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) 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.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8374272 | PMC |
http://dx.doi.org/10.1016/j.mex.2021.101311 | DOI Listing |
Environ Res
January 2025
School of Chemistry and Environmental Engineering, Hubei Minzu University, 39 College Road, Enshi, 445000, China. Electronic address:
Recovery of phosphate from swine wastewater is significant for alleviating eutrophication in aquatic ecosystems and addressing the increasing scarcity of phosphorus resources. In this study, a method for phosphate recovery from swine wastewater using corn carbon as an additive and non-dynamic magnesium metal self-corrosion was studied. The effects of reaction time, C:Mg mass ratio, stirring rate, and aeration rate on phosphate recovery were discussed, and eight experimental models were explored.
View Article and Find Full Text PDFSci Total Environ
January 2025
Laboratorio de Limnología, Unidad de Ecología y Sistemática (UNESIS), Departamento de Biología, Pontificia Universidad Javeriana, Bogotá, Colombia.
In this study, we focused on Lake Tota (Colombia) as a model for investigating the impact of anthropogenic activities on lake productivity. Two sediment cores collected from the two main basins of the lake (Lago Grande and Lago Chico) were dated using alpha spectrometry for Pb. Changes in organic matter, carbon and nitrogen isotope ratios, C:N ratios, diatoms and elemental fractions were examined as indicators of productivity.
View Article and Find Full Text PDFWater Res
December 2024
Key Laboratory of Poyang Lake Environment and Resource Utilization, Engineering Research Center of Watershed Carbon Neutralization, Ministry of Education, School of Resource and Environment, Nanchang University, Nanchang 330031, China. Electronic address:
To effectively mitigate global eutrophication in lakes, regulating sedimentary phosphorus release remains a primary strategy. Enhancing the adsorption and stabilization performance of passivating agents is integral to addressing endogenous phosphorus pollution in aquatic systems. This study presents a novel aerogel with a high specific surface area (663.
View Article and Find Full Text PDFWater Res
January 2025
UK Centre for Ecology & Hydrology, Lake Ecosystems Group, Lancaster LA1 4AP, UK.
Anthropogenic inputs of nitrogen and phosphorus to lakes have increased worldwide, causing phytoplankton chlorophyll concentrations to increase at many sites, with negative implications for biodiversity and human usage of lake resources. However, the conversion of nutrients to chlorophyll varies among lakes, hindering effective management actions to improve water quality. Here, using a rich global dataset, we explore how the relationship between chlorophyll-a (Chla) and nitrogen and phosphorus and inferred nutrient limitation is modified by climate, catchment, hydrology and lake characteristics.
View Article and Find Full Text PDFEnviron Sci Technol
January 2025
School of Ocean Sciences, Bangor University, Menai Bridge, Anglesey LL59 5AB, U.K.
Accurate prediction of chlorophyll- (Chl-) concentrations, a key indicator of eutrophication, is essential for the sustainable management of lake ecosystems. This study evaluated the performance of Kolmogorov-Arnold Networks (KANs) along with three neural network models (MLP-NN, LSTM, and GRU) and three traditional machine learning tools (RF, SVR, and GPR) for predicting time-series Chl- concentrations in large lakes. Monthly remote-sensed Chl- data derived from Aqua-MODIS spanning September 2002 to April 2024 were used.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!