IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v37y2023i5d10.1007_s11269-023-03465-5.html
   My bibliography  Save this article

Impact of Climate Change on Crop Irrigation Requirements in Arid Regions

Author

Listed:
  • Maha Alotaibi

    (Kuwait University)

  • Nawaf S. Alhajeri

    (Kuwait University)

  • Fahad M. Al-Fadhli

    (Kuwait University)

  • Salem Al Jabri

    (Sultan Qaboos University)

  • Mohamed Gabr

    (Higher Institute for Engineering and Technology)

Abstract

The nations that comprise the Gulf Cooperation Council (GCC) are located in one of the most water-stressed regions in the world. This region has faced serious socioeconomic and environmental development issues as a result of its increasing water demand over time. The extreme aridity, high rates of evaporation, and scarcity of nonrenewable groundwater resources in the GCC countries pose a significant threat to food security. This study aims to explore the impact of climate change on the potential availability of irrigation water in the State of Kuwait, which serves as an example of all GCC nations. A modeling scheme using CropWat8 was developed to study the impact of four climate change scenarios (encompassing the past, present, and future) on the net and gross irrigation water requirements (NIWR and GIWR) for selected agricultural crops, while also determining optimum irrigation schedules. Scenario 1 represented past climate conditions (1996–2006), while Scenario 2 represented the current situation (2007–2021). Projected scenarios (3 and 4) were analyzed using Representative Concentration Pathways (RCP) 4.5 and RCP 8.5, which were adopted by the IPCC to project the concentrations of greenhouse gases (GHG) emissions for 2060. The simulation results showed that compared with the current GHG levels, the increase in GHG emissions also increased the demand for NIWR by a minimum of 8.2% and a maximum of 15% for the same agricultural areas and cropping patterns. The measured GIWR in the field was 1915 m3, while the simulated NIWR was 1724 m3. With a drip irrigation efficiency of 90%, the model adequately demonstrated the validity of the CropWat8 package for simulating the climate impact on crop water requirements with a precision of approximately 92.2%. These findings suggest that the GCC countries should develop strategies to minimize GHG emissions and adopt innovative solutions for better management of water resources.

Suggested Citation

  • Maha Alotaibi & Nawaf S. Alhajeri & Fahad M. Al-Fadhli & Salem Al Jabri & Mohamed Gabr, 2023. "Impact of Climate Change on Crop Irrigation Requirements in Arid Regions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(5), pages 1965-1984, March.
    • Handle: RePEc:spr:waterr:v:37:y:2023:i:5:d:10.1007_s11269-023-03465-5
    DOI: 10.1007/s11269-023-03465-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-023-03465-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-023-03465-5?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. Vishwakarma, Dinesh Kumar & Pandey, Kusum & Kaur, Arshdeep & Kushwaha, N.L. & Kumar, Rohitashw & Ali, Rawshan & Elbeltagi, Ahmed & Kuriqi, Alban, 2022. "Methods to estimate evapotranspiration in humid and subtropical climate conditions," Agricultural Water Management, Elsevier, vol. 261(C).
    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. Abdullah A. Elshennawy & Magdy Y. Abdelaal & Ahmed M. Hamed & Mohamed M. Awad, 2023. "Evaluating Mesh Geometry and Shade Coefficient for Fog Harvesting Collectors," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(15), pages 6107-6126, December.
    2. Dang, Chiheng & Zhang, Hongbo & Yao, Congcong & Mu, Dengrui & Lyu, Fengguang & Zhang, Yu & Zhang, Shuqi, 2024. "IWRAM: A hybrid model for irrigation water demand forecasting to quantify the impacts of climate change," Agricultural Water Management, Elsevier, vol. 291(C).
    3. Lin, Yu-Pin & Hsu, Chia- Chuan & Wuryandani, Shafira & Yang, Feng-An, 2024. "A decision-making framework based on rain-fed crop suitability, water scarcity, and economic benefits for determination multiple-crop rotation strategy," Agricultural Water Management, Elsevier, vol. 306(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. Jitendra Rajput & Man Singh & Khajanchi Lal & Manoj Khanna & Arjamadutta Sarangi & Joydeep Mukherjee & Shrawan Singh, 2024. "Selection of alternate reference evapotranspiration models based on multi-criteria decision ranking for semiarid climate," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(5), pages 11171-11216, May.
    2. Amarjeet Kumar & Vijay Kumar Singh & Bhagwat Saran & Nadhir Al-Ansari & Vinay Pratap Singh & Sneha Adhikari & Anjali Joshi & Narendra Kumar Singh & Dinesh Kumar Vishwakarma, 2022. "Development of Novel Hybrid Models for Prediction of Drought- and Stress-Tolerance Indices in Teosinte Introgressed Maize Lines Using Artificial Intelligence Techniques," Sustainability, MDPI, vol. 14(4), pages 1-17, February.
    3. M. Babaei & H. Ketabchi, 2022. "Determining Groundwater Recharge Rate with a Distributed Model and Remote Sensing Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(14), pages 5401-5423, November.
    4. Saravanan Karuppanan & Saravanan Ramasamy & Balaji Lakshminarayanan & Sreemanthrarupini Nariangadu Anuthaman, 2025. "An effective machine learning model for the estimation of reference evapotranspiration under data-limited conditions," Research in Agricultural Engineering, Czech Academy of Agricultural Sciences, vol. 71(1), pages 22-37.
    5. Malik, Anurag & Jamei, Mehdi & Ali, Mumtaz & Prasad, Ramendra & Karbasi, Masoud & Yaseen, Zaher Mundher, 2022. "Multi-step daily forecasting of reference evapotranspiration for different climates of India: A modern multivariate complementary technique reinforced with ridge regression feature selection," Agricultural Water Management, Elsevier, vol. 272(C).
    6. Abhinav Kumar Singh & Pankaj Kumar & Rawshan Ali & Nadhir Al-Ansari & Dinesh Kumar Vishwakarma & Kuldeep Singh Kushwaha & Kanhu Charan Panda & Atish Sagar & Ehsan Mirzania & Ahmed Elbeltagi & Alban Ku, 2022. "An Integrated Statistical-Machine Learning Approach for Runoff Prediction," Sustainability, MDPI, vol. 14(13), pages 1-30, July.

    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:spr:waterr:v:37:y:2023:i:5:d:10.1007_s11269-023-03465-5. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.