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Water scarcity is a growing social, economic, and political issue, especially in Southern European countries that are becoming even more arid and where different crops can be cultivated only if irrigation is possible. In this context, strategies to enhance water use efficiency are regarded as critical from both an economic and an environmental standpoint. The present work aims to analyse water use efficiency and productivity of processing tomato in Apulia region of Southern Italy. Specifically, the study examines the potential enhancements in economic and physical water productivity through the simulation of the fully coupled FEST-EWB-SAFY model, a hydrological crop model that estimates the optimal water requirements for irrigation using satellite and ground data. The model's estimates suggest that plants require significantly less water than that provided by conventional irrigation systems. The simulations also suggest that information technology, when combined with irrigation water-saving techniques, can lead to a reduction in water waste, an increase in water productivity, and lower incidence of water costs. Policy interventions should integrate water efficiency into existing regulatory measures and promote better water usage planning through the adoption of smart delivery systems aimed at supplying water only when necessary and at optimal volumes. [ABSTRACT FROM AUTHOR]

The presence of road ice has always been a key issue during winter months. A reliable forecast system capable of predicting the Land Surface Temperature (LST) and, consequently, its formation is one of the best strategies to operate towards reducing both vehicles accidents and waste of chemical solvents used for prevention which have a significant economic and environmental impact. Hence, the Meteo Expert Centre (MEC) has developed an algorithm for LST forecasts able to issue ice risk warnings as well. This algorithm operationally works every day in real-time and it is here tested, first, on a paved area of the Pedemontana Lombarda motorway and the Milano Linate airport airstrip, and, afterwards, since the LST plays a crucial role in understanding phenomena of energy exchange between soil, vegetation, and atmosphere, its knowledge and prediction becomes relevant also for other purposes such as agricultural management and irrigation system control, further experiments are carried out over two agricultural fields, one in the North and the other in the South of Italy during the SIM (Smart Irrigation Management) project. All LST analyses showed encouraging results with reasonable high values of statistical scores, in both applications on asphalted and different vegetated terrains, demonstrating that the developed algorithm has a high versatility even on completely different types of surfaces, and it can be applied as a valid tool for road ice risk warnings too. [ABSTRACT FROM AUTHOR]

The Food and Agricultural Organization (FAO) method for potential evapotranspiration assessment is based on the crop coefficient, which allows one to relate the reference evapotranspiration of well irrigated grass to the potential evapotranspiration of specific crops. The method was originally developed for cultivated species based on lysimeter measurements of potential evapotranspiration. Not many applications to natural vegetated areas exist due to the lack of available data for these species. In this paper we investigate the potential of using evapotranspiration measurements acquired by micrometeorological stations for the definition of crop coefficient functions of natural vegetated areas and extrapolation to ungauged sites through remotely sensed data. Pastures, deciduous and evergreen forests have been considered and lower crop coefficient values are found with respect to FAO data. [ABSTRACT FROM AUTHOR]

The triangle method has been applied to derive a weekly indicator of evaporative fraction on vegetated areas in a temperate region in Northern Italy. Daily MODIS Aqua Land Surface Temperature (MYD11A1) data has been combined with air temperature maps and 8-day composite MODIS NDVI (MOD13Q1/MYD13Q1) data to estimate the Evaporative Fraction (EF) at 1 km resolution, on a daily basis. Measurements at two eddy covariance towers located within the study area have been exploited to assess the reliability of satellite based EF estimations as well as the robustness of input data. Weekly syntheses of the daily EF indicator (EFw) were then derived at regional scale for the years 2010, 2011 and 2012 as a proxy of overall surface moisture condition. EFw showed a temporal behavior consistent with growing cycles and agro-practices of the main crops cultivated in the study area (rice, forages and corn). Comparison with official regional corn yield data showed that variations in EFw cumulated over summer are related with crop production shortages induced by water scarcity. These results suggest that weekly-averaged EF estimated from MODIS data is sensible to water stress conditions and can be used as an indicator of crops' moisture conditions at agronomical district level. Advantages and disadvantages of the proposed approach to provide information useful to issue operational near real time bulletins on crop conditions at regional scale are discussed. [ABSTRACT FROM AUTHOR]

This paper presents a system for supporting hydropower production on mountainous areas. The system couples the outputs of a numerical weather prediction model and a snow melting and accumulation temperature-based model. Several procedures are presented for interpolating meteorological variables and calibrating and validating model parameters that can be generalized to any other mountainous area where the estimation of current and forecasted snow water equivalent and melting amount is required. The system reliability has been assessed through the validation of three components: spatial interpolation of meteorological data, mathematical modeling, and quantitative meteorological forecast. The results show that good accuracy of meteorological data spatial interpolation can be achieved when the data from snow gauges are used for assessing the precipitation lapse rate at higher altitudes, and the temperature lapse rate is computed from data at each time step. The temperature-based hydrological model proved to be effective in simulating lake inflow water volume and energy production. No clear result has been found for snow melt forecast due to the difficulties in providing reliable quantitative weather forecast in complex alpine area. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The feasibility of combining remotely sensed land surface temperature data (LST) and an energy–water balance model for improving evapotranspiration estimates over time distributed in space in the Capitanata irrigation consortium is analysed. The energy–water balance FEST-EWB model (flash flood event-based spatially distributed rainfall–runoff transformation—energy–water balance model) computes continuously in time and is distributed in space soil moisture (SM) and evapotranspiration (ET) fluxes solving for a land surface temperature that closes the energy–water balance equations. The comparison between modelled and observed LST was used to calibrate the model soil parametres with a newly developed pixel to pixel calibration procedure. The effects of the calibration procedure were analysed against ground measures of soil moisture and evapotranspiration. The FEST-EWB model was run at 30 m of spatial resolution for the period between 2013 and 2018. Absolute errors of 2.5 °C were obtained for LST estimates against satellite data; while RMSE around 0.06 and 40 Wm−2 are found for ground measured soil moisture and latent heat flux, respectively. [ABSTRACT FROM AUTHOR]

Numerous Surface Soil Moisture (SSM) products are available from remote sensing, encompassing different spatial, temporal, and radiometric resolutions and retrieval techniques. Notwithstanding this variety, all products should be coherent with water inputs. In this work, we have cross-compared precipitation and irrigation with different SSM products: Soil Moisture Ocean Salinity (SMOS), Soil Moisture Active Passive (SMAP), European Space Agency (ESA) Climate Change Initiative (ESA-CCI) products, Copernicus SSM1km, and Advanced Microwave Scanning Radiometer 2 (AMSR2). The products have been analyzed over two agricultural sites in Italy (Chiese and Capitanata Irrigation Consortia). A Hydrological Consistency Index (HCI) is proposed as a means to measure the coherency between SSM and precipitation/irrigation. Any time SSM is available, a positive or negative consistency is recorded, according to the rainfall registered since the previous measurement and the increase/decrease of SSM. During the irrigation season, some agreements are labeled as "irrigation-driven". No SSM dataset stands out for a systematic hydrological coherence with the rainfall. Negative consistencies cluster just below 50% in the non-irrigation period and lose 20–30% in the irrigation period. Hybrid datasets perform better (+15–20%) than single-technology measurements, among which active data provide slightly better results (+5–10%) than passive data. [ABSTRACT FROM AUTHOR]

Total suspended matter (TSM) concentration is an extremely important parameter for water quality definition. The aim of this work is the evaluation of the effect of the Three Gorges Dam on total suspended sediments using remote sensing data at different temporal and spatial resolutions. TSM is estimated for the middle Yangtze river, China, before and after the construction of the Three Gorges Dam. The retrieved values are correlated to ground daily discharge values, finding relations between the physical quantities and discharge. Then, the application of the obtained relations to the discharge dataset provides continuous daily estimations of TSM values, also covering the days for which satellite scenes were lacking. This daily dataset will allow us to estimate the annual volume of river solid sediments. According to this work, both low spatial resolution MODIS (Moderate Resolution Imaging Spectroradiometer) data and high-resolution. Landsat 5 and 7 are able to detect the changes in TSM distribution over space and time induced by the building of the Three Gorges Dam, with a variation of even 50 mg/L over summer season. The confrontation of solid discharge with daily estimated TSM values shows that the single band MODIS algorithm performs better for medium-low concentrations, while the dual-band algorithm for MODIS and the selected Landsat algorithm perform better with high concentrations. [ABSTRACT FROM AUTHOR]

This study shows the feasibility of the combined use of multi-satellite data and an energy–water balance model for improving the estimates of water fluxes over time and distributed in space in the Yangtze River basin. In particular, a new methodology is used to constrain an internal model variable of the distributed hydrological model based on the satellite land surface temperature. The hydrological FEST-EWB model (flash flood event-based spatially distributed rainfall–runoff transformation–energy water balance model) with its energy–water balance scheme allows to continuously compute in time and distributed in space soil moisture and evapotranspiration (ET) fluxes thanks to a double link with satellite-derived data as input parameters (e.g., LAI) and as variables for model states' updates as the land surface temperature (LST). This LST was used to calibrate the model soil parameters instead of using only dedicated ground measurements. The effects of the calibration procedure were evaluated at four available river cross-sections along the Yangtze River, considering also the presence of the Three Gorges Dam. Flow duration curves were also considered to understand the volume storages' changes. The Poyang and Dongting Lakes dynamics were simulated from FEST-EWB and compared against satellite water extended from MERIS and ASAR data and water levels from LEGOS altimetry data (Topex/Poseidon). The FEST-EWB model was run at 0.009° spatial resolution and three hours of temporal resolutions for the period between 2003 and 2006. Absolute errors on LST estimates of 3 °C were obtained while discharge data were simulated with errors of 10%. Errors on the water area extent of 7% and on the water level of 3% were obtained for the two lakes. [ABSTRACT FROM AUTHOR]