Modelling Accuracy Uncertainties Impact Mapping: Difference between revisions
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=What are the reasons
* 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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*Accuracy of the input data (e.g. terrain, landuse, hydrologic inflows).
*Approach used for solving the underlying mathematical equations describing free surface fluid flow.
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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?=
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=What approaches are
Establishing guidelines for mapping tolerances for flood impact assessments typically follow one of the approaches below, with the approach taken dependent on the objectives and the type of hydraulic modelling output field being mapped:
*A percentage, for example, a maximum increase in velocity of 10%. A threshold or cutoff is sometimes used below which the impact is assumed to be inconsequential or to discard slight changes to near zero values.
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* Use depth varying manning's n (lower manning's n for shallow water depths), specifically for direct rainfall models.
* Set appropriate <font color="blue"><tt>Map Cutoff Depth </tt></font> for the modelling task. e.g. direct rainfall models might have higher values to avoid undesirable noise on the wet/dry interface.<br>
* Use smaller 1D timestep for models with 1D features.
* Try double precision, specifically for models with higher elevation, 1D features and or very small flow/rainfall depth increments.
* When running HPC and or Quadtree, test control number factor smaller than 1.
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Prior to 2020-10-AB release, the new boundary method introduced in TUFLOW HPC 2020-01-AA release for inflowing HT and QT boundaries (refer see Section 6.1 of the 2020 Release Notes) can in rare situations be affected by bitwise reproducibility when parallelised. When this issue occurs, very slight numerical differences can occur throughout the model, noting that they will be of a much smaller magnitude than those that occur when carrying out impact assessments, but will cause undesirable numerical noise in the impact mapping.<br>
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