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

Author

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  • 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
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    References listed on IDEAS

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    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.
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    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.

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