From Compliant to Critical: Forecasting Emerging E. coli Risk in New Zealand’s South Island Rivers

Abstract

Freshwater quality is degrading globally, and regulatory monitoring remains largely retrospective, identifying non-compliance only after it occurs. This study identifies whether multi-year, regulatorily relevant compliance breaches can be forecast from sparse monthly monitoring records alone and whether such forecasts improve on the assumption that next year resembles the current one. Using approximately two decades (2004–2024) of Land, Air, Water Aotearoa (LAWA) data from 497 South Island, New Zealand river sites, a single pooled gradient-boosted (LightGBM) classifier was trained to forecast Escherichia coli worst-band (Band E) non-compliance under the National Policy Statement for Freshwater Management at one-, two-, and three-year horizons, benchmarked against persistence, trend projection, and majority-class baselines under strictly temporal validation. The model discriminated breaches reliably (AUC 0.84–0.85) and exceeded persistence in balanced accuracy at all three horizons, significantly at two and three years. Its principal value was early warning: among currently compliant sites, it recovered roughly half of subsequent breaches, transitions that persistence cannot detect by construction, yielding a forward watchlist of 97 sites at risk of entering the worst band (Band E) by 2027, concentrated in pastoral catchments. Forecasting from monitoring data alone imposes an honest ceiling; scores are reported as risk rankings. The findings support a shift from reactive to anticipatory freshwater management.