The natural variation in stable water isotope ratio data, also known as water isoscape, is a spatiotemporal fingerprint and a powerful natural tracer that has been widely applied in disciplines as diverse as hydrology, paleoclimatology, ecology and forensic investigation. Although much effort has been devoted to developing a predictive water isoscape model, it remains a central challenge for scientists to generate high accuracy, fine scale spatiotemporal water isoscape prediction. Here we develop a novel approach of using the MODIS-EVI (the Moderate Resolution Imagining Spectroradiometer-Enhanced Vegetation Index), to predict δ 18O in precipitation at the regional scale. Using a structural equation model, we show that the EVI and precipitated δ 18O are highly correlated and thus the EVI is a good predictor of precipitated δ 18O. We then test the predictability of our EVI-δ 18O model and demonstrate that our approach can provide high accuracy with fine spatial (250×250 m) and temporal (16 days) scale δ 18O predictions (annual and monthly predictabilities [ r] are 0.96 and 0.80, respectively). We conclude the merging of the EVI and δ 18O in precipitation can greatly extend the spatial and temporal data availability and thus enhance the applicability for both the EVI and water isoscape.