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River Hydraulics Shallow Water Inversion L1-421

Environmental ScienceHydrologyδ=3 · standardL_DAG = 3📋 Stub — not mineable
📋

Unclaimed Principle — open for contribution

This Principle is declared in the catalog but has no reference solver, no pinned dataset, and is not registered on-chain. There is no reward pool. Submitting a cert against this Principle today will record the cert for reproducibility but pay zero PWM.

To claim it as a Bounty #7 contribution: open a PR adding (1) a reference solver, (2) ≥1 dataset pinned to IPFS, (3) updates to the L3 manifest with dataset CIDs. After verifier-agent triple-review, the founders' 3-of-5 multisig signs PWMRegistry.register() and the Principle becomes mineable.

Forward model E

River Hydraulics Shallow Water Inversion: River hydraulics inversion: infer Manning's roughness and bathymetry from water level and discharge observations. The forward operator produces the measurement through a 3-node primitive DAG (M.swe.saint_venant…); recovery is posed as a parameter_estimation problem. Difficulty tier delta=3 with effective condition number kappa_eff~80; bank_overflow_uncertainty, sediment_transport_coupling set the accuracy floor at the Omega boundary. See the forward_model field for the closed-form equation.

L-DAG

D.space -> O.least_squares.rating_curve -> S.fdm.flood_routing
D.spaceO.least_squares.rating_curveS.fdm.flood_routing

Well-posedness W

Existence:
true
Uniqueness:
true
Stability:
conditional
κ:
2000

Existence of the recovered Manning_roughness_bathymetry is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by declared priors. Stability is conditionally stable (kappa_eff ~= 80); bank_overflow_uncertainty dominates the stability cliff; the remaining mismatch parameters contribute higher-order bias terms. Gaussian sets the irreducible data-fidelity floor.

Solvability C

Solver class:
classical [HEC-RAS or TELEMAC or adjoint_Saint_Venant]
Convergence rate q:
2
Complexity:
O(N_cross_sections * N_timesteps) for 1D routing per iteration

Specs (0)

No L2 specs registered yet for this principle.