Optimization of irrigation scheduling using crop–water simulation, water pricing, and quantitative weather forecasts

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發表在:Frontiers in Agronomy vol. 6 (Oct 2024), p. 1376231-1376243
主要作者: Abd El Baki, Hassan M.
其他作者: Fujimaki, Haruyuki, Tokumoto, Ieyasu, Saito, Tadaomi
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Frontiers Media SA
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024 7 |a 10.3389/fagro.2024.1376231  |2 doi 
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045 2 |b d20241001  |b d20241031 
100 1 |a Abd El Baki, Hassan M.  |u Sustainable Natural Resources Management Section, International Center for Biosaline Agriculture (ICBA), United Arab Emirates 
245 1 |a Optimization of irrigation scheduling using crop–water simulation, water pricing, and quantitative weather forecasts 
260 |b Frontiers Media SA  |c Oct 2024 
513 |a Journal Article 
520 3 |a Numerical models of crop response to irrigation and weather forecasts with internet access should be fully utilized in modern irrigation management. In this respect, we developed a new numerical scheme to optimize irrigation depth that maximizes net income over each irrigation interval. The scheme applies volumetric water prices to inspire farmers to save water, and it provides growers with real-time estimates of irrigation depth and net income over the growing season. To evaluate this scheme, we carried out a field experiment for groundnut (Arachis hypogaea L.) grown in a sandy field of the Arid Land Research Center (ALRC), Tottori University, Japan. Two treatments were established to compare the net income of the proposed scheme with that of an automated irrigation system. Results showed that although the proposed scheme gave a larger amount of seasonal irrigation water 28%, it achieved 2.18 times of net income owing to 51% higher yield compared to results of the automated irrigation system. The accuracy of rainfall forecast had little effect on the scheme outputs, where the root mean square error (RMSE) between observed and forecasted rainfall was 4.63 mm. By utilizing numerical simulation information of the soil–plant–atmosphere system into the proposed scheme, it would be a more cost-effective tool for optimizing irrigation depths than automated irrigation systems. 
653 |a Weather forecasting 
653 |a Software 
653 |a Research facilities 
653 |a Irrigation 
653 |a Arid zones 
653 |a Water shortages 
653 |a Rainfall 
653 |a Irrigation scheduling 
653 |a Weather 
653 |a Optimization 
653 |a Water depth 
653 |a Computer simulation 
653 |a Irrigation water 
653 |a Arid lands 
653 |a Efficiency 
653 |a Irrigation systems 
653 |a Scheduling 
653 |a Growing season 
653 |a Drought 
653 |a Income 
653 |a Water management 
653 |a Root-mean-square errors 
653 |a Numerical models 
653 |a Mathematical models 
653 |a Net income 
653 |a Sensors 
653 |a Water resources 
653 |a Water use 
653 |a Crops 
653 |a Information processing 
653 |a Internet access 
653 |a Real time 
653 |a Cost control 
653 |a Environmental 
700 1 |a Fujimaki, Haruyuki  |u Division of Dryland Agriculture, Arid Land Research Center, Tottori University, Japan 
700 1 |a Tokumoto, Ieyasu  |u Department of Environmental Science, Graduate School of Agriculture, Saga University, Japan 
700 1 |a Saito, Tadaomi  |u Department of Agricultural, Life and Environmental Sciences, Faculty of Agriculture, Tottori University, Japan 
773 0 |t Frontiers in Agronomy  |g vol. 6 (Oct 2024), p. 1376231-1376243 
786 0 |d ProQuest  |t Agriculture Science Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3265440756/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3265440756/fulltextwithgraphics/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3265440756/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch