Applied ML Systems · Capstone brief
DS-23 · Is the water safe, and how would you know?
Using water-quality monitoring records for a Virginia watershed, classify whether a sample exceeds a standard — and quantify how much monitoring gaps limit what can be said.
The question
Using water-quality monitoring records for a Virginia watershed, classify whether a sample exceeds a standard — and quantify how much monitoring gaps limit what can be said.
Data
USGS Water Quality Portal (https://www.waterqualitydata.us/). EPA water quality standards documentation (https://www.epa.gov/waterdata/water-quality-data). USGS NWIS streamflow (https://waterdata.usgs.gov/).
Expected failure modes
Detection limits mean many readings are "below X" rather than numbers; substituting zero or the limit itself biases results in opposite directions. Sampling is not random — agencies sample when they suspect problems, and often after rain. Different labs and methods are not directly comparable.
Done looks like
A classification model with non-detects handled by a defensible, named method, sampling bias discussed, and results reported per parameter rather than pooled into a single "safe/unsafe" verdict.
Five C's
CT: recognizing censored data as a distinct statistical problem. CR: choosing and defending a non-detect method. CO: peer replication under a different method. CM: a public-facing summary that does not alarm or reassure beyond the evidence. CZ: drinking and recreational water safety is a direct public-health claim.
Mentor role
An environmental scientist, water utility analyst, or watershed-group staffer reviews non-detect handling at Checkpoint 1 and public framing at Checkpoint 2. School-supervised.
Rubric calibration
R1: one watershed, named parameters. R2: non-detects handled with a named method and sensitivity shown. R3: a base-rate baseline. R4: per-parameter results. R5: calibrated public language. R6: explicitly declines to declare water "safe."
Two ways this goes wrong
(a) Non-detects become zeros and average concentrations drop below reality. (b) The student pools parameters into one verdict and publishes that a creek is unsafe on the strength of one exceedance.
Source moved or something unclear? Send feedback on this brief. Mentors are advisory; the school supervises. These briefs do not produce verified computer-science credit.