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Real-time scheduling of supplemental irrigation for potatoes using a decision model and short-term weather forecasts

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  • Gowing, J. W.
  • Ejieji, C. J.

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  • Gowing, J. W. & Ejieji, C. J., 2001. "Real-time scheduling of supplemental irrigation for potatoes using a decision model and short-term weather forecasts," Agricultural Water Management, Elsevier, vol. 47(2), pages 137-153, March.
    • Handle: RePEc:eee:agiwat:v:47:y:2001:i:2:p:137-153
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    1. Rao, N. H. & Sarma, P. B. S. & Chander, Subhash, 1992. "Real-time adaptive irrigation scheduling under a limited water supply," Agricultural Water Management, Elsevier, vol. 20(4), pages 267-279, February.
    2. Luis R. Zavaleta & Ronald D. Lacewell & C. Robert Taylor, 1980. "Open-Loop Stochastic Control of Grain Sorghum Irrigation Levels and Timing," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 62(4), pages 785-792.
    3. Lee, E. S. & Raju, K. S. & Biere, Arlo W., 1991. "Dynamic irrigation scheduling with stochastic rainfall," Agricultural Water Management, Elsevier, vol. 19(3), pages 253-270, April.
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    Cited by:

    1. Sangha, Laljeet & Shortridge, Julie & Frame, William, 2023. "The impact of nitrogen treatment and short-term weather forecast data in irrigation scheduling of corn and cotton on water and nutrient use efficiency in humid climates," Agricultural Water Management, Elsevier, vol. 283(C).
    2. Kögler, F. & Söffker, D., 2017. "Water (stress) models and deficit irrigation: System-theoretical description and causality mapping," Ecological Modelling, Elsevier, vol. 361(C), pages 135-156.
    3. Cao, Jingjing & Tan, Junwei & Cui, Yuanlai & Luo, Yufeng, 2019. "Irrigation scheduling of paddy rice using short-term weather forecast data," Agricultural Water Management, Elsevier, vol. 213(C), pages 714-723.
    4. Gavilan, Pedro & Higueras, José L. & Lozano, David & Ruiz, Natividad, 2024. "The Riego Berry mobile application: A powerful tool to improve on-farm irrigation performance in berry crops," Agricultural Water Management, Elsevier, vol. 292(C).
    5. 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.
    6. Gavilán, Pedro & Ruiz, Natividad & Lozano, David, 2015. "Daily forecasting of reference and strawberry crop evapotranspiration in greenhouses in a Mediterranean climate based on solar radiation estimates," Agricultural Water Management, Elsevier, vol. 159(C), pages 307-317.
    7. 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).
    8. Mishra, Ashok & Siderius, Christian & Aberson, Kenny & van der Ploeg, Martine & Froebrich, Jochen, 2013. "Short-term rainfall forecasts as a soft adaptation to climate change in irrigation management in North-East India," Agricultural Water Management, Elsevier, vol. 127(C), pages 97-106.
    9. Corbari, Chiara & Salerno, Raffaele & Ceppi, Alessandro & Telesca, Vito & Mancini, Marco, 2019. "Smart irrigation forecast using satellite LANDSAT data and meteo-hydrological modeling," Agricultural Water Management, Elsevier, vol. 212(C), pages 283-294.

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