How to estimate people served per borehole from a point inventory

A point inventory gets you most of the way to a coverage number, but not all the way. You've got coordinates, a capture date, and maybe a photo if the field team was thorough. What you don't have, straight out of the file, is who each point serves on the ground. That takes a second step: turning points into catchment areas, then overlaying population.

This is the calculation behind every "X people per water point" figure in a district WASH plan, and it's worth knowing how it's built, because the shortcuts people take change the number a lot.

Drawing the catchment: radius versus Thiessen

The simplest approach is a fixed-radius buffer around each point. Sphere standards use 500 m as the maximum acceptable walking distance to a water source in most contexts, tighter in dense urban settlements, looser in dispersed rural ones. Draw a 500 m circle around each borehole, clip it to the settlement boundary, and you've got a rough service area.

The problem with fixed radii shows up where points are unevenly spaced. Two boreholes 300 m apart end up with overlapping circles and double-counted population. A borehole sitting alone at the edge of a catchment gets a full circle even though half of it falls outside any settlement at all.

Thiessen polygons (also called Voronoi polygons) fix the overlap problem by splitting the whole area between points based on proximity, so every parcel of land belongs to its nearest water point and nothing is counted twice. It's the better method for district-level ratios, though it still assumes people walk to the nearest point rather than the one with better yield or shorter queue, which isn't always true on the ground.

For a first-pass estimate, start with Thiessen and clip to a reasonable walking-distance limit. That gets you catchments that don't overlap and don't stretch across half the district because of one isolated borehole.

Overlaying population and getting the ratio

Once you have catchment boundaries, the ratio itself is arithmetic: population inside the catchment, divided by the number of functional points inside it. The harder part is the population side.

Census enumeration areas are the standard reference where they're current and line up with where people live right now. In a lot of under-mapped districts they're neither, census boundaries lag migration and informal settlement growth by years. Gridded population datasets like WorldPop or LandScan fill that gap: pick a grid resolution, sum the cells that fall inside each catchment polygon, and you've got a population figure that doesn't depend on administrative boundaries being redrawn on your schedule.

Sum the population per catchment, divide by points serving that catchment (usually one, if you built Thiessen polygons correctly), and you get people served per borehole for that specific catchment, not a district-wide average that hides which pumps are overloaded and which are barely used.

One thing a point inventory from aerial or satellite imagery can't tell you is functionality. A borehole and a handpump stand show up on the imagery whether the pump works or not. The ratio you calculate from an unfiltered inventory is people per mapped water point, not people per working water point, and those two numbers can be very different in a district that hasn't had a functionality survey in a while. Flag that distinction when you present the number, or someone downstream will treat it as a service-level figure it isn't.

Where to start if you don't have the points yet

None of this works without a current, geolocated list of boreholes to begin with, and in a lot of districts that list is the actual bottleneck, not the GIS. A point inventory built from an annual high-resolution imagery pass gives you dated coordinates for every borehole, tank stand, and latrine block visible on the ground, exportable as GeoJSON or CSV, which is what the catchment and population steps above need as input before a field team ever gets deployed.

If your district doesn't have that starting list yet, that's the gap Sanitation Mapping is built to close.