MONTPEL: a multi-1 component Penman-Monteith energy balance 2 model

Authors: ALBASHA, RAMI - University Of Montpellier; MANCEAU, LOÏC - University Of Montpellier; WEBBER, HEIDI - Leibniz Centre; CHELLE, MICHAËL - Université Paris-Saclay; KIMBALL, BRUCE - Retired ARS Employee; MARTRE, PIERRE - University Of Montpellier

Submitted to: Agricultural and Forest Meteorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/5/2024
Publication Date: 9/12/2024
Citation: Albasha, R., Manceau, L., Webber, H., Chelle, M., Kimball, B., Martre, P. 2024. MONTPEL: a multi-1 component Penman-Monteith energy balance 2 model. Agricultural and Forest Meteorology. 358. Article 110221. https://doi.org/10.1016/j.agrformet.2024.110221.
DOI: https://doi.org/10.1016/j.agrformet.2024.110221

Interpretive Summary: Crop growth models that simulate effects of weather, soils, and management practices on crop growth and yield are valuable tools for assisting today’s farmers in their management decisions, as well as for developing strategies to cope with future global change. However, most “grow” their crops at air temperature rather than at the crop’s vegetation temperature, which can differ from air temperature by several degrees, especially for irrigated agriculture. If an accounting is made of all the significant energy flows to and from a crop canopy, it is possible to compute the crop’s temperature, as well as its water use. Such code was written for a new wheat growth model called MONTPEL, which can compute the canopy temperature at several heights within the canopy for sunlit and shaded leaves. Comparisons with observed data showed that generally the model can simulate the energy flows, canopy temperatures, and water use well. Therefore, the MONTPEL model has promise for helping to improve present and future crop management practices, which will help all consumers of food and fiber.

Technical Abstract: Mechanistic modelling is gradually replacing empiricism in crop models, emphasizing leaf-level physiological processes, but many crop models still uses empirically-determined formalisms to simulate canopy temperature. Simulating temperature at different depths inside the canopy, for sunlit and shaded leaves, on hourly intervals, becomes essential for precise leaf-level process modeling. We developed MONTPEL, a multi-component Penman-Monteith model that allows simulating the crop energy balance with flexible canopy representations (“BigLeaf” vs. “Layered”, “Lumped” vs. “Sunlit-Shaded”) and accounts for atmospheric stability conditions. We analyzed the model behavior, sensitivity and accuracy, using measurements from four wheat (Triticum aestivum L.) experiments conducted under varying pedoclimatic and water stress conditions. Measurements included hourly energy balance terms (total net radiation, soil heat flux, sensible and latent energy fluxes), hourly temperature of the canopy surface or of leaves at different depths inside the canopy, and sunlit and shaded leaf temperatures around solar noon at different dates. MONTPEL satisfactorily reproduced measurements. The root mean square error (RMSE) of energy balance terms ranged from 20 to 88.7 Wm-2 and the coefficient of determination (R²) exceeded 0.65 for all experiments. The model's accuracy in simulating canopy temperature, with RMSE = 2.2 °C and R² = 0.91, remained consistent regardless of measurement scale. The atmospheric stability correction functions minimized simulated canopy temperature errors, notably in semi-arid conditions. Crop latent energy flux and temperature were most sensitive to the maximal stomatal conductance parameter. Simulating the energy balance with distinct sunlit and shaded canopy fractions systematically resulted in lower latent energy fluxes compared to “Lumped” canopy representation results. Analysis revealed certain limitations in the multi-component approach, particularly an unrealistic uniform temperature shift across leaf layers regardless of their position within the canopy, when soil surface temperature changes. Additionally, this approach would overestimate crop latent energy flux and underestimate sensible heat flux under dense canopy conditions.