Uncertainty of water footprint estimates caused by harvested area inputs

Global water footprint (WF) assessments guide critical water management decisions, yet their uncertainty remains poorly understood. While a few studies have assessed WF sensitivity to reference evapotranspiration and crop model inputs, uncertainty arising from harvested area (HA) variation has received little attention. This study quantified the uncertainty of WF for major crops (rice, maize, wheat, and soybeans) using five global HA datasets for the years 2000, 2010, and 2015. We applied statistical metrics, including bias, standard deviation, and coefficient of variation (CV), to quantify WF uncertainty and mapped spatial patterns to identify regional uncertainty hotspots. Results reveal substantial uncertainty in the total WF of the major crops, with average CVs of 28%, 32%, and 17% in 2000, 2010, and 2015, respectively. Green WF estimates exhibit even higher uncertainty than the total WF across all crops and years. In 2015, blue WF uncertainty exceeded total WF uncertainty for all crops except wheat, whereas in 2000 and 2010, this pattern was observed only for rice. Soybeans exhibited the highest variability in blue WF (24%, 28%, and 58% in 2000, 2010, and 2015) and green WF (53% in 2000, 69% in 2010), while wheat led in green WF variability in 2015 (35% CV). Hotspots of high WF variability of the major crops are found in China, India, Brazil, Southeast Asia, and parts of the US. Notably, WF uncertainty exceeds HA uncertainty, indicating amplification as uncertainty propagates from area inputs to WF estimates due to spatial variation in ET. These findings underscore the risk of misinformed water allocation and sustainability strategies, potentially exacerbating water and food insecurity. We highlight the need for systematic documentation of uncertainties and investment in crop area monitoring through enhanced field validation and farmer engagement.