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Knowledge of actual crop transpiration (T) is important for advanced crop management but challenging to obtain due to the large spatial and temporal variation of T. Remote sensing offers various possibilities to assess T dynamics, while particularly sun-induced chlorophyll fluorescence (SIF) has been demonstrated as a sensitive empirical proxy for T. Despite this success, the advancement of the mechanistic understanding of how SIF relates to T dynamics is key for the future development and implementation of robust and reliable SIF-based T products. This study aims to contribute insights by experimentally assessing the sensitivity of several SIF-based T estimation strategies for evolving soil water limitation. We investigated extensive in situ and airborne data acquired during a water limitation experiment in a maize canopy in northern Italy. We evaluated five empirical strategies to integrate SIF in a T modelling framework based on the Penman-Monteith (PM) and the Ball-Berry-Leuning (BBL) concepts. Our results indicate that replacing model parameters sensitive to canopy conductance with SIF results in the best agreement between modelled and measured T under evolving water limitation. Our study contributes expanding existing knowledge with empirical insights on the sensitivity of SIF based T approaches under increasing soil water limitation at short time scales. [ABSTRACT FROM AUTHOR]

Reducing water losses in agriculture needs a solid understanding of when evaporation (E) losses occur and how much water is used through crop transpiration (T). Partitioning ecosystem T is however challenging, and even more so when it comes to short‐statured crops, where many standard methods lead to inaccurate measurements. In this study, we combined biometeorological measurements with a Soil‐Plant‐Atmosphere Crop (SPA‐Crop) model to estimate T and E at a Swiss cropland over two crop seasons with winter cereals. We compared our results with two data‐driven approaches: The Transpiration Estimation Algorithm (TEA) and the underlying Water Use Efficiency (uWUE). Despite large differences in the productivity of both years, the T to evapotranspiration (ET) ratio had relatively similar seasonal and diurnal dynamics, and averaged to 0.72 and 0.73. Our measurements combined with a SPA‐Crop model provided T estimates similar to the TEA method, while the uWUE method produced systematically lower T even when the soil and leaves were dry. T was strongly related to the leaf area index, but additionally varied due to climatic conditions. The most important climatic drivers controlling T were found to be the photosynthetic photon flux density (R2 = 0.84 and 0.87), and vapor pressure deficit (R2 = 0.86 and 0.70). Our results suggest that site‐specific studies can help establish T/ET ratios, as well as identify dominant climatic drivers, which could then be used to partition T from reliable ET measurements. Moreover, our results suggest that the TEA method is a suitable tool for ET partitioning in short‐statured croplands. Plain Language Summary: To reduce water losses linked to agriculture, we need to understand how much water the crops transpire and how much water is evaporated from irrigation surplus. Measuring how much water plants transpire is however difficult, especially for short‐statured crops like wheat or barley, because they are too small for the usual measurement techniques. In our study, we use detailed climate and vegetation measurements at a cropland in Switzerland combined with a model, and compare with two other data‐driven partitioning approaches (Transpiration Estimation Algorithm (TEA), underlying Water Use Efficiency (uWUE)). Our results show that the measurements combined with a model compared well with one of the approach (TEA), while the other (uWUE) was less well suited for our cropland. Our results demonstrate that there are ratios of the transpiration to evapotranspiration (i.e., including evaporation) that tend to be stable for specific ecosystems, and that could therefore be used once they are known for an ecosystem. Our results also show that the amount of light and the atmospheric demand for water vapor are important drivers for transpiration on a daily basis, while the plant cover determines the overall rate. Key Points: High agreement between transpiration (T) from measurements combined with a process‐based model (Soil‐Plant‐Atmosphere Crop) and a data‐driven method (Transpiration Estimation Algorithm)Diurnal and seasonal T to evapotranspiration ratios were relatively similar despite differences in crop and productivity between yearsDetailed crop specific models are a powerful method for partitioning T in short‐statured croplands to address lack of measurement methods [ABSTRACT FROM AUTHOR]

The global exchange of gas (CO2, H2O) and energy (sensible and latent heat) between forest ecosystems and the atmosphere is often assessed using remote sensing (RS) products. Although these products are essential in quantifying the spatial variability of forest–atmosphere exchanges, large uncertainties remain from a measurement bias towards top of canopy fluxes since optical RS data are not sensitive for the vertically integrated forest canopy. We hypothesize that a tomographic perspective opens new pathways to advance upscaling gas exchange processes from leaf to forest stands and larger scales. We suggest a 3D modelling environment comprising principles of ecohydrology and radiative transfer modelling with measurements of micrometeorological variables, leaf optical properties and forest structure, and assess 3D fields of net CO2 assimilation (An) and transpiration (T) in a Swiss temperate forest canopy. 3D simulations were used to quantify uncertainties in gas exchange estimates inherent to RS approaches and model assumptions (i.e. a big‐leaf approximation in modelling approaches). Our results reveal substantial 3D heterogeneity of forest gas exchange with top of canopy An and T being reduced by up to 98% at the bottom of the canopy. We show that a simplified use of RS causes uncertainties in estimated vertical gas exchange of up to 300% and that the spatial variation of gas exchange in the footprint of flux towers can exceed diurnal dynamics. We also demonstrate that big‐leaf assumptions can cause uncertainties up to a factor of 10 for estimates of An and T. Concluding, we acknowledge the large potential of 3D assessments of gas exchange to unravelling the role of vertical variability and canopy structure in regulating forest–atmosphere gas and energy exchange. Such information allows to systematically link canopy with global scale controls on forest functioning and eventually enables advanced understanding of forest responses to environmental change. [ABSTRACT FROM AUTHOR]