This research was conducted with the aim of efficiently managing large scale of rivers such like Songyang-river through predicting water quality change with analyzing the characteristics of the flowing in nutrients and pollutants. The main result will be used as basic data for effectively operating reservoirs through controling water quality and quantity. The relationship between quantity of flow and water quality was analyzed and pollution loading into the basin was estimated. Three areas of Soyang-river upstream and one area of Suip-cheon in Yanggu-gun were selected as research sites. Flow and water quality were measured simultaneously. The relation between quantity of discharge and pollution concentration and between quantity of discharge and pollution loading were analyzed by statistical method, respectively. We provided a rating curve through measuring quantity of discharge(collecting quantity of discharge) and pollutograph and pollution loading curve through water quality data. Also, we analyzed the correlation between quantity of discharge per unit area and pollution loading per unit area in each basin. As resurt of this research, Buk-cheon spot revealed an excellent first grade water quality for the items including $BOD_5$, DO, and SS. The correlation coefficient between Buk-cheon spot's quantity of discharge and pollution loading was 0.896~0.996, showing the validity of analysis applying correlation curve formula of quantity of discharge and pollution loading in the same spot. Also, pollution loading per unit area of the items including $BOD_5$, COD, DO, SS, T-N, T-P increased as the area of basins get increased following the sequence of Buk-cheon, Suip-cheon, Naelin-cheon spots.
This study was based on water quality data of the Lake Doam watershed, monitored from 2010 to 2013 at eight different sites with multiple physiochemical parameters. The dataset was divided into two sub-datasets, namely, non-rainy and rainy. Principal component analysis (PCA) and factor analysis (FA) techniques were applied to evaluate seasonal correlations of water quality parameters and extract the most significant parameters influencing stream water quality. The first five principal components identified by PCA techniques explained greater than 80% of the total variance for both datasets. PCA and FA results indicated that total nitrogen, nitrate nitrogen, total phosphorus, and dissolved inorganic phosphorus were the most significant parameters under the non-rainy condition. This indicates that organic and inorganic pollutants loads in the streams can be related to discharges from point sources (domestic discharges) and non-point sources (agriculture, forest) of pollution. During the rainy period, turbidity, suspended solids, nitrate nitrogen, and dissolved inorganic phosphorus were identified as the most significant parameters. Physical parameters, suspended solids, and turbidity, are related to soil erosion and runoff from the basin. Organic and inorganic pollutants during the rainy period can be linked to decayed matters, manure, and inorganic fertilizers used in farming. Thus, the results of this study suggest that principal component analysis techniques are useful for analysis and interpretation of data and identification of pollution factors, which are valuable for understanding seasonal variations in water quality for effective management.
Communications for Statistical Applications and Methods
/
v.17
no.1
/
pp.39-45
/
2010
As the value of environment is increasing, the water quality has been a matter of interest to the nation and people. Research on water quality has been widely studied, but focused on geographical characteristic and river characteristics like inflow, outflow, quantity and speed of water. In this paper, two approaches to measure the similarity of sampling sites by using water quality data are discussed and compared with two-years empirical data of Yongdam-Dam. The existing method has calculated their similarities with principal component scores. The proposed approach in this paper use correlation matrix of water quality related variables and MDS for measuring the similarity, which is shown to be better in the sense of being clustering which is identical to geographical clustering since it can consider the time series pattern of water quality.
In order to understand shoreline environment characteristics of Korean reservoirs, the interrelationships between environmental factors of geomorphology, hydrology, water quality and shoreline soil were analyzed, and the reservoir types were classified according to their environmental characteristics in the 35 reservoirs selected by considering the purpose of dam operations and annual water-level fluctuations. Geomorphological and hydrological characteristics of reservoirs were correlated with the altitude and the size scale of reservoirs. The annual range of water level fluctuation showed a wide variation from 1 m to 27 m in the various reservoirs in Korea. The levels of eutrophication of most reservoirs were mesotrophic or eutrophic. From the result of the soil texture analysis, sand contents were high in reservoir shorelines. Range, frequency and duration of water-level fluctuation were distinctive from the primary function of reservoirs. Flood control reservoirs had a wide range with low frequency and waterpower generation reservoirs had a narrow range with high frequency in the water-level fluctuation. According to the result of CART (classification and regression tree) analysis, the water quality of reservoirs was classified by water depth, range of water-level fluctuation and altitude. The result of PCA (principal component analysis) showed that the type of reservoirs was classified by reservoir size, water-level fluctuation, water quality, soil texture and soil organic matter. In conclusion, reservoir size, the water-level fluctuation, water quality and soil characteristics might be major factors in the environment of reservoir shorelines in Korea.
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.
Kim, So-Yeon;Choi, Jung-Hyun;Na, Eun-Hye;Park, Seok-Soon
Journal of Korean Society of Environmental Engineers
/
v.27
no.1
/
pp.43-51
/
2005
This paper presents a waste load allocation study for the Incheon coastal environment, where a computer model, called AQUASEA, was applied. A finite element mesh was constructed and refined to cover the complicated geometry of Incheon coastal sea. The tidal height at 13 places of Incheon coastal boundary and flow of the Han River were given as an input condition to the tidal simulation. All pollution sources that discharge into Incheon coast were given as input data to the water quality simulation. The modeled parameters include tidal flow and COD(Chemical Oxygen Demand). The model was calibrated and verified with the field measurements. The model results showed reasonable agreements with field measurements in both tidal flow and water quality. Systems analysis showed that the pollution load from the Han River caused recognizable impacts on the water quality of Incheon coast from Yeomhwa waterway to northern area of Younghungdo. The loads from Incheon City affected water quality from the area below Youngjongdo to the area above Jawalldo. The discharge from the Sihwa Lake caused discernible impacts on the coastal zone from the dike outlet to the Incheon harbor, and pollution loads from Kyungkido affected the sea near the Oido. An effective water quality management plan was developed from the waste load allocation analysis of the validated model, that the maximum waste loads can be discharged without violating the water quality standard given in the Incheon coastal environment.
Urban areas in watersheds increase the impervious surface, and agricultural areas deteriorate the water quality of rivers due to the use of fertilizers. As such, anthropogenic land use affects the type, intensity and quantity of land use and is closely related to the amount of substances and nutrients discharged to nearby streams. Riparian vegetation reduce the concentration of pollutants entering the watershed and mitigate the negative impacts of land use on rivers. This study analyzes the data through correlation analysis and regression analysis through point data measured twice a year in spring and autumn in 21 selected damaged tributary rivers within the Han River area, and then uses a structural equation model to determine the area land use. In the negative impact on water quality, the mitigation effect of riparian vegetation was estimated. As a result of the correlation analysis, the correlation between the agricultural area and water quality was stronger than that of the urban area, and the area ratio of riparian vegetation showed a negative correlation with water quality. As a result of the regression analysis, it was found that agricultural areas had a negative effect on water quality in all models, but the results were not statistically significant in the case of urban areas. As a result of the model estimated through the structural equation, BOD, COD, TN, and TP showed a mitigation effect due to the accumulation effect of river water quality through riparian vegetation in agricultural areas, but the effect of riparian vegetation through riparian vegetation was found in urban areas. There was no These results were interpreted as having a fairly low distribution rate in urban areas, and in the case of the study area, there was no impact due to riparian forests due to the form of scattered and distributed settlements rather than high-density urbanized areas. The results of this study were judged to be unreasonable to generalize by analyzing the rivers where most of the agricultural areas are distributed, and a follow-up to establish a structural equation model by expanding the watershed variables in urban areas and encompassing the variables of various factors affecting water quality research is required.
Water quality improvement projects are being implemented without predicting the effect of water quality improvement on Lake Sapgyo. As the method of selecting the target stream for the effective conduct of water quality improvement projects the method of rating the streams were studied. To build a stream grading method, 60 major streams in the Lake Sapgyo system were monitored. The selection method of rivers subject to priority management for water quality improvement was applied to the stream grading method using the Analytic Hierarchy Process (AHP). The analysis of importance by site by stream grading method revealed the following: water quality (36.0%), flow (26.1%), travel load (13.4%), TMDL density (12.0%), TMDL (8.9%), and area (3.7%). The pollution level of the river was scored by using the stream grading method, and the ranking of 51 streams was calculated. Based on this, the group was classified into six grades (A-F). Among the groups, the F and E groups were selected as the priority management streams. Cheonan-Cheon (Cheonan City) was selected as the first stream to establish water quality improvement measures in the Lake Sapgyo system, and Seowoo-Cheon (Dangjin City) was selected as the second site, and Oncheon-Cheon (Asan City) was selected as the third site. Each local government is expected to improve the water quality improvement effect with limited resources when establishing and implementing water quality improvement measures for the streams (F group, E group) to be managed in this study.
This study aims to estimate chlorophyll-a concentration in rivers using multi-spectral RapidEye imagery and Spectral Mixture Analysis (SMA) and assess the applicability of SMA for multi-temporal imagery analysis. Comparison between images (acquired on Oct. and Nov., 2013) predicted and ground reference chlorophyll-a concentration showed significant performance statistically with determination coefficients of 0.49 and 0.51, respectively. Two band (Red-RE) model for the October and November 2013 RapidEye images showed low performance with coefficient of determinations ($R^2$) of 0.26 and 0.16, respectively. Also Three band (Red-RE-NIR) model showed different performance with $R^2$ of 0.016 and 0.304, respectively. SMA derived Chlorophyll-a concentrations showed relatively higher accuracy than band ratio models based values. SMA was the most appropriate method to calculate Chlorophyll-a concentration using images which were acquired on period of low Chlorophyll-a concentrations. The results of SMA for multi-temporal imagery showed low performance because of the spatio-temporal variation of each end members. This approach provides the potential of providing a cost effective method of monitoring river water quality and management using multi-spectral imagery. In addition, the calculated Chlorophyll-a concentrations using multi-spectral RapidEye imagery can be applied to water quality modeling, enhancing the predicting accuracy.
This study was to provide basic data for aquatic ecosystem research using fishes. Field sampling was carried out at five selected sites of Gap Stream, and fish samples, especially for a selection of sentinel species were collected three times in June, September, and October 2007. We analyzed total length distribution of Zacco platypus in relation with the season and the sampling sites, and then compared with total body weight, condition factor (K), and age distribution of the fish. The fish population data were compared with physico-chemical water quality, obtained from the Ministry of Environment, Korea. Water quality analysis showed a significant nutrient enrichment, based on total nitrogen (TN) and total phosphorus (TP), and organic matter pollution, based on biological oxygen demand (BOD) and chemical oxygen demand (COD) in the Site 5, which is directly influenced by wastewater disposal plant (WDP). Population analysis of the sentinel species showed that the total number of individuals, age distribution, and the population size-structure were influenced by the effluents from the WDP, and that reproductive failure of young-age population were evident in Site 5. According to the relation analysis of total weight to K, the disturbed population was mainly attributed to combined effects of habitat modifications and chemical degradations. Regression analysis of K values against water quality parameters showed significant (p<0.05) positive relations with nutrient and organic matter contents. Our data suggest that the population structure using a sentinel fish species reflected the ambient water quality in the stream and that diagnosis of aquatic ecosystem health using Z. platypus population may be practical for water resource and ecosystem conservations.
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