IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i20p13554-d948040.html
   My bibliography  Save this article

Crop Water Requirements with Changing Climate in an Arid Region of Saudi Arabia

Author

Listed:
  • Mohd Anul Haq

    (Department of Computer Science, College of Computer Science and Information Sciences, Majmaah University, Al-Majmaah 11952, Saudi Arabia)

  • Mohd Yawar Ali Khan

    (Department of Hydrogeology, Faculty of Earth Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

Abstract

Agriculture is critical for a country’s population growth and economic expansion. In Saudi Arabia (SA), agriculture relies on groundwater, seasonal water, desalinated water, and recycled water due to a lack of surface water resources, a dry environment, and scanty rainfall. Estimating water consumption to plan crop water requirements (CWR) in changing environments is difficult due to a lack of micro-level data on water consumption, particularly in agricultural systems. High-resolution satellite data combined with environmental data provides a valuable tool for computing the CWR. This study aimed to estimate the CWR with a greater spatial and temporal resolution and localized field data and environmental variables. Obtaining this at the field level is appropriate, but geospatial technology can produce repeatable, time-series phenomena and align with environmental data for wider coverage regions. The CWR in the study area has been investigated through two methods: firstly, based on the high-resolution PlanetScope (PS) data, and secondly, using the FAO CROPWAT model v8.0. The analysis revealed that evapotranspiration (ET o ) showed a minimum response of 2.22 mm/day in January to a maximum of 6.13 mm/day in July, with high temperatures (42.8). The humidity reaches a peak of 51%, falling to a minimum in June of 15%. Annual CWR values (in mm) for seven crops studied in the present investigation, including date palm, wheat, citrus, maize, barley, clover, and vegetables, were 1377, 296, 964, 275, 259, 1077, 214, respectively. The monthly averaged CWR derived using PS showed a higher correlation (r = 0.83) with CROPWAT model results. The study was promising and highlighted that such analysis is decisive and can be implemented in any region by using Machine Learning and Deep Learning for in-depth insights.

Suggested Citation

  • Mohd Anul Haq & Mohd Yawar Ali Khan, 2022. "Crop Water Requirements with Changing Climate in an Arid Region of Saudi Arabia," Sustainability, MDPI, vol. 14(20), pages 1-24, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:20:p:13554-:d:948040
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/20/13554/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/20/13554/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mahmoud, Shereif H. & Gan, Thian Yew, 2019. "Irrigation water management in arid regions of Middle East: Assessing spatio-temporal variation of actual evapotranspiration through remote sensing techniques and meteorological data," Agricultural Water Management, Elsevier, vol. 212(C), pages 35-47.
    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. Feng Fang & Jing Wang & Jingjing Lin & Yuxia Xu & Guoyang Lu & Xin Wang & Pengcheng Huang & Yuhan Huang & Fei Yin, 2023. "Risk Assessment of Maize Yield Losses in Gansu Province Based on Spatial Econometric Analysis," Agriculture, MDPI, vol. 13(7), pages 1-26, June.

    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. Filgueiras, Roberto & Almeida, Thomé Simpliciano & Mantovani, Everardo Chartuni & Dias, Santos Henrique Brant & Fernandes-Filho, Elpídio Inácio & da Cunha, Fernando França & Venancio, Luan Peroni, 2020. "Soil water content and actual evapotranspiration predictions using regression algorithms and remote sensing data," Agricultural Water Management, Elsevier, vol. 241(C).
    2. Zhang, Yu & Han, Wenting & Zhang, Huihui & Niu, Xiaotao & Shao, Guomin, 2023. "Evaluating maize evapotranspiration using high-resolution UAV-based imagery and FAO-56 dual crop coefficient approach," Agricultural Water Management, Elsevier, vol. 275(C).
    3. Nagat Ahmed Elmulthum & Faisal Ibrahim Zeineldin & Suliman Ali Al-Khateeb & Khalid Mohammed Al-Barrak & Tagelsir Ahmed Mohammed & Muhammad Naeem Sattar & Akbar S. Mohmand, 2023. "Water Use Efficiency and Economic Evaluation of the Hydroponic versus Conventional Cultivation Systems for Green Fodder Production in Saudi Arabia," Sustainability, MDPI, vol. 15(1), pages 1-13, January.
    4. Campana, P.E. & Lastanao, P. & Zainali, S. & Zhang, J. & Landelius, T. & Melton, F., 2022. "Towards an operational irrigation management system for Sweden with a water–food–energy nexus perspective," Agricultural Water Management, Elsevier, vol. 271(C).
    5. Potopová, V. & Trnka, M. & Vizina, A. & Semerádová, D. & Balek, J. & Chawdhery, M.R.A. & Musiolková, M. & Pavlík, P. & Možný, M. & Štěpánek, P. & Clothier, B., 2022. "Projection of 21st century irrigation water requirements for sensitive agricultural crop commodities across the Czech Republic," Agricultural Water Management, Elsevier, vol. 262(C).
    6. Chi Yunxian & Li Renjie & Zhao Shuliang & Guo Fenghua, 2020. "Measuring multi-spatiotemporal scale tourist destination popularity based on text granular computing," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-33, April.
    7. Zhao, Tianxing & Zhu, Yan & Ye, Ming & Yang, Jinzhong & Jia, Biao & Mao, Wei & Wu, Jingwei, 2022. "A new approach for estimating spatial-temporal phreatic evapotranspiration at a regional scale using NDVI and water table depth measurements," Agricultural Water Management, Elsevier, vol. 264(C).
    8. Pôças, I. & Calera, A. & Campos, I. & Cunha, M., 2020. "Remote sensing for estimating and mapping single and basal crop coefficientes: A review on spectral vegetation indices approaches," Agricultural Water Management, Elsevier, vol. 233(C).
    9. Maselli, F. & Chiesi, M. & Angeli, L. & Fibbi, L. & Rapi, B. & Romani, M. & Sabatini, F. & Battista, P., 2020. "An improved NDVI-based method to predict actual evapotranspiration of irrigated grasses and crops," Agricultural Water Management, Elsevier, vol. 233(C).
    10. Laishram Kanta Singh & Madan K. Jha & V. M. Chowdary, 2021. "Evaluation of water demand and supply under varying meteorological conditions in Eastern India and mitigation strategies for sustainable agricultural production," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(2), pages 1264-1291, February.
    11. Santos, Jannaylton Everton Oliveira & Cunha, Fernando França da & Filgueiras, Roberto & Silva, Gustavo Henrique da & Castro Teixeira, Antônio Heriberto de & Santos Silva, Francisco Charles dos & Sediy, 2020. "Performance of SAFER evapotranspiration using missing meteorological data," Agricultural Water Management, Elsevier, vol. 233(C).
    12. Bashar Bashir & Abdullah Alsalman & Arsalan Ahmed Othman & Ahmed K. Obaid & Hussein Bashir, 2021. "New Approach to Selecting Civil Defense Centers in Al-Riyadh City (KSA) Based on Multi-Criteria Decision Analysis and GIS," Land, MDPI, vol. 10(11), pages 1-19, October.

    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:gam:jsusta:v:14:y:2022:i:20:p:13554-:d:948040. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.