A sensitivity analysis of a FAO-56 dual crop coefficient-based model under various field conditions. (February 2023)

• Record Type: Journal Article
• Authors: Laluet, Pierre; Olivera-Guerra, Luis; Rivalland, Vincent; Simonneaux, Vincent; Inglada, Jordi; Bellvert, Joaquim; Er-raki, Salah; Merlin, Olivier
• Is Part Of: Environmental modelling & software. Volume 160(2023)
• Publication Date: 2023-02
• Subjects: FAO-56 model -- Sobol sensitivity analysis -- Evapotranspiration -- Deep percolation -- Remote sensing -- Calibration; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2022.105608
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: FAO-56 dual crop coefficient (FAO-2Kc) based model are increasingly applied at large scale for agricultural water monitoring, requiring field-scale data over the spatial extent of interest. Given the lack of in-situ measurements, satellite products can be used to estimate indirectly the parameters through calibration. However, a lack of knowledge about model sensitivity can lead to suboptimal use of satellite data. This study aims to analyze the sensitivity of SAMIR, a FAO-2Kc-based model using satellite data. The Sobol method was applied for evapotranspiration (ET) and deep percolation (DP) simulations on 37 contrasted agricultural seasons. Results indicate that SAMIR's sensitivity mainly depends on the modeled water stress. We proposed a proxy for the model sensitivity which can determine 84% (73%) of the ET (DP) among the agricultural seasons. An interaction analysis allowed reducing the calibration problem to the adjustment of only two parameters (a_Kcb and Zr_max), accounting for most of the sensitivity. Highlights: The sensitivity of a FAO-2Kc-based crop water balance model is analyzed. Evapotranspiration and deep percolation are analyzed over contrasted crop sites. Two parameters are found to be the most sensitive (a_Kcb and Zr_max). A proxy for the model's sensitivity is derived from the modeled crop water stress. The proxy explains 73–84% of the variability in the model output sensitivity.