Regional and global climate projections increase mid-century yield variability and crop productivity in Belgium

Abstract

The impact of mid-century climatic changes on crop productivity of winter wheat, maize, potato and sugar beet was assessed for a temperate maritime climate in the Flemish Region, Belgium. Climatic projections of multiple regional and global climate models (RCMs from the EU-ENSEMBLES project and GCMs from the Coupled Model Intercomparison Project phase 3) were stochastically downscaled by the LARS-WG weather generator for use in the crop models AquaCrop and Sirius. Primarily positive effects on mean yield were simulated. Crops benefitted from elevated CO 2., and from more radiation interception if the cropping period was adapted in response to higher temperatures. However, increased productivity was linked with increased susceptibility to water stress and greater inter-annual yield variability, particularly with adapted management. Impacts differed among and within ensembles of climate models, and among crops and environments. Although RCMs may be more suitable for local impact assessments than GCMs, inter-ensemble differences and contingent wider ranges of impacts with GCM projections found in this study indicate that applying RCMs driven by a limited number of GCMs alone would not give the full range of possible impacts. Further, this study suggests that the simulated inter-model variation can be larger than spatial variation within the region. These findings advocate the use of both GCM and RCM ensembles in assessments where temperature and precipitation are central, such as for crop production.

The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO2

“…Given the relatively favorable future growth condition in this region (Fig. 2), the projected high yield losses might be a result of mismatch in cultivar or planting date; thus, tuning cultivars and planting dates with future climate change may counterbalance the negative impact (e.g., Vanuytrecht et al, 2016).…”

Modeling Sugar Beet Responses to Irrigation with AquaCrop for Optimizing Water Allocation

“…This model can simulate the yield response to water more accurately with a relatively small number of parameters than other models, which makes it more attractive for simulations under water-limited conditions or for irrigation scheduling. For these reasons, AquaCrop has been implemented to assess the sugar beet production under different scenarios [23,24]. Nevertheless, as for any model application, AquaCrop must be accurately calibrated and validated.…”

“…Once the model is properly parameterized, it can be used for multiple purposes, both at the plot scale (e.g., irrigation scheduling, as in Reference [25]) or farm scale (e.g., optimization of the irrigation and cropping patterns, as in Reference [26]) and at basin (e.g., integrated assessment modelling, as in Reference [27]) or regional level (e.g., crops responses to climate change [23]). Ultimately, AquaCrop can be a useful tool for supporting decision-making at different levels, especially in terms of irrigation water management for a crop such as sugar beet, which is facing water scarcity challenges in most of the production areas.…”

Simulation of the Responses of Dry Beans (Phaseolus vulgaris L.) to Irrigation

“…A number of reports have been published recently on that subject for maize (Ahmadi et al, 2015), sorghum (Araya et al, 2016), winter wheat (Xiangxiang et al, 2013), potato (Montoya et al, 2016), and soybean (Adeboye et al, 2017). Beyond the plot scale, AquaCrop has been used for economic optimization at the farm scale (García-Vila and Fereres, 2012), for yield gap analyses (Nyakudya and Stroosnijder, 2014;Angella et al, 2016), and for yield prediction in climate change scenarios (Vanuytrecht et al, 2016;Yang et al, 2017).…”