IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v266y2022ics0378377422001251.html
   My bibliography  Save this article

Nocturnal transpiration in field crops: Implications for temporal aggregation and diurnal weighing of vapor pressure deficit

Author

Listed:
  • Kukal, Meetpal S.
  • Irmak, Suat

Abstract

Daytime transpiration is driven by evaporative demand (vapor pressure deficit, VPD) and radiative energy, dominantly accounting for daily transpiration (T). Recent modeling approaches recommend weighing VPD for diurnal cycle of T using radiation to predict T, as opposed to using daily mean VPD. This proposition requires field evaluation so that diurnal patterns of water use are represented fairly. In this research, hourly T was measured concurrently for irrigated maize, sorghum, and soybean in a dry sub-humid climate. Various VPD conditioning approaches available to the user that differed in measurement frequency, spectral sampling, and weighing strategies were evaluated to explain variance in T. The locally derived radiation-based weighing coefficient (Frac) showed substantial variability with mean estimates of 0.61 (annual) and 0.58 (growing season), which were lower than the classically recommended Tanner-Sinclair coefficient (0.75). The use of a constant Frac value for weighing VPD was suboptimal to dynamic weighing of VPD for each day, accounting for day-to-day variability. This is primarily because of considerable nighttime water use: Tn demonstrated values that were 6–16% of T across the three crops. Tn was driven by wind speed and VPD during nighttime hours. These field observations of Tn hold implications for (un)suitability of radiation-based weighing procedures, which assume no Tn. Diurnally weighted VPD was suboptimal to using daily mean VPD, as the former does not account for dark period-VPD. Additionally, reference evapotranspiration (ETo), the standardized metric of crop water use was either negative or zero for nocturnal periods when Tn ≠ 0, and thus, failed to appropriately represent Tn. A variable of transpiration, based on daily mean VPD and total daily radiation, was the most effective in explaining T variance in all crops. With increasing asymmetry between daytime and nighttime warming and aridity, it becomes increasingly important to appropriately precondition VPD data to predict T. Caution should be exercised while using radiation-weighted VPD in crops, environments and seasons with non-negligible Tn.

Suggested Citation

  • Kukal, Meetpal S. & Irmak, Suat, 2022. "Nocturnal transpiration in field crops: Implications for temporal aggregation and diurnal weighing of vapor pressure deficit," Agricultural Water Management, Elsevier, vol. 266(C).
    • Handle: RePEc:eee:agiwat:v:266:y:2022:i:c:s0378377422001251
    DOI: 10.1016/j.agwat.2022.107578
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377422001251
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2022.107578?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kukal, M.S. & Irmak, S., 2020. "Characterization of water use and productivity dynamics across four C3 and C4 row crops under optimal growth conditions," Agricultural Water Management, Elsevier, vol. 227(C).
    2. James A. Screen, 2014. "Arctic amplification decreases temperature variance in northern mid- to high-latitudes," Nature Climate Change, Nature, vol. 4(7), pages 577-582, July.
    3. Chen, Dianyu & Wang, Youke & Liu, Shouyang & Wei, Xinguang & Wang, Xing, 2014. "Response of relative sap flow to meteorological factors under different soil moisture conditions in rainfed jujube (Ziziphus jujuba Mill.) plantations in semiarid Northwest China," Agricultural Water Management, Elsevier, vol. 136(C), pages 23-33.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jiaojiao Huang & Sha Zhang & Jiahua Zhang & Xin Zheng & Xianye Meng & Shanshan Yang & Yun Bai, 2024. "Integrating Meteorological and Remote Sensing Data to Simulate Cropland Nocturnal Evapotranspiration Using Machine Learning," Sustainability, MDPI, vol. 16(5), pages 1-24, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kukal, M.S. & Irmak, S., 2020. "Impact of irrigation on interannual variability in United States agricultural productivity," Agricultural Water Management, Elsevier, vol. 234(C).
    2. Chen, Dianyu & Hu, Xiaotao & Duan, Xingwu & Yang, Daxin & Wang, Youke & Wang, Xing & Saifullah, Muhammad, 2024. "Improving canopy transpiration model performance by considering concurrent hot and dry conditions," Agricultural Systems, Elsevier, vol. 217(C).
    3. Xiaoting Sun & Qinghua Ding & Shih-Yu Simon Wang & Dániel Topál & Qingquan Li & Christopher Castro & Haiyan Teng & Rui Luo & Yihui Ding, 2022. "Enhanced jet stream waviness induced by suppressed tropical Pacific convection during boreal summer," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    4. Min Tang & Hongchen Li & Chao Zhang & Xining Zhao & Xiaodong Gao & Pute Wu, 2021. "Mulching Measures Improve Soil Moisture in Rain-Fed Jujube ( Ziziphus jujuba Mill.) Orchards in the Loess Hilly Region of China," Sustainability, MDPI, vol. 13(2), pages 1-13, January.
    5. Ouyang, Lei & Wu, Jin & Zhao, Ping & Li, Yanqiong & Zhu, Liwei & Ni, Guangyan & Rao, Xingquan, 2021. "Consumption of precipitation by evapotranspiration indicates potential drought for broadleaved and coniferous plantations in hilly lands of South China," Agricultural Water Management, Elsevier, vol. 252(C).
    6. Huanyuan Wang & Baoguo Li & Liang Jin & Kelin Hu, 2020. "Exploring a Sustainable Cropping System in the North China Plain Using a Modelling Approach," Sustainability, MDPI, vol. 12(11), pages 1-16, June.
    7. Malanson, George P. & DeRose, R. Justin & Bekker, Matthew F., 2019. "Individual variation and ecotypic niches in simulations of the impact of climatic volatility," Ecological Modelling, Elsevier, vol. 411(C).
    8. Wang, Di & Wang, Li, 2017. "Dynamics of evapotranspiration partitioning for apple trees of different ages in a semiarid region of northwest China," Agricultural Water Management, Elsevier, vol. 191(C), pages 1-15.
    9. Dirk Olonscheck & Andrew P. Schurer & Lucie Lücke & Gabriele C. Hegerl, 2021. "Large-scale emergence of regional changes in year-to-year temperature variability by the end of the 21st century," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    10. Pan, Daili & Song, Yaqian & Dyck, Miles & Gao, Xiaodong & Wu, Pute & Zhao, Xining, 2017. "Effect of plant cover type on soil water budget and tree photosynthesis in jujube orchards," Agricultural Water Management, Elsevier, vol. 184(C), pages 135-144.
    11. Haoming Xia & Ainong Li & Gary Feng & Yang Li & Yaochen Qin & Guangbin Lei & Yaoping Cui, 2018. "The Effects of Asymmetric Diurnal Warming on Vegetation Growth of the Tibetan Plateau over the Past Three Decades," Sustainability, MDPI, vol. 10(4), pages 1-14, April.
    12. Sharma, Kiran & Irmak, Suat & Kukal, Meetpal S., 2021. "Propagation of soil moisture sensing uncertainty into estimation of total soil water, evapotranspiration and irrigation decision-making," Agricultural Water Management, Elsevier, vol. 243(C).
    13. Jiang, Xuelian & Kang, Shaozhong & Li, Fusheng & Du, Taisheng & Tong, Ling & Comas, Louise, 2016. "Evapotranspiration partitioning and variation of sap flow in female and male parents of maize for hybrid seed production in arid region," Agricultural Water Management, Elsevier, vol. 176(C), pages 132-141.
    14. Chen, Dianyu & Wang, Xing & Liu, Shouyang & Wang, Youke & Gao, Zhiyong & Zhang, Linlin & Wei, Xinguang & Wei, Xindong, 2015. "Using Bayesian analysis to compare the performance of three evapotranspiration models for rainfed jujube (Ziziphus jujuba Mill.) plantations in the Loess Plateau," Agricultural Water Management, Elsevier, vol. 159(C), pages 341-357.
    15. Minxia Zhang & Shulin Chen & Hong Jiang & Yong Lin & Jinmeng Zhang & Xinzhang Song & Guomo Zhou, 2019. "Water-Use Characteristics and Physiological Response of Moso Bamboo to Flash Droughts," IJERPH, MDPI, vol. 16(12), pages 1-18, June.
    16. Zheng, Jing & Fan, Junliang & Zhang, Fucang & Wu, Lifeng & Zou, Yufeng & Zhuang, Qianlai, 2021. "Estimation of rainfed maize transpiration under various mulching methods using modified Jarvis-Stewart model and hybrid support vector machine model with whale optimization algorithm," Agricultural Water Management, Elsevier, vol. 249(C).
    17. Li Yang & Haijun Liu & Shabtai Cohen & Zhuangzhuang Gao, 2022. "Microclimate and Plant Transpiration of Tomato ( Solanum lycopersicum L.) in a Sunken Solar Greenhouse in North China," Agriculture, MDPI, vol. 12(2), pages 1-21, February.
    18. Jun Ge & Qi Liu & Beilei Zan & Zhiqiang Lin & Sha Lu & Bo Qiu & Weidong Guo, 2022. "Deforestation intensifies daily temperature variability in the northern extratropics," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    19. Claudia Simolo & Susanna Corti, 2022. "Quantifying the role of variability in future intensification of heat extremes," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    20. Gao, Zhiyong & Shi, Wenjuan & Wang, Xing & Wang, Youke & Yang, Yi & Zhang, Linlin & Chen, Dianyu, 2022. "Response of dew and hydraulic redistribution to soil water in a rainfed dryland jujube plantation in China’s Hilly Loess Region," Agricultural Water Management, Elsevier, vol. 271(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agiwat:v:266:y:2022:i:c:s0378377422001251. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.