Process Based Modeling

Process-based models representing the soil-plant-atmosphere continuum are increasingly capable of leveraging high-resolution remote sensing data to predict the dynamics of water and carbon fluxes in ecosystems. These models incorporate detailed mechanistic representations across multiple scales, enhancing our understanding of ecosystem functioning. The assimilation of high-resolution observations into these models using inversion frameworks facilitates the quantification of ecosystem responses to environmental stressors while also improving the structural formulation of the models, leading to more accurate and robust predictions.