• 한국산림과학회지
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• 제90권5호
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• pp.593-599
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• 2001

다변량분석법(주성분분석법, PCA)을 이용하여 무척추동물 군집에 백강균 처리가 미치는 영향을 검정하였다. 좌표공간내의 군집들간의 거리를 이용하여, 군집구조에 미치는 요인들의 영향을 통계 검정하였다. 백강균 처리는 낙엽과 토양의 무척추동물 군집에 유의한 영향을 주지 않았다.

• 한국환경과학회지
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• 제27권10호
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• pp.883-899
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• 2018

In this study, water quality data of eight main sites in the Geumho River watershed were collected and analyzed for long-term changes in water quality over the period from 2005 to 2015. The results showed that BOD concentration was gradually improved by the Total Maximum Daily Load (TMDL), stages 1 and 2. Recently, a tendency of increasing BOD concentration was observed in the downstream section of the river. The concentration of COD was analyzed to be contaminated throughout the water system regardless of the water quality improvement project, and the TN concentration tended to increase in the midstream of the river from 2013. The TP concentration has clearly decreased from 2012 after the second stage of TMDL. For the statistical analysis of PCA ordination, monthly water qualities (pH, DO, Electrical Conductivity (EC), Water Temperature (WT), BOD, COD, TN, TP, TOC, and SS) and flow rate data for 5 years from 2012 to 2016 were used. Seasonally the Geumho River showed an increase in the TN concentration at point sources during the dry season (December to February). TP showed the effect of non-point sources in the summer, because rainfall has caused a rise in flow rate in the upstream. Besides, the origin of pollution source was changed from non-point sources with BOD, COD, and TOC.

• 한국환경보건학회지
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• 제41권2호
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• pp.90-101
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• 2015

Objective: This study was conducted to develop a chemical oxygen demand (COD) regression model using water quality monitoring data (January, 2014) obtained from the Han River auto-monitoring stations. Methods: Surface water quality data at 198 sampling stations along the six major areas were assembled and analyzed to determine the spatial distribution and clustering of monitoring stations based on 18 WQPs and regression modeling using selected parameters. Statistical techniques, including combined genetic algorithm-multiple linear regression (GA-MLR), cluster analysis (CA) and principal component analysis (PCA) were used to build a COD model using water quality data. Results: A best GA-MLR model facilitated computing the WQPs for a 5-descriptor COD model with satisfactory statistical results ($r^2=92.64$,$Q{^2}_{LOO}=91.45$,$Q{^2}_{Ext}=88.17$). This approach includes variable selection of the WQPs in order to find the most important factors affecting water quality. Additionally, ordination techniques like PCA and CA were used to classify monitoring stations. The biplot based on the first two principal components (PCs) of the PCA model identified three distinct groups of stations, but also differs with respect to the correlation with WQPs, which enables better interpretation of the water quality characteristics at particular stations as of January 2014. Conclusion: This data analysis procedure appears to provide an efficient means of modelling water quality by interpreting and defining its most essential variables, such as TOC and BOD. The water parameters selected in a COD model as most important in contributing to environmental health and water pollution can be utilized for the application of water quality management strategies. At present, the river is under threat of anthropogenic disturbances during festival periods, especially at upstream areas.

• 한국습지학회지
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• 제17권2호
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• pp.124-129
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• 2015

하천의 복원을 위한 기초자료로 사용하고자 인간의 간섭에 의한 훼손이 없거나 적은 10개의 자연하천을 군집생태학적 방법으로 조사하여 통계적으로 분석하였다. 그 결과 신갈나무군락과 소나무군락, 사시나무군락, 굴참나무군락, 산벚나무군락 등 총 29개의 식물군락으로 확인되었다. 하천식생은 계곡 계반림과 하변림으로 나누어졌다. 계곡 계반림은 경사가 급하고 물에 의한 영향이 적어 경목림이 우점하였고, 하변 연목림은 버드나무류로 대변되었다. 하천 선택시 자연성이 기준이 되어 인간의 간섭이 많은 하류보다 중 상류에 위치한 조사지가 많았고, 그에 따라 출현군락의 92%(44 plot)는 경목림이었고, 8%(4 plot)는 연목림이었다. 전층을 이용한 PCA 분석에서는 신갈나무군락 그룹과 산벚나무군락 그룹, 소나무군락 그룹, 산벚나무군락과 소나무군락 혼합 그룹, 기타군락 그룹으로 크게 5개의 그룹으로 나누어졌다. 교목층을 이용한 PCA 분석은 신갈나무군락 그룹, 산벚나무군락 그룹, 기타군락 그룹으로 크게 3개의 그룹으로 나누어졌다. 하천변에 출현한 식물군락은 경목림과 연목림으로 나누어졌으며, 이를 통해 하천제방권 및 고수위권은 신갈나무, 소나무, 사시나무, 굴참나무와 산벚나무 등의 종을 식재하는 것이 적합하고, 고수부지권 및 저수위권은 버드나무속 식물을 식재하는 것이 적합할 것으로 판단된다. 식재될 목본에 따른 초본의 선택은 통계분석에서 같은 그룹에 속해있고, 높은 빈도로 출현하는 종으로 하는 것이 적합하다고 판단된다.