The Low Impact Development (LID) API for PySWMM provides Python access to the LID objects from the OpenWaterAnalytics Stormwater Management Model. This provides programmatic access to edit parameters and observe results during a running simulation. There are many potential applications for the LID API. Some examples include dynamic control of LIDs, calibration of LID models, manipulation of LID parameters within a simulation, and optimization of LID design.
An example application of the LID API was applied to an existing permeable pavement system which has been monitored over several storm events. A sensitivity analysis was conducted using the LID extension for PySWMM on a heuristically calibrated model. A range was selected for each LID layer parameter to quantify the impact that each parameter had on the simulation results for 12 events. For each simulation, an LID control parameter was changed individually to isolate the potential impact on the simulation results and its effect on the model calibration. Sensitive parameters were then adjusted automatically to calibrate the model to measured data using EmNet’s optimization framework.
Results of the sensitivity analysis indicate that the following parameters should be adjusted during calibration: clog factor; storage seepage; drain coefficient; drainage offset; soil conductivity; and external drainage area. These factors significantly impacted peak event flow, total event volume, or both peak flow and event volume. The automatically calibrated model results show a better goodness of fit than the heuristically calibrated model in a fraction of the time. This API is a powerful tool that can be used to optimize LID design and exposes the functionality for a broad set of future applications