반의 경우 실험범위 내에선 교반속도에 관계없이 높은 클로로필 a (90~94%) 및 탁도(91~93%) 제거효율을 보였다. 완속교반의 경우 클로로필 a는 30 rpm (96%)에서, 탁도는 30 rpm 이상(90% 이상)에서 가장 높은 제거효율을 보였다. 주입농도 실험에서 클로로필 a와 탁도는 TiCl₄의 농도가 증가할수록 제거효율이 증가하는 경향을 보였다. 클로로필 a는 0.25 mM, 탁도는 0.39 mM 이상에서 90% 이상의 제거효율을 보였다. pH의 경우 클로로필 a는 3~8에서 90% 이상, 탁도는 6 이상에서 87% 이상의 제거효율을 보였다. 따라서 클로로필 a와 탁도를 동시에 90% 이상의 제거효율을 얻기 위한 조건은 급속교반속도에 관계없이 완속교반 30 rpm, 주입농도 0.39 mM, pH 6~8로 나타났다. This study evaluated the efficiency of titanium tetrachloride (TiCl₄) on chlorophyll-a (105.7 ± 10.2 μg/L) and turbidity (17.5 ± 5.7 NTU (nephelometry turbidity unit)) removals in a pond water compared to aluminum potassium sulfate (AlK(SO₄)₂). Jar-test experiments were performed at various mixing speeds (rapid: 110~170 rpm, slow: 20~60 rpm), coagulant doses (0.02~0.48 mM), and pH levels (1~12) to determine the conditions at which chlorophyll-a and turbidity removals were most efficient. Within the experimental range, the chlorophyll-a (90~94%) and turbidity (91~93%) removals were high regardless of rapid-mixing speed. The maximum chlorophyll-a removal was 96% at 30 rpm of slow-mixing speed and turbidity removal was ≥90% at ≥30 rpm of slow-mixing speed. The chlorophyll-a removal and turbidity efficiencies increased as TiCl4 concentration ([TiCl₄]) increased. The chlorophyll-a removal at [TiCl4]=0.25 mM and the turbidity removal at [TiCl₄]=0.39 mM were ≥90%. The chlorophyll-a removals at pH=3~8 were ≥90% and the turbidity removals at pH≥6 were ≥87%. Therefore, the conditions with ≥90% chlorophyll-a and turbidity removals were slow mixing=30 rpm, [TiCl4]≥0.39 mM, and 6≤pH≤8 regardless of rapid-mixing speed.

Landsat 8호 영상을 이용한 진양호의 클로로필 a 농도의 공간분포와 영양상태 분석

장민원 ( Min Won Jang ),조현경 ( Hyun Kyung Cho ),김상민 ( Sang Min Kim ) 한국물환경학회(구 한국수질보전학회) 2019 한국물환경학회지 Vol.35 No.1

The purpose of this study is to evaluate the nutritional status of Lake Jinyang using Landsat 8 satellite image band correlated with chlorophyll-a, which is also related to algae proliferation. We selected 20 Landsat 8 images dating from 2013 to 2017, taken close to water quality measurement date when the cloud cover was less than 20 %. Based on the results of the previous studies, analyzing the correlation between chlorophyll-a, and Landsat 8 satellite image band, we selected near infrared wavelength, band 5 which is closely related to the population of algae. The nutritional status was classified using the Aizaki trophic state index (TSIm). The results of the regression equation between band 5 and the observed chlorophyll-a data was used to calculate chlorophyll-a for the image data from 2013 to 2017. The concentration of chlorophyll-a ranged from 3 to 16.1 mg/m³. To illustrate the spatial distribution of chlorophyll-a within the lake, the chlorophyll-a concentration was divided into five grades. The images on October 14, 2014 and April 10, 2016 showed relatively high value of chlorophyll-a, while January 18, 2015 and December 6, 2016 chlorophyll-a value were below 5. The images on October 14, 2014 and April 10, 2016 were rated as eutrophic status in most areas. The results of simulating water quality for the day when the water quality was not measured resulted to an approximate value for the Panmun station while the Naedong station needed some corrections.

고해상도 위성영상을 이용한 낙동강 유역의 클로로필-a농도 추정

최은영 ( Eun Young Choe ),이재운 ( Jae Woon Lee ),이재관 ( Jae Kwan Lee ) 대한원격탐사학회 2011 大韓遠隔探査學會誌 Vol.27 No.5

본 연구에서는 Moderate Imaging Spectroradiometer(MODIS), Sea-viewing Wide Fieldfo-view Sensor(SeaWiFS), Medium Resolution Imaging Spectrometer(MERIS) 등의 광역관측 위성 영상을 이용한 해수나 연안수의 클로로필 농도 분석을 통해 가능성이 확인되었던 밴드 비를 이용한 비교적 간단한 추정 모델을 수체의 크기와 폭이 현저히 작고 탁도가 있는 하천에 대해 클로로필- a농도값을 추정하고자 고해상도 위성영상에 Two-band 및 Three-band reflectance 모델을 적용하여 가능성을 파악하였다. 특히 RapidEye 영상을 이용하여 일반적으로 탁도가 있는 수체에 대해 Red와 NIR 영역을 활용하는 이들 모델에 Red-edge(RE) 밴드를 적용하였다. Red와 NIR을 이용한 Two-band Reflectance 모델은 계산식의 결정계수 R2 값이 0.38로 유의성 없는 결과를 나타내었다. 그러나 RapidEye의 Red-edge (RE) 파장대를 이용한 Red-RE Two-band 모델과 Red-RE-NIR Three-band 모델을 이용한 계산식에 대해서는, 2차함수에 의한 Three-band 모델의 결과는 Red-RE Two-band 모델의 결과와 통계적인 값이 거의 유사하였고 Two-band와 3차함수에 의한 Three-band 모델 추정식은 각각 0.66, 0.73 의 R2값을 나타내어 Red-edge 밴드의 적용 가능성을 보였고, 실측치와의 Root Mean Square Error (RMSE)는 24.8, 22.4 mg m-3, Relative Percent Difference(RPD)는 각각 1.30, 1.29로 1.5 이하의 대략적인 추정(Approximate Prediction) 수준을 나타내었다. 고해상도 위성영상에 Red-RE-NIR Three-band 모델을 적용한 계산식을 이용해 대략적인 추정이지만 가장 유의한 수준의 클로로필- a농도를 추정할 수 있었다. 영상에서 추정된 클로로필 -a분포를 비교하였을 때 3차함수에 의한 Three-band 모델 추정식이 Two-band 모델에 비해 낮은 값의 분포를 보였다. 향후 하천의 스펙트럼을 실측하여 파장별 부유물질, 유기물과의 상관성 및 클로로필 농도와의 간섭 정도를 시뮬레이션하여 보정식을 산출·적용한다면 탁도가 다소 높은 하천에서의 클로로필 -a농도 계산식의 정확도를 더욱 높일 수 있을 것으로 기대된다. This study assessed the feasibility to apply Two-band and Three-band reflectance models for chlorophyll-a estimation in turbid productive waters whose scale is smaller and narrower than ocean using a high spatial resolution image. Those band ratio models were successfully applied to analyzing chlorophyll-a concentrations of ocean or coastal water using Moderate Imaging Spectroradiometer(MODIS), Sea-viewing Wide Field-fo-view Sensor(SeaWiFS), Medium Resolution Imaging Spectrometer(MERIS), etc. Two-band and Three-band models based on band ratio such as Red and NIR band were generally used for the Chl-a in turbid waters. Two-band modes using Red and NIR bands of RapidEye image showed no significant results with R2 0.38. To enhance a band ratio between absorption and reflection peak, We used red-edge band(710 nm) of RapidEye image for Twoband and Three-band models. Red-RE Two-band and Red-RE-NIR Three-band reflectance model (with cubic equation) for the RapidEye image provided significance performances with R2 0.66 and 0.73, respectively. Their performance showed the ``Approximate Prediction`` with RPD, 1.39 and 1.29 and RMSE, 24.8, 22.4, respectively. Another three-band model with quadratic equation showed similar performances to Red-RE two-band model. The findings in this study demonstrated that Two-band and Three-band reflectance models using a red-edge band can approximately estimate chlorophyll-a concentrations in a turbid river water using high-resolution satellite image. In the distribution map of estimated Chl-a concentrations, three-band model with cubic equation showed lower values than twoband model. In the further works, quantification and correction of spectral interferences caused by suspended sediments and colored dissolved organic matters will improve the accuracy of chlorophyll-a estimation in turbid waters.

Comparison of Composite Methods of Satellite Chlorophyll-a Concentration Data in the East Sea

박경애,박지은,이민선,강창근 대한원격탐사학회 2012 大韓遠隔探査學會誌 Vol.28 No.6

To produce a level-3 monthly composite image from daily level-2 Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll-a concentration data set in the East Sea, we applied four average methods such as the simple average method, the geometric mean method, the maximum likelihood average method, and the weighted averaging method. Prior to performing each averaging method, we classified all pixels into normal pixels and abnormal speckles with anomalously high chlorophyll-a concentrations to eliminate speckles from the following procedure for composite methods. As a result, all composite maps did not contain the erratic effect of speckles. The geometric mean method tended to underestimate chlorophyll-a concentration values all the time as compared with other methods. The weighted averaging method was quite similar to the simple average method, however, it had a tendency to be overestimated at high-value range of chlorophyll-a concentration. Maximum likelihood method was almost similar to the simple average method by demonstrating small variance and high correlation (r=0.9962) of the differences between the two. However, it still had the disadvantage that it was very sensitive in the presence of speckles within a bin. The geometric mean was most significantly deviated from the remaining methods regardless of the magnitude of chlorophyll-a concentration values. Its bias error tended to be large when the standard deviation within a bin increased with less uniformity. It was more biased when data uniformity became small. All the methods exhibited large errors as chlorophyll-a concentration values dominantly scatter in terms of time and space. This study emphasizes the importance of the speckle removal process and proper selection of average methods to reduce composite errors for diverse scientific applications of satellite-derived chlorophyll-a concentration data.

북서태평양의 표층엽록소 변동성

박지수,석문식,윤석,유신재 한국해양과학기술원 2008 Ocean and Polar Research Vol.30 No.3

We collected information on seasonal and interannual variability of surface chlorophyll a concentration between 1997-2007 from the Northwest Pacific Ocean. Satellite data were used to acquire chlorophyll a and sea surface temperature from six regions: East Sea/Ulleung Basin, East China Sea, Philippin Sea, Warm Pool region, Warm Pool North region, and Warm Pool East region. Mixed layer depth (MLD) was calculated from temperature profiles of ARGO floats data in four of the six regions during 2002-2007. In the East Sea/Ulleung Basin, seasonal variability of chlorophyll a concentration was attributed to seasonal change of MLD, while there was no significant relationship between chlorophyll a concentration and MLD in the Warm Pool region. Interannual anomaly in sea surface temperature were similar among the East Sea, East China Sea, Philippin Sea, and Warm Pool North region. The anomaly pattern was reversed in the Warm Pool East region. However, the anomaly pattern in the Warm Pool region was intermediate of the two patterns. In relation to chlorophyll a, there was a reversed interannual anomaly pattern between Warm Pool North and Warm Pool East, while the anomaly pattern in the Warm Pool region was similar to that of Warm Pool North except for the El Ni? years (1997/1998, 2002/2003, 2006/2007). However, there was no distinct relationship among other seas. Interestingly, in the Warm Pool and Warm Pool East regions, sea surface temperature showed a pronounced inverse pattern with chlorophyll a. This indicates a strong interrelationship among sea surface temperature-MLD-chlorophyll a in the regions. In the Warm Pool and Warm Pool East, zonal distribution of chlorophyll a concentration within the past 10 years has shown a good relationship with sea surface temperature which reflects ENSO variability.

Studies on Simultaneous Determination of Chlorophyll a and b, Pheophorbide a, and $\beta-Carotene$ in Chlorella and Spirulina Products

이영자,김소희,김진숙,한정아,서해점,임효정,최수영,Lee Young Ja,Kim So Hee,Kim Jin-Sook,Han Jeong A,Seo Hae Jeom,Lim Hyo Jeong,Choi Soo Young The Korean Society of Food Hygiene and Safety 2005 한국식품위생안전성학회지 Vol.20 No.3

역상 컬럼을 이용하여 건강기능식품 중 클로렐라 및 스피루리나제품에 함유되어 있는 엽록소 a, b,페오포르바이드 a 및 $\beta$-카로틴의 HPLC동시분석법을 확립하였으며, 첨가농도 $50\;\mug/ml$에서 엽록소 a, b, 페오포르바이드 a 및 $\beta$-카로틴에 대한 회수율시험결과, 각각 2.8, 6.0, 10.6 및 $10.4\%$의 상대표준편차와 70.3, 71.6, 60.1 및 $90.5\%$의 회수율을 각각 나타냈다. 이때 검출한계는 $0.1\sim1.0\;\mug/ml$, 정량한계는 $0.2\sim2.0\;\mug/ml$이었으며 검량선 상관계수도 0.995 이상의 직선성을 보여주었다. 국내유통 클로렐라 및 스피루리나제품에 대한 엽록소 a, b,페오포르바이드 a및 $\beta$-카로틴의 함유량을 분석한 결과 엽록소 a $121.g\sim543$, 엽록소 b $0.6\sim160.0$, 페오포르바이드 a 및 P-카로틴 $383.6\sim1713.7mg/ml$ 수준으로 나타났다. 엽록소 b의 함유량은 클로렐라제품에서 평균 374.0 mg/100 g 으로 스피루리나제품의 평균 10.5 mg/100 g 보다 30배 이상 함유하고 있는 것으로 확인되었다. 그러나 $\beta$-카로틴의 함유량은 스피루리나제품이 평균 1335.4 mg/100 g 로 클로렐라제품의 평균 495.0 mg/100 g 보다 평균 함유량에서 2.7배 높은 것으로 나타났다. 국내 건강기능식품공전 중 클로렐라 및 스피루리나제품의 엽록소 a b, 및 페오포르바이드 항목의 규격검사를 본 연구의 동시분석법으로 개정함으로써 각 성분 함량의 정량, 분석시간의 단축 및 비용절감 둥 시험방법을 크게 개선할 수 있을 것으로 기대된다. A simple and sensitive analysis method based on reverse phase (RP) HPLC with UV detector was developed for simultaneous determination of chlorophyll a and b, pheophorbide a and $\beta-Carotene$ in Chlorella and Spirulina products. For added concentration $(50\;\mug/ml)$ of chlorophyll a and b, pheophorbide a and $\beta-Carotene$, recoveries of those were 70.3, 71.6, 60.1 and $90.5\%$, respectively, with relative standard deviations of 2.8,6.0, 10.6 and $10.4\%$. Limit of detection and quantification had ranges of $0.1\sim1.0\;\mug/ml$ and $0.2\sim2.0\;\mug/ml$, respectively. Calibration curve was linear with correlation coefficient of 0.995 for chlorophyll a and b, pheophorbide a and $\beta-Carotene$. Results of simultaneous determination in Chlorella and Spirulina products were showed ranges of $121.g\sim543.0\;\mug/ml$ for chlorophyll a,$0.6\sim160.0\;\mug/ml$ for chlorophyll b, $19.2\sim60.3\;\mug/ml$ for pheophorbide a and $383.6\sim1713.7\;\mug/ml$ for $\beta-Carotene$, respectively. Chlorophyll b contents in Chlorella products were detected above 30 times level to those in Spirulina products. $\beta-Carotene$ contents in Spirulina products were detected 2.7 times level to those in Chlorella products.

Comparison of Composite Methods of Satellite Chlorophyll-a Concentration Data in the East Sea

Park, Kyung-Ae,Park, Ji-Eun,Lee, Min-Sun,Kang, Chang-Keun The Korean Society of Remote Sensing 2012 大韓遠隔探査學會誌 Vol.28 No.6

To produce a level-3 monthly composite image from daily level-2 Sea-viewing Wide Field-of-view Sensor (SeaWiFS) chlorophyll-a concentration data set in the East Sea, we applied four average methods such as the simple average method, the geometric mean method, the maximum likelihood average method, and the weighted averaging method. Prior to performing each averaging method, we classified all pixels into normal pixels and abnormal speckles with anomalously high chlorophyll-a concentrations to eliminate speckles from the following procedure for composite methods. As a result, all composite maps did not contain the erratic effect of speckles. The geometric mean method tended to underestimate chlorophyll-a concentration values all the time as compared with other methods. The weighted averaging method was quite similar to the simple average method, however, it had a tendency to be overestimated at high-value range of chlorophyll-a concentration. Maximum likelihood method was almost similar to the simple average method by demonstrating small variance and high correlation (r=0.9962) of the differences between the two. However, it still had the disadvantage that it was very sensitive in the presence of speckles within a bin. The geometric mean was most significantly deviated from the remaining methods regardless of the magnitude of chlorophyll-a concentration values. Its bias error tended to be large when the standard deviation within a bin increased with less uniformity. It was more biased when data uniformity became small. All the methods exhibited large errors as chlorophyll-a concentration values dominantly scatter in terms of time and space. This study emphasizes the importance of the speckle removal process and proper selection of average methods to reduce composite errors for diverse scientific applications of satellite-derived chlorophyll-a concentration data.

담수호 수질관리를 위한 측정자료의 통계적 분석방법 연구

제갈선동,김진 한국수자원학회 2024 한국수자원학회논문집 Vol.57 No.1

본 연구는 공개된 수질측정 자료를 이용하여 담수호의 수질변화추이를 분석하고 수질항목의 이상여부의 판단기준을 마련하며, 자료로부터 부영양화의 지표인 Chlorophyll-a를 예측할 수 있는 회귀모형을 구성하여 담수호 관리에 이용할 수 있는 방안을 검토하고자 하였다. 이에 따라 서해안 담수호 3개소를 선정하여 약 20년간의 수질항목자료를 회귀분석 방법으로 분석하고, 각 수질항목의 연중 주기적인 변화를 나타내는 회귀식과 신뢰도 95%에서의 표준편차를 산정함으로서 이상 여부의 판단방법을 제시하였다. 또한 불규칙한 관측일로부터 Chlorophyll-a의 시간적 변화율을 산정하고, 다른 수질항목간의 상관관계 분석 및 회귀모형을 구성하여 분석함으로서 수질측정 자료만을 이용하여 Chlorophyll-a의 변화를 예상할 수 있는 방법을 제시하였다. 본 연구결과는 통계학적 모형에 의한 근사적인 수질예측방법으로서 향후 수질측정 자료의 양적·질적 개선이 이루어진다면 담수호 수질관리에 기여할 것으로 기대된다. As using public monitoring data, analysing a trends of water quality change, establishing a criteria to determine abnormal status and constructing a regression model that can predict Chlorophyll-a, an indicator of eutrophication, was studied. Accordingly, the three freshwater lakes were selected, approximately 20 years of water quality monitoring data were analyzed for periodic changes in water quality each year using regression analysis, and a method for determining abnormalities was presented by the standard deviation at confidence level 95%. By calculating the temporal change rate of Chlorophyll-a from irregular observed data, analyzing correlations between the rate and other water quality items, and constructing regression models, a method to predict changes in Chlorophyll-a was presented. The results of this study are expected to contribute to freshwater lake water quality management as an approximate water quality prediction method using the statistical model.

GOCI-II 및 극궤도 위성 자료를 병합한 Chlorophyll-a 산출물생산방법 소개 및 활용 가능성 평가

신혜경,권재엽,김평중,김태호 대한원격탐사학회 2023 大韓遠隔探査學會誌 Vol.39 No.6

Satellite-based chlorophyll-a concentration, produced as a long-term time series, is crucialfor global climate change research. The production of data without gaps through the merging of timesynthesizedor multi-satellite data is essential. However, studies related to satellite-based chlorophyll-aconcentration in the waters around the Korean Peninsula have mainly focused on evaluating seasonalcharacteristics or proposing algorithms suitable for research areas using a single ocean color sensor. In this study, a merging dataset of remote sensing reflectance from the geostationary sensor GOCI-IIand polar-orbiting sensors (MODIS, VIIRS, OLCI) was utilized to achieve high spatial coverage ofchlorophyll-a concentration in the waters around the Korean Peninsula. The spatial coverage in theresults of this study increased by approximately 30% compared to polar-orbiting sensor data, effectivelycompensating for gaps caused by clouds. Additionally, we aimed to quantitatively assess accuracythrough comparison with global chlorophyll-a composite data provided by Ocean Colour Climate ChangeInitiative (OC-CCI) and GlobColour, along with in-situ observation data. However, due to the limitednumber of in-situ observation data, we could not provide statistically significant results. Nevertheless,we observed a tendency for underestimation compared to global data. Furthermore, for the evaluation ofpractical applications in response to marine disasters such as red tides, we qualitatively compared ourresults with a case of a red tide in the East Sea in 2013. The results showed similarities to OC-CCI ratherthan standalone geostationary sensor results. Through this study, we plan to use the generated data forfuture research in artificial intelligence models for prediction and anomaly utilization. It is anticipatedthat the results will be beneficial for monitoring chlorophyll-a events in the coastal waters around Korea.