JalDrishti

Phase 2 audit

The data this model needs
mostly isn’t published

Bengaluru is not short of water data. It is short of water data at the resolution a neighbourhood model runs on. The audit graded every variable the index requires against the resolution it actually needs — and consumption, losses and supply reliability all came back at the bottom of the scale. That finding is the reason this prototype exists, so it is shown first rather than buried in a limitations section.

Grades A–C

4

variables usable at or aggregable to ward level

Grade D

1

categorical evidence only — vulnerability, not measurement

Grade E

3

not available at the resolution the model requires

Availability by variable

Select a row to read what stopped the variable reaching a usable grade.

VariableWardZoneStationBest

Indicators feeding the index

  • Groundwater depletionCSynthetichigher = more stress

    How far the local aquifer has drawn down relative to the rest of the city.

    Audit: station observations exist, but reviewed metadata do not identify Bengaluru Urban stations well enough to assign them to wards.

  • Supply reliabilityESyntheticreversed

    Share of planned piped supply hours a ward actually receives.

    Audit: no systematic ward or DMA record of supply hours, interruption frequency or pressure was identified.

  • Non-revenue waterESynthetichigher = more stress

    Water put into the network that never reaches a billed connection.

    Audit: only city-level loss evidence was identified; no ward or DMA measurements are published.

  • Demand pressureESynthetichigher = more stress

    Demand per connection measured against the ward's available supply.

    Audit: no sufficiently usable public ward or DMA consumption series was identified.

  • Rainfall deficitChigher = more stress

    Shortfall against the 1991–2020 long-period average of 1,077.1 mm.

    City-level series is real (IMD, republished by OpenCity). The ward-level split shown here is synthetic: Bengaluru shows low spatial rainfall variability, which limits ward discrimination.

  • Tanker dependenceDSynthetichigher = more stress

    How far households fall back on tankers and private borewells.

    Audit: vulnerability evidence exists as a categorical critical-ward notification, not as a measured quantity.

The one real result

Rainfall is the only variable in the paper with a complete, reproducible public series. Across 33 complete years (1991–2023), annual totals ranged from 587.2 mm in 1994 to 1,957.7 mm in 2022. 18 of those years fell below the 1,077.1 mm long-period average.

It is a single city series. It supports a climate-context indicator; it cannot rank one ward against another.

Generated inputs

The ward lattice and every grade-E series are produced by a seeded generator so any figure on this site can be reproduced exactly and discarded just as easily.

Seed
20300322
Generator
gen_wards.py@1.0.0
Wards
36
Geometry
Schematic, WGS84

Sources

DatasetPublisherResolutionLimitation
Bengaluru monthly rainfall1901–2024IMD, republished by OpenCitySingle city seriesNot ward or DMA resolved; 2024 incomplete.
Bengaluru Urban rainfall stations2024KSNDMC, republished by OpenCityStation / talukNot joined to verified ward boundaries.
Supply-line geometry2025Utility source, republished by OpenCityLine map, diameter classesNo published DMA flow, pressure, demand or reliability series.
Groundwater monitoringPeriodicCentral Ground Water BoardMonitoring wells / stationsNo consistent ward crosswalk in reviewed metadata.
Ward boundary resources2022–2026Municipal / metropolitan authorityWard polygonsWard schemes change between releases and no matching operational observations exist.
Ward operational seriesSynthetic2021–2026 (generated)JalDrishti synthetic generatorWard, monthlyFabricated under a documented seed. Carries no evidential weight and must not be read as a measurement.
Representative distribution networkSyntheticStatic topologyJalDrishti synthetic generatorNetwork zoneA stand-in topology. Not a calibrated Bengaluru DMA and not an EPANET solver run.

JalDrishti 2030 is a decision-support prototype built from a student research paper. It is not connected to any utility system, it does not control anything, and it reports no validated result for Bengaluru. Where the audit found no data, the prototype shows fabricated data and says so.

Data & system status

Data: Prototype / synthetic

API: Not configured

83% synthetic

Analytical outputs are prototype/simulated and demonstrate the JalDrishti digital-twin workflow; they are not current real-world measurements or validated operational predictions.