Stripping every inherited assumption from Rainfall-Dependent Infiltration & Inflow modeling. What survives is what's real. Everything else was a choice.
What almost everyone takes for granted when working with RDII. Each of these is treated as "how it works" when it's actually "how we chose to model it."
Convention: RDII response is a triangular unit hydrograph parameterized by R (fraction), T (time-to-peak), K (recession ratio). Up to three triangles per month.
Why it's inherited: Chosen in the 1990s for computational simplicity and parameter identifiability. Three calibration-friendly parameters became "the RDII method" — not because sewers produce triangles.
Convention: Double the rain, double the RDII. Responses superimpose additively.
Reality: Saturated soil, surcharged pipes, and flooded depressions are nonlinear and state-dependent.
Convention: I/I taught as two categories. The mental model persists even though SWMM5's RTK lumps them.
Reality: A cracked joint at 4 ft is "infiltration" in dry weather and "inflow" when the depression fills. The boundary is a continuum.
Convention: RTK varies by calendar month — 12 discrete states that jump on the 1st.
Reality: Soil moisture is a continuous function of antecedent rain, ET, and temperature — not a step function.
Convention: One RTK set represents an entire sewershed.
Reality: Clay/VCP/shallow GW on one end vs. sand/PVC/deep GW on the other does not have one response.
A 3-week drought in March ≠ a 3-day gap between storms in March. Antecedent moisture is event-specific, not month-specific.
Unit hydrograph theory assumes return to baseline. But GW mounding persists for days. Baseflow-like sustained RDII between events is common.
Tidal fluctuations, snowmelt, irrigation, rising GW, barometric pressure — all can drive water into pipes. Rainfall is dominant but not exclusive.
With 3–9 free parameters per month, equifinality is rampant. Many parameter sets produce similar fits. Calibrated parameters may not be physically meaningful or transferable.
Treating the pipe boundary as the model boundary discards all mechanistic information about the soil-pipe continuum.
What is fundamentally, provably true — independent of SWMM5, RTK, or any framework.
Every molecule of water that enters a pipe came from somewhere through some pathway. Mass balance is inviolable.
V_rain = V_runoff + V_evap + V_ET + V_soil_infil + V_RDII + V_other
At the pipe boundary:
V_RDII = V_gw_in + V_surface_in + V_depression_in + V_other_entries
Q_RDII ∝ f(H_soil - H_pipe, K_soil, defect_geometry)
This is Darcy's Law + orifice/weir at defects.
Not a triangle. Not a unit hydrograph. Physics.
Soil state S(t) ∈ [0, S_max]
dS/dt = P(t) - ET(t) - K(S)·∇H - Q_deep
K(S) is highly nonlinear (exponential in many models)
The soil's "unit hydrograph" changes shape with state.
For defect at depth d:
Q_defect = C_d · A_defect · √(2g · ΔH) [orifice]
Q_defect = C_w · L_defect · (ΔH)^1.5 [weir]
Total RDII = Σ Q_defect(i) — additive but NOT linear in rainfall.
GW elevation is spatially and temporally continuous. It responds to recharge, discharge, and regional flow.
Depressions, direct connections, and surcharged conditions create direct hydraulic pathways — separate from subsurface but physically connected at the surface.
Soil moisture, GW elevation, and surface conditions are continuous functions. Monthly discretization is a convenience, not physics.
Pipe age, material, soil type, water table depth, land use, and connection density all vary spatially. This is measurable.
The simplest physically-grounded RDII model needs:
// STATE VARIABLES (per spatial unit)
S(t) // soil moisture [0, S_max]
H_gw(t) // groundwater head [m]
// FORCING
P(t) // rainfall intensity [m/s]
ET(t) // evapotranspiration [m/s]
H_pipe(t) // pipe head [m] (from flow model)
// 1. Soil moisture balance
dS/dt = P(t)·f_inf(S) − ET(t) − K_sat·g(S)·(∂H/∂z)
f_inf(S) = (1 − S/S_max)^β // Green-Ampt-like
g(S) = exp(α·(S − S₀)) // relative conductivity
// 2. Groundwater (simplified lumped)
dH_gw/dt = (1/S_y)·[K_sat·g(S)·(∂H/∂z) − Q_drain(H_gw)]
// 3. RDII transfer
ΔH(t) = max(0, H_gw(t) − H_pipe(t))
Q_rdii(t) = C·A_defects·√(2g·ΔH(t))
// 4. Surface direct inflow
Q_direct(t) = η·[P(t) − f_inf(S)·P(t)]
// TOTAL
Q_total(t) = Q_rdii(t) + Q_direct(t)
| Trade-off | Simplified | Kept |
|---|---|---|
| Lumped vs. distributed soil | Spatial variability | State-dependent nonlinear response |
| 1D groundwater | Full 3D GW flow | Head-driven flow with storage |
| Effective defect area | Individual crack geometry | Aggregate orifice behavior |
| Simplified ET | Full energy balance | Seasonal drying capacity |
| No explicit surface routing | 2D surface hydraulics | Depression storage → direct connection |
| Legacy Element | Status | Why |
|---|---|---|
| Triangular unit hydrograph | Obsolete | Shape emerges from soil/GW physics, not assumed. |
| R, T, K parameters | Obsolete | Replaced by measurable physical properties. |
| Monthly parameter tables | Obsolete | Continuous state evolution. Seasonality from ET(T). |
| Up to 3 superimposed triangles | Obsolete | Complex shapes produced directly by the physics. |
| Event separation | Obsolete | Continuous simulation eliminates inter-event assumptions. |
| Calibration-only parameters | Replaced | Lab tests, soil surveys, CCTV, literature all constrain values. |
| RDII as black-box input | Obsolete | Mechanistic output of coupled soil-GW-pipe physics. |
With soil surveys, pipe inspection, and GW monitoring — estimate RDII for unmonitored sewersheds. RTK requires flow monitoring; there is no un-calibrated RTK prediction.
GIS data on soil, pipe age/material, and water table depth → spatially explicit RDII potential maps for targeted rehabilitation.
Natural coupling with 2D surface and 3D GW models. Enables surcharge-induced exfiltration, bidirectional phenomena.
ET has a diurnal cycle. Tidal influence has sub-daily cycles. The continuous model captures these naturally.
Include time-dependent A_defects(t) that grows with age. Predict when rehabilitation becomes cost-effective.
| Aspect | Legacy | Rebuilt |
|---|---|---|
| Coupling | One-way: rain → RDII → pipes | Two-way: pipes ↔ soil ↔ atmosphere |
| State | Stateless (memoryless UH) | Stateful (S, H_gw evolve continuously) |
| Temporal | Event-based with gaps | Continuous |
| Spatial | Lumped per sewershed | Distributed (as fine as data supports) |
| Modularity | Monolithic RTK block | Separable modules |
| Extensibility | Cannot add new forcings | Any forcing → state equations |
| Data integration | Needs flow monitoring | Soil data, CCTV, GW monitoring, flow |
class RDIISoilGWModel {
S, H_gw // state
S_max, K_sat, S_y, A_defects, C_d // physical params
step(P, ET, H_pipe, dt) {
f_inf = (1 - S/S_max)^1.5
I = P * f_inf
K_rel = exp(10 * (S - 0.7))
drain = K_sat * K_rel
S += (I - ET - drain) * dt
H_gw += (drain/S_y - 0.01*(H_gw - H_base)) * dt
dH = max(0, H_gw - H_pipe)
return C_d * A_defects * sqrt(2*9.81*dH) + η*P*(1-f_inf)
}
}
~15 lines of core logic. RTK is similarly compact — but this captures physics RTK structurally cannot represent.
See the difference. The rebuilt model shows less RDII for the first storm (dry soil) and more for subsequent storms (wet soil). RTK produces the same response every time.
| Element | Status | Verdict |
|---|---|---|
| Conservation of mass | fundamental | Non-negotiable. |
| Head-driven flow through defects | fundamental | Darcy + orifice/weir. Cannot be simplified away. |
| Soil as stateful nonlinear reservoir | fundamental | The mechanism that creates the hydrograph shape. |
| Triangular unit hydrograph | arbitrary | 1930s convenience. Sewers don't produce triangles. |
| R, T, K parameterization | arbitrary | Calibratability, not physical meaning. |
| Monthly parameter variation | arbitrary | Discretization hack. System is continuous. |
| Linear superposition | arbitrary | Violated by every nonlinear soil in existence. |
| Rainfall as sole forcing | arbitrary | Dominant but not exclusive. |
| SWMM5's computational architecture | arbitrary | 1980s constraints. We can do better now. |