Install
openclaw skills install swmm-builderAssemble a runnable SWMM INP deterministically from subcatchment geometry/attributes, merged parameter JSON, network JSON, and climate references. Use when creating auditable INP + manifest artifacts for downstream swmm-runner/calibration.
openclaw skills install swmm-builderPart of Agentic SWMM — install the project first for the executable toolchain (aiswmm CLI, SWMM solver, MCP servers).
Build a runnable SWMM .inp using explicit file inputs:
subcatchments.csv (shape/area/outlet/routing basics)swmm-paramsswmm-networkswmm-climateThe builder writes:
--out-inp)--out-manifest) with source paths + SHA256 + key metadata[OPTIONS], [RAINGAGES], [TIMESERIES], [SUBCATCHMENTS], [SUBAREAS], [INFILTRATION], and current network sections)Required columns:
subcatchment_idoutletarea_hawidth_mslope_pctOptional columns:
rain_gage (falls back to default gage from climate/config)curb_length_m (default 0)snow_pack (default blank)Expected to match skills/swmm-params/scripts/merge_swmm_params.py output:
sections.subcatchments (id, pct_imperv)sections.subareas (id, runoff/subarea fields)sections.infiltration (id, Green-Ampt fields)%Imperv and routing percentages must be 0..100).Expected to match skills/swmm-network schema (junctions, outfalls, conduits, etc.).
Builder now validates required network fields used to emit [JUNCTIONS], [OUTFALLS], [CONDUITS], [XSECTIONS], [COORDINATES], and [VERTICES].
Provide either:
--timeseries-text directly, or--rainfall-json produced by swmm-climate/format_rainfall.py (must include outputs.timeseries_text)For [RAINGAGES], provide either:
--raingage-json from swmm-climate/build_raingage_section.py, orseries_name.--raingage-json supports both the original single-gage form and a multi-gage form:
{
"gages": [
{
"id": "RG1",
"rain_format": "VOLUME",
"interval_min": 5,
"scf": 1.0,
"source": {"kind": "TIMESERIES", "series_name": "TS_RG1"}
},
{
"id": "RG2",
"rain_format": "VOLUME",
"interval_min": 5,
"scf": 1.0,
"source": {"kind": "TIMESERIES", "series_name": "TS_RG2"}
}
]
}
The timeseries text must include rows for every referenced series_name, and each subcatchment rain_gage must reference one of the emitted gage IDs.
Validation behavior:
[TIMESERIES] rows are validated for series-name consistency and basic token/time/value correctness.validation plus validation_diagnostics metadata.scripts/build_swmm_inp.py
MCP wrapper location:
mcp/swmm-builder/server.js (was previously skills/swmm-builder/scripts/mcp/; moved during the mcp/ root restructure)Exposed tools:
build_inp — assemble a runnable SWMM INP + manifest from
subcatchments CSV, area-weighted params JSON, network JSON, rainfall
JSON + timeseries text, and an options-config JSON. Required args:
subcatchmentsCsvPath, paramsJsonPath, networkJsonPath,
outInpPath, outManifestPath. Optional: rainfallJsonPath,
raingageJsonPath, timeseriesTextPath, configJsonPath,
defaultGageId, waterQualityJsonPath (path to a WQ config JSON —
enables [POLLUTANTS]/[LANDUSES]/[BUILDUP]/[WASHOFF]/[COVERAGES]/
[LOADINGS] sections for pollutant buildup/washoff simulation).
The subcatchments CSV must carry outlet values that point to real
upstream junctions (use swmm-network-mcp.assign_subcatchment_outlets
first if it currently points to the literal outfall).The builder requires upstream outputs from swmm-params and swmm-climate.
Generate them first, then call build_swmm_inp.py:
# 1. Generate merged params from the bundled examples
mkdir -p /tmp/builder-smoke
python3 skills/swmm-params/scripts/landuse_to_swmm_params.py \
--input skills/swmm-params/examples/landuse_input.csv \
--output /tmp/builder-smoke/landuse.json
python3 skills/swmm-params/scripts/soil_to_greenampt.py \
--input skills/swmm-params/examples/soil_input.csv \
--output /tmp/builder-smoke/soil.json
python3 skills/swmm-params/scripts/merge_swmm_params.py \
--landuse-json /tmp/builder-smoke/landuse.json \
--soil-json /tmp/builder-smoke/soil.json \
--output /tmp/builder-smoke/merged_params.json
# 2. Format rainfall from the bundled climate example
python3 skills/swmm-climate/scripts/format_rainfall.py \
--input skills/swmm-climate/examples/rainfall_event.csv \
--out-json /tmp/builder-smoke/rainfall.json \
--out-timeseries /tmp/builder-smoke/rainfall_timeseries.txt
# 3. Build the INP
python3 skills/swmm-builder/scripts/build_swmm_inp.py \
--subcatchments-csv skills/swmm-builder/examples/subcatchments_input.csv \
--params-json /tmp/builder-smoke/merged_params.json \
--network-json skills/swmm-network/examples/basic-network.json \
--rainfall-json /tmp/builder-smoke/rainfall.json \
--config-json skills/swmm-builder/examples/options_config.json \
--out-inp /tmp/builder-smoke/example_model.inp \
--out-manifest /tmp/builder-smoke/example_manifest.json
Pass --water-quality-json <path> to enable pollutant buildup/washoff
simulation. The JSON must satisfy the schema in
skills/swmm-water-quality/SKILL.md. Omit the flag for pure hydrology runs
(Water Quality: NO in the INP).
# Build an INP with water quality (TSS, 1 landuse, executed example):
python3 skills/swmm-builder/scripts/build_swmm_inp.py \
--subcatchments-csv skills/swmm-builder/examples/subcatchments_input.csv \
--params-json /tmp/builder-smoke/merged_params.json \
--network-json skills/swmm-network/examples/basic-network.json \
--water-quality-json /tmp/wq_example.json \
--out-inp /tmp/wq_model.inp \
--out-manifest /tmp/wq_manifest.json
The builder validates all cross-references (pollutant/landuse/subcatchment consistency) before writing the INP.
rain_gage is explicitly set per row.