OpenHydro Bench

Track B corpus

1,396 EPA SWMM models from HydroCouple openswmm.engine.benchmarks at commit 63eb8bc5b4e7, each run on the pinned EPA SWMM 5.2.4 engine. Models are not copied here: the index records each file's URL at that commit and its SHA-256. The HydroCouple corpus is the 1729 SWMM5 models library before its repairs; R. E. Dickinson's 1729-SWMM5-Models-2030 fixes many of the input errors counted below, and a census from it is planned.

Does each model run on the reference engine?

Census outcome on EPA SWMM 5.2.4Ran cleanlyRan cleanly: 941 models941941 modelsInput errorInput error: 296 models296296 modelsTimed out (60 s)Timed out (60 s): 157 models157157 modelsHarness errorHarness error: 1 models1 modelsEngine errorEngine error: 1 models1 models

A model joins a tier only if it runs cleanly and SWMM's own continuity error stays within ±5 %: a reference that loses or creates water cannot anchor parity. 297 models stop with input or engine errors (mostly older-version syntax: ERROR 205, 207, 209, 211, 235, and 32 missing rainfall files, ERROR 317), 157 exceed the 60 s census limit, and 98 run but fail the continuity rule. All stay in the index so upstream maintainers can see them.

Tiers

TierModelsSelection ruleDownload
PR40 + 3 catalog casesRuns in ≤ 5 s, picked for feature-tag coverage across collections, at least five control-rule models; gates every pull requestselection.json
Nightly500Runs in ≤ 10 s, picked greedily so every tag is coveredselection.json
Release773Every model that runs, keeps continuity within ±5 % and has a verified licenceselection.json

Does another engine match SWMM 5.2.4?

Any SWMM-compatible engine can be scored against the reference across a whole tier with scripts/corpus_parity.py: both engines run every model, and each model gets the worst node (relative peak depth) and worst link (relative volume of |Q|) — the same metrics as the catalog's Track B cases. Two candidates are scored here: the previous release, EPA SWMM 5.1.15 (OWA build in swmm-toolkit 0.10.0), HydroCouple's rewritten OpenSWMM Engine v6 (pre-release openswmm 6.0.0a4 on PyPI, run with its new engine, both with each model's own routing and with its new finite-volume routing, FLOW_ROUTING FV, which changes the numerical method and so is expected to differ), and NEER AI's Hydra 17 urban-drainage engine (CLI 4.1.1). Each week the same comparison runs on Bellinge (Odense, Denmark; Pedersen et al. 2021, CC BY 4.0), a real combined sewer system of about 1,000 nodes and 1,000 links with pumps, weirs and control rules, on a two-day storm.

Each candidate against EPA SWMM 5.2.4: worst element per modelEPA SWMM 5.1.15, pr tier (40)Identical: 21 modelsWithin 1 %: 3 models1–5 %: 5 modelsOver 5 %: 5 modelsCandidate could not run it: 5 models39 modelsHydra 17 (urban drainage), nightly tier (500)Identical: 33 models33Within 1 %: 32 models321–5 %: 60 models60Over 5 %: 352 models352Candidate could not run it: 20 models497 modelsOpenSWMM Engine v6, finite-volume routing, nightly tier (500)Identical: 30 modelsWithin 1 %: 11 models1–5 %: 7 modelsOver 5 %: 429 models429Candidate could not run it: 21 models498 modelsOpenSWMM Engine v6, nightly tier (500)Identical: 207 models207Within 1 %: 172 models1721–5 %: 46 models46Over 5 %: 71 models71Candidate could not run it: 1 models497 modelsEPA SWMM 5.1.15, nightly tier (500)Identical: 355 models355Within 1 %: 76 models761–5 %: 17 modelsOver 5 %: 22 modelsCandidate could not run it: 26 models496 modelsHydra 17 (urban drainage), bellinge network (1 real system) (1)Over 5 %: 1 models1 modelsOpenSWMM Engine v6, finite-volume routing, bellinge network (1 real system) (1)Over 5 %: 1 models1 modelsOpenSWMM Engine v6, bellinge network (1 real system) (1)Over 5 %: 1 models1 models
  • Identical
  • Within 1 %
  • 1–5 %
  • Over 5 %
  • Candidate could not run it
Most legacy models are bit-identical. On the EXTRAN examples 5.1.15 and 5.2.4 produce the same numbers to every stored digit, so a tier made only of them cannot detect most engine changes. The PR tier is therefore picked for feature coverage.
Differences cluster in features that changed. Low-impact development, groundwater, seepage and some hydrology models differ by tens to hundreds of percent at their worst element: these are real behaviour changes between releases, not noise.
OpenSWMM v6 runs almost everything, and changes more. It runs 499 of 500 nightly models (SWMM 5.1.15: 479), and 425 of the 496 it scores are within 5 % of 5.2.4. In 20 of the 71 over 5 % the worst node is an outfall, where v6 reports a depth and 5.2.4 almost none. One model, weir-overtopping, shows water created at an outfall (routing continuity −48 %), and long continuous runs are up to 57 times slower. Details for the developers: docs/openswmm.md.
Hydra is a different drainage engine, by design. Hydra states that it follows conservation laws, not SWMM's numbers. On the nightly tier 125 of 476 scored models are within 5 % of SWMM 5.2.4 (median worst element 29 %). Hydrology-only models agree (16 of 17 LID models); routed flows differ, even on the classic EXTRAN examples (median 7.5 %), so the difference is its Preissmann-slot routing rather than units or input reading. Details: docs/hydra.md.
A difference is not a defect. Track B says how far a candidate is from the reference engine, not which one is right. Whether 5.2.4 is physically better is a Track A question.

EPA SWMM 5.1.15, pr tier: largest differences

ModelWorstPeak depth (worst node)Volume (worst link)
hydrology/greenroofs438 %worst of 19 elements: 33 (+438.4 %)worst of 17 elements: 1 (+0 %)
swmm5-ncimm/270-h-h-elements46.32 %worst of 93 elements: 60 (+46.32 %)worst of 90 elements: 29 (+3.547 %)
swmm5-ncimm/greenville-epa11.58 %worst of 170 elements: JCT-142 (+11.4 %)worst of 233 elements: PUMP-17 (+11.58 %)
semi-real-models/490-kw-h-h-elements7.625 %worst of 180 elements: 2003 (+0.004309 %)worst of 225 elements: N_I90-ORIFICE (+7.625 %)
swmm5-ncimm/399-h-h-elements7.625 %worst of 180 elements: 2003 (+0.004309 %)worst of 225 elements: N_I90-ORIFICE (+7.625 %)
swmm5-ncimm/usgs-runoff4.601 %worst of 6 elements: FLOWFROMSUB (-2.708 %)worst of 6 elements: 1 (-4.601 %)
hydraulics/pid-extran-master-swmm34-example-sw54.473 %worst of 61 elements: 15009b (+0.01879 %)worst of 58 elements: OR1@82309d-82308d (-4.473 %)
epa/pid-extran-master-swmm34-example-sw54.473 %worst of 61 elements: 15009b (+0.01879 %)worst of 58 elements: OR1@82309d-82308d (-4.473 %)
hydrology/suds-swmm5-example41.776 %worst of 8 elements: D (-0.01622 %)worst of 7 elements: 5 (-1.776 %)
hydrology/master-gw1.333 %worst of 5 elements: P011 (-0.3584 %)worst of 4 elements: P011 (-1.333 %)
xpswmm/sprenger0.535 %worst of 141 elements: SMCPMCD-I (+0.5349 %)worst of 139 elements: CHIGMAU (+0.1096 %)
swmm5-ncimm/1710-2014-20year-r30.0635 %worst of 40 elements: Pond1 (+0.001583 %)worst of 57 elements: C18 (-0.06355 %)

5 model(s) the candidate could not run: lew-chi-swmm5-2/control-rules-test, lew-chi-swmm5-2/example7-inlets, lew-chi-swmm5-2/onsag-curb-inlet-12-inflow, lew-chi-swmm5-2/onsag-grate-inlet-11-inflow, swmm5-ncimm/lid1d. Most use input syntax added after 5.1 (inlets, newer options), which an older engine rejects with ERROR 200.

Hydra 17 (urban drainage), nightly tier: largest differences

ModelWorstPeak depth (worst node)Volume (worst link)
swmm5-ncimm/90-h-h-si-units-elementsinf %1 reference elements missing from results (e.g. Exutório)worst of 31 elements: Sol9 (+356.4 %)
swmm5-ncimm/77-h-h-elementsinf %1 reference elements missing from results (e.g. Exutório)worst of 31 elements: Sol9 (+356.4 %)
semi-real-models/90-h-h-si-units-elements-2inf %1 reference elements missing from results (e.g. Exutório)worst of 31 elements: Sol9 (+398.3 %)
semi-real-models/90-h-h-si-units-elements-1inf %1 reference elements missing from results (e.g. Exutório)worst of 31 elements: Sol9 (+398.3 %)
ncimm-routing/swmm-ehh-geog-alvaromiguel-cenario1inf %1 reference elements missing from results (e.g. Exutório)worst of 31 elements: Sol9 (+356.4 %)
semi-real-models/77-h-h-elements-1inf %1 reference elements missing from results (e.g. Exutório)worst of 31 elements: Sol9 (+398.3 %)
hydrology/runoff31-sw5975,669,200,979,173,248 %worst of 2 elements: Node201 (+1061 %)worst of 1 elements: Node301 (+9.757e+17 %)
swmm5-ncimm/hechms2,308,130,645,751,953 %worst of 1 elements: DUMMY2 (+2.308e+15 %)–
lid/lid-single-outfall-upstream100,000 %worst of 3 elements: 1 (+1e+05 %)worst of 1 elements: 1 (+3.876e+04 %)
epa/all-outfall-types-model23,343 %worst of 6 elements: TimeSeries_Outfall (+1.429e+04 %)worst of 5 elements: 7000 (+2.334e+04 %)
swmm5-ncimm/780-h-h-si-units-elements18,124 %worst of 394 elements: F4014 (+1.569e+04 %)worst of 403 elements: 13117 (+1.812e+04 %)
epa/extran1-dummy15,492 %worst of 10 elements: 10309 (+1.549e+04 %)worst of 9 elements: 1570 (+5.012e-06 %)

20 model(s) the candidate could not run: epa/3-pumps-kw-ideal-pumps, epa/linear-links, epa/pressure-net, epa/small-pump-fm-model, hydrology/25-subcatchments-cn-infiltration, hydrology/feng-scs-test-model, hydrology/feng-scs-test-model-v13, hydrology/horton-continuous-model …. Hydra refuses these with an explicit validation message (for example incomplete subcatchment data or ground below the initial water table), or took longer than 600 s; see docs/hydra.md.

OpenSWMM Engine v6, finite-volume routing, nightly tier: largest differences

ModelWorstPeak depth (worst node)Volume (worst link)
swmm5-ncimm/6867-h-elements2,438,540,597,569,654,882,304 %worst of 3414 elements: LS-13_WW (+9.411e+16 %)worst of 3449 elements: 23 (+2.439e+21 %)
swmm5-ncimm/6869-h-elements2,438,540,597,569,654,882,304 %worst of 3414 elements: LS-13_WW (+9.411e+16 %)worst of 3449 elements: 23 (+2.439e+21 %)
swmm5-ncimm/weir-overtopping556,016,352,539,062,501,376 %worst of 3 elements: Spill (+7.606e+05 %)worst of 2 elements: road_overtop (+5.56e+20 %)
hydrology/runoff31-sw5966,849,049,066,566,784 %worst of 2 elements: Node201 (+1062 %)worst of 1 elements: Node301 (+9.668e+17 %)
swmm5-ncimm/mjtestofnoslope877,462,163,517,521 %worst of 289 elements: N10.10.10B (+6.896e+11 %)worst of 303 elements: CDT-27 (+8.775e+14 %)
swmm5-ncimm/duobiocell39,025,348,992,454 %worst of 3 elements: 2 (+3.903e+13 %)worst of 2 elements: 23 (+2.11e+11 %)
hydrology/lar-zero-rtk9,999,533,358 %worst of 2 elements: 1 (+1e+10 %)worst of 1 elements: 1 (+1.582e+09 %)
swmm5-ncimm/100yr-event-epa-swmm-5-1-test119,728,030 %worst of 3 elements: Cell_E_FB (+2.906e+05 %)worst of 2 elements: FB_WEIR (+1.197e+08 %)
epa/inlet-pipe-test3,936,972 %worst of 90 elements: 48 (+3.937e+06 %)worst of 90 elements: 92 (+59.73 %)
hydrology/137-h-h-elements1,339,178 %worst of 43 elements: EOF_OUTFALL (+1.339e+06 %)worst of 67 elements: GOLF_COURSE_EOF (+1411 %)
ncimm-routing/29street571,521 %worst of 80 elements: ChelsaMan5 (+5.715e+05 %)worst of 79 elements: Chelsa54.4 (+57.49 %)
swmm5-ncimm/219-elements-dw-si-units265,978 %worst of 77 elements: J43 (+2.66e+05 %)worst of 74 elements: P10 (+571.3 %)

21 model(s) the candidate could not run: epa/3-pumps-kw-ideal-pumps, epa/extran1-dummy, hydraulics/extran1-dummy, hydrology/ejemplo-epa, hydrology/greenroofs, owa-update-v5111/porous-pavement, swmm5-ncimm/1765-nodes, swmm5-ncimm/1943-h-h-elements-si-units ….

OpenSWMM Engine v6, nightly tier: largest differences

ModelWorstPeak depth (worst node)Volume (worst link)
swmm5-ncimm/weir-overtopping556,016,352,539,062,501,376 %worst of 3 elements: Spill (+7.606e+05 %)worst of 2 elements: road_overtop (+5.56e+20 %)
epa/inlet-pipe-test3,936,972 %worst of 90 elements: 48 (+3.937e+06 %)worst of 90 elements: 14 (+0.005452 %)
hydrology/137-h-h-elements1,339,188 %worst of 43 elements: EOF_OUTFALL (+1.339e+06 %)worst of 67 elements: JUNC_23_EOF (-3.691 %)
swmm5-ncimm/559-h-h-elements144,709 %worst of 234 elements: 12223912 (+9184 %)worst of 241 elements: 12223911.3 (+1.447e+05 %)
hydrology/9-subs10,004 %worst of 22 elements: 2888_FES (+1e+04 %)worst of 20 elements: LS4_18IN_FM (+9.298 %)
epa/pumps-activated-sludge9,961 %worst of 5 elements: TreatedWater (+9961 %)worst of 5 elements: AS_Weir (+0 %)
epa/tunnelmh9,961 %worst of 4 elements: Overflow (+9961 %)worst of 3 elements: Gate (+0 %)
hydraulics/tunnelmh9,961 %worst of 4 elements: Overflow (+9961 %)worst of 3 elements: Gate (+0 %)
owa-routing/routing-combo-all-links8,127 %worst of 6 elements: OvfOut (+8127 %)worst of 6 elements: C1 (+0 %)
epa/diversion-weir-network8,074 %worst of 10 elements: OFALL-14 (+8074 %)worst of 8 elements: CDT-31 (-7.621 %)
ncimm-routing/small-si-transects4,579 %worst of 15 elements: Outfall (+4579 %)worst of 14 elements: 28 (+0.1168 %)
swmm5-ncimm/1943-h-h-elements-si-units3,788 %worst of 449 elements: Z2.1-MH-24 (+3788 %)worst of 444 elements: P4Z4.18-MH-04 (-1.313 %)

1 model(s) the candidate could not run: swmm5-ncimm/3525-nodes. The v6 pre-release stops at initialisation with an unexplained parse error; see docs/openswmm.md.

EPA SWMM 5.1.15, nightly tier: largest differences

ModelWorstPeak depth (worst node)Volume (worst link)
pumps/extran6-type186,829 %worst of 11 elements: 16109 (+775.1 %)worst of 11 elements: 1630 (+8.683e+04 %)
pumps/extran6-type486,829 %worst of 11 elements: 16109 (+775.1 %)worst of 11 elements: 1630 (+8.683e+04 %)
pumps/extran6-type372,392 %worst of 11 elements: 16109 (+784.8 %)worst of 11 elements: 1630 (+7.239e+04 %)
swmm5-ncimm/lid-imperviouscapture1,048 %worst of 19 elements: 33 (+1048 %)worst of 17 elements: 1 (+0 %)
hydrology/ejemplo-epa903 %worst of 33 elements: 50 (+902.8 %)worst of 32 elements: 10 (+0 %)
swmm5-ncimm/new-mikeurbancn478 %worst of 9 elements: 6037 (+477.6 %)worst of 8 elements: 25482.1 (+0.4077 %)
hydrology/greenroofs438 %worst of 19 elements: 33 (+438.4 %)worst of 17 elements: 1 (+0 %)
swmm5-ncimm/treattest1268 %worst of 14 elements: 18 (+268 %)worst of 13 elements: 1 (+0 %)
owa-user/user3-horiz-ellipse-varied55.07 %worst of 141 elements: SCANOUT1 (-55.07 %)worst of 139 elements: SCANOUT1 (-0.07794 %)
swmm5-ncimm/270-h-h-elements46.32 %worst of 93 elements: 60 (+46.32 %)worst of 90 elements: 29 (+3.547 %)
epa/pump-speed-ratio22.32 %worst of 61 elements: 82308D (-22.32 %)worst of 58 elements: OR1@82309D-82308D (+1.871 %)
swmm5-ncimm/pump4-rating-curve-comparison17.52 %worst of 61 elements: 80608e (+17.52 %)worst of 58 elements: OR1@82309d-82308d (+6.893 %)

26 model(s) the candidate could not run: epa/master-extran-rtc, lew-chi-swmm5-2/control-rules-test, lew-chi-swmm5-2/drop-grate-inlet-17, lew-chi-swmm5-2/drop-grate-inlet-18, lew-chi-swmm5-2/example7-inlets, lew-chi-swmm5-2/onsag-curb-inlet-12, lew-chi-swmm5-2/onsag-curb-inlet-12-backwater, lew-chi-swmm5-2/onsag-curb-inlet-12-inflow …. Most use input syntax added after 5.1 (inlets, newer options), which an older engine rejects with ERROR 200.

Hydra 17 (urban drainage), bellinge network (1 real system): largest differences

ModelWorstPeak depth (worst node)Volume (worst link)
bellinge146 %worst of 1020 elements: G61F012 (+145.6 %)worst of 1044 elements: G72R33Bout1 (+82.49 %)

OpenSWMM Engine v6, finite-volume routing, bellinge network (1 real system): largest differences

ModelWorstPeak depth (worst node)Volume (worst link)
bellinge86,877 %worst of 1020 elements: G71F350 (+8.688e+04 %)worst of 1044 elements: G80F66Yw2 (+1084 %)

OpenSWMM Engine v6, bellinge network (1 real system): largest differences

ModelWorstPeak depth (worst node)Volume (worst link)
bellinge95.1 %worst of 1020 elements: G74F130 (+95.1 %)worst of 1044 elements: G71F05R_skylo1 (-14.16 %)

The self-check (5.2.4 scored against itself) must give exactly 0 on every PR-tier model; CI runs it on every pull request.

Parity over time

One row per nightly run of each candidate (newest first). The result collector appends a row after every nightly run and opens an issue when five or more models move in or out of "within 1 %", when the number of models a candidate cannot run changes, or when its version changes.

DateCandidateVersionModelsWithin 1 %Within 5 %Cannot run
2026-10-17EPA SWMM 5.1.155.1.1550043144821
2026-10-17OpenSWMM Engine v66.0.0a4.dev15003794251
2026-10-17OpenSWMM Engine v6, finite-volume routing6.0.0a4.dev1500414816
2026-10-17Hydra 17 (urban drainage)17.0.0/4.1.15006512518
2026-10-16EPA SWMM 5.1.155.1.1550043044721
2026-10-16OpenSWMM Engine v66.0.0a4.dev15003794251
2026-10-16Hydra 17 (urban drainage)17.0.0/4.1.15006512518
2026-10-15EPA SWMM 5.1.155.1.1550043144821
2026-10-15OpenSWMM Engine v66.0.0a4.dev15003794251
2026-10-15Hydra 17 (urban drainage)17.0.0/4.1.15006512518

history.csv

Does another engine match EPANET 2.2?

The same comparison for water-distribution engines, on the six example networks bundled with WNTR 1.5.0 (EPANET's Net1, Net2, Net3 and Net6 and two Kentucky utility networks), so the set is independent of any candidate's own test fixtures. Each cell gives the worst node's relative peak pressure and the worst pipe's relative volume of |Q| against EPANET 2.2, from scripts/epanet_parity.py.

NetworkHydra 17 water distribution, its defaultsHydra 17 water distribution, EPANET tank stepping (--tank-tolerance 0)EPANET 2.0 (2.00.12), for scale
Net1-0.113 % / 0.0911 %0.0247 % / -0.00401 %0 % / -1.6e-07 %
Net20.0257 % / -0.0631 %0.0257 % / -0.0631 %-3.4e-05 % / -1.6e-05 %
Net3-0.657 % / -4.667 %0.0279 % / -0.0335 %-9.5e-06 % / -7.4e-06 %
Net60.664 % / 26.82 %0.155 % / 3.432 %0.0305 % / -0.0122 %
ky40.0235 % / -0.346 %0.0235 % / -0.346 %0 % / -2e-05 %
ky100.101 % / 0.545 %0.101 % / 0.545 %11.16 % / -0.00271 %
Hydra's tanks are deliberately different. With its default second-order tank integration Hydra matches EPANET 2.2 within 1 % on four networks and differs by up to 27 % in pipe volume on Net6. With EPANET's first-order tank stepping (--tank-tolerance 0) five of six match within 1 % and Net6 within 3.4 %; pressures agree within 0.7 % either way.

Runtime

Runtime on SWMM 5.2.4 of the models that ran (one CPU core)< 0.1 s< 0.1 s: 301 models301301 models0.1–0.3 s0.1–0.3 s: 183 models183183 models0.3–1 s0.3–1 s: 105 models105105 models1–3 s1–3 s: 95 models9595 models3–10 s3–10 s: 118 models118118 models10–30 s10–30 s: 98 models9898 models30–60 s30–60 s: 41 models4141 models

What the tiers cover

Models per tag and tier (24 most common tags)regressionPR tier: 40Nightly tier: 460460Release tier only: 273273Not in a tier: 6236231,396hydraulicsPR tier: 37Nightly tier: 431431Release tier only: 261261Not in a tier: 5865861,315dynamic wavePR tier: 32Nightly tier: 431431Release tier only: 273273Not in a tier: 5535531,289evaporationPR tier: 39Nightly tier: 434434Release tier only: 229229Not in a tier: 5615611,263circular xsectPR tier: 32Nightly tier: 376376Release tier only: 229229Not in a tier: 5505501,187hydrologyPR tier: 25Nightly tier: 210210Release tier only: 137137Not in a tier: 362362734infiltrationPR tier: 25Nightly tier: 207207Release tier only: 134134Not in a tier: 358358724storagePR tier: 24Nightly tier: 188188Release tier only: 9393Not in a tier: 391391696pumpPR tier: 10Nightly tier: 114114Release tier only: 38Not in a tier: 298298460dwfPR tier: 15Nightly tier: 103103Release tier only: 53Not in a tier: 272272443surchargePR tier: 14Nightly tier: 206206Release tier only: 37Not in a tier: 129129386weirPR tier: 13Nightly tier: 8888Release tier only: 48Not in a tier: 197197346orificePR tier: 15Nightly tier: 8989Release tier only: 26Not in a tier: 169169299controlsPR tier: 16Nightly tier: 56Release tier only: 29Not in a tier: 184184285rtcPR tier: 16Nightly tier: 56Release tier only: 29Not in a tier: 184184285floodingPR tier: 10Nightly tier: 162162Release tier only: 18Not in a tier: 8787277flow instabilityPR tier: 11Nightly tier: 135135Release tier only: 26Not in a tier: 9797269force mainPR tier: 3Nightly tier: 67Release tier only: 24Not in a tier: 167167261irregular xsectPR tier: 7Nightly tier: 52Release tier only: 42Not in a tier: 103103204rdiiPR tier: 11Nightly tier: 23Release tier only: 12Not in a tier: 111111157pollutantsPR tier: 13Nightly tier: 47Release tier only: 4Not in a tier: 57121qualityPR tier: 13Nightly tier: 47Release tier only: 4Not in a tier: 57121lidPR tier: 9Nightly tier: 33Not in a tier: 5597kinematic wavePR tier: 5Nightly tier: 26Not in a tier: 5889
  • PR
  • Nightly
  • Release only
  • Not in a tier

Largest routing continuity errors on SWMM 5.2.4

Continuity error is SWMM's own mass-balance check. Models beyond ±5 % are excluded from every tier: their reference results are not physically meaningful, so agreeing with them proves nothing.

ModelRouting continuityRuntime
swmm5-ncimm/1900-nodes-9064495.70 %4.77 s
epa/allow-ponding-high-ce-104835.88 %0.61 s
swmm5-ncimm/392-nodes-30190.04 %34.43 s
swmm5-ncimm/952-nodes-1902.62 %51.71 s
ncimm-routing/daily-rainfall-286.77 %19.49 s
owa-extran/extran7-type3-high-pump-rate-220.03 %0.07 s
epa/attenuation-kw-high-ce-204.95 %29.59 s
swmm5-ncimm/neid3-existingb-m-201.08 %22.80 s
swmm5-ncimm/110-h-elements-196.39 %3.51 s
swmm5-ncimm/3600-h-elements-132.53 %29.93 s
epa/attenuation-dw-high-ce-113.89 %30.22 s
hydrology/kw-no-links-swmm5-runoff+100.00 %0.25 s

Median absolute routing continuity error across models that ran: 0.156 %.

Data

Download the full index as CSV or Parquet. Fetch models with python scripts/fetch_track_b_models.py --tier nightly; every file is checked against its hash.