Better estimation of evapotranspiration and transpiration using an improved modified Priestly-Taylor model based on a new parameter of leaf senescence in a rice field.

Yujie Zhang, Zhaozhong Feng, Yuqing Zhou, Yansen Xu, Jianghua Wu, Shiyun Xu

Journal: The Science of the total environment 2024;927():171842

PMID: 38513864

Abstract

Evapotranspiration (ET) is at the heart of the global water, energy, and carbon cycles. As ET is difficult and expensive to measure, it is crucial to develop estimation models that can be widely applied. Currently, an improved Priestley-Taylor (PT) model considers soil moisture stress, temperature constraints, and leaf senescence; however, its parameter (f) for simulating crop senescence is based on empirical values, making it difficult to apply to different varieties and complex external conditions and thus challenging to generalize. We improved the parameters f in the original model based on the chlorophyll decomposition that accompanies crop senescence through easily observable SPAD values (Soil-Plant Analysis Development readings) in the field. We validated the improved model by obtaining ET of different rice varieties in 2022 and 2023 using the energy balance residual method at the Free Air Concentration Enrichment Experimental (FACE) Facility located in Yangzhou City, China. The results showed that the simulation of leaf senescence using SPAD values was feasible and could be extended to different varieties. The new model using improved leaf senescence parameter for estimating ET and transpiration (T) in three plots (2022 and 2023) exhibited slightly enhanced accuracy, particularly at the later stages of crop growth. Moreover, the higher the T/ET ratio of the cropland, the more significant the improvement. This new development enhances the ability of PT models to estimate ET and T using readily available field observations and provides some suggestions for wider application in the field for other crop species.

Copyright © 2024 Elsevier B.V. All rights reserved.

Address: Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, China.; Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, China.; Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, China; Environment and Sustainability, School of Science and the Environment, Memorial University of Newfoundland, Corner Brook, NL A2H 5G4, Canada.; Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, China. Electronic address: [email protected].

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