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Niswonger, R. G., Morway, E. D., Triana, E., et al. (2017). Managed aquifer recharge through off‐ season irrigation in agricultural regions. Water Resources Research,, 53(8), 6970-6992.Search in Google Scholar
Ramanjaneyulu, A. V., Ramulu, V., Ramana, M. V., et al. (2022). Crop performance, water use, economics and energy indices in rabi groundnut (Arachis hypogaea L.) under micro irrigation methods. Journal of environmental biology, (2), 43.Search in Google Scholar
Shi, L., Shi, G., Qiu, H. (2019). General review of intelligent agriculture development in China. China Agricultural Economic Review, 11.Search in Google Scholar
Zhong, H., Sun, L., Fischer, G., et al. (2019). Optimizing regional cropping systems with a dynamic adaptation strategy for water sustainable agriculture in the Hebei Plain. Agricultural Systems, 173.Search in Google Scholar
Li, R., Lin, H., Niu, H., et al. (2017). Effects of irrigation on the ecological services in an intensive agricultural region in China: A trade-off perspective. Journal of Cleaner Production, 156(jul.10), 41-49.Search in Google Scholar
Veerachamy, R., Ramar, R., Balaji, S., et al. (2022). Autonomous Application Controls on Smart Irrigation[J]. Computers & Electrical Engineering, 100, 107855-.Search in Google Scholar
Xing, Zikang., Ma, Miaomiao,. Wei, Yongqiang,. Zhang, Xuejun,.Yu, Zhongbo., Yi, Peng. (2020). A new agricultural drought index considering the irrigation water demand and water supply availability. Natural Hazards, 104(3).Search in Google Scholar
Bhrugubanda, M., Rao, A., Shanmukhi, M., et al. (2021). Sustainable and Intelligent IoT Based Precision Agriculture-Smart Farming. Solid State Technology.Search in Google Scholar
Valikhan-Anaraki, M., Mousavi, S. F., Farzin, S., et al. (2019). Development of a Novel Hybrid Optimization Algorithm for Minimizing Irrigation Deficiencies. Sustainability, 11(8), 2337.Search in Google Scholar
González, Perea, R., Camacho, Poyato, E., & Rodríguez, Díaz, J. A. (2021). Forecasting of applied irrigation depths at farm level for energy tariff periods using Coactive neuro-genetic fuzzy system. Agricultural Water Management, 256.Search in Google Scholar
Zhang, F., He, C., Yaqiong, F., et al. (2022). Canal delivery and irrigation scheduling optimization based on crop water demand. Agricultural Water Management, 260.Search in Google Scholar
Mason, B., M. Rufí-Salís, Parada, F., et al. (2019). Intelligent urban irrigation systems: Saving water and maintaining crop yields. Agricultural Water Management, 226.Search in Google Scholar
Orojloo, M., Shahdany, S., Roozbahani, A. (2018). Developing an integrated risk management framework for agricultural water conveyance and distribution systems within fuzzy decision making approaches. Science of The Total Environment, 627(JUN.15), 1363-1376.Search in Google Scholar
Benyezza, H., Bouhedda, M., Rebouh, S. (2021). Zoning irrigation smart system based on fuzzy control technology and IoT for water and energy saving. Journal of Cleaner Production, 302, 127001-.Search in Google Scholar
Kumar, K. A., Jayaraman, K. (2020). Irrigation control system‐data gathering in WSN using IOT. International Journal of Communication Systems.Search in Google Scholar
Boursianis, A. D., Papadopoulou, M. S., Gotsis, A., et al. (2020). Smart Irrigation System for Precision Agriculture - The AREThOU5A IoT Platform. IEEE Sensors Journal, PP(99), 1-1.Search in Google Scholar
Wu, Di., Cui, Yuanlai., Li, Dacheng., Chen, Manyu., Ye, Xugang., Fan, Guofu., Gong, Lanqiang. (2021). Calculation framework for agricultural irrigation water consumption in multi-source irrigation systems. Agricultural Water Management, 244(1).Search in Google Scholar
Zhang, Y., Wei, Z., Lin, Q., et al. (2018). MBD of grey prediction fuzzy-PID irrigation control technology. Desalination & Water Treatment, 110(APR.), 328-336.Search in Google Scholar