Regionalising a global gridded crop model using satellite-based phenology for water footprint analysis in the Upper Syr Darya Basin

Study region The Upper Syr Darya Basin (USB) in Central Asia is a transboundary, water-stressed system where cotton production depends on irrigation, and ground-based monitoring is sparse. Spatial and temporal estimates of crop water footprint are essential for water allocation policy. Study focus Global gridded crop models provide water footprint accounts in data-scarce basins, but default crop calendars lack spatial and temporal detail, leading to uncertainties in key model outputs – evapotranspiration and crop yield. To improve phenological representation, this study regionalises the crop calendar of AquaCrop-Earth@lternatives (ACEA) using satellite-derived phenometrics. We compare our regionalised version (ACEA-USB), incorporating remotely sensed phenometrics at 5 arcminute resolution, with the global version (ACEA-G) on default calendars at 30 arcminute resolution. New hydrological insights for the region ACEA-USB captured spatial variation in cotton phenology across the basin. Planting dates ranged from April to May, with valley regions planting 3–4 weeks earlier than foothills, and growing seasons varied from 164 to 196 days. This variability produced differences in annual evapotranspiration: ACEA-USB simulated 602 mm, slightly higher than ACEA-G (590 mm) and closer to satellite-based ET estimates. These differences carried through to crop water footprints, revealing provincial blue water-footprint variation linked to phenology and irrigation patterns that ACEA-G masked. We conclude that satellite-derived phenology marks a methodological improvement in observation-scarce regional crop modelling and provides greater detail for local water management.