Agriculture is directly related to food security as it determines the global food supply. Research in agriculture to predict crop productivity and losses helps avoid high food demand with little supply and price spikes. Here, we review ten crop models and one intercomparison project used for simulating crop growth and productivity under various impacts from soil–crop–atmosphere interactions. The review outlines food security and production assessments using numerical models for maize, wheat, and rice production. A summary of reviewed studies shows the following: (1) model ensembles provide smaller modeling errors compared to single models, (2) single models show better results when coupled with other types of models, (3) the ten reviewed crop models had improvements over the years and can accurately predict crop growth and yield for most of the locations, management conditions, and genotypes tested, (4) APSIM and DSSAT are fast and reliable in assessing broader output variables, (5) AquaCrop is indicated to investigate water footprint, quality and use efficiency in rainfed and irrigated systems, (6) all models assess nitrogen dynamics and use efficiency efficiently, excluding AquaCrop and WOFOST, (7) JULES specifies in evaluating food security vulnerability, (8) ORYZA is the main crop model used to evaluate paddy rice production, (9) grain filling is usually assessed with APSIM, DAISY, and DSSAT, and (10) the ten crop models can be used as tools to evaluate food production, availability, and security.

Droughts exert widespread impacts on both natural and social systems, and there is accumulating evidence that this situation may worsen in the context of global warming. Despite the importance of assessing changes in droughts to understand their potential future impacts on society, studies are unevenly distributed worldwide. In this study, utilizing bias-corrected CMIP6 simulations and a standard precipitation-evaporation index based approach, we quantified expected changes in future drought properties across 735 Brazilian catchments under SSP2-4.5 and SSP5-8.5 scenarios. Beyond evaluating the statistical properties of future droughts, we assessed their occurrence under both land use and water demand perspectives and propose a new framework to better understand their link with changes in long- and short-term conditions of precipitation ( P ) and potential evapotranspiration ( PET ). Our results indicate that drought events are projected to become more frequent and severe in the future, with high CMIP6 model agreement. According to the SSP5-8.5 scenario, at least half of Brazilian cropland and pasture areas will experience an increase of over 30% in drought properties by the end of the century. Furthermore, among the 85% of catchments expected to experience more severe droughts, nearly 90% are also projected to exhibit increased water demand, which will likely exacerbate future water scarcity. The investigation of the relationship between droughts changes and climate variables suggests that catchments with augmented droughts in the future will likely exhibit increased long-term average PET and P -variability, but not necessarily long-term average P . For instance, over 50% of evaluated Brazilian catchments are expected to experience an intensification of drought properties even with increases in P mean . We believe this study may contribute (a) to improve Brazilian water resiliency by helping achieve the objectives of the National Water Security Plan and (b) to deepen our understanding of droughts in an uncertain future.

The global food supply and food security are altered by field, soil, and weather conditions during crop production. Researching food productivity became crucial as the global population increased. In particular, crop losses bring low food supply and price instabilities at the regional and global levels. With that in mind, we reviewed ten crop models and the most simulated impacts from soil-crop-atmosphere interactions in maize, rice, and wheat production. Since 2012, modellers have mainly used APSIM to predict water availability, temperature changes and Greenhouse Gas (GHG) concentration to predict crop phenology, growth and development, grain filling and nutrient content, and yield. Since 2013, AquaCrop has been used to simulate scenarios focused on water balance in crop production systems, water stress and irrigation planning. Interestingly, Biome-BGCMuso was developed as a biogeochemical model and was not considered good by crop modellers. However, After updates, version v6.2 can simulate different management and field conditions for fifteen crops, considering heat, nitrogen and drought stress. Since 2008, crop modellers used CropSyst to evaluate water availability, nitrogen use efficiency (UE), temperature shifts and GHG concentration in rainfed and irrigated crop systems. Since 2002, crop modellers have used DAISY to predict crop growth, nitrogen and water UE, grain content, yield gap, and losses. Since 2011, researchers have used DSSAT-CERES for mitigation strategy planning by predicting crop growth, soil characteristics, changes in land use, and nitrogen and water UE. Since 2015, JULES has been used to determine land-atmosphere interactions, changes in land use and GHG impacts on agriculture. Since 2008, ORYZA modellers have mainly predicted nitrogen and water UE, salinity impacts, and toxicity to rice. STICS was developed in 1996, and since 2008, it has been primarily used to simulate fertilization and irrigation systems, nitrogen leaching, and water availability. Since 2000, researchers have used WOFOST to analyze water availability, crop growth, and productivity under temperature changes. Crop models are fast and reliable resources when simulating crop production and food availability.