swmm-params

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Deterministic mapping from land use and soil texture to SWMM runoff/subarea and Green-Ampt infiltration parameters. Use when generating first-pass subcatchment parameter tables for swmm-builder.

AI & Automation 21 stars 9 forks Updated 3 days ago MIT

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Skill Content

# SWMM Params (MVP mapping layer) Part of [Agentic SWMM](https://github.com/Zhonghao1995/agentic-swmm-workflow) — install the project first for the executable toolchain (aiswmm CLI, SWMM solver, MCP servers). ## What this skill provides - Transparent CSV-to-JSON mapping for: - land use class -> SWMM `[SUBCATCHMENTS]` + `[SUBAREAS]` defaults - soil texture/type -> SWMM `[INFILTRATION]` (Green-Ampt) defaults - Deterministic, auditable outputs with explicit fallback usage and unmatched-key reporting. - Optional merge step that emits one builder-ready JSON artifact. ## Scripts - `scripts/landuse_to_swmm_params.py` - maps `subcatchment_id + landuse_class` to runoff/subarea parameters - `scripts/soil_to_greenampt.py` - maps `subcatchment_id + soil_texture` to Green-Ampt infiltration parameters - `scripts/merge_swmm_params.py` - merges outputs from the two mapping scripts into one JSON package for future `swmm-builder` ## Default lookup tables By default, scripts read bundled lookup CSVs: - `skills/swmm-params/references/landuse_class_to_subcatch_params.csv` - `skills/swmm-params/references/soil_texture_to_greenampt.csv` You can override lookup paths with CLI flags. ## Minimal input format Land use input CSV: - required columns: `subcatchment_id`, `landuse_class` Soil input CSV: - required columns: `subcatchment_id`, `soil_texture` Example files are provided under `examples/`. ## Outputs Each mapper writes explicit JSON containing: - `records` (row-level audit tra...

Details

Author
Zhonghao1995
Repository
Zhonghao1995/agentic-swmm-workflow
Created
5 months ago
Last Updated
3 days ago
Language
Python
License
MIT

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