First-Principles Deconstruction

The St. Venant Equations
in SWMM5 — Stripped Bare

A rigorous deconstruction of every inherited assumption, convention, and sacred cow baked into how we implement 1D unsteady flow. We separate what physics demands from what engineering tradition chose, then rebuild from bedrock truths alone.

What SWMM5 Actually Solves

SWMM5 solves a discretized version of the 1D Saint-Venant equations over a node-link network representing stormwater and sewer infrastructure. The two governing PDEs are:

── Continuity (mass conservation) ────────────────────── ∂A/∂t + ∂Q/∂x = 0 ── Momentum (Newton's 2nd law for a fluid column) ────── ∂Q/∂t + ∂(Q²/A)/∂x + gA ∂h/∂x + gA S_f = 0 convective pressure gradient friction where: A = flow cross-section area [L²] Q = discharge [L³/T] h = water surface elevation [L] S_f = friction slope (empirical) [-] g = gravitational acceleration [L/T²]

SWMM5 then makes a cascade of implementation choices. Each one feels inevitable. Most aren't.


The Twelve Inherited Assumptions

Every assumption below is widely treated as self-evident. We tag each: Fundamental (physics demands it at this scale), Partial (partially justified, partially convention), or Arbitrary (engineering choice, not physics).

01 One-Dimensional Flow Representation Partial

The Inherited Belief

Flow varies only along the pipe/conduit axis. Velocity is a scalar function of one spatial coordinate and time: v = v(x, t). Cross-sectional quantities (area, depth) are treated as single-valued.

First-Principles Truth

Real flow is 3D Navier-Stokes. The 1D reduction is justified when:

  • Aspect ratio — conduit length >> hydraulic diameter (typically >10:1 in pipes). This is almost always true in sewer/stormwater networks.
  • Dominant flow direction — pressure gradients and inertia primarily align with the conduit axis. Valid for prismatic conduits without severe bends.
  • Cross-sectional mixing — velocity profile shape is approximately self-similar (fully developed turbulent flow). This is reasonable at moderate Reynolds numbers.

Where it breaks: junctions, transitions, inlet structures, surcharging, storage nodes, any location where 3D flow structure dominates. These are precisely the places SWMM5 uses "node" abstractions to punt on the problem.

Verdict

1D is partially fundamental — the aspect ratio of pipes genuinely justifies reduction from 3D. But the specific way SWMM5 collapses cross-sections into a single area-depth curve, and the specific way it handles junctions as zero-volume "nodes," are engineering conventions, not physics. A 1.5D or quasi-2D approach at junctions would be more honest.

02 Hydrostatic Pressure Distribution Fundamental

The Inherited Belief

Pressure at any depth equals ρgh. Vertical acceleration of water is neglected. The pressure term in momentum reduces to gA ∂h/∂x.

First-Principles Truth

This follows from the Froude number being small in the vertical direction — vertical accelerations (including free-surface curvature) are negligible compared to gravity when:

|∂²η/∂x²| · H << 1 (wave curvature × depth is small) For stormwater: H ~ 0.1–3m, pipe length ~ 100m → curvature × depth ~ 0.003–0.3 ✓ almost always valid

Where it breaks: hydraulic jumps, sharp transitions, plunging flow at drop structures, wave breaking. These are all situations where the 1D model is already suspect.

Verdict

Genuinely fundamental at the scales SWMM5 operates. The vertical Froude number in pipes and open channels is almost always ≪ 1. This isn't convention — it's a provable consequence of the geometry. Don't waste time questioning this one.

03 Manning's Equation for Friction Arbitrary

The Inherited Belief

Friction slope is computed via Manning's equation:

S_f = (n² Q |Q|) / (A² R^(4/3)) where: n = Manning's roughness coefficient [T/L^(1/3)] R = hydraulic radius = A/P [L] P = wetted perimeter [L]

First-Principles Truth

The only thing physics demands is that friction dissipates energy. The actual turbulent boundary layer creates a shear stress τ_w on the wetted perimeter. The energy slope is:

S_f = τ_w / (ρgR) (this is definitional, always true) The question is: how do we model τ_w?

Manning's equation is one of several empirical correlations. It assumes:

  • Fully rough turbulent flow (Reynolds number independence)
  • Roughness is characterized by a single scalar n
  • n is constant with depth (often false — composite channels)
  • The velocity profile follows a power-law shape implied by n
  • The 6/10 exponent on R is empirical, not derived

Alternatives that are equally (or more) physically grounded:

  • Darcy-Weisbach: S_f = f·(V²/2gR) — connects to Moody diagram, Reynolds-number dependent
  • Colebrook-White: implicit form, more accurate in transition regime
  • Nikuradse: explicit for fully rough regime
Verdict

Purely arbitrary. Manning's n is a 19th-century empirical fit. It works well in the range it was calibrated for (full-pipe turbulent flow in rough conduits). But it's not fundamental — it's a curve fit with a specific functional form that happens to be convenient. The Darcy-Weisbach formulation is more physically transparent and connects to fluid mechanics fundamentals. SWMM5's choice of Manning is tradition, not truth.

04 Kinematic / Diffusion Wave Simplification Arbitrary

The Inherited Belief

SWMM5 offers three wave formulations. Most users select kinematic wave (the default), which drops most of the momentum equation:

── Full Dynamic Wave ────────────────── ∂Q/∂t + ∂(Q²/A)/∂x + gA∂h/∂x + gAS_f = 0 ── Diffusion Wave (drop inertia) ────── gA∂h/∂x + gAS_f = 0 ⟹ S_f = -∂h/∂x ── Kinematic Wave (drop inertia + pressure) ── S_f = S_0 ⟹ friction slope = bed slope No backwater effects. No flow reversal. No storage.

First-Principles Truth

The momentum equation has four terms. Each represents a physical force balance:

  • ∂Q/∂t — local acceleration (temporal inertia)
  • ∂(Q²/A)/∂x — convective acceleration
  • gA∂h/∂x — pressure gradient (gravity + hydrostatic)
  • gAS_f — friction resistance

Dropping terms is justified when their ratio to the dominant terms is small. The relevant dimensionless numbers:

── Froude Number ────────────────────── Fr = V / √(gD) Fr << 1: subcritical, pressure dominates Fr >> 1: supercritical, inertia dominates Fr ≈ 1: critical, all terms comparable ── Kinematic Wave Number ────────────── k = S_0 · L / (Fr² · D) k >> 1: kinematic wave valid k ~ 1: diffusion wave needed k << 1: full dynamic wave needed

The kinematic wave is valid only when: steep slopes, long reaches, no downstream control, no backwater. For flat-gradient sewers (common!), it's wrong.

Verdict

Arbitrary and often wrong. The kinematic wave is the default because it's numerically stable and fast, not because it's correct. For the majority of urban drainage systems with flat slopes, backwater effects from downstream controls (outfalls, weirs, pumps) dominate. Using kinematic wave in these systems isn't simplification — it's error. The full dynamic wave should be the default; kinematic should be the opt-in for steep, long reaches.

05 Preissmann Slot for Pressurized Flow Arbitrary

The Inherited Belief

When a closed conduit is full, SWMM5 inserts a narrow hypothetical slot (Preissmann slot) on top of the cross-section to maintain a free-surface representation:

── Standard cross-section ──────────── Area = f(depth) for depth ≤ crown ── With Preissmann slot ─────────────── Area = A_conduit + W_slot × (depth - crown) for depth > crown where W_slot is very narrow (~1% of conduit width)

This avoids a discontinuity in the governing equations at the transition between open-channel and pressurized flow.

First-Principles Truth

Physics doesn't care about equation continuity. When a pipe is full:

  • The free surface ceases to exist — there's no ∂h/∂x in the usual sense
  • Pressure becomes the independent variable, not depth
  • Acoustic waves (pressure transients) propagate at c ≈ √(K/ρ) ≈ 1400 m/s
  • Water hammer dynamics become relevant

The Preissmann slot artificially slows these pressure waves to the speed of the "slot wave" (~10–50 m/s), which is orders of magnitude slower than real pressure transients.

Verdict

Arbitrary numerical convenience. It works adequately for slowly-varying surcharge conditions. But it fundamentally cannot capture water hammer, rapid filling events, or the true transient pressure dynamics that damage infrastructure. Alternative approaches (characteristic method, shock-capturing schemes, or explicit free-surface/pressurized switching) are more physically honest but harder to implement. The slot is a pragmatic hack, not a physical model.

06 Node-Link Network Topology Arbitrary

The Inherited Belief

The drainage system is represented as a graph: nodes (junctions, storage units, outfalls) connected by links (conduits, pumps, orifices, weirs). Mass is conserved at nodes; momentum is solved along links.

[Inflow] ──→ (Node) ──→ [Conduit] ──→ (Node) ──→ [Conduit] ──→ (Outfall) Node: stores mass, zero volume (except storage nodes) Link: carries flow, has geometry, solves momentum

First-Principles Truth

Real junctions have finite volume, 3D flow patterns, energy losses, and flow separation. The node-link abstraction:

  • Treats junctions as dimensionless points (mass in = mass out instantaneously)
  • Requires ad-hoc "loss coefficients" at junctions (K values) that are poorly characterized
  • Creates artificial numerical issues at junctions (sudden area changes, reflection of waves)
  • Cannot represent manhole hydraulics, drop structures, or complex junction chambers
Verdict

Arbitrary graph abstraction. The real system is a connected volume, not a graph. The node-link split forces mass conservation into nodes and momentum conservation into links, creating artificial boundaries where physics demands continuity. A finite-volume approach that treats the entire network as interconnected control volumes would be more physically natural. The node-link convention persists because it maps to CAD/GIS workflows and makes input data manageable — not because it reflects hydraulic reality.

07 Finite-Difference Spatial Discretization Arbitrary

The Inherited Belief

Each conduit is divided into N computational reaches. Derivatives are replaced by finite differences:

∂Q/∂x ≈ (Q_j - Q_{j-1}) / Δx (backward difference) ∂h/∂x ≈ (h_{j+1} - h_j) / Δx (forward difference)

First-Principles Truth

The PDE is continuous. Any discretization is an approximation. Alternatives:

  • Finite Volume: conserves mass/momentum by construction; handles shocks naturally
  • Finite Element: better for complex geometries; natural for adaptive refinement
  • Spectral methods: exponential convergence for smooth solutions
  • Smooth Particle Hydrodynamics: mesh-free, handles large deformations
Verdict

Arbitrary numerical method choice. Finite difference is the simplest to implement and understand, which is why SWMM5 uses it. Finite volume would be more physically honest (it enforces conservation laws at the discrete level by construction, not by hoping the discretization is fine enough). The choice affects accuracy, stability, and conservation properties — but not the underlying physics being approximated.

08 Implicit Time Integration (Preissmann Scheme) Partial

The Inherited Belief

SWMM5 uses a weighted implicit scheme where spatial derivatives are evaluated at time level n+θ:

∂f/∂x |_{n+θ} = θ · ∂f/∂x |_{n+1} + (1-θ) · ∂f/∂x |_n θ = 0.5: Crank-Nicolson (2nd order, conditionally stable) θ = 1.0: Fully implicit (1st order, unconditionally stable) SWMM5 uses θ ≈ 0.55–0.6 typically

First-Principles Truth

Time integration is a numerical artifact. Physics is continuous in time. The choice of scheme affects:

  • Stability: implicit schemes allow larger Δt (Courant number > 1)
  • Accuracy: Crank-Nicolson is 2nd-order but can produce oscillations
  • Numerical diffusion: fully implicit adds artificial viscosity
  • Computational cost: implicit requires solving a linear system each step
Verdict

Partially fundamental. The need to discretize in time is fundamental (we can't solve continuous PDEs on computers). But the specific scheme, weighting parameter, and time step are all trade-offs between accuracy, stability, and cost. The implicit choice is justified by the Courant number variability in sewer networks (reaches of different lengths, depths, velocities). But it introduces numerical diffusion that can smear flood peaks — a real physical error, not just a numerical artifact.

09 Incompressible Flow Fundamental

The Inherited Belief

Water density ρ is constant. The continuity equation uses ∂A/∂t + ∂Q/∂x = 0, not the compressible form with ∂ρ/∂t.

First-Principles Truth

The Mach number in stormwater systems:

Ma = V / c_sound ≈ (1–5 m/s) / 1400 m/s ≈ 0.001–0.004 For Ma < 0.3, incompressible assumption introduces < 3% error. At Ma ~ 0.003, the error is negligible.

Exception: during water hammer (rapid valve closure), pressure waves propagate at the true sound speed, and compressibility matters. But SWMM5 can't handle this anyway (see Preissmann slot).

Verdict

Genuinely fundamental at normal operating conditions. Mach numbers are ≪ 0.1. Compressibility is irrelevant except during transient events that the model can't capture regardless. Don't question this one.

10 Uniform Velocity Across Cross-Section Partial

The Inherited Belief

Q = VA, where V is a single velocity value. The actual velocity profile (parabolic in laminar, logarithmic/power-law in turbulent) is collapsed to one number via the "energy coefficient" or "Boussinesq coefficient":

α = (1/A) ∫(v/V)³ dA (Coriolis coefficient, kinetic energy correction) β = (1/A) ∫(v/V)² dA (Boussinesq coefficient, momentum correction) SWMM5 implicitly sets α = β = 1 (uniform velocity). Real turbulent pipe flow: α ≈ 1.03–1.10, β ≈ 1.01–1.05

First-Principles Truth

The velocity profile is determined by the balance of turbulent shear stress, wall roughness, and pressure gradient. It's never truly uniform. But:

  • For fully rough turbulent flow (high Re), the profile flattens and α → 1
  • The correction factors are small (3–10%) for typical pipe flows
  • At junctions, transitions, and partially-filled pipes, the profile is highly non-uniform
Verdict

Partially justified. The correction factors are small for fully-developed turbulent pipe flow, so α = β = 1 is a reasonable approximation. But the assumption silently fails at every junction, transition, and partially-filled section — precisely where the node-link abstraction already struggles. The error is small in magnitude but systematic (it underestimates momentum flux).

11 Rigid Boundaries (No Sediment / Morphology) Arbitrary

The Inherited Belief

Conduit geometry is fixed. Roughness coefficients are constant. The bed doesn't erode, deposit, or change shape. Sediment transport is ignored or handled externally.

First-Principles Truth

Flow exerts shear stress on the bed. When τ > τ_critical, sediment moves. This changes:

  • Cross-sectional geometry (aggradation/degradation)
  • Roughness (sediment bedforms change n or f)
  • Capacity (deposited sediment reduces area)

For many systems (combined sewers, channels with significant sediment), this is a first-order effect on long-term performance.

Verdict

Arbitrary scope limitation. SWMM5 is a hydraulic model, not a morphodynamic model. This is a legitimate engineering scope choice. But it means the model can't answer "how does system capacity change over decades?" — a question that matters for asset management. Coupling with sediment transport models is possible but not built-in.

12 Quasi-Steady Friction in Unsteady Flow Arbitrary

The Inherited Belief

Friction is computed using the steady-flow Manning/Darcy-Weisbach formula at each time step, as if the flow were steady. The instantaneous Q and A go into the friction formula.

First-Principles Truth

In unsteady flow, the velocity profile lags behind the bulk flow. The actual friction includes:

  • Quasi-steady component: same as steady-flow friction at instantaneous Q
  • Unsteady component: convolution integral of past accelerations (history effect)
  • Wall shear stress memory: the boundary layer takes time to adjust

The unsteady friction correction can be 5–20% of total friction during rapid transients.

Verdict

Arbitrary simplification. For slowly-varying hydrographs (typical storm events), quasi-steady friction is adequate. For rapid transients (pump start/stop, valve closure, rapid filling), it introduces systematic error. Models like Brunone or Vardy-Brown unsteady friction models exist but add significant computational cost.


Bedrock Truths — What Survives

After stripping away every convention, here is what is provably, physically, mathematically true about 1D unsteady flow in conduits:

1

Mass is conserved in every control volume.

For any fixed volume V in the system: rate of mass in − rate of mass out = rate of mass accumulation. This is Newtonian physics. No exceptions at these scales. The integral form ∮ ρv·dA + ∂/∂t ∫ρ dV = 0 is exact.

2

Momentum changes equal net forces (F = ma).

For a fluid control volume: d(momentum)/dt = Σ forces. Forces include: gravity (body force), pressure on all surfaces (including walls), and wall shear stress. This is exact. The challenge is representing each force term accurately in 1D.

3

Gravity acts downward with magnitude g.

The gravitational body force on a fluid element is ρgV, directed vertically downward. In the momentum equation, this projects onto the conduit axis as ρgA·S_0 (bed slope component). Exact.

4

Pressure is hydrostatic in the vertical (at these scales).

Proven: vertical Froude number ≪ 1 for all practical pipe/channel flows. Pressure at depth h below the surface = ρgh. This reduces the pressure force to gA·(∂h/∂x). This is not an approximation — it's a provable consequence of the geometry.

5

Wall shear stress dissipates energy.

τ_w exists on every wetted surface. The energy dissipation rate = τ_w · V · P · L (shear × velocity × perimeter × length). The force on the fluid is τ_w · P · L directed opposite to flow. This is exact. The only question is how to model τ_w as a function of flow state.

6

Flow cross-sections have geometry: A(h), P(h), and their derivatives.

Any conduit has a shape. Given water depth h, the area A and wetted perimeter P are deterministic functions. The top width T = dA/dh. These are geometric facts, not physical assumptions.

7

Energy is conserved (1st law of thermodynamics).

Total mechanical energy + dissipated energy = input energy. In practice, this manifests as the energy grade line (EGL) declining in the flow direction at rate S_f. The EGL equation H = z + h + αV²/2g is a statement of energy conservation.

── The bedrock system (exact in 1D) ────────────────── Mass: ∂A/∂t + ∂Q/∂x = q_lateral Momentum: ∂Q/∂t + ∂(βQ²/A)/∂x + gA∂h/∂x + gAS_f = 0 ── where S_f must be modeled ────────────────────────── S_f = τ_w / (ρgR) (exact definition) τ_w = f(Re, ε/D, flow_history) × ½ρV² (must be modeled) ── Geometry (exact for any shape) ──────────────────── A = A(h), P = P(h), T = dA/dh, R = A/P

Rebuilt From Bedrock

Starting from only the seven truths above, here is the minimal viable model and its invariants.

Minimal Viable Model

── Control Volume Formulation ──────────────────────── Replace node-link graph with explicit control volumes. Each CV has: geometry, state (A, Q), connections to neighbors. State vector per CV: [A, Q] or equivalently [h, V] ── Evolution (per time step Δt) ────────────────────── For each control volume i: Mass: A_i^{n+1} = A_i^n + (Δt/Δx_i) × (Q_in - Q_out) + Δt × q_i Mom: Q_i^{n+1} = Q_i^n + Δt × F_net_i / m_i where F_net includes: + gravity: ρg A_i S_{0,i} pressure: ρg A_i (h_{i+1} - h_{i-1}) / (2Δx) friction: τ_{w,i} × P_i × Δx ± convective: computed from Q²/A fluxes at CV faces

Key Invariants (What the Model Must Preserve)

Invariant 1

Mass conservation is exact at the discrete level. Total water volume in system = initial volume + ∫(inflow − outflow) dt. This must hold to machine precision, not just approximately.

Invariant 2

Energy dissipation is non-negative. S_f must have the same sign as Q (friction always opposes flow). The model must never create energy from friction.

Invariant 3

Monotonicity of area-depth. dA/dh = T ≥ 0 (more depth = more area). The cross-section geometry must be physically realizable.

Invariant 4

Causality. Information propagates at finite speed (≤ celerity of gravity waves √(gD) or pressure waves √(K/ρ)). No instantaneous action at a distance.

Invariant 5

Positivity. A ≥ 0, h ≥ 0. Negative depths are unphysical. The numerics must enforce this.

Invariant 6

Galilean consistency. Adding a uniform velocity to the entire system should not change the relative dynamics. The equations are frame-invariant.

Necessary Trade-Offs

No model avoids trade-offs. But we can be honest about what we're trading:

Trade-Off Option A Option B What Determines the Choice
Dimensionality 1D (fast, scalable) 2D/3D (accurate at junctions) Aspect ratio of conduits; junction complexity
Friction model Algebraic (Manning, D-W) History-dependent (unsteady friction) Rate of flow change; accuracy needs
Time stepping Implicit (large Δt, stable) Explicit (small Δt, accurate transients) Courant number variation; transient importance
Spatial discretization Structured (simple, fast) Adaptive (accurate where needed) Flow regime gradients; computational budget
Pressurization Smooth transition (slot) Sharp interface (front-tracking) Importance of transient pressure; water hammer risk

Cleanest Expression of the Domain

If we could design the ideal computational framework from scratch, ignoring all legacy code:

── Ideal Architecture ───────────────────────────────── 1. CONSERVATION-VOLUME MESH Not a node-link graph. A mesh of control volumes where each CV has geometry, state, and flux connections. Junctions are explicit CVs with 3D-inspired loss models. 2. FINITE-VOLUME DISCRETIZATION Mass and momentum conservation enforced at the CV level. Fluxes computed at faces using Riemann solvers. Guarantees discrete conservation by construction. 3. ADAPTIVE WAVE RESOLUTION Full dynamic wave everywhere by default. Automatic detection of kinematic/diffusion wave regions (where the solution is smooth and slopes are steep). Reduction is automatic, not user-selected. 4. PHYSICS-BASED FRICTION Darcy-Weisbach with Moody/Colebrook-White. Re-dependent (captures laminar/turbulent transition). Optional unsteady correction for rapid transients. Manning available as a legacy convenience layer. 5. EXPLICIT PRESSURE TRANSITION Free-surface and pressurized flow handled by different equation sets with a sharp, tracked interface. Pressure wave speed = true acoustic speed. Water hammer captured naturally. 6. COUPLED TIME INTEGRATION Adaptive time stepping based on CFL condition. Higher-order scheme (RK4 or SSP-RK3) for smooth regions. TVD limiting near shocks/discontinuities.

Legacy vs. Rebuilt — Side by Side

Aspect SWMM5 / Conventional Rebuilt from First Principles
Network representation Node-link graph. Junctions = dimensionless points. Mass balance at nodes, momentum in links. Control volume mesh. Junctions = explicit volumes with loss physics. No artificial mass/momentum split.
Default wave type Kinematic wave (user must opt-in to dynamic). Backwater effects require explicit choice. Full dynamic wave everywhere. Automatic reduction to diffusion/kinematic where physics allows.
Friction Manning's n (empirical, Re-independent, constant-n assumption). Darcy-Weisbach with Moody. Re-dependent. Composite roughness for irregular sections.
Pressurization Preissmann slot (artificial narrow slot, slows pressure waves by 100×). Explicit free-surface/pressurized interface. True acoustic wave speed. Water hammer capable.
Discretization Finite difference. User specifies number of reaches per conduit. Finite volume with Riemann solver. Adaptive refinement. Conservation by construction.
Time integration Weighted implicit (θ ≈ 0.55). Fixed time step. Numerical diffusion at high Courant numbers. Adaptive explicit/implicit hybrid. CFL-limited Δt. TVD limiting for sharp fronts.
Junction losses User-specified K coefficients (often guessed or defaulted to 0). Physics-based loss models from junction geometry. Borda-Carnot, expansion/contraction, bend losses computed from geometry.
Cross-section Pre-defined shapes (circular, rectangular, trapezoidal, etc.) with lookup tables. Arbitrary polygonal cross-sections. Moment-based properties. Composite roughness per segment.
Conservation Approximate. Mass errors can accumulate. Momentum conservation not guaranteed at discretization level. Exact at machine precision. Finite volume guarantees discrete conservation.

What Becomes Optional or Obsolete

Obsolete

User selection of wave type. The solver should determine when kinematic/diffusion approximations are valid based on local flow conditions (Fr, k). Users shouldn't have to know about wave types.

Obsolete

Preissmann slot. Replaced by explicit interface tracking. The slot was always a hack; removing it unlocks real transient analysis.

Obsolete

Manual reach discretization. Users specify "number of computational reaches" per conduit — a numerical parameter masquerading as a physical one. Adaptive refinement makes this automatic.

Optional

Manning's n. Still usable as a convenience input (auto-converted to equivalent Darcy-Weisbach f), but no longer the primary friction parameter. D-W is the native format.

Optional

Junction K-loss coefficients. Still overridable, but the default is computed from junction geometry. Most users currently guess these anyway.

Obsolete

The node-link mental model. Replaced by the control-volume mesh. This changes how users conceptualize their system — from a "plumbing diagram" to a "connected volume field."


New Capabilities Unlocked

I Real Transient / Water Hammer Analysis

With explicit pressure-wave propagation (true c ≈ 1400 m/s), the rebuilt model can answer:

  • What happens when a pump trips? (pressure surge magnitude, reflection timing)
  • What's the maximum transient pressure in a force main?
  • Do we need a surge tank? What size?

Currently, these questions require a separate model (e.g., HAMMER, Wanda). The rebuilt architecture handles them natively.

II Adaptive Resolution — "Smart" Wave Selection

Instead of the user choosing kinematic/diffusion/dynamic, the solver monitors:

Local Fr = V/√(gD) Local k = S_0·L / (Fr²·D) ∂h/∂x magnitude (backwater indicator) Courant number Co = (V + √(gD))·Δt/Δx

and automatically uses the minimum-fidelity solver that maintains accuracy. Steep, long reach with Fr >> 1? Kinematic wave. Flat reach with downstream weir? Full dynamic. This gives the speed of kinematic with the accuracy of dynamic, without user intervention.

III Guaranteed Conservation — Trustworthy Mass Balance

Finite volume discretization means mass is conserved to machine precision regardless of grid resolution, time step, or flow regime. No more mysterious "mass balance errors" in SWMM5 reports. This is critical for:

  • Regulatory compliance (permit reporting requires mass balance closure)
  • Long simulations (small errors accumulate over days/weeks of continuous modeling)
  • Calibration (you can trust that discrepancies are physical, not numerical)
IV Junction Physics — No More K-Coefficient Guessing

Junctions modeled as explicit control volumes with:

  • Borda-Carnot losses from area expansion: K = (1 - A₁/A₂)²
  • Contraction losses: K from empirical curves as function of A₂/A₁
  • Bend losses: K from bend angle and R/D ratio
  • Momentum mixing at confluences: computed from junction geometry and angle

All computed from geometry. Users input the physical junction shape, not a guessed K.

V Composite Cross-Sections with Segment-Specific Roughness

Real channels are rarely one material. A natural channel might have:

┌─────────────────────────────┐ vegetation (n=0.05) ← floodplain concrete (n=0.013) ← main channel gravel (n=0.030) ← invert └─────────────────────────────┘

The rebuilt model computes A, P, and effective roughness per segment, then combines using Einstein's divided-channel method or Lotter's method — not a single averaged n.

VI Unified Open-Channel / Pressurized / Transient Solver

One solver handles the full spectrum:

  • Dry → partially full (open channel)
  • Partially full → full (filling transition)
  • Full, steady (pressurized flow)
  • Full, transient (water hammer, pump trip)
  • Full → partially full (emptying transition, column separation)

No mode switching, no separate models, no slot hacks. The same equations, with the same conservation guarantees, across all regimes.


The Scorecard

Assumption Status Why
1D flow Keep (modified) Aspect ratio justifies it in conduits. Add quasi-2D at junctions.
Hydrostatic pressure Keep Vertically proven at these scales. Fundamental.
Manning's friction Replace Arbitrary empirical form. D-W is more physically transparent.
Kinematic wave default Replace Wrong for flat slopes. Auto-detect instead of user choice.
Preissmann slot Replace Numerical hack. Explicit interface tracking is more honest.
Node-link topology Replace Arbitrary graph abstraction. CV mesh is more physical.
Finite difference Replace Doesn't guarantee conservation. Finite volume does.
Implicit time stepping Modify Keep implicit capability, add adaptive explicit for transients.
Incompressible flow Keep Mach ≈ 0.003. Error < 0.001%. Fundamental.
Uniform velocity Keep (modified) α, β corrections small for pipe flow. Add at junctions.
Rigid boundaries Scope choice Legitimate for hydraulics. Add coupling for morphodynamics.
Quasi-steady friction Modify Fine for storms. Add unsteady correction for transients.
Summary

Of 12 inherited assumptions: 3 are genuinely fundamental (hydrostatic pressure, incompressibility, 1D reduction at conduit scale). 3 are partially justified (implicit time stepping, uniform velocity, quasi-steady friction). 6 are arbitrary conventions that persist because of legacy code, pedagogical inertia, and the path of least resistance — not because physics demands them.

The rebuilt model is not more complex — it's more honest. It uses the same two PDEs. It just refuses to pretend that engineering shortcuts are physical laws.