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Irrigation scheduling using intervention of Geomatics tools—A case study of Khedli minor

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  • Singh, Avinash Kumar
  • Dubey, O.P.
  • Ghosh, S.K.

Abstract

Food is the basic and compulsory requirement of the human being. It is expected that demand for food crops will double during the next 50 years with limited land and water resources. Production of food requires water. Global estimates indicates that irrigated agriculture sector consumes about 85% of the available water. Further it is expected that in this sector will witness increase water consumption about 20% by the year 2025. The requirement of water increases as the production increases. Proper utilization of water resource is required which is known as scheduling of water for irrigation or irrigation scheduling. Studies carried out in the water deficit area indicated that proper irrigation scheduling may save water and energy up to 35%. The present trend of irrigation has caused 25% depletion in ground water reserve by 2010. Research shows that increasing trend in demand of water in irrigation may lead to total depletion of the ground water table within 50 years. More enhancements required in techniques of irrigation scheduling as the data associated with the estimation of scheduling of water are not sufficient and reliable. An attempt has been made to solve some of the existing problems of data insufficiency and non reliable data can better be solved by the help of remote sensing and GIS. An endeavor has been made to compute the three main parameters influencing the irrigation scheduling namely, crop coefficient, albedo and crop surface temperature through intervention of remote sensing. The approach suggested for the irrigation scheduling using remote sensing and GIS can save irrigation water by 12.5% as compared to the conventional or prevailing approach in study area.

Suggested Citation

  • Singh, Avinash Kumar & Dubey, O.P. & Ghosh, S.K., 2016. "Irrigation scheduling using intervention of Geomatics tools—A case study of Khedli minor," Agricultural Water Management, Elsevier, vol. 177(C), pages 454-460.
    • Handle: RePEc:eee:agiwat:v:177:y:2016:i:c:p:454-460
    DOI: 10.1016/j.agwat.2016.05.024
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    Cited by:

    1. Zhang, Zhenyu & Li, Xiaoyu & Liu, Lijuan & Wang, Yugang & Li, Yan, 2020. "Influence of mulched drip irrigation on landscape scale evapotranspiration from farmland in an arid area," Agricultural Water Management, Elsevier, vol. 230(C).
    2. Avinash Bharti & Kunwar Paritosh & Venkata Ravibabu Mandla & Aakash Chawade & Vivekanand Vivekanand, 2021. "GIS Application for the Estimation of Bioenergy Potential from Agriculture Residues: An Overview," Energies, MDPI, vol. 14(4), pages 1-15, February.
    3. Zhang, Zepeng & Wang, Qingzheng & Guan, Qingyu & Xiao, Xiong & Mi, Jimin & Lv, Songjian, 2023. "Research on the optimal allocation of agricultural water and soil resources in the Heihe River Basin based on SWAT and intelligent optimization," Agricultural Water Management, Elsevier, vol. 279(C).
    4. Tang, Yikuan & Zhang, Fan & Wang, Sufen & Zhang, Xiaodong & Guo, Shanshan & Guo, Ping, 2019. "A distributed interval nonlinear multiobjective programming approach for optimal irrigation water management in an arid area," Agricultural Water Management, Elsevier, vol. 220(C), pages 13-26.

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