IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v274y2022ics0378377422005042.html
   My bibliography  Save this article

Real-time irrigation scheduling of maize using Degrees Above Non-Stressed (DANS) index in semi-arid environment

Author

Listed:
  • Nakabuye, Hope Njuki
  • Rudnick, Daran
  • DeJonge, Kendall C.
  • Lo, Tsz Him
  • Heeren, Derek
  • Qiao, Xin
  • Franz, Trenton E.
  • Katimbo, Abia
  • Duan, Jiaming

Abstract

Irrigation scheduling methods have been used to determine the timing and amount of water applied to crops. Scheduling techniques can include measurement of soil water content, quantification of crop water use, and monitoring of crop physiological response to water stress. The aim of this study was to evaluate the performance of a simplified crop canopy temperature measurement (CTM) method as Irrigation Principles. Soil and Water Conservation Engineera technique to schedule irrigation for maize. Specifically, the Degrees Above Non-Stressed (DANS) index, which suggests water stress when canopy temperature exceeds the non-stressed canopy temperature (Tcns), was determined by estimating Tcns from a weather based multilinear regression model. The modeled Tcns had a strong correlation with observed Tcns with a pooled R2 values of 0.94 across the 2018, 2019, and 2020 growing seasons. This DANS index was also highly correlated with the conventionally used Crop Water Stress Index (CWSI) with R2 values of 0.67, 0.59, and 0.76 in 2018, 2019, and 2020, respectively. Furthermore, DANS had a strong linear relationship with soil water depletion above 60% in the 0.60 m soil profile with an R2 of 0.78. The CTM method was also compared to more commonly used scheduling methods namely: soil moisture monitoring (SMM) and crop evapotranspiration modeling (ETM). Grain yield was significantly lower for the CTM method than for the ETM method in 2018 and 2020 but not in 2019. No significant differences were observed in Irrigation Water Productivity (IWP) in 2018; however, all treatments were significantly different with the CTM method having the greatest IWP in 2020. For attempting to trigger full irrigation with the CTM method, a fixed DANS threshold of 0.5 °C was found to be more appropriate than the literature value of 1.0 °C, but consideration of crop growth stage would further improve scheduling.

Suggested Citation

  • Nakabuye, Hope Njuki & Rudnick, Daran & DeJonge, Kendall C. & Lo, Tsz Him & Heeren, Derek & Qiao, Xin & Franz, Trenton E. & Katimbo, Abia & Duan, Jiaming, 2022. "Real-time irrigation scheduling of maize using Degrees Above Non-Stressed (DANS) index in semi-arid environment," Agricultural Water Management, Elsevier, vol. 274(C).
    • Handle: RePEc:eee:agiwat:v:274:y:2022:i:c:s0378377422005042
    DOI: 10.1016/j.agwat.2022.107957
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377422005042
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2022.107957?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. O’Shaughnessy, Susan A. & Evett, Steven R. & Colaizzi, Paul D., 2015. "Dynamic prescription maps for site-specific variable rate irrigation of cotton," Agricultural Water Management, Elsevier, vol. 159(C), pages 123-138.
    2. Payero, J.O. & Tarkalson, D.D. & Irmak, S. & Davison, D. & Petersen, J.L., 2009. "Effect of timing of a deficit-irrigation allocation on corn evapotranspiration, yield, water use efficiency and dry mass," Agricultural Water Management, Elsevier, vol. 96(10), pages 1387-1397, October.
    3. Drechsler, Kelley & Kisekka, Isaya & Upadhyaya, Shrinivasa, 2019. "A comprehensive stress indicator for evaluating plant water status in almond trees," Agricultural Water Management, Elsevier, vol. 216(C), pages 214-223.
    4. Lo, Tsz Him & Rudnick, Daran R. & Burr, Charles A. & Stockton, Matthew C. & Werle, Rodrigo, 2019. "Approaches to evaluating grower irrigation and fertilizer nitrogen amount and timing," Agricultural Water Management, Elsevier, vol. 213(C), pages 693-706.
    5. Han, Ming & Zhang, Huihui & DeJonge, Kendall C. & Comas, Louise H. & Gleason, Sean, 2018. "Comparison of three crop water stress index models with sap flow measurements in maize," Agricultural Water Management, Elsevier, vol. 203(C), pages 366-375.
    6. Katimbo, Abia & Rudnick, Daran R. & DeJonge, Kendall C. & Lo, Tsz Him & Qiao, Xin & Franz, Trenton E. & Nakabuye, Hope Njuki & Duan, Jiaming, 2022. "Crop water stress index computation approaches and their sensitivity to soil water dynamics," Agricultural Water Management, Elsevier, vol. 266(C).
    7. Singh, Jasreman & Ge, Yufeng & Heeren, Derek M. & Walter-Shea, Elizabeth & Neale, Christopher M.U. & Irmak, Suat & Woldt, Wayne E. & Bai, Geng & Bhatti, Sandeep & Maguire, Mitchell S., 2021. "Inter-relationships between water depletion and temperature differential in row crop canopies in a sub-humid climate," Agricultural Water Management, Elsevier, vol. 256(C).
    8. King, B.A. & Tarkalson, D.D. & Sharma, V. & Bjorneberg, D.L., 2021. "Thermal Crop Water Stress Index Base Line Temperatures for Sugarbeet in Arid Western U.S," Agricultural Water Management, Elsevier, vol. 243(C).
    9. Payero, José O. & Tarkalson, David D. & Irmak, Suat & Davison, Don & Petersen, James L., 2008. "Effect of irrigation amounts applied with subsurface drip irrigation on corn evapotranspiration, yield, water use efficiency, and dry matter production in a semiarid climate," Agricultural Water Management, Elsevier, vol. 95(8), pages 895-908, August.
    10. Evett, Steven R. & Schwartz, Robert C. & Casanova, Joaquin J. & Heng, Lee K., 2012. "Soil water sensing for water balance, ET and WUE," Agricultural Water Management, Elsevier, vol. 104(C), pages 1-9.
    11. 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.
    12. O'Shaughnessy, Susan A. & Evett, Steven R. & Colaizzi, Paul D. & Howell, Terry A., 2012. "A crop water stress index and time threshold for automatic irrigation scheduling of grain sorghum," Agricultural Water Management, Elsevier, vol. 107(C), pages 122-132.
    13. Kullberg, Emily G. & DeJonge, Kendall C. & Chávez, José L., 2017. "Evaluation of thermal remote sensing indices to estimate crop evapotranspiration coefficients," Agricultural Water Management, Elsevier, vol. 179(C), pages 64-73.
    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. Hongjun Lei & Jie Yu & Hongwei Pan & Jie Li & Shah Jahan Leghari & Chongju Shang & Zheyuan Xiao & Cuicui Jin & Lili Shi, 2023. "A New Agricultural Drought Disaster Risk Assessment Framework: Coupled a Copula Function to Select Return Periods and the Jensen Model to Calculate Yield Loss," Sustainability, MDPI, vol. 15(4), pages 1-16, February.
    2. DeJonge, Kendall C. & Thorp, Kelly R. & Brekel, Josh & Pokoski, Tyler & Trout, Thomas J., 2024. "Customizing pyfao56 for evapotranspiration estimation and irrigation scheduling at the Limited Irrigation Research Farm (LIRF), Greeley, Colorado," Agricultural Water Management, Elsevier, vol. 299(C).
    3. Feng, Xudong & Bi, Shaojie & Li, Hongjun & Qi, Yongqing & Chen, Suying & Shao, Liwei, 2024. "Soil moisture forecasting for precision irrigation management using real-time electricity consumption records," Agricultural Water Management, Elsevier, vol. 291(C).

    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. Katimbo, Abia & Rudnick, Daran R. & DeJonge, Kendall C. & Lo, Tsz Him & Qiao, Xin & Franz, Trenton E. & Nakabuye, Hope Njuki & Duan, Jiaming, 2022. "Crop water stress index computation approaches and their sensitivity to soil water dynamics," Agricultural Water Management, Elsevier, vol. 266(C).
    2. Katimbo, Abia & Rudnick, Daran R. & Liang, Wei-zhen & DeJonge, Kendall C. & Lo, Tsz Him & Franz, Trenton E. & Ge, Yufeng & Qiao, Xin & Kabenge, Isa & Nakabuye, Hope Njuki & Duan, Jiaming, 2022. "Two source energy balance maize evapotranspiration estimates using close-canopy mobile infrared sensors and upscaling methods under variable water stress conditions," Agricultural Water Management, Elsevier, vol. 274(C).
    3. Ezenne, G.I. & Jupp, Louise & Mantel, S.K. & Tanner, J.L., 2019. "Current and potential capabilities of UAS for crop water productivity in precision agriculture," Agricultural Water Management, Elsevier, vol. 218(C), pages 158-164.
    4. Zhang, Minne & Zhao, Weixia & Zhu, Changxin & Li, Jiusheng, 2024. "Influence of the sampling time interval of canopy temperature on the dynamic zoning of variable rate irrigation," Agricultural Water Management, Elsevier, vol. 295(C).
    5. Bhatti, Sandeep & Heeren, Derek M. & Evett, Steven R. & O’Shaughnessy, Susan A. & Rudnick, Daran R. & Franz, Trenton E. & Ge, Yufeng & Neale, Christopher M.U., 2022. "Crop response to thermal stress without yield loss in irrigated maize and soybean in Nebraska," Agricultural Water Management, Elsevier, vol. 274(C).
    6. Wu, Yinshan & Jiang, Jie & Zhang, Xiufeng & Zhang, Jiayi & Cao, Qiang & Tian, Yongchao & Zhu, Yan & Cao, Weixing & Liu, Xiaojun, 2023. "Combining machine learning algorithm and multi-temporal temperature indices to estimate the water status of rice," Agricultural Water Management, Elsevier, vol. 289(C).
    7. Anzhen Qin & Dongfeng Ning & Zhandong Liu & Sen Li & Ben Zhao & Aiwang Duan, 2021. "Determining Threshold Values for a Crop Water Stress Index-Based Center Pivot Irrigation with Optimum Grain Yield," Agriculture, MDPI, vol. 11(10), pages 1-16, October.
    8. Stepanovic, Strahinja & Rudnick, Daran & Kruger, Greg, 2021. "Impact of maize hybrid selection on water productivity under deficit irrigation in semiarid western Nebraska," Agricultural Water Management, Elsevier, vol. 244(C).
    9. Zhang, Liyuan & Zhang, Huihui & Zhu, Qingzhen & Niu, Yaxiao, 2023. "Further investigating the performance of crop water stress index for maize from baseline fluctuation, effects of environmental factors, and variation of critical value," Agricultural Water Management, Elsevier, vol. 285(C).
    10. Tarkalson, David D. & King, Bradley A. & Bjorneberg, Dave L., 2022. "Maize grain yield and crop water productivity functions in the arid Northwest U.S," Agricultural Water Management, Elsevier, vol. 264(C).
    11. Kukal, M.S. & Irmak, S., 2020. "Impact of irrigation on interannual variability in United States agricultural productivity," Agricultural Water Management, Elsevier, vol. 234(C).
    12. Mukherjee, A. & Kundu, M. & Sarkar, S., 2010. "Role of irrigation and mulch on yield, evapotranspiration rate and water use pattern of tomato (Lycopersicon esculentum L.)," Agricultural Water Management, Elsevier, vol. 98(1), pages 182-189, December.
    13. Zou, Haiyang & Fan, Junliang & Zhang, Fucang & Xiang, Youzhen & Wu, Lifeng & Yan, Shicheng, 2020. "Optimization of drip irrigation and fertilization regimes for high grain yield, crop water productivity and economic benefits of spring maize in Northwest China," Agricultural Water Management, Elsevier, vol. 230(C).
    14. 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).
    15. Rudnick, D.R. & Irmak, S. & Djaman, K. & Sharma, V., 2017. "Impact of irrigation and nitrogen fertilizer rate on soil water trends and maize evapotranspiration during the vegetative and reproductive periods," Agricultural Water Management, Elsevier, vol. 191(C), pages 77-84.
    16. Wu, Yang & Jia, Zhikuan & Ren, Xiaolong & Zhang, Yan & Chen, Xin & Bing, Haoyang & Zhang, Peng, 2015. "Effects of ridge and furrow rainwater harvesting system combined with irrigation on improving water use efficiency of maize (Zea mays L.) in semi-humid area of China," Agricultural Water Management, Elsevier, vol. 158(C), pages 1-9.
    17. 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).
    18. Shao, Guomin & Han, Wenting & Zhang, Huihui & Zhang, Liyuan & Wang, Yi & Zhang, Yu, 2023. "Prediction of maize crop coefficient from UAV multisensor remote sensing using machine learning methods," Agricultural Water Management, Elsevier, vol. 276(C).
    19. Ihuoma, Samuel O. & Madramootoo, Chandra A., 2019. "Crop reflectance indices for mapping water stress in greenhouse grown bell pepper," Agricultural Water Management, Elsevier, vol. 219(C), pages 49-58.
    20. Zhang, Liyuan & Zhang, Huihui & Han, Wenting & Niu, Yaxiao & Chávez, José L. & Ma, Weitong, 2022. "Effects of image spatial resolution and statistical scale on water stress estimation performance of MGDEXG: A new crop water stress indicator derived from RGB images," Agricultural Water Management, Elsevier, vol. 264(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:274:y:2022:i:c:s0378377422005042. 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.