Digitalizing river aquatic ecosystems
Jiuhui Qu , Yaohui Bai , Hui Lin , Chenchen Wang , Qiaojuan Wang
DOI:10.1016/j.jes.2023.03.012
Received October 20, 2022,Revised , Accepted March 08, 2023, Available online March 21, 2023
Volume 36,2024,Pages 677-680
Traditional river health assessment relies on limited water quality indices and representative organism activity, but does not comprehensively obtain biotic and abiotic information of the ecosystem. Here, we propose a new approach to evaluate the ecological and health risks of river aquatic ecosystems. First, detailed physicochemical and biological characterization of a river ecosystem can be obtained through pollutant determination (especially emerging pollutants) and DNA/RNA sequencing. Second, supervised machine learning can be applied to perform classification analysis of characterization data and ascertain river ecosystem ecology and health. Our proposed methodology transforms river ecosystem health assessment and can be applied in river management.
