Towards Better Agricultural Drought Assessment and Irrigation Management: Improving the Simulation and Understanding of Plant Water Stress for Crops in Noah-MP Surface Model

Accurately quantifying plant water use is critically important for understanding ecosystem response to drought, yet the current modeling approaches have large uncertainties. This study provides a unified framework of different theories for modeling plant water use, illustrates the relationships and conversions between different models, quantifies their similarities and differences and evaluated their applicability under different environmental conditions. Through this study, we have three important findings. First, we found that mathematically simplified models can be represented by a full plant hydraulic model under certain conditions. For example, the supply-demand balance scheme is a plant hydraulic model with infinite xylem to leaf conductance and a step function- like leaf stomata response to leaf water potential. Second, we decomposed the difference of the aggregate behaviors between the fill model and the simplified model and found that the simplified models can recover the missing processes by introducing new components. Third, we argue that the importance of the discrepancies between the simplified models and the full model can be assessed in a systematic way. We thus propose a framework for assessing the applicability of simplified models under different environmental conditions. This framework improves our understanding of modeling plant water use and would greatly help modelers choose the most suitable models for the intended applications. This study would have broad interest from ecosystem modeling applications and especially contribute to agricultural water management (e.g., irrigation) and help achieve the cosustainability of food production and water resources.

  • PI: Kaiyu Guan
  • PI Institution: University of Illinois
  • March 1, 2020 – December 31, 2021