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Modelling Accuracy Uncertainties Impact Mapping: Difference between revisions

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=What are the reasons whyfor models to vary widely in their accuracy?=
* The level of uncertainty/inaccuracy in the input data, especially uncertainties in hydrological inflows (which can be considerable) and topography.
* Whether the model is calibrated, and if calibrated, the range of calibration events and quantity/quality/type of calibration data. A model well calibrated to a range of flood events will be much more accurate than an uncalibrated model. More information on calibration can be found in <u>[https://www.tuflow.com/Download/Publications/October2016_FMA_Newsletter_HuxleyRyan.pdf Flood Modelling: How Accurate is Your Model?]</u> or an Australian Water School webinar <u>[https://www.tuflow.com/library/webinars/#maximise_accuracy Maximising Hydraulic Model Accuracy]</u>.
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*Approach used for solving the underlying mathematical equations describing free surface fluid flow.
*Degree and quality of model calibration / verification.
*Understanding the degree of uncertainty is important for setting absolute metrics such as design levels and freeboard. While less important for impact mapping because the uncertainties are present in both sides of the comparison. The hydraulic modelling carried out should be based on recommended industry and software guidelines, and follow sound modelling practices.<br> An overview on uncertainties in flood modelling can be viewed in Australian Water School webinar <u>[https://www.tuflow.com/library/webinars/#jul2019_how_wrong How Wrong is Your Flood Model?]</u> <br> <br>
 
=What is numerical noise?=
The nonlinear nature of the shallow water (long wave) equations used for modelling floods, can cause localised differences in the results that occur in locations well removed from where the model has changed. These differences should be treated as artefacts of the solution, often referred to as numerical noise.<br>
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