Determining threshold values for root-soil water weighted plant water deficit index based smart irrigation

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).

Plant water deficit index (PWDI) represents the extent of water stress by relating soil moisture to the ability of a plant to take up water including consideration of the relative distribution of soil water to roots. However, for a smart irrigation decision support system, we are challenged in determining reliable thresholds of PWDI to initiate irrigation events to achieve predetermined yield and/or water use efficiency (WUE) targets. Taking drip irrigated maize and sprinkler irrigated alfalfa as examples, field experiments were conducted to investigate the choice and effects of PWDI thresholds. The results indicated that, with increasing PWDI thresholds, irrigation times and quantity of water, as well as crop transpiration, growth, and yield, were all significantly limited while WUE was enhanced except under extremely stressed conditions. To disconnect the unpredictable effects of other factors, yield and WUE were normalized to their corresponding potential values. Within the experimentally determined range of PWDI, relative yield and WUE were described with linear functions for maize, and linear and quadratic functions for alfalfa, allowing identification of the most efficient threshold value according to the objective parameter of choice. The method described can be adopted in smart irrigation decision support systems with consideration of spatial variability and after further verification and improvement under more complicated situations with various crop types and varieties, environmental conditions, cultivation modes, and wider or dynamic PWDI thresholds allowing regulated deficit irrigation.

This research was supported partly by National Key Research and Development Program of China (2017YFE0118100, 2016YFD0200303), 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