Estimation of sensible and latent heat flux and evapotranspiration in arid regions using inverse analysis

Abstract

ABSTRACT Drylands cover approximately 40% of the earth’s land and account for up to 44% of cultivated lands. Therefore, evapotranspiration in drylands is an essential indicator of global warming because net radiation is partitioned into sensible (H, warming) and latent (LE, cooling) heat flux. This study aimed to estimate H (H est) and LE (LE est) in arid regions using an inverse analysis (IA) method. The observed sensible (H obs) and latent energy fluxes (LE obs) were compared with H est and LEest over four-time scales to confirm the reliability of the method, demonstrating that H est and LE est were highly similar to H obs and LE obs. Estimation accuracy was evaluated by the root mean squared error (RMSE) at each time scale, indicating that H est and LE est can be reasonably estimated using IA. The method is expected to contribute significantly to estimating evapotranspiration for global warming research by providing for estimating H and LE in drylands.