The influence of elevated atmospheric CO₂ (eCO₂), particularly under future scenarios exceeding 660 ppm, presents a critical uncertainty in modeling the water-food nexus. eCO₂ affects both plant physiology (e.g., stomatal conductance, transpiration, biomass accumulation) and hydrological processes (e.g., evapotranspiration, runoff generation), making its integration into modeling frameworks increasingly important.
I am currently exploring which hydrological and crop growth models are capable of incorporating eCO₂ effects, and to what extent they represent the associated physiological and hydrological mechanisms. Moreover, I am interested in understanding the complexity of these models in terms of how CO₂ response functions are embedded in their algorithms and equations.
Could you recommend hydrologic and crop models that can simulate eCO₂ impacts realistically? How do these models differ in their assumptions, parameterization, and overall representation of CO₂-driven processes?
Your insights, experiences, and any relevant literature would be greatly appreciated.
According to the Annals of Botany and Nature Index, simulating the impacts of elevated atmospheric CO₂ on water and food systems requires models that can capture both plant physiological responses and the broader hydrological dynamics at play. In practice, researchers typically use a combination of advanced crop models and hydrological models—or increasingly, integrated frameworks that couple the two—to achieve robust projections. Here are some prominent examples:
Crop Models
Hydrological Models
Integrated Ecohydrological Frameworks
Recent research is moving toward coupled modeling frameworks that integrate crop physiological responses (including CO₂ fertilization, acclimation, and nutrient feedbacks) directly into hydrological simulations. These advanced models aim to resolve the interactions between improved crop water use efficiency (due to CO₂ effects), altered evapotranspiration rates, and subsequent impacts on regional water cycles. For instance, studies highlighted in recent literature are working to bridge the gap between crop response models and hydrological models, thereby improving the simulation of these feedbacks.
Validation and Calibration
A key strength of these models lies in their calibration against field experiments such as Free-Air CO₂ Enrichment (FACE) studies. Such validations ensure that models accurately capture the real-world responses of crop productivity and water dynamics under elevated CO₂ levels.
Conclusion
While no single model completely encapsulates all the complexities, the state-of-the-art approach involves:
- Utilizing advanced crop models (like APSIM, DSSAT, AquaCrop, EPIC, or LPJmL) modified to simulate enhanced photosynthesis and water use efficiency.
- Coupling these with hydrological models (such as SWAT or VIC) or using integrated ecohydrological frameworks to address water resource implications.
This multi-model approach—and ongoing developments in integrated modeling—offer the most effective means for simulating and predicting the intertwined impacts of elevated atmospheric CO₂ on water and food systems.
Jorge Morales Pedraza Thank you for your comprehensive response.
Rouhollah Davarpanah
Rising atmospheric CO₂ concentrations (eCO₂), particularly in projections forecasting levels exceeding 660 ppm in the coming decades, represent a significant source of uncertainty in modeling the interconnections between water and food systems. eCO₂ directly affects plant physiology—primarily stomatal conductance, transpiration, photosynthesis, and biomass accumulation—and indirectly influences hydrological processes, including evapotranspiration, soil water balance, and surface runoff generation. Therefore, integrating these effects into models is essential for reliable planning under climate change conditions.
Currently available models vary in terms of complexity, the way CO₂ response functions are implemented, and the assumptions on which they are based. Among the models that allow for realistic simulation of eCO₂ effects, the following stand out:
- APSIM (Agricultural Production Systems sIMulator) – A mechanistic model that simulates crop growth processes in detail under elevated CO₂ conditions, including changes in stomatal behavior and water use efficiency (WUE). It is well-suited for precise plot- and region-scale studies.
- DSSAT (Decision Support System for Agrotechnology Transfer) – A widely used model that applies empirical functions to simulate the effects of CO₂ on photosynthesis and transpiration. Although somewhat simplified compared to APSIM, it provides valuable insights into crop productivity under various climate scenarios.
- SWAT (Soil and Water Assessment Tool) – A hydrological model that incorporates CO₂ effects through adjusted coefficients for plant growth and transpiration. However, it relies on fixed, empirical approaches and does not simulate physiological responses of plants dynamically.
- LPJmL (Lund–Potsdam–Jena managed Land model) – A dynamic global model for land and vegetation management, integrating biogeophysical processes and explicitly simulating the effects of eCO₂ on productivity, evapotranspiration, and water fluxes.
These models differ across key parameters: assumptions (empirical vs. mechanistic functions), parameterization (based on FACE experiment data or localized calibration), and model complexity (number of required inputs, temporal and spatial resolution).
From my research experience and review of relevant literature, I believe the most realistic approaches arise from combining agrometeorological and hydrological models (e.g., APSIM + SWAT), which allow for multiscale analysis—from plant level to watershed scale. However, it is crucial that simulations are always supported by experimental data, particularly from FACE (Free-Air CO₂ Enrichment) studies, to avoid errors arising from over-reliance on unvalidated empirical coefficients.
- Badges
- Science topic