How to Cite#

Cite our Paper#

Please acknowledge use of PySWMM by citing our paper:

McDonnell, Bryant E., Ratliff, Katherine M., Tryby, Michael E., Wu, Jennifer Jia Xin, & Mullapudi, Abhiram. (2020). PySWMM: The Python Interface to Stormwater Management Model (SWMM). Journal of Open Source Software, 5(52), 2292, https://doi.org/10.21105/joss.02292

Oberascher, M., Kinzel, C., Kastlunger, U., Kleidorfer, M., Zingerle, C., Rauch, W., Sitzenfrei, R., 2021. Integrated urban water management with micro storages developed as an IoT-based solution – the smart rain barrel. Environmental Modelling & Software, 105028. https://doi.org/10.1016/j.envsoft.2021.105028.
Li, J., Burian, S., & Oroza, C. (2019). Exploring the Potential for Simulating System-Level Controlled Smart Stormwater System. In World Environmental and Water Resources Congress 2019: Water, Wastewater, and Stormwater; Urban Water Resources; and Municipal Water Infrastructure (pp. 46-56). Reston, VA: American Society of Civil Engineers. https://ascelibrary.org/doi/abs/10.1061/9780784482360.006
Sadler, J. M., Goodall, J. L., Behl, M., Morsy, M. M., Culver, T. B., & Bowes, B. D. (2019). Leveraging open source software and parallel computing for model predictive control of urban drainage systems using EPA-SWMM5. Environmental Modelling & Software, 120, 104484. https://doi.org/10.1016/j.envsoft.2019.07.009
Ratliff, K. M., McDonnell, B., Tryby, M., & Mikelonis, A. (2018). Expanding the EPA Storm Water Management Model (SWMM5) API for Tracking Contamination in Urban Environments. In AGU Fall Meeting Abstracts.