IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v250y2021ics0378377421001050.html
   My bibliography  Save this article

Simulated efficient growth-stage-based deficit irrigation strategies for maximizing cotton yield, crop water productivity and net returns

Author

Listed:
  • Himanshu, Sushil Kumar
  • Fan, Yubing
  • Ale, Srinivasulu
  • Bordovsky, James

Abstract

Declining water levels in the southern Ogallala Aquifer and associated reduction in irrigation capacities and increasing pumping costs necessitate adoption of deficit/limited irrigation practices for sustaining cotton production in the Texas High Plains (THP) region. The overall goal of this study was to evaluate the response of cotton crop to water stress in different growth stages and suggest efficient growth-stage-based deficit (GSBD) irrigation schedules for maximizing yield, crop water productivity (CWP) and economic returns under contrasting weather conditions using the CROPGRO-Cotton model. Five growth stages including seedling emergence/germination, squaring, early bloom/flower initiation, peak bloom, and boll opening/late bloom were considered. A combination of five irrigation scenarios (S1 through S5 with seasonal irrigation amounts of 240, 300, 360, 420 and 480 mm) and six irrigation treatments (T1 through T5: no irrigation in one of the five growth stages, and T6: irrigation applied in all five growth stages) were then simulated with a center pivot irrigation system. Skipping irrigation during the peak bloom growth stage (T4 treatment) resulted in the lowest yield, CWP and net returns under all weather conditions. The T1 irrigation treatment in which irrigation was skipped during the seedling emergence/germination stage was identified as the most efficient irrigation strategy for maximizing yield, CWP and net returns among all irrigation scenarios. Application of more than 360, 420 and 480 mm of irrigation water in wet, normal and dry years, respectively, did not significantly improve yield or net returns, and resulted in a decrease in CWP. These results imply that cotton responses to water deficit vary by growth stages, and adoption of appropriate GSBD irrigation strategies could optimize the use of limited water resources and extend the life of the southern Ogallala Aquifer.

Suggested Citation

  • Himanshu, Sushil Kumar & Fan, Yubing & Ale, Srinivasulu & Bordovsky, James, 2021. "Simulated efficient growth-stage-based deficit irrigation strategies for maximizing cotton yield, crop water productivity and net returns," Agricultural Water Management, Elsevier, vol. 250(C).
    • Handle: RePEc:eee:agiwat:v:250:y:2021:i:c:s0378377421001050
    DOI: 10.1016/j.agwat.2021.106840
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377421001050
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2021.106840?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. Geneille E. Greaves & Yu-Min Wang, 2017. "Identifying Irrigation Strategies for Improved Agricultural Water Productivity in Irrigated Maize Production through Crop Simulation Modelling," Sustainability, MDPI, vol. 9(4), pages 1-17, April.
    2. Geerts, Sam & Raes, Dirk, 2009. "Deficit irrigation as an on-farm strategy to maximize crop water productivity in dry areas," Agricultural Water Management, Elsevier, vol. 96(9), pages 1275-1284, September.
    3. Mitchell-McCallister, Donna & Williams, Ryan B. & Bordovsky, James & Mustian, Joseph & Ritchie, Glen & Lewis, Katie, 2020. "Maximizing profits via irrigation timing for capacity-constrained cotton production," Agricultural Water Management, Elsevier, vol. 229(C).
    4. Pereira, Luis S. & Cordery, Ian & Iacovides, Iacovos, 2012. "Improved indicators of water use performance and productivity for sustainable water conservation and saving," Agricultural Water Management, Elsevier, vol. 108(C), pages 39-51.
    5. O’Shaughnessy, Susan A. & Kim, Minyoung & Andrade, Manuel A. & Colaizzi, Paul D. & Evett, Steven R., 2020. "Site-specific irrigation of grain sorghum using plant and soil water sensing feedback - Texas High Plains," Agricultural Water Management, Elsevier, vol. 240(C).
    6. Kothari, Kritika & Ale, Srinivasulu & Bordovsky, James P. & Thorp, Kelly R. & Porter, Dana O. & Munster, Clyde L., 2019. "Simulation of efficient irrigation management strategies for grain sorghum production over different climate variability classes," Agricultural Systems, Elsevier, vol. 170(C), pages 49-62.
    7. Wang, Xingpeng & Wang, Hongbo & Si, Zhuanyun & Gao, Yang & Duan, Aiwang, 2020. "Modelling responses of cotton growth and yield to pre-planting soil moisture with the CROPGRO-Cotton model for a mulched drip irrigation system in the Tarim Basin," Agricultural Water Management, Elsevier, vol. 241(C).
    8. Himanshu, Sushil Kumar & Ale, Srinivasulu & Bordovsky, James & Darapuneni, Murali, 2019. "Evaluation of crop-growth-stage-based deficit irrigation strategies for cotton production in the Southern High Plains," Agricultural Water Management, Elsevier, vol. 225(C).
    9. Shareef, Muhammad & Gui, Dongwei & Zeng, Fanjiang & Waqas, Muhammad & Zhang, Bo & Iqbal, Hassan, 2018. "Water productivity, growth, and physiological assessment of deficit irrigated cotton on hyperarid desert-oases in northwest China," Agricultural Water Management, Elsevier, vol. 206(C), pages 1-10.
    10. Adhikari, Pradip & Ale, Srinivasulu & Bordovsky, James P. & Thorp, Kelly R. & Modala, Naga R. & Rajan, Nithya & Barnes, Edward M., 2016. "Simulating future climate change impacts on seed cotton yield in the Texas High Plains using the CSM-CROPGRO-Cotton model," Agricultural Water Management, Elsevier, vol. 164(P2), pages 317-330.
    11. Pereira, L.S. & Paredes, P. & Sholpankulov, E.D. & Inchenkova, O.P. & Teodoro, P.R. & Horst, M.G., 2009. "Irrigation scheduling strategies for cotton to cope with water scarcity in the Fergana Valley, Central Asia," Agricultural Water Management, Elsevier, vol. 96(5), pages 723-735, May.
    12. Zwart, Sander J. & Bastiaanssen, Wim G. M., 2004. "Review of measured crop water productivity values for irrigated wheat, rice, cotton and maize," Agricultural Water Management, Elsevier, vol. 69(2), pages 115-133, September.
    13. Araya, A. & Gowda, P.H. & Golden, B. & Foster, A.J. & Aguilar, J. & Currie, R. & Ciampitti, I.A. & Prasad, P.V.V., 2019. "Economic value and water productivity of major irrigated crops in the Ogallala aquifer region," Agricultural Water Management, Elsevier, vol. 214(C), pages 55-63.
    14. Garibay, Victoria M. & Kothari, Kritika & Ale, Srinivasulu & Gitz, Dennis C. & Morgan, Gaylon D. & Munster, Clyde L., 2019. "Determining water-use-efficient irrigation strategies for cotton using the DSSAT CSM CROPGRO-cotton model evaluated with in-season data," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    15. Li, Meng & Du, Yingji & Zhang, Fucang & Bai, Yungang & Fan, Junliang & Zhang, Jianghui & Chen, Shaoming, 2019. "Simulation of cotton growth and soil water content under film-mulched drip irrigation using modified CSM-CROPGRO-cotton model," Agricultural Water Management, Elsevier, vol. 218(C), pages 124-138.
    16. Fan, Yubing & Wang, Chenggang & Nan, Zhibiao, 2018. "Determining water use efficiency of wheat and cotton: A meta-regression analysis," Agricultural Water Management, Elsevier, vol. 199(C), pages 48-60.
    17. Hunsaker, D.J. & French, A.N. & Waller, P.M. & Bautista, E. & Thorp, K.R. & Bronson, K.F. & Andrade-Sanchez, P., 2015. "Comparison of traditional and ET-based irrigation scheduling of surface-irrigated cotton in the arid southwestern USA," Agricultural Water Management, Elsevier, vol. 159(C), pages 209-224.
    18. Playan, Enrique & Mateos, Luciano, 2006. "Modernization and optimization of irrigation systems to increase water productivity," Agricultural Water Management, Elsevier, vol. 80(1-3), pages 100-116, February.
    19. Islam, Adlul & Ahuja, Lajpat R. & Garcia, Luis A. & Ma, Liwang & Saseendran, Anapalli S. & Trout, Thomas J., 2012. "Modeling the impacts of climate change on irrigated corn production in the Central Great Plains," Agricultural Water Management, Elsevier, vol. 110(C), pages 94-108.
    20. Buttar, G.S. & Aujla, M.S. & Thind, H.S. & Singh, C.J. & Saini, K.S., 2007. "Effect of timing of first and last irrigation on the yield and water use efficiency in cotton," Agricultural Water Management, Elsevier, vol. 89(3), pages 236-242, May.
    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. Kumar, Hemendra & Srivastava, Puneet & Lamba, Jasmeet & Diamantopoulos, Efstathios & Ortiz, Brenda & Morata, Guilherme & Takhellambam, Bijoychandra & Bondesan, Luca, 2022. "Site-specific irrigation scheduling using one-layer soil hydraulic properties and inverse modeling," Agricultural Water Management, Elsevier, vol. 273(C).
    2. Manyowa N. Meki & Javier M. Osorio & Evelyn M. Steglich & James R. Kiniry, 2022. "Drought-Induced Nitrogen and Phosphorus Carryover Nutrients in Corn/Soybean Rotations in the Upper Mississippi River Basin," Sustainability, MDPI, vol. 14(22), pages 1-23, November.
    3. Liu, Lining & Zuo, Qiang & Shi, Jianchu & Wu, Xun & Wei, Congmin & Sheng, Jiandong & Jiang, Pingan & Chen, Quanjia & Ben-Gal, Alon, 2023. "Balancing economic benefits and environmental repercussions based on smart irrigation by regulating root zone water and salinity dynamics," Agricultural Water Management, Elsevier, vol. 285(C).
    4. Himanshu, Sushil K. & Ale, Srinivasulu & Bell, Jourdan & Fan, Yubing & Samanta, Sayantan & Bordovsky, James P. & Gitz III, Dennis C. & Lascano, Robert J. & Brauer, David K., 2023. "Evaluation of growth-stage-based variable deficit irrigation strategies for cotton production in the Texas High Plains," Agricultural Water Management, Elsevier, vol. 280(C).
    5. Imran Sajid & Bernhard Tischbein & Christian Borgemeister & Martina Flörke, 2022. "Assessing Barriers in Adaptation of Water Management Innovations under Rotational Canal Water Distribution System," Agriculture, MDPI, vol. 12(7), pages 1-16, June.
    6. Fan, Yubing & Himanshu, Sushil K. & Ale, Srinivasulu & DeLaune, Paul B. & Zhang, Tian & Park, Seong C. & Colaizzi, Paul D. & Evett, Steven R. & Baumhardt, R. Louis, 2022. "The synergy between water conservation and economic profitability of adopting alternative irrigation systems for cotton production in the Texas High Plains," Agricultural Water Management, Elsevier, vol. 262(C).
    7. Yang, Linshan & Feng, Qi & Lu, Tiaoxue & Adamowski, Jan F. & Yin, Zhenliang & Hatami, Shadi & Zhu, Meng & Wen, Xiaohu, 2023. "The response of agroecosystem water use efficiency to cropland change in northwest China’s Hexi Corridor," Agricultural Water Management, Elsevier, vol. 276(C).
    8. Desheng Wang & Chengkun Wang & Lichao Xu & Tiecheng Bai & Guozheng Yang, 2022. "Simulating Growth and Evaluating the Regional Adaptability of Cotton Fields with Non-Film Mulching in Xinjiang," Agriculture, MDPI, vol. 12(7), pages 1-20, June.
    9. Xiao, Chao & Ji, Qingyuan & Zhang, Fucang & Li, Yi & Fan, Junliang & Hou, Xianghao & Yan, Fulai & Liu, Xiaoqiang & Gong, Kaiyuan, 2023. "Effects of various soil water potential thresholds for drip irrigation on soil salinity, seed cotton yield and water productivity of cotton in northwest China," Agricultural Water Management, Elsevier, vol. 279(C).
    10. Wang, Hongbo & Li, Guohui & Huang, Weixiong & Li, Zhaoyang & Wang, Xingpeng & Gao, Yang, 2024. "Compensation of cotton yield by nitrogen fertilizer in non-mulched fields with deficit drip irrigation," Agricultural Water Management, Elsevier, vol. 298(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. Fan, Yubing & Himanshu, Sushil K. & Ale, Srinivasulu & DeLaune, Paul B. & Zhang, Tian & Park, Seong C. & Colaizzi, Paul D. & Evett, Steven R. & Baumhardt, R. Louis, 2022. "The synergy between water conservation and economic profitability of adopting alternative irrigation systems for cotton production in the Texas High Plains," Agricultural Water Management, Elsevier, vol. 262(C).
    2. Himanshu, Sushil K. & Ale, Srinivasulu & Bell, Jourdan & Fan, Yubing & Samanta, Sayantan & Bordovsky, James P. & Gitz III, Dennis C. & Lascano, Robert J. & Brauer, David K., 2023. "Evaluation of growth-stage-based variable deficit irrigation strategies for cotton production in the Texas High Plains," Agricultural Water Management, Elsevier, vol. 280(C).
    3. Himanshu, Sushil Kumar & Ale, Srinivasulu & Bordovsky, James & Darapuneni, Murali, 2019. "Evaluation of crop-growth-stage-based deficit irrigation strategies for cotton production in the Southern High Plains," Agricultural Water Management, Elsevier, vol. 225(C).
    4. Brar, Harjeet Singh & Singh, Pritpal, 2022. "Pre-and post-sowing irrigation scheduling impacts on crop phenology and water productivity of cotton (Gossypium hirsutum L.) in sub-tropical north-western India," Agricultural Water Management, Elsevier, vol. 274(C).
    5. Komlan Koudahe & Aleksey Y. Sheshukov & Jonathan Aguilar & Koffi Djaman, 2021. "Irrigation-Water Management and Productivity of Cotton: A Review," Sustainability, MDPI, vol. 13(18), pages 1-21, September.
    6. Ren, Dongyang & Xu, Xu & Engel, Bernard & Huang, Quanzhong & Xiong, Yunwu & Huo, Zailin & Huang, Guanhua, 2021. "A comprehensive analysis of water productivity in natural vegetation and various crops coexistent agro-ecosystems," Agricultural Water Management, Elsevier, vol. 243(C).
    7. Li, Xiaolin & Tong, Ling & Niu, Jun & Kang, Shaozhong & Du, Taisheng & Li, Sien & Ding, Risheng, 2017. "Spatio-temporal distribution of irrigation water productivity and its driving factors for cereal crops in Hexi Corridor, Northwest China," Agricultural Water Management, Elsevier, vol. 179(C), pages 55-63.
    8. Nouri, Milad & Homaee, Mehdi & Pereira, Luis S. & Bybordi, Mohammad, 2023. "Water management dilemma in the agricultural sector of Iran: A review focusing on water governance," Agricultural Water Management, Elsevier, vol. 288(C).
    9. Cheng, Minghui & Wang, Haidong & Fan, Junliang & Zhang, Shaohui & Wang, Yanli & Li, Yuepeng & Sun, Xin & Yang, Ling & Zhang, Fucang, 2021. "Water productivity and seed cotton yield in response to deficit irrigation: A global meta-analysis," Agricultural Water Management, Elsevier, vol. 255(C).
    10. 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).
    11. Liu, Qi & Niu, Jun & Wood, Jeffrey D. & Kang, Shaozhong, 2022. "Spatial optimization of cropping pattern in the upper-middle reaches of the Heihe River basin, Northwest China," Agricultural Water Management, Elsevier, vol. 264(C).
    12. Liu Liu & Zezhong Guo & Guanhua Huang & Ruotong Wang, 2019. "Water Productivity Evaluation under Multi-GCM Projections of Climate Change in Oases of the Heihe River Basin, Northwest China," IJERPH, MDPI, vol. 16(10), pages 1-17, May.
    13. Zhou, Qing & Zhang, Yali & Wu, Feng, 2021. "Evaluation of the most proper management scale on water use efficiency and water productivity: A case study of the Heihe River Basin, China," Agricultural Water Management, Elsevier, vol. 246(C).
    14. Mirshadiev, Mirzokhid & Fleskens, Luuk & van Dam, Jos & Pulatov, Alim, 2018. "Scoping of promising land management and water use practices in the dry areas of Uzbekistan," Agricultural Water Management, Elsevier, vol. 207(C), pages 15-25.
    15. Desheng Wang & Chengkun Wang & Lichao Xu & Tiecheng Bai & Guozheng Yang, 2022. "Simulating Growth and Evaluating the Regional Adaptability of Cotton Fields with Non-Film Mulching in Xinjiang," Agriculture, MDPI, vol. 12(7), pages 1-20, June.
    16. 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.
    17. 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).
    18. Darouich, Hanaa & Karfoul, Razan & Ramos, Tiago B. & Moustafa, Ali & Shaheen, Baraa & Pereira, Luis S., 2021. "Crop water requirements and crop coefficients for jute mallow (Corchorus olitorius L.) using the SIMDualKc model and assessing irrigation strategies for the Syrian Akkar region," Agricultural Water Management, Elsevier, vol. 255(C).
    19. Gao, Yang & Yang, Linlin & Shen, Xiaojun & Li, Xinqiang & Sun, Jingsheng & Duan, Aiwang & Wu, Laosheng, 2014. "Winter wheat with subsurface drip irrigation (SDI): Crop coefficients, water-use estimates, and effects of SDI on grain yield and water use efficiency," Agricultural Water Management, Elsevier, vol. 146(C), pages 1-10.
    20. Iqbal, M. Anjum & Bodner, G. & Heng, L.K. & Eitzinger, J. & Hassan, A., 2010. "Assessing yield optimization and water reduction potential for summer-sown and spring-sown maize in Pakistan," Agricultural Water Management, Elsevier, vol. 97(5), pages 731-737, May.

    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:250:y:2021:i:c:s0378377421001050. 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.