Abstract
As stated in Preface of this book, water quality data are crucial in modeling for management. What if the model results do not mimic the data? The immediate response is modifying the model coefficient(s) with justifications. What if this change still does not work? Could there be something else? A classic case study is presented to demonstrate that not reproducing the data should not be viewed as a negative outcome. On the contrarily, it offers an opportunity to expose previously hidden model mechanisms or interactions that are significant from a decision-making point of view.
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Lung, WS. (2022). Challenges in Modeling for Water Quality Management. In: Water Quality Modeling That Works. Springer, Cham. https://doi.org/10.1007/978-3-030-90483-8_1
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DOI: https://doi.org/10.1007/978-3-030-90483-8_1
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