An Inverse Calibrator For VFSMOD-W Using The Global Multilevel Coordinate Search/ Nelder-Mead Simplex Algorithm

When designing vegetative filter strips (VFS) for trapping sediments, the modeler faces the challenge of identifying the appropriate model parameters for the specific application conditions. When possible, local runoff/sediment inflow/outflow through the VFS and precipitation data should be collected to support the modeling predictions. Although manual model calibration is often used, this procedure generally lacks objectivity and the outcome is linked to the expertise of the user. An automated inverse optimization procedure can be used as an objective and robust model calibration alternative. The graphical user interface of VFSMOD-W, a vegetative filter strip design system, was extended to allow for the inverse optimization of the hydraulic and sediment components of the model. A robust and efficient optimization technique, the Global Multilevel Coordinate Search algorithm in sequential combination with the local Nelder-Mead Simplex algorithm (GMCS-NMS), was selected for this purpose. This is a good alternative to other existing optimization procedures, because it is adapted for solving complex nonlinear problems accurately and efficiently, does not require powerful computing resources, and initial values of the parameters to be optimized are not needed. Several examples are presented to demonstrate the benefits of the GMCS-NMS strategy compared to manual calibration when identifying the VFSMOD-W most sensitive parameters.