A Station-Anchored Open-Data Reference Evapotranspiration Screening Workflow for Climate-Resilient Water-Demand Assessment Under Incomplete Meteorological Records

Abstract

Incomplete station meteorological records constrain sustainable water-demand planning and climate-adaptation decisions in data-limited regions. Open-data reference evapotranspiration (ETo) products can provide continuous hydroclimatic information for atmospheric-demand screening, but they do not directly represent realized water demand and their use as station substitutes may introduce bias because gridded and station-derived ETo represent related but non-identical calculation and spatial domains. This study develops a station-anchored open-data ETo screening workflow for assessing local product compatibility under incomplete meteorological records. The workflow combines four official Turkish State Meteorological Service (MGM) stations in the eastern Marmara region, station-derived Hargreaves–Samani (HS) ETo for 1990–2020, TerraClimate v1.1 reference ETo, calendar-month and anomaly diagnostics, blocked historical gap-transfer tests in which omitted periods are excluded from correction fitting and tuning, and measured-radiation FAO-56 Penman–Monteith (PM) sensitivity subsets. TerraClimate reproduced the first-order annual ETo cycle strongly (r = 0.972–0.978), but mean TerraClimate-minus-HS bias remained station-dependent (+1.78 to +11.55 mm month−1) and strongly calendar-month-dependent. After removing each series’ calendar-month climatology, Pearson correlation decreased to 0.559–0.849, indicating that the common annual cycle explains a substantial part of the raw agreement. Train-only monthly-bias and nested L2 residual corrections reduced pooled blocked out-of-sample MAE, although no correction method was universally superior across stations. Measured-radiation PM subsets at Kocaeli and Yalova showed PM-minus-HS mean offsets of −4.42% and +3.37%, respectively. The blocked tests evaluate transfer to omitted historical periods rather than prospective forecasting. The results support local, season-aware compatibility screening before gridded ETo is used for climate-resilient water-resource planning; they should not be interpreted as validation of actual ET, crop water use, irrigation withdrawals, or realized water demand.