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Optimal planning and management of the limited water resources for maximum productivity in agriculture requires quantifying the irrigation applied at a regional scale. However, most efforts involving remote sensing applications in assessing large-scale irrigation applied (IA) have focused on supplying spatial variables for crop models or studying evapotranspiration (ET) inversions, rather than directly building a remote sensing data-based model to estimate IA. In this study, based on remote sensing data, an IA estimation model together with an ET calculation model (ETWatch) is set up to simulate the spatial distribution of IA in the Haihe Plain of northern China. We have verified this as an effective approach for the simulation of regional IA, being more reflective of regional characteristics and of higher resolution compared to single site-specific results. The results show that annual ET varies from 527 mm to 679 mm and IA varies from 166 mm to  289 mm, with average values of 602 mm and 225 mm, respectively, from 2002 to 2007. We confirm that the region along the Taihang Mountain in Hebei Plain has serious water resource sustainability problems, even while receiving water from the South-North Water Transfer (SNWT) project. This is due to the region’s intensive agricultural production and declining groundwater tables. Water-saving technologies, including more timely and accurate geo-specific IA assessments, may help reduce this threat

Regional Water Balance Based on Remotely Sensed Evapotranspiration and Irrigation: An Assessment of the Haihe Plain, China