The magnitude and extent of runoff reduction, drought intensification, and dryland expansion under climate change are unclear and contentious. A primary reason is disagreement between global circulation models and current potential evaporation (PE) models for evaporative demand under warming climatic conditions. An emerging body of research suggests that current PE models including Penman-Monteith and Priestley-Taylor may overestimate future evaporative demand. However, they are still widely used for climatic impact analysis although the underlying physical mechanisms for PE projections remain unclear. Here, we show that current PE models diverge from observed non-water-stressed evaporation, a proxy of evaporative demand, across site (>1500 flux tower site years), watershed (>10,000 watershed-years), and global (25 climate models) scales. By not incorporating land-atmosphere feedback processes, current models overestimate non-water-stressed evaporation and its driving factors for warmer and drier conditions. To resolve this, we introduce a land-atmosphere coupled PE model that accurately reproduces non-water-stressed evaporation across spatiotemporal scales. We demonstrate that terrestrial evaporative demand will increase at a similar rate to ocean evaporation, but much slower than rates suggested by current PE models. This finding suggests that land-atmosphere feedbacks moderate continental drying trends. Budyko-based runoff projections incorporating our PE model are well aligned with those from coupled climate simulations, implying that land-atmosphere feedbacks are key to improving predictions of climatic impacts on water resources. Our approach provides a simple and robust way to incorporate coupled land-atmosphere processes into water management tools.

Although evapotranspiration (ET) from the land surface is a key variable in Earth systems models, the accurate estimation of ET based on physical principles remains challenging. Parameters used in current ET models are largely empirically based, which could be problematic under rapidly changing climatic conditions. Here, we propose a physically-based ET model that estimates ET based on the surface flux equilibrium (SFE) theory and the maximum entropy production (MEP) principle. We derived an expression for aerodynamic resistance based on the MEP principle, then propose a novel ET model that complementarily depends on the SFE theory and the MEP principle. The proposed model, which is referred to as the SFE-MEP model, becomes equivalent to the MEP state in non-equilibrium conditions when turbulent mixing is weak and the land surface is dry. On the contrary, the SFE-MEP model is similar to ET estimation based on the SFE theory in other conditions meeting land-atmosphere equilibrium. This feature of the SFE-MEP ET model allows accurate ET estimation for most inland regions by incorporating both equilibrium and non-equilibrium characteristics of the atmospheric boundary layer. As a result, the SFE-MEP model significantly improves the performance of SFE ET estimation, particularly for arid regions. The proposed model and its high accuracy in ET estimation enable novel insight into various Earth system models as it does not require any empirical parameters and only uses readily obtainable meteorological variables including reference height air temperature, relative humidity, available energy, and radiometric surface temperature.