Agricultural and Forest Meteorology

Abstract Irrigation is practiced on approximately 20% of the agricultural land in the world and accounts for approximately 40% of the total crop production. However, with global warming and an increasing population, the agricultural water consumption increases, leaving generally less water for the natural ecosystems. An increase in water efficiency of agro-ecosystems, especially irrigated agro-ecosystems in arid and semi-arid regions, is an urgent task. The use of computer models to simulate interactions and feedbacks between relevant processes during crop growth is becoming more common and almost a prerequisite for proper management of irrigation water. In this paper, we describe the integration of SHAW, a soil-vegetation-atmosphere transfer (SVAT) model, with a stomatal-photosynthesis model and WOFOST, a crop growth model, to simulate the energy, water and carbon budgets during crop growth. The coupled model was tested and applied for a field study on irrigated maize [38°51′ N, 100°25′ E, altitude 1519 m a.s.l.], located in an irrigation oasis of the Heihe river basin in arid Northwest China. The coupled model performs well in simulating the diurnal variation of the leaf water potential, stomatal resistance and transpiration at leaf scale, before and after irrigation. At the canopy scale, the coupled model also reproduces the daily changes in the sensible and latent heat fluxes, carbon dioxide flux, and dynamic soil water content during maize growth and fallow periods. Moreover, there was good agreement between the simulated maize biomass and the field measurements. These results demonstrate that the holistic coupled model not only successfully simulates the actual effect of soil water stress on crop transpiration and photosynthesis, but also can describe the interactions of energy, water, and carbon cycles of the agro-ecosystem and predict crop production under irrigation. This is encouraging for the modelling of crop response to droughts and changed cropping and irrigation regimes aiming at optimized water use. Meanwhile, this study indicates that integrating methods of different physically based models is highly efficient and useful for a better understanding of the interaction between hydrological and ecological processes in the agro-ecosystem.