A novel method for estimating film-flow-controlled bare soil evaporation

Gong, Chengcheng , Berli, Markus , Zhang, Zaiyong , Wang, Wenke , Wang, Yunquan

2025-12-01 JOURNAL OF HYDROLOGY-REGIONAL STUDIES 2025   62(卷), null(期), (null页)

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  • Study region: Arid and semi-arid regions. Study focus: The precise estimation of bare soil evaporation is essential for effective water resource management, particularly in arid and semi-arid regions. Although stage 2 evaporation (using three evaporation stage notation), characterized by film flow following the breakdown of capillary flow, is an important process, it is often neglected due to the difficulties associated with accurately estimating it. This study focuses on proposing an innovative method that explicitly integrates film flow processes to enhance the estimation of stage 2 evaporation. New hydrological insights for the region: We proposed a method to estimate stage 2 evaporation rates. The proposed method represents actual evaporation as a linear function of potential evapotranspiration, incorporating a critical threshold that signifies the transition from capillary to film flow, and uses one of the following as an input variable: soil water content, pressure head, or relative humidity near the soil surface. The proposed method was examined through data obtained from three laboratory experiments and a large-scale weighing lysimeter located in the Mojave Desert (an arid region), USA. The results show that evaporation rates in stage 2 can be accurately reproduced across various experimental setups and soil textures, yielding regression coefficients (b0) between 0.89 and 1.08, coefficients of determination (R2) values up to 0.99, and RMSE as low as 0.06-1.3 mm/day. This study addresses a critical gap in the estimation of evaporation by offering a simple and field-applicable tool for accurately quantifying stage 2 evaporation, which is beneficial for improving water resource management in arid and semi-arid regions. In addition, the proposed method relies on readily measurable surface variables, such as soil moisture, which can be obtained through remote sensing, making the approach especially practical for large-scale and field applications in the future.