Under climate change conditions, optimizing water resources management in rainfed agricultural production systems requires the reasonable choice of crops. In this context, the adoption of crops diversification is promoted to increase the agricultural production and the added value per cubic meter of rain water (green water) used by crops. Contributing, therefore, to increase agricultural production and to preserve soil and water resources. The objective of this study is: (i) to identify mixed crops within agricultural fields and, (ii) to evaluate the biomass production and the water productivity in the Lebna watershed (Cap-Bon, Tunisia) using remote sensing and field measurements. The study area, covering 210 km2, is characterized by the predominant of cereals, legumes and fodder cropping systems. The experiments allowed the quantification of crop evapotranspiration and the observed biomass production at the agricultural field plots. The use of the sentinel images and the observations at different agricultural fields allowed to produce NDVI maps. The results first confirmed a good correlation between biomass production and NDVI values. The exponential relationships showed a values of R2 greater than 0.7. The use of sentinel images and GIS allowed to compute water productivity from field to watershed scale. The results revealed a considerable spatial variation in water productivity values for different crops. Compared to a single crop, the cereal-legume mixture cropping improved the water productivity. The maximum value with 9.07 kg m−3 is observed for the mixture crops. The lowest value (0.12 to 2.40 kg m−3) was obtained for the cereal crop. These results help to recommend adaptation measures in agricultural production systems to climate change.

Abstract : Irrigated olive trees constitute the main arboricultural component of orchards in semi-arid regions, and the optimization of irrigation practices is crucial to sustain the production, increase agricultural water productivity and reallocate water savings to other higher-value uses. Numerous technical strategies have been implemented in the last two decades, to promote water conservation in irrigated agriculture, namely the adoption of subsurface drip irrigation system. This study delves into a comprehensive comparative analysis between subsurface (SDI) and surface (DI) drip irrigation systems over an olive orchard, with an emphasis on the evolution of evaporative fraction (EF) and the ratio of transpiration (T) to evapotranspiration (ET), soil moisture distribution patterns, as well as water use efficiency and water productivity. The experiment was carried out over two irrigated olive plots located in the Tensift basin (Morocco), from May to October 2022. Each plot is subjected to a specific irrigation pattern, and equipped with an Eddy-Covariance system to quantify the energy balance components, along with Time-Domain-Reflectometry (TDR) sensors installed at various depths, to monitor the soil water content. Besides, the partitioning of ET into T and evaporation (E) over the two irrigation systems was performed using the Conditional Eddy-Covariance (CEC) scheme and validated using sap flow measurements collected over SDI plot during April 2023. The ET of the DI system was higher than that of the SDI one, with diurnal ET values ranging between 0.58-3.02 (mm/day) and 0.48-2.74 (mm/day) for DI and SDI systems, respectively. Our findings suggest that although a smaller irrigation water amount was applied in SDI (194 mm) compared to DI (320 mm), crop yield revealed no significant differences. This thorough assessment intends to add substantial knowledge to the lasting debate about sustainable irrigation practices over olive orchards and assist policymakers in making informed decisions to enhance water use efficiency while sustaining overall agricultural production.Keywords: subsurface and surface drip irrigation; evapotranspiration; water productivity; water use efficiency; olive trees; semi-arid areas.

Mediterranean hilly landscapes, surface runoff is one of the main hydrological processes that redistributes water from upslope to downslope. In agricultural catchments, surface runoff causes rainfall water to transfer from upstream plots to downstream plots due to hydrological connectivity. The water thus redistributed can then infiltrate into the soil of the downstream plot, depending on the soil's infiltration capacity, thereby increasing water availability in the root zone. While the impact of hydrological connectivity on hydrological processes such as streamflow generation is well recognized, few studies evaluate its effect on crop functioning. In general, crop functioning is studied using multilocal methods that assume hydrological independence between plots, overlooking the influence of hydrological connectivity. In the development of catchment agro-hydrological models, the coupling between the crop model and the hydrological model is partly conditioned by the effect of hydrological connectivity.The objective is to study the effect of water redistribution through runoff on crop functioning in the context of Mediterranean rainfed annual crops, using a modelling approach. A numerical experiment using the AquaCrop model was performed, considering two hydrologically connected plots. The experiment explored a range of agro-pedo-climatic conditions upstream and downstream: crop type, soil texture and depth, climate forcing, and the size of the upstream plot. Data collected over the past 25 years from the OMERE Environmental Research Observatory in northeastern Tunisia (Molénat et al., 2018) were used, along with data from the literature. The Aquacrop model was previously parametrised and validated for the soil, crop and climate conditions of this in northeastern Tunisia site (Dhouib et al., 2022).Results show that annual crop production under semi-arid and subhumid climatic conditions can be increased due to hydrological processe in a moderate number of cases (16% for wheat and 33% for faba bean on average for above-ground biomass and yield) (Dhouib et al., 2024). Positive impacts are mainly observed for higher soil water retention capacity and under semi-arid and dry subhumid climate conditions, with a significant effect of the intra-annual distribution of rainfall in relation to crop phenology. Dhouib M., Zitouna-Chebbi R., Prevot L., Molénat J., Mekki I., Jacob F. (2022). Multicriteria evaluation of the AquaCrop crop model in a hilly rainfed Mediterranean agrosystem. Agricultural Water Management, 273, 107912, https://dx.doi.org/10.1016/j.agwat.2022.107912Dhouib M, Molénat J., Prevot L., Mekki M, Zitouna-Chebbi, C et Jacob F.. Numerical exploration of the impact of hydrological connectivity on rainfed annual crops in Mediterranean hilly landscapes. Agronomy for Sustainable Development, 2024, 44 (6), 51 p. ⟨10.1007/s13593-024-00981-5⟩. ⟨hal-04752688⟩Molénat J., Raclot D., Zitouna R., et al., 2018. OMERE, a long-term observatory of soil and water resources in interaction with agricultural and land management in Mediterranean hilly areas. Vadose Zone journal, 17(1), doi:10.2136/vzj2018.04.008

Rainfed agriculture supports a significant share of global food production, balancing water storage with competing demands through runoff management. Human interventions to manage runoff range from temporary practices (e.g., tillage adjustments, crop residue retention) to permanent structures such as terraces and ditches. While practices are adaptable, structures are less flexible but critical for climate resilience. Their life-cycle comprises design/construction, maintenance, abandonment/destruction, and rehabilitation. Despite extensive research on design, rehabilitation, and abandonment, the description, understanding, and impact of maintenance practices remain understudied. This paper addresses this gap through a configurative review (1954-2024), integrating scattered knowledge. We show that rainfall variability, driven by climate change, accelerates biophysical degradation (e.g., terrace deformation, ditch occlusion), requiring adaptation and knowledge sharing to ensure structural stability and hydrological connectivity. Results highlight how regional inconsistencies in structure names hinder cross-regional comparisons and research consolidation. Our contributions include a framework for standardizing: (1) a context-specific evaluation of maintenance practices and (2) an assessment of runoff management structure efficiency under climate change. By integrating biophysical durability, socioeconomic feasibility, and adaptive governance, this framework provides stakeholders and academic actors with a common basis for systematically evaluating and improving runoff management. In practice, we urge policymakers and practitioners to adopt proactive, climate-adaptive maintenance, and to incentivize local community involvement for hybridizing traditional knowledge and technical innovation. By integrating maintenance into farming system design and management, these structures may effectively mitigate the impacts of an increasingly unpredictable climate, ensuring long-term resilience and sustainability in rainfed agriculture.

Within hilly agricultural landscapes, topography induces lateral transfers of runoff water, so-called interplot hydrological connectivity. Runoff water from upstream plots can infiltrate downstream plots, thus influencing the water content in the root zone that drives crop functioning. The impact of runoff on crop functioning can be crucial for optimizing agricultural landscape management strategies. However, to our knowledge, no study has specifically focused on the impact on crop yield. The current study aims to comprehensively investigate the impact of runoff on crop functioning in the context of Mediterranean rainfed annual crops. To quantify this impact, we conduct a numerical experiment using the AquaCrop model and consider two hydrologically connected plots. The experiment explores a range of upstream and downstream agro-pedo-climatic conditions: crop type, soil texture and depth, climate forcing, and the area of the upstream plot. The experiment relies on data collected over the last 25 years in OMERE, an environment research observatory in northeastern Tunisia, and data from literature. A key finding in the results is that water supply through hydrological connectivity can enhance annual crop production under semiarid and subhumid climate conditions. Specifically, the results show that the downstream infiltration of upstream runoff has a positive impact on crop functioning in a moderate number of situations, ranging from 16

In the Mediterranean region, considered as the prominent hotspot in future climate change projections, water scarcity becomes the main challenge for the agricultural sector. This is mainly the case of the Tunisian agriculture that is substantially based on rainfed crops to ensure food security. Thus, monitoring and assessing the vegetation conditions may provide accurate information, which allows improving water productivity and helps decision-making including water management. Currently, satellite-derived vegetation data has been widely used to assess the crop production and the effect of water shortage and extreme climatic events. In this context, the FAO portal to monitor water productivity through open-access of remotely sensed derived data (WaPOR) WAPOR database was developed to monitor the water productivity through remotely sensed derived data. The aim of this work is to evaluate WAPOR ability to estimate the biomass of rainfed annual crops in the Cap Bon region in the North-East of Tunisia. The WAPOR products covering the study area are available at the national level (Level 2) with a spatial resolution of 100 m. Measured aboveground of local cereals varieties of wheat, barley and oat and mixed fodder crops (faba-bean, triticale and vetch) was compared to the estimated actual evapotranspiration and interception (ETa_WAPOR), during four years with different climatic conditions. The area of the considered agricultural fields varies from less than one hectare to around 10 ha. The estimated cumulative actual evapotranspiration (ETa_WAPOR) calculated from the predicted decadal ETa shows an acceptable correlation with the monitored dry biomass (R2 = 0.78) but with high RMSE value of around 2.7 ton/ha. The performance of WAPOR estimation doesn't seem to vary with seasonal climatic conditions.

Olives constitute a frequently grown crop in semi-arid areas. Therefore, accurate quantification of evapotranspiration (ET) within olive groves is crucial to enhance agricultural water productivity and promote their resilience to water scarcity and future climate scenarios. In the present work, we assessed the accuracy of 3 versions of the Two-Source-Energy-Balance (TSEB) model, the first one "TSEB-SPT" using a standard Priestley-Taylor coefficient (αPT) to estimate the transpiration, the second one called "TSEB-CPT" constrained by a computed αPT using measured ET along with the equilibrium term, and the third one "TSEB-SM" where soil moisture is used as an additional constraint to improve the soil evaporation. The 3 models were applied over an irrigated olive orchard in the Tensift basin (Morocco) during two growing periods of 2003 and 2004. The comparison with ground-based flux measurements from Eddy-Covariance tower and sap flow data revealed that the TSEB-SPT model overestimates ET with an average relative error of 87% and a percentage bias of ‐78% during the two growing seasons. Conversely, TSEB-SM and TSEB-CPT improved ET estimates as compared to TSEB-SPT, with mean relative errors of 31% and 24% and an average percentage bias of 0.6% and ‐7.4%, respectively. For ET partitioning, TSEB-SM appears to be less effective in estimating transpiration, while the simulated transpiration by TSEB-CPT fits well the actual one with a root mean square error of 0.27 mm, mainly during the summer of 2003. These results open a path for future improvements: by reviewing the calibration procedure of αPT, and implementing alternative formulas to compute the evaporation, the TSEB-SM could be potentially a robust tool for monitoring the seasonal variation of ET and its partitioning over a heterogeneous canopy cover.

Rainfed Mediterranean agriculture (MA) must adapt to water scarcity due to climate change and pressures on water resources. According to recent literature, two adaptation solutions based on the concept of diversification can be explored. The first solution is crop diversification at the field level. Three main cropping systems, namely agroforestry, intercropping, and service crops, have been shown to increase soil water availability and to improve crop water use. The second solution is to consider diversification at the landscape level by diversifying crops and associated agricultural management practices (in number, abundance, and spatial organization) and building small-scale water-harvesting infrastructures (WHI). In order to move toward a sustainable MA, one of the main scientific challenges ahead is to provide knowledge and tools, such as integrated agro-hydrological models, useful to evaluate several spatiotemporal combinations of these solutions in order to optimize soil water availability and crop water use.

Abstract Water scarcity is already set to be one of the main issues of the 21st century, because of competing needs between civil, industrial, and agricultural use. Agriculture is currently the largest user of water, but its share is bound to decrease as societies develop and clearly it needs to become more water efficient. Improving water use efficiency (WUE) at the plant level is important, but translating this at the farm/landscape level presents considerable challenges. As we move up from the scale of cells, organs, and plants to more integrated scales such as plots, fields, farm systems, and landscapes, other factors such as trade-offs need to be considered to try to improve WUE. These include choices of crop variety/species, farm management practices, landscape design, infrastructure development, and ecosystem functions, where human decisions matter. This review is a cross-disciplinary attempt to analyse approaches to addressing WUE at these different scales, including definitions of the metrics of analysis and consideration of trade-offs. The equations we present in this perspectives paper use similar metrics across scales to make them easier to connect and are developed to highlight which levers, at different scales, can improve WUE. We also refer to models operating at these different scales to assess WUE. While our entry point is plants and crops, we scale up the analysis of WUE to farm systems and landscapes.

The current study aims to document evapotranspiration and associated surface energy fluxes for rainfed annual crops within a Mediterranean hilly agrosystem, in order to provide information on crop water use under such little-studied conditions. For this, an experimental study is conducted within the Tunisian study site of the OMERE observatory (French acronym for the Mediterranean Observatory of Water and the Rural Environment), located in the north-eastern Cap Bon peninsula. It relies on eddy covariance (EC) measurements at the plot scale. We report that (1) observations are consistent with previous studies under Mediterranean or semi-arid contexts, with time series of energy fluxes that depict classical seasonal dynamics, (2) common flux ratios (i.e., Bowen Ratio, ratio of actual to reference evapotranspiration) may change according to upwinds and downwinds, which requires further investigations about possible changes in aerodynamic conditions, and (3) a reference evapo-transpiration value of 4 mm day(-1) seems to be a threshold beyond which actual evapotranspiration decreases systematically and rapidly. In terms of agricultural water management, the current study suggests to look for early sowing species/varieties, in order to reduce the evaporation-based water loss in autumn. Overall, EC measurements seem promising over rainfed annual crops within semiarid hilly agrosystems, for long term ob-servations, environmental modelling and operational purposes. Since the current study is conducted over few small fields within a specific hilly topography, the original results we report here need to be strengthened with complementary studies.

Soil available water capacity (SAWC) is a key factor to be considered when assessing soil capability to provide ecosystem services. The current study deepens the use of remotely sensed data for mapping SAWC and its components from crop model inversion. The inversion was conducted using the STICS (Simulateur mulTI-discplinaire pour les Cultures Standard) crop model along with the GLUE (Generalized Likelihood Uncertainty Estimation) algorithm on a panel of 14 sites within a rainfed vineyard catchment located in Southern France. Several constraint variables derived from Landsat 7 ETM + satellite imagery (leaf area index -LAI -and evapotranspiration -ET) or in-situ measurements (surface soil moisture -SSM), were used in the inversion process alone or in combination. Three main outcomes could be reported when comparing retrievals of both SAWC and its components against field estimates. First, retrievals were significantly correlated with ground estimates for some SAWC components and some scenarios of constraint variables, although overall retrieving performances were quite poor. Second, poor retrieving performances for two scenarios of constraint variables were related to few sites for which specific processes were disregarded by the modelling framework, namely allochthonous water supply and waterlogging during wet autumn and summer. Third, we could identify some promising combinations of constraint variables, after the removal of the aforementioned sites with specific processes. These promising combinations were (LAI, ET) and even more (LAI, ET, SSM) for estimating SAWC and root zone thickness, as well as SSM for estimating soil moistures at field capacity and wilting point of the topsoil layer. Provided we can avoid site-specific processes, our approach may further provide spatial sampling of SAWC and related components, to be used as surrogate input data for DSM models.

Evapotranspiration (ET) is a major component of both the hydrological cycle and the surface energy balance. Furthermore, ET is strongly linked to the primary production of natural and cultivated vegetation covers. Therefore, obtaining spatialized estimates of ET is of paramount importance in Mediterranean areas, submitted to hot and dry summers, all the more so as climate change is expected to worsen the water deficit in this region. In the framework of the preparation of the TRISHNA satellite mission, the objective of this study was (1) to produce maps of ET over a small Mediterranean region from high resolution satellites, and (2) compare these satellite estimates with local measurements of ET from flux towers. The studied area was located in the Hérault river area, south of France. During the period 2013 - 2019, 63 clear sky Landsat 7 and 8 images were collected and processed, having spatial resolutions of 60 and 100 meters, respectively. Maps of ET were generated using the EVASPA processing tool (Gallego-Elvira, 2013), with various methods for estimating the soil heat flux and the evaporative fraction. These satellite estimates were compared to those measured by long term flux towers installed on three biomes representative of Mediterranean landscapes: Puechabon (Quercus ilex forest on a rocky soil), Larzac (grassland on a limestone plateau) and Roujan (vineyards in the plain). In the estimation of ET from satellite images, intermediate variables (albedo, net radiation, soil heat flux, surface temperature) were first compared to those measured locally, when available. Finally, instantaneous and daily satellite estimates of ET were compared to the local measurements. Depending on sites and EVAPSA methods, the RMSE of instantaneous estimates of ET ranged between 39 and 202 W.m-2. The RMSE of daily estimates of ET ranged between 0.96 and 1.82 mm.day-1. Future work will be conducted to analyze the effect of air temperature variations, induced by altitude variations, on ET satellite estimates. This will allow to extend this study to larger regions of southern France.

In preparation of the micro-bolometer-based MIcro Satellite for Thermal Infrared GRound surface Imaging (MISTIGRI) mission, we study the error budget of the Temperature-Emissivity Separation (TES) method using several spectral configurations that differ in channel numbers, locations, and widths. The error budget quantifies the contribution of 1) the TES underlying assumption about emissivity spectral contrast, 2) the errors on atmospheric corrections, and 3) the instrumental noise. When dealing with atmospheric corrections, we consider errors in atmospheric temperature, water vapor content, and concentrations of CO 2 and O 3 . To that end, we design an end-to-end simulator of MISTIGRI measurements in order to simulate the radiative and biophysical quantities involved in the data processing. We conduct numerous simulations over a wide range of realistic setups that include cavity effect, i.e., radiance trapping within vegetation canopy. In the case of micro-bolometer-based sensing, the current study highlights that atmospheric and instrumental noises have similar impacts on the TES retrievals, with resulting errors twice as large as those due to the TES intrinsic assumption about spectral contrast, where the latter contributes to the TES error budget within the [0.005–0.009] interval for emissivity, and within the [0.3–0.4 K] interval for land surface temperature (LST). Also, we show that retrieval performance of surface temperature is very similar across all considered MISTIGRI spectral configurations, with RMSE variation within 0.2 K. Eventually, our study permits us to select a 4-channels spectral configuration as the most suited for the MISTIGRI instrument, notably because it enables a moderately better capture of the emissivity contrast than a 3-channels one.

The spatial organization of crops at the landscape scale is a promising solution to be explored within Mediterranean hilly agrosystems, for agroecological transition and adaptation to climate change. In this perspective, it is necessary to ensure the capacity of crop models to simulate a range of agro-hydrological processes within these agrosystems. The objective of this study is to perform a multi-criteria assessment of the FAO AquaCrop model to simulate crop functioning for a diversity of plant and soil combinations, by considering several hydro-climatic years. This multi-criteria assessment includes canopy cover (CC), dry above-ground biomass (biomass), soil water content (SWC), actual evapotranspiration (ETa) and runoff (non-infiltrated rain). The study area is the small rainfed watershed of Kamech located within the Lebna regional watershed, Cap Bon Peninsula, North-eastern Tunisia. The data, collected in the framework of the OMERE Observatory, are derived from ten measurement campaigns between 2001 and 2013 that focus on (1) predominant soils (Cambisols, Luvisols, Vertisols), and (2) representative crops of the region (wheat and barley as grain cereals, oats as fodder and faba bean as legume). Except ETa, which simulations are quite poor (R2 of 0.3, RMSE of 0.9 mm/d and NRMSE of 44%), AquaCrop correctly simulates the water transfer within the soil-plant continuum along with crop growth, for the ten aforementioned campaigns. First, CC is correctly simulated (R2 of 0.6, RMSE of 3% and NRMSE of 9%), as is runoff (R2 of 0.5 and RMSE of 0.7) mm. Second, SWC is well simulated (R2 of 0.88, RMSE of 8.34 mm and NRMSE of 2.34%), as is above-ground dry matter (R2 of 0.83, RMSE of 0.17 ton/ha and NRMSE of 5.9%). These results indicate that AquaCrop is relevant for characterizing the water use efficiency under the influence of intra-plot runoff.

We propose an original approach to optimize the Thermal infraRed Imaging Satellite for High-resolution Natural resource Assessment (TRISHNA) instrument spectral configuration for the split-window (SW) method. First, we consider as input of end-to-end simulations an emissivity data set that accounts for cavity effect within vegetation canopy. Second, we propose a bidimensional approach where both locations of TRISHNA SW channels, namely $\lambda _{c}^{\text {TIR3}}$ and $\lambda _{c}^{\text {TIR4}}$ , can slide within predefined spectral intervals. We report a large sensitivity to channel positions, with variations of root mean square error (RMSE) on retrieved land surface temperature (LST) up to 3 K. Our bidimensional approach shows that this sensitivity is consistent with the underlying assumptions of the SW method. Indeed, two regions are observed in the $(\lambda _{c}^{\text {TIR3}},\,\lambda _{c}^{\text {TIR4}})$ space: 1) an unfavorable region corresponding to $\lambda _{c}^{\text {TIR3}}\leq 10.0~\mu \text{m}$ , where large RMSE values are ascribed to large differences between emissivities in both SW channels, and 2) a favorable region corresponding to $\lambda _{c}^{\text {TIR3}}\geq 10.3~\mu \text{m}$ , where differences between emissivities in both SW channels are small and RMSE values are driven by the differences between atmospheric transmittance in both SW channels. Overall, it is necessary to better account for the difference in surface emissivities between the two SW channels, whereas disregarding the cavity effect within vegetation canopy is not critical. Eventually, our bidimensional approach permits to define an optimal position for $\lambda _{c}^{\text {TIR3}}$ at $10.6~\mu \text{m}$ , which induces larger robustness to uncertainties on channel positions. By applying our study on two structurally different SW formulations and addressing impacts of uncertainties on land surface emissivity (LSE) and atmospheric water vapor content (AWVC), we show that these results can be generalized to other SW formulations.

Exploring crop spatial organizations within landscapes is a promising solution for agroecological transitions and climate change adaptation in Mediterranean rainfed hilly agrosystems. A prerequisite is to ensure that crop models can simulate a range of agrohydrological processes in such agrosystems. The current study deepened the evaluation of the AquaCrop model by conducting a multicriteria evaluation (canopy cover CC, dry aboveground biomass AGB, actual evapotranspiration ETa, runoff R, soil water content SWC) for a range of crop and soil combinations, and for contrasted hydroclimatic years in northeastern Tunisia. The data were collected in the Kamech catchment (OMERE Observatory) during nine measurement campaigns on predominant soils and crops. AquaCrop simulations were based on field observations and parameters from the literature. AquaCrop could simulate plant dynamics and water fluxes for contrasted hydroclimatic years, with a slight dependence on soil class and a significant dependence on crop type. Model simulations were of moderate quality for CC (R-2 of 0.45, RMSE of 0.24 on average) and of acceptable quality for AGB (R-2 of 0.81, RMSE of 0.85 ton ha(-1) on average). AquaCrop acceptably simulated water transfer across the soil-plant continuum (R-2 of 0.62, RMSE of 0.77 mm day(-1) on average for ETa; R-2 of 0.68, RMSE of 0.75 mm day(-1) on average for R; R-2 of 0.86, RMSE of 27.4 mm on average for SWC). The model performances were satisfactory for most cases, with p values larger than 5 % for the Student's t test on linear regressions of validation. Our results were similar to those reported in previous studies over flat terrain, including delayed senescence by model simulations with subsequent overestimation of CC and AGB observations. Additionally, soil cracks likely altered the AquaCrop ability to simulate runoff. Despite these limitations, our results support the application of AquaCrop to evaluate water productivity in hilly agrosystems.

In preparation of the Thermal infraRed Imaging Satellite for High-resolution Natural resource Assessment (TRISHNA) mission, we conducted a thorough analysis of sensitivity for the Temperature-Emissivity Separation (TES) method to the position of the four TRISHNA spectral channels, notably to find an optimal spectral configuration. To that purpose, we designed a fast-computing end-to-end simulator including several components, which we implemented to simulate both pixel-size TRISHNA measurements and land surface temperature (LST) retrievals. Firstly, simulations were conducted over a wide range of realistic scenarii, notably by including vegetation canopy-scale cavity effect. Secondly, the experimental design included the features of second generation Mercury-Cadmium-Telluride (MCT) cooled detectors with lower instrumental noises and finer channels. Thirdly, as opposed to previous studies that used predefined spectral configurations to determine the most suited one, we conducted an optimization of the spectral configuration by crossing, on a pair basis, several positions of the four TIR channels over a range of wavelengths. Fourthly, we quantified the TES sensitivity to atmospheric perturbations, by comparing LST retrievals with and without atmospheric noise. We observed an overall moderate sensitivity of TES LST retrievals to the spectral channel positions, with a maximum RMSE variation of 0.31 K within the atmospheric spectral windows. Furthermore, the TES method was sensitive to three main parameters, namely the instrumental noise, the atmospheric downwelling irradiance, and the transmittance due to ozone and water vapor, with RMSEs larger than 1 K for specific channel locations. Moreover, by considering possible superimposition of two channels, we noted that the TES method could achieve similar performance by considering three or four channels. Eventually, our study enabled us to recommend a new spectral configuration for the TRISHNA TIR instrument, that is more robust to atmospheric perturbations and to uncertainties on channel positions and bandwidths.

Agriculture provides humanity with food, fibers, fuel, and raw materials that are paramount for human livelihood. Today, this role must be satisfied within a context of environmental sustainability and climate change, combined with an unprecedented and still-expanding human population size, while maintaining the viability of agricultural activities to ensure both subsistence and livelihoods. Remote sensing has the capacity to assist the adaptive evolution of agricultural practices in order to face this major challenge, by providing repetitive information on crop status throughout the season at different scales and for different actors. We start this review by making an overview of the current remote sensing techniques relevant for the agricultural context. We present the agronomical variables and plant traits that can be estimated by remote sensing, and we describe the empirical and deterministic approaches to retrieve them. A second part of this review illustrates recent research developments that permit to strengthen applicative capabilities in remote sensing according to specific requirements for different types of stakeholders. Such agricultural applications include crop breeding, agricultural land use monitoring, crop yield forecasting, as well as ecosystem services in relation to soil and water resources or biodiversity loss. Finally, we provide a synthesis of the emerging opportunities that should strengthen the role of remote sensing in providing operational, efficient and long-term services for agricultural applications.