Incorporating a plant water supply-demand framework into Noah-MP land surface model to simulate hydrological fluxes for agroecosystems

Abstract:

Understanding plant water stress is key to evaluation of drought impacts and irrigation management for agroecosystems. However, the quantification of plant water stress in earth system models has long been a challenge. The empirical soil water stress function in most earth system models is over-simplified and tends to overestimate soil water stress under water limited conditions. Plant hydraulic models, on the other side, explicitly resolve water movement through the soil-plant-atmosphere continuum (SPAC) and can most realistically represent the plant-water relationship; however, these models have increased complexities and the various parameters involved could be challenging to constrain. Here, we incorporate a plant water supply-demand framework into the Noah-MP land surface model to quantify plant water stress and improve the simulation of hydrological fluxes. The plant water demand is calculated as the potential transpiration assuming no soil water stress, which is driven by atmospheric dryness (i.e., the vapor pressure deficit (VPD)), and the plant water supply is the root water uptake rate under given soil moisture. The actual transpiration is then determined as the minimum of supply and demand. This new approach (1) avoided the problematic soil water stress function, and (2) used a parsimonious method to equivalently simulate the complex plant hydraulic response as the balance between water supply and demand. This approach is especially effective for crops because of their relatively short hydraulic pathways. We demonstrate that this supply-demand model can improve the simulation performance under water limited conditions compared to the empirical soil water stress function, and can also reproduce similar stomatal responses to soil and atmospheric dryness compared to plant hydraulic models. The simulation results further highlight the increasing water stress risk for crops with rising VPD under climate change. We envision this parsimonious supply-demand based model to be a useful tool in precision agricultural applications as well as in improving our understanding and modeling capabilities in land-atmosphere interactions.