IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v230y2020ics0378377419314283.html
   My bibliography  Save this article

Modeling corn growth and root zone salinity dynamics to improve irrigation and fertigation management under semi-arid conditions

Author

Listed:
  • Chauhdary, Junaid Nawaz
  • Bakhsh, Allah
  • Ragab, Ragab
  • Khaliq, Abdul
  • Engel, Bernard A.
  • Rizwan, Muhammad
  • Shahid, Muhammad Adnan
  • Nawaz, Qamar

Abstract

Modeling is an advanced technique to study the effects of crop management practices as management scenario simulations in a convenient and economical way. A multi seasonal study was conducted on corn, sown under drip irrigation, to assess its growth under three irrigation intervals (I1: irrigation on daily basis, I2: irrigation on 3rd day and I3: irrigation on 5th day) and three fertigation levels [F1:100 % RFA (recommended fertigation applications), F2:75 % RFA and F3:50 % RFA)] of two types of fertilizers (M1: Imported and M2: Indigenous). The SALTMED model was calibrated and validated, using data collected from experiments, to explore different management scenarios of corn production. The accuracy of the validation process was examined by root mean square error (RMSE), percentage of difference (%D), coefficient of residual mass (CRM) and coefficient of determination (R2). The results showed that corn produced statistically highest plant height (183.7 cm), dry matter (16.9 t/ha), grain yield (8.57 t/ha) and water productivity (1.52 kg/m3) under I1 in comparison to that under other irrigation intervals. Similarly, M1 and F1 produced statistically highest plant height, dry matter, grain yield and water productivity as compared to M2 and other fertigation levels, respectively. SALTMED simulated soil moisture and soil salinity accurately with average values of RMSE, R2 and CRM as 0.013, 0.850 and -0.002, respectively for soil moisture and 0.479, 0.864 and 0.130, respectively for soil salinity. The SALTMED simulations showed good results also for grain yield (RMSE = 0.475, R2 = 0.873, CRM = -0.0013 and highest %D = -4.9 %) and dry matter (RMSE = 0.596, R2 = 0.909, CRM = -0.027 and highest %D = 4.2 %). Overall, it was concluded that corn should be irrigated on daily basis under drip irrigation and fertilized with 100 % RFA. Moreover, the SALTMED model proved to be a useful tool for simulations of different management scenarios regarding corn growth and root zone salinity dynamics with reliable results under semi-arid conditions.

Suggested Citation

  • Chauhdary, Junaid Nawaz & Bakhsh, Allah & Ragab, Ragab & Khaliq, Abdul & Engel, Bernard A. & Rizwan, Muhammad & Shahid, Muhammad Adnan & Nawaz, Qamar, 2020. "Modeling corn growth and root zone salinity dynamics to improve irrigation and fertigation management under semi-arid conditions," Agricultural Water Management, Elsevier, vol. 230(C).
  • Handle: RePEc:eee:agiwat:v:230:y:2020:i:c:s0378377419314283
    DOI: 10.1016/j.agwat.2019.105952
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377419314283
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.agwat.2019.105952?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. El-Hendawy, Salah E. & Schmidhalter, Urs, 2010. "Optimal coupling combinations between irrigation frequency and rate for drip-irrigated maize grown on sandy soil," Agricultural Water Management, Elsevier, vol. 97(3), pages 439-448, March.
    2. Hassanli, Mohammad & Ebrahimian, Hamed & Mohammadi, Ehsan & Rahimi, Amirreza & Shokouhi, Amirhossein, 2016. "Simulating maize yields when irrigating with saline water, using the AquaCrop, SALTMED, and SWAP models," Agricultural Water Management, Elsevier, vol. 176(C), pages 91-99.
    3. Ragab, R. & Malash, N. & Abdel Gawad, G. & Arslan, A. & Ghaibeh, A., 2005. "A holistic generic integrated approach for irrigation, crop and field management: 1. The SALTMED model and its calibration using field data from Egypt and Syria," Agricultural Water Management, Elsevier, vol. 78(1-2), pages 67-88, September.
    4. Chauhdary, Junaid Nawaz & Bakhsh, Allah & Engel, Bernard A. & Ragab, Ragab, 2019. "Improving corn production by adopting efficient fertigation practices: Experimental and modeling approach," Agricultural Water Management, Elsevier, vol. 221(C), pages 449-461.
    5. Afzal, M. & Battilani, A. & Solimando, D. & Ragab, R., 2016. "Improving water resources management using different irrigation strategies and water qualities: Field and modelling study," Agricultural Water Management, Elsevier, vol. 176(C), pages 40-54.
    6. Dagdelen, Necdet & Yilmaz, Ersel & Sezgin, Fuat & Gurbuz, Talih, 2006. "Water-yield relation and water use efficiency of cotton (Gossypium hirsutum L.) and second crop corn (Zea mays L.) in western Turkey," Agricultural Water Management, Elsevier, vol. 82(1-2), pages 63-85, April.
    7. Ragab, R. & Malash, N. & Gawad, G. Abdel & Arslan, A. & Ghaibeh, A., 2005. "A holistic generic integrated approach for irrigation, crop and field management: 2. The SALTMED model validation using field data of five growing seasons from Egypt and Syria," Agricultural Water Management, Elsevier, vol. 78(1-2), pages 89-107, September.
    8. Flowers, T.J. & Ragab, R. & Malash, N. & Gawad, G. Abdel & Cuartero, J. & Arslan, A., 2005. "Sustainable strategies for irrigation in salt-prone Mediterranean: SALTMED," Agricultural Water Management, Elsevier, vol. 78(1-2), pages 3-14, September.
    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. Muhammad Adnan Shahid & Junaid Nawaz Chauhdary & Muhammad Usman & Muhammad Uzair Qamar & Abdul Shabbir, 2022. "Assessment of Water Productivity Enhancement and Sustainability Potential of Different Resource Conservation Technologies: A Review in the Context of Pakistan," Agriculture, MDPI, vol. 12(7), pages 1-16, July.
    2. Yu, Qihua & Kang, Shaozhong & Hu, Shunjun & Zhang, Lu & Zhang, Xiaotao, 2021. "Modeling soil water-salt dynamics and crop response under severely saline condition using WAVES: Searching for a target irrigation volume for saline water irrigation," Agricultural Water Management, Elsevier, vol. 256(C).
    3. Chauhdary, Junaid Nawaz & Li, Hong & Akbar, Nadeem & Javaid, Maria & Rizwan, Muhammad & Akhlaq, Muhammad, 2024. "Evaluating corn production under different plant spacings through integrated modeling approach and simulating its future response under climate change scenarios," Agricultural Water Management, Elsevier, vol. 293(C).
    4. Pereira, L.S. & Paredes, P. & Hunsaker, D.J. & López-Urrea, R. & Mohammadi Shad, Z., 2021. "Standard single and basal crop coefficients for field crops. Updates and advances to the FAO56 crop water requirements method," Agricultural Water Management, Elsevier, vol. 243(C).
    5. Liu, Meihan & Shi, Haibin & Paredes, Paula & Ramos, Tiago B. & Dai, Liping & Feng, Zhuangzhuang & Pereira, Luis S., 2022. "Estimating and partitioning maize evapotranspiration as affected by salinity using weighing lysimeters and the SIMDualKc model," Agricultural Water Management, Elsevier, vol. 261(C).
    6. Che, Zheng & Wang, Jun & Li, Jiusheng, 2022. "Modeling strategies to balance salt leaching and nitrogen loss for drip irrigation with saline water in arid regions," Agricultural Water Management, Elsevier, vol. 274(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. Chauhdary, Junaid Nawaz & Bakhsh, Allah & Engel, Bernard A. & Ragab, Ragab, 2019. "Improving corn production by adopting efficient fertigation practices: Experimental and modeling approach," Agricultural Water Management, Elsevier, vol. 221(C), pages 449-461.
    2. Karandish, Fatemeh & Šimůnek, Jiří, 2019. "A comparison of the HYDRUS (2D/3D) and SALTMED models to investigate the influence of various water-saving irrigation strategies on the maize water footprint," Agricultural Water Management, Elsevier, vol. 213(C), pages 809-820.
    3. El-Shafie, A.F. & Osama, M.A. & Hussein, M.M. & El-Gindy, A.M. & Ragab, R., 2017. "Predicting soil moisture distribution, dry matter, water productivity and potato yield under a modified ‎gated pipe irrigation system: SALTMED model application using field experimental data," Agricultural Water Management, Elsevier, vol. 184(C), pages 221-233.
    4. Chen, Weiping & Hou, Zhenan & Wu, Laosheng & Liang, Yongchao & Wei, Changzhou, 2010. "Evaluating salinity distribution in soil irrigated with saline water in arid regions of northwest China," Agricultural Water Management, Elsevier, vol. 97(12), pages 2001-2008, November.
    5. Abdelraouf R. E. & H. G. Ghanem & Najat A. Bukhari & Mohamed El-Zaidy, 2020. "Field and Modeling Study on Manual and Automatic Irrigation Scheduling under Deficit Irrigation of Greenhouse Cucumber," Sustainability, MDPI, vol. 12(23), pages 1-20, November.
    6. Ramos, Tiago B. & Darouich, Hanaa & Šimůnek, Jiří & Gonçalves, Maria C. & Martins, José C., 2019. "Soil salinization in very high-density olive orchards grown in southern Portugal: Current risks and possible trends," Agricultural Water Management, Elsevier, vol. 217(C), pages 265-281.
    7. Minhas, P.S. & Ramos, Tiago B. & Ben-Gal, Alon & Pereira, Luis S., 2020. "Coping with salinity in irrigated agriculture: Crop evapotranspiration and water management issues," Agricultural Water Management, Elsevier, vol. 227(C).
    8. Wang, Lichun & Ning, Songrui & Chen, Xiaoli & Li, Youli & Guo, Wenzhong & Ben-Gal, Alon, 2021. "Modeling tomato root water uptake influenced by soil salinity under drip irrigation with an inverse method," Agricultural Water Management, Elsevier, vol. 255(C).
    9. Afzal, M. & Battilani, A. & Solimando, D. & Ragab, R., 2016. "Improving water resources management using different irrigation strategies and water qualities: Field and modelling study," Agricultural Water Management, Elsevier, vol. 176(C), pages 40-54.
    10. Zou, Ping & Yang, Jingsong & Fu, Jianrong & Liu, Guangming & Li, Dongshun, 2010. "Artificial neural network and time series models for predicting soil salt and water content," Agricultural Water Management, Elsevier, vol. 97(12), pages 2009-2019, November.
    11. Barnard, J.H. & Bennie, A.T.P. & van Rensburg, L.D. & Preez, C.C. du, 2015. "SWAMP: A soil layer water supply model for simulating macroscopic crop water uptake under osmotic stress," Agricultural Water Management, Elsevier, vol. 148(C), pages 150-163.
    12. Yang, Chenyao & Fraga, Helder & Ieperen, Wim Van & Santos, João Andrade, 2017. "Assessment of irrigated maize yield response to climate change scenarios in Portugal," Agricultural Water Management, Elsevier, vol. 184(C), pages 178-190.
    13. Abdulaziz G. Alghamdi & Anwar A. Aly & Hesham M. Ibrahim, 2022. "Effect of Climate Change on the Quality of Soil, Groundwater, and Pomegranate Fruit Production in Al-Baha Region, Saudi Arabia: A Modeling Study Using SALTMED," Sustainability, MDPI, vol. 14(20), pages 1-16, October.
    14. Hassanli, Mohammad & Ebrahimian, Hamed & Mohammadi, Ehsan & Rahimi, Amirreza & Shokouhi, Amirhossein, 2016. "Simulating maize yields when irrigating with saline water, using the AquaCrop, SALTMED, and SWAP models," Agricultural Water Management, Elsevier, vol. 176(C), pages 91-99.
    15. 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.
    16. Gheysari, Mahdi & Mirlatifi, Seyed Majid & Bannayan, Mohammad & Homaee, Mehdi & Hoogenboom, Gerrit, 2009. "Interaction of water and nitrogen on maize grown for silage," Agricultural Water Management, Elsevier, vol. 96(5), pages 809-821, May.
    17. Yunfeng Li & Quanqing Feng & Dongwei Li & Mingfa Li & Huifeng Ning & Qisheng Han & Abdoul Kader Mounkaila Hamani & Yang Gao & Jingsheng Sun, 2022. "Water-Salt Thresholds of Cotton ( Gossypium hirsutum L.) under Film Drip Irrigation in Arid Saline-Alkali Area," Agriculture, MDPI, vol. 12(11), pages 1-21, October.
    18. Feng, Genxiang & Zhu, Chengli & Wu, Qingfeng & Wang, Ce & Zhang, Zhanyu & Mwiya, Richwell Mubita & Zhang, Li, 2021. "Evaluating the impacts of saline water irrigation on soil water-salt and summer maize yield in subsurface drainage condition using coupled HYDRUS and EPIC model," Agricultural Water Management, Elsevier, vol. 258(C).
    19. Tsakmakis, I.D. & Gikas, G.D. & Sylaios, G.K., 2021. "Integration of Sentinel-derived NDVI to reduce uncertainties in the operational field monitoring of maize," Agricultural Water Management, Elsevier, vol. 255(C).
    20. Robel Admasu & Abraham W Michael & Tilahun Hordofa, 2019. "Senior Irrigation Researcher, Melkassa Agricultural Research Center, Ethiopia," International Journal of Environmental Sciences & Natural Resources, Juniper Publishers Inc., vol. 16(4), pages 83-87, January.

    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:230:y:2020:i:c:s0378377419314283. 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.