IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v14y2024i7p1141-d1435032.html
   My bibliography  Save this article

A Review of Precision Irrigation Water-Saving Technology under Changing Climate for Enhancing Water Use Efficiency, Crop Yield, and Environmental Footprints

Author

Listed:
  • Imran Ali Lakhiar

    (Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang 212013, China)

  • Haofang Yan

    (Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang 212013, China
    State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing 210029, China)

  • Chuan Zhang

    (School of Agricultural Equipment Engineering, Jiangsu University, Zhenjiang 212013, China)

  • Guoqing Wang

    (State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing 210029, China)

  • Bin He

    (National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China, Guangdong Key Laboratory of Integrated Agro-Environmental Pollution Control and Management, Institute of Eco-Environmental and Soil Sciences, Guangdong Academy of Sciences, Guangzhou 510650, China)

  • Beibei Hao

    (National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China, Guangdong Key Laboratory of Integrated Agro-Environmental Pollution Control and Management, Institute of Eco-Environmental and Soil Sciences, Guangdong Academy of Sciences, Guangzhou 510650, China)

  • Yujing Han

    (Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang 212013, China
    National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China, Guangdong Key Laboratory of Integrated Agro-Environmental Pollution Control and Management, Institute of Eco-Environmental and Soil Sciences, Guangdong Academy of Sciences, Guangzhou 510650, China)

  • Biyu Wang

    (Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang 212013, China)

  • Rongxuan Bao

    (Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang 212013, China)

  • Tabinda Naz Syed

    (College of Engineering, Nanjing Agricultural University, Nanjing 210031, China)

  • Junaid Nawaz Chauhdary

    (Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang 212013, China
    Water Management Research Centre, University of Agriculture, Faisalabad 38000, Pakistan)

  • Md. Rakibuzzaman

    (Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang 212013, China
    Department of Mechanical Engineering, International University of Business Agriculture and Technology, Dhaka 1230, Bangladesh)

Abstract

Water is considered one of the vital natural resources and factors for performing short- and long-term agricultural practices on Earth. Meanwhile, globally, most of the available freshwater resources are utilized for irrigation purposes in agriculture. Currently, many world regions are facing extreme water shortage problems, which can worsen if not managed properly. In the literature, numerous methods and remedies are used to cope with the increasing global water crises. The use of precision irrigation water-saving systems (PISs) for efficient water management under climate change is one of them and is a highly recommended approach by researchers. It can mitigate the adverse effects of changing climate and help enhance water use efficiency, crop yield, and environmental footprints. Thus, the present study aimed to comprehensively examine and review PISs, focusing on their development, implementation, and positive impacts on sustainable water management. In addition, we searched the literature using different online search engines and reviewed and summarized the main results of the previously published papers on PISs. We discussed the traditional irrigation method and its modernization for enhancing water use efficiency, PIS monitoring and controlling, architecture, data sharing communication technologies, the role of artificial intelligence for irrigation water-saving, and the future prospects of the PIS. Based on the brief literature review, the present study concluded that the future of PISs seems bright, driven by the need for efficient irrigation water management systems, technological advancements, and increasing environmental awareness. As the water scarcity problem intensifies due to climate change and population growth, the PIS is poised to play a critical role in optimizing and modernizing water usage, increasing water use efficiency, and reducing environmental footprints, thus ensuring sustainable agriculture development.

Suggested Citation

  • Imran Ali Lakhiar & Haofang Yan & Chuan Zhang & Guoqing Wang & Bin He & Beibei Hao & Yujing Han & Biyu Wang & Rongxuan Bao & Tabinda Naz Syed & Junaid Nawaz Chauhdary & Md. Rakibuzzaman, 2024. "A Review of Precision Irrigation Water-Saving Technology under Changing Climate for Enhancing Water Use Efficiency, Crop Yield, and Environmental Footprints," Agriculture, MDPI, vol. 14(7), pages 1-40, July.
  • Handle: RePEc:gam:jagris:v:14:y:2024:i:7:p:1141-:d:1435032
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/14/7/1141/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/14/7/1141/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. González-Dugo, M.P. & Escuin, S. & Cano, F. & Cifuentes, V. & Padilla, F.L.M. & Tirado, J.L. & Oyonarte, N. & Fernández, P. & Mateos, L., 2013. "Monitoring evapotranspiration of irrigated crops using crop coefficients derived from time series of satellite images. II. Application on basin scale," Agricultural Water Management, Elsevier, vol. 125(C), pages 92-104.
    2. Yassin, Mohamed A. & Alazba, A.A. & Mattar, Mohamed A., 2016. "Artificial neural networks versus gene expression programming for estimating reference evapotranspiration in arid climate," Agricultural Water Management, Elsevier, vol. 163(C), pages 110-124.
    3. Mason, Brooke & Rufí-Salís, Martí & Parada, Felipe & Gabarrell, Xavier & Gruden, Cyndee, 2019. "Intelligent urban irrigation systems: Saving water and maintaining crop yields," Agricultural Water Management, Elsevier, vol. 226(C).
    4. 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.
    5. Daccache, A. & Knox, J.W. & Weatherhead, E.K. & Daneshkhah, A. & Hess, T.M., 2015. "Implementing precision irrigation in a humid climate – Recent experiences and on-going challenges," Agricultural Water Management, Elsevier, vol. 147(C), pages 135-143.
    6. Li Bin & Muhammad Shahzad & Hira Khan & Muhammad Mehran Bashir & Arif Ullah & Muhammad Siddique, 2023. "Sustainable Smart Agriculture Farming for Cotton Crop: A Fuzzy Logic Rule Based Methodology," Sustainability, MDPI, vol. 15(18), pages 1-18, September.
    7. Zhang, Chuan & Akhlaq, Muhammad & Yan, Haofang & Ni, Yuxin & Liang, Shaowei & Zhou, Junan & Xue, Run & Li, Min & Adnan, Rana Muhammad & Li, Jun, 2023. "Chlorophyll fluorescence parameter as a predictor of tomato growth and yield under CO2 enrichment in protective cultivation," Agricultural Water Management, Elsevier, vol. 284(C).
    8. Delgoda, Dilini & Saleem, Syed K. & Malano, Hector & Halgamuge, Malka N., 2016. "Root zone soil moisture prediction models based on system identification: Formulation of the theory and validation using field and AQUACROP data," Agricultural Water Management, Elsevier, vol. 163(C), pages 344-353.
    9. Matthew Champness & Leigh Vial & Carlos Ballester & John Hornbuckle, 2023. "Evaluating the Performance and Opportunity Cost of a Smart-Sensed Automated Irrigation System for Water-Saving Rice Cultivation in Temperate Australia," Agriculture, MDPI, vol. 13(4), pages 1-16, April.
    10. Chen, Mengting & Cui, Yuanlai & Wang, Xiaonan & Xie, Hengwang & Liu, Fangping & Luo, Tongyuan & Zheng, Shizong & Luo, Yufeng, 2021. "A reinforcement learning approach to irrigation decision-making for rice using weather forecasts," Agricultural Water Management, Elsevier, vol. 250(C).
    11. Siti Nadhirah Zainurin & Wan Zakiah Wan Ismail & Siti Nurul Iman Mahamud & Irneza Ismail & Juliza Jamaludin & Nor Azlina Ab. Aziz, 2023. "Integration of Sensing Framework with a Decision Support System for Monitoring Water Quality in Agriculture," Agriculture, MDPI, vol. 13(5), pages 1-14, April.
    12. Bwambale, Erion & Abagale, Felix K. & Anornu, Geophrey K., 2022. "Smart irrigation monitoring and control strategies for improving water use efficiency in precision agriculture: A review," Agricultural Water Management, Elsevier, vol. 260(C).
    13. Hedley, C.B. & Yule, I.J., 2009. "A method for spatial prediction of daily soil water status for precise irrigation scheduling," Agricultural Water Management, Elsevier, vol. 96(12), pages 1737-1745, December.
    14. Siva K. Balasundram & Redmond R. Shamshiri & Shankarappa Sridhara & Nastaran Rizan, 2023. "The Role of Digital Agriculture in Mitigating Climate Change and Ensuring Food Security: An Overview," Sustainability, MDPI, vol. 15(6), pages 1-23, March.
    15. Alibabaei, Khadijeh & Gaspar, Pedro D. & Assunção, Eduardo & Alirezazadeh, Saeid & Lima, Tânia M., 2022. "Irrigation optimization with a deep reinforcement learning model: Case study on a site in Portugal," Agricultural Water Management, Elsevier, vol. 263(C).
    16. Zeng, Yuan-Fu & Chen, Ching-Tien & Lin, Gwo-Fong, 2023. "Practical application of an intelligent irrigation system to rice paddies in Taiwan," Agricultural Water Management, Elsevier, vol. 280(C).
    17. Vuolo, Francesco & D’Urso, Guido & De Michele, Carlo & Bianchi, Biagio & Cutting, Michael, 2015. "Satellite-based irrigation advisory services: A common tool for different experiences from Europe to Australia," Agricultural Water Management, Elsevier, vol. 147(C), pages 82-95.
    18. Thompson, R.B. & Gallardo, M. & Valdez, L.C. & Fernandez, M.D., 2007. "Using plant water status to define threshold values for irrigation management of vegetable crops using soil moisture sensors," Agricultural Water Management, Elsevier, vol. 88(1-3), pages 147-158, March.
    Full references (including those not matched with items on IDEAS)

    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. Jovanovic, N. & Pereira, L.S. & Paredes, P. & Pôças, I. & Cantore, V. & Todorovic, M., 2020. "A review of strategies, methods and technologies to reduce non-beneficial consumptive water use on farms considering the FAO56 methods," Agricultural Water Management, Elsevier, vol. 239(C).
    2. Guilherme Jesus & Martim L. Aguiar & Pedro D. Gaspar, 2022. "Computational Tool to Support the Decision in the Selection of Alternative and/or Sustainable Refrigerants," Energies, MDPI, vol. 15(22), pages 1-20, November.
    3. Ahmed A. Abdelmoneim & Roula Khadra & Angela Elkamouh & Bilal Derardja & Giovanna Dragonetti, 2023. "Towards Affordable Precision Irrigation: An Experimental Comparison of Weather-Based and Soil Water Potential-Based Irrigation Using Low-Cost IoT-Tensiometers on Drip Irrigated Lettuce," Sustainability, MDPI, vol. 16(1), pages 1-15, December.
    4. 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).
    5. Campos, Isidro & Neale, Christopher M.U. & Suyker, Andrew E. & Arkebauer, Timothy J. & Gonçalves, Ivo Z., 2017. "Reflectance-based crop coefficients REDUX: For operational evapotranspiration estimates in the age of high producing hybrid varieties," Agricultural Water Management, Elsevier, vol. 187(C), pages 140-153.
    6. Garrido-Rubio, Jesús & González-Piqueras, Jose & Campos, Isidro & Osann, Anna & González-Gómez, Laura & Calera, Alfonso, 2020. "Remote sensing–based soil water balance for irrigation water accounting at plot and water user association management scale," Agricultural Water Management, Elsevier, vol. 238(C).
    7. Bhatti, Sandeep & Heeren, Derek M. & Barker, J. Burdette & Neale, Christopher M.U. & Woldt, Wayne E. & Maguire, Mitchell S. & Rudnick, Daran R., 2020. "Site-specific irrigation management in a sub-humid climate using a spatial evapotranspiration model with satellite and airborne imagery," Agricultural Water Management, Elsevier, vol. 230(C).
    8. Umutoni, Lisa & Samadi, Vidya, 2024. "Application of machine learning approaches in supporting irrigation decision making: A review," Agricultural Water Management, Elsevier, vol. 294(C).
    9. Berbel, J. & Mateos, L., 2014. "Does investment in irrigation technology necessarily generate rebound effects? A simulation analysis based on an agro-economic model," Agricultural Systems, Elsevier, vol. 128(C), pages 25-34.
    10. Bounajra, Afaf & Guemmat, Kamal El & Mansouri, Khalifa & Akef, Fatiha, 2024. "Towards efficient irrigation management at field scale using new technologies: A systematic literature review," Agricultural Water Management, Elsevier, vol. 295(C).
    11. Emami, Somayeh & Dehghanisanij, Hossein & Hajimirzajan, Amir, 2024. "Agent-based simulation model to evaluate government policies for farmers’ adoption and synergy in improving irrigation systems: A case study of Lake Urmia basin," Agricultural Water Management, Elsevier, vol. 294(C).
    12. Laura Ávila-Dávila & José Miguel Molina-Martínez & Carlos Bautista-Capetillo & Manuel Soler-Méndez & Cruz Octavio Robles Rovelo & Hugo Enrique Júnez-Ferreira & Julián González-Trinidad, 2021. "Estimation of the Evapotranspiration and Crop Coefficients of Bell Pepper Using a Removable Weighing Lysimeter: A Case Study in the Southeast of Spain," Sustainability, MDPI, vol. 13(2), pages 1-14, January.
    13. 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).
    14. Mokhtari, Ali & Noory, Hamideh & Vazifedoust, Majid & Bahrami, Mahdi, 2018. "Estimating net irrigation requirement of winter wheat using model- and satellite-based single and basal crop coefficients," Agricultural Water Management, Elsevier, vol. 208(C), pages 95-106.
    15. Tapsuwan, Sorada & Peña-Arancibia, Jorge L. & Lazarow, Neil & Albisetti, Melisa & Zheng, Hongxing & Rojas, Rodrigo & Torres-Alferez, Vianney & Chiew, Francis H.S. & Hopkins, Richard & Penton, David J., 2022. "A benefit cost analysis of strategic and operational management options for water management in hyper-arid southern Peru," Agricultural Water Management, Elsevier, vol. 265(C).
    16. Ephrem Habyarimana & Faheem S Baloch, 2021. "Machine learning models based on remote and proximal sensing as potential methods for in-season biomass yields prediction in commercial sorghum fields," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-23, March.
    17. Ehsan Qasemipour & Ali Abbasi & Farhad Tarahomi, 2020. "Water-Saving Scenarios Based on Input–Output Analysis and Virtual Water Concept: A Case in Iran," Sustainability, MDPI, vol. 12(3), pages 1-16, January.
    18. Bonfante, A. & Monaco, E. & Manna, P. & De Mascellis, R. & Basile, A. & Buonanno, M. & Cantilena, G. & Esposito, A. & Tedeschi, A. & De Michele, C. & Belfiore, O. & Catapano, I. & Ludeno, G. & Salinas, 2019. "LCIS DSS—An irrigation supporting system for water use efficiency improvement in precision agriculture: A maize case study," Agricultural Systems, Elsevier, vol. 176(C).
    19. T. Fowe & I. Nouiri & B. Ibrahim & H. Karambiri & J. Paturel, 2015. "OPTIWAM: An Intelligent Tool for Optimizing Irrigation Water Management in Coupled Reservoir–Groundwater Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3841-3861, August.
    20. El-Naggar, A.G. & Hedley, C.B. & Horne, D. & Roudier, P. & Clothier, B.E., 2020. "Soil sensing technology improves application of irrigation water," Agricultural Water Management, Elsevier, vol. 228(C).

    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:jagris:v:14:y:2024:i:7:p:1141-:d:1435032. 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.