MARE – Marine and Environmental Sciences Centre, ARNET – Aquatic
Research Network Associate Laboratory, NOVA School of Science and
Technology, NOVA University Lisbon, Caparica, Portugal
Pedro S. Coelho
MARE – Marine and Environmental Sciences Centre, ARNET – Aquatic
Research Network Associate Laboratory, NOVA School of Science and
Technology, NOVA University Lisbon, Caparica, Portugal
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Total article views: 1,178 (including HTML, PDF, and XML)
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1,178
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BibTeX: 40
EndNote: 30
Views and downloads (calculated since 21 Nov 2022)
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Total article views: 664 (including HTML, PDF, and XML)
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453
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664
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BibTeX: 33
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Total article views: 514 (including HTML, PDF, and XML)
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351
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HTML: 351
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Cumulative views and downloads
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Viewed (geographical distribution)
Total article views: 1,178 (including HTML, PDF, and XML)
Thereof 1,134 with geography defined
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Total article views: 664 (including HTML, PDF, and XML)
Thereof 630 with geography defined
and 34 with unknown origin.
Total article views: 514 (including HTML, PDF, and XML)
Thereof 504 with geography defined
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Water temperature (WT) datasets of low-order rivers are scarce. In this study, five different models are used to predict the WT of 83 rivers. Generally, the results show that the models' hyperparameter optimization is essential and that to minimize the prediction error it is relevant to apply all the models considered in this study. Results also show that there is a logarithmic correlation among the error of the predicted river WT and the watershed time of concentration.
Water temperature (WT) datasets of low-order rivers are scarce. In this study, five different...