A double two-sources energy-water balance model for improving evapotranspiration estimates and irrigation management in fruit trees fields

Improving the use of water in irrigated agriculture is meaningful in a period of increasing water scarcity conditions. A more accurate estimate of evapotranspiration (ET) and its components thus becomes fundamental to better quantify the irrigation water volumes. Many existing models, based on different remote sensing data, provide daily estimates of latent heat flux (LE) from correlation between net radiation and instantaneous estimates of LE, computed as residual component of the energy balance equation or from a correlation of land surface temperature (LST) with vegetation indices., However, they mainly lack of solutions which are continuous in time (e.g. hourly), independent from satellite LST availability and a simultaneous estimation of soil moisture. Addressing this gap, a double two-sources energy-water balance model (FEST‐2×2‐EWB) is developed based on the decoupling of both water and energy fluxes between the bare soil or grass interrow and the trees rows. This novel parameterization approach enables the differentiation of water uptake from the root zone, which varies between tall trees and grass, considering the dynamics of soil moisture (SM) in the superficial and deep layers. Additionally, it provides partitioned values for transpiration and evaporation. The new model has been evaluated in two irrigated trees fields in the North of Italy, a walnut trees field from 2019 to 2021 and a pear trees field, for the year 2022. Results of the study showcased a root-mean-square-error (RMSE) of about 55 W m− 2 and a bias of about 40 W m− 2 for hourly latent and sensible heat fluxes when compared to the eddy covariance stations located in the fields, while a RMSE of 2 °C (bias of 1.5 °C) for LST and of 0.04 for SM. The FEST‐2×2‐EWB model significantly enhances the accuracy of ET simulation in fruits trees areas in respect to the original one source and one-layer version of the same model. Finally, the application of an irrigation optimization strategy with this new model, allowed to demonstrate its potentiality in water saving (about 90 mm in a year) in respect to farmers applied irrigation, and with a difference of about 60 mm between using the double two-sources model and single source one

Multi-scale EO-based agricultural drought monitoring indicator for operative irrigation networks management in Italy

International audienc

Proximal-Sensing-Powered Modelling of Energy-Water Fluxes in a Vineyard: A Spatial Resolution Analysis

Spatial resolution is a key parameter in energy–water surface flux modelling. In this research, scale effects are analyzed on fluxes modelled with the FEST-EWB model, by upscaling both its inputs and outputs separately. The main questions are: (a) if high-resolution remote sensing images are necessary to accurately model a heterogeneous area; and (b) whether and to what extent low-resolution modelling provides worse/better results than the upscaled results of high-resolution modelling. The study area is an experimental vineyard field where proximal sensing images were obtained by an airborne platform and verification fluxes were measured via a flux tower. Modelled fluxes are in line with those from alternative energy-balance models, and quite accurate (NSE = 0.78) with respect to those measured in situ. Field-scale evapotranspiration has resulted in both the tested upscaling approaches (with relative error within ±30%), although fewer pixels available for low-resolution calibration may produce some differences. When working at low resolutions, the model has produced higher relative errors (20% on average), but is still within acceptable bounds. This means that the model can produce high-quality results, partially compensating for the loss in spatial heterogeneity associated with low-resolution images

Ozonated water reduces susceptibility in tomato plants to Meloidogyne incognita by the modulation of the antioxidant system

Few studies have been carried out on the effect of ozonated water (O3wat) on the oxidative stress of root systems and, in particular, in combination with biotic stress. The aim of this study was to determine whether aqueous ozone is effective in the control of root-knot nematode (RKN) infection and to investigate the concomitant changes in the basal defence system. A tomato cultivar susceptible to Meloidogyne incognita was treated with O3wat as a soil drench. No negative effects were seen following ozone application in comparison with the control under the exposure conditions used. The treatment reduced significantly the nematode infection rate and induced changes in the morphology of nematode feeding sites, some of which were characterized by visible symptoms of senescence. The antioxidant response, as well as parameters of oxidative damage, were examined in untreated and O3wat-treated galls at 2, 4 and 7 days after inoculation and compared with uninfected roots. High levels of reactive oxygen species (ROS), H2O2 and malondialdehyde were generated in galls in response to combined abiotic and biotic stresses. Throughout the experimental period, the activities and relative transcript levels of the antioxidant enzymes catalase, superoxide dismutase and ascorbate peroxidase produced different responses when exposed to ozone treatment and/or infection. The results demonstrate how O3wat protects tomato against the RKN M. incognita through the modulation of basal defence mechanisms

Irrigation and Precipitation Hydrological Consistency with SMOS, SMAP, ESA-CCI, Copernicus SSM1km, and AMSR-2 Remotely Sensed Soil Moisture Products

International audienc

Evapotranspiration estimates from an energy water balance model and satellite Land Surface Temperature over the desertic Heihe river basin

Optical and Laser Remote Sensin

Multi-scale and multi-model approaches to water management – application to drought and irrigation in Morocco

International audienceWater management is a problem of matching supply and demand whilst sustaining environmental conditions for a range of sectors and ecosystems, potentially under changing conditions of climate or demand. In dryland regions, this is particularly difficult given low available water supply and high climate variability, often with lack of data for operations, planning and design. Addressing these challenges at national scale requires whole-system approaches to incorporate the range of relevant sectors and their interactions, and multi-scale approaches to capture the large-scale drivers of water availability and the fine-scale variability of supply and demand within catchments, irrigation districts or urban areas. In the context of the AFRI-SMART project “EO-Africa multi-scale smart agricultural water management” funded under the ESA EO Africa - National Incubators EXPRO+ programme, we have developed a multi-scale, multi-model approach to help address water management challenges in Morocco. On-going drought conditions in the country for the past 5 years have left reservoirs without water for irrigation, which must be prioritized for public water supply, impacting on food production, agricultural exports and farmer incomes. More accurate information on water resources distribution in space and time across scales and sectors is needed to address sustainable agriculture, to help guarantee food and water security, and increase resilience to hydro-meteorological extremes. At national scale multiple sources of information from ground observations, satellite remote sensing, and climate and hydrological models are integrated to provide the best estimate of hydroclimate and drought indices to characterize the large-scale variability in water supply. This feeds into basin scale hydrological modeling, focused on the Oum Er-rbia basin using the HydroBlocks modelling framework, which combines a 1-D land surface model with a cluster-based landscape representation, allowing large-domain simulations at 10s metres resolution. HydroBlocks is coupled to the RAPID stream flow routing scheme to provide high resolution stream flow estimates. Predicted stream flow is routed to the main reservoirs in the basin which are simulated using a simple mass balance approach. Withdrawals from the reservoirs are supplied to one of the basin’s irrigation districts of Doukkala. Actual and optimized irrigation water needs for specific crops, at fine resolution (daily, 10 m) are predicted using the energy-crop-water balance model FEST-EWB-SAFY driven by Landsat LST and Sentinel2 vegetation indices. The system is used to provide historic reconstructions of water availability and analyzed to identify times of supply risks. The system is also implemented in monitoring and seasonal forecast mode as a tool to understand upcoming risks to water supply and potential interventions to reduce risks, such as provision of early warning of risks, options for adjusted reservoir management, or altered/optimized irrigation scheduling. An open online decision support tool has been developed to provide intuitive near real-time visualization of information from the satellites/models and explore forecasts and future scenarios. We also discuss the collaboration with end user groups in helping to define the management problem and identification of critical decisions in water management across scales

Evapotranspiration and crop water use efficiency from airborne thermal infrared data at 1 to 4 m spatial resolution

International audienceAgriculture is the largest consumer of water worldwide, accounting for about 70% of the global freshwater      withdrawals. Thus, crop water use efficiency and impacts of water stress on crop water consumption are the key concerns for agricultural water management.Present study investigates the variability of evapotranspiration (ET) and crop water use efficiency by integrating very high spatial resolution (1 – 4 m) thermal infrared (TIR) data from airborne measurements and visible to near infrared data from Planet satellite with a numerical water-energy balance model and a diagnostic surface energy balance model.     The analysis is done for an intensive agriculture area in central Italy near the city of Modena, where several fruit trees fields are present along with fresh vegetables. An intensive airborne campaign was organized in the summer of 2022 for three consecutive days in July. A hyperspectral TIR camera (Telops Hyper-Cam LW) has been operated at a spectral resolution of 8 cm-1, resulting in 64 wavebands, and covering a wavelength range of 850 cm-1 to 1350 cm-1 (7,39 µm – 11,8 µm).  During the 3 days of flight acquisitions, three overpasses per day are planned: 9:00, 12:30 and 16:00 h, respectively and two areas were intensively      surveyed at both 4 and 1 m spatial resolution. Planet data at 3.7 m spatial resolution were used to derive different vegetation indices, such as vegetation fraction coverage, NDVI and leaf area index. During airborne overpasses ground data of spectral reflectance, vegetation variables, LST and soil water content (SM) were collected in different fields. In addition, two different pear trees fields were monitored with an eddy covariance station and soil moisture profile measurements, respectively.To investigate the diurnal and spatial patterns of evapotranspiration, soil moisture variability and crop water use efficiency, we used two numerical models: the surface energy balance model STIC based on Penman-Monteith and Shuttleworth-Wallace (Mallick et al., 2018) and the water-energy balance model FEST-EWB which computes continuously in time and is distributed in space soil moisture and evapotranspiration fluxes solving for a land surface temperature that closes the energy–water balance equations (Corbari et al., 2011).Differences and similarities in ET estimates have been analysed from the two models for different soil moisture conditions and crop types, considering crop water use efficiency and water stress, and have been compared to eddy covariance measurements for accuracy evaluation considering both instantaneous and daily data. The assimilation of instantaneous estimates of ET into the water-energy balance model allowed to directly derived soil moisture maps at high spatial resolution which have been found in agreement with ground SM measurements

Multi-Source Hydrological Data Products to Monitor High Asian River Basins and Regional Water Security

This project explored the integrated use of satellite, ground observations and hydrological distributed models to support water resources assessment and monitoring in High Mountain Asia (HMA). Hydrological data products were generated taking advantage of the synergies of European and Chinese data assets and space-borne observation systems. Energy-budget-based glacier mass balance and hydrological models driven by satellite observations were developed. These models can be applied to describe glacier-melt contribution to river flow. Satellite hydrological data products were used for forcing, calibration, validation and data assimilation in distributed river basin models. A pilot study was carried out on the Red River basin. Multiple hydrological data products were generated using the data collected by Chinese satellites. A new Evapo-Transpiration (ET) dataset from 2000 to 2018 was generated, including plant transpiration, soil evaporation, rainfall interception loss, snow/ice sublimation and open water evaporation. Higher resolution data were used to characterize glaciers and their response to environmental forcing. These studies focused on the Parlung Zangbo Basin, where glacier facies were mapped with GaoFeng (GF), Sentinal-2/Multi-Spectral Imager (S2/MSI) and Landsat8/Operational Land Imager (L8/OLI) data. The geodetic mass balance was estimated between 2000 and 2017 with Zi-Yuan (ZY)-3 Stereo Images and the SRTM DEM. Surface velocity was studied with Landsat5/Thematic Mapper (L5/TM), L8/OLI and S2/MSI data over the period 2013–2019. An updated method was developed to improve the retrieval of glacier albedo by correcting glacier reflectance for anisotropy, and a new dataset on glacier albedo was generated for the period 2001–2020. A detailed glacier energy and mass balance model was developed with the support of field experiments at the Parlung No. 4 Glacier and the 24 K Glacier, both in the Tibetan Plateau. Besides meteorological measurements, the field experiments included glaciological and hydrological measurements. The energy balance model was formulated in terms of enthalpy for easier treatment of water phase transitions. The model was applied to assess the spatial variability in glacier melt. In the Parlung No. 4 Glacier, the accumulated glacier melt was between 1.5 and 2.5 m w.e. in the accumulation zone and between 4.5 and 6.0 m w.e. in the ablation zone, reaching 6.5 m w.e. at the terminus. The seasonality in the glacier mass balance was observed by combining intensive field campaigns with continuous automatic observations. The linkage of the glacier and snowpack mass balance with water resources in a river basin was analyzed in the Chiese (Italy) and Heihe (China) basins by developing and applying integrated hydrological models using satellite retrievals in multiple ways. The model FEST-WEB was calibrated using retrievals of Land Surface Temperature (LST) to map soil hydrological properties. A watershed model was developed by coupling ecohydrological and socioeconomic systems. Integrated modeling is supported by an updated and parallelized data assimilation system. The latter exploits retrievals of brightness temperature (Advanced Microwave Scanning Radiometer, AMSR), LST (Moderate Resolution Imaging Spectroradiometer, MODIS), precipitation (Tropical Rainfall Measuring Mission (TRMM) and FengYun (FY)-2D) and in-situ measurements. In the case study on the Red River Basin, a new algorithm has been applied to disaggregate the SMOS (Soil Moisture and Ocean Salinity) soil moisture retrievals by making use of the correlation between evaporative fraction and soil moisture