OpenThe global record of surface-water fecal indicator monitoring
About
Fecal indicator bacteria decide whether the world's rivers, lakes, and beaches are called safe. This map is the first harmonized global picture of that record, and of where it goes dark.
Agencies almost never test water for pathogens directly. Instead they count indicator organisms: Escherichia coli in fresh water, intestinal enterococci in marine water. Those counts govern beach closures, drinking-water advisories, and compliance reporting worldwide. Until now the record behind those decisions had never been assembled and characterized at a harmonized global scale.
We compiled 11,110,309 surface-water observations from nine public sources, standardized to one schema, one indicator vocabulary, and one unit. The map plots the 189,872 monitoring sites those observations come from. Each dot is a place where somebody tested the water.
Two structural weaknesses emerge, and they are the reason this map exists.
BLIND SPOT 01 — SPACE
The United States, Europe, and Canada hold 94.5% of openly shared records. Much of the Global South is sparse, and several large monitoring nations are absent from open repositories entirely. Sparsity on this map often marks where data are shared, not where they are collected.
BLIND SPOT 02 — TIME
Contamination is a transient, weather-driven pulse, but only about 1.5% of multi-sample sites reach a near-daily cadence, almost all of them in the United States. Weekly sampling misadvises roughly one monitored day in nine; monthly, one in seven, biased toward false reassurance.
For fresh waters, both gaps are widest in the low- and middle-income regions that carry the greatest waterborne-disease burden and most often drink untreated surface water. The monitoring gap is therefore a question of public-health equity, not just data coverage. The case for wider open-data practice, and for higher-frequency, event-based, predictive monitoring tied to accountable response, follows directly from what this map shows.
Open the Map tab and use the guided tour to walk the argument, or filter by source, indicator, water-body type, and year. The heat layer shows monitoring density; switch to points to see individual sites. Click any site to pull its full observation time series.
Data
Every observation below is a surface-water fecal indicator measurement, cleaned and restricted to fresh and marine waters, standardized to colony forming units per 100 mL.
| Source | Region | Observations | Access |
|---|---|---|---|
| US Water Quality Portal | United States | 6,904,889 | API |
| Eionet (EEA bathing water) | Europe | 2,447,933 | Web scrape |
| UK Open WIMS | United Kingdom | 493,155 | API |
| DataStream | Canada | 403,931 | API |
| GEMStat | Global | 399,706 | Manual |
| Hub'Eau (Naiades) | France | 224,896 | API |
| NMMP | South Africa | 167,336 | Manual |
| LAWA | New Zealand | 67,129 | Manual |
| WPdx | Global | 1,334 | Manual |
| Total | 11,110,309 |
E. coli and intestinal enterococci are the regulatory indicators for fresh and marine water respectively. Fecal coliforms and total coliforms appear in the record and are reported for composition, but they are excluded from the safety analysis: total coliforms are not fecal-specific, and neither carries a comparable current single-sample recreational criterion.
The harmonized dataset accompanies the publication. Source data remain the property of the contributing programs, each of which should be cited directly when the underlying records are reused.
Methods
Nine national and subnational programs, each with its own schema, units, and indicator vocabulary, reduced to a single comparable record.
All concentrations were standardized to colony forming units per 100 mL. Most probable number values were treated as colony forming units, an approximation; qPCR-equivalent and nonconvertible units were dropped. Censored values were assigned a direction and filled at half the lower detection limit, or at the upper limit for right-censored values. Source-specific location descriptors were mapped to a controlled vocabulary of water-body types, and the marine and inland enterococci records were unified into a single enterococci class.
Repeated observations were averaged within each source, then deduplicated across sources using a fuzzy key with roughly 1 km coordinate tolerance, so records appearing in several portals are not double-counted. Filtering to a valid indicator, a plausible date and coordinates, and a non-negative bounded value reduced 11,151,268 harmonized records to 11,136,805. Groundwater is a distinct exposure pathway and was the only realm excluded; removing its 26,496 records yields the final analysis set of 11,110,309 surface-water observations.
For each site we computed the number of observations, the temporal span, and the median gap between consecutive distinct sampling days. Counting distinct days rather than raw records prevents same-day replicate sampling from inflating apparent frequency. Sites were binned by that median gap into daily, near-daily, weekly, monthly, quarterly, yearly, and longer classes.
The high-frequency analysis applies a stricter test for genuine near-daily monitoring: at least 30 distinct sampling days within a single recent calendar year (2018 or later), with a distinct-day median gap of at most three days, judged on each site's densest year.
Recreational safety uses realm-specific single-sample values from the 2012 US EPA recreational water quality criteria: 410 CFU/100 mL for E. coli in fresh water and 130 CFU/100 mL for enterococci in marine water.
To quantify the safety cost of coarse sampling, each near-daily site-year is treated as ground truth. We simulate monitoring programs at intervals from daily to quarterly: to every scheduled date we assign the nearest available observation, post a single-sample advisory that persists until the next scheduled sample, and score that standing advisory against the true daily state on every observed day, averaging false-safe and false-unsafe day rates over all phase offsets of the schedule.
The result is the paper's second blind spot. Slower schedules do not merely lose resolution; they systematically misadvise, and they err toward calling unsafe water safe.
Publication
The State of Global Surface-Water Fecal Indicator Monitoring
Mike Vlah and Matt Ross are at Colorado State University. Evan Thomas is at the University of Colorado Boulder.
Fecal indicator bacteria (Escherichia coli in fresh water and intestinal enterococci in marine water) are the primary tools used worldwide to judge whether surface waters are safe from waterborne pathogens, but that record has never been characterized at a harmonized global scale. We compiled, harmonized, and analyzed 11,110,309 surface-water fecal indicator observations (5.9 million freshwater, 5.2 million marine) from nine public sources, standardized to a common schema, indicator set, and unit.
Two structural weaknesses emerge. First, openly shared data are spatially unequal: the United States, Europe, and Canada hold 94.5% of records, while much of the Global South is sparse and large monitoring nations are absent from open repositories. Second, the record is temporally rigid: only about 1.5% of multi-sample sites achieve a near-daily cadence, itself almost entirely confined to the United States, even though contamination is a transient, weather-driven condition.
Using a temporal downsampling analysis, we simulated monitoring regimes across every near-daily record. On average, weekly sampling misadvises roughly one monitored day in nine, while monthly sampling misadvises one in seven, biased toward false reassurance. For fresh waters, these gaps are widest in the low- and middle-income regions that bear the greatest waterborne-disease burden and most often use surface water for drinking, making the monitoring gap a question of public-health equity. We argue for wider open-data practices and for higher frequency, event-based, predictive monitoring coupled to accountable response.