First, do no harm - Missing data treatment to support lake ecological condition assessment. (December 2022)

• Record Type: Journal Article
• Authors: Chrobak, Grzegorz; Kowalczyk, Tomasz; Fischer, Thomas B.; Szewrański, Szymon; Chrobak, Katarzyna; Wąsowicz, Barbara; Kazak, Jan K.
• Is Part Of: Environmental modelling & software. Volume 158(2022)
• Publication Date: 2022-12
• Subjects: Ecological assessment -- Decision support system -- Missing data -- Lakes -- Water quality; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2022.105558
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Indicators of ecological condition status of water bodies associated with field measurements are often subject to data gaps. This obstacle can often lead to abandonment of assessment. Furthermore, it can lead to the use of methods, based merely on their availability. In response to these challenges, a systematic approach for expert-analyst interaction for missing data treatment is proposed. A combination of algorithms with hierarchical clustering of results is used. A particular emphasis is put on the preparation and interpretation of input data and the role of an expert in the workflow. The proposed approach enhances the decision-making process by improving communication and transparency throughout interactions between experts, analysts and decision makers. Future research should focus on assessing the scale of the ecological data drift phenomenon, which, based on the observed climate change, anthropological pressure and biodiversity loss, may impact the broad concept of indicator construction for lake water ecological assessment Graphical abstract: Image 1 Highlights: Reproducible ecological lake assessment is aided by data imputation techniques. A framework for expert-friendly data treatment was introduced. Data examination is crucial for further data imputation steps. The data sense-making ability is improved by informative results display.