Method for lake eutrophication levels evaluation: TOPSIS-MCS

Song-Shun Lin; Shui-Long Shen; Ning Zhang; Annan Zhou

doi:10.1016/j.mex.2021.101311

Method for lake eutrophication levels evaluation: TOPSIS-MCS

MethodsX. 2021 Mar 18:8:101311. doi: 10.1016/j.mex.2021.101311. eCollection 2021.

Authors

Song-Shun Lin¹, Shui-Long Shen^{2

3

4}, Ning Zhang², Annan Zhou³

Affiliations

¹ Department of Civil Engineering, School of Naval Architecture, Ocean, and Civil Engineering, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai, Minhang District 200240, China.
² MOE Key Laboratory of Intelligent Manufacturing Technology, College of Engineering, Shantou University, Shantou, Guangdong 515063, China.
³ Discipline of Civil and Infrastructure, School of Engineering, Royal Melbourne Institute of Technology (RMIT), Victoria 3001, Australia.
⁴ Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure, School of Naval Architecture, Ocean, and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.

Abstract

Monte Carlo simulation (MCS) is applied in the engineering with great fuzziness and uncertainty. Technique for order preference by similarity to an ideal solution (TOPSIS) method is used to deal with multi-criteria decision-making issue. Membership function is used to determine the membership degree of evaluated index. This paper presents the method for lake eutrophication level evaluation. The developed approach merges MCS method, TOPSIS method and membership function. The evaluated results are consistent with real eutrophication level in Lake Erhai, China. Global sensitivity analysis (GSA) is conducted. Results show that potassium permanganate index (COD_Mn) displays the highest negative correlation with the evaluated results and Secchi disc (SD) performs the highest positive correlation under different errors in measured data. The novelty of this work are: (1) the application of TOPSIS considers Surface water environmental quality standards and measured data. Besides, the Monte Carlo simulation method is applied to generate a normal distributed dataset to overcome the errors caused by human and equipment in data collection. The approach is utilized in the article, titled "Approach based on TOPSIS and Monte Carlo simulation methods to evaluate lake eutrophication levels" (Lin et al., 2020) [1].•Developed approach merges TOPSIS and MCS method.•It can increase the reliability of evaluated result.

Keywords: Lake eutrophication evaluation; Membership function; Monte Carlo simulation; TOPSIS method.