Considering water-temperature synergistic factors improves simulations of stomatal conductance models under plastic film mulching

Accurately simulating stomatal behavior is crucial for understanding water, carbon, and energy fluxes between land and atmosphere. Given the significant impact of plastic film mulching on water and temperature, it is essential to incorporate water and temperature modifications into stomatal conducta...

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Main Authors: Cheng Li, Yunxin Zhang, Jingui Wang, Hao Feng, Renyou Zhang, Wenxin Zhang, Kadambot H.M. Siddique
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Agricultural Water Management
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Online Access:http://www.sciencedirect.com/science/article/pii/S037837742400547X
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author Cheng Li
Yunxin Zhang
Jingui Wang
Hao Feng
Renyou Zhang
Wenxin Zhang
Kadambot H.M. Siddique
author_facet Cheng Li
Yunxin Zhang
Jingui Wang
Hao Feng
Renyou Zhang
Wenxin Zhang
Kadambot H.M. Siddique
author_sort Cheng Li
collection DOAJ
description Accurately simulating stomatal behavior is crucial for understanding water, carbon, and energy fluxes between land and atmosphere. Given the significant impact of plastic film mulching on water and temperature, it is essential to incorporate water and temperature modifications into stomatal conductance models under these conditions. In this study, we evaluated three commonly used stomatal conductance models: Ball-Woodrow-Berry (BWB), Ball-Berry-Leuning (BBL), and unified stomatal optimization (USO), to simulate the stomatal conductance of spring maize with or without mulching. We introduced modifications based on air temperature, canopy temperature, and water-temperature synergistic factors. Our results indicate that the USO model performed best, followed by the BBL and BWB models. Introducing temperature response functions improved simulation accuracy, with water-temperature synergistic models (-Tc&T) outperforming others. Models modified by canopy temperature (-Tc) outperformed those modified by air temperature (-Ta). Specifically, for the BWB model, the -Ta, -Tc, and -Tc&T modifications decreased root mean square error (RMSE) by 11.5–33.3 %, 19.2–50.6 %, and 29.5–56.7 %, respectively. For the BBL model, these reductions were 6.0–30.4 %, 20.9–48.1 %, and 25.4–52.9 %, respectively. For the USO model, the reductions were 7.9–55.2 %, 11.1–56.3 %, and 27.8–64.4 %, respectively. By comparing the simulated stomatal conductance curves with the 95 % confidence intervals (CI) of the observed data, we determined that the water-temperature synergistic model is optimal for various temperature conditions, followed by the Tc-modified and Ta-modified models. This study enhances our understanding of stomatal conductance under different temperature conditions and offers a foundation for accurately simulating carbon and water cycles in agricultural ecosystems under diverse water and temperature conditions.
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issn 1873-2283
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publishDate 2024-12-01
publisher Elsevier
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series Agricultural Water Management
spelling doaj-art-43f909b788fe461c91748995a83450c92025-08-20T02:39:29ZengElsevierAgricultural Water Management1873-22832024-12-0130610921110.1016/j.agwat.2024.109211Considering water-temperature synergistic factors improves simulations of stomatal conductance models under plastic film mulchingCheng Li0Yunxin Zhang1Jingui Wang2Hao Feng3Renyou Zhang4Wenxin Zhang5Kadambot H.M. Siddique6School of Water Conservancy and Hydroelectric Power, Hebei University of Engineering, Handan 056038, China; Hebei Key Laboratory of Intelligent Water Conservancy, Hebei University of Engineering, Handan 056038, China; College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, ChinaSchool of Water Conservancy and Hydroelectric Power, Hebei University of Engineering, Handan 056038, China; Hebei Key Laboratory of Intelligent Water Conservancy, Hebei University of Engineering, Handan 056038, China; Corresponding authors at: School of Water Conservancy and Hydroelectric Power, Hebei University of Engineering, Handan 056038, China.School of Water Conservancy and Hydroelectric Power, Hebei University of Engineering, Handan 056038, China; Hebei Key Laboratory of Intelligent Water Conservancy, Hebei University of Engineering, Handan 056038, China; Corresponding authors at: School of Water Conservancy and Hydroelectric Power, Hebei University of Engineering, Handan 056038, China.College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China; Corresponding author.School of Water Conservancy and Hydroelectric Power, Hebei University of Engineering, Handan 056038, ChinaDepartment of Physical Geography and Ecosystem Science, Lund University, SwedenThe UWA Institute of Agriculture, The University of Western Australia, Perth, WA 6001, AustraliaAccurately simulating stomatal behavior is crucial for understanding water, carbon, and energy fluxes between land and atmosphere. Given the significant impact of plastic film mulching on water and temperature, it is essential to incorporate water and temperature modifications into stomatal conductance models under these conditions. In this study, we evaluated three commonly used stomatal conductance models: Ball-Woodrow-Berry (BWB), Ball-Berry-Leuning (BBL), and unified stomatal optimization (USO), to simulate the stomatal conductance of spring maize with or without mulching. We introduced modifications based on air temperature, canopy temperature, and water-temperature synergistic factors. Our results indicate that the USO model performed best, followed by the BBL and BWB models. Introducing temperature response functions improved simulation accuracy, with water-temperature synergistic models (-Tc&T) outperforming others. Models modified by canopy temperature (-Tc) outperformed those modified by air temperature (-Ta). Specifically, for the BWB model, the -Ta, -Tc, and -Tc&T modifications decreased root mean square error (RMSE) by 11.5–33.3 %, 19.2–50.6 %, and 29.5–56.7 %, respectively. For the BBL model, these reductions were 6.0–30.4 %, 20.9–48.1 %, and 25.4–52.9 %, respectively. For the USO model, the reductions were 7.9–55.2 %, 11.1–56.3 %, and 27.8–64.4 %, respectively. By comparing the simulated stomatal conductance curves with the 95 % confidence intervals (CI) of the observed data, we determined that the water-temperature synergistic model is optimal for various temperature conditions, followed by the Tc-modified and Ta-modified models. This study enhances our understanding of stomatal conductance under different temperature conditions and offers a foundation for accurately simulating carbon and water cycles in agricultural ecosystems under diverse water and temperature conditions.http://www.sciencedirect.com/science/article/pii/S037837742400547XPhotosynthesisCanopy temperatureTemperature response functionSpring maizeArid and semiarid area
spellingShingle Cheng Li
Yunxin Zhang
Jingui Wang
Hao Feng
Renyou Zhang
Wenxin Zhang
Kadambot H.M. Siddique
Considering water-temperature synergistic factors improves simulations of stomatal conductance models under plastic film mulching
Agricultural Water Management
Photosynthesis
Canopy temperature
Temperature response function
Spring maize
Arid and semiarid area
title Considering water-temperature synergistic factors improves simulations of stomatal conductance models under plastic film mulching
title_full Considering water-temperature synergistic factors improves simulations of stomatal conductance models under plastic film mulching
title_fullStr Considering water-temperature synergistic factors improves simulations of stomatal conductance models under plastic film mulching
title_full_unstemmed Considering water-temperature synergistic factors improves simulations of stomatal conductance models under plastic film mulching
title_short Considering water-temperature synergistic factors improves simulations of stomatal conductance models under plastic film mulching
title_sort considering water temperature synergistic factors improves simulations of stomatal conductance models under plastic film mulching
topic Photosynthesis
Canopy temperature
Temperature response function
Spring maize
Arid and semiarid area
url http://www.sciencedirect.com/science/article/pii/S037837742400547X
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