PYSWMM

Young Ho Kwon·2025년 3월 27일

SWMM

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🐍 What is `pyswmm`?

pyswmm is a Python wrapper library for the [EPA SWMM (Storm Water Management Model)] engine, enabling users to control and extend SWMM simulations directly within a Python environment.

"An interface to run, monitor, and control SWMM in real-time using Python."

🔧 Key Features

Feature	Description
✅ Run SWMM simulations	Execute `.inp` files via Python
✅ Real-time simulation tracking	Monitor the state of nodes, links, subcatchments, storage units, etc.
✅ Controllable elements	Actively control some components (e.g., storage depth, pump ON/OFF)
✅ Loop integration	Integrate with external algorithms (e.g., reinforcement learning, optimization)
✅ Scenario automation	Run multiple experiments by varying input conditions (e.g., rainfall, infrastructure size)

🧱 Core Structure (Key Classes)

Module	Description
`Simulation`	Simulation controller (used with a `with` statement)
`Nodes`	Access and control manholes, storage units, etc.
`Links`	Monitor flow/velocity in conduits, pumps, valves
`Subcatchments`	Track runoff and watershed data
`Pollutants`, `LIDControls`	Analyze pollutants and low impact development (LID) features
`RainGages`	Access rainfall data

▶️ Simple Example

from pyswmm import Simulation, Nodes

with Simulation("model.inp") as sim:
    node = Nodes(sim)["J1"]
    for step in sim:
        print(f"Time: {sim.current_time}, Depth: {node.depth:.2f} m")

📚 Key Use Cases

1. Real-Time Monitoring

Track flooding, water levels, flows in real-time
Integrate with alert and response systems

2. Smart Control

Implement automated control for pumps, storage units, etc.
Compatible with PID control, machine learning algorithms

3. Scenario Simulation

Automatically modify INP parameters → simulate → analyze
Useful for LID design optimization, runoff mitigation planning

4. AI/Reinforcement Learning Integration

Build OpenAI Gym-like environments
Train agents for intelligent control of urban water systems

⚠️ Limitations

Item	Description
No GUI	Command-line based; requires external tools for visualization (e.g., matplotlib, GUI tools)
LID real-time control limited	LID parameters can’t be adjusted in real-time; need to edit INP
Not full control of all features	Some SWMM components (e.g., rule-based logic) are partially supported

📦 Installation

pip install pyswmm

※ Supports Windows, macOS, Linux.
Note: As it depends on C-based libraries, system-specific build issues may occur → virtual environments are recommended.