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Published June 11, 2026 | Version 1.0.0

Reproducible EPA SWMM model package for LID/SUDS-based urban pluvial flood mitigation in a school area of Durán, Ecuador

  • 1. ROR icon Escuela Superior Politecnica del Litoral

Description

This repository contains a reproducible EPA SWMM model package developed to evaluate low-impact development / sustainable urban drainage system (LID/SUDS) scenarios for pluvial flood mitigation in a school area of Durán, Ecuador.

The package includes Python scripts for generating Chicago design hyetographs at 5-minute temporal resolution, station rainfall data, generated storm hyetographs, EPA SWMM input models, archived outputs from 60 SWMM simulations, R scripts for extracting and analysing SWMM report files, final tables and figures, and files required to restore the reproducible R environment.

The design storm set combines three return periods, 5, 10, and 20 years, with five storm durations, 30, 60, 120, 180, and 240 minutes, producing 15 synthetic rainfall events. These storms were applied to four SWMM scenarios: a baseline model and three LID/SUDS scenarios. The archived SWMM simulations include input, report, output, and log files for each scenario-storm combination.

The main R analysis script extracts hydrological and hydraulic indicators from SWMM report files, checks continuity errors, calculates percentage reductions relative to the baseline scenario, ranks LID/SUDS alternatives using multicriteria indicators, estimates uncertainty using bootstrap resampling, and evaluates exploratory robustness across design storms.

This dataset is intended to support reproducibility, transparency, and independent verification of the modelling workflow used in the associated study on urban pluvial flood mitigation using LID/SUDS alternatives in data-limited educational infrastructure.

Files

SWMM.zip

Files (2.0 MB)

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Additional details

Dates

Created
2026
Creation date of the reproducible dataset package.

Software

Programming language
R , Python , PowerShell
Development Status
Active