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Evaluating the Crop Water Stress Index and its correlation with latent heat and CO2 fluxes over winter wheat and maize in the North China plain

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  • Li, L.
  • Nielsen, D.C.
  • Yu, Q.
  • Ma, L.
  • Ahuja, L.R.

Abstract

Plant water status is a key factor impacting crop growth and agricultural water management. Crop water stress may alter canopy temperature, the energy balance, transpiration, photosynthesis, canopy water use efficiency, and crop yield. The objective of this study was to calculate the Crop Water Stress Index (CWSI) from canopy temperature and energy balance measurements and evaluate the utility of CWSI to quantify water stress by comparing CWSI to latent heat and carbon dioxide (CO2) flux measurements over canopies of winter wheat (Triticum aestivum L.) and summer maize (Zea mays L.). The experiment was conducted at the Yucheng Integrated Agricultural Experimental Station of the Chinese Academy of Sciences from 2003 to 2005. Latent heat and CO2 fluxes (by eddy covariance), canopy and air temperature, relative humidity, net radiation, wind speed, and soil heat flux were averaged at half-hour intervals. Leaf area index and crop height were measured every 7 days. CWSI was calculated from measured canopy-air temperature differences using the Jackson method. Under high net radiation conditions (greater than 500Wm-2), calculated values of minimum canopy-air temperature differences were similar to previously published empirically determined non-water-stressed baselines. Valid measures of CWSI were only obtained when canopy closure minimized the influence of viewed soil on infrared canopy temperature measurements (leaf area index was greater than 2.5m2m-2). Wheat and maize latent heat flux and canopy CO2 flux generally decreased linearly with increases in CWSI when net radiation levels were greater than 300Wm-2. The responses of latent heat flux and CO2 flux to CWSI did not demonstrate a consistent relationship in wheat that would recommend it as a reliable water stress quantification tool. The responses of latent heat flux and CO2 flux to CWSI were more consistent in maize, suggesting that CWSI could be useful in identifying and quantifying water stress conditions when net radiation was greater than 300Wm-2. The results suggest that CWSI calculated by the Jackson method under varying solar radiation and wind speed conditions may be used for irrigation scheduling and agricultural water management of maize in irrigated agricultural regions, such as the North China Plain.

Suggested Citation

  • Li, L. & Nielsen, D.C. & Yu, Q. & Ma, L. & Ahuja, L.R., 2010. "Evaluating the Crop Water Stress Index and its correlation with latent heat and CO2 fluxes over winter wheat and maize in the North China plain," Agricultural Water Management, Elsevier, vol. 97(8), pages 1146-1155, August.
    • Handle: RePEc:eee:agiwat:v:97:y:2010:i:8:p:1146-1155
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    References listed on IDEAS

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    1. Alderfasi, Ali Abdullah & Nielsen, David C., 2001. "Use of crop water stress index for monitoring water status and scheduling irrigation in wheat," Agricultural Water Management, Elsevier, vol. 47(1), pages 69-75, February.
    2. Li, Longhui & Yu, Qiang, 2007. "Quantifying the effects of advection on canopy energy budgets and water use efficiency in an irrigated wheat field in the North China Plain," Agricultural Water Management, Elsevier, vol. 89(1-2), pages 116-122, April.
    3. Ben-Asher, J. & Phene, C. J. & Kinarti, A., 1992. "Canopy temperature to assess daily evapotranspiration and management of high frequency drip irrigation systems," Agricultural Water Management, Elsevier, vol. 22(4), pages 379-390, December.
    4. Yuan, Guofu & Luo, Yi & Sun, Xiaomin & Tang, Dengyin, 2004. "Evaluation of a crop water stress index for detecting water stress in winter wheat in the North China Plain," Agricultural Water Management, Elsevier, vol. 64(1), pages 29-40, January.
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    1. Mohammed, Ali T. & Irmak, Suat, 2022. "Maize response to irrigation and nitrogen under center pivot, subsurface drip and furrow irrigation: Water productivity, basal evapotranspiration and yield response factors," Agricultural Water Management, Elsevier, vol. 271(C).
    2. Fang, Q.X. & Ma, L. & Green, T.R. & Yu, Q. & Wang, T.D. & Ahuja, L.R., 2010. "Water resources and water use efficiency in the North China Plain: Current status and agronomic management options," Agricultural Water Management, Elsevier, vol. 97(8), pages 1102-1116, August.
    3. Erdem, Yesim & Arin, Levent & Erdem, Tolga & Polat, Serdar & Deveci, Murat & Okursoy, Hakan & Gültas, Hüseyin T., 2010. "Crop water stress index for assessing irrigation scheduling of drip irrigated broccoli (Brassica oleracea L. var. italica)," Agricultural Water Management, Elsevier, vol. 98(1), pages 148-156, December.
    4. Feiziasl, V. & Jafarzadeh, J. & Sadeghzadeh, B. & Mousavi Shalmani, M.A., 2022. "Water deficit index to evaluate water stress status and drought tolerance of rainfed barley genotypes in cold semi-arid area of Iran," Agricultural Water Management, Elsevier, vol. 262(C).
    5. DeJonge, Kendall C. & Taghvaeian, Saleh & Trout, Thomas J. & Comas, Louise H., 2015. "Comparison of canopy temperature-based water stress indices for maize," Agricultural Water Management, Elsevier, vol. 156(C), pages 51-62.
    6. Zhang, Liyuan & Zhang, Huihui & Han, Wenting & Niu, Yaxiao & Chávez, José L. & Ma, Weitong, 2021. "The mean value of gaussian distribution of excess green index: A new crop water stress indicator," Agricultural Water Management, Elsevier, vol. 251(C).

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