Rhodium-SWMM: An open-source tool for green infrastructure placement under deep uncertainty

Nastaran Tebyanian, Jordan Fischbach, Robert Lempert, Debra Knopman, Hong Wu, Lisa Iulo, Klaus Keller

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Green Infrastructure (GI) measures are increasingly used for climate adaptation in urban areas, but it remains a challenge to evaluate their effectiveness and strategically allocate investment. Planning GI is subject to deep uncertainties and requires navigating tradeoffs between multiple objectives. Many-Objective Robust Decision Making (MORDM) can be useful in addressing these modeling challenges. Thus far, MORDM has been used sparsely for GI planning. To help mainstream MORDM applications in GI planning, we developed an open-source Python library: Rhodium-SWMM. Rhodium-SWMM connects the USEPA's Stormwater Management Model (SWMM) to Rhodium, a Python library for MORDM. Rhodium-SWMM provides a generalizable and flexible interface for taking SWMM input files and setting up a multi-objective optimization problem with the ability to define a wide range of parameters in the SWMM input file as uncertainties or levers. This opens opportunities to more conveniently analyze new research questions in multi-scale GI placement under deep uncertainty.

Original languageEnglish (US)
Article number105671
JournalEnvironmental Modelling and Software
Volume163
DOIs
StatePublished - May 2023

All Science Journal Classification (ASJC) codes

  • Software
  • Environmental Engineering
  • Ecological Modeling

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