IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v286y2023ics0378377423002561.html
   My bibliography  Save this article

Optimizing relative root-zone water depletion thresholds to maximize yield and water productivity of winter wheat using AquaCrop

Author

Listed:
  • Zhang, Ting
  • Zuo, Qiang
  • Ma, Ning
  • Shi, Jianchu
  • Fan, Yuchuan
  • Wu, Xun
  • Wang, Lichun
  • Xue, Xuzhang
  • Ben-Gal, Alon

Abstract

Determination of relative root-zone water depletion (RRWD) thresholds to trigger irrigation is crucial to create optimal irrigation schedules targeting maximum yield and/or water productivity with limited water supply for a crop. In this study, a numerical procedure to determine RRWD thresholds was developed through coupling AquaCrop software with genetic-simplex algorithms. Using a two-year field lysimetric experiment for winter wheat conducted in the North China Plain (NCP), AquaCrop adequately simulated canopy cover, final aboveground biomass, grain yield, seasonal evapotranspiration, and soil water storage, with the normalized root mean squared error (NRMSE) smaller than 15 % and determination coefficient (R2) larger than 0.84. The global optimum range of RRWD thresholds was preliminarily determined using the genetic algorithm, and subsequently final RRWD thresholds were optimized by fine tuning using the simplex algorithm. The RRWD threshold combinations (composed of the RRWD thresholds to trigger different sequential irrigation events) for varying number of irrigation events (i.e.1–4) were optimized based on 39 years of historical meteorological data, and the effects of climate change on the optimal crop yield (Ya, opt), water productivity (WPopt), and the combinations of optimized RRWD threshold (RRWDopt) were investigated. The results indicated that both Ya, opt and WPopt generally increased with time showing a tendency of gradually elevated annual CO2 concentration and seasonal average effective temperature. Irrespective of the number of irrigation events during the winter wheat growing season, the differences of RRWDopt for different combinations of irrigation sequence and event in the same kind of hydrological year were relatively small, with a coefficient of variation consistently less than 23 % and a mean of 8 %. When combinations of mean RRWDopt were applied into AquaCrop to trigger irrigation for winter wheat in various hydrological years, the simulated yield (Ya, sim) and water productivity (WPsim) under 1–4 irrigation events were found to be comparable to their respective optimums (Ya, opt and WPopt), with all the values of Ya, sim (WPsim) falling in the range of 92 %Ya, opt (90 %WPopt). Therefore, the mean RRWDopt should be helpful to formulate rational irrigation management strategies of winter wheat under changing climatic conditions in the NCP.

Suggested Citation

  • Zhang, Ting & Zuo, Qiang & Ma, Ning & Shi, Jianchu & Fan, Yuchuan & Wu, Xun & Wang, Lichun & Xue, Xuzhang & Ben-Gal, Alon, 2023. "Optimizing relative root-zone water depletion thresholds to maximize yield and water productivity of winter wheat using AquaCrop," Agricultural Water Management, Elsevier, vol. 286(C).
  • Handle: RePEc:eee:agiwat:v:286:y:2023:i:c:s0378377423002561
    DOI: 10.1016/j.agwat.2023.108391
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377423002561
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.agwat.2023.108391?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. Paredes, P. & Wei, Z. & Liu, Y. & Xu, D. & Xin, Y. & Zhang, B. & Pereira, L.S., 2015. "Performance assessment of the FAO AquaCrop model for soil water, soil evaporation, biomass and yield of soybeans in North China Plain," Agricultural Water Management, Elsevier, vol. 152(C), pages 57-71.
    2. Umesh, Barikara & Reddy, K.S. & Polisgowdar, B.S. & Maruthi, V. & Satishkumar, U. & Ayyanagoudar, M.S. & Rao, Sathyanarayan & Veeresh, H., 2022. "Assessment of climate change impact on maize (Zea mays L.) through aquacrop model in semi-arid alfisol of southern Telangana," Agricultural Water Management, Elsevier, vol. 274(C).
    3. Fernández, J.E. & Alcon, F. & Diaz-Espejo, A. & Hernandez-Santana, V. & Cuevas, M.V., 2020. "Water use indicators and economic analysis for on-farm irrigation decision: A case study of a super high density olive tree orchard," Agricultural Water Management, Elsevier, vol. 237(C).
    4. Iqbal, M. Anjum & Shen, Yanjun & Stricevic, Ruzica & Pei, Hongwei & Sun, Hongyoung & Amiri, Ebrahim & Penas, Angel & del Rio, Sara, 2014. "Evaluation of the FAO AquaCrop model for winter wheat on the North China Plain under deficit irrigation from field experiment to regional yield simulation," Agricultural Water Management, Elsevier, vol. 135(C), pages 61-72.
    5. Shi, Jianchu & Wu, Xun & Wang, Xiaoyu & Zhang, Mo & Han, Le & Zhang, Wenjing & Liu, Wen & Zuo, Qiang & Wu, Xiaoguang & Zhang, Hongfei & Ben-Gal, Alon, 2020. "Determining threshold values for root-soil water weighted plant water deficit index based smart irrigation," Agricultural Water Management, Elsevier, vol. 230(C).
    6. Feng, Dingrui & Li, Guangyong & Wang, Dan & Wulazibieke, Mierguli & Cai, Mingkun & Kang, Jing & Yuan, Zicheng & Xu, Houcheng, 2022. "Evaluation of AquaCrop model performance under mulched drip irrigation for maize in Northeast China," Agricultural Water Management, Elsevier, vol. 261(C).
    7. Wu, Xun & Zhang, Wenjing & Liu, Wen & Zuo, Qiang & Shi, Jianchu & Yan, Xudong & Zhang, Hongfei & Xue, Xuzhang & Wang, Lichun & Zhang, Mo & Ben-Gal, Alon, 2017. "Root-weighted soil water status for plant water deficit index based irrigation scheduling," Agricultural Water Management, Elsevier, vol. 189(C), pages 137-147.
    8. Alonso Campos, J.C. & Jiménez-Bello, M.A. & Martínez Alzamora, F., 2020. "Real-time energy optimization of irrigation scheduling by parallel multi-objective genetic algorithms," Agricultural Water Management, Elsevier, vol. 227(C).
    9. Li, Jiang & Song, Jian & Li, Mo & Shang, Songhao & Mao, Xiaomin & Yang, Jian & Adeloye, Adebayo J., 2018. "Optimization of irrigation scheduling for spring wheat based on simulation-optimization model under uncertainty," Agricultural Water Management, Elsevier, vol. 208(C), pages 245-260.
    10. Andarzian, B. & Bannayan, M. & Steduto, P. & Mazraeh, H. & Barati, M.E. & Barati, M.A. & Rahnama, A., 2011. "Validation and testing of the AquaCrop model under full and deficit irrigated wheat production in Iran," Agricultural Water Management, Elsevier, vol. 100(1), pages 1-8.
    11. Toumi, J. & Er-Raki, S. & Ezzahar, J. & Khabba, S. & Jarlan, L. & Chehbouni, A., 2016. "Performance assessment of AquaCrop model for estimating evapotranspiration, soil water content and grain yield of winter wheat in Tensift Al Haouz (Morocco): Application to irrigation management," Agricultural Water Management, Elsevier, vol. 163(C), pages 219-235.
    12. Adeboye, Omotayo B. & Schultz, Bart & Adekalu, Kenneth O. & Prasad, Krishna C., 2019. "Performance evaluation of AquaCrop in simulating soil water storage, yield, and water productivity of rainfed soybeans (Glycine max L. merr) in Ile-Ife, Nigeria," Agricultural Water Management, Elsevier, vol. 213(C), pages 1130-1146.
    13. Allen, Richard G. & Pereira, Luis S. & Howell, Terry A. & Jensen, Marvin E., 2011. "Evapotranspiration information reporting: I. Factors governing measurement accuracy," Agricultural Water Management, Elsevier, vol. 98(6), pages 899-920, April.
    14. Zhang, Xiying & Chen, Suying & Sun, Hongyong & Shao, Liwei & Wang, Yanzhe, 2011. "Changes in evapotranspiration over irrigated winter wheat and maize in North China Plain over three decades," Agricultural Water Management, Elsevier, vol. 98(6), pages 1097-1104, April.
    15. Seyed Ahmadi & Elnaz Mosallaeepour & Ali Kamgar-Haghighi & Ali Sepaskhah, 2015. "Modeling Maize Yield and Soil Water Content with AquaCrop Under Full and Deficit Irrigation Managements," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2837-2853, June.
    16. You, Yongliang & Song, Ping & Yang, Xianlong & Zheng, Yapeng & Dong, Li & Chen, Jing, 2022. "Optimizing irrigation for winter wheat to maximize yield and maintain high-efficient water use in a semi-arid environment," Agricultural Water Management, Elsevier, vol. 273(C).
    17. Tan, Shuai & Wang, Quanjiu & Zhang, Jihong & Chen, Yong & Shan, Yuyang & Xu, Di, 2018. "Performance of AquaCrop model for cotton growth simulation under film-mulched drip irrigation in southern Xinjiang, China," Agricultural Water Management, Elsevier, vol. 196(C), pages 99-113.
    18. Zhang, Chao & Xie, Ziang & Wang, Qiaojuan & Tang, Min & Feng, Shaoyuan & Cai, Huanjie, 2022. "AquaCrop modeling to explore optimal irrigation of winter wheat for improving grain yield and water productivity," Agricultural Water Management, Elsevier, vol. 266(C).
    19. Foster, T. & Brozović, N., 2018. "Simulating Crop-Water Production Functions Using Crop Growth Models to Support Water Policy Assessments," Ecological Economics, Elsevier, vol. 152(C), pages 9-21.
    20. Xu, Junzeng & Bai, Wenhuan & Li, Yawei & Wang, Haiyu & Yang, Shihong & Wei, Zheng, 2019. "Modeling rice development and field water balance using AquaCrop model under drying-wetting cycle condition in eastern China," Agricultural Water Management, Elsevier, vol. 213(C), pages 289-297.
    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. Zhu, Hongyan & Zheng, Bingyan & Nie, Weibo & Fei, Liangjun & Shan, Yuyang & Li, Ge & Liang, Fei, 2024. "Optimization of maize irrigation strategy in Xinjiang, China by AquaCrop based on a four-year study," Agricultural Water Management, Elsevier, vol. 297(C).
    2. Ewa Panek-Chwastyk & Ceren Nisanur Ozbilge & Katarzyna Dąbrowska-Zielińska & Konrad Wróblewski, 2024. "Assessment of Grassland Biomass Prediction Using AquaCrop Model: Integrating Sentinel-2 Data and Ground Measurements in Wielkopolska and Podlasie Regions, Poland," Agriculture, MDPI, vol. 14(6), pages 1-16, May.

    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. Zhu, Hongyan & Zheng, Bingyan & Nie, Weibo & Fei, Liangjun & Shan, Yuyang & Li, Ge & Liang, Fei, 2024. "Optimization of maize irrigation strategy in Xinjiang, China by AquaCrop based on a four-year study," Agricultural Water Management, Elsevier, vol. 297(C).
    2. Ran, Hui & Kang, Shaozhong & Li, Fusheng & Tong, Ling & Ding, Risheng & Du, Taisheng & Li, Sien & Zhang, Xiaotao, 2017. "Performance of AquaCrop and SIMDualKc models in evapotranspiration partitioning on full and deficit irrigated maize for seed production under plastic film-mulch in an arid region of China," Agricultural Systems, Elsevier, vol. 151(C), pages 20-32.
    3. Er-Raki, S. & Bouras, E. & Rodriguez, J.C. & Watts, C.J. & Lizarraga-Celaya, C. & Chehbouni, A., 2021. "Parameterization of the AquaCrop model for simulating table grapes growth and water productivity in an arid region of Mexico," Agricultural Water Management, Elsevier, vol. 245(C).
    4. Wang, Haidong & Cheng, Minghui & Liao, Zhenqi & Guo, Jinjin & Zhang, Fucang & Fan, Junliang & Feng, Hao & Yang, Qiliang & Wu, Lifeng & Wang, Xiukang, 2023. "Performance evaluation of AquaCrop and DSSAT-SUBSTOR-Potato models in simulating potato growth, yield and water productivity under various drip fertigation regimes," Agricultural Water Management, Elsevier, vol. 276(C).
    5. Zhang, Chao & Xie, Ziang & Wang, Qiaojuan & Tang, Min & Feng, Shaoyuan & Cai, Huanjie, 2022. "AquaCrop modeling to explore optimal irrigation of winter wheat for improving grain yield and water productivity," Agricultural Water Management, Elsevier, vol. 266(C).
    6. Feng, Dingrui & Li, Guangyong & Wang, Dan & Wulazibieke, Mierguli & Cai, Mingkun & Kang, Jing & Yuan, Zicheng & Xu, Houcheng, 2022. "Evaluation of AquaCrop model performance under mulched drip irrigation for maize in Northeast China," Agricultural Water Management, Elsevier, vol. 261(C).
    7. Pereira, Luis S. & Paredes, Paula & Rodrigues, Gonçalo C. & Neves, Manuela, 2015. "Modeling malt barley water use and evapotranspiration partitioning in two contrasting rainfall years. Assessing AquaCrop and SIMDualKc models," Agricultural Water Management, Elsevier, vol. 159(C), pages 239-254.
    8. Cheng, Minghui & Wang, Haidong & Fan, Junliang & Xiang, Youzhen & Liu, Xiaoqiang & Liao, Zhenqi & Abdelghany, Ahmed Elsayed & Zhang, Fucang & Li, Zhijun, 2022. "Evaluation of AquaCrop model for greenhouse cherry tomato with plastic film mulch under various water and nitrogen supplies," Agricultural Water Management, Elsevier, vol. 274(C).
    9. Tinashe Lindel Dirwai & Aidan Senzanje & Tafadzwanashe Mabhaudhi, 2021. "Calibration and Evaluation of the FAO AquaCrop Model for Canola ( Brassica napus ) under Varied Moistube Irrigation Regimes," Agriculture, MDPI, vol. 11(5), pages 1-18, May.
    10. Ran, Hui & Kang, Shaozhong & Li, Fusheng & Du, Taisheng & Tong, Ling & Li, Sien & Ding, Risheng & Zhang, Xiaotao, 2018. "Parameterization of the AquaCrop model for full and deficit irrigated maize for seed production in arid Northwest China," Agricultural Water Management, Elsevier, vol. 203(C), pages 438-450.
    11. Alex Zizinga & Jackson Gilbert Majaliwa Mwanjalolo & Britta Tietjen & Bobe Bedadi & Ramon Amaro de Sales & Dennis Beesigamukama, 2022. "Simulating Maize Productivity under Selected Climate Smart Agriculture Practices Using AquaCrop Model in a Sub-humid Environment," Sustainability, MDPI, vol. 14(4), pages 1-17, February.
    12. Ahmad, Mirza Junaid & Iqbal, Muhammad Anjum & Choi, Kyung Sook, 2020. "Climate-driven constraints in sustaining future wheat yield and water productivity," Agricultural Water Management, Elsevier, vol. 231(C).
    13. Wu, Hui & Yue, Qiong & Guo, Ping & Xu, Xiaoyu & Huang, Xi, 2022. "Improving the AquaCrop model to achieve direct simulation of evapotranspiration under nitrogen stress and joint simulation-optimization of irrigation and fertilizer schedules," Agricultural Water Management, Elsevier, vol. 266(C).
    14. Sandhu, Rupinder & Irmak, Suat, 2019. "Performance of AquaCrop model in simulating maize growth, yield, and evapotranspiration under rainfed, limited and full irrigation," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    15. Qiu, Rangjian & Li, Longan & Liu, Chunwei & Wang, Zhenchang & Zhang, Baozhong & Liu, Zhandong, 2022. "Evapotranspiration estimation using a modified crop coefficient model in a rotated rice-winter wheat system," Agricultural Water Management, Elsevier, vol. 264(C).
    16. 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).
    17. Adeboye, Omotayo B. & Schultz, Bart & Adekalu, Kenneth O. & Prasad, Krishna C., 2019. "Performance evaluation of AquaCrop in simulating soil water storage, yield, and water productivity of rainfed soybeans (Glycine max L. merr) in Ile-Ife, Nigeria," Agricultural Water Management, Elsevier, vol. 213(C), pages 1130-1146.
    18. Ahmadzadeh Araji, Hamidreza & Wayayok, Aimrun & Massah Bavani, Alireza & Amiri, Ebrahim & Abdullah, Ahmad Fikri & Daneshian, Jahanfar & Teh, C.B.S., 2018. "Impacts of climate change on soybean production under different treatments of field experiments considering the uncertainty of general circulation models," Agricultural Water Management, Elsevier, vol. 205(C), pages 63-71.
    19. Toumi, J. & Er-Raki, S. & Ezzahar, J. & Khabba, S. & Jarlan, L. & Chehbouni, A., 2016. "Performance assessment of AquaCrop model for estimating evapotranspiration, soil water content and grain yield of winter wheat in Tensift Al Haouz (Morocco): Application to irrigation management," Agricultural Water Management, Elsevier, vol. 163(C), pages 219-235.
    20. Zhang, Chao & Liu, Jiangui & Shang, Jiali & Dong, Taifeng & Tang, Min & Feng, Shaoyuan & Cai, Huanjie, 2021. "Improving winter wheat biomass and evapotranspiration simulation by assimilating leaf area index from spectral information into a crop growth model," Agricultural Water Management, Elsevier, vol. 255(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:286:y:2023:i:c:s0378377423002561. 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.