EVALUATION OF SIMULATION BASED DEFICIT IRRIGATION AND FERTILIZATION STRATEGIES TO MAXIMIZE WATER PRODUCTIVITY AND NITROGEN USE EFFICIENCY

摘要

A doubling in global food demand projected for the next 50 years poses huge challenges forrnthe sustainability of crop production. Moreover, society is becoming increasingly concernedrnwith agricultural use of water and nitrogen which are two critical resources for crop growth.rnAvoiding excessive percolation and adjusting N-applications are prerequisites to reducernN-leaching while maintaining high crop yields. For that, Soil-Vegetation-Atmosphere Transferrn(SVAT) models, which describe physical and physiological processes of crop growth as wellrnas of water and matter transport, enhance optimal irrigation and fertilization management.rnIn this study, a new simulation based optimization framework for simultaneous schedulingrnof irrigation and N-fertilization was developed in order to maximize water productivity (WP)rnand at the same time nitrogen use efficiency (NUE). The employed framework consists of arntailor-made evolutionary optimization algorithm and the process-based SVAT-model DAISYrnfor simulating water balance, nitrogen balance and crop growth. The optimization frameworkrnfor optimizing irrigation and N-fertilization was applied in experiments in 2010, were corn (Zearnmays L.) was cultivated in a vegetation hall. Irrigation water and nitrogen were simultaneouslyrnand optimally distributed over one growing period to achieve maximum WP and NUE. Thernsimultaneous scheduling strategy was compared to different other deficit irrigation and deficitrnN-fertilization strategies. The results showed that applying the framework, WP was increased.