Preprints
https://doi.org/10.5194/egusphere-2024-1321
https://doi.org/10.5194/egusphere-2024-1321
03 Jun 2024
 | 03 Jun 2024
Status: this preprint is open for discussion.

On the Estimation of Global Plant Water Requirement

Yunfei Wang, Yijian Zeng, Zengjing Song, Danyang Yu, Qianqian Han, Enting Tang, Henk de Bruin, and Zhongbo Su

Abstract. Water supply is the most critical constraint for vegetation growth and food security. The amount of water demand by plant growth is usually estimated by plant water requirement which unfortunately cannot be directly measured at any large scale in field conditions. Different estimation methods have been proposed in the past seven decades for estimating plant water requirements using the concept of reference evapotranspiration (ET0) methods or potential evapotranspiration (PET) methods. In addition, using PET or ET0 to estimate actual evapotranspiration (ETa) is a critical approach in hydrological and climate models. However, different PET or ET0 models provide diverse results for irrigation water requirement (IWR) that in turn may result in a huge waste of irrigation water. Here, we assess the suitability of six common methods for estimating PET at 170 eddy covariance flux sites and propose a practical approach for estimating the IWR using a physically consistent model STEMMUS-SCOPE.

Notably, the Priestley-Taylor and LSA_SAF method excels in providing reasonable approximations of daily PET. Consequently, in scenarios where net radiation data and ground heat flux are accessible, the Priestley-Taypor method emerges as the recommended choice. The LSA_SAF method is the better one when only net radiation data is available. Alternatively, in cases where only global radiation data is available, the Makkink and Hargreaves methods serve as viable substitutes. Although the FAO56 Penman-Monteith method is much better than the original Penman-Monteith method when wind speed and air humidity data are at hand, its suitability falls short of the preferred status. This study contributes to understanding and quantifying the applicability of different methods in estimating PET and IWR, based on input data availability and physical considerations.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Yunfei Wang, Yijian Zeng, Zengjing Song, Danyang Yu, Qianqian Han, Enting Tang, Henk de Bruin, and Zhongbo Su

Status: open (until 29 Jul 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'a few papers for reference', Joshua Fisher, 03 Jun 2024 reply
Yunfei Wang, Yijian Zeng, Zengjing Song, Danyang Yu, Qianqian Han, Enting Tang, Henk de Bruin, and Zhongbo Su

Data sets

STEMMUS-SCOPE for PLUMBER2: A Physically Consistent Dataset Across the Soil-Plant-Atmosphere Continuum Yunfei Wang et al. https://zenodo.org/records/11057907

Model code and software

STEMMUS-SCOPE Yunfei Wang et al. https://github.com/EcoExtreML/STEMMUS_SCOPE

Yunfei Wang, Yijian Zeng, Zengjing Song, Danyang Yu, Qianqian Han, Enting Tang, Henk de Bruin, and Zhongbo Su

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Short summary
Various methods were proposed to estimate irrigation water requirements (IWR). However, the simulated IWR exhibits large differences. This study evaluates six potential evapotranspiration (PET) methods and proposes a practical approach to estimate IWR. The radiation-based methods show promise in approximating daily PET accurately, and the STEMMUS-SCOPE model can reliably estimate IWR. This research enhances our understanding of different PET methods and their implications for water management.