Wellhead Delineation

Where does a well’s water actually come from — and why isn’t that the same as where it lowers the water table?

What you’re watching A pumping well between two rivers, with nested colored zones traced by running the flow backward in time — red is the close-in, short-travel-time area; blue is the full area that drains to the well over ten years.

The mechanism Two distinct ideas. The area of influence is where pumping lowers head (the cone of depression). The area of contribution — the capture zone — is where the captured water originates, found by releasing particles at the well and tracking them backward along flow lines. In a uniform aquifer it forms a teardrop reaching up-gradient, not a circle around the well.

Why it matters Confusing the two is the classic mistake. You protect a supply by controlling its area of contribution — the land that drains to it — not the circle where it happens to lower the water table. That is the entire basis of wellhead protection.

IGW-NET Backward particle tracking can’t be watched in a real aquifer. IGW-NET runs the flow in reverse and draws the capture zone as it forms — simulating and seeing in one act — turning an invisible source area into a map you can zone and protect.

How does directional conductivity reshape where a well’s water comes from?

What you’re watching The capture zone in an anisotropic aquifer — stretched and reoriented compared with the isotropic teardrop.

The mechanism Anisotropy steers flow toward the high-conductivity direction, so the capture zone elongates and tilts along that axis. The source area is no longer a simple symmetric tongue.

Why it matters A protection area drawn assuming isotropy can leave the true source land unprotected — and protect the wrong parcels.

IGW-NET Change the conductivity ellipse and watch the capture zone swing to follow — the link between aquifer fabric and source area, visible at once.

Is the capture zone a sharp line, or a fuzzy band?

What you’re watching The capture zone computed with dispersivity included — its edges blur into a gradational boundary rather than a crisp curve.

The mechanism Pure advection (following flow lines) gives a sharp capture boundary. Adding dispersion lets solute cross streamlines, so a parcel just outside the advective capture zone still has some chance of reaching the well — the boundary becomes probabilistic even in a uniform aquifer.

Why it matters Protection zones drawn as hard lines give false confidence; real source areas have fuzzy edges, and contamination just outside a line can still arrive.

IGW-NET Toggle dispersivity and watch the crisp boundary soften — a subtlety obvious on screen and easy to miss on paper.

How does known geology distort the source area?

What you’re watching The capture zone in an aquifer with mapped (deterministic) zones of different conductivity — it bulges through high-K zones and pinches around low-K ones.

The mechanism Capture follows the easy paths. Where conductivity is high, flow lines converge from farther away and extend the capture zone; low-K zones deflect it. The source area mirrors the geology.

Why it matters Delineation that ignores known geology can miss the actual contributing land — the parcels that most need land-use control.

IGW-NET Draw the zones and watch the capture zone deform to match — geology and source area linked in real time.

If we don’t know the exact geology, can we trust a single capture zone?

What you’re watching The capture zone in one random (stochastic) realization of a heterogeneous aquifer — fingered and irregular, following the random high-K paths.

The mechanism Real geology is known only statistically. One realization gives one plausible, fingered capture zone — but it is only one of many consistent with the data.

Why it matters A single heterogeneous delineation looks precise but is just one draw; trusting it can leave real source land unprotected.

IGW-NET Generate a random field and watch the capture zone finger out — then regenerate, and it changes. Uncertainty made visible.

How different can the source area be for the same well and the same statistics?

What you’re watching A second random realization — the capture zone takes a noticeably different shape and reach than Case 1, though the aquifer statistics are identical.

The mechanism Equal-statistics aquifers route capture differently. The spread across realizations is the uncertainty in the source area.

Why it matters This variability is exactly why modern wellhead protection is probabilistic rather than a single line.

IGW-NET Running realization after realization in real time builds an honest intuition for how wide the uncertainty really is.

How do neighboring wells divide up the aquifer between them?

What you’re watching Several wells pumping at different rates, each capturing its own zone; the divides between capture zones shift toward the weaker wells.

The mechanism Each well captures a share set by its rate and position. Stronger wells claim larger capture zones and push the dividing streamlines toward weaker neighbors.

Why it matters In a shared aquifer, one operator’s rate changes what everyone else captures — the quality-side parallel to well interference on the quantity side.

IGW-NET Adjust each well’s rate and watch the capture boundaries migrate live — the negotiation between wells made visible.

What happens to the divides when the pumping mix changes?

What you’re watching The same wellfield with a different distribution of pumping rates; the capture zones and the divides between them rearrange.

The mechanism Capture geometry responds continuously to the pumping pattern — there is no fixed ‘ownership’ of the aquifer, only what the current rates dictate.

Why it matters Managing a wellfield for source-water protection means managing the whole pumping pattern, not each well alone.

IGW-NET Side-by-side real-time runs show how sensitive capture partitioning is to the operating plan.

How does a nearby river or lake change where a well’s water comes from?

What you’re watching Capture-zone delineation with rivers and lakes present; the surface water bounds or feeds the capture zone, truncating it where the well pulls water from the river.

The mechanism A river acts as a constant-head line source/sink. When a well’s capture reaches it, part of the well’s water is captured from the river — induced infiltration — and the up-gradient land capture zone shrinks accordingly.

Why it matters If a well captures river water, river quality becomes the well’s quality concern — and the protection area must include the surface-water source.

IGW-NET Add a river and watch the capture zone snap to it — connecting wellhead protection to the stream–aquifer interaction seen elsewhere.

Seen together, how different are these capture zones?

What you’re watching A side-by-side comparison of capture zones from the preceding cases — homogeneous, anisotropic, heterogeneous — making the differences in shape and reach explicit.

The mechanism Laying the cases together shows that the same well can have very different source areas depending on what is assumed about the aquifer.

Why it matters It underscores why delineation method and data matter — the ‘right’ protection area depends on getting the conceptual model right.

IGW-NET Comparing runs at a glance is what a real-time digital laboratory makes routine — the assumptions become a controlled variable.

If every realization gives a different capture zone, how do we draw one protection area?

What you’re watching Four realizations of a heterogeneous aquifer, each with its own fingered capture zone for the same well — visibly different from one another.

The mechanism No single realization is ‘the’ capture zone. Overlaying many shows where capture happens in most realizations (high probability) versus only a few (low probability) — the raw material for a probabilistic capture zone.

Why it matters Probabilistic capture zones let managers protect land by its likelihood of contributing water — spending protection effort where it most reduces risk.

IGW-NET Accumulating realizations on the fly and tallying capture frequency is how IGW-NET turns Monte Carlo into a usable protection map.

What does a defensible, uncertainty-aware protection area look like?

What you’re watching A single probabilistic capture zone — contours of the probability that water at each location is captured by the well, compiled from many realizations.

The mechanism Each point is colored by the fraction of realizations in which it drains to the well. Inner contours are near-certain source area; outer ones are possible-but-uncertain.

Why it matters This is the modern standard for wellhead protection under real, uncertain geology — honest about what we don’t know, and still actionable.

IGW-NET The probability map emerges directly from re-simulating and tallying — uncertainty quantified by visualization rather than formula.

What exactly is a Wellhead Protection Area — and which concept does it use?

What you’re watching A definitions panel laying out the Wellhead Protection Area (WHPA) and its building blocks: zone of influence, zone of contribution, and time-of-travel zones.

The mechanism The zone of influence is the cone of depression (quantity). The zone of contribution is the capture zone — the land contributing water (quality). Time-of-travel zones subdivide the capture zone by how long water takes to reach the well (1-, 5-, 10-year zones), guiding tiered land-use controls.

Why it matters Regulations base wellhead protection on the zone of contribution and time of travel; confusing it with the zone of influence misdirects protection and money.

IGW-NET Seeing the influence cone and the contribution zone drawn for the same well, side by side, fixes the single most common confusion in the field.

How likely is it that a given parcel actually feeds the well?

What you’re watching A capture-probability map — each location shaded by its probability of contributing water to the well.

The mechanism Built from the realization ensemble, capture probability turns the fuzzy, uncertain source area into a quantitative risk surface that can be thresholded for decisions.

Why it matters It lets a protection program rank land by contamination risk to the well and target monitoring, easements, and restrictions where they pay off most.

IGW-NET Real-time tallying of capture across realizations produces the probability surface directly — the decision-ready end product of the digital laboratory.