Journal of Hydrology X (Aug 2023)

Estimating evapotranspiration from soil moisture using the improved soil water balance method in cold mountainous areas

  • Yao Lai,
  • Jie Tian,
  • Weiming Kang,
  • Shuchen Guo,
  • Yongxu Zhou,
  • Chansheng He

Journal volume & issue
Vol. 20
p. 100154

Abstract

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Evapotranspiration (ET) is critical for ecosystem protection and water services, especially in the mountainous areas of arid and semi-arid watersheds. The lysimeter and Eddy Covariance (EC) methods are widely used for directly measuring ET, but are difficult to install and apply in mountainous areas with complex topography. The commonly used indirect methods for estimating ET, such as the Penman-Monteith (PM) method, present significant challenges in mountainous areas with scarce data. The simple soil water balance (SWB) method, which estimates ET from soil moisture dynamics, is another reliable and simple method for estimating ET. However, a drawback of the original SWB method is that it assumes soil moisture depletion only occurs through ET, ignoring the process of deep percolation. This restriction limits the applicability of the SWB method. In this study, we improve the SWB method (ISWB) by incorporating a deep percolation module into the soil water balance equation. Subsequently, we compare the estimated ET obtained from the ISWB, the Food and Agriculture Organization (FAO)-56 PM, and the Hargreaves-Samani (HS) methods with the observed ET. Results show that the ISWB method for estimating ET performs better when using the soil moisture of the 0–25 cm and below layers, compared to the 0–20 cm and above layers. Meanwhile, there is no significant difference in performance between using the soil moisture of the 0–25 cm layer and the soil layers below 25 cm. In addition, ignoring interception evaporation has an obvious influence on ET estimation using the ISWB. Furthermore, the comparison indicated that the performance of the ISWB method is superior to that of the FAO-56 PM and HS methods in the study areas. Our study shows that the ISWB method has significant potential for ET estimation in data-scarce and topographic-complex mountainous areas.

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