Fifty years of research have deepened uncertainties in global irrigation water withdrawals

Abstract For five decades, refining models and datasets has been regarded as central to reducing uncertainty in global irrigation water withdrawal estimates. However, whether these efforts have succeeded remains unclear. Here we compile 1,624 global estimates from 65 studies published between 1974 and 2025 and evaluate them across 360 analytical pathways, spanning a comprehensive range of plausible statistical designs. Our results indicate that uncertainty in global irrigation water withdrawals has not declined: only 17% of pathways show any reduction over time, falling to 10% once projections to 2100 are excluded. The most common outcome is an increase in uncertainty (40% of pathways), followed by an unstable trend (34%). Progress may therefore require the field to renounce the goal of reducing uncertainty and instead double down on what it has historically done best: expanding it, until uncertainty reaches the boundary of what current knowledge of global irrigation cannot exclude.