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Characterising retrieval uncertainty of chlorophyll-a algorithms in oligotrophic and mesotrophic lakes and reservoirs 1 1 Introduction 1 2 Data 2 3 Methods 3 3.1 Explanatory variables and uncertainty model definition 3 3.2 Chlorophyll-a retrieval 6 3.3 Uncertainty characterisation 8 3.4 Performance metrics 9 4 Results 11 4.1 Optical and biogeochemical properties of the dataset 11 4.2 Chlorophyll-a algorithm performance 12 4.3 Uncertainty quantification 12 4.4 Uncertainty characterisation 12 5 Discussion 14 5.1 Blue/green algorithms 14 5.2 Red/NIR algorithms 14 5.3 Machine learning algorithms 15 5.4 Semi-analytical algorithms 16 6 Conclusions 16 CRediT authorship contribution statement 16 Declaration of Competing Interest 16 Acknowledgements 16 Appendix A Description of Wisconsin DNR in situ data 17 Radiometric measurements 17 Field measurements and laboratory analysis 17 Appendix B Description of University of Stirling (UoStirling) in situ data 18 Appendix C Uncertainty models 18 Appendix D SHAP and standard variable importance 19 References 19

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nonfiction