OPENAIRE OpenAire Sygma Recolector de Ciencia Abierta, RECOLECTA DIGITAL.CSIC Crossref Microsoft Academic Graph European Union Open Data Portal Agricultural Water Management Open Access 2021-02-05 Open AccessThis research was supported partly by National Key Research and Development Program of China (2016YFD0200303, 2017YFE0118100), National Natural Science Foundation of China (U1706211, 51790532), Special Fund for Scientific Research in the Public Interest (201411009), and the European Union’s Horizon 2020 Research and Innovation Programme under Project SHui, grant agreement No 773903. Open AccessThis research was supported partly by National Key Research and Development Program of China (2016YFD0200303, 2017YFE0118100), National Natural Science Foundation of China (U1706211, 51790532), Special Fund for Scientific Research in the Public Interest (201411009), and the European Union’s Horizon 2020 Research and Innovation Programme under Project SHui, grant agreement No 773903. Peer reviewed Open AccessThis research was supported partly by National Key Research and Development Program of China (2016YFD0200303, 2017YFE0118100), National Natural Science Foundation of China (U1706211, 51790532), Special Fund for Scientific Research in the Public Interest (201411009), and the European Union’s Horizon 2020 Research and Innovation Programme under Project SHui, grant agreement No 773903. Peer reviewed Knowledge-driven 'smart' irrigation proposes to achieve explicitly targeted crop yield and/or irrigation water use efficiency (WUE). A coupled crop growth and soil water transport model was established and applied to schedule irrigation for drip-irrigated and film-mulched maize through numerical simulation. By designing various scenarios with either a constant or variable threshold of plant water deficit index (PWDI) to initiate irrigation, the quantitative relationship between PWDI threshold and the corresponding yield and WUE was investigated with acceptable errors between the measured and simulated values (R2 > 0.85). The model allowed determination of PWDI thresholds designed to reach specific combinations of yield and WUE to consider actual conditions such as availability and cost of water resources. Regulated deficit irrigation with a variable threshold, considering variability of physiological response to water stress, was superior to a constant PWDI threshold in improving WUE. A constant PWDI threshold of 0.54 and 45 threshold combinations among various growth stages were suggested to obtain same relative values of yield and WUE. Numerical simulation has the potential to provide reliable dynamic information regarding soil water and crop growth, necessary for smart irrigation scheduling, due to its ability in integrating the effects of environmental conditions and economic considerations and, as such, should be further studied to enhance simulation accuracy and subsequently to optimize irrigation scheduling under complex situations. Open AccessThis research was supported partly by National Key Research and Development Program of China (2016YFD0200303, 2017YFE0118100), National Natural Science Foundation of China (U1706211, 51790532), Special Fund for Scientific Research in the Public Interest (201411009), and the European Union’s Horizon 2020 Research and Innovation Programme under Project SHui, grant agreement No 773903. Peer reviewed Knowledge-driven 'smart' irrigation proposes to achieve explicitly targeted crop yield and/or irrigation water use efficiency (WUE). A coupled crop growth and soil water transport model was established and applied to schedule irrigation for drip-irrigated and film-mulched maize through numerical simulation. By designing various scenarios with either a constant or variable threshold of plant water deficit index (PWDI) to initiate irrigation, the quantitative relationship between PWDI threshold and the corresponding yield and WUE was investigated with acceptable errors between the measured and simulated values (R2 > 0.85). The model allowed determination of PWDI thresholds designed to reach specific combinations of yield and WUE to consider actual conditions such as availability and cost of water resources. Regulated deficit irrigation with a variable threshold, considering variability of physiological response to water stress, was superior to a constant PWDI threshold in improving WUE. A constant PWDI threshold of 0.54 and 45 threshold combinations among various growth stages were suggested to obtain same relative values of yield and WUE. Numerical simulation has the potential to provide reliable dynamic information regarding soil water and crop growth, necessary for smart irrigation scheduling, due to its ability in integrating the effects of environmental conditions and economic considerations and, as such, should be further studied to enhance simulation accuracy and subsequently to optimize irrigation scheduling under complex situations. Project Co-ordinators: Dr. Jose Alfonso Gómez Calero (Instituto de Agricultura Sostenible (IAS-CISC), Dr. Weifeng Xu (Fujian Agriculture and Forest University, FAFU). -- Trabajo desarrollado bajo la financiación del proyecto “Soil Hydrology research platform underpinning innovation to manage water scarcity in European and Chinese cropping Systems” (773903), coordinado por José Alfonso Gómez Calero, investigador del Instituto de Agricultura Sostenible (IAS). 0106 biological sciences 2. Zero hunger Crop growth 0401 agriculture, forestry, and fisheries 04 agricultural and veterinary sciences 15. Life on land Soil water transport 01 natural sciences Irrigation scheduling Decision support system Regulated deficit irrigation 6. Clean water Alon Ben-Gal, Xiaoguang Wu, Jianchu Shi, Jianchu Shi, Qiang Zuo, Qiang Zuo, Xiaoyu Wang, Xiaoyu Wang, Mo Zhang, Mo Zhang, Hongfei Zhang, Xun Wu, 2021-04-01 journalpaper Open AccessThis research was supported partly by National Key Research and Development Program of China (2016YFD0200303, 2017YFE0118100), National Natural Science Foundation of China (U1706211, 51790532), Special Fund for Scientific Research in the Public Interest (201411009), and the European Union’s Horizon 2020 Research and Innovation Programme under Project SHui, grant agreement No 773903. Open AccessThis research was supported partly by National Key Research and Development Program of China (2016YFD0200303, 2017YFE0118100), National Natural Science Foundation of China (U1706211, 51790532), Special Fund for Scientific Research in the Public Interest (201411009), and the European Union’s Horizon 2020 Research and Innovation Programme under Project SHui, grant agreement No 773903. Peer reviewed Open AccessThis research was supported partly by National Key Research and Development Program of China (2016YFD0200303, 2017YFE0118100), National Natural Science Foundation of China (U1706211, 51790532), Special Fund for Scientific Research in the Public Interest (201411009), and the European Union’s Horizon 2020 Research and Innovation Programme under Project SHui, grant agreement No 773903. Peer reviewed Knowledge-driven 'smart' irrigation proposes to achieve explicitly targeted crop yield and/or irrigation water use efficiency (WUE). A coupled crop growth and soil water transport model was established and applied to schedule irrigation for drip-irrigated and film-mulched maize through numerical simulation. By designing various scenarios with either a constant or variable threshold of plant water deficit index (PWDI) to initiate irrigation, the quantitative relationship between PWDI threshold and the corresponding yield and WUE was investigated with acceptable errors between the measured and simulated values (R2 > 0.85). The model allowed determination of PWDI thresholds designed to reach specific combinations of yield and WUE to consider actual conditions such as availability and cost of water resources. Regulated deficit irrigation with a variable threshold, considering variability of physiological response to water stress, was superior to a constant PWDI threshold in improving WUE. A constant PWDI threshold of 0.54 and 45 threshold combinations among various growth stages were suggested to obtain same relative values of yield and WUE. Numerical simulation has the potential to provide reliable dynamic information regarding soil water and crop growth, necessary for smart irrigation scheduling, due to its ability in integrating the effects of environmental conditions and economic considerations and, as such, should be further studied to enhance simulation accuracy and subsequently to optimize irrigation scheduling under complex situations. Open AccessThis research was supported partly by National Key Research and Development Program of China (2016YFD0200303, 2017YFE0118100), National Natural Science Foundation of China (U1706211, 51790532), Special Fund for Scientific Research in the Public Interest (201411009), and the European Union’s Horizon 2020 Research and Innovation Programme under Project SHui, grant agreement No 773903. Peer reviewed Knowledge-driven 'smart' irrigation proposes to achieve explicitly targeted crop yield and/or irrigation water use efficiency (WUE). A coupled crop growth and soil water transport model was established and applied to schedule irrigation for drip-irrigated and film-mulched maize through numerical simulation. By designing various scenarios with either a constant or variable threshold of plant water deficit index (PWDI) to initiate irrigation, the quantitative relationship between PWDI threshold and the corresponding yield and WUE was investigated with acceptable errors between the measured and simulated values (R2 > 0.85). The model allowed determination of PWDI thresholds designed to reach specific combinations of yield and WUE to consider actual conditions such as availability and cost of water resources. Regulated deficit irrigation with a variable threshold, considering variability of physiological response to water stress, was superior to a constant PWDI threshold in improving WUE. A constant PWDI threshold of 0.54 and 45 threshold combinations among various growth stages were suggested to obtain same relative values of yield and WUE. Numerical simulation has the potential to provide reliable dynamic information regarding soil water and crop growth, necessary for smart irrigation scheduling, due to its ability in integrating the effects of environmental conditions and economic considerations and, as such, should be further studied to enhance simulation accuracy and subsequently to optimize irrigation scheduling under complex situations. Project Co-ordinators: Dr. Jose Alfonso Gómez Calero (Instituto de Agricultura Sostenible (IAS-CISC), Dr. Weifeng Xu (Fujian Agriculture and Forest University, FAFU). -- Trabajo desarrollado bajo la financiación del proyecto “Soil Hydrology research platform underpinning innovation to manage water scarcity in European and Chinese cropping Systems” (773903), coordinado por José Alfonso Gómez Calero, investigador del Instituto de Agricultura Sostenible (IAS). Numerically scheduling plant water deficit index-based smart irrigation to optimize crop yield and water use efficiency 10.1016/j.agwat.2021.106774 https://doi.org/10.1016/j.agwat.2021.106774 773903