Literature DB >> 30463149

Modelling eutrophication in lake ecosystems: A review.

Brigitte Vinçon-Leite1, Céline Casenave2.   

Abstract

Eutrophication is one of the main causes of the degradation of lake ecosystems. Its intensification during the last decades has led the stakeholders to seek for water management and restoration solutions, including those based on modelling approaches. This paper presents a review of lake eutrophication modelling, on the basis of a scientific appraisal performed by researchers for the French ministries of Environment and Agriculture. After a brief introduction presenting the scientific context, a bibliography analysis is presented. Then the main results obtained with process-based models are summarized. A synthesis of the scientist recommendations in order to improve the lake eutrophication modelling is finally given before the conclusion.
Copyright © 2018 Elsevier B.V. All rights reserved.

Keywords:  Cyanobacteria; Global change; Management; Phytoplankton; Process-based models; Watershedlake continuum

Mesh:

Year:  2018        PMID: 30463149     DOI: 10.1016/j.scitotenv.2018.09.320

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  4 in total

Review 1.  Harmful Cyanobacterial Blooms (HCBs): innovative green bioremediation process based on anti-cyanobacteria bioactive natural products.

Authors:  Soukaina El Amrani Zerrifi; Richard Mugani; El Mahdi Redouane; Fatima El Khalloufi; Alexandre Campos; Vitor Vasconcelos; Brahim Oudra
Journal:  Arch Microbiol       Date:  2020-08-14       Impact factor: 2.552

2.  Analysis of Biogenic Secondary Pollution Materials from Sludge in Surface Waters.

Authors:  Laima Česonienė; Edita Mažuolytė-Miškinė; Daiva Šileikienė; Kristina Lingytė; Edmundas Bartkevičius
Journal:  Int J Environ Res Public Health       Date:  2019-11-25       Impact factor: 3.390

3.  Application of a Mechanistic Model for the Prediction of Microcystin Production by Microcystis in Lab Cultures and Tropical Lake.

Authors:  Nur Hanisah Bte Sukarji; Yiliang He; Shu Harn Te; Karina Yew-Hoong Gin
Journal:  Toxins (Basel)       Date:  2022-01-28       Impact factor: 4.546

4.  Chlorophyll soft-sensor based on machine learning models for algal bloom predictions.

Authors:  Alberto Mozo; Jesús Morón-López; Stanislav Vakaruk; Ángel G Pompa-Pernía; Ángel González-Prieto; Juan Antonio Pascual Aguilar; Sandra Gómez-Canaval; Juan Manuel Ortiz
Journal:  Sci Rep       Date:  2022-08-08       Impact factor: 4.996

  4 in total

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