Evaluation of Correlation between Chlorophyll-a and Multiple Parameters by Multiple Linear Regression Analysis

Lim, Ji-Sung; Kim, Young-Woo; Lee, Jae-Ho; Park, Tae-Joo; Byun, Im-Gyu; Lim, Ji-Sung; Kim, Young-Woo; Lee, Jae-Ho; Park, Tae-Joo; Byun, Im-Gyu

doi:2015.37.5.253

The Korean text of this paper can be translated into multiple languages on the website of http://jksee.or.kr through Google Translator.

J Korean Soc Environ Eng > Volume 37(5); 2015 > Article

Original Paper

J Korean Soc Environ Eng 2015;37(5): 253-261. doi: https://doi.org/10.4491/KSEE.2015.37.5.253

다중회귀분석을 이용한 낙동강 하류의 Chlorophyll-a 농도와 복합 영향인자들의 상관관계 분석

임지성¹, 김영우¹, 이재호¹, 박태주¹, 변임규²

¹부산대학교 사회환경시스템공학부
²부산대학교 환경기술･산업개발연구소

Evaluation of Correlation between Chlorophyll-a and Multiple Parameters by Multiple Linear Regression Analysis

Ji-Sung Lim¹, Young-Woo Kim¹, Jae-Ho Lee¹, Tae-Joo Park¹, Im-Gyu Byun²

¹Department of Civil and Environmental Engineering, Pusan National University
²Institute for Environmental Technology and Industry, Pusan National University

Corresponding author

Im-Gyu Byun ,Tel: 051-510-7381, Fax: 051-581-5035, Email: big815@pusan.ac.kr

Received: March 23, 2015; Revised: April 23, 2015; Accepted: May 11, 2015. Published online: May 31, 2015.

ABSTRACT

In this study, Chlorophyll-a (chl-a) prediction model and multiple parameters affecting algae occurrence in Mulgeum site were evaluated by statistical analysis using water quality, hydraulic and climate data at Mulgeum site (1998~2008). Before the analysis, control chart method and effect period of typhoon were adopted for improving reliability of the data. After data preprocessing step two methods were used in this study. In method 1, chl-a prediction model was developed using preprocessed data. Another model was developed by Method 2 using significant parameters affecting chl-a after data preprocessing step. As a result of correlation analysis, water temperature, pH, DO, BOD, COD, T-N, NO₃-N, PO₄-P, flow rate, flow velocity and water depth were revealed as significant multiple parameters affecting chl-a concentration. Chl-a prediction model from Method 1 and 2 showed high R² value with 0.799 and 0.790 respectively. Validation for each prediction model was conducted with the data from 2009 to 2010. Training period and validation period of Method 1 showed 20.912 and 24.423 respectively. And Method 2 showed 21.422 and 26.277 in each period. Especially BOD, DO and PO₄-P played important role in both model. So it is considered that analysis of algae occurrence at Mulgeum site need to focus on BOD, DO and PO₄-P.

Key Words: Nakdong River, Chl-a, Multiple parameters, Data Preprocessing, Multivariate Statistics