Soil water content assessment: Critical issues concerning the operational application of the triangle method

Knowledge of soil water content plays a key role in water management efforts to improve irrigation efficiency. Among the indirect estimation methods of soil water content via Earth Observation data is the triangle method, used to analyze optical and thermal features because these are primarily controlled by water content within the near-surface evaporation layer and root zone in bare and vegetated soils. Although the soil-vegetation-atmosphere transfer theory describes the ongoing processes, theoretical models reveal limits for operational use. When applying simplified empirical formulations, meteorological forcing could be replaced with alternative variables when the above-canopy temperature is unknown, to mitigate the effects of calibration inaccuracies or to account for the temporal admittance of the soil. However, if applied over a limited area, a characterization of both dry and wet edges could not be properly achieved; thus, a multi-temporal analysis can be exploited to include outer extremes in soil water content. A diachronic empirical approach introduces the need to assume a constancy of other meteorological forcing variables that control thermal features. Airborne images were acquired on a Sicilian vineyard during most of an entire irrigation period (fruit-set to ripening stages, vintage 2008), during which in situ soil water content was measured to set up the triangle method. Within this framework, we tested the triangle method by employing alternative thermal forcing. The results were inaccurate when air temperature at airborne acquisition was employed. Sonic and aerodynamic air temperatures confirmed and partially explained the limits of simultaneous meteorological forcing, and the use of proxy variables improved model accuracy. The analysis indicates that high spatial resolution does not necessarily imply higher accuracies

Errata: Mapping soil water content under sparse vegetation and changeable sky conditions: comparison of two thermal inertia approaches

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Power Sensitivity Analysis of Multi-Frequency, Multi-Polarized, Multi-Temporal SAR Data for Soil-Vegetation System Variables Characterization

The knowledge of spatial and temporal variability of soil water content and others soil-vegetation variables (leaf area index, fractional cover) assumes high importance in crop management. Where and when the cloudiness limits the use of optical and thermal remote sensing techniques, synthetic aperture radar (SAR) imagery has proven to have several advantages (cloud penetration, day/night acquisitions and high spatial resolution). However, measured backscattering is controlled by several factors including SAR configuration (acquisition geometry, frequency and polarization), and target dielectric and geometric properties. Thus, uncertainties arise about the more suitable configuration to be used. With the launch of the ALOS Palsar, Cosmo-Skymed and Sentinel 1 sensors, a dataset of multi-frequency (X, C, L) and multi-polarization (co- and cross-polarizations) images are now available from a virtual constellation; thus, significant issues concerning the retrieval of soil-vegetation variables using SAR are: (i) identifying the more suitable SAR configuration; (ii) understanding the affordability of a multi-frequency approach. In 2006, a vast dataset of both remotely sensed images (SAR and optical/thermal) and in situ data was collected in the framework of the AgriSAR 2006 project funded by ESA and DLR. Flights and sampling have taken place weekly from April to August. In situ data included soil water content, soil roughness, fractional coverage and Leaf Area Index (LAI). SAR airborne data consisted of multi-frequency and multi-polarized SAR images (X, C and L frequencies and HH, HV, VH and VV polarizations). By exploiting this very wide dataset, this paper, explores the capabilities of SAR in describing four of the main soil-vegetation variables (SVV). As a first attempt, backscattering and SVV temporal behaviors are compared (dynamic analysis) and single-channel regressions between backscattering and SVV are analyzed. Remarkably, no significant correlations were found between backscattering and soil roughness (over both bare and vegetated plots), whereas it has been noticed that the contributions of water content of soil underlying the vegetation often did not influence the backscattering (depending on canopy structure and SAR configuration). Most significant regressions were found between backscattering and SVV characterizing the vegetation biomass (fractional cover and LAI). Secondly, the effect of SVV changes on the spatial correlation among SAR channels (accounting for different polarization and/or frequencies) was explored. An inter-channel spatial/temporal correlation analysis is proposed by temporally correlating two-channel spatial correlation and SVV. This novel approach allowed a widening in the number of significant correlations and their strengths by also encompassing the use of SAR data acquired at two different frequencie

Power Sensitivity Analysis of Multi-Frequency, Multi-Polarized, Multi-Temporal SAR Data for Soil-Vegetation System Variables Characterization

The knowledge of spatial and temporal variability of soil water content and others soil-vegetation variables (leaf area index, fractional cover) assumes high importance in crop management. Where and when the cloudiness limits the use of optical and thermal remote sensing techniques, synthetic aperture radar (SAR) imagery has proven to have several advantages (cloud penetration, day/night acquisitions and high spatial resolution). However, measured backscattering is controlled by several factors including SAR configuration (acquisition geometry, frequency and polarization), and target dielectric and geometric properties. Thus, uncertainties arise about the more suitable configuration to be used. With the launch of the ALOS Palsar, Cosmo-Skymed and Sentinel 1 sensors, a dataset of multi-frequency (X, C, L) and multi-polarization (co- and cross-polarizations) images are now available from a virtual constellation; thus, significant issues concerning the retrieval of soil-vegetation variables using SAR are: (i) identifying the more suitable SAR configuration; (ii) understanding the affordability of a multi-frequency approach. In 2006, a vast dataset of both remotely sensed images (SAR and optical/thermal) and in situ data was collected in the framework of the AgriSAR 2006 project funded by ESA and DLR. Flights and sampling have taken place weekly from April to August. In situ data included soil water content, soil roughness, fractional coverage and Leaf Area Index (LAI). SAR airborne data consisted of multi-frequency and multi-polarized SAR images (X, C and L frequencies and HH, HV, VH and VV polarizations). By exploiting this very wide dataset, this paper, explores the capabilities of SAR in describing four of the main soil-vegetation variables (SVV). As a first attempt, backscattering and SVV temporal behaviors are compared (dynamic analysis) and single-channel regressions between backscattering and SVV are analyzed. Remarkably, no significant correlations were found between backscattering and soil roughness (over both bare and vegetated plots), whereas it has been noticed that the contributions of water content of soil underlying the vegetation often did not influence the backscattering (depending on canopy structure and SAR configuration). Most significant regressions were found between backscattering and SVV characterizing the vegetation biomass (fractional cover and LAI). Secondly, the effect of SVV changes on the spatial correlation among SAR channels (accounting for different polarization and/or frequencies) was explored. An inter-channel spatial/temporal correlation analysis is proposed by temporally correlating two-channel spatial correlation and SVV. This novel approach allowed a widening in the number of significant correlations and their strengths by also encompassing the use of SAR data acquired at two different frequencie

Assessing the performance of thermal inertia and Hydrus models to estimate surface soil water content

The knowledge of soil water content (SWC) dynamics in the upper soil layer is important for several hydrological processes. Due to the difficulty of assessing the spatial and temporal SWC dynamics in the field, some model-based approaches have been proposed during the last decade. The main objective of this work was to assess the performance of two approaches to estimate SWC in the upper soil layer under field conditions: the physically-based thermal inertia and the Hydrus model. Their validity was firstly assessed under controlled laboratory conditions. Thermal inertia was firstly validated in laboratory conditions using the transient line heat source (TLHS) method. Then, it was applied in situ to analyze the dynamics of soil thermal properties under two extreme conditions of soil-water status (well-watered and air-dry), using proximity remote-sensed data. The model performance was assessed using sensor-based measurements of soil water content acquired through frequency (FDR) and time domain reflectometry (TDR). During the laboratory experiment, the Root Mean Square Error (RMSE) was 0.02 m3 m??3 for the Hydrus model and 0.05 m3m-3for the TLHS model approach. On the other hand, during the in situ experiment, the temporal variability of SWCs simulated by the Hydrus model and the corresponding values measured by the TDR method evidenced good agreement (RMSE ranging between 0.01 and 0.005 m3m-3). Similarly, the average of the SWCs derived from the thermal diffusion model was fairly close to those estimated by Hydrus (spatially averaged RMSE ranging between 0.03 and 0.02 m3m-3)

Assessing the performance of different model-based techniques to estimate water content in the upper soil layer

The knowledge of soil water content (SWC) of the upper soil layer is important for most hydrological processes occurring over vegetated areas and under dry climate. Because direct field measurements of SWC are difficult, the use of different type of sensors and model-based approaches have been proposed and extensively used during the last decade. The main objective of this work is to assess the performance of two models estimating SWC of the upper soil layer: the transient line heat source method and the physically based Hydrus-1D model. The models’ performance is assessed using field measurements acquired through a Time Domain Reflectometer (TDR). The experiment was carried out on an olive orchard located near the town of Castelvetrano (South-West of Sicily - latitude 37.6429◦ , longitude 12.8471◦ ). The temporal dynamic of topsoil water content was investigated in two samplers, under wet and dry conditions. The samplers were opened at the upper boundary and inserted into the soil to ensure the continuity of the soil surface. A K2D Pro sensor allowed to measure the soil thermal properties allowing to estimate soil thermal inertia and then SWC. The physically based Hydrus-1D model was also used to estimate SWC of both samples. Hourly records of soil water contents, acquired by a TDR100 probe, were used to validate both the considered models. The comparison between SWCs simulated by Hydrus-1D and the corresponding values measured by the TDR method evidenced a good agreement. Similarly, even SWCs derived from the thermal diffusion model resulted fairly close to those measured with the TDR

The impact of soil erosion on soil fertility and vine vigor. A multidisciplinary approach based on field, laboratory and remote sensing approaches

Soil erosion processes in vineyards, beyond surface runoff and sediment transport, have a strong effect on soil organic carbon (SOC) loss and redistribution along the slope. Variation in SOC across the landscape can determine differences in soil fertility and vine vigor. The goal of this research was to analyze the interactions among vines vigor, sediment delivery and SOC in a sloping vineyard located in Sicily. Six pedons were studied along the slope by digging 6 pits up to 60 cmdepth. Soilwas sampled every 10 cm and SOC, water extractable organic carbon (WEOC) and specific ultraviolet absorbance (SUVA) were analyzed. Erosion rates, detachment and deposition areas were measured by the pole height method which allowed mapping of the soil redistribution. The vigor of vegetation, expressed as Normalized Difference Vegetation Index (NDVI), derived from highresolution satellite multispectral data, was compared with measured pruning weight. Results confirmed that soil erosion, sediment redistribution and SOC across the slope was strongly affected by topographic features, slope and curvature. The erosion ratewas 16Mg ha−1 y−1 since the timeof planting (6 years). SOC redistribution was strongly correlated with the detachment or deposition areas as highlighted by pole height measurements. The off-farm SOC loss over six years amounted to 1.2 Mg C ha−1. SUVA254 values, which indicate hydrophobic material rich in aromatic constituents of WEOC, decreased significantly along the slope, demonstrating that WEOC in the detachment site ismore stable in comparison to deposition sites. The plant vigor was strongly correlated with WEOC constituents. Results demonstrated that high resolution passive remote sensing data combined with soil and plant analyses can survey areas with contrasting SOC, soil fertility, soil erosion and plant vigor. Thiswill allowmonitoring of soil erosion and degradation risk areas and support decision-makers in developing measures for friendly environmental management

Large-Eddy Simulation e tecnica LS-PIV: lo studio della turbolenza superficiale

Gli avanzamenti tecnologici degli ultimi decenni hanno fatto registrare la rapida diffusione di tecnologie innovative con cui condurre un monitoraggio ambientale più efficiente ed efficace. Nel campo del monitoraggio fluviale sono sempre più utilizzate le tecniche basate sull’elaborazione di immagini, fornendo una valida alternativa alle metodologie tradizionalmente adottate. Le tecniche ottiche restituiscono infatti misure non intrusive, assicurando migliori condizioni di sicurezza per gli operatori. I metodi ottici più utilizzati sono la Large-Scale Particle Image Velocimetry (LS-PIV) [1] e la Large-Scale Particle Tracking Velocimetry (LS-PTV) [2]. Le tecniche LS-PIV e LS-PTV si basano sulla registrazione video del movimento di un tracciante opportunamente introdotto sulla superficie libera di un corso d’acqua assumendo che le particelle traccianti si muovano in maniera solidale con i filetti liquidi superficiali. I dispositivi di registrazione generalmente utilizzati sono costituiti dalle comuni fotocamere digitali, o dai più moderni smartphone, o ancora dai droni. I video risultanti sono successivamente elaborati attraverso software open-source, i quali applicano un’analisi di cross-correlazione statistica al fine di stimare il campo di velocità superficiale istantaneo. L’obiettivo di questo lavoro è analizzare le performance dei software LS-PIV più largamente utilizzati nella stima del campo di velocità superficiale di un corso d’acqua, tenendo in considerazione la presenza di strutture turbolente. I vortici turbolenti sono elementi frequentemente osservabili nei corsi d’acqua naturali che possono rendere senz’altro complesso il tracciamento degli spostamenti delle particelle traccianti sulla superficie libera. La valutazione dello spostamento di ogni singolo elemento tracciante è resa ancor più difficoltosa dal fenomeno negativo dell’aggregazione tra le particelle, portando spesso a stime incorrette dei vettori velocità. In questo lavoro, lo studio della turbolenza idraulica di un corso d’acqua naturale è stato condotto da un punto di vista numerico. È stato utilizzato uno dei software di fluidodinamica computazionale più conosciuti, ANSYS Fluent, adottando la Large-Eddy Simulation come schema risolutivo per la turbolenza. ANSYS Fluent risolve le equazioni del moto tridimensionale per fluidi incomprimibili utilizzando il metodo ai volumi finiti. Le analisi sono state condotte su casi reali opportunamente modellati con ANSYS Fluent. I domini idraulici presi in esame sono caratterizzati da sezioni trasversali regolari, accuratamente derivate da campagne di rilievi topografici, e da scabrezze del fondo alveo piuttosto ridotte. La modellazione numerica ha permesso di derivare diverse sequenze sintetiche del moto del tracciante sulla superficie libera, successivamente elaborate con i software di analisi LS-PIV. I risultati di queste analisi numeriche hanno permesso una valutazione delle performance della tecnica LS-PIV, espresse in termini di errori valutando la velocità media superficiale e le velocità lungo transetti trasversali

Modelling soil carbon fate under erosion process in vineyard

Soil erosion processes in vineyards beyond water runoff and sediment transport have a strong effect on soil organic carbon loss (SOC) and redistribution along the slope. The variation of SOC across the landscape determines a difference in soil fertility and vine productivity. The aim of this research was to study erosion of a Mediterranean vineyard, develop an approach to estimate the SOC loss, correlate the vines vigor with sediment and carbon erosion. The study was carried out in a Sicilian (Italy) vineyard, planted in 2011. Along the slope, six pedons were studied by digging 6 pits up to 60cm depth. Soil was sampled in each pedon every 10cm and SOC was analyzed. Soil erosion, detachment and deposition areas were measured by pole height method. The vigor of vegetation was expressed in term of NDVI (Normalized difference Vegetation Index) derived from a satellite image (RapidEye) acquired at berry pre-veraison stage (July) and characterized by 5 spectral bands in the shortwave region, including a band in the red wavelength (R, 630-685 nm) and in the near infrared (NIR, 760-850 nm) . Results showed that soil erosion, sediments redistribution and SOC across the hill was strongly affected by topographic features, slope and curvature. The erosion rate was 46Mg ha-1 y-1 during the first 6 years since planting. The SOC redistribution was strongly correlated with the detachment or deposition area as highlighted by pole height measurements. The approach developed to estimate the SOC loss showed that during the whole study period the off-farm SOC amounts to 1.6Mg C ha-1. As highlighted by NDVI results, the plant vigor is strong correlated with SOC content and therefore, developing an accurate NDVI approach could be useful to detect the vineyard areas characterized by low fertility due to erosion process

CALYPSO an operational network of HF radars for the Malta-Sicily Channel

An HF radar observing system composed of three CODAR SeaSondes is providing real-time surface current pseudo-Eulerian maps every hour in the strip of sea dividing Malta and Sicily. This initiative forms part of the CALYPSO project that principally aims to support the efficient response against marine oil spills in this busy area of maritime transportation in the Mediterranean. In combination to numerical models, an operational chain of activities provides essential data to a spectrum of applications and addresses the needs of a number of responsible entities in Malta and Sicily, targeting the better control of the trans-boundary maritime space and greater efficiency for security and safety at sea. The usefulness of this effort is measured by the level of usage of the data provided by CALYPSO through dedicated web services with browsing, viewing, and user-defined download of data. The project comprised several validation and system performance tuning exercises through the matching of radar data with direct sea current measurements using drifters and ADCP deployments. The spatial coverage and high temporal resolution of the HF radar data collected since September 2012 is permitting a unique and detailed characterization of the surface circulation variability in the area at sub-to-mesoscale and seasonal scales. Substantial eddy field structures are evidenced; their origin, dynamics, evolution and linkages to biological processes and the location of fisheries is the subject of ongoing research.peer-reviewe