Dynamic parameterization of Priestley–Taylor coefficient for a more accurate potential evapotranspiration estimation in ungauged regions

Abstract Potential evapotranspiration (PET), defined as the evapotranspirative flux from a region under fully saturated conditions, is a critical variable in hydrologic modeling, water stress assessment, and understanding ecosystem responses to climate. The widely used Priestley–Taylor method provides a simple, low-data requirement approach for estimating PET. However, it uses a fixed coefficient ( α P T = 1.26) in most applications, but this oversimplification neglects biome-specific variability, limiting its accuracy across diverse environments. Although numerous studies have attempted to derive dynamic characterizations of α P T , most estimates are developed for either obtaining reference evapotranspiration (ET 0 ) or actual evapotranspiration (ET). Consequently, these approaches do not provide α P T that accounts for ecosystem-specific aerodynamic and plant conductance constraints required to fully represent true ecosystem-level PET. In this study, we utilized 3128 site-years of eddy covariance data from 246 FluxNet sites worldwide to optimize α P T values across a broad range of biomes. Results showed significant spatial and seasonal variability in α P T , with higher values in forests and winter months and lower values in savannas’ summer. Temperature and radiation emerged as key drivers of this variability. Using the influencing variables, we next derived functional equations to estimate α P T based on key bio-environmental variables. These equations yielded demonstrable improvements in PET estimates, and can be directly incorporated into land surface and hydrologic models, and generation of remote sensing products. Furthermore, PET derived using our simplified functional equations of α P T , when applied to obtain the evaporative stress index and ET, yielded improved estimates of both ET and plant stress. Overall, these findings offer a more ecologically representative approach to PET estimation using the Priestley–Taylor method, with broad implications for hydrologic modeling and drought assessment.