Impact of irrigation scheduling on yield and water productivity of soybeans in a sub-humid environment: A modelling approach.

In sub-humid areas, supplementary irrigation is often needed to meet crop water requirements and avoid yield reduction. The effect of water scarcity on agriculture is worsened in locations where summer rainfall is decreasing as a consequence of climate change. In order to stabilize crop production through sustainable water management, improvements of irrigation scheduling methods are required. For instance, traditional irrigation scheduling criteria that provided adequate yields in the past, may no longer be appropriate under drier conditions. Models that combine crop physiological and soil hydrological processes can help improving irrigation scheduling to optimize water productivity. The purpose of this study was to evaluate irrigation management approaches traditionally used by farmers in Austria, specifically at a study site located in the largest crop production area of the country (ca. 35 km east from Vienna), by means of a modelling approach. This study also aimed at proposing an irrigation schedule that increases water productivity, thereby aiding water conservation.

AquaCrop is a crop growth model developed by the Food and Agriculture Organization of the United Nations (FAO) that uses an empirical and mechanistic approach to simulate yield response to water for a variety of crops. In this study, AquaCrop was used to simulate crop water requirements of soybeans in a sub-humid environment under different water management practices. The model was validated after adjustments on the non-conservative crop parameters based on field measurements. The experimental field was divided into four plots. One plot was rainfed and the others were irrigated – each of them by means of a different irrigation system. The systems used were sprinklers on a pipe network, drip lines and a hose reel boom. Irrigation was managed by the farmers based on their experience. The collected data included leaf area index to obtain green canopy cover development and soil samples at different depths to characterize the soil. After the validation process, an irrigation schedule that covered the full crop water requirements was automatically generated by the model. Additionally, irrigation schedules for each irrigated plot were generated based on percentage of readily available soil water (RAW) thresholds.

The simulated yields were in good agreement with the observed data, with a model efficiency coefficient (EF) > 0.80 for the four plots. The irrigated plots revealed a certain level of stress during the critical crop growth stage of flowering, even though they were expected to represent well-watered conditions. After simulating net crop water requirements, the resulting potential yield was larger than the observed yields. Furthermore, the irrigation events generated using RAW thresholds also produced larger yields than the observed ones. The results showed that to schedule the irrigation events earlier in the season and distribute the same total irrigation water amount in four events rather than three – as scheduled by the farmers – increased the yield and thus, water productivity. Therefore, AquaCrop model predictions can help improving farmers’ irrigation scheduling strategies for soybeans under this study conditions. This might be helpful for local farmers in situations of increasing pressure on water resources.